D’Amen, M., Zimmermann, N. E. & Pearman, P. B. Conservation of phylogeographic lineages under climate change. Glob. Ecol. Biogeogr. 22, 93–104. https://doi.org/10.1111/j.1466-8238.2012.00774.x (2013).
Google Scholar
Espíndola, A. et al. Predicting present and future intra-specific genetic structure through niche hindcasting across 24 millennia. Ecol. Lett. 15, 649–657. https://doi.org/10.1111/j.1461-0248.2012.01779.x (2012).
Google Scholar
Manel, S., Schwartz, M. K., Luikart, G. & Taberlet, P. Landscape genetics: combining landscape ecology and population genetics. Tr. Ecol. Evolut. 18, 189–197. https://doi.org/10.1016/S0169-5347(03)00008-9 (2003).
Google Scholar
Fontaine, C., Lovett, P., Sanou, H., Maley, J. & Bouvet, J. M. Genetic diversity of the shea tree (Vitellaria paradoxa CF Gaertn), detected by RAPD and chloroplast microsatellite markers. Heredity 93, 639 (2004).
Google Scholar
Hampe, A., El Masri, L. & Petit, R. J. Origin of spatial genetic structure in an expanding oak population. Mol. Ecol. 19, 459–471. https://doi.org/10.1111/j.1365-294X.2009.04492.x (2010).
Google Scholar
Omondi, S. F., Odee, D. W., Ongamo, G. O., Kanya, J. I. & Khasa, D. P. Genetic consequences of anthropogenic disturbances and population fragmentation in Acacia senegal. Conserv. Genet. 17, 1235–1244. https://doi.org/10.1007/s10592-016-0854-1 (2016).
Google Scholar
Hewitt, G. Postglacial recolonization of European biota. Biol. J. Lin. Soc. 68, 87–112 (1999).
Google Scholar
Donkpegan, A. S. L. et al. Population genomics of the widespread African savannah trees Afzelia africana and Afzelia quanzensis reveals no significant past fragmentation of their distribution ranges. Am. J. Bot. 107, 498–509. https://doi.org/10.1002/ajb2.1449 (2020).
Google Scholar
Etterson, J. R. & Shaw, R. G. Constraint to adaptive evolution in response to global warming. Science 294, 151–154. https://doi.org/10.1126/science.1063656 (2001).
Google Scholar
Holderegger, R. & Wagner, H. Landscape genetics. Bioscience 58, 199–207. https://doi.org/10.1641/B580306 (2008).
Google Scholar
Hampe, A. & Petit, R. J. Conserving biodiversity under climate change: the rear edge matters. Ecol. Lett. 8, 461–467. https://doi.org/10.1111/j.1461-0248.2005.00739.x (2005).
Google Scholar
Parmesan, C. & Yohe, G. A globally coherent fingerprint of climate change impacts across natural systems. Nature 421, 37–42. https://doi.org/10.1038/nature01286 (2003).
Google Scholar
Pauls, S. U., Nowak, C., Bálint, M. & Pfenninger, M. The impact of global climate change on genetic diversity within populations and species. Mol. Ecol. 22, 925–946. https://doi.org/10.1111/mec.12152 (2013).
Google Scholar
Arnell, N. W. & Lloyd-Hughes, B. The global-scale impacts of climate change on water resources and flooding under new climate and socio-economic scenarios. Climatic Ch. 122, 127–140. https://doi.org/10.1007/s10584-013-0948-4 (2014).
Google Scholar
Moss, R. H. et al. The next generation of scenarios for climate change research and assessment. Nature 463, 747 (2010).
Google Scholar
van Vuuren, D. P. et al. The representative concentration pathways: an overview. Climatic Ch. 109, 5–31. https://doi.org/10.1007/s10584-011-0148-z (2011).
Google Scholar
Prather, M. et al. Annex II: climate system scenario tables. Climate Ch. 1395–1445 (2013).
Pachauri, R. K. et al. Climate change 2014: synthesis report. Contribution of Working Groups I, II and III to the fifth assessment report of the Intergovernmental Panel on Climate Change. Synthesis report (Intergovernmental Panel on Climate Change, Geneva, Switzerland, 2014).
Müller, C. Climate change impact on Sub-Saharan Africa. An overview and analysis of scenarios and models (Dt. Inst. für Entwicklungspolitik, Bonn, 2009).
