More stories

  • in

    Distinct late Pleistocene subtropical-tropical divergence revealed by fifteen low-copy nuclear genes in a dominant species in South-East China

    1.
    Qian, H. & Ricklefs, R. E. Large-scale processes and the Asian bias in species diversity of temperate plants. Nature 407, 180–182 (2000).
    ADS  CAS  PubMed  Article  Google Scholar 
    2.
    Wu, Z. Y., Sun, H., Zhou, Z. K., Li, D. Z. & Peng, H. Floristics of Seed Plants From China (Science Press, Beijing, 2010).
    Google Scholar 

    3.
    Ying, T. S. & Chen, M. L. Plant Geography of China (Shanghai Scientific and Technical Publishers, Shanghai, 2011).
    Google Scholar 

    4.
    Ye, J. W., Zhang, Y. & Wang, X. J. Phylogeographic breaks and their forming mechanisms in Sino-Japanese Floristic Region. Chin. J. Plant Ecol. 41, 1003–1019 (2017).
    Article  Google Scholar 

    5.
    Guo, X. D. et al. Evolutionary history of a widespread tree species Acer mono in East Asia. Ecol. Evol. 4, 4332–4345 (2014).
    PubMed  PubMed Central  Article  Google Scholar 

    6.
    Liu, C. P. et al. Genetic structure and hierarchical population divergence history of Acer mono var. mono in south and northeast china. PLoS ONE 9, e87187 (2014).
    ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

    7.
    Bai, W. N., Wang, W. T. & Zhang, D. Y. Phylogeographic breaks within Asian butternuts indicate the existence of a phytogeographic divide in East Asia. New Phytol. 209, 1757–1772 (2016).
    CAS  PubMed  Article  Google Scholar 

    8.
    Ye, J. W., Bai, W. N., Bao, L., Wang, H. F. & Ge, J. P. Sharp genetic discontinuity in the arid-sensitive species Lindera obtusiloba (Lauraceae): Solid evidence supporting the Tertiary floral subdivision in East Asia. J. Biogeogr. 44, 2082–2095 (2017).
    Article  Google Scholar 

    9.
    Cao, Y. N., Comes, H. P., Sakaguchi, S., Chen, L. Y. & Qiu, Y. X. Evolution of East Asia’s Arcto-Tertiary relict Euptelea (Eupteleaceae) shaped by Late Neogene vicariance and Quaternary climate change. BMC Evol. Biol. 16, 1–17 (2016).
    Article  CAS  Google Scholar 

    10.
    Qi, X. S., Yuan, N., Comes, H. P., Sakaguchi, S. & Qiu, Y. X. A strong “filter” effect of the East China Sea land bridge for East Asia’s temperate plant species: Inferences from molecular phylogeography and ecological niche modelling of Platycrater arguta (Hydrangeaceae). BMC Evol. Biol. 14, 14–41 (2014).
    Article  Google Scholar 

    11.
    Ye, J. W., Zhang, Y. & Wang, X. J. Phylogeographic history of broad-leaved forest plants in subtropical China. Acta Ecol. Sin. 37, 5894–5904 (2017).
    Google Scholar 

    12.
    Wang, Y. H. et al. Molecular phylogeography and ecological niche modelling of a widespread herbaceous climber, Tetrastigma hemsleyanum (Vitaceae): Insights into Plio-Pleistocene range dynamics of evergreen forest in subtropical China. New Phytolt. 206, 852–867 (2015).
    Article  Google Scholar 

    13.
    Fan, D. M. et al. Idiosyncratic responses of evergreen broad-leaved forest constituents in China to the late Quaternary climate changes. Sci. Rep.-U.K. 6, 31044 (2016).
    ADS  CAS  Article  Google Scholar 

    14.
    Mu, H. P. et al. Genetic variation of Ardisia crenata in south China revealed by nuclear microsatellite. J. Syst. Evol. 48, 279–285 (2010).
    Article  Google Scholar 

    15.
    Shi, M. M., Michalski, S. G., Welk, E., Chen, X. Y. & Durka, W. Phylogeography of a widespread Asian subtropical tree: Genetic east-west differentiation and climate envelope modelling suggest multiple glacial refugia. J. Biogeogr. 41, 1710–1720 (2014).
    Article  Google Scholar 

    16.
    Zheng, J. Y., Yin, Y. H. & Li, B. Y. A new scheme for climate regionalization in China. Acta Geogr. Sin. 65, 3–12 (2010).
    ADS  Google Scholar 

    17.
    Bai, W. N. & Zhang, D. Y. Current status and future direction in plant phylogeography. Chin. Bull. Life Sci. 26, 125–137 (2014).
    Google Scholar 

    18.
    Wang, X. H., Kent, M. & Fang, X. F. Evergreen broad-leaved forest in Eastern China: Its ecology and conservation and the importance of resprouting in forest restoration. For. Ecol. Manag. 245, 76–87 (2007).
    Article  Google Scholar 

    19.
    Hirayama, D., Itoh, A. & Yamakura, T. Implications from seed traps for reproductive success, allocation and cost in a tall tree species Lindera erythrocarpa. Plant Spec. Biol. 19, 185–196 (2004).
    Article  Google Scholar 

    20.
    Ye, J. W., Li, D. Z. & Hampe, A. Differential Quaternary dynamics of evergreen broadleaved forests in subtropical China revealed by phylogeography of Lindera aggregata (Lauraceae). J. Biogeogr. 46, 1112–1123 (2019).
    Article  Google Scholar 

    21.
    Wright, S. Isolation by distance. Genetics 28, 114 (1943).
    CAS  PubMed  PubMed Central  Google Scholar 

    22.
    Wang, I. J. & Bradburd, G. S. Isolation by environment. Mol. Ecol. 23, 5649–5662 (2014).
    PubMed  Article  Google Scholar 

    23.
    McRae, B. H. & Beier, P. Circuit theory predicts gene flow in plant and animal populations. Proc. Natl. Acad. Sci. U. S. A. 104, 19885–19890 (2007).
    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

    24.
    Drouin, G., Daoud, H. & Xia, J. Relative rates of synonymous substitutions in the mitochondrial, chloroplast and nuclear genomes of seed plants. Mol. Phylogenet. Evol. 49, 827–831 (2008).
    CAS  PubMed  Article  Google Scholar 

    25.
    Meirmans, P. G. The trouble with isolation by distance. Mol. Ecol. 21, 2839–2846 (2012).
    PubMed  Article  Google Scholar 

    26.
    Meirmans, P. G. Seven common mistakes in population genetics and how to avoid them. Mol. Ecol. 24, 3223–3231 (2015).
    PubMed  Article  Google Scholar 

    27.
    Gong, W. et al. From glacial refugia to wide distribution range: Demographic expansion of Loropetalum chinense (Hamamelidaceae) in Chinese subtropical evergreen broadleaved forest. Org. Divers. Evol. 16, 23–38 (2016).
    Article  Google Scholar 

    28.
    Li, X. H., Shao, J. W., Lu, C., Zhang, X. P. & Qiu, Y. X. Chloroplast phylogeography of a temperate tree Pteroceltis tatarinowii (Ulmaceae) in China. J. Syst. Evol. 50, 325–333 (2012).
    Article  Google Scholar 

    29.
    Tian, S. et al. Phylogeography of Eomecon chionantha in subtropical China: The dual roles of the Nanling Mountains as a glacial refugium and a dispersal corridor. BMC Evol. Biol. 18, 20 (2018).
    PubMed  PubMed Central  Article  Google Scholar 

    30.
    Waters, J. M., Fraser, C. I. & Hewitt, G. M. Founder takes all: Density-dependent processes structure biodiversity. Trends Ecol. Evol. 28, 78–85 (2013).
    PubMed  Article  Google Scholar 

    31.
    Smith, C. G. III., Hamel, P. B., Devall, M. S. & Schiff, N. M. Hermit thrush is the first observed dispersal agent for pondberry (Lindera melissifolia). Castanea 69, 1–8 (2004).
    Article  Google Scholar 

    32.
    Excoffier, L., Foll, M. & Petit, R. J. Genetic consequences of range expansions. Annu. Rev. Ecol. Evol. S 40, 481–501 (2009).
    Article  Google Scholar 

    33.
    Ge, X. J. et al. Inferring multiple refugia and phylogeographical patterns in Pinus massoniana based on nucleotide sequence variation and DNA fingerprinting. PLoS ONE 7, e43717 (2012).
    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

    34.
    Chen, Y. et al. Genetic diversity and variation of Chinese fir from Fujian province and Taiwan, China, based on ISSR markers. PLoS ONE 12, e0175571 (2017).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    35.
    Jiang, X. L., Gardner, E. M., Meng, H. H., Deng, M. & Xu, G. B. Land bridges in the Pleistocene contributed to flora assembly on the continental islands of South China: Insights from the evolutionary history of Quercus championii. Mol. Phylogenet. Evol. 132, 36–45 (2019).
    PubMed  Article  Google Scholar 

    36.
    Hewitt, G. M. Genetic consequences of climatic oscillations in the Quaternary. Philos. Trans. R. Soc. B 359, 183–195 (2004).
    CAS  Article  Google Scholar 

    37.
    Miller, K. G., Mountain, G. S., Wright, J. D. & Browning, J. V. A 180-million-year record of sea level and ice volume variations from continental margin and deep-sea isotopic records. Oceanography 24, 40–53 (2011).
    Article  Google Scholar 

    38.
    Voris, H. K. Maps of Pleistocene sea levels in Southeast Asia: Shorelines, river systems and time durations. J. Biogeogr. 27, 1153–1167 (2000).
    Article  Google Scholar 

    39.
    Yao, Y. T., Harff, J., Meyer, M. & Zhan, W. H. Reconstruction of paleocoastlines for the northwestern South China Sea since the Last Glacial Maximum. Sci. China Ser. D Earth Sci. 52, 1127–1136 (2009).
    ADS  CAS  Article  Google Scholar 

    40.
    He, J. K., Gao, Z. F., Su, Y. Y., Lin, S. L. & Jiang, H. S. Geographical and temporal origins of terrestrial vertebrates endemic to Taiwan. J. Biogeogr. 45, 2458–2470 (2018).
    Article  Google Scholar 

    41.
    Li, H. W. Parallel evolution in Litsea and Lindera of lauraceae. Acta Bot. Yunnanica 7, 129–135 (1985).
    Google Scholar 

    42.
    Tian, X. Y., Ye, J. W. & Song, Y. Plastome sequences help to improve the systematic position of trinerved Lindera species in the family Lauraceae. Peerj 7, e7662 (2019).
    PubMed  PubMed Central  Article  Google Scholar 

    43.
    Rozas, J., Sánchez-DelBarrio, J. C., Messeguer, X. & Rozas, R. DnaSP, DNA polymorphism analyses by the coalescent and other methods. Bioinformatics 19, 2496–2497 (2003).
    CAS  PubMed  Article  Google Scholar 

    44.
    Falush, D., Stephens, M. & Pritchard, J. K. Inference of population structure using multilocus genotype data: Dominant markers and null alleles. Mol. Ecol. Notes 7, 574–578 (2007).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    45.
    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 

    46.
    Heled, J. & Drummond, A. J. Bayesian inference of species trees from multilocus data. Mol. Biol. Evol. 27, 570–580 (2010).
    CAS  PubMed  Article  Google Scholar 

    47.
    Drummond, A. J. & Rambaut, A. BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evol. Biol. 7, 214 (2007).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    48.
    Cornuet, J. M. et al. DIYABC v2.0: A software to make approximate Bayesian computation inferences about population history using single nucleotide polymorphism, DNA Sequence and microsatellite data. Bioinformatics 30, 1187–1189 (2014).
    CAS  PubMed  Article  Google Scholar 

    49.
    Yu, Y., Harris, A. J., Blair, C. & He, X. RASP (Reconstruct Ancestral State in Phylogenies): A tool for historical biogeography. Mol. Phylogenet. Evol. 87, 46–49 (2015).
    PubMed  Article  Google Scholar 

    50.
    R Core Team R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. http://www.Rproject.org/. Accessed 24 May 2014. (2013).

