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Soil organic carbon sequestration in cotton production systems of the southeastern United States: a review 总被引:1,自引:0,他引:1
Causarano HJ Franzluebbers AJ Reeves DW Shaw JN 《Journal of environmental quality》2006,35(4):1374-1383
Past agricultural management practices have contributed to the loss of soil organic carbon (SOC) and emission of greenhouse gases (e.g., carbon dioxide and nitrous oxide). Fortunately, however, conservation-oriented agricultural management systems can be, and have been, developed to sequester SOC, improve soil quality, and increase crop productivity. Our objectives were to (i) review literature related to SOC sequestration in cotton (Gossypium hirsutum L.) production systems, (ii) recommend best management practices to sequester SOC, and (iii) outline the current political scenario and future probabilities for cotton producers to benefit from SOC sequestration. From a review of 20 studies in the region, SOC increased with no tillage compared with conventional tillage by 0.48 +/- 0.56 Mg C ha(-1) yr(-1) (H(0): no change, p < 0.001). More diverse rotations of cotton with high-residue-producing crops such as corn (Zea mays L.) and small grains would sequester greater quantities of SOC than continuous cotton. No-tillage cropping with a cover crop sequestered 0.67 +/- 0.63 Mg C ha(-1) yr(-1), while that of no-tillage cropping without a cover crop sequestered 0.34 +/- 47 Mg C ha(-1) yr(-1) (mean comparison, p = 0.04). Current government incentive programs recommend agricultural practices that would contribute to SOC sequestration. Participation in the Conservation Security Program could lead to government payments of up to Dollars 20 ha(-1). Current open-market trading of C credits would appear to yield less than Dollars 3 ha(-1), although prices would greatly increase should a government policy to limit greenhouse gas emissions be mandated. 相似文献
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YOAN PAILLET LAURENT BERGÈS JOAKIM HJÄLTÉN PÉTER ÓDOR CATHERINE AVON MARKUS BERNHARDT‐RÖMERMANN RIENK‐JAN BIJLSMA LUC DE BRUYN MARC FUHR ULF GRANDIN ROBERT KANKA LARS LUNDIN SANDRA LUQUE TIBOR MAGURA SILVIA MATESANZ ILONA MÉSZÁROS M.‐TERESA SEBASTIÀ WOLFGANG SCHMIDT TIBOR STANDOVÁR BÉLA TÓTHMÉRÉSZ ANNELI UOTILA FERNANDO VALLADARES KAI VELLAK RISTO VIRTANEN 《Conservation biology》2010,24(4):1157-1160
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Causarano HJ Doraiswamy PC McCarty GW Hatfield JL Milak S Stern AJ 《Journal of environmental quality》2008,37(4):1345-1353
Depending on management, soil organic carbon (SOC) is a potential source or sink for atmospheric CO(2). We used the EPIC model to study impacts of soil and crop management on SOC in corn (Zea mays L.) and soybean (Glycine max L. Merr.) croplands of Iowa. The National Agricultural Statistics Service crops classification maps were used to identify corn-soybean areas. Soil properties were obtained from a combination of SSURGO and STATSGO databases. Daily weather variables were obtained from first order meteorological stations in Iowa and neighboring states. Data on crop management, fertilizer application and tillage were obtained from publicly available databases maintained by the NRCS, USDA-Economic Research Service (ERS), and Conservation Technology Information Center. The EPIC model accurately simulated state averages of crop yields during 1970-2005 (R(2) = 0.87). Simulated SOC explained 75% of the variation in measured SOC. With current trends in conservation tillage adoption, total stock of SOC (0-20 cm) is predicted to reach 506 Tg by 2019, representing an increase of 28 Tg with respect to 1980. In contrast, when the whole soil profile was considered, EPIC estimated a decrease of SOC stocks with time, from 1835 Tg in 1980 to 1771 Tg in 2019. Hence, soil depth considered for calculations is an important factor that needs further investigation. Soil organic C sequestration rates (0-20 cm) were estimated at 0.50 to 0.63 Mg ha(-1) yr(-1) depending on climate and soil conditions. Overall, combining land use maps with EPIC proved valid for predicting impacts of management practices on SOC. However, more data on spatial and temporal variation in SOC are needed to improve model calibration and validation. 相似文献
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