This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-bes/543/170. The abstract below was extracted from the Level 0 data package and is included for context: 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 seen heard direction time_class

This data package is formatted as a Darwin Core Archive (DwC-A, event core). For more information on Darwin Core see https://www.tdwg.org/standards/dwc/. This Level 2 data package was derived from the Level 1 data package found here: https://pasta.lternet.edu/package/metadata/eml/edi/191/4, which was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-bes/543/170. The abstract below was extracted from the Level 0 data package and is included for context: 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 seen heard direction time_class

This data package is formatted according to the "ecocomDP", a data package design pattern for ecological community surveys, and data from studies of composition and biodiversity. For more information on the ecocomDP project see https://github.com/EDIorg/ecocomDP/tree/master, or contact EDI https://environmentaldatainitiative.org.This Level 1 data package was derived from the Level 0 data package found here: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-bes&identifier=543&revision=170The abstract below was extracted from the Level 0 data package and is included for context: 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

Stream chemistry for core sites in Gwynns Falls: concentration of Cl, NO3, PO4, total N and P, SO4, dissolved oxygen, E. coli, plus temperature, pH, clarity, turbidity, isotopes, and pharmaceuticals doi:10.6073/pasta/89eb8f9c94842c3ec0b1e8f80c300e95 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 core long-term monitoring sites. Sampling began at most of these sites in Fall 1998 and is ongoing. A detailed description of these sites is posted at: http://md.water.usgs.gov/BES/. Streamflow data for this site are posted at: http://waterdata.usgs.gov/md/nwis/nwisman?site_no=01583570 Codes and Abbreviations 1 - GFGL - Gwynns Falls at Glyndon (grab samples) - Suburban headwaters - 15-Oct-98 - ongoing 2 - GFGLcomp - Gwynns Falls at Glyndon (ISCO sampler) - Suburban headwaters - 30-Jan-09 - ongoing 3 - GFGB - Gwynns Falls at Gwynnbrook Avenue (Delight) - Suburban - 15-Oct-98 - ongoing 4 - GFVN - Gwynns Falls at Villa Nova (grab samples) - Suburban/urban boundary - 15-Oct-98 - ongoing 5 - GFVNcomp - Gwynns Falls at Villa Nova (ISCO sampler) - Suburban/urban boundary - 1-Apr-08 - ongoing (with gap from June 2002 to January 2004) 6 - GFCP - Gwynns Falls at Carroll Park - Urban - 15-Oct-98 - ongoing 7 - POBR - Pond Branch forested reference site - Forested reference - 15-Oct-98 - ongoing 8 - BARN - Baisman Run at Ivy Hill Road - Suburban unsewered - 4-Dec-98 - onging 8 - MCDN - McDonogh agricultural site - Agricultural - 9-Dec-99 - ongoing 9 - DRKR - Dead Run at Krome Avenue - Urban - 24-Nov-98 - ongoing 10 - MAWI - Maidens Choice at Wilkens Avenue - Urban - 18-Feb-04 - ongoing 11 - RGHT - Rognel Heights (grab samples) - Urban - 25-Feb-99 - ongoing 12 - RGHTisco - Rognel Heights (ISCO sampler) - Urban - 18-Feb-02 - ongoing 13 - GRGF - Gwynns Run at Gwynns Falls - Urban - 27-Aug-01 - onging 14 - GFuGR - Gwynns Falls above Gwynns Run - Urban - 21-Jan-04 - ongoing 15 - CRBR - Cranberry Branch - Exurban - 2-Jun-11 - ongoing 16 - JBHH - Jennifer Branch at Hartford Hills - Suburban - 12-Aug-03 - 5/11/2010 17 - JBNW - Jennifer Branch at Northwind - Suburban - 12-Aug-03 - 6/8/2010 18 - JBON - Jennifer Branch at Ontario - Suburban - 12-Aug-03 - 6/8/2010 19 - LANV - Lanvale street station in WS263 (grab samples) - Urban - 6-Apr-04 - 5/4/2010 20 - LANVisco - Lanvale street station in WS263 (ISCO sampler) - Urban - 1-Apr-04 - 5/7/2009 21 - BALTisco - Baltimore street station in WS263 (ISCO sampler) - Urban - 1-Apr-04 - 5/7/2009 22 - BALT - Baltimore street station in WS263 (grab samples) - Urban - 6-Apr-04 - 5/4/2010 23 - GRuTW - Gwynns Run above trash weir - Urban - 20-Jun-06 - 25-Jul-06 Column,Variable (units) A,Date B,Year C,Julian Date D,Site E,Cl (mg/L) F,NO3 (mg N/L) G,PO4 (ug P/L) H,SO4 (mg/L) I,TN (mg N/L) J,TP (ugP/L) K,time L,stage (ft) M,temperature (deg C) N,dox (mg/L) O,ph P,clarity Q,Turbidity (NTU) R,Ecoli (CFU/100 mL) S,1,7-Dimethylxanthine (ug/L) T,Acetaminophen (ug/L) U,Amphetamine (ug/L) V,Caffeine (ug/L) W,Carbamazepine (ug/L) X,Cimetidine (ug/L) Y,Cotinine (ug/L) Z,Diphenhydramine (ug/L) AA,MDMA (ug/L) AB,Methamphetamine (ug/L) AC,Morphine (ug/L) AD,Sulfadimethoxine (ug/L) AE,Sulfamethoxazole (ug/L) AF,Thiabendazole (ug/L) AG,d15N-NO3 (0/00) AH,d18O-NO3 (0/00) AI,Ca (mg/L) AJ,HCO3 (estimated mg/L) AK,K (mg/L) AL,Mg (mg/L) AM,Na (mg/L) Methods: Samples are collected weekly at an established sampling location at each station. Sampling locations were chosen based on adequate concentration of flow, proximity to weir and staff gage, and low vulnerability to disturbance. Samples are collected and stored in polyethylene bottles in a laboratory at the University of Maryland Baltimore County (UMBC). Approximately every six weeks, samples are shipped to the Cary Institute of Ecosystem Studies (CIES) for analysis. Weekly analyses includes nitrate, phosphate, total nitrogen, total phosphorus, chloride and sulfate, turbidity, temperature, dissolved oxygen and pH. Fecal coliforms, cations, dissolved organic carbon and nitrogen and metals are measured on selected samples. Samples for anion and cation analysis are filtered (0.45 micron). Samples for total N, total P, turbidity, and fecal coliform analysis are not filtered. One blank from the laboratory distilled water source is prepared each week and stored along with the samples. Once every six weeks one extra filtered sample is collected at three stations, Carroll Park, Villanova, and Glyndon, for percent recovery (spike) analysis. Back at the UMBC lab, the extra bottle is spiked with one mL each of a 1000 ppm NO3- and a 1000 ppb PO4- standard per 100 ml of solution; the cation bottle is spiked with a combined nitrate and phosphate standard and stored and analyzed with other samples. Samples are stored at 4 degrees C. Concentrations of nitrate, chloride and sulfate are analyzed on a Dionex LC20 series ion chromatograph. Concentrations of phosphate are analyzed on a Lachat Quikchem 8000 flow injection analyzer. Total nitrogen and phosphorus are analyzed by persulfate digestion followed by analysis of nitrate and phosphate on a Lachat Quikchem 8000 flow injection analyzer. If the value for total N is more than 0.10 mg N L-1 less than nitrate-N, the total N value for that sample is set to the nitrate value. If the value for total P is more than 0.01 mg P L-1 less than the phosphate P, the total P value for that sample is set to the phosphate value. An HF Scientific DRT-15CE turbidimeter is used to analyze turbidity. Temperature, pH, conductivity and dissolved oxygen are measured using a handheld meter during weekly visits for sample collection. Fecal coliform analysis was done from October 2001 through September 2004 using Micrology Laboratories' Coliscan EasyGel method. This work was led by Karin Readel at UMBC. Concentrations of pharmaceuticals and personal care products (PPCPs) were monitored at the GRFG, GFCP, DRKR, GFGB, BARN and POBR. Surface water samples were collected in precleaned 250 mL amber glass jars from each site and chilled on ice until they could be frozen upon return to the laboratory. Thawed samples were filtered using a Whatman 25 mm GF/F glass fiber filter, and then a 100 mL portion weighed for polymeric solid phase extraction (SPE) with Oasis 200 mg HLB sorbent (Waters Corporation, Milford, MA). Cartridges were conditioned with 6 mL each of high purity acetone and methanol (Optima grade, Fisher Scientific, St. Louis, MO, U.S.A.), followed by 6 mL of purified reagent water (Barnstead Nanopure, Dubuque, IA, U.S.A.). Cartridges were eluted with 6 mL acetone, followed by 6 mL of methanol, and the eluates were concentrated under vacuum and constant stream of nitrogen gas. Residues were dissolved in 200 microliter methanol/water (50:50) and fortified with 100 ng of internal standards. Standard compounds, purchased from Sigma-Aldrich (St. Louis, MO) and Cerilliant, included D-amphetamine (AMPH), methamphetamine, MDMA (3,4-methylenedioxy-methamphetamine), acetaminophen, caffeine, 1,7-dimethylxanthine, diphenhydramine, cimetidine, sulfamethoxazole, sulfadimethoxine, cotinine, morphine, carbamazepine, and thiabendazole. Labeled internal standards (13C3-caffeine, methamphetamine-d8, MDMA-d8, morphine-d3, and 13C6-sulfamethazine) were purchased from Cerilliant (Round Rock, TX) and Cambridge Isotopes (Tewksbury, MA). Extracts were analyzed using multiple reaction monitoring (MRM) using liquid chromatography tandem mass spectrometry (LC-MS/MS) on a Quattro Micro (Waters Corporation, Milford, MA) triple quadrupole mass spectrometer interfaced with a Waters 2695 HPLC. Method detection limits, determined from repeated analysis of a low-level (0.005 microgram/L) fortified water sample, ranged from 0.001 to 0.017 microgram/L. For more details on instrumental conditions and method validation, see the Supporting Information S1 at doi: 10.1021/acs.est.6b03717. Analysis of the stable isotopic concentration of nitrates and POM were carried out on stream samples collected bi-weekly from June 2005 through December 2005 at the POBR, MCDN, BARN, GFGL, DRKR, GFCP, GFGR and RGHT sites. Frozen samples were analyzed for d15N-NO3 and 18O-NO3 using the denitrifier method at the USGS Stable Isotope Laboratory in Menlo Park, CA