Serdeczny, O. et al. Climate change impacts in Sub-Saharan Africa: From physical changes to their social repercussions. Reg. Environ. Ch. 17, 1585–1600. https://doi.org/10.1007/s10113-015-0910-2 (2016).
Google Scholar
Linder, H. P. et al. The partitioning of Africa: Statistically defined biogeographical regions in sub-Saharan Africa. J. Biogeogr. 39, 1189–1205. https://doi.org/10.1111/j.1365-2699.2012.02728.x (2012).
Google Scholar
Sexton, G. J. et al. Influence of putative forest refugia and biogeographic barriers on the level and distribution of genetic variation in an African savannah tree, Khaya senegalensis (Desr.) A. Juss. Tree Genet. Genomes https://doi.org/10.1007/s11295-015-0933-3 (2015).
Google Scholar
Linder, H. P. et al. Numerical re-evaluation of the sub-Saharan phytopchoria of mainland Africa. Biologiske Skrifter 55, 229–252 (2005).
Google Scholar
Ruiz Guajardo, J. C. et al. Landscape genetics of the key African acacia species Senegalia mellifera (Vahl)- the importance of the Kenyan Rift Valley. Mol. Ecol. 19, 5126–5139. https://doi.org/10.1111/j.1365-294X.2010.04833.x (2010).
Google Scholar
Kebede, M., Enrich, D., Taberlet, P., Nemomissa, S. & Brochmann, C. Phylogeography and conservation genetics of a giant lobelia (Lobelia giberroa) in Ethiopian and Tropical East African mountains. Mol. Ecol. 16, 1233–1243. https://doi.org/10.1111/j.1365-294x.2007.03232.x (2007).
Google Scholar
Kadu, C. et al. Phylogeography of the Afromontane Prunus africana reveals a former migration corridor between East and West African highlands. Mol. Ecol. 20, 165–178. https://doi.org/10.1111/j.1365-294X.2010.04931.x (2011).
Google Scholar
Lyam, P. T., Duque-Lazo, J., Schnitzler, J., Hauenschild, F. & Müllner-Riehl, A. N. Testing the forest refuge hypothesis in sub-Saharan Africa using species distribution modeling for a key savannah tree species, Senegalia senegal (L.) Britton. Front. Biogeogr. https://doi.org/10.21425/F5FBG48689 (2020).
Google Scholar
Logossa, Z. A. et al. Molecular data reveal isolation by distance and past population expansion for the shea tree (Vitellaria paradoxa C.F. Gaertn) in West Africa. Mol. Ecol. 20, 4009–4027. https://doi.org/10.1111/j.1365-294X.2011.05249.x (2011).
Google Scholar
Lompo, D., Vinceti, B., Konrad, H., Gaisberger, H. & Geburek, T. Phylogeography of African locust bean (Parkia biglobosa) reveals genetic divergence and spatially structured populations in west and central Africa. J. Heredity 109, 811–824. https://doi.org/10.1093/jhered/esy047 (2018).
Google Scholar
Leong Pock Tsy, J.-M. et al. Chloroplast DNA phylogeography suggests a West African centre of origin for the baobab, Adansonia digitata L. (Bombacoideae, Malvaceae). Mol. Ecol. 18, 1707–1715. https://doi.org/10.1111/j.1365-294X.2009.04144.x (2009).
Google Scholar
Allal, F. et al. Past climate changes explain the phylogeography of Vitellaria paradoxa over Africa. Heredity 107, 174–186. https://doi.org/10.1038/hdy.2011.5 (2011).
Google Scholar
Fagg, C. W. & Allison, G. E. Acacia Senegal and the gum arabic trade: monograph and annotated bibliography (University of Oxford, United Kingdom, 2004).
Lézine, A. M. Late Quaternary vegetation and climate of the Sahel. Quatern. Res. 32, 317–334 (1989).
Google Scholar
Steele, T. Vertebrate records: Late Pleistocene of Africa. In Encyclopedia of Quaternary Science, edited by S. Elias. (Elsevier, Oxford, 2007), 3139–3150.
Raddad, E., Salih, A., Fadl, M., Kaarakka, V. & Luukkanen, O. Symbiotic nitrogen fixation in eight Acacia senegal provenances in dryland clays of the Blue Nile Sudan estimated by the 15N natural abundance method. Plant Soil 275, 261–269. https://doi.org/10.1007/s11104-005-2152-4 (2005).
