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GLOBAL BIOGEOCHEMICAL CYCLES, VOL. 20, GB3004, doi:10.1029/2005GB002507, 2006
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Large-area spatially explicit estimates of tropical soil carbon stocks and response to land-cover change Karen W. Holmes,1,2 Oliver A. Chadwick,3 Phaedon C. Kyriakidis,3 Eliomar P. Silva de Filho,4 Joa˜o Vianei Soares,5 and Dar A. Roberts3 Received 10 March 2005; revised 3 March 2006; accepted 27 April 2006; published 18 July 2006.
[1] Studies of tropical soil organic carbon (SOC) response to deforestation present
conflicting results, confounding estimates of the regional effects of land-cover change on carbon storage. We calculated the change in SOC stocks due to deforestation through 1996 for the state of Rondoˆnia, Brazil, in the southwestern Amazon basin. Whereas the net change in SOC for the state as a whole was slightly negative (0.5% or 5012 Gg), spatially explicit maps suggest dramatic local changes, ranging from 76% to +74%, with outliers as high as +330%. The direction and magnitude of change in SOC following forest clearing is related to original forest soil carbon and pH, which in turn provides a general measure for overall nutrient availability and possible toxicities. When native soil carbon is high, SOC decreases in response to land-cover conversion from forest to pasture; conversely, low soil carbon and low soil fertility lead to gains in carbon under pasture. Mapping variability, rather than relying on large-area averages, illustrates why results from individual field sites have been contradictory. Citation: Holmes, K. W., O. A. Chadwick, P. C. Kyriakidis, E. P. Silva de Filho, J. V. Soares, and D. A. Roberts (2006), Large-area spatially explicit estimates of tropical soil carbon stocks and response to land-cover change, Global Biogeochem. Cycles, 20, GB3004, doi:10.1029/2005GB002507.
1. Introduction [2] In the Amazon, land-cover conversion dramatically reduces standing biomass as forests are converted to pasture or crop land. Typically, land-use change is unidirectional, leading to a one-time release of carbon and resulting in lower carbon sequestration potential due to the nature of agroecosystems [Fearnside and Barbosa, 1998; Lugo and Brown, 1993; Paustian et al., 1997]. Compared with the standing biomass in tropical forests, tropical soils sequester a relatively small amount of carbon, but both inherent soil properties and management decisions can modify the carbon sequestration capacity of tropical soils after land conversion [Cerri et al., 2003; Neill and Davidson, 2000; Paustian et al., 1997]. Unfortunately, regional prediction and mapping of the impacts of tropical deforestation on soil carbon pools and fluxes include uncertainties because of varied distributions of soil properties [Richter and Babbar, 1 School of Earth and Geographical Sciences and School of Plant Biology, University of Western Australia, Crawley, Western Australia, Australia. 2 Formerly at Geography Department, University of California, Santa Barbara, California, USA. 3 Geography Department, University of California, Santa Barbara, California, USA. 4 Departamento de Geografı´a, Universidade Federal de Rondoˆnia (UNIR), Porto Velho, Brazil. 5 Instituto de Pesquisas Espacias (INPE), Sao Jose dos Campos, Brazil.
