4.7 Article

An increased understanding of soil organic carbon stocks and changes in non-temperate areas: National and global implications

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AGRICULTURE ECOSYSTEMS & ENVIRONMENT
卷 122, 期 1, 页码 125-136

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ELSEVIER
DOI: 10.1016/j.agee.2007.01.012

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The GEFSOC Modelling System; soils; soil organic carbon; soil organic carbon stock change; land use; non-temperate

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National and sub-national scale estimates of soil organic carbon (SOC) stocks and changes can provide information land degradation risk, C sequestration possibilities and the potential sustainability of proposed land management plans. Under a GEF co-financed project, 'The GEFSOC Modelling System' was used to determine SOC stocks and projected stock change rates for four case study areas; The Brazilian Amazon, The Indo-Gangetic Plains of India, Kenya and Jordan. Each case study represented soil and vegetation types, climates and land management systems that are under represented globally, in terms of an understanding of land use and land management systems and the effects these systems have on SOC stocks. The stocks and stock change rates produced were based on detailed geo-referenced datasets of soils, climate, land use and management information. These datasets are unique as they bring together national and regional scale data on the main variables determining SOC, for four contrasting non-temperate eco-regions. They are also unique, as they include information on land management practices used in subsistence agriculture in tropical and and areas. Implications of a greater understanding of SOC stocks and stock change rates in non-temperate areas are considered. Relevance to national land use plans are explored for each of the four case studies, in terms of sustainability, land degradation and greenhouse gas mitigation potential. Ways in which such information will aid the case study countries in fulfilling obligations under the United Nations Conventions on Climate Change, Biodiversity and Land Degradation are also considered. The need for more detailed land management data to improve SOC stock estimates in non-temperate areas is discussed. (C) 2007 Elsevier B.V. All rights reserved.

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