More stories

  • in

    UCYN-A/haptophyte symbioses dominate N2 fixation in the Southern California Current System

    1.Karl D, Letelier R, Tupas L, Dore J, Christian J, Hebel D. The role of nitrogen fixation in biogeochemical cycling in the subtropical North Pacific Ocean. Nature. 1997;388:533–8.CAS 
    Article 

    Google Scholar 
    2.Jickells TD, Buitenhuis E, Altieri K, Baker AR, Capone D, Duce RA, et al. A reevaluation of the magnitude and impacts of anthropogenic atmospheric nitrogen inputs on the ocean. Glob Biogeochem Cycles. 2017;31:289–305.CAS 

    Google Scholar 
    3.Knapp A. The sensitivity of marine N2 fixation to dissolved inorganic nitrogen. Front Microbiol. 2012;3:374.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    4.Rees AP, Gilbert JA, Kelly-Gerreyn BA. Nitrogen fixation in the western English Channel (NE Atlantic Ocean). Mar Ecol Prog Ser. 2009;374:7–12.CAS 
    Article 

    Google Scholar 
    5.Shiozaki T, Nagata T, Ijichi M, Furuya K. Nitrogen fixation and the diazotroph community in the temperate coastal region of the northwestern North Pacific. Biogeosciences. 2015;12:4751–64.Article 

    Google Scholar 
    6.Tang W, Cerdán-García E, Berthelot H, Polyviou D, Wang S, Baylay A, et al. New insights into the distributions of nitrogen fixation and diazotrophs revealed by high-resolution sensing and sampling methods. ISME J. 2020;14:2514–26.CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    7.Tang W, Wang S, Fonseca-Batista D, Dehairs F, Gifford S, Gonzalez AG, et al. Revisiting the distribution of oceanic N2 fixation and estimating diazotrophic contribution to marine production. Nat Commun. 2019;10:1–10.Article 
    CAS 

    Google Scholar 
    8.Hamersley M, Turk K, Leinweber A, Gruber N, Zehr J, Gunderson T, Capone D. Nitrogen fixation within the water column associated with two hypoxic basins in the Southern California Bight. Aquat Microb Ecol. 2011;63:193–205.Article 

    Google Scholar 
    9.Mulholland MR, Bernhardt PW, Blanco-Garcia JL, Mannino A, Hyde K, Mondragon E, et al. Rates of dinitrogen fixation and the abundance of diazotrophs in North American coastal waters between Cape Hatteras and Georges Bank. Limnol Oceanogr. 2012;57:1067–83.CAS 
    Article 

    Google Scholar 
    10.Mulholland MR, Bernhardt PW, Widner BN, Selden CR, Chappell PD, Clayton S, et al. High rates of N2 fixation in temperate, western North Atlantic coastal waters expands the realm of marine diazotrophy. Glob Biogeochem Cycles. 2019;33:826–40.CAS 
    Article 

    Google Scholar 
    11.Bentzon-Tilia M, Traving SJ, Mantikci M, Knudsen-Leerbeck H, Hansen JL, Markager S, et al. Significant N2 fixation by heterotrophs, photoheterotrophs and heterocystous cyanobacteria in two temperate estuaries. ISME J. 2015;9:273–85.CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    12.Wen Z, Lin W, Shen R, Hong H, Kao SJ, Shi D. Nitrogen fixation in two coastal upwelling regions of the Taiwan Strait. Sci Rep. 2017;7:1–10.Article 
    CAS 

    Google Scholar 
    13.Voss M, Bombar D, Loick N, Dippner JW. Riverine influence on nitrogen fixation in the upwelling region off Vietnam, South China Sea. Geophys Res Lett. 2006;33:L07604.Article 
    CAS 

    Google Scholar 
    14.Shiozaki T, Furuya K, Kodama T, Kitajima S, Takeda S, Takemura T, et al. New estimation of N2 fixation in the western and central Pacific Ocean and its marginal seas. Glob Biogeochem Cycles. 2010;24:GB1015–n/a.15.Blais M, Tremblay JÉ, Jungblut AD, Gagnon J, Martin J, Thaler M, et al. Nitrogen fixation and identification of potential diazotrophs in the Canadian Arctic. Glob Biogeochem Cycles. 2012;26:GB3022.Article 
    CAS 

    Google Scholar 
    16.Shiozaki T, Fujiwara A, Inomura K, Hirose Y, Hashihama F, Harada N. Biological nitrogen fixation detected under Antarctic sea ice. Nat Geosci. 2020;13:729–32.CAS 
    Article 

    Google Scholar 
    17.Harding K, Turk-Kubo KA, Sipler RE, Mills MM, Bronk DA, Zehr JP. Symbiotic unicellular cyanobacteria fix nitrogen in the Arctic Ocean. Proc Natl Acad Sci USA. 2018;115:13371–5.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    18.Thompson AW, Foster RA, Krupke A, Carter BJ, Musat N, Vaulot D, et al. Unicellular cyanobacterium symbiotic with a single-celled eukaryotic alga. Science. 2012;337:1546–50.CAS 
    PubMed 
    Article 

    Google Scholar 
    19.Zehr JP, Shilova IN, Farnelid HM, del Carmen Muñoz-MarínCarmen M, Turk-Kubo KA. Unusual marine unicellular symbiosis with the nitrogen-fixing cyanobacterium UCYN-A. Nat Microbiol. 2016;2:16214.PubMed 
    Article 
    CAS 

    Google Scholar 
    20.Zehr JP, Bench SR, Carter BJ, Hewson I, Niazi F, Shi T, et al. Globally distributed uncultivated oceanic N2-fixing cyanobacteria lack oxygenic photosystem II. Science. 2008;322:1110–2.CAS 
    PubMed 
    Article 

    Google Scholar 
    21.Tripp HJ, Bench SR, Turk KA, Foster RA, Desany BA, Niazi F, et al. Metabolic streamlining in an open-ocean nitrogen-fixing cyanobacterium. Nature. 2010;464:90–4.CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    22.Church MJ, Mahaffey C, Letelier RM, Lukas R, Zehr JP, Karl DM. Physical forcing of nitrogen fixation and diazotroph community structure in the North Pacific subtropical gyre. Glob Biogeochem Cycles. 2009;23:GB2020.23.Langlois RJ, Hummer D, LaRoche J. Abundances and distributions of the dominant nifH phylotypes in the Northern Atlantic Ocean. Appl Environ Microbiol. 2008;74:1922–31.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    24.Moisander PH, Beinart RA, Hewson I, White AE, Johnson KS, Carlson CA, et al. Unicellular cyanobacterial distributions broaden the oceanic N2 fixation domain. Science. 2010;327:1512–4.CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    25.Krupke A, Lavik G, Halm H, Fuchs BM, Amann RI, Kuypers MM. Distribution of a consortium between unicellular algae and the N2 fixing cyanobacterium UCYN-A in the North Atlantic Ocean. Environ Microbiol. 2014;16:3153–67.CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    26.Shiozaki T, Bombar D, Riemann L, Hashihama F, Takeda S, Yamaguchi T, et al. Basin scale variability of active diazotrophs and nitrogen fixation in the North Pacific, from the tropics to the subarctic Bering Sea. Glob Biogeochem Cycles 2017;31:996–1009.CAS 
    Article 

    Google Scholar 
    27.Krupke A, Musat N, Laroche J, Mohr W, Fuchs BM, Amann RI, et al. In situ identification and N2 and C fixation rates of uncultivated cyanobacteria populations. Syst Appl Microbiol. 2013;36:259–71.CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    28.Martínez-Pérez C, Mohr W, Löscher CR, Dekaezemacker J, Littmann S, Yilmaz P, et al. The small unicellular diazotrophic symbiont, UCYN-A, is a key player in the marine nitrogen cycle. Nat Microbiol. 2016;1:16163.PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    29.Mills MM, Turk-Kubo KA, van Dijken GL, Henke BA, Harding K, Wilson ST, et al. Unusual marine cyanobacteria/haptophyte symbiosis relies on N2 fixation even in N-rich environments. ISME J. 2020;14:2395–406.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    30.Scavotto RE, Dziallas C, Bentzon-Tilia M, Riemann L, Moisander PH. Nitrogen-fixing bacteria associated with copepods in coastal waters of the North Atlantic Ocean. Environ. Microbiol. 2015;17:3754–65.CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    31.Conroy BJ, Steinberg DK, Song B, Kalmbach A, Carpenter EJ, Foster RA. Mesozooplankton graze on cyanobacteria in the amazon river plume and western tropical North Atlantic. Front Microbiol. 2017;8:1436.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    32.Turk-Kubo KA, Connell P, Caron D, Hogan ME, Farnelid HM, Zehr JP. In situ diazotroph population dynamics under different resource ratios in the North Pacific Subtropical Gyre. Front Microbiol. 2018;9:1616.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    33.Needham DM, Fuhrman JA. Pronounced daily succession of phytoplankton, archaea and bacteria following a spring bloom. Nat Microbiol. 2016;1:16005.CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    34.Shiozaki T, Fujiwara A, Ijichi M, Harada N, Nishino S, Nishi S, et al. Diazotroph community structure and the role of nitrogen fixation in the nitrogen cycle in the Chukchi Sea (western Arctic Ocean). Limnol Oceanogr. 2018;63:2191–205.CAS 
    Article 

    Google Scholar 
    35.Sohm JA, Hilton JA, Noble AE, Zehr JP, Saito MA, Webb EA. Nitrogen fixation in the South Atlantic Gyre and the Benguela Upwelling system. Geophys Res Lett. 2011;38:L16608–n/a.Article 
    CAS 

    Google Scholar 
    36.Moreira-Coello V, Mouriño-Carballido B, Marañón E, Fernández-Carrera A, Bode A, Varela MM. Biological N2 fixation in the upwelling region off NW Iberia: magnitude, relevance, and players. Front Mar Sci. 2017;4:303.Article 

    Google Scholar 
    37.Cabello AM, Turk-Kubo KA, Hayashi K, Jacobs L, Kudela RM, Zehr JP. Unexpected presence of the nitrogen-fixing symbiotic cyanobacterium UCYN-A in Monterey Bay, California. J Phycol. 2020;56:1521–33.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    38.Deutsch C, Frenzel H, McWilliams JC, Renault L, Kessouri F, Howard E, et al. Biogeochemical variability in the California Current System. Prog Oceanogr. 2021;196:102565.Article 

    Google Scholar 
    39.Grasshoff K, Kremling K, Ehrhardt M, editors. Methods of seawater analysis. 3rd ed. Weinheim: Wiley-VCH; 1999.40.Welschmeyer NA. Fluorometric analysis of chlorophyll a in the presence of chlorophyll b and phaeopigments. Limnol Oceanogr. 1994;39:1985–92.CAS 
    Article 

    Google Scholar 
    41.Moisander PH, Beinart RA, Voss M, Zehr JP. Diversity and abundance of diazotrophic microorganisms in the South China Sea during intermonsoon. ISME J. 2008;2:954–67.CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    42.Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods. 2010;7:335–6.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    43.Edgar RC. Search and clustering orders of magnitude faster than BLAST. Bioinformatics. 2010;26:2460–1.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    44.Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics. 2011;27:2194–200.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    45.Zehr JP, Jenkins BD, Short SM, Steward GF. Nitrogenase gene diversity and microbial community structure: a cross-system comparison. Environ Microbiol. 2003;5:539–54.CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    46.Eren AM, Maignien L, Sul WJ, Murphy LG, Grim SL, Morrison HG, et al. Oligotyping: differentiating between closely related microbial taxa using 16S rRNA gene data. Methods Ecol Evol. 2013;4:1111–9.PubMed Central 
    Article 
    PubMed 

    Google Scholar 
    47.Turk-Kubo KA, Farnelid HM, Shilova IN, Henke B, Zehr JP. Distinct ecological niches of marine symbiotic N2-fixing cyanobacterium Candidatus Atelocyanobacterium thalassa sublineages. J Phycol. 2017;53:451–61.CAS 
    PubMed 
    Article 

    Google Scholar 
    48.Henke BA, Turk-Kubo KA, Bonnet S, Zehr JP. Distributions and abundances of sublineages of the N2-fixing cyanobacterium Candidatus Atelocyanobacterium thalassa (UCYN-A) in the New Caledonian Coral Lagoon. Front Microbiol. 2018;9:554.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    49.Gradoville MR, Farnelid H, White AE, Turk‐Kubo KA, Stewart B, Ribalet F, et al. Latitudinal constraints on the abundance and activity of the cyanobacterium UCYN‐A and other marine diazotrophs in the North Pacific. Limnol Oceanogr. 2020;65:1858–75.CAS 
    Article 

    Google Scholar 
    50.McMurdie PJ, Holmes S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE. 2013;8:e61217.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    51.Church M, Jenkins B, Karl D, Zehr J. Vertical distributions of nitrogen-fixing phylotypes at Stn ALOHA in the oligotrophic North Pacific Ocean. Aquat Microb Ecol. 2005;38:3–14.Article 

    Google Scholar 
    52.Thompson A, Carter BJ, Turk-Kubo K, Malfatti F, Azam F, Zehr JP. Genetic diversity of the unicellular nitrogen-fixing cyanobacteria UCYN-A and its prymnesiophyte host. Environ Microbiol. 2014;16:3238–49.CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    53.Foster RA, Subramaniam A, Mahaffey C, Carpenter EJ, Capone DG, Zehr JP. Influence of the Amazon River plume on distributions of free-living and symbiotic cyanobacteria in the western tropical north Atlantic Ocean. Limnol Oceanogr. 2007;52:517–32.CAS 
    Article 

    Google Scholar 
    54.Goebel NL, Turk KA, Achilles KM, Paerl R, Hewson I, Morrison AE, et al. Abundance and distribution of major groups of diazotrophic cyanobacteria and their potential contribution to N2 fixation in the tropical Atlantic Ocean. Environ Microbiol. 2010;12:3272–89.CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    55.Farnelid H, Turk-Kubo K, Munoz-Marin MD, Zehr JP. New insights into the ecology of the globally significant uncultured nitrogen-fixing symbiont UCYN-A. Aquat Microb Ecol. 2016;77:125–38.Article 

    Google Scholar 
    56.Mohr W, Grosskopf T, Wallace DWR, LaRoche J. Methodological underestimation of oceanic nitrogen fixation rates. PLoS ONE. 2010;5:e12583.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    57.Montoya JP, Voss M, Kahler P, Capone DG. A simple, high-precision, high-sensitivity tracer assay for N2 fixation. Appl Environ Microbiol. 1996;62:986–93.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    58.Gradoville MR, Bombar D, Crump BC, Letelier RM, Zehr JP, White AE. Diversity and activity of nitrogen-fixing communities across ocean basins. Limnol Oceanogr. 2017;62:1895–909.Article 

    Google Scholar 
    59.White AE, Granger J, Selden C, Gradoville MR, Potts L, Bourbonnais A, et al. A critical review of the 15N2 tracer method to measure diazotrophic production in pelagic ecosystems. Limnol Oceanogr Methods. 2020;18:129–47.Article 

    Google Scholar 
    60.Cornejo-Castillo FM, Cabello AM, Salazar G, Sánchez-Baracaldo P, Lima-Mendez G, Hingamp P, et al. Cyanobacterial symbionts diverged in the late Cretaceous towards lineage-specific nitrogen fixation factories in single-celled phytoplankton. Nat Commun. 2016;7:11071.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    61.Cabello AM, Cornejo-Castillo FM, Raho N, Blasco D, Vidal M, Audic S, et al. Global distribution and vertical patterns of a prymnesiophyte-cyanobacteria obligate symbiosis. ISME J. 2016;10:693–706.PubMed 
    Article 

    Google Scholar 
    62.Polerecky L, Adam B, Milucka J, Musat N, Vagner T, Kuypers MM. Look@ NanoSIMS–a tool for the analysis of nanoSIMS data in environmental microbiology. Environ Microbiol. 2012;14:1009–23.CAS 
    PubMed 
    Article 

    Google Scholar 
    63.Krupke A, Mohr W, LaRoche J, Fuchs BM, Amann RI, Kuypers MM. The effect of nutrients on carbon and nitrogen fixation by the UCYN-A-haptophyte symbiosis. ISME J. 2015;9:1635–47.CAS 
    PubMed 
    Article 

    Google Scholar 
    64.Meyer NR, Fortney J, Dekas AE. NanoSIMS sample preparation decreases isotope enrichment: magnitude, variability and implications for single-cell rates of microbial activity. Environ Microbiol. 2020;23:81–98.PubMed 
    Article 
    CAS 

    Google Scholar 
    65.Durazo R. Seasonality of the transitional region of the California Current System off Baja California. J Geophys Res Oceans. 2015;120:1173–96.Article 

    Google Scholar 
    66.Bakun A. Coastal upwelling indices, west coast of North America, 1946–71.67.Redfield AC. On the proportions of organic derivatives in sea water and their relation to the composition of plankton. Vol. 1. Liverpool: University Press of Liverpool; 1934. p. 176–92.68.Bograd SJ, Schroeder ID, Jacox MG. A water mass history of the Southern California current system. Geophys. Res. Lett. 2019;46:6690–8.Article 

