| Human development can negatively impact the ecological integrity of natural resources. Likewise, public health has been affected due to ecosystem rebounds. Not all communities are equally impacted by environmental hazards, which is a subject addressed by environmental justice. Due to the complexity of coupled natural and human systems, we rely on modeling tools capable of characterizing dynamic processes occurring over space, time, and organizational units. This study aims to advance the understanding of these processes and explores the utility of integrating stream health indicators with socioeconomic measures of communities, focusing on the Saginaw River Watershed located in Michigan. The following research objectives were established to characterize the relationships between stream health and socioeconomic measures: 1) by utilizing spatial multi-factor models and bivariate mapping to identify vulnerable areas for resource allocation, 2) by utilizing spatial clustering techniques to improve predictability of Structural Equation Models (SEMs). Regarding the first objective, this study showed that in the Saginaw River Watershed, regions with the worst stream health and most vulnerable social populations were located around highly populated areas and intensive agricultural activities. For the second objective, the results showed that solutions for SEMs can be sought by adjusting cluster size while considering socioeconomic variable characteristics within a cluster. |
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