    51.
    Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978 (2005).
    Article  Google Scholar 

    52.
    Phillips, S. J., Anderson, R. P. & Schapire, R. E. Maximum entropy modeling of species geographic distributions. Ecol. Model 190, 231–259 (2006).
    Article  Google Scholar 

    53.
    Wang, Y. H., Yang, K. C., Bridgman, C. L. & Lin, L. K. Habitat suitability modelling to correlate gene flow with landscape connectivity. Landsc. Ecol. 23, 989–1000 (2008).
    Google Scholar 

    54.
    Wang, I. J. Examining the full effects of landscape heterogeneity on spatial genetic variation: A multiple matrix regression approach for quantifying geographic and ecological isolation. Evolution 67, 3403–3411 (2013).
    PubMed  Article  Google Scholar  More

  • in

    An elongated COI fragment to discriminate botryllid species and as an improved ascidian DNA barcode

    1.
    Blanchoud, S., Rutherford, K., Zondag, L., Gemmell, N. J. & De Wilson, M. J. De novo draft assembly of the Botrylloides leachii genome provides further insight into tunicate evolution. Sci. Rep. 8, 5518 (2018).
    ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 
    2.
    Lambert, G. Invasive sea squirts: A growing global problem. J. Exp. Mar. Biol. Ecol. 342, 3–4 (2007).
    Article  Google Scholar 

    3.
    Manni, L., Zaniolo, G., Cima, F., Burighel, P. & Ballarin, L. Botryllus schlosseri: A model ascidian for the study of asexual reproduction. Dev. Dyn. 236, 335–352 (2007).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    4.
    McKitrick, T. R., Muscat, C. C., Pierce, J. D., Bhattacharya, D. & De Tomaso, A. W. Allorecognition in a basal chordate consists of independent activating and inhibitory pathways. Immunity 34, 616–626 (2011).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    5.
    Rosengarten, R. D. & Nicotra, M. L. Model systems of invertebrate allorecognition. Curr. Biol. 21, R82-92 (2011).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    6.
    Voskoboynik, A. & Weissman, I. L. Botryllus schlosseri, an emerging model for the study of aging, stem cells, and mechanisms of regeneration. Invertebr. Reprod. Dev. 59, 33–38 (2015).
    PubMed  Article  PubMed Central  Google Scholar 

    7.
    Gasparini, F. et al. Sexual and asexual reproduction in the colonial ascidian Botryllus schlosseri. Genes. N. Y. N 2000(53), 105–120 (2015).
    Google Scholar 

    8.
    Manni, L. et al. Sixty years of experimental studies on the blastogenesis of the colonial tunicate Botryllus schlosseri. Curr. Dir. Tunicate Dev. 448, 293–308 (2019).
    CAS  Google Scholar 

    9.
    Bock, D. G., MacIsaac, H. J. & Cristescu, M. E. Multilocus genetic analyses differentiate between widespread and spatially restricted cryptic species in a model ascidian. Proc. R. Soc. B Biol. Sci. 279, 2377–2385 (2012).
    Article  Google Scholar 

    10.
    Brunetti, R. Botryllid species (Tunicata, Ascidiacea) from the Mediterranean coast of Israel, with some considerations on the systematics of Botryllinae. Zootaxa 2289, 18–32 (2009).
    Article  Google Scholar 

    11.
    Monniot, C. & Monniot, F. Les ascidies de Polynésie francaise. Mem Mus Nat Hist Nat Paris 136, 1–154 (1987).
    Google Scholar 

    12.
    Milne Edwards, H. Observation sur les Ascidies composées des côtes de la Manche. Mém. Académie Sci. Inst. Fr. 18, 217–326 (1841).
    Google Scholar 

    13.
    Saito, Y., Shirae, M., Okuyama, M. & Cohen, S. Phylogeny of botryllid ascidians. in The Biology of Ascidians (eds. Sawada, H., Yokosawa, H. & Lambert, C. C.) 315–320 (Springer-Verlag, 2001).

    14.
    Saito, Y. & Okuyama, M. Studies on Japanese botryllid ascidians. IV. A new species of the genus Botryllus with a unique colony shape, from the vicinity of Shimoda. Zoolog. Sci. 20, 1153–61 (2003).

    15.
    Saito, Y., Mukai, H. & Watanabe, H. Studies of Japanese compound styelid ascidians I. Two new species of Botryllus from the vicinity of Shimoda. Publ. Seto Mar. Biol. Lab. 26, 347–355 (1981).

    16.
    Saito, Y., Mukai, H. & Watanabe, H. Studies on Japanese compound styelid ascidians. II. A new species of the genus Botrylloides and redescription of B. violaceus Oka. Publ. Seto Mar. Biol. Lab. 26, 357–368 (1981).

    17.
    Saito, Y. & Watanabe, H. Studies on Japanese compound styelid ascidians IV. Three new species of the genus Botrylloides from the vicinity of Shimoda. Publ. Seto Mar. Biol. Lab. 30, 227–240 (1985).

    18.
    Lopez-Legentil, S., Turon, X. & Planes, S. Genetic structure of the star sea squirt, Botryllus schlosseri, introduced in southern European harbours. Mol. Ecol. 15, 3957–3967 (2006).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    19.
    Pérez-Portela, R., Bishop, J. D., Davis, A. R. & Turon, X. Phylogeny of the families Pyuridae and Styelidae (Stolidobranchiata, Ascidiacea) inferred from mitochondrial and nuclear DNA sequences. Mol. Phylogenet. Evol. 50, 560–570 (2009).
    PubMed  Article  CAS  PubMed Central  Google Scholar 

    20.
    Yund, P. O., Collins, C. & Johnson, S. L. Evidence of a native Northwest Atlantic COI haplotype clade in the cryptogenic colonial ascidian Botryllus schlosseri. Biol. Bull. 228, 201–216 (2015).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    21.
    Hebert, P. D., Cywinska, A., Ball, S. L. & deWaard, J. R. Biological identifications through DNA barcodes. Proc. R. Soc. B Biol. Sci. 270, 313–21 (2003).

    22.
    Folmer, O., Black, M., Hoeh, W., Lutz, R. & Vrijenhoek, R. DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. Mol. Mar. Biol. Biotechnol. 3, 294–299 (1994).
    CAS  PubMed  PubMed Central  Google Scholar 

    23.
    Haydar, D., Hoarau, G., Olsen, J. L., Stam, W. T. & Wolff, W. J. Introduced or glacial relict? Phylogeography of the cryptogenic tunicate Molgula manhattensis (Ascidiacea, Pleurogona). Divers. Distrib. 17, 68–80 (2011).
    Article  Google Scholar 

    24.
    Monniot, F., Dettaï, A., Eléaume, M., Cruaud, C. & Améziane, N. Antarctic Ascidians (Tunicata) of the French-Australian survey CEAMARC in Terre Adélie. Zootaxa 2817, 1–54 (2011).
    Article  Google Scholar 

    25.
    Nydam, M. L. & Harrison, R. G. Genealogical relationships within and among shallow-water Ciona species (Ascidiacea). Mar. Biol. 151, 1839–1847 (2007).
    Article  Google Scholar 

    26.
    Pérez-Portela, R., Duran, S., Palacín, C. & Turon, X. The genus Pycnoclavella (Ascidiacea) in the Atlanto-Mediterranean region: a combined molecular and morphological approach. Invertertebrate Syst. 21, 187–205 (2007).
    Article  Google Scholar 

    27.
    Rubinstein, N. D. et al. Deep sequencing of mixed total DNA without barcodes allows efficient assembly of highly plastic ascidian mitochondrial genomes. Genome Biol. Evol. 5, 1185–1199 (2013).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    28.
    Stefaniak, L. et al. Genetic conspecificity of the worldwide populations of Didemnum vexillum Kott, 2002. Aquat. Invasions 4, 29–44 (2009).
    Article  Google Scholar 

    29.
    Cohen, C. S., Saito, Y. & Weissman, I. L. Evolution of allorecognition in Botryllid ascidians inferred from a molecular phylogeny. Evolution 52, 746–756 (1998).
    PubMed  Article  PubMed Central  Google Scholar 

    30.
    Atsumi, M. O. & Saito, Y. Studies on Japanese botryllid ascidians. V. A New species of the genus Botrylloides very similar to Botrylloides simodensis in morphology. Zoolog. Sci. 28, 532–542 (2011).

    31.
    Griggio, F. et al. Ascidian mitogenomics: comparison of evolutionary rates in closely related taxa provides evidence of ongoing speciation events. Genome Biol. Evol. 6, 591–605 (2014).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    32.
    Nydam, M. L., Giesbrecht, K. B. & Stephenson, E. E. Origin and dispersal history of two colonial ascidian clades in the Botryllus schlosseri species complex. PLoS ONE 12, e0169944 (2017).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    33.
    Reem, E., Douek, J., Paz, G., Katzir, G. & Rinkevich, B. Phylogenetics, biogeography and population genetics of the ascidian Botryllus schlosseri in the Mediterranean Sea and beyond. Mol. Phylogenetic Evol. 107, 221–231 (2017).
    Article  Google Scholar 

    34.
    Berrill, N. J. The Tunicata with an account of the British species. vol. 133 (1950).

    35.
    Ben-Shlomo, R., Reem, E., Douek, J. & Rinkevich, B. Population genetics of the invasive ascidian Botryllus schlosseri from South American coasts. Mar. Ecol. Prog. Ser. 412, 85–92 (2010).
    ADS  Article  Google Scholar 

    36.
    Lord, J. Temperature, space availability, and species assemblages impact competition in global fouling communities. Biol. Invasions 19, 43–55 (2017).
    Article  Google Scholar 

    37.
    Rocha, R. M. et al. The power of combined molecular and morphological analyses for the genus Botrylloides: identification of a potentially global invasive ascidian and description of a new species. Syst. Biodivers. 17, 509–526 (2019).
    Article  Google Scholar 

    38.
    Brunetti, R., Griggio, F., Mastrototaro, F., Gasparini, F. & Gissi, C. Toward a resolution of the cosmopolitan Botryllus schlosseri species complex (Ascidiacea, Styelidae): mitogenomics and morphology of clade E (Botryllus gaiae). Zool. J. Linn. Soc. 190, 1175–1192 (2020).
    Google Scholar 

    39.
    Brunetti, R., Manni, L., Mastrototaro, F., Gissi, C. & Gasparini, F. Fixation, description and DNA barcode of a neotype for Botryllus schlosseri (Pallas, 1766) (Tunicata, Ascidiacea). Zootaxa 4353, 29–50 (2017).
    PubMed  Article  PubMed Central  Google Scholar 

    40.
    Bay-Nouailhat, A., Bay-Nouailhat, W., Gasparini, F. & Brunetti, R. Botrylloides crystallinus n. sp., a new Botryllinae Adams & Adams, 1858 (Ascidiacea) from Mediterranean Sea. Zoosystema 42, 131–138 (2020).

