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LTER Data

DatasetID Data Package Title/Authors/DOI

knb-lter-bes.1000.170 Urban Forest Effects Model (UFORE) to calculate forest structure and function from sample ground data. Two part set. -- Nowak, David;
doi:10.6073/pasta/f499b08931ce01b01280f1f89e5c1ee9

Authors: Nowak, David;

Full Metadata and Download Link: knb-lter-bes.1000.170

Abstract:
Within the City of Baltimore, 195 permanent 1/10 circular plots were established based on a stratified random sample among land uses in 1999. These plots were re-measured in 2004 and 2009 and will be re-measured again in 2014. On each plot, all trees (as defined as woody vegetation with a stem diameter at 4.5 ft (dbh) greater than one-inch) are recorded. For each tree, data are recorded on species, dbh, height, crown width, condition, crown competition, percent canopy missing and distance and direction to nearby residential buildings. These data are analyzed using the i-Tree model (www.itreetools.org) to assess ecosystem services and values. However, more importantly, these plots along with a comparable set of plots established in Syracuse, NY in 1999 are the first and most spatially comprehensive set of long-term urban forest monitoring data within cities globally. These data are being used to understand how urban forest structure and associated ecosystem services are changing through time in the City of Baltimore.

knb-lter-bes.104.610 GIS Shapefile - Inventory of Historic Properties, Harford County -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/85116131a2229cce69e4381b73a00ea3

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.104.610

Abstract:
Inventory of Historic Properties for Harford County. The Maryland Inventory of Historic Properties vector layers are depictions of the approximate locations of historic structures, monuments, districts, and other properties that are listed on the Maryland Inventory of Historic Properties. No attribute information is available for this dataset. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.105.610 GIS Shapefile - Inventory of Historic Properties, Howard County -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/da4d5f6fdb0cfc9c84d80fa94efcda81

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.105.610

Abstract:
Inventory of Historic Properties for Howard County. The Maryland Inventory of Historic Properties vector layers are depictions of the approximate locations of historic structures, monuments, districts, and other properties that are listed on the Maryland Inventory of Historic Properties. No attribute information is available for this dataset. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.106.610 GIS Shapefile - National Register of Historic Places, MD -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/e3369771cacdf55795963f1f25d7ae41

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.106.610

Abstract:
Polygons depict properties in Maryland listed on the National Register of Historic Places, a listing maintained by the U.S. Department of Interior. The number of National Register listings in Maryland as of March 21, 2000 is 1230. Of the 1,230 listings, the following were not digitized: Queen City Hotel in Allegany County, demolished; and Steamship Nobska, which was moved to Massachusetts; Timonium Mansion in Baltimore county,demolished; the Messina Archeological Site in Cecil County, delisted; 100 Hopkins Place in Baltimore City, delisted; and the William Costen House in Somerset County, delisted. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.110.600 GIS Shapefile - Crime Risk Database, MSA -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/e72f2007aa632003296482dc06ced87b

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.110.600

Abstract:
Crime data assembled by census block group for the MSA from the Applied Geographic Solutions' (AGS) 1999 and 2005 'CrimeRisk' databases distributed by the Tetrad Computer Applications Inc. CrimeRisk is the result of an extensive analysis of FBI crime statistics. Based on detailed modeling of the relationships between crime and demographics, CrimeRisk provides an accurate view of the relative risk of specific crime types at the block group level. Data from 1990 - 1996,1999, and 2004-2005 were used to compute the attributes, please refer to the 'Supplemental Information' section of the metadata for more details. Attributes are available for two categories of crimes, personal crimes and property crimes, along with total and personal crime indices. Attributes for personal crimes include murder, rape, robbery, and assault. Attributes for property crimes include burglary, larceny, and mother vehicle theft. 12 block groups have no attribute information. CrimeRisk is a block group and higher level geographic database consisting of a series of standardized indexes for a range of serious crimes against both persons and property. It is derived from an extensive analysis of several years of crime reports from the vast majority of law enforcement jurisdictions nationwide. The crimes included in the database are the "Part I" crimes and include murder, rape, robbery, assault, burglary, theft, and motor vehicle theft. These categories are the primary reporting categories used by the FBI in its Uniform Crime Report (UCR), with the exception of Arson, for which data is very inconsistently reported at the jurisdictional level. Part II crimes are not reported in the detail databases and are generally available only for selected areas or at high levels of geography. In accordance with the reporting procedures using in the UCR reports, aggregate indexes have been prepared for personal and property crimes separately, as well as a total index. While this provides a useful measure of the relative "overall" crime rate in an area, it must be recognized that these are unweighted indexes, in that a murder is weighted no more heavily than a purse snatching in the computation. For this reason, caution is advised when using any of the aggregate index values. The block group boundaries used in the dataset come from TeleAtlas's (formerly GDT) Dynamap data, and are consistent with all other block group boundaries in the BES geodatabase. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.1100.110 Synoptic water chemistry and discharge data for the Glyndon and Baismans Run sampling sites - 2001 - 2002 -- Band, Larry;
doi:10.6073/pasta/55bccb16f5e804e434a3115fbef177d3

Authors: Band, Larry;

Full Metadata and Download Link: knb-lter-bes.1100.110

Abstract:
This is stream water quality and discharge data collected by Steven Kenworthy using flow velocity measurement method. Samples and discharge measurments were taken approximately once per month from June 2001 to June 2002. Locations within Pond Branch, Baisman Run, and Glyndon are denoted in the MetadataCodes Tab of the Excel Workssheet. Flow and Streamwater Sampling Station Codes........ Pond Branch........ PB4 (PBC2)........Upper PB spring (PBC2 was an error in labeling) PB3a........PB @ upper riparian wells PB3........PB below gas line PB2a........PB @ lower riparian wells POBR........Pond Branch at gage Baisman Run........ BR5a........Baisman Run @ upper gage (Red's flume) BR5........Baisman Run Northwest tributary basin BR6........Baisman Run Southwest tributary basin BR4........Northern tributary (west of Pond Branch) BR3........Southern tributary BR7........Baisman Run upstream of Pond Branch Confluence BR2........Pond Branch between pond and yellow trail BARN........Baisman at gage (Ivy Hill Rd.) Gwynns Falls @ Glyndon........ GL9........GF southern tributary (Glyndon Gate) in woods upstream of pond and ditch GL6........GF main channel in forest downstream of log cabin GL4........GF downstream of Sacred Heart Rd. GL3........GF upstream of Chatsworth ave (@ lower riparian wells) GL2 (GFGL side) ........Schoolbus lot / Dyer Rd. tributary GL2a (GFGL main) ........GF above schoolbus trib junction (reg. stream crew did this > sometimes) GFGL/GL1........Gwynns Falls @ Glyndon Gage NO3 and TN are mg of N/L........ Cl and SO4 are mg/L........ PO4 and TP are mg of P/L Concentrations that were below the lowest standard run are reported as follows: NO3 and TN 0.01 CL and SO4 0.05 PO4 and TP 1.5

knb-lter-bes.111.600 GIS Shapefile - Environmental Health Complaints, Baltimore City -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/3fae39f1bbef56155bb4e2e3f93547a9

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.111.600

Abstract:
Environmental Health Complaints for Baltimore City, January 2001. The dataset was geocoded against the Baltimore City Street Centerline file (Centerln.xxx) generated on 11/11/99 by the Department of PublicWorks. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.113.600 GIS Shapefile - Housing Complaints, Baltimore City, 01/2001 -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/8e356e8fe8503ffc3e5994a937df663d

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.113.600

Abstract:
Description Housing Complaints for Baltimore City, January 2001. The dataset was geocoded against the Baltimore City Street Centerline file (Centerln.xxx) generated on 11/11/99 by the Department of PublicWorks. Credits There are no credits for this item. Use limitations There are no access and use limitations for this item. Extent West -76.712014 East -76.527925 North 39.372712 South 39.220401 Scale Range This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.114.600 GIS Shapefile - Housing Complaints, Baltimore City, 02/2001 -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/217955e260091043e955e8f4da1a5dbc

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.114.600

Abstract:
Description Housing complaints for Baltimore City, February 2001. The dataset was geocoded against the Baltimore City Street Centerline file (Centerln.xxx) generated on 11/11/99 by the Department of PublicWorks. Credits There are no credits for this item. Use limitations There are no access and use limitations for this item. Extent West -76.712781 East -76.528961 North 39.373558 South 39.219890 This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.116.600 GIS Shapefile - Housing Notices, Baltimore City, 01/2001 -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/2a045cbcdfac90dd504edaf6fcd86d5d

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.116.600

Abstract:
Description Housing Notices for Balimore City, January 2001. The dataset was geocoded against the Baltimore City Street Centerline file (Centerln.xxx) generated on 11/11/99 by the Department of PublicWorks. Credits There are no credits for this item. Use limitations There are no access and use limitations for this item. Extent West -76.711617 East -76.527976 North 39.372414 South 39.219335 This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.117.600 GIS Shapefile - Housing Notices, Baltimore City, 02/2001 -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/fe40cadce421cfe007c3362c914d0576

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.117.600

Abstract:
Description Housing Notices for Balimore City, February 2001. The dataset was geocoded against the Baltimore City Street Centerline file (Centerln.xxx) generated on 11/11/99 by the Department of PublicWorks. Credits There are no credits for this item. Use limitations There are no access and use limitations for this item. Extent West -76.711617 East -76.527976 North 39.372414 South 39.219335 This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.118.600 GIS Shapefile - Baltimore City Liquor Licenses -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/d8e455651d83cff1293fd5a691c69baf

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.118.600

Abstract:
This feature class is a dataset based on liquor licenses as reported by Baltimore City Liquor License Board listing circa October 2004. This dataset includes the establishments that sell liquor in Baltimore, Maryland. Each establishment was geocoded by its street address. Those unable to be placed with a point by geocoding were given "U" for unmatched under the field "Status". Each establishment also has an associated liquor license particular to what type of alcohol is sold and the type of establishment. These liquor license types are defined by the Baltimore City Liquor License Board on their website, http://www.ci.baltimore.md.us/government/liquor. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.120.600 GIS Shapefile - Ordinance_parcels -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/5fcffdc9bc7e7e51a610f0bc628736ea

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.120.600

Abstract:
social system, socio-economic resources, justice, BES, Environmental disamentities, Environmental Justice, Zoning Board of Appeals Summary For use in the environmental injustices study of Baltimore relating to patterns of environmental disamenties in relation to low income/minority communities. Description This feature class layer is a point dataset of authorizing ordinances from the Baltimore City Council and Mayor from 1930 until 1999 concerning identified environmental disamentities. The data was gathered from records from the City Council since 1930 relating to decisions concerning land-uses considered to be environmental disamentities and is to be used to examine environmental injustices involving low income/minority communities in Baltimore. To examine if environmental injustices exist in Baltimore, this point layer will be overlayed with race/income data to determine if patterns of inequity exist. Points were placed manually using the associated addresses from the Ordinance_master dataset and using ISTAR 2004 data in conjunction with Baltimore parcel data. The Ordinance_ID number associated with each point relates to its appeal number from the City Council. Multiple points on the data layer have the same Ordinance_ID. This point layer can be joined with the Ordinance_master data layer based on the field "Ordinance_ID" and using the relationship "Ordinance_point_relationship". Credits UVM Spatial Analysis Lab Use limitations None. There are no restrictions on the use of this dataset. The authors of this dataset make no representations of any kind, including but not limited to the warranties of merchantability or fitness for a particular use, nor are any such warranties to be implied with respect to the data. Extent West -76.707701 East -76.526991 North 39.371885 South 39.200794 This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.1200.110 Synoptic water chemistry and discharge data for the Baismans Run sampling sites - 2007 - 2008 -- Band, Larry;
doi:10.6073/pasta/a0afc97959212405b46cddac9bec772a

Authors: Band, Larry;

Full Metadata and Download Link: knb-lter-bes.1200.110

Abstract:
This is stream water quality and discharge data collected by Monica Smith using flow velocity measurment method. Samples and discharge measurments were taken approximately once per month from August 2008 to October 2007. Locations within Baisman Run are denoted below: Department of Geography University of North Carolina at Chapel Hill. UTM 18N BA3-SF1B 353952.4775 4370933.534 BA3-SF2A 353824.1488 4370802.221 BA3-SF2B 353871.899 4370793.268 BA3-SF3A 353746.5547 4370644.048 BA3-SF3B 353794.3049 4370638.08 BA3-SF2R 353991.2746 4370888.768 BA3-SF1L 353979.337 4370918.612 BA3 354500.9953 4371320.992 BA5a-JC1 353278.0057 4371970.732 BA5a-JC2 353474.9753 4372018.482 BA3-SF1A 353913.6804 4370964.855

knb-lter-bes.121.600 GIS Shapefile - Ordinance_point -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/35f2f92626c5f1795f3d4be5ba037b6a

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.121.600

Abstract:
Tags social system, socio-economic resources, justice, BES, Environmental disamentities, Environmental Justice, Zoning Board of Appeals Summary For use in the environmental injustices study of Baltimore relating to patterns of environmental disamenties in relation to low income/minority communities. Description This feature class layer is a point dataset of authorizing ordinances from the Baltimore City Council and Mayor from 1930 until 1999 concerning identified environmental disamentities. The data was gathered from records from the City Council since 1930 relating to decisions concerning land-uses considered to be environmental disamentities and is to be used to examine environmental injustices involving low income/minority communities in Baltimore. To examine if environmental injustices exist in Baltimore, this point layer will be overlayed with race/income data to determine if patterns of inequity exist. Points were placed manually using the associated addresses from the Ordinance_master dataset and using ISTAR 2004 data in conjunction with Baltimore parcel data. The Ordinance_ID number associated with each point relates to its appeal number from the City Council. Multiple points on the data layer have the same Ordinance_ID. This point layer can be joined with the Ordinance_master data layer based on the field "Ordinance_ID" and using the relationship "Ordinance_point_relationship". Credits UVM Spatial Analysis Lab Use limitations None. There are no restrictions on the use of this dataset. The authors of this dataset make no representations of any kind, including but not limited to the warranties of merchantability or fitness for a particular use, nor are any such warranties to be implied with respect to the data. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.123.600 GIS Shapefile - Transportation Complaints, Baltimore City, 01/2001 -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/a573358578f887d4cab0d2b3da36762e

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.123.600

Abstract:
Description Transportation Complaints for Baltimore City, January 2001. The dataset was geocoded against the Baltimore City Street Centerline file (Centerln.xxx) generated on 11/11/99 by the Department of PublicWorks. Credits There are no credits for this item. Use limitations There are no access and use limitations for this item. Extent West -76.711659 East -76.528419 North 39.374130 South 39.199924 This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.124.600 GIS Shapefile - Transportation Complaints, Baltimore City, 02/2001 -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/c3c15f0c06a48203c37532d1af6677da

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.124.600

Abstract:
Description Transportation Complaints for Baltimore City, February 2001. The dataset was geocoded against the Baltimore City Street Centerline file (Centerln.xxx) generated on 11/11/99 by the Department of PublicWorks. Credits There are no credits for this item. Use limitations There are no access and use limitations for this item. Extent West -76.711659 East -76.528419 North 39.374130 South 39.199924

knb-lter-bes.126.600 GIS Shapefile - Trash Complaints, Baltimore City, 01/2001 -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/10747803d96e0e422edf8f28bd3e09f8

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.126.600

Abstract:
Description Trash Complaints for Baltimore City, January 2001. The dataset was geocoded against the Baltimore City Street Centerline file (Centerln.xxx) generated on 11/11/99 by the Department of PublicWorks. Credits There are no credits for this item. Use limitations There are no access and use limitations for this item. Extent West -76.712815 East -76.527905 North 39.373999 South 39.219456 Scale Range

knb-lter-bes.127.600 GIS Shapefile - Trash Complaints, Baltimore City, 02/2001 -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/ad84baba9c52cafeb538a267b946ce24

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.127.600

Abstract:
Description Trash Complaints for Baltimore City, February 2001. The dataset was geocoded against the Baltimore City Street Centerline file (Centerln.xxx) generated on 11/11/99 by the Department of PublicWorks. Credits There are no credits for this item. Use limitations There are no access and use limitations for this item. Extent West -76.710792 East -76.529215 North 39.373983 South 39.223455 Scale Range

knb-lter-bes.130.600 GIS Shapefile - Water-Sewer Complaints, Baltimore City, 01/2001 -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/9c99d92bed2c4d299f4c45c9391a4084

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.130.600

Abstract:
Description Water and Sewer Complaints for Baltimore City, January 2001. The dataset was geocoded against the Baltimore City Street Centerline file (Centerln.xxx) generated on 11/11/99 by the Department of PublicWorks. Credits There are no credits for this item. Use limitations There are no access and use limitations for this item. Extent West -76.712560 East -76.527713 North 39.374140 South 39.202377 Scale Range

knb-lter-bes.1300.110 BES bird survey for Watershed 263, winter, 2012, survey data. This dataset pairs with a file of same name containing a summary of the survey. -- Nilon, Charlie;
doi:10.6073/pasta/fcfaa945f97b0f358f8d9bf1c628adfe

Authors: Nilon, Charlie;

Full Metadata and Download Link: knb-lter-bes.1300.110

Abstract:
This dataset is associated with BES Bird Monitoring Bird Monitoring Project: ================= The BES Bird Monitoring Project is a breeding bird survey designed to find out what birds are found in the breeding season in Baltimore and where. Our monitoring efforts will show associations among block group socioeconomic variables, land cover, land use, and habitat features with breeding bird abundance, to provide information for land managers on possible consequences of land use changes on bird communities. A distinguishing feature of the bird monitoring at BES LTER, relative to other urban bird work, is the capacity for long-term monitoring of features at multiple scales through links to other parts of the project. Different processes influence habitat for birds at different scales, e.g. ongoing household level human decision-making at lot scale vs. block or neighborhood scale abandonment/re-development. Our project seeks to understand how these processes impact bird occurrence, abundance, and composition differ at the lot, block and neighborhood scale. The data consists of four major elements, Sites, Surveys, Taxalist, and Birds. Sites records the sites and their characteristics. Surveys describe the actual outings or sampling sessions. They describe the weather, the temperature, the sites visited. Taxalist provides the integration of speciaies abbreviations and common names, and Birds describes the actual sightings, linking to the other three tables. Attribute information: Here are the fields Surveys: site_id FK->Sites[site_id] survey_id survey_date time_start time_end observer wind_speed wind_dir air_temp temp_units cloud_cover notes Sites: site_id park_code park_district park_name point_code point_location park_acreage Taxalist: species_id common_name Birds: survey_id FK->surveys[survey_id] site_id FK->surveys[site_id] species_id FK->taxalist[species_id] distance bird_count notes seen heard direction time_class

knb-lter-bes.131.600 GIS Shapefile - Water-Sewer Complaints, Baltimore City, 02/2001 -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/bbc2ff3cb086a5c4b2728abef2ddc0b4

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.131.600

Abstract:
Description Water and Sewer Complaints for Baltimore City, February 2001. The dataset was geocoded against the Baltimore City Street Centerline file (Centerln.xxx) generated on 11/11/99 by the Department of PublicWorks. Credits There are no credits for this item. Use limitations There are no access and use limitations for this item. Extent West -76.713228 East -76.527109 North 39.374160 South 39.214046

knb-lter-bes.1310.110 BES bird survey for Watershed 263, winter, 2012, survey summary. This dataset pairs with a file of same name containing the data (counts) for the survey. -- Nilon, Charlie;
doi:10.6073/pasta/8e58b4b61396e4dd973fe698da5e7766

Authors: Nilon, Charlie;

Full Metadata and Download Link: knb-lter-bes.1310.110

Abstract:
This dataset is associated with BES Bird Monitoring Bird Monitoring Project: ================= The BES Bird Monitoring Project is a breeding bird survey designed to find out what birds are found in the breeding season in Baltimore and where. Our monitoring efforts will show associations among block group socioeconomic variables, land cover, land use, and habitat features with breeding bird abundance, to provide information for land managers on possible consequences of land use changes on bird communities. A distinguishing feature of the bird monitoring at BES LTER, relative to other urban bird work, is the capacity for long-term monitoring of features at multiple scales through links to other parts of the project. Different processes influence habitat for birds at different scales, e.g. ongoing household level human decision-making at lot scale vs. block or neighborhood scale abandonment/re-development. Our project seeks to understand how these processes impact bird occurrence, abundance, and composition differ at the lot, block and neighborhood scale. The data consists of four major elements, Sites, Surveys, Taxalist, and Birds. Sites records the sites and their characteristics. Surveys describe the actual outings or sampling sessions. They describe the weather, the temperature, the sites visited. Taxalist provides the integration of speciaies abbreviations and common names, and Birds describes the actual sightings, linking to the other three tables. Attribute information: Here are the fields Surveys: site_id FK->Sites[site_id] survey_id survey_date time_start time_end observer wind_speed wind_dir air_temp temp_units cloud_cover notes Sites: site_id park_code park_district park_name point_code point_location park_acreage Taxalist: species_id common_name Birds: survey_id FK->surveys[survey_id] site_id FK->surveys[site_id] species_id FK->taxalist[species_id] distance bird_count notes seen heard direction time_class

knb-lter-bes.1320.110 BES bird survey habitat features. This is a collection of the habitat features for the BES bird sampling points. Features include number of houses, proximity to trees, shrubs, grass, annuals, and other vegetation and physical features. -- Nilon, Charlie;
doi:10.6073/pasta/451fc1ff62ec6ea9dc7252be41e01ca1

Authors: Nilon, Charlie;

Full Metadata and Download Link: knb-lter-bes.1320.110

Abstract:
This dataset is associated with BES Bird Monitoring Bird Monitoring Project: ================= The BES Bird Monitoring Project is a breeding bird survey designed to find out what birds are found in the breeding season in Baltimore and where. Our monitoring efforts will show associations among block group socioeconomic variables, land cover, land use, and habitat features with breeding bird abundance, to provide information for land managers on possible consequences of land use changes on bird communities. A distinguishing feature of the bird monitoring at BES LTER, relative to other urban bird work, is the capacity for long-term monitoring of features at multiple scales through links to other parts of the project. Different processes influence habitat for birds at different scales, e.g. ongoing household level human decision-making at lot scale vs. block or neighborhood scale abandonment/re-development. Our project seeks to understand how these processes impact bird occurrence, abundance, and composition differ at the lot, block and neighborhood scale. The data consists of four major elements, Sites, Surveys, Taxalist, and Birds. Sites records the sites and their characteristics. Surveys describe the actual outings or sampling sessions. They describe the weather, the temperature, the sites visited. Taxalist provides the integration of speciaies abbreviations and common names, and Birds describes the actual sightings, linking to the other three tables. Attribute information: Here are the fields Surveys: site_id FK->Sites[site_id] survey_id survey_date time_start time_end observer wind_speed wind_dir air_temp temp_units cloud_cover notes Sites: site_id park_code park_district park_name point_code point_location park_acreage Taxalist: species_id common_name Birds: survey_id FK->surveys[survey_id] site_id FK->surveys[site_id] species_id FK->taxalist[species_id] distance bird_count notes seen heard direction time_class

knb-lter-bes.133.600 GIS Shapefile - ZBA_parcels -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/1665997cea45505597aa7bd4159244b1

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.133.600

Abstract:
social system, socio-economic resources, justice, BES, parcles, property, environmental justice, Zoning Board of Appeals Summary For use in the environmental injustices study of Baltimore relating to patterns of environmental disamenties in relation to low income/minority communities. Description This feature class layer is a dataset of the Baltimore parcels that contain points from the ZBA_point dataset. The parcels have an associated count of the sum of ZBA_points that are contained within each parcel. The points correspond to appeals to the Zoning Board of Appeals (ZBA) from 1938 to 1999 concerning identified environmental disamentities. The data was gathered from records from the Zoning Board of Appeals to be used to examine environmental injustices involving low income/minority communities in Baltimore. Parcels were extracted from the Parcels_2004_BACI dataset by a "select by location" query to extract those parcels that contain ZBA_points. This new layer was joined based on spatial location with the ZBA_point layer and the number of points contained by each parcel was summarized by sum. Credits UVM Spatial Analysis Lab Use limitations None. There are no restrictions on the use of this dataset. The authors of this dataset make no representations of any kind, including but not limited to the warranties of merchantability or fitness for a particular use, nor are any such warranties to be implied with respect to the data. Extent West -76.710411 East -76.527316 North 39.371887 South 39.197048 This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.151.640 GIS Shapefile - Transportation, Street Centerlines, Baltimore City -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/ffbf3407c8d03755443186274f82b275

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.151.640

Abstract:
Detailed street center lines for Baltimore City. No metadata was provided with this dataset; the UVM Spatial Analysis Lab has attempted to evaluate this dataset and generate metadata. This dataset depicts the linear boundaries for street and paved areas in Baltimore City and has an extremely high degree of positional accuracy. For the best available transportation data use the Roads_GDT_MSA dataset. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.152.640 GIS Shapefile - Transportation, Street Boundaries, Baltimore City -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/a830075114f9a19b09dc71f8b3e65a62

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.152.640

Abstract:
Detailed street boundaries for Baltimore City. No metadata was provided with this dataset; the UVM Spatial Analysis Lab has attempted to evaluate this dataset and generate metadata. This dataset depicts the linear boundaries for street and paved areas in Baltimore City and has an extremely high degree of positional accuracy. For the best available transportation data use the Roads_GDT_MSA dataset. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.153.650 GIS Shapefile - Transportation, Subway Route, Baltimore City -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/616bfa05f73d51717ebacdd787cc4717

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.153.650

Abstract:
Single subway route for Baltimore City that extends into Baltimore County. No metadata was provided with this dataset; the UVM Spatial Analysis Lab has attempted to evaluate this dataset and generate metadata. There are no attributes associated with this dataset. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.154.650 GIS Shapefile - Transportation, Subway Stations, Baltimore City -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/b8a58a040476f58108f3c7d68f3fb9da

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.154.650

Abstract:
Subway Stations for a single subway route that runs from Baltimore City to Baltimore County. No metadata was provided with this dataset; the UVM Spatial Analysis Lab has attempted to evaluate this dataset and generate metadata. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.155.650 GIS Shapefile - Transportation, Highways, Baltimore City -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/13148835f080c81ce3d0156178910e72

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.155.650

Abstract:
Baltimore City Highways. No metadata was provided with this dataset; the UVM Spatial Analysis Lab has attempted to evaluate this dataset and generate metadata. When compared to high-resolution imagery and detailed street data offsets as great as 50m were observed. Due to positional accuracy errors this dataset should be used with caution. There are no attributes associated with this dataset. For the best available transportation data use the Roads_GDT_MSA dataset. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.156.600 GIS Shapefile - ZBA_point -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/cdef361577706303aed82d78c575dba5

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.156.600

Abstract:
Tags Social system, socio-economic resources, justice, BES, Environmental Justice, Environmental disamentities, Zoning Board of Appeals Summary For use in the environmental injustices study of Baltimore relating to patterns of environmental disamenties in relation to low income/minority communities. Description This feature class layer is a point dataset of appeals to the Zoning Board of Appeals (ZBA) from 1938 to 1999 concerning identified environmental disamentities. The data was gathered from records from the Zoning Board of Appeals decisions since 1931 relating to environmental disamentities and to be used to examine environmental injustices involving low income/minority communities in Baltimore. To see if environmental injustices exist in Baltimore, this point layer will be overlayed with race/income data to determine if patterns of inequity exist. Points were placed manually using the associated addresses from the ZBA_master dataset. The ID number associated with each point is related to its appeal number from the Zoning Board of Appeals. Multiple points on the data layer have the same ZBA_ID number, making it a one-to-many relationship. This layer can be joined with the ZBA_master table using the "ZBA_point_relationship" and the field "ZBA_ID". Credits UVM Spatial Analysis Lab Use limitations None. There are no restrictions on the use of this dataset. The authors of this dataset make no representations of any kind, including but not limited to the warranties of merchantability or fitness for a particular use, nor are any such warranties to be implied with respect to the data. Extent West -76.708848 East -76.527906 North 39.371642 South 39.199548 This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.2000.120 Stewardship Mapping And Assessment Project (STEW-MAP) -- Romolini, Michele;
doi:10.6073/pasta/d1102f6505c48a107a5a27fd942fbaec

Authors: Romolini, Michele;

Full Metadata and Download Link: knb-lter-bes.2000.120

Abstract:
9/19/2013

knb-lter-bes.2020.130 Baltimore Ecosystem Study: Denitrification potential in riparian zones and streams -- Groffman, Peter M; Martel, Lisa D;
doi:10.6073/pasta/fde12cde89277cb26f8d3e7a661e229e

Authors: Groffman, Peter M; Martel, Lisa D;

Full Metadata and Download Link: knb-lter-bes.2020.130

Abstract:
Denitrification potential and a series of ancillary variables (inorganic nitrogen concentrations, moisture content, organic matter content, microbial biomass carbon and nitrogen content, potential net nitrogen mineralization and nitrification, microbial respiration, root biomass) has been measured in riparian zone soils and stream geomorphic features by a series of undergraduate and graduate student researchers as part of the Baltimore Ecosystem Study since the early 2000s. These studies often center on the series of sites where there has been long-term monitoring (since 2000) of riparian water tables and groundwater chemistry along four first or second order steams in and around the Gwynns Falls watershed in Baltimore City and County, MD (https://doi.org/10.6073/pasta/f7721ec5a4fab5b031f8056824e07e7d). One site is in the completely forested Pond Branch catchment that serves as a "reference" study area for the Baltimore LTER (BES). Two sites (Glyndon, Gwynbrook) are in suburban areas of the watershed; one just upstream from the Glyndon BES long-term stream monitoring site in the headwaters of the Gwynns Falls, and one along a tributary that enters the Gwynns Falls just above the Gwynnbrook BES long-term stream monitoring site farther downstream. The final, urban site (Cahill) is along a tributary to the Gwynns Falls in Leakin Park in the urban core of the watershed. Other sites were used in different studies as described in the publications associated with each study. The different studies also varied in just which ancillary variables were measured.

knb-lter-bes.2030.110 Immature mosquito abundances in container habitat, 2013. -- LaDeau, Shannon;
doi:10.6073/pasta/3b6ad60c5dae9b10ce5dcf4b88e7eabf

Authors: LaDeau, Shannon;

Full Metadata and Download Link: knb-lter-bes.2030.110

Abstract:
These data represent relative weekly abundances of container-breeding mosquitoes at sites located across the BES long-term stream sampling sites and Watershed 263. The numbers in each cell under a species heading represent relative total larval abundance per sample site (counts). Column Headers Week.deploy The week (of the year) that the trap was put out. All traps were then collected one week later. Drycups The number of traps at a site that were completely dry after one week (out of 3 traps total). Site Site code date Date deployed C.erraticus Mosquito species C.pipiens Mosquito species C.restuans Mosquito species C.salinarius Mosquito species C.territans Mosquito species Oc.canadensis Mosquito species Oc.japonicus Mosquito species Oc.triseriatus Mosquito species Ae.aegypti Mosquito species Ae.albopictus Mosquito species Ae.cinereus Mosquito species Ae.vexans Mosquito species An.punctipennis Mosquito species An.quadrimaculatus Mosquito species Ps.ferox Mosquito species Orth.Signifera Mosquito species Tox.septentrionalis Mosquito species pupae Pupae of any species Aedes.unid Unidentified larvae from Aedes genus Culex.unid Unidentified larvae from Culex genus Anoph.unid Unidentified larvae from Anopholes genus The following worksheets include additional information about these data: Species: a list of potential species in our samples - not all are found regularly or in every year. Site Description: GIS information about each site Sample.methods: A description of how the data in meanlarvae.wk2013 were collected and processed. These data are the property of the Baltimore Ecosystem Study. Any sharing of data or results for the public should be cleared first with Dr. LaDeau. > LaDeau mailing and contact info: LADEAUS@Caryinstitute.org > 2801 Sharon Turnpike > Millbrook, NY > 845-677-5343 ext 204

knb-lter-bes.2040.150 Data for L.R. Johnson and S.N. Handel - Restoration treatments in urban park forests drive long-term changes in vegetation trajectories - Ecological Applications doi:10.1890/14-2063.1 -- Johnson, Lea;
doi:10.6073/pasta/96ac7ad2d051559fdd8d977a7f45a881

Authors: Johnson, Lea;

Full Metadata and Download Link: knb-lter-bes.2040.150

Abstract:
Initial data from long-term research plots in New York City Park forest patches invaded by exotic woody plant species. Half (n = 30) of the sites were restored 15-20 years prior to first sampling in 2009-2010. The same suite of invasive plants was recorded in the other half of the sites at the time of initial restoration in the late 1980s and early 1990s (n = 30), but they were not restored in 2009-2010.

knb-lter-bes.2070.190 Baltimore Ecosystem Study: Stream metabolism data for core sites in Gwynns Falls -- Reisinger, Alexander; Rosi, Emma;
doi:10.6073/pasta/ce7f30e6013e003bfe28c5fd7d4aed23

Authors: Reisinger, Alexander; Rosi, Emma;

