Social Network Analysis and Mining, Год журнала: 2024, Номер 14(1)
Опубликована: Ноя. 9, 2024
Язык: Английский
Social Network Analysis and Mining, Год журнала: 2024, Номер 14(1)
Опубликована: Ноя. 9, 2024
Язык: Английский
Forests, Год журнала: 2025, Номер 16(4), С. 604 - 604
Опубликована: Март 30, 2025
Ecosystem services play a crucial role in maintaining ecological balance, providing essential functions. This study examines the trade-offs and synergies among five key ecosystem forests across different regions of Hunan Province, China. Various machine learning models are compared to predict service value (ESV) levels, with most effective predictive model identified. The SHAP (SHapley Additive exPlanations) analysis is employed identify environmental management factors influencing services. Our findings reveal significant regional variations services, eastern western showing superior soil conservation forest nutrient retention. In contrast, southern regions, particularly karst areas, display fewer between likely due effectiveness policies. further reveals that such as precipitation during warmest quarter, central government compensation funds, timber harvesting volume strongly influence ESV. provides valuable insights for improving policy-making rapidly developing underscoring importance protection strategies sustainable development.
Язык: Английский
Процитировано
0Modeling Earth Systems and Environment, Год журнала: 2025, Номер 11(3)
Опубликована: Апрель 11, 2025
Язык: Английский
Процитировано
0Theoretical and Applied Climatology, Год журнала: 2024, Номер unknown
Опубликована: Окт. 1, 2024
Язык: Английский
Процитировано
2Social Network Analysis and Mining, Год журнала: 2024, Номер 14(1)
Опубликована: Ноя. 9, 2024
Язык: Английский
Процитировано
0