More stories

  • in

    Unexpected myriad of co-occurring viral strains and species in one of the most abundant and microdiverse viruses on Earth

    1.Roux S, Adriaenssens EM, Dutilh BE, Koonin EV, Kropinski AM, Krupovic M, et al. Minimum information about an uncultivated virus genome (MIUVIG). Nat Biotechnol 2019;37:29–37.PubMed 

    Google Scholar 
    2.Paez-Espino D, Eloe-Fadrosh EA, Pavlopoulos GA, Thomas AD, Huntemann M, Mikhailova N, et al. Uncovering Earth’s virome. Nature. 2016;536:425–30.PubMed 

    Google Scholar 
    3.Gregory AC, Zayed AA, Conceição-Neto N, Temperton B, Bolduc B, Alberti A, et al. Marine DNA viral macro- and microdiversity from pole to pole. Cell. 2019;177:1109–23.PubMed 
    PubMed Central 

    Google Scholar 
    4.Kavagutti VS, Andrei AŞ, Mehrshad M, Salcher MM, Ghai R. Phage-centric ecological interactions in aquatic ecosystems revealed through ultra-deep metagenomics. Microbiome. 2019;7:1–15.
    Google Scholar 
    5.Schulz F, Alteio L, Goudeau D, Ryan EM, Yu FB, Malmstrom RR, et al. Hidden diversity of soil giant viruses. Nat Commun 2018;9:1–9.
    Google Scholar 
    6.Trubl G, Jang H Bin, Roux S, Emerson JB, Solonenko N, Vik DR, et al. Soil viruses are underexplored players in ecosystem carbon processing. mSystems 2018;3:e00076–18.PubMed 
    PubMed Central 

    Google Scholar 
    7.Guerin E, Shkoporov A, Stockdale SR, Clooney AG, Ryan FJ, Sutton TDS, et al. Biology and taxonomy of crAss-like bacteriophages, the most abundant virus in the human gut. Cell Host Microbe. 2018;24:653–664.e6.PubMed 

    Google Scholar 
    8.Martinez-Hernandez F, Fornas O, Lluesma Gomez M, Bolduc B, de la Cruz Peña MJ, Martínez JM, et al. Single-virus genomics reveals hidden cosmopolitan and abundant viruses. Nat Commun 2017;8:1–13.
    Google Scholar 
    9.Aguirre de Cárcer D, Angly FE, Alcamí A. Evaluation of viral genome assembly and diversity estimation in deep metagenomes. BMC Genomics. 2014;15:1–12.
    Google Scholar 
    10.Roux S, Emerson JB, Eloe-Fadrosh EA, Sullivan MB. Benchmarking viromics: an in silico evaluation of metagenome-enabled estimates of viral community composition and diversity. PeerJ. 2017;5:e3817.PubMed 
    PubMed Central 

    Google Scholar 
    11.Avrani S, Wurtzel O, Sharon I, Sorek R, Lindell D. Genomic island variability facilitates Prochlorococcus-virus coexistence. Nature. 2011;474:604–8.PubMed 

    Google Scholar 
    12.Rodriguez-Valera F, Martin-Cuadrado A-B, Rodriguez-Brito B, Pasic L, Thingstad TF, Rohwer F, et al. Explaining microbial population genomics through phage predation. Nat Rev Microbiol 2009;7:828–36.PubMed 

    Google Scholar 
    13.Marston MF, Pierciey FJ, Shepard A, Gearin G, Qi J, Yandava C, et al. Rapid diversification of coevolving marine Synechococcus and a virus. Proc Natl Acad Sci USA 2012;109:4544–9.PubMed 
    PubMed Central 

    Google Scholar 
    14.Enav H, Kirzner S, Lindell D, Mandel-Gutfreund Y, Béjà O. Adapt sub-Optim hosts is a Driv viral Diversif ocean Nat Comm 2018;9:1–11.
    Google Scholar 
    15.Boon M, Holtappels D, Lood C, van Noort V, Lavigne R. Host range expansion of pseudomonas virus LUZ7 is driven by a conserved tail fiber mutation. PHAGE. 2020;1:87–90.
    Google Scholar 
    16.Bernheim A, Sorek R. The pan-immune system of bacteria: antiviral defence as a community resource. Nat Rev Microbiol 2020;18:113–9.PubMed 

    Google Scholar 
    17.Sørensen MA, Kurland CG, Pedersen S. Codon usage determines translation rate in Escherichia coli. J Mol Biol 1989;207:365–77.PubMed 

    Google Scholar 
    18.Varenne S, Buc J, Lloubes R, Lazdunski C. Translation is a non-uniform process. Effect of tRNA availability on the rate of elongation of nascent polypeptide chains. J Mol Biol 1984;180:549–76.PubMed 

    Google Scholar 
    19.Yu CH, Dang Y, Zhou Z, Wu C, Zhao F, Sachs MS, et al. Codon Usage Influences the Local Rate of Translation Elongation to Regulate Co-translational Protein Folding. Mol Cell. 2015;59:744–54.PubMed 
    PubMed Central 

    Google Scholar 
    20.Plotkin JB, Kudla G. Synonymous but not the same: The causes and consequences of codon bias. Nat Rev Genet 2011;12:32–42.PubMed 

    Google Scholar 
    21.Chu D, Wei L. Nonsynonymous, synonymous and nonsense mutations in human cancer-related genes undergo stronger purifying selections than expectation. BMC Cancer. 2019;19:359.PubMed 
    PubMed Central 

    Google Scholar 
    22.Deng L, Ignacio-Espinoza JC, Gregory AC, Poulos BT, Weitz JS, Hugenholtz P, et al. Viral tagging reveals discrete populations in Synechococcus viral genome sequence space. Nature. 2014;513:242–5.PubMed 

    Google Scholar 
    23.Edwards RA, Vega AA, Norman HM, Ohaeri M, Levi K, Dinsdale EA, et al. Global phylogeography and ancient evolution of the widespread human gut virus crAssphage. Nat Microbiol 2019;4:1727–36.PubMed 
    PubMed Central 

    Google Scholar 
    24.Ignacio-Espinoza JC, Ahlgren NA, Fuhrman JA. Long-term stability and Red Queen-like strain dynamics in marine viruses. Nat. Microbiol. 2019;5:1–7.25.Coutinho FH, Rosselli R, Rodríguez-Valera F. Trends of microdiversity reveal depth-dependent evolutionary strategies of viruses in the Mediterranean. mSystems. 2019;4:1–17.
    Google Scholar 
    26.Needham DM, Sachdeva R, Fuhrman JA. Ecological dynamics and co-occurrence among marine phytoplankton, bacteria and myoviruses shows microdiversity matters. ISME J. 2017;11:1614–29.PubMed 
    PubMed Central 

    Google Scholar 
    27.Martinez-Hernandez F, Fornas Ò, Lluesma Gomez M, Garcia-Heredia I, Maestre-Carballa L, López-Pérez M, et al. Single-cell genomics uncover Pelagibacter as the putative host of the extremely abundant uncultured 37-F6 viral population in the ocean. ISME J. 2019;13:232–6.PubMed 

    Google Scholar 
    28.McMullen A, Martinez‐Hernandez F, Martinez‐Garcia M. Absolute quantification of infecting viral particles by chip‐based digital polymerase chain reaction. Environ Microbiol Rep. 2019;11:855–60.PubMed 

    Google Scholar 
    29.Marston MF, Amrich CG. Recombination and microdiversity in coastal marine cyanophages. Environ Microbiol. 2009;11:2893–903.PubMed 

    Google Scholar 
    30.Marston MF, Martiny JBH. Genomic diversification of marine cyanophages into stable ecotypes. Environ Microbiol 2016;18:4240–53.PubMed 

    Google Scholar 
    31.Cordero OX. Endemic cyanophages and the puzzle of phage-bacteria coevolution. Environ Microbiol 2017;19:420–2.PubMed 

    Google Scholar 
    32.Shannon CE. The mathematical theory of communication. 1963. MD Comput. 1997;14:306–17.PubMed 

    Google Scholar 
    33.Roux S, Brum JR, Dutilh BE, Sunagawa S, Duhaime MB, Loy A, et al. Ecogenomics and potential biogeochemical impacts of globally abundant ocean viruses. Nature. 2016;537:689–93.PubMed 

    Google Scholar 
    34.Bobay L-M, Ochman H. Biological species in the viral world. Proc Natl Acad Sci USA 2018;115:6040–5.PubMed 
    PubMed Central 

    Google Scholar 
    35.Henson MW, Lanclos VC, Faircloth BC, Thrash JC. Cultivation and genomics of the first freshwater SAR11 (LD12) isolate. ISME J. 2018;12:1846–60.PubMed 
    PubMed Central 

    Google Scholar 
    36.Paez-Espino D, Roux S, Chen I-MA, Palaniappan K, Ratner A, Chu K, et al. IMG/VR v.2.0: an integrated data management and analysis system for cultivated and environmental viral genomes. Nucleic Acids Res. 2019;47:D678–D686.PubMed 

    Google Scholar 
    37.Brum JR, Ignacio-Espinoza JC, Kim E-H, Trubl G, Jones RM, Roux S, et al. Illuminating structural proteins in viral ‘dark matter’ with metaproteomics. Proc Natl Acad Sci USA 2016;113:2436–41.PubMed 
    PubMed Central 

    Google Scholar 
    38.Sakowski EG, Arora-Williams K, Tian F, Zayed AA, Zablocki O, Sullivan MB, et al. Interaction dynamics and virus–host range for estuarine actinophages captured by epicPCR. Nat. Microbiol. 2021;6:1–13.39.Alonso-Sáez L, Morán XAG, Clokie MR. Low activity of lytic pelagiphages in coastal marine waters. ISME J. 2018;12:2100–2.PubMed 
    PubMed Central 

    Google Scholar 
    40.Martinez‐Hernandez F, Luo E, Tominaga K, Ogata H, Yoshida T, DeLong EF, et al. Diel cycling of the cosmopolitan abundant Pelagibacter virus 37‐F6: one of the most abundant viruses in Earth. Environ Microbiol Rep. 2020;12:214–21941.Mruwat N, Carlson MCG, Goldin S, Ribalet F, Kirzner S, Hulata Y, et al. A single-cell polony method reveals low levels of infected Prochlorococcus in oligotrophic waters despite high cyanophage abundances. ISME J. 2021;15:41–54.PubMed 

    Google Scholar 
    42.de Avila e Silva S, Echeverrigaray S, Gerhardt GJL. BacPP: bacterial promoter prediction-A tool for accurate sigma-factor specific assignment in enterobacteria. J Theor Biol 2011;287:92–99.PubMed 

    Google Scholar 
    43.Sampaio M, Rocha M, Oliveira H, Dias O. Predicting promoters in phage genomes using PhagePromoter. Bioinformatics. 2019;35:5301–2.PubMed 

    Google Scholar 
    44.Allert M, Cox JC, Hellinga HW. Multifactorial determinants of protein expression in prokaryotic open reading frames. J Mol Biol. 2010;402:905–18.PubMed 
    PubMed Central 

    Google Scholar 
    45.Dressaire C, Picard F, Redon E, Loubière P, Queinnec I, Girbal L, et al. Role of mRNA stability during bacterial adaptation. PLoS ONE 2013;8:e59059.PubMed 
    PubMed Central 

    Google Scholar 
    46.Deana A, Belasco JG. Lost in translation: The influence of ribosomes on bacterial mRNA decay. Genes Dev. 2005;19:2526–33.PubMed 

    Google Scholar 
    47.Zhao Y, Temperton B, Thrash JC, Schwalbach MS, Vergin KL, Landry ZC, et al. Abundant SAR11 viruses in the ocean. Nature. 2013;494:357–60.PubMed 

    Google Scholar 
    48.Zhang Z, Qin F, Chen F, Chu X, Luo H, Zhang R, et al. Culturing novel and abundant pelagiphages in the ocean. Environ Microbiol 2020;1462-2920:15272.
    Google Scholar 
    49.Zhao Y, Qin F, Zhang R, Giovannoni SJ, Zhang Z, Sun J, et al. Pelagiphages in the Podoviridae family integrate into host genomes. Environ Microbiol. 2018;21:1989–2001.50.Morris RM, Cain KR, Hvorecny KL, Kollman JM. Lysogenic host–virus interactions in SAR11 marine bacteria. Nat Microbiol 2020;5:1011–5.PubMed 
    PubMed Central 

    Google Scholar 
    51.Konstantinidis KT, Ramette A, Tiedje JM. The bacterial species definition in the genomic era. Philos Trans R Soc Lond, B, Biol Sci 2006;361:1929–40.
    Google Scholar 
    52.Rosselló-Mora R. Updating prokaryotic taxonomy. J Bacteriol. 2005;187:6255–7.PubMed 
    PubMed Central 

    Google Scholar 
    53.Parks DH, Rinke C, Chuvochina M, Chaumeil P-A, Woodcroft BJ, Evans PN, et al. Recovery of nearly 8,000 metagenome-assembled genomes substantially expands the tree of life. Nat Microbiol 2017;2:1533–42.PubMed 

    Google Scholar 
    54.Richter M, Rossello-Mora R. Shifting the genomic gold standard for the prokaryotic species definition. Proc Natl Acad Sci 2009;106:19126–31.PubMed 
    PubMed Central 

    Google Scholar 
    55.Pope WH, Bowman CA, Russell DA, Jacobs-Sera D, Asai DJ, Cresawn SG, et al. Whole genome comparison of a large collection of mycobacteriophages reveals a continuum of phage genetic diversity. eLife 2015;4:e06416.PubMed 
    PubMed Central 

    Google Scholar 
    56.Gregory AC, Solonenko SA, Ignacio-Espinoza JC, LaButti K, Copeland A, Sudek S, et al. Genomic differentiation among wild cyanophages despite widespread horizontal gene transfer. BMC genomics. 2016;17:930.PubMed 
    PubMed Central 

    Google Scholar 
    57.Martinez-Hernandez F, Garcia-Heredia I, Lluesma Gomez M, Maestre-Carballa L, Martínez Martínez J, Martinez-Garcia M. Droplet digital PCR for estimating absolute abundances of widespread Pelagibacter viruses. Front Microbiol 2019;10:1226.PubMed 
    PubMed Central 

    Google Scholar 
    58.Warwick-Dugdale J, Solonenko N, Moore K, Chittick L, Gregory AC, Allen MJ, et al. Long-read viral metagenomics captures abundant and microdiverse viral populations and their niche-defining genomic islands. PeerJ. 2019;7:e6800.PubMed 
    PubMed Central 

    Google Scholar 
    59.Beaulaurier J, Luo E, Eppley JM, Uyl P Den, Dai X, Burger A, et al. Assembly-free single-molecule sequencing recovers complete virus genomes from natural microbial communities. Genome Res. 2020;30:437–46.PubMed 
    PubMed Central 

    Google Scholar 
    60.Murigneux V, Rai SK, Furtado A, Bruxner TJC, Tian W, Harliwong I, et al. Comparison of long-read methods for sequencing and assembly of a plant genome. GigaScience 2020;9:giaa146.61.Wenger AM, Peluso P, Rowell WJ, Chang PC, Hall RJ, Concepcion GT, et al. Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome. Nat Biotechnol 2019;37:1155–62.PubMed 
    PubMed Central 

    Google Scholar 
    62.Martínez Martínez J, Martinez-Hernandez F, Martinez-Garcia M. Single-virus genomics and beyond. Nat Rev Microbiol. 2020;18:705–16.PubMed 

    Google Scholar 
    63.Labonté JM, Swan BK, Poulos B, Luo H, Koren S, Hallam SJ, et al. Single-cell genomics-based analysis of virus-host interactions in marine surface bacterioplankton. ISME J. 2015;9:2386–99.PubMed 
    PubMed Central 

    Google Scholar 
    64.Mizuno CM, Rodriguez-Valera F, Kimes NE, Ghai R. Expanding the marine virosphere using metagenomics. PLoS Genet. 2013;9:e1003987.PubMed 
    PubMed Central 

    Google Scholar 
    65.Mizuno CM, Ghai R, Saghaï A, López-García P, Rodriguez-Valera F. Genomes of abundant and widespread viruses from the deep ocean. mBio. 2016;7:e00805–16.PubMed 
    PubMed Central 

    Google Scholar 
    66.Ye J, Coulouris G, Zaretskaya I, Cutcutache I, Rozen S, Madden TL. Primer-BLAST: a tool to design target-specific primers for polymerase chain reaction. BMC Bioinforma. 2012;13:134.
    Google Scholar 
    67.Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–20.PubMed 
    PubMed Central 

    Google Scholar 
    68.Li W, Godzik A. Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics. 2006;22:1658–9.PubMed 

    Google Scholar 
    69.Philosof A, Yutin N, Flores-Uribe J, Sharon I, Koonin EV, Béjà O. Novel abundant oceanic viruses of uncultured marine group II Euryarchaeota. Curr Biol. 2017;27:1362–8.PubMed 
    PubMed Central 

    Google Scholar 
    70.Vik DR, Roux S, Brum JR, Bolduc B, Emerson JB, Padilla CC, et al. Putative archaeal viruses from the mesopelagic ocean. PeerJ. 2017;5:e3428.PubMed 
    PubMed Central 

    Google Scholar 
    71.Bin Jang H, Bolduc B, Zablocki O, Kuhn JH, Roux S, Adriaenssens EM, et al. Taxonomic assignment of uncultivated prokaryotic virus genomes is enabled by gene-sharing networks. Nat Biotechnol 2019;37:632–9.
    Google Scholar 
    72.Bobay L-M, Ellis BS-H, Ochman H. ConSpeciFix: classifying prokaryotic species based on gene flow. Bioinformatics. 2018;34:3738–40.PubMed 
    PubMed Central 

    Google Scholar 
    73.Bobay L-M, Ochman H. Biological species are universal across life’s domains. Genome Biol Evol. 2017;9:491–501.PubMed Central 

    Google Scholar 
    74.Hyatt D, Chen G-L, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinforma. 2010;11:119.
    Google Scholar 
    75.Edgar RC. Search and clustering orders of magnitude faster than BLAST. Bioinformatics. 2010;26:2460–1.PubMed 
    PubMed Central 

    Google Scholar 
    76.Harris CD, Torrance EL, Raymann K, Bobay L-M. CoreCruncher: Fast and robust construction of core genomes in large prokaryotic data sets. Mol. Biol. Evol. 2020;38:727–734.77.Edgar RC. MUSCLE: Multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004;32:1792–7.PubMed 
    PubMed Central 

    Google Scholar 
    78.Rice P, Longden L, Bleasby A EMBOSS: The European Molecular Biology Open Software Suite. Trends Genet. 2000. Elsevier Ltd., 16: 276–779.Džunková M, Low SJ, Daly JN, Deng L, Rinke C, Hugenholtz P. Defining the human gut host–phage network through single-cell viral tagging. Nat Microbiol 2019;4:2192–203.PubMed 

    Google Scholar 
    80.Price MN, Dehal PS, Arkin AP. FastTree 2 – approximately maximum-likelihood trees for large alignments. PLoS ONE. 2010;5:e9490.PubMed 
    PubMed Central 

    Google Scholar 
    81.Stamatakis A. RAxML version 8: A tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics. 2014;30:1312–3.PubMed 
    PubMed Central 

    Google Scholar 
    82.Swan BK, Ehrhardt CJ, Reifel KM, Moreno LI, Valentine DL. Archaeal and bacterial communities respond differently to environmental gradients in anoxic sediments of a california hypersaline lake, the Salton Sea. Appl Environ Microbiol 2010;76:757–68.PubMed 

    Google Scholar 
    83.Baran N, Goldin S, Maidanik I, Lindell D. Quantification of diverse virus populations in the environment using the polony method. Nat Microbiol 2018;3:62–72.PubMed 

    Google Scholar  More

  • in

    Horizontal gene transfer and adaptive evolution in bacteria

    1.Maynard Smith, J., Feil, E. J. & Smith, N. H. Population structure and evolutionary dynamics of pathogenic bacteria. Bioessays 22, 1115–1122 (2000).
    Google Scholar 
    2.Garud, N. R., Good, B. H., Hallatschek, O. & Pollard, K. S. Evolutionary dynamics of bacteria in the gut microbiome within and across hosts. PLoS Biol. 17, e3000102 (2019). Using metagenomic samples form the human gut microbiome, the authors infer lineage structure from within-host polymorphisms in more than 40 species to show adaptation on short timescales can be seeded by HGT.PubMed 
    PubMed Central 

    Google Scholar 
    3.Frazão, N., Sousa, A., Lässig, M. & Gordo, I. Horizontal gene transfer overrides mutation in Escherichia coli colonizing the mammalian gut. Proc. Natl Acad. Sci. USA 116, 17906–17915 (2019). Using the mouse microbiome as a study system, the authors show that rapid, phage-mediated HGT can transfer beneficial genes — already present in a resident strain — to an invading strain.PubMed 
    PubMed Central 

    Google Scholar 
    4.Smith, J. M., Smith, N. H., O’Rourke, M. & Spratt, B. G. How clonal are bacteria? Proc. Natl Acad. Sci. USA 90, 4384–4388 (1993).PubMed 
    PubMed Central 

