Causes and consequences of signal divergence across species


I am currently a postdoctoral researcher at Uppsala University working with Anna Qvarnström. In 2012, I completed my PhD in Trevor Price's lab at the University of Chicago and, from 2012-2014, completed a NSF research fellowship in Anna Qvarnström's lab in Uppsala.

My research explores the causes and consequences of signal divergence across species. I've used a variety of songbird systems to tackle these issues. Songbirds are ideal subjects, both because of the diversity of species and because most species produce multiple signals (alarm calls) whose acoustic form is innate and others that are learned (songs), which has allowed me to to explore the social and ecological factors promoting signal divergence versus stasis and those promoting different mechanisms of signal recognition. What factors lead to signal divergence across species? How do individuals come to recognize the (variable) signals of other species? What mechanisms focus learning onto relevant signals?

1) Associative learning and the evolution of alarm calls.

During my PhD work, I studied the formation of cooperative anti-predator groups comprised of individuals from many species, called mobs, that are formed when surrounding birds are attracted to characteristic calls signaling alarm. In multi-species communities, the formation of mobs depends on individuals from one species recognizing the calls produced by co-occurring species.

My work demonstrated that calls generally vary greatly across even closely related species (Wheatcroft and Price 2013, 2014), potentially because they are also used in a variety of species-specific contexts that may promote divergence across species (Wheatcroft accepted). Despite dissimilarity across species, a combination of learning (Wheatcroft and Price 2013) and recognition of common acoustic features allows widespread communication (Wheatcroft and Price 2013, 2014; Wheatcroft accepted).

My work also addressed the evolutionary rate of alarm calls using recently developed methods to compare rates of evolution of multiple traits shared by the same species. We demonstrated that the number and variety of receivers may strongly influence the rate and nature of signal divergence: alarm calls directed at a narrower set of receivers evolve at slower rates than those directed at a more diverse set of receivers (Wheatcroft and Price 2014). In extreme cases, communication between a pair of species may even promote call convergence through copying or mimicry (2013).

2) Causes of song divergence

Coming soon...

3) Innate learning predispositions and song recognition.

Coming soon...