Stock and recruitment: generalizations about maximum reproductive rate, density dependence, and variability using meta-analytic approaches

Abstract

Myers, R. A. 2001. Stock and recruitment: generalizations about maximum reproductive rate, density dependence, and variability using meta-analytic approaches. -ICES Journal of Marine Science, 58: 937-951.I describe the development and application of meta-analytic techniques to understand population dynamics. These methods have been applied to a compilation of over 700 populations of fish, which includes multivariate time-series of egg production, population size, natural mortality, and anthropogenic mortality. The key requirements of this approach are to make all units comparable and to make all model parameters random variables that describe the variation among populations. Parameters are then estimated using hierarchical Bayesian or classical mixed models. This approach allows patterns to be determined that are not detected otherwise. For example, the maximum annual reproductive rate is relatively constant for all species examined: between 1 and 7 replacement spawners are produced per spawner per year at low population size. Using these approaches, I also show a 20-fold variation in carrying capacity per unit area for cod, and a decrease in carrying capacity with temperature. Recruitment variability generally increases at low population sizes, for species with higher fecundity, for populations at the edge of their range, and in regions with less oceanographic stability. The spatial scale of recruitment correlations for marine species is approximately 500 km, compared with less than 50 km for freshwater species; anadromous species fall between these two scales. Recruitment variability generally decreases with age for marine demersal fish, but often increases with age for some salmonids.2001 International Council for the Exploration of the Sea

The stochastic nature of larval connectivity among nearshore marine populations

“…Connectivity among nearshore populations on annual time scales will not be well modeled by using mean field approaches such as advection/diffusion models, which will make the management of nearshore fisheries difficult (28). Fisheries scientists have long tried to explain the sources of recruitment variability so that recruitment can be predicted knowing only adult population size and environmental factors (6,7,12,28,29). Our work indicates that local rates of larval settlement will be showing the alongshore source locations (y axis), settling times (x axis), and density (color) of larvae that successfully settle anywhere within the model domain (a), the ''arrival density'' showing the density (color) of arrival locations for settlers (y axis) from all source locations and settling times (x axis) (b), and the alongshore wind speed for the base case simulation (negative is upwelling favorable) (c).…”

“…largely decoupled from local stocks, suggesting that stochastic larval connectivity provides an unexplored source of unresolvable noise in observed stock-recruitment relationships (28,29). The packet model introduced here provides a way for assessing the variability in larval connectivity in stock-recruitment models.…”

An evaluation of an iterative harvest strategy for data-poor fisheries using the length-based spawning potential ratio assessment methodology

“…However, these harvest strategies are often 128 data-intensive, and often rely on the output of age-structured assessment models, conditioned 129 on a time-series of catch data, together with an estimate of the current biomass, to provide a 130 recommendation for the adjustment to the TAC. Furthermore, the calculation of biomass-131 based reference points requires detailed information on the biology of the species, including 132 knowledge of the underlying stock-recruitment relationship, which can be difficult to 133 estimate (Hilborn and Walters, 1992;Myers, 2001 Ideally, the SPR target should be such that the spawning stock biomass (SSB) is 206 maintained at a sustainable level, while still providing a reasonable level of catch (Clark, 207 2002). The relationship between SPR and the equilibrium SSB depletion level (%SSB0) is 208 determined by the steepness parameter (often denoted as h) in the stock-recruitment model 209…”

Comment on “Fisheries mismanagement”

“…There is a wealth of literature on recruitment and its variability (see e.g. Myers, 2001) with good reason to suppose it has a clear mode and is right-skewed with a long tail giving lower probability to extreme events. Both the log-normal or gamma distributions have these characteristics and are commonly used in simulation models (e.g.…”