    Google Scholar 
    5.Dykhuizen, D. E. & Green, L. Recombination in Escherichia coli and the definition of biological species. J. Bacteriol. 173, 7257–7268 (1991).PubMed 
    PubMed Central 

    Google Scholar 
    6.Feil, E. J. et al. Recombination within natural populations of pathogenic bacteria: short-term empirical estimates and long-term phylogenetic consequences. Proc. Natl Acad. Sci. USA 98, 182–187 (2001).PubMed 
    PubMed Central 

    Google Scholar 
    7.Suerbaum, S. et al. Free recombination within Helicobacter pylori. PNAS 95, 12619–12624 (1998).PubMed 
    PubMed Central 

    Google Scholar 
    8.Smillie, C. S. et al. Ecology drives a global network of gene exchange connecting the human microbiome. Nature 480, 241–244 (2011).PubMed 

    Google Scholar 
    9.Lozupone, C. A. et al. The convergence of carbohydrate active gene repertoires in human gut microbes. Proc. Natl Acad. Sci. USA 105, 15076–15081 (2008).PubMed 
    PubMed Central 

    Google Scholar 
    10.Bradley, P. H., Nayfach, S. & Pollard, K. S. Phylogeny-corrected identification of microbial gene families relevant to human gut colonization. PLoS Computational Biol. 14, e1006242 (2018). The authors use phylogenetic linear regression to control for important confounders and identify genes potentially involved in adaptation to the human gut.
    Google Scholar 
    11.Andreani, N. A., Hesse, E. & Vos, M. Prokaryote genome fluidity is dependent on effective population size. ISME J. 11, 1719–1721 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    12.Mcinerney, J. O., Mcnally, A. & Connell, M. J. O. Why prokaryotes have pangenomes. Nat. Publ. Gr. 2, 1–5 (2017).
    Google Scholar 
    13.Shapiro, B. J. The population genetics of pangenomes. Nat. Microbiol. 2, 1005860 (2017).
    Google Scholar 
    14.Vos, M. & Eyre-walker, A. Are pangenomes adaptive or not? Nat. Microbiol. https://doi.org/10.1038/s41564-017-0067-5 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    15.Johnsborg, O., Eldholm, V. & Håvarstein, L. S. Natural genetic transformation: prevalence, mechanisms and function. Res. Microbiol. 158, 767–778 (2007).PubMed 

    Google Scholar 
    16.Johnston, C., Martin, B., Fichant, G., Polard, P. & Claverys, J. P. Bacterial transformation: distribution, shared mechanisms and divergent control. Nat. Rev. Microbiol. 12, 181–196 (2014).PubMed 

    Google Scholar 
    17.Pimentel, Z. T. & Zhang, Y. Evolution of the natural transformation protein, ComEC, in Bacteria. Front. Microbiol. 9, 1–10 (2018).
    Google Scholar 
    18.Roux, S., Hallam, S. J., Woyke, T. & Sullivan, M. B. Viral dark matter and virus–host interactions resolved from publicly available microbial genomes. eLife 4, 1–20 (2015).
    Google Scholar 
    19.Camarillo-Guerrero, L. F. et al. Massive expansion of human gut bacteriophage diversity. Cell 184, 1098–1109.e9 (2021).PubMed 
    PubMed Central 

    Google Scholar 
    20.Guglielmini, J., Quintais, L., Garcillán-Barcia, M. P., de la Cruz, F. & Rocha, E. P. C. The repertoire of ice in prokaryotes underscores the unity, diversity, and ubiquity of conjugation. PLoS Genet. 7, e1002222 (2011).PubMed 
    PubMed Central 

    Google Scholar 
    21.Dubey, G. P. & Ben-Yehuda, S. Intercellular nanotubes mediate bacterial communication. Cell 144, 590–600 (2011).PubMed 

    Google Scholar 
    22.Abe, K., Nomura, N. & Suzuki, S. Biofilms: hot spots of horizontal gene transfer (HGT) in aquatic environments, with a focus on a new HGT mechanism. FEMS Microbiol. Ecol. 96, 1–12 (2020).
    Google Scholar 
    23.Bárdy, P. et al. Structure and mechanism of DNA delivery of a gene transfer agent. Nat. Commun. 11, 3034 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    24.Hasegawa, H., Suzuki, E. & Maeda, S. Horizontal plasmid transfer by transformation in Escherichia coli: environmental factors and possible mechanisms. Front. Microbiol. 9, 1–6 (2018).
    Google Scholar 
    25.Seitz, P. & Blokesch, M. Cues and regulatory pathways involved in natural competence and transformation in pathogenic and environmental Gram-negative bacteria. FEMS Microbiol. Rev. 37, 336–363 (2013).PubMed 

    Google Scholar 
    26.Wall, D. Kin recognition in bacteria. Annu. Rev. Microbiol. 70, 143–160 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    27.Frye, S. A., Nilsen, M., Tønjum, T. & Ambur, O. H. Dialects of the DNA uptake sequence in Neisseriaceae. PLoS Genet. https://doi.org/10.1371/journal.pgen.1003458 (2013).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    28.Redfield, R. J. et al. Evolution of competence and DNA uptake specificity in the Pasteurellaceae. BMC Evol. Biol. 6, 1–15 (2006).
    Google Scholar 
    29.Dion, M. B., Oechslin, F. & Moineau, S. Phage diversity, genomics and phylogeny. Nat. Rev. Microbiol. https://doi.org/10.1038/s41579-019-0311-5 (2020).Article 
    PubMed 

    Google Scholar 
    30.Siguier, P., Gourbeyre, E. & Chandler, M. Bacterial insertion sequences: their genomic impact and diversity. FEMS Microbiol. Rev. 38, 865–891 (2014).PubMed 

    Google Scholar 
    31.Vulić, M., Dionisio, F., Taddei, F. & Radman, M. Molecular keys to speciation: DNA polymorphism and the control of genetic exchange in enterobacteria. Proc. Natl Acad. Sci. USA 94, 9763–9767 (1997).PubMed 
    PubMed Central 

    Google Scholar 
    32.Majewski, J. et al. Barriers to genetic exchange between bacterial species: Streptococcus pneumoniae transformation. J. Bacteriol. 182, 1016–1023 (2000).PubMed 
    PubMed Central 

    Google Scholar 
    33.Wyres, K. L. et al. Pneumococcal capsular switching: a historical perspective. J. Infect. Dis. 207, 439–449 (2013).PubMed 

    Google Scholar 
    34.Hallet, B. & Sherratt, D. J. Transposition and site-specific recombination: adapting DNA cut-and-paste mechanisms to a variety of genetic rearrangements. FEMS Microbiol. Rev. 21, 157–178 (1997).PubMed 

    Google Scholar 
    35.Durrant, M. G., Li, M. M., Siranosian, B. A., Montgomery, S. B. & Bhatt, A. S. A bioinformatic analysis of integrative mobile genetic elements highlights their role in bacterial adaptation. Cell Host Microbe 27, 140–153.e9 (2020).PubMed 

    Google Scholar 
    36.Rajeev, L., Malanowska, K. & Gardner, J. F. Challenging a paradigm: the role of DNA homology in tyrosine recombinase reactions. Microbiol. Mol. Biol. Rev. 73, 300–309 (2009).PubMed 
    PubMed Central 

    Google Scholar 
    37.Hickman, A. B., Chandler, M. & Dyda, F. Integrating prokaryotes and eukaryotes: DNA transposases in light of structure. Crit. Rev. Biochem. Mol. Biol. 45, 50–69 (2010).PubMed 
    PubMed Central 

    Google Scholar 
    38.Oliveira, P. H., Touchon, M., Cury, J. & Rocha, E. P. C. The chromosomal organization of horizontal gene transfer in bacteria. Nat. Commun. 8, 1–10 (2017).
    Google Scholar 
    39.Wadsworth, C. B., Arnold, B. J., Sater, M. R. A. & Grad, Y. Azithromycin resistance through interspecific acquisition of an epistasis-dependent efflux pump component and transcriptional regulator in Neisseria gonorrhoeae. mBio 9, 1–17 (2018).
    Google Scholar 
    40.Arevalo, P., VanInsberghe, D., Elsherbini, J., Gore, J. & Polz, M. F. A reverse ecology approach based on a biological definition of microbial populations. Cell 178, 820–834.e14 (2019). The authors create a metric of recent gene flow to define ecological populations and discover genes that have experienced positive selection across populations.PubMed 

    Google Scholar 
    41.Croucher, N. J. et al. Horizontal DNA transfer mechanisms of bacteria as weapons of intragenomic conflict. PLoS Biol. 14, 1–42 (2016). A model of transformation with known bias towards the acquisition of shorter alleles suggests HGT may effectively purge bacterial genomes of parasitic MGEs.
    Google Scholar 
    42.Apagyi, K. J., Fraser, C. & Croucher, N. J. Transformation asymmetry and the evolution of the bacterial accessory genome. Mol. Biol. Evol. 35, 575–581 (2018).PubMed 

    Google Scholar 
    43.Mira, A., Ochman, H. & Moran, N. A. Deletional bias and the evolution of bacterial genomes. Trends Genet. 17, 589–596 (2001).PubMed 

    Google Scholar 
    44.Kuo, C.-H. & Ochman, H. Deletional bias across the three domains of life. Genome Biol. Evol. 1, 145–152 (2009).PubMed 
    PubMed Central 

    Google Scholar 
    45.Lawrence, J. G. & Roth, J. R. Selfish operons: horizontal transfer may drive the evolution of gene clusters. Genetics 143, 1843–1860 (1996).PubMed 
    PubMed Central 

    Google Scholar 
    46.Hehemann, J. H. et al. Transfer of carbohydrate-active enzymes from marine bacteria to Japanese gut microbiota. Nature 464, 908–912 (2010).PubMed 

    Google Scholar 
    47.Campbell, A. Prophage insertion sites. Res. Microbiol. 154, 277–282 (2003).PubMed 

    Google Scholar 
    48.Chu, N. D. et al. A mobile element in mutS drives hypermutation in a marine Vibrio. mBio 8, 1–13 (2017).
    Google Scholar 
    49.Bobay, L. M., Rocha, E. P. C. & Touchon, M. The adaptation of temperate bacteriophages to their host genomes. Mol. Biol. Evol. 30, 737–751 (2013).PubMed 

    Google Scholar 
    50.Lee, H., Doak, T. G., Popodi, E., Foster, P. L. & Tang, H. Insertion sequence-caused large-scale rearrangements in the genome of Escherichia coli. Nucleic Acids Res. 44, 7109–7119 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    51.Parkhill, J. et al. Comparative analysis of the genome sequences of Bordetella pertussis, Bordetella parapertussis and Bordetella bronchiseptica. Nat. Genet. 35, 32–40 (2003).PubMed 

    Google Scholar 
    52.Moran, N. A. & Plague, G. R. Genomic changes following host restriction in bacteria. Curr. Opin. Genet. Dev. 14, 627–633 (2004).PubMed 

    Google Scholar 
    53.Hendry, T. et al. Ongoing transposon-mediated genome reduction in the luminous bacterial symbionts of deep-sea ceratioid anglerfishes. mBio https://doi.org/10.1128/mBio.01033-18 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    54.Waterworth, S. C. et al. Horizontal gene transfer to a defensive symbiont with a reduced genome in a multipartite beetle microbiome. mBio https://doi.org/10.1128/mBio.02430-19 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    55.Vos, M. et al. Rates of lateral gene transfer in prokaryotes: high but why? Trends Microbiol. 23, 598–605 (2015).PubMed 

    Google Scholar 
    56.Cohen, E., Kessler, D. A. & Levine, H. Recombination dramatically speeds up evolution of finite populations. Phys. Rev. Lett. 94, 1–4 (2005).
    Google Scholar 
    57.Levin, B. R. & Cornejo, O. E. The population and evolutionary dynamics of homologous gene recombination in bacteria. PLoS Genet. https://doi.org/10.1371/journal.pgen.1000601 (2009).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    58.Arnold, B. J. et al. Weak epistasis may drive adaptation in recombining bacteria. Genetics 208, 1247–1260 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    59.Moradigaravand, D. & Engelstädter, J. The effect of bacterial recombination on adaptation on fitness landscapes with limited peak accessibility. PLoS Comput. Biol. 8, 35–37 (2012).
    Google Scholar 
    60.Cooper, T. F. Recombination speeds adaptation by reducing competition between beneficial mutations in populations of Escherichia coli. PLoS Biol. 5, 1899–1905 (2007).
    Google Scholar 
    61.Winkler, J. & Kao, K. C. Harnessing recombination to speed adaptive evolution in Escherichia coli. Metab. Eng. 14, 487–495 (2012).PubMed 

    Google Scholar 
    62.Chu, H. Y., Sprouffske, K. & Wagner, A. The role of recombination in evolutionary adaptation of Escherichia coli to a novel nutrient. J. Evol. Biol. 30, 1692–1711 (2017).PubMed 

    Google Scholar 
    63.Arnold, B. et al. Fine-scale haplotype structure reveals strong signatures of positive selection in a recombining bacterial pathogen. Mol. Biol. Evol. https://doi.org/10.1093/molbev/msz225 (2019).Article 
    PubMed Central 

    Google Scholar 
    64.Yahara, K. et al. The landscape of realized homologous recombination in pathogenic bacteria. Mol. Biol. Evol. 33, 456–471 (2016).PubMed 

    Google Scholar 
    65.Engelstädter, J. & Moradigaravand, D. Adaptation through genetic time travel? Fluctuating selection can drive the evolution of bacterial transformation. Proc. R. Soc. B Biol. Sci. 281, 20132609 (2014).
    Google Scholar 
    66.Cohan, F. M. Periodic selection and ecological diversity in bacteria. Selective Sweep https://doi.org/10.1007/0-387-27651-3_7 (2007).Article 

    Google Scholar 
    67.Shapiro, B. J., David, L. A., Friedman, J. & Alm, E. J. Looking for Darwin’s footprints in the microbial world. Trends Microbiol. 17, 196–204 (2009).PubMed 

    Google Scholar 
    68.Shapiro, B. J. et al. Population genomics of early events in the ecological differentiation of bacteria. Science 336, 48–51 (2012).PubMed 
    PubMed Central 

    Google Scholar 
    69.Rosen, M., Davison, M., Bhaya, D. & Fisher, D. S. Fine-scale diversity and extensive recombination in a quasisexual bacterial population occupying a broad niche. Science 348, 1019–1024 (2015).PubMed 

    Google Scholar 
    70.Bendall, M. L. et al. Genome-wide selective sweeps and gene-specific sweeps in natural bacterial populations. ISME J. 10, 1589–1601 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    71.Porter, S. S., Chang, P. L., Conow, C. A., Dunham, J. P. & Friesen, M. L. Association mapping reveals novel serpentine adaptation gene clusters in a population of symbiotic Mesorhizobium. ISME J. 11, 248–262 (2017).PubMed 

    Google Scholar 
    72.Crits-Christoph, A., Olm, M. R., Diamond, S., Bouma-Gregson, K. & Banfield, J. F. Soil bacterial populations are shaped by recombination and gene-specific selection across a grassland meadow. ISME J. https://doi.org/10.1038/s41396-020-0655-x (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    73.Woods, L. C. et al. Horizontal gene transfer potentiates adaptation by reducing selective constraints on the spread of genetic variation. Proc. Natl Acad. Sci. USA 117, 26868–26875 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    74.Miralles, R., Gerrish, P. J., Moya, A. & Elena, S. F. Clonal interference and the evolution of RNA viruses. Science 285, 1745–1747 (1999).PubMed 

    Google Scholar 
    75.De Visser, J. A. G. M., Zeyl, C. W., Gerrish, P. J., Blanchard, J. L. & Lenski, R. E. Diminishing returns from mutation supply rate in asexual populations. Science 283, 404–406 (1999).PubMed 

    Google Scholar 
    76.Good, B. H., Rouzine, I. M., Balick, D. J., Hallatschek, O. & Desai, M. M. Distribution of fixed beneficial mutations and the rate of adaptation in asexual populations. Proc. Natl Acad. Sci. USA 109, 4950–4955 (2012).PubMed 
    PubMed Central 

    Google Scholar 
    77.Takeuchi, N., Cordero, O. X., Koonin, E. V. & Kaneko, K. Gene-specific selective sweeps in bacteria and archaea caused by negative frequency-dependent selection. BMC Biol. 13, 1–11 (2015). The authors show that in the presence of NFDS, genes or mutations that are unconditionally beneficial can spread through populations only via HGT, giving rise to gene-specific sweeps.
    Google Scholar 
    78.Corander, J. et al. Frequency-dependent selection in vaccine-associated pneumococcal population dynamics. Nat. Ecol. Evol. 2017, 1950–1960 (2018).
    Google Scholar 
    79.Rodriguez-Valera, F. et al. Explaining microbial population genomics through phage predation. Nat. Rev. Microbiol. 7, 828–836 (2009).PubMed 

    Google Scholar 
    80.Good, B. H., McDonald, M. J., Barrick, J. E., Lenski, R. E. & Desai, M. M. The dynamics of molecular evolution over 60,000 generations. Nature 551, 45–50 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    81.Ramiro, R. S., Durão, P., Bank, C. & Gordo, I. Low mutational load allows for high mutation rate variation in gut commensal bacteria. PLoS Biol. https://doi.org/10.1101/568709 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    82.Holt, R. D. Bringing the Hutchinsonian niche into the 21st century: ecological and evolutionary perspectives. Proc. Natl Acad. Sci. USA 106, 19659–19665 (2009).PubMed 
    PubMed Central 

    Google Scholar 
    83.Cohan, F. M. Transmission in the origins of bacterial diversity, from ecotypes to phyla. Microbiol. Spectr. https://doi.org/10.1128/9781555819743.ch18 (2017).Article 
    PubMed 

    Google Scholar 
    84.Fondi, M. et al. “Every gene is everywhere but the environment selects”: global geolocalization of gene sharing in environmental samples through network analysis. Genome Biol. Evol. 8, 1388–1400 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    85.Cohan, F. M. The effects of rare but promiscuous genetic exchange on evolutionary divergence in prokaryotes. Am. Nat. 143, 965–986 (1994).
    Google Scholar 
    86.Majewski, J. & Cohan, F. M. Adapt globally, act locally: the effect of selective sweeps on bacterial sequence diversity. Genetics 152, 1459–1474 (1999).PubMed 
    PubMed Central 

    Google Scholar 
    87.Messer, P. W. & Petrov, D. A. Population genomics of rapid adaptation by soft selective sweeps. Trends Ecol. Evol. https://doi.org/10.1016/j.tree.2013.08.003 (2013).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    88.Cui, Y. et al. Epidemic clones, oceanic gene pools, and Eco-LD in the free living marine pathogen Vibrio parahaemolyticus. Mol. Biol. Evol. 32, 1396–1410 (2015).PubMed 

    Google Scholar 
    89.Skwark, M. et al. Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis. PLoS Genet. https://doi.org/10.1371/journal.pgen.1006508 (2016).Article 

    Google Scholar 
    90.Pensar, J. et al. Genome-wide epistasis and co-selection study using mutual information. Nucleic Acids Res. 47, e112–e112 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    91.Puranen, S. et al. SuperDCA for genome-wide epistasis analysis. Microb. Genomics 4, e000184 (2018).
    Google Scholar 
    92.Whelan, F. J., Rusilowicz, M. & McInerney, J. O. Coinfinder: detecting significant associations and dissociations in pangenomes. Microb. Genomics 6, e000338 (2020).
    Google Scholar 
    93.Slomka, S. et al. Experimental evolution of bacillus subtilis reveals the evolutionary dynamics of horizontal gene transfer and suggests adaptive and neutral effects. Genetics 216, 543–558 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    94.Maddamsetti, R. & Lenski, R. E. Analysis of bacterial genomes from an evolution experiment with horizontal gene transfer shows that recombination can sometimes overwhelm selection. PLoS Genet. 14, 1–30 (2018).
    Google Scholar 
    95.Knöppel, A., Lind, P. A., Lustig, U., Näsvall, J. & Andersson, D. I. Minor fitness costs in an experimental model of horizontal gene transfer in bacteria. Mol. Biol. Evol. 31, 1220–1227 (2014).PubMed 

    Google Scholar 
    96.Collins, R. E. & Higgs, P. G. Testing the infinitely many genes model for the evolution of the bacterial core genome and pangenome. Mol. Biol. Evol. 29, 3413–3425 (2012).PubMed 

    Google Scholar 
    97.Baumdicker, F., Hess, W. R. & Pfaffelhuber, P. The infinitely many genes model for the distributed genome of bacteria. Genome Biol. Evol. 4, 443–456 (2012).PubMed 
    PubMed Central 

    Google Scholar 
    98.Haegeman, B. & Weitz, J. S. A neutral theory of genome evolution and the frequency distribution of genes. BMC Genomics 13, 196 (2012).PubMed 
    PubMed Central 

    Google Scholar 
    99.Hughes, A. L. Evidence for abundant slightly deleterious polymorphisms in bacterial populations. Genetics 169, 533–538 (2005).PubMed 
    PubMed Central 

