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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
agricultural and biological sciences
The Difficulty of Predicting Evolutionary Change in Response to Novel Ecological Interactions: A Field Experiment with Anolis Lizards
American Naturalist, Volume 201, No. 4, Year 2023
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Description
Determining whether and how evolution is predictable is an important goal, particularly as anthropogenic disturbances lead to novel species interactions that could modify selective pres-sures. Here, we use a multigeneration field experiment with brown anole lizards (Anolis sagrei) to test hypotheses about the predictabil-ity of evolution. We manipulated the presence/absence of predators and competitors of A. sagrei across 16 islands in the Bahamas that had preexisting brown anole populations. Before the experiment and again after roughly five generations, we measured traits related to lo-comotor performance and habitat use by brown anoles and used double-digest restriction enzyme–associated DNA sequencing to estimate genome-wide changes in allele frequencies. Although previous work showed that predators and competitors had characteristic effects on brown anole behavior, diet, and population sizes, we found that evolutionary change at both phenotypic and genomic levels was diffi-cult to forecast. Phenotypic changes were contingent on sex and habitat use, whereas genetic change was unpredictable and not measur-ably correlated with phenotypic changes, experimental treatments, or other environmental factors. Our work shows how differences in ecological context can alter evolutionary outcomes over short timescales and underscores the difficulty of forecasting evolutionary responses to multispecies interactions in natural conditions, even in a well-studied system with ample supporting ecological information. © 2023 The University of Chicago.
Authors & Co-Authors
Thurman, Timothy J.
Canada, Montreal
Université Mcgill
United States, Washington, D.c.
Smithsonian Tropical Research Institute
United States, Little Rock
University of Arkansas for Medical Sciences
Palmer, Todd M.
United States, Gainesville
University of Florida
Askary, Arash M.
Canada, Montreal
Université Mcgill
Kartzinel, Tyler R.
United States, Providence
Brown University
Spiller, David A.
United States, Davis
University of California, Davis
Losos, Jonathan B.
United States, St. Louis
Washington University in St. Louis
Pringle, Robert M.
United States, Princeton
Princeton University
Barrett, Rowan D.H.
Canada, Montreal
Université Mcgill
Statistics
Citations: 2
Authors: 8
Affiliations: 13
Identifiers
Doi:
10.1086/723209
ISSN:
00030147
Research Areas
Genetics And Genomics
Study Design
Cross Sectional Study
Study Approach
Quantitative