More stories

  • in

    Genome-wide analysis of diamondback moth, Plutella xylostella L., from Brassica crops and wild host plants reveals no genetic structure in Australia

    1.
    Zalucki, M. P. & Furlong, M. J. Forecasting Helicoverpa populations in Australia: a comparison of regression based models and a bioclimatic based modelling approach. Insect Sci. 12, 45–56 (2005).
    Article  Google Scholar 
    2.
    Mazzi, D. & Dorn, S. Movement of insect pests in agricultural landscapes. Ann. Appl. Biol. 160, 97–113 (2012).
    Article  Google Scholar 

    3.
    Eigenbrode, S. D. et al. Host-adapted aphid populations differ in their migratory patterns and capacity to colonize crops. J. Appl. Ecol. 53, 1382–1390. https://doi.org/10.1111/1365-2664.12693 (2016).
    Article  Google Scholar 

    4.
    Furlong, M. J., Wright, D. J. & Dosdall, L. M. Diamondback moth ecology and management: problems, progress, and prospects. Annu. Rev. Entomol. 58, 517–541. https://doi.org/10.1146/annurev-ento-120811-153605 (2013).
    CAS  Article  PubMed  Google Scholar 

    5.
    Downes, S. et al. A perspective on management of Helicoverpa armigera: transgenic Bt cotton, IPM, and landscapes. Pest Manag. Sci. 73, 485–492. https://doi.org/10.1002/ps.4461 (2017).
    CAS  Article  PubMed  Google Scholar 

    6.
    Endersby, N. M., Ridland, P. M. & Hoffmann, A. A. The effects of local selection versus dispersal on insecticide resistance patterns: longitudinal evidence from diamondback moth (Plutella xylostella (Lepidoptera: Plutellidae)) in Australia evolving resistance to pyrethroids. Bull. Entomol. Res. 98, 145–157. https://doi.org/10.1017/S0007485307005494 (2008).
    CAS  Article  PubMed  Google Scholar 

    7.
    Broquet, T. & Petit, E. J. Molecular estimation of dispersal for ecology and population genetics. Annu. Rev. Ecol. Evol. Syst. 40, 193–216. https://doi.org/10.1146/annurev.ecolsys.110308.120324 (2009).
    Article  Google Scholar 

    8.
    Pelissie, B., Crossley, M. S., Cohen, Z. P. & Schoville, S. D. Rapid evolution in insect pests: the importance of space and time in population genomics studies. Curr. Opin. Insect Sci. 26, 8–16. https://doi.org/10.1016/j.cois.2017.12.008 (2018).
    Article  PubMed  Google Scholar 

    9.
    Parry, H. R. et al. A native with a taste for the exotic: weeds and pasture provide year-round habitat for Nysius vinitor (Hemiptera: Orsillidae) across Australia, with implications for area-wide management. Aust. Entomol. 58, 237–247. https://doi.org/10.1111/aen.12391 (2019).
    Article  Google Scholar 

    10.
    Wei, S. J. et al. Genetic structure and demographic history reveal migration of the diamondback moth Plutella xylostella (Lepidoptera: Plutellidae) from the southern to northern regions of China. PLoS ONE 8, e59654. https://doi.org/10.1371/journal.pone.0059654 (2013).
    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

    11.
    Hereward, J. P., Walter, G. H., DeBarro, P. J., Lowe, A. J. & Riginos, C. Gene flow in the green mirid, Creontiades dilutus (Hemiptera: Miridae), across arid and agricultural environments with different host plant species. Ecol. Evol. 3, 807–821. https://doi.org/10.1002/ece3.510 (2013).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    12.
    Zalucki, M. P. et al. Estimating the economic cost of one of the worlds major insect pests, Plutella xylostella (Lepidoptera: Plutellidae): just how long is a piece of string? J. Econ. Entomol. 105, 1115–1129. https://doi.org/10.1603/EC12107 (2012).
    Article  PubMed  Google Scholar 

    13.
    Li, Z., Feng, X., Liu, S.-S., You, M. & Furlong, M. J. Biology, ecology, and management of the diamondback moth in China. Annu. Rev. Entomol. 61, 277–296. https://doi.org/10.1146/annurev-ento-010715-023622 (2016).
    CAS  Article  PubMed  Google Scholar 

    14.
    Talekar, N. S. & Shelton, A. Biology, ecology, and management of the diamondback moth. Annu. Rev. Entomol. 38, 275–301. https://doi.org/10.1146/annurev.en.38.010193.001423 (1993).
    Article  Google Scholar 

    15.
    Mosiane, S. M., Kfir, R. & Villet, M. H. Seasonal phenology of the diamondback moth, Plutella xylostella (L.), (Lepidoptera: Plutellidae), and its parasitoids on canola, Brassica napus (L.), in Gauteng province, South Africa. Afr. Entomol. 11, 277–285 (2003).
    Google Scholar 

    16.
    Dosdall, L. M., Mason, P. G., Olfert, O., Kaminski, L. & Keddie, B. A. The origins of infestations of diamondback moth, Plutella xylostella (L.), in canola in western Canada. In The Management of Diamondback Moth and Other Crucifer Pests: Proceedings of the Fourth International Workshop (eds Endersby, N. M. & Ridland, P. M.) 95–100 (The Regional Institute Ltd, Gosford, New South Wales, Australia, 2004).

    17.
    Dosdall, L. M., Soroka, J. J. & Olfert, O. The diamondback moth in canola and mustard: current pest status and future prospects. Prairie Soils and Crops J. 4, 66–76 (2011).
    Google Scholar 

    18.
    Furlong, M. J. et al. Ecology of diamondback moth in Australian canola: landscape perspectives and the implications for management. Aust. J. Exp. Agric. 48, 1494–1505. https://doi.org/10.1071/EA07413 (2008).
    Article  Google Scholar 

    19.
    Endersby, N. M., McKechnie, S. W., Ridland, P. M. & Weeks, A. R. Microsatellites reveal a lack of structure in Australian populations of the diamondback moth, Plutella xylostella (L.). Mol. Ecol. 15, 107–118. https://doi.org/10.1111/j.1365-294X.2005.02789.x (2006).
    CAS  Article  PubMed  Google Scholar 

    20.
    ABARES. Australian commodity production statistics. Australian Bureau of Agricultural and Resource Economics and Sciences cat. no. 7113.0 (2017).

    21.
    Gu, H., Fitt, G. P. & Baker, G. H. Invertebrate pests of canola and their management in Australia: a review. Aust. J. Entomol. 46, 231–243. https://doi.org/10.1111/j.1440-6055.2007.00594.x (2007).
    Article  Google Scholar 

    22.
    Baker, G. J. Crucifer vegetable insecticide resistance management strategies and issues in Australia. In The Sixth International Workshop on Management of the Diamondback Moth and Other Crucifer Insect Pests (eds Srinivasan, R., Shelton, A. M. & Collins, H. L.) 21–25 (AVRDC – The World Vegetable Centre, Tainan, Taiwan, 2011).

    23.
    Mo, J. H., Baker, G., Keller, M. & Roush, R. Local dispersal of the diamondback moth (Plutella xylostella (L.)) (Lepidoptera: Plutellidae). Environ. Entomol. 32, 71–79. https://doi.org/10.1603/0046-225X-32.1.71 (2003).
    Article  Google Scholar 

    24.
    Baker, G. J. Improving management of diamondback moth in Australian canola: final report for GRDC (DAS00134). Technical Report, South Australian Research and Development Institute (2015).

    25.
    Pichon, A. et al. Genetic differentiation among various populations of the diamondback moth, Plutella xylostella (Lepidoptera: Yponomeutidae). B. Entomol. Res. 96, 137–144. https://doi.org/10.1079/BER2005409 (2006).
    CAS  Article  Google Scholar 

    26.
    Juric, I., Salzburger, W. & Balmer, O. Spread and global population structure of the diamondback moth Plutella xylostella (Lepidoptera: Plutellidae) and its larval parasitoids Diadegma semiclausum and Diadegma fenestrale (Hymenoptera: Ichneumonidae) based on mtDNA. B. Entomol. Res. 107, 155–164. https://doi.org/10.1017/S0007485316000766 (2017).
    CAS  Article  Google Scholar 

    27.
    Kim, I. et al. Mitochondrial COI gene sequence-based population genetic structure of the diamondback moth, Plutella xylostella, Korea. Korean J. Genet. 25, 155–170 (2003).
    CAS  Google Scholar 

    28.
    Yang, J. et al. Insight into the migration routes of Plutella xylostella in China using mtCOI and ISSR markers. PLoS ONE 10, e0130905. https://doi.org/10.1371/journal.pone.0130905 (2015).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    29.
    Caprio, M. A. & Tabashnik, B. E. Allozymes used to estimate gene flow among populations of diamondback moth (Lepidoptera, Plutellidae) in Hawaii. Environ. Entomol. 21, 808–816. https://doi.org/10.1093/ee/21.4.808 (1992).
    Article  Google Scholar 

    30.
    Chang, W. X. Z. et al. Mitochondrial DNA sequence variation among geographic strains of diamondback moth (Lepidoptera: Plutellidae). Ann. Entomol. Soc. Am. 90, 590–595. https://doi.org/10.1093/aesa/90.5.590 (1997).
    CAS  Article  Google Scholar 

    31.
    Saw, J., Endersby, N. M. & McKechnie, S. W. Low mtDNA diversity among widespread Australian diamondback moth Plutella xylostella (L.) suggests isolation and a founder effect. Insect Sci. 13, 365–373 (2006).
    CAS  Article  Google Scholar 

    32.
    Endersby, N. M. Population structure and gene flow in diamondback moth in Australia and around the world: current state of knowledge and directions for the future. In The Management of Diamondback Moth and Other Crucifer Pests: Proceedings of the Fifth International Workshop (eds Shelton A. M. et al.) 132–147 (China Agricultural Science and Technology Press, Beijing, 2008).

    33.
    Fu, X., Xing, Z., Liu, Z., Ali, A. & Wu, K. Migration of diamondback moth, Plutella xylostella, across the Bohai sea in northern China. Crop Prot. 64, 143–149. https://doi.org/10.1016/j.cropro.2014.06.021 (2014).
    Article  Google Scholar 

    34.
    Delgado, A. M. & Cook, J. M. Effects of a sex-ratio distorting endosymbiont on mtDNA variation in a global insect pest. BMC Evol. Biol. 9, 49. https://doi.org/10.1186/1471-2148-9-49 (2009).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    35.
    Perry, K. D. et al. Cryptic Plutella species show deep divergence despite the capacity to hybridize. BMC Evol. Biol. 18, 77. https://doi.org/10.1186/s12862-018-1183-4 (2018).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    36.
    Roux, O. et al. ISSR-PCR: tool for discrimination and genetic structure analysis of Plutella xylostella populations native to different geographical areas. Mol. Phylogenet. Evol. 43, 240–250. https://doi.org/10.1016/j.ympev.2006.09.017 (2007).
    CAS  Article  PubMed  Google Scholar 

    37.
    Landry, J. F. & Hebert, P. D. N. Plutella australiana (Lepidoptera, Plutellidae), an overlooked diamondback moth revealed by DNA barcodes. Zookeys 327, 43–63. https://doi.org/10.3897/zookeys.327.5831 (2013).
    Article  Google Scholar 

    38.
    Goodwin, S., McPherson, J. D. & McCombie, W. R. Coming of age: ten years of next-generation sequencing technologies. Nat. Rev. Genet. 17, 333–351. https://doi.org/10.1038/nrg.2016.49 (2016).
    CAS  Article  PubMed  Google Scholar 

    39.
    Davey, J. W. et al. Genome-wide genetic marker discovery and genotyping using next-generation sequencing. Nat. Rev. Genet. 12, 499–510. https://doi.org/10.1038/nrg3012 (2011).
    ADS  CAS  Article  PubMed  Google Scholar 

    40.
    Narum, S. R., Buerkle, C. A., Davey, J. W., Miller, M. R. & Hohenlohe, P. A. Genotyping-by-sequencing in ecological and conservation genomics. Mol. Ecol. 22, 2841–2847. https://doi.org/10.1111/mec.12350 (2013).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    41.
    Baird, N. A. et al. Rapid SNP discovery and genetic mapping using sequenced RAD markers. PLoS ONE 3, e3376. https://doi.org/10.1371/journal.pone.0003376 (2008).
    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

    42.
    Baxter, S. W. et al. Linkage mapping and comparative genomics using next-generation RAD sequencing of a non-model organism. PLoS ONE 6, e19315. https://doi.org/10.1371/journal.pone.0019315 (2011).
    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

    43.
    Andrews, K. R., Good, J. M., Miller, M. R., Luikart, G. & Hohenlohe, P. A. Harnessing the power of RADseq for ecological and evolutionary genomics. Nat. Rev. Genet. 17, 81–92. https://doi.org/10.1038/nrg.2015.28 (2016).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    44.
    Davey, J. L. & Blaxter, M. W. RADSeq: next-generation population genetics. Brief. Funct. Genomics 9, 416–423. https://doi.org/10.1093/bfgp/elq031 (2010).
    CAS  Article  PubMed  Google Scholar 

    45.
    Putman, A. I. & Carbone, I. Challenges in analysis and interpretation of microsatellite data for population genetic studies. Ecol. Evol. 4, 4399–4428. https://doi.org/10.1002/ece3.1305 (2014).
    Article  PubMed  PubMed Central  Google Scholar 

    46.
    Haasl, R. J. & Payseur, B. A. Multi-locus inference of population structure: a comparison between single nucleotide polymorphisms and microsatellites. Heredity 106, 158–171. https://doi.org/10.1038/hdy.2010.21 (2011).
    CAS  Article  PubMed  Google Scholar 

    47.
    Vendrami, D. L. J. et al. RAD sequencing resolves fine-scale population structure in a benthic invertebrate: implications for understanding phenotypic plasticity. R. Soc. Open Sci. 4, 160548. https://doi.org/10.1098/rsos.160548 (2017).
    ADS  Article  PubMed  PubMed Central  Google Scholar 

    48.
    Rasic, G. et al. Aedes aegypti has spatially structured and seasonally stable populations in Yogyakarta, Indonesia. Parasit. Vectors 8, 610. https://doi.org/10.1186/s13071-015-1230-6 (2015).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    49.
    Rasic, G. et al. Contrasting genetic structure between mitochondrial and nuclear markers in the dengue fever mosquito from Rio de Janeiro: implications for vector control. Evol. Appl. 8, 901–915. https://doi.org/10.1111/eva.12301 (2015).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    50.
    Perry, K. D., Pederson, S. M. & Baxter, S. W. Genome-wide SNP discovery in field and laboratory colonies of Australian Plutella species. In Proceedings of the Seventh International Workshop on Management of the Diamondback Moth and Other Crucifer Insect Pests, Mysore J. Agric. Sci., 51A, 18–31 (2017).

    51.
    Fountain, E. D., Pauli, J. N., Reid, B. N., Palsboll, P. J. & Peery, M. Z. Finding the right coverage: the impact of coverage and sequence quality on single nucleotide polymorphism genotyping error rates. Mol. Ecol. Resour. 16, 966–978. https://doi.org/10.1111/1755-0998.12519 (2016).
    CAS  Article  PubMed  Google Scholar 

    52.
    Wright, S. Isolation by distance. Genetics 28, 114–138 (1943).
    CAS  PubMed  PubMed Central  Google Scholar 

    53.
    Grapputo, A., Boman, S., Lindstrom, L., Lyytinen, A. & Mappes, J. The voyage of an invasive species across continents: genetic diversity of North American and European Colorado potato beetle populations. Mol. Ecol. 14, 4207–4219. https://doi.org/10.1111/j.1365-294X.2005.02740.x (2005).
    CAS  Article  PubMed  Google Scholar 

    54.
    Janes, J. K. et al. The (K=2) conundrum. Mol. Ecol. 26, 3594–3602. https://doi.org/10.1111/mec.14187 (2017).
    Article  PubMed  Google Scholar 

    55.
    Pritchard, J., Stephens, M. & Donnelly, P. Inference of population structure using multilocus genotype data. Genetics 155, 945–959 (2000).
    CAS  PubMed  PubMed Central  Google Scholar 

    56.
    Kalinowski, S. T. The computer program STRUCTURE does not reliably identify the main genetic clusters within species: simulations and implications for human population structure. Heredity 106, 625–632. https://doi.org/10.1038/hdy.2010.95 (2011).
    CAS  Article  PubMed  Google Scholar 

    57.
    Rodriguez-Ramilo, S. T. & Wang, J. The effect of close relatives on unsupervised Bayesian clustering algorithms in population genetic structure analysis. Mol. Ecol. Resour. 12, 873–884. https://doi.org/10.1111/j.1755-0998.2012.03156.x (2012).
    Article  PubMed  Google Scholar 

    58.
    Wang, J. Effects of sampling close relatives on some elementary population genetics analyses. Mol. Ecol. Resour. 18, 41–54. https://doi.org/10.1111/1755-0998.12708 (2018).
    Article  PubMed  Google Scholar 

    59.
    Ward, C. M. & Baxter, S. W. Assessing genomic admixture between cryptic Plutella moth species following secondary contact. Genome Biol. Evol. 10, 2973–2985. https://doi.org/10.1093/gbe/evy224 (2018).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    60.
    Epps, C. W. & Keyghobadi, N. Landscape genetics in a changing world: disentangling historical and contemporary influences and inferring change. Mol. Ecol. 24, 6021–6040. https://doi.org/10.1111/mec.13454 (2015).
    Article  PubMed  Google Scholar 

    61.
    Donnelly, M., Licht, M. & Lehmann, T. Evidence for recent population expansion in the evolutionary history of the malaria vectors Anopheles arabiensis and Anopheles gambiae. Mol. Biol. Evol. 18, 1353–1364. https://doi.org/10.1093/oxfordjournals.molbev.a003919 (2001).
    CAS  Article  PubMed  Google Scholar 

    62.
    Niu, Y. Q., Nansen, C., Li, X. W. & Liu, T. X. Geographical variation of Plutella xylostella (Lepidoptera: Plutellidae) populations revealed by mitochondrial COI gene in China. J. Appl. Entomol. 138, 692–700. https://doi.org/10.1111/jen.12130 (2014).
    CAS  Article  Google Scholar 

    63.
    Hurst, G. D. D. & Jiggins, F. M. Problems with mitochondrial DNA as a marker in population, phylogeographic and phylogenetic studies: the effects of inherited symbionts. Proc. R. Soc. B Biol. Sci. 272, 1525–1534. https://doi.org/10.1098/rspb.2005.3056 (2005).
    CAS  Article  Google Scholar 

    64.
    You, M. et al. Variation among 532 genomes unveils the origin and evolutionary history of a global insect herbivore. Nat. Commun. 11, 2321. https://doi.org/10.1038/s41467-020-16178-9 (2020).
    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

    65.
    Slatkin, M. Gene flow in natural populations. Annu. Rev. Ecol. Syst. 16, 393–430. https://doi.org/10.1146/annurev.ecolsys.16.1.393 (1985).
    Article  Google Scholar 

    66.
    Mills, L. S. & Allendorf, F. W. The one-migrant-per-generation rule in conservation and management. Cons. Biol. 10, 1509–1518. https://doi.org/10.1046/j.1523-1739.1996.10061509.x (1996).
    Article  Google Scholar 

    67.
    Perry, K. D. The colonisation of canola crops by the diamondback moth, Plutella xylostella L., in southern Australia. Ph.D. thesis, The University of Adelaide (2019).

