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    Hunting shapes wildlife disease transmission

    1.Wobeser, G. Rev. Sci. Tech. 21, 159–178 (2002).CAS 
    Article 

    Google Scholar 
    2.Fountain-Jones, N. M. et al. Nat. Ecol. Evol. https://doi.org/10.1038/10.1038/s41559-021-01635-5 (2021).Article 

    Google Scholar 
    3.Lloyd-Smith, J. O. et al. Trends Ecol. Evol. 20, 511–519 (2005).Article 

    Google Scholar 
    4.Woodroffe, R. et al. Proc. Natl Acad. Sci. USA 103, 14713–14717 (2006).CAS 
    Article 

    Google Scholar 
    5.Ham, C., Donnelly, C. A., Astley, K. L., Jackson, S. Y. B. & Woodroffe, R. J. Appl. Ecol. 56, 2390–2399 (2019).Article 

    Google Scholar 
    6.Logan, K. A. & Runge, J. P. Wildl. Monogr. 209, 1–35 (2021).Article 

    Google Scholar 
    7.Fountain-Jones, N. M. et al. Commun. Biol. 4, 12 (2021).Article 

    Google Scholar  More

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    Niche differentiation of sulfur-oxidizing bacteria (SUP05) in submarine hydrothermal plumes

    1.Gartman A, Findlay AJ. Impacts of hydrothermal plume processes on oceanic metal cycles and transport. Nat Geosci. 2020;13:396–402.CAS 

    Google Scholar 
    2.Sander SG, Koschinsky A. Metal flux from hydrothermal vents increased by organic complexation. Nat Geosci. 2011;4:145–50.CAS 

    Google Scholar 
    3.German CR, Casciotti KA, Dutay JC, Heimbürger LE, Jenkins WJ, Measures CI, et al. Hydrothermal impacts on trace element and isotope ocean biogeochemistry. Philos Trans R Soc A Math Phys Eng Sci. 2016;374:20160035.
    Google Scholar 
    4.Ardyna M, Lacour L, Sergi S, d’Ovidio F, Sallée JB, Rembauville M, et al. Hydrothermal vents trigger massive phytoplankton blooms in the Southern Ocean. Nat Commun. 2019;10:1–8.CAS 

    Google Scholar 
    5.McCollom TM. Geochemical constraints on primary productivity in submarine hydrothermal vent plumes. Deep Res Part I Oceanogr Res Pap. 2000;47:85–101.CAS 

    Google Scholar 
    6.Dick GJ, Tebo BM. Microbial diversity and biogeochemistry of the Guaymas Basin deep-sea hydrothermal plume. Environ Microbiol. 2010;12:1334–47.CAS 
    PubMed 

    Google Scholar 
    7.Nakamura K, Takai K. Theoretical constraints of physical and chemical properties of hydrothermal fluids on variations in chemolithotrophic microbial communities in seafloor hydrothermal systems. Prog Earth Planet Sci. 2014;1:1–24.
    Google Scholar 
    8.Dick GJ. The microbiomes of deep-sea hydrothermal vents: distributed globally, shaped locally. Nat Rev Microbiol. 2019;17:271–83.CAS 
    PubMed 

    Google Scholar 
    9.Sunamura M, Higashi Y, Miyako C, Ishibashi JI, Maruyama A. Two bacteria phylotypes are predominant in the Suiyo Seamount hydrothermal plume. Appl Environ Microbiol. 2004;70:1190–8.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    10.Lavik G, Stührmann T, Brüchert V, Van Der Plas A, Mohrholz V, Lam P, et al. Detoxification of sulphidic African shelf waters by blooming chemolithotrophs. Nature. 2009;457:581–4.CAS 
    PubMed 

    Google Scholar 
    11.Canfield DE, Stewart FJ, Thamdrup B, De Brabandere L, Dalsgaard T, Delong EF, et al. A cryptic sulfur cycle in oxygen-minimum-zone waters off the Chilean coast. Science. 2010;330:1375–8.CAS 
    PubMed 

    Google Scholar 
    12.Callbeck CM, Lavik G, Ferdelman TG, Fuchs B, Gruber-Vodicka HR, Hach PF, et al. Oxygen minimum zone cryptic sulfur cycling sustained by offshore transport of key sulfur oxidizing bacteria. Nat Commun. 2018;9:1.CAS 