Copyright 2006 by the American Geophysical Union. 0886-6236/06/2005GB002507$12.00
1991], strong environmental gradients [Prince and Steininger, 1999], and heterogeneous patterns of land cover conversion [Curran et al., 1994]. The regional (over hundreds of square kilometers) consequences of deforestation on soil organic carbon (SOC) levels can only be effectively evaluated by using quantitative empirical estimates of biogeochemical change collected and modeled on a regional basis. These data are difficult to come by and difficult to analyze. The relationship between the change in SOC (DSOC) following deforestation and the full suite of original forest edaphic properties has not been well defined, nor investigated over a large and geographically diverse area. Here we evaluate regional relationships between preclearing soil nutrient levels and changes in SOC following deforestation to provide a regional context for previous field studies and future regional biogeochemical analysis of the effects of land-cover change in the Amazon basin. [3] Localized research in the Amazon indicates that landcover change impacts soil C stocks with conflicting results [Lugo and Brown, 1993; Murty et al., 2002; Neill and Davidson, 2000; Neill et al., 1997], ranging from a decrease [Desjardins et al., 1994; Veldkamp, 1994], to no detectable change [Kauffman et al., 1998; McGrath et al., 2001], to an increase in C stocks [Mora˜es et al., 1996; Neill et al., 1996; Numata et al., 2003; Trumbore et al., 1995; Van Noordwijk et al., 1997]. These mixed results reflect different C-cycling dynamics across geographically diverse field areas and reduce our ability to predict carbon levels from presentday environmental conditions or from any ‘‘average’’ re-
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HOLMES ET AL.: SPATIALLY EXPLICIT ESTIMATES OF SOIL CARBON STOCKS
gional environmental descriptors. However, soil carbon is correlated with easily measured soil properties, such as grain size (% clay) and pH [Van Noordwijk et al., 1997]. Neill and Davidson [2000] found a positive correlation between preclearing forest soil carbon and postclearing C dynamics, which suggests that primary forest soil fertility may be useful for predicting the biogeochemical effects of deforestation. [4] In this paper, we use a geostatistical approach to map regional patterns of soil carbon stocks [Bernoux et al., 1998b; Cerri et al., 2000, 2004], and extend the analysis to map changes following forest clearing in the southwestern Amazon. A large regional soil profile database and remotely sensed classification of land cover were used to estimate SOC levels prior to and following deforestation, and the resulting maps combined to produce spatially explicit estimates of DSOC. Forest nutrient stocks were tested as predictors for DSOC, as a means of forecasting biogeochemical changes in undisturbed tropical forests. Our specific objectives were threefold: (1) to estimate and map forest soil C stocks for a large area in Amazoˆnia; (2) to produce gridded maps of the change in soil C stocks following deforestation; and (3) to assess the relationship between the magnitude and direction of C-stock changes and the undisturbed forest edaphic properties.
2. Data and Methods [5] The following steps were performed: Carbon and other soil nutrient stocks from 0 – 30 cm depth were calculated at all sample locations; soil profile data were divided into two subsets, forested and nonforested sites; spatial dependence in each data set was modeled and interpolated to produce regional maps of C stocks in forest and nonforest on 1-km grids; the difference between the two maps was calculated to produce a final map of DSOC following deforestation through 1996; and the magnitude and direction of change in C stocks were compared with a suite of preclearing soil properties using linear multivariate regression. 2.1. Study Area [6] The study covered approximately 195,000 km2 in Rondoˆnia, Brazil, located in the southwestern Amazon basin (Figure 1). Diverse rock types, tectonic quiescence, and high rainfall have produced a rolling landscape with variable, often highly weathered, soils [Holmes et al., 2004]. Natural vegetation ranges from dense tropical rain forest to deciduous rain forest to savanna along the roughly north-south decreasing precipitation gradient decreasing from 2600 mm yr1 in the north to 1600 mm yr1 in the south [Dunne, 1999]. Agricultural settlement over the last 30 years has led to high deforestation rates (since 1970’s, 0.5 to 2.5% per year [Roberts et al., 2002]); the most common trend for land-cover change is conversion of forest to cattle pasture [Fearnside, 1993; Schneider et al., 2000]. 2.2. Soil Profile Data [7] The soil profile data were collected in 1996 for a state zoning project (2a ZEE-RO, Segunda Aproximac¸a˜o do
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Zoneamento So´cio-Econoˆmico Ecolo´gico do Estado de Rondoˆnia), and consist of field observations and auger samples georeferenced by hand-held GPS, and laboratory analyses for all samples [Cochrane and Cochrane, 1998]. No previously collected samples were included (http:// www.whrc.org/southamerica/LBAData/Amaz_Soil_prof. htm) to avoid increased modeling error due to differences in carbon analysis methods and lower accuracy georeferencing. One advantage of the data set described here is that all samples were collected within approximately 1 year and were analyzed by one laboratory, thus providing a temporal snapshot of soil nutrient status and analysis consistency. We calculated weighted averages of soil properties to a depth of 30 cm for organic carbon (SOC: %), phosphorus (P: ppm), nitrogen (N: %), exchangeable calcium, magnesium, potassium, aluminum, effective cation exchange capacity (Ca, Mg, K, Al, ECEC: cmolc kg1 soil), soil pH, clay (%), silt (%), and bulk density (BD: g cm3) at 2454 profile locations. The SOC was measured on the dried fine earth fraction (
