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    There is little evidence that spicy food in hot countries is an adaptation to reducing infection risk

    1.
    Sherman, P. W. & Billing, J. Darwinian gastronomy: why we use spices: spices taste good because they are good for us. BioScience 49, 453–463 (1999).
    Article  Google Scholar 
    2.
    Billing, J. & Sherman, P. W. Antimicrobial functions of spices: why some like it hot. Q. Rev. Biol. 73, 3–49 (1998).
    CAS  PubMed  Article  Google Scholar 

    3.
    Galton, F. Comment on ‘On a method of investigating the development of institutions; applied to laws of marriage and descent’ by E. B. Tylor. J. Anthropol. Inst. Gt Br. Irel. 18, 245–272 (1889).
    Google Scholar 

    4.
    Bromham, L., Hua, X., Cardillo, M., Schneemann, H. & Greenhill, S. J. Parasites and politics: why cross-cultural studies must control for relatedness, proximity and covariation. R. Soc. Open Sci. 5, 181100 (2018).
    PubMed  PubMed Central  Article  Google Scholar 

    5.
    Mace, R. & Holden, C. J. A phylogenetic approach to cultural evolution. Trends Ecol. Evol. 20, 116–121 (2005).
    PubMed  Article  Google Scholar 

    6.
    Freckleton, R. P. & Jetz, W. Space versus phylogeny: disentangling phylogenetic and spatial signals in comparative data. Proc. R. Soc. B 276, 21–30 (2008).
    Article  Google Scholar 

    7.
    Hua, X., Greenhill, S. J., Cardillo, M., Schneemann, H. & Bromham, L. The ecological drivers of variation in global language diversity. Nat. Commun. 10, 2047 (2019).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    8.
    Ohtsubo, Y. Adaptive ingredients against food spoilage in Japanese cuisine. Int. J. Food Sci. Nutr. 60, 677–687 (2009).
    PubMed  Article  Google Scholar 

    9.
    Murray, D. R. & Schaller, M. Historical prevalence of infectious diseases within 230 geopolitical regions: a tool for investigating origins of culture. J. Cross Cult. Psychol. 41, 99–108 (2010).
    Article  Google Scholar 

    10.
    Sherman, P. W. & Hash, G. A. Why vegetable recipes are not very spicy. Evol. Hum. Behav. 22, 147–163 (2001).
    PubMed  Article  Google Scholar 

    11.
    Havelaar, A. H. et al. World Health Organization global estimates and regional comparisons of the burden of foodborne disease in 2010. PLoS Med. 12, e1001923 (2015).
    PubMed  PubMed Central  Article  Google Scholar 

    12.
    Lewnard, J. A., Lo, N. C., Arinaminpathy, N., Frost, I. & Laxminarayan, R. Childhood vaccines and antibiotic use in low- and middle-income countries. Nature 581, 94–99 (2020).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    13.
    McMichael, A. J. & Beaglehole, R. The changing global context of public health. Lancet 356, 495–499 (2000).
    CAS  PubMed  Article  Google Scholar 

    14.
    Salomon, J. A. et al. Healthy life expectancy for 187 countries, 1990–2010: a systematic analysis for the Global Burden Disease Study 2010. Lancet 380, 2144–2162 (2012).
    PubMed  Article  Google Scholar 

    15.
    Kummu, M. & Varis, O. The world by latitudes: a global analysis of human population, development level and environment across the north–south axis over the past half century. Appl. Geogr. 31, 495–507 (2011).
    Article  Google Scholar 

    16.
    Johnell, O., Borgstrom, F., Jonsson, B. & Kanis, J. Latitude, socioeconomic prosperity, mobile phones and hip fracture risk. Osteoporos. Int. 18, 333–337 (2007).
    CAS  PubMed  Article  Google Scholar 

    17.
    Kanis, J. A. et al. Variations in latitude may or may not explain the worldwide variation in hip fracture incidence. Osteoporos. Int. 23, 2401–2402 (2012).
    Article  Google Scholar 

    18.
    Fisman, D. et al. Geographical variability in the likelihood of bloodstream infections due to Gram-negative bacteria: correlation with proximity to the equator and health care expenditure. PLoS ONE 9, e114548 (2014).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    19.
    Coccia, M. The effect of country wealth on incidence of breast cancer. Breast Cancer Res. Treat. 141, 225–229 (2013).
    PubMed  Article  Google Scholar 

    20.
    Buchter, B., Dunkel, M. & Li, J. Multiple sclerosis: a disease of affluence? Neuroepidemiology 39, 51–56 (2012).
    PubMed  Article  Google Scholar 

    21.
    Roberts, S. & Winters, J. Linguistic diversity and traffic accidents: Lessons from statistical studies of cultural traits. PLoS ONE 8, e70902 (2013).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    22.
    Guernier, V., Hochberg, M. E. & Guégan, J.-F. Ecology drives the worldwide distribution of human diseases. PLoS Biol. 2, e141 (2004).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    23.
    Jones, K. E. et al. Global trends in emerging infectious diseases. Nature 451, 990–993 (2008).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    24.
    Hawkins, B. A. et al. Energy, water, and broad-scale geographic patterns of species richness. Ecology 84, 3105–3117 (2003).
    Article  Google Scholar 

    25.
    Kreft, H. & Jetz, W. Global patterns and determinants of vascular plant diversity. Proc. Natl Acad. Sci. USA 104, 5925–5930 (2007).
    CAS  PubMed  Article  Google Scholar 

    26.
    Dunn, R. R., Davies, T. J., Harris, N. C. & Gavin, M. C. Global drivers of human pathogen richness and prevalence. Proc. R. Soc. B 277, 2587–2595 (2010).
    PubMed  Article  Google Scholar 

    27.
    Luck, G. W. A review of the relationships between human population density and biodiversity. Biol. Rev. 82, 607–645 (2007).
    PubMed  Article  Google Scholar 

    28.
    Collen, B. et al. Global patterns of freshwater species diversity, threat and endemism. Glob. Ecol. Biogeogr. 23, 40–51 (2014).
    PubMed  Article  Google Scholar 

    29.
    Just, M. G. et al. Global biogeographic regions in a human‐dominated world: the case of human diseases. Ecosphere 5, 1–21 (2014).
    Article  Google Scholar 

    30.
    Morand, S., Owers, K. & Bordes, F. in Confronting Emerging Zoonoses (eds Yamada, A. et al.) 27–41 (Springer, 2014).

    31.
    Turner, J. Spice: the History of a Temptation (Alfred A. Knopf, 2004).

    32.
    Kraft, K. H. et al. Multiple lines of evidence for the origin of domesticated chili pepper, Capsicum annuum, in Mexico. Proc. Natl Acad. Sci. USA 111, 6165–6170 (2014).
    CAS  PubMed  Article  Google Scholar 

    33.
    Portnoy, S. in The SAGE Encyclopedia of Food Issues Vol. 1 (ed. Albala, K.) 84–86 (SAGE Publications, 2015).

    34.
    Jain, A., Rakhi, N. & Bagler, G. Analysis of food pairing in regional cuisines of India. PLoS ONE 10, e0139539 (2015).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    35.
    Zhu, Y.-X. et al. Geography and similarity of regional cuisines in China. PLoS ONE 8, e79161 (2013).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    36.
    Kline, M. A., Shamsudheen, R. & Broesch, T. Variation is the universal: making cultural evolution work in developmental psychology. Philos. Trans. R. Soc. B 373, 20170059 (2018).
    Article  Google Scholar 

    37.
    Bagler, G. CulinaryDB (Indraprastha Institute of Information Technology Delhi, 2017); https://cosylab.iiitd.edu.in/culinarydb/

    38.
    Iranshahy, M. & Iranshahi, M. Traditional uses, phytochemistry and pharmacology of asafoetida (Ferula assa-foetida oleo-gum-resin)—a review. J. Ethnopharmacol. 134, 1–10 (2011).
    CAS  PubMed  Article  Google Scholar 

    39.
    Nakamura, Y. et al. Comparison of the glucosinolate–myrosinase systems among daikon (Raphanus sativus, Japanese white radish) varieties. J. Agric. Food Chem. 56, 2702–2707 (2008).
    CAS  PubMed  Article  Google Scholar 

    40.
    Gupta, S. & Abu-Ghannam, N. Recent developments in the application of seaweeds or seaweed extracts as a means for enhancing the safety and quality attributes of foods. Innov. Food Sci. Emerg. Technol. 12, 600–609 (2011).
    CAS  Article  Google Scholar 

    41.
    Devi, K. P., Suganthy, N., Kesika, P. & Pandian, S. K. Bioprotective properties of seaweeds: in vitro evaluation of antioxidant activity and antimicrobial activity against food borne bacteria in relation to polyphenolic content. BMC Complement. Altern. Med. 8, 1 (2008).
    Article  CAS  Google Scholar 

    42.
    Cox, S., Abu-Ghannam, N. & Gupta, S. An assessment of the antioxidant and antimicrobial activity of six species of edible Irish seaweeds. Int. Food Res. J. 17, 205–220 (2010).
    CAS  Google Scholar 

    43.
    Lipkin, A. et al. An antimicrobial peptide Ar-AMP from amaranth (Amaranthus retroflexus L.) seeds. Phytochemistry 66, 2426–2431 (2005).
    CAS  PubMed  Article  Google Scholar 

    44.
    Maiyo, Z., Ngure, R., Matasyoh, J. & Chepkorir, R. Phytochemical constituents and antimicrobial activity of leaf extracts of three Amaranthus plant species. Afr. J. Biotechnol. 9, 3178–3182 (2010).
    Google Scholar 

    45.
    Dan, S. Antibacterial activity of paeonol in vitro. Her. Med. 9, 009 (2012).
    Google Scholar 

    46.
    Uddin, G., Sadat, A. & Siddiqui, B. S. Phytochemical screening, in vitro antioxidant and antimicrobial activities of the crude fractions of Paeonia emodi Wall. Ex Royle. Middle East J. Sci. Res. 17, 367–373 (2013).
    Google Scholar 

    47.
    Joung, Y.-M. et al. Antioxidative and antimicrobial activities of lilium species extracts prepared from different aerial parts. Korean J. Food Sci. Technol. 39, 452–457 (2007).
    Google Scholar 

    48.
    He, J., Chen, L., Heber, D., Shi, W. & Lu, Q.-Y. Antibacterial compounds from Glycyrrhiza uralensis. J. Nat. Prod. 69, 121–124 (2006).
    CAS  PubMed  Article  Google Scholar 

    49.
    Dhingra, V., Pakki, S. R. & Narasu, M. L. Antimicrobial activity of artemisinin and its precursors. Curr. Sci. 78, 709–713 (2000).
    CAS  Google Scholar 

    50.
    Gupta, V. K. et al. Antimicrobial potential of Glycyrrhiza glabra roots. J. Ethnopharmacol. 116, 377–380 (2008).
    PubMed  Article  Google Scholar 

    51.
    Chen, C. et al. Chemical composition and antimicrobial and DPPH scavenging activity of essential oil of Toona sinensis (A. Juss.) Roem from China. BioResources 9, 5262–5278 (2014).
    Google Scholar 

    52.
    Arzanlou, M. & Bohlooli, S. Introducing of green garlic plant as a new source of allicin. Food Chem. 120, 179–183 (2010).
    CAS  Article  Google Scholar 

    53.
    Shittu, L. et al. Antibacterial and antifungal activities of essential oils of crude extracts of Sesame radiatum against some common pathogenic micro-organisms. Iran. J. Pharmacol. Ther. 6, 165–170 (2008).
    Google Scholar 

    54.
    Medina, E., Romero, C., Brenes, M. & de Castro, A. Antimicrobial activity of olive oil, vinegar, and various beverages against foodborne pathogens. J. Food Prot. 70, 1194–1199 (2007).
    CAS  PubMed  Article  Google Scholar 

    55.
    South, A. rworldmap: a new R package for mapping global data. R J. 3, 35–43 (2011).
    Article  Google Scholar 

    56.
    R Core Team. R: A Language and Environment for Statistical Computing http://www.R-project.org/ (R Foundation for Statistical Computing, 2016).

    57.
    GADM Maps and Data (GADM, 2012); https://www.gadm.org

    58.
    Bivand, R. et al. rgeos: interface to geometry engine—open source (GEOS) v.0.3-21 https://cran.r-project.org/package=rgeos (2016).