    41.
    Shenkar, N. & Monniot, F. A new species of the genus Botryllus (Ascidiacea) from the Red Sea. Zootaxa 1256, 11–19 (2006).
    Google Scholar 

    42.
    Brunetti, R. Fixation and redescription of a neotype for Polyclinus renierii Lamarck, 1815 (Tunicata, Ascidiacea, Styelidae, Botryllinae). Bolletino Mus. Storia Nat. Venezia 62, 105–113 (2011).
    Google Scholar 

    43.
    Sigovini, M., Keppel, E. & Tagliapietra, D. Open Nomenclature in the biodiversity era. Methods Ecol. Evol. 7, 1217–1225 (2016).
    Article  Google Scholar 

    44.
    Kearse, M. et al. 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 

    45.
    Crooks, G. E., Hon, G., Chandonia, J.-M. & Brenner, S. E. WebLogo: a sequence logo generator. Genome Res. 14, 1188–1190 (2004).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    46.
    Gouy, M., Guindon, S. & Gascuel, O. SeaView version 4: A multiplatform graphical user interface for sequence alignment and phylogenetic tree building. Mol. Biol. Evol. 27, 221–224 (2010).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    47.
    Durrheim, G. A., Corfield, V. A., Harley, E. H. & Ricketts, M. H. Nucleotide sequence of cytochrome oxidase (subunit III) from the mitochondrion of the tunicate Pyura stolonifera: evidence that AGR encodes glycine. Nucleic Acids Res. 21, 3587–3588 (1993).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    48.
    Yokobori, S., Ueda, T. & Watanabe, K. Codons AGA and AGG are read as glycine in ascidian mitochondria. J. Mol. Evol. 36, 1–8 (1993).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    49.
    Iannelli, F., Griggio, F., Pesole, G. & Gissi, C. The mitochondrial genome of Phallusia mammillata and Phallusia fumigata (Tunicata, Ascidiacea): high genome plasticity at intra-genus level. BMC Evol. Biol. 7, 155 (2007).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    50.
    Hirose, M. & Hirose, E. DNA barcoding in photosymbiotic species of Diplosoma (Ascidiacea: Didemnidae), with the description of a new species from the southern Ryukyus Japan. Zool. Sci. 26, 564–568 (2009).
    CAS  Article  Google Scholar 

    51.
    Fulton, T. M., Chunwongse, J. & Tanksley, S. D. Microprep protocol for extraction of DNA from tomato and other herbaceous plants. Plant Mol. Biol. Report. 13, 207–209 (1995).
    CAS  Article  Google Scholar 

    52.
    Viard, F., Roby, C., Turon, X., Bouchemousse, S. & Bishop, J. Cryptic diversity and database errors challenge non-indigenous species surveys: an illustration with Botrylloides spp. in the English channel and Mediterranean Sea. Front. Mar. Sci. 6, (2019).

    53.
    Brunetti, R. & Mastrototaro, F. Ascidiacea of the European waters. (Edagricole – Edizioni Agricole di New Business Media Srl, 2017).

    54.
    Zeng, L., Jacobs, M. W. & Swalla, B. J. Coloniality has evolved once in Stolidobranch ascidians. Integr. Comp. Biol. 46, 255–268 (2006).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    55.
    Katoh, K. & Toh, H. Recent developments in the MAFFT multiple sequence alignment program. Brief. Bioinform. 9, 286–298 (2008).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    56.
    Lacoursiere-Roussel, A. et al. Disentangling invasion processes in a dynamic shipping-boating network. Mol. Ecol. 21, 4227–4241 (2012).
    PubMed  Article  PubMed Central  Google Scholar 

    57.
    Lejeusne, C., Bock, D. G., Therriault, T. W., MacIsaac, H. J. & Cristescu, M. E. Comparative phylogeography of two colonial ascidians reveals contrasting invasion histories in North America. Biol. Invasions 13, 635–650 (2011).
    Article  Google Scholar 

    58.
    Guindon, S. & Gascuel, O. A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52, 696–704 (2003).
    PubMed  PubMed Central  Article  Google Scholar 

    59.
    Lefort, V., Longueville, J. E. & Gascuel, O. SMS: Smart Model Selection in PhyML. Mol. Biol. Evol. 34, 2422–2424 (2017).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    60.
    Ronquist, F. et al. MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space. Syst. Biol. 61, 539–542 (2012).

    61.
    Puillandre, N., Lambert, A., Brouillet, S. & Achaz, G. ABGD, automatic barcode gap discovery for primary species delimitation. Mol. Ecol. 21, 1864–1877 (2012).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    62.
    Zhang, J., Kapli, P., Pavlidis, P. & Stamatakis, A. A general species delimitation method with applications to phylogenetic placements. Bioinformatics 29, 2869–2876 (2013).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    63.
    Jukes, T. H. & Cantor, C. R. Evolution of protein molecules. (Academic Press, 1969).

    64.
    Kimura, M. A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J. Mol. Evol. 16, 111–120 (1980).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    65.
    Tang, C. Q., Humphreys, A. M., Fontaneto, D. & Barraclough, T. G. Effects of phylogenetic reconstruction method on the robustness of species delimitation using single-locus data. Methods Ecol. Evol. 5, 1086–1094 (2014).
    PubMed  PubMed Central  Article  Google Scholar 

    66.
    Voskoboynik, A. et al. The genome sequence of the colonial chordate Botryllus schlosseri. eLife 2, e00569 (2013).
    PubMed  PubMed Central  Article  Google Scholar 

    67.
    Stach, T. & Turbeville, J. M. Phylogeny of Tunicata inferred from molecular and morphological characters. Mol. Phylogenet. Evol. 25, 408–428 (2002).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    68.
    Webb, K. E., Barnes, D. K. A., Clark, M. S. & Bowden, D. A. DNA barcoding: A molecular tool to identify Antarctic marine larvae. Deep Sea Res. Part II Top. Stud. Oceanogr. 53, 1053–1060 (2006).

    69.
    Bock, D. G., Zhan, A., Lejeusne, C., MacIsaac, H. J. & Cristescu, M. E. Looking at both sides of the invasion: Patterns of colonization in the violet tunicate Botrylloides violaceus. Mol. Ecol. 20, 503–516 (2011).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    70.
    Bishop, J. D. D. et al. The Southern Hemisphere ascidian Asterocarpa humilis is unrecognised but widely established in NW France and Great Britain. Biol. Invasions 15, 253–260 (2013).
    Article  Google Scholar 

    71.
    Geller, J., Meyer, C., Parker, M. & Hawk, H. Redesign of PCR primers for mitochondrial cytochrome c oxidase subunit I for marine invertebrates and application in all-taxa biotic surveys. Mol. Ecol. Resour. 13, 851–861 (2013).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    72.
    Erpenbeck, D., Hooper, J. N. A. & Wörheide, G. CO1 phylogenies in diploblasts and the ‘Barcoding of Life’— are we sequencing a suboptimal partition?. Mol. Ecol. Notes 6, 550–553 (2006).
    CAS  Article  Google Scholar 

    73.
    Herdman, W. A. Descriptive catalogue of the Tunicata in the Australian Museum Sydney N.S.W. Aust. Mus. Syd. Cat. 17, 1–139 (1899).

    74.
    Herdman, W. A. A revised classification of the Tunicata, with definitions of the orders, suborders, families, subfamilies, and genera, and analytical keys to the species. J. Linn. Soc. Lond. Zool. 23, 558–652 (1891).
    Article  Google Scholar 

    75.
    Kott, P. Catalogue of Tunicata in Australian waters. Australian Biological Resources Study. (2005).

    76.
    Kott, P. The Australian Ascidiacea. Part I, Phlebobranchia and Stolidobranchia. Mem. Qld. Mus. 23, 1–440 (1985).

    77.
    Tsagkogeorga, G. et al. An updated 18S rRNA phylogeny of tunicates based on mixture and secondary structure models. BMC Evol. Biol. 9, 187 (2009).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    78.
    Turon, X. & Lopez-Legentil, S. Ascidian molecular phylogeny inferred from mtDNA data with emphasis on the Aplousobranchiata. Mol. Phylogenet. Evol. 33, 309–320 (2004).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    79.
    Swalla, B. J., Cameron, C. B., Corley, L. S. & Garey, J. R. Urochordates are monophyletic within the deuterostomes. Syst. Biol. 49, 52–64 (2000).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    80.
    Delsuc, F., Brinkmann, H., Chourrout, D. & Philippe, H. Tunicates and not cephalochordates are the closest living relatives of vertebrates. Nature 439, 965–968 (2006).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    81.
    Tsagkogeorga, G., Turon, X., Galtier, N., Douzery, E. J. P. & Delsuc, F. Accelerated evolutionary rate of housekeeping genes in tunicates. J. Mol. Evol. 71, 153–167 (2010).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    82.
    Yokobori, S. i et al. Complete DNA sequence of the mitochondrial genome of the ascidian Halocynthia roretzi (Chordata, Urochordata). Genetics 153, 1851–1862 (1999).

    83.
    Haye, P. A. & Muñoz-Herrera, N. C. Isolation with differentiation followed by expansion with admixture in the tunicate Pyura chilensis. BMC Evol. Biol. 13, 252 (2013).
    PubMed  PubMed Central  Article  Google Scholar 

    84.
    Pérez-Portela, R. & Turon, X. Cryptic divergence and strong population structure in the colonial invertebrate Pycnoclavella communis (Ascidiacea) inferred from molecular data. Zool. Jena 111, 163–178 (2008).
    Article  Google Scholar 

    85.
    Sheets, E. A., Cohen, C. S., Ruiz, G. M. & Rocha, R. M. Investigating the widespread introduction of a tropical marine fouling species. Ecol. Evol. 6, 2453–2471 (2016).
    PubMed  PubMed Central  Article  Google Scholar 

    86.
    Smith, K. F. et al. Increased inter-colony fusion rates are associated with reduced COI haplotype diversity in an invasive colonial ascidian Didemnum vexillum. PLoS ONE 7, e30473 (2012).
    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

    87.
    Tarjuelo, I., Posada, D., Crandall, K. A., Pascual, M. & Turon, X. Phylogeography and speciation of colour morphs in the colonial ascidian Pseudodistoma crucigaster. Mol. Ecol. 13, 3125–3136 (2004).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    88.
    Tarjuelo, I., Posada, D., Crandall, K., Pascual, M. & Turon, X. Cryptic species of Clavelina (Ascidiacea) in two different habitats: Harbours and rocky littoral zones in the northwestern Mediterranean. Mar. Biol. 139, 455–462 (2001).
    Article  Google Scholar 

    89.
    de France, F. Harant, H. & Vernieres, P. Tuniciers. Fasc. 1. Ascidies. in. In. Paris 27, 1–101 (1933).
    Google Scholar 

    90.
    Lambert, G. Ecology and natural history of the protochordates. Can. J. Zool. 83, 34–50 (2005).
    Article  Google Scholar 

    91.
    Millar, R. H. The biology of ascidians. Adv. Mar. Biol. 9, 1–100 (1971).
    ADS  Article  Google Scholar 

    92.
    da Silva Oliveira, F. A., Michonneau, F. & da Cruz Lotufo, T. M. Molecular phylogeny of Didemnidae (Ascidiacea: Tunicata). Zool. J. Linn. Soc. 180, 603–612 (2017).

    93.
    Tabudravu, J. N. et al. LC-HRMS-Database screening metrics for rapid prioritization of samples to accelerate the discovery of structurally new natural products. J. Nat. Prod. 82, 211–220 (2019).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    94.
    Mastrototaro, F. et al. An integrative taxonomic framework for the study of the genus Ciona (Ascidiacea) and description of a new species Ciona intermedia. Zool. J. Linn. Soc. 190, 1193–1216 (2020).
    Google Scholar 

    95.
    Mastrototaro, F. et al. Hitch-hikers of the sea: concurrent morphological and molecular identification of Symplegma brakenhielmi (Tunicata: Ascidiacea) in the western Mediterranean Sea. Mediterr. Mar. Sci. 20, 197–207 (2019).
    Google Scholar  More

  • in

    Vivid biofluorescence discovered in the nocturnal Springhare (Pedetidae)

    1.
    Zhao, H. et al. The evolution of color vision in nocturnal mammals. PNAS 106, 8980–8985 (2009).
    ADS  CAS  Article  Google Scholar 
    2.
    Douglas, R. H. & Jeffery, G. The spectral transmission of ocular media suggests ultraviolet sensitivity is widespread among mammals. Proc. R. Soc. B. 281, 1471–2954. https://doi.org/10.1098/rspb.2013.2995 (2014).
    Article  Google Scholar 

    3.
    Pearn, S. M., Bennett, A. T. & Cuthill, I. C. Ultraviolet vision, fluorescence and mate choice in a parrot, the budgerigar Melopsittacus undulates. Proc. R. Soc. B. 268, 2273–2279. https://doi.org/10.1098/rspb.2001.1813 (2001).
    CAS  Article  PubMed  Google Scholar 

    4.
    Olofsson, M., Vallin, A., Jakobsson, S. & Wiklund, C. Marginal eyespots on butterfly wings deflect bird attacks under low light intensities with UV wavelengths. PLoS ONE 5, e10798. https://doi.org/10.1371/journal.pone.0010798 (2010).
    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

    5.
    Honkavaara, J., Koivula, M., Korpimaki, E., Siitari, H. & Viitala, J. Ultraviolet vision and foraging in terrestrial vertebrates. Oikos 98, 505–511. https://doi.org/10.1034/j.1600-0706.2002.980315.x (2008).
    Article  Google Scholar 

    6.
    McDonald, B., Geiger, B. & Vrla, S. Ultraviolet vision in Ord’s kangaroo rat (Dipodomys ordii). J. Mammal. https://doi.org/10.1093/jmammal/gyaa083 (2020).
    Article  Google Scholar 

    7.
    Hunt, D. M., Carvalho, L. S., Cowing, J. A. & Davies, W. L. Evolution and spectral tuning of visual pigments in birds and mammals. Phil. Trans. R. Soc. B. 364, 2941–2955. https://doi.org/10.1098/rstb.2009.0044 (2009).
    CAS  Article  PubMed  Google Scholar 

    8.
    Davies, W. L. et al. Visual pigments of the platypus: a novel route to mammalian colour vision. Curr. Biol. 17, R161–R163. https://doi.org/10.1016/j.cub.2007.01.037 (2007).
    CAS  Article  PubMed  Google Scholar 

    9.
    Jeng, M.-L. Biofluorescence in terrestrial animals, with emphasis on fireflies: A review and field observation. In Bioluminescence – analytical applications and basic biology (ed. Suzuki, H.) Ch. 6, https://doi.org/10.5772/intechopen.86029 (IntechOpen, 2019).

