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. 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.

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. However, associated evaluations are commonly biased towards well observed areas and consequently, station-based datasets. As evaluations on vegetation monitoring abilities are lacking for regions with poor data availability, we analyzed the potential of several state-of-the-art climate datasets (CHIRPS, CRU, ERA5-Land, GPCC-Monitoring-Product, IMERG-GPM, MERRA-2, MODIS-MOD10A1) for assessing NDVI anomalies (MODIS-MOD13Q1) in two particularly suitable remote conservation areas. We calculated anomalies of 156 climate variables and seasonal periods during 2001-2018, correlated these with vegetation anomalies while taking the multiple comparison problem into consideration, and computed their spatial performance to derive suitable parameters. Our results showed that four datasets (MERRA-2, ERA5-Land, MOD10A1, CRU) were suitable for vegetation analysis in both regions, by showing significant correlations controlled at a false discovery rate < 5% and in more than half of the analyzed areas. Cross-validated variable selection and importance assessment based on the Boruta algorithm indicated high importance of the reanalysis datasets ERA5-Land and MERRA-2 in both areas but higher differences and variability between the regions with all other products. CHIRPS, GPCC and the bias-corrected version of MERRA-2 were unsuitable and not important in both regions. We provide evidence that reanalysis datasets are most suitable for spatiotemporally consistent environmental analysis whereas gauge- or satellite-based products and their combinations are highly variable and may not be applicable in peripheral areas.

Preserving a Comprehensive Vegetation Knowledge Base--An Evaluation of Four Historical Soviet Vegetation Maps of the Western Pamirs (Tajikistan).

We edited, redrew, and evaluated four unpublished historical vegetation maps of the Western Pamirs (Tajikistan) by the Soviet geobotanist Okmir E. Agakhanjanz. These maps cover an area of 5,188 km2 and date from 1958 to 1960. The purpose of this article is to make the historic vegetation data available to the scientific community and thus preserve a hitherto non available and up to now neglected or forgotten data source with great potential for studies on vegetation and ecosystem response to global change. The original hand-drawn maps were scanned, georeferenced, and digitized and the corresponding land cover class was assigned to each polygon. The partly differing legends were harmonized and plant names updated. Furthermore, a digital elevation model and generalized additive models were used to calculate response curves of the land cover classes and to explore vegetation-topography relationships quantitatively. In total, 2,216 polygons belonging to 13 major land cover classes were included that are characterized by 252 different plant species. As such, the presented maps provide excellent comparison data for studies on vegetation and ecosystem change in an area that is deemed to be an important water tower in Central Asia.

Realities and myths of the Teresken Syndrome--an evaluation of the exploitation of dwarf shrub resources in the Eastern Pamirs of Tajikistan.

In the Eastern Pamirs extensive livestock herding is the predominant land use option and dwarf shrubs - teresken (Krascheninnikovia ceratoides) and to a lesser extent wormwood (Artemisia spp.) - are an important source of thermal energy and are crucial forage plants, particularly in winter. For the post-Soviet period, many papers and reports suggest rapidly increasing exploitation rates with sometimes alarming figures for degradation. Conventional knowledge about the Pamirs pinpoints the frightening and irreversible extraction of teresken as a dwindling resource causing land degradation - termed the 'Teresken Syndrome'. However, these publications are based on limited empirical evidence. This paper discusses the socio-economic role of dwarf shrubs as fuel and forage - today and in the past - and provides an overview of the extent of dwarf shrub distribution and degraded areas. Although our observations confirm extensive dwarf shrub exploitation, general assumptions of severe desertification as a result of dwarf shrub extraction do not yield reliable scenarios. The effects of harvesting on the vegetation cover vary widely depending on extraction practices and yields of different dwarf shrub-dominated formations. Furthermore, considerable and increasing shares of energy needs are satisfied by animal manure and imported coal. On the other hand, for low-income households harvesting dwarf shrubs is an important and reliable option to ensure both their own household energy supply and an income source. We argue that the term 'Teresken Syndrome', which was introduced after the emergency replacement of Soviet coal supplies by dwarf shrubs in the 1990s, is not appropriate anymore to describe the current use of natural resources in the Eastern Pamirs. However, under the current economic circumstances the nexus remains that the Pamir people are caught in the dilemma of using dwarf shrubs as energy and as forage resource. However, the observed negotiation practices concerning competitive use between dwarf shrub extractors and herders could be developed into community-based management schemes of this common pool resource.