    59.
    Bromham, L. Curiously the same: swapping tools between linguistics and evolutionary biology. Biol. Philos. 32, 855–886 (2017).
    Article  Google Scholar 

    60.
    Mace, R. & Pagel, M. The comparative method in anthropology. Curr. Anthropol. 35, 549–564 (1994).
    Article  Google Scholar 

    61.
    Harvey, P. H. & Pagel, M. The Comparative Method in Evolutionary Biology (Oxford Univ. Press, 1991).

    62.
    Felsenstein, J. Phylogenies and the comparative method. Am. Nat. 125, 1–15 (1985).
    Article  Google Scholar 

    63.
    Miller, M. A. & Paige, J. C. Other food borne infections. Vet. Clin. North Am. Food Anim. Pract. 14, 71–89 (1998).
    CAS  PubMed  Article  Google Scholar 

    64.
    Fisman, D. N. & Laupland, K. Guess who’s coming to dinner? Emerging foodborne zoonoses. Can. J. Infect. Dis. Med. Microbiol. 21, 8–10 (2010).
    PubMed  PubMed Central  Article  Google Scholar 

    65.
    Sookias, R. B., Passmore, S. & Atkinson, Q. D. Deep cultural ancestry and human development indicators across nation states. R. Soc. Open Sci. 5, 171411 (2018).
    PubMed  PubMed Central  Article  Google Scholar 

    66.
    Johnson, P. C. D., Barry, S. J. E., Ferguson, H. M. & Muller, P. Power analysis for generalized linear mixed models in ecology and evolution. Methods Ecol. Evol. 6, 133–142 (2015).
    PubMed  Article  Google Scholar 

    67.
    O’Hagan, A. Kendall’s Advanced Theory Of Statistics Vol. 2B: Bayesian Inference (Halsted, 1994).

    68.
    Bonds, M. H., Keenan, D. C., Rohani, P. & Sachs, J. D. Poverty trap formed by the ecology of infectious diseases. Proc. R. Soc. B: 277, 1185–1192 (2010).
    Article  Google Scholar  More

  • in

    Wolbachia affects mitochondrial population structure in two systems of closely related Palaearctic blue butterflies

    1.
    Jiggins, F. M. Male-killing Wolbachia and mitochondrial DNA: Selective sweeps, hybrid introgression and parasite population dynamics. Genetics 164, 5–12 (2003).
    CAS  PubMed  PubMed Central  Google Scholar 
    2.
    Poinsot, D., Charlat, S. & Merçot, H. On the mechanism of Wolbachia-induced cytoplasmic incompatibility: Confronting the models with the facts. BioEssays 25, 259–265 (2003).
    PubMed  Article  Google Scholar 

    3.
    Werren, J. H., Baldo, L. & Clark, M. E. Wolbachia: Master manipulators of invertebrate biology. Nat. Rev. Microbiol. 6, 741–751 (2008).
    CAS  PubMed  Article  Google Scholar 

    4.
    Vavre, F., Fleury, F., Lepetit, D., Fouillet, P. & Boulétreau, M. Phylogenetic evidence for horizontal transmission of Wolbachia in host-parasitoid associations. Mol. Biol. Evol. 16, 1711–1723 (1999).
    CAS  PubMed  Article  Google Scholar 

    5.
    Sintupachee, S., Milne, J. R., Poonchaisri, S., Baimai, V. & Kittayapong, P. Closely related Wolbachia strains within the pumpkin arthropod community and the potential for horizontal transmission via the plant. Microb. Ecol. 51, 294–301 (2006).
    CAS  PubMed  Article  Google Scholar 

    6.
    Li, S.-J. et al. Plantmediated horizontal transmission of Wolbachia between whiteflies. ISME J. 11, 1019–1028 (2017).
    CAS  PubMed  Article  Google Scholar 

    7.
    Turelli, M. & Hoffmann, A. A. Rapid spread of an inherited incompatibility factor in California Drosophila. Nature 353, 440 (1991).
    ADS  CAS  PubMed  Article  Google Scholar 

    8.
    Oliveira, D. C. S. G., Raychoudhury, R., Lavrov, D. V. & Werren, J. H. Rapidly evolving mitochondrial genome and directional selection in mitochondrial genes in the parasitic wasp Nasonia (Hymenoptera: Pteromalidae). Mol. Biol. Evol. 25, 2167–2180 (2008).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    9.
    Raychoudhury, R. et al. Phylogeography of Nasonia vitripennis (Hymenoptera) indicates a mitochondrial–Wolbachia sweep in North America. Heredity 104, 318–326 (2010).
    CAS  PubMed  Article  Google Scholar 

    10.
    Telschow, A., Gadau, J., Werren, J. H. & Kobayashi, Y. Genetic incompatibilities between mitochondria and nuclear genes: Effect on gene flow and speciation. Front. Genet. 10, 62 (2019).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    11.
    Kodandaramaiah, U., Simonsen, T. J., Bromilow, S., Wahlberg, N. & Sperling, F. Deceptive single-locus taxonomy and phylogeography: Wolbachia-associated divergence in mitochondrial DNA is not reflected in morphology and nuclear markers in a butterfly species. Ecol. Evol. 3, 5167–5176 (2013).
    PubMed  PubMed Central  Article  Google Scholar 

    12.
    Ritter, S. et al. Wolbachia infections mimic cryptic speciation in two parasitic butterfly species, Phengaris teleius and P. nausithous (Lepidoptera: Lycaenidae). PLoS ONE 8, e78107 (2013).
    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

    13.
    Whitworth, T. L., Dawson, R. D., Magalon, H. & Baudry, E. DNA barcoding cannot reliably identify species of the blowfly genus Protocalliphora (Diptera: Calliphoridae). Proc. R. Soc. B Biol. Sci. 274, 1731–1739 (2007).
    CAS  Article  Google Scholar 

    14.
    Barton, N. & Bengtsson, B. O. The barrier to genetic exchange between hybridising populations. Heredity 57, 357–376 (1986).
    PubMed  Article  Google Scholar 

    15.
    Vavre, F., Fleury, F., Varaldi, J., Fouillet, P. & Boulétreau, M. Infection polymorphism and cytoplasmic incompatibility in Hymenoptera-Wolbachia associations. Heredity 88, 361–365 (2002).
    CAS  PubMed  Article  Google Scholar 

    16.
    Jaenike, J., Dyer, K. A., Cornish, C. & Minhas, M. S. Asymmetrical reinforcement and Wolbachia infection in Drosophila. PLoS Biol. 4, e325 (2006).
    PubMed  PubMed Central  Article  Google Scholar 

    17.
    Telschow, A., Flor, M., Kobayashi, Y., Hammerstein, P. & Werren, J. H. Wolbachia-induced unidirectional cytoplasmic incompatibility and speciation: Mainland-island model. PLoS ONE 2, e701 (2007).
    ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

    18.
    Flor, M., Hammerstein, P. & Telschow, A. Wolbachia-induced unidirectional cytoplasmic incompatibility and the stability of infection polymorphism in parapatric host populations. J. Evol. Biol. 20, 696–706 (2007).
    CAS  PubMed  Article  Google Scholar 

    19.
    Graham, R. I. & Wilson, K. Male-killing Wolbachia and mitochondrial selective sweep in a migratory African insect. BMC Evol. Biol. 12, 204 (2012).
    PubMed  PubMed Central  Article  Google Scholar 

    20.
    Ahmed, M. Z., Breinholt, J. W. & Kawahara, A. Y. Evidence for common horizontal transmission of Wolbachia among butterflies and moths. BMC Evol. Biol. 16, 118 (2016).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    21.
    Salunkhe, R. C., Narkhede, K. P. & Shouche, Y. S. Distribution and evolutionary impact of Wolbachia on butterfly hosts. Indian J. Microbiol. 54, 249 (2014).
    PubMed  PubMed Central  Article  Google Scholar 

    22.
    Talavera, G., Lukhtanov, V. A., Pierce, N. E. & Vila, R. Establishing criteria for higher-level classification using molecular data: The systematics of Polyommatus blue butterflies (Lepidoptera, Lycaenidae). Cladistics 29, 166–192 (2013).
    Article  Google Scholar 

    23.
    Espeland, M. et al. A Comprehensive and dated phylogenomic analysis of butterflies. Curr. Biol. 28, 770-778.e5 (2018).
    CAS  PubMed  Article  Google Scholar 

    24.
    Dincă, V., Lee, K. M., Vila, R. & Mutanen, M. The conundrum of species delimitation: A genomic perspective on a mitogenetically super-variable butterfly. Proc. R. Soc. B Biol. Sci. 286, 20191311 (2019).
    Article  CAS  Google Scholar 

    25.
    Gaunet, A. et al. Two consecutive Wolbachia-mediated mitochondrial introgressions obscure taxonomy in Palearctic swallowtail butterflies (Lepidoptera, Papilionidae). Zool. Scr. 48, 507–519 (2019).
    Article  Google Scholar 

    26.
    Dinca, V., Zakharov, E. V., Hebert, P. D. N. & Vila, R. Complete DNA barcode reference library for a country’s butterfly fauna reveals high performance for temperate Europe. Proc. R. Soc. B Biol. Sci. 278, 347–355 (2011).
    Article  Google Scholar 

    27.
    Ugelvig, L. V., Vila, R., Pierce, N. E. & Nash, D. R. A phylogenetic revision of the Glaucopsyche section (Lepidoptera: Lycaenidae), with special focus on the Phengaris-Maculinea clade. Mol. Phylogenet. Evol. 61, 237–243 (2011).
    CAS  PubMed  Article  Google Scholar 

    28.
    Sañudo-Restrepo, C. P., Dincă, V., Talavera, G. & Vila, R. Biogeography and systematics of Aricia butterflies (Lepidoptera, Lycaenidae). Mol. Phylogenet. Evol. 66, 369–379 (2013).
    PubMed  Article  Google Scholar 

    29.
    Todisco, V. et al. Molecular phylogeny of the Palaearctic butterfly genus Pseudophilotes (Lepidoptera: Lycaenidae) with focus on the Sardinian endemic P. barbagiae. BMC Zool. 3, 4 (2018).
    Article  Google Scholar 

    30.
    Sucháčková Bartoňová, A., Beneš, J., Fric, Z. F. & Konvička, M. Genetic confirmation of Aricia artaxerxes (Fabricius, 1793) (Lepidoptera, Lycaenidae) in the Czech Republic, its conservation significance and biogeographic context. Nota Lepidopterol. 42(2), 163–176 (2019).
    Article  Google Scholar 

    31.
    Kames, P. Die Aufklärung des Differenzierungsgrades und der Phylogenese der beiden Aricia-Arten agestis Den. et Schiff. und artaxerxes Fabr. (allous G.-Hb.) mit Hilfe von Eizuchten und Kreuzungsversuchen (Lep., Lycaenidae). Mitt. Entomol. Ges. Basel, N. F. 26, 7–13, 29–64 (1976).

    32.
    Korb, S., Faltynek Fric, Z. & Bartonova, A. On the status of Aricia cf. scythissa (Nekrutenko, 1985) (Lepidoptera: Lycaenidae) based on molecular investigations. Euroasian Entomol. J. 14, 237–240 (2015).
    Google Scholar 

    33.
    Wiemers, M., Chazot, N., Wheat, C. W., Schweiger, O. & Wahlberg, N. A complete time-calibrated multi-gene phylogeny of the European butterflies. ZooKeys 938, 97–124 (2020).
    PubMed  PubMed Central  Article  Google Scholar 

    34.
    Settele, J., Steiner, R., Reinhardt, R., Feldmann, R. & Hermann, G. Schmetterlinge: Die Tagfalter Deutschlands (Ulmer Eugen Verlag, Stuttgart, 2015).
    Google Scholar 

    35.
    Monteiro, A. & Pierce, N. E. Phylogeny of Bicyclus (Lepidoptera: Nymphalidae) inferred from COI, COII, and EF-1alpha gene sequences. Mol. Phylogenet. Evol. 18, 264–281 (2001).
    CAS  PubMed  Article  Google Scholar 

    36.
    Wahlberg, N. & Wheat, C. W. Genomic outposts serve the phylogenomic pioneers: Designing novel nuclear markers for genomic DNA extractions of lepidoptera. Syst. Biol. 57, 231–242 (2008).
    CAS  PubMed  Article  Google Scholar 

    37.
    Braig, H. R., Zhou, W., Dobson, S. L. & O’Neill, S. L. Cloning and characterization of a gene encoding the major surface protein of the bacterial endosymbiont Wolbachia pipientis. J. Bacteriol. 180, 2373–2378 (1998).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    38.
    Sahoo, R. K. et al. Evolution of Hypolimnas butterflies (Nymphalidae): Out-of-Africa origin and Wolbachia-mediated introgression. Mol. Phylogenet. Evol. 123, 50–58 (2018).
    PubMed  Article  Google Scholar 

    39.
    Baldo, L. et al. Multilocus sequence typing system for the endosymbiont Wolbachia pipientis. Appl. Environ. Microbiol. 72, 7098–7110 (2006).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    40.
    Kearse, M. Geneious basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics 28, 1647–1649 (2012).
    PubMed  PubMed Central  Article  Google Scholar 

    41.
    Kajtoch, Ł et al. Using host species traits to understand the Wolbachia infection distribution across terrestrial beetles. Sci. Rep. 9, 847 (2019).
    ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

    42.
    Ratnasingham, S. & Hebert, P. D. N. bold: The Barcode of Life Data System (http://www.barcodinglife.org). Mol. Ecol. Notes 7, 355–364 (2007).