    Google Scholar 
    69.Langlois R, Großkopf T, Mills M, Takeda S, LaRoche J. Widespread distribution and expression of gamma A (UMB), an uncultured, diazotrophic, γ-proteobacterial nifH phylotype. PLoS ONE. 2015;10:e0128912.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    70.Dekaezemacker J, Bonnet S, Grosso O, Moutin T, Bressac M, Capone DG. Evidence of active dinitrogen fixation in surface waters of the eastern tropical South Pacific during El Niño and La Niña events and evaluation of its potential nutrient controls. Glob Biogeochem Cycles 2013;27:768–79.CAS 
    Article 

    Google Scholar 
    71.Chen M, Lu Y, Jiao N, Tian J, Kao SJ, Zhang Y. Biogeographic drivers of diazotrophs in the western Pacific Ocean. Limnol Oceanogr. 2019;64:1403–21.CAS 
    Article 

    Google Scholar 
    72.Turk KA, Rees AP, Zehr JP, Pereira N, Swift P, Shelley R, et al. Nitrogen fixation and nitrogenase (nifH) expression in tropical waters of the eastern North Atlantic. ISME J. 2011;5:1201–12.CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    73.White AE, Foster RA, Benitez-Nelson CR, Masqué P, Verdeny E, Popp BN, et al. Nitrogen fixation in the Gulf of California and the Eastern Tropical North Pacific. Prog Oceanogr. 2013;109:1–17.Article 

    Google Scholar 
    74.Selden CR, Mulholland MR, Bernhardt PW, Widner B, Macías‐Tapia A, Ji Q, et al. Dinitrogen fixation across physico-chemical gradients of the eastern tropical North Pacific oxygen deficient zone. Glob Biogeochem Cycles. 2019;33:1187–202.CAS 
    Article 

    Google Scholar 
    75.Sohm JA, Webb EA, Capone DG. Emerging patterns of marine nitrogen fixation. Nat Rev Microbiol. 2011;9:499–508.CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    76.Carlucci A, Bowes PM. Production of vitamin B12, thiamine, and biotin by phytoplankton. J Phycol. 1970;6:351–7.CAS 

    Google Scholar 
    77.Gledhill M, Buck KN. The organic complexation of iron in the marine environment: a review. Front Microbiol. 2012;3:69.PubMed 
    PubMed Central 

    Google Scholar 
    78.Biddanda B, Benner R. Carbon, nitrogen, and carbohydrate fluxes during the production of particulate and dissolved organic matter by marine phytoplankton. Limnol Oceanogr. 1997;42:506–18.CAS 
    Article 

    Google Scholar 
    79.Hernández de la Torre B, Gaxiola Castro G, Álvarez Borrego S, Gallegos García A, Aguirre Gómez R. New organic carbon in front of the Baja California Peninsula: time series and climatology. Hidrobiológica. 2015;25:74–85.
    Google Scholar 
    80.Xiu P, Chai F, Curchitser EN, Castruccio FS. Future changes in coastal upwelling ecosystems with global warming: the case of the California Current System. Sci. Rep. 2018;8:2866.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    81.Kimor B, Reid F, Jordan J. An unusual occurrence of Hemiaulus membranaceus Cleve (Bacillariophyceae) with Richelia intracelluaris Schmidt (Cyanophyceae) off the coast of Southern California. Phycologia. 1978;17:162–6.Article 

    Google Scholar 
    82.White AE, Prahl FG, Letelier RM, Popp BN. Summer surface waters in the Gulf of California: Prime habitat for biological N2 fixation. Glob Biogeochem Cycles. 2007;21:GB2017–n/a.83.Pyle AE, Johnson AM, Villareal TA. Isolation, growth, and nitrogen fixation rates of the Hemiaulus-Richelia (diatom-cyanobacterium) symbiosis in culture. PeerJ. 2020;8:e10115.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    84.Foster RA, Kuypers MM, Vagner T, Paerl RW, Musat N, Zehr JP. Nitrogen fixation and transfer in open ocean diatom–cyanobacterial symbioses. ISME J. 2011;5:1484–93.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    85.Caputo A, Nylander JAA, Foster RA. The genetic diversity and evolution of diatom-diazotroph associations highlights traits favoring symbiont integration. FEMS Microbiol Lett. 2019;366:fny297.CAS 
    PubMed Central 
    Article 

    Google Scholar 
    86.Thompson AR. State of the California Current 2017–18: still not quite normal in the north and getting interesting in the south. California cooperative oceanic fisheries investigations, Data report. 2018.87.Larkin AA, Moreno AR, Fagan AJ, Fowlds A, Ruiz A, Martiny AC. Persistent El Nino driven shifts in marine cyanobacteria populations. PLoS ONE. 2020;15:e0238405.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    88.Hagino K, Takano Y, Horiguchi T. Pseudo-cryptic speciation in Braarudosphaera bigelowii (Gran and Braarud) Deflandre. Mar Micropaleontol. 2009;72:210–21.Article 

    Google Scholar 
    89.Selden CR, Chappell PD, Clayton S, Macías‐Tapia A, Bernhardt PW, Mulholland MR. A coastal N2 fixation hotspot at the Cape Hatteras front: elucidating spatial heterogeneity in diazotroph activity via supervised machine learning. Limnol Oceanogr. 2021;66:1832–49.Article 

    Google Scholar 
    90.Wang S, Tang W, Delage E, Gifford S, Whitby H, González AG, et al. Investigating the microbial ecology of coastal hotspots of marine nitrogen fixation in the western North Atlantic. Sci Rep. 2021;11:5508.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar  More

  • in

    The microbiome extends host evolutionary potential

    1.Blaser, M. J. & Falkow, S. What are the consequences of the disappearing human microbiota? Nat. Rev. Microbiol. 7, 887–894 (2009).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    2.Friesen, M. L. et al. Microbially mediated plant functional traits. Annu. Rev. Ecol. Evol. Syst. 42, 23–46 (2011).Article 

    Google Scholar 
    3.McFall-Ngai, M. et al. Animals in a bacterial world, a new imperative for the life sciences. Proc. Natl Acad. Sci. 110, 3229–3236 (2013).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    4.Douglas, A. E. Symbiosis as a general principle in eukaryotic evolution. Cold Spring Harb. Perspect. Biol. 6, a016113 (2014).5.Stappenbeck, T. S. & Virgin, H. W. Accounting for reciprocal host-microbiome interactions in experimental science. Nature 534, 191–199 (2016).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    6.Moran, N. A. & Sloan, D. B. The hologenome concept: helpful or hollow? PLoS Biol. 13, e1002311 (2015).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    7.Douglas, A. E. & Werren, J. H. Holes in the hologenome: why host-microbe symbioses are not holobionts. MBio 7, e02099 (2016).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    8.Koskella, B., Hall, L. J. & Metcalf, C. J. E. The microbiome beyond the horizon of ecological and evolutionary theory. Nat. Ecol. Evol. 1, 1606–1615 (2017).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    9.Morimoto, J. & Baltrus, D. A. The extended genotype: to what extent? A comment on Carthey et al. Trends Ecol. Evol. 34, 186–187 (2019).10.Scheuring, I. & Yu, D. W. How to assemble a beneficial microbiome in three easy steps. Ecol. Lett. 15, 1300–1307 (2012).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    11.Dawkins, R. The Extended Phenotype: The Long Reach of the Gene. (Oxford University Press, USA, 1982).12.Whitham, T. G. et al. A framework for community and ecosystem genetics: from genes to ecosystems. Nat. Rev. Genet. 7, 510–523 (2006).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    13.Mueller, U. G. & Sachs, J. L. Engineering Microbiomes to Improve Plant and Animal Health. Trends Microbiol 23, 606–617 (2015).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    14.Zilber-Rosenberg, I. & Rosenberg, E. Role of microorganisms in the evolution of animals and plants: the hologenome theory of evolution. FEMS Microbiol. Rev. 32, 723–735 (2008).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    15.Bordenstein, S. R. & Theis, K. R. Host biology in light of the microbiome: ten principles of holobionts and hologenomes. PLoS Biol. 13, e1002226 (2015).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    16.Alberdi, A., Aizpurua, O., Bohmann, K., Zepeda-Mendoza, M. L. & Gilbert, M. T. P. Do vertebrate gut metagenomes confer rapid ecological adaptation? Trends Ecol. Evol. 31, 689–699 (2016).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    17.Shapira, M. Gut Microbiotas and host evolution: scaling up symbiosis. Trends Ecol. Evol. 31, 539–549 (2016).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    18.Carrier, T. J. & Reitzel, A. M. The hologenome across environments and the implications of a host-associated microbial repertoire. Front. Microbiol. 8, 802 (2017).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    19.Hurst, G. D. D. Extended genomes: symbiosis and evolution. Interface Focus 7, 20170001 (2017).20.Sudakaran, S., Kost, C. & Kaltenpoth, M. Symbiont acquisition and replacement as a source of ecological innovation. Trends Microbiol 25, 375–390 (2017).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    21.Carthey, A. J. R., Gillings, M. R. & Blumstein, D. T. The extended genotype: microbially mediated olfactory communication. Trends Ecol. Evol. 33, 885–894 (2018).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    22.Rosenberg, E. & Zilber-Rosenberg, I. The hologenome concept of evolution after 10 years. Microbiome 6, 78 (2018).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    23.Futuyma, D. J. & Moreno, G. The evolution of ecological specialization. Annu. Rev. Ecol. Syst. 19, 207–233 (1988).Article 

    Google Scholar 
    24.Piersma, T. & Drent, J. Phenotypic flexibility and the evolution of organismal design. Trends Ecol. Evol. 18, 228–233 (2003).Article 

    Google Scholar 
    25.Lande, R. Natural selection and random genetic drift in phenotypic. Evolution. Evolution 30, 314–334 (1976).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    26.West-Eberhard, M. J. Phenotypic plasticity and the origins of diversity. Annu. Rev. Ecol. Syst. 20, 249–278 (1989).Article 

    Google Scholar 
    27.Ghalambor, C. K., McKay, J. K., Carroll, S. P. & Reznick, D. N. Adaptive versus non-adaptive phenotypic plasticity and the potential for contemporary adaptation in new environments. Funct. Ecol. 21, 394–407 (2007).Article 

    Google Scholar 
    28.Bolnick, D. I. et al. Why intraspecific trait variation matters in community ecology. Trends Ecol. Evol. 26, 183–192 (2011).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    29.Metcalf, C. J. E. & Koskella, B. Protective microbiomes can limit the evolution of host pathogen defense. Evol. Lett. 3, 534–543 (2019).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    30.Rosenberg, E., Koren, O., Reshef, L., Efrony, R. & Zilber-Rosenberg, I. The role of microorganisms in coral health, disease and evolution. Nat. Rev. Microbiol. 5, 355–362 (2007).CAS 
    PubMed 
    Article 

    Google Scholar 
    31.Theis, K. R. et al. Getting the hologenome concept right: an eco-evolutionary framework for hosts and their microbiomes. mSystems 1, e00028 (2016).32.Funkhouser, L. J. & Bordenstein, S. R. Mom knows best: the universality of maternal microbial transmission. PLoS Biol. 11, e1001631 (2013).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    33.Salem, H., Florez, L., Gerardo, N. & Kaltenpoth, M. An out-of-body experience: the extracellular dimension for the transmission of mutualistic bacteria in insects. Proc. R. Soc. Lond. B. 282, 20142957 (2015).34.Vacher, C. et al. The phyllosphere: microbial jungle at the plant–climate interface. Annu. Rev. Ecol. Evol. Syst. 47, 1–24 (2016).Article 

    Google Scholar 
    35.Rothschild, D. et al. Environment dominates over host genetics in shaping human gut microbiota. Nature 555, 210–215 (2018).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    36.Grieneisen, L. E. et al. Genes, geology and germs: gut microbiota across a primate hybrid zone are explained by site soil properties, not host species. Proc. R. Soc. B: Biol. Sci. 286, 20190431 (2019).Article 

    Google Scholar 
    37.McKenney, E. A., Koelle, K., Dunn, R. R. & Yoder, A. D. The ecosystem services of animal microbiomes. Mol. Ecol. 27, 2164–2172 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    38.Sprockett, D., Fukami, T. & Relman, D. A. Role of priority effects in the early-life assembly of the gut microbiota. Nat. Rev. Gastroenterol. Hepatol. 15, 197–205 (2018).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    39.Uhr, G. T., Dohnalová, L. & Thaiss, C. A. The dimension of time in host-microbiome interactions. mSystems 4, e00216–18 (2019).40.van Vliet, S. & Doebeli, M. The role of multilevel selection in host microbiome evolution. Proc. Natl Acad. Sci. U.S.A. 116, 20591–20597 (2019).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    41.Benson, A. K. The gut microbiome—an emerging complex trait. Nat. Genet. 48, 1301 (2016).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    42.van Opstal, E. J. & Bordenstein, S. R. Rethinking heritability of the microbiome. Science 349, 1172–1173 (2015).ADS 
    PubMed 
    Article 

    Google Scholar 
    43.Beilsmith, K. et al. Genome-wide association studies on the phyllosphere microbiome: embracing complexity in host–microbe interactions. Plant J. 97, 164–181 (2019).44.Goodrich, J. K. et al. Human genetics shape the gut microbiome. Cell 159, 789–799 (2014).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    45.Goodrich, J. K. et al. Genetic determinants of the gut microbiome in UK twins. Cell Host Microbe 19, 731–743 (2016).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    46.Early, A. M., Shanmugarajah, N., Buchon, N. & Clark, A. G. Drosophila genotype influences commensal bacterial levels. PLoS ONE 12, e0170332 (2017).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    47.Walters, W. A. et al. Large-scale replicated field study of maize rhizosphere identifies heritable microbes. Proc. Natl Acad. Sci. U. S. A. 115, 7368–7373 (2018).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    48.Camarinha-Silva, A. et al. Host genome influence on gut microbial composition and microbial prediction of complex traits in pigs. Genetics 206, 1637–1644 (2017).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    49.Difford, G. F. et al. Host genetics and the rumen microbiome jointly associate with methane emissions in dairy cows. PLoS Genet 14, e1007580 (2018).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    50.Koga, R., Meng, X.-Y., Tsuchida, T. & Fukatsu, T. Cellular mechanism for selective vertical transmission of an obligate insect symbiont at the bacteriocyte–embryo interface. Proc. Natl Acad. Sci. U.S.A. 109, E1230–E1237 (2012).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    51.Nyholm, S. V. & McFall-Ngai, M. The winnowing: establishing the squid–vibrio symbiosis. Nat. Rev. Microbiol. 2, 632–642 (2004).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    52.Kaltenpoth, M., Göttler, W., Herzner, G. & Strohm, E. Symbiotic bacteria protect wasp larvae from fungal infestation. Curr. Biol. 15, 475–479 (2005).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    53.Clark, R. I. et al. Distinct shifts in microbiota composition during Drosophila aging impair intestinal function and drive mortality. Cell Rep. 12, 1656–1667 (2015).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    54.Franzosa, E. A. et al. Identifying personal microbiomes using metagenomic codes. Proc. Natl Acad. Sci. U.S.A. 112, E2930–E2938 (2015).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    55.Lokmer, A. et al. Spatial and temporal dynamics of pacific oyster hemolymph microbiota across multiple scales. Front. Microbiol. 7, 1367 (2016).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    56.Elena, S. F. & Lenski, R. E. Evolution experiments with microorganisms: the dynamics and genetic bases of adaptation. Nat. Rev. Genet. 4, 457–469 (2003).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    57.Lapierre, P. & Gogarten, J. P. Estimating the size of the bacterial pan-genome. Trends Genet 25, 107–110 (2009).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    58.Koonin, E. V. & Wolf, Y. I. Evolution of microbes and viruses: a paradigm shift in evolutionary biology? Front. Cell. Infect. Microbiol. 2, 119 (2012).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    59.Ferreiro, A., Crook, N., Gasparrini, A. J. & Dantas, G. Multiscale evolutionary dynamics of host-associated microbiomes. Cell 172, 1216–1227 (2018).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    60.Kikuchi, Y., Hosokawa, T. & Fukatsu, T. Specific developmental window for establishment of an insect-microbe gut symbiosis. Appl. Environ. Microbiol. 77, 4075–4081 (2011).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    61.Kikuchi, Y. et al. Symbiont-mediated insecticide resistance. Proc. Natl Acad. Sci. U.S.A. 109, 8618–8622 (2012).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    62.Itoh, H. et al. Infection dynamics of insecticide-degrading symbionts from soil to insects in response to insecticide spraying. ISME J. 12, 909–920 (2018).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    63.Kohl, K. D. & Dearing, M. D. The woodrat gut microbiota as an experimental system for understanding microbial metabolism of dietary toxins. Front. Microbiol. 7, 1165 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    64.Kohl, K. D., Weiss, R. B., Cox, J., Dale, C. & Dearing, M. D. Gut microbes of mammalian herbivores facilitate intake of plant toxins. Ecol. Lett. 17, 1238–1246 (2014).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    65.Miller, A. W., Kohl, K. D. & Dearing, M. D. The gastrointestinal tract of the white-throated Woodrat (Neotoma albigula) harbors distinct consortia of oxalate-degrading bacteria. Appl. Environ. Microbiol. 80, 1595–1601 (2014).ADS 
    PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    66.Miller, A. W., Oakeson, K. F., Dale, C. & Dearing, M. D. Effect of dietary oxalate on the gut microbiota of the mammalian herbivore Neotoma albigula. Appl. Environ. Microbiol. 82, 2669–2675 (2016).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    67.Kohl, K. D., Stengel, A. & Dearing, M. D. Inoculation of tannin-degrading bacteria into novel hosts increases performance on tannin-rich diets. Environ. Microbiol. 18, 1720–1729 (2016).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    68.Kohl, K. D. & Dearing, M. D. Experience matters: prior exposure to plant toxins enhances diversity of gut microbes in herbivores. Ecol. Lett. 15, 1008–1015 (2012).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    69.Redman, R. S., Sheehan, K. B., Stout, R. G., Rodriguez, R. J. & Henson, J. M. Thermotolerance generated by plant/fungal symbiosis. Science 298, 1581 (2002).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    70.Rodriguez, R. J. et al. Stress tolerance in plants via habitat-adapted symbiosis. ISME J. 2, 404–416 (2008).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    71.Miller, E. T., Svanbäck, R. & Bohannan, B. J. M. Microbiomes as Metacommunities: Understanding Host-Associated Microbes through Metacommunity Ecology. Trends Ecol. Evol. 33, 926–935 (2018).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    72.Newell, P. D. & Douglas, A. E. Interspecies interactions determine the impact of the gut microbiota on nutrient allocation in Drosophila melanogaster. Appl. Environ. Microbiol. 80, 788–796 (2014).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    73.Keebaugh, E. S., Yamada, R., Obadia, B., Ludington, W. B. & Ja, W. W. Microbial quantity impacts drosophila nutrition, development, and lifespan. Science 4, 247–259 (2018).CAS 

