Refined revealing the chain path of multiple ecosystem services under diverse environmental factor gradients.

Sci Total Environ

Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China. Electronic address:

Published: March 2023

A fragile karst ecosystem presents ecosystem services affected by the environment and interactions between ecosystem services. However, the ecosystem in the karst area is characterized by low environmental capacity and low resistance to force disturbance. Current research mainly focuses on the trade-off/synergy of ecosystem services in the karst area yet it lacks inductive analysis of the multiple chain path among ecosystem services. This paper quantitatively identified dominant factors influencing spatial differentiation of surface runoff, soil moisture, sediment yield, and net primary productivity (NPP) and determined the chain path. The chain paths of surface runoff-soil moisture-NPP and NPP-surface runoff-sediment yield were analyzed. The results showed that land use and soil type were the dominant factors, and chain effects of ecosystem services were diverse under the various dominant factor gradients. The mediation effects of paddy soil (97.21 %) and mountain meadow soil (55.56 %) were high, and surface runoff had a greater impact on NPP by affecting soil moisture. Among the diverse land use types, the mediation effect of surface runoff on NPP affecting sediment yield varied greatly (from 5 to 100 %). In addition, its variation trend was consistent with that of the soil moisture as the mediation variable. The mediation effect of surface runoff on construction land was the highest (99.43 %). This study provides the scientific basis for selecting more effective water and soil conservation measures by analyzing the chain relationships of multiple ecosystem services under different environmental factor gradients.

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Source
http://dx.doi.org/10.1016/j.scitotenv.2022.161187DOI Listing

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