Browsing by Author "Muhling, Barbara"

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    Reproductive resilience: a paradigm shift in understanding spawner-recruit systems in exploited marine fish
    (WILEY, 2017) Lowerre Barbieri, Susan; DeCelles, Greg; Pepin, Pierre; Catalan, Ignacio A.; Muhling, Barbara; Erisman, Brad; Cadrin, Steven X.; Alos, Josep; Ospina Alvarez, Andres; Stachura, Megan M.; Tringali, Michael D.; Burnsed, Sarah Walters; Paris, Claire B.
    A close relationship between adult abundance and stock productivity may not exist for many marine fish stocks, resulting in concern that the management goal of maximum sustainable yield is either inefficient or risky. Although reproductive success is tightly coupled with adult abundance and fecundity in many terrestrial animals, in exploited marine fish where and when fish spawn and consequent dispersal dynamics may have a greater impact. Here, we propose an eco-evolutionary perspective, reproductive resilience, to understand connectivity and productivity in marine fish. Reproductive resilience is the capacity of a population to maintain the reproductive success needed to result in long-term population stability despite disturbances. A stock's reproductive resilience is driven by the underlying traits in its spawner-recruit system, selected for over evolutionary timescales, and the ecological context within which it is operating. Spawner-recruit systems are species specific, have both density-dependent and fitness feedback loops and are made up of fixed, behavioural and ecologically variable traits. They operate over multiple temporal, spatial and biological scales, with trait diversity affecting reproductive resilience at both the population and individual (i.e. portfolio) scales. Models of spawner-recruit systems fall within three categories: (i) two-dimensional models (i.e. spawner and recruit); (ii) process-based biophysical dispersal models which integrate physical and environmental processes into understanding recruitment; and (iii) complex spatially explicit integrated life cycle models. We review these models and their underlying assumptions about reproductive success vs. our emerging mechanistic understanding. We conclude with practical guidelines for integrating reproductive resilience into assessments of population connectivity and stock productivity.