    Google Scholar 
    13.Glaubitz S, Kießlich K, Meeske C, Labrenz M, Jürgens K. SUP05 Dominates the gammaproteobacterial sulfur oxidizer assemblages in pelagic redoxclines of the central baltic and black seas. Appl Environ Microbiol. 2013;79:2767–76.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    14.Pjevac P, Korlević M, Berg JS, Bura-Nakić E, Ciglenečki I, Amann R, et al. Community shift from phototrophic to chemotrophic sulfide oxidation following anoxic holomixis in a stratified seawater lake. Appl Environ Microbiol. 2015;81:298–308.PubMed 

    Google Scholar 
    15.Zhou K, Zhang R, Sun J, Zhang W, Tian RM, Chen C, et al. Potential interactions between clade SUP05 sulfur-oxidizing bacteria and phages in hydrothermal vent sponges. Appl Environ Microbiol. 2019;85:1–20.
    Google Scholar 
    16.Duperron S, Nadalig T, Caprais JC, Sibuet M, Fiala-Médioni A, Amann R, et al. Dual symbiosis in a Bathymodiolus sp. mussel from a methane seep on the Gabon Continental Margin (Southeast Atlantic): 16S rRNA phylogeny and distribution of the symbionts in gills. Appl Environ Microbiol. 2005;71:1694–700.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    17.Ansorge R, Romano S, Sayavedra L, Porras MÁG, Kupczok A, Tegetmeyer HE, et al. Functional diversity enables multiple symbiont strains to coexist in deep-sea mussels. Nat Microbiol. 2019;4:2487–97.PubMed 

    Google Scholar 
    18.Anantharaman K, Breier JA, Sheik CS, Dick GJ. Evidence for hydrogen oxidation and metabolic plasticity in widespread deep-sea sulfur-oxidizing bacteria. Proc Natl Acad Sci USA. 2013;110:330–5.CAS 
    PubMed 

    Google Scholar 
    19.Wang W, Li Z, Zeng L, Dong C, Shao Z. The oxidation of hydrocarbons by diverse heterotrophic and mixotrophic bacteria that inhabit deep-sea hydrothermal ecosystems. ISME J. 2020;14:1994–2006.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    20.Spietz RL, Lundeen RA, Zhao X, Nicastro D, Ingalls AE, Morris RM. Heterotrophic carbon metabolism and energy acquisition in Candidatus Thioglobus singularis strain PS1, a member of the SUP05 clade of marine Gammaproteobacteria. Environ Microbiol. 2019;21:2391–401.CAS 
    PubMed 

    Google Scholar 
    21.Marshall KT, Morris RM. Isolation of an aerobic sulfur oxidizer from the SUP05/Arctic96BD-19 clade. ISME J. 2013;7:452–5.CAS 
    PubMed 

    Google Scholar 
    22.Shah V, Morris RM. Genome sequence of “Candidatus Thioglobus autotrophica” strain EF1, a chemoautotroph from the SUP05 clade of marine Gammaproteobacteria. Genome Announc. 2015;3:e01156–15.PubMed 
    PubMed Central 

    Google Scholar 
    23.van Vliet DM, von Meijenfeldt FAB, Dutilh BE, Villanueva L, Sinninghe Damsté JS, Stams AJM, et al. The bacterial sulfur cycle in expanding dysoxic and euxinic marine waters. Environ Microbiol. 2021;23:2834–57.PubMed 

    Google Scholar 
    24.De Ronde CEJ, Baker ET, Massoth GJ, Lupton JE, Wright IC, Feely RA, et al. Intra-oceanic subduction-related hydrothermal venting, Kermadec volcanic arc, New Zealand. Earth Planet Sci Lett. 2001;193:359–69.
    Google Scholar 
    25.De Ronde CEJ, Baker ET, Massoth GJ, Lupton JE, Wright IC, Sparks RJ, et al. Submarine hydrothermal activity along the mid-Kermadec Arc, New Zealand: large-scale effects on venting. Geochem Geophys Geosyst. 2007;8:Q07007.
    Google Scholar 
    26.Kleint C, Bach W, Diehl A, Fröhberg N, Garbe-Schönberg D, Hartmann JF, et al. Geochemical characterization of highly diverse hydrothermal fluids from volcanic vent systems of the Kermadec intraoceanic arc. Chem Geol. 2019;528:119289.CAS 