    10.
    Sparks, J. S. et al. The covert world of fish biofluorescence: A phylogenetically widespread and phenotypically variable phenomenon. PLoS ONE https://doi.org/10.1371/journal.pone.0083259 (2014).
    Article  PubMed  PubMed Central  Google Scholar 

    11.
    Park, H. B. et al. Bright green biofluorescence in sharks derives from Bromo-kynurenine metabolism. iScience 19, 1277–1286. https://doi.org/10.1016/j.isci.2019.07.019 (2019).
    CAS  Article  Google Scholar 

    12.
    Gruber, D. F. & Sparks, J. S. First observation of fluorescence in marine turtles. Am. Mus. Novit. 3845, 1–8. https://doi.org/10.1206/3845.1 (2015).
    Article  Google Scholar 

    13.
    Taboada, C. et al. Naturally occurring fluorescence in frogs. PNAS 114, 3672–3677. https://doi.org/10.1073/pnas.1701053114 (2017).
    CAS  Article  PubMed  Google Scholar 

    14.
    Prötzel, D. et al. Widespread bone-based fluorescence in chameleons. Sci. Rep. 8, 698. https://doi.org/10.1038/s41598-017-19070-7 (2018).
    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

    15.
    Goutte, S. et al. Intense bone fluorescence reveals hidden patterns in pumpkin toadlets. Sci. Rep. 9, 5388. https://doi.org/10.1038/s41598-019-41959-8 (2019).
    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

    16.
    Lamb, J. Y. & Davis, M. P. Salamanders and other amphibians are aglow with biofluorescence. Sci. Rep. 10, 2821. https://doi.org/10.1038/s41598-020-58528-9 (2020).
    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

    17.
    Weidensaul, C. S., Colvin, B. A., Brinker, D. F. & Huy, J. S. Use of ultraviolet light as an aid in age classification of owls. Wilson J Ornithol. 123, 373–377. https://doi.org/10.1676/09-125.1 (2011).
    Article  Google Scholar 

    18.
    Camacho, C., Negro, J. J., Redondo, I., Palacios, S. & Sáez-Gómez, P. Correlates of individual variation in the porphyrin-based fluorescence of red-necked nightjars. Sci. Rep. 9, 19115. https://doi.org/10.1038/s41598-019-55522-y (2019).
    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

    19.
    Kohler, A. M., Olson, E. R., Martin, J. G. & Anich, P. S. Ultraviolet fluorescence discovered in New World flying squirrels (Glaucomys). J. Mammal. 100, 21–30. https://doi.org/10.1093/jmammal/gyy177 (2019).
    Article  Google Scholar 

    20.
    Meisner, D. H. Psychedelic opossums: fluorescence of the skin and fur of Didelphis virginiana Kerr. Ohio J. Sci. 83, 4 (1983).
    Google Scholar 

    21.
    Pine, R. H., Rice, J. E., Bucher, J. E., Tank, D. J. Jr. & Greenhall, A. M. Labile pigments and fluorescent pelage in Didelphid marsupials. Mammalia 49, 249–256 (1985).
    Article  Google Scholar 

    22.
    Anich, P. S. et al. Biofluorescence in the platypus (Orinthorhynchus anatinus). Mammalia https://doi.org/10.1515/mammalia-2020-0027 (2020).
    Article  Google Scholar 

    23.
    Matthee, C. A. & Robinson, T. J. Mitochondrial DNA phylogeography and comparative cytogenetics of the springhare, Pedetes capensis (Mammalia: Reodentia). J. Mammal. Evol. 4, 53–73. https://doi.org/10.1023/A:1027331727034 (1997).
    Article  Google Scholar 

    24.
    Augustine, D. J., Manzon, A., Klopp, C. & Elter, J. Habitat selection and group foraging of the springhare, Pedetes capensis larvalis Hollister, East Africa. Afr. J. Ecol. 33, 347–357 (1995).
    Article  Google Scholar 

    25.
    Peinke, D. M. & Brown, C. R. Habitat use by the southern springhare (Pedetes capensis) in the Eastern Cape Province, South Africa. S. Afr. J. Wildl. Res. 36(2), 103–111 (2006).
    Google Scholar 

    26.
    Kennedy, G. Y. & Vevers, H. G. The occurrence of porphyrins in certain marine invertebrates. J. Mar. Biol. Ass. UK 33, 663–576 (1954).
    CAS  Article  Google Scholar 

    27.
    Comfort, A. The pigmentation of molluscan shells. Biol. Rev. 26, 285–301. https://doi.org/10.1111/j.1469-185X.1951.tb01358.x (1951).
    CAS  Article  Google Scholar 

    28.
    Thomas, D. B., McGoverin, C. M., McGraw, K. J., James, H. F. & Madden, O. Vibrational spectroscopic analyses of unique yellow feather pigments (spheniscins) in penguins. J. R. Soc. Interface 10, 20121065. https://doi.org/10.1098/rsif.2012.1065 (2012).
    Article  Google Scholar 

    29.
    With, T. K. On porphyrins in feathers of owls and bustards. Int. J. Biochem. 9, 893–895 (1978).
    CAS  Article  Google Scholar 

    30.
    With, T. K. Pure unequivocal uroporphyrin III simplified method of preparation from turaco feathers. J. Clin. Lab Invest. 9, 398–401 (1957).
    CAS  Article  Google Scholar 

    31.
    Dooley, A. C. Jr. & Moncrief, N. D. Fluorescence provides evidence of congenital erythropoietic porphyria in 7000-year-old specimens of the eastern fox squirrel (Sciurus niger) from the Devil’s Den. J. Vert. Paleontol. 32, 495–497 (2012).
    Article  Google Scholar 

    32.
    Ajioka, R. S., Phillips, J. D. & Kushner, J. P. Biosynthesis of heme in mammals. Biochem. Biophys. Acta. 1763, 723–736. https://doi.org/10.1016/j.bbamcr.2006.05.005 (2006).
    CAS  Article  PubMed  Google Scholar 

    33.
    Seo, I., Tseng, S. H., Cula, G. O., Bargo, P. R. & Kollias, N. Fluorescence spectroscopy for endogenous porphyrins in human facial skin. Proc. SPIE. https://doi.org/10.1117/12.811913 (2009).
    Article  Google Scholar 

    34.
    Heckl, C. et al. Rapid spectrophotometric quantification of urinary porphyrins and porphobilinogen as screening tool for attacks of acute porphyria. Proc. SPIE. https://doi.org/10.1117/12.2527105 (2019).
    Article  Google Scholar 

    35.
    Levin, E. Y. & Flyger, V. Erythropoietic Porphyria of Fox Squirrel Sciurus niger. J. Clin. Invest. 52, 96–105 (1973).
    CAS  Article  Google Scholar 

    36.
    Turner, W. J. Studies on porphyria. I. Observations on the fox squirrel, Sciurus niger. J. Biol. Chem. 118, 519–530 (1937).
    CAS  Article  Google Scholar 

    37.
    Rivera, D. F. & Leung, L.K.-P. A rare autosomal recessive condition, congenital erythropoietic porphyria, found in canefield rat Rattus sordidus Gould 1858. Integative Zool. 216–218, 2008. https://doi.org/10.1111/j.1749-4877.2008.00088.x (2008).
    Article  Google Scholar 

    38.
    Bickers, D. R., Keogh, L., Rifkind, A. B., Harber, L. C. & Kappas, A. Studies in porphyria VI. Biosynthesis of porphyrins in mammalian skin and in the skin of porphyric patients. J. Invest. Dermatol. 68(1), 5–9. https://doi.org/10.1111/1523-1747.ep12485121 (1977).
    CAS  Article  PubMed  Google Scholar 

    39.
    Yolton, R. L., Yolton, D. P., Renz, J. & Jacobs, G. H. Preretinal absorbance in sciurid eyes. J. Mammal. 55, 14–20 (1974).
    CAS  Article  Google Scholar 

    40.
    Friedmann, H. C. & Baldwin, E. T. Reverse-phase purification and silica gel thin-layer chromatography of porphyrin carboxylic acids. Anal. Biochem 137, 473–480 (1984).
    CAS  Article  Google Scholar 

    41.
    Lim, C. K. & Peters, T. J. Urine and faecal porphyrin profiles by reversed-phase high performance liquid chromatography in the porphyrias. Clin. Chim. Acta. 139, 55–63 (1984).
    CAS  Article  Google Scholar 

    42.
    To-Figueras, J., Ozalla, D. & Mateu, C. H. Long-standing changes in the urinary profile of porphyrin isomers after clinical remission of porphyria cutanea tarda. Ann. Clin. Lab. Sci. 33, 251–256 (2003).
    CAS  PubMed  Google Scholar  More

  • in

    The Late Miocene Rifian corridor as a natural laboratory to explore a case of ichnofacies distribution in ancient gateways

    Oceanic gateways play a key role in controlling global ocean circulation and climate systems1. Ancient seaways are unique environments in which a complex interplay of processes may take place (i.e., oceanic-, tidal-, bottom-, turbiditic- and wind-currents)2,3. The constricted morphology of the seaway usually funnels and amplifies the currents that shape the seafloor (i.e., tidal currents)4. Previous sedimentological studies of ancient seaways have been largely focussed on shallow counterparts (generally between 100 and 150 m of water depth)4,5,6. Few published examples of deep ancient seaways ( > 150 m) and associated deposits can be found. However, oceanographic studies have shown that deep seaways are different from shallow ones, with bottom-currents sometimes playing a dominant role7,8,9. The Rifian Corridor is one of those few examples (Fig. 1)2,3,10,11.
    Figure 1

    Palaeogeographic reconstruction of the late Miocene western Mediterranean with the location of the studied outcrops; red (lower) and orange (upper) arrows show palaeo-Mediterranean Outflow Water (palaeo-MOW) branches (modified from de Weger et al.2). Below, schematic sedimentary logs of the studied outcrops. Map created with Adobe Illustrator, version 22.1.0 (https://www.adobe.com/products/illustrator.html).

