Related Experiment Video
Updated: Jul 31, 2026

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)
Published on: October 11, 2016
Integration of local and regional species-area relationships from space-time species accumulation
Jason D Fridley1, Robert K Peet, Eddy van der Maarel
1Department of Biology, University of North Carolina, Chapel Hill, NC 27599, USA. fridley@unc.edu
Abstract:
A long-standing observation in community ecology is that the scaling of species richness, as exemplified by species-area curves, differs on local and regional scales. This decoupling of scales may be largely due to sampling processes (the increasing constraint imposed by sampling fewer individuals at fine scales), as distinct from ecological processes, such as environmental heterogeneity, that operate across scales. Removal of the sampling constraint from fine-scale richness estimates should yield species-area curves that behave like those of the regions in which they are embedded, but an effective method for this removal has not been available. We suggest an approach that incorporates the manner in which small areas accumulate species over time as a way to remove the signature of sampling processes from fine-scale species-area curves. We report for three species-rich grasslands from two continents how local plant species richness is distributed through time at multiple, nested spatial scales, and we ask whether sampling-corrected curves reflect the spatial scaling of richness of each larger floristic province. Our analysis suggests that fine-scale values of richness are highly constrained by sampling processes, but once these constraints are removed, the spatial scaling of species richness is consistent from the scale of individuals to that of an entire province.
Related Concept Videos
Distribution and Dispersion
Speciation Rates
Conservation of Small Populations
Conservation of Declining Populations
Area Computation by the Alternative Coordinate Method
Growth Models with Integration: Problem Solving