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. Soil coring took place over a one month period during the summer of 2007. For residential sites, we overlaid a grid onto a map of each property and randomly chose two locations for coring. Locations beneath impervious surfaces (buildings, walkways, driveways) or within close proximity to belowground pipes and power lines were excluded and another random location identified. Undisturbed one-meter soil cores were extracted from each of these locations using a 3.3 cm diameter soil corer. Cores were enclosed in plastic sleeves with end-caps, put into coolers, and transported to the laboratory where they were stored at 4 oC until they could be processed. Coring in the forested reference plots followed a similar procedure, with two cores taken from random locations at each site. In total, 80 intact soil cores were collected from 32 residential properties and 8 forest sites. Digital photos were taken of each soil core followed by a visual inspection to determine horizon depths and Munsell color. Soil cores were also inspected for obvious signs of disturbance such as buried horizons, lithologic discontinuities, or human artifacts of less than 3.3 cm (the diameter of the soil core). Cores were divided into four soil depth intervals (0 to 10 cm, 10 to 30 cm, 30 to 70 cm, and 70 to 100cm) and sorted to remove coarse roots and rocks (> 2 mm). The roots and rocks were dried at 105 oC, weighed and set aside. Rock volume was determined by mass and an assumed density of 2.7 g/cm3. Subsamples of homogenized soil from each depth interval were analyzed for soil dry weight and percent moisture (48 hrs at 105 oC). Bulk density (BD) was calculated as BD = (Total Dry Mass - Rock Mass) / (Total Volume - Rock Volume). Soil texture was obtained by the hydrometer method (Gee and J.W. 1986). Total C and N were obtained by flash-combustion / oxidation using a Thermo Finnigan Flash EA 1112 elemental analyzer (0.06% C and 0.01% N detection limits). For all data, the density of C in a unit area (1 m2) was calculated as C = CfBD(1-d2mm)V, where C is carbon density, d2mm is the fraction of material larger than 2 mm diameter, BD is bulk density, Cf is the fraction by mass of organic C, and V is the volume of the soil core (Post et al., 1982). Subsamples of homogenized soil from each depth interval were set aside to determine 1) initial KCl exchangeable NO3- and NH4+, 2) net nitrification, net mineralization and basal respiration, and 3) microbial biomass C and N. Exchangeable inorganic N (NO3-, NH4+) was extracted from approximately 10 g (dry mass) of soil with 40 ml of 2 M KCl. Samples were agitated for 60 min at 200 rpm on an orbital shaker table and then left undisturbed for 2 hours. The supernatant liquid from each sample was then collected and filtered through Whatman number 42 filter paper into nalgene bottles. Samples were analyzed colorimetrically for NO3- and NH4+ concentration using a Lachat Flow Injection Analyzer (Lachat Instruments, Loveland, CO 80539). Rates of potential net N mineralization, nitrification, and respiration were measured in a 10-day laboratory incubation of soils at room temperature. Soils (25 grams per incubation) were placed in 946-mL glass jars with lids fitted with septa for gas sampling. After 10 days, the headspace of the jars was sampled by syringe, and the gas samples were analyzed for carbon dioxide (CO2) by thermal conductivity gas chromatography. Inorganic N was extracted as described above. Mineralization was calculated as the accumulation of total inorganic N, nitrification was calculated as the accumulation of NO3-, and respiration was calculated as the accumulation of CO2 over the course of the 10-day incubation. Microbial biomass C and N were measured using the chloroform fumigation-incubation method (Jenkinson and Powlson 1976). Field moist soils (25 grams) were fumigated to lyse microbial