Full Metadata and Download Link: knb-lter-bes.2070.190

Abstract:
An ongoing component of the Baltimore urban long-term ecological research (LTER) project (Baltimore Ecosystem Study, BES) is the use of the watershed approach and monitoring of stream water quality to evaluate the integrated ecosystem functioning of Baltimore. The LTER research has focused on the Gwynns Falls watershed, which spans a gradient from highly urban, urban-residential, and suburban zones. In addition, a forested watershed serves as a reference. The long-term sampling network includes four longitudinal sampling sites along the Gwynns Falls mainstem, as well as several small (40-100 ha) watershed within or near the Gwynns Falls, providing data on water quality in different land use zones of the watersheds. Each study site is continuously monitored for discharge and is sampled weekly for water chemistry. Those data are available elsewhere on the BES website. We are interested in studying the bioreactivity of streams in our watersheds in an attempt to quantify how streams themselves may affect or be affected by water quality. To assess the bioreactivity of streams, we measure whole stream metabolism, which is an integrative metric which quantifies the production and consumption of energy by a stream ecosystem. Stream metabolism represents how energy is created (primary production) and used (respiration) within a stream; it can be thought of as a stream breathing, with primary production being similar to an inhale, and respiration as an exhale. We are monitoring stream metabolism in each of our long-term water quality monitoring stations by deploying sensors that record dissolve oxygen and temperature of the stream every five minutes, and we also have deployed light sensors to record irradiance every five minutes at long-term BES water chemistry streams, which is needed for metabolism modeling. In addition, each dissolved oxygen sensor is located near a USGS gage which estimates discharge every 15 minutes. We used USGS manual discharge estimations linked with channel geometry measurements to develop a unique discharge-stream depth relationship (contact AJ Reisinger for details). The combination of the USGS discharge data and our discharge-depth relationship allows us to estimate average daily discharge and depth. We have included these data as well as dissolved oxygen, temperature, and PAR, allowing metabolism to be scaled on an areal basis. Primary production and respiration of streams integrate all biological activity in a stream, and therefore are good metrics to assess the state of an ecosystem. These metrics can also be used to predict other ecosystem functions. This dataset includes all information needed for whole-stream metabolism modeling using the streammetabolizer R package. Data will updated as it becomes available from the core stream study sites (see http://md.water.usgs.gov/BES for a detailed description of these sites).

knb-lter-bes.2080.190 Baltimore Ecosystem Study: Stream biofilm bacterial community composition -- Lee, Sylvia S; Rosi, Emma J; Kelly, John J;
doi:10.6073/pasta/0acc34afb2b5155e069dcc517e046d72

Authors: Lee, Sylvia S; Rosi, Emma J; Kelly, John J;

Full Metadata and Download Link: knb-lter-bes.2080.190

Abstract:
The Baltimore Ecosystem Study stream biofilm bacterial community composition was obtained from 8 long-term sampling network sites in and near the Gwynns Falls watershed to examine how bacterial communities differ along an urban-rural gradient. Sampling was conducted at the same time as stream chemistry sampling on 18 June 2014 and 21 Oct 2014. Note: biofilm samples were taken about 50 meters east from the Carroll Park monitoring station, just under the I95 highway overpass, due to high water depth, high water flow, and lack of rock substrates for sampling. This dataset presents the number of sequences matching the taxonomic classifications in a reference database of 16S rRNA genes. See the full metadata record for detailed methods.

knb-lter-bes.3000.101 Baltimore Ecosystem Study: Riparian vegetation data - 1 of 11 - 1999 and 2004 trees -- Brush, Grace;
doi:10.6073/pasta/2b9a8e0e3507aeca420b20303e0628d8

Authors: Brush, Grace;

Full Metadata and Download Link: knb-lter-bes.3000.101

Abstract:
This is one of 11 datasets generated in a study of riparian vegetation in the Baltimore Ecosystem Study from 1999-2004. Comparisons of vegetation between the rural/suburban (upper) and urban (lower) sections of the watershed show distinct patterns across an urban to rural gradient. In the lower, more urban section of the watershed, wetland tree species are either absent or occur as small stems while upland species are abundant, in mixed sizes. A comparison of the number of wetland and upland species in the mostly urbanized Gwynns Falls riparian zone with non-urbanized Piedmont floodplains throughout Maryland shows approximately twice as many upland species in the urban floodplain than in non-urbanized floodplains. The majority of shrubs in riparian zones through the Gwynns Falls are upland species. For herbaceous species, frequencies of upland and wetland species are about equal in the upper and middle regions of the watershed, but upland species are more common in the more urban lower floodplains by a factor of greater than two.

knb-lter-bes.3010.101 Baltimore Ecosystem Study: Riparian vegetation data - 2 of 11 -1999_plot_and_2004_transect_locations -- Brush, Grace;
doi:10.6073/pasta/45917d936a9eab4ab62d4a9f6e5753d1

Authors: Brush, Grace;

Full Metadata and Download Link: knb-lter-bes.3010.101

Abstract:
This is one of 11 datasets generated in a study of riparian vegetation in the Baltimore Ecosystem Study from 1999-2004. Comparisons of vegetation between the rural/suburban (upper) and urban (lower) sections of the watershed show distinct patterns across an urban to rural gradient. In the lower, more urban section of the watershed, wetland tree species are either absent or occur as small stems while upland species are abundant, in mixed sizes. A comparison of the number of wetland and upland species in the mostly urbanized Gwynns Falls riparian zone with non-urbanized Piedmont floodplains throughout Maryland shows approximately twice as many upland species in the urban floodplain than in non-urbanized floodplains. The majority of shrubs in riparian zones through the Gwynns Falls are upland species. For herbaceous species, frequencies of upland and wetland species are about equal in the upper and middle regions of the watershed, but upland species are more common in the more urban lower floodplains by a factor of greater than two.

knb-lter-bes.3020.102 Baltimore Ecosystem Study: Riparian vegetation data - 3 of 11 - 1999 riparian herb data -- Brush, Grace;
doi:10.6073/pasta/9387470c91b0b9f4bc534ebfc7fdd85c

Authors: Brush, Grace;

Full Metadata and Download Link: knb-lter-bes.3020.102

Abstract:
This is one of 11 datasets generated in a study of riparian vegetation in the Baltimore Ecosystem Study from 1999-2004. Comparisons of vegetation between the rural/suburban (upper) and urban (lower) sections of the watershed show distinct patterns across an urban to rural gradient. In the lower, more urban section of the watershed, wetland tree species are either absent or occur as small stems while upland species are abundant, in mixed sizes. A comparison of the number of wetland and upland species in the mostly urbanized Gwynns Falls riparian zone with non-urbanized Piedmont floodplains throughout Maryland shows approximately twice as many upland species in the urban floodplain than in non-urbanized floodplains. The majority of shrubs in riparian zones through the Gwynns Falls are upland species. For herbaceous species, frequencies of upland and wetland species are about equal in the upper and middle regions of the watershed, but upland species are more common in the more urban lower floodplains by a factor of greater than two.

knb-lter-bes.3030.102 Baltimore Ecosystem Study: Riparian vegetation data - 4 of 11 - 1999 riparian shrub data -- Brush, Grace;
doi:10.6073/pasta/9cb539da2f063001d371dfaa46c66244

Authors: Brush, Grace;

Full Metadata and Download Link: knb-lter-bes.3030.102

Abstract:
This is one of 11 datasets generated in a study of riparian vegetation in the Baltimore Ecosystem Study from 1999-2004. Comparisons of vegetation between the rural/suburban (upper) and urban (lower) sections of the watershed show distinct patterns across an urban to rural gradient. In the lower, more urban section of the watershed, wetland tree species are either absent or occur as small stems while upland species are abundant, in mixed sizes. A comparison of the number of wetland and upland species in the mostly urbanized Gwynns Falls riparian zone with non-urbanized Piedmont floodplains throughout Maryland shows approximately twice as many upland species in the urban floodplain than in non-urbanized floodplains. The majority of shrubs in riparian zones through the Gwynns Falls are upland species. For herbaceous species, frequencies of upland and wetland species are about equal in the upper and middle regions of the watershed, but upland species are more common in the more urban lower floodplains by a factor of greater than two.

knb-lter-bes.3040.102 Baltimore Ecosystem Study: Riparian vegetation data - 5 of 11 - 1999 seedling data -- Brush, Grace;
doi:10.6073/pasta/53f8dd32894fa2f53155b27eeb58fa90

Authors: Brush, Grace;

Full Metadata and Download Link: knb-lter-bes.3040.102

Abstract:
This is one of 11 datasets generated in a study of riparian vegetation in the Baltimore Ecosystem Study from 1999-2004. Comparisons of vegetation between the rural/suburban (upper) and urban (lower) sections of the watershed show distinct patterns across an urban to rural gradient. In the lower, more urban section of the watershed, wetland tree species are either absent or occur as small stems while upland species are abundant, in mixed sizes. A comparison of the number of wetland and upland species in the mostly urbanized Gwynns Falls riparian zone with non-urbanized Piedmont floodplains throughout Maryland shows approximately twice as many upland species in the urban floodplain than in non-urbanized floodplains. The majority of shrubs in riparian zones through the Gwynns Falls are upland species. For herbaceous species, frequencies of upland and wetland species are about equal in the upper and middle regions of the watershed, but upland species are more common in the more urban lower floodplains by a factor of greater than two.

knb-lter-bes.3050.102 Baltimore Ecosystem Study: Riparian vegetation data - 6 of 11 - 1999 transect descriptions -- Brush, Grace;
doi:10.6073/pasta/bc4eaa09032963d71857301aaca94202

Authors: Brush, Grace;

Full Metadata and Download Link: knb-lter-bes.3050.102

Abstract:
This is one of 11 datasets generated in a study of riparian vegetation in the Baltimore Ecosystem Study from 1999-2004. Comparisons of vegetation between the rural/suburban (upper) and urban (lower) sections of the watershed show distinct patterns across an urban to rural gradient. In the lower, more urban section of the watershed, wetland tree species are either absent or occur as small stems while upland species are abundant, in mixed sizes. A comparison of the number of wetland and upland species in the mostly urbanized Gwynns Falls riparian zone with non-urbanized Piedmont floodplains throughout Maryland shows approximately twice as many upland species in the urban floodplain than in non-urbanized floodplains. The majority of shrubs in riparian zones through the Gwynns Falls are upland species. For herbaceous species, frequencies of upland and wetland species are about equal in the upper and middle regions of the watershed, but upland species are more common in the more urban lower floodplains by a factor of greater than two.

knb-lter-bes.3060.101 Baltimore Ecosystem Study: Riparian vegetation data - 7 of 11 - 2004 plot elevations -- Brush, Grace;
doi:10.6073/pasta/c8b23153e30d14fac822a9408f7abd6c

Authors: Brush, Grace;

Full Metadata and Download Link: knb-lter-bes.3060.101

Abstract:
This is one of 11 datasets generated in a study of riparian vegetation in the Baltimore Ecosystem Study from 1999-2004. Comparisons of vegetation between the rural/suburban (upper) and urban (lower) sections of the watershed show distinct patterns across an urban to rural gradient. In the lower, more urban section of the watershed, wetland tree species are either absent or occur as small stems while upland species are abundant, in mixed sizes. A comparison of the number of wetland and upland species in the mostly urbanized Gwynns Falls riparian zone with non-urbanized Piedmont floodplains throughout Maryland shows approximately twice as many upland species in the urban floodplain than in non-urbanized floodplains. The majority of shrubs in riparian zones through the Gwynns Falls are upland species. For herbaceous species, frequencies of upland and wetland species are about equal in the upper and middle regions of the watershed, but upland species are more common in the more urban lower floodplains by a factor of greater than two.

knb-lter-bes.3070.101 Baltimore Ecosystem Study: Riparian vegetation data - 8 of 11 - 2004_riparian herb data -- Brush, Grace;
doi:10.6073/pasta/e8c3a6166ab861d6b3a8742c8bfe627b

Authors: Brush, Grace;

Full Metadata and Download Link: knb-lter-bes.3070.101

Abstract:
This is one of 11 datasets generated in a study of riparian vegetation in the Baltimore Ecosystem Study from 1999-2004. Comparisons of vegetation between the rural/suburban (upper) and urban (lower) sections of the watershed show distinct patterns across an urban to rural gradient. In the lower, more urban section of the watershed, wetland tree species are either absent or occur as small stems while upland species are abundant, in mixed sizes. A comparison of the number of wetland and upland species in the mostly urbanized Gwynns Falls riparian zone with non-urbanized Piedmont floodplains throughout Maryland shows approximately twice as many upland species in the urban floodplain than in non-urbanized floodplains. The majority of shrubs in riparian zones through the Gwynns Falls are upland species. For herbaceous species, frequencies of upland and wetland species are about equal in the upper and middle regions of the watershed, but upland species are more common in the more urban lower floodplains by a factor of greater than two.

knb-lter-bes.3080.102 Baltimore Ecosystem Study: Riparian vegetation data - 9 of 11 - 2004 riparian shrub data -- Brush, Grace;
doi:10.6073/pasta/54abe0a8fe270699eec5fbaf06a6d740

Authors: Brush, Grace;

Full Metadata and Download Link: knb-lter-bes.3080.102

Abstract:
This is one of 11 datasets generated in a study of riparian vegetation in the Baltimore Ecosystem Study from 1999-2004. Comparisons of vegetation between the rural/suburban (upper) and urban (lower) sections of the watershed show distinct patterns across an urban to rural gradient. In the lower, more urban section of the watershed, wetland tree species are either absent or occur as small stems while upland species are abundant, in mixed sizes. A comparison of the number of wetland and upland species in the mostly urbanized Gwynns Falls riparian zone with non-urbanized Piedmont floodplains throughout Maryland shows approximately twice as many upland species in the urban floodplain than in non-urbanized floodplains. The majority of shrubs in riparian zones through the Gwynns Falls are upland species. For herbaceous species, frequencies of upland and wetland species are about equal in the upper and middle regions of the watershed, but upland species are more common in the more urban lower floodplains by a factor of greater than two.

knb-lter-bes.3090.102 Baltimore Ecosystem Study: Riparian vegetation data - 10 of 11 - elevations at transect locations -- Brush, Grace;
doi:10.6073/pasta/ca3e213bdd81afa9a61c083ae83891f8

Authors: Brush, Grace;

Full Metadata and Download Link: knb-lter-bes.3090.102

Abstract:
This is one of 11 datasets generated in a study of riparian vegetation in the Baltimore Ecosystem Study from 1999-2004. Comparisons of vegetation between the rural/suburban (upper) and urban (lower) sections of the watershed show distinct patterns across an urban to rural gradient. In the lower, more urban section of the watershed, wetland tree species are either absent or occur as small stems while upland species are abundant, in mixed sizes. A comparison of the number of wetland and upland species in the mostly urbanized Gwynns Falls riparian zone with non-urbanized Piedmont floodplains throughout Maryland shows approximately twice as many upland species in the urban floodplain than in non-urbanized floodplains. The majority of shrubs in riparian zones through the Gwynns Falls are upland species. For herbaceous species, frequencies of upland and wetland species are about equal in the upper and middle regions of the watershed, but upland species are more common in the more urban lower floodplains by a factor of greater than two.

knb-lter-bes.3100.101 Baltimore Ecosystem Study: Riparian vegetation data - 11 of 11 - species lists -- Brush, Grace;
doi:10.6073/pasta/fbd65b79a956484059d2e9c27741c9e6

Authors: Brush, Grace;

Full Metadata and Download Link: knb-lter-bes.3100.101

Abstract:
This is one of 11 datasets generated in a study of riparian vegetation in the Baltimore Ecosystem Study from 1999-2004. Comparisons of vegetation between the rural/suburban (upper) and urban (lower) sections of the watershed show distinct patterns across an urban to rural gradient. In the lower, more urban section of the watershed, wetland tree species are either absent or occur as small stems while upland species are abundant, in mixed sizes. A comparison of the number of wetland and upland species in the mostly urbanized Gwynns Falls riparian zone with non-urbanized Piedmont floodplains throughout Maryland shows approximately twice as many upland species in the urban floodplain than in non-urbanized floodplains. The majority of shrubs in riparian zones through the Gwynns Falls are upland species. For herbaceous species, frequencies of upland and wetland species are about equal in the upper and middle regions of the watershed, but upland species are more common in the more urban lower floodplains by a factor of greater than two.

knb-lter-bes.3110.220 Baltimore Ecosystem Study: Precipitation measurements at eight stations -- Welty, Claire; Lagrosa, John;
doi:10.6073/pasta/d641020eacb963f4e9a3db40c0de4ec0

Authors: Welty, Claire; Lagrosa, John;

Full Metadata and Download Link: knb-lter-bes.3110.220

Abstract:
Abstract: Rain depth is collected using model 6011-A tipping bucket rain gauges manufactured by All Weather Inc. (formerly Qualimetrics). Two raingauges (RG1 and RG2) are installed at each of eight stations. Each rain gauge tip represents a depth of 0.01 inches of rainfall. Data are recorded by a data logger at the station and telemetered hourly to UMBC, where the data are stored in a data base. The rain gauges are not heated and therefore snow and ice storms are removed from the published record. The QA/QC procedure applied to the raw data includes removal of false tips and snow/ice events, accumulating tip data to a time series in inches/min, applying a laboratory-based calibration curve to the data, and converting corrected data to a one-minute time series in units of mm/min for publication.

knb-lter-bes.3120.150 Geodatabase for the Baltimore Ecosystem Study Spatial Data -- O'Neal-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/377da686246f06554f7e517de596cd2b

Authors: O'Neal-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.3120.150

Abstract:
The establishment of a BES Multi-User Geodatabase (BES-MUG) allows for the storage, management, and distribution of geospatial data associated with the Baltimore Ecosystem Study. At present, BES data is distributed over the internet via the BES website. While having geospatial data available for download is a vast improvement over having the data housed at individual research institutions, it still suffers from some limitations. BES-MUG overcomes these limitations; improving the quality of the geospatial data available to BES researches, thereby leading to more informed decision-making. BES-MUG builds on Environmental Systems Research Institute's (ESRI) ArcGIS and ArcSDE technology. ESRI was selected because its geospatial software offers robust capabilities. ArcGIS is implemented agency-wide within the USDA and is the predominant geospatial software package used by collaborating institutions. Commercially available enterprise database packages (DB2, Oracle, SQL) provide an efficient means to store, manage, and share large datasets. However, standard database capabilities are limited with respect to geographic datasets because they lack the ability to deal with complex spatial relationships. By using ESRI's ArcSDE (Spatial Database Engine) in conjunction with database software, geospatial data can be handled much more effectively through the implementation of the Geodatabase model. Through ArcSDE and the Geodatabase model the database's capabilities are expanded, allowing for multiuser editing, intelligent feature types, and the establishment of rules and relationships. ArcSDE also allows users to connect to the database using ArcGIS software without being burdened by the intricacies of the database itself. For an example of how BES-MUG will help improve the quality and timeless of BES geospatial data consider a census block group layer that is in need of updating. Rather than the researcher downloading the dataset, editing it, and resubmitting to through ORS, access rules will allow the authorized user to edit the dataset over the network. Established rules will ensure that the attribute and topological integrity is maintained, so that key fields are not left blank and that the block group boundaries stay within tract boundaries. Metadata will automatically be updated showing who edited the dataset and when they did in the event any questions arise. Currently, a functioning prototype Multi-User Database has been developed for BES at the University of Vermont Spatial Analysis Lab, using Arc SDE and IBM's DB2 Enterprise Database as a back end architecture. This database, which is currently only accessible to those on the UVM campus network, will shortly be migrated to a Linux server where it will be accessible for database connections over the Internet. Passwords can then be handed out to all interested researchers on the project, who will be able to make a database connection through the Geographic Information Systems software interface on their desktop computer. This database will include a very large number of thematic layers. Those layers are currently divided into biophysical, socio-economic and imagery categories. Biophysical includes data on topography, soils, forest cover, habitat areas, hydrology and toxics. Socio-economics includes political and administrative boundaries, transportation and infrastructure networks, property data, census data, household survey data, parks, protected areas, land use/land cover, zoning, public health and historic land use change. Imagery includes a variety of aerial and satellite imagery. See the readme: http://96.56.36.108/geodatabase_SAL/readme.txt See the file listing: http://96.56.36.108/geodatabase_SAL/diroutput.txt

knb-lter-bes.3130.100 CENTURY modeled urban residential soil and tree carbon -- Trammell, Tara; Yesilonis, Ian;
doi:10.6073/pasta/3c10627e2344d74141b45e70a9144ccb

Authors: Trammell, Tara; Yesilonis, Ian;

Full Metadata and Download Link: knb-lter-bes.3130.100

Abstract:
Soils constitute the largest sink of terrestrial carbon (C), and urban soils have the potential to provide significant soil C storage. Soils in urbanized landscapes experience a multitude of human alterations, such as compaction and management subsidies, that impact soil C dynamics. While field studies may provide data on urban soil C storage, modeling soil C dynamics under various human impact scenarios will provide a basis for identifying drivers of urban soil C dynamics and for predicting the potential for these highly altered soils to store C over time intervals not typically amenable to empirical validation. The goal of this study was to model soil C dynamics in residential lawns using CENTURY, a dynamic mechanistic model, to determine whether drivers of soil C dynamics in natural systems (e.g., soil texture) were equally useful for estimating soil C content of highly modified soils in urban residential areas. Without incorporating human impacts, we found no relationship between initial CENTURY model simulations and observed soil C (p > 0.05). Factors that best explained soil C accumulation for the observed soil C (bulk density: r2= 0.30; home age: r2= 0.37; p < 0.01) differed from those found important from the CENTURY model simulations (% sand: r2= 0.72, p < 0.001). Therefore, we conducted a modeling exercise to test whether simulating potential construction disturbance and lawn management practices would improve modeled soil and tree C. We found that incorporating these factors did improve CENTURY�s ability to model soil and tree C (p < 0.001). The results from this analysis suggest that incorporating various human disturbances and management practices that occur in urban landscapes into CENTURY model runs will improve its ability to predict urban soil C dynamics, at least within a 100-year time frame. Thus, enhancing our ability to provide recommendations for management and development practices that result in increasing urban soil C storage.

knb-lter-bes.3140.610 GIS Shapefile - Vegetation by block group Baltimore City -- O'Neal-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/8bff9d0053ab350a977dde3206ef7028

Authors: O'Neal-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.3140.610

Abstract:
Areal summary of vegetation by census block group for Baltimore City. This dataset summarizes area occupied by vegetation (forest and grass) for every block group in Baltimore City. It also presents the normalized vegetaion area for each census block group. The area was normalized by taking the vegetation area and dividing it by the area of the block group. The vegetation data used in this dataset came from MD DNR's IKONOS derived SUFA vegetation layer. The census boundaries are from GDT's Dynamap census dataset.

knb-lter-bes.3141.610 GIS Shapefile - Analysis of potential stewardship in support of BES research, residential. -- O'Neal-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/239691b8b1c4a35cc1e403a3179a6c4a

Authors: O'Neal-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.3141.610

Abstract:
Potential stewardship for Residential parcels in Baltimore City summarized by block group. Residential was defined as those parcels with a land use code of residential, residential commercial, residential condominium, or apartments based on the 2003 Maryland Property View A&T database. PRIZM 5, 15, and 62 classes are also present. PRIZM is the Potential Rating Index by Zip code Markets produced by the Claritas Corporation - (http://www.clusterbigip1.claritas.com/claritas/Default.jsp). Total Potential stewardship is that land within a parcels not occupied by buildings, that is land that could potentially support vegetation, regardless of whether or not any vegetation is present. Realized Potential Stewardship is land that is currently occupied by vegetation. Not Realized Potential Stewardship is the land not occupied by buildings or existing vegetation, and is thus the land that is potentially available for "greening" initiatives. Normalization for realized and not realized potential stewardship is carried out by dividing by the total potential stewardship. The potential stewardship was calculated using parcel data, building footprints, and GDT census block groups. Building footprints were erased from the parcel area, resulting in a layer indicating the potential stewardship for each parcel. The potential stewardship layer was then unioned MD DNR's 2001 SUFA vegetation layer. All polygons corresponding to water features were deleted since water features cannot undergo "greening." All polygons that did fall in the potential stewardship area were deleted. This resulted in a layer in which the polygons represented the potential stewardship land along with the potential stewardship land occupied by either grass or trees. This layer was then intersected with the census block group layer resulting in a layer that had the potential stewardship land, potential stewardship vegetation, and block group IDs. All attributes were then summarized at the block group level. A cursory analysis of the parcel data indicated that parcel data was outdated for the following block groups: 245102503031, 245102503032, and 245102503033. Certain block groups with very high Normalized Total Potential Stewardship values may be indicative of the fact that building footprint data was missing, although the extent of this problem is unknown. Note: transportation networks are not part of the parcel data, and thus were appropriately not part of this analysis.

knb-lter-bes.3142.610 GIS Shapefile - Analysis of potential stewardship in support of BES research, parcel level -- O'Neal-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/0bcdd353939353ff312a573728b659fd

Authors: O'Neal-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.3142.610

Abstract:
Parcel-level potential stewardship for Baltimore City. Potential stewardship is that land within a parcel not occupied by buildings, that is land that could potentially undergo "greening." This dataset contians polygons that represent potential stewardship land along with the vegetation that falls within the potential stewardship land. Potential stewardship should be estimated using the polygons with a land use (LU) code equal to 0. Parcel land use codes and census block group information is also present. A cursory analysis of the parcel data indicated that parcel data was outdated for the following block groups: 245102503031, 245102503032, and 245102503033. Note: transportation networks are not part of the parcel data, and thus were appropriately not part of this analysis. In addition a single BLOCKLOT may consist of two or more parcels in certain instances.

knb-lter-bes.3143.610 GIS Shapefile - Analysis of potential stewardship in support of BES research, block group -- O'Neal-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/4e77a1cd16c3aeb806c3460522a633e6

Authors: O'Neal-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.3143.610

Abstract:
Potential stewardship for Baltimore City summarized by block group. PRIZM 5, 15, and 62 classes are also present. PRIZM is the Potential Rating Index by Zip code Markets produced by the Claritas corportation - (http://www.clusterbigip1.claritas.com/claritas/Default.jsp). Potential stewardship is that land within a parcels not occupied by buildings, that is land that could potentially undergo "greening." Not Realized Potential Stewardship is the land not occupied by buildings or existing vegetation, and is thus the land that is potentially available for "greening" initiatives. This dataset provides several summarizations at the block group level: 1) total potential stewardship area, 2) not realized potential stewardship, 3) normalized potential stewardship (potential stewardship area / block group area), 4) normalized not realized potential stewardship (not realized potential stewardship area / block group area), and 5) tree potential stewardship area. The potential stewardship was calculated using parcel data, building footprints, and GDT census block groups. Building footprints were erased from the parcel area, resulting in a layer indicating the potential stewardship for each parcel. The potential stewardship layer was then unioned MD DNR's SUFA vegetation layer. All polygons corresponding to water features were deleted since water features cannot undergo "greening." All polygons that did fall in the potential stewardship area were deleted. This resulted in a layer in which the polygons represented the potential stewardship land along with the potential stewardship land occupied by either grass or trees. This layer was then intersected with the census block group layer resulting in a layer that had the potential stewardship land, potential stewardship vegetation, and block group IDs. All attributes were then summarized at the block group level. Total Potential Stewardship (Tot_PotStew) is the area of parcel land in a block group that is not occupied by buildings or water. Not Realized Potential Stewardship (NotReal_PotStew) is the area of parcel land in a block group that is not occupied by buildings, water, or vegetation, and is thus the land that is actually available for greening. Normalized Potential Stewardship (Norm_PotStew) is the Potential Stewardship area � Block Group area. Normalized Not Realized Potential Stewardship (Norm_NotReal_PotStew) is the Not Realized Potential Stewardship area � Block Group area. Summations of grass (Grass), tree (Trees), and vegetation (Tot_Veg) area within the potential steward zone are also presented. Tree potential stewardship (Tree_PotStew) was calculated by identifying the land that is available for plating trees, i.e. not building, water, or existing trees. Normalized tree potential stewardship (Norm_Tree_Pot_Stew) was calculated by dividing by the area of the block group. Standardized tree potential stewardship (Std_Tree_PotStew) was calculated from the normalized tree potential stewardship: ((value - min) / range) * 100. A cursory analysis of the parcel data indicated that parcel data was outdated for the following block groups: 245102503031, 245102503032, and 245102503033. Note: transportation networks are not part of the parcel data, and thus were appropriately not part of this analysis.

knb-lter-bes.3144.610 GIS Shapefile - Analysis of potential stewardship in support of BES research, Baltimore City, block group -- O'Neal-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/b5c01723bbaf8f285c61c8c71822e9b9

Authors: O'Neal-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.3144.610

Abstract:
Potential stewardship for Residential parcels in Baltimore City summarized by block group. Residential parcels was defined as only those parcels with a land use code of residential (LU_CODE = "R") based on the 2003 Maryland Property View A&T database. PRIZM 5, 15, and 62 classes are also present. PRIZM is the Potential Rating Index by Zip code Markets produced by the Claritas Corporation - > http://www.clusterbigip1.claritas.com/claritas/Default.jsp>. Total Potential stewardship is that land within a parcels not occupied by buildings, that is land that could potentially support vegetation, regardless of whether or not any vegetation is present. Realized Potential Stewardship is land that is currently occupied by vegetation. Not Realized Potential Stewardship is the land not occupied by buildings or existing vegetation, and is thus the land that is potentially available for "greening" initiatives. Normalization for realized and not realized potential stewardship is carried out by dividing by the total potential stewardship. The potential stewardship was calculated using parcel data, building footprints, and GDT census block groups. Building footprints were erased from the parcel area, resulting in a layer indicating the potential stewardship for each parcel. The potential stewardship layer was then unioned MD DNR's 2001 SUFA vegetation layer. All polygons corresponding to water features were deleted since water features cannot undergo "greening." All polygons that did fall in the potential stewardship area were deleted. This resulted in a layer in which the polygons represented the potential stewardship land along with the potential stewardship land occupied by either grass or trees. This layer was then intersected with the census block group layer resulting in a layer that had the potential stewardship land, potential stewardship vegetation, and block group IDs. All attributes were then summarized at the block group level. A cursory analysis of the parcel data indicated that parcel data was outdated for the following block groups: 245102503031, 245102503032, and 245102503033. Certain block groups with very high Normalized Total Potential Stewardship values may be indicative of the fact that building footprint data was missing, although the extent of this problem is unknown. Note: transportation networks are not part of the parcel data, and thus were appropriately not part of this analysis.

knb-lter-bes.3145.610 GIS Shapefile - Identification of priority planting locations for trees within Baltimore City -- O'Neal-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/81bb5a19eff8d01a3fda4b49d31034b0

Authors: O'Neal-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.3145.610

Abstract:
Priority Planting locations by block group for Baltimore City using the index developed by Nowak et al. (unpublished) of the USDA Forest Service Northeastern Experiment Station. The criteria used to make the index were: - Population density: the greater the population density, the greater the priority for tree planting - Tree stocking levels: the lower the tree stocking level (the percent of available greenspace (tree, grass, and soil cover areas) that is occupied by tree canopies), the greater the priority for tree planting - Tree cover per capita: the lower the amount of tree canopy cover per capita (m2/capita), the greater the priority for tree planting Each criteria was standardized on a scale of 0 to 1 with 1 representing the census block with the highest value in relation to priority of tree planting (i.e., the census block with highest population density, lowest stocking density or lowest tree cover per capita were standardized to a rating of 1). Individual scores were combined based on the following formula to produce an overall priority index value between 0 and 100: I = (PD * 40) + (TS * 30) + (TPC * 30) Where I = index value, PD is standardized population density, TS is standardized tree stocking, and TPC is standardized tree cover per capita. Based on this index, Planting priority maps were produced. Standardized value for population density was calculated as PD = (PD_n - PD_m) / PD_r, where PD is the value (0-1), PD_n is the value for the census block (population / km2), PD_m is the minimum value for all census blocks, and PD_r is the range of values among all census blocks (maximum value - minimum value). Standardized value for tree stocking was calculated as TS = (100 - ((T/(T+G)) * 100)) / 100, where TS is the value (0-1), T is percent tree cover, and G is percent grass cover. Standardized value for tree cover per capita was calculated as TPC = 1 - [(TPC_n - TPC_m) / TPC_r], where TPC is the value (0-1), TPC_n is the value for the census block (m2/capita), TPC_m is the minimum value for all census blocks, and TPC_r is the range of values among all census blocks (maximum value - minimum value).

knb-lter-bes.3146.610 GIS Shapefile - Vegetation for private lands, Baltimore City -- O'Neal-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/7f5f622ab2f9e112c4a6a64414552630