    Google Scholar 
    74.Gould, A. L. et al. Microbiome interactions shape host fitness. Proc. Natl Acad. Sci. U.S.A. 115, E11951–E11960 (2018).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    75.Mushegian, A. A., Walser, J.-C., Sullam, K. E. & Ebert, D. The microbiota of diapause: How host-microbe associations are formed after dormancy in an aquatic crustacean. J. Anim. Ecol. 87, 400–413 (2017).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    76.Panke-Buisse, K., Poole, A. C., Goodrich, J. K., Ley, R. E. & Kao-Kniffin, J. Selection on soil microbiomes reveals reproducible impacts on plant function. ISME J. 9, 980–989 (2015).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    77.Rolig, A. S., Parthasarathy, R., Burns, A. R., Bohannan, B. J. M. & Guillemin, K. Individual members of the microbiota disproportionately modulate host innate immune responses. Cell Host Microbe 18, 613–620 (2015).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    78.Webster, N. S. & Reusch, T. B. H. Microbial contributions to the persistence of coral reefs. ISME J. 11, 2167–2174 (2017).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    79.Bourne, D. G., Morrow, K. M. & Webster, N. S. Insights into the coral microbiome: underpinning the health and resilience of reef ecosystems. Annu. Rev. Microbiol. 70, 317–340 (2016).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    80.Ainsworth, T. D., Thurber, R. V. & Gates, R. D. The future of coral reefs: a microbial perspective. Trends Ecol. Evol. 25, 233–240 (2010).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    81.Sommer, F. et al. The gut microbiota modulates energy metabolism in the hibernating brown bear Ursus arctos. Cell Rep. 14, 1655–1661 (2016).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    82.Metcalf, C. J. E., Henry, L. P., Rebolleda-Gómez, M. & Koskella, B. Why evolve reliance on the microbiome for timing of ontogeny? MBio 10, e01496-19 (2019).83.Gilbert, S. F., Bosch, T. C. G. & Ledón-Rettig, C. Eco-Evo-Devo: developmental symbiosis and developmental plasticity as evolutionary agents. Nat. Rev. Genet. 16, 611–622 (2015).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    84.Philippi, T. & Seger, J. Hedging one’s evolutionary bets, revisited. Trends Ecol. Evol. 4, 41–44 (1989).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    85.Storelli, G. et al. Lactobacillus plantarum promotes Drosophila systemic growth by modulating hormonal signals through TOR-dependent nutrient sensing. Cell Metab. 14, 403–414 (2011).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    86.Bruijning, M., Henry, L. P., Forsberg, S. K. G., Metcalf, C. J. E. & Ayroles, J. F. When the microbiome defines the host phenotype: selection on vertical transmission in varying environments. bioRxiv 2020.09.02.280040 (2020) https://doi.org/10.1101/2020.09.02.280040.87.Boone, C. K. et al. Bacteria associated with a tree-killing insect reduce concentrations of plant defense compounds. J. Chem. Ecol. 39, 1003–1006 (2013).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    88.Berasategui, A. et al. Gut microbiota of the pine weevil degrades conifer diterpenes and increases insect fitness. Mol. Ecol. 26, 4099–4110 (2017).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    89.Ceja-Navarro, J. A. et al. Gut microbiota mediate caffeine detoxification in the primary insect pest of coffee. Nat. Commun. 6, 7618 (2015).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    90.Berasategui, A. et al. The gut microbiota of the pine weevil is similar across Europe and resembles that of other conifer-feeding beetles. Mol. Ecol. 25, 4014–4031 (2016).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    91.Sachs, J. L., Skophammer, R. G. & Regus, J. U. Evolutionary transitions in bacterial symbiosis. Proc. Natl Acad. Sci. U.S.A 108, 10800–10807 (2011).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    92.Ohbayashi, T. et al. Insect’s intestinal organ for symbiont sorting. Proc. Natl Acad. Sci. U.S.A 112, E5179–E5188 (2015).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    93.Itoh, H. et al. Host–symbiont specificity determined by microbe–microbe competition in an insect gut. Proc. Natl Acad. Sci. U.S.A. 116, 22673–22682 (2019).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    94.Bennett, G. M. & Moran, N. A. Heritable symbiosis: the advantages and perils of an evolutionary rabbit hole. Proc. Natl Acad. Sci. 112, 10169–10176 (2015).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    95.Knight, R. et al. Best practices for analysing microbiomes. Nat. Rev. Microbiol. 16, 410–422 (2018).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    96.Klassen, J. L. Defining microbiome function. Nat. Microbiol 3, 864–869 (2018).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    97.Lau, J. A. & Lennon, J. T. Rapid responses of soil microorganisms improve plant fitness in novel environments. Proc. Natl Acad. Sci. U.S.A. 109, 14058–14062 (2012).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    98.Xu, L. et al. Drought delays development of the sorghum root microbiome and enriches for monoderm bacteria. Proc. Natl Acad. Sci. U.S.A 115, E4284–E4293 (2018).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    99.Cho, I. & Blaser, M. J. The human microbiome: at the interface of health and disease. Nat. Rev. Genet. 13, 260–270 (2012).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    100.Raymann, K., Bobay, L.-M. & Moran, N. A. Antibiotics reduce genetic diversity of core species in the honeybee gut microbiome. Mol. Ecol. 27, 2057–2066 (2018).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    101.David, L. A. et al. Diet rapidly and reproducibly alters the human gut microbiome. Nature 505, 559–563 (2014).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    102.Ziegler, M., Seneca, F. O., Yum, L. K., Palumbi, S. R. & Voolstra, C. R. Bacterial community dynamics are linked to patterns of coral heat tolerance. Nat. Commun. 8, 14213 (2017).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    103.Pollock, J., Glendinning, L., Wisedchanwet, T. & Watson, M. The madness of microbiome: attempting to find consensus ‘best practice’ for 16S microbiome studies. Appl. Environ. Microbiol. 84, e02627–17 (2018).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    104.Roth-Schulze, A. J. et al. Functional biogeography and host specificity of bacterial communities associated with the Marine Green Alga Ulva spp. Mol. Ecol. 27, 1952–1965 (2018).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    105.Lozupone, C. A., Stombaugh, J. I., Gordon, J. I., Jansson, J. K. & Knight, R. Diversity, stability and resilience of the human gut microbiota. Nature 489, 220–230 (2012).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    106.Meaden, S., Metcalf, C. J. E. & Koskella, B. The effects of host age and spatial location on bacterial community composition in the English Oak tree (Quercus robur). Environ. Microbiol. Rep. 8, 649–658 (2016).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    107.Lambais, M. R., Barrera, S. E., Santos, E. C., Crowley, D. E. & Jumpponen, A. Phyllosphere metaproteomes of trees from the Brazilian atlantic forest show high levels of functional redundancy. Microb. Ecol. 73, 123–134 (2017).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    108.Kwong, W. K. & Moran, N. A. Gut microbial communities of social bees. Nat. Rev. Microbiol. 14, 374–384 (2016).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    109.Oh, J. et al. Temporal stability of the human skin microbiome. Cell 165, 854–866 (2016).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    110.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).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    111.Asnicar, F. et al. Studying vertical microbiome transmission from mothers to infants by strain-level metagenomic profiling. mSystems 2, e00164–16 (2017).112.Yassour, M. et al. Strain-level analysis of mother-to-child bacterial transmission during the first few months of life. Cell Host Microbe 24, 146–154.e4 (2018).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    113.Fierer, N. Embracing the unknown: disentangling the complexities of the soil microbiome. Nat. Rev. Microbiol. 15, 579–590 (2017).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    114.Gilbert, J. A. et al. Current understanding of the human microbiome. Nat. Med. 24, 392–400 (2018).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    115.Abubucker, S. et al. Metabolic reconstruction for metagenomic data and its application to the human microbiome. PLoS Comput. Biol. 8, e1002358 (2012).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    116.Jorth, P. et al. Metatranscriptomics of the human oral microbiome during health and disease. MBio 5, e01012–e01014 (2014).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    117.Bashiardes, S., Zilberman-Schapira, G. & Elinav, E. Use of metatranscriptomics in microbiome research. Bioinform. Biol. Insights 10, 19–25 (2016).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    118.Franzosa, E. A. et al. Relating the metatranscriptome and metagenome of the human gut. Proc. Natl Acad. Sci. U.S.A. 111, E2329–E2338 (2014).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    119.Abu-Ali, G. S. et al. Metatranscriptome of human faecal microbial communities in a cohort of adult men. Nat. Microbiol. 3, 356–366 (2018).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    120.Hoang, K. L., Morran, L. T. & Gerardo, N. M. Experimental evolution as an underutilized tool for studying beneficial animal–microbe interactions. Front. Microbiol. 7, 1444 (2016).121.Martino, M. E. et al. Bacterial adaptation to the host’s diet is a key evolutionary force shaping drosophila-lactobacillus symbiosis. Cell Host Microbe 24, 109–119.e6 (2018).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    122.Schlötterer, C., Kofler, R., Versace, E., Tobler, R. & Franssen, S. U. Combining experimental evolution with next-generation sequencing: a powerful tool to study adaptation from standing genetic variation. Heredity 114, 431–440 (2015).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    123.Henry, L. P. & Ayroles, J. F. Meta-analysis suggests the microbiome responds to Evolve and Resequence experiments in Drosophila melanogaster. BMC Microbiol 21, 108 (2021).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    124.Wagner, M. R. et al. Natural soil microbes alter flowering phenology and the intensity of selection on flowering time in a wild Arabidopsis relative. Ecol. Lett. 17, 717–726 (2014).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    125.Hendry, A. P. Eco-evolutionary Dynamics. (Princeton University Press, 2017).126.Bang, C. et al. Metaorganisms in extreme environments: do microbes play a role in organismal adaptation? Zoology 127, 1–19 (2018).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    127.Hoyt, J. R. et al. Bacteria isolated from bats inhibit the growth of Pseudogymnoascus destructans, the causative agent of white-nose syndrome. PLoS ONE 10, e0121329 (2015).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    128.Cheng, T. L. et al. Efficacy of a probiotic bacterium to treat bats affected by the disease white-nose syndrome. J. Appl. Ecol. 54, 701–708 (2016).Article 

    Google Scholar 
    129.Woodhams, D. C., Bletz, M., Kueneman, J. & McKenzie, V. Managing amphibian disease with skin microbiota. Trends Microbiol. 24, 161–164 (2016).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    130.Weiss, B. & Aksoy, S. Microbiome influences on insect host vector competence. Trends Parasitol. 27, 514–522 (2011).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    131.Zitvogel, L., Ma, Y., Raoult, D., Kroemer, G. & Gajewski, T. F. The microbiome in cancer immunotherapy: diagnostic tools and therapeutic strategies. Science 359, 1366–1370 (2018).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    132.Toju, H. et al. Core microbiomes for sustainable agroecosystems. Nat. Plants 4, 247–257 (2018).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    133.Costello, E. K., Stagaman, K., Dethlefsen, L., Bohannan, B. J. M. & Relman, D. A. The application of ecological theory toward an understanding of the human microbiome. Science 336, 1255–1262 (2012).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    134.Christian, N., Whitaker, B. K. & Clay, K. Microbiomes: unifying animal and plant systems through the lens of community ecology theory. Front. Microbiol. 6, 869 (2015).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    135.Trevelline, B. K., Fontaine, S. S., Hartup, B. K. & Kohl, K. D. Conservation biology needs a microbial renaissance: a call for the consideration of host-associated microbiota in wildlife management practices. Proc. Biol. Sci. 286, 20182448 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    136.Mueller, E. A., Wisnoski, N. I., Peralta, A. L. & Lennon, J. T. Microbial rescue effects: how microbiomes can save hosts from extinction. Funct. Ecol. 34, 2055-2064 (2020).137.Hird, S. M. Evolutionary biology needs wild microbiomes. Front. Microbiol. 8, 725 (2017).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    138.Wade, M. J. The co-evolutionary genetics of ecological communities. Nat. Rev. Genet. 8, 185–195 (2007).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    139.Hammer, T. J., Janzen, D. H., Hallwachs, W., Jaffe, S. P. & Fierer, N. Caterpillars lack a resident gut microbiome. Proc. Natl Acad. Sci. 114, 9641–9646 (2017).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    140.Hammer, T. J., Sanders, J. G. & Fierer, N. Not all animals need a microbiome. FEMS Microbiol. Lett. 366, fnz117 (2019).141.Heath, K. D. & Stinchcombe, J. R. Explaining mutualism variation: a new evolutionary paradox? Evolution 68, 309–317 (2014).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    142.Sandoval-Motta, S., Aldana, M., Martínez-Romero, E. & Frank, A. The human microbiome and the missing heritability problem. Front. Genet. 8, 80 (2017).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    143.Wallace, R. J. et al. A heritable subset of the core rumen microbiome dictates dairy cow productivity and emissions. Sci. Adv. 5, eaav8391 (2019).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    144.Vollmar, S. et al. The gut microbial architecture of efficiency traits in the domestic poultry model species japanese quail (Coturnix japonica) assessed by mixed linear models. G3 10, 2553–2562 (2020).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    145.Hoffmann, A. A., Sgrò, C. M. & Kristensen, T. N. Revisiting adaptive potential, population size, and conservation. Trends Ecol. Evol. 32, 506–517 (2017).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    146.Bruijning, M., Metcalf, C. J. E., Jongejans, E. & Ayroles, J. F. The evolution of variance control. Trends Ecol. Evol. 35, 22–33 (2020).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    147.Douglas, G. M., Bielawski, J. P. & Langille, M. G. I. Re-evaluating the relationship between missing heritability and the microbiome. Microbiome 8, 87 (2020).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    148.Johannes, F., Colot, V. & Jansen, R. C. Epigenome dynamics: a quantitative genetics perspective. Nat. Rev. Genet. 9, 883–890 (2008).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    149.Slatkin, M. Epigenetic inheritance and the missing heritability problem. Genetics 182, 845–850 (2009).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    150.Hernando-Herraez, I., Garcia-Perez, R., Sharp, A. J. & Marques-Bonet, T. DNA methylation: insights into human evolution. PLoS Genet 11, e1005661 (2015).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    151.Pujol, B. et al. The missing response to selection in the wild. Trends Ecol. Evol. 33, 337–346 (2018).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    152.Shaw, R. G. From the past to the future: considering the value and limits of evolutionary prediction. Am. Nat. 193, 1–10 (2019).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    153.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).154.Truong, D. T., Tett, A., Pasolli, E., Huttenhower, C. & Segata, N. Microbial strain-level population structure and genetic diversity from metagenomes. Genome Res. 27, 626–638 (2017).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    155.Spor, A., Koren, O. & Ley, R. Unravelling the effects of the environment and host genotype on the gut microbiome. Nat. Rev. Microbiol. 9, 279–290 (2011).CAS 
    PubMed 
    Article 

