Natural driving mechanism and trade-off and synergy analysis of the spatiotemporal dynamics of multiple typical ecosystem services in Northeast Qinghai-Tibet Plateau

Abstract

Research on the natural driving mechanism and trade-offs and synergies of ecosystem services (ES) is a prerequisite for the implementation of scientific integrated ecosystem management, especially in ecologically fragile alpine ecological barrier regions. This study mainly studies the spatiotemporal dynamics and natural driving mechanism of water yield (WY), soil conservation (SC), windbreak and sand fixation (WS) and carbon sequestration (CS) in the northeast of the Qinghai-Tibet Plateau, identifies the trade-off and synergy features between ES in horizontal space. The results showed that the distribution of four ES presents different geographical spatial patterns, and an obvious increasing trend during the study period. Seven natural factors (precipitation, temperature, windspeed, etc.) can explain 38.1～47.0% of the spatiotemporal dynamics of ES in 2000, 2010 and 2020. Vegetation characteristics and elevation are the main explanatory variables controlling ES spatial pattern with the total contribution rate of 29.3% in 2000 and 26.5% in 2010. Temperature and elevation are the two most critical natural factors affecting ES, with the contribution ratio of 29.9% in 2020. The contribution of single nature factor on each ES pattern is different in the same year, and show interannual changes in different year. The contributions of wind speed, precipitation and slope to SC are uncertain, and the effect of temperature on CS is nonlinear. The trade-off and synergy cluster areas are mostly agglomerated and embedded in the compatibility region, with the characteristics of regional differentiation. The trade-offs and synergies between ES generally present the characteristics of interannual fluctuation, except WY-SC and WS-CS, which show a weakening trend in 2000, 2010 and 2020. Based on the above findings, we further discussed the complex trade-off and synergy relationships of ES, and the results provide scientific support for sustainable development by creating win–win scenarios under future climate change trends.