We conducted a PHABSIM study on Bingham Creek, Washington, by using validated habitat suitability criteria for the rearing of coho salmon Oncorhynchus kisutch. We compared the relationship between weighted usable area (WUA) and flow with a previously determined empirical relationship that showed increasing coho salmon smolt production with increasing summer low flow (). The relationship between juvenile coho salmon WUA and flow indicated that the greatest amount of habitat occurred at a flow that was lower than our low‐flow measurement, and the amount of habitat decreased with increasing flow. Thus, PHABSIM results were contrary to empirical measurement of coho salmon smolt production. Based on the relationship between summer flow and smolt production, production of smolts would decline if flow was reduced to the flow that maximizes WUA. The failure of PHABSIM to be consistent with empirical results may have be related to habitat suitability being influenced more by the numerous subdominant, schooling juvenile coho salmon and less by the dominant, territorial individuals, which have higher survival and prefer higher velocities.
Instream flow models link a physical habitat model that predicts flow‐related changes in hydraulics to a biological model that predicts the response of fish to altered velocity and depth. Habitat suitability curves (HSCs) based on frequency of habitat use (fish occurrence relative to available habitat) remain the most widely used biological models in habitat simulations. However, in some contexts fish density may be a poor indicator of habitat quality, leading to biased predictions of optimal flow. We explore the use of bioenergetics to derive mechanistic HSCs based on the fundamental energetics of habitat use. Using flow‐related changes in production of Coho Salmon Oncorhynchus kisutch smolt as reference data to evaluate model predictions, we found that bioenergetic‐based HSCs matched the validation data better than frequency‐based HSCs, which systematically underestimated optimal flows. However, biases remained using bioenergetic HSCs, suggesting that habitat suitability may not be independent of discharge as is often assumed. Declining invertebrate drift concentration, increasing temperature, and density dependence of growth at low flows are potential mechanisms of flow‐related declines in habitat suitability; measuring these effects and incorporating them into flow models is an important step in further improving model predictions, particularly at low flows.
Received December 3, 2015; accepted May 11, 2016
SynopsisWe sampled fish at pairs of sites of the same stream order on opposite sides of drainage divides in the Cascade Mountains and in the southwest portion of Washington state. Elevation, gradient, drainage area, and stream order were significantly correlated with number of fish species collected at a site. Elevation accounted for the greatest portion of the variation in number of species and stream order for the least, but in low gradient, low elevation streams, stream order was significantly related to number of species. Species richness was greatest in low elevation, low gradient, high order streams. Species richness of a site reflected species richness of the drainage: in paired comparisons, sites in a drainage with a richer ichthyofauna had more fish species than sites in a drainage with fewer species. Addition of species with increasing stream order occurred in most streams, but replacement was more frequent than in other studies relating fish to stream order. The apparently higher frequency of replacement in this study appeared to be a result of headwater introductions of brook charr, Salvelinus fontinalis, and a tendency for cutthroat trout, Salmo clarki, to occupy headwaters when in freshwater.
We tested an assumption of the Physical Habitat Simulation of the Instream Flow Incremental Methodology (IFIM) that fish select microhabitats based on the quality of one or several hydraulic conditions. We developed preference curves for juvenile steelhead (Oncorhynchus mykiss) in Morse Creek, Washington, USA, that accounted for availability of depths and velocities and their utilization by steelhead parr. To allow comparison of intervals among preference curves from different studies, we developed preference indices. We then evaluated the relationship between steelhead parr density and preference or preference indices for depth, velocity, and depth and velocity combined using an independent data set from a different year and an adjacent location in Morse Creek; these indices reflected observed densities of steelhead parr. There was a significant rank correlation between steelhead parr density and preferences or preference indices of steelhead parr for velocity alone and for depth and velocity combined, but not for depth alone. Steelhead parr strongly avoided habitat in which depth preference was 0.0, but velocity preference appeared to influence use of habitat where depth preference was not 0.0. Steelhead parr avoided cells with low preference indices and preferred cells with high preference indices. These relationships support an assumption of the IFIM.
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