    68.
    Hatami, B. Seasonal occurrence and abundance of diamondback moth, Plutella xylostella (L.), and its major parasitoids on brassicaceous plants in South Australia. Ph.D. thesis, The University of Adelaide (1996).

    69.
    Ridland, P. M. & Endersby, N. M. Seasonal phenology of diamondback moth populations in southern Australia. In The Management of Diamondback Moth and Other Crucifer Pests: Proceedings of the Fifth International Workshop (eds Shelton A. M. et al.) 90–101 (China Agricultural Science and Technology Press, Beijing, 2008).

    70.
    Roush, R. T. & McKenzie, J. A. Ecological genetics of insecticide and acaricide resistance. Annu. Rev. Entomol. 32, 361–380. https://doi.org/10.1146/annurev.en.32.010187.002045 (1987).
    CAS  Article  PubMed  Google Scholar 

    71.
    Zalucki, M. P. & Furlong, M. J. Predicting outbreaks of a migratory pest: an analysis of DBM distribution and abundance revisited. In The Sixth International Workshop on Management of the Diamondback Moth and Other Crucifer Insect Pests (eds Srinivasan, R., Shelton, A. M. & Collins, H. L.) 8–14 (AVRDC – The World Vegetable Centre, Tainan, Taiwan, 2011).

    72.
    Benestan, L. et al. Sex matters in massive parallel sequencing: evidence for biases in genetic parameter estimation and investigation of sex determination systems. Mol. Ecol. 26, 6767–6783. https://doi.org/10.1111/mec.14217 (2017).
    CAS  Article  PubMed  Google Scholar 

    73.
    Robertson, P. L. Diamondback moth investigation in New Zealand. N. Z. J. Sci. Technol. 20, 330–340 (1939).
    Google Scholar 

    74.
    Zraket, C., Barth, J., Heckel, D. & Abbott, A. Genetic linkage mapping with restriction fragment length polymorphisms in the tobacco budworm, Heliothis virescens. In Molecular Insect Science (eds Hagedorn, H. H., Hildebrand, J. G., Kidwell M. G. & Law, J. H.) 13–20 (Springer, Boston, MA, 1990). https://doi.org/10.1007/978-1-4899-3668-4_2

    75.
    Andrews, S. FASTQC: a quality control tool for high throughput sequence data. http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ (2010). Accessed August 2016.

    76.
    Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120. https://doi.org/10.1093/bioinformatics/btu170 (2014).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    77.
    Lunter, G. & Goodson, M. Stampy: a statistical algorithm for sensitive and fast mapping of Illumina sequence reads. Genome Res. 21, 936–939. https://doi.org/10.1101/gr.111120.110 (2011).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    78.
    Broad Institute. http://broadinstitute.github.io/picard/. Accessed 10 December 2017.

    79.
    McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303. https://doi.org/10.1101/gr.107524.110 (2010).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    80.
    DePristo, M. A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43, 491. https://doi.org/10.1038/ng.806 (2011).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    81.
    Danecek, P. et al. The variant call format and VCFtools. Bioinformatics 27, 2156–2158. https://doi.org/10.1093/bioinformatics/btr330 (2011).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    82.
    Lischer, H. E. L. & Excoffier, L. PGDSpider: an automated data conversion tool for connecting population genetics and genomics programs. Bioinformatics 28, 298–299. https://doi.org/10.1093/bioinformatics/btr642 (2012).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    83.
    Perry, K. D. https://github.com/kymperry01/PlutellaCanola. Accessed November 2018.

    84.
    Goudet, J. & Jombart, T. hierfstat: Estimation and tests of hierarchical F-statistics (2015). R package version 0.04-22.

    85.
    Nei, M. Molecular Evolutionary Genetics (Columbia University Press, New York, 1987).
    Google Scholar 

    86.
    Weir, B. & Cockerham, C. Estimating F-statistics for the analysis of population structure. Evolution 38, 1358–1370. https://doi.org/10.2307/2408641 (1984).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    87.
    Keenan, K., McGinnity, P., Cross, T. F., Crozier, W. W. & Prodoehl, P. A. diveRsity: an R package for the estimation and exploration of population genetics parameters and their associated errors. Methods Ecol. Evol. 4, 782–788. https://doi.org/10.1111/2041-210X.12067 (2013).
    Article  Google Scholar 

    88.
    Rousset, F. GENEPOP ‘007: a complete re-implementation of the GENEPOP software for Windows and Linux. Mol. Ecol. Resour. 8, 103–106. https://doi.org/10.1111/j.1471-8286.2007.01931.x (2008).
    Article  PubMed  Google Scholar 

    89.
    Holm, S. A simple sequentially rejective multiple test procedure. Scand. J. Stat. 6, 65–70 (1979).
    MathSciNet  MATH  Google Scholar 

    90.
    Armstrong, R. A. When to use the Bonferroni correction. Ophthal. Physiol. Opt. 34, 502–508. https://doi.org/10.1111/opo.12131 (2014).
    Article  Google Scholar 

    91.
    R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2017).

    92.
    Slatkin, M. A measure of population subdivision based on microsatellite allele frequencies. Genetics 139, 457–462 (1995).
    CAS  PubMed  PubMed Central  Google Scholar 

    93.
    Dray, S. & Dufour, A. B. The ade4 package: implementing the duality diagram for ecologists. J. Stat. Softw. 22, 1–20 (2007).
    Article  Google Scholar 

    94.
    Hijmans, R. J. geosphere: Spherical Trigonometry. R package version 1.5-7 (2017).

    95.
    Kamvar, Z. N., Tabima, J. F. & Gruenwald, N. J. Poppr: an R package for genetic analysis of populations with clonal, partially clonal, and/or sexual reproduction. PeerJ 2, e281. https://doi.org/10.7717/peerj.281 (2014).
    Article  PubMed  PubMed Central  Google Scholar 

    96.
    Evanno, G., Regnaut, S. & Goudet, J. Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol. Ecol. 14, 2611–2620. https://doi.org/10.1111/j.1365-294X.2005.02553.x (2005).
    CAS  Article  PubMed  Google Scholar 

    97.
    Earl, D. A. & von Holdt, B. M. STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv. Genet. Resour. 4, 359–361. https://doi.org/10.1007/s12686-011-9548-7 (2012).
    Article  Google Scholar 

    98.
    Jakobsson, M. & Rosenberg, N. A. CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics 23, 1801–1806. https://doi.org/10.1093/bioinformatics/btm233 (2007).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    99.
    Rosenberg, N. A. DISTRUCT: a program for the graphical display of population structure. Mol. Ecol. Notes 4, 137–138. https://doi.org/10.1046/j.1471-8286.2003.00566.x (2004).
    Article  Google Scholar 

    100.
    Jombart, T. adegenet: an R package for the multivariate analysis of genetic markers. Bioinformatics 24, 1403–1405. https://doi.org/10.1093/bioinformatics/btn129 (2008).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    101.
    Jombart, T. & Ahmed, I. adegenet 1.3-1: new tools for the analysis of genome-wide SNP data. Bioinformatics 27, 3070–3071. https://doi.org/10.1093/bioinformatics/btr521 (2011).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    102.
    Ryman, N. & Palm, S. POWSIM: a computer program for assessing statistical power when testing for genetic differentiation. Mol. Ecol. Notes 6, 600–602. https://doi.org/10.1111/j.1365-294X.2006.01378.x (2006).
    Article  Google Scholar  More

  • in

    Effects of vegetation restoration and environmental factors on understory vascular plants in a typical karst ecosystem in southern China

    1.
    Gilliam, F. S. The ecological significance of the herbaceous layer in temperate forest ecosystems. Bioscience 57, 845–858 (2007).
    Google Scholar 
    2.
    Cervellini, M. et al. Relationships between understory specialist species and local management practices in coppiced forests—evidence from the Italian Apennines. For. Ecol. Manag. 385, 35–45 (2017).
    Google Scholar 

    3.
    Hamelin, C., Gagnon, D. & Truax, B. Exotic invasive shrub glossy buckthorn reduces restoration potential for native forest herbs. Sustainability 9, 1–13 (2017).
    Google Scholar 

    4.
    Lü, X. T., Yin, J. X. & Tang, J. W. Diversity and composition of understory vegetation in the tropical seasonal rain forest of Xishuangbanna, SW China. Rev. Biol. Trop. 59, 455–463 (2011).
    PubMed  Google Scholar 

    5.
    Yazdanshenas, H., Kalagar, M. & Toularoud, M. M. Understory plant species diversity of Asalem’s forests, northern Iran. For. Res. Eng. Int. J. 3, 56–62 (2019).
    Google Scholar 

    6.
    Li, Y. L., Wang, S. L. & Yan, S. K. Short-term effects of understory vegetation removal on nutrient cycling in litter layer of Chinese fir plantation. Chin. J. Appl. Ecol. 22, 2560–2566 (2011) (in Chinese with English abstract).
    Google Scholar 

    7.
    Yang, Y. et al. Mechanism of litter and understory vegetation effects on soil carbon and nitrogen hydrolase activities in Chinese fir forests. Acta Ecol. Sin. 36, 8102–8110 (2016) (in Chinese with English abstract).
    Google Scholar 

    8.
    Berkowitz, A. R., Canham, C. D. & Kelly, V. R. Competition vs. facilitation of tree seedling growth and survival in early successional communities. Ecology 76, 1156–1168 (1995).
    Google Scholar 

    9.
    Padilla, F. M. & Pugnaire, F. I. The role of nurse plants in the restoration of degraded environments. Front. Ecol. Environ. 4, 196–202 (2006).
    Google Scholar 

    10.
    Feng, Q. H. et al. Effects of density adjustment on ground cover and soil hydrological function of Picea asperata plantation in the subalpine region of western Sichuan Province, China. J. Nanjing For. Univ. Nat. Sci. Ed. 42, 98–104 (2018) (in Chinese with English abstract).
    Google Scholar 

    11.
    Rasingam, L. & Parthasarathy, N. Diversity of understory plants in undisturbed and disturbed tropical lowland forests of Little Andaman Island, India. Biodiv. Cons. 18, 1045–1065 (2009).
    Google Scholar 

    12.
    Boonstra, R., Krebs, C. J. & Cowcill, K. Responses of key understory plants in the boreal forests of western North America to natural versus anthropogenic nitrogen levels. For. Ecol. Manag. 401, 45–54 (2017).
    Google Scholar 

    13.
    Ou, Z. Y., Su, Z. Y., Ye, Y. C., Zhu, J. Y. & Liu, S. S. Ground vegetation as indicators of topsoil chemical properties in Dongguan, South China. Acta Ecol. Sin. 29, 984–992 (2009) (in Chinese with English abstract).
    CAS  Google Scholar 

    14.
    Su, Z. Y., Ke, X. D. & Zhang, S. J. Vascular plants as indicators of organic carbon gradient in subtropical forested soil. Pol. J. Environ. Stud. 21, 1393–1398 (2012).
    CAS  Google Scholar 

    15.
    Dolan, B. & Kilgore, J. Forest regeneration following emerald ash borer (Agrilus planipennis Fairemaire) enhances mesophication in eastern hardwood forests. Forests 9, 353–366 (2018).
    Google Scholar 

    16.
    Zhang, J. W., Young, D. H., Oliver, W. W. & Fiddler, G. Effect of overstorey trees on understorey vegetation in California (USA) ponderosa pine plantations. Forest. Int. J. Forest Res. 89, 91–99 (2016).
    Google Scholar 

    17.
    Curzon, M., Baker, S., Kern, C., Palik, B. J. & D’Amato, A. W. Influence of mature overstory trees on adjacent 12-year regeneration and the woody understory: Aggregated retention versus intact forest. Forests 8, 31. https://doi.org/10.3390/f8020031 (2017).
    Article  Google Scholar 

    18.
    Ádám, R., Ódor, P. & Bölöni, J. The effects of stand characteristics on the understory vegetation in Quercus petraea and Q. cerris dominated forests. Commun. Ecol. 14, 101–109 (2013).
    Google Scholar 

    19.
    Navroud, B. B., Vajari, K. A., Pilehvar, B. & Kooch, Y. Interactions between tree and herb layers vegetation along a gradient of tree composition in Hyrcanian forests. Russ. J. Ecol. 46, 483–486 (2015).
    Google Scholar 

    20.
    Mestre, L. et al. The influence of canopy-layer composition on understory plant diversity in southern temperate forests. For. Ecosyst. 4, 6. https://doi.org/10.1186/s40663-017-0093-z (2017).
    Article  Google Scholar 

    21.
    Yu, M. & Sun, O. J. Effects of forest patch type and site on herb-layer vegetation in a temperate forest ecosystem. Forest Ecology and Managemen t300, 14–20 (2013).

    22.
    Huo, H., Feng, Q. & Su, Y. H. The influences of canopy species and topographic variables on understory species diversity and composition in coniferous forests. Sci. World J. https://doi.org/10.1155/2014/252489 (2014).
    Article  Google Scholar 

    23.
    Hicks, D. J. & Taylor, M. S. Effects of Aesculus glabra canopy on understory community structure and environment in a temperate deciduous forest. Castanea 80, 8–19 (2015).
    Google Scholar 

    24.
    Riegel, G. M., Miller, R. F. & Krueger, W. C. Competition for resources between understory vegetation and overstory Pinus ponderosa in northeastern Oregon. Ecol. Appl. 2, 71–85 (1992).
    PubMed  Google Scholar 

    25.
    Barbier, S., Gosselin, F. & Balandier, P. Influence of tree species on understory vegetation diversity and mechanisms involved—a critical review for temperate and boreal forests. For. Ecol. Manag. 254, 1–15 (2008).
    Google Scholar 

    26.
    Giesbrecht, I. J. W., Saunders, S. C., MacKinnon, A. & Lertzman, K. P. Overstory structure drives fine-scale coupling of understory light and vegetation in two temperate rainforest floodplains. Can. J. For. Res. 47, 1244–1256 (2017).
    Google Scholar 

    27.
    Mataji, A. et al. Understory vegetation as environmental factors indicator in forest ecosystems. Int. J. Environ. Sci. Tech. 7, 629–638 (2010).
    Google Scholar 

    28.
    McCalip, B. et al. Site factors influence on herbaceous understory diversity in east Texas Pinus palustris savannas. Int. J. Biol. 11, 1. https://doi.org/10.5539/ijb.v11n1p1 (2019).
    Article  Google Scholar 

    29.
    Bartels, S. F. & Chen, H. Y. H. Interactions between overstorey and understorey vegetation along an overstorey compositional gradient. J. Veg. Sci. 24, 543–552 (2013).
    Google Scholar 

    30.
    Olivero, A. M. & Hix, D. M. Influence of aspect and stand age on ground flora of southeastern Ohio forest ecosystems. Plant Ecol. 139, 177–187 (1998).
    Google Scholar 

    31.
    Warren, R. J. Mechanisms driving understory evergreen herb distributions across slope aspects: As derived from landscape position. Plant Ecol. 198, 297–308 (2008).
    Google Scholar 

    32.
    Ou, Y. D., Su, Z. Y., Ke, X. D. & Li, Z. Vascular ground flora in relation to topography, canopy structure and gap light regimes in a subtropical broadleaved forest (South China). Pol. J. Ecol. 60, 463–476 (2012).
    Google Scholar 

    33.
    Wang, B. W., Zhang, G. H. & Duan, J. Relationship between topography and the distribution of understory vegetation in a Pinus massoniana forest in Southern China. Int. Soil Water Conserv. Res. 3, 291–304 (2015).
    Google Scholar 

    34.
    Costa, F. R. C., Magnusson, W. E. & Luizao, R. C. Mesoscale distribution patterns of Amazonian understorey herbs in relation to topography, soil and watersheds. J. Ecol. 93, 863–878 (2005).
    CAS  Google Scholar 

    35.
    Gracia, M., Montané, F., Piqué, J. & Retana, J. Overstory structure and topographic gradients determining diversity and abundance of understory shrub species in temperate forests in central Pyrenees (NE Spain). For. Ecol. Manag. 242, 391–397 (2007).
    Google Scholar 

    36.
    Zeng, F. P. et al. Changes in vegetation after 22 years’ natural restoration in the karst disturbed area in Northwest Guangxi. Acta Ecol. Sin. 27, 5110–5119 (2007) (in Chinese with English abstract).
    Google Scholar 

    37.
    Song, T. Q. et al. Spatial pattern of forest communities and environmental interpretation in Mulun National Nature Reserve, karst cluster-peak depression region. Chin. J. Plant Ecol. 34, 298–308 (2010) (in Chinese with English abstract).
    Google Scholar 

    38.
    Liu, Y. G., Liu, C. C., Wei, Y. F., Liu, Y. G. & Guo, K. Species composition and community structure at different vegetation successional stages in Puding, Guizhou Province, China. Chin. J. Plant Ecol. 35, 1009–1018 (2011) (in Chinese with English abstract).
    Google Scholar 

    39.
    Wu, K. Y., Jiang, Z. C. & Luo, W. Q. Techniques of ecological restoration and evaluation of economic value of their results in Guohua demonstration area. Earth Environ. 35, 159–165 (2007) (in Chinese with English abstract).
    Google Scholar 

    40.
    Pang, S. L. et al. Edaphic characteristics of different regeneration patterns in karst mountainous areas of Guangxi. J. Cent. South Univ. For. Technol. 36, 60–66 (2016) (in Chinese with English abstract).
    Google Scholar 

    41.
    Ou, Z. Y. et al. Effect of soil fertility and topographic factors on woody plant communities in the karst mountains of Southwest Guangxi, China. Acta Ecol. Sin. 34, 3672–3681 (2014) (in Chinese with English abstract).
    Google Scholar 

    42.
    Ou, Z. Y., Zhu, J. Y., Peng, Y. H., He, Q. F. & Pang, S. L. Relationship between plant diversity and environmental factors of Excentrodendron hsienmu community in karst mountains in Pinguo County, Guangxi. Bull. Bot. Res. 34, 204–211 (2014) (in Chinese with English abstract).
    CAS  Google Scholar 

    43.
    Liu, Y., He, B. Y. & Kou, J. F. Landsat thermal remote sensing to investigate the present situation and variation characteristics of karst rocky desertification in Pingguo County of Guangxi, Southwest China. Sci. Soil Water Conserv. 15, 125–131 (2017) (in Chinese with English abstract).
    Google Scholar 

