five

Replication Data for: Checklist of the Baturité Mountain Environmental Protection Area, Ceará, Brazil

收藏
doi.org2024-11-18 更新2025-01-15 收录
下载链接:
https://doi.org/10.48331/scielodata.5ZLMNF
下载链接
链接失效反馈
官方服务:
资源简介:
The present work carried out an inventory of species from the Baturité Mountain Environmental Protection Area. Five kingdoms of living beings were registered through the analysis of 135 publications and the online platform of the virtual herbarium of the Rio de Janeiro Botanical Garden, providing data on occurrence, conservation status, endemism and exotic and migratory species, resulting in the compilation of 1,338 tax distributed across nine phyla, 20 classes, 92 orders and 260 families, with 672 species belonging to the Animalia Kingdom, 654 species from the Plantae Kingdom, 10 species from the Fungi Kingdom, one species from the Monera Kingdom and one species from the Protist Kingdom. A total of 206 endemic species to the Brazilian territory and 110 nationally and internationally threatened species were identified, in addition to 39 species of exotic animals and plants from the Brazilian territory and 33 migratory birds. These numbers highlight the Baturité Mountain EPA as a priority preservation area of extreme biological importance, exposing the great biodiversity and distribution of these taxa in this relictual forest, facilitating access to such information for dissemination and scientific research, as well as the conservation and preservation of the biodiversity of this Protected Area in the face of the current overexploitation of natural resources.

本研究对巴图里特山环境保护区内的物种进行了全面梳理。通过分析135篇出版物以及里约热内卢植物园虚拟标本馆的在线平台,记录了生物的五个界,包括物种的分布、保护状况、特有性以及外来和迁徙物种的数据。最终汇编了1,338个物种,涵盖九个门、二十个纲、九十二个目和二百六十个科,其中动物界有672种,植物界有654种,真菌界有10种,原核界有1种,原生生物界有1种。此外,还识别出206种巴西特有物种和110种国内外濒危物种,以及来自巴西领土的39种外来动植物和33种候鸟。这些数据凸显了巴图里特山环境保护区作为具有极高生物保护优先性的区域,揭示了这些生物类群在此遗迹森林中的巨大生物多样性和分布情况,有助于此类信息的传播和科学研究的开展,同时为应对当前自然资源过度开发,保护该保护区生物多样性提供了有力支持。
提供机构:
SciELO Data
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作