EAPSI: Insect mouthparts as indicators of excessive fine sediment in streams

Edwards Patrick M, Portland OR

Investigators

Abstract

Excessive fine-sediment in streams is the leading cause of surface water degradation in the United States and across the world. Fine-sediment transport and deposition on the stream bottom is a natural process; however, human activities can result in excessive amounts of sediment delivery to streams where it harms reproductive habitat for fish and other stream biota. Fine sediment is hard to measure directly in the stream thus this research seeks to develop insect-based indicators as proxies for monitoring fine-sediment conditions on the stream bottom. This research will be conducted in collaboration with Dr. Beixin Wang at Nanjing Agricultural University. Using the agricultural streams of southeast China as study sites will allow extension of the sediment gradient used in statistical models. For environmental managers in the United States and across the world, the findings of this research are of potential value in assisting with the identification of biologically-relevant changes in stream fine sediment conditions and support efforts to balance economic needs while protecting critical stream habitat. By using the mouthpart characteristics of stream insect grazers, this research represents a novel approach to the development of sediment indicators. This method will not only identify trait-based indicators, but may also reveal causal mechanisms associated with macroinvertebrate sensitivity to inorganic fine sediment. Stream insects will be collected across a wide gradient of fine sediment conditions and examined using a Scanning Electron Microscope. Mouthpart structure and wear will be quantified and used to categorize insect tolerance. The hypothesis of this research is to show that the structure of insect mouthparts and corresponding wear on their mandibles are a useful biologic indicator of excessive inorganic fine sediment conditions on the bottom of streams. This NSF EAPSI award is funded in collaboration with the Chinese Ministry of Science and Technology.