    44.
    Bao, S. D. The Agro-Chemical Analysis of Soil (China Agriculture Press, Beijing, 2000) (in Chinese)).
    Google Scholar 

    45.
    McCune, B. & Mefford, M. J. PC-ORD. Multivariate Analysis of Ecological Data (Version 5) (MjM Software Design, Oregon, 2006).
    Google Scholar 

    46.
    Ister, S. I. & Gokbulak, F. Effect of stand types on understory vegetation. J. Environ. Biol. 30, 595–600 (2009).
    PubMed  Google Scholar 

    47.
    Légaré, S., Bergeron, Y. & Paré, D. Influence of forest composition on understory cover in boreal mixedwood forests of western Quebec. Silva Fenn 36, 353–366 (2002).
    Google Scholar 

    48.
    Hameed, M. et al. Influence of plantation type on ground flora composition and diversity in Gatwala artificial forest plantation. Pak. J. Bot. 43, 1867–1872 (2011).
    Google Scholar 

    49.
    Sagar, R., Singh, A. & Singh, J. S. Differential effect of woody plant canopies on species composition and diversity of ground vegetation: A case study. Trop. Ecol. 49, 189–197 (2008).
    Google Scholar 

    50.
    Si, B., Yao, X. H. & Ben, H. D. Species composition and diversity in the process of natural succession of Karst vegetation in Central Guizhou: Case study of Puding Country in Guizhou. For. Res. 21, 669–674 (2008) (in Chinese with English abstract).
    Google Scholar 

    51.
    Bazzaz, F. A. Plant species diversity in old-field successional ecosystems in southern Illinois. Ecology 56, 485–488 (1975).
    Google Scholar 

    52.
    Augusto, L., Dupouey, J. L. & Ranger, J. Effects of tree species on understory vegetation and environmental conditions in temperate forests. Ann. For. Sci. 60, 823–831 (2003).
    Google Scholar 

    53.
    Widyatmoko, D. & Burgman, M. A. Influences of edaphic factors on the distribution and abundance of a rare palm (Cyrtostachys renda) in a peat swamp forest in eastern Sumatra, Indonesia. Aust. Ecol. 31, 964–974 (2006).
    Google Scholar 

    54.
    Zhang, Z. H., Hu, G., Zhu, J. D. & Ni, J. Spatial heterogeneity of soil nutrients and its impact on tree species distribution in a karst forest of Southwest China. Chin. J. Plant Ecol. 35, 1038–1049 (2011) (in Chinese with English abstract).
    ADS  CAS  Google Scholar 

    55.
    Song, T. Q. et al. Community composition and biodiversity characteristics of forests in Karst cluster-peak-depression region. Biodivers. Sci. 18, 355–364 (2010) (in Chinese with English abstract).
    Google Scholar 

    56.
    Ou, Z. Y. et al. Coupling relationships between woody plants in Excentrodendron hsienmu community and related edaphic and topographic factors. Chin. J. Ecol. 32, 3182–3189 (2013) (in Chinese with English abstract).
    Google Scholar 

    57.
    Tan, Y. B. et al. Effect of environmental factors on understory species diversity in Southwest Guangxi Excentrodendron tonkinense forests. Biodivers. Sci. 27, 970–983 (2019) (in Chinese with English abstract).
    Google Scholar  More

  • in

    Harmonizing hybridization dissonance in conservation

    Biodiversity is in crisis and the main reasons are human activities inducing habitat modifications and the introduction of invasive species1. In addition, global climate change will probably alter habitat characteristics, migration patterns, reproduction time, and place of various species2. Such human disturbances may produce new breeding overlaps, breaking the independent evolution of organisms and leading to hybridization (see Glossary, Table 1)3. The role of hybridization in the evolution of several plant and animal taxa has been recognized in the light of newly developed molecular tools4. This has also alerted biologists about the threat this phenomenon may represent to biodiversity when enhanced by anthropogenic factors5. We identified three types of hybridization regarding the reproductive properties of first-generation hybrids (F1). This is proposed as a framework to investigate the demographic and genetic effects of hybridization on biodiversity.
    Table 1 Glossary.
    Full size table

    Our perspectives come from the development of modeling simulation approaches applied to various real case studies, which helped us to explore the outcomes of hybridization from both conservation and evolutionary perspectives. We bring here a novel view of conservation guidelines aiming to state the conditions under which hybridization may represent priorities for conservation programmes or, alternatively, new evolutionary opportunities. We highlight that hybridization may certainly lead to biodiversity loss when enhanced by human factors, leading for instance to outbreeding depression or the introgression of maladaptive genes. However, it may also drive the emergence of new biodiversity, reducing the effects of inbreeding depression, and increasing the opportunities to adapt to changing environmental conditions.
    Species concept problem and interspecific hybridization
    The widely accepted biological species concept formulated by Mayr6 states that species are “groups of actually or potentially interbreeding natural populations which are reproductively isolated from other such groups”. The key idea under this vision is the reproductive isolation that delimits the species unit. This was already proposed by Georges-Louis Leclerc, Comte de Buffon, more than 260 years ago7. Buffon realized that a horse and a donkey are morphologically more similar than some different races of dogs. However, the reproduction in the first case leads to an infertile offspring (a mule) while in the second case, the offspring is fertile, highlighting that a line can be drawn between organisms that cannot reproduce in order to differentiate species.
    Charles Darwin supported a different view and dedicated an entire chapter of “On the Origin of Species” to the hybridization concept8. The observation of interbreeding between distinct morphological species, with different degrees of offspring fertility, from completely sterile to even more fertile than parental species in determined conditions, was an argument against sterility or fecundity as a species delineation factor. Darwin agreed with the notion that species may hardly remain different when free sympatric mating occurs, but supported a more continuous conception of species, influenced by the gradual effect of natural selection. However, the idea of species with various degrees of fertility was abandoned during the modern evolutionary synthesis6,9,10.
    Much of the understanding about reproductive isolation and interspecific hybridization has been revealed by experimental studies of Drosophila11. Those works revealed that: (i) reproductive isolation is positively correlated with the phylogenetic distance between hybridizing species; (ii) at the same level of genetic divergence, reproductive isolation is higher between sympatric than allopatric species; and (iii) hybrid offspring follow Haldane’s rule, meaning that if one sex is less viable or sterile, it is more likely to be the heterozygotic sex12,13. During most of the 20th century, interspecific hybridization was considered to be rare in nature, mainly arising by human translocation of species and with a small effect in evolution, with hybrids supposedly having lower fertility in most cases14.
    Despite the wide acceptance of reproductive isolation as a key element to define species, a large controversy persists around the biological species concept (Box 1). This is mainly motivated by the semipermeable breeding barriers between some species and the difficulty of testing this notion in organisms with nonoverlapping spatial or temporal distribution ranges15,16.

    Box 1 Alternative species concepts

    Three of the most popular alternative definitions of species are the ecological, phylogenetic, and evolutionary concepts. Ecological species are of closely related lineage using minimally differentiated adaptive zones, also denominated as ecological niches93. Evolutionary species are defined as ancestral-descendant lineages with their own identity, evolutionary tendency and historical fate94. Phylogenetic species are in turn considered to be the minimal cluster of organisms with a pattern of ancestry and descendance95. These three definitions have also been criticized. The ecological and evolutionary species concepts have been judged to be too vague to determine a cut-off point between species15,17. The phylogenetic species concept has been defended by various authors in the field of conservation biology, who consider it an encompassing view of unique ancestral and derived features for separate species, e.g., refs. 15,19. However, this definition has also been the focus of criticism, mainly due to an inflated number of species16. This is because different regions of the genome may express very different evolutionary histories and because hybridization may also perturb phylogenetic classifications by altering monophyletic lineages20. Mallet96 recognized various cases of speciation that are influenced by fertile hybridization in nature and tried to rescue and adapt the more continuous view of species proposed by Charles Darwin. He understood species as groups of genotypes that remain distinct in the face of actual or potential hybridization96,97. He highlighted the fact that genotypes may remain distinct with reproductive isolation, but this would be a way to maintain species or to reach speciation rather than being a means of species discrimination96. To date, there are around 30 definitions of species and a large debate about species concept and the relation with hybridization, e.g., refs. 15,17,18,98.

    Species concept and conservation
    A problematic view arises when applying the biological species concept, which does not make room for interspecific hybridization17. The semipermeable barriers between genetically, morphologically or ecologically distinct organisms have motivated a large debate about species and hybridization, e.g., refs. 15,18. This discussion is not superfluous for conservation biology because it delimits the main unit of protection17. Yet, what are the central criteria to delineate the units that deserve protection? Some authors consider that because species are evolutionary units, the most appropriate way to diagnose them objectively is through the phylogenetic species concept19. But the use of the phylogenetic species concept has been criticized because small, isolated populations may become well diagnosed evolutionary lineages through the effect of strong genetic drift, inflating the number of species and rendering protection actions more complex. Other authors have advocated that the criteria to delineate conservation units should rely on evidence of reproductive isolation or reduced reproductive fitness20, but these criteria are less objective and sometimes difficult to evidence.
    The debate about species concept and hybridization is not only a matter for biologists, but also for scientists from very different domains, as well as politicians who define legal aspects of wildlife protection21. In this sense, Pasachnik et al.22 propose that whatever else a species is, in the field of conservation biology it should be a group of organisms deserving legal protection because its extinction would constitute a meaningful loss of biodiversity. The evolution of biodiversity represents a continuum, in which speciation processes may occur slowly or relatively fast, but will always have a period of uncertainty regarding genetic differentiation between emerging species23. Conservation biology may therefore consider the level of uncertainty due to hybridization by protecting biodiversity as a dynamic system, which is not focused on reproductive isolation to delimit discrete units, but on the sum of features for which the loss of certain organisms may represent a detrimental effect on biodiversity.
    Evolution of new biodiversity
    Botanists first highlighted the important role of natural hybridization on the speciation process of several species, i.e., in generating new biodiversity, e.g., 24,25. Later, zoologists recognized the major evolutionary effects of introgression on numerous insects e.g., ref. 26, fishes, e.g. ref. 27, amphibians, e.g., ref. 28, reptiles, e.g., ref. 29, birds, e.g., ref. 30, mammals, e.g., ref. 31; and other organisms, e.g., ref. 32, including modern humans (Box 2). There are around 25% of plants and 10% of animals that are currently known to hybridize with another species and the effect of this phenomenon in evolution is considered to be much more important than previously thought33.
    Species can naturally change their historical home range in response to changing environmental conditions and meet closely related taxa34. Several species carry signatures of hybrid ancestry from the last Ice Age period, e.g., ref. 27. For this reason we can find DNA of brown bears in polar bears, because ancient hybridization events occurred during the Pleistocene35. The Bering Land Bridge recurrently emerged during this time, allowing organisms to migrate between Eurasia and North America, leading to opportunities of hybridization, such as those observed between Canada lynx (Lynx canadensis) and Eurasian lynx (Lynx lynx)31. Organisms can have introgressed genes from locally extinct species even if they have never been in contact, because a third species, acting as a temporal bridge to gene flow, has hybridized with both of them e.g., ref. 36.
    Natural selection may fix beneficial alleles obtained by hybridization or, to the contrary, remove detrimental introgressed alleles. Adaptive introgression has been important for several speciation processes33. For instance, the antipredatory mimicry of three Heliconius butterflies in South America has been acquired by interspecific hybridization, for which the parts of the genome related to color patterns have more introgressed alleles than other regions of the genome37. Introgressed alleles can rapidly spread among individuals when they are related to adaptive traits. For example, “warfarin” is a rodenticide that was developed in 1948 to control house mice (Mus musculus). Mice started to be resistant during the 1960s by acquiring a single gene from the Algerian mouse (M. spretus) through hybridization38. These species were isolated until the development of human agricultural lands. They rarely interbreed and hybrids have limited survival with half of them being sterile, but the resistance gene rapidly spread across Europe. In Germany, where both species do not mingle, one third of house mice have the introgressed resistance gene coming from Algerian mice38. A similar case was documented between two species of mosquitos that are vectors of malaria and have different levels of resistance to an insecticide39. The insecticide acted as a selective pressure driving the spread of resistant alleles obtained by hybridization, even when hybrids had reduced fertility40. The reduced fertility of the offspring is therefore not necessarily selected against and can also represent adaptive mate choice41.
    Opportunities for speciation as a result of hybridization can be generated when hybrids exploit unique ecological niches. For instance, a rapid incipient speciation was recently observed in the offspring of two species of yeast, Saccharomyces paradoxus and S. cerevisiae, whose hybrids have the potential to exploit a unique ecology that is intermediate between those of the parental species32. The new genetic architecture generated by hybridization can thus also facilitate ecological divergence, promoting a speciation process by exploiting a specific niche, e.g., ref. 42.
    Positive selection can fix adaptive alleles and purifying selection can remove the detrimental alleles, e.g., ref. 27, but introgressed genes can remain even without the effect of natural selection. Neutral introgressed alleles can persist in high proportion, even when the original species is extinct. Currat et al.43 demonstrated through computer simulations and by a review of the literature, that invasive species in range expansion may carry a large quantity of neutral alleles that are introgressed from a local species. The reverse is not necessarily true unless interbreeding is rare (Fig. 1). When hybridization occurs during the expansion of an invasive species into the territory of a local species, introgression is indeed expected to be much higher in the invasive species than in the local species (Fig. 1). This pattern of asymmetric introgression is generally robust to the density and population structure within both species and to the level of interspecific competition. It results from the hybridization level and from the population demographic imbalance at the wave front of the invasion, in which introgressed alleles that are continuously introduced in the invasive species along its expansion, may surf and reach a higher frequency than expected under a stationary context44. While this pattern may be perturbed by density-dependent dispersal45 and long-distance dispersal46, there are several real cases of asymmetrical introgression between demographically imbalanced species that have been proposed to follow this neutral expectation, e.g. refs. 47,48.
    Fig. 1: Expected pattern of introgression of neutral genes between local and invasive organisms in range expansion.

    a The context of this expected pattern of introgression is the expansion of an invasive species (in beige) in an area where the local species (in blue) is already in demographic equilibrium. The invasive species starts its colonization from the bottom left side of the area with few individuals. b The level of introgression is asymmetrical and higher in the invasive organisms when the interbreeding rate is large enough (after the dotted line in the x-axis). The value of the admixture rate that delineates this expected higher introgression in the invasive taxon depends on the combination of demographic and migration parameters43. The introgression asymmetry between the two species is due to local alleles continuously introduced at the wave front of the invasive range expansion, with a relatively high probability of increasing in frequency due to the surfing process44. The invasive organisms are not necessarily non-indigenous and may also represent threatened organisms that increase in frequency at the expense of exotic organisms45.

    Full size image

    Box 2 Hybridization and human evolution

    Hybridization has probably also played a role in our own evolution when modern humans spread out of Africa and met other closely related hominids. Analyses of ancient DNA estimated around two percent of Neanderthal ancestry in the genome of modern humans outside Africa99,100,101. The introgressed genes may have persisted through neutral processes102 or as a result of positive selection e.g., ref. 103. Recently, it has been proposed that some introgressed alleles, adaptive in the past, may currently be associated with certain diseases104. Modern humans are likely to have met and potentially interbred with other hominids in addition to Neanderthals. Huerta-Sánchez et al105. recognized positive selection in haplotypes related to survival at high altitudes in current Tibetans, which seem to have been introgressed from Denisovans. Other haplotypes from Denisovan ancestry seem to be frequent in the current genome of Melanesians106. Our own genome may thus carry the result of various ancient hybridization events during human evolution107.

    Biodiversity loss
    Hybridization is considered as a major conservation concern when it is motivated by anthropogenic factors, such as translocation of invasive species or by modification of natural habitats5,49. The breakdown of the reproductive barriers between organisms may disrupt their independent evolution and has already increased the risk of extinction of several plant and animal taxa, e.g., refs. 50,51.
    Hybridization may lead to different but potentially interacting mechanisms that threaten species persistence. First, outbreeding depression may represent a significant loss of reproductive value and detonates a rapid extinction when it interacts with a demographic decline. This may be stronger between genetically distant species e.g., ref. 52, but organisms do not need to be distantly related to be affected by outbreeding depression. For instance, the human domestication of Atlantic salmon (Salmo salar) has led to lower fertility when mating with conspecifics in the wild, representing a serious threat for wild salmon in Norway53. Second, native genotypes can disappear by genetic swamping and be replaced by the numerical or competitive advantage of invasive genotypes. Third, the introgression of non-native genes can disrupt local adaptations by introducing maladaptive gene complexes54. Fourth, the behavior of wild animals may be perturbed in a way that is difficult to predict, more particularly when it concerns human domesticated animals55, which have been artificially selected according to human lifestyle and, when spreading their genes in nature, may influence a whole network of ecological interactions, e.g., ref. 56. Fifth, hybridization may affect the effective population size of the interacting species with major consequences for rare or threatened species, which already have a reduced number of breeders57. Finally, an important problem for conservation biology arises when the few remaining individuals of a threatened species show a level of introgression that may cause them to lose their legal protection status when hybrids are not considered to be protected organisms, even though the hybrids may have an ecological function otherwise lost with the extinction of parental species21,58.
    The loss of species distinctiveness due to introgression has also been called “speciation reversal”, e.g., ref. 59. This may seriously affect key ecological adaptations that appeared during species radiation. Vonlanthen et al.60 documented the rapid extinction of whitefish (Coregonus spp.) in Swiss lakes, which evolved according to ecological opportunities, but human eutrophication and homogenization of the environment is driving extinction by hybridization and demographic decline. A similar case was documented for cichlid fishes of Lake Victoria (East Africa), for which the coloration pattern is a key character that determines mate choice and reproductive isolation, but the turbidity of the water induced by eutrophication relaxed sexual selection, destroying the diversification mechanism61. Speciation reversal is a conservation concern, because it erodes the ecological and genetic distinctiveness between closely related, but ecologically divergent, species60. In a context of climate change, Owens and Samuk62 refers to hybridization as a double edge sword, because even when increasing the pool of potentially adaptive genes, some of these genes may be related to reproductive isolation, weakening any reproductive barrier. The various cases of hybridization leading speciation reversal, e.g., refs. 59,61, suggest that the extinction risk may be more extensive than previously thought60.
    Hybridization between wild and domesticated organisms is a worldwide problem of conservation. For instance, the main current threat for the persistence of European wildcats (Felis silvestris) is the hybridization with domestic cats (Felis catus)63,64. Domestic cats were originally domesticated from a wildcat inhabiting the Near East (Felis lybica), but they are genetically distinct to all current F. lybica subspecies65. There are still some wildcat populations remaining in Europe, e.g., ref. 66, but the complete admixture and the loss of genetic distinctiveness have already been achieved in some countries67. Domestic dogs (Canis familiaris) can hybridize with any kind of wolf-like canids and have already led to conservation issues in various cases50, such as for the gray wolf (Canis lupus) in Europe, e.g., ref. 68 the coyote (Canis latrans) in North America, e.g., ref. 56 or the Ethiopian wolf (Canis simensis) in Africa, e.g. ref. 69. Ellington and Murray56 found that hybridization with domestic dogs was driving changes in the space occupied by coyotes, suggesting consequences at the ecosystem level. A particular threat is the hybridization of domestic dogs with the Ethiopian wolf, which is the world’s most endangered canid, persisting with around 500 individuals in 6 isolated populations69,70. The detrimental effects of hybridization with domesticated organisms is reinforced, because they far outnumber their wild counterparts, e.g., ref. 71, in which the extinction risk can be particularly accelerated when rare species hybridize with more abundant species.
    Genetically modified organisms and genetic engineering have generated a large debate on how to regulate the spread of modified genes in nature through hybridization e.g., ref. 72. Genomic alteration for economic purposes may induce higher fertility and resistance to pathogens that make crops or hybrids highly invasive73. The reduced fertility of the first-generation hybrids (F1) is not a barrier for the spread of advantageous alleles74, which are frequently observed in the wild, e.g., ref. 75 with hybrids becoming invasive in various cases76. The ecological release of their natural predators or pathogens conferred by the resistant alleles has been proposed as a factor that is initiating this invasion73. A serious risk has been detected in the single wild population of rice in Costa Rica (Oryza glumaepatula) that hybridizes with invasive commercial rice (O. sativa)77. The concerns are not only related to modified plant crops, but also to animals of economic interest, usually with unpredictable ecological effects, e.g., ref. 78 or to non-target insects, as has been documented for the monarch butterfly Danaus plexippus of North America, e.g., ref. 79.
    Types of hybridization
    We defined three main types of hybridization that may be used as a framework for the understanding of the ecological and evolutionary consequences of hybridization (Fig. 2). These categories include: (1) distant species hybridization, mostly preventing gene flow because hybrids are infertile (Type 1) or (2) because homologous chromosomes do not recombine (Type 2); and (3) interbreeding between more closely related taxa, in which homologous chromosomes recognize themselves during meiosis, resulting in gene flow and consequent introgression between parental organisms (Type 3) (Box 3).
    Fig. 2: Three types of hybridization regarding the reproductive characteristics of first-generation hybrids (F1).

