Many fish species depend on migration for various parts of their life cycle. Well-known examples include diadromous fish such as salmon and eels that need both fresh water and salt water to complete their life cycle. Migration also occurs within species that depend only on fresh water. In recent decades, anthropogenic pressures on freshwater systems have increased greatly, and have resulted, among other effects, in drastic habitat fragmentation. Fishways have been developed to mitigate the resulting habitat fragmentation, but these are not always effective. To improve fishway efficiency, the variety of navigation cues used by fish must be better understood: fish use a multitude of sensory inputs ranging from flow variables to olfactory cues. The reaction of a fish is highly dependent on the intensity of the cue, the fish species involved, and individual traits. Recently developed monitoring technologies allow us to gain insights into different combinations of environmental and physiological conditions. By combining fish behavioural models with environmental models, interactions among these components can be investigated. Several methods can be used to analyse fish migration, with state-space models, hidden Markov models, and individual-based models potentially being the most relevant since they can use individual data and can tie them to explicit spatial locations within the considered system. The aim of this review is to analyse the navigational cues used by fish and the models that can be applied to gather knowledge on these processes. Such knowledge could greatly improve the design and operation of fishways for a wider range of fish species and conditions.

中文翻译：

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在鱼道附近寻找导航线索

许多鱼类在其生命周期的各个阶段都依赖于洄游。众所周知的例子包括鲑鱼和鳗鱼等产鱼鱼类，它们需要淡水和咸水来完成其生命周期。迁徙也发生在仅依赖淡水的物种内。近几十年来，淡水系统的人为压力大大增加，并导致栖息地急剧破碎化等影响。人们开发了鱼道来减轻由此产生的栖息地破碎化，但这些并不总是有效。为了提高鱼道效率，必须更好地理解鱼类使用的各种导航线索：鱼类使用从流量变量到嗅觉线索的多种感官输入。鱼的反应很大程度上取决于提示的强度、涉及的鱼种和个体特征。最近开发的监测技术使我们能够深入了解环境和生理条件的不同组合。通过将鱼类行为模型与环境模型相结合，可以研究这些组成部分之间的相互作用。可以使用多种方法来分析鱼类迁徙，其中状态空间模型、隐马尔可夫模型和基于个体的模型可能是最相关的，因为它们可以使用个体数据并将其与所考虑系统内的显式空间位置联系起来。本次综述的目的是分析鱼类使用的导航线索以及可用于收集有关这些过程的知识的模型。这些知识可以极大地改善鱼道的设计和操作，以适应更广泛的鱼类种类和条件。