cells in the samples. The fumigated samples were then inoculated with fresh soil, allowing microorganisms to regrow using the dead cells as substrate. The flushes of CO2 and 2 M KCl-extractable inorganic N (NH4+ and NO3-) released by the cells during the incubation were assumed to be proportional to the C and N in the microbial biomass of the original sample. A proportionality constant (0.45) was used to calculate biomass C from the CO2 ?ush, which was measured by thermal conductivity gas chromatography. Inorganic N flush data were not corrected with a proportionality constant. Column Names: Description 1. Site: House designation or name of Baltimore Ecosystem Study forested reference plot 2. REP#: Used to distinguish between multiple measurements at a single Site 3. Depth: Depth interval from which the soil was collected. Soil in a given depth interval was homogenized prior to analyses. 4. Core_Z_Ht_cm: Height of this subsection of the soil core in cm. For instance, if the depth interval was 0 - 10 cm, this would equal a z-height of 10cm. 5. LU_Current: Current land use (residential or forest) 6. LU_Previous: Land use prior to development (forest or agriculture). Only relevant for sites that are currently residential. Based on historical aerial photos and housing age (see Wehling MA. 2001. Land use/land cover change from 1915 to 1999 in the Gwynns Falls Watershed, Baltimore County, Maryland: creation of a suburban social ecology. [Dissertation]. Athens (OH): Department of Geography, Ohio University.) 7. Yr_Built: Year the house was built (from the Maryland Property View database) 8. CoarseVeg: Coarse vegetation density (i.e. trees) descriptor from the HERCULES land use classification system. See Cadenasso ML, Pickett TA, Schwarz K. 2007. Spatial heterogeneity in urban ecosystems: reconceptualizing land cover and a framework for classification. Front Ecol Environ 5(2):80-8. 9. StructDen: Structure density (i.e. density of buildings/houses) descriptor from the HERCULES land use classification system. See Cadenasso ML, Pickett TA, Schwarz K. 2007. Spatial heterogeneity in urban ecosystems: reconceptualizing land cover and a framework for classification. Front Ecol Environ 5(2):80-8. 10. BD: Bulk Density (g/cm3) 11. N_Perc: Percent nitrogen of the mineral soil 12. C_Perc: Percent carbon of the mineral soil 13. C_N: Carbon to Nitrogen Ratio of the mineral soil 14. N_gm2: Nitrogen content of the mineral soil (g/m2) 15. C_gm2: Carbon content of the mineral soil (g/m2) 16. Sand_Perc: Percent Sand (from soil texture analysis using the hydrometer method; Gee and Bauder 1986) 17. Clay_Perc: Percent Clay (from soil texture analysis using the hydrometer method; Gee and Bauder 1986) 18. Silt_Perc: Percent Silt (from soil texture analysis using the hydrometer method; Gee and Bauder 1986) 19. MB Carbon: Microbial Biomass Carbon; Microbial biomass C and N were measured using the chloroform fumigation-incubation method (Jenkinson and Powlson 1976). 20. Respiration1: Respiration; (ug C/g soil/day) 21. Initial NO3 (+NO2): Initial NO3 (+NO2); (ug N/g soil) 22. Initial NH4: Initial NH4 (ug N/g soil) 23. MBN: Microbial Biomass Nitrogen; (ug N/g soil) 24. Potential Net N Min: Potential Net Nitrogen Mineralization; (ug N/g soil/day) 25. Potential Net Nitrification: Potential Net Nitrogen Mineralization; (ug N/g soil/day) * Ref Plots = Baltimore Ecosystem Study forested reference plot ** House1 to House32 refer to individual addresses, which have been removed to protect anonymity. *** Rates of potential net N mineralization, nitrification, and respiration were measured in a 10-day laboratory incubation of soils at room temperature. (For detailed methods, consult Groffman et al. [1999]). The latitudes and longitudes posted in this record encompass all the plot locations. Individual plot locations are withheld to protect the homeowners' privacy. Data have been published in Raciti et al. (2011a, 2011b) Literature Cited: 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. Gee, G. W. and B. J.W. 1986. Particle size analysis. Pages 383-411 in A. Klute, editor. Methods of Soil Analysis, part 1. Physical and mineralogical methods, Second Edition. American Society of Agronomy, Madison, WI. 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. Jenkinson, D. S. and D. S. Powlson. 1976. The effects of biocidal treatments on metabolism in soil V. A method for measuring soil biomass. Soil Biology and Biochemistry 8:209-213. 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.