    Type 1 represents infertile or inviable hybrids. Type 2 hybrids are fertile but introgression is prevented in further generations due to the generation of gametes without recombination during gametogenesis in hybrid offspring. Type 3 hybrids are fertile and there is recombination during gametogenesis allowing introgression in further generations. Non-human-induced hybridization represents hybrids naturally found in nature, in which evolutionary opportunities arise when hybrids are fertile. Conservation guidelines are proposed for human-induced hybridization, which are motivated by any anthropogenic factor. They represent either a purely demographic or both a demographic and genetic effect on interbreeding taxa. The conservation priorities to avoid biodiversity loss are highlighted in red and basically represent human-induced hybridization that produces demographic decline or ecological disequilibrium. A potential tool to increase genetic diversity is highlighted in green.

    Full size image

    Fig. 3: Identification of the type of hybridization.

    Different steps that may be considered to recognize the type of hybridization when there is evidence of interbreeding between taxa (modified from Quilodrán et al.81).

    Full size image

    Type 1: Infertile hybrids, no introgression
    The first type of hybridization does not result in introgression, because offspring are inviable or infertile. This type of hybridization represents an extinction risk when the loss of reproductive value enhances a demographic decline for one (or both) parental species. The reasons could be either because small populations interbreed with more abundant populations and therefore waste reproductive efforts, or because additional threats are accumulated, such as a disease. For example, in the case of hybridization between Atlantic salmon (Salmo salar) and brown trout (Salmo trutta), hybridization alone is likely not a threat, but could lead to the extinction of some local salmon populations that are already threatened by a parasitic disease80. This type of hybridization may be considered an evolutionary dead-end.
    Type 2: Fertile hybrids, no introgression
    The second type of hybridization results in fertile F1 hybrids, but introgression is prevented because their offspring are clonal or hemiclonal, transmitting a single parental genome, also called hybridization with genome exclusion. We recently showed that the extinction of natives and the invasion of exotic organisms might be reached in very few generations81. For instance, in the case of hybridogenesis between Western European water-frogs (Pelophylax species complex)51, the extinction risk is not genetically driven, but determined by the “demographic flow” between parental species and mediated by hybrid offspring. We previously demonstrated that this hybridization is a highway to extinction, which may be underappreciated because it emulates the result of hybridization type 1 (i.e., only displaying F1 hybrid phenotypes)81. Evolutionary opportunities may emerge from these systems by generating self-reproducing polyploid forms82, which are observed in plants but rarely found in animals83.
    Type 3: Fertile hybrids, introgression
    The third type of hybridization defines interbreeding with gene flow between parental organisms leading to genomic mixing and therefore to introgression. This type of hybridization may result in two different effects on biodiversity, either a genetic and demographic risk of species extinction5, or the opportunity of adaptation and evolution of novel diversity14. For instance, hybrids may replace native species and facilitate biological invasions as in the case of mallard (Anas platyrhynchos), which has been widely translocated, cohabiting with other duck species and threatening them by hybridization84. In another example, however, genes from extinct hominids may still be found in high frequency in current human populations due to old hybridization events43,85. This type of hybridization can also represent a new evolutionary opportunity by increasing genetic diversity and possibilities of adaptation84.

    Box 3 Assignment to hybridization type

    The three types of hybridization constitute a useful guideline for the understanding of the genetics and/or demographics effects of hybridization on biodiversity. However, to determine one of these types in a specific real system is not always an easy task to achieve, especially when it regards the past evolution of already extinct organisms or when it regards the projection of long-term effects. For instance, infertile hybrids, but with very small introgressions, are observed between Atlantic salmon and brown trout108. A small level of introgression may be ignored, when there is a short-term effect of hybridization producing extinction risk80, but it would not be the case when projecting evolutionary long-term effects, and even more so when concerning range expansions (see Fig. 1), in which case it would be considered as type 3. Moreover, detection of hybridization type 3 with low levels of introgression strongly depends on the amount of genetic markers evaluated4.
    Because hybridization type 1 and type 2 are both producing only F1 phenotypes, we recently developed a genetic framework to determine the type of hybridization81 (Fig. 3). Type 3 is easier to recognize due to multiple hybrid phenotypes being present in a population caused by different levels of introgression. If only F1 phenotypes are observed, often with a phenotype intermediate between parental taxa, we recommend defining hybrid fertility by performing controlled breeding experiments. If these experiments are not possible because, for instance, the few remaining individuals of the involved species are threatened, it would be useful to observe their demography and sex ratio. Hybridization type 2 generally produces a very fast demographic decline, and most of the time favors the production of a single sex (namely females). When hybridization type 2 is suspected, it is important to define whether hybrids’ gametes are producing a single (non-alternative) or both (alternative) parental genomes. This may be clarified with a pool of gametes haplotyping test, which will show whether all gametes of an individual have a single allele per gene, in which case hybridization type 2 will be of the non-alternative form. If two alleles are present for some loci, this test reveals hybridization type 2 of the alternative form. In this last case, a single gamete haplotyping method may be implemented to determine the proportion of gametes generated from each of the parental taxa. If those tests result in more than two haplotypes, it would indicate introgression with very low fitness: either type 1 when regarding ecological short-term effects or type 3 when considering evolutionary long-term effects. Details about the pool of gametes and single gametes haplotyping test are presented in Quilodrán et al.81.

    Conservation guidelines
    Allendorf et al.49 proposed hybridization categories that are widely used to prioritize conservation actions. They considered three categories, but defined differently than ours: (i) sterile hybrids, (ii) widespread introgression, and (iii) complete admixture. Indeed, they ignore the effect of fertile hybrids without introgression (hybridization type 2), which is the category that may induce faster extinctions. In addition, they considered the anthropogenic motivation a sine qua non condition to distinguish the conservation issues of hybridization. We highlight here that hybridization, even when induced by humans, is potentially representing a source of genetic variation that could be useful for conservation purposes.
    The classification of Allendorf et al.49 has been employed during the past 20 years, but the wider understanding of hybridization impact brought by more recent studies allows us to propose a novel view of conservation priorities (Fig. 2). Given our classification, the conservation priorities are also found in human-induced hybridization, but this is not the single cut-off to delimit them. Hybridization type 1 is a conservation concern when promoting demographic decline, either because two species with high density-imbalance interbreed or because hybridization amplifies other existing risks80. Hybridization type 2 is always a threat that may precipitate extinction within very few generations81. Hybridization type 3 is also a priority when affecting key ecological interactions, either by enhancing demographic decline or because it changes the behavior of wild individuals84.
    Hybridization types 1 and 3 should not represent a priority when they are not triggering demographic decline or the disruption of ecological functions80,84. We suggest that the resources to protect biodiversity may be redirected either to other conservation issues or other threatened organisms. In such conditions, hybridization type 3 may even be used as a conservation tool to increase genetic diversity. However, all of these should be implemented carefully84. The potential fitness loss and the detrimental ecological effects of hybridization have first to be evaluated, and this is often difficult to achieve. In the first case, controlled breeding experiments may help to assess the fertility of hybrids. If this is not possible, monitoring the demography of parental species may help to evaluate a potential fitness loss due to hybridization. A detrimental ecological effect of hybridization is more difficult to evaluate but the behavior of hybrids may provide valuable information. As an example, in Britain, extent hybridization has been registered between Scottish wildcats and domestic cats86, as well as between European polecat and feral ferrets87. While the phenotype of Scottish wildcats has been seriously affected86, the polecat phenotype has been much less affected due to hybridization87. In both cases, the increased genetic diversity may have a positive effect in front of changing environmental conditions, but the impact of hybridization on the behavior of wildcats55, and on the fitness of the polecat population88, deserve more attention before rejecting hybridization as a threat or proposing it as a conservation management tool.
    We propose that phylogenetically closer taxa with similar ecological requirements may offer some guidelines for assisted hybridization as a tool in conservation. For instance, assisted hybrization between subspecies of panthers has promoted the recovery of Florida panthers (Puma concolor coryi) by increasing heterozygosity and decreasing inbreeding, resulting in an overall increase of survival and fitness89. Hybridization between different species has also promoted the recovery of American chestnuts (Castanea dentata) through the transfer of pathogen resistance from Chinese chestnuts (C. mollisima)90. In circumstances where organisms are evolutionarily close and share similar ecologies, and when the local species is on the brink of extinction, hybrids may also represent a subject of protection, even when hybridization is caused by anthropogenic factors. An example is the interspecific hybridization between coral reefs, in which the parental species Acropora palmata and A. cervicornis have been in a critical decline over the last decades, but their hybrids (also called A. prolifera) have increased in several locations91. The hybrids have been shown to be as fit or even more fit than the parental species92. While the parental species are legally protected, protecting hybrids represents a legal challenge, which may help to preserve functional ecosystems otherwise lost with the extinction of the parental species91. More

  • in

    Sheep feeding preference as a tool to control pine invasion in Patagonia: influence of foliar toughness, terpenoids and resin content

    1.
    Augustine, D. J. & McNaughton, S. J. Ungulate effects on the functional species composition of plant communities: herbivore selectivity and plant tolerance. J. Wildl. Manag. 62, 1165–1183 (1998).
    Google Scholar 
    2.
    Huntly, N. Herbivores and the dynamics of communities and ecosystems. Annu. Rev. Ecol. Syst. 22, 477–503 (1991).
    Google Scholar 

    3.
    Keane, R. M. & Crawley, M. J. Exotic plant invasions and the enemy release hypothesis. Trends Ecol. Evol. 17, 164–170 (2002).
    Google Scholar 

    4.
    Maron, J. L. & Vila, M. When do herbivores affect plant invasion? Evidence for the natural enemies and biotic resistance hypotheses. Oikos 95, 361–373 (2001).
    Google Scholar 

    5.
    Lockwood, J. L., Hoopes, M. F. & Marchetti, M. P. Establishment success: the influence of biotic interactions. In Invasion Ecology (eds Lockwood, J. L. et al.) 107–131 (Wiley, Hoboken, 2013).
    Google Scholar 

    6.
    Meijer, K., Schilthuizen, M., Beukeboom, L. & Smit, C. A review and meta-analysis of the enemy release hypothesis in plant-herbivorous insect systems. PeerJ https://doi.org/10.7717/peerj.2778 (2016).
    Article  PubMed  PubMed Central  Google Scholar 

    7.
    Nunez-Mir, G. C. et al. Biotic resistance to exotic invasions: its role in forest ecosystems, confounding artifacts, and future directions. Biol. Invasions 19, 3287–3299 (2017).
    Google Scholar 

    8.
    Jeschke, J. M. & Heger, T. Invasion Biology. Hypotheses and Evidence (CABI, Wallingford, 2018).
    Google Scholar 

    9.
    Averill, K. M., Mortensen, D. A., Smithwick, E. A. H. & Post, E. Deer feeding selectivity for invasive plants. Biol. Invasions 18, 1247–1263 (2016).
    Google Scholar 

    10.
    Parker, J., Burkepile, D. & Hay, M. Opposing effects of native and exotic herbivores on plant invasions. Science 311, 1459–1461. https://doi.org/10.1126/science.1121407 (2006).
    ADS  CAS  Article  PubMed  Google Scholar 

    11.
    Hobbs, R. J. Synergisms among habitat fragmentation, livestock grazing, and biotic invasions in Southwestern Australia. Conserv. Biol. 15, 1522–1528 (2001).
    Google Scholar 

    12.
    Knight, T. M., Dunn, J. L., Smith, L. A., Davis, J. & Kalisz, S. Deer facilitate invasive plant success in a Pennsylvania forest understory. Nat. Areas J. 29, 110–116 (2009).
    Google Scholar 

    13.
    Nuñez, M. A. et al. Exotic mammals disperse exotic fungi that promote invasion by exotic trees. PLoS ONE 8, 1–6 (2013).
    Google Scholar 

    14.
    Oduor, A. M. O., Gómez, J. M. & Strauss, S. Y. Exotic vertebrate and invertebrate herbivores differ in their impacts on native and exotic plants: a meta-analysis. Biol. Invasions 12, 407–419 (2010).
    Google Scholar 

    15.
    Spear, D. & Chown, S. L. Non-indigenous ungulates as a threat to biodiversity. J. Zool. 279, 1–17 (2009).
    Google Scholar 

    16.
    Vavra, M., Parks, C. G. & Wisdom, M. J. Biodiversity, exotic plant species, and herbivory: the good, the bad, and the ungulate. For. Ecol. Manag. 246, 66–72 (2007).
    Google Scholar 

    17.
    Loydi, A. & Zalba, S. M. Feral horses dung piles as potential invasion windows for alien plant species in natural grasslands. Plant Ecol. 201, 471–480 (2009).
    Google Scholar 

    18.
    Richardson, D. M. & Rejmánek, M. Conifers as invasive aliens: a global survey and predictive framework. Divers. Distrib. 10, 321–331 (2004).
    Google Scholar 

    19.
    Simberloff, D. et al. Spread and impact of introduced conifers in South America: lessons from other southern hemisphere regions. Austral. Ecol. 35, 489–504 (2010).
    Google Scholar 

    20.
    Rejmánek, M. & Richardson, D. M. What attributes make some plant species more invasive?. Ecology 77, 1655–1661 (1996).
    Google Scholar 

    21.
    Nuñez, M. A., Simberloff, D. & Relva, M. A. Seed predation as a barrier to alien conifer invasions. Biol. Invasions 10, 1389–1398 (2008).
    Google Scholar 

    22.
    Nuñez, M. A., Relva, M. A. & Simberloff, D. Enemy release or invasional meltdown? Deer preference for exotic and native trees on Isla Victoria Argentina. Austral. Ecol. 33, 317–323 (2008).
    Google Scholar 

    23.
    Nuñez, M. A. & Medley, K. A. Pine invasions: climate predicts invasion success; something else predicts failure. Divers. Distrib. 17, 703–713 (2011).
    Google Scholar 

    24.
    Relva, M. A., Nuñez, M. A. & Simberloff, D. Introduced deer reduce native plant cover and facilitate invasion of non-native tree species: evidence for invasional meltdown. Biol. Invasions 12, 303–311 (2010).
    Google Scholar 

    25.
    Osem, Y., Lavi, A. & Rosenfeld, A. Colonization of Pinus halepensis in Mediterranean habitats: consequences of afforestation, grazing and fire. Biol. Invasions 13, 485–498 (2011).
    Google Scholar 

    26.
    de Villalobos, A., Zalba, S. M. & Peláez, D. V. Pinus halepensis invasion in mountain pampean grassland: effects of feral horses grazing on seedling establishment. Environ. Res. 111, 953–959 (2011).
    PubMed  Google Scholar 

    27.
    Sarasola, M. M., Rusch, V. E., Schlichter, T. M. & Ghersa, C. M. Invasión de coníferas forestales en áreas de estepa y bosques de ciprés de la cordillera en la Región Andino Patagónica. Ecol. Austral. 16, 143–156 (2006).
    Google Scholar 

    28.
    Chauchard, S., Pille, G. & Carcaillet, C. Large herbivores control the invasive potential of nonnative Austrian black pine in a mixed deciduous Mediterranean forest. Can. J. For. Res. 36, 1047–1053 (2006).
    Google Scholar 

    29.
    Boulant, N., Kunstler, G., Rambal, S. & Lepart, J. Seed supply, drought, and grazing determine spatio-temporal patterns of recruitment for native and introduced invasive pines in grasslands. Divers. Distrib. 14, 862–874 (2008).
    Google Scholar 

    30.
    Becerra, P. I. & Bustamante, R. O. The effect of herbivory on seedling survival of the invasive exotic species Pinus radiata and Eucalyptus globulus in a Mediterranean ecosystem of Central Chile. For. Ecol. Manag. 256, 1573–1578 (2009).
    Google Scholar 

    31.
    Bartolomé, J., Boada, M., Saurí, D., Sánchez, S. & Plaixats, J. Conifer dispersion on subalpine pastures in Northeastern Spain: characteristics and implications for rangeland management. Rangel. Ecol. Manag. 61, 218–225 (2008).
    Google Scholar 

    32.
    Forbes, J. M. Learning about food: conditioned preferences and aversions. In Voluntary Food Intake and Diet Selection in Farm Animals (ed. Forbes, J. M.) 117–143 (CABI, Wallingford, 2007).
    Google Scholar 

    33.
    Danell, K., Bergström, R. & Edenius, L. Effects of large mammalian browsers on architecture, biomass, and nutrients of woody plants. Source J. Mammal. 75, 833–844 (1994).
    Google Scholar 