    43.
    Clement, M., Posada, D. & Crandall, K. A. TCS: A computer program to estimate gene genealogies. Mol. Ecol. 9, 1657–1659 (2000).
    CAS  PubMed  Article  Google Scholar 

    44.
    Leigh, J. W. & Bryant, D. POPART: Full-feature software for haplotype network construction. Methods Ecol. Evol. 6, 1110–1116 (2015).
    Article  Google Scholar 

    45.
    Cheng, L., Connor, T. R., Sirén, J., Aanensen, D. M. & Corander, J. Hierarchical and spatially explicit clustering of DNA sequences with BAPS software. Mol. Biol. Evol. 30, 1224–1228 (2013).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    46.
    Tonkin-Hill, G., Lees, J. A., Bentley, S. D., Frost, S. D. W. & Corander, J. RhierBAPS: An R implementation of the population clustering algorithm hierBAPS. Wellcome Open Res. 3 (2018).

    47.
    R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. https://www.R-project.org/ (2019).

    48.
    Librado, P. & Rozas, J. DnaSP v5: A software for comprehensive analysis of DNA polymorphism data. Bioinformatics 25, 1451–1452 (2009).
    CAS  Article  Google Scholar 

    49.
    Dellicour, S. & Mardulyn, P. SPADS 1.0: A toolbox to perform spatial analyses on DNA sequence data sets. Mol. Ecol. Resour. 14, 647–651 (2014).
    PubMed  Article  Google Scholar 

    50.
    Watson, D. F. & Philip, G. M. A Refinement of inverse distance weighted interpolation. Geoprocessing 2, 315–327 (1985).
    Google Scholar 

    51.
    Manni, F., Guérard, E. & Heyer, E. Geographic patterns of (genetic, morphologic, linguistic) variation: How barriers can be detected by using Monmonier’s algorithm. Hum. Biol. 76, 173–190 (2004).
    PubMed  Article  Google Scholar 

    52.
    Suchard, M. A. et al. Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10. Virus Evol. 4, 016 (2018).
    Article  Google Scholar 

    53.
    Posada, D. jModelTest: Phylogenetic model averaging. Mol. Biol. Evol. 25, 1253–1256 (2008).
    CAS  PubMed  Article  Google Scholar 

    54.
    Rambaut, A., Suchard, M. A., Xie, D. & Drummond, A. J. Tracer v1.6. http://tree.bio.ed.ac.uk/software/tracer/. (2014).

    55.
    Ronquist, F. & Huelsenbeck, J. P. MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics 19, 1572–1574 (2003).
    CAS  PubMed  Article  Google Scholar 

    56.
    Miller, M. A., Pfeiffer, W. & Schwartz, T. Creating the CIPRES Science Gateway for inference of large phylogenetic trees. in 2010 Gateway Computing Environments Workshop (GCE) 1–8 (2010).

    57.
    Aagaard, K. et al. Phylogenetic relationships in brown argus butterflies (Lepidoptera: Lycaenidae: Aricia) from northwestern Europe. Biol. J. Linn. Soc. 75, 27–37 (2002).
    Article  Google Scholar 

    58.
    Hernández-Roldán, J. L. et al. Integrative analyses unveil speciation linked to host plant shift in Spialia butterflies. Mol. Ecol. 25, 4267–4284 (2016).
    PubMed  Article  Google Scholar 

    59.
    Jiang, W. et al. Wolbachia infection status and genetic structure in natural populations of Polytremis nascens (Lepidoptera: Hesperiidae). Infect. Genet. Evol. 27, 202–211 (2014).
    PubMed  Article  Google Scholar 

    60.
    Mallet, J., Wynne, I. R. & Thomas, C. D. Hybridisation and climate change: Brown argus butterflies in Britain (Polyommatus subgenus Aricia). Insect Conserv. Divers. 4, 192–199 (2011).
    Article  Google Scholar 

    61.
    Gutzwiller, F., Dedeine, F., Kaiser, W., Giron, D. & Lopez-Vaamonde, C. Correlation between the green-island phenotype and Wolbachia infections during the evolutionary diversification of Gracillariidae leaf-mining moths. Ecol. Evol. 5, 4049–4062 (2015).
    PubMed  PubMed Central  Article  Google Scholar 

    62.
    Mascarenhas, R. O., Prezotto, L. F., Perondini, A. L. P., Marino, C. L. & Selivon, D. Wolbachia in guilds of Anastrepha fruit flies (Tephritidae) and parasitoid wasps (Braconidae). Genet. Mol. Biol. 39, 600–610 (2016).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    63.
    Sucháčková Bartoňová, A. et al. Recently lost connectivity in the Western Palaearctic steppes: The case of a scarce specialist butterfly. Conserv. Genet. 21, 561–575 (2020).
    Article  Google Scholar 

    64.
    Schmitt, T. & Varga, Z. Extra-Mediterranean refugia: The rule and not the exception?. Front. Zool. 9, 1–12 (2012).
    Article  Google Scholar 

    65.
    de Lattin, G. Grundriss der Zoogeographie (VEB Gustav Fischer Verlag, Jena, 1967).
    Google Scholar 

    66.
    Hewitt, G. M. Some genetic consequences of ice ages, and their role in divergence and speciation. Biol. J. Linn. Soc. 58, 247–276 (1996).
    Article  Google Scholar 

    67.
    Schmitt, T. Molecular biogeography of Europe: Pleistocene cycles and postglacial trends. Front. Zool. 4, 11 (2007).
    PubMed  PubMed Central  Article  Google Scholar 

    68.
    Hampe, A. & Petit, R. J. Conserving biodiversity under climate change: The rear edge matters. Ecol. Lett. 8, 461–467 (2005).
    PubMed  Article  Google Scholar 

    69.
    Heiser, M., Dapporto, L. & Schmitt, T. Coupling impoverishment analysis and partitioning of beta diversity allows a comprehensive description of Odonata biogeography in the Western Mediterranean. Org. Divers. Evol. 14, 203–214 (2014).
    Article  Google Scholar 

    70.
    Vodă, R. et al. Historical and contemporary factors generate unique butterfly communities on islands. Sci. Rep. 6, 28828 (2016).
    ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

    71.
    Scalercio, S. et al. How long is 3 km for a butterfly? Ecological constraints and functional traits explain high mitochondrial genetic diversity between Sicily and the Italian Peninsula. J. Anim. Ecol. 89, 2013–2026 (2020).
    PubMed  Article  Google Scholar 

    72.
    Descimon, H. & Mallet, J. Bad species. in Ecology and Evolution of European Butterflies (Oxford University Press, Oxford, 2009).

    73.
    Habel, J. C., Schmitt, T. & Müller, P. The fourth paradigm pattern of post-glacial range expansion of European terrestrial species: The phylogeography of the Marbled White butterfly (Satyrinae, Lepidoptera). J. Biogeogr. 32, 1489–1497 (2005).
    Article  Google Scholar 

    74.
    Varga, Z. Das Prinzip der areal-analytischen Methode in der Zoogeographie und die Faunenelement-Einteilung der europäischen Tagschmetterlinge (Lepidoptera: Diurna). Acta Biol. Debrecina 14, 223–285 (1977).
    Google Scholar 

    75.
    Schmitt, T. & Zimmermann, M. To hybridize or not to hybridize: What separates two genetic lineages of the Chalk-hill Blue Polyommatus coridon (Lycaenidae, Lepidoptera) along their secondary contact zone throughout eastern Central Europe?. J. Zool. Syst. Evol. Res. 50, 106–115 (2012).
    Article  Google Scholar 

    76.
    Janoušek, V. et al. Genome-wide architecture of reproductive isolation in a naturally occurring hybrid zone between Musmusculus musculus and M. m. domesticus. Mol. Ecol. 21, 3032–3047 (2012).
    PubMed  Article  Google Scholar 

    77.
    Nürnberger, B., Lohse, K., Fijarczyk, A., Szymura, J. M. & Blaxter, M. L. Para-allopatry in hybridizing fire-bellied toads (Bombinabombina and B. variegata): Inference from transcriptome-wide coalescence analyses. Evolution 70, 1803–1818 (2016).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    78.
    Vitali, F. & Schmitt, T. Ecological patterns strongly impact the biogeography of western Palaearctic longhorn beetles (Coleoptera: Cerambycoidea). Org. Divers. Evol. 17, 163–180 (2017).
    Article  Google Scholar 

    79.
    Narita, S., Nomura, M., Kato, Y. & Fukatsu, T. Genetic structure of sibling butterfly species affected by Wolbachia infection sweep: Evolutionary and biogeographical implications. Mol. Ecol. 15, 1095–1108 (2006).
    CAS  PubMed  Article  Google Scholar 

    80.
    Kageyama, S. et al. Feminizing Wolbachia endosymbiont disrupts maternal sex chromosome inheritance in a butterfly species. Evol. Lett. 1, 232–244 (2017).
    PubMed  PubMed Central  Article  Google Scholar 

    81.
    Nosil, P., Harmon, L. J. & Seehausen, O. Ecological explanations for (incomplete) speciation. Trends Ecol. Evol. (Amst.) 24, 145–156 (2009).
    Article  Google Scholar 

    82.
    Talavera, G., Lukhtanov, V. A., Rieppel, L., Pierce, N. E. & Vila, R. In the shadow of phylogenetic uncertainty: The recent diversification of Lysandra butterflies through chromosomal change. Mol. Phylogenet. Evol. 69, 469–478 (2013).
    PubMed  Article  Google Scholar 

    83.
    Kühne, G., Kosuch, J., Hochkirch, A. & Schmitt, T. Extra-Mediterranean glacial refugia in a Mediterranean faunal element: The phylogeography of the chalk-hill blue Polyommatus coridon (Lepidoptera, Lycaenidae). Sci. Rep. 7, srep43533 (2017).
    ADS  Article  Google Scholar 

    84.
    Wiemers, M., Keller, A. & Wolf, M. ITS2 secondary structure improves phylogeny estimation in a radiation of blue butterflies of the subgenus Agrodiaetus (Lepidoptera: Lycaenidae: Polyommatus). BMC Evol. Biol. 9, 300 (2009).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    85.
    Duron, O. & Hurst, G. D. Arthropods and inherited bacteria: From counting the symbionts to understanding how symbionts count. BMC Biol. 11, 45 (2013).
    PubMed  PubMed Central  Article  Google Scholar 

    86.
    Bailly-Bechet, M. et al. How long does Wolbachia remain on board?. Mol. Biol. Evol. 34, 1183–1193 (2017).
    CAS  PubMed  Article  Google Scholar  More

  • in

    Comparison between 16S rRNA and shotgun sequencing data for the taxonomic characterization of the gut microbiota

    Relative species abundance distribution
    In order to evaluate sample quality, we analysed both the Relative Species Abundance distribution (RSA) and the rarefaction curves. For each sample, we compared the RSA derived by shotgun and 16S sequencing. RSA histograms in logarithmic scale show that the distributions obtained by shotgun and 16S have similar shape at phylum level (Fig. 1a, b). In Fig. 1b, the 16S sample is characterized by a more patchy distribution, having identified less phyla. At phylum level, both strategies produce positively skewed samples in the log2-transformed distributions, except for 16S outliers, because none of the phyla is significantly rare (Fig. 2a).
    Figure 1

    RSA histograms in logarithmic scale (Preston plots 21) of bacterial abundances in one sample selected as anexample (caeca25): (a) genera sampled by shotgun sequencing, (b) genera sampled by 16S rRNA sequencing, (c) phyla sampled by shotgun sequencing and (d) phyla sampled by 16S sequencing.