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. Link to BES vegetation reserarch and data: http://beslter.org/frame4-page_3b.html Data from these plots has been published in Groffman et al. (2006, 2009) and Groffman and Pouyat (2009). 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 sec N, 76 deg 42 min 16.49 sec W Hillsdale 2: 39 deg 19 min 31.24 sec N, 76 deg 42 min 28.62 sec W Leakin 1: 39 deg 18 min 1.32 sec N, 76 deg 41 min 37.08 sec W Leakin 2: 39 deg 18 min 5.42 sec N, 76 deg 41 min 34.15 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 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, 76deg 41 min 18.24 sec W Oregon top-slope - 2: 39 deg 29 min 12.74 sec N, 76deg 41 min 22.88 sec W Oregon mid-slope - 2: 39 deg 29 min 12.68 sec N, 76deg 41 min 18.62 sec W McDonogh 1: 39 deg 23 min 44.31 sec N, 76deg 46 min 19.26 sec W McDonogh 2: 39 deg 23 min 52.26 sec N, 76deg 46 min 23.52 sec W UMBC 1: 39 deg 15 min 8.82 sec N, 76deg 42 min 10.43 sec W UMBC 2: 39 deg 14 min 6.50 sec N, 76deg 42 min 48.71 sec W Soil Moisture Soil moisture is measured once every four to six weeks at each plot. In each of the forested plots, five (six at Leakin plot #2) time domain reflectometry waveguide probes from SoilMoisture Equipment Corporation were installed vertically into the soil at random locations throughout the plot. The waveguide probes are 20 cm long, so those vertically installed span a depth of 0 to 20 cm below ground. Each forested plot also has one (two at Leakin plot #2) set of four waveguide probes installed horizontally into the soil in one location at four depths: 10, 20, 30, and 50 cm below ground. The McDonogh plots each have two sets of horizontal and no vertical waveguide probes. Attached to each belowground waveguide is an aboveground cable with a BNC Male Coaxial Fitting on the end. This fitting connects with SoilMoisture's Trase System I (Model 6050X1, Version 2000 Software), which uses time domain reflectometry (TDR) to measure soil moisture. Every four to six weeks each individual vertical and horizontal waveguide in each plot is connected to the portable Trase TDR processor; soil moisture is measured instantaneously and stored in the processor. After all plots are completed, the stored data is downloaded onto a computer at the BES office at UMBC. 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.

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. Soil coring took place over a one month period during the summer of 2007. For residential sites, we overlaid a grid onto a map of each property and randomly chose two locations for coring. Locations beneath impervious surfaces (buildings, walkways, driveways) or within close proximity to belowground pipes and power lines were excluded and another random location identified. Undisturbed one-meter soil cores were extracted from each of these locations using a 3.3 cm diameter soil corer. Cores were enclosed in plastic sleeves with end-caps, put into coolers, and transported to the laboratory where they were stored at 4 oC until they could be processed. Coring in the forested reference plots followed a similar procedure, with two cores taken from random locations at each site. In total, 80 intact soil cores were collected from 32 residential properties and 8 forest sites. Digital photos were taken of each soil core followed by a visual inspection to determine horizon depths and Munsell color. Soil cores were also inspected for obvious signs of disturbance such as buried horizons, lithologic discontinuities, or human artifacts of less than 3.3 cm (the diameter of the soil core). Cores were divided into four soil depth intervals (0 to 10 cm, 10 to 30 cm, 30 to 70 cm, and 70 to 100cm) and sorted to remove coarse roots and rocks (> 2 mm). The roots and rocks were dried at 105 oC, weighed and set aside. Rock volume was determined by mass and an assumed density of 2.7 g/cm3. Subsamples of homogenized soil from each depth interval were analyzed for soil dry weight and percent moisture (48 hrs at 105 oC). Bulk density (BD) was calculated as BD = (Total Dry Mass - Rock Mass) / (Total Volume - Rock Volume). Soil texture was obtained by the hydrometer method (Gee and J.W. 1986). Total C and N were obtained by flash-combustion / oxidation using a Thermo Finnigan Flash EA 1112 elemental analyzer (0.06% C and 0.01% N detection limits). For all data, the density of C in a unit area (1 m2) was calculated as C = CfBD(1-d2mm)V, where C is carbon density, d2mm is the fraction of material larger than 2 mm diameter, BD is bulk density, Cf is the fraction by mass of organic C, and V is the volume of the soil core (Post et al., 1982). Subsamples of homogenized soil from each depth interval were set aside to determine 1) initial KCl exchangeable NO3- and NH4+, 2) net nitrification, net mineralization and basal respiration, and 3) microbial biomass C and N. Exchangeable inorganic N (NO3-, NH4+) was extracted from approximately 10 g (dry mass) of soil with 40 ml of 2 M KCl. Samples were agitated for 60 min at 200 rpm on an orbital shaker table and then left undisturbed for 2 hours. The supernatant liquid from each sample was then collected and filtered through Whatman number 42 filter paper into nalgene bottles. Samples were analyzed colorimetrically for NO3- and NH4+ concentration using a Lachat Flow Injection Analyzer (Lachat Instruments, Loveland, CO 80539). Rates