    34.
    McNaughton, S. J. Grazing as an optimization process: grass-ungulate relationships in the Serengeti. Am. Nat. 113, 691–703 (1979).
    Google Scholar 

    35.
    Canham, C. D., McAninch, J. B. & Wood, D. M. Effects of the frequency, timing, and intensity of simulated browsing on growth and mortality of tree seedlings. Can. J. For. Res. 24, 817–825 (1994).
    Google Scholar 

    36.
    Persson, I. L., Danell, K. & Bergström, R. Different moose densities and accompanied changes in tree morphology and browse production. Ecol. Appl. 15, 1296–1305 (2005).
    Google Scholar 

    37.
    Pollock, M. L., Lee, W. G., Walker, S. & Forrester, G. Ratite and ungulate preferences for woody New Zealand plants: influence of chemical and physical traits. N. Z. J. Ecol. 31, 68–78 (2007).
    Google Scholar 

    38.
    Duncan, A. J., Hartley, S. E. & Iason, G. R. The effect of monoterpene concentrations in Sitka Spruce (Picea sitchensis) on the browsing behavior of red deer (Cervus elaphus). Can. J. Zool. Can. Zool. 72, 1715–1720 (1994).
    CAS  Google Scholar 

    39.
    Kimball, B. A., Russell, J. H. & Ott, P. K. Phytochemical variation within a single plant species influences foraging behavior of deer. Oikos 121, 743–751 (2012).
    Google Scholar 

    40.
    Zhang, X. & States, J. S. Selective herbivory of Ponderosa pine by Abert squirrels: a re-examination of the role of terpenes. Biochem. Syst. Ecol. 19, 111–115 (1991).
    CAS  Google Scholar 

    41.
    Elliott, S. & Loudon, A. Effects of monoterpene odors on food selection by red deer calves (Cervus elaphus). J. Chem. Ecol. 13, 1343–1349 (1987).
    CAS  PubMed  Google Scholar 

    42.
    Bryant, J. P. et al. Interactions between woody plants and browsing mammals mediated by secondary metabolites. Annu. Rev. Ecol. Syst. 22, 431–446 (1991).
    Google Scholar 

    43.
    Bryant, J. P., Reichardt, P. B. & Clausen, T. P. Chemically mediated interactions between woody plants and browsing mammals. J. Range Manag. 45, 18–24 (1992).
    Google Scholar 

    44.
    Baraza, E., Hódar, J. A. & Zamora, R. Consequences of plant-chemical diversity for domestic goat food preference in Mediterranean forests. Acta Oecol. 35, 117–127 (2009).
    ADS  Google Scholar 

    45.
    Moreira, X. et al. Trade-offs between constitutive and induced defences drive geographical and climatic clines in pine chemical defences. Ecol. Lett. 17, 537–546 (2014).
    PubMed  Google Scholar 

    46.
    Radwan, M. A. & Crouch, G. L. Selected chemical constituents and deer browsing preference of Douglas Fir. J. Chem. Ecol. 4, 675–683 (1978).
    CAS  Google Scholar 

    47.
    Frost, R. A. & Launchbaugh, K. L. Grazing for Rangeland Weed Managenent: a new look at an old tool. Rangelands 25, 43–47 (2003).
    Google Scholar 

    48.
    Ledgard, N. J. The spread of lodgepole pine (Pinus contorta, Dougl.) in New Zealand. For. Ecol. Manag. 141, 43–57 (2001).
    Google Scholar 

    49.
    Zamora-Nasca, L. B., Relva, M. A. & Núñez, M. A. Ungulates can control tree invasions: experimental evidence from nonnative conifers and sheep herbivory. Biol. Invasions 20, 583–591 (2018).
    Google Scholar 

    50.
    Crozier, E. R. & Ledgard, N. J. Palatability of wilding conifers and control by simulated sheep browsing. In Alternatives to the Chemical Control of Weeds. Proceedings of International Conference, Rotorua, July 1989. Bulletin No. 155 (eds Basset, C. et al.) 139–143 (Rotorua, Ministry of Forestry, Forest Research Institute, 1990).
    Google Scholar 

    51.
    Mayle, B. Domestic Stock Grazing to Enhance Woodland Biodiversity (Forestry Commission, Edinburgh, 1999).
    Google Scholar 

    52.
    Westoby, M. The LHS Strategy Scheme in Relation to Grazing and Fire. VIth International Rangeland Congress (Australian Rangeland Society, Canberra, 1999).
    Google Scholar 

    53.
    Westoby, M. An analysis of diet selection by large generalist herbivores. Am. Nat. 108, 290–304 (1974).
    Google Scholar 

    54.
    Villalba, J. J., Burritt, E. A. & Clair, S. B. S. Aspen (Populus tremuloides Michx.) intake and preference by mammalian herbivores: the role of plant secondary compounds and nutritional context. J. Chem. Ecol. 40, 1135–1145 (2014).
    CAS  PubMed  Google Scholar 

    55.
    Rhodes, A. C., Larsen, R. T., Maxwell, J. D. & St. Clair, S. B. Temporal patterns of ungulate herbivory and phenology of aspen regeneration and defense. Oecologia 188, 707–719 (2018).
    ADS  PubMed  Google Scholar 

    56.
    Cingolani, A. M., Posse, G. & Collantes, M. B. Plant functional traits, herbivore selectivity and response to sheep grazing in Patagonian steppe grasslands. J. Appl. Ecol. 42, 50–59 (2005).
    Google Scholar 

    57.
    Bran, D., Ayesa, J. & Lopez, C. Áreas ecológicas de Neuquen (Instituto Nacional de Tecnología Agropecuaria – INTA, Buenos Aires, 2002).
    Google Scholar 

    58.
    Mueller, J. Producción ovina en Argentina, situación actual y perspectivas futuras. Boletín Inf. INTA 200, 19–21 (2001).
    Google Scholar 

    59.
    Aguiar, M. R. & Sala, O. E. Interactions among grasses, shrubs, and herbivores in Patagonian grass-shrub steppes. Ecol. Austral. 8, 201–210 (1998).
    Google Scholar 

    60.
    Zamora-Nasca, L. B., Relva, M. A. & Núñez, M. A. Ungulate browsing on introduced pines differs between plant communities: implications for invasion process and management. Austral. Ecol. 44, 973–982 (2019).
    Google Scholar 

    61.
    Bonvissuto, G. L., Somlo, R. C., Lanciotti, M. L., Carteau, A. G. & Busso, C. A. Guías de Condición para Pastizales Naturales de ‘Precordillera’, ‘Sierras y Mesetas’ y ‘Monte Austral’ de Patagonia (Instituto Nacional de Tecnología Agrpecuaria – INTA, Buenos Aires, 2008).
    Google Scholar 

    62.
    Siffredi, G. L. et al. Guía para la evaluación de Pastizales. Para las áreas ecológicas de Sierras y Mesetas Occidentales y de Monte de Patagonia Norte (INTA, Buenos Aires, 2013).
    Google Scholar 

    63.
    SENASA. Manual de Bienestar Animal Un enfoqe práctico para el buen manejo de especies domésticas durante su tenencia, producción, concentración, transporte y faena (Servicio Nacional de Sanidad y Calidad Agroalimentaria, Buenos Aires, 2015).
    Google Scholar 

    64.
    Álvarez, J. M. et al. Bienestar animal Ovino (2005).

    65.
    Mumm, R. & Hilker, M. Direct and indirect chemical defence of pine against folivorous insects. Trends Plant Sci. 11, 351–358 (2006).
    CAS  PubMed  Google Scholar 

    66.
    Moreira, X. et al. Inducibility of chemical defences by two chewing insect herbivores in pine trees is specific to targeted plant tissue, particular herbivore and defensive trait. Phytochemistry 94, 113–122 (2013).
    CAS  PubMed  Google Scholar 

    67.
    Crawley, M. J. Mixed-effect models. In The R Book 681–714 (Wiley, 2013).

    68.
    Zuur, A. F., Ieno, E. N., Walker, N. J., Saveliev, A. A. & Smith, G. M. Mixed Effects Models and extensions in Ecology with R (Springer, Berlin, 2009).
    Google Scholar 

    69.
    Lenth, M. R. Package ‘lsmeans’. CRAN (2013).

    70.
    Bates, D. M., Machler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).
    Google Scholar 

    71.
    Skaug, H., Fournier, D., Nielsen, A., Magnusson, A. & Bolker, B. M. Generalized linear mixed models using ‘AD model builder’. Optim. Methods Softw. 27, 233–249 (2012).
    MathSciNet  Google Scholar 

    72.
    Hothorn, T. et al. Package ‘multcomp’ – Simultaneous Inference in General Parametric Models. (2017). https://cran.r-project.org/web/packages/multcomp/multcomp.pdf

    73.
    Giraudoux, P., Antonietti, J.-P., Beale, C., Pleydell, D. & Treglia, M. Package ‘pgirmess’: Spatial Analysis and Data Mining for Field Ecologists (2018). https://doi.org/10.1145/3097983.3098168doi:

    74.
    Dormann, C. F. et al. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography (Cop.) 36, 027–046 (2013).
    Google Scholar 

    75.
    Peuke, A. D. Correlations in concentrations, xylem and phloem flows, and partitioning of elements and ions in intact plants. A summary and statistical re-evaluation of modelling experiments in Ricinus communis. J. Exp. Bot. 61, 635–655 (2010).
    CAS  PubMed  Google Scholar 

    76.
    Wickham, H. ggplot2. Elegant Graphics for Data Analysis (2009). doi:10.1007/978-0-387-98141-3.

    77.
    R Development Core Team. R: A language and environment for statistical computing. Vienna, Austria. https://www.R-project.org/ (2018).

    78.
    Zamora, R., Gómez, J. M., Hódar, J. A., Castro, J. & García, D. Effect of browsing by ungulates on sapling growth of Scots pine in a mediterranean environment: consequences for forest regeneration. For. Ecol. Manag. 144, 33–42 (2001).
    Google Scholar 

    79.
    Estell, R. E. et al. Effects of volatile compounds on consumption of alfalfa pellets by sheep. J. Anim. Sci. 76, 228–233 (1998).
    CAS  PubMed  Google Scholar 

    80.
    Kruska, D. & Stephan, H. Volumenvergleich allokortikaler Hirnzentren hei Wild- und Hausschweinen. Acta Anat. 84, 387–415 (1973).
    CAS  PubMed  Google Scholar 

    81.
    Arnold, G. W., De Boer, E. S. & Boundy, C. A. P. The influence of odour and taste on the food preferences and food intake of sheep. Aust. J. Agric. Res. 31, 571–587 (1980).
    CAS  Google Scholar 

    82.
    Tribe, D. E. The importance of the sense of smell to the grazing sheep. J. Agric. Sci. 39, 309–312 (1949).
    Google Scholar 

    83.
    Villalba, J. J. & Provenza, F. D. Effects of food structure and nutritional quality and animal nutritional state on intake behaviour and food preferences of sheep. Appl. Anim. Behav. Sci. 63, 145–163 (1999).
    Google Scholar 

    84.
    Evju, M., Austrheim, G., Halvorsen, R. & Mysterud, A. Grazing responses in herbs in relation to herbivore selectivity and plant traits in an alpine ecosystem. Oecologia 161, 77–85 (2009).
    ADS  PubMed  Google Scholar 

    85.
    Cadenasso, M. L., Pickett, S. T. A. & Morin, P. J. Experimental test of the role of mammalian herbivores on old field succession: Community structure and seedling survival. J. Torrey Bot. Soc. 129, 228–237 (2002).
    Google Scholar 

    86.
    Capó, E. A., Aguilar, R. & Renison, D. Livestock reduces juvenile tree growth of alien invasive species with a minimal effect on natives: a field experiment using exclosures. Biol. Invasions 18, 2943–2950 (2016).
    Google Scholar 

    87.
    Dimock, E. J., Silen, R. R. & Allen, V. E. Genetic resistance in Douglas -fir to damage by snowshoe hare and black-tailed deer. For. Sci. 22, 106–121 (1976).
    Google Scholar 

    88.
    Mobæk, R., Mysterud, A., Egil Loe, L., Holand, Ø & Austrheim, G. Density dependent and temporal variability in habitat selection by a large herbivore; an experimental approach. Oikos 118, 209–218 (2009).
    Google Scholar 

    89.
    Iason, G. R., O’Reilly-Wapstra, J. M., Brewer, M. J., Summers, R. W. & Moore, B. D. Do multiple herbivores maintain chemical diversity of Scots pine monoterpenes? Philos. Trans. R. Soc. Lond. B. Biol. Sci. 366, 1337–1345 (2011).
    PubMed  PubMed Central  Google Scholar  More

  • in

    Miocene cladocera from Poland

    The lignite mine at Bełchatów, Central Poland (Fig. 1), has recently yielded abundant Miocene remains of several species of branchiopod microcrustaceans. They pertain to the order Anomopoda or water fleas, families Chydoridae and Bosminidae. The main synapomorphy of the anomopods is the ephippium, a structure in which sexual or resting eggs are deposited and that forms when external conditions deteriorate. The Daphniidae include the well-known and speciose genus Daphnia, a highly specialized pelagic component of the freshwater zooplankton. The ephippium fossilizes well and is mostly the only structure that survives as a fossil. The Chydoridae are mostly found in the littoral of lakes and ponds, among water plants. The Bosminidae are pelagic, like Daphnia, but are much smaller (around 0.5 mm in body size) while Daphnia and other daphniids may reach up to 6–7 mm.
    Figure 1

    (A) View of the Bełchatów Lignite Mine outcrop (photo from the nineties of the twentieth century, when the material was collected). The sedimentary unit with deposits with the cladoceran fossils is to the lower right of the picture (photo: G. Worobiec). (B) Piece of mudstone with cladoceran remains (Collection KRAM-P 225, stored in the W. Szafer Institute of Botany, Polish Academy of Sciences). On the exposed surface leaves of trees and shrubs as well as the water plant Potamogeton (red circle) are seen (photo: A. Pociecha).

    Full size image

    The fossil-bearing deposits belong to a clayey-sandy (I-P) unit considered to be of mid to late Miocene age1,2. Beside by geology, this age is supported by fission track dating, and fossils of different animal (mollusks, fish) and plant (higher plants, water plants and algae) groups1,2,3,4,5,6,7. The fission track ages were 16.5 to 18.1 million years, while the Miocene, also known as the age of mammals, extended from 23 to 5.3 million years BP.
    The Branchiopoda (a class of the Crustacea composed ten extant orders) include some of the most ancient extant crustaceans (the Anostraca or fairy shrimp) with several credible fossils8. However, the fossil record is patchy. While the oldest known anostracan-like representatives date back to the Cambrian, fossils of the four extant so-called cladoceran orders, with an estimated 1,000 extant species, is poor9 and somewhat paradoxical. The order Ctenopoda is known from ca 60 extant species and several Mesozoic fossils (possibly representing orders in their own right) but is rare in the most abundant source of fossils, the sediments of late Pleistocene–Holocene lakes10,11. The Anomopoda, in contrast, have to date a limited Mesozoic fossil record, but their subfossils abound in Holocene lake sediments.
    The family Chydoridae is represented in Bełchatów by at least four genera: Alona, Acroperus, Camptocercus, and Chydorus. Alona s.l. rivals Daphnia as the most species-rich genus of the order9. All Alona fossils seen so far had two connected head-pores (Fig. 2), placing them near or in the somewhat controversial genus Biapertura. In modern European faunas, and except for Biapertura affinis, three-pored species are dominant, while two-pored ones tend to be typical of warm-climate faunas. The postabdomen, another typical anomopod structure functioning more or less as a ‘tail’, is similar but not identical to that of Biapertura affinis. Furthermore, distinct other species (Fig. 2) have been found as well.
    Figure 2

    Alona with two head pores from Miocene mudstone from Bełchatów [(A–C), headshields; (B) arrow, labrum; (D, F, G, H) abdomens; (E) shell with abdomen] (photo: A. Pociecha, E. Zawisza).

    Full size image

    Another type of fossils (Fig. 3) shares characters of the genera Acroperus and Camptocercus. Some body parts suggest the presence of Acroperus cf. harpae, others are Campocercus like. One three-dimensional fossil of a first trunk limb (P1) with soft parts preserved shows an IDL (inner distal lobe) with two setae and a moderately well developed claw. In Acroperus, a seta instead of a claw is found here. In Camptocercus, P1 has a big hook here, and our fossils are therefore intermediate between both genera, suggesting the fossil to belong to an extinct ancestral stage. The genus Chydorus is represented by C. sphaericus-like fossils (Fig. 3), but the postabdomen is needed to decide on its taxonomic status.
    Figure 3

    Acroperus-Camptocercus from Miocene mudstone at Bełchatów [(A) complete animal with shell, headshield, and first antenna; (B) abdomen; (C) shell; (D) claw; (E) shell with abdomen; (F) headshield with soft parts, viz. first and second trunk limbs with IDL setae conserved] (photo: A. Pociecha, E. Zawisza).

    Full size image

    Significantly, Bosminidae in our material were almost as abundant as Alona, while in this family no pre-Pleistocene fossils were previously known at all. Most body parts have been recovered (Fig. 4), but not the postabdomen, which is diagnostic. There is strong variation in the fossils, like in the length of the first antenna (compare Fig. 4B with Fig. 4C,E) and the posterior mucro of the valve. It is impossible to decide whether these antennae belong to several or to a single cyclomorphotic species. However, the distinctly swollen mucros like in Fig. 4A, arrow, are not known in any modern Bosmina, and suggest an extinct taxon.
    Figure 4

    Bosmina from Miocene mudstone from Bełchatów [(A, D, F) shell; (B) shell with headshield; (C) headshield with first antenna; (E) first antenna)] (photo: A. Pociecha, E. Zawisza).

