Predicting the genetic consequences of future climate change: The power of coupling spatial demography, the coalescent, and historical landscape changes

Author(s)

Brown, Jason L. ^[1] ; Weber, Jennifer J. ^[2] ; Alvarado-Serrano, Diego F. ^[1] ; Hickerson, Michael J. ^{[3, 1, 4]} ; Franks, Steven J. ^[2] ; Carnaval, Ana C. ^{[3, 1]}

Affiliation

^[1] CUNY City Coll, Dept Biol, 138Th St & Convent Ave, New York, NY 10031 - USA

^[2] Fordham Univ, Dept Biol Sci, Bronx, NY 10458 - USA

^[3] CUNY, Grad Ctr, New York, NY 10016 - USA

^[4] Amer Museum Nat Hist, Dept Invertebrate Zool, New York, NY 10024 - USA

• Document type: Journal article
• Source: AMERICAN JOURNAL OF BOTANY; v. 103, n. 1, p. 153-163, JAN 2016.
• Web of Science Citations: 13

Abstract

PREMISE OF THE STUDY: 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. KEY 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. (AU)

• FAPESP's process: 13/50297-0 - Dimensions US-BIOTA São Paulo: a multidisciplinary framework for biodiversity prediction in the Brazilian Atlantic forest hotspot
• Grantee: Cristina Yumi Miyaki
• Support Opportunities: BIOTA-FAPESP Program - Thematic Grants