    Google Scholar 
    27.Baker ET, Resing JA, Haymon RM, Tunnicliffe V, Martinez F, Ferrini V, et al. How many vent fields? New estimates of vent field populations on ocean ridges from precise mapping of hydrothermal discharge locations. Prog Earth Planet Sci. 2016;449:186–96.CAS 

    Google Scholar 
    28.Walker SL, Baker ET, Resing JA, Nakamura K, McLain PD. A new tool for detecting hydrothermal plumes: an ORP sensor for the PMEL MAPR. AGU Fall Meet Abstr. 2007;2007:V21D–0753.
    Google Scholar 
    29.Herlemann DPR, Labrenz M, Jürgens K, Bertilsson S, Waniek JJ, Andersson AF. Transitions in bacterial communities along the 2000 km salinity gradient of the Baltic Sea. ISME J. 2011;5:1571–9.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    30.Reintjes G, Tegetmeyer HE, Bürgisser M, Orlić S, Tews I, Zubkov M, et al. On-site analysis of bacterial communities of the ultraoligotrophic South Pacific Gyre. Appl Environ Microbiol. 2019;85:e00184–19.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    31.Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 2011;17:10–2.
    Google Scholar 
    32.Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, et al. Introducing mothur: Open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol. 2009;75:7537–41.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    33.Bushnell B. BBMap (version 35.14) [Software]. 2015. https://sourceforge.net/projects/bbmap/.34.Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 2013;41:D590–6.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    35.Ludwig W, Strunk O, Westram R, Richter L, Meier H, Yadhukumar A, et al. ARB: a software environment for sequence data. Nucleic Acids Res. 2004;32:1363–71.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    36.Pernthaler A, Pernthaler J, Amann R.  Fluorescence in situ hybridization and catalyzed reporter deposition for the identification of marine bacteria. Appl Environ Microbiol. 2002;68:3094–101.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    37.Andrews S. FastQC: a quality control tool for high throughput sequence data. Babraham Bioinformatics; 2010.38.Rodriguez-R LM, Gunturu S, Tiedje JM, Cole JR, Konstantinidis KT. Nonpareil 3: fast estimation of metagenomic coverage and sequence diversity. mSystems. 2018;3:e00039–18.PubMed 
    PubMed Central 

    Google Scholar 
    39.Li D, Luo R, Liu CM, Leung CM, Ting HF, Sadakane K, et al. MEGAHIT v1.0: a fast and scalable metagenome assembler driven by advanced methodologies and community practices. Methods. 2016;102:3–11.CAS 
    PubMed 

    Google Scholar 
    40.Strous M, Kraft B, Bisdorf R, Tegetmeyer HE. The binning of metagenomic contigs for microbial physiology of mixed cultures. Front Microbiol. 2012;3:410.PubMed 
    PubMed Central 

    Google Scholar 
    41.Alneberg J, Bjarnason BS, De Bruijn I, Schirmer M, Quick J, Ijaz UZ, et al. Binning metagenomic contigs by coverage and composition. Nat Methods. 2014;11:1144–6.CAS 
    PubMed 

    Google Scholar 
    42.Eren AM, Kiefl E, Shaiber A, Veseli I, Miller SE, Schechter MS, et al. Community-led, integrated, reproducible multi-omics with anvi’o. Nat Microbiol. 2021;6:3–6.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    43.Meier DV, Bach W, Girguis PR, Gruber-Vodicka HR, Reeves EP, Richter M, et al. Heterotrophic proteobacteria in the vicinity of diffuse hydrothermal venting. Environ Microbiol. 2016;18:4348–68.PubMed 

    Google Scholar 
    44.Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012;19:455–77.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    45.Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 2015;25:1043–55.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    46.Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–20.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    47.Kopylova E, Noé L, Touzet H. SortMeRNA: fast and accurate filtering of ribosomal RNAs in metatranscriptomic data. Bioinformatics. 2012;28:3211–7.CAS 
    PubMed 

