Moving Beyond Water Quality Indices: How Can Macroinvertebrate Data from Fish Habitat Monitoring Programs Inform Food Web Analyses?

Fish habitat monitoring programs frequently include the collection of stream macroinvertebrates, primarily for the purpose of calculating water quality indices. However, these data also have the potential to provide a picture of riverine food webs as they relate to fish. Standard bioassessment tools, using taxonomic composition or relative abundance of organisms, are common goals of fish monitoring programs worldwide as they are sensitive to environmental stressors such as water temperature or streambed sediment. Yet beyond describing water quality, these data can also help examine riverine food webs as they relate to fish. The structure of food webs can provide insight into important ecosystem process such as competition, predation, and food limitation. In this symposium, various opportunities to couple emerging research methodologies with past and ongoing macroinvertebrate data collection programs will be explored, including predicting energetic carrying capacity of stream habitats, fish foraging indices, network models of stream productivity, body size-abundance and trophic linkage approaches, trait-based analyses, contribution of aquatic versus terrestrial inputs, and landscape-scale food web analyses. Challenges to these and other approaches will be addressed, including standardization of field, laboratory, and data management procedures (including efforts to agree on a standard taxonomic effort); understanding spatial and temporal variability of benthic communities; and discrepancies in ecological traits of benthic organisms. The goal of this symposium is to provide information to both watershed managers hoping to expand their knowledge of ecological conditions with existing data collection and to food web researchers hoping to tap into larger regional or national data to expand their understanding of food webs to a landscape scale.
Seth White
Amy Puls, Ryan Bellmore and Robert Danehy
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