Google Scholar
Gray, A. et al. Does geographic origin dictate ecological strategies in Acacia senegal (L.) Willd? Evidence from carbon and nitrogen stable isotopes. Plant Soil 369, 479–496. https://doi.org/10.1007/s11104-013-1593-4 (2013).
Google Scholar
Ross, J. H. A conspectus of African acacia species (1979).
Odee, D. W., Telford, A., Wilson, J., Gaye, A. & Cavers, S. Plio-Pleistocene history and phylogeography of Acacia senegal in dry woodlands and savannahs of sub-Saharan tropical Africa: evidence of early colonisation and recent range expansion. Heredity 109, 372–382. https://doi.org/10.1038/hdy.2012.52 (2012).
Google Scholar
Lyam, P. et al. Genetic diversity and distribution of Senegalia senegal (L.) Britton under climate change scenarios in West Africa. PLoS ONE 13, e0194726 (2018).
Google Scholar
Nicotra, A. B. et al. Plant phenotypic plasticity in a changing climate. Trends in Plant Science 15, 684–692; https://doi.org/10.1016/j.tplants.2010.09.008 (2010).
Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978. https://doi.org/10.1002/joc.1276 (2005).
Google Scholar
ESRI. ArcGIS Desktop: Release 10.5. Redlands, CA: Environmental Systems Research Institute (2020).
Kopelman, N. M., Mayzel, J., Jakobsson, M., Rosenberg, N. A. & Mayrose, I. Clumpak: a program for identifying clustering modes and packaging population structure inferences across K. Mol. Ecol. Res. 15, 1179–1191. https://doi.org/10.1111/1755-0998.12387 (2015).
Google Scholar
Elhadji, S. D. et al. Exploring genetic diversity and structure of Acacia senegal (L.) Willd to improve its conservation in Niger. African J. Biotechnol. 16, 1650–1659 (2017).
Google Scholar
Muriira, N. G., Muchugi, A., Yu, A., Xu, J. & Liu, A. Genetic Diversity Analysis Reveals Genetic Differentiation and Strong Population Structure in Calotropis Plants. Sci. Rep. 8, 7832 (2018).
Google Scholar
Conord, C., Gurevitch, J. & Fady, B. Large-scale longitudinal gradients of genetic diversity: a meta-analysis across six phyla in the Mediterranean basin. Ecol. Evol. 2, 2600–2614. https://doi.org/10.1002/ece3.350 (2012).
Google Scholar
Omondi, S. F. et al. Genetic diversity and population structure of Acacia senegal (L) Willd Kenya. Trop. Plant Biol. 3, 59–70 (2010).
Google Scholar
Marko, P. B. & Hart, M. W. The complex analytical landscape of gene flow inference. Trends Ecol. Evol. 26, 448–456. https://doi.org/10.1016/j.tree.2011.05.007 (2011).
Google Scholar
Goncalves, A. L., García, M. V., Heuertz, M. & González-Martínez, S. C. Demographic history and spatial genetic structure in a remnant population of the subtropical tree Anadenanthera colubrina var cebil (Griseb.) Altschul (Fabaceae). Ann. Forest Sci. https://doi.org/10.1007/s13595-019-0797-z (2019).
Google Scholar
Rosenzweig, M. L. Species diversity in space and time (Cambridge university press, 1995).
Vellend, M. & Geber, M. A. Connections between species diversity and genetic diversity. Ecol. Lett. 8, 767–781. https://doi.org/10.1111/j.1461-0248.2005.00775.x (2005).
Google Scholar
Ackerly, D. D. et al. The geography of climate change: implications for conservation biogeography. Divers. Distrib. 16, 476–487. https://doi.org/10.1111/j.1472-4642.2010.00654.x (2010).
Google Scholar
Waldvogel, A.-M. et al. Evolutionary genomics can improve prediction of species’ responses to climate change. Evol. Lett. 4, 4–18. https://doi.org/10.1002/evl3.154 (2020).
Google Scholar
Hutchison, D. W. & Templeton, A. R. Correlation of pairwise genetic and geographic distance measures: inferring the relative influences of gene flow and drift on the distribution of genetic variability. Evol.; Int. J. Org. Evol. 53, 1898–1914 (1999).
