The bii4africa dataset of faunal and floral population intactness estimates across Africa's major land uses.

The bii4africa dataset of faunal and floral population intactness estimates across Africa's major land uses.
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bii4africa 数据集对非洲主要土地利用的动物和花卉种群完整性进行了估计。

DOI:
10.1038/s41597-023-02832-6
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发表时间:
2024
期刊:
影响因子:
9.8
通讯作者:
Clements HS
Clements HS
中科院分区:
综合性期刊2区
文献类型:
--
作者:
Clements HS

文献摘要

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撒哈拉以南非洲在全球生物多样性数据集中的代表性不足,特别是在土地利用对物种种群丰度的影响方面。为了确保数据的一致性,利用专家启发的最新进展,200名专家使用改进的德尔菲法来估计“完整性评分”:特定土地利用中物种组“完整”参考种群的剩余比例,范围从0(没有剩余的个体)到1(与参考相同的丰度),在极少数情况下,到2(在人类改造的景观中茁壮成长的种群)。由此产生的bii 4africa数据集包含代表撒哈拉以南非洲地区主要土地利用(城市、农田、牧场、种植园、保护区等)的陆生脊椎动物(四足动物:± 5,400种两栖动物、爬行动物、鸟类、哺乳动物)和维管植物(± 45,000种杂类植物、禾本科植物、树木、灌木)的完整性评分。和强度(例如, 大规模与小规模耕地)。该数据集是作为非洲生物多样性完整性指数项目的一部分共同制作的。其他用途包括评估生态系统状况;纠正全球生物多样性指标和地图中的地理/分类偏差;以及为生态系统红色清单提供信息。
Sub-Saharan Africa is under-represented in global biodiversity datasets, particularly regarding the impact of land use on species' population abundances. Drawing on recent advances in expert elicitation to ensure data consistency, 200 experts were convened using a modified-Delphi process to estimate 'intactness scores': the remaining proportion of an 'intact' reference population of a species group in a particular land use, on a scale from 0 (no remaining individuals) to 1 (same abundance as the reference) and, in rare cases, to 2 (populations that thrive in human-modified landscapes). The resulting bii4africa dataset contains intactness scores representing terrestrial vertebrates (tetrapods: ±5,400 amphibians, reptiles, birds, mammals) and vascular plants (±45,000 forbs, graminoids, trees, shrubs) in sub-Saharan Africa across the region's major land uses (urban, cropland, rangeland, plantation, protected, etc.) and intensities (e.g., large-scale vs smallholder cropland). This dataset was co-produced as part of the Biodiversity Intactness Index for Africa Project. Additional uses include assessing ecosystem condition; rectifying geographic/taxonomic biases in global biodiversity indicators and maps; and informing the Red List of Ecosystems.