    Google Scholar 
    156.Guo, Y. et al. Networks underpinning symbiosis revealed through cross-species eQTL mapping. Genetics 206, 2175–2184 (2017).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    157.Kohl, K. D. An introductory ‘how-to’ guide for incorporating microbiome research into integrative and comparative biology. Integr. Comp. Biol. 57, 674–681 (2017).PubMed 
    Article 

    Google Scholar 
    158.Marchesi, J. R. & Ravel, J. The vocabulary of microbiome research: a proposal. Microbiome 3, 31 (2015).PubMed 
    Article 
    PubMed Central 

    Google Scholar  More

  • in

    Novel and disappearing climates in the global surface ocean from 1800 to 2100

    1.IPCC. Climate Change 2013: The Physical Science Basis. Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge University Press, 2013).
    Google Scholar 
    2.Dunne, J. P. et al. GFDL’s ESM2 global coupled climate-carbon earth system models. Part II: Carbon system formulation and baseline simulation characteristics. J. Clim. 26, 2247–2267 (2013).Article 
    ADS 

    Google Scholar 
    3.Jiang, L.-Q., Carter, B. R., Feely, R. A., Lauvset, S. K. & Olsen, A. Surface ocean pH and buffer capacity: Past, present and future. Nat. Sci. Rep. 9, 18624 (2019).CAS 
    Article 
    ADS 

    Google Scholar 
    4.Caldeira, K. & Wickett, M. E. Oceanography: Anthropogenic carbon and ocean pH. Nature 425, 365–365 (2003).CAS 
    PubMed 
    Article 
    ADS 

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

    Google Scholar 
    6.Hönisch, B. et al. The geological record of ocean acidification. Science 335, 1058–1063 (2012).PubMed 
    Article 
    ADS 
    CAS 

    Google Scholar 
    7.Williams, J. W., Jackson, S. T. & Kutzbach, J. E. Projected distributions of novel and disappearing climates by 2100 AD. Proc. Natl. Acad. Sci. U. S. A. 104, 5738–5742 (2007).CAS 
    PubMed 
    PubMed Central 
    Article 
    ADS 

    Google Scholar 
    8.Williams, J. W. & Jackson, S. T. Novel climates, no-analog communities, and ecological surprises. Front. Ecol. Environ. 5, 475–482 (2007).Article 

    Google Scholar 
    9.Radeloff, V. C. et al. The rise of novelty in ecosystems. Ecol. Appl. 25, 2051–2068 (2015).PubMed 
    Article 

    Google Scholar 
    10.Sunday, J. M., Bates, A. E. & Dulvy, N. K. Thermal tolerance and the global redistribution of animals. Nat. Clim. Change 2, 686–690 (2012).Article 
    ADS 

    Google Scholar 
    11.Pinsky, M. L., Worm, B., Fogarty, M. J., Sarmiento, J. L. & Levin, S. A. Marine taxa track local climate velocities. Science 341, 1239–1242 (2013).CAS 
    PubMed 
    Article 
    ADS 
    PubMed Central 

    Google Scholar 
    12.Pinsky, M. L., Selden, R. L. & Kitchel, Z. J. Climate-driven shifts in marine species ranges: Scaling from organisms to communities. Ann. Rev. Mar. Sci. 12, 153–179 (2020).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    13.Bell, G. & Collins, S. Adaptation, extinction and global change. Evol. Appl. 1, 3–16 (2008).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    14.Lancaster, L. T., Morrison, G. & Fitt, R. N. Life history trade-offs, the intensity of competition, and coexistence in novel and evolving communities under climate change. Philos. Trans. R. Soc. Lond. B Biol. Sci. 372, 20160046 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    15.Henson, S. A. et al. Rapid emergence of climate change in environmental drivers of marine ecosystems. Nat. Commun. 8, 14682 (2017).PubMed 
    PubMed Central 
    Article 
    ADS 

    Google Scholar 
    16.Bruno, J. F. et al. Climate change threatens the world’s marine protected areas. Nat. Clim. Change 8, 499–503 (2018).Article 
    ADS 

    Google Scholar 
    17.Turk, D. et al. Time of emergence of surface ocean carbon dioxide trends in the North American coastal margins in support of ocean acidification observing system design. Front. Mar. Sci. 6, 91 (2019).Article 

    Google Scholar 
    18.Jiang, L.-Q. et al. Climatological distribution of aragonite saturation state in the global oceans. Global Biogeochem. Cycles 29, 1656–1673 (2015).CAS 
    Article 
    ADS 

    Google Scholar 
    19.Orr, J. C. et al. Anthropogenic ocean acidification over the twenty-first century and its impact on calcifying organisms. Nature 437, 681–686 (2005).CAS 
    PubMed 
    Article 
    ADS 
    PubMed Central 

    Google Scholar 
    20.Feely, R. A., Doney, S. C. & Cooley, S. R. Ocean acidification: Present conditions and future changes in a high-CO2 world. Oceanography 22, 36–47 (2009).Article 

    Google Scholar 
    21.Tittensor, D. P. et al. Global patterns and predictors of marine biodiversity across taxa. Nature 466, 1098–1101 (2010).CAS 
    PubMed 
    Article 
    ADS 
    PubMed Central 

    Google Scholar 
    22.Allen, A. P., Brown, J. H. & Gillooly, J. F. Global biodiversity, biochemical kinetics, and the energetic-equivalence rule. Science 297, 1545–1548 (2002).CAS 
    PubMed 
    Article 
    ADS 
    PubMed Central 

    Google Scholar 
    23.Donner, S. D. Coping with commitment: Projected thermal stress on coral reefs under different future scenarios. PLoS ONE 4, e5712 (2009).PubMed 
    PubMed Central 
    Article 
    ADS 
    CAS 

    Google Scholar 
    24.Walsh, P. J. & Louise Milligan, C. Coordination of metabolism and intracellular acid–base status: Ionic regulation and metabolic consequences. Can. J. Zool. 67, 2994–3004 (1989).CAS 
    Article 

    Google Scholar 
    25.Nilsson, G. E. et al. Near-future carbon dioxide levels alter fish behaviour by interfering with neurotransmitter function. Nat. Clim. Change 2, 201–204 (2012).CAS 
    Article 
    ADS 

    Google Scholar 
    26.Clark, T. D. et al. Ocean acidification does not impair the behaviour of coral reef fishes. Nature 577, 370–375 (2020).CAS 
    PubMed 
    Article 
    ADS 
    PubMed Central 

    Google Scholar 
    27.Waldbusser, G. G. et al. A developmental and energetic basis linking larval oyster shell formation to acidification sensitivity. Geophys. Res. Lett. 40, 2171–2176 (2013).CAS 
    Article 
    ADS 

    Google Scholar 
    28.Waldbusser, G. G. et al. Saturation-state sensitivity of marine bivalve larvae to ocean acidification. Nat. Clim. Change 5, 273–280 (2015).CAS 
    Article 
    ADS 

    Google Scholar 
    29.Dunne, J. P. et al. GFDL’s ESM2 global coupled climate-carbon earth system models. Part I: Physical formulation and baseline simulation characteristics. J. Clim. 25, 6646–6665 (2012).Article 
    ADS 

    Google Scholar 
    30.Mahony, C. R., Cannon, A. J., Wang, T. & Aitken, S. N. A closer look at novel climates: New methods and insights at continental to landscape scales. Glob. Change Biol. https://doi.org/10.1111/gcb.13645 (2017).Article 

    Google Scholar 
    31.Millar, R. J. et al. Emission budgets and pathways consistent with limiting warming to 1.5 °C. Nat. Geosci. 10, 741–747 (2017).CAS 
    Article 
    ADS 

    Google Scholar 
    32.Sanderson, B. M., O’Neill, B. C. & Tebaldi, C. What would it take to achieve the Paris temperature targets?. Geophys. Res. Lett. 43, 7133–7142 (2016).Article 
    ADS 

    Google Scholar 
    33.Friedlingstein, P. et al. Persistent growth of CO2 emissions and implications for reaching climate targets. Nat. Geosci. 7, 709–715 (2014).CAS 
    Article 
    ADS 

    Google Scholar 
    34.Steele, J. H., Brink, K. H. & Scott, B. E. Comparison of marine and terrestrial ecosystems: Suggestions of an evolutionary perspective influenced by environmental variation. ICES J. Mar. Sci. 76, 50–59 (2019).Article 

    Google Scholar 
    35.Munday, P. L., Warner, R. R., Monro, K., Pandolfi, J. M. & Marshall, D. J. Predicting evolutionary responses to climate change in the sea. Ecol. Lett. 16, 1488–1500 (2013).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    36.Kelly, M. W. & Hofmann, G. E. Adaptation and the physiology of ocean acidification. Funct. Ecol. 27, 980–990 (2013).Article 

    Google Scholar 
    37.Sunday, J. M. et al. Evolution in an acidifying ocean. Trends Ecol. Evol. 29, 117–125 (2014).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    38.Pinsky, M. L., Eikeset, A. M., McCauley, D. J., Payne, J. L. & Sunday, J. M. Greater vulnerability to warming of marine versus terrestrial ectotherms. Nature 569, 108–111 (2019).CAS 
    PubMed 
    Article 
    ADS 
    PubMed Central 

    Google Scholar 
    39.Hoegh-Guldberg, O. Climate change, coral bleaching and the future of the world’s coral reefs. Mar. Freshw. Res. 50, 839–866 (1999).
    Google Scholar 
    40.Donelson, J. M., Salinas, S., Munday, P. L. & Shama, L. N. S. Transgenerational plasticity and climate change experiments: Where do we go from here?. Glob. Change Biol. 24, 13–34 (2018).Article 
    ADS 

    Google Scholar 
    41.Ross, P. M., Parker, L. & Byrne, M. Transgenerational responses of molluscs and echinoderms to changing ocean conditions. ICES J. Mar. Sci. 73, 537–549 (2016).Article 

    Google Scholar 
    42.Eirin-Lopez, J. M. & Putnam, H. M. Marine environmental epigenetics. Ann. Rev. Mar. Sci. 11, 335–368 (2019).PubMed 
    Article 

    Google Scholar 
    43.Baumann, H. & Smith, E. M. Quantifying metabolically driven pH and oxygen fluctuations in US nearshore habitats at diel to interannual time scales. Estuaries Coasts 41, 1102–1117 (2018).CAS 
    Article 

    Google Scholar 
    44.Chan, F. et al. Persistent spatial structuring of coastal ocean acidification in the California Current System. Sci. Rep. 7, 1–7 (2017).Article 
    CAS 

    Google Scholar 
    45.Steinacher, M. et al. Projected 21st century decrease in marine productivity: A multi-model analysis. Biogeosciences 7, 27 (2010).Article 

    Google Scholar 
    46.Gruber, N. Warming up, turning sour, losing breath: Ocean biogeochemistry under global change. Philos. Trans. A Math. Phys. Eng. Sci. 369, 1980–1996 (2011).CAS 
    PubMed 
    ADS 

    Google Scholar 
    47.Wang, D., Gouhier, T. C., Menge, B. A. & Ganguly, A. R. Intensification and spatial homogenization of coastal upwelling under climate change. Nature 518, 390–394 (2015).CAS 
    PubMed 
    Article 
    ADS 

    Google Scholar 
    48.Bakun, A. Global climate change and intensification of coastal ocean upwelling. Science 247, 198–201 (1990).CAS 
    PubMed 
    Article 
    ADS 

    Google Scholar 
    49.Bopp, L. et al. Potential impact of climate change on marine export production. Global Biogeochem. Cycles 15, 81–99 (2001).CAS 
    Article 
    ADS 

    Google Scholar 
    50.Doney, S. C. et al. Climate change impacts on marine ecosystems. Ann. Rev. Mar. Sci. 4, 11–37 (2012).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    51.Vaquer-Sunyer, R. & Duarte, C. M. Thresholds of hypoxia for marine biodiversity. Proc. Natl. Acad. Sci. U. S. A. 105, 15452–15457 (2008).CAS 
    PubMed 
    PubMed Central 
    Article 
    ADS 

    Google Scholar 
    52.Curry, R., Dickson, B. & Yashayaev, I. A change in the freshwater balance of the Atlantic Ocean over the past four decades. Nature 426, 826–829 (2003).CAS 
    PubMed 
    Article 
    ADS 
    PubMed Central 

    Google Scholar 
    53.Briggs, J. C. Marine centres of origin as evolutionary engines. J. Biogeogr. 30, 1–18 (2003).Article 

    Google Scholar 
    54.Bowen, B. W., Rocha, L. A., Toonen, R. J., Karl, S. A. & ToBo Laboratory. The origins of tropical marine biodiversity. Trends Ecol. Evol. 28, 359–366 (2013).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    55.Burke, L. M., Reytar, K., Spalding, M. & Perry, A. Reefs at Risk Revisited in the Coral Triangle (World Resources Institute, 2012).
    Google Scholar 
    56.Boyd, P. W., Lennartz, S. T., Glover, D. M. & Doney, S. C. Biological ramifications of climate-change-mediated oceanic multi-stressors. Nat. Clim. Chang. 5, 71 (2014).Article 
    ADS 

    Google Scholar 
    57.Hoegh-Guldberg, O. & Bruno, J. F. The impact of climate change on the world’s marine ecosystems. Science 328, 1523–1528 (2010).CAS 
    PubMed 
    Article 
    ADS 
    PubMed Central 

    Google Scholar 
    58.Bakker, D. C. E. et al. A multi-decade record of high-quality fCO2 data in version 3 of the Surface Ocean CO2 Atlas (SOCAT). Earth Syst. Sci. Data 8, 383–413 (2016).Article 
    ADS 

    Google Scholar 
    59.Lauvset, S. K. et al. A new global interior ocean mapped climatology: The 1 × 1 GLODAP version 2. Earth Syst. Sci. Data 8, 325–340 (2016).Article 
    ADS 

    Google Scholar 
    60.Carter, B. R. et al. Updated methods for global locally interpolated estimation of alkalinity, pH, and nitrate. Limnol. Oceanogr. Methods 16, 119–131 (2017).Article 
    CAS 

    Google Scholar 
    61.Lueker, T. J., Dickson, A. G. & Keeling, C. D. Ocean pCO2 calculated from dissolved inorganic carbon, alkalinity, and equations for K1 and K2: Validation based on laboratory measurements of CO2 in gas and seawater at equilibrium. Mar. Chem. 70, 105–119 (2000).CAS 
    Article 

    Google Scholar 
    62.Dickson, A. G. Standard potential of the reaction: AgCl (s) + 12H2 (g) = Ag (s) + HCl (aq), and and the standard acidity constant of the ion HSO4− in synthetic sea water from 273.15 to 318.15 K. J. Chem. Thermodyn. 22, 113–127 (1990).CAS 
    Article 

    Google Scholar 
    63.Perez, F. F. & Fraga, F. Association constant of fluoride and hydrogen ions in seawater. Mar. Chem. 21, 161–168 (1987).CAS 
    Article 

    Google Scholar 
    64.Uppström, L. R. The boron/chlorinity ratio of deep-sea water from the Pacific Ocean. Deep Sea Res. Oceanogr. Abstr. 21, 161–162 (1974).Article 
    ADS 

    Google Scholar 
    65.van Heuven, S. et al. MATLAB Program Developed for CO2 System Calculations (Carbon Dioxide Information Analysis Center, 2011). https://doi.org/10.3334/cdiac/otg.co2sys_matlab_v1.1Book 

    Google Scholar 
    66.Lewis, E., Wallace, D. & Allison, L. J. Program Developed for CO2 System Calculations (ORNL/CDIAC-105, Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U. S. Department of Energy, 1998). https://doi.org/10.2172/63971267.Orr, J. C., Epitalon, J.-M., Dickson, A. G. & Gattuso, J.-P. Routine uncertainty propagation for the marine carbon dioxide system. Mar. Chem. 207, 84–107 (2018).CAS 
    Article 

    Google Scholar 
    68.IPCC. Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC, 2014).
    Google Scholar 
    69.NOAA. Extended Reconstructed Sea Surface Temperature (ERSST.v5) (National Centers for Environmental Information, 2017). www.ncdc.noaa.gov/data-access/marineocean-data/extended-reconstructed-sea-surface-temperature-ersst70.Takahashi, T. et al. Climatological distributions of pH, pCO2, total CO2, alkalinity, and CaCO3 saturation in the global surface ocean, and temporal changes at selected locations. Mar. Chem. 164, 95–125 (2014).CAS 
    Article 

    Google Scholar 
    71.Locarnini, R. A. et al. World Ocean Atlas 2013, Volume 1: Temperature (NOAA Atlas NESDIS 73, 2013).
    Google Scholar 
    72.Barth, A., Beckers, J.-M., Troupin, C., Alvera-Azcárate, A. & Vandenbulcke, L. Divand-1.0: n-dimensional variational data analysis for ocean observations. Geosci. Model Dev. 7, 225–241 (2014).Article 
    ADS 