    Google Scholar 
    48.Gomes AÉ, Stuchi LP, Siqueira NM, Henrique JB, Vicentini R, Ribeiro ML, et al. Selection and validation of reference genes for gene expression studies in Klebsiella pneumoniae using Reverse Transcription Quantitative real-time PCR. Sci Rep. 2018;8:1–4.
    Google Scholar 
    49.Kolde R. pheatmap: Pretty heatmaps. 2015. https://CRAN.R-project.org/package=pheatmap.50.Garnier S. viridis: Default Color Maps from’matplotlib’. 2017. https://CRAN.R-project.org/.51.R Core Team. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2013.52.Oksanen J, Blanchet FG, Friendly M, Kindt R, Legendre P, McGlinn D, et al. Vegan: Community ecology package. 2020.53.Pena EA, Slate EH. gvlma: Global validation of linear models assumptions. R package version 1.0.0.3. 2019. https://CRAN.R-project.org/package=gvlma.54.Anderson MJ. A new method for non parametric multivariate analysis of variance. Austral Ecol. 2001;26:32–46.
    Google Scholar 
    55.Waite DW, Chuvochina M, Pelikan C, Parks DH, Yilmaz P, Wagner M, et al. Proposal to reclassify the proteobacterial classes Deltaproteobacteria and Oligoflexia, and the phylum Thermodesulfobacteria into four phyla reflecting major functional capabilities. Int J Syst Evol Microbiol. 2020;70:5972–6016.CAS 
    PubMed 

    Google Scholar 
    56.Anantharaman K, Breier JA, Dick GJ. Metagenomic resolution of microbial functions in deep-sea hydrothermal plumes across the Eastern Lau Spreading Center. ISME J. 2016;10:225–39.CAS 
    PubMed 

    Google Scholar 
    57.Biller SJ, Berube PM, Dooley K, Williams M, Satinsky BM, Hackl T, et al. Data descriptor: marine microbial metagenomes sampled across space and time. Sci Data. 2018;5:1–7.
    Google Scholar 
    58.Meier DV, Pjevac P, Bach W, Hourdez S, Girguis PR, Vidoudez C, et al. Niche partitioning of diverse sulfur-oxidizing bacteria at hydrothermal vents. ISME J. 2017;11:1545–58.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    59.Chaumeil P-A, Mussig AJ, Hugenholtz P, Parks DH. GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database. Bioinformatics. 2019;36:1925–7.PubMed Central 

    Google Scholar 
    60.Zhou Z, Tran PQ, Kieft K, Anantharaman K. Genome diversification in globally distributed novel marine Proteobacteria is linked to environmental adaptation. ISME J. 2020;14:2060–77.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    61.Parks DH, Rinke C, Chuvochina M, Chaumeil PA, 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.CAS 
    PubMed 

    Google Scholar 
    62.Blackburn NT, Clarke AJ. Identification of four families of peptidoglycan lytic transglycosylases. J Mol Evol. 2001;52:78–84.CAS 
    PubMed 

    Google Scholar 
    63.Hashimoto W, Ochiai A, Momma K, Itoh T, Mikami B, Maruyama Y, et al. Crystal structure of the glycosidase family 73 peptidoglycan hydrolase FlgJ. Biochem Biophys Res Commun. 2009;381:16–21.CAS 
    PubMed 

    Google Scholar 
    64.Ilbert M, Bonnefoy V. Insight into the evolution of the iron oxidation pathways. Biochim Biophys Acta Bioenerg. 2013;1827:161–75.CAS 

    Google Scholar 
    65.Barco RA, Emerson D, Sylvan JB, Orcutt BN, Jacobson Meyers ME, Ramírez GA, et al. New insight into microbial iron oxidation as revealed by the proteomic profile of an obligate iron-oxidizing chemolithoautotroph. Appl Environ Microbiol. 2015;81:5927–37.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    66.Guo J, Bolduc B, Zayed AA, Varsani A, Dominguez-Huerta G, Delmont TO, et al. VirSorter2: a multi-classifier, expert-guided approach to detect diverse DNA and RNA viruses. Microbiome. 2021;9:1–13.67.Duarte CM. Seafaring in the 21st century: the Malaspina 2010 circumnavigation expedition. Limnol Oceanogr Bull. 2015;24:11–14.
    Google Scholar 
    68.Sheik CS, Anantharaman K, Breier JA, Sylvan JB, Edwards KJ, Dick GJ. Spatially resolved sampling reveals dynamic microbial communities in rising hydrothermal plumes across a back-arc basin. ISME J. 2015;9:1434–45.PubMed 