    Full size image

    Daphniid fossil evidence goes back to the Jurassic/Cretaceous boundary. Fossils are fairly common but only consist of resting eggs (ephippia). Ephippia can tentatively be identified to genus level, which has led to the idea that the two subfamilies of Daphniidae have been around, apparently unchanged, for more than 140 million years9. This is known as the morphological stasis hypothesis. Its factual basis is weak although we accept that true Daphnia ephippia occur in the cretaceous of China, Mongolia and Australia9. Credible ephippia have also been isolated from Eocene age Messel pit-oil shales11. Moina (a water flea related to Daphnia) ephippia have been recovered from the early Miocene Barstow formation12,13,14. In the latter place, fossils are three-dimensional, like in our case in Bełchatów. It should be emphasized, however, that at Bełchatów no daphniid fossils have to date been discovered.
    A variety of plant and animal groups, including water plants like Potamogeton have been documented from the Bełchatów site. Many are as beautifully preserved as the cladocerans3,4,5,6,7 and attempts have been made to reconstruct the climatic environment in which they lived. It is suggested to have been warmer than today (average 13.5°–16.5°C, cooling down gradually towards the end of the Miocene). The water was probably slowly flowing, through what may have been a swamp or a group of oxbow lakes from freshwater ecosystems2,15.
    That we recovered no daphniid fossils may refine our insight into the nature of the Bełchatów aquatic environment: We favour the idea of a series of shallow oxbow lakes in a climate warmer than todays, with at least locally an abundance of macrophytes. Chydorids thrive in such environments, and the genus Simocephalus among daphniids also prefers such an environment. Simocephalus is quite common and widespread in modern weedy lakes but it has not been found in Bełchatów either. Like Daphnia, Bosminids are truly planktonic and need open water. Therefore, the Bełchatów lakes were probably a patchwork of macrophyte beds and open water.
    So where did all the daphniids go? Daphniids are also relatively large species (up to several mm in size), while chydorids and bosminids are typically below a millimeter in size. This suggests size-selective predation on the zooplankton, most probably by fish16. Fish (tench, pike, and unidentified species) were present at Bełchatów4, at least until the middle Miocene. Tench is an omnivore and Pike is zooplanktivorous in its early stages, turning to piscivory in later life. Predation-driven exclusion of these large cladocerans may therefore well have acted in concert with the physical environment.
    Predatory exclusion is seldom absolute, especially in a non-tropical climate with a cold season (‘winter’) during which predation is relaxed. This allows the prey to recover. In Bełchatów, we see no such a recovery, so another factor must have intervened. We suggest this may have been linked to water chemistry. Cladocerans, though of worldwide occurrence, are sensitive to water chemistry, more than the copepods, the second main group making up the zooplankton. We are unable to specify the precise nature behind the chemical exclusion of daphniids, but there are many examples of lakes in which Cladocera are chemically depressed. Sometimes, like in Lake Tanganyika (Africa), and the Mallili lakes (Indonesia), Cladocera are excluded altogether17,18.
    In conclusion, our Miocene assemblage significantly expand our insights in anomopod evolution. They resemble modern faunas but at the same time show stronger signs of evolution at the species and at the genus level than expected under the morphological stasis hypothesis based on Daphnia ephippia. We also find clear indications of a species diversity that resembles todays’, with morphologies that look familiar at first sight but prove divergent in the details.
    Bosminid fossils used to be known from the Pleistocene only, but in the Bełchatów fauna they are remarkably abundant and some of them show an unfamiliar morphology. This is best interpreted as a case of paleo-competitive release. Daphniids normally dominate the pelagic and keep bosminid abundances down. But their absence gives these small crustaceans a chance to prosper and dominate the open waters. More

  • in

    Vertical distribution of brittle star larvae in two contrasting coastal embayments: implications for larval transport

    1.
    Uthicke, S., Schaffelke, B. & Byrne, M. A boom-bust phylum? Ecological and evolutionary consequences of density variations in echinoderms. Ecol. Monogr. 79, 3–24 (2009).
    Google Scholar 
    2.
    Sala, E. & Knowlton, N. Global marine biodiversity trends. Annu. Rev. Environ. Resour. 31, 93–122 (2006).
    Google Scholar 

    3.
    Fabricius, K. E., Okaji, K. & De’ath, G. Three lines of evidence to link outbreaks of the crown-of-thorns seastar Acanthaster planci to the release of larval food limitation. Coral Reefs 29, 593–605 (2010).
    ADS  Google Scholar 

    4.
    Hock, K., Wolff, N. H., Condie, S. A., Anthony, K. R. N. & Mumby, P. J. Connectivity networks reveal the risks of crown-of-thorns starfish outbreaks on the Great Barrier Reef. J. Appl. Ecol. 51, 1188–1196 (2014).
    Google Scholar 

    5.
    Wolfe, K., Graba-Landry, A., Dworjanyn, S. A. & Byrne, M. Larval phenotypic plasticity in the boom-and-bust crown-of-thorns seastar, Acanthaster planci. Mar. Ecol. Prog. Ser. 539, 179–189 (2015).
    ADS  Google Scholar 

    6.
    Pearson, T. H., Josefson, A. B. & Rosenberg, R. Petersen’s benthic stations revisited. I. Is the Kattegatt becoming eutrophic?. J. Exp. Mar. Biol. Ecol. 92, 157–206 (1985).
    Google Scholar 

    7.
    Barnes, D. K. A., Verling, E., Crook, A., Davidson, I. & O’Mahoney, M. Local population disappearance follows (20 yr after) cycle collapse in a pivotal ecological species. Mar. Ecol. Prog. Ser. 226, 311–313 (2002).
    ADS  Google Scholar 

    8.
    Hereu, B. et al. Multiple processes regulate long-term population dynamics of sea urchins on Mediterranean rocky reefs. PLoS ONE 7, e36901 (2012).
    ADS  CAS  PubMed  PubMed Central  Google Scholar 

    9.
    Guillou, M. Biotic and abiotic interactions controlling starfish outbreaks in the Bay of Douarnenez, Brittany, France. Oceonol. Acta 19, 415–420 (1996).
    Google Scholar 

    10.
    Van Nes, E. H., Amaro, T., Scheffer, M. & Duineveld, G. C. A. Possible mechanisms for a marine benthic regime shift in the North Sea. Mar. Ecol. Prog. Ser. 330, 39–47 (2007).
    ADS  Google Scholar 

    11.
    Blanchet-Aurigny, A. et al. Multi-decadal changes in two co-occurring ophiuroid populations. Mar. Ecol. Prog. Ser. 460, 79–90 (2012).
    ADS  Google Scholar 

    12.
    Guillou, M., Blanchet-Aurigny, A. & Le Goaster, E. Density fluctuations of the ophiuroids Ophiothrix fragilis and Ophiocomina nigra in the Bay of Douarnenez, Brittany, France. Mar. Biodivers. Rec. 6, 1–5 (2013).
    Google Scholar 

    13.
    Blanchet-Aurigny, A., Dubois, S. F., Quéré, C., Guillou, M. & Pernet, F. Trophic niche of two co-occurring ophiuroid species in impacted coastal systems, derived from fatty acid and stable isotope analyses. Mar. Ecol. Prog. Ser. 525, 127–141 (2015).
    ADS  CAS  Google Scholar 

    14.
    Murat, A., Méar, Y., Poizot, E., Dauvin, J. C. & Beryouni, K. Silting up and development of anoxic conditions enhanced by high abundance of the geoengineer species Ophiothrix fragilis. Cont. Shelf Res. 118, 11–22 (2016).
    ADS  Google Scholar 

    15.
    Geraldi, N. R. et al. Aggregations of brittle stars can perform similar ecological roles as mussel reefs. Mar. Ecol. Prog. Ser. 563, 157–167 (2017).
    ADS  CAS  Google Scholar 

    16.
    Mortensen, T. Die Echinodermen-larven. Nord. Plankt. 9, 1–30 (1900).
    Google Scholar 

    17.
    Mortensen, T. Studies of the development and larval forms of Echinoderms. Copenhagen 266 pp (1921).

    18.
    Strathmann, R. R. The feeding behavior of planktotrophic echinoderm larvae: mechanisms, regulation, and rates of suspension-feeding. J. Exp. Mar. Biol. Ecol. 6, 109–160 (1971).
    Google Scholar 

    19.
    Cowen, R. K., Gawarkiewicz, G., Pineda, J., Thorrold, S. R. & Werner, F. E. Population connectivity in marine systems: An overview. Oceanography 20, 14–21 (2007).
    Google Scholar 

    20.
    Uthicke, S., Doyle, J., Duggan, S., Yasuda, N. & McKinnon, A. D. Outbreak of coral-eating crown-of-thorns creates continuous cloud of larvae over 320 km of the Great Barrier Reef. Sci. Rep. 5, 1–7 (2015).
    Google Scholar 

    21.
    Pratchett, M. S. et al. Thirty years of research on crown-of-thorns starfish (1986–2016): Scientific advances and emerging opportunities. Diversity 9, 1–50 (2017).
    Google Scholar 

    22.
    Wolfe, K., Graba-Landry, A., Dworjanyn, S. A. & Byrne, M. Superstars: Assessing nutrient thresholds for enhanced larval success of Acanthaster planci, a review of the evidence. Mar. Pollut. Bull. 116, 307–314 (2017).
    CAS  PubMed  Google Scholar 

    23.
    Metaxas, A. & Saunders, M. Quantifying the ‘Bio-’ components in biophysical models of larval transport in marine benthic invertebrates: advances and pitfalls. Biol. Bull. 216, 257–272 (2009).
    PubMed  Google Scholar 

    24.
    Cowen, R. K. & Sponaugle, S. Larval dispersal and marine population connectivity. Ann. Rev. Mar. Sci. 1, 443–466 (2009).
    PubMed  Google Scholar 

    25.
    Pineda, J., Hare, J. A. & Sponaugle, S. Larval transport and dispersal in the coastal ocean and consequences for population connectivity. Oceanography 20, 22–39 (2007).
    Google Scholar 

    26.
    Shanks, A. L. Pelagic larval duration and dispersal distance revisited. Biol. Bull. 216, 373–385 (2009).
    PubMed  Google Scholar 

    27.
    DiBacco, C., Sutton, D. & McConnico, L. Vertical migration behavior and horizontal distribution of brachyuran larvae in a low-inflow estuary: Implications for bay-ocean exchange. Mar. Ecol. Prog. Ser. 217, 191–206 (2001).
    ADS  Google Scholar 

    28.
    Chia, F. S. Locomotion of marine invertebrate larvae: A review. Can. J. Zool. 62, 1205–1222 (1984).
    Google Scholar 

    29.
    Thiébaut, E., Dauvin, J. C. & Lagadeuc, Y. Transport of Owenia fusiformis larvae (Annelida: Polychaeta) in the Bay of Seine. I. Vertical distribution in relation to water column stratification and ontogenetic vertical migration. Mar. Ecol. Prog. Ser. 80, 29–39 (1992).
    ADS  Google Scholar 

    30.
    Kunze, H. B., Morgan, S. G. & Lwiza, K. M. Field test of the behavioral regulation of larval transport. Mar. Ecol. Prog. Ser. 487, 71–87 (2013).
    ADS  Google Scholar 

    31.
    Miyake, Y. et al. Roles of vertical behavior in the open-ocean migration of teleplanic larvae: A modeling approach to the larval transport of Japanese spiny lobster. Mar. Ecol. Prog. Ser. 539, 93–109 (2015).
    ADS  Google Scholar 

    32.
    Gallager, S. M., Manuel, J. L., Manning, D. A. & O’Dor, R. Ontogenetic changes in the vertical distribution of giant scallop larvae, Placopecten magellanicus, in 9-m deep mesocosms as a function of light, food, and temperature stratification. Mar. Biol. 124, 679–692 (1996).
    Google Scholar 

    33.
    Daigle, R. M. & Metaxas, A. Modeling of the larval response of green sea urchins to thermal stratification using a random walk approach. J. Exp. Mar. Biol. Ecol. 438, 14–23 (2012).
    Google Scholar 

    34.
    Bonicelli, J. et al. Diel vertical migration and cross-shore distribution of barnacle and bivalve larvae in the central Chile inner-shelf. J. Exp. Mar. Biol. Ecol. 485, 35–46 (2016).
    Google Scholar 

    35.
    Lefebvre, A. & Davoult, D. Vertical distribution of the ophioplutei of Ophiothrix fragilis (Echinodermata: Ophiuroidea) in the Dover Strait (Eastern English Channel, France). In Fifth European Conference on Echinoderms—Echinoderm Research 1998 (eds Carnevali, M. D. C. & Bonasoro, F.) 505–509 (Balkema, Rotterdam, 1998).
    Google Scholar 

    36.
    Grünbaum, D. & Strathmann, R. R. Form, performance and trade-offs in swimming and stability of armed larvae. J. Mar. Res. 61, 659–691 (2003).
    Google Scholar 

    37.
    Roy, A., Metaxas, A. & Ross, T. Swimming patterns of larval Strongylocentrotus droebachiensis in turbulence in the laboratory. Mar. Ecol. Prog. Ser. 453, 117–127 (2012).
    ADS  Google Scholar 

    38.
    Sameoto, J. A., Ross, T. & Metaxas, A. The effect of flow on larval vertical distribution of the sea urchin, Strongylocentrotus droebachiensis. J. Exp. Mar. Biol. Ecol. 383, 156–163 (2010).
    Google Scholar 

    39.
    Fuchs, H. L., Gerbi, G. P., Hunter, E. J., Christman, A. J. & Diez, F. J. Hydrodynamic sensing and behavior by oyster larvae in turbulence and waves. J. Exp. Biol. 218, 1419–1432 (2015).
    PubMed  Google Scholar 

    40.
    Wheeler, J. D., Chan, K. Y. K., Anderson, E. J. & Mullineaux, L. S. Ontogenetic changes in larval swimming and orientation of pre-competent sea urchin Arbacia punctulata in turbulence. J. Exp. Biol. 219, 1303–1310 (2016).
    PubMed  PubMed Central  Google Scholar 

    41.
    Strathmann, R. R. & Grünbaum, D. Good eaters, poor swimmers: compromises in larval form. Integr. Comp. Biol. 46, 312–322 (2006).
    PubMed  Google Scholar 

    42.
    Forward, R. B., Cronin, T. W. & Stearns, D. E. Control of diel vertical migration: Photoresponses of a larval crustacean. Limnol. Oceanogr. 29, 146–154 (1984).
    ADS  Google Scholar 

    43.
    Forward, R. B. Behavioral responses of larvae of the crab Rhithropanopeus harrisii (Brachyura: Xanthidae) during diel vertical migration. Mar. Biol. 90, 9–18 (1985).
    Google Scholar 

    44.
    Garland, E. D., Zimmer, C. A. & Lentz, S. J. Larval distributions in inner-shelf waters: The roles of wind-driven cross-shelf currents and diel vertical migrations. Limnol. Oceanogr. 47, 803–817 (2002).
    ADS  Google Scholar 

    45.
    Pennington, J. T. & Emlet, R. B. Ontogenetic and diel vertical migration of a planktonic echinoid larva, Dendraster excentricus (Eschscholtz): Occurrence, causes, and probable consequences. J. Exp. Mar. Biol. Ecol. 104, 69–95 (1986).
    Google Scholar 

    46.
    Lesser, M. P. & Barry, T. M. Survivorship, development, and DNA damage in echinoderm embryos and larvae exposed to ultraviolet radiation (290–400 nm). J. Exp. Mar. Biol. Ecol. 292, 75–91 (2003).
    CAS  Google Scholar 

    47.
    Tauchman, E. C. & Pomory, C. M. Effect of ultraviolet radiation on growth and percent settlement of larval Lytechinus variegatus (Echinodermata: Echinoidea). Invertebr. Reprod. Dev. 55, 152–161 (2011).
    Google Scholar 

    48.
    Metaxas, A. & Burdett-Coutts, V. Response of invertebrate larvae to the presence of the ctenophore Bolinopsis infundibulum, a potential predator. J. Exp. Mar. Biol. Ecol. 334, 187–195 (2006).
    Google Scholar 

    49.
    Raby, D., Lagadeuc, Y., Dodson, J. J. & Mingelbier, M. Relationship between feeding and vertical distribution of bivalve larvae in stratified and mixed waters. Mar. Ecol. Prog. Ser. 103, 275–284 (1994).
    ADS  Google Scholar 

    50.
    Burdett-Coutts, V. & Metaxas, A. The effect of the quality of food patches on larval vertical distribution of the sea urchins Lytechinus variegatus (Lamarck) and Strongylocentrotus droebachiensis (Mueller). J. Exp. Mar. Biol. Ecol. 308, 221–236 (2004).
    Google Scholar 

    51.
    Sameoto, J. A. & Metaxas, A. Interactive effects of haloclines and food patches on the vertical distribution of 3 species of temperate invertebrate larvae. J. Exp. Mar. Biol. Ecol. 367, 131–141 (2008).
    Google Scholar 

    52.
    Birrien, J. L., Wafar, M. V. M., Le Corre, P. & Riso, R. Nutrients and primary production in a shallow stratified ecosystem in the Iroise Sea. J. Plankton Res. 13, 721–742 (1991).
    Google Scholar 

    53.
    Le Corre, P., L’Helguen, S., Morin, P. & Birrien, J. L. Conditions de formation d’eaux colorées toxiques sur le plateau continental Manche-Atlantique; cas de Gyrodinium cf. aureolum. Hydroécologie Appliquée 2, 173–188 (1992).
    Google Scholar 

    54.
    Clay, T. W. & Grünbaum, D. Morphology-flow interactions lead to stage-selective vertical transport of larval sand dollars in shear flow. J. Exp. Biol. 213, 1281–1292 (2010).
    CAS  PubMed  Google Scholar 

    55.
    Soars, N. A. & Byrne, M. Contrasting arm elevation angles of multi- and two-armed sea urchin echinoplutei supports Grünbaum and Strathmann’s hydromechanical model. Mar. Biol. 162, 607–616 (2015).
    Google Scholar 

    56.
    Chan, K. Y. K., Grünbaum, D., Arnberg, M. & Dupont, S. Impacts of ocean acidification on survival, growth, and swimming behaviours differ between larval urchins and brittlestars. ICES J. Mar. Sci. 73, 951–961 (2016).
    Google Scholar 

    57.
    Burke, R. D. Structure of the digestive tract of the pluteus larva of Dendraster excentricus (Echinodermata: Echinoida). Zoomorphology 98, 209–225 (1981).
    Google Scholar 

    58.
    Chadwick, H. C. Echinoderm larvae. L.M.B.C. Mem. XXII (1914).

    59.
    Mileikovsky, S. A. Speed of active movement of pelagic larvae of marine bottom invertebrates and their ability to regulate their vertical position. Mar. Biol. 23, 11–17 (1973).
    Google Scholar 

    60.
    Fortier, L. & Leggett, W. C. Fickian transport and the dispersal of fish larvae in estuaries. Can. J. Fish. Aquat. Sci. 39, 1150–1163 (1982).
    Google Scholar 

    61.
    Knights, A. M., Crowe, T. P. & Burnell, G. Mechanisms of larval transport: Vertical distribution of bivalve larvae varies with tidal conditions. Mar. Ecol. Prog. Ser. 326, 167–174 (2006).
    ADS  Google Scholar 

    62.
    Rigal, F., Viard, F., Ayata, S. D. & Comtet, T. Does larval supply explain the low proliferation of the invasive gastropod Crepidula fornicata in a tidal estuary?. Biol. Invasions 12, 3171–3186 (2010).
    Google Scholar 

    63.
    Herbert, R. J. H. et al. Invasion in tidal zones on complex coastlines: Modelling larvae of the non-native Manila clam, Ruditapes philippinarum, in the UK. J. Biogeogr. 39, 585–599 (2012).
    Google Scholar 

    64.
    Hock, K. et al. Controlling range expansion in habitat networks by adaptively targeting source populations. Conserv. Biol. 30, 856–866 (2016).
    PubMed  Google Scholar 

    65.
    Dupont, S., Havenhand, J., Thorndyke, W., Peck, L. & Thorndyke, M. Near-future level of CO2-driven ocean acidification radically affects larval survival and development in the brittlestar Ophiothrix fragilis. Mar. Ecol. Prog. Ser. 373, 285–294 (2008).
    ADS  CAS  Google Scholar 

    66.
    Strathmann, R. R., Fenaux, L. & Strathmann, M. F. Heterochronic developmental plasticity in larval sea urchins and its implications for evolution of nonfeeding larvae. Evolution 46, 972–986 (1992).
    PubMed  Google Scholar 

    67.
    Augris, C. et al. Atlas thématique de l’environnement marin de la baie de Douarnenez (Finistère). Edition IFREMER, Brest (2005).

