Quantifying Degradation Classifications on Alpine Grassland in the Lhasa River Basin, Qinghai-Tibetan Plateau

The Qinghai-Tibetan Plateau (QTP) has the world’s largest alpine grassland ecosystem. The QTP ecosystem is extremely fragile and suffers continuous degradation. An accurate determination of the status of alpine grassland is the first crucial step in monitoring its degradation. A novel method combining field survey with remote sensing information based on ecological indicators is proposed. The degradation classification of alpine grassland was identified by multivariate hierarchical analysis based on 270 field plots. The spatial pattern of alpine grassland degradation was mapped by determining remote sensing variables that corresponded to field indicators of the degradation classification system. The results showed that clustering analysis divided the degradation classification of alpine grassland into five classes: Non-Degraded (ND), Slightly Degraded (SLD), Moderately Degraded (MD), Severely Degraded (SD), and Extremely Degraded (ED). The most significant factors for alpine grassland degradation included the dominance of Cyperaceae plants, soil total nitrogen content, soil organic carbon content, soil total carbon content, soil bulk density, soil pH, dominance of miscellaneous plants, and elevation among all 17 variables. The assessment and mapping of alpine grassland degradation provide an important basis for alpine grassland protection and management, particularly at a large scale

Impacts of Human Activity Intensity on Ecosystem Services for Conservation in the Lhasa River Basin

Quantifying the impacts of human activities on ecosystems and ecosystem services is crucial for the sustainable development of ecosystems at the local scale. We used the InVEST model to quantify ecosystem services and the human footprint index to calculate the human activity intensity (HAI). We evaluated the spatial correlations and fitting relationships between HAI and the key ecosystem services for the Lhasa River basin. The results showed that the spatial patterns of the 4 ecosystem services exhibited obvious heterogeneity. Excluding soil retention, the other ecosystem services exhibited overall downward trends from 2000 to 2018. The overall trend in HAI was ascending, with an average slope of 0.11. The spatial correlations between HAI and the 4 ecosystem services exhibited statistically significant differences (P < 0.01). The curve fitting results showed that water conservation and soil retention consistently decreased as HAI increased. Carbon sequestration and habitat quality increased and then decreased as HAI increased. Our findings help to understand the spatial interactions between HAI and multiple ecosystem services, thereby contributing to the development of a general scientific framework for ecological protection and integrated management