of potential net N mineralization, nitrification, and respiration were measured in a 10-day laboratory incubation of soils at room temperature. Soils (25 grams per incubation) were placed in 946-mL glass jars with lids fitted with septa for gas sampling. After 10 days, the headspace of the jars was sampled by syringe, and the gas samples were analyzed for carbon dioxide (CO2) by thermal conductivity gas chromatography. Inorganic N was extracted as described above. Mineralization was calculated as the accumulation of total inorganic N, nitrification was calculated as the accumulation of NO3-, and respiration was calculated as the accumulation of CO2 over the course of the 10-day incubation. Microbial biomass C and N were measured using the chloroform fumigation-incubation method (Jenkinson and Powlson 1976). Field moist soils (25 grams) were fumigated to lyse microbial cells in the samples. The fumigated samples were then inoculated with fresh soil, allowing microorganisms to regrow using the dead cells as substrate. The flushes of CO2 and 2 M KCl-extractable inorganic N (NH4+ and NO3-) released by the cells during the incubation were assumed to be proportional to the C and N in the microbial biomass of the original sample. A proportionality constant (0.45) was used to calculate biomass C from the CO2 ?ush, which was measured by thermal conductivity gas chromatography. Inorganic N flush data were not corrected with a proportionality constant. Column Names: Description 1. Site: House designation or name of Baltimore Ecosystem Study forested reference plot 2. REP#: Used to distinguish between multiple measurements at a single Site 3. Depth: Depth interval from which the soil was collected. Soil in a given depth interval was homogenized prior to analyses. 4. Core_Z_Ht_cm: Height of this subsection of the soil core in cm. For instance, if the depth interval was 0 - 10 cm, this would equal a z-height of 10cm. 5. LU_Current: Current land use (residential or forest) 6. LU_Previous: Land use prior to development (forest or agriculture). Only relevant for sites that are currently residential. Based on historical aerial photos and housing age (see Wehling MA. 2001. Land use/land cover change from 1915 to 1999 in the Gwynns Falls Watershed, Baltimore County, Maryland: creation of a suburban social ecology. [Dissertation]. Athens (OH): Department of Geography, Ohio University.) 7. Yr_Built: Year the house was built (from the Maryland Property View database) 8. CoarseVeg: Coarse vegetation density (i.e. trees) descriptor from the HERCULES land use classification system. See Cadenasso ML, Pickett TA, Schwarz K. 2007. Spatial heterogeneity in urban ecosystems: reconceptualizing land cover and a framework for classification. Front Ecol Environ 5(2):80-8. 9. StructDen: Structure density (i.e. density of buildings/houses) descriptor from the HERCULES land use classification system. See Cadenasso ML, Pickett TA, Schwarz K. 2007. Spatial heterogeneity in urban ecosystems: reconceptualizing land cover and a framework for classification. Front Ecol Environ 5(2):80-8. 10. BD: Bulk Density (g/cm3) 11. N_Perc: Percent nitrogen of the mineral soil 12. C_Perc: Percent carbon of the mineral soil 13. C_N: Carbon to Nitrogen Ratio of the mineral soil 14. N_gm2: Nitrogen content of the mineral soil (g/m2) 15. C_gm2: Carbon content of the mineral soil (g/m2) 16. Sand_Perc: Percent Sand (from soil texture analysis using the hydrometer method; Gee and Bauder 1986) 17. Clay_Perc: Percent Clay (from soil texture analysis using the hydrometer method; Gee and Bauder 1986) 18. Silt_Perc: Percent Silt (from soil texture analysis using the hydrometer method; Gee and Bauder 1986) 19. MB Carbon: Microbial Biomass Carbon; Microbial biomass C and N were measured using the chloroform fumigation-incubation method (Jenkinson and Powlson 1976). 20. Respiration1: Respiration; (ug C/g soil/day) 21. Initial NO3 (+NO2): Initial NO3 (+NO2); (ug N/g soil) 22. Initial NH4: Initial NH4 (ug N/g soil) 23. MBN: Microbial Biomass Nitrogen; (ug N/g soil) 24. Potential Net N Min: Potential Net Nitrogen Mineralization; (ug N/g soil/day) 25. Potential Net Nitrification: Potential Net Nitrogen Mineralization; (ug N/g soil/day) * Ref Plots = Baltimore Ecosystem Study forested reference plot ** House1 to House32 refer to individual addresses, which have been removed to protect anonymity. *** Rates of potential net N mineralization, nitrification, and respiration were measured in a 10-day laboratory incubation of soils at room temperature. (For detailed methods, consult Groffman et al. [1999]). The latitudes and longitudes posted in this record encompass all the plot locations. Individual plot locations are withheld to protect the homeowners' privacy. Data have been published in Raciti et al. (2011a, 2011b) Literature Cited: 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. Gee, G. W. and B. J.W. 1986. Particle size analysis. Pages 383-411 in A. Klute, editor. Methods of Soil Analysis, part 1. Physical and mineralogical methods, Second Edition. American Society of Agronomy, Madison, WI. 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. Jenkinson, D. S. and D. S. Powlson. 1976. The effects of biocidal treatments on metabolism in soil V. A method for measuring soil biomass. Soil Biology and Biochemistry 8:209-213. 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.

