Regulations of activities and protection levels in marine protected areas of the European Union: A dataset compiled from multiple data sources.

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES Data in Brief Pub Date : 2024-12-04 eCollection Date: 2024-12-01 DOI:10.1016/j.dib.2024.111177
Juliette Aminian-Biquet, Claire Colegrove, Alex Driedger, Nicole Raudsepp, Jennifer Sletten, Timothé Vincent, Virgil Zetterlind, Julia Roessger, Anastasiya Laznya, Natașa Vaidianu, Joachim Claudet, Juliette Young, Barbara Horta E Costa
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Abstract

The dataset gathers available regulations of human activities and protection levels of Marine Protected Areas (MPAs) of the European Union (EU). The MPA list and polygons were extracted from the MPA database of the European Environment Agency (EEA) and completed with available zoning systems (all were filtered for their marine area reported under the Marine Strategy Framework Directive). Fully-overlapping MPAs were merged. In the resulting dataset, MPA features are provided (gathered from EEA, WDPA, ProtectedSeas), including the year of designation, designation types (e.g., national, Natura 2000) and subtypes (e.g., reserves, national parks), database identifiers (WDPA, Natura 2000, OSPAR, etc.), IUCN categories, and main protection focus. We provide summarized data on maritime activities that overlap with MPA polygons from two types of datasets: activities-focused datasets (national marine spatial plans, and additional European and regional databases, like EMODnet) and MPA-focused datasets gathering data from management plans (ProtectedSeas, expert-based assessments about OSPAR and Portuguese MPAs). This dataset therefore compiles data that could be gathered from accessible legal frameworks regarding aquaculture, fisheries, anchoring, infrastructures (including harbors and renewable energy), mining, transport, coastal land-based uses (desalinization, sewage plants) and other non-extractive uses (e.g., recreational), making them readily accessible. Using the MPA Guide classification system, we computed two scenarios of potential impact for each activity, which were used to assess two scenarios of protection levels per MPA. Some MPAs could not be associated with any MPA features, regulations, or protection levels. Finally, we detail the protocol to match information from multiple databases (e.g., with MPA polygons formatted differently) and provide a quality check by comparing this dataset to previous assessments. This dataset was used to analyze MPAs' protection levels across countries, regions and MPA features (e.g., IUCN categories, designations). It was also used to investigate the sources of information available and the levels of regulations for each maritime activity in EU MPAs. This dataset can therefore be used for further analyses on the use of EU MPAS to regulate activities and to compare with future assessments or with additional data we did not have access to (e.g., gathered at national scale). Such research is crucial to plan and monitor the implementation of the EU 2030 Biodiversity Strategy, targeting 10% of strictly protected MPAs in each sea region.

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欧盟海洋保护区的活动法规和保护水平:从多个数据源汇编的数据集。
该数据集收集了欧盟(EU)现有的人类活动法规和海洋保护区(MPAs)保护水平。MPA列表和多边形是从欧洲环境署(EEA)的MPA数据库中提取出来的,并使用可用的分区系统完成(根据海洋战略框架指令对其海洋区域进行了过滤)。完全重叠的海洋保护区被合并。在结果数据集中,提供了MPA特征(收集自EEA, WDPA, ProtectedSeas),包括指定年份,指定类型(例如,国家,Natura 2000)和子类型(例如,保护区,国家公园),数据库标识符(WDPA, Natura 2000, OSPAR等),IUCN类别和主要保护重点。我们从两种类型的数据集提供了与海洋保护区多边形重叠的海洋活动的汇总数据:以活动为重点的数据集(国家海洋空间计划,以及其他欧洲和区域数据库,如EMODnet)和以海洋保护区为重点的数据集,收集来自管理计划的数据(ProtectedSeas,关于OSPAR和葡萄牙海洋保护区的专家评估)。因此,该数据集汇编了可从有关水产养殖、渔业、锚泊、基础设施(包括港口和可再生能源)、采矿、运输、沿海陆基用途(脱盐、污水处理厂)和其他非采掘用途(如娱乐)的无障碍法律框架中收集的数据,使其易于获取。利用MPA指南分类系统,我们计算了每项活动的两种潜在影响情景,并使用这两种情景来评估每MPA的两种保护水平。一些海洋保护区不能与任何海洋保护区的特征、法规或保护水平相关联。最后,我们详细介绍了匹配来自多个数据库的信息的协议(例如,具有不同格式的MPA多边形),并通过将该数据集与先前的评估进行比较来提供质量检查。该数据集用于分析不同国家、地区和MPA特征(例如,IUCN类别、名称)的海洋保护区保护水平。它还用于调查现有资料的来源和欧盟海洋保护区内每项海洋活动的规章水平。因此,该数据集可用于进一步分析欧盟海洋保护区管理活动的使用情况,并与未来的评估或我们无法获得的其他数据(例如,在国家范围内收集的数据)进行比较。此类研究对于规划和监测欧盟2030年生物多样性战略的实施至关重要,该战略的目标是在每个海洋区域内严格保护10%的海洋保护区。
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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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