High-resolution assessment of the carrying capacity and utilization intensity in mountain rangelands with remote sensing and field data.

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.

Reanalysis datasets outperform other gridded climate products in vegetation change analysis in peripheral conservation areas of Central Asia.

Global environmental research requires long-term climate data. Yet, meteorological infrastructure is missing in the vast majority of the world's protected areas. Therefore, gridded products are frequently used as the only available climate data source in peripheral regions.

Evaluation needs and temporal performance differences of gridded precipitation products in peripheral mountain regions.

Gridded datasets are of paramount importance to globally derive precipitation quantities for a multitude of scientific and practical applications. However, as most studies do not consider the impacts of temporal and spatial variations of included measurements in the utilized datasets, we conducted a quantitative assessment of the ability of several state of the art gridded precipitation products (CRU, GPCC Full Data Product, GPCC Monitoring Product, ERA-interim, ERA5, MERRA-2, MERRA-2 bias corrected, PERSIANN-CDR) to reproduce monthly precipitation values at climate stations in the Pamir mountains during two 15 year periods (1980-1994, 1998-2012) that are characterized by considerable differences in incorporated observation data. Results regarding the GPCC products illustrated a substantial and significant performance decrease with up to four times higher errors during periods with low observation inputs (1998-2012 with 2 stations on average per 124,000 km) compared to periods with high quantities of regionally incorporated station data (1980-1994 with 14 stations on average per 124,000 km).