    Google Scholar 
    100.Van Passel, M. W. J., Marri, P. R. & Ochman, H. The emergence and fate of horizontally acquired genes in Escherichia coli. PLoS Comput. Biol. 4, e1000059 (2008).PubMed 
    PubMed Central 

    Google Scholar 
    101.Hao, W. & Golding, G. B. The fate of laterally transferred genes: life in the fast lane to adaptation or death. Genome Res. 16, 636–643 (2006).PubMed 
    PubMed Central 

    Google Scholar 
    102.Lerat, E., Daubin, V., Ochman, H. & Moran, N. A. Evolutionary origins of genomic repertoires in bacteria. 3, e130 (2005).103.Lobkovsky, A. E., Wolf, Y. I. & Koonin, E. V. Gene frequency distributions reject a neutral model of genome evolution. Genome Biol. Evol. 5, 233–242 (2013).PubMed 
    PubMed Central 

    Google Scholar 
    104.Sela, I., Wolf, Y. I. & Koonin, E. V. Theory of prokaryotic genome evolution. Proc. Natl Acad. Sci. USA 113, 11399–11407 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    105.Charlesworth, B. Effective population size and patterns of molecular evolution and variation. Nat. Rev. Genet. https://doi.org/10.1038/nrg2526 (2009).Article 
    PubMed 

    Google Scholar 
    106.Cohan, F. M. & Perry, E. B. A systematics for discovering the fundamental units of bacterial diversity. Curr. Biol. 17, 373–386 (2007).
    Google Scholar 
    107.Domingo-Sananes, M. R. & McInerney, J. O. Selection-based model of prokaryote pangenomes. bioRxiv https://doi.org/10.1101/782573 (2019).Article 

    Google Scholar 
    108.Azarian, T. et al. Frequency-dependent selection can forecast evolution in Streptococcus pneumoniae. PLoS Biol. 18, e3000878 (2020). The authors provide evidence that NFDS is a pervasive evolutionary force that shapes the accessory genome of S. pneumoniae.PubMed 
    PubMed Central 

    Google Scholar 
    109.Bobay, L. M., Touchon, M. & Rocha, E. P. C. Pervasive domestication of defective prophages by bacteria. Proc. Natl Acad. Sci. USA 111, 12127–12132 (2014). Although prophages can be considered parasitic, the authors show evidence of purifying selection within prophage genes, suggesting that they serve a beneficial purpose within their bacterial hosts.PubMed 
    PubMed Central 

    Google Scholar 
    110.Puigbò, P., Lobkovsky, A. E., Kristensen, D. M., Wolf, Y. I. & Koonin, E. V. Genomes in turmoil: quantification of genome dynamics in prokaryote supergenomes. BMC Med. 12, 1–19 (2014).
    Google Scholar 
    111.Lynch, M. Streamlining and simplification of microbial genome architecture. Annu.Rev.Microbiol. 60, 327–349 (2006).PubMed 

    Google Scholar 
    112.Bobay, L. & Ochman, H. Factors driving effective population size and pan-genome evolution in bacteria. BMC Evol. Biol. 18, 15 (2018).
    Google Scholar 
    113.Brito, I. L. et al. Mobile genes in the human microbiome are structured from global to individual scales. Nature 535, 435–439 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    114.Evans, T. G. Considerations for the use of transcriptomics in identifying the ‘genes that matter’ for environmental adaptation. J. Exp. Biol. 218, 1925–1935 (2015).PubMed 

    Google Scholar 
    115.Cain, A. K. et al. A decade of advances in transposon-insertion sequencing. Nat. Rev. Genet. 21, 526–540 (2020).PubMed 

    Google Scholar 
    116.Wu, M. et al. Genetic determinants of in vivo fitness and diet responsiveness in multiple human gut Bacteroides. Science (80-.) 350, aac5992 (2015).
    Google Scholar 
    117.Poulsen, B. E. et al. Defining the core essential genome of Pseudomonas aeruginosa. Proc. Natl Acad. Sci. USA 116, 10072–10080 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    118.Pál, C., Papp, B. & Lercher, M. J. Adaptive evolution of bacterial metabolic networks by horizontal gene transfer. Nat. Genet. 37, 1372–1375 (2005).PubMed 

    Google Scholar 
    119.Ansari, A. & Didelot, X. Inference of the properties of the recombination process from whole bacterial genomes. Genetics 196, 253–265 (2014).PubMed 

    Google Scholar 
    120.Lin, M. & Kussell, E. Inferring bacterial recombination rates from large-scale sequencing datasets. Nat. Methods 16, 199–204 (2019). The authors develop a fast and clever method that uses linkage information to estimate recombination rates and the diversity of the gene pool that has contributed alleles to the sample via HGT.PubMed 

    Google Scholar 
    121.Marttinen, P. et al. Detection of recombination events in bacterial genomes from large population samples. Nucleic Acids Res. 40, 1–12 (2012).
    Google Scholar 
    122.Didelot, X. & Wilson, D. J. ClonalFrameML: efficient inference of recombination in whole bacterial genomes. PLoS Comput. Biol. 11, 1–18 (2015).
    Google Scholar 
    123.Croucher, N. J. et al. Rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences using Gubbins. https://doi.org/10.1371/journal.pcbi.1004041 (2015).124.Mostowy, R. et al. Efficient inference of recent and ancestral recombination within bacterial populations. Mol. Biol. Evol. 34, 1167–1182 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    125.Yahara, K., Didelot, X., Ansari, M. A., Sheppard, S. K. & Falush, D. Efficient inference of recombination hot regions in bacterial genomes. Mol. Biol. Evol. 31, 1593–1605 (2014).PubMed 
    PubMed Central 

    Google Scholar 
    126.Daubin, V., Moran, N. A. & Ochman, H. Phylogenetics and the cohesion of bacterial genomes. Science 301, 829–832 (2003).PubMed 

    Google Scholar 
    127.Daubin, V. & Szollosi, G. Horizontal gene transfer and the tree of life. Cold Spring Harb. Perspect. Biol. https://doi.org/10.1007/978-94-007-2941-4_37 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    128.Bertelli, C., Tilley, K. E. & Brinkman, F. S. L. Microbial genomic island discovery, visualization and analysis. Brief. Bioinform. 20, 1685–1698 (2019).PubMed 

    Google Scholar 
    129.Rocha, E. P. C. et al. Comparisons of dN/dS are time dependent for closely related bacterial genomes. J. Theor. Biol. 239, 226–235 (2006).PubMed 

    Google Scholar 
    130.Kryazhimskiy, S. & Plotkin, J. B. The population genetics of dN/dS. PLoS Genet. https://doi.org/10.1371/journal.pgen.1000304 (2008).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    131.Charlesworth, B. & Charlesworth, D. Elements of Evolutionary Genetics (Roberts and Company Publishers, 2010).132.Castillo-Ramírez, S. et al. The impact of recombination on dN/dS within recently emerged bacterial clones. PLoS Pathog. https://doi.org/10.1371/journal.ppat.1002129 (2011).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    133.David, S. et al. Dynamics and impact of homologous recombination on the evolution of Legionella pneumophila. PLoS Genet. 13, 1–21 (2017).
    Google Scholar 
    134.Dillon, M., Thakur, S., Almeida, R. & Guttman, D. Recombination of ecologically and evolutionarily significant loci maintains genetic cohesion in the Pseudomonas syringae species complex. Genome Biol. https://doi.org/10.1101/227413 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar  More

  • in

    The influence of rainfall and tillage on wheat yield parameters and weed population in monoculture versus rotation systems

    1.Navarra, A. & Tubiana, L. (eds) Regional Assessment of Climate Change in the Mediterranean, Advances in Global Change Research (Springer Netherlands, 2013). https://doi.org/10.1007/978-94-007-5772-1.Book 

    Google Scholar 
    2.Solomon, S. S. IPCC (2007): Climate Change the Physical Science Basis. AGUFM 2007, U43D-01 (2007).3.Seneviratne, S. et al. Changes in Climate Extremes and Their Impacts on the Natural Physical Environment: An Overview of the IPCC SREX report, Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change (IPCC) (2012).4.Bates, B., Kundzewicz, Z. & Wu, S. Climate Change and Water. Intergovernmental Panel on Climate Change Secretariat (2008).5.Neve, P., Vila-Aiub, M. & Phytologist, F.R.-N. Evolutionary-thinking in agricultural weed management. New Phytol. 184(4), 783–793 (2009).Article 

    Google Scholar 
    6.Harrison, M. T., Cullen, B. R. & Rawnsley, R. P. Modelling the sensitivity of agricultural systems to climate change and extreme climatic events. Agric. Syst. https://doi.org/10.1016/j.agsy.2016.07.006 (2016).Article 

    Google Scholar 
    7.Moret, D., Arrúe, J. L., López, M. V. & Gracia, R. Winter barley performance under different cropping and tillage systems in semiarid Aragon (NE Spain). Eur. J. Agron. 26, 54–63. https://doi.org/10.1016/j.eja.2006.08.007 (2007).Article 

    Google Scholar 
    8.FAO (Food and Agriculture Organization). Rome: Introduction to Conservation Agriculture (Its Principles and Benefits). http://teca.fao.org/technology/introduction-conservationagriculture-its-principles-benefits (2013).9.Kertész, À. & Madarász, B. Conservation agriculture in Europe. Int. Soil Water Conserv. Res. 2(1), 91–96 (2014).Article 

    Google Scholar 
    10.Álvaro-Fuentes, J., López, M. V., Cantero-Martínez, C. & Arrúe, J. L. Tillage effects on soil organic carbon fractions in Mediterranean dryland agroecosystems. Soil Sci. Soc. Am. J. 72, 541–547 (2008).ADS 
    Article 

    Google Scholar 
    11.Bouchery, Y., Ghaffari, A., Jemai, Z. & Dallery, Y. Including sustainability criteria into inventory models. Eur. J. Oper. Res. 222, 229–240 (2012).MathSciNet 
    Article 

    Google Scholar 
    12.Soane, B. D. et al. No-till in northern, western and south-western Europe: A review of problems and opportunities for crop production and the environment. Soil Tillage Res. 118, 66–87 (2012).Article 

    Google Scholar 
    13.Madejón, E. et al. Effect of long-term conservation tillage on soil biochemical properties in Mediterranean Spanish areas. Soil Tillage Res. 105, 55–62 (2009).Article 

    Google Scholar 
    14.De Vita, P., Di Paolo, E., Fecondo, G., Di Fonzo, N. & Pisante, M. No-tillage and conventional tillage effects on durum wheat yield, grain quality and soil moisture content in southern Italy. Soil Tillage Res. 92, 69–78. https://doi.org/10.1016/j.still.2006.01.012 (2007).Article 

    Google Scholar 
    15.Giambalvo, D. et al. Faba bean grain yield, N2 fixation, and weed infestation in a long-term tillage experiment under rainfed Mediterranean conditions. Plant Soil 360, 215–227. https://doi.org/10.1007/s11104-012-1224-5 (2012).CAS 
    Article 

    Google Scholar 
    16.Ruisi, P. et al. Conservation tillage in a semiarid Mediterranean environment: Results of 20 years of research. Ital. J. Agron. 9(560), 1–7. https://doi.org/10.4081/ija.2014.560 (2014).Article 

    Google Scholar 
    17.Plaza-Bonilla, D., Cantero-Martínez, C., Viñas, P. & Álvaro-Fuentes, J. Soil aggregation and organic carbon protection in a no-tillage chronosequence under Mediterranean conditions. Geoderma 193–194, 76–82 (2013).ADS 
    Article 

    Google Scholar 
    18.Barberi, P. & Lo Cascio, B. Long-term tillage and crop rotation effects on weed seed bank size and composition. Weed Res. 41(4), 325–340. https://doi.org/10.1046/j.1365-3180.2001.00241.x (2001).Article 

    Google Scholar 
    19.Batey, T. & McKenzie, D. C. Soil compaction: Identification directly in the field. Soil Use Manag. 22, 123–131. https://doi.org/10.1111/j.1475-2743.2006.00017.x (2006).Article 

    Google Scholar 
    20.Lampurlanés, J., Plaza-Bonilla, D., Álvaro-Fuentes, J. & Cantero-Martínez, C. Long-term analysis of soil water conservation and crop yield under different tillage systems in Mediterranean rainfed conditions. Field Crops Res. 198, 59–67. https://doi.org/10.1016/j.fcr.2016.02.010 (2016).Article 

    Google Scholar 
    21.Ruisi, P. et al. Weed seedbank size and composition in a long-term tillage and crop sequence experiment. Weed Res. 55, 320–328. https://doi.org/10.1111/wre.12142 (2015).Article 

    Google Scholar 
    22.Mahli, S. S. & Lemke, R. Tillage, crop residue and N fertilizer effects on crop yield, nutrient uptake, soil quality and nitrous oxide gasemissions in a second 4-yr rotation cycle. Soil Tillage Res. 96, 269–283. https://doi.org/10.1016/j.still.2007.06.011 (2007).Article 

    Google Scholar 
    23.Santín-Montanyá, M. I., Gandía, M. L., Zambrana, E. & Tenorio, J. L. Effects of tillage systems on wheat and weed water relationships over time when growing together, in semiarid conditions. Ann. Appl. Biol. 177, 256–265. https://doi.org/10.1111/aab.12620 (2020).Article 

    Google Scholar 
    24.Chaghazardi, H. R., Jahansouz, M. R., Ahmadi, A. & Gorji, M. Effects of tillage management on productivity of wheat and chickpea under cold, rainfed conditions in western Iran. Soil Tillage Res. 162, 26–33. https://doi.org/10.1016/j.still.2016.04.010 (2016).Article 

    Google Scholar 
    25.López-Bellido, L., Fuentes, M., Castillo, J. E., López-Garrido, F. J. & Fernández, E. J. Long-term tillage, crop rotation, and nitrogen fertiliser effects on wheat yield under rainfed Mediterranean conditions. Agron. J. 88, 783–791 (1996).Article 

    Google Scholar 
    26.Cantero-Martínez, C., Angás, P. & Lampurlanés, J. Long-term yield and water use efficiency under various tillage systems in Mediterranean rainfed conditions. Ann. Appl. Biol. 150, 293–305. https://doi.org/10.1111/j.1744-7348.2007.00142.x (2007).Article 

    Google Scholar 
    27.Campiglia, E., Mancinelli, R., De Stefanis, E., Pucciarmati, S. & Radicetti, E. The long-term effects of conventional and organic ropping systems, tillage managements and weather conditions on yield and grain quality of durum wheat (Triticum durum Desf.) in the Mediterranean environment of central Italy. Field Crops Res. 176, 34–44. https://doi.org/10.1016/j.fcr.2015.02.021 (2015).Article 

    Google Scholar 
    28.Bennett, A. J., Bending, G. D., Chandler, D., Hilton, S. & Mills, P. Meeting the demand for crop production: The challenge of yield decline in crops grown in short rotations. Biol. Rev. 87, 52–71 (2012).Article 

    Google Scholar 
    29.Plourde, J. D., Pijanowski, B. C. & Pekin, B. K. Evidence for increased monoculture cropping in the Central United States. Agric. Ecosyst. Environ. 165, 50–59 (2013).Article 

    Google Scholar 
    30.Seymour, M., Kirkegaard, J. A., Peoples, M. B., White, P. F. & French, R. J. Break-crop benefits to wheat in Western Australia—Insights from over three decades of research. Crop Pasture Sci. 63, 1 (2012).Article 

    Google Scholar 
    31.Wang, H. & Ortiz-Bobea, A. Market-driven corn monocropping in the U.S. Midwest. Agric. Resour. Econ. Rev. 48, 274–296 (2019).Article 

    Google Scholar 
    32.Tekin, S., Yazar, A. & Barut, H. Comparison of wheat-based rotation systems vs monocropping under dryland Mediterranean conditions. Int. J. Agric. Biol. Eng. 10, 203–213. https://doi.org/10.25165/j.ijabe.20171005.3443 (2017).Article 

    Google Scholar 
    33.Ryan, J., Singh, M. & Pala, M. Long-term cereal-based rotation trials in the Mediterranean region: Implications for cropping sustainability. Adv. Agron. 97, 273–319. https://doi.org/10.1016/S0065-2113(07)00007-7 (2008).CAS 
    Article 

    Google Scholar 
    34.Bowles, T. M. et al. Long-term evidence shows that crop-rotation diversification increases agricultural resilience to adverse growing conditions in North America. One Earth 2, 284–293 (2020).Article 

    Google Scholar 
    35.Marini, L. et al. Crop rotations sustain cereal yields under a changing climate. Environ. Res. Lett. 15(12), 124011 (2020).Article 

    Google Scholar 
    36.Renard, D. & Tilman, D. National food production stabilized by crop diversity. Nature 571, 257–260 (2019).ADS 
    CAS 
    Article 

    Google Scholar 
    37.Amato, G. et al. Long-term tillage and crop sequence effects on wheat grain yield and quality. Agron. J. 105, 1317–1327 (2013).Article 

    Google Scholar 
    38.Loke, P. F., Kotzé, E. & Du Preez, C. C. Impact of long-term wheat production management practices on soil acidity, phosphorus and some micronutrients in a semi-arid Plinthosol. Soil Res. 51, 415–426. https://doi.org/10.1071/SR12359 (2013).CAS 
    Article 

    Google Scholar 
    39.Martin-Rueda, I. et al. Tillage and crop rotation effects on barley yield and soil nutrients on a Calciortidic Haploxeralf. Soil Tillage Res. 92, 1–9 (2007).Article 

    Google Scholar 
    40.Hadjichristodoulou, A. The relationship of grain yield with harvest index and total biological yield of barley in drylands. Tech. Bull. 126, 1–10 (1991).
    Google Scholar 
    41.Zimdahl, R. L. Weed-Crop Competition: A Review 49–50, 109–145 (Blackwell Publishing, 2004).42.Nkoa, R., Owen, M. D. K. & Swanton, C. J. Weed abundance, distribution, diversity, and community analyses. Weed Sci. 63, 64–90. https://doi.org/10.1614/ws-d-13-00075.1 (2015).Article 

    Google Scholar 
    43.Ter Braak, C. J. F. Canonical correspondence analysis: A new eigenvector technique for multivariate direct gradient analysis. Ecology 67, 1167–1179 (1986).Article 

    Google Scholar 
    44.Fried, G., Petit, S. & Reboud, X. A specialist-generalist classification of the arable flora and its response to changes in agricultural practices. BMC Ecol. 10, 20 (2010).Article 

    Google Scholar 
    45.Korres, N. E. et al. Cultivars to face climate change effects on crops and weeds: A review. Agron. Sustain. Dev. 36, 1–22. https://doi.org/10.1007/s13593-016-0350-5 (2016).Article 

    Google Scholar 
    46.Acevedo, E. H., Silva, P. C., Silva, H. R. & Solar, B. R. Wheat production in Mediterranean environments. In Wheat: Ecology and Physiology of Yield Determination 295–331 (1999).47.Ramesh, K., Matloob, A., Aslam, F., Florentine, S. K. & Chauhan, B. S. Weeds in a changing climate: Vulnerabilities, consequences, and implications for future weed management. Front. Plant Sci. 8, 1–12. https://doi.org/10.3389/fpls.2017.00095 (2017).CAS 
    Article 

    Google Scholar 
    48.Calzarano, F. et al. Durum wheat quality, yield and sanitary status under conservation agriculture. Agriculture https://doi.org/10.3390/agriculture8090140 (2018).Article 

    Google Scholar 
    49.Santín-Montanyá, M. I., Fernández-Getino, A. P., Zambrana, E. & Tenorio, J. L. Effects of tillage on winter wheat production in Mediterranean dryland fields. Arid Land Res. Manag. 31(3), 269–282. https://doi.org/10.1080/15324982.2017.1307289 (2017).Article 

    Google Scholar 
    50.Shimshi, D., Bielorai, H. & Mantell, A. Irrigation of field crops. In Arid Zone Irrigation 369–381 (Springer, 1973).51.Schultz, J. E. Crop production in a rotation trial at Tarlee, South Australia. Aust. J. Exp. Agric. 35, 865–876. https://doi.org/10.1071/EA9950865 (1995).Article 

    Google Scholar 
    52.Alarcón, R. et al. Effects of no-tillage and non-inversion tillage on weed community diversity and crop yield over nine years in a Mediterranean cereal-legume cropland. Soil Tillage Res. 179, 54–62. https://doi.org/10.1016/j.still.2018.01.014 (2018).Article 

    Google Scholar 
    53.Šíp, V., Vavera, R., Chrpová, J., Kusá, H. & Růžek, P. Winter wheat yield and quality related to tillage practice, input level and environmental conditions. Soil Tillage Res. 132, 77–85. https://doi.org/10.1016/j.still.2013.05.002 (2013).Article 

    Google Scholar 
    54.Woźniak, A. Effect of cereal monoculture and tillage systems on grain yield and weed infestation of winter durum wheat. Int. J. Plant Prod. 14, 1–8. https://doi.org/10.1007/s42106-019-00062-8 (2020).Article 

    Google Scholar 
    55.Schulte, B. J., Tomasek, B. J., Davis, A. S., Andersson, L. & Benoit, D. L. An investigation to enhance understanding of the stimulation of weed seedling emergence by soil disturbance. Weed Res. 54, 1–12. https://doi.org/10.1111/wre.12054 (2014).Article 

