five

The paleobiologic implications of modern nonmarine ecological gradients

收藏
NIAID Data Ecosystem2026-05-02 收录
下载链接:
http://datadryad.org/dataset/doi%253A10.5061%252Fdryad.pc866t1z7
下载链接
链接失效反馈
官方服务:
资源简介:
In modern nonmarine settings, previous studies have demonstrated the importance of elevation-correlated ecological gradients, but such studies tend to focus on relatively small areas and only one higher taxon. Here, we analyze GBIF occurrence records from a wide variety of taxa across the southeastern United States coastal plain. Many taxa display ecological gradients (gradients in proportional or relative abundance) correlated with elevation, distance to the coast, and latitude. These gradients tend to be steepest within a few tens of kilometers near the coast and at elevations less than 25 m. Some taxa, notably terrestrial mammals, do not display gradients correlated with elevation and distance to the coast. The small sample sizes of these groups and their heterogeneous sampling raise concerns about whether sufficient data exists. Coupled with previous studies of these ecological gradients, their common presence over distances of tens to hundreds of kilometers and elevations of tens to hundreds of meters suggests they are likely important in the nonmarine fossil record. Because elevation and distance to the coast change predictably with cycles of accommodation and sediment flux, these ecological gradients are predicted to occur in the nonmarine stratigraphic record, especially through intervals that record transgression or regression. Such gradients will affect the local composition of species associations and occurrences, even in the absence of regional species origination, immigration, and extinction and in the absence of regional change in the structure of ecological gradients. The ordination of taxon counts in stratigraphically limited samples has great potential for establishing their existence. Methods The data was downloaded from GBIF and analyzed through a series of R scripts, as described in README
创建时间:
2024-05-17
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