Regional modelling of soil carbon at multiple depths within a subtropical watershed.

article i nfo Environmental factors that exert control over fine-scale spatial patterns of soil organic carbon (SOC) within profiles and across large regions differ by geographic location and landscape setting. Regions with large SOC storage and high variability can serve as natural laboratories to investigate how environmental factors generate vertical and horizontal SOC patterns across the landscape. This was investigated in the Santa Fe River watershed (SFRW), Florida, where we modelled the spatial distribution of total C (TC) at four depths to 180 cm (0-30, 30-60, 60-120, and 120-180 cm) and at an aggregated depth of 0-100 cm. A total of 554 samples from 141 sampling sites distributed along land use and soil order combinations were analyzed for TC by high-temperature combustion. A vertical trend of TC stocks decreasing with depth was identified. Horizontal trends of TC were modelled to identify the environmental determinants of TC in the SFRW. We used analysis of variance (ANOVA) and compared regression block kriging with lognormal block kriging to scale up TC across the SFRW. Total soil C was influenced by soil depth, land use, soil type, soil drainage class, and geologic unit. Regression kriging performed better than block kriging to scale up TC at three out of five depth intervals. This indicates that in the majority of cases environmental factors were the major determinants of the spatial distribution of TC relative to its spatial autocorrelation. At 60-120 and 120- 180 cm, the local spatial dependence of TC was more important than environmental factors to explain its variation across the watershed. Our models show that 54.0 Tg (teragrams) of C is held in the upper 1 m of soils in the SFRW, and significant amounts are stored in deeper layers. They also identified the major factors responsible for regional spatial patterns of TC in this subtropical region, providing information to support current efforts of conservation of soil resources in Florida, and under similar environmental conditions in the southeastern U.S. and elsewhere.

[1]  R. Pouyata,et al.  Soil carbon pools and fluxes in urban ecosystems , 2009 .

[2]  Ross E. McMurtrie,et al.  Does conversion of forest to agricultural land change soil carbon and nitrogen? a review of the literature , 2002 .

[3]  C. Dunnett.  Pairwise Multiple Comparisons in the Unequal Variance Case , 1980 .

[4]  H. Levene.  Robust tests for equality of variances , 1961 .

[5]  Neil McKenzie,et al.  Integrating forest soils information across scales: spatial prediction of soil properties under Australian forests. , 2000 .

[6]  F. D. Coninck.  Major mechanisms in formation of spodic horizons , 1980 .

[7]  M. Jurado-Expósito,et al.  Using geostatistical and remote sensing approaches for mapping soil properties , 2005 .

[8]  P. Gong,et al.  Analysis of Factors Controlling Soil Carbon in the Conterminous United States , 2006 .

[9]  Neil McKenzie,et al.  A quantitative Australian approach to medium and small scale surveys based on soil stratigraphy and environmental correlation , 1993 .

[10]  Gary A. Peterson,et al.  Soil Attribute Prediction Using Terrain Analysis , 1993 .

[11]  Igor V. Florinsky,et al.  Prediction of soil properties by digital terrain modelling , 2002, Environ. Model. Softw..

[12]  F. J. Pierce,et al.  Soil Carbon Maps , 2003 .

[13]  B. Henderson,et al.  Australia-wide predictions of soil properties using decision trees , 2005 .

[14]  Jerome L. Myers,et al.  Research Design and Statistical Analysis , 1991 .

[15]  R. Bryant,et al.  Sources of Uncertainty Affecting Soil Organic Carbon Estimates in Northern New York , 2003 .

[16]  M. Fiorella,et al.  Regional Soil organic carbon storage estimates for western Oregon by multiple approaches , 1998 .

[17]  Gu Lb,et al.  Soil carbon stocks and land use change : a meta analysis , 2022 .

[18]  Lawrence E. Band,et al.  Characterizing the Spatial Pattern of Soil Carbon and Nitrogen Pools in the Turkey Lakes Watershed: A Comparison of Regression Techniques , 2002 .

[19]  Mogens Humlekrog Greve,et al.  Preliminary estimates of contemporary soil organic carbon stocks in Denmark using multiple datasets and four scaling-up methods , 2003 .

[20]  G. P. Robertson,et al.  Can topographical and yield data substantially improve total soil carbon mapping by regression kriging , 2007 .

[21]  G. Heuvelink,et al.  A generic framework for spatial prediction of soil variables based on regression-kriging , 2004 .

[22]  Alex B. McBratney,et al.  Spatial prediction of soil properties from landform attributes derived from a digital elevation model , 1994 .