    Google Scholar 
    73.HOTS, station ALOHA. HOTS (Hawaii Ocean Time Series), station ALOHA. http://hahana.soest.hawaii.edu/hot/hot-dogs/bextraction.html (2018).74.UNH_CML. CML (University of New Hampshire Coastal Marine Laboratory), Salisbury, J. UNH CML Station—Coastal Marine Laboratory. http://www.neracoos.org/erddap/tabledap/UNH_CML.html (2019).75.BBH. BBH (Boothbay Harbor) Sea Water Temperature Record in Maine. https://www.maine.gov/dmr/science-research/weather-tides/bbhenv.html (2019).76.Sutton, A. J. et al. High-Resolution Ocean and Atmosphere pCO2 Time-Series Measurements from Mooring NH_70W_43N (NCEI Accession 0115402). (NOAA (National Oceanic and Atmospheric Administration) National Centers for Environmental Information, 2014). https://www.nodc.noaa.gov/archive/arc0062/0115402/8.8/data/0-data/ More

  • in

    Predation by avian predators may have initiated the evolution of myrmecomorph spiders

    1.McIver, D. J. & Stonedahl, G. Myrmecomorphy: Morphological and behavioral mimicry of ants. Annual Rev. Entomol. 38, 351–377. https://doi.org/10.1146/annurev.en.38.010193.002031 (1993).Article 

    Google Scholar 
    2.Cushing, P. E. Spider-ant associations: An updated review of myrmecomorphy, myrmecophily, and myrmecophagy in spiders. Psyche 2012, 151989. https://doi.org/10.1155/2012/151989 (2012).Article 

    Google Scholar 
    3.Jackson, R. R., Nelson, X. J. & Salm, K. The natural history of Myrmarachne melanotarsa, a social ant-mimicking jumping spider. N. Z. J. Zool. 35, 225–235. https://doi.org/10.1080/03014220809510118 (2008).Article 

    Google Scholar 
    4.Nelson, J. X., Jackson, R. R., Li, D., Barrion, T. A. & Edwards, B. G. Innate aversion to ants (Hymenoptera: Formicidae) and ant mimics: Experimental findings from mantises (Mantodea). Biol. J. Linnean Soc. 88, 23–32. https://doi.org/10.1111/j.1095-8312.2006.00598.x (2006).Article 

    Google Scholar 
    5.Pekár, S. & Jarab, M. Life-history constraints in inaccurate Batesian myrmecomorphic spiders (Araneae: Corinnidae, Gnaphosidae). Eur. J. Entomol. 108, 255–260. https://doi.org/10.14411/eje.2011.034 (2011).Article 

    Google Scholar 
    6.Pekár, S. & Jarab, M. Assessment of color and behavioral resemblance to models by inaccurate myrmecomorphic spiders (Araneae). Invertebr. Biol. 130, 83–90. https://doi.org/10.1111/j.1744-7410.2010.00217.x (2011).Article 

    Google Scholar 
    7.Pekár, S. & Král, J. Mimicry complex in two central European zodariid spiders (Araneae: Zodariidae): How Zodarion deceives ants. Biol. J. Linnean Soc. 75, 517–532. https://doi.org/10.1046/j.1095-8312.2002.00043.x (2002).Article 

    Google Scholar 
    8.Hölldobler, B. Communication between ants and their guests. Sci. Am. 224, 86–95 (1971).Article 

    Google Scholar 
    9.Jackson, R. R. & Wilcox, R. S. Aggressive mimicry, prey-specific predatory behaviour and predator recognition in the predator-prey interactions of Portia fimbriata and Euryattus sp., jumping spiders from Queensland. Behav. Ecol. Sociobiol. 26, 111–119. https://doi.org/10.1007/BF00171580 (1990).Article 

    Google Scholar 
    10.Hölldobler, B. Host finding by odor in the myrmecophilic beetle Atemeles pubicollis Bris. (Staphylinidae). Science 166, 757–758. https://doi.org/10.1126/science.166.3906.757 (1969).ADS 
    Article 
    PubMed 

    Google Scholar 
    11.Elgar, A. M. & Allan, A. R. Chemical mimicry of the ant Oecophylla smaragdina by the myrmecophilous spider Cosmophasis bitaeniata: Is it colony-specific?. J. Ethol. 24, 239–246. https://doi.org/10.1007/s10164-005-0188-9 (2006).Article 

    Google Scholar 
    12.von Beeren, C., Hashim, R. & Witte, V. The social integration of a myrmecophilous spider does not depend exclusively on chemical mimicry. J. Chem. Ecol. 38, 262–271. https://doi.org/10.1007/s10886-012-0083-0 (2012).CAS 
    Article 

    Google Scholar 
    13.Nelson, X. J. & Jackson, R. R. Vision-based innate aversion to ants and ant mimics. Behav. Ecol. 17, 676–681. https://doi.org/10.1093/beheco/ark017 (2006).Article 

    Google Scholar 
    14.Edmunds, M. Does mimicry of ants reduce predation by wasps on salticid spiders?. Mem. Queensl. Mus. 33, 23–32 (1993).
    Google Scholar 
    15.Huang, J. N., Cheng, R. C., Li, D. & Tso, I. M. Salticid predation as one potential driving force of ant mimicry in jumping spiders. Proc. R. Soc. B 278, 1356–1364. https://doi.org/10.1098/rspb.2010.1896 (2011).Article 
    PubMed 

    Google Scholar 
    16.Lindström, L. Experimental approaches to studying the initial evolution of conspicuous aposematic signalling. Evol. Ecol. 13, 605–618. https://doi.org/10.1023/A:1011004129607 (1999).Article 

    Google Scholar 
    17.Ruxton, G. D., Allen, W. L., Sherratt, T. N. & Speed, M. P. Avoiding Attack: The Evolutionary Ecology of Crypsis, Aposematism, and Mimicry (Oxford University Press, 2019).
    Google Scholar 
    18.Veselý, P. & Fuchs, R. Newly emerged Batesian mimicry protects only unfamiliar prey. Evol. Ecol. 23, 919–929. https://doi.org/10.1007/s10682-008-9281-1 (2009).Article 

    Google Scholar 
    19.Nelson, X. J. & Jackson, R. R. Collective Batesian mimicry of ant groups by aggregating spiders. Anim. Behav. 78, 123–129. https://doi.org/10.1016/j.anbehav.2009.04.005 (2009).Article 

    Google Scholar 
    20.Cramp, S. & Brooks, D. J. Handbook of the Birds of Europe, the Middle East and North Africa. The Birds of the Western Palearctic. Warbles Vol. VI (Oxford University Press, 1992).
    Google Scholar 
    21.Cramp, S. & Perrins, C. M. Handbook of the Birds of Europe, the Middle East and North Africa. The Birds of the Western Palearctic. Flycatchers to Shrikes Vol. VII (Oxford University Press, 1993).
    Google Scholar 
    22.Cramp, S. & Simmons, K. E. L. Handbook of the Birds of Europe, the Middle East and North Africa: The Birds of the Western Palearctic. Terns to woodpeckers Vol. IV (Oxford University Press, 1985).
    Google Scholar 
    23.Cramp, S., Perrins, C. M. & Brooks, D. J. Handbook of the birds of Europe, the Middle East, and North Africa: The birds of the Western Palearctic. Crows to finches Vol. VIII (Oxford University Press, 1994).
    Google Scholar 
    24.Veselý, P., Luhanová, D., Prášková, M. & Fuchs, R. Generalization of mimics imperfect in colour patterns: The point of view of wild avian predators. Ethology 119, 138–145. https://doi.org/10.1111/j.1095-8312.2010.01463.x (2013).Article 

    Google Scholar 
    25.Průchová, A., Nedvěd, O., Veselý, P., Ernestová, B. & Fuchs, R. Visual warning signals of the ladybird Harmonia axyridis: The avian predators’ point of view. Entomol. Exp. Appl. 151, 128–134. https://doi.org/10.1111/eea.12176 (2014).Article 

    Google Scholar 
    26.Kevan, P. G., Chittka, L. & Dyer, A. G. Limits to the salience of ultraviolet: Lessons from colour vision in bees and birds. J. Exp. Biol. 204, 2571–2580 (2001).CAS 
    Article 

    Google Scholar 
    27.Pekár, S., Petráková, L., Bulbert, M. W., Whiting, M. J. & Herberstein, M. E. The golden mimicry complex uses a wide spectrum of defence to deter a community of predators. Elife 6, e22089. https://doi.org/10.7554/eLife.22089 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    28.Uma, D., Durkee, C., Herzner, G. & Weiss, M. Double deception: Ant-mimicking spiders elude both visually-and chemically-oriented predators. PLoS ONE 8, e79660. https://doi.org/10.1371/journal.pone.0079660 (2013).ADS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    29.Lindström, L., Alatalo, R. V., Lyytinen, A. & Mappes, J. The effect of alternative prey on the dynamics of imperfect Batesian and Müllerian mimicries. Evolution 58, 1294–1302. https://doi.org/10.1111/j.0014-3820.2004.tb01708.x (2004).Article 
    PubMed 

    Google Scholar 
    30.McNab, B. K. Physiological convergence amongst ant-eating and termite-eating mammals. J. Zool. Lond. 203, 485–510. https://doi.org/10.1111/j.1469-7998.1984.tb02345.x (1984).Article 

    Google Scholar 
    31.Naef-Daenzer, L., Naef-Daenzer, B. & Nager, R. G. Prey selection and foraging performance of breeding Great Tits Parus major in relation to food availability. J. Avian Biol. 31, 206–214. https://doi.org/10.1034/j.1600-048X.2000.310212.x (2000).Article 

    Google Scholar 
    32.Wilkin, T. A., King, L. E. & Sheldon, B. C. Habitat quality, nestling diet, and provisioning behaviour in great tits Parus major. J. Avian Biol. 40, 135–145. https://doi.org/10.1111/j.1600-048X.2009.04362.x (2009).Article 

    Google Scholar 
    33.Svádová, K. et al. Role of different colours of aposematic insects in learning, memory and generalization of naïve bird predators. Anim. Behav. 77, 327–336. https://doi.org/10.1016/j.anbehav.2008.09.034 (2009).Article 

    Google Scholar 
    34.Sendoya, S. F., Freitas, A. V. & Oliveira, P. S. Egg-laying butterflies distinguish predaceous ants by sight. Am. Nat. 174, 134–140. https://doi.org/10.1086/599302 (2009).Article 
    PubMed 

    Google Scholar 
    35.Exnerová, A. et al. Different reactions to aposematic prey in 2 geographically distant populations of great tits. Behav. Ecol. 26, 1361–1370. https://doi.org/10.1093/beheco/arv086 (2015).Article 

    Google Scholar 
    36.Harrap, S. & Quinn, D. Chickadees, Tits, Nuthatches & Treecreepers (Princeton University Press, 1995).
    Google Scholar 
    37.Pagani-Núñez, E., Ruiz, Í., Quesada, J., Negro, J. J. & Senar, J. C. The diet of Great Tit Parus major nestlings in a Mediterranean Iberian forest: The important role of spiders. Anim. Biodivers. Conserv. 34, 355–361 (2011).
    Google Scholar 
    38.Exnerová, A. et al. Reactions of passerine birds to aposematic and non-aposematic firebugs (Pyrrhocoris apterus; Heteroptera). Biol. J. Linnean Soc. 78, 517–525. https://doi.org/10.1046/j.0024-4066.2002.00161.x (2003).Article 

    Google Scholar 
    39.Exnerová, A. et al. Importance of colour in the reaction of passerine predators to aposematic prey: Experiments with mutants of Pyrrhocoris apterus (Heteroptera). Biol. J. Linnean Soc. 88, 143–153. https://doi.org/10.1111/j.1095-8312.2006.00611.x (2006).Article 

    Google Scholar 
    40.Cibulková, A., Veselý, P. & Fuchs, R. Importance of conspicuous colours in warning signals: The great tit’s (Parus major) point of view. Evol. Ecol. 28, 427–439. https://doi.org/10.1007/s10682-014-9690-2 (2014).Article 

    Google Scholar 
    41.Prokopová, M., Veselý, P., Fuchs, R. & Zrzavý, J. The role of size and colour pattern in protection of developmental stages of the red firebug (Pyrrhocoris apterus) against avian predators. Biol. J. Linnean Soc. 100, 890–898. https://doi.org/10.1111/j.1095-8312.2010.01463.x (2010).Article 

    Google Scholar 
    42.R Core Team. R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, 2020). https://www.R-project.org.43.Yamasaki, T. Studies on taxonomy, biogeography and mimicry of the genus Myrmarachne in Southeast Asia. Acta Arachnol. 64, 49–56 (2015).Article 

    Google Scholar 
    44.Nelson, X. J. & Jackson, R. R. How spiders practice aggressive and Batesian mimicry. Curr. Zool. 58, 620–629. https://doi.org/10.1093/czoolo/58.4.620 (2012).Article 

    Google Scholar  More

  • in

    Rapid, but limited, zooplankton adaptation to simultaneous warming and acidification

    1.Hönisch, B. et al. The geological record of ocean acidification. Science 335, 1058–1063 (2012).Article 
    CAS 

    Google Scholar 
    2.Bindoff, N. L. et al. in Special Report on the Ocean and Cryosphere in a Changing Climate (eds Pörtner, H.-O. et al.) 447–588 (IPCC, 2019).3.Pörtner, H.-O. et al. in Special Report on the Ocean and Cryosphere in a Changing Climate (eds Pörtner, H.-O. et al.) 35–74 (IPCC, 2019).4.Caldeira, K. & Wickett, M. E. Anthropogenic carbon and ocean pH. Nature 425, 365 (2003).CAS 
    Article 

    Google Scholar 
    5.Cai, W. J. et al. Acidification of subsurface coastal waters enhanced by eutrophication. Nat. Geosci. 4, 766–770 (2011).CAS 
    Article 

    Google Scholar 
    6.Wallace, R. B., Baumann, H., Grear, J. S., Aller, R. C. & Gobler, C. J. Coastal ocean acidification: the other eutrophication problem. Estuar. Coast. Shelf Sci. 148, 1–13 (2014).CAS 
    Article 

    Google Scholar 
    7.Munday, P. L., Warner, R. R., Monro, K., Pandolfi, J. M. & Marshall, D. J. Predicting evolutionary responses to climate change in the sea. Ecol. Lett. 16, 1488–1500 (2013).Article 

    Google Scholar 
    8.Schlichting, C. D. & Pigliucci, M. Phenotypic Evolution: A Reaction Norm Perspective (Sinauer Associates, 1998).9.Kelly, M. W. & Hofmann, G. E. Adaptation and the physiology of ocean acidification. Funct. Ecol. 27, 980–990 (2013).Article 

    Google Scholar 
    10.Pespeni, M. H. et al. Evolutionary change during experimental ocean acidification. Proc. Natl Acad. Sci. USA 110, 6937–6942 (2013).CAS 
    Article 

    Google Scholar 
    11.Thor, P. & Dupont, S. Transgenerational effects alleviate severe fecundity loss during ocean acidification in a ubiquitous planktonic copepod. Glob. Change Biol. 21, 2261–2271 (2015).Article 

    Google Scholar 
    12.Donelson, J. M., Salinas, S., Munday, P. L. & Shama, L. N. S. Transgenerational plasticity and climate change experiments: where do we go from here? Glob. Change Biol. 24, 13–34 (2018).Article 

    Google Scholar 
    13.Chevin, L. M., Lande, R. & Mace, G. M. Adaptation, plasticity, and extinction in a changing environment: towards a predictive theory. PLoS Biol. 8, e1000357 (2010).Article 
    CAS 

    Google Scholar 
    14.Angilletta, M. J. Thermal Adaptation: A Theoretical and Empirical Synthesis (Oxford University Press, 2009).15.Byrne, M. in Oceanography and Marine Biology: An Annual Review Vol. 49 (eds Gibson, R. N. et al.) Ch. 1 (CRC Press, 2011).16.Whiteley, N. M. Physiological and ecological responses of crustaceans to ocean acidification. Mar. Ecol. Prog. Ser. 430, 257–271 (2011).CAS 
    Article 

    Google Scholar 
    17.Cripps, G., Lindeque, P. & Flynn, K. J. Have we been underestimating the effects of ocean acidification in zooplankton? Glob. Change Biol. 20, 3377–3385 (2014).Article 

    Google Scholar 
    18.Baumann, H. Experimental assessments of marine species sensitivities to ocean acidification and co-stressors: how far have we come? Can. J. Zool. 97, 399–408 (2019).Article 

    Google Scholar 
    19.Gibbin, E. M. et al. Can multi-generational exposure to ocean warming and acidification lead to the adaptation of life history and physiology in a marine metazoan? J. Exp. Biol. 220, 551–563 (2017).
    Google Scholar 
    20.Gibbin, E. M., Massamba N’Siala, G., Chakravarti, L. J., Jarrold, M. D. & Calosi, P. The evolution of phenotypic plasticity under global change. Sci. Rep. 7, 17253 (2017).Article 
    CAS 

    Google Scholar 
    21.Gonzalez, A., Ophelie, R., Ferriere, R. & Hochberg, M. E. Evolutionary rescue: an emerging focus at the intersection between ecology and evolution. Philos. Trans. R. Soc. Lond. B 368, 20120404 (2012).Article 

