Assessing the Effects of Catch‐and‐Release Regulations on a Brook Trout Population Using an Age‐Structured Model

Abstract

As populations of wild brook trout Salvelinus fontinalis decline across the species' native range in North America, angling regulations such as fly‐fishing only and catch and release are being used by management agencies to conserve fish while maintaining angling opportunities. Postrelease (hooking) mortality may significantly shift the age structure and size structure of populations. To assess the possible influence of catch‐and‐release fishing on brook trout population structure, we applied data from several sources to build a deterministic population model that included age‐classes up to age 5. To assess the potential effect of fishing, we examined the changes in population density and age structure at varying levels of angler effort (0–400 angler‐hours·ha−1·year−1) and hooking mortality rates (0–14%). Assuming a low (5%) hooking mortality rate, trophy brook trout density (ages 4 and 5) decreased by 50% at an angling intensity of 160 angler‐hours·ha−1·year−1. As angling effort increased, the proportion of older fish (ages 3–5) declined further. At very high levels of angling effort (>300 angler‐hours·ha−1·year−1), age‐4 and age‐5 fish were eliminated from the population. Increases in postrelease mortality rates resulted in similar declines for older age‐classes. The results of this simulation indicate that hooking mortality rates as might be common in catch‐and‐release fisheries may significantly shift the age structure of a population, thus reducing trophy angling potential.

Spatial variability in adult brook trout (Salvelinus fontinalis) survival within two intensively surveyed headwater stream networks

“…Apparent survival rate (survival + emigration) depends on the spatial extent of the study area; thus direct comparison of apparent survival estimates is not always easy across different studies. Still, our values fell within the range of survival estimates reported in other lotic populations of brook trout (Petty et al 2005;Letcher et al 2007;Risley and Zydlewski 2010). For example, Petty et al (2005) reported that apparent survival rate for small adults (mostly age 1+) was approximately 0.50 in 100 m stream sites over seasonal intervals (3-6 months) in West Virginia.…”

“…For example, Petty et al (2005) reported that apparent survival rate for small adults (mostly age 1+) was approximately 0.50 in 100 m stream sites over seasonal intervals (3-6 months) in West Virginia. Risley and Zydlewski (2010) assumed an annual true survival rate (not apparent survival rate) of 0.50 for age 1+ individuals in an adfluvial brook trout population.…”

Catch and Exploitation of Shoal Bass in the Flint River, Georgia, USA: Implications for Harvest Restrictions

“…These potential effects were not quantified or accounted for during the present study, and increases in mortality or decreases in growth due to multiple catch-and-release experiences may reduce some of the benefits that were predicted to result from the higher MLL or the slot limit. Risley and Zydlewski (2010) used a simulation model to show that high rates of catch and release, with associated hooking mortality, could shift the age structure of Brook Trout Salvelinus fontinalis populations in Maine, thus reducing the trophy angling potential of those fisheries. Future work examining the effects of catch and release on Shoal Bass biology is warranted since these fish are obviously extremely vulnerable to anglers, as has been demonstrated for other species (e.g., Brook Trout).…”

Modeling White Sucker (Catostomus commersonii) populations to assess commercial harvest influence on age structure

“…Local sensitivity of the model outputs was evaluated by altering input life history parameters by 1% (Haefner 2005;Risley and Zydlewski 2010;Bailey and Zydlewski 2013). Assessed parameters included a, b, natural mortality (M), the fecundity-fork length relationship constants (a and b), probability of spawning of young age-classes (where recruitment was less than 1.0), was assessed in aggregate (i.e., a 1% change was imposed on P Age 3 , P Age 4 , and P Age 5 , for the analysis).…”