    Full size image

    Figure 2

    Box plot of the RSA skewness of bacterial communities at (a) phylum level and (b) genus level. Bacterial communities are sampled with (left) shotgun sequencing and (right) 16S sequencing.

    Full size image

    On the other hand, at genus level, the two strategies display different shapes (Fig. 1c, d, Supplementary Fig. S1, S2, S3, S4). Indeed, the log2-transformed distributions derived by shotgun sequencing generally have a skewness closer to zero compared to those obtained by 16S, i.e. are more symmetrical (Figure 2b): a paired Student’s t-test on the skewness shows a significant difference between them (P = 8·10–6). This indicates that shotgun samples are characterized by a higher sampling size. According to Preston, left-skewed shapes of the RSA can be explained as artefacts of small sample size21,22, since insufficient sampling of the original space produces a truncation of the left tail of the RSA, increasing its skewness.
    In shotgun samples, the RSA skewness at genus level is related to the total number of reads (Supplementary Fig. S5): the shotgun samples with the lowest total number of reads have the largest skewness. Specifically, Supplementary Figure S5 shows that shotgun samples cluster in two groups, one characterized by a low number of reads (# reads  500,000, 50/78 samples) and a less skewed RSA.
    Noticeably, the high-skewness group includes all 9 samples from 1st day, all 15 crop samples from 14th day and 4 out of 18 crop samples from 35th day. The samples collected at day 1 were very poor in terms of biomass and the crop samples contained more feed residues than caecal samples, making the DNA extraction less efficient both in terms of DNA quantity and quality. For the comparative analysis we removed samples with less than 500,000 reads being characterized by a low quality. This choice was corroborated by the analysis of the rarefaction curves, showing that shotgun samples with less than 500,000 reads do not reach a plateau in terms of identified genera (Supplementary Fig. S6). All the 50 samples included in the comparative analysis have a total number of reads  > 500,000 and a skewness lower than the median of 16S samples, indicating a good sampling depth. Since included samples were characterized by a high microbial load, we are confident to extend the results of the following analyses only to samples with few contaminant DNA and low cross-contaminations. Nonetheless, we have shown that shotgun samples have a RSA similar to 16S samples when a low number of total reads is available, thus hypothesizing that in differential analyses carried on samples with a low microbial load regime, shotgun sequencing could perform similarly to 16S sequencing or even worse.
    For a balanced comparison, also 16S samples corresponding to the discarded shotgun samples were removed.
    Differential analysis for the experimental conditions
    Since in many situations a metagenomic analysis is used to discriminate between different experimental conditions, we compared the results of differential analysis performed on reads obtained by the two strategies. To this aim, we analysed the fold changes of genera abundances between compartments of the GI tract and between sampling times (Fig. 3 for caeca vs crop, Supplementary Fig. S7 for 14th vs. 35th day) common to both sequencing strategies (288 genera for caeca vs crop, and 246 for 14th vs. 45th day). Comparing the genera abundances between caeca and crop, 16S identified 108 statistically significant differences (adjusted P  More

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    Ancient CO2 levels favor nitrogen fixing plants over a broader range of soil N compared to present

    1.
    Tajika, E. Climate change during the last 150 million years: Reconstructing from a carbon cycle model. Earth Planet Sci. Lett. 160, 659–707 (1998).
    Article  Google Scholar 
    2.
    Li, H.-L. et al. Large-scale phylogenetic analyses reveal multiple gains of actinorhizal nitrogen-fixing symbioses in angiosperms associated with climate change. Sci. Rep. 5, 14023 (2015).
    ADS  PubMed  PubMed Central  Article  Google Scholar 

    3.
    van Velzen, R., Doyle, J. J. & Geurts, R. A resurrected scenario: Single gain and massive loss of nitrogen-fixing nodulation. Trends Plant Sci. 24, 49–57 (2019).
    PubMed  Article  CAS  PubMed Central  Google Scholar 

    4.
    Griesmann, M. et al. Phylogenomics reveals multiple losses of nitrogen-fixing root nodule symbiosis. Science 361, eaat1743 (2018).
    PubMed  Article  CAS  PubMed Central  Google Scholar 

    5.
    Menge, D. N. L. & Crews, T. E. Can evolutionary constraints explain the rarity of nitrogen-fixing trees in high-latitude forests?. New Phytol. 211, 1195–1201 (2016).
    PubMed  Article  PubMed Central  Google Scholar 

    6.
    Menge, D. N. L. et al. Nitrogen-fixing tree abundance in higher-latitude North America is not constrained by diversity. Ecol. Lett. 20, 842–851 (2017).
    ADS  PubMed  Article  PubMed Central  Google Scholar 

    7.
    Tedersoo, L. et al. Global database of plants with root-symbiotic nitrogen fixation: NodDB. J. Veg. Sci. 29, 560–568 (2018).
    Article  Google Scholar 

    8.
    Swensen, S. M. & Benson, D. R. Evolution of actinorhizal host plants and Frankia endosymbionts. In Nitrogen-fixing Actinorhizal Symbioses, 73–104 (Springer Netherlands, 2008).

    9.
    Houlton, B. Z., Wang, Y.-P., Vitousek, P. M. & Field, C. B. A unifying framework for dinitrogen fixation in the terrestrial biosphere. Nature 454, 327–330 (2008).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    10.
    Luo, Y. et al. Progressive nitrogen limitation of ecosystem responses to rising atmospheric carbon dioxide. Bioscience 54, 731 (2004).
    Article  Google Scholar 

    11.
    Cheng, W., Inubushi, K., Yagi, K., Sakai, H. & Kobayashi, K. Effects of elevated carbon dioxide concentration on biological nitrogen fixation, nitrogen mineralization and carbon decomposition in submerged rice soil. Biol. Fertil. Soils. 34, 7–13 (2001).
    CAS  Article  Google Scholar 

    12.
    Ainsworth, E. A. & Long, S. P. What have we learned from 15 years of free-air CO2 enrichment (FACE)? A meta-analytic review of the responses of photosynthesis, canopy properties and plant production to rising CO2. New Phytol. 165, 351–372 (2004).
    Article  Google Scholar 

    13.
    Pawlowski, K. & Newton, W. E. Nitrogen-fixing Actinorhizal Symbioses. (Springer Netherlands, 2008). https://doi.org/10.1007/978-1-4020-3547-0.

    14.
    Dentener, F. et al. Nitrogen and sulfur deposition on regional and global scales: A multimodel evaluation. Glob. Biogeochem. Cycles. 20, GB4003 (2006).
    ADS  Article  CAS  Google Scholar 

    15.
    Vitousek, P. M. et al. Human alteration of the global nitrogen cycle: Sources and consequences. Ecol. Appl. 7, 737–750 (1997).
    Google Scholar 

    16.
    Benjamin, W. S. et al. Spatially robust estimates of biological nitrogen (N) fixation imply substantial human alteration of the tropical N cycle. PNAS 111, 8101–8106 (2014).
    Article  CAS  Google Scholar 

    17.
    Li, X. et al. Seasonal and spatial variations of bulk nitrogen deposition and the impacts on the carbon cycle in the arid/semiarid grassland of inner Mongolia, China. PLoS ONE 10, e0144689 (2015).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    18.
    Lamarque, J. F. et al. Assessing future nitrogen deposition and carbon cycle feedback using a multimodel approach: Analysis of nitrogen deposition. J. Geophys. Res. Atmos. 110, D19303 (2005).
    ADS  Article  Google Scholar 

    19.
    Tian, D. & Niu, S. A global analysis of soil acidification caused by nitrogen addition. Environ. Res. Lett. 10, 24019 (2015).
    Article  CAS  Google Scholar 

    20.
    Binkley, D. & Högberg, P. Tamm review: Revisiting the influence of nitrogen deposition on Swedish forests. For. Ecol. Manag. 368, 222–239 (2016).
    Article  Google Scholar 

    21.
    Lee, J. A. Unintentional experiments with terrestrial ecosystems: Ecological effects of sulphur and nitrogen pollutants. J. Ecol. 86, 1–12 (1998).
    CAS  Article  Google Scholar 

    22.
    Southon, G. E., Field, C., Caporn, S. J. M., Britton, A. J. & Power, S. A. Nitrogen deposition reduces plant diversity and alters ecosystem functioning: Field-scale evidence from a nationwide survey of UK heathlands. PLoS ONE 8, e59031 (2013).
    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

    23.
    Vitousek, P. M., Menge, D. N. L., Reed, S. C. & Cleveland, C. C. Biological nitrogen fixation: Rates, patterns and ecological controls in terrestrial ecosystems. Philos. Trans. R. Soc. B. 368, 20130119 (2013).
    Article  CAS  Google Scholar 

    24.
    Skogen, K. A., Holsinger, K. E. & Cardon, Z. G. Nitrogen deposition, competition and the decline of a regionally threatened legume, Desmodium cuspidatum. Oecologia 165, 261–269 (2011).
    ADS  PubMed  Article  PubMed Central  Google Scholar 

    25.
    Salvagiotti, F. et al. Growth and nitrogen fixation in high-yielding soybean: Impact of nitrogen fertilization. Agron J. 101, 958–970 (2009).
    CAS  Article  Google Scholar 

    26.
    Markham, J. H. & Zekveld, C. Nitrogen fixation makes biomass allocation to roots independent of soil nitrogen supply. Can. J. Bot. 85, 787–793 (2007).
    CAS  Article  Google Scholar 

    27.
    Coley, P. D. Possible effects of climate change on plant/herbivore interactions in moist tropical forests. Clim. Change. 39, 455–472 (1998).
    Article  Google Scholar 

    28.
    Coley, P. D., Massa, M., Lovelock, C. E. & Winter, K. Effects of elevated CO2 on foliar chemistry of saplings of nine species of tropical tree. Oecologia 133, 62–69 (2002).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    29.
    Roger, M. G., Damian, J. B. & Jason, L. L. The effects of elevated [CO2] on the C:N and C:P mass ratios of plant tissues. Plant Soil 224, 1–14 (2000).
    Article  Google Scholar 

    30.
    McLauchlan, K. K., Williams, J. J., Craine, J. M. & Jeffers, E. S. Changes in global nitrogen cycling during the Holocene epoch. Nature 495, 352–355 (2013).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    31.
    Hossain, M. A., Ishimine, Y., Akamine, H. & Kuramochi, H. Effect of nitrogen fertilizer application on growth, biomass production and N-uptake of torpedograss (Panicum repens L.). Weed Biol. Manag. 4, 86–94 (2004).
    CAS  Article  Google Scholar 

    32.
    Thomas, R. B., Bashkin, M. A. & Richter, D. D. Nitrogen inhibition of nodulation and N2 fixation of a tropical N2-fixing tree (Gliricidia sepium) grown in elevated atmospheric CO2. New Phytol. 145, 233–243 (2000).
    CAS  Article  Google Scholar 

    33.
    Dordas, C. A. & Sioulas, C. Safflower yield, chlorophyll content, photosynthesis, and water use efficiency response to nitrogen fertilization under rainfed conditions. Ind. Crops Prod. 27, 75–85 (2008).
    CAS  Article  Google Scholar 

    34.
    Xu, D. et al. Interactive effects of nitrogen and silicon addition on growth of five common plant species and structure of plant community in alpine meadow. CATENA 169, 80–89 (2018).
    CAS  Article  Google Scholar 

    35.
    Roy, A. & Bousquet, J. The evolution of the actinorhizal symbiosis through phylogenetic analysis of host plants. Acta Bot. Gall 143, 635–650 (1996).
    Article  Google Scholar 

    36.
    Swensen, S. M. The evolution of actinorhizal symbioses: Evidence for multiple origins of the symbiotic association. Am. J. Bot. 83, 1503–1512 (1996).
    Article  Google Scholar 

    37.
    van Velzen, R. et al. Comparative genomics of the nonlegume Parasponia reveals insights into evolution of nitrogen-fixing rhizobium symbioses. Proc. Natl. Acad. Sci. 115, E4700–E4709 (2018).
    PubMed  Article  CAS  PubMed Central  Google Scholar 

