Growth of fish is an important contributor to individual fitness as well as fish production. Explaining and predicting growth variation across populations is thus important from fundamental and applied perspectives, which requires knowledge about the ecological factors involved in shaping growth. To that end, we estimated environment‐dependent von Bertalanffy growth models for 13 gravel pit lake populations of Eurasian perch (Perca fluviatilis) from north‐western Germany. To identify the main drivers of perch growth, we evaluated the performance of 16 different biotic or abiotic lake variables in explaining growth variation among lakes. In addition, we compared growth predictions from the best‐performing model incorporating “complex” variables that require intensive sampling effort, with a model using only “simple”, easily measurable lake variables (e.g. shoreline development factor). The derivation of a simple model aimed at future applications in typically data‐poor inland fisheries, predicting expected growth potential from easily measurable lake variables. A model combining metabolic biomass of predators, maximum depth and shoreline development factor performed best in predicting perch growth variation across gravel pits. All three parameters in this model were positively related to perch growth. The best‐performing simple model consisted only of the shoreline development factor. Length‐at‐age predictions from both models were largely identical, highlighting the utility of shoreline development factor in approximating growth potential of perch in gravel pits similar to our study lakes. Our results can be used to inform fisheries management and restoration efforts at existing or newly excavated gravel pit lakes.

中文翻译：

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砾石坑湖鲈鱼（Perca fluviatilis）生长的环境决定因素以及简单与复杂生态预测因子的相对性能

鱼的生长是个体健康以及鱼生产的重要因素。因此，从基本和应用的角度解释和预测人口的增长差异非常重要，这需要了解影响增长的生态因素。为此，我们估算了欧亚鲈（Perca fluviatilis）的13个砾石坑湖种群的环境依赖性von Bertalanffy生长模型）来自德国西北部。为了确定鲈鱼生长的主要驱动力，我们评估了16种不同的生物或非生物湖泊变量在解释湖泊之间生长差异方面的性能。此外，我们将最佳表现模型的增长预测与需要大量采样工作的“复杂”变量进行了比较，将其与仅使用“简单”，易于测量的湖泊变量（例如海岸线发展因子）的模型进行了比较。推导了一个简单的模型，该模型针对通常在数据贫乏的内陆渔业中的未来应用，并通过易于测量的湖泊变量预测了预期的增长潜力。结合捕食者的代谢生物量，最大深度和海岸线发展因子的模型在预测整个砾石坑中鲈鱼生长变化方面表现最佳。该模型中的所有三个参数均与鲈鱼生长呈正相关。性能最佳的简单模型仅包括海岸线发展因素。两种模型的年龄预测在很大程度上是相同的，这突显了海岸线发展因子在近似类似于我们研究湖泊的砾石坑中鲈鱼生长潜力方面的效用。我们的结果可用于为现有或新开挖的砾石坑湖的渔业管理和恢复工作提供信息。