    Full size image

    During the late Miocene, the Atlantic Ocean and the Mediterranean Sea were connected by two principal gateways, with a complex morphology, sills and channels through south Iberia and north Africa —the Betic and Rifian corridors, respectively12,13. The Rifian Corridor was a main deep seaway of this network (Fig. 1). This gateway progressively closed (7.1–6.9 Ma) due to tectonically induced uplift, leading to the onset of the Mediterranean Salinity Crisis in the late Miocene13,14. During the late Tortonian, the seaway evolved into a narrow, deep corridor hosting a complex interplay of processes2,3.
    Ichnological analysis comprises a wide range of tools (e.g., ichnofabric approach, ichnofacies model) that prove very useful in sedimentary basin research15. The ichnofacies model is of special interest for detailed palaeoenvironmental reconstructions and for recognizing, distinguishing, and interpreting sedimentary environments16,17,18,19. Recent steps in ichnological research have established means of recognising and characterising contouritic processes, revealing the importance of ichnology as a proxy for discerning between contourites, turbidites, hemipelagites and pelagites20,21,22,23,24, but not without scepticism25. At any rate, the relationship between deep-sea settings and trace fossils is very complex, and depends highly upon the palaeonvironmental factors that affect trace makers26.
    Trace-fossil research on seaway environments has been conducted mainly on shallow marine settings, including brackish-water ecosystems (i.e., estuarine complexes, resulting in the so-called “brackish-water model”27,28), beach–shoreface complexes with evidence of tidal processes29,30, and compound dune fields31. Still, detailed trace-fossil analysis and ichnofacies characterisation of ancient deep seaways has never been carried out. The aim of this research is to conduct a detailed ichnological analysis of selected outcrops of the Rifian Corridor (Ain Kansera, Sidi Chahed, Kirmta and Sidi Harazem), as a unique opportunity to assess trace-fossil variations to interpret an ancient deep-water seaway where shallow marine processes (i.e., tidal variations), pelagic/hemipelagic settling, turbiditic supplies and contouritic flows closely (less than 20 km) interact2,3. We evaluate the importance of palaeoenvironmental factors such as nutrients, oxygenation, and flow velocity in a setting dominated by bottom currents, and their incidence on the trace maker community. The utility of the ichnofacies approach is underlined within the framework of improving high-resolution palaeoenvironmental reconstructions in different depositional environments of ancient deep gateways.
    Trace-fossil assemblages at the Rifian Corridor
    In both contouritic and turbiditic deposits, ichnodiversity is low (4 and 5 ichnogenera, respectively), whereas trace-fossil abundance is high in the former and moderate in the latter. Shallow marine deposits from the southern Rifian Corridor feature an abundant and moderately diverse trace-fossil assemblage (9 ichnogenera). Within the selected outcrops, the clear ichnological variability can be attributed to the different facies.
    The Sidi Harazem turbiditic ichnoassemblage consists of 5 ichnogenera —Ophiomorpha (O. rudis), Planolites, Spirophyton, Thalassinoides, and Zoophycos (Fig. 3E–H)— and the thick sandstone beds are more bioturbated than the marly ones. Ophiomorpha is the most abundant ichnogenus, and appears in the thick turbiditic sandstone beds; Thalassinoides is common, Planolites rare, and Zoophycos and Spirophyton is occasionally found. The trace-fossil assemblage of marly pelagic and hemipelagic deposits from the Sidi Harazem consists of abundant undifferentiated structures and scarce Planolites-like and Thalassinoides-like trace fossils.
    The sandy contourites in Kirmta and Sidi Chahed comprise a highly abundant and scarcely diverse trace-fossil assemblage (4 ichnogenera), dominated by Macaronichnus and Scolicia, and common Planolites and Thalassinoides (Fig. 2). Trace fossils were predominantly found in the planar-stratified and cross-bedded sandstone. Turbidites show an absence of discrete trace fossils. The trace = fossil assemblage of muddy contourite deposits from both outcrops consist of regular undifferentiated biogenic structures and scarce Planolites-like and Thalassinoides-like trace fossils.
    Figure 2

    Trace-fossil specimens from the sandy contourite deposits at Sidi Chahed (A–D) and Kirmta (E–H) outcrops. (A, B) Scolicia in the sole of sandy clastic contouritic beds of Sidi Chahed; (C) Close-up view of Macaronichnus at Sidi Chahed; (D) Planolites within the interbedding of the foresets at Sidi Chahed. (E) Scolicia and some Macaronichnus at Kirmta; (F, G) Macaronichnus isp. and some Thalassinoides in the sole of sandy clastic contouritic beds at Kirmta; (H) Close-up view of Macaronichnus at Kirmta. Macaronichnus (Ma), Planolites (Pl), Scolicia (Sc), and Thalassinoides (Th).

    Full size image

    The Ain Kansera section is characterised by a shallow marine ichnoassemblage with high ichnodiversity and an abundance of vertical structures, including 9 ichnogenera in the sandstone beds: Conichnus, Diplocraterion, Macaronichnus, Ophiomorpha, Parahaentzschelinia, Planolites, Scolicia, Skolithos, and Thalassinoides (Fig. 3A–D). The sandstone beds with swaley cross-stratification show a change in the trace-fossil assemblage towards the top of the outcrop. The lower sandstone beds present dominant Conichnus and Macaronichnus, common Parahaentzschelinia and Thalassinoides, and rare Diplocraterion, Planolites, and Scolicia. The upper sandstone beds record the disappearance of Conichnus and Parahaentzschelinia, while Ophiomorpha and Skolithos become dominant.
    Figure 3

    Trace-fossil specimens from shallow marine deposits at Ain Kansera (A–D) and turbiditic deposits at Sidi Harazem (E–H). (A) Close-up view of Macaronichnus at Ain Kansera; (B) Densely Conichnus assemblage at Ain Kansera; (C) Macaronichnus cross-cut by a Skolithos at Ain Kansera; (D) Skolithos and Ophiomorpha at Ain Kansera; (E, F) Ophiomorpha (O. rudis) at Sidi Harazem; (G) Zoophycos cross-cut by a Thalassinoides at Sidi Harazem; (H) Close-up view of Spyrophyton at Sidi Harazem. Conichnus (Co), Macaronichnus (Ma), Ophiomorpha (Op), Skolithos (Sk), Spyrophyton (Sp), Thalassinoides (Th), and Zoophycos (Zo).

    Full size image

    Ichnofacies characterisation
    The trace-fossil assemblage of Sidi Harazem is typified by vertical burrows of Ophiomorpha rudis and some Thalassinoides. Ophiomorpha is generally but not exclusively characteristic of high-energy environments (i.e., shoreface) in well-sorted, shifting sandy substrates, constituting a common element of the Skolithos and Cruziana ichnofacies17,18. However, the appearance of Ophiomorpha in deep-sea environments is also recorded, and usually explained as an effect of transport of the trace makers by currents from shallow marine environments into the deep-sea33,34. Uchman35 proposed the Ophiomorpha rudis ichnosubfacies within the Nereites ichnofacies for the record of ichnoassemblages dominated by Ophiomorpha rudis in thick sandstone beds related with channels and proximal lobes in turbiditic systems36. Accordingly, the Sidi Harazem trace-fossil assemblage could be associated with the Ophiomorpha rudis ichnosubfacies. Ichnosubfacies/ichnofacies assignation is tentative due to the absence of other components of this ichnosubfacies (e.g., Scolicia, Nereites, graphoglyptids); this uncertainty is tied to outcrop limitations, e.g. the low exposure of turbiditic soles and difficulties in observing discrete trace fossils in the non-compact hemipelagic and pelagic deposits.
    The trace-fossil assemblages of Kirmta and Sidi Chahed feature high abundance and low ichnodiversity, being dominated by horizontal trace fossils, such as Macaronichnus and Scolicia. Macaronichnus is usually interpreted as a shallow marine (up to foreshore) trace fossil37 that occasionally appears in deeper water environments38,39 and is commonly associated with the Skolithos ichnofacies17,18,19,40. Scolicia presents a wide environmental range, but is a typical element of the deep-marine Nereites and the shelfal Cruziana ichnofacies40. The proximal expression of the Cruziana ichnofacies is dominated by deposit-feeding burrows, but also includes structures of passive carnivores, omnivores, suspension feeders, as well as grazing forms41. This ichnofacies is defined as a transition between the distal expression of the Skolithos ichnofacies and the archetypal Cruziana ichnofacies41. The low ichnodiversity observed within the contourite facies from Kirmta and Sidi Chahed outcrops, together with the ubiquity of the dominant trace fossils, hamper a conclusive ichnofacies assignation. Still, though Macaronichnus is typical from high energy shallow marine environments, it may locally appear in the proximal Cruziana ichnofacies41. Considering the dominance of horizontal feeding trace fossils produced by deposit and detritus feeders over dwelling structures of suspension feeding structures, contourite ichnoassemblages at the Rifian Corridor, registered at Kirmta and Sidi Chahed outcrops, can therefore be tentatively assigned to an impoverished proximal Cruziana ichnofacies18.
    The trace-fossil assemblage of Ain Kansera is characterised by moderate ichnodiversity with a dominance of vertical (Skolithos and Ophiomorpha), cylindrical or conic-shaped (Conichnus) dwelling burrows of suspension feeders and passive predators. Horizontal trace fossils produced by a mobile fauna are scarce, mainly associated with Macaronichnus trace makers. According to these ichnological features, shallow marine facies at the Rifian Corridor —represented by Ain Kansera sediments— can be clearly assigned to the Skolithos ichnofacies, with predominant burrow systems having vertical, cylindrical, or U-shaped components of suspension feeders and passive predators, and a scarcity of horizontal trace fossils17,18,19,40,42.
    Ichnofacies in the Rifian Corridor seaways: hydrodynamic energy and the incidence of bottom currents
    Over the past years, detailed ichnological research has revealed the major incidence of particular environmental factors (e.g., organic-matter content, oxygenation, sedimentation rate) on ichnological attributes from deep-sea environments, including ichnofacies characterisation and distribution26. The deep sea is a complex environment where several depositional processes co-exist, including pelagic/hemipelagic settling, bottom currents and gravity flows9. Trace-fossil analysis has proven useful for discerning and characterising such sedimentary environments and associated deposits21. Hydrodynamic conditions are a very significant limiting factor for trace makers, inducing variations in distribution and behaviour, hence in the preservation of trace fossils19,29,43,44. Typically, ichnoassemblages related to high energy conditions are characterised by vertical dwelling structures of infaunal suspension feeders and/or passive predators, forming low-diversity suites; ichnoassemblages related to low energy conditions are dominated by horizontal feeding trace fossils of deposit and detritus feeders, as well as higher diversity19. Ichnofacies identification is mainly based on the recognition of key features that connect biological structures with physical parameters (i.e., environmental conditions)17,18,19. Accordingly, ichnofacies reflect specific combinations of organisms´ responses to a wide range of environmental conditions.
    In the case of seaways, prevailing hydrodynamic conditions are a main environmental factor, along with controlling depositional processes and sedimentation regimes6,30. Even though the number of trace-fossil studies is considerably lower than in other clastic shallow or deep marine environments, ichnological analysis has proven to be useful to characterise waves, tides or storms in shallow seaways29,30, overlooking deep seaways and their implications. Deep seaways with narrow palaeogeographical configuration, as is the case of the Rifian Corridor10, would promote higher energetic conditions than those typical of deep-sea environments. In the study area, clearly distinct sedimentary environments —in terms of hydrodynamic conditions, bathymetry, rate of sedimentation, etc.— are closely spaced2, passing from shallow marine to turbiditic slope systems in less than 20 km (Fig. 4). Such variations in palaeoenvironmental conditions are supported by ichnofacies characterisation and distribution.
    Figure 4

    Palaeogeographic model of the late Miocene Rifian Corridor (Morocco) with ichnofacies distribution (lower red and upper orange branches indicate palaeo-MOW location; modified from de Weger et al.2). Conichnus (Co), Diplocraterion (Di), Macaronichnus (Ma), Ophiomorpha (Op), Parahaentzschelinia (Ph), Planolites (Pl), Scolicia (Sc), Skolithos (Sk), Spyrophyton (Sp), Thalassinoides (Th), and Zoophycos (Zo).

