From Past to Future: Overall Patterns, Nonlinear Relationships, Spatial Heterogeneity and Drivers of Ecosystem Service Trade‐Offs and Synergies in the Yangtze River Economic Belt

ABSTRACT Land‐use change and climate change are reshaping watershed ecological functions and may intensify the risk of localized ecological degradation. However, existing studies have primarily focused on the spatiotemporal patterns of ecosystem services (ESs) during historical periods, while the nonlinear changes, spatial heterogeneity, and driving mechanisms of ESs trade‐offs and synergies under future land‐use scenarios remain insufficiently understood. Taking the Yangtze River Economic Belt (YREB) as the study area, this study developed an integrated framework combining future land‐use scenario simulation, ESs assessment, trade‐off/synergy diagnosis, nonlinear boundary identification, and interpretable driver analysis. The framework was used to systematically reveal the spatiotemporal evolution, trade‐offs and synergies, nonlinear constraints, and spatial differentiation of carbon storage (CS), habitat quality (HQ), sediment delivery ratio (SDR), and water yield (WY) from 2000 to 2050, and to identify the key drivers, relative contributions, and stage‐dependent effects associated with different ESs. The results showed that: (1) From 2000 to 2020, CS and HQ remained generally stable. Mean CS was 110.41 t ha −1 , while mean HQ was 0.74 and decreased by only 0.01. Mean SDR was 6428.03 t ha −1 and increased by 2.57 t ha −1 , whereas mean WY was 844.63 mm and decreased by 1.27 mm. Under future scenarios, CS, HQ, and WY generally exhibited declining trends, while SDR showed pronounced scenario dependence and stage‐specific fluctuations. CS decreased by 0.29, 0.40, and 0.52 t ha −1 under SSP126, SSP245, and SSP585, respectively, indicating a greater risk of ecological function degradation under high‐intensity development scenarios. (2) Synergies generally dominated the relationships among the four ESs, with the strongest synergy occurring between CS and HQ. SDR showed moderate synergies with CS and HQ, with correlation coefficients ranging from 0.458 to 0.572 and from 0.451 to 0.550, respectively. By contrast, WY exhibited relatively weak synergies with the other services, and the WY–SDR correlation coefficient ranged from only 0.046 to 0.146. Nonlinear boundary analysis further demonstrated that ESs relationships did not follow stable linear responses but instead exhibited threshold shifts, marginal changes, boundary constraints, and scenario‐dependent differentiation. Spatially, synergistic relationships were concentrated mainly in the middle and lower reaches of the Yangtze River, whereas trade‐offs were more prevalent in upstream areas such as Sichuan and Yunnan. (3) ESs patterns were jointly shaped by natural background constraints and human activity regulation, with Slope, PRE, DEM, and NDVI identified as the principal natural drivers. Slope contributed 23.5% to CS, PRE contributed 25.3% to WY, and DEM and Slope contributed 18.9% and 17.2%, respectively, to SDR. The effects of anthropogenic factors, including POP, GDP, and HFP, on HQ and WY displayed pronounced service‐specific and stage‐dependent characteristics. By integrating future land‐use scenarios, nonlinear ecosystem service relationships, and interpretable driving mechanisms within a unified analytical framework, this study provides a scientific basis for ecological function conservation, region‐specific ecological restoration, and sustainable land management in the YREB.