Finnish Environment Institute (Syke), Helsinki, Finland.
Finnish Natural History Museum (LUOMUS), University of Helsinki, Helsinki, Finland.
Sci Data. 2024 Nov 27;11(1):1297. doi: 10.1038/s41597-024-04092-4.
Since 2004, marine biodiversity inventory data have been systematically collected with diving, video, and benthic sampling methods in Finland. To date, this collection of data consists of more than 194 000 spatially explicit observations, covering more than 280 aquatic genera, representing mainly macroalgae, vascular plants, water mosses, and invertebrates. We describe the data collection and storage methods, data extraction from national databases, and provide potential users a curated, open-access version of the inventory data. Additionally, examples of data applications and discussion on potential limitations are provided. This extensive dataset can be used in ecological and biogeographical studies to provide general descriptions of biodiversity patterns and species distributions, as well as in more applied studies to support marine management, conservation, and sustainable use of marine areas. The sampling strategy and high spatial and taxonomic resolution allow for statistical modelling, which further increases the usability of the data in research, for instance in identifying key biodiversity areas, estimating biodiversity loss, and assessing efficiency of conservation.
自 2004 年以来,芬兰一直采用潜水、录像和底栖抽样方法系统地收集海洋生物多样性清单数据。迄今为止,这些数据包括 194000 多个具有空间明确观测值,涵盖了超过 280 种水生属,主要代表藻类、维管植物、水藓和无脊椎动物。我们描述了数据收集和存储方法、从国家数据库中提取数据的方法,并为潜在用户提供了经过策展的、开放获取的清单数据版本。此外,还提供了数据应用的示例和对潜在限制的讨论。这个广泛的数据集可用于生态和生物地理学研究,以提供生物多样性模式和物种分布的一般描述,也可用于更具应用意义的研究,以支持海洋管理、保护和可持续利用海洋区域。采样策略和高空间和分类分辨率允许进行统计建模,这进一步提高了数据在研究中的可用性,例如,在确定关键生物多样性区域、估计生物多样性损失和评估保护效率方面。