Changes and assessment of grassland ecosystem health in alpine region, as in Eastern Kunlun Mountains

Introduction The health of grassland ecosystems is of great significance for regional ecological security. The alpine grassland is fragile and sensitive to climate change and human activities, but studies on the assessment and mechanism of the grassland ecosystem health are scarce. Methods Based on the Pressure-State-Response (PSR) model, together with the entropy method, obstruction degree model and optimal parameter-based geographical detector, we constructed a health assessment system for the grassland ecosystem in Eastern Kunlun Mountains (EKM) and systematically assessed the spatio-temporal dynamics changes of the ecosystem health in EKM from 1990 to 2020. Moreover, we dynamically identified the obstacle factor and driving factor of the grassland ecosystem health in EKM. Results The results show that: (1) Over the past 30 years (1990-2020), the health index (HI) of the grassland ecosystem in EKM exhibited a fluctuating upward trend with average value of 0.2231. The grassland presented a healthier pattern in the southeast than in the northwest of EKM, generally at a medium-to-low health level (nearly 70%). (2) The health grades of the grassland ecosystem in EKM underwent significant changes. The percentage of the low health area dropped to 34.42%, and the combined percentage of the health and high health area fluctuated upward to 23.50%. The net improvement rate of the whole EKM region was +7.35%, but there was a slight degradation in the internal part of the grassland with a net improvement rate of -1.84%. (3) During 1990-2000, the structural pressure caused primarily by grassland area reduction and water resource constraints was the major obstacle, then in 2005-2015, it shifted to functional and climate stress featured with vegetation degradation (NDVI decline), and climatic drought. In 2020, a compound pressure pattern was formed with the simultaneous appearance of high obstruction degrees of multiple factors, including NDVI, standardized precipitation evapotranspiration index (SPEI) and precipitation. (4) The factor detection results show that the land use area ratio (Q = 0.247), grassland area ratio (Q = 0.238), sediment flux (Q = 0.181) and grazing intensity (Q = 0.123) are the key factors dominating the spatial differentiation of grassland health. All the factor pairs exhibit either bivariate enhancement or nonlinear enhancement. Discussion Overall, this study has integrated the obstacle diagnosis model with the geographical detector and revealed the dynamic evolution and spatial differentiation mechanisms of alpine grassland ecosystem health from the dual perspectives of constraint and driving. This is a valuable basis for protecting grassland ecological system in alpine regions and performing corresponding management.