LITERATURE CITED
Aguirre-Liguori, J. A., Ramírez-Barahona, S., Tiffin, P., & Eguiarte, L. E. (2019). Climate change is predicted to disrupt patterns of local adaptation in wild and cultivated maize. Proceedings of the Royal Society B: Biological Sciences, 286(1906), 20190486.
Bay, R. A., Harrigan, R. J., Underwood, V. L., Gibbs, H. L., Smith, T. B., & Ruegg, K. (2018). Genomic signals of selection predict climate-driven population declines in a migratory bird. Science, 359(6371), 83–86.
Blois, J. L., Williams, J. W., Fitzpatrick, M. C., Jackson, S. T., & Ferrier, S. (2013). Space can substitute for time in predicting climate-change effects on biodiversity. Proceedings of the National Academy of Sciences,110(23), 9374–9379.
Bower, A. D., St Clair, J. B., & Erickson, V. (2014). Generalized provisional seed zones for native plants. Ecological Applications: A Publication of the Ecological Society of America, 24(5), 913–919.
Breiman, L. (2001). Random Forests. Machine Learning, 45(1), 5–32.
Capblancq, T., Fitzpatrick, M. C., Bay, R. A., Exposito-Alonso, M., & Keller, S. R. (2020). Genomic Prediction of (Mal)Adaptation Across Current and Future Climatic Landscapes. Annual Review of Ecology, Evolution, and Systematics.
Chamberlain, S. (2017). rnoaa: “NOAA” Weather Data from R. R package version 0.7.0 (Version 0.7.0). Retrieved from https://CRAN.R-project.org/package=rnoaa
Chhatre, V. E., Fetter, K. C., Gougherty, A. V., Fitzpatrick, M. C., Soolanayakanahally, R. Y., Zalesny, R. S., & Keller, S. R. (2019). Climatic niche predicts the landscape structure of locally adaptive standing genetic variation (p. 817411). doi: 10.1101/817411
Dawson, T. P., Jackson, S. T., House, J. I., Prentice, I. C., & Mace, G. M. (2011). Beyond predictions: Biodiversity conservation in a changing climate.Science, 332(6025), 53–58.
Ellis, N., Smith, S. J., & Pitcher, C. R. (2012). Gradient forests: calculating importance gradients on physical predictors. Ecology, 93(1), 156–168.
Fetter, K. C., Nelson, D. M., & Keller, S. R. (2019). Trade-offs and selection conflicts in hybrid poplars indicate the stomatal ratio as an important trait regulating disease resistance. BioRxiv. Retrieved from https://www.biorxiv.org/content/10.1101/814046v1.abstract
Fitzpatrick, M. C., Blois, J. L., Williams, J. W., Nieto-Lugilde, D., Maguire, K. C., & Lorenz, D. J. (2018). How will climate novelty influence ecological forecasts? Using the Quaternary to assess future reliability. Global Change Biology, 24(8), 3575–3586.
Fitzpatrick, M. C., & Keller, S. R. (2015). Ecological genomics meets community‐level modelling of biodiversity: mapping the genomic landscape of current and future environmental adaptation. Ecology Letters, 18(1), 1–16.
Fitzpatrick, M. C., Keller, S. R., & Lotterhos, K. E. (2018). Comment on “Genomic signals of selection predict climate-driven population declines in a migratory bird.” Science, 361(6401). doi: 10.1126/science.aat7279
Frichot, E., Schoville, S. D., Bouchard, G., & François, O. (2013). Testing for associations between loci and environmental gradients using latent factor mixed models.Molecular Biology and Evolution, 30(7), 1687–1699.
Gougherty, A. V., Keller, S. R., Chhatre, V. E., & Fitzpatrick, M. C. (2020). Future climate change promotes novel gene-climate associations in balsam poplar (Populus balsamifera L.), a forest tree species (p. 2020.02.28.961060). doi: 10.1101/2020.02.28.961060
Gugger, P. F., Liang, C. T., Sork, V. L., Hodgskiss, P., & Wright, J. W. (2018). Applying landscape genomic tools to forest management and restoration of Hawaiian koa (Acacia koa) in a changing environment. Evolutionary Applications, 11(2), 231–242.