    Full size image

    Turbidite deposits from Sidi Harazem, emplaced on the slope of the Rifian Corridor, are typified by vertical trace fossils, mainly by the record of Ophiomorpha rudis. These ichnological attributes are similar to those associated with particular sub-environments (e.g., channels and proximal trubiditic lobes) of the turbiditic systems, conforming the Ophiomorpha rudis ichnosubfacies inside the Nereites ichnofacies36.
    Sandy contourite 2D- and 3D-dune facies (upper slope environment) (Fig. 4) from Sidi Chahed and Kirmta are related to high-energy deep-water environments. However, they are dominated by horizontal trace fossils (Macaronichnus and Scolicia) produced by mobile deposit- and detritus-feeders, discarding a direct assignation to the Skolithos ichnofacies. In this case, palaeoenvironmental conditions other than hydrodynamic energy must be considered to explain the dominance of horizontal forms and the absence of vertical biogenic structures. The record of densely Macaronichnus ichnoasemblages in these contourite sediments was recently linked to high nutrient supply provided by ancient bottom currents39,45. This agrees with the record of Scolicia: its abundance and size usually increase in conjunction with greater amounts and nutritious values of benthic food20,46. Thus, the strong palaeo-MOW bottom currents that dominated the slope may have created well-oxygenated and nutrient-rich benthic environments, favouring colonisation by trace makers that could exploit such accumulations of organic matter inside the sediment. Macaronichnus and Scolicia producers could develop an opportunistic behaviour, determining rapid and complete bioturbation, avoiding colonisation by other trace makers —including suspension feeders—these ichnological features resemble the Cruziana ichnofacies attributes. Notwithstanding, the high ichnodiversity that is characteristic of the Cruziana ichnofacies is absent here. The great abundance and low ichnodiversity observed for the contourite facies appear to indicate the absence of an archetypal Cruziana ichnofacies, but the development of the proximal Cruziana ichnofacies. Bottom currents and their associated deposits (i.e., contourites) have been previously linked to both the Cruziana and Zoophycos ichnofacies in Cyprus Miocene carbonate contourite deposits22,23, meaning that contourite deposits are not exclusively related to a single ichnofacies. The replacement from the Zoophycos to Cruziana ichnofacies was interpreted to be mainly controlled by sea level dynamics23.
    The shallow marine facies from Ain Kansera (shoreface environment) are dominated by vertical, cylindrical, or U-shaped dwelling burrows (Conichnus, Ophiomorpha and Skolithos) of suspension feeders (Fig. 4). These attributes are usually related to high energetic conditions developed in shallow marine environments conforming the Skolithos ichnofacies18.
    In short, at the Rifian Corridor, ichnofacies distributions from proximal to distal settings are controlled by bottom currents (palaeo-MOW), with hydrodynamic conditions being the major palaeonvironmental limiting factor. Particularly noteworthy is the development of the proximal Cruziana ichnofacies in deeper settings from the slope environments; bottom currents generated high energetic conditions similar to those of shallow/proximal areas. More

  • in

    Conservation priorities in an endangered estuarine seahorse are informed by demographic history

    1.
    Ramos-Onsins, S. E. & Rozas, J. Statistical properties of new neutrality tests against population growth. Mol. Biol. Evol. 19, 2092–2100 (2000).
    Article  Google Scholar 
    2.
    Wan, Q.-H., Wu, H., Fujihara, T. & Fang, S.-G. Which genetic marker for which conservation genetics issue? Electrophoresis 25, 2165–2176 (2004).
    CAS  PubMed  Article  Google Scholar 

    3.
    Selkoe, K. A. & Toonen, R. J. Microsatellites for ecologists: a practical guide to using and evaluating microsatellite markers. Ecol. Lett. 9, 615–629 (2006).
    PubMed  Article  Google Scholar 

    4.
    Rogers, A. R. & Harpending, H. Population growth makes waves in the distribution of pairwise genetic differences. Mol. Biol. Evol. 9, 552–569 (1992).
    CAS  PubMed  Google Scholar 

    5.
    Nabholz, B., Mauffrey, J.-F., Bazin, E., Galtier, N. & Glemin, S. Determination of mitochondrial genetic diversity in mammals. Genetics 178, 351–361 (2008).
    PubMed  PubMed Central  Article  Google Scholar 

    6.
    Whitfield, A., Mkare, T. K., Teske, P. R., James, N. & Cowley, P. D. Life-histories explain the conservation status of two estuary-associated pipefishes. Biol. Conserv. 212, 256–264 (2017).
    Article  Google Scholar 

    7.
    Leffler, E. M. et al. Revisiting an old riddle: what determines genetic diversity levels within species?. PLoS Biol. 10, e1001388 (2012).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    8.
    Kimura, M. & Crow, J. F. The number of alleles that can be maintained in a finite population. Genetics 49, 725–738 (1964).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    9.
    Kimura, M. The Neutral Theory of Molecular Evolution (Cambridge University Press, Cambridge, 1983).
    Google Scholar 

    10.
    Romiguier, J. et al. Comparative population genomics in animals uncovers the determinants of genetic diversity. Nature 515, 261–263 (2014).
    ADS  CAS  PubMed  Article  Google Scholar 

    11.
    Ellegren, H. & Galtier, N. Determinants of genetic diversity. Nat. Rev. Genet. 17, 422–433 (2016).
    CAS  PubMed  Article  Google Scholar 

    12.
    Caley, M. J. et al. Recruitment and the local dynamics of open marine populations. Annu. Rev. Ecol. Syst. 27, 477–500 (1996).
    Article  Google Scholar 

    13.
    Teske, P. R. et al. Implications of life history for genetic structure and migration rates of southern African coastal invertebrates: planktonic, abbreviated and direct development. Mar. Biol. 152, 697–711 (2007).
    Article  Google Scholar 

    14.
    Mkare, T. K., van Vuuren, B. J. & Teske, P. R. Conservation implications of significant population differentiation in an endangered estuarine seahorse. Biodivers. Conserv. 26, 1275–1293 (2017).
    Article  Google Scholar 

    15.
    Vandewoestijne, S., Schtickzelle, N. & Baguette, M. Positive correlation between genetic diversity and fitness in a large, well-connected metapopulation. BMC Biol. 6, 46 (2008).
    PubMed  PubMed Central  Article  Google Scholar 

    16.
    Frankham, R. Genetic rescue of small inbred populations: meta-analysis reveals large and consistent benefits of gene flow. Mol. Ecol. 24, 2610–2618 (2015).
    PubMed  Article  Google Scholar 

    17.
    Nussear, K. E. et al. Translocation as a conservation tool for Agassiz’s desert tortoises: survivorship, reproduction, and movements. J. Wildl. Manag. 76, 1341–1353 (2012).
    Article  Google Scholar 

    18.
    Wright, D. J. et al. The impact of translocations on neutral and functional genetic diversity within and among populations of the Seychelles warbler. Mol. Ecol. 23, 2165–2177 (2014).
    PubMed  PubMed Central  Article  Google Scholar 

    19.
    Whiteley, A. R., Fitzpatrick, S. W., Funk, W. C. & Tallmon, D. A. Genetic rescue to the rescue. Trends Ecol. Evol. 30, 42–49 (2015).
    PubMed  Article  Google Scholar 

    20.
    Edmands, S. & Timmerman, C. C. Modeling factors affecting the severity of outbreeding depression. Conserv. Biol. 17, 883–892 (2003).
    Article  Google Scholar 

    21.
    Tallmon, D. A., Luikart, G. & Waples, R. S. The alluring simplicity and complex reality of genetic rescue. Trends Ecol. Evol. 19, 489–496 (2004).
    PubMed  Article  Google Scholar 

    22.
    Frankham, R. et al. Predicting the probability of outbreeding depression. Conserv. Biol. 25, 465–475 (2011).
    PubMed  Article  Google Scholar 

    23.
    Miller, K. A. et al. Securing the demographic and genetic future of tuatara through assisted colonization. Conserv. Biol. 26, 790–798 (2012).
    PubMed  Article  Google Scholar 

    24.
    Frankham, R. Genetics and extinction. Biol. Conserv. 126, 131–140 (2005).
    Article  Google Scholar 

    25.
    Peniche, G. et al. Protecting free-living dormice: molecular identification of cestode parasites in captive dormice (Muscardinus avellanarius) destined for reintroduction. EcoHealth 14, 106–116 (2017).
    PubMed  Article  Google Scholar 

    26.
    Pollom, R. Hippocampus capensis. The IUCN Red List of Threatened Species 2017: .T10056A54903534. http://dx.doi.org/https://doi.org/10.2305/IUCN.UK.2017-3.RLTS.T10056A54903534.en (2017).

    27.
    Bell, E. M., Lockyear, J. F., McPherson, J. M., Marsden, A. D. & Vincent, A. C. J. First field studies of an endangered South African seahorse, Hippocampus capensis. Environ. Biol. Fishes 67, 35–46 (2003).
    Article  Google Scholar 

    28.
    Lockyear, J. F., Hecht, T., Kaiser, H. & Teske, P. R. The distribution and abundance of the endangered Knysna seahorse Hippocampus capensis (Pisces: Syngnathidae) in South African estuaries. Afr. J. Aquat. Sci. 31, 275–283 (2006).
    Article  Google Scholar 

    29.
    Teske, P. R., Cherry, M. I. & Matthee, C. A. Population genetics of the endangered Knysna seahorse, Hippocampus capensis. Mol. Ecol. 12, 1703–1715 (2003).
    CAS  PubMed  Article  Google Scholar 

    30.
    López, A., Vera, M., Planas, M. & Bouza, C. Conservation genetics of threatened Hippocampus guttulatus in vulnerable habitats in NW Spain: temporal and spatial stability of wild populations with flexible polygamous mating system in captivity. PLoS ONE 10, e0117538 (2015).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    31.
    Pickrell, J. K. & Pritchard, J. K. Inference of population splits and mixtures from genome-wide allele frequency data. PLoS Genet. 8, e1002967 (2012).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    32.
    Lande, R. Genetics and demography in biological conservation. Science 241, 1455–1460 (1988).
    ADS  CAS  PubMed  Article  Google Scholar 

    33.
    Wang, J. Estimation of effective population sizes from data on genetic markers. Phil. Trans. R. Soc. B360, 1395–1409 (2005).
    Article  CAS  Google Scholar 

    34.
    Schwartz, M. K., Luikart, G. & Waples, R. S. Genetic monitoring as a promising tool for conservation and management. Trends Ecol. Evol. 22, 25–33 (2007).
    PubMed  Article  Google Scholar 

    35.
    Armstrong, D. P. & Seddon, P. J. Directions in reintroduction biology. Trends Ecol. Evol. 23, 20–25 (2008).
    PubMed  Article  Google Scholar 

    36.
    Cerón-Souza, I. et al. Contrasting demographic history and gene flow patterns of two mangrove species on either side of the Central American Isthmus. Ecol. Evol. 5, 3486–3499 (2015).
    PubMed  PubMed Central  Article  Google Scholar 

    37.
    Woodall, L. C., Koldewey, H. J., Boehm, J. T. & Shaw, P. W. Past and present drivers of population structure in a small coastal fish, the European long snouted seahorse Hippocampus guttulatus. Conserv. Genet. 16, 1139–1153 (2015).
    Article  Google Scholar 

    38.
    Teske, P. R. et al. Molecular evidence for long-distance colonization in an Indo-Pacific seahorse lineage. Mar. Ecol. Prog. Ser. 286, 249–260 (2005).
    ADS  CAS  Article  Google Scholar 

    39.
    Heydorn, A. E. F. & Grindley, J. R. Estuaries of the Cape: Part II Synopses of available information on individual systems. Report 30. (Associated Printing and Publishing Co. (Pty) Ltd., 1985).

    40.
    Turpie, J. K. & Clark, B. Development of a conservation plan for temperate South African estuaries on the basis of biodiversity importance, ecosystem health and economic costs and benefits. Report by Anchor Environmental Consultants. C.A.P.E. Regional Estuarine Management Programme. 125 (2007).

