Exploring potential mechanisms linking urban landscapes to instream stressors and macroinvertebrates in the Southeast Piedmont: Implications for watershed management

Abstract

Urbanization has greatly degraded stream health, particularly in the rapidly urbanizing southeastern United States. Recent studies identified primary instream stressors affecting biological communities along urban gradients in the Southeast Piedmont. However, a comprehensive understanding of the complex mechanisms is still lacking, which impedes effective management actions. To improve our understanding, we investigated the potential pathways by which urbanization, as represented by the landscape development intensity index (LDII), and important environmental characteristics affected instream stressors and macroinvertebrate communities using structural equation modeling (SEM) and the U.S. Geological Survey Southeast Stream Quality Assessment dataset. We investigated the direct, indirect, and total effects of LDII and environmental characteristics on instream stressors and macroinvertebrate communities as well as the interactions of instream stressors. Moreover, we explored alternative reasonable relationships between variables by using an alternative model approach. We found that LDII had moderate to strong total effects on all instream stressors and macroinvertebrates with complex impact pathways revealed in SEM models, demonstrating the dominant impact of urban landscape development on stream ecosystems in the Southeast Piedmont. Flow disturbance and pesticides were major mediators transmitting most of LDII’s effects on macroinvertebrates. Furthermore, we found potential interactions among instream stressors, which were not widely discussed in previous studies. Compared with agricultural watersheds, urban watersheds represented different land use impact mechanisms. Our findings contributed to an improved understanding of urbanization’s impact on stream ecosystems and demonstrated the usefulness of an alternative model approach that provided insights into the underlying mechanisms. In addition, we demonstrated the utility of LDII in characterizing landscape development and improving SEM models. Finally, we explored the potential of SEM in global watershed management activities by discussing the practical implications of impact pathways and the innovative use of SEM as a decision-making tool.