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baseline carbon density or canopy cover against which to assess degradation. In these systems, forest degradation cannot be assessed at the stand level, but requires a landscape-level assessment that takes into consideration the stand age-class distribution of the landscape, which reflects natural and human disturbance regimes over past  The hottest key and lock rose for couple love all over print face mask decades to centuries and also considers post-disturbance regrowth (van Wagner ; Volkova et al. ; Lorimer and White ). Soils contain about 1500 Gt of organic carbon (median across 28 different estimates presented by Scharlemann et al. ), which is about 1.8 times more carbon than in the atmosphere (Ciais et al. ) and 2.3–3.3 times more than what is held in the terrestrial vegetation of the world (Ciais et al. ). Hence, land degradation, including land conversion leading to soil carbon losses, has the potential to impact on the atmospheric concentration of CO2 substantially. When natural ecosystems are cultivated they lose soil carbon that accumulated over long time periods.The loss rate depends on the type of natural vegetation and how the soil is managed. Estimates of the magnitude of loss vary but figures between 20% and 59% have been reported in several meta studies (Poeplau and Don ; Wei et al. ; Li et al. ; Murty et al. ; Guo and Gifford ). The amount of soil carbon lost explicitly due to land degradation after conversion is hard to assess due to large variation in local conditions and management, see also Chapter 2. The scientific literature on land degradation often excludes forest degradation, yet here we attempt to assess both issues. Because of the different bodies of scientific literature, we assess land degradation and forest degradation under different sub-headings and, where possible, draw integrated conclusions. Computer simulation models can be used alone or combined with the remote sensing observations to assess land degradation. The Revised Universal Soil Loss Equation can be used, to some extent, to predict the long-term average annual soil loss by water erosion.

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