An ecological connectivity dataset for Black Sea obtained from sea currents

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES Data in Brief Pub Date : 2025-02-01 DOI:10.1016/j.dib.2024.111268
Nikolaos Nagkoulis , Christos Adam , Ioannis Mamoutos , Stelios Katsanevakis , Antonios D. Mazaris
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Abstract

Incorporating ecological connectivity into spatial conservation planning is increasingly recognized as a key strategy to facilitate species movements, especially under changing environmental conditions. However, obtaining connectivity data is challenging, especially in the marine realm. Sea currents are essential for exploring marine structural connectivity, but transforming sea current data into spatial connectivity matrices involves complex and resource-intensive processing steps to ensure accuracy and usability. Here, an applied a graph-based methodology has been developed to transform current data into formats suitable for delineating ecological corridors and applied to Black Sea. The dataset produced can be integrated to spatial conservation prioritization tools to incorporate connectivity in the analysis. This approach involved converting current centroids into points and projecting current directions and magnitudes onto a nearest-neighbour graph connecting these points. Using open-source data from the Copernicus Black Sea Physics Reanalysis dataset from 1993 to 2023, a high-resolution dataset of graph objects (edge lists) and shapefiles (points and edges) for the Black Sea has been created. Analyses were conducted in R, and the algorithm developed to produce the data is accessible on Zenodo. The resulting datasets are compatible with multiple software platforms (e.g., R, Python, and QGIS). A total of 17 datasets are provided from 1993 to 2023: twelve for monthly, four for seasonal, and one for yearly aggregation, supporting diverse spatial and temporal analysis needs. Overall, the datasets can be used to analyse connectivity patterns across the entire Black Sea or focus on specific regions, particularly useful for ecological modelling, and environmental protection purposes.

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黑海海流生态连通性数据集。
将生态连通性纳入空间保护规划越来越被认为是促进物种迁移的关键策略,特别是在不断变化的环境条件下。然而,获取连接数据具有挑战性,特别是在海洋领域。海流对于探索海洋结构连通性至关重要,但将海流数据转换为空间连通性矩阵涉及复杂且资源密集型的处理步骤,以确保准确性和可用性。在这里,一种基于图形的方法已经开发出来,将当前数据转换为适合描绘生态走廊的格式,并应用于黑海。生成的数据集可以集成到空间保护优先级工具中,以将连通性纳入分析。这种方法包括将当前的质心转换为点,并将当前的方向和大小投影到连接这些点的最近邻图上。利用1993年至2023年哥白尼黑海物理再分析数据集的开源数据,创建了黑海图形对象(边缘列表)和形状文件(点和边)的高分辨率数据集。分析是在R中进行的,用于生成数据的算法可以在Zenodo上访问。生成的数据集与多个软件平台(如R、Python和QGIS)兼容。1993 - 2023年共提供了17个数据集,其中12个为月度数据集,4个为季节性数据集,1个为年度数据集,支持不同的时空分析需求。总的来说,这些数据集可以用来分析整个黑海的连通性模式,或者专注于特定地区,对生态建模和环境保护目的特别有用。
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来源期刊
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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