    38.
    Rogers, A., Ainsworth, E. A. & Leakey, A. D. B. Will elevated carbon dioxide concentration amplify the benefits of nitrogen fixation in legumes?. Plant Physiol. 151, 1009–1016 (2009).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    39.
    DeLuca, T. H., Zackrisson, O., Gundale, M. J. & Nilsson, M. C. Ecosystem feedbacks and nitrogen fixation in boreal forests. Science 320, 1181 (2008).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    40.
    Zheng, M., Zhou, Z., Luo, Y., Zhao, P. & Mo, J. Global pattern and controls of biological nitrogen fixation under nutrient enrichment: A meta-analysis. Glob. Change Biol. 25, 3018–3030 (2019).
    ADS  Article  Google Scholar 

    41.
    Fisher, J. B. et al. Carbon cost of plant nitrogen acquisition: A mechanistic, globally applicable model of plant nitrogen uptake, retranslocation, and fixation. Glob. Biogeochem. Cycles. 24, GB1014 (2010).
    ADS  Article  CAS  Google Scholar 

    42.
    Gentili, F., Wall, L. G. & Huss-Danell, K. Effects of phosphorus and nitrogen on nodulation are seen already at the stage of early cortical cell divisions in Alnus incana. Ann. Bot. 98, 309–315 (2006).
    PubMed  PubMed Central  Article  Google Scholar 

    43.
    Chen, H. & Markham, J. Using microcontrollers and sensors to build an inexpensive CO2 control system for growth chambers. Appl. Plant Sci. 8, e11393 (2020).
    PubMed  PubMed Central  Article  Google Scholar 

    44.
    Werner, G. D. A., Cornwell, W. K., Sprent, J. I., Kattge, J. & Kiers, E. T. A single evolutionary innovation drives the deep evolution of symbiotic N2-fixation in angiosperms. Nat. Commun. 5, 4087 (2014).
    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

    45.
    Chen, H., Renault, S. & Markham, J. The effect of Frankia and multiple ectomycorrhizal fungil species on Alnus growing in low fertility soil. Symbiosis. 80, 207–215 (2020).
    CAS  Article  Google Scholar 

    46.
    Noridge, N. A. & Benson, D. R. Isolation and nitrogen-fixing activity of Frankia sp. strain CpI1 vesicles. J. Bacteriol. 166, 301–305 (1986).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    47.
    Markham, J. H. Does Dryas integrifolia fix nitrogen?. Botany. 87, 1106–1109 (2009).
    CAS  Article  Google Scholar  More

  • in

    Pseudomonas eucalypticola sp. nov., a producer of antifungal agents isolated from Eucalyptus dunnii leaves

    Phylogenetic analysis
    A 1444 bp fragment of the 16S rRNA gene was amplified from the P. eucalypticola strain NP-1 T, sequenced and the sequence deposited in GenBank under accession number MN 238,862. A similarity search with this sequence was performed using EzBioCloud. Thirty valid species belonging to P. fluorescens intrageneric group (IG) proposed by Mulet et al.15 exhibited at least 97% similarity with NP-1 T, and these include P. vancouverensis ATCC 700688 T (98.8% similarity), P. moorei DSM12647T (98.8% similarity), P. koreensis Ps9-14 T (98.8% similarity), P. parafulva NBRC16636T (98.5% similarity) and P. reinekei Mt-1 T (98.5% similarity). The similarities with the other 25 species are provided in Supplementary Table S1. A phylogenetic tree based on the 16S rRNA sequence was constructed and is shown in Fig. 1. Strain NP-1 T forms a weakly supported cluster with P. kuykendallii NRRL B-59562 T, but both strains are situated on separate branches. Strain NP-1 T grouped in none known group or subgroup within P. fluorescens lineage, and it clusters of the outer edge of a much larger group containing several Pseudomonas groups/subgroups. However, Pseudomonas species cannot be identified based only on 16S rRNA analysis.
    Figure 1

    Neighbor-joining phylogenetic tree based on the 16S rRNA gene of Pseudomonas eucalypticola NP-1T and phylogenetically close members of Pseudomonas. The evolutionary distances were computed using the Jukes-Cantor method. The optimal tree with a sum of branch length = 0.23535266 is shown. The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) is shown next to the branches. Cellvibrio japonicus Ueda107T was used as outgroup.

    Full size image

    The MLSA approach based on the concatenated sequences of the partial 16S rRNA, gyrB, rpoB and rpoD genes, has been demonstrated to greatly facilitate the identification of new Pseudomonas strains16. According to the 16S rRNA alignment, 33 species from P. fluorescens IG and one species from P. pertucinogena IG were selected for MLSA. The concatenated sequences of the type strains of each selected species comprised a total of 3813 bp (Supplementary Table S2) and were used for phylogenetic tree construction. The analysis of concatenated gene sequences indicated that strain NP-1 T belongs to the P. fluorescens lineage, and this finding was supported by a bootstrap value of 91% (Fig. 2).However, NP-1 T still cannot be determined which group belongs to17.
    Figure 2

    Neighbor-joining phylogenetic tree based on concatenated 16S rRNA, gyrB, rpoB and rpoD gene partial of Pseudomonas eucalypticola NP-1T and the type strains of other Pseudomonas species. The evolutionary distances were computed using the Jukes-Cantor method. The evolutionary distances were computed using the Jukes-Cantor method e optimal tree with the sum of branch length = 1.37677586 is shown. The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) is shown next to the branches.

    Full size image

    For further identification of NP-1 T, a phylogenomic tree inferred with GBDP was constructed by using Type (Strain) Genome Server (TYGS)18, and all reference type strains and their genome sources are listed in Supplementary Table S3. The result showed the presence of an independent branch supported by a bootstrap value of 88% that can be differentiated from the other Pseudomonas species type strains (Fig. 3) and revealed that NP-1 T clustered with P. coleopterorum LMG 28558 T and P. rhizosphaerae LMG 21640 T which affiliated with P. fluorescens IG, but does not belong to any group. Strain NP-1 T was not be affiliated with any previously described Pseudomonas species and can thus be considered to represent a novel species. Based on above-described the results, P. coleopterorum, P. rhizosphaerae, P. graminis and P. lutea were selected for further analysis with NP-1 T.
    Figure 3

    Phylogenomic tree of strain NP-1T and related type strains of the genus Pseudomonas available on the TYGS database. The tree inferred with FastME 2.1.6.1 based on GBDP distances calculated from the genome sequences. The branch lengths are scaled in terms of the GBDP distance formula d5. The numbers above the branches show the GBDP pseudo-bootstrap support values  > 60% from 100 replications, and the average branch support is 94.6%.

    Full size image

    General taxonomic genome feature
    The draft genome assembly of strain NP-1 T contains 6,401,699 bp. The genome of NP-1 T, which consists of one chromosome and one plasmid, has been deposited in GenBank under the accession numbers CP056030 and CP056031, respectively. The genome has a G + C content of 63.96 mol%, as determined from the complete genome sequence, and 83.45% of the genome is coding and consists of 5,788 genes. The similarity of the genome of P. eucalypticola NP-1 T to other publicly available genomes of closely related Pseudomonas species was determined using ANI, digital DDH and G + C mol %5,6,7,8,9. Each of these comparisons yielded different ANIm and ANIb values, but the highest ANIb and ANIm values of 78.7 and 86.5 were obtained for NP-1 T and P. rhizosphaerae LMG 21640 T. The similarity between P. coleopterorum LMG 28558 T and NP-1 T was higher than that between P. graminis DSM 11363 T and P. lutea LMG 21974 T (Table 1). All ANIb and ANIm values obtained from the comparisons of NP-1 T with the other tested species were below 95%, which confirmed that strain NP-1 T belongs to an independent species. The TETRA frequencies between NP-1 T and the other tested type strains were lower than 0.99, which is the recommended cutoff value for species (Table 2). The digital DNA-DNA hybridization (dDDH) comparison with the draft genome of the type strain NP-1 T yielded low percentages ( More

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    Water column gradients beneath the summer ice of a High Arctic freshwater lake as indicators of sensitivity to climate change

    1.
    Hampton, S. E. et al. Ecology under lake ice. Ecol. Lett. 20, 98–111 (2017).
    Article  Google Scholar 
    2.
    Vincent, W. F., Hobbie, J. E. & Laybourn-Parry, J. Introduction to the limnology of high-latitude lake and river ecosystems. In Polar Lakes and Rivers: Limnology of Arctic and Antarctic Aquatic Ecosystems (eds. Vincent, W. F. & Laybourn-Parry, J.) 1–24 (Oxford, Oxford University Press, 2008).

    3.
    Paquette, M., Fortier, D., Mueller, D. R., Sarrazin, D. & Vincent, W. F. Rapid disappearance of perennial ice on Canada’s most northern lake. Geophys. Res. Lett. 42, 1433–1440 (2015).
    ADS  Article  Google Scholar 

    4.
    Lehnherr, I. et al. The world’s largest High Arctic lake responds rapidly to climate warming. Nat. Commun. 9, 1290. https://doi.org/10.1038/s41467-018-03685-z (2018).
    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

    5.
    Obryk, M. K., Doran, P. T. & Priscu, J. C. Prediction of ice-free conditions for a perennially ice-covered Antarctic lake. J. Geophys. Res. Earth Surf. 124, 686–694 (2019).
    ADS  Article  Google Scholar 

    6.
    Vincent, W. F. et al. Extreme ecosystems and geosystems in the Canadian High Arctic: Ward Hunt Island and vicinity. Ecoscience 18, 236–261 (2011).
    Article  Google Scholar 

    7.
    Spigel, R. H. & Priscu, J. C. Physical limnology of the McMurdo Dry Valleys lakes. In Ecosystem Dynamics in a Polar Desert: The McMurdo Dry Valleys, Antarctica (ed. Priscu, J. C.) 153–187 (London, American Geophysical Union, 1998).

    8.
    Pernica, P., North, R. L. & Baulch, H. M. In the cold light of day: The potential importance of under-ice convective mixed layers to primary producers. Inland Waters 7, 138–150 (2017).
    CAS  Article  Google Scholar 

    9.
    Kelly, J. R. & Scheibling, R. E. Fatty acids as dietary tracers in benthic food webs. Mar. Ecol. Prog. Ser. 446, 1–22 (2012).
    ADS  CAS  Article  Google Scholar 

    10.
    Taipale, S. et al. Fatty acid composition as biomarkers of freshwater microalgae: analysis of 37 strains of microalgae in 22 genera and in seven classes. Aquat. Microb. Ecol. 71, 165–178 (2013).
    Article  Google Scholar 

    11.
    Mohit, V., Culley, A., Lovejoy, C., Bouchard, F. & Vincent, W. F. Hidden biofilms in a far northern lake and implications for the changing Arctic. NPJ Biofilms Microbiomes 3, 17. https://doi.org/10.1038/s41522-017-0024-3 (2017).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    12.
    Paquette, M., Fortier, D. & Vincent, W. F. Water tracks in the High Arctic: a hydrological network dominated by rapid subsurface flow through patterned ground. Arct. Sci. 3, 334–353 (2017).
    Article  Google Scholar 

    13.
    Vincent, W. F. & Mueller, D. Witnessing ice habitat collapse in the Arctic. Science 370, 1031–1032 (2020).
    ADS  CAS  Article  Google Scholar 

    14.
    MacIntyre, S., Cortés, A. & Sadro, S. Sediment respiration drives circulation and production of CO2 in ice-covered Alaskan arctic lakes. Limnol. Oceanogr. Lett. 3, 302–310 (2018).
    CAS  Article  Google Scholar 

    15.
    Cortés, A. & MacIntyre, S. Mixing processes in small arctic lakes during spring. Limnol. Oceanogr. 65, 260–288 (2020).
    ADS  Article  Google Scholar 

    16.
    Bégin, P. N. et al. The littoral zone of polar lakes: Inshore-offshore contrasts in an ice-covered High Arctic lake. Arct. Sci. 7, 1–24. https://doi.org/10.1139/as-2020-0026 (2021).
    Article  Google Scholar 

    17.
    Bégin, P. N. et al. Extreme warming and regime shift toward amplified variability in a far northern lake. Limnol. Oceanogr. 65, 1–23. https://doi.org/10.1002/lno.11546 (2020).
    Article  Google Scholar 

    18.
    Spaulding, S. A., MCKnight, D. M., Smith, R. L. & Dufford, R. Phytoplankton population dynamics in perennially ice-covered Lake Fryxell, Antarctica. J. Plankton Res. 16, 527–541 (1994).