    Google Scholar 
    56.Calado, J. M. G., Basch, G. & de Carvalho, M. Weed emergence as influenced by soil moisture and air temperature. J. Pest Sci. 82, 81–88. https://doi.org/10.1007/s10340-008-0225-x (2009).Article 

    Google Scholar 
    57.Siddique, K. H. M. et al. Innovations in agronomy for food legumes. A review. Agron. Sustain. Dev. 32, 45–64 (2012).Article 

    Google Scholar 
    58.Payne, W. A., Rasmussen, P. E., Chen, C. & Ramig, R. E. Assessing simple wheat and pea models using data from a long-term tillage experiment. Agron. J. 93, 250–260. https://doi.org/10.2134/agronj2001.931250x (2001).Article 

    Google Scholar 
    59.Machado, S., Petrie, S., Rhinhart, K. & Ramig, R. E. Tillage effects on water use and grain yield of winter wheat and green pea in rotation. Agron. J. 100, 154–162. https://doi.org/10.2134/agrojnl2006.0218 (2008).Article 

    Google Scholar 
    60.Copec, K., Filipovic, D., Husnjak, S., Kovacev, I. & Kosustic, S. Effects of tillage systems on soil water content and yield in maize and winter wheat production. Plant Soil Environ. 61(5), 213–219. https://doi.org/10.17221/156/2015-pse (2015).Article 

    Google Scholar 
    61.López-Bellido, L., López-Bellido, R. J., Redondo, R. & Benítez, J. Faba bean nitrogen fixation in a wheat-based rotation under rainfed Mediterranean conditions: Effect of tillage system. Field Crop Res. 98, 253–260 (2006).Article 

    Google Scholar 
    62.López-Bellido, R. J., López-Bellido, L., Benítez-Vega, J. & López-Bellido, F. J. Tillage system, preceding crop, and nitrogen fertilizer in wheat crop: I. Soil water content. Agron. J. 99, 59–65. https://doi.org/10.2134/agronj2006.0025 (2007).Article 

    Google Scholar 
    63.López-Bellido, L., Muñoz-Romero, V., Fernández-García, P. & López-Bellido, R. J. Ammonium accumulation in soil: The long-term effects of tillage, rotation and N rate in a Mediterranean vertisol. Soil Use Manag. 30(4), 471–479 (2014).Article 

    Google Scholar 
    64.Bilalis, D., Efthimiadis, P. & Sidiras, N. Effect of three tillage systems on weed flora in a 3-year rotation with four crops. J. Agron. Crop Sci. 186, 135–141. https://doi.org/10.1046/j.1439-037X.2001.00458.x (2001).Article 

    Google Scholar 
    65.Feledyn-Szewczyk, B., Smagacz, J., Kwiatkowski, C. A., Harasim, E. & Woźniak, A. Weed flora and soil seed bank composition as affected by tillage system in three-year crop rotation. Agriculture https://doi.org/10.3390/agriculture10050186 (2020).Article 

    Google Scholar 
    66.Pala, M., Ryan, J., Zhang, H., Singh, M. & Harris, H. C. Water-use efficiency of wheat-based rotation systems in a Mediterranean environment. Agric. Water Manag. 93, 136–144. https://doi.org/10.1016/j.agwat.2007.07.001 (2007).Article 

    Google Scholar 
    67.Légère, A., Stevenson, F. C. & Benoit, D. L. Diversity and assembly of weed communities: Contrasting responses across cropping systems. Weed Res. 45, 303–315. https://doi.org/10.1111/j.1365-3180.2005.00459.x (2005).Article 

    Google Scholar 
    68.Sans, F. X., Berner, A., Armengot, L. & Mäder, P. Tillage effects on weed communities in an organic winter wheat-sunflower-spelt cropping sequence. Weed Res. 51, 413–421. https://doi.org/10.1111/j.1365-3180.2011.00859.x (2011).Article 

    Google Scholar 
    69.Sarani, M., Oveisi, M., Mashhadi, H. R., Alizade, H. & Gonzalez-Andujar, J. L. Interactions between the tillage system and crop rotation on the crop yield and weed populations under arid conditions. Weed Biol. Manag. 14, 198–208. https://doi.org/10.1111/wbm.12047 (2014).Article 

    Google Scholar 
    70.Pardo, G. et al. Effects of reduced and conventional tillage on weed communities: Results of a long-term experiment in Southwestern Spain. Planta Daninha https://doi.org/10.1590/s0100-83582019370100152 (2019).Article 

    Google Scholar 
    71.Fennimore, S. A. & Jackson, L. E. Organic amendment and tillage effects on vegetable field weed emergence and seedbanks 1. Weed Technol. 17, 42–50. https://doi.org/10.1614/0890-037x(2003)017[0042:oaateo]2.0.co;2 (2003).Article 

    Google Scholar 
    72.Francis, A. & Warwick, S. I. The biology of Canadian weeds. 3. Lepidium draba L., L. chalepense L., L. appelianum Al-Shehbaz (updated). Can. J. Plant Sci. 88, 379–401. https://doi.org/10.4141/CJPS07100 (2008).Article 

    Google Scholar  More

  • in

    High species richness of tachinid parasitoids (Diptera: Calyptratae) sampled with a Malaise trap in Baihua Mountain Reserve, Beijing, China

    1.Wilson, E. O. The little things that run the world (The importance and conservation of invertebrates). Conserv. Biol. 1, 344–346 (1987).
    Google Scholar 
    2.Stork, N. E. How many species are there?. Biodivers. Conserv. 2, 215–232 (1993).
    Google Scholar 
    3.Erwin, T. L. Tropical forests: Their richness in Coleoptera and other arthropod species. Coleopts. Bull. 36, 74–75 (1982).
    Google Scholar 
    4.Novotny, V. et al. Low host specificity of herbivorous insects in a tropical forest. Nature 416, 841–844 (2002).CAS 
    PubMed 
    ADS 

    Google Scholar 
    5.Stork, N. E. How many species of insects and other terrestrial arthropods are there on earth?. Annu. Rev. Entomol. 63, 31–45 (2018).CAS 
    PubMed 

    Google Scholar 
    6.Linnaeus, C. Amoenitates Academicae, seu Dissertationes Variae Physicae, Medicae, Botanicae, Volume 2. (Laurentium Salvium, 1749).7.Linnaeus, C. Systema Naturae per Regna tria Naturae, Secundum Classes, Ordines, Genera, Species cum Characteribus, Differentiis, Synonymis, Locis. (Laurentium Salvium, 1758).8.Metcalf, Z. P. How many insects are there in the world?. Entomol. News 51, 219–222 (1940).
    Google Scholar 
    9.Ødegaard, F. The relative importance of trees versus lianas as hosts for phytophagous beetles (Coleoptera) in tropical forests. J. Biogeogr. 27, 283–296 (2000).
    Google Scholar 
    10.Geiger, M. F. et al. The global Malaise trap program–how well does the current barcode reference library identify flying insects in Germany? Biodivers. Data J. 4, e10671 (2016).11.D’Souza, M. L. & Hebert, P. D. N. Stable baselines of temporal turnover underlie high beta diversity in tropical arthropod communities. Mol. Ecol. 27, 2447–2460 (2018).PubMed 

    Google Scholar 
    12.Srivathsan, A. et al. Rapid, large-scale species discovery in hyperdiverse taxa using 1D MinION sequencing. Bmc. Biol. 17, 96 (2019).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    13.Wu, Y. et al. Explaining the species richness of birds along a subtropical elevational gradient in the Hengduan Mountains. J. Biogeogr. 40, 2310–2323 (2013).
    Google Scholar 
    14.Morelli, F. et al. Taxonomic diversity, functional diversity and evolutionary uniqueness in bird communities of Beijing’s urban parks: Effects of land use and vegetation structure. Urban For. Urban Green. 23, 84–92 (2017).
    Google Scholar 
    15.White, E. P. Spatiotemporal scaling of species richness: Patterns, processes and implications. In Scaling biodiversity (eds Storch, D. et al.) 325–346 (Cambridge University Press, 2007).
    Google Scholar 
    16.Schwartz, M. D. Phenology: An Integrative Environmental Science. (Springer, 2013).17.Brehm, G., Colwell, R. K. & Kluge, J. The role of environment and mid-domain effect on moth species richness along a tropical elevational gradient. Glob. Ecol. Biogeogr. 16, 205–219 (2007).
    Google Scholar 
    18.Sundqvist, M. K., Sanders, N. J. & Wardle, D. A. Community and ecosystem responses to elevational gradients: Processes, mechanisms, and insights for global change. Annu. Rev. Ecol. Evol. Syst. 44, 261–280 (2013).
    Google Scholar 
    19.Le, C. M., Wilson, S. W. & Soulier-Perkins, A. Elevational gradient of Hemiptera (Heteroptera, Auchenorrhyncha) on a tropical mountain in Papua New Guinea. PeerJ 3, e978 (2015).
    Google Scholar 
    20.McCravy, K. W. A review of sampling and monitoring methods for beneficial arthropods in agroecosystems. Insects 9, 170 (2018).PubMed Central 

    Google Scholar 
    21.Karlsson, D. et al. The Swedish Malaise trap project: A 15 year retrospective on a countrywide insect inventory. Biodivers. Data J. 8, e47255 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    22.Borkent, A. et al. Remarkable fly (Diptera) diversity in a patch of Costa Rican cloud forest: Why inventory is a vital science. Zootaxa 4402, 53–90 (2018).PubMed 

    Google Scholar 
    23.Fraser, S. E. M., Dytham, C. & Mayhew, P. J. The effectiveness and optimal use of Malaise traps for monitoring parasitoid wasps. Insect Conserv. Divers. 1, 22–31 (2008).
    Google Scholar 
    24.Gaston, K. J., Gauld, I. D. & Hanson, P. The size and composition of the hymenopteran fauna of Costa Rica. J. Biogeogr. 23, 105–113 (1996).
    Google Scholar 
    25.Townes, H. K. Design of a Malaise trap. Proc. Entomol. Soc. Wash. 64, 253–262 (1962).
    Google Scholar 
    26.O’Hara, J. E. History of tachinid classification (Diptera, Tachinidae). ZooKeys 316, 1–34 (2013).
    Google Scholar 
    27.O’Hara, J. E., Henderson, S. J. & Wood, D. M. Preliminary Checklist of the Tachinidae of the World. Version 2.1. http://www.nadsdiptera.org/Tach/WorldTachs/Checklist/Worldchecklist.html (2020).28.Stireman, J. O., O’Hara, J. E. & Wood, D. M. Tachinidae: Evolution, behavior, and ecology. Annu. Rev. Entomol. 51, 525–555 (2006).CAS 
    PubMed 

    Google Scholar 
    29.Cerretti, P. et al. Signal through the noise? Phylogeny of the Tachinidae (Diptera) as inferred from morphological evidence. Syst. Entomol. 39, 335–353 (2014).
    Google Scholar 
    30.Stireman, J. O., Dyer, L. A. & Greeney, H. F. Specialised generalists? Food web structure of a tropical tachinid-caterpillar community. Insect Conserv. Diver. 10, 367–384 (2017).
    Google Scholar 
    31.Belshaw, R. Tachinid (Diptera) assemblages in habitats of a secondary succession in southern Britain. Entomology 111, 151–161 (1992).
    Google Scholar 
    32.Inclán, D. J. & Stireman, J. O. Tachinid (Diptera: Tachinidae) Parasitoid diversity and temporal abundance at a single site in the northeastern United States. Ann. Entomol. Soc. Am. 104, 287–296 (2011).
    Google Scholar 
    33.Cerretti, P., Whitmore, D., Mason, F. & Taglianti, A. V. Survey on the spatio-temporal distribution of tachinid flies: Using Malaise traps (Diptera, Tachinidae). In Invertebrati diuna foresta della Pianura Padana, Bosco della Fontana, Secondo contributo (eds Cerretti, P. et al.) 229–256 (Springer, 2004).34.Stireman, J. O. Alpha and beta diversity of a tachinid parasitoid community. Ann. Entomol. Soc. Am. 101, 362–370 (2008).
    Google Scholar 
    35.Pei, W. Y. et al. Species diversity of Tachinidae in Baihuashan National Nature Reserve of Beijing, China. J. Environ. Entomol. 41, 1218–1225 (2019).
    Google Scholar 
    36.Zhao, Y. et al. Fauna resource investigation of Tachinidae (Diptera) from Mt. Huangyi, Eastern Liaoning, China. J. Environ. Entomol. 41, 1208–1217 (2019).
    Google Scholar 
    37.Zhang, Y. Z. et al. Fauna resource investigation of Tachinidae (Diptera) from the grasslands, Inner Mongolia of China. J. Environ. Entomol. 40, 1353–1363 (2018).
    Google Scholar 
    38.Zhang, C. T. et al. Preliminary investigation on Tachinidae (Diptera) of Hanma National Nature Reserve, Inner Mongolia, China. J. Environ. Entomol. 35, 257–264 (2017).CAS 

    Google Scholar 
    39.Liang, H. C. et al. Fauna resource of Tachinidae in Liaoning Hun River Source Nature Reserve of China. J. Environ. Entomol. 38, 1214–1223 (2016).
    Google Scholar 
    40.Zhang, C. T. et al. Faunistic investigation of Tachinidae in Liaoning Bailang Mountain National Nature Reserve of China. J. Environ. Entomol. 37, 726–734 (2015).
    Google Scholar 
    41.Zhang, D. et al. Study on Tachinidae fauna in Songshan National Nature Reserve of Beijing, China. Chin. J. Vector Biol. Control 22, 459–465 (2011).
    Google Scholar 
    42.Herting, B. & Dely-Draskovits, A. Family Tachinidae. In Catalogue of Palaearctic Diptera. Volume 13. Anthomyiidae–Tachinidae. (eds Soós, A. & Papp, L.) 118–458 (Hungarian Natural History Museum, 1993).43.O’Hara, J. E. & Henderson, S. J. World Genera of the Tachinidae (Diptera) and Their Regional Occurrence. Version 11.0. http://www.nadsdiptera.org/Tach/WorldTachs/Genera/Worldgenera.html (2020).44.Tschorsnig, H. P. & Richter, V. A. Family Tachinidae. In Contributions to a Manual of Palaearctic Diptera (with special reference to flies of economic importance) (eds Papp, L. & Darvas, B) 691–827 (Higher Brachycera Science Herald Press, 1998).45.Cerretti, P., Tschorsnig, H. P., Lopresti, M. & Giovanni, F. D. MOSCHweb: A matrix-based interactive key to the genera of the Palaearctic Tachinidae (Insecta, Diptera). ZooKeys 205, 5–18 (2012).
    Google Scholar 
    46.Andersen, S. Revision of European species of Phytomyptera Rondani (Diptera: Tachinidae). Insect Syst. Evol. 19, 43–80 (1988).
    Google Scholar 
    47.Andersen, S. The Siphonini (Diptera: Tachinidae) of Europe. Fauna Entomol. Scand. 33, 1–146 (1996).
    Google Scholar 
    48.Chao, C. M. et al. Tachinidae. In Flies of China Vol. 2 (eds Xue, W. Q. & Chao, C. M.) (Liaoning Science and Technology Press, 1998).
    Google Scholar 
    49.Chao, C. M. et al. Fauna Sinica. Insecta. Vol. 23. Diptera. Tachinidae (1) (Science Press, 2001).
    Google Scholar 
    50.O’Hara, J. E., Shima, H. & Zhang, C. T. Annotated catalogue of the Tachinidae (Insecta: Diptera) of China. Zootaxa 2190, 1–236 (2009).
    Google Scholar 
    51.Tachi, T. & Shima, H. Systematic study of the genus Peribaea Robineau-Desvoidy of East Asia (Diptera: Tachinidae). Tijdschr. voor Entomol. 145, 115–144 (2002).
    Google Scholar 
    52.Tschorsnig, H. P. Preliminary Host Catalogue of Palaearctic Tachinidae (Diptera). http://www.nadsdiptera.org/Tach/WorldTachs/CatPalHosts/Home.html (2017).53.Zhang, C. T., Shima, H. & Chen, X. L. A review of the genus Dexia Meigen in the Palearctic and Oriental Regions (Diptera: Tachinidae). Zootaxa 2705, 1–81 (2010).
    Google Scholar 
    54.Colwell, R. K. Estimates: Statistical Estimation of Species Richness and Shared Species from Samples. Version 9.1.0. http://viceroy.eeb.uconn.edu/estimates/ (2019).55.Oksanen, J. F. et al. Vegan: Community Ecology Package. R Package Version 2.4-3. https://CRAN.R-project.org/package=vegan. Accessed 20 May 2018 (2017).56.Mielke, P. W. 34 Meteorological applications of permutation techniques based on distance functions. Handb. Stat. 4, 813–830 (1984).
    Google Scholar 
    57.Ge, Y. et al. Exotic spartina alterniflora invasion changes temporal dynamics and composition of spider community in a salt marsh of Yangtze Estuary, China. Estuar. Coast. Shelf. Sci. 239, 106755 (2020).
    Google Scholar 
    58.Haq, F. et al. Multivariate approach to the classification and ordination of the forest ecosystem of Nandiar valley western Himalayas. Ecol. Indic. 80, 232–241 (2017).
    Google Scholar 
    59.Oara, J. E., Zhang, C. T. & Shima, H. Catalogue of the Tachinidae (Insecta: Diptera) of China. In Catalogue of Life China: 2021 Annual Checklist, Volume 2 Animals, Insect (VI), Diptera (3) (eds Yang, D. et al.) 845–1170 (The Biodiversity Committee of Chinese Academy of Sciences, 2021).60.McCain, C. M. & Grytnes, J. A. Elevational gradients in species richness. In Encyclopedia of Life Sciences (eds Wiley, J. & Ltd, S.) 1–10 (Wiley, 2010).
    Google Scholar 
    61.Zhang, J. T., Xu, B. & Li, M. Vegetation patterns and species diversity along elevational and disturbance gradients in the Baihua Mountain Reserve, Beijing, China. Mt. Res. Dev. 33, 170–178 (2013).ADS 

    Google Scholar 
    62.Huang, Y. et al. The effects of habitat area, vegetation structure and insect richness on breeding bird populations in Beijing urban parks. Urban For. Urban Green. 14, 1027–1039 (2015).
    Google Scholar 
    63.Eldegard, K., Totland, Ø. & Moe, S. R. Edge effects on plant communities along power line clearings. J. Appl. Ecol. 52, 871–880 (2015).
    Google Scholar 
    64.Fahrig, L. Effects of habitat fragmentation on biodiversity. Annu. Rev. Ecol. Evol. Syst. 34, 487–515 (2003).
    Google Scholar 
    65.Harper, K. A. et al. Edge influence on forest structure and composition in fragmented landscapes. Conserv. Biol. 19, 768–782 (2005).
    Google Scholar 
    66.Laurance, W. F. et al. Habitat fragmentation, variable edge effects, and the landscape-divergence hypothesis. PLoS ONE 2, e1017 (2007).67.Stireman, J. O. III., Cerretti, P., Whitmore, D., Hardersen, S. & Gianelle, D. Composition and stratification of a tachinid (Diptera: Tachinidae) parasitoid community in a European temperate plain forest. Insect Conserv. Divers. 5, 346–357 (2012).
    Google Scholar 
    68.Burington, Z. L. et al. Latitudinal patterns in tachinid parasitoid diversity (Diptera: Tachinidae): A review of the evidence. Insect Conserv. Divers. 13, 419–431 (2020).
    Google Scholar 
    69.Campbell, J. W., Hanula, J. L. & Waldrop, T. A. Effects of prescribed fire and fire surrogates on floral visiting insects of the blue ridge province in North Carolina. Biol. Conserv. 134, 393–404 (2007).
    Google Scholar 
    70.Alfred, D. J. et al. A study on five sampling methods of parasitic hymenopterans in rice ecosystem. Biol. Control. 32, 187–192 (2018).
    Google Scholar 
    71.Wells, W. & Decker, T. A comparison of three types of insect traps for collecting non-Formicidae Hymenoptera on the Island of Dominica. Southwest. Entomol. 31, 59–68 (2006).
    Google Scholar  More

  • in

    Past, present, and future climate space of the only endemic vertebrate genus of the Italian peninsula

    1.Hewitt, G. H. The genetic legacy of Quaternary ice ages. Nature 405, 907–913 (2000).ADS 
    CAS 
    PubMed 

    Google Scholar 
    2.Hewitt, G. H. Speciation, hybrid zones and phylogeography—or seeing genes in space and time. Mol. Ecol. 10, 537–549 (2001).CAS 
    PubMed 

