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  • Baltimore Ecosystem Study: Physical, chemical and biological properties of forest and home lawn soils
  • Groffman, Peter M; Cary Institute of Ecosystem Studies
    Raciti, Steve; Hofstra University
  • 2023-12-19
  • Groffman, P.M. and S. Raciti. 2023. Baltimore Ecosystem Study: Physical, chemical and biological properties of forest and home lawn soils ver 301. Environmental Data Initiative. https://doi.org/DOI_PLACE_HOLDER (Accessed 2024-11-21).
  • 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.

  • Geographic Coordinates
    • N: 39.3245, S: 39.3245, E: -76.705, W: -76.705
    • N: 39.3253, S: 39.3253, E: -76.708, W: -76.708
    • N: 39.3004, S: 39.3004, E: -76.694, W: -76.694
    • N: 39.3015, S: 39.3015, E: -76.693, W: -76.693
    • N: 39.4809, S: 39.4809, E: -76.69, W: -76.69
    • N: 39.4809, S: 39.4809, E: -76.688, W: -76.688
    • N: 39.4869, S: 39.4869, E: -76.69, W: -76.69
    • N: 39.4869, S: 39.4869, E: -76.689, W: -76.689
    • N: 39.722, S: 39.19, E: -76.33, W: -76.93
  • knb-lter-bes.584.301  (Uploaded 2023-12-19)  
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  • DOI PLACE HOLDER
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