Evaluating a possible new paradigm for recruitment dynamics: predicting poor recruitment for striped bass (Morone saxatilis) from an environmental variable

Understanding what causes large year classes and predicting them has been called the holy grail of fisheries science, one last great unanswered questions. Recruitment prediction, or forecasting, is an important component for setting fishery catch limits. We propose a new approach, “poor-recruitment paradigm”, recruitment using environmental variables. This approach hypothesizes that it easier to predict poor rather than good because variable affects only when its value extreme (lethal); otherwise, may be benign not influence recruitment. Thus, necessitates all conditions harmful some especially favorable; recruitment, however, requires extreme. idea was evaluated river discharge data striped bass (Morone saxatilis) from seven major spawning tributaries Chesapeake Bay. Low spring reliably resulted in bass. Specifically, rivers, median standard deviation were lower low compared average high; additionally, proportion years with higher high discharge. The consistent predictability potential improve stock projections, therefore, advice.