This data package is formatted according to the "ecocomDP", a data package design pattern for ecological community surveys, and data from studies of composition and biodiversity. For more information on the ecocomDP project, contact EDI or see https://environmentaldatainitiative.org.This Level 1 data package was derived from the Level 0 data package found here: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-bes&identifier=543&revision=170The abstract below was extracted from the Level 0 data package and is included for context: 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

This data package is formatted according to the "ecocomDP", a data package design pattern for ecological community surveys, and data from studies of composition and biodiversity. For more information on the ecocomDP project, contact EDI or see https://environmentaldatainitiative.org.This Level 1 data package was derived from the Level 0 data package found here: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-bes&identifier=543&revision=170The abstract below was extracted from the Level 0 data package and is included for context: 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

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. Soil coring took place over a one month period during the summer of 2007. For residential sites, we overlaid a grid onto a map of each property and randomly chose two locations for coring. Locations beneath impervious surfaces (buildings, walkways, driveways) or within close proximity to belowground pipes and power lines were excluded and another random location identified. Undisturbed one-meter soil cores were extracted from each of these locations using a 3.3 cm diameter soil corer. Cores were enclosed in plastic sleeves with end-caps, put into coolers, and transported to the laboratory where they were stored at 4 oC until they could be processed. Coring in the forested reference plots followed a similar procedure, with two cores taken from random locations at each site. In total, 80 intact soil cores were collected from 32 residential properties and 8 forest sites. Digital photos were taken of each soil core followed by a visual inspection to determine horizon depths and Munsell color. Soil cores were also inspected for obvious signs of disturbance such as buried horizons, lithologic discontinuities, or human artifacts of less than 3.3 cm (the diameter of the soil core). Cores were divided into four soil depth intervals (0 to 10 cm, 10 to 30 cm, 30 to 70 cm, and 70 to 100cm) and sorted to remove coarse roots and rocks (> 2 mm). The roots and rocks were dried at 105 oC, weighed and set aside. Rock volume was determined by mass and an assumed density of 2.7 g/cm3. Subsamples of homogenized soil from each depth interval were analyzed for soil dry weight and percent moisture (48 hrs at 105 oC). Bulk density (BD) was calculated as BD = (Total Dry Mass - Rock Mass) / (Total Volume - Rock Volume). Soil texture was obtained by the hydrometer method (Gee and J.W. 1986). Total C and N were obtained by flash-combustion / oxidation using a Thermo Finnigan Flash EA 1112 elemental analyzer (0.06% C and 0.01% N detection limits). For all data, the density of C in a unit area (1 m2) was calculated as C = CfBD(1-d2mm)V, where C is carbon density, d2mm is the fraction of material larger than 2 mm diameter, BD is bulk density, Cf is the fraction by mass of organic C, and V is the volume of the soil core (Post et al., 1982). Subsamples of homogenized soil from each depth interval were set aside to determine 1) initial KCl exchangeable NO3- and NH4+, 2) net nitrification, net mineralization and basal respiration, and 3) microbial biomass C and N. Exchangeable inorganic N (NO3-, NH4+) was extracted from approximately 10 g (dry mass) of soil with 40 ml of 2 M KCl. Samples were agitated for 60 min at 200 rpm on an orbital shaker table and then left undisturbed for 2 hours. The supernatant liquid from each sample was then collected and filtered through Whatman number 42 filter paper into nalgene bottles. Samples were analyzed colorimetrically for NO3- and NH4+ concentration using a Lachat Flow Injection Analyzer (Lachat Instruments, Loveland, CO 80539). Rates of potential net N mineralization, nitrification, and respiration were measured in a 10-day laboratory incubation of soils at room temperature. Soils (25 grams per incubation) were placed in 946-mL glass jars with lids fitted with septa for gas sampling. After 10 days, the headspace of the jars was sampled by syringe, and the gas samples were analyzed for carbon dioxide (CO2) by thermal conductivity gas chromatography. Inorganic N was extracted as described above. Mineralization was calculated as the accumulation of total inorganic N, nitrification was calculated as the accumulation