Field and remotely sensed measures of soil and vegetation carbon and nitrogen across an urbanization gradient in the Boston metropolitan area
- 941 Downloads
Understanding the impact of urbanization on terrestrial biogeochemistry is critical for addressing society’s grand challenge of global environmental change. We used field observations and remotely sensed data to quantify the effects of urbanization on vegetation and soils across a 100-km urbanization gradient extending from Boston to Harvard Forest and Worcester, MA. At the field-plot scale, the normalized difference vegetation index (NDVI) was positively correlated with aboveground biomass (AGB) and foliar nitrogen (N) content and negatively correlated with impervious surface fraction. Unlike previous studies, we found no significant relationship between NDVI or impervious surface area (ISA) fraction and foliar N concentration. Patterns in foliar N appeared to be driven more strongly by changes in species composition rather than phenotypic plasticity across the urbanization gradient. For forest and non-residential development, soil nitrogen content increased with urban intensity. In contrast, residential land had consistently high soil N content across the gradient of urbanization. When field observations were scaled-up to the Boston Metropolitan Statistical Area (MSA), we found that soil and vegetation N content were negatively correlated with ISA fraction, an indicator of urban intensity. Our results demonstrated the importance of accounting for the influence of impervious surfaces when scaling field data across urban ecosystems. The combination of field data with remote sensing holds promise for disentangling the complex interactions that drive biogeochemical cycling in urbanizing landscapes. Empirical data that accurately characterize variations in urban biogeochemistry are critical to gain a mechanistic understanding of urban ecosystem function and to guide policy makers and planners in developing ecologically sensitive development strategies.
KeywordsUrbanization Gradient Vegetation Soil Nitrogen Carbon Remote sensing NDVI
This research was financially supported by the National Science Foundation and US Forest Service Urban Long Term Research Area Exploratory Awards (ULTRA-Ex) program (DEB-0948857), a National Science Foundation CAREER award (DEB-1149471), and Boston University. We are grateful to Marc-Andre Giasson for his help with sample preparation and instrumental analysis; and Max Brondfield and Byungman Yoon for their assistance in field data collection.
- Berland A (2012) Long-term urbanization effects on tree canopy cover along an urban-rural gradient. Urban Ecosystems 1–18Google Scholar
- Bettez N (2009) Impacts of chronic low level nitrogen deposition along a roadside deposition gradient on forest and estuarine N loading. Ph.D. Dissertation, Cornell University, 93 ppGoogle Scholar
- Efron B, Tibshirani R (1993) An introduction to the bootstrap. Monographs on Statistics and Applied Probability 57Google Scholar
- Energy Information Administration (2008) Emissions of greenhouse gases in the United States. US Department of Energy, Washington, DCGoogle Scholar
- Finzi AC, Van Breemen N, Canham CD (1998) Canopy tree soil interactions within temperate forests: Species effects on soil carbon and nitrogen. Ecol Appl 8(2):440–446Google Scholar
- Forest Inventory and Analysis (2005) http://fia.fs.fed.us/. Accessed 12 October 2011.
- Foster DR (1992) Land-use history (1730–1990) and vegetation dynamics in central New England, USA. Journal of Ecology 753–771Google Scholar
- Foster DR, Aber JD, Cogbill CV (2010) Wildlands and woodlands: A vision for the New England landscape. Harvard University, Harvard ForestGoogle Scholar
- Harris W, Goldstein R, Henderson G (1973) Analysis of forest biomass pools, annual primary production and turnover of biomass for a mixed deciduous forest watershed. In: Young H (ed) IUFRO biomass studies, Nancy, France and Vancouver, BC. University of Maine, College of Life Sciences and Agriculture, Orono, ME, pp 41–64Google Scholar
- Hollinger DY, Ollinger SV, Richardson AD, Meyers TP, Dail DB, Martin ME, Scott NA, Arkebauer TJ, Baldocchi DD, Clark KL, Curtis PS, Davis KJ, Desai AR, Dragoni D, Goulden ML, Gu L, Katul GG, Pallardy SG, Paw UKT, Schmid HP, Stoy PC, Suyker AE, Verma SB (2009) Albedo estimates for land surface models and support for a new paradigm based on foliage nitrogen concentration. Glob Chang Biol 16(2):696–710CrossRefGoogle Scholar
- Jenkins JC, United States. Forest Service. Northeastern Research S (2004) Comprehensive database of diameter-based biomass regressions for North American tree species. United States Department of Agriculture, Forest Service, Northeastern Research StationGoogle Scholar
- Massachusetts Office of Geographic Information, MassGIS (2009) Land Use (2005) data layer. http://www.mass.gov/mgis/lus2005.htm Accessed 2 May 2011.