    19.
    Charvet, S., Vincent, W. F. & Lovejoy, C. Chrysophytes and other protists in High Arctic lakes: molecular gene surveys, pigment signatures and microscopy. Polar Biol. 35, 733–748 (2012).
    Article  Google Scholar 

    20.
    Jones, R. I. Mixotrophy in planktonic protists: an overview. Freshw. Biol. 45, 219–226 (2000).
    Article  Google Scholar 

    21.
    Bonilla, S., Villeneuve, V. & Vincent, W. F. Benthic and planktonic algal communities in a High Arctic lake: pigment structure and contrasting responses to nutrient enrichment. J. Phycol. 41, 1120–1130 (2005).
    CAS  Article  Google Scholar 

    22.
    Quesada, A., Fernández-Valiente, E., Hawes, I. & Howard-Williams, C. Benthic primary production in polar lakes and rivers. In Polar Lakes and Rivers: Limnology of Arctic and Antarctic Aquatic Ecosystems (eds. Vincent, W. F. & Laybourn-Parry, J.) 179–196 (Oxford University Press, Oxford, 2008).
    Google Scholar 

    23.
    Rautio, M. et al. Shallow freshwater ecosystems of the circumpolar Arctic. Ecoscience 18, 204–222 (2011).
    Article  Google Scholar 

    24.
    Markager, S. & Vincent, W. F. Light absorption by phytoplankton: development of a matching parameter for algal photosynthesis under different spectral regimes. J. Plankton Res. 23, 1373–1384 (2001).
    Article  Google Scholar 

    25.
    Duarte, C. M. & Prairie, Y. T. Prevalence of heterotrophy and atmospheric CO2 emissions from aquatic ecosystems. Ecosystems 8, 862–870 (2005).
    CAS  Article  Google Scholar 

    26.
    Denfeld, B. A., Baulch, H. M., del Giorgio, P. A., Hampton, S. E. & Karlsson, J. A synthesis of carbon dioxide and methane dynamics during the ice-covered period of northern lakes: Under-ice CO 2 and CH 4 dynamics. Limnol. Oceanogr. Lett. 3, 117–131 (2018).
    CAS  Article  Google Scholar 

    27.
    Kling, G. W., Kipphut, G. W. & Miller, M. C. Arctic lakes and streams as gas conduits to the atmosphere: implications for tundra carbon budgets. Science 251, 298–301 (1991).
    ADS  CAS  Article  Google Scholar 

    28.
    Matveev, A., Laurion, I. & Vincent, W. F. Winter accumulation of methane and its variable timing of release from thermokarst lakes in subarctic peatlands. J. Geophys. Res. Biogeosci. 124, 3521–3535 (2019).
    CAS  Article  Google Scholar 

    29.
    Paquette, M., Fortier, D., Lafrenière, M. & Vincent, W. F. Periglacial slopewash dominated by solute transfers and subsurface erosion on a High Arctic slope. Permafr. Periglac. Process. 31, 472–486 (2020).
    Article  Google Scholar 

    30.
    Negandhi, K. et al. Small thaw ponds: an unaccounted source of methane in the Canadian High Arctic. PLoS ONE 8, e78204. https://doi.org/10.1371/journal.pone.0078204 (2013).
    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

    31.
    Lyons, W. B. & Finlay, J. Biogeochemical processes in high-latitude lakes and rivers. In Polar Lakes and Rivers: Limnology of Arctic and Antarctic Aquatic Ecosystems (eds. Vincent, W. F. & Laybourn-Parry, J.) 137–156 (Oxford University Press, Oxford, 2008).
    Google Scholar 

    32.
    Watanabe, S., Laurion, I., Chokmani, K., Pienitz, R. & Vincent, W. F. Optical diversity of thaw ponds in discontinuous permafrost: a model system for water color analysis. J. Geophys. Res. Biogeosci. 116, G02003. https://doi.org/10.1029/2010jg001380 (2011).
    ADS  Article  Google Scholar 

    33.
    Retamal, L., Vincent, W. F., Martineau, C. & Osburn, C. L. Comparison of the optical properties of dissolved organic matter in two river-influenced coastal regions of the Canadian Arctic. Estuar. Coast. Shelf Sci. 72, 261–272 (2007).
    ADS  Article  Google Scholar 

    34.
    Wauthy, M. et al. Increasing dominance of terrigenous organic matter in circumpolar freshwaters due to permafrost thaw. Limnol. Oceanogr. Lett. 3, 186–198 (2018).
    CAS  Article  Google Scholar 

    35.
    Murphy, K. R., Stedmon, C. A., Waite, T. D. & Ruiz, G. M. Distinguishing between terrestrial and autochthonous organic matter sources in marine environments using fluorescence spectroscopy. Mar. Chem. 108, 40–58 (2008).
    CAS  Article  Google Scholar 

    36.
    Jakkila, J., Leppäranta, M., Kawamura, T., Shirasawa, K. & Salonen, K. Radiation transfer and heat budget during the ice season in Lake Pääjärvi Finland. Aquat. Ecol. 43, 681–692 (2009).
    Google Scholar 

    37.
    CEN. Climate station data from Northern Ellesmere Island in Nunavut, Canada, v. 1.7 (2002–2019). Nordicana D1. https://doi.org/10.5885/44985SL-8F203FD3ACCD4138 (2020).

    38.
    Pawlowicz, R. Calculating the conductivity of natural waters. Limnol. Oceanogr. Methods 6, 489–501 (2008).
    CAS  Article  Google Scholar 

    39.
    Prėskienis, V. et al. Seasonal patterns in greenhouse gas emissions from lakes and ponds in a High Arctic polygonal landscape. Limnol. Oceanogr. https://doi.org/10.1002/lno.11660 (2021).
    Article  Google Scholar 

    40.
    Yamamoto, S., Alcauskas, J. B. & Crozier, T. E. Solubility of methane in distilled water and seawater. J. Chem. Eng. Data 21, 78–80 (1976).
    CAS  Article  Google Scholar 

    41.
    Helms, J. R. et al. Absorption spectral slopes and slope ratios as indicators of molecular weight, source, and photobleaching of chromophoric dissolved organic matter. Limnol. Oceanogr. 53, 955–969 (2008).
    ADS  Article  Google Scholar 

    42.
    Weishaar, J. L. et al. Evaluation of specific ultraviolet absorbance as an indicator of the chemical composition and reactivity of dissolved organic carbon. Environ. Sci. Technol. 37, 4702–4708 (2003).
    ADS  CAS  Article  Google Scholar 

    43.
    Loiselle, S. A. et al. Variability in photobleaching yields and their related impacts on optical conditions in subtropical lakes. J. Photochem. Photobiol. Biol. 95, 129–137 (2009).
    CAS  Article  Google Scholar 

    44.
    McKnight, D. M. et al. Spectrofluorometric characterization of dissolved organic matter for indication of precursor organic material and aromaticity. Limnol. Oceanogr. 46, 38–48 (2001).
    ADS  CAS  Article  Google Scholar 

    45.
    Murphy, K. R., Stedmon, C. A., Graeber, D. & Bro, R. Fluorescence spectroscopy and multi-way techniques PARAFAC. Anal. Methods 5, 6557–6566 (2013).
    Google Scholar 

    46.
    Murphy, K. R. et al. Measurement of dissolved organic matter fluorescence in aquatic environments: an interlaboratory comparison. Environ. Sci. Technol. 44, 9405–9412 (2010).
    ADS  CAS  Article  Google Scholar 

    47.
    Borcard, D., Gillet, F. & Legendre, P. Numerical Ecology with R (Springer, Berlin, 2011).
    Google Scholar 

    48.
    IOCCG Protocol Series. Inherent optical property measurements and protocols: absorption coefficient. In Ocean Optics and Biogeochemistry Protocols for Satellite Ocean Colour Sensor Validation (eds. Neeley, A. R. & Mannino, A.) vol. 1.0. https://doi.org/10.25607/OBP-119 (2018).

    49.
    Roy, S. Phytoplankton Pigments: Characterization, Chemotaxonomy and Applications in Oceanography (Cambridge University Press, Cambridge, 2011).
    Google Scholar 

    50.
    Glew, J. R. Miniature gravity corer for recovering short sediment cores. J. Paleolimnol. 5, 285–287 (1991).
    ADS  Article  Google Scholar 

    51.
    Schneider, T., Grosbois, G., Vincent, W. F. & Rautio, M. Saving for the future: Pre-winter uptake of algal lipids supports copepod egg production in spring. Freshw. Biol. 62, 1063–1072 (2017).
    CAS  Article  Google Scholar 

    52.
    Grosbois, G., Mariash, H., Schneider, T. & Rautio, M. Under-ice availability of phytoplankton lipids is key to freshwater zooplankton winter survival. Sci. Rep. 7, 11543. https://doi.org/10.1038/s41598-017-10956-0 (2017).
    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar  More

  • in

    Cryptochrome 1 mediates light-dependent inclination magnetosensing in monarch butterflies

    1.
    Dreyer, D. et al. The Earth’s magnetic field and visual landmarks steer migratory flight behavior in the nocturnal Australian Bogong Moth. Curr. Biol. 28, 2160–2166 (2018).
    CAS  Article  Google Scholar 
    2.
    Guerra, P. A., Gegear, R. J. & Reppert, S. M. A magnetic compass aids monarch butterfly migration. Nat. Commun. 5, 4164 (2014).
    ADS  CAS  Article  Google Scholar 

    3.
    Mouritsen, H. Long-distance navigation and magnetoreception in migratory animals. Nature 558, 50–59 (2018).
    ADS  CAS  Article  Google Scholar 

    4.
    Uebe, R. & Schuler, D. Magnetosome biogenesis in magnetotactic bacteria. Nat. Rev. Microbiol. 14, 621–637 (2016).
    CAS  Article  Google Scholar 

    5.
    Hore, P. J. & Mouritsen, H. The radical-pair mechanism of magnetoreception. Annu. Rev. Biophys. 45, 299–344 (2016).
    CAS  Article  Google Scholar 

    6.
    Ritz, T., Adem, S. & Schulten, K. A model for photoreceptor-based magnetoreception in birds. Biophys. J. 78, 707–718 (2000).
    CAS  Article  Google Scholar 

    7.
    Schulten, K., Swenberg, C. E. & Weller, A. A biomagnetic sensory mechanism based on magnetic field modulated coherent electron spin motion. Z. Phys. Chem. 111, 1–5 (1978).
    Article  Google Scholar 

    8.
    Rodgers, C. T. & Hore, P. J. Chemical magnetoreception in birds: the radical pair mechanism. Proc. Natl Acad. Sci. USA 106, 353–360 (2009).
    ADS  CAS  Article  Google Scholar 

    9.
    Kerpal, C. et al. Chemical compass behaviour at microtesla magnetic fields strengthens the radical pair hypothesis of avian magnetoreception. Nat. Commun. 10, 3707 (2019).
    ADS  Article  Google Scholar 

    10.
    Maeda, K. et al. Magnetically sensitive light-induced reactions in cryptochrome are consistent with its proposed role as a magnetoreceptor. Proc. Natl Acad. Sci. USA 109, 4774–4779 (2012).
    ADS  CAS  Article  Google Scholar 

    11.
    Emery, P. et al. Drosophila CRY is a deep brain circadian photoreceptor. Neuron 26, 493–504 (2000).
    CAS  Article  Google Scholar 

    12.
    Zhu, H. et al. The two CRYs of the butterfly. Curr. Biol. 15, R953–R954 (2005).
    CAS  Article  Google Scholar 

    13.
    Zoltowski, B. D. et al. Chemical and structural analysis of a photoactive vertebrate cryptochrome from pigeon. Proc. Natl Acad. Sci. USA 116, 19449–19457 (2019).
    CAS  Article  Google Scholar 

    14.
    Merlin, C., Beaver, L. E., Taylor, O. R., Wolfe, S. A. & Reppert, S. M. Efficient targeted mutagenesis in the monarch butterfly using zinc-finger nucleases. Genome Res. 23, 159–168 (2013).
    CAS  Article  Google Scholar 

    15.
    Michael, A. K., Fribourgh, J. L., Van Gelder, R. N. & Partch, C. L. Animal cryptochromes: divergent roles in light perception, circadian timekeeping and beyond. Photochem. Photobiol. 93, 128–140 (2017).
    CAS  Article  Google Scholar 

