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Predicting fish recruitment from juvenile abundance and environmental indices

机译:从少年丰度和环境指数预测鱼的补充

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Prediction of year-class strength is a critical challenge for fisheries managers. Theoretically, predictions of recruitment should be better when they are based on estimates of cohort size taken close to the age of recruitment and may improve if the effects of environmental factors that influence pre-recruit mortality are accounted for. In practice, measurement error and difficulties in establishing robust recruitment-environment relationships complicate the picture. For 5 fish stocks of 4 species in 3 ecosystems, we examined the usefulness of indices of juvenile abundance relative to larval abundance for predicting recruitment. Further, we examined whether the use of environmental covariates improved predictions. For 2 of 4 stocks with sufficient data (1 stock did not have larval data), juvenile abundance was a better predictor of recruitment compared to larval indices. For the 2 other stocks, we found that juvenile indices were not superior to larval indices, possibly because of error in the measurement of juvenile abundance. In all 5 of these stocks, regression analysis showed that inclusion of environmental correlates contributed significantly to explaining recruitment variation compared to models based on juvenile indices alone. Further, cross validation showed that forecasts of future recruitment were either improved or qualitatively unchanged by including environmental correlates. This was despite apparent nonstationarity in the recruitment-environment relationships; most of the environmental variables and pre-recruit abundance indices were significantly correlated with recruitment for only parts of the studied period. Such complex responses to environmental changes are difficult to anticipate, yet the environmental information should not be ignored altogether.
机译:对渔业管理者来说,预测年级强度是一个严峻的挑战。从理论上讲,对招募的预测应基于与招募年龄相近的队列规模的估计而更好,并且如果考虑到影响招募前死亡率的环境因素的影响,则可能会有所改善。在实践中,测量错误和建立稳固的招聘环境之间的困难使情况变得复杂。对于3个生态系统中4个物种的5种鱼类种群,我们研究了幼鱼丰度相对于幼虫丰度的指数在预测募集方面的有用性。此外,我们检查了使用环境协变量是否可以改善预测。对于4个具有足够数据的种群中的2个(其中1个种群没有幼虫数据),与幼体指数相比,幼虫的丰度是更好的招聘指标。对于其他2只股票,我们发现少年指数不比幼虫指数高,这可能是由于少年丰度测量中的误差所致。在所有这5只股票中,回归分析表明,与仅基于少年指数的模型相比,包含环境相关因素显着有助于解释招聘差异。此外,交叉验证表明,通过纳入环境相关因素,对未来招聘的预测有所改善或在质量上没有变化。尽管招聘与环境之间的关系明显不稳定,但这仍然存在。在大多数研究时期中,大多数环境变量和招募前的丰度指数都与招募显着相关。对环境变化的这种复杂反应很难预料,但是环境信息不应完全被忽略。

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