Hull International Fisheries Institute, School of Natural Sciences, University of Hull, Hull, HU6 7RX, UK.
Sci Data. 2024 Nov 22;11(1):1271. doi: 10.1038/s41597-024-04127-w.
Long-term datasets provide context and understanding of complex ecological processes, including temporal variations in species diversity and ecosystem dynamics. This dataset is comprised of body length measurements (mm) of more than 380,000 larval or juvenile fish of 30 species from five English river catchments collected almost monthly over two decades. Such information can be used to determine growth rates, future recruitment success, population structure and compliance with monitoring protocols and conservation objectives. The dataset provides a baseline for analysing the impacts of anthropogenic disturbances such as climate change, pollution and habitat degradation, and, given that many fish populations are size structured with a positive relationship between fish body length and various biological attributes such as swimming ability, survival and fecundity, it will be invaluable for investigating natural and human- induced disturbances.
长期数据集提供了对复杂生态过程的背景和理解，包括物种多样性和生态系统动态的时间变化。本数据集包含了来自英国五个河流流域的 30 种鱼类的超过 38 万个幼虫或幼鱼的体长测量值（mm），这些鱼类是在过去二十年中几乎每月收集的。这些信息可用于确定生长率、未来的补充成功率、种群结构以及对监测协议和保护目标的遵守情况。该数据集为分析人为干扰的影响提供了基线，例如气候变化、污染和生境退化，并且由于许多鱼类种群的大小结构与鱼类体长与各种生物属性（如游泳能力、生存能力和繁殖力）之间存在正相关关系，因此对于调查自然和人为干扰将非常有价值。