    68.
    Bodin, P., Boucher, D., Guillou, J. & Guillou, M. The trophic system of the benthic communities in the bay of Douarnenez (Brittany). In Proceedings of the 19th European Marine Biology Symposium, Plymouth, Devon, UK, 16–21 September 1984 (ed Gibbs, P. E.) 361–370 (Cambridge University Press, 1985).

    69.
    Blanchet, A., Chevalier, C., Gaffet, J. & Hamon, D. Bionomie benthique subtidale en baie de Douarnenez. DEL/EC/BB.RST.04.01, Ifremer (2004).

    70.
    Del Amo, Y. et al. Impacts of high-nitrate freshwater inputs on macrotidal ecosystems. I. Seasonal evolution of nutrient limitation for the diatom-dominated phytoplankton of the Bay of Brest (France). Mar. Ecol. Prog. Ser. 161, 213–224 (1997).
    ADS  Google Scholar 

    71.
    Bowmer, T. Reproduction in Amphiura filiformis (Echinodermata: Ophiuroidea): Seasonality in gonad development. Mar. Biol. 68, 281–290 (1982).
    Google Scholar 

    72.
    Lefebvre, A., Davoult, D., Gentil, F. & Janquin, M. Spatio-temporal variability in the gonad growth of Ophiothrix fragilis (Echinodermata: Ophiuroidea) in the English Channel and estimation of carbon and nitrogen outputs towards the pelagic system. Hydrobiologia 414, 25–34 (1999).
    Google Scholar 

    73.
    Narasimhamurti, N. The development of Ophiocoma nigra. Q. J. Microsc. Sci. 76, 63–88 (1933).
    Google Scholar 

    74.
    Morgan, R. & Jangoux, M. Larval morphometrics and influence of adults on settlement in the gregarious ophiuroid Ophiothrix fragilis (Echinodermata). Biol. Bull. 208, 92–99 (2005).
    PubMed  Google Scholar 

    75.
    Dupont, S., Thorndyke, W., Thorndyke, M. C. & Burke, R. D. Neural development of the brittlestar Amphiura filiformis. Dev. Genes Evol. 219, 159–166 (2009).
    PubMed  Google Scholar 

    76.
    Schlitzer, R. Ocean Data View. odv.awi.de (2018).

    77.
    Lazure, P. & Dumas, F. An external-internal mode coupling for a 3D hydrodynamical model for applications at regional scale (MARS). Adv. Water Resour. 31, 233–250 (2008).
    ADS  Google Scholar 

    78.
    Jouanneau, N., Sentchev, A. & Dumas, F. Numerical modelling of circulation and dispersion processes in Boulogne-sur-mer harbour (Eastern English Channel): Sensitivity to physical forcing and harbour design. Ocean Dyn. 63, 1321–1340 (2013).
    ADS  Google Scholar 

    79.
    Smagorinsky, J. General circulation experiments with the primitive equation. I. The basic experiment. Mon. Weather Rev. 111, 99–165 (1963).
    ADS  Google Scholar 

    80.
    Lazure, P., Garnier, V., Dumas, F., Herry, C. & Chifflet, M. Development of a hydrodynamic model of the Bay of Biscay: Validation of hydrology. Cont. Shelf Res. 29, 985–997 (2009).
    ADS  Google Scholar 

    81.
    Caillaud, M., Petton, S., Dumas, F., Rochette, S. & Mickael, V. Rejeu hydrodynamique à 500 m de résolution avec le modèle MARS3D-AGRIF-Zone Manche-Gascogne. Ifremer https://doi.org/10.12770/3edee80f-5a3e-42f4-9427-9684073c87f5 (2016).
    Article  Google Scholar 

    82.
    Frontier, S. Sur une méthode d’analyse faunistique rapide du zooplancton. J. Exp. Mar. Biol. Ecol. 3, 18–26 (1969).
    Google Scholar 

    83.
    MacBride, E. W. The development of Ophiothrix fragilis. J. Cell Sci. 51, 557–606 (1907).
    Google Scholar 

    84.
    Mortensen, T. Handbook of the Echinoderms of the British Isles (Oxford University Press, London, 1927).
    Google Scholar 

    85.
    Geiger, S. R. Echinodermata: Larvae. Classes: Ophiuroidea and Echinoidea (Plutei). In Fiches d’identification du zooplancton, Sheet 105 (eds Fraser, J. H. & Hansen, V. K.) 1–5 (Andr. Fred. Høst & Fils, Copenhagen, 1964).
    Google Scholar 

    86.
    Stöhr, S. Who’s who among baby brittle stars (Echinodermata: Ophiuroidea): Postmetamorphic development of some North Atlantic forms. Zool. J. Linn. Soc. 143, 543–576 (2005).
    Google Scholar 

    87.
    Planque, B., Lazure, P. & Jegou, A. M. Typology of hydrological structures modelled and observed over the Bay of Biscay shelf. Sci. Mar. 70, 43–50 (2006).
    Google Scholar 

    88.
    Tapia, F. J., DiBacco, C., Jarrett, J. & Pineda, J. Vertical distribution of barnacle larvae at a fixed nearshore station in southern California: stage-specific and diel patterns. Estuar. Coast. Shelf Sci. 86, 265–270 (2010).
    ADS  Google Scholar 

    89.
    Beet, A., Solow, A. R. & Bollens, S. M. Comparing vertical plankton profiles with replication. Mar. Ecol. Prog. Ser. 262, 285–287 (2003).
    ADS  Google Scholar 

    90.
    Hayek, L.-A. C. & Buzas, M. A. Surveying natural populations: quantitative tools for assessing biodiversity (Columbia University Press, New York, 1997).
    Google Scholar 

    91.
    Rowe, P. M. & Epifanio, C. E. Flux and transport of larval weakfish in Delaware Bay, USA. Mar. Ecol. Prog. Ser. 110, 115–120 (1994).
    ADS  Google Scholar  More

  • in

    Unravelling the different causes of nitrate and ammonium effects on coral bleaching

    1.
    Dubinsky, Z. & Jokiel, P. L. Ratio of energy and nutrient fluxes regulates symbiosis between zooxanthellae and corals. Pac. Sci. 48, 313–324 (1994).
    Google Scholar 
    2.
    LaJeunesse, T. C. et al. Systematic revision of Symbiodiniaceae highlights the antiquity and diversity of coral endosymbionts. Curr. Biol. 28, 2570–2580 (2018).
    CAS  PubMed  Google Scholar 

    3.
    Falkowski, P. G., Dubinsky, Z., Muscatine, L. & Porter, J. W. Light and the bioenergetics of a symbiotic coral. Bioscience 34, 705–709 (1984).
    CAS  Google Scholar 

    4.
    Grover, R., Maguer, J.-F., Reynaud-Vaganay, S. & Ferrier-Pagès, C. Uptake of ammonium by the scleractinian coral Stylophora pistillata: effect of feeding, light, and ammonium concentrations. Limnol. Oceanogr. 47, 782–790 (2002).
    ADS  Google Scholar 

    5.
    Grover, R., Maguer, J.-F., Allemand, D. & Ferrier-Pagès, C. Nitrate uptake in the scleractinian coral Stylophora pistillata. Limnol. Oceanogr. 48, 2266–2274 (2003).
    ADS  CAS  Google Scholar 

    6.
    Godinot, C., Ferrier-Pagès, C. & Grover, R. Kinetics of phosphate uptake by the scleractinian coral Stylophora pistillata. Limnol. Oceanogr. 54, 1627–1633 (2009).
    ADS  Google Scholar 

    7.
    Muscatine, L., McCloskey, L. R. & Marian, R. E. Estimating the daily contribution of carbon from zooxanthellae to coral animal respiration. Limnol. Oceanogr. 26, 601–611 (1981).
    ADS  CAS  Google Scholar 

    8.
    Trembley, P., Grover, R., Maguer, J.-F., Legendre, L. & Ferrier-Pagè, C. Autotrophic carbon budget in coral tissue: a new 13C-based model of photosynthate translocation. J. Exp. Biol. 215, 1384–1393 (2012).
    Google Scholar 

    9.
    Hoegh-Guldberg, O. et al. Coral reefs under rapid climate change and ocean acidification. Science 318, 1737–1742 (2007).
    ADS  CAS  PubMed  Google Scholar 

    10.
    Claar, D. C., Szostek, L., McDevitt-Irwin, J. M., Schanze, J. J. & Baum, J. K. Global patterns and impacts of El Niño events on coral reefs: A meta-analysis. PLoS ONE 13, e0190957 (2018).
    PubMed  PubMed Central  Google Scholar 

    11.
    Lough, J. M., Anderson, K. D. & Ughes, T. P. Increasing thermal stress for tropical coral reefs: 1871–2017. Sci. Rep. 8, 6079 (2018).
    ADS  CAS  PubMed  PubMed Central  Google Scholar 

    12.
    Hughes, T. P. et al. Spatial and temporal patterns of mass bleaching of corals in the Anthropocene. Science 359, 80–83 (2018).
    ADS  CAS  PubMed  Google Scholar 

    13.
    Lapointe, B. E., Brewton, R. A., Herren, L. W., Porter, J. W. & Hu, C. Nitrogen enrichment, altered stoichiometry, and coral reef decline at Looe Key, Florida Keys, USA: a 3-decade study. Mar. Biol. 166, 108 (2019).
    Google Scholar 

    14.
    Wiedenmann, J. et al. Nutrient enrichment can increase the susceptibility of reef corals to bleaching. Nat. Clim. Chang. 3, 160–164 (2013).
    ADS  CAS  Google Scholar 

    15.
    Burkepile, D. E. et al. Nitrogen identity drives differential impacts of nutrients on coral bleaching and mortality. Ecosystems https://doi.org/10.1007/s10021-019-00433-2 (2019).
    Article  Google Scholar 

    16.
    Shantz, A. A. & Burkepile, D. E. Context-dependent effects of nutrient loading on the coral-algal mutualism. Ecology 95, 1995–2005 (2014).
    PubMed  Google Scholar 

    17.
    Nordemar, I., Nyströn, M. & Dizon, R. Effects of elevated seawater temperature and nitrate enrichment on the branching coral Porites cylindrica in the absence of particulate food. Mar. Biol. 142, 669–677 (2003).
    CAS  Google Scholar 

    18.
    Béraud, E., Gevaert, F., Rottier, C. & Ferrier-Pagès, C. The response of the scleractinian coral Turbinaria reniformis to thermal stress depends on the nitrogen status of the coral holobiont. J. Exp. Biol. 216, 2665–2674 (2013).
    PubMed  Google Scholar 

    19.
    Ezzat, L., Maguer, J.-F., Grover, R. & Ferrier-Pagès, C. Limited phosphorus availability is the Achilles heel of tropical reef corals in a warming ocean. Sci. Rep. 6, 31768 (2015).
    ADS  Google Scholar 

    20.
    Lesser, M. P. Elevated temperatures and ultraviolet radiation cause oxidative stress and inhibit photosynthesis in symbiotic dinoflagellates. Limnol. Oceanogr. 41, 271–283 (1996).
    ADS  CAS  Google Scholar 

    21.
    Lesser, M. P. Oxidative stress causes coral bleaching during exposure to elevated temperatures. Coral Reefs 16, 187–192 (1997).
    ADS  Google Scholar 

    22.
    Lesser, M. P. Oxidative stress in marine environments: biochemistry and physiological Ecology. Annu. Rev. Physiol. 68, 253–278 (2006).
    CAS  PubMed  Google Scholar 

    23.
    Downs, C. A. et al. Oxidative stress and seasonal coral bleaching. Free Rad. Biol. Med. 33, 533–543 (2002).
    CAS  PubMed  Google Scholar 

    24.
    Perez, S. & Weis, V. Nitric oxide and cnidarians bleaching: an eviction notice mediates breakdown of a symbiosis. J. Exp. Biol. 209, 2804–2810 (2006).
    CAS  PubMed  Google Scholar 

    25.
    Weis, V. M. Cellular mechanisms of Cnidarian bleaching: stress causes the collapse of symbiosis. J. Exp. Biol. 211, 59–66 (2008).
    Google Scholar 

    26.
    Halliwell, B. & Gutteridge, J.M.C. (eds.) Free Radicals in Biology and Medicine. (Oxford, 2007).

    27.
    Pörtner, H. O. & Farrell, A. P. Physiology and climate change. Science 322, 690–692 (2008).
    PubMed  Google Scholar 

    28.
    Sokolova, I. M. Energy-Limited tolerance to stress as a conceptual framework to integrate the effects of multiple stressors. Integ. Comp. Biol. 53, 597–608 (2013).
    Google Scholar 

    29.
    Dominguez-Valdivia, M. D. et al. Nitrogen nutrtion and antioxidant metabolism in ammonium-tolerant and –sensitive plants. Phys. Plant. 132, 359–369 (2008).
    CAS  Google Scholar 

    30.
    Bouchard, J. N. & Yamasaki, H. Heat stress stimulates nitric oxide production in Symbiodinium microadriaticum: a possible linkage between nitric oxide and the coral bleaching phenomenon. Plant. Cell Physiol. 49, 641–652 (2008).
    CAS  PubMed  Google Scholar 

    31.
    Yamasaki, H. & Sakihama, Y. Simultaneous production of nitric oxide and peroxynitrite by plant nitrate reducatase: in vitro evidence for the NR*dependent formation of active nitrogen species. FEBS. 468, 89–92 (2000).
    CAS  Google Scholar 

    32.
    Bethke, P. C., Badger, M. R. & Jones, R. L. Apoplastic synthesis of nitric oxide by plant tissues. Plant. Cell. 16, 332–341 (2004).
    CAS  PubMed  PubMed Central  Google Scholar 

    33.
    Tischner, R., Planchet, E. & Kaiser, W. M. Mitochondrial electron transport as a source of nitric oxide in the unicellular green algae Chlorella sorokiniana. FEBS Lett. 576, 151–155 (2004).
    CAS  PubMed  Google Scholar 

    34.
    Planchet, E., Gupta, K. J., Sonoda, M. & Kaiser, W. M. Nitric oxide emission from tabacco leaves and cell suspensions: rate limiting factors and evidence for the involvement of mitochondrial electron transport. Plant. J. 41, 732–743 (2005).
    CAS  PubMed  Google Scholar 

    35.
    Bartesaghi, S. & Radi, R. Fundamentals on the biochemistry of peroxynitrite and protein tyrosine nitration. Redox. Biol. 14, 618–625 (2018).
    CAS  PubMed  Google Scholar 

    36.
    Brodie, J., Devlin, M., Heynes, D. & Waterhouse, J. Assessment of the eutrophication status of the Great Barrier Reef lagoon (Australia). Biogeochemistry 106, 281–302 (2011).
    CAS  Google Scholar 

    37.
    Govers, L. L., Lamers, L. P., Bouma, T. J., de Brouwer, J. H. & van Katwijk, M. M. Eutrophication threatens Caribbean seagrass: an example from Curaçao and Bonaire. Mar. Poll. Bull. 89, 481–486 (2014).
    CAS  Google Scholar 

    38.
    Naumann, M. S., Bednarz, V. N., Ferse, S. C., Niggl, W. & Wild, C. Monitoring of coastal coral reefs near Dahab (Gulf of Aqaba, red sea) indicates local eutrophication as potential cause for change in benthic communities. Environ. Monit. Assess. 187, 1–14 (2015).
    CAS  Google Scholar 

    39.
    Rouzé, H., Lecellier, G., Langlade, M., Planes, S. & Berteaux-Lecellier, V. Fringing reefs exposed to different levels of eutrophication and sedimentation can support similar benthic communities. Mar. Pollut. Bull. 92, 212–221 (2015).
    PubMed  Google Scholar 

    40.
    Hoogenboom, M., Beraud, E. & Ferrier-Pagè, C. Relationship between symbiont density and photosynthetic carbon acquisition in the temperate coral Cladocora caespitosa. Coral Reefs 29, 21–29 (2010).
    ADS  Google Scholar 

    41.
    Bradford, M. M. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal. Biochem. 7, 248–254 (1976).
    Google Scholar 

    42.
    Jeffrey, S. & Humphrey, G. New spectrophotometric equations for determining chlorophylls a, b, c1 and c2 in higher plants, algae and natural phytoplankton. Biochem. Physiol. Pfl. 167, 191–194 (1975).
    CAS  Google Scholar 

    43.
    Veal, C. J., Carmi, M., Fine, M. & Hoegh-Guldberg, O. Increasing the accuracy of surface area estimation using single wax dipping of coral fragments. Coral Reefs 29, 893–897 (2010).
    ADS  Google Scholar 

    44.
    Jones, R. J., Kildea, T. & Hoegh-Guldberg, O. PAM chlorophyll fluorometry: a new in situ technique for stress assessment in scleractinian corals, used to examine the effects of cyanide from cyanide fishing. Mar. Pollut. Bull. 38, 864–874 (1999).
    CAS  Google Scholar 

    45.
    Jones, R. The ecotoxicological effects of photosystem II herbicides on corals. Mar. Pollut. Bull. 51, 495–506 (2005).
    CAS  PubMed  Google Scholar 

    46.
    Davies, P. S. Short-term growth measurements of corals using an accurate buoyant weighing technique. Mar. Biol. 101, 389–395 (1989).
    Google Scholar 

    47.
    Aguiar, R. B. et al. Estradiol valerate and tibolone: effects upon brain oxidative stress and blood biochemistry during aging in female rats. Biogerontology 9, 285–298 (2008).
    CAS  PubMed  Google Scholar 

    48.
    Oakes, K. D. & van der Kraak, G. J. Utility of the TBARS assay in detecting oxidative stress in white sucker (Catostomus commersoni) populations exposed to pulp mill effluent. Aquat. Toxicol. 63, 447–463 (2003).
    CAS  PubMed  Google Scholar 

    49.
    Huang, D., Ou, B. & Prior, R. L. The chemistry behind antioxidant capacity assays. J. Agric. Food. Chem. 53, 1841–1856 (2005).
    CAS  PubMed  Google Scholar 