Guisan, A., Thuiller, W., & Zimmermann, N. E. (2017). Habitat Suitability and Distribution Models: with Applications in R. Cambridge University Press.
Günther, T., & Coop, G. (2013). Robust identification of local adaptation from allele frequencies. Genetics, 195(1), 205–220.
Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G., & Jarvis, A. (2005). Very high resolution interpolated climate surfaces for global land areas.International Journal of Climatology, 25(15), 1965–1978.
Hudson, R. R. (2002). Generating samples under a Wright–Fisher neutral model of genetic variation. Bioinformatics , 18(2), 337–338.
Ingvarsson, P. K., & Bernhardsson, C. (2020). Genome‐wide signatures of environmental adaptation in European aspen ( Populus tremula ) under current and future climate conditions. Evolutionary Applications,13(1), 132–142.
Jia, K., Zhao, W., Maier, P. A., Hu, X., Jin, Y., Zhou, S., … Mao, J. (2020). Landscape genomics predicts climate change‐related genetic offset for the widespread Platycladus orientalis (Cupressaceae). Evolutionary Applications, 13(4), 665–676.
Keller, S. R., Levsen, N., Ingvarsson, P. K., Olson, M. S., & Tiffin, P. (2011). Local selection across a latitudinal gradient shapes nucleotide diversity in Balsam Poplar, Populus balsamifera L. Genetics, 188(4), 941–952.
Keller, S. R., Levsen, N., Olson, M. S., & Tiffin, P. (2012). Local adaptation in the flowering-time gene network of balsam poplar, Populus balsamifera L.Molecular Biology and Evolution, 29(10), 3143–3152.
Keller, S. R., Olson, M. S., Silim, S., Schroeder, W., & Tiffin, P. (2010). Genomic diversity, population structure, and migration following rapid range expansion in the Balsam Poplar, Populus balsamifera. Molecular Ecology,19(6), 1212–1226.
Keller, S. R., Soolanayakanahally, R. Y., Guy, R. D., Silim, S. N., Olson, M. S., & Tiffin, P. (2011). Climate-driven local adaptation of ecophysiology and phenology in balsam poplar, Populus balsamifera L.(Salicaceae).American Journal of Botany, 98(1), 99–108.
Landguth, E. L., & Cushman, S. A. (2010). cdpop: A spatially explicit cost distance population genetics program. Molecular Ecology Resources, 10(1), 156–161.
Little, E. L. (1971). Atlas of United States trees. Volume 1. Conifers and important hardwoods.Miscellaneous Publications. United States Department of Agriculture, (1146.).
Lotterhos, K. E., & Whitlock, M. C. (2014). Evaluation of demographic history and neutral parameterization on the performance of FST outlier tests.Molecular Ecology, 23(9), 2178–2192.
Mahalanobis, P. C. (1936). On the generalized distance in statistics. Proceedings of the National Institute of Sciences of India, 2, 49–55. New Delhi.
Mahony, C. R., MacLachlan, I. R., Lind, B. M., Yoder, J. B., Wang, T., & Aitken, S. N. (2020). Evaluating genomic data for management of local adaptation in a changing climate: A lodgepole pine case study. Evolutionary Applications,13(1), 116–131.
Martins, K., Gugger, P. F., Llanderal-Mendoza, J., González-Rodríguez, A., Fitz-Gibbon, S. T., Zhao, J.-L., … Sork, V. L. (2018). Landscape genomics provides evidence of climate-associated genetic variation in Mexican populations of Quercus rugosa. Evolutionary Applications, 11(10), 1842–1858.
Mátyás, C. (1996). Climatic adaptation of trees: rediscovering provenance tests. Euphytica, Vol. 92, pp. 45–54. doi: 10.1007/bf00022827
Meirmans, P. G., Godbout, J., Lamothe, M., Thompson, S. L., & Isabel, N. (2017). History rather than hybridization determines population structure and adaptation in Populus balsamifera. Journal of Evolutionary Biology, 30(11), 2044–2058.