of NO3-, and respiration was calculated as the accumulation of CO2 over the course of the 10-day incubation. Microbial biomass C and N were measured using the chloroform fumigation-incubation method (Jenkinson and Powlson 1976). Field moist soils (25 grams) were fumigated to lyse microbial cells in the samples. The fumigated samples were then inoculated with fresh soil, allowing microorganisms to regrow using the dead cells as substrate. The flushes of CO2 and 2 M KCl-extractable inorganic N (NH4+ and NO3-) released by the cells during the incubation were assumed to be proportional to the C and N in the microbial biomass of the original sample. A proportionality constant (0.45) was used to calculate biomass C from the CO2 ?ush, which was measured by thermal conductivity gas chromatography. Inorganic N flush data were not corrected with a proportionality constant. Column Names: Description 1. Site: House designation or name of Baltimore Ecosystem Study forested reference plot 2. REP#: Used to distinguish between multiple measurements at a single Site 3. Depth: Depth interval from which the soil was collected. Soil in a given depth interval was homogenized prior to analyses. 4. Core_Z_Ht_cm: Height of this subsection of the soil core in cm. For instance, if the depth interval was 0 - 10 cm, this would equal a z-height of 10cm. 5. LU_Current: Current land use (residential or forest) 6. LU_Previous: Land use prior to development (forest or agriculture). Only relevant for sites that are currently residential. Based on historical aerial photos and housing age (see Wehling MA. 2001. Land use/land cover change from 1915 to 1999 in the Gwynns Falls Watershed, Baltimore County, Maryland: creation of a suburban social ecology. [Dissertation]. Athens (OH): Department of Geography, Ohio University.) 7. Yr_Built: Year the house was built (from the Maryland Property View database) 8. CoarseVeg: Coarse vegetation density (i.e. trees) descriptor from the HERCULES land use classification system. See Cadenasso ML, Pickett TA, Schwarz K. 2007. Spatial heterogeneity in urban ecosystems: reconceptualizing land cover and a framework for classification. Front Ecol Environ 5(2):80-8. 9. StructDen: Structure density (i.e. density of buildings/houses) descriptor from the HERCULES land use classification system. See Cadenasso ML, Pickett TA, Schwarz K. 2007. Spatial heterogeneity in urban ecosystems: reconceptualizing land cover and a framework for classification. Front Ecol Environ 5(2):80-8. 10. BD: Bulk Density (g/cm3) 11. N_Perc: Percent nitrogen of the mineral soil 12. C_Perc: Percent carbon of the mineral soil 13. C_N: Carbon to Nitrogen Ratio of the mineral soil 14. N_gm2: Nitrogen content of the mineral soil (g/m2) 15. C_gm2: Carbon content of the mineral soil (g/m2) 16. Sand_Perc: Percent Sand (from soil texture analysis using the hydrometer method; Gee and Bauder 1986) 17. Clay_Perc: Percent Clay (from soil texture analysis using the hydrometer method; Gee and Bauder 1986) 18. Silt_Perc: Percent Silt (from soil texture analysis using the hydrometer method; Gee and Bauder 1986) 19. MB Carbon: Microbial Biomass Carbon; Microbial biomass C and N were measured using the chloroform fumigation-incubation method (Jenkinson and Powlson 1976). 20. Respiration1: Respiration; (ug C/g soil/day) 21. Initial NO3 (+NO2): Initial NO3 (+NO2); (ug N/g soil) 22. Initial NH4: Initial NH4 (ug N/g soil) 23. MBN: Microbial Biomass Nitrogen; (ug N/g soil) 24. Potential Net N Min: Potential Net Nitrogen Mineralization; (ug N/g soil/day) 25. Potential Net Nitrification: Potential Net Nitrogen Mineralization; (ug N/g soil/day) * Ref Plots = Baltimore Ecosystem Study forested reference plot ** House1 to House32 refer to individual addresses, which have been removed to protect anonymity. *** Rates of potential net N mineralization, nitrification, and respiration were measured in a 10-day laboratory incubation of soils at room temperature. (For detailed methods, consult Groffman et al. [1999]). The latitudes and longitudes posted in this record encompass all the plot locations. Individual plot locations are withheld to protect the homeowners' privacy. Data have been published in Raciti et al. (2011a, 2011b) Literature Cited: 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. Gee, G. W. and B. J.W. 1986. Particle size analysis. Pages 383-411 in A. Klute, editor. Methods of Soil Analysis, part 1. Physical and mineralogical methods, Second Edition. American Society of Agronomy, Madison, WI. 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. Jenkinson, D. S. and D. S. Powlson. 1976. The effects of biocidal treatments on metabolism in soil V. A method for measuring soil biomass. Soil Biology and Biochemistry 8:209-213. 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.