    Google Scholar 
    3.Hauswaldt, J. S. et al. From species divergence to population structure: A multimarker approach on the most basal lineage of Salamandridae, the spectacled salamanders (genus Salamandrina) from Italy. Mol. Phylogenetics Evol. 70, 1–12 (2014).
    Google Scholar 
    4.Gomez, A. & Lunt, D. H. Refugia within refugia: Patterns of phylogeographic concordance in the Iberian Peninsula. In Phylogeography of Southern European Refugia (eds Weiss, S. & Ferrand, N.) 155–188 (Springer, 2007).
    Google Scholar 
    5.Hewitt, G. H. Mediterranean peninsulas: The evolution of hotspots. In Biodiversity Hotspots: Distribution and Protection of Conservation Priority (eds Zachos, F. E. & Habel, J. C.) 123–148 (Springer, 2011).
    Google Scholar 
    6.Lanza, B. & Corti, C. Evolution of knowledge on the Italian herpetofauna during the 20th century. Boll. Mus. Civ. St. Nat. Verona 20, 373–436 (1996).
    Google Scholar 
    7.Sindaco, R., Eremčenko, V. K. & Venchi, A. Mediterranean reptiles: State of knowledge, hot spots, areas of endemism, conservation. In Abstracts of the VI Congress of the Societas Herpetologica Italica (eds Bologna, M.A., Capula, M., Carpaneto, G.M., Luiselli, L., Marangoni, C. & Venchi, A.), (Roma, September 27–October 1 2006), Stilgrafica, Roma, pp. 101–102 (2006).8.Borkin, L. J. Distribution of amphibians in North Africa, Europe, Western Asia and Former Soviet Union. In Patterns of Distribution of Amphibians. A Global Perspective (ed. Duellman, W. E.) 329–420 (Johns Hopkins University Press, 1999).
    Google Scholar 
    9.Speybroeck, J. et al. Species list of the European herpetofauna–2020 update by the Taxonomic Committee of the Societas Europaea Herpetologica. Amphibia-Reptilia 41, 139–189 (2020).
    Google Scholar 
    10.Venczel, M. & Sanchíz, B. A fossil plethodontids salamander from the Middle Miocene of Slovakia (Caudata, Plethodontidae). Amphibia-Reptilia 26, 408–411 (2005).
    Google Scholar 
    11.Venczel, M. & Hír, J. Amphibians and squamates from the Miocene of Felsötárkány Basin, N-Hungary. Palaeontogr. Abt. A 300, 117–158 (2013).
    Google Scholar 
    12.Georgalis, G. L., Villa, A., Ivanov, M., Vasilyan, D. & Delfino, M. Fossil amphibians and reptiles from the Neogene locality of Maramena (Greece), the most diverse European herpetofauna at the Miocene/Pliocene transition boundary. Palaeontol. Electron. 22, 1–99 (2019).
    Google Scholar 
    13.Macaluso, L. et al. A progressive extirpation: An overview of the fossil record of Salamandrina (Salamandridae, Urodela). Hist. Biol., 1–18 (2021).14.Delfino, M., Bailon, S. & Pitruzzella, G. The late pliocene amphibians and reptiles from “Capo Mannu D1 Local Fauna” (Mandriola, Sardinia, Italy). Geodiversitas 33(2), 357–382 (2011).
    Google Scholar 
    15.Lanza, B. Salamandrina terdigitata (Lacépède, 1788): Emblem of the Unione Zoologica Italiana. Boll. Zool. 55, 1–4 (1988).
    Google Scholar 
    16.Agustí, J. et al. A calibrated mammal scale for the Neogene of Western Europe. State of the art. Earth-Sci. Rev. 52, 247–260 (2001).ADS 

    Google Scholar 
    17.Stewart, J. R., Lister, A. M., Barnes, I. & Dalén, L. Refugia revisited: Individualistic responses of species in space and time. P. Roy. Soc. B-Biol. Sci. 277, 661–671 (2010).
    Google Scholar 
    18.Baselga, A., Lobo, J. M., Svenning, J. C. & Araujo, M. B. Global patterns in the shape of species geographical ranges reveal range determinants. J. Biogeogr. 39, 760–771 (2012).
    Google Scholar 
    19.Iannella, M., D’Alessandro, P. & Biondi, M. Evidences for a shared history for spectacled salamanders, haplotypes and climate. Sci. Rep. 8(1), 1–11 (2018).CAS 

    Google Scholar 
    20.Phillips, S. J., Anderson, R. P. & Schapire, R. E. Maximum entropy modelling of species geographic distributions. Ecol. Modell. 190(3–4), 231–259 (2006).
    Google Scholar 
    21.Ficetola, G. F. et al. Knowing the past to predict the future: Land-use change and the distribution of invasive bullfrogs. Glob. Change Biol. 16(2), 528–537 (2010).ADS 

    Google Scholar 
    22.Elith, J., Kearney, M. & Phillips, S. The art of modelling range-shifting species. Methods Ecol. Evol. 1(4), 330–342 (2010).
    Google Scholar 
    23.Chiarenza, A. A. et al. Ecological niche modelling does not support climatically-driven dinosaur diversity decline before the Cretaceous/Paleogene mass extinction. Nat. Commun. 10(1), 1–14 (2019).CAS 

    Google Scholar 
    24.Jones, L. A. et al. Coupling of palaeontological and neontological reef coral data improves forecasts of biodiversity responses under global climatic change. R. Soc. Open Sci. 6, 182111 (2019).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    25.Moss, R. et al. Towards new scenarios for the analysis of emissions: Climate change, impacts and response strategies. Intergovernmental Panel on Climate Change Secretariat (IPCC), pp. 132 (2008).26.Wayne, G. P. The beginner’s guide to representative Concentration pathways. Skeptical science Version 1.0 (2013).27.GBIF.org (2021) GBIF Occurrence Download https://doi.org/10.15468/dl.as6sk2.28.Brown, J. L., Hill, D. J., Dolan, A. M., Carnaval, A. C. & Haywood, A. M. PaleoClim, high spatial resolution paleoclimate surfaces for global land areas. Nat. Sci. Data 5, 180254 (2018).
    Google Scholar 
    29.R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria (2013). http://www.R-project.org/.30.Karger, D. N., Nobis, M. P., Normand, S., Graham, C. H, & Zimmermann, N. E. CHELSA-TraCE21k v1. 0. Downscaled transient temperature and precipitation data since the last glacial maximum. Clim. Past Discuss., 1–27 (2021).31.Otto-Bliesner, B. L., Marshall, S. J., Overpeck, J. T., Miller, G. H. & Hu, A. Simulating Arctic climate warmth and icefield retreat in the last interglaciation. Science 311(5768), 1751–1753 (2006).ADS 
    CAS 
    PubMed 

    Google Scholar 
    32.Hill, D. J. The non-analogue nature of Pliocene temperature gradients. EPSL 425, 232–241 (2015).ADS 
    CAS 

    Google Scholar 
    33.Dolan, A. M. et al. Modelling the enigmatic late Pliocene glacial event—Marine Isotope Stage M2. Glob. Planet. Change 128, 47–60 (2015).ADS 

    Google Scholar 
    34.Sillero, N. & Barbosa, A. M. Common mistakes in ecological niche models. Int. J. Geogr. Inf. Sci. 35(2), 213–226 (2021).
    Google Scholar 
    35.Thuiller, W., Georges, D. & Engler, R. biomod2: Ensemble platform for species distribution modelling. R package version 3.1–64 (2014). http://CRAN.R-project.org/package=biomod2.36.McCullagh, P. & Nelder, J. A. Generalized Linear Models 511 (Chapman and Hall, 1989).MATH 

    Google Scholar 
    37.Liaw, A. & Wiener, M. Classification and regression by randomForest. R News 2, 18–22 (2002).
    Google Scholar 
    38.Phillips, S. J., Anderson, R. P., Dudík, M., Schapire, R. E. & Blair, M. E. Opening the black box: An opensource release of Maxent. Ecography 40, 887–893 (2017).
    Google Scholar 
    39.QGIS Development Team (2021). QGIS Geographic Information System. Open Source Geospatial Foundation Project. http://qgis.osgeo.org.40.Elith, J. et al. A statistical explanation of MaxEnt for ecologists. Divers. Distrib. 17(1), 43–57 (2011).
    Google Scholar 
    41.Allouche, O., Tsoar, A. & Kadmon, R. Assessing the accuracy of species distribution models: Prevalence, kappa and the true skill statistic (TSS). J. Appl. Ecol. 43, 1223–1232 (2006).
    Google Scholar 
    42.Weiss, S. & Ferrand, N. Phylogeography of Southern European Refugia Evolutionary Perspectives on the Origins and Conservation of European Biodiversity 377 (Springer, 2007).
    Google Scholar 
    43.Martinetto, E. The role of central Italy as a centre of refuge for thermophilous plants in the late Cenozoic. Acta Palaeobot. 41(2), 299–319 (2001).
    Google Scholar 
    44.Martinetto, E. et al. Late persistence and deterministic extinction of “humid thermophilous plant taxa of East Asian affinity”(HUTEA) in southern Europe. Palaeogeogr. Palaeoclimatol. Palaeoecol. 467, 211–231 (2017).
    Google Scholar 
    45.Villa, A. & Delfino, M. Fossil lizards and worm lizards (Reptilia, Squamata) from the Neogene and Quaternary of Europe: An overview. Swiss J. Palaeontol. 138, 177–211 (2019).
    Google Scholar 
    46.Montuire, S., Maridet, O. & Legendre, S. Late Miocene–early Pliocene temperature estimates in Europe using rodents. Palaeogeogr. Palaeoclimatol. Palaeoecol. 238(1–4), 247–262 (2006).
    Google Scholar 
    47.Velitzelos, D., Bouchal, J. M. & Denk, T. Review of the Cenozoic floras and vegetation of Greece. Rev. Palaeobot. Palyno. 204, 56–117 (2014).
    Google Scholar 
    48.Martinetto, E. & Vieira, M. New Pliocene records of plant fossil-taxa from NW Portugal and their relevance for the assessment of diversity loss patterns in the late Cenozoic of Europe. Rev. Palaeobot. Palyno. 104286 (2020).49.Beck, H. E. et al. Present and future Köppen-Geiger climate classification maps at 1-km resolution. Sci. Data 5, 180214 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    50.Jylhä, K. et al. Observed and projected future shifts of climatic zones in Europe and their use to visualize climate change information. Weather Clim. Soc. 2(2), 148–167 (2010).
    Google Scholar 
    51.Meinshausen, M. et al. The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Clim. Change 109(1–2), 213 (2011).ADS 
    CAS 

    Google Scholar 
    52.Rutledge, D. Estimating long-term world coal production with logit and probit transforms. Int. J. Coal Geol. 85(1), 23–33 (2011).CAS 

    Google Scholar 
    53.Hausfather, Z. & Peters, G. Emissions: The “business as usual” story is misleading. Nature 577(7792), 618–620 (2020).ADS 
    CAS 
    PubMed 

    Google Scholar 
    54.Delfino, M. Letters to the Editor: The past and future of extant amphibians. Science 308, 49–50 (2005).CAS 
    PubMed 

    Google Scholar 
    55.Lanza, B., Andreone, F., Bologna, M. A., Corti, C. & Razzetti, E. Fauna d’Italia, Vol. XLII, Amphibia. Calderini, Bologna, XI + 537 pp (2007).56.Martínez-Monzón, A., Cuenca-Bescós, G., Bisbal-Chinesta, J.-F. & Blain, H.-A. One million years of diversity shifts in amphibians and reptiles in a Mediterranean landscape: Resilience rules the Quaternary. Palaeontology https://doi.org/10.1111/pala.12547 (2021).Article 

    Google Scholar 
    57.Basile, M. et al. Seasonality and microhabitat selection in a forest-dwelling salamander. Sci. Nat. 104(9–10), 80 (2017).
    Google Scholar 
    58.Macaluso, L. et al. Osteology of the Italian endemic spectacled salamanders, Salamandrina spp. (Amphibia, Urodela, Salamandridae): Selected skeletal elements for palaeontological investigations. J. Morph. 281(11), 1391–1410 (2020).PubMed 

    Google Scholar 
    59.Sanchiz, B. On the presence of zogosphene-zigantrum vertebral articulations in salamandrids. Acta Zool. Cracov. 31(6), 493–504 (1988).
    Google Scholar 
    60.Utzeri, C., Antonelli, D. & Angelini, C. Note on the behavior of the Spectacled Salamander Salamandrina terdigitata (Lacépede, 1788). Herpetozoa 18, 182–185 (2005).
    Google Scholar 
    61.Weitzman, M. L. The Noah’s Ark Problem. Econometrica 66, 1279–1298 (1998).MathSciNet 
    MATH 

    Google Scholar 
    62.Erwin, D. H. Extinction as the loss of evolutionary history. PNAS 105(1), 11520–11527 (2008).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    63.Margules, C. R. & Pressey, R. L. Systematic conservation planning. Nature 405, 243–253 (2000).CAS 
    PubMed 

    Google Scholar 
    64.Brooks, T. M. et al. Global biodiversity conservation priorities. Science 313, 58–61 (2006).ADS 
    CAS 
    PubMed 

    Google Scholar 
    65.Brum, F. T. et al. Global priorities for conservation across multiple dimensions of mammalian diversity. PNAS 114, 7641–7646 (2017).CAS 
    PubMed 
    PubMed Central 

    Google Scholar  More

  • in

    Connectivity dynamics in Irish mudflats between microorganisms including Vibrio spp., common cockles Cerastoderma edule, and shorebirds

    1.Thieltges, D. W., Mouritsen, K. N. & Poulin, R. in Mudflat Ecology (ed Beninger, P.) (Springer International Publishing, 2018).2.Tyler-Walters, H. Cerastoderma edule Common cockle. Marine Life Information Network: Biology and Sensitivity Key Information Reviews (2007).3.Malham, S. K., Hutchinson, T. H. & Longshaw, M. A review of the biology of European cockles (Cerastoderma spp.). J. Mar. Biol. Assoc. U. K. 92, 1563–1577 (2012).4.Magalhaes, L., Freitas, R., Dairain, A. & De Montaudouin, X. Can host density attenuate parasitism?. J. Mar. Biol. Assoc. U. K. 97, 497–505 (2017).
    Google Scholar 
    5.Carss, D. N. et al. Ecosystem services provided by a non-cultured shellfish species: The common cockle Cerastoderma edule. Mar. Environ. Res. 158, 104931 (2020).CAS 
    PubMed 

    Google Scholar 
    6.Lassalle, G., de Montaudouin, X., Soudant, P. & Paillard, C. Parasite co-infection of two sympatric bivalves, the Manila clam (Ruditapes philippinarum) and the cockle (Cerastoderma edule) along a latitudinal gradient. Aquat. Living Resour. 20, 33–42 (2007).
    Google Scholar 
    7.Hoberg, E. P. Faunal diversity among avian parasite assemblages: the interaction of history, ecology and biogeography in marine systems. Bull. Scand. Soc. Parasitol. 6, 65–89 (1996).
    Google Scholar 
    8.Muzaffar, S. B. & Jones, I. L. Parasites and diseases of auks (Alcidae) of the world and their ecology-A review. Mar. Ornithol. 32, 121–146 (2004).
    Google Scholar 
    9.Lafferty, K. D., Dobson, A. P. & Kuris, A. M. Parasites dominate food web links. Proc. Natl. Acad. Sci. U. S. A. 103, 11211–11216 (2006).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    10.Lafferty, K. D. et al. Parasites in food webs: The ultimate missing links. Ecol. Lett. 11, 533–546 (2008).PubMed 
    PubMed Central 

    Google Scholar 
    11.Johnson, P. T. J. et al. When parasites become prey: ecological and epidemiological significance of eating parasites. Trends Ecol. Evol. 25, 362–371 (2010).PubMed 

    Google Scholar 
    12.Zannella, C. et al. Microbial diseases of bivalve mollusks: Infections, immunology and antimicrobial defense. Mar. Drugs 15, 182 (2017).PubMed Central 

    Google Scholar 
    13.Fermer, J., Culloty, S. C., Kelly, T. C. & O’riordan, R. M. Parasitological survey of the edible cockle Cerastoderma edule (Bivalvia) on the south coast of Ireland. J. Mar. Biol. Assoc. U. K. 91, 923–928 (2011).
    Google Scholar 
    14.Longshaw, M. & Malham, S. K. A review of the infectious agents, parasites, pathogens and commensals of European cockles (Cerastoderma edule and C. glaucum) (vol 93, pg 227, 2013). J. Mar. Biol. Assoc. U. K. 93, 1141 (2013).15.Newman, S. H. et al. Aquatic bird disease and mortality as an indicator of changing ecosystem health. Mar. Ecol. Prog. Ser. 352, 299–309 (2007).ADS 

    Google Scholar 
    16.Vezzulli, L. et al. Climate influence on Vibrio and associated human diseases during the past half-century in the coastal North Atlantic. Proc. Natl. Acad. Sci. U. S. A. 113, E5062–E5071 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    17.Jesser, K. J. & Noble, R. T. Vibrio ecology in the Neuse River Estuary, North Carolina, characterized by next-generation amplicon sequencing of the gene encoding heat shock protein 60 (hsp60). Appl. Environ. Microbiol. 84, e00333-e418 (2018).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    18.Romalde, J. L., Dieguez, A. L., Lasa, A. & Balboa, S. New Vibrio species associated to molluscan microbiota: A review. Front. Microbiol. 4, 413 (2014).PubMed 
    PubMed Central 

    Google Scholar 
    19.Allam, B., Paillard, C. & Ford, S. Pathogenicity of Vibrio tapetis, the etiological agent of brown ring disease in clams. Dis. Aquat. Org. 48, 221–231 (2002).
    Google Scholar 
    20.Waechter, M., Le Roux, F., Nicolas, J., Marissal, E. & Berthe, F. Characterisation of Crassostrea gigas spat pathogenic bacteria. C.R. Biol. 325, 231–238 (2002).CAS 
    PubMed 

    Google Scholar 
    21.Gay, M., Renault, T., Pons, A. & Le Roux, F. Two Vibrio splendidus related strains collaborate to kill Crassostrea gigas: Taxonomy and host alterations. Dis. Aquat. Org. 62, 65–74 (2004).
    Google Scholar 
    22.Paillard, C., Le Roux, F. & Borrego, J. Bacterial disease in marine bivalves, a review of recent studies: Trends and evolution. Aquat. Living Resour. 17, 477–498 (2004).
    Google Scholar 
    23.Prado, S., Romalde, J., Montes, J. & Barja, J. Pathogenic bacteria isolated from disease outbreaks in shellfish hatcheries. First description of Vibrio neptunius as an oyster pathogen. Dis. Aquat. Org. 67, 209–215 (2005).CAS 

    Google Scholar 
    24.Garnier, M., Labreuche, Y. & Nicolas, J. Molecular and phenotypic characterization of Vibrio aestuarianus subsp francensis subsp nov., a pathogen of the oyster Crassostrea gigas. Syst. Appl. Microbiol. 31, 358–365 (2008).CAS 
    PubMed 

    Google Scholar 
    25.Egerton, S., Culloty, S., Whooley, J., Stanton, C. & Ross, R. P. The gut microbiota of marine fish. Front. Microbiol. 9, 873 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    26.Vezzulli, L., Colwell, R. R. & Pruzzo, C. Ocean warming and spread of pathogenic vibrios in the aquatic environment. Microb. Ecol. 65, 817–825 (2013).PubMed 

    Google Scholar 
    27.Vezzulli, L. et al. Aquatic ecology of the oyster pathogens Vibrio splendidus and Vibrio aestuarianus. Environ. Microbiol. 17, 1065–1080 (2015).CAS 
    PubMed 

    Google Scholar 
    28.Azandegbe, A. et al. Occurrence and seasonality of Vibrio aestuarianus in sediment and Crassostrea gigas haemolymph at two oyster farms in France. Dis. Aquat. Org. 91, 213–221 (2010).
    Google Scholar 
    29.Burreson, E. & Ford, S. A review of recent information on the Haplosporidia, with special reference to Haplosporidium nelsoni (MSX disease). Aquat. Living Resour. 17, 499–517 (2004).
    Google Scholar 
    30.Engelsma, M. Y. et al. Digenean trematodes and haplosporidian protozoans associated with summer mortality of cockles Cerastoderma edule in the Oosterschelde, The Netherlands. (European Association of Fish Pathologists Conference, Split, Croatia., 2011).31.Arzul, I. & Carnegie, R. B. New perspective on the haplosporidian parasites of molluscs. J. Invertebr. Pathol. 131, 32–42 (2015).PubMed 

    Google Scholar 
    32.Carnegie, R. B., Arzul, I. & Bushek, D. Managing marine mollusc diseases in the context of regional and international commerce: Policy issues and emerging concerns. Philos. Trans. R. Soc. B-Biol. Sci. 371, 20150215 (2016).
    Google Scholar 
    33.Ramilo, A., Abollo, E., Villalba, A. & Carballal, M. J. A Minchinia mercenariae-like parasite infects cockles Cerastoderma edule in Galicia (NW Spain). J. Fish Dis. 41, 41–48 (2018).CAS 
    PubMed 

    Google Scholar 
    34.Lynch, S. A. et al. Detection of haplosporidian protistan parasites supports an increase to their known diversity, geographic range and bivalve host specificity. Parasitology 147, 584–592 (2020).CAS 
    PubMed 

    Google Scholar 
    35.Albuixech-Marti, S., Lynch, S. A. & Culloty, S. C. Biotic and abiotic factors influencing haplosporidian species distribution in the cockle Cerastoderma edule in Ireland. J. Invertebr. Pathol. 174, 107425 (2020).CAS 
    PubMed 

