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• W4285081946 abstract "Accurate and reliable estimation of terrestrial ecosystem degradation is critical to meeting the challenge of reversing land degradation. Remote sensing data (especially land productivity dynamics) is commonly used to estimate land degradation, and this study uses the TRENDS.EARTH toolbox for the period covering 2000–2018, demonstrating the benefit of tracking the degradation process (SDG 15.3.1) at a biophysical unit. Contributing to the country’s SDG 15.3.1 monitoring, anthropogenic degradation was estimated based on RESTREND land productivity, biome-specific land cover trends, and soil organic carbon (SOC) stocks. Underlying degradation was evaluated by reclassifying a 28-year national land cover change dataset to match the UNCCD land cover legend. Analysis results indicate that land productivity changes (especially in stable grasslands, afforested, and cropland areas) mainly influenced the degradation status of the biome (19.9% degraded & 25.6% improvement). Global datasets also suggest that land cover and SOC had a minimal contribution (<2%) to anthropogenic degradation dynamics in the biome between 2000 and 2018. The GIS analysis showed that long-term, the major contributors to the biome’s underlying 9% anthropogenic degradation were woody proliferation into the Grassland Biome, urban expansion, and wetland drainage. Contextualising the UNCCD matrix helped interpret the SDG 15.3.1 indicator results, showing significant contestations that need careful consideration to avoid misleading policy guidance. The study also outlines the accompanying implications for degradation assessments." @default.
• W4285081946 created "2022-07-14" @default.
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• W4285081946 date "2022-10-01" @default.
• W4285081946 modified "2023-09-30" @default.
• W4285081946 title "Towards SDG 15.3: The biome context as the appropriate degradation monitoring dimension" @default.
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• W4285081946 doi "https://doi.org/10.1016/j.envsci.2022.07.008" @default.
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