Yellow Perch in South Dakota: Population Variability and Predicted Effects of Creel Limit Reductions and Minimum Length Limits

Abstract

We collected annual gill-net samples of yellow perch Perca flavescens in six South Dakota lakes over 4-5 years. We also simulated the effects of reductions in daily creel limits for yellow perch (i.e., from 25 fish/angler to 5, 10, or 15 fish/angler) and use of minimum total length limits (229 and 254 mm). Population indices varied widely among lakes and among years within lakes to the extent that indices from any individual year were largely uninformative. Creel surveys indicated that few anglers typically achieved a daily creel limit of 25 yellow perch. Except in Waubay Lake, lowering the creel limit from 25 to 5 fish/angler would be necessary to achieve harvest reductions of 25% or more within most of the fisheries we examined. Minimum length limits were projected to improve size and age structure, but harvest reductions often exceeded 50% and yield declined or only slightly increased (by 13%). Yellow perch in these lakes had achieved much of their full growth potential by the time they reached 229 and 254 mm. Consequently, although length limits were predicted to increase age and size structures, asymptotic growth prevented yellow perch from attaining substantially larger sizes. Length limits were predicted to be most beneficial when fishing mortality represented most of the total mortality in each population and when growth occurred at median or fast rates. A 229-mm length limit was predicted to improve size and age structures with less-severe reductions in harvest or yield than a 254-mm limit. Population dynamics and the harvest-oriented nature of yellow perch anglers may dictate that yield maximization is still a reasonable management goal for many South Dakota yellow perch fisheries. Increasing the number of yellow perch that attain 229 mm is possible for certain fisheries if angler harvest represents the dominant source of mortality.

Quantifying inter-population variability in yellow perch sexual size dimorphism

“…Predicted lengths from the 13 populations used in the predicted length-at-age comparisons were used for this analysis. Predicted lengths-at-age-3 were used because this age group is commonly used for yellow perch growth assessments (Lott et al 1996(Lott et al , 1998Isermann et al 2007). SSD (the difference between female and male predicted lengths-at-age-3) was regressed against several variables including productivity of the lake [Trophic State Index based on total phosphorus (TSI TP , Carlson 1977)], lake morphometry (surface area in ha, maximum depth in m, and mean depth in m), and yellow perch gender-combined population dynamics: growth (K), maximum predicted length (L 1 ), total annual mortality (A), and recruitment variability (recruitment coefficient of determination, RCD).…”

“…Recent trends in recreational fisheries regulations have been toward reducing daily creel limits (Webb and Ott 1991;Jacobson 2005) and implementing lengthbased regulations (Boxrucker 2002;Paukert et al 2002;Isermann et al 2007). Creel limits can work to reduce harvest, but they are often too liberal to reduce harvest mortality (Cook et al 2001;Isermann et al 2007).…”

“…Creel limits can work to reduce harvest, but they are often too liberal to reduce harvest mortality (Cook et al 2001;Isermann et al 2007). Therefore, length limits are often used to restrict the harvest of certain size classes of fish (Cook et al 2001;Isermann et al 2007).…”

“…Creel limits can work to reduce harvest, but they are often too liberal to reduce harvest mortality (Cook et al 2001;Isermann et al 2007). Therefore, length limits are often used to restrict the harvest of certain size classes of fish (Cook et al 2001;Isermann et al 2007). Even when length limits are not set by the managing natural resource agency, anglers have been shown to be size selective by setting personal minimum length limits and voluntarily harvesting longer or more robust individuals (Goedde and Coble 1981;Parsons and Reed 1998;Isermann et al 2005).…”

An assessment of participation, catch and effort in the KwaZulu-Natal shore-based marine linefishery, with comments on management effectiveness

“…However, currently catch-and-effort data form an important part in assessing the efficacy of management and Introduction Dunlop and Mann 480 in providing information for specific management regulations. For example, data from roving-creel surveys are needed to set and evaluate daily bag limits (Paragamian 1984, Attwood and Bennett 1995, Isermann et al 2007, whereas catch per unit effort (CPUE) data from such surveys provide information on trends in relative stock abundance, catch composition and distribution of catch between sectors (Caputi 1976, Clarke and Buxton 1989, Claytor and O'Niel 1991, Griffiths et al 1999, Brouwer and Buxton 2002, Rangel and Erzini 2007, Veiga et al 2010, Smallwood et al 2011. Importantly, long-term monitoring of catch and effort can provide warning of possible overexploitation in a fishery and allow for subsequent management interventions to be made before any collapse occurs.…”