EARLY HEARING DETECTION AND INTERVENTION VIRTUAL CONFERENCE
MARCH 2-5, 2021
(Virtually the same conference, without elevators, airplane tickets, or hotel room keys)
5/26/2021 | 8:30 AM - 10:30 AM | COMBINING TAXONOMIC AND FUNCTIONAL APPROACHES TO EXAMINE HOW RIVERINE COMMUNITIES RESPOND TO ENVIRONMENTAL HETEROGENEITY AT DIFFERENT SCALES | Virtual Platform
COMBINING TAXONOMIC AND FUNCTIONAL APPROACHES TO EXAMINE HOW RIVERINE COMMUNITIES RESPOND TO ENVIRONMENTAL HETEROGENEITY AT DIFFERENT SCALES
Functional trait-based approaches have long been used in ecology to gain additional insights into patterns and processes but has rarely been applied to longer-lived and sessile aquatic taxa, such as freshwater mussels, to understand how the response of their community composition to environmental heterogeneity changes with spatial scale. We used freshwater mussels to examine how community composition changes in response to different environmental factors both within and between different segments of a river. We collected spatially extensive distribution data in three 20-km segments (upstream, midstream, downstream) in the San Saba River, Texas. As predicted by the network position hypothesis, local environmental variables explained significantly more of the variation in the functional composition in the upstream compared to the downstream segment. Regional environmental variables explained the highest amount of variation between segments. The functional-based approach explained up to 17% more of variation in the distribution of mussels compared to the taxonomic level approach. Our results suggest that stochasticity may play a larger role for species composition, whereas functional composition is more predictable, especially changes between up- and downstream.
- Ecological dynamics
- Freshwater continuum
- Stream
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Presenters/Authors
Zachary Mitchell
(), Texas State University, zmitchell9186@gmail.com;
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Joshua Robledo
(), Texas State University, j_r728@txstate.edu;
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Karl Cottenie
(), University of Guelph, cottenie@uoguelph.ca;
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Astrid Schwalb
(), Texas State University, schwalb@txstate.edu;
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