    Google Scholar 
    22.Bell, G. & Gonzalez, A. Evolutionary rescue can prevent extinction following environmental change. Ecol. Lett. 12, 942–948 (2009).Article 

    Google Scholar 
    23.Carlson, S. M., Cunningham, C. J. & Westley, P. A. H. Evolutionary rescue in a changing world. Trends Ecol. Evol. 29, 521–530 (2014).Article 

    Google Scholar 
    24.Hardy, A. The Open Sea: The World of Plankton (Fontana Collins, 1970).25.Huys, R. & Boxshall, G. A. Copepod Evolution (The Ray Society, 1991).26.Beaugrand, G. & Reid, P. C. Long-term changes in phytoplankton, zooplankton and salmon related to climate. Glob. Change Biol. 9, 801–817 (2003).Article 

    Google Scholar 
    27.Möllmann, C., Müller-Karulis, B., Kornilovs, G. & St John, M. A. Effects of climate and overfishing on zooplankton dynamics and ecosystem structure: regime shifts, trophic cascade, and feedback loops in a simple ecosystem. ICES J. Mar. Sci. 65, 302–310 (2008).Article 

    Google Scholar 
    28.Steinberg, D. K. & Landry, M. R. Zooplankton and the ocean carbon cycle. Annu. Rev. Mar. Sci. 9, 413–444 (2017).Article 

    Google Scholar 
    29.Mauchline, J. (ed.) The Biology of Calanoid Copepods (Academic Press, 1998).30.Turner, J. T. The Feeding Ecology of Some Zooplankters That Are Important Prey Items of Larval Fish. NOAA NMFS Technical Report (1984).31.Rice, E., Dam, H. G. & Stewart, G. Impact of climate change on estuarine zooplankton: surface water warming in Long Island Sound is associated with changes in copepod size and community structure. Estuaries Coast 38, 13–23 (2015).Article 

    Google Scholar 
    32.Gobler, C. J. & Baumann, H. Hypoxia and acidification in marine ecosystems: coupled dynamics and effects on ocean life. Biol. Lett. 12, 20150976 (2016).Article 
    CAS 

    Google Scholar 
    33.Côté, I. M., Darling, E. S. & Brown, C. J. Interactions among ecosystem stressors and their importance in conservation. Proc. R. Soc. Lond. B 283, 20152592 (2016).
    Google Scholar 
    34.Burt, A. Perspective: the evolution of fitness. Evolution 49, 1–8 (1995).
    Google Scholar 
    35.Hendry, A. P. & Gonzalez, A. Whither adaptation? Biol. Philos. 23, 673–699 (2008).Article 

    Google Scholar 
    36.Arnold, S. J., Pfrender, M. E. & Jones, A. G. The adaptive landscape as a conceptual bridge between micro- and macroevolution. Genetica 112–113, 9–32 (2001).Article 

    Google Scholar 
    37.Caswell, H. Matrix Population Models: Construction, Analysis, and Interpretation (Sinauer Associates, 2001).38.Sasaki, M. C. & Dam, H. G. Integrating patterns of thermal tolerance and phenotypic plasticity with population genetics to improve understanding of vulnerability to warming in a widespread copepod. Glob. Change Biol. 25, 4147–4164 (2019).Article 

    Google Scholar 
    39.Luikart, G., England, P. R., Tallmon, D., Jordan, S. & Taberlet, P. The power and promise of population genomics: from genotyping to genome typing. Nat. Rev. Genet. 4, 981–994 (2003).CAS 
    Article 

    Google Scholar 
    40.Black, W. C. IV, Baer, C. F., Antolin, M. F. & DuTeau, N. M. Population genomics: genome-wide sampling of insect populations. Annu. Rev. Entomol. 46, 441–469 (2001).CAS 
    Article 

    Google Scholar 
    41.Brennan, R. et al. Loss and recovery of transcriptional plasticity after long-term adaptation to global change conditions in a marine copepod. Preprint at bioRxiv https://doi.org/10.1101/2020.01.29.925396 (2020).42.Kingsolver, J. G. & Pfennig, D. W. Patterns and power of phenotypic selection in nature. Bioscience 57, 561–572 (2007).Article 

    Google Scholar 
    43.Crespi, B. J. & Bookstein, F. L. A path-analytic model for the measurement of selection on morphology. Evolution 43, 18–28 (1989).Article 

    Google Scholar 
    44.Pigliucci, M. & Kaplan, J. Making Sense of Evolution (Univ. Chicago Press, 2006); https://doi.org/10.7208/chicago/9780226668352.001.000145.Bush, A. et al. Incorporating evolutionary adaptation in species distribution modelling reduces projected vulnerability to climate change. Ecol. Lett. 19, 1468–1478 (2016).Article 

    Google Scholar 
    46.Riebesell, U. & Gattuso, J. Lessons learned from ocean acidification research. Nat. Clim. Change 5, 2014–2016 (2015).Article 
    CAS 

    Google Scholar 
    47.Langer, J. A. F., Meunier, C. L., Ecker, U. & Horn, H. G. Acclimation and adaptation of the coastal calanoid copepod Acartia tonsa to ocean acidification: a long-term laboratory investigation. Mar. Ecol. Prog. Ser. 619, 35–51 (2019).CAS 
    Article 

    Google Scholar 
    48.De Wit, P., Dupont, S. & Thor, P. Selection on oxidative phosphorylation and ribosomal structure as a multigenerational response to ocean acidification in the common copepod Pseudocalanus acuspes. Evol. Appl. 9, 1112–1123 (2016).Article 
    CAS 

    Google Scholar 
    49.Chakravarti, L. J. et al. Can trans-generational experiments be used to enhance species resilience to ocean warming and acidification? Evol. Appl. 9, 1133–1146 (2016).CAS 
    Article 

    Google Scholar 
    50.Carrier-Belleau, C., Drolet, D., McKindsey, C. W. & Archambault, P. Environmental stressors, complex interactions and marine benthic communities’ responses. Sci. Rep. 11, 4194 (2021).CAS 
    Article 

    Google Scholar 
    51.Dam, H. G. & Baumann, H. in Climate Change Impacts on Fisheries and Aquaculture: A Global Analysis (eds Phillips, B. F. and Pérez-Ramírez, M.) 851–874 (Wiley, 2017).52.Bell, G. Evolutionary rescue and the limits of adaptation. Philos. Trans. R. Soc. Lond. B 368, 20120080 (2013).Article 

    Google Scholar 
    53.Falconer, D. S. Introduction to Quantitative Genetics (Longman Scientific and Technical, 1989).54.Angilletta, M. J. Jr Estimating and comparing thermal performance curves. J. Therm. Biol. 31, 541–545 (2006).Article 

    Google Scholar 
    55.Feinberg, L. R. & Dam, H. G. Effects of diet on dimensions, density and sinking rates of fecal pellets of the copepod Acartia tonsa. Mar. Ecol. Prog. Ser. 175, 87–96 (1998).Article 

    Google Scholar 
    56.Pierrot, D., Lewis, E. & Wallace, D. W. R. MS Excel Program Developed for CO2 System Calculations. ORNL/CDIAC-105a. (Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, 2006); https://doi.org/10.3334/CDIAC/otg.CO2SYS_XLS_CDIAC105a57.Lueker, T. J., Dickson, A. G. & Keeling, C. D. Ocean (p_{{mathrm{CO}}_2}) calculated from dissolved inorganic carbon, alkalinity, and equations for K1 and K2: validation based on laboratory measurements of CO2 in gas and seawater at equilibrium. Mar. Chem. 70, 105–119 (2000).58.Dickson, A. G. Standard potential of the reaction: AgCl(s) + 12H2 (g) = Ag(s) + HCl (aq), and the standard acidity constant of the ion HSO4– in synthetic sea water from 273.15 to 318.15 K. J. Chem. Thermodyn. 22, 113–127 (1990).CAS 
    Article 

    Google Scholar 
    59.Uppström, L. R. The boron/chlorinity ratio of deep-sea water from the Pacific Ocean. Deep Sea Res. Oceanogr. Abstr. 21, 161–162 (1974).Article 

    Google Scholar 
    60.Murray, C. S. & Baumann, H. You better repeat it: complex CO2× temperature effects in Atlantic silverside offspring revealed by serial experimentation. Diversity 10, 69 (2018).CAS 
    Article 

    Google Scholar 
    61.Schank, J. C. & Koehnle, T. J. Pseudoreplication is a Pseudoproblem. J. Comp. Psychol. 123, 421–433 (2009).Article 

    Google Scholar 
    62.Oksanen, L. Logic of experiments in ecology: is pseudoreplication a pseudoissue? Oikos 94, 27–38 (2001).Article 

    Google Scholar 
    63.Therneau, T. A Package for Survival Analysis in R. R package 3.2-11 (2021); https://CRAN.R-project.org/package=survival64.Lande, R. & Arnold, S. J. The measurement of selection on correlated characters. Evolution 37, 1210–1226 (1983).Article 

    Google Scholar 
    65.Rosseel, Y. lvaan: an R package for structural equation modeling. J. Stat. Softw. https://doi.org/10.18637/jss.v048.i02 (2012).66.Epskamp, S., Stuber, S., Nak, J., Veenman, M. & Jorgensen, T. D. semPlot: Path Diagrams and Visual Analysis of Various SEM Packages’ Output. (2019); https://CRAN.R-project.org/package=semPlot67.Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).CAS 
    Article 

    Google Scholar 
    68.Jørgensen, T. S. et al. The genome and mRNA transcriptome of the cosmopolitan calanoid copepod Acartia tonsa Dana improve the understanding of copepod genome size evolution. Genome Biol. Evol. 11, 1440–1450 (2019).Article 
    CAS 

    Google Scholar 
    69.Li, H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. Preprint at https://arxiv.org/abs/1303.3997 (2013).70.Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).Article 
    CAS 

    Google Scholar 
    71.Kofler, R. et al. Popoolation: a toolbox for population genetic analysis of next generation sequencing data from pooled individuals. PLoS One 6, e15925 (2011).CAS 
    Article 

    Google Scholar 
    72.R Core Team. R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, 2020); https://www.R-project.org/73.Wood, S. N. Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. J. R. Stat. Soc. Ser. B 73, 3–36 (2011).Article 

    Google Scholar 
    74.Simpson, G. L. Modelling palaeoecological time series using generalised additive models. Front. Ecol. Evol. 6, 149 (2018).Article 

    Google Scholar 
    75.Dam, H. G. et al. Data and code repository for ‘Rapid, but limited, zooplankton adaptation to simultaneous warming and acidification’. Zenodo https://doi.org/10.5281/zenodo.5115103 (2021). More

  • in

    Causes of admission, length of stay and outcomes for common kestrels in rehabilitation centres in the Czech Republic

    1.McClure, C. J. W. et al. State of the world’s raptors: Distributions, threats, and conservation recommendations. Biol. Conserv. 227, 390–402 (2018).Article 

    Google Scholar 
    2.Bernardino, J. et al. Bird collisions with power lines: State of the art and priority areas for research. Biol. Conserv. 222, 1–13 (2018).Article 

    Google Scholar 
    3.Hager, S. B. Human-related threats to urban raptors. J. Raptor Res. 43, 210–226 (2009).Article 

    Google Scholar 
    4.Molina-López, R. A., Casal, J. & Darwich, L. Causes of morbidity in wild raptor populations admitted at a wildlife rehabilitation centre in Spain from 1995–2007: A long term retrospective study. PLoS ONE 6, e24603. https://doi.org/10.1371/journal.pone.0024603 (2011).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    5.Rodríguez, B., Rodríguez, A., Siverio, F. & Siverio, M. Causes of raptor admissions to a wildlife rehabilitation centre in Tenerife (Canary Islands). J. Raptor Res. 44, 30–39 (2010).Article 

    Google Scholar 
    6.Komnenou, A. T., Georgopoulou, I., Savvas, I. & Dessiris, A. (2005) A retrospective study of presentation, treatment, and outcome of fre-ranging raptors in Greece. J. Zoo. Wildl. Med. 36, 222–228 (2005).PubMed 
    Article 

    Google Scholar 
    7.Harris, M. C. § Sleeman, J. M. Morbidity and mortality of Bald Eagles (Haliaeetus leucocephalus) and Peregrine Falcons (Falco peregrinus) admitted to the wildlife center of Virginia, 1993–2003. J.Zoo Wildl. Med. 38, 62–66 (2007).8.IUCN Red List. 2020. Common kestrel [online]. [vid. 31st 11. 2020]. Available from: https://www.iucnredlist.org/species/22696362/935564299.Smallwood, J. A. et al. Why are American kestrel (Falco sparverius) populations declining in North America? Evidence from nest-box programs. J. Raptor Res. 43, 274–282 (2009).Article 

    Google Scholar 
    10.Wendell, M. D., Sleeman, J. M. & Kratz, G. Retrospective study of morbidity and mortality of raptors admitted to Colorado State University Veterinary Teaching Hospital during1995 to 1998. J. Wildl. Dis. 38, 101–106 (2002).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    11.Costantini, D., Dell Omo, G., La Fata, I. & Casagrande, S. Reproductive performance of Eurasian Kestrel Falco tinnunculus in an agricultural landscape with a mosaic of land uses. Ibis 156, 768–776 (2014).12.Buck, A., Carrillo-Hidalgo, J., Camarero, P. R. & Mateo, R. Organochlorine pesticides and polychlorinated biphenyls in common kestrel eggs from the Canary Islands: Spatio temporal variations and effects on egg shell and reproduction. Chemosphere 261, 127722; https://doi.org/10.1016/j.chemosphere.2020.127722 (2020).13.Wienburg, C. L. & Shore, R. F. Factors influencing liver PCB concentrations in sparrowhawks (Accipiter nisus), kestrels (Falco tinnunculus) and herons (Ardea cinerea) in Britain. Environ. Pollut. 132, 41–50 (2004).CAS 
    PubMed 
    Article 

    Google Scholar 
    14.Pain, D. J. & Amiardtriquet, C. Lead poisoning of raptors in France and elsewhere. Ecotoxicol. Environ. Saf. 25, 183–192 (1993).CAS 
    PubMed 
    Article 

    Google Scholar 
    15.Newton, I., Wyllie, I. & Dale, L. Trends in the numbers and mortality patterns of sparrowhawks (Accipiter nisus) and kestrels (Falco tinnunculus) in Britain, as revealed by carcass analyses. J. Zool. 248, 139–147 (1999).Article 

    Google Scholar 
    16.Burfield, I. J. The conservation status and trends of raptors and owls in Europe. Ambio 37, 401–407 (2008).PubMed 
    Article 

    Google Scholar 
    17.González, L. M. et al. Causes and spatio-temporal variations of non-natural mortality in the vulnerable Spanish imperial eagle Aquila Adalbert during a recovery period. Oryx 41, 495–502 (2007).Article 

    Google Scholar 
    18.Sumasgutner, P., Schulze, C. H., Krenn, H. W. & Gamauf, A. Conservation related conflicts in nest-site selection of the Eurasian kestrel (Falco tinnunculus) and the distribution of its avian prey. Landscape Urban. Plan. 127, 94–103 (2014).Article 

    Google Scholar 
    19.Sumasgutner, P., Adrion, M. & Gamauf, A. Carotenoid coloration and health status of urban Eurasian kestrels (Falco tinnunculus). PLoS ONE 13, e0191956. https://doi.org/10.1371/journal.pone.0191956 (2018).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    20.Rejt, L., Rutkowvsi, R. & Gryczynska-Siemiatkowska, A. Genetic variability of urban kestrels in Warsaw – preliminary data. Zool. Pol. 49, 199–209 (2004).
    Google Scholar 
    21.Riddle, G. S.The kestrel in Ayrshire 1970–1978. The Journal of the Scottish Ornithologists´ Club 10, 200–216 (1979).22.Forero, M. G., Tella, J. L., Donázar, J. A. & Hiraldo, F. Canister specific competition and nest site availability explain the decrease of lesser kestrel Falcon populations?. Biol. Conserv. 78, 289–293 (1996).Article 

    Google Scholar 
    23.Medica, D. L., Clauser, R. & Bildstein, K. Prevalence of West Nile Virus antibodies in a breeding population of American kestrels (Falco sparverius) in Pennsylvania. J. Wildl. Dis. 43, 538–541 (2007).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    24.Griffith, J. E., Dhand, N. K., Krockenberger, M. B. & Higgins, D. P. A retrospective study of admission trends of koalas to a rehabilitation facility over 30 years. J. Wildl. Dis. 49, 18–28 (2013).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    25.Long, R. B., Krumlauff, K. & Young, A. M. Characterizing trends in human-wildlife conflicts in the American Midwest using wildlife rehabilitation records. PLoS ONE 15, e0238805. https://doi.org/10.1371/journal.pone.0238805 (2020).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    26.Lukesova, G., Voslarova, E., Vecerek, V. & Vucinic, M. Trends in intake and outcomes for European hedgehog (Erinaceus europaeus) in the Czech rescue centres. PLoS One 16, e0248422; https://doi.org/10.1371/journal.pone.0248422 (2021).27.Crespo Martínez, J., Izquierdo Rosique, A. & Surroca Royo, M. Causes of admission and final dispositions of hedgehogs admitted to three Wildlife Rehabilitation Centres in eastern Spain. Hystrix 25, 107–110 (2014).28.Kelly, A. & Bland, M. Admissions, diagnoses, and outcomes for Eurasian sparrowhawks (Accipiter nisus) brought to a wildlife rehabilitation centre in England. J. Raptor. Res. 40, 231–235 (2006).Article 