    16.
    Yuan, Q., Metterville, D., Briscoe, A. D. & Reppert, S. M. Insect cryptochromes: gene duplication and loss define diverse ways to construct insect circadian clocks. Mol. Biol. Evol. 24, 948–955 (2007).
    CAS  Article  Google Scholar 

    17.
    Zhang, Y., Markert, M. J., Groves, S. C., Hardin, P. E. & Merlin, C. Vertebrate-like CRYPTOCHROME 2 from monarch regulates circadian transcription via independent repression of CLOCK and BMAL1 activity. Proc. Natl Acad. Sci. USA 114, E7516–E7525 (2017).
    CAS  Article  Google Scholar 

    18.
    Fedele, G. et al. Genetic analysis of circadian responses to low frequency electromagnetic fields in Drosophila melanogaster. PLoS Genet. 10, e1004804 (2014).
    Article  Google Scholar 

    19.
    Fedele, G., Green, E. W., Rosato, E. & Kyriacou, C. P. An electromagnetic field disrupts negative geotaxis in Drosophila via a CRY-dependent pathway. Nat. Commun. 5, 4391 (2014).
    ADS  CAS  Article  Google Scholar 

    20.
    Gegear, R. J., Casselman, A., Waddell, S. & Reppert, S. M. Cryptochrome mediates light-dependent magnetosensitivity in Drosophila. Nature 454, 1014–1018 (2008).
    ADS  CAS  Article  Google Scholar 

    21.
    Gegear, R. J., Foley, L. E., Casselman, A. & Reppert, S. M. Animal cryptochromes mediate magnetoreception by an unconventional photochemical mechanism. Nature 463, 804–807 (2010).
    ADS  CAS  Article  Google Scholar 

    22.
    Foley, L. E., Gegear, R. J. & Reppert, S. M. Human cryptochrome exhibits light-dependent magnetosensitivity. Nat. Commun. 2, 356 (2011).
    ADS  Article  Google Scholar 

    23.
    Kutta, R. J., Archipowa, N., Johannissen, L. O., Jones, A. R. & Scrutton, N. S. Vertebrate cryptochromes are vestigial flavoproteins. Sci. Rep. 7, 44906 (2017).
    ADS  CAS  Article  Google Scholar 

    24.
    Zhu, H., Gegear, R. J., Casselman, A., Kanginakudru, S. & Reppert, S. M. Defining behavioral and molecular differences between summer and migratory monarch butterflies. BMC Biol. 7, 14 (2009).
    Article  Google Scholar 

    25.
    Lin, C., Top, D., Manahan, C. C., Young, M. W. & Crane, B. R. Circadian clock activity of cryptochrome relies on tryptophan-mediated photoreduction. Proc. Natl Acad. Sci. USA 115, 3822–3827 (2018).
    CAS  Article  Google Scholar 

    26.
    Nohr, D. et al. Extended electron-transfer in animal cryptochromes mediated by a tetrad of aromatic amino acids. Biophys. J. 111, 301–311 (2016).
    ADS  CAS  Article  Google Scholar 

    27.
    Nohr, D. et al. Determination of radical-radical distances in light-active proteins and their implication for biological magnetoreception. Angew. Chem. Int. Ed. Engl. 56, 8550–8554 (2017).
    CAS  Article  Google Scholar 

    28.
    Palomares, L. A., Joosten, C. E., Hughes, P. R., Granados, R. R. & Shuler, M. L. Novel insect cell line capable of complex N-glycosylation and sialylation of recombinant proteins. Biotechnol. Prog. 19, 185–192 (2003).
    CAS  Article  Google Scholar 

    29.
    Bazalova, O. et al. Cryptochrome 2 mediates directional magnetoreception in cockroaches. Proc. Natl Acad. Sci. USA 113, 1660–1665 (2016).
    ADS  CAS  Article  Google Scholar 

    30.
    Merlin, C., Gegear, R. J. & Reppert, S. M. Antennal circadian clocks coordinate sun compass orientation in migratory monarch butterflies. Science 325, 1700–1704 (2009).
    ADS  CAS  Article  Google Scholar 

    31.
    Yoshii, T., Ahmad, M. & Helfrich-Forster, C. Cryptochrome mediates light-dependent magnetosensitivity of Drosophila’s circadian clock. PLoS Biol. 7, e1000086 (2009).
    Article  Google Scholar 

    32.
    Worster, S., Mouritsen, H. & Hore, P. J. A light-dependent magnetoreception mechanism insensitive to light intensity and polarization. J. R. Soc. Interface 14, (2017).

    33.
    Oztürk, N., Song, S.-H., Selby, C. P. & Sancar, A. Animal type 1 cryptochromes. Analysis of the redox state of the flavin cofactor by site-directed mutagenesis. J. Biol. Chem. 283, 3256–3263 (2008).
    Article  Google Scholar 

    34.
    Wu, H., Scholten, A., Einwich, A., Mouritsen, H. & Koch, K.-W. Protein-protein interaction of the putative magnetoreceptor cryptochrome 4 expressed in the avian retina. Sci. Rep. 10, 7364 (2020).
    ADS  CAS  Article  Google Scholar 

    35.
    Wan, G.-J. et al. Reduced geomagnetic field may affect positive phototaxis and flight capacity of a migratory rice planthopper. Anim. Behav. 121, 107–116 (2016).
    Article  Google Scholar 

    36.
    Hwang, W. Y. et al. Efficient genome editing in zebrafish using a CRISPR-Cas system. Nat. Biotechnol. 31, 227–229 (2013).
    CAS  Article  Google Scholar 

    37.
    Iiams, S. E., Lugena, A. B., Zhang, Y., Hayden, A. N. & Merlin, C. Photoperiodic and clock regulation of the vitamin A pathway in the brain mediates seasonal responsiveness in the monarch butterfly. Proc. Natl Acad. Sci. USA 116, 25214–25221 (2019).
    CAS  Article  Google Scholar 

    38.
    Markert, M. J. et al. Genomic access to monarch migration using TALEN and CRISPR/Cas9-mediated targeted mutagenesis. G3 (Bethesda) 6, 905–915 (2016).
    CAS  Article  Google Scholar 

    39.
    Jao, L. E., Wente, S. R. & Chen, W. Efficient multiplex biallelic zebrafish genome editing using a CRISPR nuclease system. Proc. Natl Acad. Sci. USA 110, 13904–13909 (2013).
    ADS  CAS  Article  Google Scholar 

    40.
    Kim, J. M., Kim, D., Kim, S. & Kim, J. S. Genotyping with CRISPR-Cas-derived RNA-guided endonucleases. Nat. Commun. 5, 3157 (2014).
    ADS  Article  Google Scholar 

    41.
    Zhu, H. et al. Cryptochromes define a novel circadian clock mechanism in monarch butterflies that may underlie sun compass navigation. PLoS Biol. 6, e4 (2008).
    Article  Google Scholar  More

  • in

    Physical and ecological isolation contribute to maintain genetic differentiation between fire salamander subspecies

    Abellán P, Svenning JC (2014) Refugia within refugia–patterns in endemism and genetic divergence are linked to Late Quaternary climate stability in the Iberian Peninsula. Biol J Linn Soc 113:13–28
    Article  Google Scholar 

    Alarcón-Ríos L, Nicieza AG, Kaliontzopoulou A, Buckley D, Velo-Antón G (2020) Evolutionary history and not heterochronic modifications associated with viviparity drive head shape differentiation in a reproductive polymorphic species, Salamandra salamandra. Evol Biol 47:43–55
    Article  Google Scholar 

    Alcobendas M, Castanet J (2000) Bone growth plasticity among populations of Salamandra salamandra: interactions between internal and external factors. Herpetologica 56:14–26
    Google Scholar 

    Alcobendas M, Buckley D, Tejedo M (2004) Variability in survival, growth and metamorphosis in the larval fire salamander (Salamandra salamandra): effects of larval birth size, sibship and environment. Herpetologica 60:232–245
    Article  Google Scholar 

    Antunes B, Lourenço A, Caeiro-Dias G, Dinis M, Gonçalves H, Martínez-Solano I et al. (2018) Combining phylogeography and landscape genetics to infer the evolutionary history of a short-range Mediterranean relict, Salamandra salamandra longirostris. Conserv Genet 19:1411–1424
    CAS  Article  Google Scholar 

    Arntzen JW, van Belkom J (2020) ‘Mainland-island’ population structure of a terrestrial salamander in a forest-bocage landscape with little evidence for in situ ecological speciation. Sci Rep 10:1–15
    Article  CAS  Google Scholar 

    Balkenhol N, Cushman SA, Waits LP, Storfer A (2016) Current status, future opportunities, and remaining challenges in landscape genetics. In: Balkenhol N, Cushman SA, Storfer AT, Waits LP (eds) Landscape genetics: concepts, methods, applications, John Wiley and Sons Ltd, Chichester, pp 247–255.

    Barton NH, Gale KS (1993) Genetic analysis of hybrid zones. Hybrid zones and the evolutionary process. In: Harrison RG (ed) Hybrid zones and the evolutionary process. Oxford University Press, Oxford, p 13–45
    Google Scholar 

    Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B Stat Methodol 57:289–300
    Google Scholar 

    Beukema W, Nicieza AG, Lourenço A, Velo‐Antón G (2016) Colour polymorphism in Salamandra salamandra (Amphibia: Urodela), revealed by a lack of genetic and environmental differentiation between distinct phenotypes. J Zool Syst Evol 54:127–136
    Article  Google Scholar 

    Bisconti R, Porretta D, Arduino P, Nascetti G, Canestrelli D (2018) Hybridization and extensive mitochondrial introgression among fire salamanders in peninsular Italy. Sci Rep 8:13187
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    Bosch J, López-Bueis I (1994) Comparative study of the dorsal pattern in Salamandra salamandra bejarae (Wolterstorff, 1934) and S. s. almanzoris (Müller & Hellmich, 1935). Herpetol J 4:46–48
    Google Scholar 

    Burgon JD, Vieites DR, Jacobs A, Weidt SK, Gunter HM, Steinfartz S et al. (2020) Functional colour genes and signals of selection in colour polymorphic salamanders. Mol Ecol 29:1284–1299
    CAS  PubMed  Article  Google Scholar 

    Burgon JD, Vences M, Steinfartz S, Bogaerts S, Bonato L, Donaire-Barroso D, Martínez-Solano I, Velo-Antón G, Vieites DR, Mable BK, Elmer KR (2021) Phylogenomic inference of species and subspecies diversity in the Pal earctic salamander genus Salamandra. Molecular Phylogenetics and Evolution 157:107063

    Chybicki IJ, Burczyk J (2009) Simultaneous estimation of null alleles and inbreeding coefficients. J Hered 100:106–113
    CAS  PubMed  Article  Google Scholar 

    Clarke RT, Rothery P, Raybould AF (2002) Confidence limits for regression relationships between distance matrices: estimating gene flow with distance. JABES 7:361
    Google Scholar 

    Cushman SA (2006) Effects of habitat loss and fragmentation on amphibians: a review and prospectus. Biol Conserv 128:231–240
    Article  Google Scholar 

    Czypionka T, Goedbloed DJ, Steinfartz S, Nolte AW (2018) Plasticity and evolutionary divergence in gene expression associated with alternative habitat use in larvae of the European Fire Salamander. Mol Ecol 27:2698–2713
    PubMed  Article  Google Scholar 

    Dinis M, Joger U, Slimani T, Martínez-Freiría F, Merabet K, Donaire D et al. (2018) Allopatric diversification and evolutionary melting pot in a North African Palearctic relict: the biogeographic history of Salamandra algira. Mol Phylogenet Evol 130:81–91
    PubMed  Article  Google Scholar 

    Domínguez-Villar D, Carrasco RM, Pedraza J, Cheng H, Edwards R, Willenbring JK (2013) Early maximum extent of paleoglaciers from Mediterranean mountains during the last glaciation. Sci Rep. 3:2034
    PubMed  PubMed Central  Article  Google Scholar 

    Dufresnes C, Pribille M, Alard B, Dubey S, Perrin N, Gonçalves H et al. (2020) Integrating hybrid zone analyses in species delimitation: lessons from two anuran radiations of the Western Mediterranean. Heredity 124:423–438
    CAS  PubMed  Article  Google Scholar 

    Earl DA, VonHoldt BM (2012) STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv Genet Resour 4:359–361
    Article  Google Scholar 