    Google Scholar 
    36.Azevedo, C., Conchas, R. & Montes, J. Description of Haplosporidium edule n. sp (Phylum Haplosporidia), a parasite of Cerastoderma edule (Mollusca, Bivalvia) with complex spore ornamentation. Eur. J. Protistol. 39, 161–167 (2003).
    Google Scholar 
    37.Carballal, M., Diaz, S. & Villalba, A. Urosporidium sp hyperparasite of the turbellarian Paravortex cardii in the cockle Cerastoderma edule. J. Invertebr. Pathol. 90, 104–107 (2005).PubMed 

    Google Scholar 
    38.Daoust, P., Conboy, G., McBurney, S. & Burgess, N. Interactive mortality factors in common loons from Maritime Canada. J. Wildl. Dis. 34, 524–531 (1998).CAS 
    PubMed 

    Google Scholar 
    39.Converse, K. & Kidd, G. Duck plague epizootics in the United States, 1967–1995. J. Wildl. Dis. 37, 347–357 (2001).CAS 
    PubMed 

    Google Scholar 
    40.Friend, M., McLean, R. & Dein, F. Disease emergence in birds: Challenges for the twenty-first century. Auk 118, 290–303 (2001).
    Google Scholar 
    41.Hubalek, Z. An annotated checklist of pathogenic microorganisms associated with migratory birds. J. Wildl. Dis. 40, 639–659 (2004).PubMed 

    Google Scholar 
    42.Quesada, R. J. et al. Detection and phylogenetic characterization of a novel herpesvirus from the trachea of two stranded common loons (Gavia immer). J. Wildl. Dis. 47, 233–239 (2011).PubMed 

    Google Scholar 
    43.Niemeyer, C. et al. Genetically diverse herpesviruses in South American Atlantic coast seabirds. PLoS ONE 12, e0178811 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    44.Bookelaar, B., Lynch, S. A. & Culloty, S. C. Host plasticity supports spread of an aquaculture introduced virus to an ecosystem engineer. Parasit. Vectors 13, 498 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    45.Honjo, M. N., Minamoto, T. & Kawabata, Z. Reservoirs of Cyprinid herpesvirus 3 (CyHV-3) DNA in sediments of natural lakes and ponds. Vet. Microbiol. 155, 183–190 (2012).CAS 
    PubMed 

    Google Scholar 
    46.Evans, O., Paul-Pont, I. & Whittington, R. J. Detection of ostreid herpesvirus 1 microvariant DNA in aquatic invertebrate species, sediment and other samples collected from the Georges River estuary, New South Wales, Australia. Dis. Aquat. Org. 122, 247–255 (2017).CAS 

    Google Scholar 
    47.Slodkowicz-Kowalska, A. et al. Microsporidian species known to infect humans are present in aquatic birds: Implications for transmission via water?. Appl. Environ. Microbiol. 72, 4540–4544 (2006).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    48.Malcekova, B., Valencakova, A., Molnar, L. & Kocisova, A. First detection and genotyping of human-associated microsporidia in wild waterfowl of Slovakia. Acta Parasitol. 58, 13–17 (2013).CAS 
    PubMed 

    Google Scholar 
    49.Fermer, J., Culloty, S. C., Kelly, T. C. & O’Riordan, R. M. Intrapopulational distribution of Meiogymnophallus minutus (Digenea, Gymnophallidae) infections in its first and second intermediate host. Parasitol. Res. 105, 1231–1238 (2009).PubMed 

    Google Scholar 
    50.Yun, Y. et al. Phylogenetic analysis of severe fever with thrombocytopenia syndrome virus in South Korea and migratory bird routes between China, South Korea, and Japan. Am. J. Trop. Med. Hyg. 93, 468–474 (2015).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    51.Xu, Y., Gong, P., Wielstra, B. & Si, Y. Southward autumn migration of waterfowl facilitates cross-continental transmission of the highly pathogenic avian influenza H5N1 virus. Sci. Rep. 6, 30262 (2016).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    52.King, R. A., Read, D. S., Traugott, M. & Symondson, W. O. C. Molecular analysis of predation: A review of best practice for DNA-based approaches. Mol. Ecol. 17, 947–963 (2008).CAS 
    PubMed 

    Google Scholar 
    53.Harper, G. et al. Rapid screening of invertebrate predators for multiple prey DNA targets. Mol. Ecol. 14, 819–827 (2005).CAS 
    PubMed 

    Google Scholar 
    54.Martin, D. L., Ross, R. M., Quetin, L. B. & Murray, A. E. Molecular approach (PCR-DGGE) to diet analysis in young Antarctic krill Euphausia superba. Mar. Ecol. Prog. Ser. 319, 155–165 (2006).ADS 
    CAS 

    Google Scholar 
    55.Read, D. S., Sheppard, S. K., Bruford, M. W., Glen, D. M. & Symondson, W. O. C. Molecular detection of predation by soil micro-arthropods on nematodes. Mol. Ecol. 15, 1963–1972 (2006).CAS 
    PubMed 

    Google Scholar 
    56.Harwood, J. D. et al. Tracking the role of alternative prey in soybean aphid predation by Orius insidiosus: A molecular approach. Mol. Ecol. 16, 4390–4400 (2007).CAS 
    PubMed 

    Google Scholar 
    57.Albuixech-Martí, S., Culloty, S. C. & Lynch, S. A. Co-occurrence of pathogen assemblages in a keystone species the common cockle Cerastoderma edule on the Irish coast. Parasitology, 1–15 (2021).58.Lewis, L. J. & Tierney, T. D. Low tide waterbird surveys: Survey methods and guidance notes. Irish Wildlife Manuals 80 (2014).59.Garcia, C. et al. Vibrio aestuarianus subsp. cardii subsp. nov., pathogenic to the edible cockles Cerastoderma edule in France, and establishment of Vibrio aestuarianus subsp. aestuarianus subsp. nov. and Vibrio aestuarianus subsp. francensis subsp. nov. Int. J. Syst. Evol. Microbiol. 71, 004654 (2021).60.Lacoste, A. et al. A Vibrio splendidus strain is associated with summer mortality of juvenile oysters Crassostrea gigas in the Bay of Morlaix (North Brittany, France). Dis. Aquat. Org. 46, 139–145 (2001).CAS 

    Google Scholar 
    61.Le Roux, F. et al. Comparative analysis of Vibrio splendidus-related strains isolated during Crassostrea gigas mortality events. Aquat. Living Resour. 15, 251–258 (2002).
    Google Scholar 
    62.Garnier, M., Labreuche, Y., Garcia, C., Robert, A. & Nicolas, J. Evidence for the involvement of pathogenic bacteria in summer mortalities of the Pacific oyster Crassostrea gigas. Microb. Ecol. 53, 187–196 (2007).CAS 
    PubMed 

    Google Scholar 
    63.McCleary, S. & Henshilwood, K. Novel quantitative TaqMan (R) MGB real-time PCR for sensitive detection of Vibrio aestuarianus in Crassostrea gigas. Dis. Aquat. Org. 114, 239–248 (2015).CAS 

    Google Scholar 
    64.Halpern, M., Senderovich, Y. & Izhaki, I. Waterfowl-The missing link in epidemic and pandemic cholera dissemination?. PLoS Pathog. 4, e1000173 (2008).PubMed 
    PubMed Central 

    Google Scholar 
    65.Rodríguez, J., López, P., Muñoz, J. & Rodríguez, N. Detection of Vibrio cholerae no toxigenico in migratory and resident birds (Charadriiformes) in a coastal lagoon from northeastern Venezuela. Saber 22, 122–126 (2010).
    Google Scholar 
    66.Fernandez-Delgado, M. et al. Prevalence and distribution of Vibrio spp. in wild aquatic birds of the Southern Caribbean Sea, Venezuela, 2011–12. J. Wildl. Dis. 52, 621–626 (2016).67.Laviad-Shitrit, S., Izhaki, I. & Halpern, M. Accumulating evidence suggests that some waterbird species are potential vectors of Vibrio cholerae. PLoS Pathog. 15, e1007814 (2019).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    68.Buck, J. D. Isolation of Candida-albicans and halophilic Vibrio spp. from aquatic birds in Connecticut and Florida. Appl. Environ. Microbiol. 56, 826–828 (1990).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    69.Miyasaka, J. et al. Isolation of Vibrio parahaemolyticus and Vibrio vulnificus from wild aquatic birds in Japan. Epidemiol. Infect. 134, 780–785 (2006).CAS 
    PubMed 

    Google Scholar 
    70.Fu, S. et al. Long-distance transmission of pathogenic Vibrio species by migratory waterbirds: A potential threat to the public health. Sci. Rep. 9, 16303 (2019).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    71.Senderovich, Y., Izhaki, I. & Halpern, M. Fish as reservoirs and vectors of Vibrio cholerae. PLoS ONE 5, e8607 (2010).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    72.Laviad-Shitrit, S. et al. Great cormorants (Phalacrocorax carbo) as potential vectors for the dispersal of Vibrio cholerae. Sci. Rep. 7, 7973 (2017).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    73.Hossain, Z. Z., Farhana, I., Tulsiani’, S. M., Beguml, A. & Jensen, P. K. M. Transmission and toxigenic potential of Vibrio cholerae in hilsha fish (Tenualosa ilisha) for human consumption in Bangladesh. Front. Microbiol. 9, 222 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    74.Bryant, D. M. Effects of prey density and site character on estuary usage by overwintering waders (Charadrii). Estuar. Coast. Mar. Sci. 9, 369–384 (1979).ADS 

    Google Scholar 
    75.Hicklin, P. W. & Smith, P. C. Selection of foraging sites and invertebrate prey by migrant semipalmated sandpipers, Calidris-pusilla (Pallas), in Minas Basin, Bay of Fundy. Can. J. Zool. 62, 2201–2210 (1984).
    Google Scholar 
    76.Colwell, M. A. & Landrum, S. L. Nonrandom shorebird distribution and fine-scale variation in prey abundance. Condor 95, 94–103 (1993).
    Google Scholar 
    77.Ben-Horin, T., Bidegain, G., Huey, L., Narvaez, D. A. & Bushek, D. Parasite transmission through suspension feeding. J. Invertebr. Pathol. 131, 155–176 (2015).PubMed 

    Google Scholar 
    78.Pruzzo, C., Vezzulli, L. & Colwell, R. R. Global impact of Vibrio cholerae interactions with chitin. Environ. Microbiol. 10, 1400–1410 (2008).CAS 
    PubMed 

    Google Scholar 
    79.Vezzulli, L., Pruzzo, C., Huq, A. & Colwell, R. R. Environmental reservoirs of Vibrio cholerae and their role in cholera. Environ. Microbiol. Rep. 2, 27–33 (2010).PubMed 

    Google Scholar 
    80.Freitas, C., Glatter, T. & Ringgaard, S. The release of a distinct cell type from swarm colonies facilitates dissemination of Vibrio parahaemolyticus in the environment. ISME J. 14, 230–244 (2020).PubMed 

    Google Scholar 
    81.Vezzulli, L. et al. Benthic ecology of Vibrio spp. and pathogenic Vibrio species in a coastal Mediterranean environment (La Spezia Gulf, Italy). Microb. Ecol. 58, 808–818 (2009).CAS 
    PubMed 

    Google Scholar 
    82.Piersma, T., Degoeij, P. & Tulp, I. An evaluation of intertidal feeding habitats from a shorebird perspective – Towards relevant comparisons between temperate and tropical mudflats. Neth. J. Sea Res. 31, 503–512 (1993).
    Google Scholar 
    83.Hervas, A., Tully, O., Hickey, J., O’Keefe, E. & Kelly, K. Assessment, monitoring and management of the Dundalk Bay and Waterford Cockle (Cerastoderma edule) Fisheries in 2007. BIM Fisheries Resource Series 7 (2008).84.Martins, R. C., Catry, T., Santos, C. D., Palmeirim, J. M. & Granadeiro, J. P. Seasonal variations in the diet and foraging behaviour of dunlins Calidris alpina in a South European Estuary: Improved feeding conditions for northward migrants. PLoS ONE 8, e81174 (2013).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    85.Walsh, P. S., Metzger, D. A. & Higuchi, R. Chelex-100 as a medium for simple extraction of DNA for PCR-based typing from forensic material. Biotechniques 10, 506–513 (1991).CAS 
    PubMed 

    Google Scholar 
    86.Lynch, S. A., Mulcahy, M. F. & Culloty, S. C. Efficiency of diagnostic techniques for the parasite, Bonamia ostreae, in the flat oyster, Ostrea edulis. Aquaculture 281, 17–21 (2008).
    Google Scholar 
    87.Zeale, M. R. K., Butlin, R. K., Barker, G. L. A., Lees, D. C. & Jones, G. Taxon-specific PCR for DNA barcoding arthropod prey in bat faeces. Mol. Ecol. Resour. 11, 236–244 (2011).CAS 
    PubMed 

    Google Scholar 
    88.Freire, R., Arias, A., Mendez, J. & Insua, A. Identification of European commercial cockles (Cerastoderma edule and C. glaucum) by species-specific PCR amplification of the ribosomal DNA ITS region. Eur. Food Res. Technol. 232, 83–86 (2011).89.Thompson, J. et al. Diversity and dynamics of a North Atlantic coastal Vibrio community. Appl. Environ. Microbiol. 70, 4103–4110 (2004).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    90.Vezzulli, L. et al. Long-term effects of ocean warming on the prokaryotic community: Evidence from the vibrios. ISME J. 6, 21–30 (2012).PubMed 

    Google Scholar 
    91.Renault, T. et al. Haplosporidiosis in the pacific oyster Crassostrea gigas from the French Atlantic coast. Dis. Aquat. Org. 42, 207–214 (2000).CAS 

    Google Scholar 
    92.Molloy, D. P., Giamberini, L., Stokes, N. A., Burreson, E. M. & Ovcharenko, M. A. Haplosporidium raabei n. sp (Haplosporidia): A parasite of zebra mussels, Dreissena polymorpha (Pallas, 1771). Parasitology 139, 463–477 (2012).93.Lynch, S. A., Dillane, E., Carlsson, J. & Culloty, S. C. Development and assessment of a sensitive and cost-effective polymerase chain reaction to detect ostreid herpesvirus 1 and variants. J. Shellfish Res. 32, 657–664 (2013).
    Google Scholar  More

  • in

    Limited thermal plasticity may constrain ecosystem function in a basally heat tolerant tropical telecoprid dung beetle, Allogymnopleurus thalassinus (Klug, 1855)

    1.Intergovernmental Panel on Climate Change (IPCC). Climate Change 2014: Synthesis Report (Intergovernmental Panel on Climate Change, Geneva) p 52 (2014). https://www.ipcc.ch/report/ar5/wg2/2.Easterling, D. R., Meehl, G. A., Parmesan, C., Karl, T. R. & Mearns, L. O. Climate extremes: Observations, modelling and impacts. Science 5487, 2068–2074 (2000).ADS 

    Google Scholar 
    3.Intergovernmental Panel on Climate Change (IPCC). Climate Change 2007: Synthesis Report (Intergovernmental Panel on Climate Change, Geneva) p 52 (2007). https://www.ipcc.ch/report/ar5/syr/4.Ju, R. T., Zhu, H. Y., Gao, L., Zhu, X. H. & Li, B. Increase in both temperature means, and extremes likely facilitates invasive herbivore outbreaks. Sci. Rep. 5, 15715. https://doi.org/10.1038/srep15715 (2015).CAS 
    Article 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 
    5.World Meteorological Organisation (WMO). State of the Climate in Africa. WMO-No. 1253. 2020. Available at: https://library.wmo.int/doc_num.php?explnum_id=10421. Accessed 12 September 2021.6.Dube, O. P. Impact of climate change vulnerability and adaptation options: Exploring the case for Botswana through Southern Africa: A review. Botswana Notes Rec. 35, 147–168 (2003).
    Google Scholar 
    7.Deutsch, C. A. et al. Impacts of climate warming on terrestrial ectotherms across latitude. Proc. Natl Acad. Sci. 105, 6668–6672 (2008).CAS 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 
    8.Perkins-Kirkpatrick, S. E. & Lewis, S. C. Increasing trends in regional heatwaves. Nat. Commun. 11, 3357. https://doi.org/10.1038/s41467-020-16970-7(2020).9.National Oceanic and Atmospheric Administration (NOAA). Astounding heat obliterates all-time records across the Pacific Northwest and Western Canada in June 2021. Climate. Gov. Science and Information for Climate smart Nation. Available at: https://www.climate.gov/news-features/event-tracker/astounding-heat-obliterates-all-time-records-across-pacific-northwest. Accessed 03 July, 2021.10.UK Met Office. Record breaking Heat wave, July 2019. (2020). Available at: https://www.metoffice.gov.uk/binaries/content/assets/metofficegovuk/pdf/weather/learn-about/uk-past-events/interesting/2019/2019_007_july_heatwave.pdf. Accessed 10 June, 2021.11.Kendon, M. et al. State of the UK Climate 2019. Int. J. Climatol. 40, 1–69 (2020).
    Google Scholar 
    12.Head, L., Adams, M., McGregor, H. V. & Toole, S. Climate change and Australia. Wiley Interdiscipl. Rev. WIREs Clim. Change 5, 175–197 (2014).
    Google Scholar 
    13.Nangombe, S. et al. Record-breaking climate extremes in Africa under stabilized 1.5 °C and 2 °C Global warming scenarios. Nat. Clim. Change 8, 375–380 (2018).14.Gergis, J., Ashcroft, L. & Whetton, P. A. historical perspective on Australian temperature extremes. Clim. Dyn. 55, 843–868 (2020).
    Google Scholar 
    15.Carpaneto, G. M., Mazziotta, A. & Valerio, L. Inferring species decline from collection records: roller dung beetles in Italy (Coleoptera, Scarabaeidae). Divers. Distrib. 13, 903–919 (2007).
    Google Scholar 
    16.Walther, G. R. et al. Ecological responses to recent climate change. Nature 416, 389–395 (2002).CAS 
    PubMed 
    ADS 

    Google Scholar 
    17.Chown, S. L. & Nicolson, S. W. Insect Physiological Ecology: Mechanisms and Patterns (Oxford University Press, 2004).
    Google Scholar 
    18.Huey, R. B. & Kearney, M. R. Dynamics of death by heat. Science 369, 1163. https://doi.org/10.1126/science.abe0320 (2020).CAS 
    Article 
    PubMed 
    ADS 

    Google Scholar 
    19.Jørgensen, L. B. et al. A unifying model to estimate thermal tolerance limits in ectotherms across static, dynamic and fluctuating exposures to thermal stress. Sci. Rep. 11, 12840. https://doi.org/10.1038/s41598-021-92004-6 (2021)20.Buyantuyev, A. & Wu, J. Urban heat islands and landscape heterogeneity: Linking spatiotemporal variations in surface temperatures to land-cover and socioeconomic patterns. Landsc. Ecol. 25, 17–33 (2010).
    Google Scholar 
    21.Aalto, J., Riihimäki, H., Meineri, E., Hylander, K. & Luoto, M. Revealing topoclimatic heterogeneity using meteorological station data. Int. J. Climatol. 37, 544–556 (2017).
    Google Scholar 
    22.Holley, J. M. & Andrew, N. R. Experimental warming alters the relative survival and emigration of two dung beetle species from an Australian dung pat community. Austral. Ecol. 44, 800–811 (2019).
    Google Scholar 
    23.Giannini, T. C. et al. Pollination services at risk: Bee habitats will decrease owing to climate change in Brazil. Ecol. Model. 244, 127–131 (2012).
    Google Scholar 
    24.Wu, X. W. & Sun, S. C. Artificial warming advances egg laying and decreases larval size in the dung beetle, Aphodius erractus (Coleoptera: Scarabaeidae) in a Tibetan alpine meadow. Ann. Zool. Fennici. 49, 174–181 (2012).
    Google Scholar 
    25.Mamantov, M. A. & Sheldon, K. S. Behavioural responses to warming differentially impact survival in introduced and native dung beetles. J. Anim. Ecol. 90, 273–281 (2021).PubMed 

    Google Scholar 
    26.Clusella-Trullas, S., Blackburn, T. N. & Chown, S. L. Climate predictors of temperature performance curves parameters in ectotherms. Am. Nat. 177, 738–751 (2011).PubMed 

    Google Scholar 
    27.Ma, G., Rudolf, V. H. & Ma, C. S. Extreme temperature events alter demographic rates, relative fitness and community structure. Glob. Change Biol. 21, 1794–1808 (2014).ADS 

    Google Scholar 
    28.Gunderson, A. R. & Stillman, J. H. Plasticity in thermal tolerance has limited potential to buffer ectotherms from global warming. Proc. R. Soc. B 282, 20150401. https://doi.org/10.1098/rspb.2015.0401 (2015).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    29.van Heerwaarden, B., Kellermann, V. & Sgrò, C. M. Limited scope for plasticity to increase upper thermal limits. Funct. Ecol. 30, 1947–1956 (2016).
    Google Scholar 
    30.Nyamukondiwa, C., Terblamche, J. S., Marshall, K. E. & Sinclair, B. K. Basal cold but not heat tolerance constrains plasticity among Drosophila species (Diptera: Drosophilidae). J. Evol. Biol. 24, 1927–1938 (2011).CAS 
    PubMed 

