Aquaculture 2022

February 28 - March 4, 2022

San Diego, California

WITHIN-GENERATION RESPONSES TO SELECTION ACROSS HABITAT HETEROGENEITIES – WHEN, WHERE, AND WHY DOES IT MATTER?

 

Matthew Hare* , Honggang Zhao, Avi Simon

 

Department of Natural Resources & the Environment

Cornell University

Ithaca, NY 14850 , USA

mph75@cornell.edu

 



 

Evolutionary adaptation is a primary mechanism through which species can avoid extinction from climate change effects. When and where the multigenerational process of local a daptation will be rapid enough to prevent extinction is an important question. Within a life span,  adaptive plasticity can generate phenotypic differentiation at microgeographic scales where gene flow prevents local adaptation.  Natural selection (differential survival)  also causes differentiation of genotype frequencies across habitat heterogeneities. At large spatial scales relative to the average dispersal distance this can lead to local adaptation, but at smaller spatial scales gene flow erases the differentiation each generation so there is no cumulative adaptation. Population genetic theory largely ignores the impact of selection within a cohort under these conditions, but that does not mean there is no impact. F or high-fecundity species experiencing high early mortality (many marine species), a considerable portion of microspatial differentiation in each cohort can be due to within-generation selection . We refer to this as “cohort adaptation” because it can increase population fitness . Traits experiencing spatially heterogeneous selection are likely to be polygenic , with small contributions to trait variation from many loci, making detection challenging . In this presentation we will review empirical demonstrations of within-generation selection, outline the life history and environmental contexts where cohort adaptation is more likely to be important, and discuss why this relatively unstudied mechanism may be important in the context of selective breeding for aquaculture as well as for predicting population responses to climate change.