The Difficulty of Predicting Evolutionary Change in Response to Novel Ecological Interactions: A Field Experiment with Anolis Lizards

Timothy J. Thurman, Todd M. Palmer, Jason J. Kolbe, Arash M. Askary, Kiyoko M. Gotanda, Oriol Lapiedra, Tyler R. Kartzinel, Naomi Man In’T Veld, Liam J. Revell, Johanna E. Wegener, Thomas W. Schoener, David A. Spiller, Jonathan B. Losos, Robert M. Pringle, Rowan D.H. Barrett

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)537-556
Number of pages20
JournalAmerican Naturalist
Volume201
Issue number4
DOIs
StatePublished - Apr 1 2023

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics

Keywords

  • adaptation
  • experimental evolution
  • parallel evolution
  • species in-teractions

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