@article{e181a36008b1405eacaefb1fd97d896a,
title = "A New Perspective on Ecological Prediction Reveals Limits to Climate Adaptation in a Temperate Tree Species",
abstract = "Forests absorb a large fraction of anthropogenic CO2 emission, but their ability to continue to act as a sink under climate change depends in part on plant species undergoing rapid adaptation. Yet models of forest response to climate change currently ignore local adaptation as a response mechanism. Thus, considering the evolution of intraspecific trait variation is necessary for reliable, long-term species and climate projections. Here, we combine ecophysiology and predictive climate modeling with analyses of genomic variation to determine whether sugar and starch storage, energy reserves for trees under extreme conditions, have the heritable variation and genetic diversity necessary to evolve in response to climate change within populations of black cottonwood (Populus trichocarpa). Despite current patterns of local adaptation and extensive range-wide heritable variation in storage, we demonstrate that adaptive evolution in response to climate change will be limited by a lack of heritable variation within northern populations and by a need for extreme genetic changes in southern populations. Our method can help design more targeted species management interventions and highlights the power of using genomic tools in ecological prediction to scale from molecular to regional processes to determine the ability of a species to respond to future climates.",
keywords = "carbon storage, conservation genomics, ecological modeling, genomic adaptation, global climate change, nonstructural carbohydrates, plant ecophysiology",
author = "Meghan Blumstein and Andrew Richardson and David Weston and Jin Zhang and Wellington Muchero and Robin Hopkins",
note = "Funding Information: We thank M.E. Furze, C.F. White, D.L. Des Marais, N.M. Holbrook, and N. Freidman for comments and A. Viser, L. Gunter, E. Borjigin-Wang, and A. Chan for lab assistance. This material is based upon work supported by the US Department of Energy , Office of Science, Office of Workforce Development for Teachers and Scientists, Office of Science Graduate Student Research (SCGSR) program; by the National Science Foundation Graduate Research Fellowship under grant no. DGE1745303 ; and the Explorer{\textquoteright}s Club . The SCGSR program is administered by the Oak Ridge Institute for Science and Education (ORISE) for the DOE. ORISE is managed by ORAU under contract number DE-SC0014664 . Funding Information: We thank M.E. Furze, C.F. White, D.L. Des Marais, N.M. Holbrook, and N. Freidman for comments and A. Viser, L. Gunter, E. Borjigin-Wang, and A. Chan for lab assistance. This material is based upon work supported by the US Department of Energy, Office of Science, Office of Workforce Development for Teachers and Scientists, Office of Science Graduate Student Research (SCGSR) program; by the National Science Foundation Graduate Research Fellowship under grant no. DGE1745303; and the Explorer's Club. The SCGSR program is administered by the Oak Ridge Institute for Science and Education (ORISE) for the DOE. ORISE is managed by ORAU under contract number DE-SC0014664. Conceptualization, M.B. A.R. and R.H.; Data Collection/Processing, M.B. GWAS, J.Z. and W.M.; Statistical Analysis and Modeling, M.B.; Writing, M.B. and R.H.; Review and Editing, M.B. A.R. D.W. J.Z. W.M. and R.H. The authors declare no competing interests. Publisher Copyright: {\textcopyright} 2020 Elsevier Ltd",
year = "2020",
month = apr,
day = "20",
doi = "10.1016/j.cub.2020.02.001",
language = "English (US)",
volume = "30",
pages = "1447--1453.e4",
journal = "Current Biology",
issn = "0960-9822",
publisher = "Cell Press",
number = "8",
}