    Google Scholar 
    29.Kübler, S., Kupko, S. & Zeller, U. The kestrel (Falco tinnunculus L.) in Berlin: Investigation of breeding biology and feeding ecology. J. Ornithol. 146, 271–278 (2005).Article 

    Google Scholar 
    30.Carrillo, J. & González-Dávila, E. Impact of weather on breeding success of the Eurasian kestrel Falco tinnunculus in a semi-arid island habitat. Ardea 98, 51–58 (2010).Article 

    Google Scholar 
    31.Carrillo, J. & Aparicio, J. M. Nest defense behavior of the Eurasian kestrel (Falco tinnunculus) against human predators. Ethology 107, 865–875 (2001).Article 

    Google Scholar 
    32.Strasser, E. H. & Heath, J. S. Reproductive failure of a human – tolerant species, the American kestrel, is associated with stress and human disturbance. J. Appl. Ecol. 50, 912–919 (2013).Article 

    Google Scholar 
    33.Baudains, T. P. & Lloyd, P. Habituation and habitat changes can moderate the impacts of human disturbance on shorebird breeding performance. Anim. Conserv. 1, 400–407 (2007).Article 

    Google Scholar 
    34.French, S. S., González-Suárez, M., Young, J. K., Durham, S. & Gerber, L. R. Human disturbance influences reproductive success and growth rate in California Sea Lions (Zalophus californianus). PLoS ONE 6, e17686. https://doi.org/10.1371/journal.pone.0017686 (2011).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    35.Halfwerk, W., Holleman, L. J. M., Lessells, C., Kate, M. & Slabbekoorn, H. Negative impact of traffic noise on avian reproductive success: Traffic noise and avian reproductive success. J. Appl. Ecol. 48, 210–219 (2011).Article 

    Google Scholar 
    36.Ponce, C., Alonso, J. C., Argandoña, G., García Fernández, A. & Carrasco, M. Carcass removal by scavengers and search accuracy affect bird mortality estimates at power lines: Bias sources affecting power-line bird mortality estimates. Anim. Conserv. 13, 603–612 (2010).Article 

    Google Scholar 
    37.Lasch, U., Zerbe, S. & Lenk, M. Electrocution of raptors at power lines in Central Kazakhstan. Waldokologie Online 9, 95–100 (2010).
    Google Scholar 
    38.Rubolini, D., Bassi, E., Bogliani, G., Galeotti, P. & Garavaglia, R. Eagle Owl Bubo bubo and power line interactions in the Italian Alps. Bird Conserv. Int. 11, 19–324 (2001).Article 

    Google Scholar 
    39.López-López, P., Ferrer, M., Madero, A., Casado, E. & McGrady, M. Solving man-induced large-scale conservation problems: the Spanish Imperial Eagle and power lines. PLoS ONE 6, e17196. https://doi.org/10.1371/journal.pone.0017196 (2011).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    40.Bevanger, K. Biological and conservation aspects of bird mortality caused by electricity power lines: A review. Biol. Conserv. 86, 67–76 (1998).Article 

    Google Scholar 
    41.Janss, G. F. E. Avian mortality from power lines: A morphological approach of a species-specific mortality. Biol. Conserv. 95, 353–359 (2000).Article 

    Google Scholar 
    42.Eccleston, D.T. & Harness, R. E. Raptor electrocutions and power line collisions in Birds of Prey (ed. Eccleston, D.T. & Harness, R. E) 273–302 (Sarasola J, Grande J &Negro J, 2018).43.Bevanger, K. (2008) Bird interactions with utility structures: Collision and electrocution, causes and mitigating measures. Ibis 136, 412–425 (2008).Article 

    Google Scholar 
    44.Guil, F. et al. Minimising mortality in endangered raptors due to power lines: The importance of spatial aggregation to optimize the application of mitigation measures. PLoS ONE 6, e28212. https://doi.org/10.1371/journal.pone.0028212 (2011).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    45.Sergio, F., Marchesi, L., Pedrini, P., Ferrer, M. & Penteriani, V. Electrocution alters the distribution and density of a top predator, the eagle owl Bubo bubo: Effects of electrocution on eagle owls. J. Appl. Ecol. 41, 836–845 (2004).Article 

    Google Scholar 
    46.Mañosa, S. Strategies to identify dangerous electricity pylons for birds. Biodivers. Conserv. 10, 1997–2012 (2001).Article 

    Google Scholar 
    47.Guyonne, F. E. & Ferrer, M. Mitigation of raptor electrocution on steel power poles. Wildl. Society Bulletin 27, 263–273 (1999).
    Google Scholar 
    48.Zoubi, M. Y. A., Hamidan, N. A., Baker, M. A. A. & Amr, Z. Causes of raptor admissions to rehabilitation in Jordan. J. Raptor Res. 54, 273–278 (2020).Article 

    Google Scholar 
    49.Montesdeoca, N., Calabuig, P., Corbera, J. A., Rocha, J. & Orós, J. Final outcome of raptors admitted to the Tafira Wildlife Rehabilitation Centre, Gran Canaria Island, Spain (2003–2013). Anim. Biodivers. Conserv. 40, 211–220 (2017).Article 

    Google Scholar 
    50.Cooper, J. E. Raptor care and rehabilitation: precedents, progress and potential. J. Raptor Res. 21, 21–26 (1987).
    Google Scholar 
    51.Lam, S. W., Leenen, L. P. H., van Solinge, W. W., Hietbrink, F. & Huisman, A. Evaluation of hematological parameters on admission for the prediction of 7-day in-hospital mortality in a large trauma cohort. Clin. Chem. Lab. Med. 49, 493–499 (2011).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    52.Sara, R. & Craig, G. A. A retrospective study of mortality and rehabilitation of raptors in the southern United States. J. Raptor Res. 38, 77–81 (2004).
    Google Scholar 
    53.Goldberg, H. K. Hearing impairment: a family crisis. Soc. Work Health Care 5, 33–40 (1979).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    54.Molina-López, R. A., Mañosa, S., Torres-Riera, A., Pomarol, M. & Darwich, L. Morbidity, outcomes and cost-benefit analysis of wildlife rehabilitation in Catalonia (Spain). PLoS ONE 12, e0181331. https://doi.org/10.1371/journal.pone.0181331 (2017).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    55.Molony, S.E., Baker, P. J., Garland, L., Cuthill, I. C. & Harris, S. 2007. Factors that can be used to predict release rates for wildlife casualties. Anim. Welfare 16, 361–367 (2007).56.Kirkwood, J. & Best, R. Treatment and rehabilitation of wildlife casualties: legal and ethical aspects. Practice 20, 214–216 (1998).Article 

    Google Scholar 
    57.Naldo, J. L. & Samour, J. H. Causes of morbidity and mortality in falcons in Saudi Arabia. J. Avian Med. Surg. 18, 229–241 (2004).Article 

    Google Scholar 
    58.Pain, D. J., Mateo, R. § Green, R. E. Effects of lead from ammunition on birds and other wildlife: A review and update. Ambio 48, 935–953 (2019).59.Thompson, L. J., Hoffman, B. & Brown, M. Causes of admissions to a raptor rehabilitation centre in KwaZulu-Natal South Africa. Afr. Zool. 48, 359–366 (2013).Article 

    Google Scholar 
    60.Tintó, A., Real, J. & Mañosa, S. Predicting and correcting electrocution of birds in Mediterranean areas. J. Wildl. Manage. 74, 1852–1862 (2010).Article 

    Google Scholar 
    61.Kemper, M. K., Court, G. S. & Beck, J. A. Estimating raptor electrocution mortality on distribution power lines in Alberta Canada. J. Wildl. Manage. 77, 1342–1352 (2013).Article 

    Google Scholar 
    62.Csermely, D. Duration of the rehabilitation period and familiarity with the prey affect the predatory behavior of captive wild kestrels (Falco tinnunculus). B. Zool. 60, 211–214 (1993).Article 

    Google Scholar 
    63.Fischer, D., Hampel, M. R. & Lierz, M. Monitoring of rehabilitated and evaluated grapevine medium Telemetry as success control. Tierarztl. Prax. K. H. 42, 29–35 (2014).CAS 
    Article 

    Google Scholar 
    64.Republic, C. Act on the protection of animals against cruelty. Collection of Law. 50, 1284–1290 (1992).
    Google Scholar  More

  • in

    High aboveground carbon stock of African tropical montane forests

    Department of Environment and Geography, University of York, York, UKAida Cuni-Sanchez, Philip J. Platts, Rob Marchant & Andrew MarshallDepartment of International Environmental and Development Studies (NORAGRIC), Norwegian University of Life Sciences, Ås, NorwayAida Cuni-SanchezDepartment of Natural Sciences, Manchester Metropolitan University, Manchester, UKMartin J. P. SullivanSchool of Geography, University of Leeds, Leeds, UKMartin J. P. Sullivan, Simon L. Lewis, Serge K. Begne, Amy C. Bennett, Martin Gilpin, Jon Lovett & Oliver L. PhillipsLeverhulme Centre for Anthropocene Biodiversity, University of York, York, UKPhilip J. PlattsClimate Change Specialist Group, Species Survival Commission, International Union for Conservation of Nature, Gland, SwitzerlandPhilip J. PlattsDepartment of Geography, University College London, London, UKSimon L. LewisBiology Department, Université Officielle de Bukavu, Bukavu, Democratic Republic of the CongoGérard Imani & Christian AmaniService of Wood Biology, Royal Museum for Central Africa, Tervuren, BelgiumWannes Hubau, Hans Beeckman & John T. MukendiDepartment of Environment, Laboratory of Wood Technology (Woodlab), Ghent University, Ghent, BelgiumWannes HubauUniversity of Jos, Jos, NigeriaIveren AbiemNigerian Montane Forest Project, Yelwa Village, NigeriaIveren Abiem & Hazel ChapmanDepartment of Geosciences and Geography, University of Helsinki, Helsinki, FinlandHari Adhikari, Janne Heiskanen & Petri PellikkaDepartment of Zoology, Faculty of Science, Charles University, Prague, Czech RepublicTomas AlbrechtInstitute of Vertebrate Biology, Czech Academy of Sciences, Brno, Czech RepublicTomas AlbrechtInstitute of Botany of the Czech Academy of Science, Třeboň, Czech RepublicJan Altman & Jiri DolezalCollege of Natural and Computational Science, Addis Ababa University, Addis Ababa, EthiopiaAbreham B. Aneseyee & Teshome SoromessaDepartment of Natural Resource Management, College of Agriculture and Natural Resource, Wolkite University, Wolkite, EthiopiaAbreham B. AneseyeeEuropean Commission, Joint Research Centre, Ispra, ItalyValerio AvitabileUK Centre for Ecology and Hydrology, Edinburgh, UKLindsay BaninUniversité du Cinquantenaire Lwiro, Département de sciences de l’environnement, Kabare, Democratic Republic of the CongoRodrigue BatumikeIsotope Bioscience Laboratory (ISOFYS), Ghent University, Ghent, BelgiumMarijn Bauters, Pascal Boeckx & Joseph OkelloPlant Systematic and Ecology Laboratory, Higher Teachers’ Training College, University of Yaoundé I, Yaoundé, CameroonSerge K. Begne, Vincent Droissart, Marie-Noel Kamdem, Murielle Simo-Droissart & Bonaventure SonkéInstitute of Tropical Forest Conservation, Mbarara University of Science and Technology, Mbarara, UgandaRobert BitarihoBiodiversity and Landscape Unit, Gembloux Agro-Bio Tech, Université de Liege, Liège, BelgiumJan BogaertInstitute for Geography, Friedrich Alexander University, Erlangen–Nuremberg, GermanyAchim Bräuning & Ulrike HiltnerDépartement de Eaux et Forêts, Institut Supérieur d’Agroforesterie et de Gestion de l’Environnement de Kahuzi-Biega (ISAGE-KB), Kalehe, Democratic Republic of the CongoFranklin BulonvuUN Environment World Conservation Monitoring Center (UNEP-WCMC), Cambridge, UKNeil D. BurgessComputational and Applied Vegetation Ecology (CAVElab), Faculty of Bioscience Engineering, Ghent University, Ghent, BelgiumKim Calders & Hans VerbeeckDepartment of Anthropology, George Washington University, Washington DC, USAColin ChapmanSchool of Life Sciences, University of KwaZulu-Natal, Pietermaritzburg, South AfricaColin ChapmanShaanxi Key Laboratory for Animal Conservation, Northwest University, Xi’an, ChinaColin ChapmanInternational Centre of Biodiversity and Primate Conservation, Dali University, Dali, ChinaColin ChapmanUniversity of Canterbury, Canterbury, New ZealandHazel ChapmanInventory and Monitoring Program, National Park Service, Fredericksburg, VA, USAJames ComiskeyUniversity of Ghent, Ghent, BelgiumThales de HaullevilleWorld Agroforestry (ICRAF), Nairobi, KenyaMathieu DecuyperLaboratory of Geo-Information Science and Remote Sensing, Wageningen University, Wageningen, The NetherlandsMathieu Decuyper & Martin HeroldGeography, Environment and Geomatics, University of Guelph, Guelph, Ontario, CanadaBen DeVriesFaculty of Science, University of South Bohemia, České Budějovice, Czech RepublicJiri DolezalAMAP Lab, Université de Montpellier, IRD, CNRS, INRAE, CIRAD, Montpellier, FranceVincent DroissartFaculté de Gestion de Ressources Naturelles Renouvelables, Université de Kisangani, Kisangani, Democratic Republic of the CongoCorneille Ewango & Janvier LisingoCollege of Development Studies, Addis Ababa University, Addis Ababa, EthiopiaSenbeta FeyeraDendrochronology Laboratory, World Agroforestry Centre (ICRAF), Nairobi, KenyaAster GebrekirstosMissouri Botanical Garden, St Louis, MO, USARoy GereauDepartment of Biology, University of Burundi, Bujumbura, BurundiDismas HakizimanaSmithsonian Institution Forest Global Earth Observatory (ForestGEO), Smithsonian Tropical Research Institute, Washington DC, USAJefferson Hall & David KenfackKunming Institute of Botany, Kunming, ChinaAlan HamiltonUniversité Libre de Bruxelles, Brussels, BelgiumOlivier HardyDivision of Vertebrate Zoology, Yale Peabody Museum of Natural History, New Haven, CT, USATerese HartInstitute for Atmospheric and Earth System Research, Faculty of Science, University of Helsinki, Helsinki, FinlandJanne HeiskanenDepartment of Plant Systematics, University of Bayreuth, Bayreuth, GermanyAndreas HempHelmholtz Center Potsdam GFZ German Research Centre for Geosciences, Section 1.4 Remote Sensing and Geoinformatics, Potsdam, GermanyMartin HeroldHelmholtz-Centre for Environmental Research (UFZ), Leipzig, GermanyUlrike HiltnerDepartment of Ecology, Faculty of Science, Charles University, Prague, Czech RepublicDavid Horak & Ondrej SedlacekInternational Gorilla Conservation Programme, Musanze, RwandaCharles Kayijamahe & Eustrate UzabahoDepartment of Natural Resources, Karatina University, Karatina, KenyaMwangi J. KinyanjuiDepartment of Ecosystem Science and Sustainability, Colorado State University, Fort Collins, CO, USAJulia KleinEco2librium LLC, Boise, ID, USAMark LungDepartment of Ecology, Université de Kisangani, Kisangani, Democratic Republic of the CongoJean-Remy MakanaEnvironmental Change Institute, School of Geography and the Environment, University of Oxford, Oxford, UKYadvinder MalhiTropical Forests and People Research Centre, University of the Sunshine Coast, Sippy Downs, Queensland, AustraliaAndrew Marshall & Alain S. K. NguteFlamingo Land Ltd, Malton, UKAndrew MarshallCollege of African Wildlife Management, Mweka, TanzaniaEmanuel H. MartinSchool of GeoSciences, University of Edinburgh, Edinburgh, UKEdward T. A. Mitchard & Charlotte WheelerDepartment of Geography and Environmental Sciences, University of Dundee, Dundee, UKAlexandra MorelIndependent Botanist, Harare, ZimbabweTom MullerDepartment of Horticultural Sciences, Faculty of Applied Sciences, Cape Peninsula University of Technology, Bellville, South AfricaFelix NchuBiology Department, University of Rwanda, Kigali, RwandaBrigitte Nyirambangutse & Etienne ZiberaDepartment of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, SwedenBrigitte Nyirambangutse & Göran WallinMountains of the Moon University, Fort Portal, UgandaJoseph OkelloNational Agricultural Research Organisation, Mbarara Zonal Agricultural Research and Development Institute, Mbarara, UgandaJoseph OkelloSchool of Biological Sciences, University of Southampton, Southampton, UKKelvin S.-H. PehConservation Science Group, Department of Zoology, University of Cambridge, Cambridge, UKKelvin S.-H. PehState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, ChinaPetri PellikkaKey Biodiversity Areas Secretariat, BirdLife International, Cambridge, UKAndrew PlumptreSchool of Life Sciences, University of Lincoln, Lincoln, UKLan QieDepartment of Biology, University of Florence, Sesto Fiorentino, ItalyFrancesco RoveroTropical Biodiversity Section, Museo delle Scienze, Trento, ItalyFrancesco RoveroTropical Plant Exploration Group (TroPEG), Mundemba, CameroonMoses N. SaingeCenter for Development Research (ZEF), University of Bonn, Bonn, GermanyChristine B. SchmittConservation and Landscape Ecology, University of Freiburg, Freiburg, GermanyChristine B. SchmittApplied Biology and Ecology Research Unit, University of Dschang, Dschang, CameroonAlain S. K. NguteForest Ecology and Forest Management Group, Wageningen University, Wageningen, The NetherlandsDouglas SheilWater and Land Resources Center, Addis Ababa University, Addis Ababa, EthiopiaDemisse ShelemeAfrican Wildlife Foundation (AWF), Biodiversity Conservation and Landscape Management Program, Simien Mountains National Park, Debark, EthiopiaTibebu Y. SimegnFaculty of Forestry, University of British Columbia, Vancouver, British Columbia, CanadaTerry SunderlandCenter for International Forestry Research (CIFOR), Bogor, IndonesiaTerry SunderlandDepartment of Forest Ecology, Faculty of Forestry and Wood Sciences, Czech University of Life Sciences, Prague, Czech RepublicMiroslav SvobodaDepartment of Plant Biology, Faculty of Sciences, University of Yaoundé I, Yaoundé, CameroonHermann TaedoumgBioversity International, Yaoundé, CameroonHermann TaedoumgUK Research and Innovation, London, UKJames TaplinDepartment of Geography, National University of Singapore, Singapore, SingaporeDavid TaylorInstitute of Forestry and Conservation, University of Toronto, Toronto, Ontario, CanadaSean C. ThomasBiodiversity Foundation for Africa, East Dean, UKJonathan TimberlakeForestry Development Authority of the Government of Liberia (FDA), Monrovia, LiberiaDarlington TuagbenSchool of Forestry and Environmental Studies, Yale University, New Haven, CT, USAPeter UmunayDepartment of Biological Sciences, Florida International University, Miami, FL, USAJason VleminckxSchool of Natural Sciences, University of Bangor, Bangor, UKSimon WillcockRothamsted Research, Harpenden, UKSimon WillcockUniversity of Liberia, Monrovia, LiberiaJohn T. WoodsA.C.-S. conceived the study and assembled the AfriMont dataset. A.C.-S. and M.J.P.S. analysed the plot data (with contributions from S.L.L.) and wrote the manuscript. P.J.P. analysed forest extents and contributed to writing. S.L.L. conceived and managed the AfriTRON forest plot recensus programme. E.T.A.M. and V.A. helped compare plot data with remote sensing carbon maps. All co-authors read and approved the manuscript. More

