TEMPORAL VARIATION FAVORS THE EVOLUTION OF GENERALISTS IN EXPERIMENTAL POPULATIONS OF DROSOPHILA MELANOGASTER

In variable environments, selection should favor generalists that maintain fitness across a range of conditions. However, costs of adaptation may generate fitness trade-offs and lead to some compromise between specialization and generalization that maximizes fitness. Here, we evaluate the evolution...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Evolution 2014-03, Vol.68 (3), p.720-728
Hauptverfasser: Condon, Catriona, Cooper, Brandon S., Yeaman, Sam, Angilletta Jr, Michael J.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:In variable environments, selection should favor generalists that maintain fitness across a range of conditions. However, costs of adaptation may generate fitness trade-offs and lead to some compromise between specialization and generalization that maximizes fitness. Here, we evaluate the evolution of specialization and generalization in 20 populations of Drosophila melanogaster experimentally evolved in constant and variable thermal environments for 3 years. We developed genotypes from each population at two temperatures after which we measured fecundity across eight temperatures. We predicted that constant environments would select for thermal specialists and that variable environments would select for thermal generalists. Contrary to our predictions, specialists and generalists did not evolve in constant and spatially variable environments, respectively. However, temporal variation produced a type of generalist that has rarely been considered by theoretical models of developmental plasticity. Specifically, genotypes from the temporally variable selective environment were more fecund across all temperatures than were genotypes from other environments. These patterns suggest certain allelic effects and should inspire new directions for modeling adaptation to fluctuating environments.
ISSN:0014-3820
1558-5646
DOI:10.1111/evo.12296