Authors: O'Neal-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.3146.610

Abstract:
Vegetation (trees and grass) for parcels defined as private land within Baltimore City. Private land parcels consisted of all those parcels with land use (LU) codes except for the category "Exempt Commercial" (EC). Roads had no LU codes. No parcels with the following LU codes were present in Baltimore City: agricultural (A), county club (CA), marsh land (MA), non-perc land (NP), and town house (TH). LU codes were determined from the Maryland Property View 2003 A&T database. A cursory analysis of the parcel data indicated that errors of omission were present due to insufficient parcel data in certain block groups. Vegetation data used in this analysis came from the MD DNR Forest Service IKONOS derived Strategic Urban Forest Assessment (SUFA) vegetation layer.

knb-lter-bes.3147.610 GIS Shapefile - Vegetation for private lands, block group, Baltimore City -- O'Neal-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/8d2abcdea8f9c3a3090997e588eb9e99

Authors: O'Neal-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.3147.610

Abstract:
Block group summary of private land vegetation (forest and grass). The private land area consists of all parcels not classified as "Exempt Commerical." A cursory analysis of the parcel data indicated that errors of omission were present due to insufficient parcel data in certain block groups. Vegetation data used in this analysis came from the MD DNR Forest Service IKONOS derived Strategic Urban Forest Assessment (SUFA) vegetation layer. The amount of private land forest, grass, and total vegetation was summarized on a block group level. In addition the normalized private land forest, grass, and total vegetation was summarized at block group level by dividing by the area of private land.

knb-lter-bes.3148.610 GIS Shapefile - Property Variables for Baltimore City -- O'Neal-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/970553e983c7bda442f584a7a9dc4717

Authors: O'Neal-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.3148.610

Abstract:
Property Variables for Baltimore City. The Property Variables dataset is a compilation of variables obtained from the MD Property View 2003 Database and derived from BES geospatial datasets. The points in this dataset were subsetted from the MD MD Property View 2003 A&T Database. The criteria used to select these points was: - Can be linked to parcel data using BLOCKLOT2 - LU = Residential (residential land use) - CONSIDR > 10,000 and < 1.5 million (purchase price greater than $10,000 and less than $1.5 million) - STRUDWEL = 01, 02 or 03 (single family home or townhome) - Sales Date after Jan 1 2001. - SQFTSTRUC > 100 (square footage of the structure greater than 100) - YEARBLT > 0 (valid year built). Please refer to the enclosed documentation for a complete data dictionary along with Austin Troy's original request document with comments by Jarlath O'Neil-Dunne.

knb-lter-bes.3149.610 GIS Shapefile - Riparian vegetation (forest and grass only) within a 100ft buffer of all 1:24K streams in Baltimore City. -- O'Neal-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/45edb4d7de7d68c5e419020fdd542543

Authors: O'Neal-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.3149.610

Abstract:
Riparian vegetation (forest and grass only) within a 100ft buffer of all 1:24K streams in Baltimore City. Vegetation data used in this analysis came from the MD DNR Forest Service IKONOS-derived Strategic Urban Forest Assessment (SUFA) vegetation layer.

knb-lter-bes.3150.610 GIS Shapefile - Riparian vegetation (forest and grass only) within a 100ft buffer of all 1:24K streams in Baltimore City, block group -- O'Neal-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/bf4fa130af9431e3ea451dac226b304a

Authors: O'Neal-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.3150.610

Abstract:
Block group summary of riparian vegetation (forest and grass only) within a 100ft buffer of all 1:24K streams in Baltimore City for only those block groups that intersect the stream buffers. The riparian area consists of all land within a 100 ft buffer of 1:24K streams. Vegetation data used in this analysis came from the MD DNR Forest Service IKONOS-derived Strategic Urban Forest Assessment (SUFA) vegetation layer.

knb-lter-bes.3151.610 GIS Shapefile - Summary of Block Group level analyses for Baltimore City. -- O'Neal-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/19d59710fcf0bcd84024ca1235b472fe

Authors: O'Neal-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.3151.610

Abstract:
Summary of Block Group level analyses for Baltimore City. This dataset contains block group level summary information for riparian vegetation, PROW (public right-of-way) vegetation, private land vegetation, and median age of homes. PRIZM codes are also present. The block group boundaries used in this dataset are from year 2000 GDT census data. The riparian analysis involved summarizing the riparian vegetation (forest and grass only) within a 100ft buffer of all 1:24K streams in Baltimore City for only those block groups that intersect the stream buffers. Vegetation data used in this analysis came from the 2001 MD DNR Forest Service IKONOS-derived Strategic Urban Forest Assessment (SUFA) vegetation layer. The amount of riparian forest, grass, and total vegetation was summarized on a block group level. In addition the percent riparian forest, grass, and total vegetation was summarized at block group level by dividing by the area of riparian land. The PROW analysis involved summarizing all PROW (non-parcel) vegetation (forest and grass) in Baltimore City. The PROW area consists of all roads and rights of way along roads. This area was delineated using Baltimore City parcel data by identifying all "non-parcel" areas. A cursory analysis of the "non-parcel" areas indicated that errors of omission were present due to insufficient parcel data. Vegetation data used in this analysis came from the 2001 MD DNR Forest Service IKONOS derived Strategic Urban Forest Assessment (SUFA) vegetation layer. The amount of urparian forest, grass, and total vegetation was summarized on a block group level. In addition the percent urparian forest, grass, and total vegetation was summarized at block group level by dividing by the area of urparian land. The private land area consists of all parcels not classified as "Exempt" or "Exempt Commerical." A cursory analysis of the parcel data indicated that errors of omission were present due to insufficient parcel data in certain block groups. Vegetation data used in this analysis came from the MD DNR Forest Service IKONOS derived Strategic Urban Forest Assessment (SUFA) vegetation layer. The amount of private land forest, grass, and total vegetation was summarized on a block group level. In addition the percent private land forest, grass, and total vegetation was summarized at block group level by dividing by the area of private land. PRIZM codes are generated from demographic and socioeconomic factors drawn from the U.S. Census data, the Claritas Company's PRIZM system classifies over 260,000 U.S. neighborhood markets into clusters. PRIZM codes can be linked with survey information. More information on PRIZM is available at http://www.clusterbigip1.claritas.com/claritas/Default.jsp?main=3&submenu=seg&subcat=segprizm. Median home age was summarized by block group from U.S. Census data. Credits

knb-lter-bes.3152.610 GIS Shapefile - Urparian (non-parcel) vegetation (forest and grass) in Baltimore City -- O'Neal-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/16ef11ae1e39edcdbefe8f9a919463e4

Authors: O'Neal-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.3152.610

Abstract:
Urparian (non-parcel) vegetation (forest and grass) in Baltimore City. The urparian area consists of all roads and rights of way along roads. This area was delineated using Baltimore City parcel data by identifying all "non-parcel" areas. A cursory analysis of the "non-parcel" areas indicated that errors of omission were present due to insufficient parcel data. Vegetation data used in this analysis came from the MD DNR Forest Service IKONOS derived Strategic Urban Forest Assessment (SUFA) vegetation layer.

knb-lter-bes.3153.610 GIS Shapefile - Urparian (non-parcel) vegetation (forest and grass) in Baltimore City, block group -- O'Neal-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/92446b35931d73d0e1932a75ad7813d0

Authors: O'Neal-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.3153.610

Abstract:
Block group summary of urparian (non-parcel) vegetation (forest and grass). The urparian area consists of all roads and rights of way along roads. This area was delineated using Baltimore City parcel data by identifying all "non-parcel" areas. A cursory analysis of the "non-parcel" areas indicated that errors of omission were present due to insufficient parcel data. Vegetation data used in this analysis came from the MD DNR Forest Service IKONOS derived Strategic Urban Forest Assessment (SUFA) vegetation layer.

knb-lter-bes.3160.600 GIS Shapefile - CrimeRisk_1999_2005_MSA -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/05c2c4517dcbce70486a087652a1dc0a

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.3160.600

Abstract:
Tags Social System, Social Institutions, Justice, Crime, BES, Murder, Rape, Robbery, Assault, Burglary, Larceny, Motor Vehicle Theft Summary Analysis of crime data for the Baltimore MSA. Description Crime data assembled by census block group for the MSA from the Applied Geographic Solutions' (AGS) 1999 and 2005 'CrimeRisk' databases distributed by the Tetrad Computer Applications Inc. CrimeRisk is the result of an extensive analysis of FBI crime statistics. Based on detailed modeling of the relationships between crime and demographics, CrimeRisk provides an accurate view of the relative risk of specific crime types at the block group level. Data from 1990 - 1996,1999, and 2004-2005 were used to compute the attributes, please refer to the 'Supplemental Information' section of the metadata for more details. Attributes are available for two categories of crimes, personal crimes and property crimes, along with total and personal crime indices. Attributes for personal crimes include murder, rape, robbery, and assault. Attributes for property crimes include burglary, larceny, and mother vehicle theft. 12 block groups have no attribute information. CrimeRisk is a block group and higher level geographic database consisting of a series of standardized indexes for a range of serious crimes against both persons and property. It is derived from an extensive analysis of several years of crime reports from the vast majority of law enforcement jurisdictions nationwide. The crimes included in the database are the "Part I" crimes and include murder, rape, robbery, assault, burglary, theft, and motor vehicle theft. These categories are the primary reporting categories used by the FBI in its Uniform Crime Report (UCR), with the exception of Arson, for which data is very inconsistently reported at the jurisdictional level. Part II crimes are not reported in the detail databases and are generally available only for selected areas or at high levels of geography. In accordance with the reporting procedures using in the UCR reports, aggregate indexes have been prepared for personal and property crimes separately, as well as a total index. While this provides a useful measure of the relative "overall" crime rate in an area, it must be recognized that these are unweighted indexes, in that a murder is weighted no more heavily than a purse snatching in the computation. For this reason, caution is advised when using any of the aggregate index values. The block group boundaries used in the dataset come from TeleAtlas's (formerly GDT) Dynamap data, and are consistent with all other block group boundaries in the BES geodatabase. Credits UVM Spatial Analysis Lab Use limitations BES use only Extent West -77.314305 East -76.049572 North 39.736284 South 38.700454

knb-lter-bes.3170.150 Biodiversity, Fauna, Vacant Lot Bird Communities -- Nilon, Charlie;
doi:10.6073/pasta/69ba063217dbf21a9862e95a1ea3a527

Authors: Nilon, Charlie;

Full Metadata and Download Link: knb-lter-bes.3170.150

Abstract:
Urban vacant lots can vary considerably in their vegetation structure, from dense, shrubby habitats to wooded remnant fragments that may provide habitat for a variety of birds. By identifying which features promote diverse bird communities, we can determine at which scale management practices should focus and the necessary habitat structure and composition features. We surveyed 150 vacant lots throughout Baltimore,Maryland for their bird communities, lot vegetation, and landscape-level forest cover. An ordination of the bird community indicated a response to a gradient of canopy cover and canopy height at the vacant lot. We also found that forest cover within 100 m of the vacant lot was the most important predictor of abundance for five bird species of interest. Species richness was spatially autocorrelated among sites, indicating that bird communities may also be driven by species� dispersal and environmental gradients across the city. Overall, bird communities are responding to habitat features across multiple scales, from the vacant lot vegetation, to landscape-level forest cover, to city-wide dynamics. Thus, we recommend management practices to focus on increasing city-wide forest cover in order to increase species richness, yet with awareness regarding where the lot occurs within the city.

knb-lter-bes.3180.120 Baltimore Ecosystem Study: Invertebrate and Restoration Habitat Data -- Swan, Christopher;
doi:10.6073/pasta/675c0b7286358f4ba2fc991bc2af1eaa

Authors: Swan, Christopher;

Full Metadata and Download Link: knb-lter-bes.3180.120

Abstract:
An often-cited benefit of river restoration is an increase in biodiversity or shift in composition to more desirable taxa. Yet, hard manipulations of habitat structure often fail to elicit a significant response in terms of biodiversity patterns. In contrast to conventional wisdom, the dispersal of organisms may have as large an influence on biodiversity patterns as environmental conditions. This influence of dispersal may be particularly influential in river networks which are linear branching, or dendritic, and thus constrain most dispersal to the river corridor. As such, some locations in river networks, such as isolated headwaters, are expected to respond less to environmental factors and less by dispersal than more well-connected downstream reaches. We applied this metacommunity framework to study how restoration drives biodiversity patterns in river networks. By comparing assemblage structure in headwater versus more well-connected mainstem sites, we learned that headwater restoration efforts supported higher biodiversity, exhibited more stable ecological communities compared with adjacent, un-restored reaches. Such differences were not evident in mainstem reaches. Consistent with theory and mounting empirical evidence, we attribute this finding to a relatively higher influence of dispersal-driven factors on assemblage structure in more well-connected, higher order reaches. An implication of this work is that, if biodiversity is to be a goal of restoration activity, such local manipulations of habitat should elicit a more profound response in small, isolated streams than in larger downstream reaches. These results offer another significant finding supporting the notion that restoration activity cannot proceed in isolation of larger scale, catchment level degradation. This dataset represents the microhabitat sampling.

knb-lter-bes.3200.100 GIS Shapefile, Spatial boundaries and land cover summaries for eight sub-watersheds of the Baltimore Ecosystem Study LTER -- Lagrosa, John; Welty, Claire;
doi:10.6073/pasta/ad0cce16ef6165913ea26b97e295f985

Authors: Lagrosa, John; Welty, Claire;

Full Metadata and Download Link: knb-lter-bes.3200.100

Abstract:
Watershed boundaries for eight sub-watersheds within the Baltimore Ecosystem Study LTER were delineated at 1-meter and 30-meter spatial resolutions. Watershed boundaries were used to calculate total area and extract and summarize existing land cover data (1m 2016 Chesapeake Conservancy Land Cover Data Project; 30m 2011 USGS National Land Cover Database). Two spatial resolutions are included to accommodate the needs of studies with different input requirements. In addition, providing data at both spatial scales highlights the importance of spatial resolution on study results.

knb-lter-bes.3210.110 GIS Shapefile, Tree Canopy Change 2007 - 2015 - Baltimore City -- O'Neil-Dunne, Jarlath;
doi:10.6073/pasta/79c1d2079271546e61823a98df2d2039

Authors: O'Neil-Dunne, Jarlath;

Full Metadata and Download Link: knb-lter-bes.3210.110

Abstract:
This layer is a high-resolution tree canopy change-detection layer for Baltimore City, MD. It contains three tree-canopy classes for the period 2007-2015: (1) No Change; (2) Gain; and (3) Loss. It was created by extracting tree canopy from existing high-resolution land-cover maps for 2007 and 2015 and then comparing the mapped trees directly. Tree canopy that existed during both time periods was assigned to the No Change category while trees removed by development, storms, or disease were assigned to the Loss class. Trees planted during the interval were assigned to the Gain category, as were the edges of existing trees that expanded noticeably. Direct comparison was possible because both the 2007 and 2015 maps were created using object-based image analysis (OBIA) and included similar source datasets (LiDAR-derived surface models, multispectral imagery, and thematic GIS inputs). OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. No accuracy assessment was conducted, but the dataset will be subjected to manual review and correction. 2006 LiDAR and 2014 LiDAR data was also used to assist in tree canopy change.

knb-lter-bes.3300.110 BESLTER Permanent Plot vegetation data combined for the survey years of 1998, 2003, and 2015 -- Templeton, Laura;
doi:10.6073/pasta/67cd7c50ea5b87369c2b64be62db366f

Authors: Templeton, Laura;

Full Metadata and Download Link: knb-lter-bes.3300.110

Abstract:
BESLTER Permanent Plot vegetation data combined for the survey years of 1998, 2003, and 2015. Introduction: Urban forests are often highly fragmented with many exotic species. Altered disturbance regimes and environmental pollutants influence urban forest vegetation. One of the best ways to understand the impacts of urban land-use on forest composition is through long-term research. In 1998, the Baltimore Ecosystem Study (BES) established eight forest plots to investigate the impacts of urbanization on natural ecosystems (Groffman et al. 2006). Four plots were established in urban forest patches and four in rural forests. All eight plots are located within the Baltimore Metropolitan Area. Purpose: Vegetation in the BES long-term plots were sampled in 1998, 2003, and 2015 to understand the influence of urbanization on species abundances and to quantify change in forest composition, diversity, and structure (Groffman et al. 2006 and Templeton 2016). Plot Structure: Six of the plots are 40�40m (1600m2). The Hillsdale 1 and 2 plots are 30�30m (900m2). The Hillsdale plots are smaller to fit within the boundaries of the forest patch. Sites were selected with the following criteria in mind: 1) to represent urban and non-urban forests, 2) away from obvious habitat boundaries or edges, 3) with consistent drainage lines within the plot, and 4) with at least 80% continuous tree canopy. All vegetation layers were sampled in order to characterize the structure and composition of the plant community. Each plot was permanently outlined with metal markers buried at or below the soil line. Between each of the plot corners, metal markers were placed at 10m intervals. The 10m markers divided the plot into 16 10x10m subplots (nine 10x10m subplots at Hillsdale). Each 10x10m subplot was then further divided into four 5x5m subplots. Only one of the four 5x5m subplots in each 10x10m subplot was used for all vegetation sampling below the tree layer. Shrubs and vines were measured along two transects. Transect lines were two adjacent sides of the 5x5m subplot. Each subplot had two 2x0.5m (1^2m) quadrats. Metal markers inside each 5x5m subplot designated the quadrat locations. Quadrats were arranged perpendicular to each other. Thus, there were 16 5x5m subplots in each 40x40m plot, with a total of 32 quadrats. In the two 30x30m plots, there were 9 5�5m subplots, with a total of 18 quadrats. Plot Locations: Urban Plots Hillsdale 1: 39 D 19 Min28.14 S N, 76 D 42 M 16.49 S W Hillsdale 2: 39 D 19 M 31.24 S N, 76 D 42 M 28.62 S W Leakin 1: 39 D 18 M 1.32 S N, 76 D 41 M 37.08 S W Leakin 2: 39 D 18 M 5.42 S N, 76 D 41 M 34.15 S W Rural Plots Oregon Upslope 1: 39 D 28 M 51.11 S N, 76 D 41 M 22.50 S W Oregon Midslope 1: 39 D 28 M 51.32 S N, 76 D 41 M 18.24 S W Oregon Upslope 2: 39 D 29 M 12.74 S N, 76 D 41 M 22.88 S W Oregon Midslope 2: 39 D 29 M 12.68 S N, 76 D 41 M 18.62 S W Sampling Design: Tree Layer: All tree species individuals with a diameter at breast height (DBH) of greater or equal to 8cm were identified as trees. DBH was measured using diameter tape. Canopy level (canopy, subcanopy, or understory) for each tree was visually determined based on crown height. In 1998, every tree within the plot was issued a tag number. In subsequent surveys, the tag number was recorded or a new tag was added in the event an individual was untagged. The height of the tallest tree in each 10x10m subplot was measured using an Opti-Logic Corporation Insight 100LH Rangefinder. Sapling Layer: All individuals classified as tree species that measured less than 8cm DBH were identified as saplings. DBH was measured to the nearest hundredth decimal place using General Ultratech digital calipers. In 1998, saplings within each 5x5 subplot were issued a tag number. In subsequent surveys, the tag number was recorded or a new tag was added in the event an individual was untagged. The height of the tallest sapling in each 5�5m subplot was measured using an Opti-Logic Corporation Insight 100LH Rangefinder. Vine and Shrub Layer: Species determined to be shrubs or vines were measured along two 5m transects. The adjacent lower and left perimeters of each 5x5m subplot were used as the two transect lines. Measurement of vines and shrubs began at the transect line that ran parallel to the numeric axis on the plot layout going in the direction towards the alphabetic axis. Sampling then progressed to the second transect line that ran parallel to the alphabetic axis on the plot layout (see link to plot layout illustration). Measurements were recorded in 1m segments starting with 0-1m as the first segment and ending with the tenth at 9-10m. For each segment, shrub and vine species that touched the transect line were measured in centimeters using a metric ruler. To be recorded, plants had to have a diameter greater than or equal to 5cm. If a shrub or vines species had less than a 10cm gap while touching the line, the recording for that species was considered one continuous measurement. The height of the tallest shrub along each pair of transects for each 5�5m subplot was measured using an Opti-Logic Corporation Insight 100LH Rangefinder. Herb and Seedling Layer: All seedlings and herbaceous species were identified, tallied, and percent cover visually estimated within each 2x0.5m quadrat. Canopy Cover: Canopy gap percentage was visually estimated in increments of 5% within each 10x10m subplot. At each subplot, all field technicians estimated canopy gap independently and a final estimate of missing canopy was determined as a consensus value. A template from the Forest Service�s field manual used in the forest inventory analysis (FIA) program was used to orient the 2015 field crew to different organizations and aggregations of canopy cover (U.S. Forest Service, 2005). Table Descriptions: Summary Table: Summarization of field data from 1998, 2003, and 2015. BA stands for basal area and is calculated from DBH using the following equation: BA=(DBH/2)^2 x Pi. Total species richness was the sum of unique species found in each plot. Trees: DBH, number of stems measured, BA per stem, total BA (sum of BA for each stem on an individual), and canopy status for each tree measured (canopy, subcanopy, or understory). Additionally, if a vine was found growing on the tree, the vine was identified and the percentage of canopy cover was estimated. A percentage of 0 means that a vine was growing on the trunk, but had not reached the canopy. A dot (.) in the tag number column indicates that an individual was not counted as a tree in prior surveys. N/A entries indicate that data was missing. Trees with multiple stems have a data row for each measured stem with only the first row listing the total number of stems. The subsequent row with the same tag number and dots in the stem columns are the associated stems. There are some instances where multiple trees have the same tag number. Tree Metrics: Abundance columns are the total number of individuals of a species, organized by region (urban or rural). Relative Abundance (Rel. Ab.) is the percentage of individuals of a species within the region. Total BA is the sum of stem BA for a given species by region. Relative Dominance (Rel. Dom.) is the percentage of total BA of a species within the region. Saplings: DBH, BA per stem, total BA (sum of BA for each stem on an individual), and number of stems measured for each sapling individual. A dot (.) in the tag number column indicates that an individual was not counted as a sapling in prior surveys. N/A entries indicate that data was missing. Multi-stemmed saplings have a sapling number greater than two in the stem columns with only one line indicating the number of stems on an individual sapling. Subsequent data lines with the same tag number and dots in the stem columns are associated stems. There are some instances where multiple saplings have the same tag number. Sapling Metrics: Abundance columns are the total number of individuals of a species organized by region (urban or rural). Relative Abundance (Rel. Ab.) is the percentage of individuals of a species within the region. Total BA is the sum of stem BA for a given species by region. Relative Dominance (Rel. Dom.) is the percentage of total BA of a species within the region. Height Data: The tallest tree, sapling, and shrub for each subplot (trees and saplings) or transect (shrubs). If no tree, sapling, or shrub was present, there is a 0 in the height column. If data is missing, a dot (.) is in the height column. Only the 2015 survey recorded species ID and tree and sapling tag numbers for the tallest individuals. Canopy Cover: The percentage of missing canopy (gap) as visually assessed by each survey year�s field team. Canopy gap was measured to the nearest 5%. Tree Seedling Cover: Each species-coded column is the sum percentage of individuals within a tree seedling species for each plot in each survey year. As percentages were summed from each quadrat within a plot, it is possible to have percentages greater than 100. Herbaceous Cover: Each species-coded column is the sum percentage of individuals within an herbaceous species for each plot in each survey year. As percentages were summed from each quadrat within a plot, it is possible to have percentages greater than 100. Shrub Cover: Each species-coded column is the amount of cover (cm) of a shrub species measured along a transect and summed for each plot in each survey year. Vine Cover: Each species-coded column is the amount of cover (cm) of a vine species measured along a transect and summed for each plot in each survey year. All Species (P/A): A table of all plant species (coded) from all forest layers measured within a plot. Given that each forest layer was measured differently, species in this table are coded as either present (1) or absent (0) within each plot. Species Codes: A list of the binomial nomenclature and common names associated with each species code used in the dataset. Out of date nomenclature used in the previous two surveys are listed in the comments column. Raw data files can be found: 1. A CD in the BES 1998 and 2003 Permanent Plot Binder in the file cabinets in the Pickett IES RA office (1998 and 2003 data only). 2. On Laura Templeton�s Dropbox account (1998, 2003, and 2015). 3. Saved on Laura Templeton�s personal computer (1998, 2003, and 2015). 1998 Project lead-Mary Cadenasso 2003 Project lead- Grace Brush (gbrush@jhu.edu ) 2015 Project lead- Laura Templeton Questions about data can be directed to: Laura Templeton: laura.templeton.k@gmail.com Cary Institute Ecosystems Studies Rm 141 5200 Westland Blvd Baltimore, MD 21227 Literature cited: Groffman, P.M., Pouyat, R.V., Cadenasso, M.L., Zipperer, W.C., Szlavecz, K., Yesilonis, I.D., and Brush, G. S., 2006. Land use context and natural soil controls on plant community composition and soil nitrogen and carbon dynamics in urban and rural forests. Forest Ecology and Management, 236, pp.177-192. Templeton, L. K., 2016. Changes in the community structure of urban and rural forest patches in Baltimore from 1998 to 2015 (Master�s Thesis, University of Maryland, College Park). U.S. Forest Service, 2005. Forest Inventory Analysis Version 3.0 Phase 3 Field Guide- Crowns: Measurements and Sampling. USDA.

knb-lter-bes.331.40 GIS Shapefile - Soil, Survey for City of Baltimore, Maryland -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/c775a5e7fc35f615a67c2e483f50b5ae

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.331.40

Abstract:
Tags soil survey, soils, Soil Survey Geographic, SSURGO Summary SSURGO depicts information about the kinds and distribution of soils on the landscape. The soil map and data used in the SSURGO product were prepared by soil scientists as part of the National Cooperative Soil Survey. Description This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a 3.75 minute quadrangle format and include a detailed, field verified inventory of soils and nonsoil areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties. Credits There are no credits for this item. Use limitations The U.S. Department of Agriculture, Natural Resources Conservation Service, should be acknowledged as the data source in products derived from these data. This data set is not designed for use as a primary regulatory tool in permitting or citing decisions, but may be used as a reference source. This is public information and may be interpreted by organizations, agencies, units of government, or others based on needs; however, they are responsible for the appropriate application. Federal, State, or local regulatory bodies are not to reassign to the Natural Resources Conservation Service any authority for the decisions that they make. The Natural Resources Conservation Service will not perform any evaluations of these maps for purposes related solely to State or local regulatory programs. Photographic or digital enlargement of these maps to scales greater than at which they were originally mapped can cause misinterpretation of the data. If enlarged, maps do not show the small areas of contrasting soils that could have been shown at a larger scale. The depicted soil boundaries, interpretations, and analysis derived from them do not eliminate the need for onsite sampling, testing, and detailed study of specific sites for intensive uses. Thus, these data and their interpretations are intended for planning purposes only. Digital data files are periodically updated. Files are dated, and users are responsible for obtaining the latest version of the data. Extent West -76.713689 East -76.526117 North 39.374398 South 39.194856 Scale Range There is no scale range for this item.

knb-lter-bes.332.600 GIS Shapefile - Soil, Survey County of Baltimore, Maryland -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/5c91d505fb2eb7a7c57fc64c8cdaadde

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.332.600

Abstract:
Tags There are no tags for this item. Summary There is no summary for this item. Description Soils for Baltimore County. No metadata exists for this dataset. It was received from Rich Pouyat (USFS) . As of 15 July 2004 SSURGO data is not available from NRCS for Baltimore County. Credits There are no credits for this item. Use limitations There are no access and use limitations for this item. Extent West -76.904439 East -76.315722 North 39.727769 South 39.177238 Scale Range There is no scale range for this item.

knb-lter-bes.333.610 GIS Shapefile - Soil, Sampling locations, Baltimore City -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/73499577fa03ee745fbcf56f98f0a73c

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.333.610

Abstract:
Soil_Samples_BACI Available only by request on a case by case basis. Contact rthe author, David Nowak, at dnowak@fs.fed.us Tags Biophysical Resources, Land, Social Institutions, Health, BES, Soil, Lead, Sample, UFORE Summary Samples were taken to relate soil data to vegetation data obtained for the Urban Forestry Effects Model (UFORE). Description The data is soil concentrations and characteristics of the following: land use, bulk density, sand, silt, clay, pH, organic matter, nitrogen, Al, P, S, Ti, Cr, Mn, Fe, Co, Ni, Cu Zn, Mo, Pb, Cd, Na, Mg, K, Ca, and V. Soils were sampled in 125 plots located within the City of Baltimore in the summer of 2000. The plots were randomly stratified by Anderson Land Cover Classification System Level II, which included commercial, industrial, institutional, transportation right-of-ways, high and medium density residential (there were no low density residential areas identified within the city boundaries), golf course, park, urban open, forest, and wetland land-use types. The number of plots situated in each land-use type was weighted to their proportion of spatial area within the City. The resultant number of plots sampled for soil by land-use type was: commercial (n = 2); industrial (n = 3); institutional (n = 10); transportation right-of-ways (n = 7); high density residential (n = 19); medium density residential (n = 33); golf course (n = 3); riparian (n=2); park (n = 10); urban open (n = 10); and forest (n = 26) land-use types, respectively. The distribution of plots represents the proportion of area covered by impervious surfaces. Credits Rich Pouyat, USDA Forest Service Use limitations Not for profit use only Extent West -76.711030 East -76.530612 North 39.371355 South 39.200686 Scale Range There is no scale range for this item. The data is soil concentrations and characteristics of the following: land use, bulk density, sand, silt, clay, pH, organic matter, nitrogen, Al, P, S, Ti, Cr, Mn, Fe, Co, Ni, Cu Zn, Mo, Pb, Cd, Na, Mg, K, Ca, and V. Soils were sampled in 125 plots located within the City of Baltimore in the summer of 2000. The plots were randomly stratified by Anderson Land Cover Classification System Level II, which included commercial, industrial, institutional, transportation right-of-ways, high and medium density residential (there were no low density residential areas identified within the city boundaries), golf course, park, urban open, forest, and wetland land-use types. The number of plots situated in each land-use type was weighted to their proportion of spatial area within the City. The resultant number of plots sampled for soil by land-use type was: commercial (n = 2); industrial (n = 3); institutional (n = 10); transportation right-of-ways (n = 7); high density residential (n = 19); medium density residential (n = 33); golf course (n = 3); riparian (n=2); park (n = 10); urban open (n = 10); and forest (n = 26) land-use types, respectively. The distribution of plots represents the proportion of area covered by impervious surfaces.

knb-lter-bes.3400.160 Baltimore Ecosystem Study: Soil moisture and temperature along an urban to rural gradient, 2011 - present -- Groffman, Peter M; Martel, Lisa D;
doi:10.6073/pasta/76e44dc0b004859a661f74ebe1d8a610

Authors: Groffman, Peter M; Martel, Lisa D;

Full Metadata and Download Link: knb-lter-bes.3400.160

Abstract:
Soil temperature and soil moisture have been measured at multiple locations in and around Baltimore Maryland to provide data on these variables in forests and lawns across an urban to rural gradient. In July 2011, we installed one Decagon Em50 Datalogger with five 5TM VWC/Temperature probes at four established forested, upslope, 20 x 20-m plots, two rural (ORU1, ORU2) and two urban (LEA1, LEA2), at 2 forested riparian sites at two transects along a stream (ORUR, ORLR), and two lawn plots on the campus of the University of Maryland Baltimore County campus (UMBC1, UMBC 2). Probes were buried horizontally at 10cm depth (except UMBC1 and UMBC2 where the five probes are mounted horizontally at a single location at depths of 50, 40, 30, 20 and 10 cm depth). At the upslope forested plots, the five probes are replicates. At the two riparian sites, probes are deployed in either "hummocks (drier, higher)" or in "hollows (lower, wetter)". Soil temperature and soil moisture were measured at hourly intervals on these plots beginning in July 2011. Earlier soil moisture data were collected monthly (1999-2011), and can be found in https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-bes&identifier=417

knb-lter-bes.349.610 GIS Shapefile - GIS Shapefile, Assessments and Taxation Database, MD Property View 2003, Baltimore City -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/66ffb24393991501d49f4fb414b453f1

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.349.610

Abstract:
AT_2003_BACI_1 File Geodatabase Feature Class Thumbnail Not Available Tags There are no tags for this item. Summary There is no summary for this item. Description MD Property View 2003 A&T Database. For more information on the A&T Database refer to the enclosed documentation. This layer was edited to remove spatial outliers in the A&T Database. Spatial outliers are those points that were not geocoded and as a result fell outside of the Baltimore City Boundary; 416 spatial outliers were removed from this layer. The field BLOCKLOT2 can be used to join this layer with the Baltimore City parcel layer. Credits There are no credits for this item. Use limitations There are no access and use limitations for this item. Extent West -76.713418 East -76.526031 North 39.374429 South 39.197452

knb-lter-bes.350.610 GIS Shapefile - GIS Shapefile, Assessments and Taxation Database, MD Property View 2004, Anne Arundel County -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/df8ce7b9e414dbc4949aba50fe2015c1

