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This article in SSSAJ

  1. Vol. 74 No. 3, p. 870-879
     
    Received: June 26, 2009
    Published: May, 2010


    * Corresponding author(s): sabgru@ufl.edu
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doi:10.2136/sssaj2009.0242

Upscaling of Dynamic Soil Organic Carbon Pools in a North-Central Florida Watershed

  1. Gustavo M. Vasquesa,
  2. Sabine Grunwald *a,
  3. James O. Sickmanb and
  4. Nicholas B. Comerfordc
  1. a Soil and Water Science Dep., Univ. of Florida, 2169 McCarty Hall, P.O. Box 110290, Gainesville, FL 32611
    b Dep. of Environmental Sciences, Univ. of California, Riverside, CA 92521
    c North Florida Research and Education Center, Univ. of Florida, Quincy, FL 32351

Abstract

Regional-scale assessment of soil C pools is essential to provide information for C cycling models, land management, and policy decisions, and elucidate the relative contribution of different C pools to total C (TC). We estimated TC and four soil C fractions, namely recalcitrant C (RC), hydrolyzable C (HC), hot-water-soluble C (SC), and mineralizable C (MC), at 0 to 30 cm across a 3585-km2 mixed-use watershed in north-central Florida. We used lognormal block kriging (BK) and regression block kriging (RK) to upscale soil C using 102 training samples and compared the models using 39 validation samples. Regression kriging produced the most accurate models for TC and RC, whereas the labile C fractions (HC, SC, and MC) were best modeled by BK. Maps produced by BK showed similar spatial patterns due to the strong correlation between the labile C fractions and the similarity of their spatial dependence structure. Estimates of TC and RC were similar due to their high correlation and the similarity of their global trend models. Total soil C amounted to 27.40 Tg across the watershed, indicating the potential of these soils to store C. Recalcitrant C totaled 22.49 Tg (82% of TC), suggesting that a large amount of TC could be potentially stored for centuries to millennia. Our estimates of soil C and fractions within a mixed-use watershed in Florida highlight the importance of appropriately characterizing the inherent spatial dependence structure of soil C, as well as relevant regional environmental patterns (e.g., hydrology), to better explain the variability of soil C.

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