University of Delaware, School of Marine Science and Policy, Newark, DE, 19716, USA.
Commonwealth Scientific and Industrial Research Organisation, Natural Systems Modelling Group, Data61, Eveleigh, NSW, 2015, Australia.
Sci Data. 2024 May 22;11(1):521. doi: 10.1038/s41597-024-03348-3.
Fish spawning locations are a crucial input into fisheries management and conservation plans, and many stocks are especially sensitive to the environmental conditions within these localized zones. Globally collated data on spawning locations across many species has been unavailable, hindering global stock assessments and analyses of sustainable development and global environmental change. To address this, we created a geocoded fish spawning dataset using qualitative spawning information from FishBase and Science and Conservation of Fish Aggregations (SCRFA). We cleaned and geocoded the spawning locations of 1,045 marine fish species into 2,931 regions. Each spawning region is defined by one or more polygons, and most spawning regions are associated with spawning months. The resulting dataset covers oceans globally. This dataset will be useful to scientists studying marine fish population dynamics and their interactions with the physical environment on regional to large scales.
鱼类产卵地是渔业管理和保护计划的关键输入因素，许多种群对这些局部区域的环境条件特别敏感。全球范围内，许多物种的产卵地数据都无法获得，这阻碍了对全球鱼类种群的评估以及对可持续发展和全球环境变化的分析。为了解决这个问题，我们利用 FishBase 和鱼类聚群的科学和保护（SCRFA）中的定性产卵信息创建了一个地理编码鱼类产卵数据集。我们对 1045 种海洋鱼类的产卵地点进行了清理和地理编码，将其归入 2931 个区域。每个产卵区域由一个或多个多边形定义，大多数产卵区域都与产卵月份有关。由此产生的数据集涵盖了全球的海洋。该数据集将对研究海洋鱼类种群动态及其与大区域物理环境相互作用的科学家非常有用。
