Earning their Stripes: The Potential of Tiger Trout and Other Salmonids as Biological Controls of Forage Fishes in a Western Reservoir

Abstract

Maintaining a balance between predator and prey populations can be an ongoing challenge for fisheries managers, especially in managing artificial ecosystems such as reservoirs. In a high‐elevation Utah reservoir, the unintentional introduction of the Utah Chub Gila atraria and its subsequent population expansion prompted managers to experimentally shift from exclusively stocking Rainbow Trout Oncorhynchus mykiss to also stocking tiger trout (female Brown Trout Salmo trutta × male Brook Trout Salvelinus fontinalis) and Bonneville Cutthroat Trout O. clarkii utah (hereafter, Cutthroat Trout) as potential biological control agents. We measured a combination of diet, growth, temperature, and abundance and used bioenergetic simulations to quantify predator demand versus prey supply. Utah Chub were the predominant prey type for tiger trout, contributing up to 80% of the diet depending on the season. Utah Chub represented up to 70% of the total diet consumed by Cutthroat Trout. Although Utah Chub dominated the fish biomass in the reservoir, we still estimated abundances of 238,000 tiger trout, 214,000 Cutthroat Trout, and 55,000 Rainbow Trout. Consequently, when expanded to the population level of each predator, tiger trout and Cutthroat Trout consumed large quantities of Utah Chub on an annual basis: tiger trout consumed 508,000 kg (2,660 g/predator) of the standing prey population, and Cutthroat Trout consumed an estimated 322,000 kg (1,820 g/predator). The estimated combined consumption by Cutthroat Trout and tiger trout exceeded the estimate of Utah Chub annual production. As such, our results suggest that the high rates of piscivory exhibited by Cutthroat Trout and tiger trout in artificial lentic ecosystems are likely sufficient to effectively reduce the overall abundance of forage fishes and to prevent forage fishes from dominating fish assemblages. Collectively, this research provides the first documented findings on tiger trout ecology and performance, which will aid managers in designing and implementing the best stocking strategy to optimize sport fish performance, control undesirable forage fish, and enhance and maintain angler satisfaction. Received April 1, 2016; accepted November 8, 2016 Published online March 8, 2017

Population Ecology and Evaluation of Suppression Scenarios for Introduced Utah Chub

“…; Winters et al. ). Regardless of the method contemplated, eradication and control efforts in large systems can be expensive (Kolar et al.…”

“…Fisheries managers may manage introduced or undesirable fish populations through eradication or control efforts (Kolar et al 2010). Techniques for eradicating or controlling introduced fish populations can be placed into three different categories: chemical (Marking 1992;Lentsch et al 2001), physical (Johnston 1961; Thompson and Rahel 1996;Ng et al 2016), and biological (Ward et al 2008;Schill et al 2016;Winters et al 2017). Regardless of the method contemplated, eradication and control efforts in large systems can be expensive (Kolar et al 2010); thus, knowledge of how much effort is required to influence introduced fish populations is needed prior to the implementation of control programs (Klein et al 2016;Brauer et al 2019).…”

“…Interactions such as these are cause for concern if Utah Chub are introduced into a system. Although Utah Chub are widely regarded as having a negative influence on desirable native fish or sport fish populations, surprisingly little is known about their population dynamics, making it difficult for fishery managers to evaluate control or suppression strategies (Winters et al 2017). Our objective was to describe the population characteristics (i.e., age and growth, mortality, and fecundity) of Utah Chub in Henrys Lake, Idaho.…”

Exploring the Contemporary Relationship between Predator and Prey in a Significant, Reintroduced Lahontan Cutthroat Trout Population

“…This decoupling can lead to unstable population dynamics, which can be risky and frustrating to manage, especially if the focal species are of economic importance, are imperiled, or sustain subsistence fisheries, for example (Stewart et al 1981; Ruzycki et al 2003; Al‐Chokhachy et al 2020). Efforts to better understand predator–prey dynamics and manage top fish predators for multiple goals range from the classic, relatively simple ratio‐based indices of predator performance relative to prey availability (e.g., proportional size distribution; reviewed by Noble 1981) to much more comprehensive and sophisticated attempts to quantify carrying capacity and predator consumption relative to prey biomass and production using multifaceted bioenergetics modeling and associated intensive field and laboratory work (e.g., Ruzycki et al 2003; Vatland et al 2008; Winters et al 2017). Alternatively, there have been considerable advances in modeling predator–prey dynamics to inform predator management, including ecosystem approaches using Ecopath (e.g., Christensen and Pauly 2004), Bayesian multispecies age‐structured models (e.g., Tsehaye et al 2014a), and a variety of elegant stock assessment tools that combine several of these approaches (e.g., He et al 2020).…”

Bolstering Piscivore Abundance to Restructure Small Impoundment Fish Communities

“…Another potential management strategy is to introduce additional predators and thereby reduce Common Carp and Gizzard Shad populations via predation. Stocking of additional piscivorous fishes has been used to reduce or eliminate undesirable fishes or to improve growth and size structure of desirable fishes in a variety of ecosystems, with varying success (e.g., Haines 2000; Boxrucker 2002; DeBoom and Wahl 2014; Koenig et al 2015; Winters et al 2017). In many cases, Largemouth Bass Micropterus salmoides , which are the primary apex predators in many small lakes, fail to control Gizzard Shad and Common Carp populations even when the Largemouth Bass populations are enhanced by stocking (Hambright et al 1991; Nowlin et al 2006; DeBoom and Wahl 2014; but see Irwin et al 2003).…”