Google Scholar
Shi, M. M., Michalski, S. G., Welk, E., Chen, X. Y. & Durka, W. Phylogeography of a widespread Asian subtropical tree: genetic east-west differentiation and climate envelope modelling suggest multiple glacial refugia. J. Biogeogr. 41, 1710–1720. https://doi.org/10.1111/jbi.12322 (2014).
Google Scholar
Voss, N., Eckstein, R. L. & Durka, W. Range expansion of a selfing polyploid plant despite widespread genetic uniformity. Ann. Botany 110, 585–593. https://doi.org/10.1093/aob/mcs117 (2012).
Google Scholar
Fiorini, C. F. et al. Phylogeography of the specialist plant Mandirola hirsuta (Gesneriaceae) suggests ancient habitat fragmentation due to savanna expansion. Flora 262, 151522 (2020).
Google Scholar
Sexton, J. P., Hangartner, S. B. & Hoffmann, A. A. Genetic isolation by environment or distance: which pattern of gene flow is most common?. Evolution 68, 1–15. https://doi.org/10.1111/evo.12258 (2014).
Google Scholar
Wang, I. J. & Bradburd, G. S. Isolation by environment. Mol. Ecol. 23, 5649–5662. https://doi.org/10.1111/mec.12938 (2014).
Google Scholar
Nosil, P., Vines, T. H. & Funk, D. J. Reproductive isolation caused by natural selection against immigrants from divergent habitats. Evol.; Int. J. Org. Evol. 59, 705–719 (2005).
Wang, I. J. & Summers, K. Genetic structure is correlated with phenotypic divergence rather than geographic isolation in the highly polymorphic strawberry poison-dart frog. Mol. Ecol. 19, 447–458. https://doi.org/10.1111/j.1365-294X.2009.04465.x (2010).
Google Scholar
Xu, B. et al. Population genetic structure is shaped by historical, geographic, and environmental factors in the leguminous shrub Caragana microphylla on the Inner Mongolia Plateau of China. BMC Plant Biol. 17, 200 (2017).
Google Scholar
Hendry, A. P. & Day, T. Population structure attributable to reproductive time: isolation by time and adaptation by time. Mol. Ecol. 14, 901–916. https://doi.org/10.1111/j.1365-294X.2005.02480.x (2005).
Google Scholar
Solomon, S., Manning, M., Marquis, M. & Qin, D. Climate change 2007-the physical science basis: Working group I contribution to the fourth assessment report of the IPCC (Cambridge university press, 2007).
Thuiller, W. Climate change and the ecologist. Nature 448, 550–552 (2007).
Google Scholar
Osland, M. J. et al. Tropicalization of temperate ecosystems in North America: The northward range expansion of tropical organisms in response to warming winter temperatures. Global Ch. Biol. 27, 3009–3034 (2021).
Google Scholar
Higgins, S. I., Lavorel, S. & Revilla, E. Estimating plant migration rates under habitat loss and fragmentation. Oikos 101, 354–366 (2003).
Google Scholar
Jump, A. S. & Penuelas, J. Running to stand still: adaptation and the response of plants to rapid climate change. Ecol. Lett. 8, 1010–1020. https://doi.org/10.1111/j.1461-0248.2005.00796.x (2005).
Google Scholar
Jump, A. S., Marchant, R. & Peñuelas, J. Environmental change and the option value of genetic diversity. Trends Plant Sci. 14, 51–58. https://doi.org/10.1016/j.tplants.2008.10.002 (2009).
Google Scholar
Kirk, H. & Freeland, J. R. Applications and implications of neutral versus non-neutral markers in molecular ecology. Int. J. Mol. Sci. 12, 3966–3988. https://doi.org/10.3390/ijms12063966 (2011).
Google Scholar
Bucharova, A. et al. Mix and match: regional admixture provenancing strikes a balance among different seed-sourcing strategies for ecological restoration. Conserv. Genet. 20, 7–17. https://doi.org/10.1007/s10592-018-1067-6 (2019).
Google Scholar
Tong, Y. et al. Ex situ conservation of Pinus koraiensis can preserve genetic diversity but homogenizes population structure. Forest Ecol. Manag. 465, 117820 (2020).