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.350.610

Abstract:
AT_2004_ANNE File Geodatabase Feature Class Thumbnail Not Available Tags Socio-economic resources, Information, Social Institutions, Hierarchy, Territory, BES, Parcel, Property, Property View, A&T, Database, Assessors, Taxation Summary Serves as a basis for performing various analyses based on parcel data. Description Assessments & Taxation (A&T) Database from MD Property View 2004 for Anne Arundel County. The A&T Database contains parcel data from the State Department of Assessments and Taxation; it incorporates parcel ownership and address information, parcel valuation information and basic information about the land and structure(s) associated with a given parcel. These data form the basis for the 2004 Database, which also includes selected Computer Assisted Mass Appraisal (CAMA) characteristics, text descriptions to make parcel code field data more readily accessible and logical True/False fields which identify parcels with certain characteristics. Documentation for A&T, including a thorough definition for all attributes is enclosed. Complete Property View documentation can be found at http://www.mdp.state.md.us/data/index.htm under the "Technical Background" tab. It should be noted that the A&T Database consists of points and not parcel boundaries. For those areas where parcel polygon data exists the A&T Database can be joined using the ACCTID or a concatenation of the BLOCK and LOT fields, whichever is appropriate. (Spaces may have to be excluded when concatenating the BLOCK and LOT fields). A cursory review of the 2004 version of the A&T Database indicates that it has more accurate data when compared with the 2003 version, particularly with respect to dwelling types. However, for a given record it is not uncommon for numerous fields to be missing attributes. Based on previous version of the A&T Database it is also not unlikely that some of the information is inaccurate. This layer was edited to remove points that did not have a valid location because they failed to geocode. There were 897 such points. A listing of the deleted points is in the table with the suffix "DeletedRecords." Credits Maryland Department of Planning Use limitations BES use only. Extent West -76.838738 East -76.395283 North 39.238726 South 38.708588 Scale Range There is no scale range for this item.

knb-lter-bes.3500.101 Mosquito Ovitrap Data from Baltimore City and County (2011-2016) -- LaDeau, Shannon;
doi:10.6073/pasta/eea5c10e7129f6f2b3edd47d0e389b9e

Authors: LaDeau, Shannon;

Full Metadata and Download Link: knb-lter-bes.3500.101

Abstract:
Mosquitoes are an important component of insect biodiversity across all ecosystems. As invertebrates, they are sensitive to abiotic conditions during both aquatic juvenile and terrestrial adult stages. The data here were collected to identify how mosquito species composition, phenology, and peak population abundances are influenced by changes in abiotic and biotic conditions along an urbanization gradient from residential Baltimore City to forested Baltimore County. Many of the sample sites were aligned with the LTER's stream sampling along the Gwynns Falls, with additional sites located in community gardens in residential neighborhoods near Watershed 263.

knb-lter-bes.351.610 GIS Shapefile - GIS Shapefile, Assessments and Taxation Database, MD Property View 2004, Baltimore City -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/13fbbd2a3feb4b5b9177a1a9cbb8f8d1

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.351.610

Abstract:
AT_2004_BACI File Geodatabase Feature Class Thumbnail Not Available Tags Socio-economic resources, Information, Social Institutions, Hierarchy, Territory, BES, Parcel, Property, Property View, A&T, Database, Assessors, Taxation Summary Serves as a basis for performing various analyses based on parcel data. Description Assessments & Taxation (A&T) Database from MD Property View 2004 for Baltimore City. The A&T Database contains parcel data from the State Department of Assessments and Taxation; it incorporates parcel ownership and address information, parcel valuation information and basic information about the land and structure(s) associated with a given parcel. These data form the basis for the 2004 Database, which also includes selected Computer Assisted Mass Appraisal (CAMA) characteristics, text descriptions to make parcel code field data more readily accessible and logical True/False fields which identify parcels with certain characteristics. Documentation for A&T, including a thorough definition for all attributes is enclosed. Complete Property View documentation can be found at http://www.mdp.state.md.us/data/index.htm under the "Technical Background" tab. It should be noted that the A&T Database consists of points and not parcel boundaries. For those areas where parcel polygon data exists the A&T Database can be joined using the ACCTID or a concatenation of the BLOCK and LOT fields, whichever is appropriate. (Spaces may have to be excluded when concatenating the BLOCK and LOT fields). A cursory review of the 2004 version of the A&T Database indicates that it has more accurate data when compared with the 2003 version, particularly with respect to dwelling types. However, for a given record it is not uncommon for numerous fields to be missing attributes. Based on previous version of the A&T Database it is also not unlikely that some of the information is inaccurate. This layer was edited to remove points that did not have a valid location because they failed to geocode. There were 379 such points. A listing of the deleted points is in the table with the suffix "DeletedRecords." Credits Maryland Department of Planning Use limitations BES use only. Extent West -76.713418 East -76.526031 North 39.374429 South 39.197452 Scale Range There is no scale range for this item.

knb-lter-bes.352.610 GIS Shapefile - GIS Shapefile, Assessments and Taxation Database, MD Property View 2004, Baltimore County -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/64b774176d162e0c339bde0987f6feb1

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.352.610

Abstract:
AT_2004_BACO File Geodatabase Feature Class Thumbnail Not Available Tags Socio-economic resources, Information, Social Institutions, Hierarchy, Territory, BES, Parcel, Property, Property View, A&T, Database, Assessors, Taxation Summary Serves as a basis for performing various analyses based on parcel data. Description Assessments & Taxation (A&T) Database from MD Property View 2004 for Baltimore County. The A&T Database contains parcel data from the State Department of Assessments and Taxation; it incorporates parcel ownership and address information, parcel valuation information and basic information about the land and structure(s) associated with a given parcel. These data form the basis for the 2004 Database, which also includes selected Computer Assisted Mass Appraisal (CAMA) characteristics, text descriptions to make parcel code field data more readily accessible and logical True/False fields which identify parcels with certain characteristics. Documentation for A&T, including a thorough definition for all attributes is enclosed. Complete Property View documentation can be found at http://www.mdp.state.md.us/data/index.htm under the "Technical Background" tab. It should be noted that the A&T Database consists of points and not parcel boundaries. For those areas where parcel polygon data exists the A&T Database can be joined using the ACCTID or a concatenation of the BLOCK and LOT fields, whichever is appropriate. (Spaces may have to be excluded when concatenating the BLOCK and LOT fields). A cursory review of the 2004 version of the A&T Database indicates that it has more accurate data when compared with the 2003 version, particularly with respect to dwelling types. However, for a given record it is not uncommon for numerous fields to be missing attributes. Based on previous version of the A&T Database it is also not unlikely that some of the information is inaccurate. This layer was edited to remove points that did not have a valid location because they failed to geocode. There were 5870 such points. A listing of the deleted points is in the table with the suffix "DeletedRecords." Credits Maryland Department of Planning Use limitations BES use only. Extent West -76.897802 East -76.335214 North 39.726520 South 39.192552 Scale Range There is no scale range for this item.

knb-lter-bes.353.610 GIS Shapefile - GIS Shapefile, Assessments and Taxation Database, MD Property View 2004, Carroll County -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/8ca97dc2b3337ab710d456af5ed61bb2

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.353.610

Abstract:
AT_2004_CARR File Geodatabase Feature Class Thumbnail Not Available Tags Socio-economic resources, Information, Social Institutions, Hierarchy, Territory, BES, Parcel, Property, Property View, A&T, Database, Assessors, Taxation Summary Serves as a basis for performing various analyses based on parcel data. Description Assessments & Taxation (A&T) Database from MD Property View 2004 for Carroll County. The A&T Database contains parcel data from the State Department of Assessments and Taxation; it incorporates parcel ownership and address information, parcel valuation information and basic information about the land and structure(s) associated with a given parcel. These data form the basis for the 2004 Database, which also includes selected Computer Assisted Mass Appraisal (CAMA) characteristics, text descriptions to make parcel code field data more readily accessible and logical True/False fields which identify parcels with certain characteristics. Documentation for A&T, including a thorough definition for all attributes is enclosed. Complete Property View documentation can be found at http://www.mdp.state.md.us/data/index.htm under the "Technical Background" tab. It should be noted that the A&T Database consists of points and not parcel boundaries. For those areas where parcel polygon data exists the A&T Database can be joined using the ACCTID or a concatenation of the BLOCK and LOT fields, whichever is appropriate. (Spaces may have to be excluded when concatenating the BLOCK and LOT fields). A cursory review of the 2004 version of the A&T Database indicates that it has more accurate data when compared with the 2003 version, particularly with respect to dwelling types. However, for a given record it is not uncommon for numerous fields to be missing attributes. Based on previous version of the A&T Database it is also not unlikely that some of the information is inaccurate. This layer was edited to remove points that did not have a valid location because they failed to geocode. There were 848 such points. A listing of the deleted points is in the table with the suffix "DeletedRecords." Credits Maryland Department of Planning Use limitations BES use only. Extent West -77.306843 East -76.779275 North 39.727017 South 39.342858 Scale Range There is no scale range for this item.

knb-lter-bes.354.610 GIS Shapefile - GIS Shapefile, Assessments and Taxation Database, MD Property View 2004, Harford County -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/9130658f46ebceeb656164b6f8feabb0

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.354.610

Abstract:
AT_2004_HARF File Geodatabase Feature Class Thumbnail Not Available Tags Socio-economic resources, Information, Social Institutions, Hierarchy, Territory, BES, Parcel, Property, Property View, A&T, Database, Assessors, Taxation Summary Serves as a basis for performing various analyses based on parcel data. Description Assessments & Taxation (A&T) Database from MD Property View 2004 for Harford County. The A&T Database contains parcel data from the State Department of Assessments and Taxation; it incorporates parcel ownership and address information, parcel valuation information and basic information about the land and structure(s) associated with a given parcel. These data form the basis for the 2004 Database, which also includes selected Computer Assisted Mass Appraisal (CAMA) characteristics, text descriptions to make parcel code field data more readily accessible and logical True/False fields which identify parcels with certain characteristics. Documentation for A&T, including a thorough definition for all attributes is enclosed. Complete Property View documentation can be found at http://www.mdp.state.md.us/data/index.htm under the "Technical Background" tab. It should be noted that the A&T Database consists of points and not parcel boundaries. For those areas where parcel polygon data exists the A&T Database can be joined using the ACCTID or a concatenation of the BLOCK and LOT fields, whichever is appropriate. (Spaces may have to be excluded when concatenating the BLOCK and LOT fields).

knb-lter-bes.360.600 GIS Shapefile - Brownfields, Baltimore City, Shapefile -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/e855a6257057a08df74ab60f7b58d4af

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.360.600

Abstract:
Brownfields_BACI File Geodatabase Feature Class Thumbnail Not Available Tags Biophysical Resources, Air, Land, Water, BES, Brownfields, Pollution Summary BES Analysis Description Brownfield parcels in Baltimore City. No metadata was provided with this dataset; the UVM Spatial Analysis Lab has attempted to evaluate this dataset and generate metadata. This dataset appears to have a high degree of positional accuracy based on comparisons with high resolution imagery. Credits Maryland Department of the Environment Use limitations BES research only. Extent West -76.661468 East -76.530941 North 39.334224 South 39.235433 Scale Range There is no scale range for this item.

knb-lter-bes.3600.150 Pharmaceutical effects on biofilm functioning quantified via contaminant exposure substrates presented in Rosi et al. 2018. -- Rosi, Emma; Reisinger, Alexander;
doi:10.6073/pasta/334c3008573cc1cf908df5dc980fa63f

Authors: Rosi, Emma; Reisinger, Alexander;

Full Metadata and Download Link: knb-lter-bes.3600.150

Abstract:
An ongoing component of the Baltimore urban long-term ecological research (LTER) project (Baltimore Ecosystem Study, BES) is the use of the watershed approach and monitoring of stream water quality to evaluate the impacts of multiple chemical stressors on urban stream ecosystem functioning within Baltimore. The LTER research has focused on the Gwynns Falls watershed, which spans a gradient from highly urban, urban-residential, and suburban zones. In addition, a forested watershed serves as a reference. The long-term sampling network includes four longitudinal sampling sites along the Gwynns Falls mainstem, as well as several small (40-100 ha) watershed within or near the Gwynns Falls, providing data on water quality in different land use zones of the watersheds. Each study site is continuously monitored for discharge and is sampled weekly for water chemistry. Those data are available elsewhere on the BES website. We are interested in studying the effects of pharmaceuticals and personal care products (PPCPs) on stream biofilm functioning within urban streams. We constructed and deployed contaminant exposure substrates (CES) in four streams within the greater Baltimore, Maryland, USA area to measure the responses of biofilms in each of the four streams to caffeine, ciprofloxacin, cimetidine, diphenhydramine, and no PPCPs. We incubated CES for 2 weeks in the four different streams, with five replicate CES for each treatment being randomly placed on plastic L-bars within each stream. After the two-week deployment, we used the light-dark incubation approach to estimate gross primary production and community respiration via change in dissolved oxygen (DO) for biofilms colonizing substrates (either cellulose sponges to select heterotrophic biofilms or fritted glass disks to select for autotrophic biofilms) topping each CES. This dataset includes all of the raw data for the light-dark incubations used to calculate gross primary production and community respiration for the various CES treatments at different sites. A subset of these data were used to estimate the effects of PPCPs on community respiration that is presented in the following publication: Rosi, E.J., H.A. Bechtold, D. Snow, M. Rojas, A.J. Reisinger, and J.J. Kelly. 2018. Urban stream microbial communities show resistance to pharmaceutical exposure. Ecosphere 9(1):e02041. doi: 10.1002/ecs2.2041 Each stream studied in this dataset is a core BES monitoring stream, and additional water chemistry and hydrology data are available elsewhere on the BES data portal. Codes and abbreviations 1 - GwynnsRun - Gwynns Run at Gwynns Falls - Urban 2 - GwynnsFalls - Gwynns Falls at Carroll Park - Urban 3 - DeadRun - Dead Run at Krome Avenue - Urban 4 - GwynnsBrook - Gwynns Falls at Gwynnbrook Avenue (Delight) - Suburban Column,Column Name,Variable-if different than Column Name (units) A,cup,identifier for CES cup replicate B,site, Site C,compound, Treatment - can be one of: Ciprofloxacin, Cimetidine, Caffeine, Control, or Diphenhydramine D,substrate, substrate topping the CES used to select for either autotrophic or heterotrophic biofilms - can be either Cellulose (heterotrophic) or Fr. Glass (autotrophic) E,light, light treatment for the incubation, either light (used to estimate NPP and GPP) or dark (used to estimate CR) F,o2.init, initial dissolved oxygen (DO) concentration of incubation water (mg O2/L) G,o2.final, final DO concentration after CES incubation has completed (mg O2/L) H,t.start, start time for the incubation - time when incubation vials were filled and closed (HH:MM:SS) I,t.end, end time for the incubation - time when incubation vials were opened and o2.final was measured (HH:MM:SS) J,blank.o2.init, initial DO concentration of incubation water used for blank incubation vials (no CES substrate) that are used to correct for water column activity (mg O2/L) K,blank.o2.final, final DO concentration of water in blank incubations that are used to correct for water column activity (mg O2/L) L,blank.t.start, start time for the blank incubations (HH:MM:SS) M,blank.t.end, end time for the blank incubations (HH:MM:SS) Methods: We used CES to measure the responses of biofilms in each of the four streams to caffeine, cimetidine, ciprofloxacin, and diphenhydramine. This contaminant exposure method allowed us to test the effects of PPCPs on the structure and function of microbial communities in situ. CES consisted of 30-mL polyethylene cups filled with a 2% (by weight) agarose gel amended with caffeine, ciprofloxacin, cimetidine, diphenhydramine, or no pharmaceutical. The concentration of PPCP in each cup was 0.05 mol/L. Each cup was capped with either a cellulose sponge cloth or a fritted glass disk to promote colonization by heterotrophic and autotrophic biofilms, respectively. Five replicate CES of each PPCP treatment and an additional control treatment were secured to the stream bottom on plastic L-bars, with treatments and replicates arranged randomly. CES were deployed for two weeks in March 2012. After deployment, CES were collected and transported to the laboratory on ice. We used the light-dark incubation approach to estimate GPP and CR from the different substrates for each CES. Each substrate was placed ina 50-mL centrifuge tube and each tube was filled with filtered stream water with known initial DO concentration. Each tube was capped underwater to remove all air bubbles and was incubated in the light and dark for 2-4h for each light treatment. We included blank tubes, which were filled with filtered stream water only, to correct for changes in background DO. After the 2-4h incubation period, we measured the final DO concentration in each of the tubes. These incubation data are what are included in this dataset. To calculate GPP and CR, standard light-dark DO incubation methods can be followed. For example, see: Tank, J.L., A.J. Reisinger, and E.J. Rosi. 2017. Ch. 31: Nutrient limitation and uptake. In Methods in Stream Ecology Vol 2: Ecosystem Function (3rd Edition), eds: G.A. Lamberti and F.R. Hauer. Academic Press, San Diego, CA, USA.

knb-lter-bes.361.600 GIS Shapefile - GIS Shapefile, Cadastral_Planimetric, Building Footprints, Baltimore City -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/5a522f4dfdc54212ecb51cef4a7f23cf

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.361.600

Abstract:
Buildings_BACI File Geodatabase Feature Class Thumbnail Not Available Tags Buildings, structures, ruins, storage tanks, silos, water towers, Baltimore City Planimetric, Biophysical Resources, Land, Socio-Economic Resources, Capital Summary This data was created as a landbase feature as part of the planimetric data. Description This dataset represents photogrammetrically captured Building footprints => 100sq. ft. including storage tanks, silos, water towers, power plants, substations, and structures under construction and ruins. Feature capture rules: Buildings - Outline edge of roofline. All buildings shall be captured as polygons. In commercial areas especially, it is important that the plotted building represent the face of the building where it meets the sidewalk. Polygons shall be created for the outer boundary of the building when a partywall exists. Does not include sheds and small temporary structures. Attached garages shall be represented as part of the building structure. Large structures such as stadiums shall also be represented. Structures under construction or demolition - Delineate the rooflines of all buildings under construction as interpreted from aerial photography. If roofline is not visible compile visible foundation or walls Ruins - Delineate old overgrown areas of old structures that have been demolished or are in disrepair. Original data will be reclassified to define as separate subtype. Storage tanks, silos, and water towers - Outlines of all storage tanks, silos and water towers. . Original data will be reclassified to define as separate subtype. Power plants and substations - Outline of power plant and substation structure. . Original data will be reclassified to define as separate subtype. Credits There are no credits for this item. Use limitations Every reasonable effort has been made to ensure the accuracy of these data. The City of Baltimore, Maryland makes no representations nor warranties, either express or implied, regarding the accuracy of this information or its suitability for any particular purpose whatsoever. The data is licensed "as is" and the City of Baltimore will not be liable for its use or misuse by any party. Reliance of these data is at the risk of the user. Extent West -76.714715 East -76.525355 North 39.375162 South 39.193953 Scale Range There is no scale range for this item.

knb-lter-bes.362.600 GIS Shapefile - GIS Shapefile, Cadastral_Planimetric, Building Footprints, Baltimore County -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/f0b6d342a545453085b830a7e89b406b

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.362.600

Abstract:
Buildings_BACO File Geodatabase Feature Class Thumbnail Not Available Tags Planimetric, BES, Building, Footprints, Structure, Cadastral, Housing, Homes Summary High resolution planimetric building data. Description Baltimore County building footprints circa 1997. This dataset was obtained from the Baltimore County Goverment; there was only limited supporting documentation. A limited assesment was conducted that compared the building footprints to high resolution aerial imagery (Emerge) flown in 1999. This assessment found that a considerable number of building footprints were missing. Those that did exist appeared to agree spatially with the Emerge imagery. The following building types are included in this dataset: residential, commercial/industrial, other structures, miscellaneous buildings, buildings under construction, toll booth plazas, rail stations, water towers, storage tanks, silos. Credits Baltimore County Government Use limitations BES research only. Extent West -76.897990 East -76.334462 North 39.727055 South 39.189542 Scale Range There is no scale range for this item.

knb-lter-bes.363.600 GIS Shapefile - GIS Shapefile, Computer Assisted Mass Appraisal (CAMA) Database, MD Property View 2003, Baltimore City -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/475336d81ed769f583141d3939704d5e

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.363.600

Abstract:
CAMA_2003_BACI_1 File Geodatabase Feature Class Thumbnail Not Available Tags There are no tags for this item. Summary There is no summary for this item. Description MD Property View 2003 CAMA Database. For more information on the CAMA Database refer to the enclosed documentation. This layer was edited to remove spatial outliers in the CAMA Database. Spatial outliers are those points that were not geocoded and as a result fell outside of the Baltimore City Boundary. 254 spatial outliers were removed from this layer. Credits There are no credits for this item. Use limitations There are no access and use limitations for this item. Extent West -76.713415 East -76.526101 North 39.374324 South 39.200707 Scale Range There is no scale range for this item.

knb-lter-bes.364.600 GIS Shapefile - GIS Shapefile, Computer Assisted Mass Appraisal (CAMA) Database, MD Property View 2004, Anne Arundel County -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/953321c34c0aa7ec35abf47cdd1794ce

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.364.600

Abstract:
CAMA_2004_ANNE File Geodatabase Feature Class Thumbnail Not Available Tags Socio-economic resources, Information, Social Institutions, Hierarchy, Territory, BES, Parcel, Property, Property View, CAMA, Database, Structure, Appraisal Summary Detailed structural information for parcels. Description The CAMA (Computer Assisted Mass Appraisal) Database is created on a yearly basis using data obtained from the State Department of Assessments and Taxation (SDAT). Each yearly download contains additional residential housing characteristics as available for parcels included in the CAMA Database and the CAMA supplementary databases for each jurisdiction.. Documentation for CAMA, including thorough definitions for all attributes is enclosed. Complete Property View documentation can be found at http://www.mdp.state.md.us/data/index.htm under the "Technical Background" tab. It should be noted that the CAMA Database consists of points and not parcel boundaries. For those areas where parcel polygon data exists the CAMA Database can be joined using the ACCTID or a concatenation of the BLOCK and LOT fields, whichever is appropriate. (Spaces may have to be excluded when concatenating the BLOCK and LOT fields). A cursory review of the 2004 version of the CAMA Database indicates that it has more accurate data when compared with the 2003 version, particularly with respect to dwelling types. However, for a given record it is not uncommon for numerous fields to be missing attributes. Based on previous version of the CAMA Database it is also not unlikely that some of the information is inaccurate. This layer was edited to remove points that did not have a valid location because they failed to geocode. There were 236 such points. A listing of the deleted points is in the table with the suffix "DeletedRecords." Credits Maryland Department of Planning Use limitations BES use only. Extent West -76.838483 East -76.395283 North 39.238726 South 38.708591 Scale Range There is no scale range for this item. You are currently using the Item Description metadata style. Change your metadata

knb-lter-bes.365.600 GIS Shapefile - GIS Shapefile, Computer Assisted Mass Appraisal (CAMA) Database, MD Property View 2004, Baltimore City -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/28339fb8bb41202b13de04b719a833f7

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.365.600

Abstract:
CAMA_2004_BACI File Geodatabase Feature Class Thumbnail Not Available Tags Socio-economic resources, Information, Social Institutions, Hierarchy, Territory, BES, Parcel, Property, Property View, CAMA, Database, Structure, Appraisal Summary Detailed structural information for parcels. Description The CAMA (Computer Assisted Mass Appraisal) Database is created on a yearly basis using data obtained from the State Department of Assessments and Taxation (SDAT). Each yearly download contains additional residential housing characteristics as available for parcels included in the CAMA Database and the CAMA supplementary databases for each jurisdiction.. Documentation for CAMA, including thorough definitions for all attributes is enclosed. Complete Property View documentation can be found at http://www.mdp.state.md.us/data/index.htm under the "Technical Background" tab. It should be noted that the CAMA Database consists of points and not parcel boundaries. For those areas where parcel polygon data exists the CAMA Database can be joined using the ACCTID or a concatenation of the BLOCK and LOT fields, whichever is appropriate. (Spaces may have to be excluded when concatenating the BLOCK and LOT fields). A cursory review of the 2004 version of the CAMA Database indicates that it has more accurate data when compared with the 2003 version, particularly with respect to dwelling types. However, for a given record it is not uncommon for numerous fields to be missing attributes. Based on previous version of the CAMA Database it is also not unlikely that some of the information is inaccurate. This layer was edited to remove points that did not have a valid location because they failed to geocode. There were 235 such points. A listing of the deleted points is in the table with the suffix "DeletedRecords." Credits Maryland Department of Planning Use limitations BES use only. Extent West -76.713415 East -76.526101 North 39.374324 South 39.200707 Scale Range There is no scale range for this item.

knb-lter-bes.366.610 GIS Shapefile - GIS Shapefile, Computer Assisted Mass Appraisal (CAMA) Database, MD Property View 2004, Baltmore County -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/d4434ec1116a67560fc01aaf5beddbde

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.366.610

Abstract:
CAMA_2004_BACO File Geodatabase Feature Class Thumbnail Not Available Tags Socio-economic resources, Information, Social Institutions, Hierarchy, Territory, BES, Parcel, Property, Property View, CAMA, Database, Structure, Appraisal Summary Detailed structural information for parcels. Description The CAMA (Computer Assisted Mass Appraisal) Database is created on a yearly basis using data obtained from the State Department of Assessments and Taxation (SDAT). Each yearly download contains additional residential housing characteristics as available for parcels included in the CAMA Database and the CAMA supplementary databases for each jurisdiction.. Documentation for CAMA, including thorough definitions for all attributes is enclosed. Complete Property View documentation can be found at http://www.mdp.state.md.us/data/index.htm under the "Technical Background" tab. It should be noted that the CAMA Database consists of points and not parcel boundaries. For those areas where parcel polygon data exists the CAMA Database can be joined using the ACCTID or a concatenation of the BLOCK and LOT fields, whichever is appropriate. (Spaces may have to be excluded when concatenating the BLOCK and LOT fields). A cursory review of the 2004 version of the CAMA Database indicates that it has more accurate data when compared with the 2003 version, particularly with respect to dwelling types. However, for a given record it is not uncommon for numerous fields to be missing attributes. Based on previous version of the CAMA Database it is also not unlikely that some of the information is inaccurate. This layer was edited to remove points that did not have a valid location because they failed to geocode. There were 3999 such points. A listing of the deleted points is in the table with the suffix "DeletedRecords." Credits Maryland Department of Planning Use limitations BES use only. Extent West -76.897802 East -76.335219 North 39.726520 South 39.192836 Scale Range There is no scale range for this item.

knb-lter-bes.367.610 GIS Shapefile - GIS Shapefile, Computer Assisted Mass Appraisal (CAMA) Database, MD Property View 2004, Carroll County -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/df0d3e37c0670bb2ae6a88d01e9c0afb

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.367.610

Abstract:
CAMA_2004_CARR File Geodatabase Feature Class Thumbnail Not Available Tags Socio-economic resources, Information, Social Institutions, Hierarchy, Territory, BES, Parcel, Property, Property View, CAMA, Database, Structure, Appraisal Summary Detailed structural information for parcels. Description The CAMA (Computer Assisted Mass Appraisal) Database is created on a yearly basis using data obtained from the State Department of Assessments and Taxation (SDAT). Each yearly download contains additional residential housing characteristics as available for parcels included in the CAMA Database and the CAMA supplementary databases for each jurisdiction.. Documentation for CAMA, including thorough definitions for all attributes is enclosed. Complete Property View documentation can be found at http://www.mdp.state.md.us/data/index.htm under the "Technical Background" tab. It should be noted that the CAMA Database consists of points and not parcel boundaries. For those areas where parcel polygon data exists the CAMA Database can be joined using the ACCTID or a concatenation of the BLOCK and LOT fields, whichever is appropriate. (Spaces may have to be excluded when concatenating the BLOCK and LOT fields). A cursory review of the 2004 version of the CAMA Database indicates that it has more accurate data when compared with the 2003 version, particularly with respect to dwelling types. However, for a given record it is not uncommon for numerous fields to be missing attributes. Based on previous version of the CAMA Database it is also not unlikely that some of the information is inaccurate. This layer was edited to remove points that did not have a valid location because they failed to geocode. There were 399 such points. A listing of the deleted points is in the table with the suffix "DeletedRecords." Credits Maryland Department of Planning Use limitations BES use only. Extent West -77.306843 East -76.779379 North 39.727017 South 39.346946 Scale Range There is no scale range for this item.

knb-lter-bes.368.620 GIS Shapefile - GIS Shapefile, Computer Assisted Mass Appraisal (CAMA) Database, MD Property View 2004, Harford County -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/7f051a55ce213658a51390804f0603d0

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.368.620

Abstract:
CAMA_2004_HARF File Geodatabase Feature Class Thumbnail Not Available Tags Socio-economic resources, Information, Social Institutions, Hierarchy, Territory, BES, Parcel, Property, Property View, CAMA, Database, Structure, Appraisal Summary Detailed structural information for parcels. Description The CAMA (Computer Assisted Mass Appraisal) Database is created on a yearly basis using data obtained from the State Department of Assessments and Taxation (SDAT). Each yearly download contains additional residential housing characteristics as available for parcels included in the CAMA Database and the CAMA supplementary databases for each jurisdiction.. Documentation for CAMA, including thorough definitions for all attributes is enclosed. Complete Property View documentation can be found at http://www.mdp.state.md.us/data/index.htm under the "Technical Background" tab. It should be noted that the CAMA Database consists of points and not parcel boundaries. For those areas where parcel polygon data exists the CAMA Database can be joined using the ACCTID or a concatenation of the BLOCK and LOT fields, whichever is appropriate. (Spaces may have to be excluded when concatenating the BLOCK and LOT fields). A cursory review of the 2004 version of the CAMA Database indicates that it has more accurate data when compared with the 2003 version, particularly with respect to dwelling types. However, for a given record it is not uncommon for numerous fields to be missing attributes. Based on previous version of the CAMA Database it is also not unlikely that some of the information is inaccurate. This layer was edited to remove points that did not have a valid location because they failed to geocode. There were 194 such points. A listing of the deleted points is in the table with the suffix "DeletedRecords." Credits Maryland Department of Planning Use limitations BES use only. Extent West -76.568860 East -76.081594 North 39.726323 South 39.392952 Scale Range There is no scale range for this item.

knb-lter-bes.369.620 GIS Shapefile - GIS Shapefile, Computer Assisted Mass Appraisal (CAMA) Database, MD Property View 2004, Howard County -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/91713c6fc71936139f71c1e668f925af

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.369.620

Abstract:
CAMA_2004_HOWA File Geodatabase Feature Class Thumbnail Not Available Tags Socio-economic resources, Information, Social Institutions, Hierarchy, Territory, BES, Parcel, Property, Property View, CAMA, Database, Structure, Appraisal Summary Detailed structural information for parcels. Description The CAMA (Computer Assisted Mass Appraisal) Database is created on a yearly basis using data obtained from the State Department of Assessments and Taxation (SDAT). Each yearly download contains additional residential housing characteristics as available for parcels included in the CAMA Database and the CAMA supplementary databases for each jurisdiction.. Documentation for CAMA, including thorough definitions for all attributes is enclosed. Complete Property View documentation can be found at http://www.mdp.state.md.us/data/index.htm under the "Technical Background" tab. It should be noted that the CAMA Database consists of points and not parcel boundaries. For those areas where parcel polygon data exists the CAMA Database can be joined using the ACCTID or a concatenation of the BLOCK and LOT fields, whichever is appropriate. (Spaces may have to be excluded when concatenating the BLOCK and LOT fields). A cursory review of the 2004 version of the CAMA Database indicates that it has more accurate data when compared with the 2003 version, particularly with respect to dwelling types. However, for a given record it is not uncommon for numerous fields to be missing attributes. Based on previous version of the CAMA Database it is also not unlikely that some of the information is inaccurate. This layer was edited to remove points that did not have a valid location because they failed to geocode. There were 897 such points. A listing of the deleted points is in the table with the suffix "DeletedRecords." Credits Maryland Department of Planning Use limitations BES use only. Extent West -77.186932 East -76.699484 North 39.373967 South 39.100772 Scale Range There is no scale range for this item.

knb-lter-bes.3700.140 Baltimore Ecosystem Study polar organic contaminant integrative sampler data for pharmaceuticals and personal care products in core sites within Gwynns Falls watershed and reference sites. -- Rosi, Emma; Reisinger, Alexander;
doi:10.6073/pasta/21acc9055810ada155b504ea2cc4fe85

Authors: Rosi, Emma; Reisinger, Alexander;

