Bioenergetic Habitat Suitability Curves for Instream Flow Modeling: Introducing User‐Friendly Software and its Potential Applications

Abstract

Habitat suitability curves (HSCs) are the biological component of habitat simulation tools used to evaluate instream flow management trade-offs (e.g., the physical habitat simulation model). However, traditional HSCs based on empirical observations of habitat use relative to availability have been criticized for generating biased estimates of flow requirements and for being poorly transferable across locations. For fish like salmonids that feed on drifting invertebrates, bioenergetics-based foraging models that relate habitat conditions to net energy gain offer an alternative approach that addresses some of these shortcomings. To make this technique more accessible for practitioners, we present free and user-friendly software for generating bioenergetics-based HSCs. The software also allows sensitivity analyses of HSCs to factors like fish size or prey abundance as well as direct integration of hydraulic data. While some caveats remain, bioenergetic HSCs should offer a more rigorous and credible means for quantifying habitat suitability for instream flow modeling.

InSTREAM 7: Instream flow assessment and management model for stream trout

“…These models (like inSTREAM) predict a trout's net rate of energy intake (NREI, often treated as equivalent to growth potential) as a function of hydraulic conditions, food availability, temperature, and fish characteristics. NREI models are used as an alternative way to evaluate habitat in PHABSIM-like models, by treating NREI as a measure of "suitability" (e.g., Jowett, Hayes, & Neuswanger, 2021;Naman et al, 2020;Naman, Rosenfeld, Neuswanger, Enders, & Eaton, 2019) and, combined with models of drift transport, to predict the "carrying capacity" of stream reaches (e.g., Hayes, Hughes, & Kelly, 2007;Wall, Bouwes, Wheaton, Saunders, & Bennett, 2015). Here we identify important specific differences between InSTREAM 7 and traditional assessment methods, specifically the use of PHABSIM and NREI models and temperature criteria.…”

Identifying and mitigating systematic biases in fish habitat simulation modeling: Implications for estimating minimum instream flows

“…This emphasizes that density may not be an accurate indicator of habitat quality for drift-feeding salmonids, particularly for juveniles at high densities or when rearing habitat is limited. This study also highlights a potential solution in the form of bioenergetic-based HSCs, which can provide an estimate of habitat quality across various depth and velocity combinations using modeled energy intake and swimming costs for drift-feeding fish based on the fundamental bioenergetics of central-placed foraging (Hughes & Dill, 1990;Naman et al, 2020a). Because net energy intake is estimated in the absence of competition, it represents a robust index of habitat quality that is independent of fish density (Naman, Rosenfeld, Neuswanger, Enders, & Eaton, 2020c;Rosenfeld et al, 2016;Rosenfeld, Bouwes, Wall, & Naman, 2014).…”

“…Calculating bioenergetic-based HSCs is a complicated process that will deter most instream flow biologists. However, userfriendly software (BioenergeticHSC; Naman et al, 2020c, see Data S1) has recently been developed to automate the creation of bioenergetic-based HSCs, which can then be used as stand-alone curves or to serve as diagnostics to flag whether empirical frequency-based curves are likely to be biased (Naman et al, 2020a). For example, any HSC that shows very high habitat quality at low velocities for fish that are known to be drift-feeders…”

“…The first source of bias relates to the assumption that the frequency of habitat use accurately reflects habitat quality; however, territoriality generates strong potential for systematic biases in velocity HSCs when dominant individuals displace subordinate fish to lower velocity micro-habitats at high densities, thereby inflating the fitness value of low-velocity habitats (Beecher, Caldwell, DeMond, Seiler, & Boessow, 2010). Second, habitat simulation models assume that fish abundance is limited by the availability of physical habitat (Orth, 1987), and ignore flow effects on prey flux and consumption (Naman et al, 2020a), which may decrease more quickly with reduced flow than available habitat (Hayes, Goodwin, Shearer, Hay, & Kelly, 2015;Rosenfeld et al, 2016;Rosenfeld & Ptolemy, 2012). Finally, the use of focal velocities to construct traditional habitat suitability curves may systematically underestimate velocity preference within the broader foraging arena of a drift-feeding fish, thereby underestimating the flows that maximize overall energy intake (Naman, Rosenfeld, Jordison, Kuzyk, & Eaton, 2020b).…”

Mechanisms of density dependence in juvenile salmonids: prey depletion, interference competition, or energy expenditure?

“…To quantify microhabitat use, snout velocity and depth were measured at the location from which foraging attempts originated with a handheld flowmeter (FH950) after the behavioral observation was terminated. The software bioen-ergeticHSC (v1.0, Naman et al 2020) was then used to estimate the NREI. Given our low sample size for behavioral observations, NREI was estimated once per density treatment (n = 4) using the average fork length, foraging velocity, temperature, and depth for that treatment, and the size-frequency distribution of invertebrates from all drift net samples pooled together.…”