Catalysis Meeting

Anthropogenic Sensory Stimuli as Drivers of Evolution: A conceptual synthesis and roadmap for an integrated citizen-science research network

PI(s): Caren Cooper (Cornell Lab of Ornithology)
Clinton D Francis (NESCent)
Jesse Barber (Boise State University)
Start Date: 15-Nov-2013
End Date: 30-Nov-2014
Keywords: adaptation, management of natural populations, phenotypic plasticity, anthropogenic effects, biodiversity

Differences in the complexity and timing of bird song and reproduction evolved in conjunction with organisms’ ability to perceive reliable environmental cues. Globally ubiquitous forms of sensory stimuli that accompany human activities, such as anthropogenic light and noise, inhibit organisms’ sensory abilities. New research suggests that these stimuli can reorganize communities by interfering with species-specific abilities to perceive time cues, habitat features, and auditory and visual signals from other organisms. Given the predominance and strength of their ecological effects, artificial light and noise have a strong potential to function as agents of selection that drive divergence in phenological traits and sensory and signaling systems, but investigations on the role of these stimuli on contemporary evolution are nearly absent. The Catalysis meeting will launch an interdisciplinary network for studying the evolutionary consequences of sensory stimuli broadly, but with immediate emphasis on the phenology of avian mating and reproductive behavior. Synthesis of tools and existing data across citizen science projects, where the public reports on nest monitoring, song recordings, and measurements of sensory stimuli, will allow the study of birds and sensory stimuli across broad scales but at fine resolution. The Catalysis Meeting objectives are to create a network for: (i) Conceptual synthesis to improve how we examine evolutionary responses to human-generated sensory stimuli; (ii) Methodological synthesis by integrating citizen science tools and protocols across projects; (iii) Data synthesis through re-purposing existing data from established citizen science networks (NestWatch and Globe At Night) and other data resources.