[23]  P. Williams,et al.  Near-Infrared Technology in the Agricultural and Food Industries , 1987 .

[24]  Sabine Grunwald.  Disaggregation and scientific visualization of earthscapes considering trends and spatial dependence structures , 2008 .

[25]  R. Hendrick,et al.  The effects of management on soil and plant carbon sequestration in slash pine plantations , 2001 .

[26]  W. Hoeffding,et al.  Contributions to Probability and Statistics: Essays in Honor of Harold Hotelling , 1961 .

[27]  H. H. Ku,et al.  Contributions to Probability and Statistics, Essays in Honor of Harold Hotelling. , 1961 .

[28]  F. Nachtergaele.  Soil taxonomy—a basic system of soil classification for making and interpreting soil surveys: Second edition, by Soil Survey Staff, 1999, USDA–NRCS, Agriculture Handbook number 436, Hardbound , 2001 .

[29]  N. McKenzie,et al.  Spatial prediction of soil properties using environmental correlation , 1999 .

[30]  D. W. Reeves,et al.  SOIL CARBON RELATIONSHIPS WITH TERRAIN ATTRIBUTES, ELECTRICAL CONDUCTIVITY, AND A SOIL SURVEY IN A COASTAL PLAIN LANDSCAPE , 2004 .

[31]  Niels H. Batjes,et al.  Mapping soil carbon stocks of Central Africa using SOTER , 2008 .

[32]  Budiman Minasny,et al.  On digital soil mapping , 2003 .

[33]  H. Elsenbeer,et al.  Soil organic carbon concentrations and stocks on Barro Colorado Island — Digital soil mapping using Random Forests analysis , 2008 .

[34]  K. Hollien,et al.  Changes across artificial E-Bh boundaries formed under simulated fluctuating water tables. , 2000 .

[35]  Budiman Minasny,et al.  Prediction and digital mapping of soil carbon storage in the Lower Namoi Valley , 2006 .

[36]  Sabine Grunwald,et al.  Multi-criteria characterization of recent digital soil mapping and modeling approaches , 2009 .

[37]  R. Reese.  Geostatistics for Environmental Scientists , 2001 .

[38]  B. L. Welch.  ON THE COMPARISON OF SEVERAL MEAN VALUES: AN ALTERNATIVE APPROACH , 1951 .

[39]  P. Gong,et al.  Quantity and spatial variability of soil carbon in the conterminous United States , 2006 .

[40]  Sabine Grunwald,et al.  Comparison of multivariate methods for inferential modeling of soil carbon using visible/near-infrared spectra , 2008 .

[41]  R. Lark,et al.  Geostatistics for Environmental Scientists , 2001 .

[42]  H. Jenny,et al.  Factors of Soil Formation , 1941 .

[43]  Luboš Borůvka,et al.  Forest soil acidification assessment using principal component analysis and geostatistics , 2007 .

[44]  A. Konopka,et al.  FIELD-SCALE VARIABILITY OF SOIL PROPERTIES IN CENTRAL IOWA SOILS , 1994 .

[45]  R. V. Rossel,et al.  Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties , 2006 .

[46]  Pierre Goovaerts,et al.  Fine-resolution mapping of soil organic carbon based on multivariate secondary data , 2006 .

[47]  Donald G. Bullock,et al.  Management practice effects on surface total carbon: Differences in spatial variability patterns , 2006 .

[48]  Leo Breiman,et al.  Classification and Regression Trees , 1984 .

[49]  S. Grunwald,et al.  Spatial Distribution of Soil Properties in Water Conservation Area 3 of the Everglades , 2006 .

[50]  Sabine Grunwald,et al.  Incorporation of spectral data into multivariate geostatistical models to map soil phosphorus variability in a Florida wetland , 2007 .

[51]  M. Koschorreck,et al.  Microbial Fe(III) Reduction in Acidic Mining Lake Sediments after Addition of an Organic Substrate and Lime , 2002 .

[52]  W. M. Post,et al.  Soil carbon sequestration and land‐use change: processes and potential , 2000 .

[53]  A. McBratney,et al.  Further results on prediction of soil properties from terrain attributes: heterotopic cokriging and regression-kriging , 1995 .

[54]  K. Reddy,et al.  Loss‐on‐Ignition Method to Assess Soil Organic Carbon in Calcareous Everglades Wetlands , 2008 .

[55]  Morton B. Brown,et al.  372: The Anova and Multiple Comparisons for Data with Heterogeneous Variances , 1974 .