CIFOR–ICRAF publishes over 750 publications every year on agroforestry, forests and climate change, landscape restoration, rights, forest policy and much more – in multiple languages.

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Divergent trends in grassland degradation and desertification under land use and climate change in Central Asia from 2000 to 2020

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Grassland degradation (within-state change) and desertification (state conversion from grasslands to deserts) are different states in the complex dynamic process of grassland deterioration. However, the dynamics and associated drivers of the two states have been rarely examined separately, which is critical for early warning and conservation policy making. Here, the grassland degradation and desertification in Central Asia (CA) were studied due to their evident vulnerability to climate extremes and human activities. We performed a two-step approach to identify the critical state zones first (i.e., grasslands, deserts, and the desertification zones) and then assess the vegetation dynamics within each zone. Finally, we quantified the roles of CO2 fertilization effect, climate change, climate variability, land use (LU), and anthropogenic climate change (ACC) on the vegetation dynamics in different state zones. The results showed that the areas of grasslands and sparse vegetation regions (including deserts and desertification zones) were stable from 2000 to 2020, but the trends of vegetation greenness were divergent with a reduction in grasslands and an increase in sparse vegetation regions. Furthermore, climate change and climate variability were the main driving force affecting grassland degradation in CA. Yet the vegetation greening in the desertification and desert zones was mainly driven by the rising CO2 and LU. Moreover, ACC degraded 20.63% of grasslands and sparsely vegetated lands in CA on the baseline of 2000. The results highlighted the risks of grassland degradation in CA. This study proposed a methodology to examine grassland degradation and desertification in detail and quantify the associated driving factors (especially ACC) at the pixel scale, which provided some insights on developing region-precise strategies for grassland conservation in CA and other drylands.

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