| 英文摘要： |
Ecosystem services (ESs) represent a complex network of multiple natural and socioeconomic driving factors. These interactions have become more common in an increasingly metacoupled world and have led to various ecosystem service bundles (ESBs). This study selected and assessed 8 representative ES types in Ningxia, including agricultural product provision (AP), water provision (WP), hay production (HP), livestock product provision (LP), wind erosion prevention (WEP), water conservation (WCON), soil retention (SR) and carbon sequestration (CS). Then, we used Spearman rank correlation coefficients to reveal the tradeoff or synergistic relationships between paired ESs at the grid, county and reginal scale and explored their linkages with socioecological driving factors. Based on the ES evaluation and ES relationship analysis, we mapped the spatiotemporal dynamic changes in ESBs in Ningxia in 2000, 2005, 2010, and 2015. The results reflected the significant differences in natural and socioeconomic conditions from south to north in Ningxia. There were both positive and negative areas for a single relationship. On the whole, the supply of agricultural products were mainly negatively correlated at all the 3 scales. Most ES pairs were mainly positively correlated at all the scales, highlighting the coupled relationships among these ESs and certain achievements in ecological construction in Ningxia. There was strong consistency and correspondence between the ES distribution patterns and their pairwise relationships. The mech-anism patterns tended to be spatially inversely distributed for the tradeoff-relationship ESs, while be more similarly distributed for the synergy-relationship ESs. Based on cluster analysis, three ESBs with similar ESs and driving factors were identified, including the Northern Agricultural Bundle (NA), Central Arid Sandstorm Prevention Bundle (CASP), and Southern Mountainous High Provision-Regulation Syn-ergy Bundle (SMHPS). This study emphasized the spatiotemporal dynamic changes in the ESBs and tried to map the ES relationships at different scales to more precisely reveal the superposition areas of tradeoffs and synergies and their linkage with driving factors. Mapping the spatiotemporal dynamic changes in ESBs can enhance the understanding of the complex ES relationships and contribute to establishing a foundation for targeted ecosystem management in different areas. (c) 2021 Elsevier Ltd. All rights reserved. |
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