Understanding local plant extinctions before it’s too late: bridging evolutionary genomics with global ecology.

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1111/nph.18718. This is version 3 of this Preprint.

Add a Comment

You must log in to post a comment.


Comments

There are no comments or no comments have been made public for this article.

Downloads

Download Preprint

Authors

Moises Exposito-Alonso 

Abstract

Understanding evolutionary genomic and population processes within a species range is key to anticipating the extinction of plant species before it is too late. However, most models of biodiversity risk projections under global change do not account for the genetic variation and local adaptation of different populations. Population diversity is critical to understanding extinction because different populations may be more or less susceptible to global change and, if lost, would reduce the total diversity within a species. Two new modeling frameworks advance our understanding of extinction from a population and evolutionary angle: Rapid climate change-driven disruptions in population adaptation are predicted from associations between genomes and local climates. Furthermore, losses of population diversity from global land use transformations are estimated by scaling relationships of species' genomic diversity with habitat area. Overall, these global eco-evolutionary methods advance the predictability—and possibly the preventability—of the ongoing extinction of plant species.

DOI

https://doi.org/10.32942/X2V885

Subjects

Biodiversity, Bioinformatics, Ecology and Evolutionary Biology, Genetics and Genomics, Life Sciences, Plant Sciences

Keywords

extinction, genetic diversity, climate change, habitat loss, macrogenetics, genomic offset, biodiversity risk, environmental niche models, mutations-area relationship, landscape genomics

Dates

Published: 2022-12-01 05:10

Last Updated: 2022-12-04 20:31

Older Versions
License

CC-BY Attribution-NonCommercial 4.0 International

Additional Metadata

Conflict of interest statement:
None