A systematic review of food-environment interactions in catchment models

流域模型中食物-环境相互作用的系统性综述

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Abstract

This paper provides a systematic review of food-environment interactions in catchment models, focusing on the complex relationships between land use, ecosystem services, and agricultural production. The review highlights the importance of catchment-scale models in understanding the impact of land use on local ecosystems, particularly in relation to water quality, biodiversity, and soil services. By examining various international catchment-scale models, with an emphasis on the micro and macro disparities, the paper identifies key methodological lessons and future opportunities to enhance these frameworks for more effective policy design and environmental management. The review is structured around a conceptual framework that categorises models into environmental models, which focus on ecosystem dynamics, and physical models, which examine structural and material aspects of land use systems, as well as human dimensions, with a specific focus on reducing net emissions and improving land productivity. This relationship is described through a conceptual framework. The paper also emphasises the significance of spatial and temporal factors in these models, noting gaps in the literature limited integration of food production into catchment models, underrepresentation of localised/catchment-level modelling, data limitations, particularly lack of georeferenced micro-level data, inadequate incorporation of climate change scenarios and temporal variability, weak integration of biophysical, economic, and social factors, insufficient analysis of policy and governance impacts at catchment scale and lack of farm-specific, actionable recommendations. The research highlights the critical need for enhanced data accessibility, environmental model maintainability, standardised land use variable definitions, and improved georeferencing in land use modelling. The findings emphasise the importance of long-term projections, integration of social, economic, and biophysical factors, and open data initiatives to bolster essential research infrastructure and foster stakeholder engagement for more effective agricultural policy and environmental management.

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