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| Analysis of interactions and spatiotemporal evolution of farmland ecosystem services in the Beijing-Tianjin-Hebei region supported by machine learning |
| Received:May 18, 2025 |
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| KeyWord:farmland;ecosystem services;machine learning algorithms;trade-offs/synergies;ecosystem service bundles |
| Author Name | Affiliation | E-mail | | DU Peiyu | College of Resources and Environment, Shandong Agricultural University, Tai'an 271018, China
Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China | | | TANG Xiumei | Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China | | | HUAI Heju | Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China | huaihj@nercita.org.cn | | GAO Yunbing | Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China | | | GE Rongfeng | China International Engineering Consulting Corporation, Beijing 100048, China | | | LIU Wen | College of Resources and Environment, Shandong Agricultural University, Tai'an 271018, China
Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China | |
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| Abstract: |
| The purpose of this study was to reveal the interaction between farmland ecosystem services and their spatiotemporal evolution characteristics, so as to support the improvement of regional cultivated land resource management and ecosystem sustainability. In this study, the farmland ecosystems in the Beijing-Tianjin-Hebei region were studied in 2000, 2015 and 2023, and four farmland ecosystem service functions, namely, food supply, carbon storage, soil conservation, and water production services, were assessed based on the InVEST model and the grain yield estimation model, and the trade-offs/synergies were quantified using Spearman's correlation and geographically-weighted regression models, and the bundles of farmland ecosystem services were identified with the support of a machine-learning algorithm support identified bundles of farmland ecosystem services. The results showed that the significant spatial and temporal variations in farmland ecosystem services occurred in the Beijing-Tianjin-Hebei region from 2000 to 2023, in which water-producing services and food production capacity were gradually enhanced, especially in the southern and coastal regions, and soil retention and carbon storage showed fluctuating changes. Water production services synergized with soil conservation and food supply services increased, while carbon storage and other services changed repeatedly between synergies and trade-offs. The farmland ecosystem service bundles showed significant evolution, with the expansion of food-dominant and water-producing-food-complex bundles, and the shrinkage of soilfood-complex and carbon storage-dominant bundles. This study developed an evaluation framework that integrates the identification of interactions among farmland ecosystem services with spatial clustering analysis. The results demonstrate that the framework can effectively capture the trade-offs and synergies among services as well as their spatiotemporal evolution patterns. |
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