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. 2015 Aug 11;112(32):9956-60.
doi: 10.1073/pnas.1504628112. Epub 2015 Jul 27.

Conversion of lowland tropical forests to tree cash crop plantations loses up to one-half of stored soil organic carbon

Oliver van Straaten  1 , Marife D Corre  1 , Katrin Wolf  1 , Martin Tchienkoua  2 , Eloy Cuellar  3 , Robin B Matthews  4 , Edzo Veldkamp  5
Affiliations

Conversion of lowland tropical forests to tree cash crop plantations loses up to one-half of stored soil organic carbon

Oliver van Straaten et al. Proc Natl Acad Sci U S A. .

Abstract

Tropical deforestation for the establishment of tree cash crop plantations causes significant alterations to soil organic carbon (SOC) dynamics. Despite this recognition, the current Intergovernmental Panel on Climate Change (IPCC) tier 1 method has a SOC change factor of 1 (no SOC loss) for conversion of forests to perennial tree crops, because of scarcity of SOC data. In this pantropic study, conducted in active deforestation regions of Indonesia, Cameroon, and Peru, we quantified the impact of forest conversion to oil palm (Elaeis guineensis), rubber (Hevea brasiliensis), and cacao (Theobroma cacao) agroforestry plantations on SOC stocks within 3-m depth in deeply weathered mineral soils. We also investigated the underlying biophysical controls regulating SOC stock changes. Using a space-for-time substitution approach, we compared SOC stocks from paired forests (n = 32) and adjacent plantations (n = 54). Our study showed that deforestation for tree plantations decreased SOC stocks by up to 50%. The key variable that predicted SOC changes across plantations was the amount of SOC present in the forest before conversion--the higher the initial SOC, the higher the loss. Decreases in SOC stocks were most pronounced in the topsoil, although older plantations showed considerable SOC losses below 1-m depth. Our results suggest that (i) the IPCC tier 1 method should be revised from its current SOC change factor of 1 to 0.6 ± 0.1 for oil palm and cacao agroforestry plantations and 0.8 ± 0.3 for rubber plantations in the humid tropics; and (ii) land use management policies should protect natural forests on carbon-rich mineral soils to minimize SOC losses.

Keywords: cacao; land-use change; oil palm; rubber; soil carbon.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. S1.
Fig. S1.
Sampling locations (formula image) in Ucayali Region, Peru, southern Cameroon, and Jambi Province, Sumatra, Indonesia.
Fig. 1.
Fig. 1.
Relative change [(forest – plantation)/forest × 100] in soil organic carbon (SOC) stock in the 0- to 3-m depth of the three plantation types across three regions (◆), Indonesia (formula image), Cameroon (formula image), and Peru (▽). Error bars indicate the 95% confidence intervals based on Student’s T distribution. Statistical significance is based on LME models at P ≤ 0.10 (†, marginally significant), P ≤ 0.05 (*), and P ≤ 0.01 (**). Cumulative decreases in SOC stocks (considering only the depths with significant changes) for oil palm were 14 ± 3 Mg C⋅ha−1 (n = 11) in Indonesia, 22 ± 1 Mg C⋅ha−1 (n = 5) in Cameroon, and 10 ± 2 Mg C⋅ha−1 (n = 5) in Peru. Cumulative decreases in SOC stocks for rubber were 7 ± 4 Mg C⋅ha−1 (n = 16) in Indonesia and 41 ± 3 Mg C⋅ha−1 (n = 6) in Cameroon. SOC loss for cacao agroforest was 35 ± 2 Mg C⋅ha−1 (n = 11) in Cameroon. The magnitude of SOC losses for the depths with significant changes are presented in the gray-shaded area.
Fig. S2.
Fig. S2.
(A) Soil organic carbon (SOC) concentration and (B) SOC stock in the 0- to 3-m soil profile of the reference forest sites across the three regions (◆), Indonesia (formula image), Cameroon (formula image), and Peru (▽). Error bars indicate 95% confidence intervals based on Student’s T distribution. The gray-shaded area on the y axis in B indicates the thickness of soil layer for which SOC stocks was determined.
Fig. S3.
Fig. S3.
Percentage change [(forest – plantation)/forest × 100] in soil C/N ratios in the 0- to 3-m soil profile of the three plantation types across the three regions (◆), Indonesia (formula image), Cameroon (formula image), and Peru (▽). Error bars indicate 95% confidence intervals based on Student’s T distribution.
Fig. S4.
Fig. S4.
Soil bulk density in the 0- to 3-m soil profile of the reference forest sites (◆), oil palm (formula image), rubber (formula image), and cacao (▽) plantations in Indonesia, Cameroon, and Peru. Error bars indicate 95% confidence intervals based on Student’s T distribution.
Fig. S5.
Fig. S5.
Percentage change [(forest – plantation)/forest × 100] in soil pH in the 0- to 10-cm and 50- to 100-cm depths of the three plantation types across the three regions (◆), Indonesia (formula image), Cameroon (formula image), and Peru (▽). Error bars indicate 95% confidence intervals based on Student’s T distribution.
Fig. 2.
Fig. 2.
(A) The higher the initial soil organic carbon (SOC) stock, the larger the SOC losses, evident from the slope (slope = 0.21, which is significantly different from the 1; P ≤ 0.01) of the regression model (R2 = 0.18; P ≤ 0.01; n = 54) of SOC stocks within 0- to 10-cm depth between paired reference forests and oil palm (formula image), rubber (◇), and cacao agroforestry (●) plantations. The size of the data points is proportional to the soil clay percentage measured in the plantation plots. (B) The residuals of the regression model explained by clay contents of the soils (R2 = 0.14; P = 0.01; n = 54).
Fig. S6.
Fig. S6.
Percentage of SOC remaining in the top 10-cm depth [(plantation/forest) × 100], following conversion of forests to oil palm, rubber, cacao plantations, and all plantations combined. The dashed lines show the best-fitted monoexponential decay functions (39), using R, version 2.14.2 (40), through the data points. The r is the Pearson correlation coefficients between observed and fitted values; a is the equilibrium ratio (%) (±SE), and k is the decay rate per year (±SE). Pearson’s r and model parameter estimates are significant at P ≤ 0.05 (*), P ≤ 0.01 (**), and marginally significant at P ≤ 0.09 (†).
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References

    1. Food and Agriculture Organization of the United Nations 2013 Food and Agriculture Organization of the United Nations Statistical Database (28/09/2009). Available at faostat.fao.org. Accessed March 3, 2015.
    1. Laumonier Y, et al. Eco-floristic sectors and deforestation threats in Sumatra: Identifying new conservation area network priorities for ecosystem-based land use planning. Biodivers Conserv. 2010;19(4):1153–1174.
    1. Warren-Thomas E, Dolman PM, Edwards DP. Increasing demand for natural rubber necessitates a robust sustainability initiative to mitigate impacts on tropical biodiversity. Conserv Lett. 2015 Available at doi.wiley.com/10.1111/conl.12170. Accessed June 1, 2015. - DOI
    1. Hergoualc’h K, Verchot LV. Stocks and fluxes of carbon associated with land use change in Southeast Asian tropical peatlands: A review. Global Biogeochem Cycles. 2011;25(2):1–13.
    1. Murdiyarso D, Hergoualc’h K, Verchot LV. Opportunities for reducing greenhouse gas emissions in tropical peatlands. Proc Natl Acad Sci USA. 2010;107(46):19655–19660. - PMC - PubMed

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