Date of Award:

2017

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Ecology

Advisor/Chair:

Joseph M. Wheaton

Abstract

Widespread habitat degradation and fragmentation has significantly altered the distribution and abundance of salmonids across the Western United States. To effectively conserve these fish, managers need tools to evaluate habitat quality in physically diverse streams and watersheds. Traditionally, habitat assessment for stream fish has focused on the physical characteristics of sites. Thus, such research has often overlooked important biological factors, such as the availability of prey or the presence and abundance of competitors or predators. In recent years, however, researchers have considered habitat from both physical and biological dimensions.

Bioenergetics models offer a way to combine the both the biotic and abiotic characteristics of streams into one currency (i.e., energetic value) of habitat selection and habitat quality. These models take into account both physical habitat characteristics (i.e., depth, velocity, substrate, and temperature) and the availability of food from drifting insects to predict favorable locations for foraging fish, and have been extended to make reach-scale predictions of total habitat capacity. Drift-foraging, bioenergetics models are increasingly being used to evaluate habitat quality and quantity, as well as carrying capacity of the sites they are run at. However, many of these bioenergetics models have been developed and applied for salmonids at sites whose populations are well below carrying capacity. Therefore, it is essential to test the predictions of these models on populations of salmonids that are abundant.

To address these concerns, I tested a bioenergetics model that Wall et al. (2016) applied to inform habitat management in the western US for cutthroat trout. I surveyed the spatial location of Bonneville cutthroat trout (BCT; Oncorhynchus clarkii utah) in the Logan River, Utah, a system where one of the most abundant populations of BCT reside, to determine if the fish were using locations with a high energetic value, predicted by a net rate of energy intake (NREI) modeling framework. I conducted snorkel surveys in both summer and fall to assess whether the modeled predictions were robust to changes in drift, temperature, or discharge. I also tested whether sampling estimates of BCT abundance were related to the NREI model predicted carrying capacity, or the proportion of suitable habitat (i.e., NREI > 0.0 J·s-1). Last of all, I tested whether the observed biomass of BCT were related to the mean NREI at each study site. I found that the majority of observed fish occupied focal positions that (i) had positive NREI and (ii) had NREI values that were significantly greater than the site mean. I also found that the simulated carrying capacity predicted for each site was significantly, positively related with the maximum BCT densities observed between 2001 and 2015 (R2=0.93, P=0.009). However, observed BCT densities and biomass were unrelated to the proportion of suitable habitat and the mean NREI at sites, respectively. I concluded that drift foraging bioenergetics models are useful tool for pin-pointing bioenergetically favorable locations within sites and discriminating capacity between sites for BCT and other similar trout species.

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