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Estimating the value of ecosystem services: A machine learning approach for Missouri wetlands

delete2026-04-02
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OA
AI
L
Luke Maddock *
F
Frank Nelson
L
Levi Altringer
S
Sophie C. McKee
DOI:10.1016/j.ecoser.2026.101849delete
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Abstract

Abstract

En 中文
• Machine learning with global data yields robust ecosystem service value estimates. • Urban proximity, precipitation, and soil content majorly shape wetland service values. • Global transferability allows multiple ecosystem value estimates with minimal local data. • SHAP analysis clarifies site-level drivers, aiding evidence-based management.
Keywords:
C53
Q57
Ecosystem valuation
Ecosystem services
Gradient boosting
Benefit transfer
Wetlands
Machine learning
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Ecosystem Services cover
Ecosystem Services
IF:
6.6
Papers:
1.8K
Citations:
1.1W

Organization

U
usda animal and plant health inspection service
Scholars:
1
Papers: 1
Citations: 0
M
missouri department of conservation
Scholars:
1
Papers: 1
Citations: 0
C
colorado state university
Scholars:
595
Papers: 285
Citations: 0
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