    41.
    Penrith, M. J. & Penrith, M. Redescription of Pandaka silvana (Barnard) (Pisces, Gobiidae). Ann. South Afr. Mus. 60, 105–108 (1972).
    Google Scholar 

    42.
    Branch, G. M. The ecology of Patella linnaeus from the cape Peninsula, South Africa I. Zonation, movements and feeding. Zool. Afr. 6, 1–38 (1971).
    Article  Google Scholar 

    43.
    Largier, J. L., Attwood, C. & Harcourt-Baldwin, J. L. The hydrographic character of the Knysna Estuary. Trans. R. Soc. South Afr. 55, 107–122 (2000).
    Article  Google Scholar 

    44.
    Russell, I. A. Mass mortality of marine and estuarine fish in the Swartvlei and Wilderness lake systems, Southern Cape. South. Afr. J. Aquat. Sci. 20, 93–96 (1994).
    Google Scholar 

    45.
    Roberts, M. J., van der Lingen, C. D., Whittle, C. & van den Berg, M. Shelf currents, lee-trapped and transient eddies on the inshore boundary of the Agulhas Current, South Africa: their relevance to the KwaZulu-Natal sardine run. Afr. J. Mar. Sci. 32, 423–447 (2010).
    Article  Google Scholar 

    46.
    Teske, P. R., Bader, S. & Golla, T. R. Passive dispersal against an ocean current. Mar. Ecol. Prog. Ser. 539, 153–163 (2015).
    ADS  CAS  Article  Google Scholar 

    47.
    Claassens, L. An artificial water body provides habitat for an endangered estuarine seahorse species. Estuar. Coast. Shelf Sci. 180, 1–10 (2016).
    ADS  Article  Google Scholar 

    48.
    Wilcove, D. S., Rothstein, D., Dubow, J., Phillips, A. & Losos, E. Quantifying threats to imperiled species in the United States: Assessing the relative importance of habitat destruction, alien species, pollution, overexploitation, and disease. Bioscience 48, 607–615 (1998).
    Article  Google Scholar 

    49.
    Hey, J. Isolation with migration models for more than two populations. Mol. Biol. Evol. 27, 905–920 (2010).
    CAS  PubMed  Article  Google Scholar 

    50.
    Claassens, L., Barnes, R. S. K., Wasserman, J., Lamberth, S. J., Miranda, A. F., van Niekerk, L. & Adams, J. B. Knysna Estuary health: ecological status, threats and options for the future. Afr. J. Aquat. 45 (2020).

    51.
    Nielsen, R. & Wakeley, J. Distinguishing migration from isolation: a Markov chain Monte Carlo approach. Genetics 158, 885–896 (2001).
    CAS  PubMed  PubMed Central  Google Scholar 

    52.
    Whitfield, A. K. Threatened fishes of the world: Hippocampus capensis Boulenger, 1900 (Syngnathidae). Environ. Biol. Fishes 44, 362–362 (1995).
    Article  Google Scholar 

    53.
    Yue, G. H., David, L. & Orban, L. Mutation rate and pattern of microsatellites in common carp (Cyprinus carpio L.). Genetica 129, 329–331 (2007).
    CAS  PubMed  Article  Google Scholar 

    54.
    Waples, R. S. & Do, C. Linkage disequilibrium estimates of contemporary Ne using highly variable genetic markers: a largely untapped resource for applied conservation and evolution. Evol. Appl. 3, 244–262 (2010).
    PubMed  Article  Google Scholar 

    55.
    Do, C. et al. NeEstimator v2: re-implementation of software for the estimation of contemporary effective population size (Ne) from genetic data. Mol. Ecol. Resour. 14, 209–214 (2014).
    CAS  PubMed  Article  Google Scholar 

    56.
    Heled, J. & Drummond, A. J. Bayesian inference of population size history from multiple loci. BMC Evol. Biol. 8, 289 (2008).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    57.
    Drummond, A. J., Suchard, M. A., Xie, D. & Rambaut, A. Bayesian phylogenetics with BEAUti and the BEAST 1.7. Mol. Biol. Evol. 29, 1969–1973 (2012).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    58.
    Peakall, R. & Smouse, P. E. GenAlEx 6.5: genetic analysis in excel. Population genetic software for teaching and research—an update. Bioinformatics 28, 2537–2539 (2012).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    59.
    Lischer, H. E. L. & Excoffier, L. PGDSpider: an automated data conversion tool for connecting population genetics and genomics programs. Bioinformatics 28, 298–299 (2012).
    CAS  PubMed  Article  Google Scholar 

    60.
    Rambaut, A., Suchard, M. A., Xie, D. & Drummond, A. J. Tracer v1.6. (2014). More

  • in

    Marauding plants steer clear of a communist-ruled island

    Cuba has hosted relatively small numbers of tourist groups given its size, which might have helped to keep invasive plants at bay. Credit: Roberto Machado Noa/LightRocket/Getty

    Ecology
    18 February 2021

    Cuba’s relatively closed economy could explain why it has fewer invasive plant species per unit area than other Caribbean islands.

    For more than 60 years, the rocky relationship between the United States and Cuba has helped to steer tourists and businesses away from the Caribbean island. Now, researchers have found that Cuba’s economic and political isolation might also have limited the spread of invasive plants.
    Meghan Brown at Hobart and William Smith Colleges in Geneva, New York, and her colleagues estimated the number of invasive plant species on 45 Caribbean islands. The researchers found that larger islands tend to have more exotic plant species than do smaller ones. But Cuba, the biggest island in the Caribbean, is home to hundreds fewer such species than expected for its size.
    Mass tourism seems to favour the introduction of invasive plants, the team found, probably because hotels plant exotic ornamental species and tourists carry seeds in their bags or on their shoes. Cuba — which has one of the region’s lowest shares of holidaymakers in comparison to its area — has about the same number of invasive species as Puerto Rico, which is one-tenth the size of Cuba but has many more visitors for its land area. More

  • in

    Dogs (Canis familiaris) recognize their own body as a physical obstacle

    1.
    Bahrick, L. E. & Watson, J. S. Detection of intermodal proprioceptive–visual contingency as a potential basis of self-perception in infancy. Dev. Psychol. 21, 963 (1985).
    Article  Google Scholar 
    2.
    Van Den Bos, E. & Jeannerod, M. Sense of body and sense of action both contribute to self-recognition. Cognition 85, 177–187 (2002).
    Article  Google Scholar 

    3.
    Wilson, M. Six views of embodied cognition. Psychon. B. Rev. 9, 625–636 (2002).
    Article  Google Scholar 

    4.
    Smith, L. & Gasser, M. The development of embodied cognition: Six lessons from babies. Artif. life 11, 13–29 (2005).
    Article  Google Scholar 

    5.
    Shettleworth, S. J. Cognition, Evolution, and Behavior. Oxford University Press.

    6.
    Kohda, M. et al. If a fish can pass the mark test, what are the implications for consciousness and self-awareness testing in animals?. PLoS Biol 17, e3000021 (2019).
    CAS  Article  Google Scholar 

    7.
    Gallup, G. G. Chimpanzees: Self-recognition. Science 167, 86–87 (1970).
    ADS  Article  Google Scholar 

    8.
    Epstein, R., Lanza, R. P. & Skinner, B. F. “Self-awareness” in the pigeon. Science 212, 695–696 (1981).
    ADS  CAS  Article  Google Scholar 

    9.
    Heyes, C. M. Self-recognition in primates: Further reflections create a hall of mirrors. Anim. Behav. 50, 1533–1542 (1995).
    Article  Google Scholar 

    10.
    Suddendorf, T. & Butler, D. L. Response to Gallup et al.: Are rich interpretations of visual self-recognition a bit too rich?. Trends. Cogn. Sci. 18, 58–59 (2014).
    Article  Google Scholar 

    11.
    Reiss, D. & Marino, L. Mirror self-recognition in the bottlenose dolphin: A case of cognitive convergence. Proc. Natl. Acad. Sci. USA 98, 5937–5942 (2001).
    ADS  CAS  Article  Google Scholar 

    12.
    Plotnik, J. M., De Waal, F. B. & Reiss, D. Self-recognition in an Asian elephant. Proc. Natl. Acad. Sci. USA 103, 17053–17057 (2006).
    ADS  CAS  Article  Google Scholar 

    13.
    Prior, H., Schwarz, A. & Güntürkün, O. Mirror-induced behavior in the magpie (Pica pica): Evidence of self-recognition. PLoS Biol 6, e202 (2008).
    Article  Google Scholar 

    14.
    Bekoff, M. & Sherman, P. W. Reflections on animal selves. Trends Ecol. Evol. 19, 176–180 (2004).
    Article  Google Scholar 

    15.
    Lenkei, R., Faragó, T., Kovács, D., Zsilák, B. & Pongrácz, P. That dog won’t fit: Body size awareness in dogs. Anim. Cogn 23, 337–350 (2019).
    Article  Google Scholar 

    16.
    Zazzo, R. Des enfants, des singes et des chiens devant le miroir. Rev. Psychol. Appl. 29, 235–246 (1979).
    Google Scholar 

    17.
    Cuthill, I. & Guilford, T. Perceived risk and obstacle avoidance in flying birds. Anim. Behav. 40, 188–190 (1990).
    Article  Google Scholar 

    18.
    Khvatov, I. A., Sokolov, A. Y. & Kharitonov, A. N. Snakes Elaphe radiata may acquire awareness of their body limits when trying to hide in a shelter. Behav. Sci. 9, 67 (2019).
    Article  Google Scholar 

    19.
    Maeda, T. & Fujita, K. Do dogs (Canis familiaris) recognize their own body size? In Proceedings of the 2nd Canine Science Forum, Vienna, Austria, 52 (2010).

    20.
    Dale, R. & Plotnik, J. M. Elephants know when their bodies are obstacles to success in a novel transfer task. Sci. Rep. 7, 46309 (2017).
    ADS  CAS  Article  Google Scholar 

    21.
    Brownell, C. A., Zerwas, S. & Ramani, G. B. “So big”: The development of body self-awareness in toddlers. Child Dev. 78, 1426–1440 (2007).
    Article  Google Scholar 

    22.
    Povinelli, D. J. & Cant, J. G. Arboreal clambering and the evolution of self-conception. Q. Rev. Biol. 70, 393–421 (1995).
    CAS  Article  Google Scholar 

    23.
    Povinelli, D. J. Failure to find self-recognition in Asian elephants (Elephas maximus) in contrast to their use of mirror cues to discover hidden food. J. Comp. Psychol. 103, 122 (1989).
    Article  Google Scholar 

    24.
    Topál, J. et al. The dog as a model for understanding human social behaviour. Adv. Stud. Behav. 39, 71–116 (2009).
    Article  Google Scholar 

    25.
    Sanford, E. M., Burt, E. R. & Meyers-Manor, J. E. Timmy’s in the well: Empathy and prosocial helping in dogs. Learn. Behav. 46, 374–386 (2018).
    Article  Google Scholar 

    26.
    Pongrácz, P., Bánhegyi, P. & Miklósi, Á. When rank counts—dominant dogs learn better from a human demonstrator in a two-action test. Behaviour 149, 111–132 (2012).
    Article  Google Scholar 

    27.
    Huber, L., Popovová, N., Riener, S., Salobir, K. & Cimarelli, G. Would dogs copy irrelevant actions from their human caregiver?. Learn. Behav. 46, 387–397 (2018).
    Article  Google Scholar 

    28.
    Virányi, Z. S., Topál, J., Miklósi, Á. & Csányi, V. A nonverbal test of knowledge attribution: A comparative study on dogs and children. Anim. Cogn. 9, 13–26 (2006).
    Article  Google Scholar 

    29.
    Polgárdi, R., Topál, J. & Csányi, V. Intentional behaviour in dog-human communication: An experimental analysis of “showing” behaviour in the dog. Anim. Cogn. 3, 159–166 (2000).
    Article  Google Scholar 

    30.
    Pongrácz, P., Hegedüs, D., Sanjurjo, B., Kővári, A. & Miklósi, Á. “We will work for you”—Social influence may suppress individual food preferences in a communicative situation in dogs. Learn. Motiv. 44, 270–281 (2013).
    Article  Google Scholar 

    31.
    Fugazza, C., Pogány, Á. & Miklósi, Á. Recall of others’ actions after incidental encoding reveals episodic-like memory in dogs. Curr. Biol. 26, 3209–3213 (2016).
    CAS  Article  Google Scholar 

    32.
    Horowitz, A. Smelling themselves: Dogs investigate their own odours longer when modified in an “olfactory mirror” test. Behav. Proc. 143, 17–24 (2017).
    Article  Google Scholar 

    33.
    Moore, C., Mealiea, J., Garon, N. & Povinelli, D. J. The development of body self-awareness. Infancy 11, 157–174 (2007).
    Article  Google Scholar 

    34.
    Howell, T. J. & Bennett, P. C. Can dogs (Canis familiaris) use a mirror to solve a problem?. J. Vet. Behav. 6, 306–312 (2011).
    Article  Google Scholar 

