title: Predicting the genetic consequences of future climate change: The power of coupling spatial demography, the coalescent, and historical landscape changes.
abstract: OBJECTIVE
  Climate change is a widely accepted threat to biodiversity. Species distribution models (SDMs) are used to forecast whether and how species distributions may track these changes. Yet, SDMs generally fail to account for genetic and demographic processes, limiting population-level inferences. We still do not understand how predicted environmental shifts will impact the spatial distribution of genetic diversity within taxa.
  
  
  METHODS
  We propose a novel method that predicts spatially explicit genetic and demographic landscapes of populations under future climatic conditions. We use carefully parameterized SDMs as estimates of the spatial distribution of suitable habitats and landscape dispersal permeability under present-day, past, and future conditions. We use empirical genetic data and approximate Bayesian computation to estimate unknown demographic parameters. Finally, we employ these parameters to simulate realistic and complex models of responses to future environmental shifts. We contrast parameterized models under current and future landscapes to quantify the expected magnitude of change.
  
  
  RESULTS
  We implement this framework on neutral genetic data available from Penstemon deustus. Our results predict that future climate change will result in geographically widespread declines in genetic diversity in this species. The extent of reduction will heavily depend on the continuity of population networks and deme sizes.
  
  
  CONCLUSIONS
  To our knowledge, this is the first study to provide spatially explicit predictions of within-species genetic diversity using climatic, demographic, and genetic data. Our approach accounts for climatic, geographic, and biological complexity. This framework is promising for understanding evolutionary consequences of climate change, and guiding conservation planning.
authors.affiliation: Biology Department, The City College of New York, New York, New York 10031 USA jasonleebrown@gmail.com.
authors.forename: Jason L
authors.initials: JL
authors.lastname: Brown
authors.affiliation: Department of Biological Sciences, Fordham University, Bronx, New York 10458 USA.
authors.forename: Jennifer J
authors.initials: JJ
authors.lastname: Weber
authors.affiliation: Biology Department, The City College of New York, New York, New York 10031 USA.
authors.forename: Diego F
authors.initials: DF
authors.lastname: Alvarado-Serrano
authors.affiliation: Biology Department, The City College of New York, New York, New York 10031 USA The Graduate Center, City University of New York, New York, New York 10016 USA Department of Invertebrate Zoology, American Museum of Natural History, New York, New York 10024 USA.
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Hickerson
authors.affiliation: Department of Biological Sciences, Fordham University, Bronx, New York 10458 USA.
authors.forename: Steven J
authors.initials: SJ
authors.lastname: Franks
authors.affiliation: Biology Department, The City College of New York, New York, New York 10031 USA The Graduate Center, City University of New York, New York, New York 10016 USA.
authors.forename: Ana C
authors.initials: AC
authors.lastname: Carnaval
mesh_terms: D001499:Bayes Theorem; D057231:Climate Change; D017753:Ecosystem; D014644:Genetic Variation; D008957:Models, Genetic; D015205:Northwestern United States; D032263:Penstemon / Q000235:genetics / Q000502:physiology*; D063148:Plant Dispersal; D015206:Southwestern United States
keywords: Penstemon deustus; Plantaginaceae; climate change; conservation; demographic inference; spatial coalescent; species distribution models