    Emel SL, Olson DH, Knowles LL, Storfer A (2019) Comparative landscape genetics of two endemic torrent salamander species, Rhyacotriton kezeri and R. variegatus: implications for forest management and species conservation. Conserv Genet 20:801–815
    CAS  Article  Google Scholar 

    Epps CW, Keyghobadi N (2015) Landscape genetics in a changing world: disentangling historical and contemporary influences and inferring change. Mol Ecol 24:6021–6040
    PubMed  Article  Google Scholar 

    Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14:2611–2620
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    Ficetola GF, Colleoni E, Renaud J, Scali S, Padoa‐Schioppa E, Thuiller W (2016) Morphological variation in salamanders and their potential response to climate change. Glob Chang Biol 22:2013–2024
    PubMed  PubMed Central  Article  Google Scholar 

    Fletcher R, Fortin M (2018) Spatial ecology and conservation modeling. Springer International Publishing, Cham
    Google Scholar 

    Fourcade Y, Engler JO, Rödder D, Secondi J (2014) Mapping species distributions with MAXENT using a geographically biased sample of presence data: a performance assessment of methods for correcting sampling bias. PLoS ONE 9:e97122
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    Francis RM (2016) pophelper: An r package and web app to analyse and visualize population structure. Mol Ecol Resour 17:27–32
    PubMed  Article  CAS  Google Scholar 

    García-París M, Alcobendas M, Alberch P (1998) Influence of the Guadalquivir river basin on mitochondrial DNA evolution of Salamandra salamandra (Caudata: Salamandridae) from southern Spain. Copeia 1998:173–176
    Article  Google Scholar 

    García-París M, Alcobendas M, Buckley D, Wake DB (2003) Dispersal of viviparity across contact zones in iberian populations of fire salamanders (Salamandra) inferred from discordance of genetic and morphological traits. Evolution 57:129–143

    Gomez A, Lunt DH (2007) Refugia within refugia: patterns of phylogeographic concordance in the Iberian Peninsula. In: Weiss S, Ferrand N (eds). Phylogeography of Southern European Refugia. Springer: Dordrecht. pp 155–188

    Gray LN, Barley AJ, Poe S, Thomson RC, Nieto‐Montes de Oca A, Wang IJ (2019) Phylogeography of a widespread lizard complex reflects patterns of both geographic and ecological isolation. Mol Ecol 28:644–657
    PubMed  Article  Google Scholar 

    Gutiérrez-Rodríguez J, Barbosa AM, Martínez-Solano I (2017a) Present and past climatic effects on the current distribution and genetic diversity of the Iberian spadefoot toad (Pelobates cultripes): an integrative approach. J Biogeogr 44:245–258
    Article  Google Scholar 

    Gutiérrez-Rodríguez J, Barbosa AM, Martínez-Solano I (2017b) Integrative inference of population history in the Ibero-Maghrebian endemic Pleurodeles waltl (Salamandridae). Mol Phylogenet Evol 112:122–137
    PubMed  Article  Google Scholar 

    Hendrix R, Schmidt BR, Schaub M, Krause ET, Steinfartz S (2017) Differentiation of movement behaviour in an adaptively diverging salamander population. Mol Ecol 26:6400–6413
    PubMed  Article  Google Scholar 

    Hendrix R, Susanne Hauswaldt J, Veith M, Steinfartz S (2010) Strong correlation between cross-amplification success and genetic distance across all members of “True Salamanders” (Amphibia: Salamandridae) revealed by Salamandra salamandra-specific microsatellite loci. Mol Ecol Resour 10:1038–1047
    CAS  PubMed  Article  Google Scholar 

    Hendry AP (2017) Eco-evolutionary dynamics. Princeton University Press, Princeton
    Google Scholar 

    Hewitt G (2000) The genetic legacy of the Quaternary ice ages. Nature 405:907–913
    CAS  Article  Google Scholar 

    Hijmans RJ, Van Etten J (2016) raster: Geographic Data Analysis and Modeling. R package version 2.5-8. Available from: http://CRAN.R-project.org/package=raster

    Jombart T, Devillard S, Balloux F (2010) Discriminant analysis of principal components: a new method for the analysis of genetically structured populations. BMC Genet 11:1–94
    Article  Google Scholar 

    Kalinowski ST (2005) HP-RARE 10: a computer program for performing rarefaction on measures of allelic richness. Mol Ecol Notes 5:187–189
    CAS  Article  Google Scholar 

    Keenan K, Mcginnity P, Cross TF, Crozier WW, Prodöhl PA (2013) DiveRsity: an R package for the estimation and exploration of population genetics parameters and their associated errors. Methods Ecol Evol 4:782–788
    Article  Google Scholar 

    Linnaeus C (1758) Systema Naturae per Regna Tria Naturae, Secundum Classes, Ordines, Genera, Species, cum Characteribus, Differentiis, Synonymis, Locis. 10th Edition. Volume 1. Stockholm, Sweden: L. Salvii

    Lourenço A, Gonçalves J, Carvalho F, Wang IJ, Velo-Antón G (2019) Comparative landscape genetics reveals the evolution of viviparity reduces genetic connectivity in fire salamanders. Mol Ecol 28:4573–4591
    PubMed  Article  CAS  Google Scholar 

    Maia-Carvalho B, Vale CG, Sequeira F, Ferrand N, Martínez-Solano I, Gonçalves H (2018) The roles of allopatric fragmentation and niche divergence in intraspecific lineage diversification in the common midwife toad (Alytes obstetricans). J Biogeogr 45:2146–2158
    Article  Google Scholar 

    Martínez-Freiría F, Freitas I, Zuffi MAL, Golay P, Ursenbacher S, Velo-Antón G (2020) Climatic refugia boosted allopatric diversification in Western Mediterranean vipers. J Biogeogr 47:1698–1713
    Article  Google Scholar 

    Martínez-Solano I (2006) Atlas de distribución y estado de conservación de los anfibios de la Comunidad de Madrid. Graellsia 62:253–291
    Article  Google Scholar 

    Martínez-Solano I, Alcobendas M, Buckley D, García-París M (2005) Molecular characterisation of the endangered Salamandra salamandra almanzoris (Caudata, Salamandridae). Ann Zool Fenn 42:57–68
    Google Scholar 

    McRae BH (2006) Isolation by resistance. Evolution 60:1551–1561
    PubMed  PubMed Central  Article  Google Scholar 

    McRae BH, Dickson BG, Keitt TH, Shah VB (2008) Concepts and synthesis emphasizing new ideas to stimulate research in ecology using circuit theory to model connectivity in ecology, evolution, and conservation. Ecology 89:2712–2724
    PubMed  Article  Google Scholar 

    Méndez L, Perdices A, Machordom A (2019) Genetic structure and diversity of the Iberian populations of the freshwater blenny Salaria fluviatilis (Asso, 1801) and its conservation implications. Conserv Genet 20:1223–1236
    Article  Google Scholar 

    Miraldo A, Hewitt GM, Paulo OS, Emerson BC (2011) Phylogeography and demographic history of Lacerta lepida in the Iberian Peninsula: multiple refugia, range expansions and secondary contact zones. BMC Evol Biol 11:170
    PubMed  PubMed Central  Article  Google Scholar 

    Mulder KP, Rodriguez NC, Grant EHC, Brand A, Fleischer RC (2019) North ‐ facing slopes and elevation shape asymmetric genetic structure in the range ‐ restricted salamander Plethodon shenandoah. Ecol Evol 9:5094–5105
    PubMed  PubMed Central  Article  Google Scholar 

    Noguerales V, Cordero PJ, Ortego J (2017) Testing the role of ancient and contemporary landscapes on structuring genetic variation in a specialist grasshopper. Ecol Evol 7:3110–3122
    PubMed  PubMed Central  Article  Google Scholar 

    Nosil P (2012) Ecological speciation. Oxford University Press, New York
    Google Scholar 

    Peakall R, Smouse PE (2006) GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Mol Ecol Notes 6:288–295
    Article  Google Scholar 

    Pereira RJ, Martínez-Solano I, Buckley D (2016) Hybridization during altitudinal range shifts: nuclear introgression leads to extensive cyto-nuclear discordance in the fire salamander. Mol Ecol 25:1551–1565
    CAS  PubMed  Article  Google Scholar 

    Peterman WE (2018) ResistanceGA: an R package for the optimization of resistance surfaces using genetic algorithms. Methods Ecol Evol 9:1638–1647
    Article  Google Scholar 

    Phillips SB, Aneja VP, Kang D, Arya SP (2006) Modelling and analysis of the atmospheric nitrogen deposition in North Carolina. IJGEI 6:231–252
    Google Scholar 

    Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959
    CAS  PubMed  PubMed Central  Google Scholar 

    Prunier JG, Colyn M, Legendre X, Nimon KF, Flamand MC (2015) Multicollinearity in spatial genetics: Separating the wheat from the chaff using commonality analyses. Mol Ecol 24:263–283
    CAS  Article  Google Scholar 

    R Core Team (2018) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, https://wwwR-project.org/
    Google Scholar 

    Rousset F (2008) GENEPOP’007: a complete re-implementation of the GENEPOP software for Windows and Linux. Mol Ecol Resour 8:103–106
    PubMed  PubMed Central  Article  Google Scholar 

    Sánchez‐Montes G, Wang J, Ariño AH, Martínez‐Solano I (2018) Mountains as barriers to gene flow in amphibians: quantifying the differential effect of a major mountain ridge on the genetic structure of four sympatric species with different life history traits. J Biogeogr 45:318–331
    Article  Google Scholar 

    Sánchez-Montes G, Recuero E, Barbosa AM, Martínez-Solano I (2019) Complementing the Pleistocene biogeography of European amphibians: testimony from a southern Atlantic species. J Biogeogr 46:568–583
    Article  Google Scholar 

    Sexton JP, Hangartner SB, Hoffmann AA (2014) Genetic isolation by environment or distance: which pattern of gene flow is most common? Evolution 68:1–15
    CAS  Article  Google Scholar 

    Silva P, López-Bao JV, Llaneza L, Álvares F, Lopes S, Blanco JC et al. (2018) Cryptic population structure reveals low dispersal in Iberian wolves. Sci Rep 8:14108
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    Steinfartz S, Küsters D, Tautz D (2004) Isolation and characterization of polymorphic tetranucleotide microsatellite loci in the fire salamander Salamandra salamandra (Amphibia: Caudata). Mol Ecol Notes 4:626–628
    CAS  Article  Google Scholar 

    Velo-Antón G, García-París M, Galán P, Cordero Rivera A (2007) The evolution of viviparity in Holocene islands: ecological adaptation versus phylogenetic descent along the transition from aquatic to terrestrial environments. J Zool Syst Evol 45:345–352
    Article  Google Scholar 

    Velo‐Antón G, Parra JL, Parra‐Olea G, Zamudio KR (2013) Tracking climate change in a dispersal‐limited species: reduced spatial and genetic connectivity in a montane salamander. Mol Ecol 22:3261–3278
    PubMed  Article  Google Scholar 

    Velo-Antón G, Buckley D (2015) Salamandra común—Salamandra salamandra. In: Salvador A, Martínez-Solano I (eds), Enciclopedia Virtual de los Vertebrados Españoles, Museo Nacional de Ciencias Naturales, CSIC www.vertebradosibericos.org

    Wang IJ (2013) 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
    PubMed  Article  Google Scholar 

    Wang IJ, Bradburd GS (2014) Isolation by environment. Mol Ecol 23:5649–5662
    PubMed  PubMed Central  Article  Google Scholar 

    Wang IJ, Glor RE, Losos JB (2013) Quantifying the roles of ecology and geography in spatial genetic divergence. Ecol Lett 16:175–182
    PubMed  Article  Google Scholar 

    Weir BS, Cockerham CC (1984) Estimating F-statistics for the analysis of population structure. Evolution 38:1358–1370
    CAS  Google Scholar 

    Winiarski KJ, Peterman WE, Whiteley AR, McGarigal K (2020) Multiscale resistant kernel surfaces derived from inferred gene flow: an application with vernal pool breeding salamanders. Mol Ecol Resour 20:97–113
    CAS  PubMed  Article  Google Scholar 

    Wogan GOU, Yuan ML, Mahler DL, Wang IJ (2020) Genome-wide epigenetic isolation by environment in a widespread Anolis lizard. Mol Ecol 29:40–55
    CAS  PubMed  Article  Google Scholar 

    Wright S (1943) Isolation by distance. Genetics 28:114–138
    CAS  PubMed  PubMed Central  Google Scholar  More