    50.
    Sokolova, I. M., Frederich, M., Bagwe, R., Lanning, G. & Sukhotin, A. A. Energy homeostasis as an integrative tool for assessing limits of envirnmental stress tolerance in aquatic organisms. Mar. Environ. Res. 79, 1–15 (2012).
    CAS  PubMed  Google Scholar 

    51.
    Underwood, A. J. Experiments in Ecology: Their Logical Design and Interpretation Using Analysis of Variance (Cambridge University Press, Cambridge, U.K., 1997).
    Google Scholar 

    52.
    Halliwell, B. Biochemistry of oxidative stress. Biochem. Soc. Trans. 35, 1147–1150 (2007).
    CAS  PubMed  Google Scholar 

    53.
    Havaux, M. & Niyogi, K. K. The violaxanthin cycle protects plants from photooxidative damage by more than one mechanism. Proc. Natl. Acad. Sci. USA 96, 8762–8767 (1999).
    ADS  CAS  PubMed  Google Scholar 

    54.
    Tardy, F. & Havaux, M. Thylakoid membrane fluidity and thermostability during the operation of the xanthophyll cycle in higher-plant chloroplasts. Biochim. Biophys. Acta. 1330, 179–193 (1997).
    CAS  PubMed  Google Scholar 

    55.
    Downs, C. A., Mueller, E., Phillips, S., Fauth, J. E. & Woodley, C. M. A molecular biomarker system for assessing the health of coral (Montastrea faveolata) during heat stress. Mar. Biotechnol. 2, 533–544 (2000).
    CAS  PubMed  Google Scholar 

    56.
    Krueger, T. et al. Differential coral bleaching—contrasting the activity and response of enzymatic antioxidants in symbiotic partners under thermal stress. Comp. Biochem. Physiol. Part A: Mol. Integ. Physiol. 190, 15–25 (2015).
    CAS  Google Scholar 

    57.
    Marangoni, L. F. B. et al. Oxidative stress biomarkers as potential tools in reef degradation monitoring: a study case in a South Atlantic reef under influence of the 2015–2016 El Niño/Southern Oscillation (ENSO). Ecol. Ind. 106, 105533 (2019).
    CAS  Google Scholar 

    58.
    Morris, L. A., Voolstra, C. R., Quigley, K. M., Bourne, D. G. & Bay, L. K. Nutrient availability and metabolism affect the stability of coral-Symbiodiniaceae Symbioses. Trends Microbiol. 8, 678–689 (2019).
    Google Scholar 

    59.
    Axenov-Gribanov, D. V. et al. A cellular and metabolic assessment of the thermal stress responses in the endemic gastropod Benedictia limnaeoides ongurensis from Lake Baikal. Comp. Biochem. Physiol. Part B. 167, 16–22 (2013).
    Google Scholar 

    60.
    Larade, S. & Storey, K. B. A profile of metabolic responses to anoxia in marine invertebrates. In Sensing, Signaling and Cell Adaptation (eds Storey, K. B. & Storey, J. M.) 27–46 (Elsevier, Amsterdam, 2002).
    Google Scholar 

    61.
    Philip, A., Macdonald, A. L. & Watt, P. W. Lactate—a signal coordinating cell and systemic function. J. Exp. Biol. 208, 4561–4575 (2005).
    Google Scholar 

    62.
    Riobò, N. A. et al. Nitric oxide inhibits mitochondrial NADH:ubiquinone reductase activity through peroxynitrite formation. Biochem. J. 359, 139–145 (2001).
    PubMed  PubMed Central  Google Scholar 

    63.
    Wang, Y. & Ruby, E. G. The roles of NO in microbial symbioses. Cell. Microbiol. 13, 518–526 (2013).
    Google Scholar 

    64.
    Higuchi, T., Yuyama, I. & Nakamura, T. The combined effects of nitrate with high temperature and high light intensity on coral bleaching and antioxidant enzyme activities. Reg. S. Mar. Sci. 2, 27–31 (2015).
    Google Scholar 

    65.
    Muscatine, L. & Porter, J. W. Reef corals-mutualistic symbioses adapted to nutrient-poor environments. Bioscience 27, 454–460 (1977).
    Google Scholar 

    66.
    Ezzat, L., Maguer, J.-F., Grover, R. & Ferrier-Pagès, C. New insights into carbon acquisition and exchanges within the coral-dinoflagellate symbiosis under NH4+ and NO3− supply. Proc. R. Soc. B. 282, 20150610 (2015).
    PubMed  Google Scholar 

    67.
    Cunning, R. & Baker, A. C. Excess algal symbionts increase the susceptibility of reef corals to bleaching. Nat. Clim. Change 3, 259–262 (2013).
    ADS  Google Scholar 

    68.
    Meyer, J. L. & Schultz, E. T. Migrating haemulid fishes as a source of nutrients and organic matter on coral reefs. Limnol. Oceanogr. 30, 146–156 (1985).
    ADS  Google Scholar  More

  • in

    Global wind patterns and the vulnerability of wind-dispersed species to climate change

    1.
    Bellard, C., Bertelsmeier, C., Leadley, P., Thuiller, W. & Courchamp, F. Impacts of climate change on the future of biodiversity. Ecol. Lett. 15, 365–377 (2012).
    Google Scholar 
    2.
    Hampe, A. Plants on the move: the role of seed dispersal and initial population establishment for climate-driven range expansions. Acta Oecol. 37, 666–673 (2011).
    Google Scholar 

    3.
    Kremer, A. et al. Long‐distance gene flow and adaptation of forest trees to rapid climate change. Ecol. Lett. 15, 378–392 (2012).
    Google Scholar 

    4.
    Pecl, G. T. et al. Biodiversity redistribution under climate change: impacts on ecosystems and human well-being. Science 355, eaai9214 (2017).
    Google Scholar 

    5.
    Felicísimo, Á. M., Muñoz, J. & González-Solis, J. Ocean surface winds drive dynamics of transoceanic aerial movements. PLoS ONE 3, e2928 (2008).
    Google Scholar 

    6.
    Gillespie, R. G. et al. Long-distance dispersal: a framework for hypothesis testing. Trends Ecol. Evol. 27, 47–56 (2012).
    Google Scholar 

    7.
    Muñoz, J., Felicísimo, Á. M., Cabezas, F., Burgaz, A. R. & Martínez, I. Wind as a long-distance dispersal vehicle in the Southern Hemisphere. Science 304, 1144–1147 (2004).
    Google Scholar 

    8.
    Smith, D. J. et al. Intercontinental dispersal of bacteria and archaea by transpacific winds. Appl. Environ. Microbiol. 79, 1134–1139 (2013).
    CAS  Google Scholar 

    9.
    Austerlitz, F., Dutech, C., Smouse, P. E., Davis, F. & Sork, V. L. Estimating anisotropic pollen dispersal: a case study in Quercus lobata. Heredity 99, 193–204 (2007).
    CAS  Google Scholar 

    10.
    Bullock, J. M. & Clarke, R. T. Long distance seed dispersal by wind: measuring and modelling the tail of the curve. Oecologia 124, 506–521 (2000).
    CAS  Google Scholar 

    11.
    Gassmann, M. I. & Pérez, C. F. Trajectories associated to regional and extra-regional pollen transport in the southeast of Buenos Aires province, Mar del Plata (Argentina). Int. J. Biometeorol. 50, 280–291 (2006).
    Google Scholar 

    12.
    Skarpaas, O. & Shea, K. Dispersal patterns, dispersal mechanisms, and invasion wave speeds for invasive thistles. Am. Naturalist 170, 421–430 (2007).
    Google Scholar 

    13.
    Wang, Z. F. et al. Pollen and seed flow under different predominant winds in wind-pollinated and wind-dispersed species Engelhardia roxburghiana. Tree Genet. Genomes 12, 19 (2016).
    CAS  Google Scholar 

    14.
    Soubeyrand, S., Enjalbert, J., Sanchez, A. & Sache, I. Anisotropy, in density and in distance, of the dispersal of yellow rust of wheat: experiments in large field plots and estimation. Phytopathology 97, 1315–1324 (2007).
    CAS  Google Scholar 

    15.
    Born, C., le Roux, P. C., Spohr, C., McGeoch, M. A. & van Vuuren, B. J. Plant dispersal in the sub‐Antarctic inferred from anisotropic genetic structure. Mol. Ecol. 21, 184–194 (2012).
    Google Scholar 

    16.
    Geremew, A., Woldemariam, M. G., Kefalew, A., Stiers, I. & Triest, L. Isotropic and anisotropic processes influence fine-scale spatial genetic structure of a keystone tropical plant. AoB Plants 10, plx076 (2018).
    Google Scholar 

    17.
    Brown, J. K. & Hovmøller, M. S. Aerial dispersal of pathogens on the global and continental scales and its impact on plant disease. Science 297, 537–541 (2002).
    CAS  Google Scholar 

    18.
    Vanschoenwinkel, B., Gielen, S., Seaman, M. & Brendonck, L. Any way the wind blows—frequent wind dispersal drives species sorting in ephemeral aquatic communities. Oikos 117, 125–134 (2008).
    Google Scholar 

    19.
    Ahmed, S., Compton, S. G., Butlin, R. K. & Gilmartin, P. M. Wind-borne insects mediate directional pollen transfer between desert fig trees 160 kilometers apart. Proc. Natl Acad. Sci. USA 106, 20342–20347 (2009).
    CAS  Google Scholar 

    20.
    Larson-Johnson, K. Field observations of Carpinus (Betulaceae) demonstrate high dispersal asymmetry and inform migration simulations with implications for times of rapid climate change. Int. J. Plant Sci. 177, 389–399 (2016).
    Google Scholar 

    21.
    Nathan, R. et al. Spread of North American wind‐dispersed trees in future environments. Ecol. Lett. 14, 211–219 (2011).
    Google Scholar 

    22.
    Sorte, C. J. Predicting persistence in a changing climate: flow direction and limitations to redistribution. Oikos 122, 161–170 (2013).
    Google Scholar 

    23.
    Loarie, S. R. et al. The velocity of climate change. Nature 462, 1052–1055 (2009).
    CAS  Google Scholar 

    24.
    Molinos, J. G., Burrows, M. T. & Poloczanska, E. S. Ocean currents modify the coupling between climate change and biogeographical shifts. Sci. Rep. 7, 1332 (2017).
    Google Scholar 

    25.
    Higgins, S. I. et al. Forecasting plant migration rates: managing uncertainty for risk assessment. J. Ecol. 91, 341–347 (2003).
    Google Scholar 

    26.
    Bullock, J. M. et al. Modelling spread of British wind‐dispersed plants under future wind speeds in a changing climate. J. Ecol. 100, 104–115 (2012).
    Google Scholar 

    27.
    Kuparinen, A., Katul, G., Nathan, R. & Schurr, F. M. Increases in air temperature can promote wind-driven dispersal and spread of plants. Proc. R. Soc. B 276, 3081–3087 (2009).
    Google Scholar 

    28.
    Davis, H. G., Taylor, C. M., Lambrinos, J. G. & Strong, D. R. Pollen limitation causes an Allee effect in a wind-pollinated invasive grass (Spartina alterniflora). Proc. Natl Acad. Sci. USA 101, 13804–13807 (2004).
    CAS  Google Scholar 

    29.
    Dullinger, S., Dirnböck, T. & Grabherr, G. Patterns of shrub invasion into high mountain grasslands of the Northern Calcareous Alps, Austria. Arct. Antarct. Alp. Res. 35, 434–441 (2003).
    Google Scholar 

    30.
    Payette, S. The range limit of boreal tree species in Québec-Labrador: an ecological and palaeoecological interpretation. Rev. Palaeobot. Palynol. 79, 7–30 (1993).
    Google Scholar 

    31.
    Sandel, B., Monnet, A. C., Govaerts, R. & Vorontsova, M. Late Quaternary climate stability and the origins and future of global grass endemism. Ann. Bot. 119, 279–288 (2016).
    Google Scholar 

    32.
    Svenning, J. C. & Skov, F. Could the tree diversity pattern in Europe be generated by postglacial dispersal limitation? Ecol. Lett. 10, 453–460 (2007).
    Google Scholar 

    33.
    Schurr, F. M. et al. Colonization and persistence ability explain the extent to which plant species fill their potential range. Glob. Ecol. Biogeogr. 16, 449–459 (2007).
    Google Scholar 

    34.
    Saha, S. et al. The NCEP Climate Forecast System Reanalysis. Bull. Am. Meteorol. Soc. 91, 1015–1058 (2010).
    Google Scholar 

    35.
    Hamann, A., Roberts, D. R., Barber, Q. E., Carroll, C. & Nielsen, S. E. Velocity of climate change algorithms for guiding conservation and management. Glob. Change Biol. 21, 997–1004 (2015).
    Google Scholar 

    36.
    Kling, M. M., Auer, S. L., Comer, P. J., Ackerly, D. D. & Hamilton, H. Multiple axes of ecological vulnerability to climate change. Glob. Change Biol. 26, 2798–2813 (2020).
    Google Scholar 

    37.
    Keeley, A. T. et al. New concepts, models, and assessments of climate-wise connectivity. Environ. Res. Lett. 13, 073002 (2018).
    Google Scholar 

    38.
    Savage, D., Barbetti, M. J., MacLeod, W. J., Salam, M. U. & Renton, M. Timing of propagule release significantly alters the deposition area of resulting aerial dispersal. Diversity Distrib. 16, 288–299 (2010).
    Google Scholar 

    39.
    Nathan, R. et al. Long‐distance biological transport processes through the air: can nature’s complexity be unfolded in silico? Divers. Distrib. 11, 131–137 (2005).
    Google Scholar 

    40.
    Zeller, K. A., McGarigal, K. & Whiteley, A. R. Estimating landscape resistance to movement: a review. Landsc. Ecol. 27, 777–797 (2012).
    Google Scholar 

    41.
    Treml, E. A., Halpin, P. N., Urban, D. L. & Pratson, L. F. Modeling population connectivity by ocean currents, a graph-theoretic approach for marine conservation. Landsc. Ecol. 23, 19–36 (2008).
    Google Scholar 

    42.
    Fernández‐López, J. & Schliep, K. rWind: download, edit and include wind data in ecological and evolutionary analysis. Ecography 42, 804–810 (2019).
    Google Scholar 

    43.
    Thompson, S. & Katul, G. Plant propagation fronts and wind dispersal: an analytical model to upscale from seconds to decades using superstatistics. Am. Naturalist 171, 468–479 (2008).
    Google Scholar 

    44.
    Savage, D., Barbetti, M. J., MacLeod, W. J., Salam, M. U. & Renton, M. Can mechanistically parameterised, anisotropic dispersal kernels provide a reliable estimate of wind-assisted dispersal? Ecol. Model. 222, 1673–1682 (2011).
    Google Scholar 

    45.
    Regal, P. J. Pollination by wind and animals: ecology of geographic patterns. Annu. Rev. Ecol. Syst. 13, 497–524 (1982).
    Google Scholar 

    46.
    Carroll, C., Lawler, J. J., Roberts, D. R. & Hamann, A. Biotic and climatic velocity identify contrasting areas of vulnerability to climate change. PLoS ONE 10, e0140486 (2015).
    Google Scholar 

    47.
    Jackson, S. T. & Sax, D. F. Balancing biodiversity in a changing environment: extinction debt, immigration credit and species turnover. Trends Ecol. Evol. 25, 153–160 (2010).
    Google Scholar 

    48.
    Ackerly, D. D. et al. The geography of climate change: implications for conservation biogeography. Divers. Distrib. 16, 476–487 (2010).
    Google Scholar 

    49.
    Owens, J. N. The Reproductive Biology of Lodgepole Pine Extension Note 07 (Forest Genetics Council of British Columbia, 2006).

    50.
    Bontrager, M. & Angert, A. L. Gene flow improves fitness at a range edge under climate change. Evol. Lett. 3, 55–68 (2019).
    Google Scholar 

    51.
    Sexton, J. P., Strauss, S. Y. & Rice, K. J. Gene flow increases fitness at the warm edge of a species’ range. Proc. Natl Acad. Sci. USA 108, 11704–11709 (2011).
    CAS  Google Scholar 

    52.
    Rehfeldt, G. E., Ying, C. C., Spittlehouse, D. L. & Hamilton, D. A. Jr Genetic responses to climate in Pinus contorta: niche breadth, climate change, and reforestation. Ecol. Monogr. 69, 375–407 (1999).
    Google Scholar 

    53.
    Wang, T., O’Neill, G. A. & Aitken, S. N. Integrating environmental and genetic effects to predict responses of tree populations to climate. Ecol. Appl. 20, 153–163 (2010).
    CAS  Google Scholar 

    54.
    Karger, D. N. et al. Climatologies at high resolution for the Earth’s land surface areas. Sci. Data 4, 170122 (2017).
    Google Scholar 

    55.
    Dobrowski, S. Z. et al. The climate velocity of the contiguous United States during the 20th century. Glob. Change Biol. 19, 241–251 (2013).
    Google Scholar 

    56.
    van Etten, J. R Package gdistance: distances and routes on geographical grids. J. Stat. Softw. 76, 1–21 (2017).
    Google Scholar 

    57.
    IPCC Special Report on Global Warming of 1.5 °C (eds Masson-Delmotte, V. et al.) (WMO, 2018).

    58.
    Schleussner, C. F. et al. Differential climate impacts for policy-relevant limits to global warming: the case of 1.5 °C and 2 °C. Earth Syst. Dyn. 7, 327–351 (2016).
    Google Scholar 

    59.
    Little, E. L. Jr Atlas of United States Trees. Volume 1, Conifers and Important Hardwoods Miscellaneous Publication 1146 (US Department of Agriculture, 1971).

    60.
    Wang, T., Hamann, A., Yanchuk, A., O’Neill, G. A. & Aitken, S. N. Use of response functions in selecting lodgepole pine populations for future climates. Glob. Change Biol. 12, 2404–2416 (2006).
    Google Scholar 

    61.
    Phillips, S. J., Anderson, R. P. & Schapire, R. E. Maximum entropy modeling of species geographic distributions. Ecol. Model. 190, 231–259 (2006).
    Google Scholar 

    62.
    Taylor, K. E., Stouffer, R. J. & Meehl, G. A. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 93, 485–498 (2012).
    Google Scholar 

    63.
    R Core Team (2017). R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2017); https://www.R-project.org/

    64.
    Kling, M. M. & Ackerly, D. D. Scripts and Data used in ‘Global Wind Patterns and the Vulnerability of Wind-Dispersed Species to Climate Change (Zenodo Repository, 2020); https://doi.org/10.5281/zenodo.3860687

    65.
    Kling, M. M. Windscape R Package v.1.0.0 (Zenodo Repository, 2020); https://doi.org/10.5281/zenodo.3857730 More