Full Metadata and Download Link: knb-lter-bes.3700.140

Abstract:
An ongoing component of the Baltimore urban long-term ecological research (LTER) project (Baltimore Ecosystem Study, BES) is the use of the watershed approach and monitoring of stream water quality to evaluate the impacts of multiple chemical stressors on urban stream ecosystem functioning within Baltimore. The LTER research has focused on the Gwynns Falls watershed, which spans a gradient from highly urban, urban-residential, and suburban zones. In addition, a forested watershed serves as a reference. The long-term sampling network includes four longitudinal sampling sites along the Gwynns Falls mainstem, as well as several small (40-100 ha) watershed within or near the Gwynns Falls, providing data on water quality in different land use zones of the watersheds. Each study site is continuously monitored for discharge and is sampled weekly for water chemistry. Those data are available elsewhere on the BES website. We are interested in studying the presence and concentrations of pharmaceuticals and personal care products (PPCPs) within urban streams, and then linking these PPCPs with various stream ecosystem functions. To quantify the concentrations of PPCPs in streams, we deploy polar organic contaminant integrative samples (POCIS), which integrate all organic contaminants that pass by them in a stream over a set period of deployment. These POCIS allow us to integrate the total amount of PPCPs within a stream over a set period of time, and then to relate these concentrations with other ecosystem processes. We monitored PPCP concentration in four suburban to urban sites within the Gwynns Falls, as well as one exurban and one forested stream monitoring site. Each POCIS was deployed for two weeks at a stream monitoring site in March 2012. After completion of the sampling period, POCIS were removed from the streams and shipped on ice to the University of Nebraska for extraction and quantification of recovered compounds. This dataset includes all compounds extracted and quantified from this specific POCIS deployment. A subset of these data are included in the following publication: Rosi, E.J., H.A. Bechtold, D. Snow, M. Rojas, A.J. Reisinger, and J.J. Kelly. 2018. Urban stream microbial communities show resistance to pharmaceutical exposure. Ecosphere 9(1):e02041. doi: 10.1002/ecs2.2041 Codes and abbreviations 1 - GRGF - Gwynns Run at Gwynns Falls - Urban 2 - GFCP - Gwynns Falls at Carroll Park - Urban 3 - DRKR - Dead Run at Krome Avenue - Urban 4 - GFGB - Gwynns Falls at Gwynnbrook Avenue (Delight) - Suburban 5 - BARN - Baisman Run at Ivy Hill Road - Suburban unsewered 6 - POBR - Pond Branch forested reference site - Forested reference Column,Column Name,Variable-if different than Column Name (units) A,LAB_ID_String, Unique identifier for laboratory analysis B,Site, Site C,Replicate D,Analysis_Date, Date POCIS were analyzed E,1,7-Dimethylxanthine (ng/L) F,Acetaminophen (ng/L) G, Amphetamine (ng/L) H, Caffeine (ng/L) I, Carbamazepine (ng/L) J, Cimetidine (ng/L) K,Cotinine (ng/L) L,Diphenhydramine (ng/L) M,MDA, 3,4-methylenedioxyamphetamine (ng/L) N,MDMA, 3,4-methylenedioxymethamphetamine (ng/L) O,Methamphetamine (ng/L) P,Morphine (ng/L) Q,Sulfadimethoxine (ng/L) R,Sulfamethazine (ng/L) S,Sulfamethoxazole (ng/L) T,Thiabendazole (ng/L) Note: Reporting Limit for all PPCPs is 0.5 ng/L per laboratory analysis. Methods: Polar Organic Contaminant Integrative Samples (POCIS; Environmental Sampling Techonlogies, EST-Lab.com) were deployed at a representative location in the stream. POCIS remained deployed for two weeks in March 2012. POCIS were then collected, transported to the lab on ice, and then shipped to the University of Nebraska where compounds were eluted from POCIS with methanol and were identified and quantified by liquid chromatography-tandem mass spectrometry (see Rosi et al. 2018 and references therein for detailed description).

knb-lter-bes.372.600 GIS Shapefile - Drug Centers, Baltimore City, Shapefile -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/3a57d91aae6923511fcbdd7f2f1360e1

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.372.600

Abstract:
DrugCenters_BACI File Geodatabase Feature Class Thumbnail Not Available Tags BES, Drug, Drug Center, Socioeconomic, BNIA Summary Socioeconomic analysis. Description Baltimore City Drug Centers. This dataset was obtained from BNIA; no metadata was provided. A limited assessment comparing this dataset to IKONOS imagery acquired in 2001 indicates that the point locations have most likely been geocoded and thus are in the vicinity of, but generally not at the precise location of the facility. Credits BNIA Use limitations BES research only. Extent West -76.702090 East -76.538658 North 39.371937 South 39.251929 Scale Range There is no scale range for this item.

knb-lter-bes.373.600 GIS Shapefile - Health Organizations, Baltimore City, Shapefile -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/a33f4214c5438674896c00c8236ce147

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.373.600

Abstract:
Health_Organizations_BACI File Geodatabase Feature Class Thumbnail Not Available Tags BES, Health Organizations Summary Socioeconomic analysis. Description Location of Baltimore City health organizations. This dataset was obtained from BNIA; no metadata was provided. A limited assessment comparing this dataset to IKONOS imagery acquired in 2001 indicates that the point locations have most likely been geocoded and thus are in the vicinity of, but generally not at the precise location of the facility. Credits BNIA Use limitations BES research only. Extent West -76.687816 East -76.556835 North 39.354983 South 39.273377 Scale Range There is no scale range for this item.

knb-lter-bes.374.600 GIS Shapefile - Hospitals, Baltimore City, Shapefile -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/7bfea307a2204c7b90f79353085c2451

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.374.600

Abstract:
hospital_BACI File Geodatabase Feature Class Thumbnail Not Available Tags BES, Hospital, Health Summary Socioeconomic analysis Description Baltimore City Hospitals. This dataset was obtained from BNIA; no metadata was provided. A limited assessment comparing this dataset to IKONOS imagery acquired in 2001 indicates that the point locations have most likely been geocoded and thus are in the vicinity of, but generally not at the precise location of the facility. Credits BNIA Use limitations BES research only. Extent West -76.674223 East -76.547131 North 39.359203 South 39.250917 Scale Range There is no scale range for this item.

knb-lter-bes.375.600 GIS Shapefile - Landmarks, Baltimore City, Shapefile -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/3bf1b9ac39b7a2b80d756e3d4896d706

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.375.600

Abstract:
landmark_BACI File Geodatabase Feature Class Thumbnail Not Available Tags BES, Landmarks Summary Socioeconomic analysis. Description Baltimore City Landmarks. Credits BNIA Use limitations BES research only. Extent West -76.678418 East -76.535599 North 39.359323 South 39.245599 Scale Range There is no scale range for this item.

knb-lter-bes.376.600 GIS Shapefile - Libraries, Baltimore City, Shapefile -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/fdaac2d98c7df74c60067c52470151f4

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.376.600

Abstract:
libraries_BACI File Geodatabase Feature Class Thumbnail Not Available Tags BES, Library Summary Socioeconomic analysis. Description Location of Baltimore City libraries. This dataset was obtained from BNIA; no metadata was provided. A limited assessment comparing this dataset to IKONOS imagery acquired in 2001 indicates that the point locations have most likely been geocoded and thus are in the vicinity of, but generally not at the precise location of the facility. Credits BNIA Use limitations BES research only. Extent West -76.700693 East -76.536224 North 39.360509 South 39.236629 Scale Range There is no scale range for this item.

knb-lter-bes.377.600 GIS Shapefile - Museums, Baltimore City, Shapefile -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/e4a084dd469d0bba6902d5014ccc0cd5

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.377.600

Abstract:
Museums_BACI File Geodatabase Feature Class Thumbnail Not Available Tags BES, Museum Summary Socioeconomic analysis. Description Location of museums in Baltimore City. This dataset was obtained from BNIA; no metadata was provided. A limited assessment comparing this dataset to IKONOS imagery acquired in 2001 indicates that the point locations have most likely been geocoded and thus are in the vicinity of, but generally not at the precise location of the facility. Credits BNIA Use limitations BES research only. Extent West -76.643310 East -76.579950 North 39.363830 South 39.262267 Scale Range There is no scale range for this item.

knb-lter-bes.378.600 GIS Shapefile - Newcomer Hotspots, Baltimore City, Shapefile -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/d79cf1b38424ca0d76b86fa774c1a57a

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.378.600

Abstract:
Newcomer_Hotspots_BACI File Geodatabase Feature Class Thumbnail Not Available Tags BES, Newcomers, Hotspots Summary BES analysis. Description Baltimore City hotspots for newcomers to the area. Credits BNIA Use limitations BES research only. Extent West -76.681749 East -76.561269 North 39.356084 South 39.236417 Scale Range There is no scale range for this item.

knb-lter-bes.380.600 GIS Shapefile - Property Parcel Boundaries, 2003 Edition, Baltimore City, Shapefile -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/6ef17855e4c39b3b0dc43fca24fe45ef

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.380.600

Abstract:
Parcels_2003_BACI File Geodatabase Feature Class Thumbnail Not Available Tags BES Summary There is no summary for this item. Description Parcel Data for Baltimore City obatined from BNIA will all extraneous fields removed. Editing in progress The following edits were performed: 1) Resolved edge matching issues with Baltimore County parcels that border it and fall within the Gwynns Falls Watershed. 2) BLOCKLOT errors were noted and if necessary corrected. The BLOCKLOT ID is used to link the parcel data to the MD Property View A&T database. It should be pointed out that in some instances a single BLOCKLOT ID in the Property View A&T database may correspond to more than one parcel. There are only 14 instances were a single BLOCKLOT ID corresponds to 4 or more parcels, these are typically railroads, utility, or government properties. In other cases a single BLOCKLOT ID may correspond to two separate parcels that are essentially one property bisected by a road. There are other instances where there appears no logical explanation for a single BLOCKLOT ID corresponding to multiple parcels. Credits UVM Spatial Analysis Lab Use limitations There are no access and use limitations for this item. Extent West -76.713328 East -76.525885 North 39.374474 South 39.195051 Scale Range There is no scale range for this item.

knb-lter-bes.3800.120 Housing and parcel transactions for the Baltimore metropolitan region (1996-2014) -- Grove, Morgan; Irwin, Elena;
doi:10.6073/pasta/155028897f60bf9a766f69b9733907d2

Authors: Grove, Morgan; Irwin, Elena;

Full Metadata and Download Link: knb-lter-bes.3800.120

Abstract:
Housing and parcel transactions for the Baltimore metropolitan region (1996-2014). Participants Morgan Grove, US Forest Service Elena Irwin, The Ohio State University Douglas Wrenn, Penn State University H. Allen Klaiber, The Ohio State University Nicholas Irwin, The Ohio State University (among others) Short abstract: This data contains the housing and land transactions for parcels located in select counties in the Baltimore metropolitan region from 1996-2014. The transactions data includes date of sale, amount of sale, type of sale and the characteristics of the house or parcel (e.g. number of bathrooms, interior square footage, acreage). The data also includes information on the spatial location of the centroid of each parcel.

knb-lter-bes.381.600 GIS Shapefile - Property Parcel Boundaries, 2003 Edition, Baltimore County, Shapefile -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/8965c4433a82c656b8b844ee3f9fc78b

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.381.600

Abstract:
Parcels_2003_BACO File Geodatabase Feature Class Thumbnail Not Available Tags Social Order, Hierarchy, Territory, Social Institutions, Government, Parcels, BES, Cadastral Summary BES Research Description Baltimore County parcel data whose mapping zones fall within the Gwynns Falls watershed . Parcel edgematching issues between the original 3 parcel layers (as_area3_assess, ph3a2_assess, phase4_assess) and Baltimore City parcel data were resolved. As of 06/18/04 editing is still underway. Metadata for this dataset is incomplete. Credits UVM Spatial Analysis Lab Use limitations BES use only Extent West -76.908689 East -76.418666 North 39.590134 South 39.209697 Scale Range There is no scale range for this item.

knb-lter-bes.382.600 GIS Shapefile - Property Parcel Boundaries, 2004 Edition, Baltimore City, Shapefile -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/81f5d40ec14c84455f700f28f990d987

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.382.600

Abstract:
Parcels_2004_BACI File Geodatabase Feature Class Thumbnail Not Available Tags Social Order, Land, Social System, Hierarchy, Territory, Parcels, BES, Property Summary Land ownership analysis. Description Property Parcel boundaries for Baltimore City, 2004 edition. Can be linked to the MD Property View Assessors and Taxation (A&T) Databse using the BLOCKLOT field. Accuracy issues have been observed in this layer, particularly in areas where there appears to have been recent construction. In those areas parcel boundaries may not correspond to actual ground conditions. In addition 12 parcels have no BLOCKLOT identifier, another 97 have BLOCKLOT codes identifying them as 'ROW', 'ERROR', or 'ERROR/ROW', leaving 109 parcels that cannot be joined to the A&T Database. Excluding these, there are 242 duplicate BLOCKLOT codes shared by 672 parcels. The number of duplicates for a single parcel ranges from 2 to 72. Credits UVM Spatial Analysis Lab Use limitations BES use only. Extent West -76.713449 East -76.525885 North 39.374474 South 39.195049 Scale Range There is no scale range for this item.

knb-lter-bes.383.600 GIS Shapefile - Baltimore County Parcels, 2007, Shapefile -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/6a40b658f08408049d415b09f5121cdf

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.383.600

Abstract:
Parcels_2007_BACO File Geodatabase Feature Class Thumbnail Not Available Tags BES Summary There is no summary for this item. Description Baltimore County parcels received on March 2, 2007 from Don Outen. This data has not yet been evaluated for accuracy or consistency. No metadata was received with this layer. Credits UVM Spatial Analysis Lab Use limitations There are no access and use limitations for this item. Extent West -76.912421 East -76.319117 North 39.726917 South 39.188766 Scale Range There is no scale range for this item.

knb-lter-bes.384.610 GIS Shapefile - Land Use by Parcel, Baltimore City, Shapefile -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/89cb094e6cfeef283a3a86788ec7f85a

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.384.610

Abstract:
Parcels_PROW_LU_2003_BACI File Geodatabase Feature Class Thumbnail Not Available Tags BES, Parcel, Land Use, Urban, Land Summary BES research Description Parcel-based land use (LU) and public rights-of-way (PROW), for Baltimore City. Land use (LU) codes were obtained from the 2003 MD Property View A&Tdatabase. Credits Jarlath O'Neil-Dunne, UVM Spatial Analysis Lab Use limitations Approved BES research only Extent West -76.713449 East -76.525885 North 39.374474 South 39.195049 Scale Range There is no scale range for this item.

knb-lter-bes.385.600 GIS Shapefile - Police Districts, Baltimore City, Shapefile -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/2d0dbae4c6166ade8b57aa3b061dfe79

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.385.600

Abstract:
policedist_BACI File Geodatabase Feature Class Thumbnail Not Available Tags BES, Police, Districts, Law enforcement, Emergency services, 911 Summary BES analysis. Description Police District Boundaries for Baltimore City. Credits BNIA Use limitations BES research only. Extent West -76.713466 East -76.525894 North 39.374483 South 39.195000 Scale Range There is no scale range for this item.

knb-lter-bes.386.600 GIS Shapefile - Public Right-of-Way Land, 2003, Baltimore City, Shapefile -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/dc599de6abaafc921bad2ecf759bd572

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.386.600

Abstract:
PROW_2003_BACI File Geodatabase Feature Class Thumbnail Not Available Tags Biophysical Resources, Land, BES, PROW, Urparian, Public Right-of-Way, Roads Summary BES research Description Public Right-of-Way (PROW) land in Baltimore City (previously referred to as the "urparian" area). PROW land generally consists of all roads and rights of way along roads. This area was delineated using Baltimore City parcel data by identifying all "non-parcel" areas. A cursory analysis of the PROW land indicated that errors of omission were present due to insufficient parcel data. These errors were present in the following census block groups: 245102503031, 245102503032, 245102503033. The parcel data used in this dataset is current as of June 2001. Credits UVM Spatial Analysis Lab Use limitations BES use only. Extent West -76.713430 East -76.526155 North 39.374452 South 39.196871 Scale Range There is no scale range for this item.

knb-lter-bes.387.600 GIS Shapefile - Recreational Centers, Baltimore City, Shapefile -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/9a747759cccbfd9c8a24dfd573fec04a

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.387.600

Abstract:
RecCenters_BACI File Geodatabase Feature Class Thumbnail Not Available Tags BES, Recreational, Rec Summary BES analysis. Description Recreational Centers in Baltimore City. This dataset was obtained from BNIA; no metadata was provided. A limited assessment comparing this dataset to IKONOS imagery acquired in 2001 indicates that the point locations have most likely been geocoded and thus are in the vicinity of, but generally not at the precise location of the facility. Credits BNIA Use limitations BES research only. Extent West -76.695292 East -76.535325 North 39.367133 South 39.223398 Scale Range There is no scale range for this item.

knb-lter-bes.388.600 GIS Shapefile - Religious Organization Parcels, Baltimore City, Shapefile -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/99f0a9a07e456680bf76997cd42b5e47

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.388.600

Abstract:
religious_orgs_BACI File Geodatabase Feature Class Thumbnail Not Available Tags BES, Religous Organizations Summary BES analysis Description Religious Organization parcels in Baltimore City. Credits BNIA Use limitations BES research only. Extent West -76.713134 East -76.527132 North 39.374461 South 39.220870 Scale Range There is no scale range for this item.

knb-lter-bes.389.600 GIS Shapefile - Schools, Baltimore City, Shapefile -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/7a3d6c67f47d7803bdaeb7fcb453a63d

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.389.600

Abstract:
schools_BACI File Geodatabase Feature Class Thumbnail Not Available Tags BES, Education, Schools Summary BES analysis. Description Locations of schools in Baltimore City. This dataset was obtained from BNIA; no metadata was provided. A limited assessment comparing this dataset to IKONOS imagery acquired in 2001 indicates that the point locations have most likely been geocoded and thus are in the vicinity of, but generally not at the precise location of the facility. Credits BNIA Use limitations BES research only. Extent West -76.705042 East -76.529645 North 39.367549 South 39.223847 Scale Range There is no scale range for this item.

knb-lter-bes.390.600 GIS Shapefile - School Parcels, Baltimore City, Shapefile -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/29e74ed57062327a0d8ded8b16bf06f0

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.390.600

Abstract:
school_parcel_BACI File Geodatabase Feature Class Thumbnail Not Available Tags BES, Schools, Parcels, Education Summary BES analysis Description School parcels in Baltimore City. Credits BNIA Use limitations BES research only. Extent West -76.709756 East -76.529478 North 39.368785 South 39.200667 Scale Range There is no scale range for this item.

knb-lter-bes.4000.180 BES Household Telephone Survey -- Grove, Morgan; Locke, Dexter;
doi:10.6073/pasta/5a4fc7bfa199f3d63748f0853ae073a0

Authors: Grove, Morgan; Locke, Dexter;

Full Metadata and Download Link: knb-lter-bes.4000.180

Abstract:
Title: Baltimore Ecosystem Study (BES) Household Telephone Survey is a core dataset. The survey was conducted in years 1999 (n = 801), 2000 (n = 813), 2003 (n = 1508), 2006 (n = 3312), and 2011 (n = 1636). In year 2011, five other Metropolitan Statistical Areas (MSA), were also sampled: Boston, MA; Miami, FL; Minneapolis-St. Paul, MN; Phoenix, AZ; and Los Angeles. The overall sample size for year 2011 was 9,840. The professional survey research firm, Hollander, Cohen, and McBride conducted the survey, asking respondents questions about their outdoor recreation activities, watershed knowledge, environmental behavior, neighborhood characteristics and quality of life, lawn maintenance, and demographic information. Questions can be addressed to Dexter H Locke (dexter.locke@gmail.com) and J Morgan Grove (jmgrove@gmail.com).

knb-lter-bes.403.120 Policy Inventory for Baltimore Maryland USA -- Dalton, Shawn;
doi:10.6073/pasta/18147a1db734a9aab97e362ff6948fa9

Authors: Dalton, Shawn;

Full Metadata and Download Link: knb-lter-bes.403.120

Abstract:
This dataset was created to compile all the federal, state, county (in Baltimore Metropolitan Statistical Area), and municipal (Baltimore City) laws and policies governing the management of critical resources as identified in the Human Ecosystem Framework. The database is searchable and, as an Excel file, easily sorted by field. Data were collected primarily through internet searches of government websites, and supplemented by some documents. Sources are included within the dataset.

knb-lter-bes.4100.110 American Residential Macrosystems -- Groffman, Peter; Cavender-Bares, Jeanine; Hobbie, Sarah; Avolio, Megan; Wheeler, Megan; Trammell, Tara; Locke, Dexter;
doi:10.6073/pasta/002035a353202c0cbb30d908c2011bcf

Authors: Groffman, Peter; Cavender-Bares, Jeanine; Hobbie, Sarah; Avolio, Megan; Wheeler, Megan; Trammell, Tara; Locke, Dexter;

Full Metadata and Download Link: knb-lter-bes.4100.110

Abstract:
In seven major U.S. metropolitan cities (Boston, Baltimore, Los Angeles, Miami, Minneapolis�St. Paul, Salt Lake City, and Phoenix), 1m2 plots were sampled in residential front and backyards, as well as nearby natural areas, in order to evaluate the plant community composition, diversity, and percent cover of plant species. In addition, in Los Angeles and Salt Lake City, full yard plant communities were also sampled for a plant community of the entire yard.

knb-lter-bes.417.160 Baltimore Ecosystem Study: Soil moisture in long-term study plots, 1999-2011 -- Groffman, Peter M; Martel, Lisa D;
doi:10.6073/pasta/93041721ef6354a66281a8506b78b69f

Authors: Groffman, Peter M; Martel, Lisa D;

Full Metadata and Download Link: knb-lter-bes.417.160

Abstract:
The Baltimore Ecosystem Study (BES) has established a network of long-term permanent biogeochemical study plots. These plots will provide long-term data on vegetation, soil and hydrologic processes in the key ecosystem types within the urban ecosystem. The current network of study plots includes eight forest plots, chosen to represent the range of forest conditions in the area, and four grass plots. These plots are complemented by a network of 200 less intensive study plots located across the Baltimore metropolitan area. Plots are currently instrumented with lysimeters (drainage and tension) to sample soil solution chemistry, time domain reflectometry probes to measure soil moisture, dataloggers to measure and record soil temperature and trace gas flux chambers to measure the flux of carbon dioxide, nitrous oxide and methane from soil to the atmosphere. Measurements of in situ nitrogen mineralization, nitrification and denitrification were made at approximately monthly intervals from Fall 1998 - Fall 2000. Detailed vegetation characterization (all layers) was done in summer 1998. This data record contains near-monthly water content measurements, and the record continues with hourly data found in: Baltimore Ecosystem Study: Soil moisture and temperature along an urban to rural gradient, 2011- present https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-bes&identifier=3400 Data from these plots has been published in the following papers: Groffman PM, Pouyat RV, Cadenasso ML, Zipperer WC, Szlavecz K, Yesilonis IC,. Band LE and Brush GS. 2006. Land use context and natural soil controls on plant community composition and soil nitrogen and carbon dynamics in urban and rural forests. Forest Ecology and Management 236:177-192. Groffman, P.M., C.O. Williams, R.V. Pouyat, L.E. Band and I.C. Yesilonis. 2009. Nitrate leaching and nitrous oxide flux in urban forests and grasslands. Journal of Environmental Quality 38:1848-1860. Groffman, P.M. and R.V. Pouyat. 2009. Methane uptake in urban forests and lawns. Environmental Science and Technology 43:5229-5235. DOI: 10.1021/es803720h.

knb-lter-bes.428.290 Baltimore Ecosystem Study: Soil solution chemistry data from long-term study plots -- Groffman, Peter M; Martel, Lisa D;
doi:10.6073/pasta/afdbfd008b8f67596ebce31ae17ef707

Authors: Groffman, Peter M; Martel, Lisa D;

Full Metadata and Download Link: knb-lter-bes.428.290

Abstract:
The Baltimore Ecosystem Study (BES) has established a network of long-term permanent biogeochemical study plots. These plots will provide long-term data on vegetation, soil and hydrologic processes in the key ecosystem types within the urban ecosystem. The current network of study plots includes eight forest plots, chosen to represent the range of forest conditions in the area, and four grass plots. These plots are complemented by a network of 200 less intensive study plots located across the Baltimore metropolitan area. Plots are currently instrumented with lysimeters (drainage and tension) to sample soil solution chemistry, time domain reflectometry probes to measure soil moisture, dataloggers to measure and record soil temperature and trace gas flux chambers to measure the flux of carbon dioxide, nitrous oxide and methane from soil to the atmosphere. Measurements of in situ nitrogen mineralization, nitrification and denitrification were made at approximately monthly intervals from Fall 1998 - Fall 2000. Detailed vegetation characterization (all layers) was done in summer 1998. Data from these plots has been published in Groffman et al. (2006, 2009) and Groffman and Pouyat (2009). In November of 1998 four rural, forested plots were established at Oregon Ridge Park in Baltimore County northeast of the Gwynns Falls Watershed. Oregon Ridge Park contains Pond Branch, the forested reference watershed for BES. Two of these four plots are located on the top of a slope; the other two are located midway up the slope. In June of 2010 measurements at the mid-slope sites on Pond Branch were discontinued. Monuments and equipment remain at the two plots. These plots were replaced with two lowland riparian plots; Oregon upper riparian and Oregon lower riparian. Each riparian sites has four 5 cm by 1-2.5 meter depth slotted wells laid perpendicular to the stream, four tension lysimeters at 10 cm depth, five time domain reflectometry probes, and four trace gas flux chambers in the two dominant microtopographic features of the riparian zones - high spots (hummocks) and low spots (hollows). Four urban, forested plots were established in November 1998, two at Leakin Park and two adjacent to Hillsdale Park in west Baltimore City in the Gwynns Falls. One of the plots in Hillsdale Park was abandoned in 2004 due to continued vandalism. In May 1999 two grass, lawn plots were established at McDonogh School in Baltimore County west of the city in the Gwynns Falls. One of these plots is an extremely low intensity management area (mowed once or twice a year) and one is in a low intensity management area (frequent mowing, no fertilizer or herbicide use). In 2009, the McDonogh plots were abandoned due to management changes at the school. Two grass lawn plots were established on the campus of the University of Maryland, Baltimore County (UMBC) in fall 2000. One of these plots is in a medium intensity management area (frequent mowing, moderate applications of fertilizer and herbicides) and one is in a high intensity management area (frequent mowing, high applications of fertilizer and herbicides). Literature Cited Bowden R, Steudler P, Melillo J and Aber J. 1990. Annual nitrous oxide fluxes from temperate forest soils in the northeastern United States. J. Geophys. Res.-Atmos. 95, 13997 14005. Driscoll CT, Fuller RD and Simone DM (1988) Longitudinal variations in trace metal concentrations in a northern forested ecosystem. J. Environ. Qual. 17: 101-107 Goldman, M. B., P. M. Groffman, R. V. Pouyat, M. J. McDonnell, and S. T. A. Pickett. 1995. CH4 uptake and N availability in forest soils along an urban to rural gradient. Soil Biology and Biochemistry 27:281-286. Groffman PM, Holland E, Myrold DD, Robertson GP and Zou X (1999) Denitrification. In: Robertson GP, Bledsoe CS, Coleman DC and Sollins P (Eds) Standard Soil Methods for Long Term Ecological Research. (pp 272-290). Oxford University Press, New York Groffman PM, Pouyat RV, Cadenasso ML, Zipperer WC, Szlavecz K, Yesilonis IC,. Band LE and Brush GS. 2006. Land use context and natural soil controls on plant community composition and soil nitrogen and carbon dynamics in urban and rural forests. Forest Ecology and Management 236:177-192. Groffman, P.M., C.O. Williams, R.V. Pouyat, L.E. Band and I.C. Yesilonis. 2009. Nitrate leaching and nitrous oxide flux in urban forests and grasslands. Journal of Environmental Quality 38:1848-1860. Groffman, P.M. and R.V. Pouyat. 2009. Methane uptake in urban forests and lawns. Environmental Science and Technology 43:5229-5235. DOI: 10.1021/es803720h. Holland EA, Boone R, Greenberg J, Groffman PM and Robertson GP (1999) Measurement of Soil CO2, N2O and CH4 exchange. In: Robertson GP, Bledsoe CS, Coleman DC and Sollins P (Eds) Standard Soil Methods for Long Term Ecological Research. (pp 258-271). Oxford University Press, New York Robertson GP, Wedin D, Groffman PM, Blair JM, Holland EA, Nadelhoffer KJ and. Harris D. 1999. Soil carbon and nitrogen availability: Nitrogen mineralization, nitrification and carbon turnover. In: Standard Soil Methods for Long Term Ecological Research (Robertson GP, Bledsoe CS, Coleman DC and Sollins P (Eds) Standard Soil Methods for Long Term Ecological Research. (pp 258-271). Oxford University Press, New York Savva, Y., K. Szlavecz, R. V. Pouyat, P. M. Groffman, and G. Heisler. 2010. Effects of land use and vegetation cover on soil temperature in an urban ecosystem. Soil Science Society of America Journal 74:469-480."

knb-lter-bes.455.380 Baltimore Ecosystem Study: Long-Term Monitoring of Riparian Water Table Depth and Groundwater Chemistry -- Groffman, Peter M; Martel, Lisa D;
doi:10.6073/pasta/f7721ec5a4fab5b031f8056824e07e7d

Authors: Groffman, Peter M; Martel, Lisa D;

Full Metadata and Download Link: knb-lter-bes.455.380

Abstract:
Long-term monitoring of riparian water tables and groundwater chemistry began in 2000 along four first or second order steams in and around the Gwynns Falls watershed in Baltimore City and County, MD. One site (Oregon Ridge) is in the completely forested Pond Branch catchment that serves as a ""reference"" study area for the Baltimore LTER (BES). Two sites (Glyndon, Gwynbrook) were in suburban areas of the watershed; one just upstream from the Glyndon BES long-term stream monitoring site in the headwaters of the Gwynns Falls, and one along a tributary that enters the Gwynns Falls just above the Gwynnbrook BES long-term stream monitoring site farther downstream. The final, urban site (Cahill) was along a tributary to the Gwynns Falls in Leakin Park in the urban core of the watershed. Water table data and more detailed descriptions of soils, vegetation, stream channel properties and microbial processes at these sites can be found in Groffman et al. (2002, Environmental Science and Technology 36:4547-4552) and Gift et al. (2010, Restoration Ecology 18:113-120).

knb-lter-bes.485.110 Land Cover, Baltimore County -- Band, Larry;
doi:10.6073/pasta/afd2d14614af38afa4de045dc763aced

Authors: Band, Larry;

Full Metadata and Download Link: knb-lter-bes.485.110

Abstract:
High resolution land cover dataset for Baltimore County, MD. Seven land cover classes were mapped: (1) tree canopy, (2) grass/shrub, (3) bare earth, (4) water, (5) buildings, (6) roads, and (7) other paved surfaces. The minimum mapping unit for the delineation of features was set at 8 square meters. The primary sources used to derive this land cover layer were color infrared aerial imagery acquired in 2007 as part of the National Agricultural Imagery Program (NAIP), a normalized Digital Surface Model (nDSM) derived from 2005 LiDAR data, LiDAR intensity data resulting from the 2005 acquisition, building footprints, road polygons, and water polygons. This land cover dataset is considered current as of August, 2007. Object-based image analysis techniques (OBIA) were employed to extract land cover information using the best available remotely sensed and vector GIS datasets. OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. No accuracy assessment was conducted, but the dataset was subject to a thorough manual quality control. Over 16,000 corrections were made to the classification.

knb-lter-bes.486.110 Land Cover, Baltimore City -- Band, Larry;
doi:10.6073/pasta/9e4259e53de358876dc9a9ebdf0cd01c

Authors: Band, Larry;

Full Metadata and Download Link: knb-lter-bes.486.110

Abstract:
High resolution land cover dataset for Baltimore City, MD. Seven land cover classes were mapped: (1) tree canopy, (2) grass/shrub, (3) bare earth, (4) water, (5) buildings, (6) roads, and (7) other paved surfaces. The minimum mapping unit for the delineation of features was set at 8 square meters. The primary sources used to derive this land cover layer were color infrared aerial imagery acquired in 2007 as part of the National Agricultural Imagery Program (NAIP), a normalized Digital Surface Model (nDSM) derived from 2006 LiDAR data, LiDAR intensity data resulting from the 2006 acquisition, building footprints, road polygons, and water polygons. This land cover dataset is considered current as of August, 2007. Object-based image analysis techniques (OBIA) were employed to extract land cover information using the best available remotely sensed and vector GIS datasets. OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. No accuracy assessment was conducted, but the dataset was subject to a thorough manual quality control. 10,184 corrections were made to the classification.

knb-lter-bes.490.340 Soil Temperature Data Water year 2000-2011 -- Groffman, Peter;
doi:10.6073/pasta/0b6503863cd5f56985c25ec007378d73

Authors: Groffman, Peter;