    Google Scholar 
    69.Konstantinidis KT, Rosselló-Móra R, Amann R. Uncultivated microbes in need of their own taxonomy. ISME J. 2017;11:2399–406.PubMed 
    PubMed Central 

    Google Scholar 
    70.Murray AE, Freudenstein J, Gribaldo S, Hatzenpichler R, Hugenholtz P, Kämpfer P, et al. Roadmap for naming uncultivated Archaea and Bacteria. Nat Microbiol. 2020;5:987–94.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    71.Shah V, Zhao X, Lundeen RA, Ingalls AE, Nicastro D, Morris RM. Morphological plasticity in a sulfur-oxidizing marine bacterium from the SUP05 clade enhances dark carbon fixation. MBio. 2019;10:e00216–19.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    72.Yamamoto M, Takai K. Sulfur metabolisms in Epsilon- and Gammaproteobacteria in deep-sea hydrothermal fields. Front Microbiol. 2011;2:192.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    73.White GF, Edwards MJ, Gomez-Perez L, Richardson DJ, Butt JN, Clarke TA. Mechanisms of bacterial extracellular electron exchange. Adv Micro Physiol. 2016;68:87–138.CAS 

    Google Scholar 
    74.Findlay AJ, Estes ER, Gartman A, Yücel M, Kamyshny A, Luther GW. Iron and sulfide nanoparticle formation and transport in nascent hydrothermal vent plumes. Nat Commun. 2019;10:1–7.CAS 

    Google Scholar 
    75.Gartman A, Luther GW. Oxidation of synthesized sub-micron pyrite (FeS2) in seawater. Geochim Cosmochim Acta. 2014;144:96–108.CAS 

    Google Scholar 
    76.Bonnefoy V, Holmes DS. Genomic insights into microbial iron oxidation and iron uptake strategies in extremely acidic environments. Environ Microbiol. 2012;14:1597–611.CAS 
    PubMed 

    Google Scholar 
    77.Singh VK, Singh AL, Singh R, Kumar A. Iron oxidizing bacteria: insights on diversity, mechanism of iron oxidation and role in management of metal pollution. Environ Sustain. 2018;1:221–31.
    Google Scholar 
    78.He S, Barco RA, Emerson D, Roden EE. Comparative genomic analysis of neutrophilic iron(II) oxidizer genomes for candidate genes in extracellular electron transfer. Front Microbiol. 2017;8:1584.PubMed 
    PubMed Central 

    Google Scholar 
    79.McAllister SM, Polson SW, Butterfield DA, Glazer BT, Sylvan JB, Chan CS. Validating the Cyc2 neutrophilic iron oxidation pathway using meta-omics of Zetaproteobacteria iron mats at marine hydrothermal vents. mSystems. 2020;5:e00553–19.PubMed 
    PubMed Central 

    Google Scholar 
    80.Barco RA, Hoffman CL, Ramírez GA, Toner BM, Edwards KJ, Sylvan JB. In-situ incubation of iron-sulfur mineral reveals a diverse chemolithoautotrophic community and a new biogeochemical role for Thiomicrospira. Environ Microbiol. 2017;19:1322–37.CAS 
    PubMed 

    Google Scholar 
    81.Lesniewski RA, Jain S, Anantharaman K, Schloss PD, Dick GJ. The metatranscriptome of a deep-sea hydrothermal plume is dominated by water column methanotrophs and lithotrophs. ISME J. 2012;6:2257–68.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    82.Reed DC, Breier JA, Jiang H, Anantharaman K, Klausmeier CA, Toner BM, et al. Predicting the response of the deep-ocean microbiome to geochemical perturbations by hydrothermal vents. ISME J. 2015;9:1857–69.PubMed 
    PubMed Central 

    Google Scholar 
    83.Maki JS. Bacterial intracellular sulfur globules: structure and function. J Mol Microbiol Biotechnol. 2013;23:270–80.CAS 
    PubMed 

    Google Scholar 
    84.Neuholz R, Kleint C, Schnetger B, Koschinsky A, Laan P, Middag R, et al. Submarine hydrothermal discharge and fluxes of dissolved Fe and Mn, and He isotopes at Brothers Volcano based on radium isotopes. Minerals. 2020;10:969.CAS 