    Google Scholar 
    31.Blackburn, S., van Heerwaarden, B., Kellermann, V. & Sgró, C. M. Evolutionary capacity of upper thermal limits: Beyond single trait assessments. J. Exp. Biol. 217, 1918–1924 (2014).PubMed 

    Google Scholar 
    32.Bowler, K. & Terblanche, J. S. Insect thermal tolerance: What is the role of ontogeny, ageing and senescence?. Biol. Rev. Camb. Philos. Soc. 83, 339–355 (2008).PubMed 

    Google Scholar 
    33.Barley, J. M., Cheng, B. S., Sasaki, M., Gignoux-Wolfsohn, S., Hays, C. G., Putnam, A. B., Sheth, S., Villeneuve, A. R. & Kelly, M. Limited plasticity in thermally tolerant ectotherm populations: Evidence for a trade-off. Proc. R. Soc. B (2021). https://doi.org/10.1098/rspb.2021.0765.34.Sgrò, C. M., Terblanche, J. S. & Hoffmann, A. A. What can plasticity contribute to insect responses to climate change?. Annu. Rev. Entomol. 61, 433–451 (2016).PubMed 

    Google Scholar 
    35.Pincebourde, S. & Woods, H. A. There is plenty of room at the bottom: Microclimates drive insect vulnerability to climate change. Curr. Opin. Insect Sci. 41, 63–70 (2020).PubMed 

    Google Scholar 
    36.Woods, A., Pincebourde, S., Dillon, M. E. & Terblanche, J. S. Extended phenotypes: Buffers or amplifiers of climate change?. Trends Ecol. Evol. https://doi.org/10.1016/j.tree.2021.05.010 (2021).Article 
    PubMed 

    Google Scholar 
    37.Gunderson, A. R., Dillon, M. E. & Stillman, J. H. Estimating the benefits of plasticity in ectotherm heat tolerance under natural thermal variability. Funct. Ecol. 31, 1529–1539 (2017).
    Google Scholar 
    38.Esperk, T., Kjaersgaard, A., Walters, R. J., Berger, D. & Blanckenhorn, W. U. Plastic and evolutionary responses to heat stress in a temperate dung fly: Negative correlation between basal and induced heat tolerance?. J. Evol. Biol. 29, 900–915 (2016).CAS 
    PubMed 

    Google Scholar 
    39.Calosi, P., Bilton, D. T. & Spicer, J. I. Thermal tolerance, acclimatory capacity and vulnerability to global climate change. Biol. Lett. 4, 99–102 (2008).PubMed 

    Google Scholar 
    40.van Heerwaarden, B. & Kellermann, V. Does plasticity trade off with basal heat tolerance?. Trends Ecol. Evol. 35, 874–885 (2020).PubMed 

    Google Scholar 
    41.Malhi, Y., Franklin, J., Seddon, N., Solan, M., Turner, M. G., Field, C. B. & Knowlton, N. Climate change and ecosystems: threats, opportunities and solutions. Philos. Trans. R. Soc. B 375, 20190104. https://doi.org/10.1098/rstb.2019.0104 (2020).42.Stillman, J. H. Heat waves, the new normal: Summertime temperature extremes will impact animals, ecosystems, and human communities. Physiology 34, 86–100 (2019).CAS 
    PubMed 

    Google Scholar 
    43.Tewksbury, J. J., Huey, R. B. & Deutsch, C. A. Ecology—Putting the heat on tropical animals. Science 320, 1296–1297 (2008).CAS 
    PubMed 

    Google Scholar 
    44.Kelley, A. M. The role thermal physiology plays in species invasion. Conserv. Physiol. 10, 2. https://doi.org/10.1093/conphys/cou045 (2014).CAS 
    Article 

    Google Scholar 
    45.Mitchell, K. A., Sgró, C. M. & Hoffmann, A. A. Phenotypic plasticity in upper thermal limits is weakly related to Drosophila species distributions. Funct. Ecol. 25, 661–670 (2011).
    Google Scholar 
    46.Allen, J. L., Chown, S. L., Janion-Scheepers, C. & Clusella-Trullas, S. Interactions between rates of temperature change and acclimation affect latitudinal patterns of warming tolerance. Conserv. Physiol. 4, 1–14 (2020).
    Google Scholar 
    47.Edwards, P. B. & Aschenborn, H. H. Patterns of nesting and dung burial in onitis dung beetles: Implications for pasture productivity and fly control. J. Appl. Ecol. 24, 837–851 (1987).
    Google Scholar 
    48.Bertone, M. A., Green, J. T., Washburn, S. P., Poore, M. H. & Watson, D. W. The contribution of tunneling dung beetles to pasture soil nutrition. Forage Grazinglands https://doi.org/10.1094/FG-2006-0711-02-RS (2006).Article 

    Google Scholar 
    49.Yamada, D., Imura, O., Shi, K. & Shibuya, T. Effect of tunneler dung beetles on cattle dung decomposition, soil nutrients and herbage growth. Grassl. Sci. 53, 121–129 (2007).
    Google Scholar 
    50.Slade, E. M. & Roslin, T. Dung beetle species interactions and multifunctionality are affected by an experimentally warmed climate. Oikos 125, 1607–1616 (2016).
    Google Scholar 
    51.Yoshihara, Y. & Sato, S. The relationship between dung beetle species richness and ecosystem functioning. Appl. Soil Ecol. 88, 21–25 (2015).
    Google Scholar 
    52.Manning, P., Slade, E. M., Beynon, S. A. & Lewis, O. T. Functionally rich dung beetle assemblages are required to provide multiple ecosystem services. Agric. Ecosyst. Environ. 218, 87–94 (2016).
    Google Scholar 
    53.Milotić, T. et al. Functionally richer communities improve ecosystem functioning: Dung removal and secondary seed dispersal by dung beetles in the Western Palaearctic. J. Biogeogr. 46, 70–82 (2019).
    Google Scholar 
    54.Slade, E. M., Riutta, T., Roslin, T. & Tuomisto, H. L. The role of dung beetles in reducing greenhouse gas emissions from cattle farming. Sci. Rep. 6, 18140. https://doi.org/10.1038/srep1814 (2016).CAS 
    Article 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 
    55.Penttilä, A. et al. Quantifying beetle-mediated effects on gas fluxes from dung pats. PLoS ONE 8, e71454. https://doi.org/10.1371/journal.pone.0071454 (2013).CAS 
    Article 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 
    56.Spector, S. Scarabaeine dung beetles (Coleoptera: Scarabaeidae: Scarabaeinae): An invertebrate focal taxon for biodiversity research and conservation. Coleopt. Bull. 5, 71–83 (2006).
    Google Scholar 
    57.Osberg, D. C., Hanrahan, S. A. & Doube, B.M. The spatial distribution of Allogymnopleurus thalassinus Klug and A. consocius (Pringuey) (Coleoptera: Scarabaeidae) in an area of mixed soil types in South Africa. J. Entomol. Soc. S. Afr. 55, 85–92 (1992).58.Global Biodiversity Information Facility (GBIF). Allogymnopleurus thalassinus (Klug. 1855) (2020) Available at: https://www.gbif.org/species/1093939. Online Database. Accessed 29 December, 2020.59.Doube, B. M. Dung beetles of Southern Africa. (In: Hanski, I & Cambefort, Y. eds, Chapter 8). In Dung beetle ecology 133–155 (Princeton University Press, Princeton, 2014).60.Janssens, A. Monographie des Gymnopleurides. Verhandelingen Koninklijk Natuurhistorisch Museum Belgie. Brussel, 2, 1–74 (1940).61.Gotcha, N., Machekano, H., Cuthbert, R. N. & Nyamukondiwa, C. Low-temperature tolerance in coprophagic beetle species (Coleoptera: Scarabaeidae): Implications for ecological services. Ecol. Entomol. https://doi.org/10.1111/een.13054 (2021).62.Gittings, T., Giller, P. S. & Stakelum, G. Dung decomposition in contrasting temperate pastures in relation to dung beetle and earthworm activity. Pedobiologia, 38, 455–474 (1994).63.Rosenlew, H. & Roslin, T. Habitat fragmentation and the functional efficiency of temperate dung beetles. Oikos 117, 1659–1666 (2008).
    Google Scholar 
    64.Mitchell, K. A. & Hoffmann, A. A. Thermal ramping rate influences evolutionary potential and species differences for upper thermal limits in Drosophila. Funct. Ecol. 24, 694–700 (2010).
    Google Scholar 
    65.Terblanche, J. S., Nyamukondiwa, C. & Kleynhans, E. Thermal variability alters climatic stress resistance and plastic responses in a globally invasive pest, the Mediterranean fruit fly (Ceratitis capitata). Entomol. Exp. Appl. 137, 304–315 (2010).
    Google Scholar 
    66.Janzen, D. H. Why mountain passes are higher in tropics. Am. Nat. 101, 233–249 (1967).
    Google Scholar 
    67.Somero, G. N. The physiology of climate change: How potentials for acclimatization and genetic adaptation will determine ‘winners’ and ‘losers’. J. Exp. Biol. 213, 912–920 (2010).CAS 
    PubMed 

    Google Scholar 
    68.Overgaard, J., Kristensen, T. N., Mitchell, K. A. & Hoffmann, A. A. Thermal tolerance in widespread and tropical Drosophila species: Does phenotypic plasticity increase with latitude?. Am. Nat. 178, S80–S96 (2011).PubMed 

    Google Scholar 
    69.Terblanche, J. S. et al. Ecologically relevant measures of tolerance to potentially lethal temperatures. J. Exp. Biol. 214, 3713–3725 (2011).PubMed 

    Google Scholar 
    70.Giménez Gómez, V.C., Verdú, J. R. & Zurita, G. A. Thermal niche helps to explain the ability of dung beetles to exploit disturbed habitats. Sci. Rep. 10, 13364. https://doi.org/10.1038/s41598-020-70284-8 (2020).71.Gotcha, N., Machekano, H., Cuthbert, R. N. & Nyamukondiwa, C. Heat tolerance may determine activity time in coprophagic beetle species (Coleoptera: Scarabaeidae). Insect Sci. https://doi.org/10.1111/1744-7917.12844 (2020).Article 
    PubMed 

    Google Scholar 
    72.Nyamukondiwa, C., Chidawanyika, F., Machekano, H., Mutamiswa, R., Sands, B., Mdigiswa, N. & Wall, R. Climate variability differentially impacts thermal fitness traits in three coprophagic beetle species. PLOS One 13(6), e0198610. https://doi.org/10.1371/journal.pone.0198610 (2018).73.Jumbam, K., Jackson, S., Terblanche, J. S., McGeoch, M. A. & Chown, S. Acclimation effects on critical and lethal thermal limits of workers of the Argentine ant, Linepithema humile. J. Insect Physiol. 54, 1008–1014 (2008).CAS 
    PubMed 

    Google Scholar 
    74.Dallas, H. F. & Rivers-Moore, N. A. Critical thermal maxima of aquatic macroinvertebrates: Towards identifying bioindicators of thermal alteration. Hydrobiologia 679, 61–76 (2012).
    Google Scholar 
    75.Gallego, B., Verdú, J. R. & Lobo, J. M. Comparative thermoregulation between different species of dung beetles (Coleoptera: Geotrupinae). J. Thermal Biol. 74, 84–91 (2018).
    Google Scholar 
    76.Qari, S. A. Thermal tolerance of the marine crab, Portunus pelagicus (Brachyura, Portunidae). Crustaceana 87, 827–833 (2014).
    Google Scholar 
    77.Azra, M. N., Mohamad, A., Hidir, A., Taufik, M., Abol-Munafi, A. B. & Ikhwanuddin, M. Critical thermal maxima of two species of intertidal crabs, Scylla olivacea and Thalamita crenata at different acclimation temperatures. Aquacul. Rep. 17, 100301. https://doi.org/10.1016/j.aqrep.2020.100301 (2020)78.Lutterschmidt, W. I. & Hutchison, V. H. The critical thermal maximum: History and critique. Can. J. Zool. 75, 1561–1574 (1997).
    Google Scholar 
    79.Käfer, H. et al. Insects 11, 197. https://doi.org/10.3390/insects11030197 (2020).Article 
    PubMed Central 

    Google Scholar 
    80.Gehring, W. J. & Wehner, R. Heat shock protein synthesis and thermotolerance in Cataglyphis, an ant from the Sahara desert. Proc Natl. Acad. Sci. 92, 2994–2998 (1995).CAS 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 
    81.Bishop, T. R., Robertson, M. P., Van Rensburg, B. & Parr, C. L. Coping with the cold: Minimum temperatures and thermal tolerances dominate the ecology of mountain ants. Ecol. Entomol. 42, 105–114 (2017).
    Google Scholar 
    82.Smolka, J. et al. Dung beetles use their dung ball as a mobile thermal refuge. Curr. Biol. 20, R863–R864. https://doi.org/10.1016/j.cub.2012.08.057 (2012).CAS 
    Article 

    Google Scholar 
    83.Terblanche, J. S., Deere, J. A., Clusella-Trullas, S., Janion, C. & Chown, S. L. Critical thermal limits depend on methodological context. Proc. R. Soc. B: Biol. Sci. 274, 2935–2943 (2007).
    Google Scholar 
    84.Chown, S. L., Jumbam, K. R., Sørensen, J. G. & Terblanche, J. S. Phenotypic variance, plasticity and heritability estimates of critical thermal limits depend on methodological context. Funct. Ecol. 23, 133–140 (2009).
    Google Scholar 
    85.Hoffmann, A. A., Sørensen, J. G. & Loeschcke, V. Adaptation of Drosophila to temperature extremes: bringing together quantitative and molecular approaches. J. Thermal Biol. 28, 175–216 (2003).
    Google Scholar 
    86.Pelster, B. & Burggren, W. W. Responses to environmental stressors in developing animals: Costs and benefits of phenotypic plasticity. In Development and environment (eds Burggren, W. & Dubansky, B.) (Springer, Cham, 2018).
    Google Scholar 
    87.Kristensen, T. N., Kjeldal, H., Schou, M. F. & Nielsen, J. L. Proteomic data reveal a physiological basis for costs and benefits associated with thermal acclimation. J. Exp. Biol. 219, 969–976 (2016).PubMed 

    Google Scholar 
    88.Chanthy, P., Martin, R. J., Gunning, R. V., & Andrew, N. R. The effects of thermal acclimation on lethal temperatures and critical thermal limits in the green vegetable bug, Nezara viridula (L.) (Hemiptera: Pentatomidae). Front. Physiol. 3, 465 https://doi.org/10.3389/fphys.2012.00465 (2012).89.Anthony, S. E., Buddle, C. M., Høye, T. T., Hein, N. & Sinclair, B. J. Thermal acclimation has limited effect on thermal tolerance of summer collected Arctic and sub-Arctic wolf spiders. Comp. Biochem. Physiol. Part A, Mol. Integr. Physiol. 257, 110974 (2021).90.Hofmann, G. & Somero, G. Evidence for protein damage at environmental temperatures: seasonal changes in levels of ubiquitin conjugates and hsp70 in the intertidal mussel Mytilus trossulus. J. Exp. Biol. 198, 1509–1518 (1995).CAS 
    PubMed 

    Google Scholar 
    91.Munang, R., Thiaw, I., Alverson, K., Liu, J. & Han, Z. The role of ecosystem services in climate change adaptation and disaster risk reduction. Curr. Opin. Environ. Sustain. 5, 47–52 (2013).
    Google Scholar 
    92.Department of Wildlife and National Parks (DWNP). Aerial census of animals in Botswana 2012 dry season. Gaborone, Republic of Botswana (2012).93.Braga, R. F., Korasaki, V., Andresen, E. & Louzada, J. Dung beetle community and functions along a habitat-disturbance gradient in the amazon: A rapid assessment of ecological functions associated to biodiversity. PLoS ONE 8, e57786. https://doi.org/10.1371/journal.pone.0057786 (2013).CAS 
    Article 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 
    94.Niino, M. et al. Diel flight activity and habitat preference of dung beetles (Coleoptera: Scarabaeidae) in Peninsular Malaysia. Raffles Bull. Zool. 62, 795–804 (2014).
    Google Scholar 
    95.Beetles of Africa. The Website for the Beetle Collector. Online database available at: http://www.beetlesofafrica.com (2021). Accessed 22 April, 2020.96.Mathur, V. & Schmidt, P. S. Adaptive patterns of phenotypic plasticity in laboratory and field environments in Drosophila melanogaster. Evol. 71, 465–474 (2017).
    Google Scholar 
    97.Chidawanyika, F., Nyamukondiwa, C., Strathie, L., Fischer, K. Effects of thermal regimes, starvation and age on heat tolerance of the Parthenium Beetle Zygogramma bicolorata (Coleoptera: Chrysomelidae) following dynamic and static protocols. PLoS ONE 12(1), e0169371. https://doi.org/10.1371/journal.pone.0169371 (2017).98.Moretti, M. et al. Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Funct. Ecol. 31, 558–567 (2017).
    Google Scholar 
    99.El-Saadi, M. I., Ritchie, M. W., Davis, H. E. & MacMillan, H. A. Warm periods in repeated cold stresses protect Drosophila against iono-regulatory collapse, chilling injury, and reproductive deficits. J. Insect Physiol. 123, 104055. https://doi.org/10.1016/j.jinsphys.2020.104055 (2020).CAS 
    Article 
    PubMed 

    Google Scholar 
    100.Morley, S. A., Peck, L. S., Sunday, J. M., Heiser, S. & Bates, A. E. Physiological acclimation and persistence of ectothermic species under extreme heat events. Glob. Ecol. Biogeogr. 28, 1018–1037 (2019).
    Google Scholar 
    101.Nyamukondiwa, C. & Terblanche, J. S. Within-generation variation of critical thermal limits in adult Mediterranean and Natal fruit flies Ceratitis capitata and Ceratitis rosa: Thermal history affects short-term responses to temperature. Physiol. Entomol. 35, 255–264 (2010).
    Google Scholar 
    102.Weldon, C. W., Terblanche, J. S. & Chown, S. L. Time-course for attainment and reversal of acclimation to constant temperature in two Ceratitis species. J. Thermal Biol. 36, 479–485 (2011).
    Google Scholar 
    103.Sullivan, J. T., Ozman-Sullivan, S. K., Lumaret, J. P., Zalucki, M. P. & Baxter, G. Does one size suit all? Dung pad size and ball production by Scarabaeus sacer (Coleoptera: Scarabaeidae: Scarabaeinae). Eur. J. Entomol. 113, 70–75 (2016).
    Google Scholar 
    104.Nervo, B., Tocco, C., Caprio, C., Palestrini, C. & Rolando, A. Effects of body mass on dung removal efficiency in dung beetles. PLoS ONE 9, e107699. https://doi.org/10.1371/journal.pone.0107699 (2014).CAS 
    Article 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 
    105.Slade, E. M., Mann, D. J., Villanueva, J. M. & Lewis, O. T. Experimental evidence for the effects of dung beetle functional group richness and composition on ecosystem function in a tropical forest. J. Anim. Ecol. 76, 1094–1104 (2007).PubMed 

    Google Scholar 
    106.R Core Team. R: A Language and environment for Statistical computing. R Foundation for Statistical computing, Vienna, Austria. 2021. Available at: https://www.R-project.org/.107.Wobbrock, J. O., Findlater, L., Gergle, D. & Higgins, J. J. The aligned rank transform for nonparametric factorial analyses using only ANOVA procedures, in Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI ’11). Vancouver, British Columbia (May 7–12, 2011) 143–146 (ACM Press, New York, 2011).108.Elkin, L. A., Kay, M., Higgins, J. & Wobbrock, J. O. An aligned rank transform procedure for multifactor contrast tests, in Proceedings of the ACM Symposium on User Interface Software and Technology (UIST ’21). Virtual Event (October 10–13, 2021) (ACM Press, New York, NY, 2021). More

  • in

    Acoustic differentiation and classification of wild belugas and narwhals using echolocation clicks

    1.Madsen, P. T. & Wahlberg, M. Recording and quantification of ultrasonic echolocation clicks from free-ranging toothed whales. Deep. Res. Part I(54), 1421–1444 (2007).
    Google Scholar 
    2.Au, W. W. L. Sonar of Dolphins (Springer, 1993).
    Google Scholar 
    3.Reeves, R. R. et al. Distribution of endemic cetaceans in relation to hydrocarbon development and commercial shipping in a warming Arctic. Mar. Policy 44, 375–389 (2014).
    Google Scholar 
    4.Hauser, D. D. W. et al. Habitat selection by two beluga whale populations in the Chukchi and Beaufort seas. PLoS One 12, e0172755 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    5.Vacquié-Garcia, J., Lydersen, C., Ims, R. A. & Kovacs, K. M. Habitats and movement patterns of white whales Delphinapterus leucas in Svalbard, Norway in a changing climate. Mov. Ecol. 6, 21 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    6.Lydersen, C., Martin, A. R., Kovacs, K. M. & Gjertz, I. Summer and autumn movements of white whales Delphinapterus leucas in Svalbard, Norway. Mar. Ecol. Prog. Ser. 219, 265–274 (2001).ADS 

