From spawner habitat selection to stock-recruitment: implications for assessment
Monday, August 2, 2021
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Stefan Skoglund, Rebecca Whitlock, Erik Petersson and Stefan Palm, Department of Aquatic Resources, Swedish University of Agricultural Sciences, Drottningholm, Sweden, Kjell Leonardsson, Department of Wildlife, Fish and Environmental Studies, Swedish University of Agricultural Sciences, Umeå, Sweden
Department of Aquatic Resources, Swedish University of Agricultural Sciences Drottningholm, Sweden
Background/Question/Methods The relationship between the reproducing stock and the subsequent number of offspring is a key factor in order to determine the productivity potential of a population. In fisheries stock assessment, obtaining unbiased parameter estimates of this relationship are crucial in order to achieve sustainable harvest of natural populations. Habitat selection has long been known to influence the productivity potential of a population, but is rarely included in the most common stock-recruitment functions used. Here we explore how habitat selective behavior of spawning individuals might influence the parameters estimated in the two most commonly used stock-recruitment functions (Beverton-Holt and Ricker). From simulated stock-recruitment (SR) data we compared the expected recruitment from four different hypothetical spawner distribution patterns: (i) habitat quality distribution (Hab Q) (spawners are proportionally distributed according to carrying capacities of local habitats, not influenced by local spawner densities); (ii) Ideal free distribution (IFD) (individuals adjust local densities according to the local habitat quality in order to maximize individual fitness); (iii) random distribution (habitat selection is random, with no influence of spawner density nor habitat quality); and (iv) stepwise distribution (a spawning site is utilized until a fixed density threshold, where after the next spawning site will be utilized until the density threshold, and so on, until all habitats are filled and additional spawners are distributed equally over all spawning areas). Potential bias in estimates of the total carrying capacity (K´) and maximum survival rate (S´) relative to underlying values (known parameter values based on the assumption of a single homogenous habitat: K and S) are quantified using the traditional SR-functions. Results/Conclusions Our results show that considerable bias is produced when the assumption of homogenously distribution of spawners is violated. The most pronounced bias was obtained when the underlying distribution behavior of spawning individuals followed an ideal free distribution pattern where the survival rate was underestimated by 55 percent on average. This result is remarkable since ideal free distribution behavior has been suggested for many managed fish species. In order to obtain unbiased parameter estimates of vital productivity parameters used as management reference point for many managed fish stocks, more consideration is needed of the underlying distribution behavior of spawners. Even if the focus of this study was fisheries orientated, our results are probably valid for other managed taxas where reproducing individual’s habitat selection influence the recruitment.