To address human dependence on natural resources and anthropogenic impacts on ecosystem health,understanding and management of the linkages between nature and human well-being(HWB)are urgently needed.One fundamental b...To address human dependence on natural resources and anthropogenic impacts on ecosystem health,understanding and management of the linkages between nature and human well-being(HWB)are urgently needed.One fundamental barrier is the lack of quantitative indicators and models that integrate HWB with direct and indirect drivers of change in natural resources.While primary surveys provide the most valid HWB measures,extensive new data collection is often costly,especially for large-scale studies.Therefore,it is vital to develop methods and indices based on existing data(e.g.,census data,survey data)for real-world application.To address this,we propose a new method of using structural equation modeling to construct robust,spatially explicit HWB indices from existing data and demonstrate its validity and usefulness in Cambodia.Our method is scale-free and applicable to different frameworks and data sources and thus supports relatively easy replication in many other contexts.Further application and refinement could improve understanding of human-nature interactions,move toward robust theory development,and guide natural resource management decisions.展开更多
基金funding from the Gordon and Betty Moore Foundation(grant number 3519).
文摘To address human dependence on natural resources and anthropogenic impacts on ecosystem health,understanding and management of the linkages between nature and human well-being(HWB)are urgently needed.One fundamental barrier is the lack of quantitative indicators and models that integrate HWB with direct and indirect drivers of change in natural resources.While primary surveys provide the most valid HWB measures,extensive new data collection is often costly,especially for large-scale studies.Therefore,it is vital to develop methods and indices based on existing data(e.g.,census data,survey data)for real-world application.To address this,we propose a new method of using structural equation modeling to construct robust,spatially explicit HWB indices from existing data and demonstrate its validity and usefulness in Cambodia.Our method is scale-free and applicable to different frameworks and data sources and thus supports relatively easy replication in many other contexts.Further application and refinement could improve understanding of human-nature interactions,move toward robust theory development,and guide natural resource management decisions.