Full Metadata and Download Link: knb-lter-bes.490.340

Abstract:
Baltimore Ecosystem Study Long-Term Study Plot Soil Metadata Participants Peter Groffman, Cary Institute of Ecosystem Studies Richard V. Pouyat, U.S. Forest Service Introduction The Baltimore Ecosystem Study (BES) has established a network of long-term permanent biogeochemical study plots. These plots will provide long-term data on vegetation, soil and hydrologic processes in the key ecosystem types within the urban ecosystem. The current network of study plots includes eight forest plots, chosen to represent the range of forest conditions in the area, and four grass plots. These plots are complemented by a network of 200 less intensive study plots located across the Baltimore metropolitan area. See Baltimore's Vegetation Structure And Its Ability To Remove Air Pollutants And Sequester Carbon Dioxide, online: http://beslter.org/frame4-page_3b_02.html . Plots are currently instrumented with lysimeters (drainage and tension) to sample soil solution chemistry, time domain reflectometry probes to measure soil moisture, dataloggers to measure and record soil temperature and trace gas flux chambers to measure the flux of carbon dioxide, nitrous oxide and methane from soil to the atmosphere. Measurements of in situ nitrogen mineralization, nitrification and denitrification were made at approximately monthly intervals from Fall 1998 - Fall 2000. Detailed vegetation characterization (all layers) was done in summer 1998. Data from these plots has been published in Groffman et al. (2006, 2009), Groffman and Pouyat (2009) and Savva et al. (2010). Plot Locations and Characterizations In November of 1998 four rural, forested plots were established at Oregon Ridge Park in Baltimore County northeast of the Gwynns Falls Watershed. Oregon Ridge Park contains Pond Branch, the forested reference watershed for BES. Two of these four plots are located on the top of a slope; the other two are located midway up the slope. In June of 2010 measurements at the mid-slope sites on Pond Branch were discontinued. Monuments and equipment remain at the two plots. These plots were replaced with two lowland riparian plots; Oregon upper riparian and Oregon lower riparian. Each riparian sites has four 5 cm by 1-2.5 meter depth slotted wells laid perpendicular to the stream, four tension lysimeters at 10 cm depth, five time domain reflectometry probes, and four trace gas flux chambers in the two dominant microtopographic features of the riparian zones --- high spots (hummocks) and low spots (hollows). Four urban, forested plots were established in November 1998, two at Leakin Park and two adjacent to Hillsdale Park in west Baltimore City in the Gwynns Falls. One of the plots in Hillsdale Park was abandoned in 2004 due to continued vandalism. In May 1999 two grass, lawn plots were established at McDonogh School in Baltimore County west of the city in the Gwynns Falls. One of these plots is an extremely low intensity management area (mowed once or twice a year) and one is in a low intensity management area (frequent mowing, no fertilizer or herbicide use). In 2009, the McDonogh plots were abandoned due to management changes at the school. Two grass lawn plots were established on the campus of the University of Maryland, Baltimore County (UMBC) in fall 2000. One of these plots is in a medium intensity management area (frequent mowing, moderate applications of fertilizer and herbicides) and one is in a high intensity management area (frequent mowing, high applications of fertilizer and herbicides). Plot locations: Hillsdale 1: 39 deg 19 min 28.14"N, 76 deg 42 min 16.49 sec W Hillsdale 2: 39 deg 19 min 31.24"N, 76 deg 42 min 28.62 sec W Leakin 1: 39 deg 18 min 1.32"N, 76 deg 41 min 37.08 sec W Leakin 2: 39 deg 18 min 5.42"N, 76 deg 41 min 34.15 sec W McDonogh 1: 39 deg 23 min 44.31"N, 76 deg 46 min 19.26 sec W McDonogh 2: 39 deg 23 min 52.26"N, 76 deg 46 min 23.52 sec W Oregon top-slope - 1: 39 deg 28 min 51.11 sec N, 76 deg 41 min 22.50 sec W Oregon mid-slope - 1: 39 deg 28 min 51.32 sec N, 76 deg 41 min 18.24 sec W Oregon top-slope - 2: 39 deg 29 min 12.74 sec N, 76 deg 41 min 22.88 sec W Oregon mid-slope - 2: 39 deg 29 min 12.68 sec N, 76 deg 41 min 18.62 sec W Oregon upper riparian: 39 deg 29 min 9.03 sec N, 76 deg 41 min 15.86 sec W Oregon lower riparian: 39 deg 28 min 52.06 sec N, 76 deg 41 min 15.54 sec W McDonogh 1: 39 deg 23 min 44.31 sec N, 76 deg 46 min 19.26 sec W McDonogh 2: 39 deg 23 min 52.26 sec N, 76 deg 46 min 23.52 sec W UMBC 1: 39 deg 15 min 8.82 sec N, 76 deg 42 min 10.43 sec W UMBC 2: 39 deg 14 min 6.50 sec N, 76 deg 42 min 48.71 sec W Soil Temperature Soil temperature is measured with HOBO H8 Pro Series Temp/External Temp data loggers from Onset Computer Corporation. One logger was installed in each plot to a depth of 10 cm. Each logger consists of an internal temperature sensor, which measures ambient air temperature at 10 cm below the surface from -30 deg C to 50 deg C, and an external temperature sensor, which measures aboveground temperature from -40 deg C to 100 deg C. Measurements are taken once every hour. Loggers are downloaded every six months either to a BoxCar shuttle or directly to a laptop computer using an interface cable. Data on the shuttle is downloaded onto a computer at the BES office at UMBC upon return from the field. Literature Cited Bowden R, Steudler P, Melillo J and Aber J. 1990. Annual nitrous oxide fluxes from temperate forest soils in the northeastern United States. J. Geophys. Res.�Atmos. 95, 13997 14005. Driscoll CT, Fuller RD and Simone DM (1988) Longitudinal variations in trace metal concentrations in a northern forested ecosystem. J. Environ. Qual. 17: 101-107 Goldman, M. B., P. M. Groffman, R. V. Pouyat, M. J. McDonnell, and S. T. A. Pickett. 1995. CH4 uptake and N availability in forest soils along an urban to rural gradient. Soil Biology and Biochemistry 27:281-286. Groffman PM, Holland E, Myrold DD, Robertson GP and Zou X (1999) Denitrification. In: Robertson GP, Bledsoe CS, Coleman DC and Sollins P (Eds) Standard Soil Methods for Long Term Ecological Research. (pp 272-290). Oxford University Press, New York Groffman PM, Pouyat RV, Cadenasso ML, Zipperer WC, Szlavecz K, Yesilonis IC,. Band LE and Brush GS. 2006. Land use context and natural soil controls on plant community composition and soil nitrogen and carbon dynamics in urban and rural forests. Forest Ecology and Management 236:177-192. Groffman, P.M., C.O. Williams, R.V. Pouyat, L.E. Band and I.C. Yesilonis. 2009. Nitrate leaching and nitrous oxide flux in urban forests and grasslands. Journal of Environmental Quality 38:1848-1860. Groffman, P.M. and R.V. Pouyat. 2009. Methane uptake in urban forests and lawns. Environmental Science and Technology 43:5229-5235. DOI: 10.1021/es803720h. Holland EA, Boone R, Greenberg J, Groffman PM and Robertson GP (1999) Measurement of Soil CO2, N2O and CH4 exchange. In: Robertson GP, Bledsoe CS, Coleman DC and Sollins P (Eds) Standard Soil Methods for Long Term Ecological Research. (pp 258-271). Oxford University Press, New York Robertson GP, Wedin D, Groffman PM, Blair JM, Holland EA, Nadelhoffer KJ and. Harris D. 1999. Soil carbon and nitrogen availability: Nitrogen mineralization, nitrification and carbon turnover. In: Standard Soil Methods for Long Term Ecological Research (Robertson GP, Bledsoe CS, Coleman DC and Sollins P (Eds) Standard Soil Methods for Long Term Ecological Research. (pp 258-271). Oxford University Press, New York Savva, Y., K. Szlavecz, R. V. Pouyat, P. M. Groffman, and G. Heisler. 2010. Effects of land use and vegetation cover on soil temperature in an urban ecosystem. Soil Science Society of America Journal 74:469-480.

knb-lter-bes.5000.2 Neighborhood Socioeconomic and demographic changes in Baltimore's (BES) Neighborhoods: 1930 to 2010 -- Locke, Dexter H;
doi:10.6073/pasta/5eb49006749681aaa3bb33e4afb7f072

Authors: Locke, Dexter H;

Full Metadata and Download Link: knb-lter-bes.5000.2

Abstract:
This dataset was created primarily to map and track socioeconomic and demographic variables from the US Census Bureau from year 1940 to year 2010, by decade, within the City of Baltimore's Mayor's Office of Information Technology (MOIT) year 2010 neighborhood boundaries. The socioeconomic and demographic variables include the percent White, percent African American, percent owner occupied homes, percent vacant homes, the percentage of age 25 and older people with a high school education or greater, and the percentage of age 25 and older people with a college education or greater. Percent White and percent African American are also provided for year 1930. Each of the the year 2010 neighborhood boundaries were also attributed with the 1937 Home Owners' Loan Corporation (HOLC) definition of neighborhoods via spatial overlay. HOLC rated neighborhoods as A, B, C, D or Undefined. HOLC categorized the perceived safety and risk of mortgage refinance lending in metropolitan areas using a hierarchical grading scale of A, B, C, and D. A and B areas were considered the safest areas for federal investment due to their newer housing as well as higher earning and racially homogenous households. In contrast, C and D graded areas were viewed to be in a state of inevitable decline, depreciation, and decay, and thus risky for federal investment, due to their older housing stock and racial and ethnic composition. This policy was inherently a racist practice. Places were graded based on who lived there; poor areas with people of color were labeled as lower and less-than. HOLC's 1937 neighborhoods do not cover the entire extent of the year 2010 neighborhood boundaries. The neighborhood boundaries were also augmented to include which of the year 2017 Housing Market Typology (HMT) the 2010 neighborhoods fall within. Finally, the neighborhood boundaries were also augmented to include tree canopy and tree canopy change year 2007 to year 2015.

knb-lter-bes.5001.1 Seeing the light: nitrate spiraling and hydrogeomorphic characteristics of restored and unrestored streams in the Baltimore, MD region. -- Reisinger, Alexander J; Groffman, Peter M; Rosi, Emma J;
doi:10.6073/pasta/1b3ad75482a940f2ed192fafa0836a05

Authors: Reisinger, Alexander J; Groffman, Peter M; Rosi, Emma J;

Full Metadata and Download Link: knb-lter-bes.5001.1

Abstract:
The continually increasing global population residing in urban landscapes impacts numerous ecosystem functions and services provided by urban streams. Urban stream restoration is often employed to offset these impacts and conserve or enhance the various functions and services these streams provide. Despite the assumption that ‘if you build it, [the function] will come’, current understanding of the effects of urban stream restoration on stream ecosystem functions are based on short term studies which may not capture variation in restoration effectiveness over time. We quantified the impact of stream restoration on nutrient and energy dynamics of urban streams by studying 10 urban stream reaches (five restored, five unrestored) in the Baltimore, Maryland, USA, region over a two-year period. We measured gross primary production (GPP) and ecosystem respiration (ER) at the whole-stream scale continuously throughout the study and nitrate (NO3-N) spiraling rates seasonally (spring, summer, autumn) across all reaches. There was no significant restoration effect on NO3-N spiraling across reaches. However, there was a significant canopy cover effect on NO3-N spiraling, and directly comparing paired sets of unrestored-restored reaches showed that restoration does affect NO3-N spiraling after accounting for other environmental variation. Furthermore, there was a change in GPP:ER seasonality, with restored and open-canopied reaches exhibiting higher GPP:ER during summer. The restoration effect, though, appears contingent upon altered canopy cover, which is likely to be a temporary effect of restoration and is a driver of multiple ecosystem services, e.g., habitat, riparian nutrient processing. Our results suggest that decision-making about stream restoration, including evaluations of nutrient benefits, clearly needs to consider spatial and temporal dynamics of canopy cover and tradeoffs among multiple ecosystem services. Here we provide site descriptions and nitrate spiraling data from nutrient releases performed at 10 sites throughout the greater Baltimore area. These estimates are included in the manuscript “Seeing the light: Urban stream restoration affects stream metabolism and nitrate uptake via changes in canopy cover” by A.J. Reisinger, T.R. Doody, P.M. Groffman, S.S. Kaushal, and Emma J. Rosi, which is currently accepted for publication in Ecological applications.

knb-lter-bes.5002.1 Seeing the light: metabolic activity of restored and unrestored streams in the Baltimore, MD region. -- Reisinger, Alexander J; Groffman, Peter M; Rosi, Emma J;
doi:10.6073/pasta/31c71a726fc07e4ff3dd1163213bf9f2

Authors: Reisinger, Alexander J; Groffman, Peter M; Rosi, Emma J;

Full Metadata and Download Link: knb-lter-bes.5002.1

Abstract:
The continually increasing global population residing in urban landscapes impacts numerous ecosystem functions and services provided by urban streams. Urban stream restoration is often employed to offset these impacts and conserve or enhance the various functions and services these streams provide. Despite the assumption that ‘if you build it, [the function] will come’, current understanding of the effects of urban stream restoration on stream ecosystem functions are based on short term studies which may not capture variation in restoration effectiveness over time. We quantified the impact of stream restoration on nutrient and energy dynamics of urban streams by studying 10 urban stream reaches (five restored, five unrestored) in the Baltimore, Maryland, USA, region over a two-year period. We measured gross primary production (GPP) and ecosystem respiration (ER) at the whole-stream scale continuously throughout the study and nitrate (NO3-N) spiraling rates seasonally (spring, summer, autumn) across all reaches. There was no significant restoration effect on NO3-N spiraling across reaches. However, there was a significant canopy cover effect on NO3-N spiraling, and directly comparing paired sets of unrestored-restored reaches showed that restoration does affect NO3-N spiraling after accounting for other environmental variation. Furthermore, there was a change in GPP:ER seasonality, with restored and open-canopied reaches exhibiting higher GPP:ER during summer. The restoration effect, though, appears contingent upon altered canopy cover, which is likely to be a temporary effect of restoration and is a driver of multiple ecosystem services, e.g., habitat, riparian nutrient processing. Our results suggest that decision-making about stream restoration, including evaluations of nutrient benefits, clearly needs to consider spatial and temporal dynamics of canopy cover and tradeoffs among multiple ecosystem services. Here we provide model estimates for GPP, ER, and net ecosystem productivity (NEP) from from 10 sites throughout the greater Baltimore area. These estimates are included in the manuscript “Seeing the light: Urban stream restoration affects stream metabolism and nitrate uptake via changes in canopy cover” by A.J. Reisinger, T.R. Doody, P.M. Groffman, S.S. Kaushal, and Emma J. Rosi, which is currently accepted for publication in Ecological applications.

knb-lter-bes.5003.1 Seeing the light: high temporal frequency (5-10min resolution) measurements of dissolved oxygen, photosynthetically active radiation, temperature, and depth used to estimate metabolism in restored and unrestored Baltimore streams. -- Reisinger, Alexander J; Groffman, Peter M; Rosi, Emma J;
doi:10.6073/pasta/2a230f0c3dba1cf7a3cd1af2c3fb7a3b

Authors: Reisinger, Alexander J; Groffman, Peter M; Rosi, Emma J;

Full Metadata and Download Link: knb-lter-bes.5003.1

Abstract:
The continually increasing global population residing in urban landscapes impacts numerous ecosystem functions and services provided by urban streams. Urban stream restoration is often employed to offset these impacts and conserve or enhance the various functions and services these streams provide. Despite the assumption that ‘if you build it, [the function] will come’, current understanding of the effects of urban stream restoration on stream ecosystem functions are based on short term studies which may not capture variation in restoration effectiveness over time. We quantified the impact of stream restoration on nutrient and energy dynamics of urban streams by studying 10 urban stream reaches (five restored, five unrestored) in the Baltimore, Maryland, USA, region over a two-year period. We measured gross primary production (GPP) and ecosystem respiration (ER) at the whole-stream scale continuously throughout the study and nitrate (NO3-N) spiraling rates seasonally (spring, summer, autumn) across all reaches. There was no significant restoration effect on NO3-N spiraling across reaches. However, there was a significant canopy cover effect on NO3-N spiraling, and directly comparing paired sets of unrestored-restored reaches showed that restoration does affect NO3-N spiraling after accounting for other environmental variation. Furthermore, there was a change in GPP:ER seasonality, with restored and open-canopied reaches exhibiting higher GPP:ER during summer. The restoration effect, though, appears contingent upon altered canopy cover, which is likely to be a temporary effect of restoration and is a driver of multiple ecosystem services, e.g., habitat, riparian nutrient processing. Our results suggest that decision-making about stream restoration, including evaluations of nutrient benefits, clearly needs to consider spatial and temporal dynamics of canopy cover and tradeoffs among multiple ecosystem services. Here we provide the raw dissolved oxygen, temperature, light, depth, and discharge data used to estimate whole-stream metabolism from 10 sites throughout the greater Baltimore area. These estimates are included in the manuscript “Seeing the light: Urban stream restoration affects stream metabolism and nitrate uptake via changes in canopy cover” by A.J. Reisinger, T.R. Doody, P.M. Groffman, S.S. Kaushal, and Emma J. Rosi, which is currently accepted for publication in Ecological applications.

knb-lter-bes.5004.2 Baltimore Ecosystem Study: Household Telephone Survey in support of Locke et al 2019 in PLoS One -- Locke, Dexter H; Grove, Morgan J; Polsky, Colin;
doi:10.6073/pasta/d1eb97f4d8c4f533a2f30d160b6c9cc8

Authors: Locke, Dexter H; Grove, Morgan J; Polsky, Colin;

Full Metadata and Download Link: knb-lter-bes.5004.2

Abstract:
This is a subset of the data found in Grove and Locke (2018), to be included with: Locke, D.H., Polsky, C., Grove, J. M., Groffman, P. M., Nelson, K.C., Larson, K. L., Cavender-Bares, J., Heffernan, J. B., Roy Chowdhury, R., Hobbie, S. E., Bettez, N., Neill, C., Ogden, L.A., O’Neil-Dunne, J. P. M.. [accepted]. Heterogeneity of practice underlies the homogeneity of ecological outcomes of United States yard care in metropolitan regions, neighborhoods and households. PLoS ONE doi:10.1371/journal.pone.0222630 These data contain answers 2011 survey questions: In the past year, which of the following has been applied to any part of your yard: Water for irrigating grass, plants, or trees? Fertilizers? Pesticides to get rid of weeds or pests? The total household annual income (8 ordinal categories), age of respondent (5 ordinal categories), and the answer to: About how many neighbors do you know by name? (recorded in 5 ordinal categories). Two additional columns are provided to indicate the metropolitan region of the respondent (one of the following six: Phoenix, Los Angeles, Minneapolis - St. Paul, Baltimore, Boston, or Miami) and the degree of urbanicity in that region (Urban, Suburban, or Exurban). See Grove and Locke 2018 for additional details. This research is supported by the Macro- Systems Biology Program (US NSF) under Grants EF-1065548, -1065737, -1065740, -1065741, -1065772, -1065785, -1065831, and -121238320 and the NIFA McIntire-Stennis 1000343 MIN-42-051. The work arose from research funded by grants from the NSF LTER program for Baltimore (DEB- 0423476, DEB-1027188); Phoenix (BCS-1026865, DEB-0423704, DEB-9714833, DEB-1637590, DEB-1832016); Plum Island, Boston (OCE-1058747 and 1238212); Cedar Creek, Minneapolis–St. Paul (DEB- 0620652); and Florida Coastal Everglades, Miami (DBI-0620409). Edna Bailey Sussman Foundation, Libby Fund Enhancement Award and the Marion I. Wright ‘46 Travel Grant at Clark University, The Warnock Foundation, the USDA Forest Service Northern Research Station, Baltimore and Philadelphia Field Stations, and the DC-BC ULTRA-Ex NSF-DEB-0948947 also provided support. This work was supported by the National Socio-Environmental Synthesis Center (SESYNC) under funding received from the National Science Foundation DBI-1052875. Anonymous reviewers supplied constructive feedback that helped to improve this paper. The findings and opinions reported here do not necessarily reflect those of the funders of this research. Citations: Grove J.M., Locke, D.H.. (2018). BES Household Telephone Survey. Environmental Data Initiative. https://doi.org/10.6073/pasta/5a4fc7bfa199f3d63748f0853ae073a0.

knb-lter-bes.5005.2 Baltimore Ecosystem Study: Estimates of population in focal watersheds based on 2010 census -- Fork, Megan L; Locke, Dexter H;
doi:10.6073/pasta/13c25e41766801474979970f6e21c7f4

Authors: Fork, Megan L; Locke, Dexter H;

Full Metadata and Download Link: knb-lter-bes.5005.2

Abstract:
This dataset includes population estimates for eight focal sub-watersheds in the Baltimore Ecosystem Study based on the proportion of 2010 census blocks located within the watershed. These data can facilitate per capita calculations of watershed fluxes.

knb-lter-bes.5006.1 Nitrogen cycling, soil properties and infiltration rates along a topographic gradient in lawns in Baltimore County, Maryland -- Suchy, Amanda K; Groffman, Peter M;
doi:10.6073/pasta/67615100eabd2f3d43718759f85c131e

Authors: Suchy, Amanda K; Groffman, Peter M;

Full Metadata and Download Link: knb-lter-bes.5006.1

Abstract:
The aim of this research was to examine how topography and homeowner fertilizer practices affected soil and hydrologic properties of residential lawns to determine if there are locations within lawns that have the potential to act as hotspots of nitrogen transport during rain events. This data set contains measurements of saturated infiltration rates, sorptivity, soil moisture, soil organic matter, pH, soil nitrate, soil ammonium, denitrification potentials and limiting factors, and nitrogen mineralization rates from fertilized and unfertilized residential and institutional lawns. Study lawns were located at homes of people who agreed to volunteer their lawn for the study from a door knocking campaign. Four sampling houses were located in an exurban neighborhood in Baisman Run. Five sampling houses were located in a suburban neighborhood in Dead Run. Two sampling locations on institutional lawns were located at University of Maryland Baltimore County. At the exurban study houses and institutional lawns sites,we identified one hillslope to conduct sampling on. At the Dead Run houses we identified one hillslope on the front yard and one in the backyard as there were distinct locations that were not present in the exurban neighborhood. In total we sampled on 16 hillslopes. At each hillslope, we identified the top, toe and swale locations. At each hillslope location, we selected three sampling locations along a transect (maximum 10 meters in length; total of 144 sampling locations). At each sampling location we ran a Cornell Sprinkle Infiltrometer to measure sorptivity and saturated infiltration rates. Volumetric water content was measured before and after infiltrometer runs with a Field Scout TDR 300 with 7.5 cm rods. In addition, at each sampling location we took two soil cores to 10 cm depth, and combined and homogenized the two cores for that sampling location for a total of 144 soil samples. Soil cores were stored on ice in the field, and then stored at 4°C in the lab until processed for variables mentioned above. Sampling for soil cores was conducted in September 2017 with one house collected on 11/1/2017 due to changes in homeowner volunteers. Cornell Sprinkle Infiltrometer measurements were taken in October 2017 with one exception for house DR3. The front yard was conducted on 1/30/2018 and the back yard was completed on 2/27/2018 due to scheduling conflicts and weather interference during October and proceeding months.

knb-lter-bes.5007.1 White oak and red maple foliar chemistry of urban and reference forests of the eastern US -- Sonti, Nancy F; Hallett, Richard A.; Griffin, Kevin L.; Sullivan, Joe H.;
doi:10.6073/pasta/0b48d8744f971ef244a30425fbec15fb

Authors: Sonti, Nancy F; Hallett, Richard A.; Griffin, Kevin L.; Sullivan, Joe H.;

Full Metadata and Download Link: knb-lter-bes.5007.1

Abstract:
Foliar chemistry values were obtained from two important native tree species (white oak (Quercus alba L.) and red maple (Acer rubrum L.)) across urban and reference forest sites of three major cities in the eastern United States during summer 2015 (New York, NY (NYC); Philadelphia, PA; and Baltimore, MD). Trees were selected from secondary growth oak-hickory forests found in New York, NY; Philadelphia, PA; and Baltimore, MD, as well as at reference forest sites outside each metropolitan area. In all three metropolitan areas, urban forest patches and references forest sites were selected based on the presence of red maple and white oak canopy dominant trees in patches of at least 1.5 hectares with slopes less than 25%, and well-drained soils of similar soil series within each metropolitan area. Within each city, several forest patches were selected to capture the variation in forest patch site conditions across an individual city. All reference sites were located in protected areas outside of the city and within intermix wildland-urban interface landscapes, in order to target similar contexts of surrounding land use and population density (Martinuzzi et al. 2015). Several reference sites were selected for each city, located within the same protected area considered representative of rural forests of the region. White oaks were at least 38.1 cm diameter at breast height (DBH), red maples were at least 25.4 cm DBH, and all trees were dominant or co-dominant canopy trees. The trees had no major trunk cavities and had crown vigor scores of 1 or 2 (less than 25% overall canopy damage; Pontius & Hallett 2014). From early July to early August 2015, sun leaves were collected from the periphery of the crown of each tree with either a shotgun or slingshot for subsequent analysis to determine differences in foliar chemistry across cities and urban vs. reference forest site types. The data were used to invstigate whether differences in native tree physiology occur between urban and reference forest patches, and whether those differences are site- and species-specific. A complete analysis of these data can be found in: Sonti, NF. 2019. Ecophysiological and social functions of urban forest patches. Ph.D. dissertation. University of Maryland, College Park, MD. 166 p. References: Martinuzzi S, Stewart SI, Helmers DP, Mockrin MH, Hammer RB, Radeloff VC. 2015. The 2010 wildland-urban interface of the conterminous United States. Research Map NRS-8. US Department of Agriculture, Forest Service, Northern Research Station: Newtown Square, PA. Pontius J, Hallett R. 2014. Comprehensive methods for earlier detection and monitoring of forest decline. Forest Science 60(6): 1156-1163.

knb-lter-bes.5008.2 Residential housing segregation and urban tree canopy in 37 US Cities; data in support of Locke et al 2021 in npj Urban Sustainability -- Locke, Dexter H;
doi:10.6073/pasta/4ccbc7087959dc2a25063e589dee7718

Authors: Locke, Dexter H;

Full Metadata and Download Link: knb-lter-bes.5008.2

Abstract:
Our goal in this paper is to examine whether there are similar patterns in the distribution of tree canopy by Home Owners’ Loan Corporation (HOLC) graded neighborhoods across 37 cities. A pre-print of the paper can be found here: https://osf.io/preprints/socarxiv/97zcs This data packages contains: 1. City-specific file geodatabases with features classes of the HOLC polygons obtained from the Mapping Inequality Project https://dsl.richmond.edu/panorama/redlining/, and tables summarizing tree canopy, and in some cases other land cover classes. 2. An *.R script that replicates all of the analyses, graphs, and tables in the paper. Other double checks, exploratory, and miscellaneous outputs are created by the script too as a bonus. Everything in the paper can be done with the script; additional work outputs are also created. 3. A *.csv file containing city, the HOLC grade, and the percent tree canopy cover. This can be used to create the main findings of the paper and this flat file is provided as an alternative to running the R script to extract information from the geodatabases, combine, and analyze them. The intention is that this file is more widely accessible; the underlying information is the same. Redlining was a racially discriminatory housing policy established by the federal government’s Home Owners’ Loan Corporation (HOLC) during the 1930s. For decades, redlining limited access to homeownership and wealth creation among racial minorities, contributing to a host of adverse social outcomes, including high unemployment, poverty, and residential vacancy, that persist today. While the multigenerational socioeconomic impacts of redlining are increasingly understood, the impacts on urban environments and ecosystems remains unclear. To begin to address this gap, we investigated how the HOLC policy administered 80 years ago may relate to present-day tree canopy at the neighborhood level. Urban trees provide many ecosystem services, mitigate the urban heat island effect, and may improve quality of life in cities. In our prior research in Baltimore, MD, we discovered that redlining policy influenced the location and allocation of trees and parks. Our analysis of 37 metropolitan areas here shows that areas formerly graded D, which were mostly inhabited by racial and ethnic minorities, have on average ~23% tree canopy cover today. Areas formerly graded A, characterized by U.S.-born white populations living in newer housing stock, had nearly twice as much tree canopy (~43%). Results are consistent across small and large metropolitan regions. The ranking system used by Home Owners’ Loan Corporation to assess loan risk in the 1930s parallels the rank order of average percent tree canopy cover today.

knb-lter-bes.5009.1 Baltimore Ecosystem Study: Forest Cover in the Gwynns Falls watershed from 1914 to 2004 -- Zhou, Weiqi; Huang, Ganlin; Cadenasso, Mary L; Pickett, Steward;
doi:10.6073/pasta/5a8d80b49ada4a976479a3116a52c1ba

Authors: Zhou, Weiqi; Huang, Ganlin; Cadenasso, Mary L; Pickett, Steward;

Full Metadata and Download Link: knb-lter-bes.5009.1

Abstract:
Landscape structure in the Eastern US experienced great changes in the last century with the expansion of forest cover into abandoned agricultural land and the clearing of secondary forest cover for urban development. In this paper, the spatial and temporal patterns of forest cover from 1914 to 2004 in the Gwynns Falls watershed in Baltimore, Maryland were quantified from historic maps and aerial photographs. Using a database of forest patches from six times—1914, 1938, 1957, 1971, 1999, and 2004—we found that forest cover changed, both temporally and spatially. While total forest area remained essentially constant, turnover in forest cover was very substantial. Less than 20% of initial forest cover remained unchanged. Forest cover became increasingly fragmented as the number, size, shape, and spatial distribution of forest patches within the watershed changed greatly. Forest patch change was also analyzed within 3-km distance bands extending from the urban core to the more suburban end of the watershed. This analysis showed that, over time, the location of high rates of forest cover change shifted from urban to suburban bands which coincides with the spatial shift of urbanization. Forest cover tended to be more stable in and near the urban center, whereas forest cover changed more in areas where urbanization was still in process. These results may have critical implications for the ecological functioning of forest patches and underscore the need to integrate multi-temporal data layers to investigate the spatial pattern of forest cover and the temporal variations of that spatial pattern. Zhou, W., G. Huang, S. T. A. Pickett, and M. L. Cadenasso. 2011. 90 Years of Forest Cover Change in an Urbanizing Watershed: Spatial and Temporal Dynamics. Landscape Ecology 26:645–659. <ulink url="https://doi.org/10.1007/s10980-011-9589-z">https://doi.org/10.1007/s10980-011-9589-z</ulink>.

knb-lter-bes.5010.1 Baltimore Ecosystem Study: Pharmaceutical concentrations for core sites in Gwynns Falls and Baisman Run -- Rosi, Emma; Fick, Jerker; Fork, Megan;
doi:10.6073/pasta/36453abc14ce8d6a33711231fdee9792

Authors: Rosi, Emma; Fick, Jerker; Fork, Megan;

Full Metadata and Download Link: knb-lter-bes.5010.1

Abstract:
Water samples from one year of weekly samples at the Baltimore Ecosystem Study core stream sites were analyzed to measure concentrations of 92 different pharmaceutical concentrations. Note that none of the sites sampled in this dataset receive effluent from wastewater treatment plants (a common source of pharmaceutical contamination). In Baisman Run, sewage is treated by onsite systems, while in the Gwynns Falls watershed, sewage is piped across the watershed boundary and treated elsewhere.

knb-lter-bes.5011.1 Georectified Mosaic of Aerial Images of Baltimore City in 1927 -- Lagrosa IV, John J; Sonti, Nancy; Grove, J Morgan;
doi:10.6073/pasta/045e3001129aca3b34fd0e91b1a6f596

Authors: Lagrosa IV, John J; Sonti, Nancy; Grove, J Morgan;

Full Metadata and Download Link: knb-lter-bes.5011.1

Abstract:
Landscape analyses are typically done using spatially explicit color aerial imagery. However, working with non-spatial black and white historical aerial photographs presents several challenges that require a combination of techniques and approaches. We analyzed 93 aerial images covering 544 km2 (210 mi2) including all of Baltimore City, and an area immediately adjacent to the city known at the time as the Metropolitan District of Baltimore County. The images were taken from a biplane between October 1926 and February 1927. High-resolution scans were georeferenced and georectified against modern satellite imagery of the area and then combined to create a single raster mosaic. This process converted the images from a disparate set of photographs into a spatially explicit GIS data set that can be used to observe changes in land patches over time—and ultimately integrated with other long-term social, economic, and ecological data.

knb-lter-bes.5012.1 Baltimore Ecosystem Study: Loss of Phylogenetic Diversity under Landscape Change -- Swan, Christopher;
doi:10.6073/pasta/e73fed99382a6409c1f3d26d1869f4a1

Authors: Swan, Christopher;

Full Metadata and Download Link: knb-lter-bes.5012.1

Abstract:
Habitat alteration and destruction are a primary driver of biodiversity loss. There is a plethora of research documenting similarly strong patterns of decline across ecosystem types and spatial scales. However, evolutionary dimensions remain largely unexplored in many systems. For example, little is known about how habitat alteration/loss can lead to phylogenetic deconstruction of ecological assemblages at the local level. That is, while species loss is evident, are some lineages favored over others? Using a long-term dataset of a globally, ecologically important guild of invertebrate consumers, stream leaf “shredders,” we created a phylogenetic tree of the taxa in the regional species pool, calculated mean phylogenetic distinctiveness for > 1000 communities spanning > 10 y period, and related species richness, phylogenetic diversity and distinctiveness to watershed-scale impervious cover. Using a combination of changepoint and compositional analyses, we learned that increasing impervious cover produced marked reductions in all three measures of diversity, and in particular, aid in understanding both phylogenetic diversity and average assemblage phylogenetic distinctiveness. Our findings suggest that, not only are species lost when there is an increase in watershed urbanization, as other studies have demonstrated, but that those lost are members of more distinct lineages relative to the community as a whole.

