Abstract

Understanding synergies and trade-offs of ecosystem services (ESs), finding influencing factors related to these ESs, and determining how these factors regulate spatiotemporal patterns are vital to the sustainability of ecosystem management. However, the spatialization of the correlation between the relationships among ESs and the influencing factors has remained a difficult analysis for the Qinghai-Tibet Plateau (QTP). Consequently, three ESs are quantified using different models, and synergies and trade-offs among the ESs are analyzed. The precipitation changes, minimum temperature changes, gross domestic product changes, population changes, normalized difference vegetation index (NDVI) changes, and the digital model (DEM) were selected as influencing factors. The influence of these influencing factors on the relationship among the ESs was then measured using the methods of logistic regression (LR) and the geographically weighted logistic regression (GWLR). The authors showed that (1) the spatially concordant high supplies of water yield (WY) and carbon storage (CS) were distributed in the southeastern forest areas and the eastern grassland areas, whereas high meat supply (MS) was primarily distributed in the eastern and the middle of the grassland areas. (2) The relationships between the WY and MS and between the CS and MS were primarily trade-offs, and their area ratios were 40% and 41%, respectively. However, the relationship between the WY and CS was primarily synergistic, and the area ratio was 54%. (3) Precipitation was more highly related to the relationships among the ESs than the other influencing factors among the six independent variables. Compared to the LR, the GWLR model provides an improved calculation to explain the correlation between the relationships among the ESs and these influencing factors. Overall, it was found that these influencing factors on the impacts of the relationship among the ESs were different, and they lacked spatial concordance. These results highlight the importance of managing nearly all areas by specifically controlling local factors.

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