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Identifying and mitigating systematic biases in fish habitat simulation modeling: Implications for estimating minimum instream flows.
- Source :
- River Research & Applications; Jul2021, Vol. 37 Issue 6, p869-879, 11p
- Publication Year :
- 2021
-
Abstract
- Habitat simulation approaches (e.g., PHABSIM) have been used to model instream flows in thousands of streams and rivers and remain the most widely implemented detailed instream flow methodology. However, recent studies suggest that conventional habitat simulation models incorporate assumptions that may systematically underestimate instream flow needs, particularly for drift‐feeding fish. These include: (i) systematic biases in velocity habitat suitability curves (HSCs) caused by territoriality where dominant individuals displace subordinate fish to lower velocity micro‐habitats at high densities, thereby inflating the fitness value of low velocities; (ii) habitat simulation models do not account for flow effects on prey flux to drift‐feeding fishes, which may decrease more rapidly with reduced flow than does available habitat; (iii) use of focal velocities to construct traditional HSCs, which systematically underestimates velocity preference within the broader foraging arena of a drift‐feeding fish, and (iv) inadvertent use of low‐velocity HSCs associated with daytime refuging behavior from predators that may underestimate the higher velocities necessary for crepuscular foraging. Collectively, these factors suggest that current and historic flow prescriptions using traditional habitat simulation methods may underestimate optimal rearing flows for salmonids and other drift‐feeding species by anywhere from 10 to 50%. This implies that traditional instream flow management may be failing to provide the intended level of protection for drift‐feeding fishes in multiple streams at landscape scales. We provide guidelines for identifying contexts where model predictions are likely to be biased and approaches for correcting them. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15351459
- Volume :
- 37
- Issue :
- 6
- Database :
- Complementary Index
- Journal :
- River Research & Applications
- Publication Type :
- Academic Journal
- Accession number :
- 151211402
- Full Text :
- https://doi.org/10.1002/rra.3803