knb-lter-bes.5013.1 A Land-use/Land Cover Classification of Baltimore City in 1927 -- Lagrosa IV, John J; Sonti, Nancy; Grove, J Morgan;
doi:10.6073/pasta/28793d6417db548f26679ab0e5197fb8

Authors: Lagrosa IV, John J; Sonti, Nancy; Grove, J Morgan;

Full Metadata and Download Link: knb-lter-bes.5013.1

Abstract:
Land-use and land cover classifications are typically created using automated methods to analyze modern, spatially explicit color aerial imagery. However, creating classifications from black and white historical aerial imagery presents a number of challenges that require a combination of more traditional, manual techniques and approaches. A georectified mosaic of 93 aerial images was digitized in ArcGIS to create a land-use/land cover classification. The analyzed area covered 585 km2 (226 mi2) including all of Baltimore City, and an area immediately adjacent to the city known at the time as the Metropolitan District of Baltimore County. A combination of 8 land-use and land cover classes were used: Agriculture, Barren, Built (Other), Forest, Grass/Shrubland, Industrial, Residential, and Water. This geospatial data set captures a moment of dynamic expansion in the city, just prior to the Great Depression and can be used to examine relationships between property ownership and forest patch dynamics across time. These insights may help inform future environmental planning, conservation, management, and stewardship goals for Baltimore City forest patches, and other cities throughout the region.

knb-lter-bes.5014.1 Baltimore Ecosystem Study: Code for calculations of annual pharmaceutical loads at Gwynns Falls Carroll Park -- Fork, Megan;
doi:10.6073/pasta/610cb67fcbc8982c2af8ed946dce8ea5

Authors: Fork, Megan;

Full Metadata and Download Link: knb-lter-bes.5014.1

Abstract:
Code for analyses presented in: Fork, M.L., J. Fick, A.J. Reisinger, and E.J. Rosi. "Dosing the coast: Leaking sewage infrastructure delivers large annual loads and dynamic mixtures of pharmaceuticals to urban rivers." In press at Environmental Science and Technology. Two markdown files contains code to pre-process other data and to analyze grab samples from BES streams collected weekly from 2 Nov 2017 through 15 Nov 2018 and analyzed for 92 target pharmaceuticals. Data and methods are available via EDI at https://doi.org/10.6073/pasta/36453abc14ce8d6a33711231fdee9792. Briefly, the analyses here: A) examine spatial and temporal variability in pharmaceutical detections and concentrations among 7 BES watersheds, and B) combine measured concentrations at the watershed outlet (GFCP) with USGS streamflow data to estimate annual loads of pharmaceuticals by resampling or by interpolating concentrations over the discharge record.

knb-lter-bes.5015.1 Green stormwater infrastructure projects voluntarily installed in Baltimore City through 2019 -- Solins, Joanna P; Phillips de Lucas, Amanda K; Cadenasso, Mary L; Grove, J. Morgan;
doi:10.6073/pasta/8e958d6009ef7229dcbbf953d0bac7fd

Authors: Solins, Joanna P; Phillips de Lucas, Amanda K; Cadenasso, Mary L; Grove, J. Morgan;

Full Metadata and Download Link: knb-lter-bes.5015.1

Abstract:
Much of the green stormwater infrastructure (GSI) in Baltimore, Maryland, USA, has been installed voluntarily by nonprofits and community groups, yet no comprehensive record of these installations previously existed. We worked with nonprofit stakeholders and Baltimore’s Department of Public Works to compile such a record, using both information provided by these agencies and publicly available data sources such as annual reports and newspaper articles. This dataset includes all voluntary green stormwater infrastructure projects that we were able to identify by the end of 2019, with the first known installation completed in 2001. The dataset includes two data tables, one with project-level information, and one with the locations of individual GSI facilities included in each project.

knb-lter-bes.5016.1 Baltimore Ecosystem Study: Lawn productivity 2006-2007 -- Jenkins, Jennifer; Groffman, Peter M; Sonti, Nancy F;
doi:10.6073/pasta/07bf9a491ea7d08459b5849ba703634f

Authors: Jenkins, Jennifer; Groffman, Peter M; Sonti, Nancy F;

Full Metadata and Download Link: knb-lter-bes.5016.1

Abstract:
Urban grasslands cover large land areas in human-dominated landscapes, but little is known about how these landscapes cycle carbon (C). In this study, we examine turfgrass biomass and productivity at thirty-three urban grassland sites within the Gwynns Fall watershed (Baltimore, MD). These sites are characteristic of residential conditions in the region and were selected to provide contrasts in urban ecosystem structure (density of coarse vegetation and built structures) as well as historical (pre-development) land use. Aboveground net primary productivity (ANPP) was measured as the sum of clipping production plus stubble, thatch, and moss production. This work provides context for understanding the impact of urban expansion on regional ecosystem C dynamics and identifies specific needs related to standardized methods for measuring turfgrass ANPP in urban grassland systems.

knb-lter-bes.5017.1 Georectified Mosaic of Aerial Images of Baltimore City in 1953 -- Lagrosa IV, John J; Sonti, Nancy; Grove, J Morgan;
doi:10.6073/pasta/6b583e08366f53fd8665e835f1bad44c

Authors: Lagrosa IV, John J; Sonti, Nancy; Grove, J Morgan;

Full Metadata and Download Link: knb-lter-bes.5017.1

Abstract:
Landscape analyses are typically done using spatially explicit color aerial imagery. However, working with non-spatial black and white historical aerial photographs presents several challenges that require a combination of techniques and approaches. We analyzed 113 aerial images covering approx. 700 km2 (270 mi2) including all of Baltimore City, and a portion of Baltimore County surrounding the City. The images were taken between August 23rd 1952 and February 14th 1953. High-resolution scans were georeferenced and georectified against modern satellite imagery of the area and then combined to create a single raster mosaic. This process converted the images from a disparate set of photographs into a spatially explicit GIS data set that can be used to observe changes in land patches over time—and ultimately integrated with other long-term social, economic, and ecological data.

knb-lter-bes.5018.1 A Land-use/Land Cover Classification of Baltimore City in 1953 -- Lagrosa IV, John J; Sonti, Nancy; Grove, J Morgan;
doi:10.6073/pasta/84b59c8e375e3915cc62dea2cf73627a

Authors: Lagrosa IV, John J; Sonti, Nancy; Grove, J Morgan;

Full Metadata and Download Link: knb-lter-bes.5018.1

Abstract:
Land-use and land cover classifications are typically created using automated methods to analyze modern, spatially explicit color aerial imagery. However, creating classifications from black and white historical aerial imagery presents a number of challenges that require a combination of more traditional, manual techniques and approaches. A georectified mosaic of 113 aerial images was digitized in ArcGIS to create a land-use/land cover classification. The analyzed area covered 700 km2 (270 mi2) including all of Baltimore City, and a portion of Baltimore County immediately surrounding the city. A combination of 8 land-use and land cover classes were used: Agriculture, Barren, Built (Other), Forest, Grass/Shrubland, Industrial, Residential, and Water. This geospatial data set captures an ecologically and socially important moment in the post-war history of the city. It can be used to examine relationships between property ownership and forest patch dynamics across time. These insights may help inform future environmental planning, conservation, management, and stewardship goals for Baltimore City forest patches, and other cities throughout the region.

knb-lter-bes.5019.1 The role of riparian functional and phylogenetic diversity on leaf litter processing in rivers -- Swan, Christopher M;
doi:10.6073/pasta/59def99040c11c2451fc50deb2cf1234

Authors: Swan, Christopher M;

Full Metadata and Download Link: knb-lter-bes.5019.1

Abstract:
While taxonomic diversity mediates changes in ecosystem function is well-studied, how deeper dimensions of biodiversity, specifically phylogenetic and functional, independent of taxonomic diversity, drive important processes is understudied. The overarching goal of this work was to determine the role of these dimensions of biodiversity independently and/or interactively explain carbon processing in rivers. Here, we explicitly link community structure and subsequent traits of riparian forests to adjacent ecosystem processing of carbon (e.g., leaf litter). This was accomplished by examining how forests are actually structured in addition to experimental manipulations of phylogenetic and functional diversities of riparian forest community inputs of leaf litter to streams. Experimental field manipulations were carried out in three Piedmont headwater streams to answer the following questions: (1) Does existing variation in taxonomic, functional and phylogenetic diversity of riparian communities differentially drive decomposition in rivers? And (2) Independent of taxonomic diversity, how does functional and phylogenetic diversity of leaf litter assemblages influence rates of decomposition in rivers? We observed significant interspecific variation in breakdown among 30 riparian tree species, in addition to significant relationships between breakdown rate and important foliar tissue chemistries. Breakdown of mixtures that reflected the composition of the riparian species composition did not vary with functional nor phylogenetic diversity, but breakdown of litter mixtures was higher than that of single species. In a separate study, when manipulated independently, functional and phylogenetic diversity were positively related to breakdown, and explained similar degrees of variation. These results are important to understand in light of deepening knowledge of the role different dimensions of biodiversity take in explaining ecosystem function, as well as how these measures can be used as tools in habitat restoration practice.

knb-lter-bes.5020.1 Baltimore Ecosystem Study: November 21, 2019 Download of TreeBaltimore data in support of Anderson et al 2022, Ecosphere -- Anderson, Elsa; Locke, Dexter H; Pickett, Steward TA; LaDeau, Shannon L;
doi:10.6073/pasta/c988d7a134ee77cda29624eeeb4ddf66

Authors: Anderson, Elsa; Locke, Dexter H; Pickett, Steward TA; LaDeau, Shannon L;

Full Metadata and Download Link: knb-lter-bes.5020.1

Abstract:
Tree Baltimore (treebaltimore.org) hired Davey Tree to conduct a census of all publicly owned trees and tree pits in the city of Baltimore. This census was completed by arborists in 2017-2018, documenting over 192,000 trees and potential tree sites that reflect the public component of Baltimore’s urban forest. Entries in this dataset include trees in parkways (street trees), mown areas of public parks (forest patches excluded), meridian trees, and vacant spaces for tree planting. Data is continuously updated and the current vintage can be found at https://baltimore.maps.arcgis.com/apps/webappviewer/index.html?id=d2cfbbe9a24b4d988de127852e6c26c8.

knb-lter-bes.5021.1 Baltimore Ecosystem Study: Increased diversity of the regional species pool via seeding augments establishment of native species in experimental vacant lot restorations -- Swan, Christopher M;
doi:10.6073/pasta/1492f59f9ebed1d51f35a085f4666832

Authors: Swan, Christopher M;

Full Metadata and Download Link: knb-lter-bes.5021.1

Abstract:
The harsh geophysical template characterized by the urban environment combined with people’s choices has led ecologists to invoke environmental filtering as the main ecological phenomena explaining urban biodiversity patterns. Yet, dispersal is often overlooked as a driving factor, especially on expanding vacant land. Does overcoming dispersal limitation by seeding native species in urban environments and increasing the functional or phylogenetic diversity of the seeding pool increase native plant species diversity and abundance in urban vacant land? We took an experimental approach to learn how different dimensions of plant biodiversity within an augmented regional species pool, via seed additions, can explain variation in community structure over a 3-year period. Vacant lots were cleared and manipulated with seeding treatments of high or low phylogenetic and functional diversities from a pool of 28 native species. Establishment success, total native cover and native species richness were followed and compared to cleared, unseeded control lots as well as un-manipulated lots. Seeding increased native plant abundance and richness over uncleared plots, as well as cleared and unseeded control plots. Phylogenetically diverse seed mixtures had greater establishment success than mixtures composed of closely related species. Diversifying seed mixtures increased the likelihood of including species that are better able to establish on vacant land. However, there were no differences in varying levels of either functional or phylogenetic diversity. Augmenting the regional species pool via diverse seed mixtures can enhance native plant cover and richness under the harsh environmental conditions conferred by land abandonment.

knb-lter-bes.5022.1 Seasonal N dynamics and fluxes of nitrogen in leachate and runoff from experimental rainfalls on fertilized and unfertilized lawns in Baltimore County, Maryland -- Suchy, Amanda K; Groffman, Peter M;
doi:10.6073/pasta/bccb237418362143cdbad53d871ae5eb

Authors: Suchy, Amanda K; Groffman, Peter M;

Full Metadata and Download Link: knb-lter-bes.5022.1

Abstract:
The aim of this research was to examine the spatial and temporal variation in export control points of nitrogen on residential lawns (locations prone to mobilizing nitrogen during a rain event) and to examine if previously measured hydrobiogeochemical properties were predictive of N mobilization in lawns. This data set contains measurements of saturated infiltration rates, sorptivity, soil moisture, soil organic matter, bulk density, pH, soil nitrate, soil ammonium, N2O, N2 and CO2 fluxes from soil cores, nitrogen mineralization rates and fluxes of N in runoff and leachate from fertilized and unfertilized residential and institutional lawns. Study lawns were located at homes of people who agreed to volunteer their lawn for the study from a door knocking campaign. Four sampling houses were located in an exurban neighborhood in Baisman Run. Five sampling houses were located in a suburban neighborhood in Dead Run. Two sampling locations on institutional lawns were located at University of Maryland Baltimore County. At the exurban study houses and institutional lawns sites, we identified one hillslope to conduct sampling on. At the Dead Run houses we identified one hillslope on the front yard and one in the backyard as there were distinct locations that were not present in the exurban neighborhood. Locations within the yards for sampling were selected based on sampling conducted in October 2017. Locations were grouped into four categories based on have either high or low potential denitrification rates and high or low saturated infiltration rates (n=48). These locations were also distributed across yard types (exurban, suburban or institutional), fertilizer treatments, and hillslope location (top or bottom of hillslope). At each sampling location we ran a Cornell Sprinkle Infiltrometer to generate an experimental rainfall during which we collected runoff and leachate to quantity N flux. We also measure sorptivity and saturated infiltration rates. Volumetric water content was measured before and after infiltrometer runs with a Field Scout TDR 300 with 7.5 cm rods. In addition, at each sampling location we took two soil cores to 10 cm depth to measure gaseous N flux and soil N processes. Soil cores were stored on ice in the field, and then stored at 4°C in the lab until processed for variables mentioned above. Sampling was conducted across four seasons (April 2018, September 2018, November 2018 and March 2019) to capture seasonal variability including the timing of fertilizer applications.

knb-lter-bes.52.600 GIS Shapefile - Main Study Area Boundary - BES Main Study Area -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/e9993a492b28f9293362a29160696503

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.52.600

Abstract:
Boundary for the BES Metropolitan Study Area (MSA) derived from year 2000 GDT census data. This is the universal MSA boundary for all BES research. The MSA consists of the following 5 counties: Baltimore City, Baltimore County, Anne Arrundel, Carroll, Harford, and Howard. This is part of a collection of Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase itself is available online at beslter.org or lternet.edu. It is considerably large. Upon request, it can be shipped to you on media, such as a flash drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.53.600 GIS Shapefile - Baltimore City Limits (not coincident with main study area boundary) -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/eea60ae4150ba2c5144237d5c9542fdc

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.53.600

Abstract:
Baltimore City boundary limits. This is the "official" city boundary used by many Baltimore agencies. It DOES NOT agree with the universal MSA boundaries dervied from GDT census data. This is part of a collection of Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase itself is available online at beslter.org or lternet.edu. It is considerably large. Upon request, it can be shipped to you on media, such as a flash drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.543.170 Biodiversity - Fauna - Bird Survey -- Nilon, Charlie; Brodsky, Christine;
doi:10.6073/pasta/c790bd0b1bdde870b5b1e7f631d3d38e

Authors: Nilon, Charlie; Brodsky, Christine;

Full Metadata and Download Link: knb-lter-bes.543.170

Abstract:
This dataset is associated with BES Bird Monitoring Bird Monitoring Project: ================= The BES Bird Monitoring Project is a breeding bird survey designed to find out what birds are found in the breeding season in Baltimore and where. Our monitoring efforts will show associations among block group socioeconomic variables, land cover, land use, and habitat features with breeding bird abundance, to provide information for land managers on possible consequences of land use changes on bird communities. A distinguishing feature of the bird monitoring at BES LTER, relative to other urban bird work, is the capacity for long-term monitoring of features at multiple scales through links to other parts of the project. Different processes influence habitat for birds at different scales, e.g. ongoing household level human decision-making at lot scale vs. block or neighborhood scale abandonment/re-development. Our project seeks to understand how these processes impact bird occurrence, abundance, and composition differ at the lot, block and neighborhood scale. The database consists of four tables. Sites, Surveys, Taxalist, and Birds. Sites records thje sites and their characteristics. Surveys describe the actual outings or sampling sessions. They describe the weather, the temperature, the sites visited. Taxalist provides the integration of speciaies abbreviations and common names, and Birds describes the actual sightings, linking to the other three tables. Attribute information: The tables form a set. Here are the fields and relationship information: Surveys: site_id FK->Sites[site_id] survey_id survey_date time_start time_end observer wind_speed wind_dir air_temp temp_units cloud_cover notes Sites: site_id park_code park_district park_name point_code point_location park_acreage Taxalist: species_id common_name Birds: survey_id FK->surveys[survey_id] site_id FK->surveys[site_id] species_id FK->taxalist[species_id] distance bird_count notes seen heard direction time_class

knb-lter-bes.544.120 Biodiversity - Fauna - Bird Survey - Table 2 of 4 - Taxalist -- Nilon, Charlie;
doi:10.6073/pasta/ea265b5b6a9ec977b28308543e7b0cc6

Authors: Nilon, Charlie;

Full Metadata and Download Link: knb-lter-bes.544.120

Abstract:
This dataset is associated with BES Bird Monitoring Bird Monitoring Project: ================= The BES Bird Monitoring Project is a breeding bird survey designed to find out what birds are found in the breeding season in Baltimore and where. Our monitoring efforts will show associations among block group socioeconomic variables, land cover, land use, and habitat features with breeding bird abundance, to provide information for land managers on possible consequences of land use changes on bird communities. A distinguishing feature of the bird monitoring at BES LTER, relative to other urban bird work, is the capacity for long-term monitoring of features at multiple scales through links to other parts of the project. Different processes influence habitat for birds at different scales, e.g. ongoing household level human decision-making at lot scale vs. block or neighborhood scale abandonment/re-development. Our project seeks to understand how these processes impact bird occurrence, abundance, and composition differ at the lot, block and neighborhood scale. The database consists of four tables. Sites, Surveys, Taxalist, and Birds. Sites records thje sites and their characteristics. Surveys describe the actual outings or sampling sessions. They describe the weather, the temperature, the sites visited. Taxalist provides the integration of speciaies abbreviations and common names, and Birds describes the actual sightings, linking to the other three tables. Attribute information: The tables form a set. Here are the fields and relationship information: Surveys: site_id FK->Sites[site_id] survey_id survey_date time_start time_end observer wind_speed wind_dir air_temp temp_units cloud_cover notes Sites: site_id park_code park_district park_name point_code point_location park_acreage Taxalist: species_id common_name Birds: survey_id FK->surveys[survey_id] site_id FK->surveys[site_id] species_id FK->taxalist[species_id] distance bird_count notes seen heard direction time_class

knb-lter-bes.545.120 Biodiversity - Fauna - Bird Survey - Table 3 of 4 - Sites -- Nilon, Charlie;
doi:10.6073/pasta/6c55f21c67e4fa823dd828a324bf6b8a

Authors: Nilon, Charlie;

Full Metadata and Download Link: knb-lter-bes.545.120

Abstract:
This dataset is associated with BES Bird Monitoring Bird Monitoring Project: ================= The BES Bird Monitoring Project is a breeding bird survey designed to find out what birds are found in the breeding season in Baltimore and where. Our monitoring efforts will show associations among block group socioeconomic variables, land cover, land use, and habitat features with breeding bird abundance, to provide information for land managers on possible consequences of land use changes on bird communities. A distinguishing feature of the bird monitoring at BES LTER, relative to other urban bird work, is the capacity for long-term monitoring of features at multiple scales through links to other parts of the project. Different processes influence habitat for birds at different scales, e.g. ongoing household level human decision-making at lot scale vs. block or neighborhood scale abandonment/re-development. Our project seeks to understand how these processes impact bird occurrence, abundance, and composition differ at the lot, block and neighborhood scale. The database consists of four tables. Sites, Surveys, Taxalist, and Birds. Sites records thje sites and their characteristics. Surveys describe the actual outings or sampling sessions. They describe the weather, the temperature, the sites visited. Taxalist provides the integration of speciaies abbreviations and common names, and Birds describes the actual sightings, linking to the other three tables. Attribute information: The tables form a set. Here are the fields and relationship information: Surveys: site_id FK->Sites[site_id] survey_id survey_date time_start time_end observer wind_speed wind_dir air_temp temp_units cloud_cover notes Sites: site_id park_code park_district park_name point_code point_location park_acreage Taxalist: species_id common_name Birds: survey_id FK->surveys[survey_id] site_id FK->surveys[site_id] species_id FK->taxalist[species_id] distance bird_count notes seen heard direction time_class

knb-lter-bes.546.120 Biodiversity - Fauna - Bird Survey - Table 4 of 4 - Surveys -- Nilon, Charlie;
doi:10.6073/pasta/075297a5f30067526f80dc928d80a292

Authors: Nilon, Charlie;

Full Metadata and Download Link: knb-lter-bes.546.120

Abstract:
This dataset is associated with BES Bird Monitoring Bird Monitoring Project: ================= The BES Bird Monitoring Project is a breeding bird survey designed to find out what birds are found in the breeding season in Baltimore and where. Our monitoring efforts will show associations among block group socioeconomic variables, land cover, land use, and habitat features with breeding bird abundance, to provide information for land managers on possible consequences of land use changes on bird communities. A distinguishing feature of the bird monitoring at BES LTER, relative to other urban bird work, is the capacity for long-term monitoring of features at multiple scales through links to other parts of the project. Different processes influence habitat for birds at different scales, e.g. ongoing household level human decision-making at lot scale vs. block or neighborhood scale abandonment/re-development. Our project seeks to understand how these processes impact bird occurrence, abundance, and composition differ at the lot, block and neighborhood scale. The database consists of four tables. Sites, Surveys, Taxalist, and Birds. Sites records thje sites and their characteristics. Surveys describe the actual outings or sampling sessions. They describe the weather, the temperature, the sites visited. Taxalist provides the integration of speciaies abbreviations and common names, and Birds describes the actual sightings, linking to the other three tables. Attribute information: The tables form a set. Here are the fields and relationship information: Surveys: site_id FK->Sites[site_id] survey_id survey_date time_start time_end observer wind_speed wind_dir air_temp temp_units cloud_cover notes Sites: site_id park_code park_district park_name point_code point_location park_acreage Taxalist: species_id common_name Birds: survey_id FK->surveys[survey_id] site_id FK->surveys[site_id] species_id FK->taxalist[species_id] distance bird_count notes seen heard direction time_class

knb-lter-bes.547.120 Biodiversity - Fauna - Soil Fauna - Cub Hill Forest Earthworms -- Szlavecz, Kathy;
doi:10.6073/pasta/4d478e75b1e4276e3a48ee9e79f4da2b

Authors: Szlavecz, Kathy;

Full Metadata and Download Link: knb-lter-bes.547.120

Abstract:
Cub Hill forest EW metadata Introduction The Baltimore Ecosystem Study (BES) has established a network of long-term permanent forest plots. These plots will provide long-term data on vegetation, soil and hydrologic processes in the key ecosystem types within the urban ecosystem. The current network of study plots includes eight forest plots, chosen to represent the range of forest conditions in the area. The goal of the soil invertebrate survey was to compare community composition and abundance of soil macrofauna, primarily earthworms (Oligochatea), terrestrial isopods (Isopoda: Oniscidea), and millipedes (Diplopoda). Plot Locations and Characterizations In November of 1998 four rural, forested plots were established at Oregon Ridge Park in Baltimore County northeast of the Gwynns Falls Watershed. Oregon Ridge Park contains Pond Branch, the forested reference watershed for BES. Two of these four plots are located on the top of a slope; the other two are located midway up the slope. Four urban, forested plots were established in November 1998, two at Leakin Park and two adjacent to Hillsdale Park in west Baltimore City in the Gwynns Falls. One of the plots in Hillsdale Park was abandoned in 2004 due to continued vandalism. Plot locations: Hillsdale 1: 39�19'28.14"N, 76�42'16.49"W Hillsdale 2: 39�19'31.24"N, 76�42'28.62"W Leakin 1: 39�18'1.32"N, 76�41'37.08"W Leakin 2: 39�18'5.42"N, 76�41'34.15"W Oregon top-slope - 1: 39�28'51.11"N, 76�41'22.50"W Oregon mid-slope - 1: 39�28'51.32"N, 76�41'18.24"W Oregon top-slope - 2: 39�29'12.74"N, 76�41'22.88"W Oregon mid-slope - 2: 39�29'12.68"N, 76�41'18.62"W Soil arthropods were sampled between November 1999 and 2000 using pitfall traps. At each plot a total of ten traps were placed which were emptied monthly. Earthworms were sampled using a combination of formalin solution (Raw 1954) and mustard suspension. 50cm x 50cm quadrats were used. Earthworms samples were taken is spring, summer and fall 1999, 2000, and 2002. In addition several qualitative samples were taken from residential and commercial areas in the city. Cub Hill forest EW metadata Samples were taken spring 2004, along two 100 m transects. 25 cm x 25 cm quadrats were used at every 10 m point along each transect. Animals were counted and weighed, later identified.

knb-lter-bes.548.120 Biodiversity - Fauna - Soil Fauna - Earthworm Localities -- Szlavecz, Kathy;
doi:10.6073/pasta/53d33bcaec9bf99251b6d7e406db9215

Authors: Szlavecz, Kathy;

Full Metadata and Download Link: knb-lter-bes.548.120

Abstract:
Earthworm localities Introduction The Baltimore Ecosystem Study (BES) has established a network of long-term permanent forest plots. These plots will provide long-term data on vegetation, soil and hydrologic processes in the key ecosystem types within the urban ecosystem. The current network of study plots includes eight forest plots, chosen to represent the range of forest conditions in the area. The goal of the soil invertebrate survey was to compare community composition and abundance of soil macrofauna, primarily earthworms (Oligochatea), terrestrial isopods (Isopoda: Oniscidea), and millipedes (Diplopoda). Plot Locations and Characterizations In November of 1998 four rural, forested plots were established at Oregon Ridge Park in Baltimore County northeast of the Gwynns Falls Watershed. Oregon Ridge Park contains Pond Branch, the forested reference watershed for BES. Two of these four plots are located on the top of a slope; the other two are located midway up the slope. Four urban, forested plots were established in November 1998, two at Leakin Park and two adjacent to Hillsdale Park in west Baltimore City in the Gwynns Falls. One of the plots in Hillsdale Park was abandoned in 2004 due to continued vandalism. Plot locations: Hillsdale 1: 39�19'28.14"N, 76�42'16.49"W Hillsdale 2: 39�19'31.24"N, 76�42'28.62"W Leakin 1: 39�18'1.32"N, 76�41'37.08"W Leakin 2: 39�18'5.42"N, 76�41'34.15"W Oregon top-slope - 1: 39�28'51.11"N, 76�41'22.50"W Oregon mid-slope - 1: 39�28'51.32"N, 76�41'18.24"W Oregon top-slope - 2: 39�29'12.74"N, 76�41'22.88"W Oregon mid-slope - 2: 39�29'12.68"N, 76�41'18.62"W Soil arthropods were sampled between November 1999 and 2000 using pitfall traps. At each plot a total of ten traps were placed which were emptied monthly. Earthworms were sampled using a combination of formalin solution (Raw 1954) and mustard suspension. 50cm x 50cm quadrats were used. Earthworms samples were taken is spring, summer and fall 1999, 2000, and 2002. In addition several qualitative samples were taken from residential and commercial areas in the city. Presence of earthworm species in several localities in the Greater Baltimore Metropolitan Area and nearby rural forests. Earthworms were collected in 2000-2005 using various methods. Specimens are deposited at the Johns Hopkins University and the Hungarian Museum of Natural History.

knb-lter-bes.549.160 Biodiversity - Fauna - Soil Fauna - Relative frequency of soil arthropod groups at Cub Hill -- Szlavecz, Kathy;
doi:10.6073/pasta/9f2f89e48f9e943f7125d1a335d96eb0

Authors: Szlavecz, Kathy;

Full Metadata and Download Link: knb-lter-bes.549.160

Abstract:
Relative frequency of soil arthropod groups at Cub Hill Introduction The Baltimore Ecosystem Study (BES) has established a network of long-term permanent forest plots. These plots will provide long-term data on vegetation, soil and hydrologic processes in the key ecosystem types within the urban ecosystem. The current network of study plots includes eight forest plots, chosen to represent the range of forest conditions in the area. The goal of the soil invertebrate survey was to compare community composition and abundance of soil macrofauna, primarily earthworms (Oligochatea), terrestrial isopods (Isopoda: Oniscidea), and millipedes (Diplopoda). Plot Locations and Characterizations In November of 1998 four rural, forested plots were established at Oregon Ridge Park in Baltimore County northeast of the Gwynns Falls Watershed. Oregon Ridge Park contains Pond Branch, the forested reference watershed for BES. Two of these four plots are located on the top of a slope; the other two are located midway up the slope. Four urban, forested plots were established in November 1998, two at Leakin Park and two adjacent to Hillsdale Park in west Baltimore City in the Gwynns Falls. One of the plots in Hillsdale Park was abandoned in 2004 due to continued vandalism. Plot locations: Hillsdale 1: 39deg19'28.14degN, 76deg42'16.49"W Hillsdale 2: 39deg19'31.24degN, 76deg42'28.62"W Leakin 1: 39deg18'1.32"N, 76deg41'37.08"W Leakin 2: 39deg18'5.42"N, 76deg41'34.15"W Oregon top-slope - 1: 39deg28'51.11"N, 76deg41'22.50"W Oregon mid-slope - 1: 39deg28'51.32"N, 76deg41'18.24"W Oregon top-slope - 2: 39deg29'12.74"N, 76deg41'22.88"W Oregon mid-slope - 2: 39deg29'12.68"N, 76deg41'18.62"W Soil arthropods were sampled between November 1999 and 2000 using pitfall traps. At each plot a total of ten traps were placed which were emptied monthly. Earthworms were sampled using a combination of formalin solution (Raw 1954) and mustard suspension. 50cm x 50cm quadrats were used. Earthworms samples were taken is spring, summer and fall 1999, 2000, and 2002. In addition several qualitative samples were taken from residential and commercial areas in the city. Data were collected during in July 2002. Soil animals were searched for half an hour at each land cover types. A total of 14 residences were selected for this survey- and adata wer always collected between 11 am and 2 pm. Data were collected by undergraduates Janelle Harris and Jennifer Stiltz, as part of an NSF supported UMBEB project (BCEB: Baltimore Collaborative for Environmental Biology).

knb-lter-bes.55.610 GIS Shapefile - Inventory of Historic Properties, Anne Arundel County -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/8a18d1d75914af9b2d1336ba11dd1073

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.55.610

Abstract:
Inventory of Historic Properties for Anne Arundel County. The Maryland Inventory of Historic Properties vector layers are depictions of the approximate locations of historic structures, monuments, districts, and other properties that are listed on the Maryland Inventory of Historic Properties. No attribute information is available for this dataset. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.550.120 Biodiversity - Fauna - Soil Fauna - Relative frequency of terrestrial isopod species in urban and rural forests -- Szlavecz, Kathy;
doi:10.6073/pasta/25d058a1cfeff10fb6a32728c47cfdf6

Authors: Szlavecz, Kathy;

