Document Type

Article

Publication Date

2-2023

Abstract

We are in a modern biodiversity crisis that will restructure community compositions and ecological functions globally. Large mammals, important contributors to ecosystem function, have been affected directly by purposeful extermination and indirectly by climate and land-use changes, yet functional turnover is rarely assessed on a global scale using metrics based on functional traits. Using ecometrics, the study of functional trait distributions and functional turnover, we examine the relationship between vegetation cover and locomotor traits for artiodactyl and carnivoran communities. We show that the ability to detect a functional relationship is strengthened when locomotor traits of both primary consumers (artiodactyls, n = 157 species) and secondary consumers (carnivorans, n = 138 species) are combined into one trophically integrated ecometric model. Overall, locomotor traits of 81% of communities accurately estimate vegeta-tion cover, establishing the advantage of trophically integrated ecometric models over single-group models (58 to 65% correct). We develop an innovative approach within the ecometrics framework, using ecometric anomalies to evaluate mismatches in model estimates and observed values and provide more nuance for understanding relationships between functional traits and vegetation cover. We apply our integrated model to five paleontological sites to illustrate mismatches in the past and today and to demonstrate the utility of the model for paleovegetation interpretations. Observed changes in com-munity traits and their associated vegetations across space and over time demonstrate the strong, rapid effect of environmental filtering on community traits. Ultimately, our trophically integrated ecometric model captures the cascading interactions between taxa, traits, and changing environments

Publication Title

PNAS

Volume

120

Issue

7

First Page

e2201947120

DOI of Published Version

10.1073/pnas.2201947120

Publisher

PNAS

Rights

Copyright © 2023 the Author(s)

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Comments

Code and data have been deposited at:
https://doi.org/10.6084/m9.figshare.19358513.v1 (99).

pnas.2201947120.sapp.pdf (1178 kB)
Appendix 01 (PDF)

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