Modeling tools for ecosystem service tradeoffs and synergies in agricultural landscapes

生态系统服务 环境资源管理 农业 生态系统 服务(商务) 环境科学 环境规划 业务 生态系统模型 农业生产力 生态系统方法 水资源管理 生态系统健康 遥感 地理 环境保护
作者
Kevin W. Li,Sarah Goslee
出处
期刊:Journal of Soil and Water Conservation [Soil and Water Conservation Society]
卷期号:80 (5): 521-537 被引量:2
标识
DOI:10.1080/00224561.2025.2533100
摘要

Researchers and decision-makers increasingly recognize the importance of considering tradeoffs and synergies between multiple ecosystem services within the landscape when managing for sustainable agriculture. Ecosystem service modeling can be a valuable approach for exploring landscape management scenarios and understanding potential outcomes, but not all modeling frameworks are equally accessible or appropriate for agroecosystems at scales broader than the field or farm. We conducted a survey of ecosystem service modeling (ESM) tools to identify frameworks that could simultaneously assess multiple ecosystem services associated with sustainable agriculture. Our criteria emphasize that models should be spatially explicit and quantify multiple agriculturally relevant ecosystem services, and ideally, they should be adaptable to livestock systems and annual and perennial crops. Models should also be findable, accessible, interoperable, and reusable (FAIR). We synthesized 28 literature reviews that compared across multiple models, focusing on modeling frameworks that appeared consistently across reviews and matched most of our criteria. These models were Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST), Artificial Intelligence for Ecosystem Services (ARIES), Soil and Water Assessment Tool (SWAT), and Social Values for Ecosystem Services (SolVES). We also included the Agricultural Policy/Environmental eXtender (APEX) and the Rangeland Production Model (RPM) as examples of modeling frameworks that focus on ecosystem services in grazing lands, which are not well-represented in the reviewed literature. Most ESM tools include climate, soil, and water processes, while fewer models cover pollination, natural habitat, or cultural values, and none include biological pest control or genetic diversity. We find that the InVEST framework covers the greatest range of agroecosystem services and is automatable, open source, freely accessible, and easily applicable to landscapes, though it lacks integrated modules for modeling processes specific to grazing land. We identify components of InVEST that must be improved to provide meaningful results in grazed or integrated crop-livestock systems. The SolVES framework is unique in focusing on social and cultural values of ecosystem services, complementing the physical processes in InVEST. These models provide different, accessible options for understanding landscape management impacts on multiple ecosystem services and have the potential to play a key role in supporting decision-making in sustainable agriculture.
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