Dataset for: Growing industrialization and poor conservation planning challenge natural resources’ management in the Amazon shelf off Brazil

Araujo et al. (2021), based on an extensive compilation of primary and secondary data, assessed the distribution of benthic habitats and spatial extent of the economic activities in Brazil’s Amazon Shelf. The present dataset was developed to support this manuscript providing geospatial data (vector and raster) in geographic latitude/longitude coordinate system (World Geodetic System; datum: WGS84), that included data about: (1) Bathymetry - main bathymetry isobaths; (2) Biodiversity Fauna - species occurrence records of sea turtles, marine mammals, marine and shore birds, and fishery resources; (3) Biodiversity Megahabitats - distribution of the main benthic megahabitats, mangrove and shoreline types; (4) Fisheries Activities - artisanal and industrial fishing; (5) Human Population - density population; (6) Infrastructure - seaports, waterway, railway, airports and marine traffic; (7) Mining Activities - mining blocks of Pará and Maranhão basins; (8) Oil & Gas Activities - drilling wells, sedimentary Basins and blocks (offered, returned, under concession); (9) Protected Areas - Protected Areas, Coastal and Marine Protected Areas (CMPA) and Priority Areas for Biodiversity Conservation, including Planned CMPA; (10) River Plume - Amazon River plume distribution. Additionally, the dataset includes two excel files, one with information about data sources and processing and another with the biodiversity database.

Araujo 等人（2021年）基于对大量一、二手数据的广泛整理，评估了巴西亚马逊大陆架底栖生境的分布及其经济活动的空间范围。本数据集旨在支持该论文的撰写，提供了地理坐标系统（世界大地测量系统；基准：WGS84）中的地理纬度/经度坐标系统的地理空间数据（矢量数据和栅格数据），其中包括以下数据：1）地形学 - 主要地形等深线；2）生物多样性动物群 - 海龟、海洋哺乳动物、海洋和海岸鸟类以及渔业资源的物种出现记录；3）生物多样性巨型生境 - 主要底栖巨型生境、红树林和海岸类型分布；4）渔业活动 - 手工业和工业捕鱼；5）人类人口 - 人口密度；6）基础设施 - 海港、水道、铁路、机场和海上交通；7）采矿活动 - 巴拉那和马拉尼昂盆地采矿区块；8）石油与天然气活动 - 钻井井口、沉积盆地和区块（提供、退还、特许经营下）；9）保护区 - 保护区、海岸和海洋保护区（CMPA）以及生物多样性保护优先区域，包括计划中的CMPA；10）河流涌流 - 亚马逊河流涌流分布。此外，数据集还包括两个Excel文件，一个包含数据来源和处理信息，另一个包含生物多样性数据库。