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Dry rangelands provide resources for half of the world's livestock, but degradation due to overgrazing is a major threat to system sustainability. Existing carrying capacity assessments are limited by low spatiotemporal resolution and high generalization, which hampers applied ecological management decisions. This paper provides an example for deriving the carrying capacity and utilization levels for cold drylands at a new level of detail by including major parts of the transhumance system. We combined field data on vegetation biomass and communities, forage quality, productivity, livestock species and quantities, grazing areas and their spatiotemporal variations with Sentinel-2 and MODIS snow cover satellite imagery to develop maps of forage requirements and availability. These products were used to calculate carrying capacity and grazing potential in the Pamir-Hindukush Mountains. Results showed high spatial variability of utilization rates between 5% and 77%. About 30% of the area showed unsustainable grazing above the carrying capacity. Utilization rates displayed strong spatial differences with unsustainable grazing in winter pastures and at lower elevations, and low rates at higher altitudes. The forage requirements of wild herbivores (ungulates and marmots) were estimated to be negligible compared to livestock, with one tenth of the biomass consumption and no increase in unsustainably grazed pastures due to the wider distribution of animals. The assessment was sensitive to model parameterization of forage requirements and demand, whereby conservative scenarios, i.e. lower fodder availability or higher fodder requirements of livestock due to climate and altitude effects, increased the area with unsustainable grazing practices to 50%. The presented approach enables an in-depth evaluation of the carrying capacity and corresponding management actions. It includes new variables relevant for transhumance systems, such as the combination of forage quantity and quality or accessibility restrictions due to snow, and shows utilization patterns at high spatial resolutions. Regional maps allow the identification of unsustainable utilization areas, such as winter pastures in this study.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10656245 | PMC |
http://dx.doi.org/10.1016/j.heliyon.2023.e21583 | DOI Listing |
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