A new optimal foraging model predicts habitat use by drift‐feeding stream minnows

Abstract

– There is substantial need for models that accurately predict habitat selection by fishes for purposes ranging from the elaboration of ecological theory to the preservation of biodiversity. We have developed a new and highly tractable optimal foraging model for drift‐feeding fishes that is based on the profitability of occupying varying focal‐point velocities in a stream. The basic model can be written as: Ix = (Ex * Px) = {(D * A * V) * [1/(1 + e(b + cV))]} − Sx, where: (1) Ix is the net energy intake at velocity x; (2) E is prey encounter rate; (3) P is prey capture success rate which can be modelled as 1/(1 + e(b + cV)) where b and c are fitting constants from the prey capture success curve; (4) D is the energy content of prey (J/m3) in the drift; (5) A is the visual reactive area of the fish; (6) V is velocity (cm/s); and (7) S is the cost of maintaining position (J/s). Given that D, A and S can be considered constant over the range of velocities occupied by these fishes, the model reduces to e(b + cV) = 1/(cV − 1) which we solved iteratively to yield an optimal focal‐point velocity for species in each sample. We tested the model by comparing its predictions to the mean focal‐point velocities (i.e. microhabitats) occupied by four species of drift‐feeding minnows in two sites in a stream in North Carolina, USA. The model successfully predicted focal‐point velocities occupied by these species (11 out of 14 cases) in three seasonal samples collected over 2 years at two sites. The unsuccessful predictions still were within 2 cm/s of the 95% confidence intervals of mean velocities occupied by fishes, whereas the overall mean deviation between optimal velocities and mean fish velocities was small (range = 0.9 and 3.3 cm/s for the warpaint shiner and the Tennessee shiner, respectively). Available focal‐point velocities ranged from 0–76 to 0–128 cm/s depending on site and season. Our findings represent one of the more rigorous field tests of an optimal foraging/habitat selection model for aquatic organisms because they encompass multiple species and years, and for one species, multiple sites. Because of the ease of parameterization of our model, it should be readily testable in a range of lotic habitats. If validated in other systems, the model should provide critical habitat information that will aid in the management of riverine systems and improve the performance of a variety of currently used management models (e.g. instream flow incremental methodology (IFIM) and total maximum daily load calculations (TMDL)).

Modeling the influence of flow on invertebrate drift across spatial scales using a 2D hydraulic model and a 1D population model

“…Rosenfeld and Taylor, 2009). With additional assumptions, they have been used to predict larger spatial patterns of biomass distribution or capacity (Grossman et al, 2002;Hayes et al, 2007;Hughes, 1998), but a remaining challenge is linking spatial patterns of growth and survival to population viability (Anderson et al, 2006b;Armstrong and Nislow, 2012;Frank et al, 2011;Locke et al, 2008). Individual-based modeling (IBM) approaches based on the bioenergetics of specific life stages for individual fish have been the most successful at this integration and have shown great utility in river management contexts (Van Winkle et al, 1998;Vincenzi et al, 2008).…”

Influence of cover on mean column hydraulic characteristics in small pool riffle morphology streams

“…Fish are thought to occupy microhabitats that maximize their net energy intake (Milinski, 1993). This approach has been used to predict microhabitat of several fish species (Fausch, 1984;Hughes and Dill, 1990;Grossman et al, 2002). Not a single approach to modelling will fit all needs; however, hydraulically based models are popular and relatively simple to apply across numerous streams compared to energetically based models.…”

Form and performance: body shape and prey-capture success in four drift-feeding minnows

“…Drift-feeding Wshes also are important components of stream Wsh faunas worldwide (Matthews 1998); thus, studies of their dynamics have the potential for generality. To brieXy describe this system, drift-feeding Wshes typically hold relatively stable foraging positions in running water from which they dash to strike at macroinvertebrates carried downstream by the current (i.e., drift) (Hughes and Dill 1990;Hill and Grossman 1993;Grossman et al 2002). Swimming to hold position against a current may impose substantial energetic costs on driftfeeding Wshes (Facey and Grossman 1990), and, at velocities higher than about 5-10 cm/s, current speed can negatively aVect the ability of Wshes to capture drifting prey (Hill and Grossman 1993;Tyler 1993;Grossman et al 2002).…”

“…To brieXy describe this system, drift-feeding Wshes typically hold relatively stable foraging positions in running water from which they dash to strike at macroinvertebrates carried downstream by the current (i.e., drift) (Hughes and Dill 1990;Hill and Grossman 1993;Grossman et al 2002). Swimming to hold position against a current may impose substantial energetic costs on driftfeeding Wshes (Facey and Grossman 1990), and, at velocities higher than about 5-10 cm/s, current speed can negatively aVect the ability of Wshes to capture drifting prey (Hill and Grossman 1993;Tyler 1993;Grossman et al 2002). However, Wshes still occupy foraging positions with velocities higher than 10 cm/s because encounter rates with drifting prey generally increase with increasing current velocity (Hughes and Dill 1990;Grossman et al 2002).…”