    Google Scholar 
    85.Waite DW, Vanwonterghem I, Rinke C, Parks DH, Zhang Y, Takai K, et al. Comparative genomic analysis of the class Epsilonproteobacteria and proposed reclassification to Epsilonbacteraeota (phyl. nov.). Front Microbiol. 2017;8:682.PubMed 
    PubMed Central 

    Google Scholar 
    86.Waite DW, Vanwonterghem I, Rinke C, Parks DH, Zhang Y, Takai K, et al. Addendum: comparative genomic analysis of the class Epsilonproteobacteria and proposed reclassification to Epsilonbacteraeota (phyl. nov.). Front Microbiol. 2018;9:772.PubMed 
    PubMed Central 

    Google Scholar  More

  • in

    Reply to: Do not downplay biodiversity loss

    1.Loreau, M. et al. Do not downplay biodiversity loss. Nature https://doi.org/10.1038/s41586-021-04179-7 (2022).2.Leung, B. et al. Clustered versus catastrophic global vertebrate declines. Nature 588, 267–271 (2020).ADS 
    CAS 
    Article 

    Google Scholar 
    3.Antão, L. H. et al. Temperature-related biodiversity change across temperate marine and terrestrial systems. Nat. Ecol. Evol. 4, 927–933 (2020).Article 

    Google Scholar 
    4.Leung, B., Greenberg, D. A. & Green, D. M. Trends in mean growth and stability in temperate vertebrate populations. Divers. Distrib. 23, 1372–1380 (2017).Article 

    Google Scholar 
    5.Daskalova, G. N., Myers-Smith, I. H. & Godlee, J. L. Rare and common vertebrates span a wide spectrum of population trends. Nat. Commun. 11, 4394 (2020).ADS 
    CAS 
    Article 

    Google Scholar 
    6.Murali, G. et al. Emphasizing declining populations in the Living Planet Report. Nature https://doi.org/10.1038/s41586-021-04165-z (2022).7.Leung, B., et al. Reply to: Emphasizing declining populations in the Living Planet Report. Nature https://doi.org/10.1038/s41586-021-04166-y (2022).8.Dornelas, M., et al. A balance of winners and losers in the Anthropocene. Ecol. Lett. 22, 847–854 (2019).Article 

    Google Scholar 
    9.Hilborn, R. Faith based fisheries. Fisheries 31, 554–555 (2006).
    Google Scholar  More

  • in

    Reply to: Emphasizing declining populations in the Living Planet Report

    Department of Biology, McGill University, Montreal, Quebec, CanadaBrian Leung & Anna L. HargreavesBieler School of Environment, McGill University, Montreal, Quebec, CanadaBrian LeungDepartment of Biological Sciences, Simon Fraser University, Burnaby, British Columbia, CanadaDan A. GreenbergSchool of Biology and Ecology and Mitchell Center for Sustainability Solutions, University of Maine, Orono, ME, USABrian McGillCentre for Biological Diversity, University of St Andrews, St Andrews, UKMaria DornelasIndicators and Assessments Unit, Institute of Zoology, Zoological Society of London, London, UKRobin FreemanB.L. wrote the response. A.C.H. and D.A.G. helped with writing, editing and discussing ideas. B.M. and M.D. discussed ideas with some editing. R.F. contributed discussions to the original manuscript2. More

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    Reply to: The Living Planet Index does not measure abundance

    Department of Biology, McGill University, Montreal, Quebec, CanadaBrian Leung & Anna L. HargreavesBieler School of Environment, McGill University, Montreal, Quebec, CanadaBrian LeungDepartment of Biological Sciences, Simon Fraser University, Burnaby, British Columbia, CanadaDan A. GreenbergSchool of Biology and Ecology and Mitchell Center for Sustainability Solutions, University of Maine, Orono, ME, USABrian McGillCentre for Biological Diversity, University of St Andrews, St Andrews, UKMaria DornelasIndicators and Assessments Unit, Institute of Zoology, Zoological Society of London, London, UKRobin FreemanB.L. wrote the response. A.L.H. and D.A.G. helped with writing, editing and discussing ideas. B.M., M.D. and R.F. discussed ideas and did some editing. More