- Matson P, Johnson L, Billow C, Miller J, Pu R (1994) Seasonal patterns and remote spectral estimation of canopy chemistry across the Oregon transect. Ecological Applications 280–298Google Scholar
- National Climatic Data Center (2011) US National Oceanic and Atmospheric Administration (2009) Online Climate Data Directory. http://lwf.ncdc.noaa.gov/oa/climate/climatedata.html.
- Nihlgard B (1985) The ammonium hypothesis: an additional explanation to the forest dieback in Europe. Ambio 2–8Google Scholar
- Nixon SW, Fulweiler RW (2011) Ecological footprints and shadows in an urban estuary, Narragansett Bay, RI (USA). Regional Environmental Change 1–14Google Scholar
- Ollinger SV, Richardson AD, Martin ME, Hollinger DY, Frolking SE, Reich PB, Plourde LC, Katul GG, Munger JW, Oren R, Smith ML, Paw UKT, Bolstad PV, Cook BD, Day MC, Martin TA, Monson RK, Schmid HP (2008) Canopy nitrogen, carbon assimilation, and albedo in temperate and boreal forests: Functional relations and potential climate feedbacks. Proc Natl Acad Sci 105(49):19336–19341. doi: 10.1073/pnas.0810021105 PubMedCrossRefGoogle Scholar
- O’Neil-Dunne JPM, MacFaden SW, Royar AR, Pelletier KC (2012) An object-based system for LiDAR data fusion and feature extraction. Geocarto International 1–16Google Scholar
- Piao SL, Ciais P, Friedlingstein P, Peylin P, Reichstein M, Luyssaert S, Margolis H, Fang JY, Barr A, Chen AP, Grelle A, Hollinger DY, Laurila T, Lindroth A, Richardson AD, Vesala T (2008) Net carbon dioxide losses of northern ecosystems in response to autumn warming. Nature 451(7174):49–U43PubMedCrossRefGoogle Scholar
- Pickett STA, Cadenasso ML, Grove JM, Groffman PM, Band LE, Boone CG, Burch WR, Grimmond CSB, Hom J, Jenkins JC, Law NL, Nilon CH, Pouyat RV, Szlavecz K, Warren PS, Wilson MA (2008) Beyond urban legends: An emerging framework of urban ecology, as illustrated by the Baltimore ecosystem study. Bioscience 58(2):139–150CrossRefGoogle Scholar
- Population Division of the Department of Economic and Social Affairs of the United Nations Secretariat (2012) World Urbanization Prospects: The 2011 Revision. New York: United NationsGoogle Scholar
- Pouyat RV, Carreiro MM, Mcdonnell MJ, Pickett STA, Groffman PM, Parmelee RW, Medley KE, Zipperer WC (1995) Carbon and Nitrogen Dynamics in Oak Stands Along an Urban-Rural Gradient. Carbon Forms and Functions in Forest Soils 569–587Google Scholar
- Schimel DS, Emanuel W, Rizzo B, Smith T, Woodward FI, Fisher H, Kittel TGF, McKeown R, Painter T, Rosenbloom N, Ojima DS, Parton WJ, Kicklighter DW, McGuire AD, Melillo JM, Pan Y, Haxeltine A, Prentice C, Sitch S, Hibbard K, Nemani R, Pierce L, Running S, Borchers J, Chaney J, Neilson R, Braswell BH (1997) Continental scale variability in ecosystem processes: Models, data, and the role of disturbance. Ecol Monogr 67(2):251–271CrossRefGoogle Scholar
- Sollins P, Reichle DE, Olson JS (1973) Organic matter budget and model for a southern Appalachian Liriodendron forest. Publ. EDFBIBP-73-2. Oak Ridge National Laboratory, Oak Ridge, TNGoogle Scholar
- Stewart ID (2007) Landscape representation and the urban-rural dichotomy in empirical urban heat island literature, 1950–2006. Acta Climatologica et Chorologica Universitatis Szegediensis, Tomus 40–41Google Scholar
- Tritton LM, Hornbeck JW (1982) Northeastern Forest Experiment S Biomass equations for major tree species of the Northeast. US Dept. of Agriculture, Forest Service, Northeastern Forest Experiment StationGoogle Scholar
- U.S. Census Bureau (2010) www.census.gov. Accessed 2 October 2011
- USDA Natural Resources Conservation Service (2009). Soil Survey of Middlesex County, Massachusetts.Google Scholar
- Zhang XY, Friedl MA, Schaaf CB, Strahler AH, Schneider A (2004a) The footprint of urban climates on vegetation phenology. Geophys Res Lett 31(12)Google Scholar