Google Scholar
Vessella, F., Simeone, M. C. & Schirone, B. Quercus suber range dynamics by ecological niche modelling: from the Last Interglacial to present time. Quat. Sci. Rev. 119, 85–93. https://doi.org/10.1016/j.quascirev.2015.04.018 (2015).
Google Scholar
Lovejoy, T. E. Climate change and biodiversity (TERI Press, India, 2006).
Poczai, P., Varga, I., Bell N.E. & Hyvonen, J. The molecular basis of plant genetic diversity. In Genomics meets biodiversity: advances in molecular marker development and their applications in plant genetic diversity assessment. The molecular basis of plant genetic diversity, edited by M. Caliskan (InTech Open Access Publisher2012), 3–31.
Botermans, M., Sosef, M. S. M., Chatrou, L. W. & Couvreur, T. L. P. Revision of the African Genus Hexalobus (Annonaceae). Syst. Bot. 36, 33–48. https://doi.org/10.1600/036364411X553108 (2011).
Google Scholar
Sosef, M. et al. Exploring the floristic diversity of tropical Africa. BMC Biol. 15, 15 (2017).
Google Scholar
Chapuis, M.-P. & Estoup, A. Microsatellite null alleles and estimation of population differentiation. Mol. Biol. Evol. 24, 621–631. https://doi.org/10.1093/molbev/msl191 (2007).
Google Scholar
Escoffier, L. & Lische, H. ARLEQUIN suite ver. 3.5. A new series of programs to perform population genetics analyses under Linux and Windows. Mol. Ecol. Res. 10, 564–567 (2010).
Google Scholar
Lewis, P. O. & Zaykin, D. Genetic data analysis: computer program for the analysis of allelic data. Mol. Ecol. 11, 1157–1164 (2002).
Google Scholar
AComputer Program to Calculate F-Statistics. Goudet, J. FSTAT (Version 1.2). J. Hered. 6, 245–246 (1995).
El Mousadik, A. & Petit, R. J. High level of genetic differentiation for allelic richness among populations of the argan tree [Argania spinosa (L.) Skeels] endemic to Morocco. Theor. Appl. Genet. 92, 832–839 (1996).
Google Scholar
Raymond, M. & Rousset, F. GENEPOP (version 1.2): population genetics software for exact tests and ecumenicism. J. Heredity 86, 248–249 (1995).
Google Scholar
Pritchard, J., Stephens, M. & Donelly, P. Inference of Population Structure Using Multilocus Genotype Data, 945–959 (2000).
Falush, D., Stephens, M. & Pritchard, J. K. Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 164, 1567–1587 (2003).
Google Scholar
Earl, D. A. & von Holdt, B. M. STRUCTURE HARVESTER A website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv. Genet. Resour. 4, 359–361. https://doi.org/10.1007/s12686-011-9548-7 (2012).
Google Scholar
Pritchard, J. K., Wen, W. & Falush, D. Documentation for STRUCTURE software: Version 2.3. University of Chicago, Chicago, IL, 1–37 (2010).
Eliades, N. G. & Eliades, D. G. HAPLOTYPE ANALYSIS: software for analysis of haplotype data. Forest Goettingen (Germany): Genetics and Forest Tree Breeding, Georg-August University Goettingen (2009).
Leigh, J. W. & Bryant, D. POPART: full-feature software for haplotype network construction. Methods Ecol. Evol. 6, 1110–1116 (2015).
Google Scholar
Peakall, R. & Smouse, P. E. Genalex 6: genetic analysis in Excel. Population genetic software for teaching and research. Mol. Ecol. Notes 6, 288–295. https://doi.org/10.1111/j.1471-8286.2005.01155.x (2006).
Google Scholar
Title, P. O. & Bemmels, J. B. ENVIREM: an expanded set of bioclimatic and topographic variables increases flexibility and improves performance of ecological niche modeling. Ecography 41, 291–307. https://doi.org/10.1111/ecog.02880 (2018).
Google Scholar
Hengl, T. et al. SoilGrids250m: Global gridded soil information based on machine learning. PLoS ONE 12, e0169748 (2017).
Google Scholar
Wang, I. J. Examining the full effects of landscape heterogeneity on spatial genetic variation: a multiple matrix regression approach for quantifying geographic and ecological isolation. Evolution 67, 3403–3411. https://doi.org/10.1111/evo.12134 (2013).
Google Scholar
Source: Ecology - nature.com