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    Reply to: Shifting baselines and biodiversity success stories

    Cite this articleLeung, B., Hargreaves, A.L., Greenberg, D.A. et al. Reply to: Shifting baselines and biodiversity success stories.
    Nature 601, E19 (2022). https://doi.org/10.1038/s41586-021-03749-zDownload citationPublished: 26 January 2022Issue Date: 27 January 2022DOI: https://doi.org/10.1038/s41586-021-03749-zShare this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard
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    Do not downplay biodiversity loss

    1.Leung, B. et al. Clustered versus catastrophic global vertebrate declines. Nature 588, 267–271 (2020).CAS 
    Article 
    ADS 

    Google Scholar 
    2.McRae, L., Deinet, S. & Freeman, R. The diversity-weighted Living Planet Index: controlling for taxonomic bias in a global biodiversity indicator. PLoS ONE 12, e0169156 (2017).Article 

    Google Scholar 
    3.Koricheva, J. & Gurevitch, J. Uses and misuses of meta-analysis in plant ecology. J. Ecol. 102, 828–844 (2014).Article 

    Google Scholar 
    4.Cardinale, B. J., Gonzalez, A., Allington, G. R. H. & Loreau, M. Is local biodiversity in decline or not? A summary of the debate over analysis of species richness time trends. Biol. Conserv. 219, 175–183 (2018).Article 

    Google Scholar 
    5.Inger, R. et al. Common European birds are declining rapidly while less abundant species’ numbers are rising. Ecol. Lett. 18, 28–36 (2015).Article 

    Google Scholar 
    6.Rosenberg, K. V. et al. Decline of the North American avifauna. Science 366, 120–124 (2019).CAS 
    Article 
    ADS 

    Google Scholar 
    7.Gonzalez, A. et al. Estimating local biodiversity change: a critique of papers claiming no net loss of local diversity. Ecology 97, 1949–1960 (2016).Article 

    Google Scholar 
    8.Scholes, R. J. et al. Toward a global biodiversity observing system. Science 321, 1044–1045 (2008).CAS 
    Article 

    Google Scholar  More

  • in

    The Living Planet Index does not measure abundance

    1.Almond, R. E. A., Grooten, M. & Petersen, T. (eds) Living Planet Report 2020 – Bending the Curve of Biodiversity Loss (WWF, 2020).2.Leung, B. et al. Clustered versus catastrophic global vertebrate declines. Nature 588, 267–271 (2020).CAS 
    Article 
    ADS 

    Google Scholar 
    3.Buckland, S. T., Studeny, A. C., Magurran, A. E., Illian, J. B. & Newson, S. E. The geometric mean of relative abundance indices: a biodiversity measure with a difference. Ecosphere 2, 1–15 (2011).Article 

    Google Scholar 
    4.McRae, L., Deinet, S. & Freeman, R. The diversity-weighted living planet index: controlling for taxonomic bias in a global biodiversity indicator. PLoS ONE 12, e0169156 (2017).Article 

    Google Scholar 
    5.Leung, B., Greenberg, D. A. & Green, D. M. Trends in mean growth and stability in temperate vertebrate populations. Divers. Distrib. 23, 1372–1380 (2017).Article 

    Google Scholar 
    6.Marconi, V., McRae, L., Deinet, S., Ledger, S. & Freeman, F. in Living Planet Report 2020 – Bending the Curve of Biodiversity Loss (eds Almond, R. E. A., Grooten, M. & Petersen, T.) (WWF, 2020).7.Daskalova, G. N., Myers-Smith, I. H. & Godlee, J. L. Rare and common vertebrates span a wide spectrum of population trends. Nat. Commun. 11, 4394 (2020).CAS 
    Article 
    ADS 

    Google Scholar 
    8.Daskalova, G. N. et al. Landscape-scale forest loss as a catalyst of population and biodiversity change. Science 368, 1341–1347 (2020).CAS 
    Article 
    ADS 

    Google Scholar 
    9.IPBES. Summary for Policymakers of the Global Assessment Report on Biodiversity and Ecosystem Services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES Secretariat, 2019).10.van Strien, A. J., Soldaat, L. L. & Gregory, R. D. Desirable mathematical properties of indicators for biodiversity change. Ecol. Indic. 14, 202–208 (2012).Article 

    Google Scholar  More