Naimi, B., Hamm, N. A. S., Groen, T. A., Skidmore, A. K., & Toxopeus, A. G. (2014). Where is positional uncertainty a problem for species distribution modelling?Ecography, 37(2), 191–203.
Olson, M. S., Levsen, N., Soolanayakanahally, R. Y., Guy, R. D., Schroeder, W. R., Keller, S. R., & Tiffin, P. (2013). The adaptive potential of Populus balsamifera L. to phenology requirements in a warmer global climate. Molecular Ecology, 22(5), 1214–1230.
Pecl, G. T., Araújo, M. B., Bell, J. D., Blanchard, J., Bonebrake, T. C., Chen, I.-C., … Williams, S. E. (2017). Biodiversity redistribution under climate change: Impacts on ecosystems and human well-being. Science,355(6332). doi: 10.1126/science.aai9214
Peres-Neto, P. R., & Jackson, D. A. (2001). How well do multivariate data sets match? The advantages of a Procrustean superimposition approach over the Mantel test.Oecologia, 129(2), 169–178.
Pike, C., Potter, K. M., Berrang, P., Crane, B., Baggs, J., Leites, L., & Luther, T. (2020). New Seed-Collection Zones for the Eastern United States: The Eastern Seed Zone Forum. Journal of Forestry, Vol. 118, pp. 444–451. doi: 10.1093/jofore/fvaa013
R Core Team. (2018). R: A language and environment for statistical computing. R Foundation for Statistical Computing. Austria: Vienna.
Ruegg, K., Bay, R. A., Anderson, E. C., Saracco, J. F., Harrigan, R. J., Whitfield, M., … Smith, T. B. (2018). Ecological genomics predicts climate vulnerability in an endangered southwestern songbird. Ecology Letters, 21(7), 1085–1096.
Sala, O. E., Chapin, F. S., Armesto, J. J., Berlow, E., Bloomfield, J., Dirzo, R., … Wall, D. H. (2000). Biodiversity - Global biodiversity scenarios for the year 2100. Science, 287, 1770–1774.
Savolainen, O., Lascoux, M., & Merilä, J. (2013). Ecological genomics of local adaptation.Nature Reviews. Genetics, 14(11), 807–820.
Soolanayakanahally, R. Y., Guy, R. D., Silim, S. N., Drewes, E. C., & Schroeder, W. R. (2009). Enhanced assimilation rate and water use efficiency with latitude through increased photosynthetic capacity and internal conductance in balsam poplar (Populus balsamifera L.). Plant, Cell & Environment, 32(12), 1821–1832.
Soolanayakanahally, R. Y., Guy, R. D., Silim, S. N., & Song, M. (2013). Timing of photoperiodic competency causes phenological mismatch in balsam poplar (Populus balsamifera L.). Plant, Cell & Environment, 36(1), 116–127.
Thornton, P. E., Thornton, M. M., Mayer, B. W., Wilhelmi, N., Wei, Y., Devarakonda, R., & Cook, R. B. (2014). Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 2. Oak Ridge National Laboratory (ORNL).
Urban, M. C. (2015). Accelerating extinction risk from climate change. Science,348(6234), 571–573.
Urban, M. C., Bocedi, G., Hendry, A. P., Mihoub, J.-B., Pe’er, G., Singer, A., … Travis, J. M. J. (2016). Improving the forecast for biodiversity under climate change. Science, 353(6304). doi: 10.1126/science.aad8466
Wang, T., Hamann, A., Yanchuk, A., O’Neill, G. A., & Aitken, S. N. (2006). Use of response functions in selecting lodgepole pine populations for future climates.Global Change Biology, Vol. 12, pp. 2404–2416. doi: 10.1111/j.1365-2486.2006.01271.x
Wang, T., O’Neill, G. A., & Aitken, S. N. (2010). Integrating environmental and genetic effects to predict responses of tree populations to climate. Ecological Applications: A Publication of the Ecological Society of America,20(1), 153–163.
Wüest, R. O., Zimmermann, N. E., Zurell, D., Alexander, J. M., Fritz, S. A., Hof, C., … Others. (2020). Macroecology in the age of Big Data–Where to go from here? Journal of Biogeography, 47(1), 1–12.