Sampling the stream landscape: Improving the applicability of an ecoregion-level capture probability model for stream fishes
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Abstract
Temporal and spatial variability in streams result in heterogeneous gear capture probability (i.e., the proportion of available individuals identified) that confounds interpretation of data used to monitor fish abundance. We modeled tow-barge electrofishing capture probability at multiple spatial scales for nine Ozark Highland stream fishes. In addition to fish size, we identified seven reach-scale environmental characteristics associated with variable capture probability: stream discharge, water depth, conductivity, water clarity, emergent vegetation, wetted width–depth ratio, and proportion of riffle habitat. The magnitude of the relationship between capture probability and both discharge and depth varied among stream fishes. We also identified lithological characteristics among stream segments as a coarse-scale source of variable capture probability. The resulting capture probability model can be used to adjust catch data and derive reach-scale absolute abundance estimates across a wide range of sampling conditions with similar effort as used in more traditional fisheries surveys (i.e., catch per unit effort). Adjusting catch data based on variable capture probability improves the comparability of data sets, thus promoting both well-informed conservation and management decisions and advances in stream-fish ecology.
Study Area
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Sampling the stream landscape: Improving the applicability of an ecoregion-level capture probability model for stream fishes |
| Series title | Canadian Journal of Fisheries and Aquatic Sciences |
| DOI | 10.1139/cjfas-2016-0422 |
| Volume | 75 |
| Issue | 10 |
| Year Published | 2018 |
| Language | English |
| Publisher | Canadian Science Publishing |
| Contributing office(s) | Coop Res Unit Atlanta |
| Description | 12 p. |
| First page | 1614 |
| Last page | 1625 |
| Country | United States |
| State | Arkansas, Missouri, Oklahoma |
| Google Analytic Metrics | Metrics page |