Increasing our ability to predict contemporary evolution
Patrik Nosil, Samuel M. Flaxman, Jeffrey L. Feder, Zachariah Gompert
Abstract
Classic debates concerning the extent to which scientists can predict evolution have gained new urgency as environmental changes force species to adapt or risk extinction. We highlight how our ability to predict evolution can be constrained by data limitations that cause poor understanding of deterministic natural selection. We then emphasize how such data limits can be reduced with feasible empirical effort involving a combination of approaches.
Topics & Concepts
Computer scienceNatural selectionSelection (genetic algorithm)Extinction (optical mineralogy)Data scienceRisk analysis (engineering)Machine learningBiologyMedicinePaleontologyEvolution and Genetic DynamicsEvolutionary Game Theory and CooperationSpecies Distribution and Climate Change