    35.
    Bekoff, M. Awareness: Animal reflections. Nature 419, 255 (2002).
    ADS  CAS  Article  Google Scholar 

    36.
    Kaplan, J. T., Aziz-Zadeh, L., Uddin, L. Q. & Iacoboni, M. The self across the senses: An fMRI study of self-face and self-voice recognition. Soc. Cogn. Affect. Neur. 3, 218–223 (2008).
    Article  Google Scholar  More

  • in

    Large-scale farmer-led experiment demonstrates positive impact of cover crops on multiple soil health indicators

    1.
    Seifert, C. A., Azzari, G. & Lobell, D. B. Satellite detection of cover crops and their effects on crop yield in the Midwestern United States. Environ. Res. Lett. 13, 064033 (2018).
    ADS  Article  Google Scholar 
    2.
    2017 Census of Agriculture, Summary and State Data (USDA, 2019); https://www.nass.usda.gov/Publications/AgCensus/2017/Full_Report/Volume_1,_Chapter_1_US/usv1.pdf

    3.
    Basche, A. D. et al. Soil water improvements with the long-term use of a winter rye cover crop. Agric. Water Manag. 172, 40–50 (2016).
    Article  Google Scholar 

    4.
    Schipanski, M. E. et al. A framework for evaluating ecosystem services provided by cover crops in agroecosystems. Agric. Syst. 125, 12–22 (2014).
    Article  Google Scholar 

    5.
    Blanco-Canqui, H. et al. Cover crops and ecosystem services: insights from studies in temperate soils. Agron. J. 107, 2449–2474 (2015).
    CAS  Article  Google Scholar 

    6.
    Andrews, S. S. et al. On‐farm assessment of soil quality in California’s central valley. Agron. J. 94, 12–23 (2002).
    Article  Google Scholar 

    7.
    Welch, R. Y., Behnke, G. D., Davis, A. S., Masiunas, J. & Villamil, M. B. Using cover crops in headlands of organic grain farms: effects on soil properties, weeds and crop yields. Agric. Ecosyst. Environ. 216, 322–332 (2016).
    Article  Google Scholar 

    8.
    Wyland, L. Winter cover crops in a vegetable cropping system: impacts on nitrate leaching, soil water, crop yield, pests and management costs. Agric. Ecosyst. Environ. 59, 1–17 (1996).
    Article  Google Scholar 

    9.
    Karlen, D. L. & Doran, J. W. Cover crop management effects on soybean and corn growth and nitrogen dynamics in an on-farm study. Am. J. Altern. Agric. 6, 71–82 (1991).
    Article  Google Scholar 

    10.
    Koch, R. L. et al. On-farm evaluation of a fall-seeded rye cover crop for suppression of soybean aphid (Hemiptera: Aphididae) on soybean: suppression of soybean aphid with rye cover crop. Agric. For. Entomol. 17, 239–246 (2015).
    Article  Google Scholar 

    11.
    Sayre, N. F., deBuys, W., Bestelmeyer, B. T. & Havstad, K. M. “The Range Problem” after a century of rangeland science: new research themes for altered landscapes. Rangeland Ecol. Manag. 65, 545–552 (2012).
    Article  Google Scholar 

    12.
    Kladivko, E. J. et al. State-wide soil health programs for education and on-farm assessment: lessons learned. J. Soil Water Conserv. 74, 12A–17A (2019).
    Article  Google Scholar 

    13.
    Poeplau, C. & Don, A. Carbon sequestration in agricultural soils via cultivation of cover crops – a meta-analysis. Agric. Ecosyst. Environ. 200, 33–41 (2015).
    CAS  Article  Google Scholar 

    14.
    Vermeulen, S. et al. A global agenda for collective action on soil carbon. Nat. Sustain. 2, 2–4 (2019).
    Article  Google Scholar 

    15.
    Lehmann, J., Bossio, D. A., Kögel-Knabner, I. & Rillig, M. C. The concept and future prospects of soil health. Nat. Rev. Earth Environ. 1, 544–553 (2020).
    ADS  PubMed  Article  Google Scholar 

    16.
    Stewart, R. D. et al. What we talk about when we talk about soil health. Agric. Environ. Lett. 3, 180033 (2018).
    Article  CAS  Google Scholar 

    17.
    Norris, C. E. et al. Introducing the North American project to evaluate soil health measurements. Agron. J. 112, 3195–3215 (2020).
    Article  Google Scholar 

    18.
    Sanderman, J., Savage, K. & Dangal, S. R. S. Mid‐infrared spectroscopy for prediction of soil health indicators in the United States. Soil Sci. Soc. Am. J. 84, 251–261 (2020).
    ADS  CAS  Article  Google Scholar 

    19.
    Rorick, J. D. & Kladivko, E. J. Cereal rye cover crop effects on soil carbon and physical properties in Southeastern Indiana. J. Soil Water Conserv. 72, 260–265 (2017).
    Article  Google Scholar 

    20.
    Faé, G. S. et al. Integrating winter annual forages into a no-till corn silage system. Agron. J. 101, 1286–1296 (2009).
    Article  Google Scholar 

    21.
    Wegner, B. R. et al. Soil response to corn residue removal and cover crops in eastern South Dakota. Soil Sci. Soc. Am. J. 79, 1179–1187 (2015).
    ADS  CAS  Article  Google Scholar 

    22.
    Karlen, D. L., Goeser, N. J., Veum, K. S. & Yost, M. A. On-farm soil health evaluations: challenges and opportunities. J. Soil Water Conserv. 72, 26A–31A (2017).
    Article  Google Scholar 

    23.
    Wade, J. et al. Improved soil biological health increases corn grain yield in N fertilized systems across the Corn Belt. Sci. Rep. 10, 3917 (2020).
    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

    24.
    Bossio, D. A. et al. The role of soil carbon in natural climate solutions. Nat. Sustain. 3, 391–398 (2020).
    Article  Google Scholar 

    25.
    Stanton, C. Y. et al. Managing cropland and rangeland for climate mitigation: an expert elicitation on soil carbon in California. Clim. Change 147, 633–646 (2018).
    ADS  CAS  Article  Google Scholar 

    26.
    Lugato, E., Leip, A. & Jones, A. Mitigation potential of soil carbon management overestimated by neglecting N2O emissions. Nat. Clim. Change 8, 219–223 (2018).
    ADS  CAS  Article  Google Scholar 

    27.
    Kaye, J. P. & Quemada, M. Using cover crops to mitigate and adapt to climate change. A review. Agron. Sustain. Dev. 37, 4 (2017).
    Article  Google Scholar 

    28.
    Basche, A. D. & DeLonge, M. S. Comparing infiltration rates in soils managed with conventional and alternative farming methods: a meta-analysis. PLoS ONE 14, e0215702 (2019).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    29.
    Basche, A. & DeLonge, M. The impact of continuous living cover on soil hydrologic properties: a meta-analysis. Soil Sci. Soc. Am. J. 81, 1179–1190 (2017).
    ADS  CAS  Article  Google Scholar 

    30.
    Roper, W. R., Osmond, D. L. & Heitman, J. L. A response to “Reanalysis validates soil health indicator sensitivity and correlation with long‐term crop yields”. Soil Sci. Soc. Am. J. 83, 1842–1845 (2019).
    ADS  CAS  Article  Google Scholar 

    31.
    King, A. E., Ali, G. A., Gillespie, A. W. & Wagner-Riddle, C. Soil organic matter as catalyst of crop resource capture. Front. Environ. Sci. 8, 50 (2020).
    Article  Google Scholar 

    32.
    Oldfield, E. E., Bradford, M. A. & Wood, S. A. Global meta-analysis of the relationship between soil organic matter and crop yields. SOIL 5, 15–32 (2019).
    CAS  Article  Google Scholar 

    33.
    Oldfield, E. E., Wood, S. A. & Bradford, M. A. Direct evidence using a controlled greenhouse study for threshold effects of soil organic matter on crop growth. Ecol. Appl. 30, e02073 (2020).
    PubMed  Article  Google Scholar 

    34.
    Wood, S. A. et al. Opposing effects of different soil organic matter fractions on crop yields. Ecol. Appl. 26, 2072–2085 (2016).
    PubMed  Article  Google Scholar 

    35.
    Fine, A. K., van Es, H. M. & Schindelbeck, R. R. Statistics, scoring functions, and regional analysis of a comprehensive soil health database. Soil Sci. Soc. Am. J. 81, 589 (2017).
    ADS  CAS  Article  Google Scholar 

    36.
    Fine, A. K., Ristow, A., Schindelbeck, R. R. & van Es, H. M. Update of scoring functions for Cornell Soil Health Test. What’s Cropping Up? Blog https://blogs.cornell.edu/whatscroppingup/2016/11/30/update-of-scoring-functions-for-cornell-soil-health-test/ (2016).

    37.
    Bradford, M. A. et al. Discontinuity in the responses of ecosystem processes and multifunctionality to altered soil community composition. Proc. Natl Acad. Sci. USA 111, 14478–14483 (2014).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    38.
    Bradford, M. A. et al. Reply to Byrnes et al.: Aggregation can obscure understanding of ecosystem multifunctionality. Proc. Natl Acad. Sci. USA 111, E5491 (2014).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    39.
    Kettler, T. A., Doran, J. W. & Gilbert, T. L. Simplified method for soil particle-size determination to accompany soil-quality analyses. Soil Sci. Soc. Am. J. 65, 849–852 (2001).
    ADS  CAS  Article  Google Scholar 

    40.
    Moebius, B. N. et al. Evaluation of laboratory-measured soil properties as indicators of soil physical quality. Soil Sci. 172, 895–912 (2007).
    ADS  CAS  Article  Google Scholar 

    41.
    Reynolds, W. & Topp, G. in Soil Sampling and Methods of Analysis (eds Carter, M. R. & Gregorich, E. G.) 981–997 (CRC Press, 2008).

    42.
    Nelson, D. & Sommers, D. in Methods of Soil Analysis. Part 3 (Sparks, D. L., Page, A. L., Helmke, P. A. & Loeppert, R. H.) 961–1010 (Soil Science Society of America, 1996).

    43.
    Weil, R. R., Islam, K. R., Stine, M. A., Gruver, J. B. & Samson-Liebig, S. E. Estimating active carbon for soil quality assessment: a simplified method for laboratory and field use. Am. J. Altern. Agric. 18, 3–17 (2003).
    Article  Google Scholar 

    44.
    Haney, R. L. & Haney, E. B. Simple and rapid laboratory method for rewetting dry soil for incubations. Commun. Soil Sci. Plant Anal. 41, 1493–1501 (2010).
    CAS  Article  Google Scholar 

    45.
    Wright, S. F. & Upadhyaya, A. Extraction of an abundant and unusual protein from soil and comparison with hyphal protein of arbuscular mycorrhizal fungi. Soil Sci. 161, 575–586 (1996).
    ADS  CAS  Article  Google Scholar 

    46.
    Bunnefeld, N. & Phillimore, A. B. Island, archipelago and taxon effects: mixed models as a means of dealing with the imperfect design of nature’s experiments. Ecography 35, 15–22 (2012).
    Article  Google Scholar 

    47.
    Gelman, A. Scaling regression inputs by dividing by two standard deviations. Stat. Med. 27, 2865–2873 (2008).
    MathSciNet  PubMed  Article  Google Scholar 

    48.
    Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).
    Article  Google Scholar 

    49.
    R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2019).

    50.
    Stan Development Team. RStan: the R interface to Stan. R package v2.17.3 (2018).

    51.
    Rasmussen, C. et al. Beyond clay: towards an improved set of variables for predicting soil organic matter content. Biogeochemistry 137, 297–306 (2018).
    CAS  Article  Google Scholar 

    52.
    Gelman, A. et al. Bayesian Data Analysis 3rd edn (Chapman and Hall, CRC, 2013).

    53.
    Howard, P. J. A. & Howard, D. M. Use of organic carbon and loss-on-ignition to estimate soil organic matter in different soil types and horizons. Biol. Fertil. Soils 9, 306–310 (1990).
    CAS  Article  Google Scholar  More