    Google Scholar 
    7.Innes, S. et al. Surveys of belugas and narwhals in the Canadian High Arctic in 1996. NAMMCO Sci. Publ. 4, 169–190 (2002).
    Google Scholar 
    8.Smith, T. G. & Martin, A. R. Distribution and movements of belugas, Delphinapterus leucas, in the Canadian High Arctic. Can. J. Fish. Aquat. Sci. 51, 1653–1663 (1994).
    Google Scholar 
    9.Hobbs, R. et al. Global review of the conservation status of Monodontid stocks. Mar. Fish. Rev. 81, 1–53 (2019).ADS 

    Google Scholar 
    10.Frost, K. J. & Lowry, L. F. Distribution, abundance, and movements of beluga whales, Delphinapterus leucas, in coastal waters of western Alaska. In Advances in Research on the Beluga Whale, Delphinapterus leucas Vol. 224 (eds Smith, T. G. et al.) 39–57 (Canadian Bulletin of Fisheries and Aquatic Sciences, 1990).
    Google Scholar 
    11.Lewis, A. E., Hammill, M. O., Power, M., Doidge, D. W. & Lesage, V. Movement and aggregation of eastern Hudson Bay beluga whales (Delphinapterus leucas): A comparison of patterns found through satellite telemetry and Nunavik Traditional Ecological Knowledge. Arctic 62, 13–24 (2009).
    Google Scholar 
    12.Ahonen, H., Stafford, K. M., Lydersen, C., Steur, L. D. & Kovacs, K. M. A multi-year study of narwhal occurrence in the western Fram Strait—detected via passive acoustic monitoring. Polar Res. 38, 1–14 (2019).
    Google Scholar 
    13.Heide-Jørgensen, M. P. et al. The migratory behaviour of narwhals (Monodon monoceros). Can. J. Zool. 81, 1298–1305 (2003).
    Google Scholar 
    14.Richard, P. R. et al. Baffin Bay narwhal population distribution and numbers: Aerial surveys in the Canadian High Arctic, 2002–04. Arctic 63, 85–99 (2010).
    Google Scholar 
    15.Dietz, R., Heide-Jørgensen, M. P., Richard, P. R. & Acquarone, M. Summer and fall movements of narwhals (Monodon monoceros) from northeastern Baffin Island towards northern Davis Strait. Arctic 54, 244–261 (2001).
    Google Scholar 
    16.Castellote, M. et al. Monitoring white whales (Delphinapterus leucas) with echolocation loggers. Polar Biol. 36, 493–509 (2013).
    Google Scholar 
    17.Frouin-Mouy, H., Kowarski, K., Martin, B. & Bröker, K. Seasonal trends in acoustic detection of marine mammals in Baffin Bay and Melville Bay, Northwest Greenland. Arctic 70, 59–76 (2017).
    Google Scholar 
    18.Sousa-Lima, R. S., Norris, T. F., Oswald, J. N. & Fernandes, D. P. A review and inventory of fixed autonomous recorders for passive acoustic monitoring of marine mammals. Aquat. Mamm. 39, 23–53 (2013).
    Google Scholar 
    19.Zhong, M. et al. Beluga whale acoustic signal classification using deep learning neural network models. J. Acoust. Soc. Am. 147, 1834–1841 (2020).ADS 
    PubMed 

    Google Scholar 
    20.Castellote, M. et al. Seasonal distribution and foraging occurrence of Cook Inlet beluga whales based on passive acoustic monitoring. Endanger. Species Res. 41, 225–243 (2020).
    Google Scholar 
    21.Sjare, B. L. & Smith, T. G. The vocal repertoire of white whales, Delphinapterus leucas, summering in Cunningham Inlet, Northwest Territories. Can. J. Zool. 64, 407–415 (1986).
    Google Scholar 
    22.Chmelnitsky, E. G. & Ferguson, S. H. Beluga whale, Delphinapterus leucas, vocalizations from the Churchill River, Manitoba, Canada. J. Acoust. Soc. Am. 131, 4821–4835 (2012).ADS 
    PubMed 

    Google Scholar 
    23.Marcoux, M., Auger-Méthé, M. & Humphries, M. M. Variability and context specificity of narwhal (Monodon monoceros) whistles and pulsed calls. Mar. Mammal Sci. 28, 649–665 (2012).
    Google Scholar 
    24.Garland, E. C., Castellote, M. & Berchok, C. L. Beluga whale (Delphinapterus leucas) vocalizations and call classification from the eastern Beaufort Sea population. J. Acoust. Soc. Am. 137, 3054–3067 (2015).ADS 
    PubMed 

    Google Scholar 
    25.Rasmussen, M. H., Koblitz, J. C. & Laidre, K. L. Buzzes and high-frequency clicks recorded from narwhals (Monodon monoceros) at their wintering ground. Aquat. Mamm. 41, 256–264 (2015).
    Google Scholar 
    26.McCullough, J. L. K., Simonis, A. E., Sakai, T. & Oleson, E. M. Acoustic classification of false killer whales in the Hawaiian islands based on comprehensive vocal repertoire. JASA Express Lett. 1, 071201 (2021).
    Google Scholar 
    27.Ford, J. K. B. & Fisher, H. D. Underwater acoustic signals of the narwhal (Monodon monoceros). Can. J. Zool. 56, 552–560 (1978).
    Google Scholar 
    28.Rankin, S. et al. Acoustic classification of dolphins in the California Current using whistles, echolocation clicks, and burst pulses. Mar. Mammal Sci. 33, 520–540 (2017).
    Google Scholar 
    29.Walmsley, S. F., Rendell, L., Hussey, N. E. & Marcoux, M. Vocal sequences in narwhals (Monodon monoceros). J. Acoust. Soc. Am. 147, 1078–1091 (2020).ADS 
    PubMed 

    Google Scholar 
    30.Shapiro, A. D. Preliminary evidence for signature vocalizations among free-ranging narwhals (Monodon monceros). J. Acoust. Soc. Am. 120, 1695–1705 (2006).ADS 
    PubMed 

    Google Scholar 
    31.Simões Amorim, T. O. et al. Integrative bioacoustics discrimination of eight delphinid species in the western South Atlantic Ocean. PLoS One 14, e0217977 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    32.Stafford, K. M., Laidre, K. L. & Heide-Jørgensen, M. P. First acoustic recordings of narwhals (Monodon monoceros) in winter. Mar. Mammal Sci. 28, 197–207 (2012).
    Google Scholar 
    33.Castellote, M. et al. Dual instrument passive acoustic monitoring of belugas in Cook Inlet, Alaska. J. Acoust. Soc. Am. 139, 2697–2707 (2016).ADS 
    PubMed 

    Google Scholar 
    34.Lammers, M. O. et al. Passive acoustic monitoring of Cook Inlet beluga whales (Delphinapterus leucas). J. Acoust. Soc. Am. 134, 2497–2504 (2013).ADS 
    PubMed 

    Google Scholar 
    35.Roch, M. A., Stinner-Sloan, J., Baumann-Pickering, S. & Wiggins, S. M. Compensating for the effects of site and equipment variation on delphinid species identification from their echolocation clicks. J. Acoust. Soc. Am. 137, 22–29 (2015).ADS 
    PubMed 

    Google Scholar 
    36.Au, W. W., Penner, R. H., Carder, D. A. & Scronce, B. Demonstration of adaptation in beluga whale echolocation signals. J. Acoust. Soc. Am. 77, 726–730 (1985).ADS 
    CAS 
    PubMed 

    Google Scholar 
    37.Au, W. W. L., Penner, R. H. & Turl, C. W. Propagation of beluga echolocation signals. J. Acoust. Soc. Am. 82, 807–813 (1987).ADS 
    CAS 
    PubMed 

    Google Scholar 
    38.Roy, N., Simard, Y., Gervaise, C. & Dtn, E. 3D tracking of foraging belugas from their clicks: Experiment from a coastal hydrophone array. Appl. Acoust. 71, 1050–1056 (2010).
    Google Scholar 
    39.Zahn, M. J., Laidre, K. L., Stilz, P., Rasmussen, M. H. & Koblitz, J. C. Vertical sonar beam width of wild belugas (Delphinapterus leucas) in West Greenland. PLoS One 16, e0257054 (2021).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    40.Rutenko, A. N. & Vishnyakov, A. A. Time sequences of sonar signals generated by a beluga whale when locating underwater objects. Acoust. Phys. 52, 314–323 (2006).ADS 

    Google Scholar 
    41.Koblitz, J. C., Stilz, P., Rasmussen, M. H. & Laidre, K. L. Highly directional sonar beam of narwhals (Monodon monoceros) measured with a vertical 16 hydrophone array. PLoS One 11, e0162069 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    42.Podolskiy, E. A. & Sugiyama, S. Soundscape of a narwhal summering ground in a glacier fjord (Inglefield Bredning, Greenland). J. Geophys. Res. Ocean. 125, e2020JC016116 (2020).ADS 

    Google Scholar 
    43.Miller, L. A., Pristed, J., Mohl, B. & Surlykke, A. The click-sounds of narwhals (Monodon monoceros) in Inglefield Bay, Northwest Greenland. Mar. Mammal Sci. 11, 491–502 (1995).
    Google Scholar 
    44.Marcoux, M., Auger-Methe, M., Chmelnitsky, E., Ferguson, S. H. & Humphries, M. M. Local passive acoustic monitoring of narwhal presence in the Canadian Arctic: A pilot project. Arctic 64, 307–316 (2011).
    Google Scholar 
    45.Overland, J. et al. The urgency of Arctic change. Polar Sci. 21, 6–13 (2019).ADS 

    Google Scholar 
    46.Comiso, J. C. & Hall, D. K. Climate trends in the Arctic as observed from space. WIREs Clim. Change 5, 389–409 (2014).
    Google Scholar 
    47.Kwok, R. Arctic sea ice thickness, volume, and multiyear ice coverage: Losses and coupled variability (1958–2018). Environ. Res. Lett. 13, 105005 (2018).
    Google Scholar 
    48.Overland, J. E. & Wang, M. When will the summer Arctic be nearly sea ice free?. Geophys. Res. Lett. 40, 2097–2101 (2013).ADS 

    Google Scholar 
    49.Smith, L. C. & Stephenson, S. R. New Trans-Arctic shipping routes navigable by midcentury. Proc. Natl. Acad. Sci. U.S.A. 110, E1191–E1195 (2013).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    50.Hauser, D. D. W., Laidre, K. L. & Stern, H. L. Vulnerability of Arctic marine mammals to vessel traffic in the increasingly ice-free Northwest Passage and Northern Sea Route. Proc. Natl. Acad. Sci. U.S.A. 115, 7617–7622 (2018).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    51.Halliday, W. D., Pine, M. K. & Insley, S. J. Underwater noise and Arctic marine mammals: Review and policy recommendations. Environ. Rev. 28, 438–448 (2020).
    Google Scholar 
    52.Halliday, W. D. et al. Underwater sound levels in the Canadian Arctic, 2014–2019. Mar. Pollut. Bull. 168, 112437 (2021).CAS 
    PubMed 

    Google Scholar 
    53.Kochanowicz, Z. et al. Using western science and Inuit knowledge to model ship-source noise exposure for cetaceans (marine mammals) in Tallurutiup Imanga (Lancaster Sound), Nunavut, Canada. Mar. Policy 130, 104557 (2021).
    Google Scholar 
    54.Stewart, R. E. A., Lesage, V., Lawson, J. W., Cleator, H. & Martin, K. A. Science technical review of the draft Environmental Impact Statement (EIS) for Baffinland’s Mary River Project (Canadian Science Advisory Secretariat, Fisheries and Oceans Canada, 2011).
    Google Scholar 
    55.Heide-Jørgensen, M. P., Hansen, R. G., Westdal, K., Reeves, R. R. & Mosbech, A. Narwhals and seismic exploration: Is seismic noise increasing the risk of ice entrapments?. Biol. Conserv. 158, 50–54 (2013).
    Google Scholar 
    56.Blackwell, S. B., Greene, C. R. & Richardson, W. J. Drilling and operational sounds from an oil production island in the ice-covered Beaufort Sea. J. Acoust. Soc. Am. 116, 3199–3211 (2004).ADS 
    PubMed 

    Google Scholar 
    57.Yang, W. et al. Anthropogenic sound exposure-induced stress in captive dolphins and implications for cetacean health. Front. Mar. Sci. 8, 606736 (2021).
    Google Scholar 
    58.Erbe, C. & Farmer, D. M. Zones of impact around icebreakers affecting beluga whales in the Beaufort Sea. J. Acoust. Soc. Am. 108, 1332–1340 (2000).ADS 
    CAS 
    PubMed 

    Google Scholar 
    59.Heide-Jørgensen, M. P. et al. Behavioral response study on seismic airgun and vessel exposures in narwhals. Front. Mar. Sci. 8, 658173 (2021).
    Google Scholar 
    60.Gillespie, D., Mellinger, D. K., Gordon, J. & Al, E. PAMGUARD: Semiautomated, open source software for real-time acoustic detection and localization of cetaceans. Proc. Inst. Acoust. 30, 54–62 (2008).
    Google Scholar 
    61.Sakai, T. PAMpal: Load and process passive acoustic data. R package version 0.12.6. http://cran.r-project.org/package=PAMpal (2021).62.R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing http://www.r-project.org/ (2021).63.Griffiths, E. T. et al. Detection and classification of narrow-band high frequency echolocation clicks from drifting recorders. J. Acoust. Soc. Am. 147, 3511–3522 (2020).ADS 
    PubMed 

    Google Scholar 
    64.Baumann-Pickering, S., Wiggins, S. M., Hildebrand, J. A., Roch, M. A. & Schnitzler, H. Discriminating features of echolocation clicks of melon-headed whales (Peponocephala electra), bottlenose dolphins (Tursiops truncatus), and Gray’s spinner dolphins (Stenella longirostris longirostris). J. Acoust. Soc. Am. 128, 2212–2224 (2010).ADS 
    PubMed 

    Google Scholar 
    65.Sakai, T. PAMpal standardClickCalcs. https://taikisan21.github.io/PAMpal/StandardCalcs.html (2021).66.Anderson, M. J. A new method for non-parametric multivariate analysis of variance. Austral Ecol. 26, 32–46 (2001).
    Google Scholar 
    67.Anderson, M. J. Distance-based tests for homogeneity of multivariate dispersions. Biometrics 62, 245–253 (2006).MathSciNet 
    PubMed 
    MATH 

    Google Scholar 
    68.Anderson, M. J. Permutational Multivariate Analysis of Variance (PERMANOVA). Wiley StatsRef Stat. Ref. Online https://doi.org/10.1002/9781118445112.stat07841 (2017).Article 

    Google Scholar 
    69.Pearson, K. On lines and planes of closest fit to systems of points in space. Philos. Mag. 2, 559–572 (1901).MATH 

    Google Scholar 
    70.Lever, J., Krzywinski, M. & Altman, N. Principal component analysis. Nat. Methods 14, 641–642 (2017).CAS 

    Google Scholar 
    71.Jackson, D. A. Stopping rules in principal components analysis: A comparison of heuristical and statistical approaches. Ecology 74, 2204–2214 (1993).
    Google Scholar 
    72.Oksanen, J. et al. Vegan: Community ecology package. R package version 2.5-7. https://cran.r-project.org/package=vegan (2020).73.Breiman, L. Random forests. Mach. Learn. 45, 5–32 (2001).MATH 

    Google Scholar 
    74.Yang, L. et al. Description and classification of echolocation clicks of Indian Ocean humpback (Sousa plumbea) and Indo-Pacific bottlenose (Tursiops aduncus) dolphins from Menai Bay, Zanzibar, East Africa. PLoS One 15, e0230319 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    75.Archer, F. I., Rankin, S., Stafford, K. M., Castellote, M. & Delarue, J. Quantifying spatial and temporal variation of North Pacific fin whale (Balaenoptera physalus) acoustic behavior. Mar. Mammal Sci. 36, 224–245 (2020).
    Google Scholar 
    76.Ross, J. C. & Allen, P. E. Random Forest for improved analysis efficiency in passive acoustic monitoring. Ecol. Inform. 21, 34–39 (2014).
    Google Scholar 
    77.Liaw, A. & Wiener, M. Classification and regression by randomForest. R News 2, 18–22 (2002).
    Google Scholar 
    78.Archer, E. rfPermute: Estimate permutation p-values for Random Forest importance metrics. R package version 2.5. https://github.com/EricArcher/rfPermute (2021).79.Gurevich, V. S. & Evans, W. E. Echolocation discrimination of complex planar targets by the Beluga whale (Delphinapterus leucas). J. Acoust. Soc. Am. 60, S5 (1976).ADS 

    Google Scholar 
    80.Soldevilla, M. S. et al. Classification of Risso’s and Pacific white-sided dolphins using spectral properties of echolocation clicks. J. Acoust. Soc. Am. 124, 609–624 (2008).ADS 
    PubMed 

    Google Scholar 
    81.Morisaka, T., Yoshida, Y., Akune, Y., Mishima, H. & Nishimoto, S. Exchange of ‘signature’ calls in captive belugas (Delphinapterus leucas). J. Ethol. 31, 141–149 (2013).
    Google Scholar 
    82.Vergara, V., Michaud, R. & Barrett-Lennard, L. G. What can captive whales tell us about their wild counterparts? Identification, usage, and ontogeny of contact calls in belugas (Delphinapterus leucas). Int. J. Comp. Psychol. 23, 278–309 (2010).
    Google Scholar 
    83.Vergara, V. & Mikus, M. A. Contact call diversity in natural beluga entrapments in an Arctic estuary: Preliminary evidence of vocal signatures in wild belugas. Mar. Mammal Sci. 35, 434–465 (2019).
    Google Scholar 
    84.Panova, E. M. et al. Intraspecific variability in the ‘vowel’-like sounds of beluga whales (Delphinapterus leucas): Intra- and interpopulation comparisons. Mar. Mammal Sci. 32, 452–465 (2016).
    Google Scholar 
    85.Ames, A. E., Blackwell, S. B., Tervo, O. M. & Heide-Jørgensen, M. P. Evidence of stereotyped contact call use in narwhal (Monodon monoceros) mother-calf communication. PLoS One 16, e0254393 (2021).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    86.Baumann-Pickering, S. et al. False killer whale and short-finned pilot whale acoustic identification. Endanger. Species Res. 28, 97–108 (2015).
    Google Scholar 
    87.Halliday, W. D. et al. Potential exposure of beluga and bowhead whales to underwater noise from ship traffic in the Beaufort and Chukchi Seas. Ocean Coast. Manag. 204, 105473 (2021).
    Google Scholar 
    88.Laidre, K. L., Jørgensen, O. A. & Treble, M. A. Deep-ocean predation by a high Arctic cetacean. ICES J. Mar. Sci. 61, 430–440 (2004).
    Google Scholar 
    89.Laidre, K. L., Heide-Jørgensen, M. P., Dietz, R., Hobbs, R. C. & Jørgensen, O. A. Deep-diving by narwhals Monodon monoceros: Differences in foraging behavior between wintering areas?. Mar. Ecol. Prog. Ser. 261, 269–281 (2003).ADS 

    Google Scholar 
    90.Lydersen, C. & Kovacs, K. M. A review of the ecology and status of white whales (Delphinapterus leucas) in Svalbard, Norway. Polar Res. 40, 5509 (2021).
    Google Scholar 
    91.Hauser, D. D. W. et al. Regional diving behavior of Pacific Arctic beluga whales Delphinapterus leucas and possible associations with prey. Mar. Ecol. Prog. Ser. 541, 245–264 (2015).ADS 

    Google Scholar 
    92.Ragen, T. J., Huntington, H. P. & Hovelsrud, G. K. Conservation of Arctic marine mammals faced with climate change. Ecol. Appl. 18, S166–S174 (2008).PubMed 

    Google Scholar 
    93.Laidre, K. L. et al. Quantifying the sensitivity of Arctic marine mammals to climate-induced habitat change. Ecol. Appl. 18, S97–S125 (2008).PubMed 

    Google Scholar 
    94.Heide-Jørgensen, M. P., Dietz, R., Laidre, K. L. & Richard, P. Autumn movements, home ranges, and winter density of narwhals (Monodon monoceros) tagged in Tremblay Sound, Baffin Island. Polar Biol. 25, 331–341 (2002).
    Google Scholar 
    95.Hauser, D. D. W., Laidre, K. L., Suydam, R. S. & Richard, P. R. Population-specific home ranges and migration timing of Pacific Arctic beluga whales (Delphinapterus leucas). Polar Biol. 37, 1171–1183 (2014).
    Google Scholar 
    96.Huntington, H. P. A preliminary assessment of threats to Arctic marine mammals and their conservation in the coming decades. Mar. Policy 33, 77–82 (2009).
    Google Scholar 
    97.Gregersen, U., Hopper, J. R. & Knutz, P. C. Basin seismic stratigraphy and aspects of prospectivity in the NE Baffin Bay, Northwest Greenland. Mar. Pet. Geol. 46, 1–18 (2013).
    Google Scholar 
    98.McCauley, R. D. et al. Widely used marine seismic survey air gun operations negatively impact zooplankton. Nat. Ecol. Evol. 1, 0195 (2017).
    Google Scholar  More