Full Metadata and Download Link: knb-lter-bes.550.120

Abstract:
Relative frequency of terrestrial isopod species in urban and rural forests Introduction The Baltimore Ecosystem Study (BES) has established a network of long-term permanent forest plots. These plots will provide long-term data on vegetation, soil and hydrologic processes in the key ecosystem types within the urban ecosystem. The current network of study plots includes eight forest plots, chosen to represent the range of forest conditions in the area. The goal of the soil invertebrate survey was to compare community composition and abundance of soil macrofauna, primarily earthworms (Oligochatea), terrestrial isopods (Isopoda: Oniscidea), and millipedes (Diplopoda). Plot Locations and Characterizations In November of 1998 four rural, forested plots were established at Oregon Ridge Park in Baltimore County northeast of the Gwynns Falls Watershed. Oregon Ridge Park contains Pond Branch, the forested reference watershed for BES. Two of these four plots are located on the top of a slope; the other two are located midway up the slope. Four urban, forested plots were established in November 1998, two at Leakin Park and two adjacent to Hillsdale Park in west Baltimore City in the Gwynns Falls. One of the plots in Hillsdale Park was abandoned in 2004 due to continued vandalism. Plot locations: Hillsdale 1: 39�19'28.14"N, 76�42'16.49"W Hillsdale 2: 39�19'31.24"N, 76�42'28.62"W Leakin 1: 39�18'1.32"N, 76�41'37.08"W Leakin 2: 39�18'5.42"N, 76�41'34.15"W Oregon top-slope - 1: 39�28'51.11"N, 76�41'22.50"W Oregon mid-slope - 1: 39�28'51.32"N, 76�41'18.24"W Oregon top-slope - 2: 39�29'12.74"N, 76�41'22.88"W Oregon mid-slope - 2: 39�29'12.68"N, 76�41'18.62"W Soil arthropods were sampled between November 1999 and 2000 using pitfall traps. At each plot a total of ten traps were placed which were emptied monthly. Earthworms were sampled using a combination of formalin solution (Raw 1954) and mustard suspension. 50cm x 50cm quadrats were used. Earthworms samples were taken is spring, summer and fall 1999, 2000, and 2002. In addition several qualitative samples were taken from residential and commercial areas in the city. Data were collected between Sep 1999 and April 2000. Ten pitfall traps were placed around each permanent forest plot and emptied monthly. Animals were later identified in the lab. N indicates total number caught during this period.

knb-lter-bes.551.120 Biodiversity - Fauna - Soil Fauna - Species List -- Szlavecz, Kathy;
doi:10.6073/pasta/68996ceeb488ad3ceab02ee965a80663

Authors: Szlavecz, Kathy;

Full Metadata and Download Link: knb-lter-bes.551.120

Abstract:
Arthropod and isopod species list

knb-lter-bes.56.610 GIS Shapefile - Inventory of Historic Properties, Baltimore County -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/267d698dbbc94fc30fca281e26af0c46

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.56.610

Abstract:
Inventory of Historic Properties for Baltimore County. The Maryland Inventory of Historic Properties vector layers are depictions of the approximate locations of historic structures, monuments, districts, and other properties that are listed on the Maryland Inventory of Historic Properties. No attribute information is available for this dataset. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.57.610 GIS Shapefile - Inventory of Historic Properties, Carroll County -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/bdd784c1d175ff6c280829e2e1481df2

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.57.610

Abstract:
Inventory of Historic Properties for Carroll County. The Maryland Inventory of Historic Properties vector layers are depictions of the approximate locations of historic structures, monuments, districts, and other properties that are listed on the Maryland Inventory of Historic Properties. No attribute information is available for this dataset. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.584.200 Baltimore Ecosystem Study: Physical, chemical and biological properties of forest and home lawn soils -- Groffman, Peter M; Raciti, Steve;
doi:10.6073/pasta/3847c58578bd9d5987a49e55066b497b

Authors: Groffman, Peter M; Raciti, Steve;

Full Metadata and Download Link: knb-lter-bes.584.200

Abstract:
Abstract: One-meter soil cores were taken to evaluate soil texture, bulk density, carbon and nitrogen pools, microbial biomass carbon and nitrogen content, microbial respiration, potential net nitrogen mineralization, potential net nitrification and inorganic nitrogen pools in 32 residential home lawns that differed by previous land use and age, but had similar soil types. These were compared to soils from 8 forested reference sites. Purpose: Soil cores were obtained from residential and forest sites in the Baltimore, MD USA metropolitan area. The residential sites were mostly within the Gwynns Falls Watershed (-76.012008W, -77.314183E, 39.724847N, 38.708367S and approximately 17 km2) Lawns on residential sites were dominated by a variety of cool season turfgrasses. Forest soil cores were taken from permanent forest plots of the Baltimore Ecosystem Study (BES) LTER (Groffman et al. 2006). These remnant forests are over 100 years old with soils that were comparable in type and texture to those underlying the residential study sites. Soils from all sites were from the Manor series (coarse-loamy, micaceous, mesic Typic Dystrudepts), which are well-drained upland soils with loamy textures and bedrock at 5 to 10 feet below the soil surface. To aid the site selection process we used neighborhoods in the Baltimore City metropolitan area that have been mapped using HERCULES, a high resolution land cover classification system designed to assist in the study of human-ecological systems (Cadenasso et al. 2007). Using HERCULES and additional data sources, we identified residential sites that were similar except for single factors that we hypothesized to be important predictors of ecosystem dynamics. These factors included land use history (agriculture and forest, n = 10 and n = 22), housing density (low and medium/high, n = 9 and n = 23), and housing age (4 to 58 yrs old, n = 32). Housing age was acquired from the Maryland Property View database. Prior land use was determined based on land use change maps developed by integrating aerial photos from 1938, 1957, 1971, and 1999 into a geographic information system. Once a list of residential parcels meeting the predefined criteria were identified, we sent mailings to property owners chosen at random from each of the factor groups with the goal of recruiting 40 property owners for a 3 year study (of which this work is a part). We had recruited 32 property owners at the time that soil cores were obtained. Data have been published in Raciti et al. (2011a, 2011b) References Cadenasso, M. L., S. T. A. Pickett, and K. Schwarz. 2007. Spatial heterogeneity in urban ecosystems: reconceptualizing land cover and a framework for classification. Frontiers in Ecology and the Environment 5:80-88. Groffman, P. M., R. V. Pouyat, M. L. Cadenasso, W. C. Zipperer, K. Szlavecz, I. D. Yesilonis, L. E. Band, and G. S. Brush. 2006. Land use context and natural soil controls on plant community composition and soil nitrogen and carbon dynamics in urban and rural forests. Forest Ecology and Management 236:177-192. Raciti, S. R., P. M. Groffman, J. C. Jenkins, R. V. Pouyat, and T. J. Fahey. 2011a. Controls on nitrate production and availability in residential soils. Ecological Applications:In press. Raciti, S. R., P. M. Groffman, J. C. Jenkins, R. V. Pouyat, T. J. Fahey, M. L. Cadenasso, and S. T. A. Pickett. 2011b. Accumulation of carbon and nitrogen in residential soils with different land use histories. Ecosystems 14:287-297.

knb-lter-bes.585.651 Baltimore Ecosystem Study: Soil atmosphere fluxes of carbon dioxide, nitrous oxide and methane -- Groffman, Peter M; Martel, Lisa D;
doi:10.6073/pasta/8052715c19a90b71ac5f1f1c49290f61

Authors: Groffman, Peter M; Martel, Lisa D;

Full Metadata and Download Link: knb-lter-bes.585.651

Abstract:
The Baltimore Ecosystem Study (BES) established a network of long-term permanent biogeochemical study plots in 1998. These plots provide long-term data on vegetation, soil and hydrologic processes in the key ecosystem types within the urban ecosystem. The network of study plots includes forest plots (upland and riparian), chosen to represent the range of forest conditions in the area and grass plots (to represent home lawns). Plots are instrumented with lysimeters (drainage and tension) to sample soil solution chemistry, time domain reflectometry probes to measure soil moisture, dataloggers to measure and record soil temperature, and trace gas flux chambers to measure the flux of carbon dioxide, nitrous oxide and methane from soil to the atmosphere. Measurements of in situ nitrogen mineralization, nitrification and denitrification were made at approximately monthly intervals from Fall 1998 - Fall 2000. Detailed vegetation characterization (all layers) was done in summer 1998 and 2015. Data from these plots has been published in Groffman et al. (2006, 2009), Groffman and Pouyat (2009), Savva et al. (2010), Costa and Groffman (2013), Duncan et al. (2013), Waters et al. (2014), Ni and Groffman (2018), Templeton et al. (2019). Literature Cited Costa, K.H. and P.M. Groffman. 2013. Factors regulating net methane flux in urban forests and grasslands. Soil Science Society of America Journal 77:850 - 855. Duncan, J. M., L. E. Band, and P. M. Groffman. 2013. Towards closing the watershed nitrogen budget: Spatial and temporal scaling of denitrification. Journal of Geophysical Research Biogeosciences 118:1-5; DOI: 10.1002/jgrg.20090 Groffman PM, Pouyat RV, Cadenasso ML, Zipperer WC, Szlavecz K, Yesilonis IC,. Band LE and Brush GS. 2006. Land use context and natural soil controls on plant community composition and soil nitrogen and carbon dynamics in urban and rural forests. Forest Ecology and Management 236:177-192. Groffman, P.M., C.O. Williams, R.V. Pouyat, L.E. Band and I.C. Yesilonis. 2009. Nitrate leaching and nitrous oxide flux in urban forests and grasslands. Journal of Environmental Quality 38:1848-1860. Groffman, P.M. and R.V. Pouyat. 2009. Methane uptake in urban forests and lawns. Environmental Science and Technology 43:5229-5235. DOI: 10.1021/es803720h. Ni, X. and P.M. Groffman. 2018. Declines in methane uptake in forest soils. Proceedings of the National Academies of Science of the United States of America 115:8587-8590. Savva, Y., K. Szlavecz, R. V. Pouyat, P. M. Groffman, and G. Heisler. 2010. Effects of land use and vegetation cover on soil temperature in an urban ecosystem. Soil Science Society of America Journal 74:469-480. Templeton, L., M.L. Cadenasso, J. Sullivan, M. Neel and P.M. Groffman. 2019. Changes in vegetation structure and composition of urban and rural forest patches in Baltimore from 1998 to 2015. Forest Ecology and Management. In press. Waters, E.R., J.L. Morse, N.D. Bettez and P.M. Groffman. 2014. Differential carbon and nitrogen controls of denitrification in riparian zones and streams along an urban to exurban gradient. Journal of Environmental Quality 43:955–963.

knb-lter-bes.609.130 Stable Isotopic Composition of Nitrates and POM in BES Streams -- Kaushal, Sujay;
doi:10.6073/pasta/917770b055b60f0571dd237f8b5f69b2

Authors: Kaushal, Sujay;

Full Metadata and Download Link: knb-lter-bes.609.130

Abstract:
In the Baltimore urban long-term ecological research (LTER) project, (Baltimore Ecosystem Study, BES) we use the watershed approach to evaluate integrated ecosystem function. The LTER research is centered on the Gwynns Falls watershed, a 17,150 ha catchment that traverses a gradient from the urban core of Baltimore, through older urban residential (1900 - 1950) and suburban (1950- 1980) zones, rapidly suburbanizing areas and a rural/suburban fringe. Stable isotopic analyses were carried out on stream samples collected bi-weekly from June 2005 through December 2005 as part of the routine Baltimore LTER sampling. Sites included POBR (forest), MCDN (agricultural), BARN (low-residential), GFGL (suburban), DRKR (urban), GFCP (urban), and RGHT (storm drain). Samples were also taken from a small tributary to the Gwynns Falls (GFGR), approximately 300 m above GFCP, that was highly contaminated with sewage. A major sewer leak to this stream was identified and repaired in April 2004. Stable isotopic analyses of soil water underneath fertilized lawns and atmospheric deposition was measured in long-term lawn study plots on the campus of the University of Maryland Baltimore County. Storm samples were also collected from 6 locations (DR1, DR3.1, DR3.2, DR4, DR5, DRKR gauge) within the Dead Run watershed over July 2005. At one site (DR3), two sets of samples were collected, one just above (DR3.1) and just below (DR3.2) an overflowing sewer. All stormflow samples were collected on the receding limb of the storm hydrograph, as the flashy nature of these urban streams makes sampling the rising limb difficult in terms of both timing and personal safety. Nitrate concentrations are a separate set of chemical analyses than the routine weekly analyses.

knb-lter-bes.62.620 GIS Shapefile - GIS Shapefile, Assessments and Taxation Database, MD Property View 2004, Howard County -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/2417a546044d792da888cdfc22317810

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.62.620

Abstract:
AT_2004_HOWA File Geodatabase Feature Class Thumbnail Not Available Tags Socio-economic resources, Information, Social Institutions, Hierarchy, Territory, BES, Parcel, Property, Property View, A&T, Database, Assessors, Taxation Summary Serves as a basis for performing various analyses based on parcel data. Description Assessments & Taxation (A&T) Database from MD Property View 2004 for Howard County. The A&T Database contains parcel data from the State Department of Assessments and Taxation; it incorporates parcel ownership and address information, parcel valuation information and basic information about the land and structure(s) associated with a given parcel. These data form the basis for the 2004 Database, which also includes selected Computer Assisted Mass Appraisal (CAMA) characteristics, text descriptions to make parcel code field data more readily accessible and logical True/False fields which identify parcels with certain characteristics. Documentation for A&T, including a thorough definition for all attributes is enclosed. Complete Property View documentation can be found at http://www.mdp.state.md.us/data/index.htm under the "Technical Background" tab. It should be noted that the A&T Database consists of points and not parcel boundaries. For those areas where parcel polygon data exists the A&T Database can be joined using the ACCTID or a concatenation of the BLOCK and LOT fields, whichever is appropriate. (Spaces may have to be excluded when concatenating the BLOCK and LOT fields). A cursory review of the 2004 version of the A&T Database indicates that it has more accurate data when compared with the 2003 version, particularly with respect to dwelling types. However, for a given record it is not uncommon for numerous fields to be missing attributes. Based on previous version of the A&T Database it is also not unlikely that some of the information is inaccurate. This layer was edited to remove points that did not have a valid location because they failed to geocode. There were 1160 such points. A listing of the deleted points is in the table with the suffix "DeletedRecords." Credits Maryland Department of Planning Use limitations BES use only. Extent West -77.186932 East -76.699458 North 39.373967 South 39.099693 Scale Range There is no scale range for this item.

knb-lter-bes.63.610 GIS Shapefile - A and T (Assessment and Taxation) DATA, Baltimore City County 2007 -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/bc39975f33d79d5096ded97d9091dbe9

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.63.610

Abstract:
AT_DATA_baci_2007 File Geodatabase Feature Class Thumbnail Not Available Tags BES, Assessments and Taxation Summary For BES research Description A point shapefile for Baltimore City County, Maryland containing ADS data from the State Department of Assessments and Taxation. It is a comprehensive data set that incorporates parcel ownership and address information, parcel valuation information and basic information about the land and structure(s) associated with a given parcel. This data form the basis for the 2004 Database, which also includes selected Computer Assisted Mass Appraisal (CAMA) characteristics, text descriptions to make parcel code field data more readily accessible and logical True/False fields which identify parcels with certain characteristics, and can be used as a basis for performing various analyses based on parcel data. For complete attribute information and further information see enclosed documents. Credits UVM Spatial Analysis Lab Use limitations Restricted to BES research Extent West -81.638161 East -76.528932 North 39.372882 South 37.577177 Scale Range There is no scale range for this item.

knb-lter-bes.700.601 Baltimore Ecosystem Study: Stream chemistry for core sites in Gwynns Falls -- Groffman, Peter M; Rosi, Emma; Martel, Lisa D;
doi:10.6073/pasta/45129da171f2a8ab5a96e9743d0d644b

Authors: Groffman, Peter M; Rosi, Emma; Martel, Lisa D;

Full Metadata and Download Link: knb-lter-bes.700.601

Abstract:
In the Baltimore urban long-term ecological research (LTER) project, (Baltimore Ecosystem Study, BES) we use the watershed approach to evaluate integrated ecosystem function. The LTER research is centered on the Gwynns Falls watershed, a 17,150 ha catchment that traverses a gradient from the urban core of Baltimore, through older urban residential (1900 - 1950) and suburban (1950- 1980) zones, rapidly suburbanizing areas and a rural/suburban fringe. Our long-term sampling network includes four longitudinal sampling sites along the Gwynns Falls as well as several small (40 - 100 ha) watersheds located within or near to the Gwynns Falls. The longitudinal sites provide data on water and nutrient fluxes in the different land use zones of the watershed (rural/suburban, rapidly suburbanizing, old suburban, urban core) and the small watersheds provide more focused data on specific land use areas (forest, agriculture, rural/suburban, urban). Each of the gaging sites is continuously monitored for discharge and is sampled weekly for chemistry. Additional chemical sampling is carried out in a supplemental set of sites to provide a greater range of land use. Weekly analyses includes nitrate, phosphate, total nitrogen, total phosphorus, chloride and sulfate, turbidity, fecal coliforms, temperature, dissolved oxygen and pH. Cations, dissolved organic carbon and nitrogen and metals are measured on selected samples. Streamflow data for this site are posted at: http://waterdata.usgs.gov/md/nwis/nwisman?site_no=015835701

knb-lter-bes.73.610 GIS Shapefile - Counties, MSA - County boundaries within the BES Main Study Area. -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/d372ed9078d265633b839029fc15bced

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.73.610

Abstract:
County boundaries for the BES Metropolitan Study Area (MSA) derived from year 2000 GDT census data. This is the universal MSA boundary for all BES research. The MSA consists of the following 5 counties: Baltimore City, Baltimore County, Anne Arrundel, Carroll, Harford, and Howard. This is part of a collection of Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase itself is available online at beslter.org or lternet.edu. It is considerably large. Upon request, it can be shipped to you on media, such as a flash drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.74.610 GIS Shapefile - Legislative Districts in Baltimore - Boundaries as defined in 2004. -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/54f8942ce2c6b8660bb9b042cce22e1b

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.74.610

Abstract:
Legislative District Boundaries for greater Baltimore. This dataset was sourced from BNIA. No metadata was provided with the dataset. This is part of a collection of Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase itself is available online at beslter.org or lternet.edu. It is considerably large. Upon request, it can be shipped to you on media, such as a flash drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.75.620 GIS Shapefile - Long Term Sampling Grid, 100 Meters, Baltimore MSA - BES Main Study Area -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/de193c9ed98b7e36204b0237d72b4f1d

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.75.620

Abstract:
Long term sampling framework for the Baltimore MSA comprised of contiguous 100 meter grid cells. Used for: telephone survey, field observation survey (observational and photo data), and key informant photo-documentation (text / narrative and photo data). A unique ID, 'GridCell', is used to establish the relationship between this layer and the field data. This is part of a collection of Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase itself is available online at beslter.org or lternet.edu. It is considerably large. Upon request, it can be shipped to you on media, such as a flash drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.76.620 GIS Shapefile - Long Term Sampling Grid, 300 Meters, Baltimore MSA - BES Main Study Area -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/aaf48dfb0a373d58734fe255c1c5eed5

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.76.620

Abstract:
Long term sampling framework for the Baltimore MSA comprised of contiguous 300 meter grid cells. Used for: telephone survey, field observation survey (observational and photo data), and key informant photo-documentation (text / narrative and photo data). A unique ID, 'GridCell', is used to establish the relationship between this layer and the field data. This is part of a collection of Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase itself is available online at beslter.org or lternet.edu. It is considerably large. Upon request, it can be shipped to you on media, such as a flash drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.77.600 GIS Shapefile - Counties, MSA - County boundaries within the BES Main Study Area. -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/77c49d734eb2100de4f8ce771f7c8755

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.77.600

Abstract:
County boundaries for the BES Metropolitan Study Area (MSA) derived from year 2000 GDT census data. This is the universal MSA boundary for all BES research. The MSA consists of the following 5 counties: Baltimore City, Baltimore County, Anne Arrundel, Carroll, Harford, and Howard. This is part of a collection of Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase itself is available online at beslter.org or lternet.edu. It is considerably large. Upon request, it can be shipped to you on media, such as a flash drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.78.640 GIS Shapefile - Neighborhood boundaries for neighborhoods within Baltimore City -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/deb7290737410277d65a342a81f318b7

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.78.640

Abstract:
Neighborhoods within Baltimore City limits. This dataset was sourced from Baltimore Neighborhood Indicators Alliance (BNIA). No additional metadata was provided with the dataset. This is part of a collection of Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.800.440 Baltimore Ecosystem Study: Stream chemistry for Gwynns Falls Upper Tributaries -- Groffman, Peter M; Rosi, Emma; Martel, Lisa D;
doi:10.6073/pasta/5f15b7aa8d3f57d9e05a0392c6f57749

Authors: Groffman, Peter M; Rosi, Emma; Martel, Lisa D;

Full Metadata and Download Link: knb-lter-bes.800.440

Abstract:
In the Baltimore urban long-term ecological research (LTER) project, (Baltimore Ecosystem Study, BES) we use the watershed approach to evaluate integrated ecosystem function. The LTER research is centered on the Gwynns Falls watershed, a 17,150 ha catchment that traverses a gradient from the urban core of Baltimore, through older urban residential (1900 - 1950) and suburban (1950- 1980) zones, rapidly suburbanizing areas and a rural/suburban fringe. Our long-term sampling network includes four longitudinal sampling sites along the Gwynns Falls as well as several small (40 - 100 ha) watersheds located within or near to the Gwynns Falls. The longitudinal sites provide data on water and nutrient fluxes in the different land use zones of the watershed (rural/suburban, rapidly suburbanizing, old suburban, urban core) and the small watersheds provide more focused data on specific land use areas (forest, agriculture, rural/suburban, urban). Each of the gaging sites is continuously monitored for discharge and is sampled weekly for chemistry. Additional chemical sampling is carried out in a supplemental set of sites to provide a greater range of land use. Weekly analyses includes nitrate, phosphate, total nitrogen, total phosphorus, chloride and sulfate, total suspended solids, turbidity, fecal coliforms, temperature, dissolved oxygen and pH. Cations, dissolved organic carbon and nitrogen and metals are measured on selected samples. This dataset presents stream chemistry from the Upper Gwynns Falls tributaries. From April 1999 to August 2000 Johns Hopkins University graduate student Mark Colosimo sampled a group of sites in the Upper Gwynns Falls (Red Run, Horsehead Branch, Scotts Level Branch, Holly Branch). There were two sites in the Red Run drainage. This watershed drains approximately 19 km2 and has been rapidly suburbanizing since the early 1990s. Percent impervious surface was approximately 10% as of 2002. Sampling station Red Run 1 (RR1) was approximately 35 m upstream of the crossing of Painters Mill Bridge Road, and 350 m upstream of the confluence with the Gwynns Falls. Sampling station Red Run 2 (RR2) was farther upstream, between the Pleasant Hill and Dolfield road crossings. There were two sites along Scotts Level Branch, an older suburban watershed which was approximately 25% impervious surface in 1970. Site SL1 drains approximately 11 km2 and is located at the outlet of the sub-watershed, just above the confluence with Gwynns Falls. Site SL2 is at the McDonogh Rd. bridge crossing. The Horsehead Branch (HH) sampling site was located at the McDonogh Road crossing. It drains approximately 5 km2 that has undergone rapid urbanization since the mid 1980s. As of 1997 percent impervious surface was approximately 12%. The Holly Bank (HB) sampling site was located just upstream of Gwynnbrook Ave. Seventy percent of land in this drainage is classified residential. The Gwynns Falls at McDonogh (GF5) site was located at the McDonogh school / McDonogh road crossing of the Gwynns Falls and samples a drainage area of approximately 51 km2, with approximately 20% impervious surface.

knb-lter-bes.83.640 GIS Shapefile - Transportation, Railroads, GDT, MSA -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/3395b86dd2b16a8c9d9a9311763056f2

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.83.640

Abstract:
Railroads for Baltimore Ecosystem Study area sourced from Geographic Data Technology (GDT) Dynamap/Transportation version 6.1. This is considered to be the best available railroads layer for the MSA. Refer to the enclosed documentation for details on Dynamap/Transportation. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.87.640 GIS Shapefile - Transportation, Light Rail, Baltimore City -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/b399232a0c70f334d382186ac88bfb6d

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.87.640

Abstract:
Single light rail line that runs north/south through Baltimore City and into Baltimore County. No metadata was provided with this dataset; the UVM Spatial Analysis Lab has attempted to evaluate this dataset and generate metadata. When compared to high-resolution imagery and other transportation datasets positional inaccuracies were observed. As a result caution should be taken when using this dataset. There are no attributes associated with this dataset. For the best available railroads data use the Railroads_GDT_MSA dataset. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.89.640 GIS Shapefile - Transportation, Parking Facilities, Baltimore City -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/2ac4f5c5dc2edbf1a8b1d97e4c742c1f

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.89.640

Abstract:
Parking lots along with related tax and owner information for Baltimore City. No metadata was provided with this dataset; the UVM Spatial Analysis Lab has attempted to evaluate this dataset and generate metadata. When compared to high-resolution imagery and other transportation datasets positional inaccuracies were observed. As a result caution should be taken when using this dataset. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.90.640 GIS Shapefile - Transportation, Railroads, Baltimore City, Main Study Area -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/c74d04a244969c18f336f40eaf74bda4

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.90.640

Abstract:
Railroads for Baltimore Ecosystem Study area sourced from Geographic Data Technology (GDT) Dynamap/Transportation version 6.1. This is considered to be the best available railroads layer for the MSA. Refer to the enclosed documentation for details on Dynamap/Transportation. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.900.450 Baltimore Ecosystem Study: Stream chemistry for Cub Hill sites -- Groffman, Peter M; Martel, Lisa;
doi:10.6073/pasta/26ec54ad3c51ac3aa6939602385c4016

Authors: Groffman, Peter M; Martel, Lisa;

Full Metadata and Download Link: knb-lter-bes.900.450

Abstract:
In the Baltimore urban long-term ecological research (LTER) project, (Baltimore Ecosystem Study, BES) we use the watershed approach to evaluate integrated ecosystem function. The LTER research is centered on the Gwynns Falls watershed, a 17,150 ha catchment that traverses a gradient from the urban core of Baltimore, through older urban residential (1900 - 1950) and suburban (1950- 1980) zones, rapidly suburbanizing areas and a rural/suburban fringe. Our long-term sampling network includes four longitudinal sampling sites along the Gwynns Falls as well as several small (40 - 100 ha) watersheds located within or near to the Gwynns Falls. The longitudinal sites provide data on water and nutrient fluxes in the different land use zones of the watershed (rural/suburban, rapidly suburbanizing, old suburban, urban core) and the small watersheds provide more focused data on specific land use areas (forest, agriculture, rural/suburban, urban). Each of the gaging sites is continuously monitored for discharge and is sampled weekly for chemistry. Additional chemical sampling is carried out in a supplemental set of sites to provide a greater range of land use. Weekly analyses includes nitrate, phosphate, total nitrogen, total phosphorus, chloride and sulfate, turbidity, fecal coliforms, temperature, dissolved oxygen and pH. Cations, dissolved organic carbon and nitrogen and metals are measured on selected samples. This dataset presents stream chemistry from the Cub Hill stream sites. The Cub Hill site is 14 km from the Baltimore city center (39 degrees 24'30.20N, 76 degrees 30'50.62W) and is the location of the first permanent urban carbon flux tower in an urban/suburban environment, established in 2001 by the U.S. Forest Service. Three stream monitoring sites were established in the residential area in the footprint of the tower; Jennifer Branch at North Wind Rd. (JBNW) and two headwater tributaries to Jennifer Branch: Harford Hills (JBHH) and Ontario (JBON). These sites were sampled weekly from August 2003 through June 2010.

knb-lter-bes.91.640 GIS Shapefile - Transportation, Light Rail Stations, Baltimore City -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/56ec510494713f9803a8189c06a91a72

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.91.640

Abstract:
Lightrail stations for a single light rail line that runs north/south through Baltimore City and into Baltimore County. No metadata was provided with this dataset; the UVM Spatial Analysis Lab has attempted to evaluate this dataset and generate metadata. When compared to high-resolution imagery and other transportation datasets positional inaccuracies were observed. As a result caution should be taken when using this dataset. Attributes consist of the station name and associated MTA bus information. For the best available railroads data use the Railroads_GDT_MSA dataset. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.910.440 Stream chemistry and stream flow overview, methods, and procedures -- Groffman, Peter;
doi:10.6073/pasta/5ba15de2f6f27cc13e5749f3dcccc876

Authors: Groffman, Peter;

Full Metadata and Download Link: knb-lter-bes.910.440

Abstract:
The Baltimore Ecosystem Study Stream Flow and Chemistry Overview document contains information regarding to BES stream chemistry. The topics are: Section 1: Sampling Network Section 2: Streamflow Analysis Section 3: Stream Chemistry Summary of Section 1: Sampling Network 1. Longitudinal sites along the Gwynns Falls 2. Small watersheds Summary of Section 2: Streamflow analysis: 2.1. Collection of Flow Data at USGS Stream Gage Stations 1. General Approach to Discharge 2. Open Channel Sites 3. Sites with Primary Devices 4. Flow Data Publication 5. USGS Methodologies and Protocols 2.2. Stream Gage Calibration and Flow Rating QAQC: Weekly Checks by BES Crews 1. Inside and Outside Gage Check 2. Low Flow Rating Check 3. High Flow Rating Check 4. Digital Photos 5. Selected Station Specific Notes 2.3. Preparation of Flow Data for Exploratory Analysis and Load computation Summary of Section 3: Stream Chemistry 1. Field Sampling 2. Blanks and Spikes 3. Chemical Analyses

knb-lter-bes.92.640 GIS Shapefile - Transportation, Major Roads, Baltimore City - GDT Roads -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/3046b7191e6728ff387e27e40802eb5a

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.92.640

Abstract:
Roads for Baltimore Ecosystem Study area sourced from Geographic Data Technology (GDT) Dynamap/Transportation version 6.1. This is considered to be the best available roads layer for the MSA. Refer to the enclosed documentation for details on Dynamap/Transportation. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.93.640 GIS Shapefile - Transportation, TIGER Road Network -- O'Neil-Dunne, Jarlath; Grove, Morgan;
doi:10.6073/pasta/27b9887e405d33b6e2ce8e75953eecae

Authors: O'Neil-Dunne, Jarlath; Grove, Morgan;

Full Metadata and Download Link: knb-lter-bes.93.640

Abstract:
TIGER road data for the MSA. When compared to high-resolution imagery and other transportation datasets positional inaccuracies were observed. As a result caution should be taken when using this dataset. TIGER, TIGER/Line, and Census TIGER are registered trademarks of the U.S. Census Bureau. ZCTA is a trademark of the U.S. Census Bureau. The Census 2000 TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER data base. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on January 1, 2000 legal boundaries. A complete set of census 2000 TIGER/Line files includes all counties and statistically equivalent entities in the United States, Puerto Rico, and the Island Areas. The Census TIGER data base represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The Census 2000 TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries. The boundary information in the TIGER/Line files are for statistical data collection and tabulation purposes only; their depiction and designation for statistical purposes does not constitute a determination of jurisdictional authority or rights of ownership or entitlement. The Census 2000 TIGER/Line files do NOT contain the Census 2000 urban areas which have not yet been delineated. The files contain information distributed over a series of record types for the spatial objects of a county. There are 17 record types, including the basic data record, the shape coordinate points, and geographic codes that can be used with appropriate software to prepare maps. Other geographic information contained in the files includes attributes such as feature identifiers/census feature class codes (CFCC) used to differentiate feature types, address ranges and ZIP Codes, codes for legal and statistical entities, latitude/longitude coordinates of linear and point features, landmark point features, area landmarks, key geographic features, and area boundaries. The Census 2000 TIGER/Line data dictionary contains a complete list of all the fields in the 17 record types. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

knb-lter-bes.950.421 Baltimore Ecosystem Study: Stream chemistry for Watershed 263 sites -- Groffman, Peter M; Rosi, Emma; Martel, Lisa D;
doi:10.6073/pasta/25b39ca1bb9853a9ed3148ef64a2c1d5

Authors: Groffman, Peter M; Rosi, Emma; Martel, Lisa D;

Full Metadata and Download Link: knb-lter-bes.950.421

Abstract:
In the Baltimore urban long-term ecological research (LTER) project, (Baltimore Ecosystem Study, BES) we use the watershed approach to evaluate integrated ecosystem function. The LTER research is centered on the Gwynns Falls watershed, a 17,150 ha catchment that traverses a gradient from the urban core of Baltimore, through older urban residential (1900 - 1950) and suburban (1950- 1980) zones, rapidly suburbanizing areas and a rural/suburban fringe. Our long-term sampling network includes four longitudinal sampling sites along the Gwynns Falls as well as several small (40 - 100 ha) watersheds located within or near to the Gwynns Falls. The longitudinal sites provide data on water and nutrient fluxes in the different land use zones of the watershed (rural/suburban, rapidly suburbanizing, old suburban, urban core) and the small watersheds provide more focused data on specific land use areas (forest, agriculture, rural/suburban, urban). Each of the gaging sites is continuously monitored for discharge and is sampled weekly for chemistry. Additional chemical sampling is carried out in a supplemental set of sites to provide a greater range of land use. Weekly analyses includes nitrate, phosphate, total nitrogen, total phosphorus, chloride and sulfate, turbidity, fecal coliforms, temperature, dissolved oxygen and pH. Cations, dissolved organic carbon and nitrogen and metals are measured on selected samples. This dataset presents stream chemistry from the Watershed 263 subwatersheds. Watershed 263 is a 364 ha urban storm drain watershed (or sewershed), with 30,000 residents with mixed industrial, institutional, and residential land uses. In March 2004, we established monitoring sites in two sub-watersheds within W263 (Baltimore Street and Lanvale Street). Both are approximately 17 ha with 50% impervious surface and 4% vegetation cover.