five

Data from: Multi-taxon inventory reveals highly consistent biodiversity responses to ecospace variation

收藏
DataCite Commons2026-03-04 更新2026-04-25 收录
下载链接:
https://datadryad.org/dataset/doi:10.5061/dryad.sf7m0cg30
下载链接
链接失效反馈
官方服务:
资源简介:
Amidst the global biodiversity crisis, identifying general principles for variation in biodiversity remains a key challenge. Scientific consensus is limited to a few macroecological rules, such as species richness increasing with area, which provide limited guidance for conservation. In fact, few agreed ecological principles apply at the scale of sites or reserve management, partly because most community-level studies are restricted to single habitat types and species groups. We used the recently proposed ecospace framework and a comprehensive data set for aggregating environmental variation to predict multi-taxon diversity. We studied richness of plants, fungi, and arthropods in 130 sites representing the major terrestrial habitat types in Denmark. We found the abiotic environment (ecospace position) to be pivotal for the richness of primary producers (vascular plants, mosses, and lichens) and, more surprisingly, little support for ecospace continuity as a driver. A peak in richness at intermediate productivity adds new empirical evidence to a long-standing debate over biodiversity responses to productivity. Finally, we discovered a dominant and positive response of fungi and insect richness to organic matter accumulation and diversification (ecospace expansion). Two simple models of producer and consumer richness accounted for 77 % of the variation in multi-taxon species richness suggesting a significant potential for generalization beyond individual species responses. Our study widens the traditional conservation focus on vegetation and vertebrate populations unravelling the importance of diversification of carbon resources for diverse heterotrophs, such as fungi and insects.
提供机构:
Dryad
创建时间:
2020-06-19
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