Quantifying selection differentials caused by recreational fishing: development of modeling framework and application to reproductive investment in pike (Esox lucius)

Abstract

Methods for quantifying selection pressures on adaptive traits affected by size-selective fishing are still scarce, and none have as yet been developed for recreational fishing. We present an ecologically realistic age-structured model specifically tailored to recreational fishing that allows estimating selection differentials on adaptive life-history traits. The model accounts for multiple ecological feedbacks, which result in density-dependent and frequency-dependent selection. We study selection differentials on annual reproductive investment under size-selective exploitation in a highly demanded freshwater recreational fish species, northern pike (Esox lucius L.). We find that recreational angling mortality exerts positive selection differentials on annual reproductive investment, in agreement with predictions from life-history theory. The strength of selection increases with the intensity of harvesting. We also find that selection on reproductive investment can be reduced by implementing simple harvest regulations such as minimum-size limits. The general, yet computationally simple, methods introduced here allow evaluating and comparing selection pressures on adaptive traits in other fish populations and species, and thus have the potential to become a tool for evolutionary impact assessment of harvesting.

Keywords: angling; fisheries-induced evolution; life history; minimum-size limit; size-selective exploitation.

Figure 1

Calculation of the selection differential S as the difference in trait means before and after selection. This is the last step in the general approach introduced in this article for estimating fishing-induced selection differentials from an age-structured life-history model. After compilation of life-history information and the specification of density dependences, the four steps involved are (A) determination of the demographic equilibrium and thereby of the ecological environment in which fitness is considered, (B) calculation of trait-specific fitness for the given ecological environment, (C) transformation of the trait distribution before selection (continuous curve) into the trait distribution after selection (dotted curve) by weighting the former by trait-specific fitness (dashed curve) and normalizing the resultant distribution, (D) calculation of the selection differential.

Figure 2

Population dynamics of pike at age 1 year and older exploited at different intensities by anglers. Curves show the equilibration of abundance density over time for different levels of maximum angling effort per area and year (u; unit h ha⁻¹ year⁻¹), with thicker curves corresponding to higher efforts. The corresponding annual exploitation rates at equilibrium are shown in Table 1 and default parameter values are listed in Table A1.

Figure 3

(A) Dependence of the standardized selection differential for annual reproductive investment g on the mean of g in a pike population size-selectively exploited by anglers at varying intensities (Table 1). Positive (negative) selection pressures are expected to increase (decrease) annual reproductive investment. Filled circles along the horizontal axis indicate the evolutionarily stable strategies at which selection pressures vanish. These vary with the maximum angling effort per area (u; unit h ha⁻¹ year⁻¹), with thicker curves corresponding to higher efforts. (B) Dependence of the evolutionarily stable strategy for g on the maximum angling effort per area. Default parameter values are listed in Table A1.

Figure 4

Influence of different minimum-size limits on the standardized selection differential for annual reproductive investment in a pike population size-selectively exploited by anglers. These vary with the maximum angling effort per area (u; unit h ha⁻¹ year⁻¹), with thicker curves corresponding to higher efforts. In the figure, the average value of annual reproductive investment g was the default value 0.1 at which the selection differential on g vanishes in the absence of angling pressure.

Figure 5

Influence of removed density dependence of either somatic growth (equation 6), relative fecundity (equation 7), or natural mortality (equations 11 and A1) relative to the baseline case with density dependence. Average values from empirical studies (Craig and Kipling 1983; Kipling 1983a) were used in density-independent cases, assuming (A) h = 18.0 cm and (B) h = 16.0 cm in equation (6), exp(−ρ) = 0.79 in equation (7), or M_b = 0.23 in equation (11). As in Fig. 3, the influence of the mean annual reproductive investment g in the resident condition on the standardized selection differential in a pike population size-selectively exploited by anglers was examined. The maximum angling effort per area was set at u = 100 h ha⁻¹ year⁻¹.

Figure 6

Influence of stochastic variations in the stock-recruitment relationship on (A) abundances of pike aged 1 year and older and (B) standardized selection differentials. We assumed multiplicative lognormally distributed fluctuations around the deterministic recruitment in equation (8), , where ν is drawn randomly from a normal distribution with mean 0 and standard deviation σ = 0.5. The maximum angling effort per area was set at u = 100 h ha⁻¹ year⁻¹.

Figure 7

Sensitivity analysis of standardized selection differentials with respect to parameters that determine the dynamics of a pike population size-selectively exploited by anglers. Black (white) bars depict the relative change in standardized selection differentials when the corresponding parameter is increased (decreased) by 5%. For easier reference, the dashed vertical lines indicate the ±5% range for the relative change in standardized selection differentials. Default parameter values are listed in Table A1.