  • in

    Interactions between temperature and energy supply drive microbial communities in hydrothermal sediment

    The results are organized into subsections on in situ temperature profiles, geochemical gradients, and microbial community data. Geochemical data include concentration and isotopic data of dissolved electron acceptors (sulfate, dissolved inorganic carbon (DIC), δ13C-DIC), electron donors (methane, sulfide, SCOAs), and respiration end products (DIC, methane, sulfide), as well as solid-phase organic carbon pools (total organic carbon (TOC), δ13C-TOC, total nitrogen (TN), TOC:TN (C:N)). Microbial community data include bacterial and archaeal 16S rRNA gene copy numbers and bacterial and archaeal community trends. All geochemical and microbiological data are shown in Supplementary Data 1–4.Temperature profilesThe in situ temperatures and temperature gradients differ greatly among sites and hydrothermal areas (Table 1; Fig. 1a, b, 1st column). Certain locations within the SA (Cold Site) and NSA (MUC02, GC13, MUC12) are uniformly cold (~3–5 °C) and thus serve as low-temperature control sites. The fact that Cold Site has no measurable depth-dependent temperature increase suggests that this site, despite being located within the SA, only has minimal hydrothermal fluid seepage. At two sites from the NSA (GC09, GC10), temperatures increase strongly, reaching ~60 °C at 400 cm below the seafloor, with temperature gradients becoming linear below 50 cm. Everest Mound, Orange Mat, and Cathedral Hill in the SA have the steepest temperature gradients ( >165 °C m−1), reaching >80 °C within 25 cm, whereas Yellow Mat from the SA only reaches ~27 °C at 45 cm. Temperature gradients are near-linear at Everest Mound, Cathedral Hill, and Yellow Mat, and in the top ~15 cm of Orange Mat. Below ~15 cm, the temperatures at Orange Mat are nearly constant.Table 1 Overview of all sampling sites.Full size tableFig. 1: Microbial abundance and community structure in relation to temperature and geochemical gradients.Depth profiles of temperature (1st column), porewater dissolved sulfate, methane, and dissolved inorganic carbon (DIC) concentrations (2nd column), bacterial and archaeal 16S rRNA gene abundances (3rd column), bacterial (4th column) and archaeal community structure (5th column) across the 10 study sites. a Sites from the NSA. b Sites from the SA. Bacteria and Archaea community structure is shown at the phylum level, except in Proteobacteria, which are displayed at the class level (see asterisk). To improve visibility, we adjusted the depth axis range for bacterial and archaeal communities at Everest Mound, only showing the top 10 cm, where microbial 16S rRNA genes were above detection. Sulfate and methane data from the NSA, except those from MUC12, were previously published27.Full size imageConcentrations of methane, sulfate, sulfide, and DICPorewater concentration profiles of methane, sulfate and DIC are consistent with higher microbial activity and higher substrate supplies in hydrothermal seep sediments compared to cold control sites or hydrothermal non-seep sediments.Independent of temperature, sediments without fluid seepage, i.e. the hydrothermal NSA sites (GC09, GC10) and low-temperature control sites (MUC02, MUC12, GC13, Cold Site), have similar concentration profiles of sulfate, methane, and DIC (Fig. 1a, b, 2nd column). Methane remains at background concentrations (≤0.02 mM), suggesting minimal methane production. DIC concentrations increase with depth by ~1–2 mM relative to seawater values (~2 mM). Sulfate decreases but remains near seawater values (~28 mM) throughout MUC02, MUC12, and the hydrothermal GC10, but drops more clearly toward the bottom of the hydrothermal GC09 (to 26.4 mM) and the cold GC13 (to 23.8 mM). The only minor deviation is Cold Site from the SA. At this site, sulfate and DIC concentrations change more with depth (sulfate drops to 23.6 mM; DIC increases to 6.2 mM), suggesting higher microbial activity relative to all hydrothermal and control sites within the NSA. Consistent with this interpretation sulfide (HS−) concentrations increase strongly with depth at Cold Site (from 2500 to 6200 µM) but not at the NSA sites, where sulfide concentrations remain much lower (0–52 µM (Supplementary Fig. 1). Furthermore, δ13C-DIC decreases with sediment depth at Cold Site (from −3.3‰ to −10.3‰), suggesting strong input of DIC from organic carbon mineralization (Supplementary Fig. 2). By contrast, δ13C-DIC remains close to seawater values (~0‰) throughout sediments of all NSA sites (−1.7‰ to −0.2‰).Compared to all NSA sites and Cold Site, sulfate, methane, and DIC concentrations are more variable at the seep sites Yellow Mat, Cathedral Hill, Orange Mat, and Everest Mound (Fig. 1b, 2nd column). Methane concentrations at Yellow Mat, Cathedral Hill, and Orange Mat are much higher than at the non-seep sites, reaching 3.3, 5.2, and 2.8 mM, respectively (no data from Everest Mound). These high methane concentrations, which can be mainly attributed to the input of thermogenic methane from below24, almost certainly underestimate in situ concentrations due to outgassing during core retrieval. Sulfate concentrations decrease more strongly with depth than at the NSA sites or Control Site, consistent with previously observed high sulfate-reducing activity6,7 and advection of sulfate-depleted fluid from below29. Nonetheless, sulfate concentrations remain in the millimolar range throughout cores from Yellow and Orange Mat. By contrast, sulfate is below detection (≤0.1 mM) at ≥4.5 cm sediment depth at Everest Mound, and in an intermittent depth interval at Cathedral Hill (~7.5–19.5 cm), below which it increases back to ~6 mM. High, i.e. millimolar, concentrations of sulfide at Orange Mat and Cathedral Hill are consistent with high rates of in situ microbial sulfate reduction and advective input of sulfide from the thermochemical reduction of sulfate in hotter, abiotic layers below (Supplementary Fig. 1). DIC concentrations reach values of >10 mM at Orange Mat, Cathedral Hill, and Yellow Mat (no data from Everest Mound). DIC concentrations fluctuate around 20 mM DIC throughout the core from Cathedral Hill, suggesting high DIC input from deeper layers. C-isotopic values of this DIC are close to those of seawater (~−3‰), suggesting an inorganic source. By contrast, surface sedimentary DIC concentrations at Yellow Mat and Orange Mat are close to seawater values but increase with depth to ~20 and ~14 mM, respectively. Lower δ13C-DIC values in surface sediments, which decrease further to values of ~−20‰ to −24‰ at Yellow Mat and −14‰ to −18‰ at Orange Mat within the top 10–20 cm, suggest that most of this DIC comes from the microbial or thermogenic breakdown of organic matter and/or the microbial anaerobic oxidation of methane.Trends in dissolved SCOAs across locationsPorewater concentration profiles of SCOAs are consistent with higher input of reactive organic carbon substrates to hydrothermal seep sediments compared to cold control sites or hydrothermal non-seep sediments.SCOA concentrations at the cold control sites and hot NSA sites are low, showing no clear depth-related trends, consistent with absence of SCOA input from below and/or biological controlled SCOA concentrations. SCOAs are dominated by acetate (cold MUC02, MUC12, and GC13: 1–3 µM; hydrothermal GCs: 3–6 µM; Cold Site: 1–7 µM), which was detected along with formate, propionate, and lactate (Fig. 2).Fig. 2: Depth profiles of short-chain organic acid (SCOA) concentrations across locations.Note the differences in concentration ranges on the x-axis and depth ranges on the y-axis (Cathedral Hill: 0–50 cm; GC13, GC09, and GC10: 0–500 cm; all others: 0–40 cm).Full size imageBy contrast, SCOA concentrations at all hydrothermal seep sites except Orange Mat, increase with depth and temperature, consistent with a thermogenic source below the cored interval. At Yellow Mat, acetate concentrations are already elevated at the seafloor (32 µM) and increase to >100 µM at 20 cm depth. Cathedral Hill has a similar acetate concentration profile, but reaches even higher concentrations (250 µM). At the hottest site, Everest Mound, acetate concentrations increase from ~150 µM at the seafloor to steady concentrations of ~600 µM below 3 cm. Formate concentrations are also (locally) elevated at Yellow Mat (5-8 µM), Cathedral Hill (to 14 µM), and Everest Mound (94-265 µM), and propionate concentrations reach high values at Cathedral Hill (to 21.8 µM) and Everest Mound (to 125 µM). The only exception among the seep sites is Orange Mat, where acetate is only slightly elevated (10–20 µM), and formate and propionate remain at background concentrations. These concentrations suggest that either thermogenic SCOA input from below is low at this site, or SCOA concentrations are biologically controlled throughout the core. Unlike the other three SCOAs, lactate concentrations remain low at all seep sites, apart from one outlier at Cathedral Hill (34.5 cm: 17.3 µM), suggesting that lactate is not a major product of thermogenic organic matter breakdown.Trends in solid-phase organic matter poolsAll sites have similar δ13C-TOC isotopic compositions, with values ranging from −19‰ to −23‰, consistent with a predominant phytoplankton origin of sedimentary organic carbon (Supplementary Fig. 3). Yet, depth profiles of TOC and TN follow different patterns across the locations (Fig. 3). All cold control sites have similar TOC (~2–4 wt%) and TN contents (~0.3–0.6 wt%), with slight decreases in values from the seafloor downward. Compared to cold controls, GC09 and GC10 have lower TOC and TN contents (TOC: ~0.5–3 wt%; TN: ~0.0–0.3 wt%), in particular in deeper horizons with elevated temperatures. Seep sites within the SA have the widest ranges. Seep sites have higher TOC in surface sediment compared to control sites, suggesting net organic carbon assimilation and synthesis by microbial growth. TOC values are 16 wt% at the seafloor of Orange Mat and 6–7 wt% at the seafloor of the other three locations, and then decrease strongly within the top 10 cm, reaching values similar to those of cold sites or hot NSA sites below 10 cm. TN values in surface sediments of seep sites are generally higher than at control sites (~0.7–0.9 wt%), providing additional evidence of net organic matter synthesis by microbial biomass production, but then decrease steeply to values that are similar to those at hot NSA sites.Fig. 3: Carbon and nitrogen contents of bulk organic matter.Depth profiles of total organic carbon (TOC), total nitrogen (TN), and TOC:TN (C:N) across all sites.Full size imageAs a result of the stable TOC and TN trends, C:N does not change much with depth at the cold locations. Yet, while C:N ranges around 4.4–5.6 at Cold Site, values are considerably higher, around 8.1–10.1, at cold locations within the NSA. By comparison, the hot NSA sites and all seep sites except Orange Mat show increases in C:N with increasing temperature and depth. This increase in C:N is modest, from ~8 to 10 at Yellow Mat, and more pronounced at the hotter GC09 (to 15.9), GC10 (to 13.4), Cathedral Hill (to 14.6), and Everest Mound (to 15.7). Orange Mat has the highest C:N ratios (14.8–26.5), and unlike the other sites does not show an increase in C:N with depth.General trends in bacterial and archaeal 16S rRNA gene copy numbers16S rRNA gene copy numbers indicate distinct trends in bacterial and archaeal abundances that follow temperature increases with sediment depth (Fig. 1a and b, 3rd column).At the four cold locations, bacterial and archaeal gene copy numbers are relatively stable with depth (Bacteria: 108−109 g−1; Archaea: 107−108 g−1). By comparison, gene copy numbers of GC09 and GC10 are in a similar range near the seafloor but decrease strongly with depth. While Archaea are quantifiable throughout both cores to ≤103 gene copies g−1 sediment, bacterial gene copy numbers are not reliably distinguishable from extraction negative controls (~1 × 104 g−1) at temperatures >60 °C. Furthermore, unlike the cold sites, which consistently have higher bacterial gene copy numbers, there is a shift from bacterial to archaeal dominance in gene copy numbers (GC09: at ~50 cm; GC10: at ~150 cm) at both hot NSA sites.Compared to the hot GCs from the NSA, gene copies decrease over much shorter distances at sites with fluid seepage in the SA. This decrease in gene copy numbers appears related to the magnitude of the temperature increase with depth. At Yellow Mat, which only reaches moderately warm temperatures (27 °C), copy numbers of both domains decrease from ~108 g−1 at the seafloor to ~106 g−1 at the bottom of the core. While Orange Mat, Cathedral Hill, and Everest Mound have similar bacterial and archaeal gene copy numbers to Yellow Mat at the seafloor, these values drop off much more steeply with depth, matching the much steeper temperature increases. At Cathedral Hill and Everest Mound, Bacteria could not be reliably detected below 20 and 7.5 cm, respectively. As the only location, the detection limit of archaeal 16S gene sequences was reached at Everest Mound, at a depth of 9.5 cm.Relationships between microbial gene abundances and temperatureWe explored the relationship between 16S rRNA gene copy number and temperature further (Fig. 4a, b). While gene copy numbers of both domains generally decrease with increasing temperature, the shape of this temperature relationship differs between both domains. In bacteria the decrease in gene copy numbers in relation to temperature is nearly linear. By contrast, in Archaea gene copy numbers follow hump-shaped distributions, i.e. they remain stable or only decrease slightly up to a certain temperature threshold, beyond which their copy numbers decrease steeply. This apparent thermal threshold varies between sites, i.e. it is ~85 °C at Orange Mat, ~70 °C at Cathedral Hill, ~50 °C at the NSA sites, and ~20 °C at Everest Mound.Fig. 4: Gene copy trends in relation to temperature.a Bacterial and (b) archaeal 16S rRNA gene copy numbers vs. temperature. c Bacteria-to-Archaea 16S rRNA gene copy ratios vs. temperature (the exponential function and its coefficient of determination (R2), both calculated in Microsoft Excel, are shown in the graph). Symbol sizes indicate the sediment depth of each sample. Cold control sites from both locations are grouped together in the legend for easier viewing.Full size imageThe differences in relationships between bacterial and archaeal gene copy numbers and temperature are reflected in Bacteria-to-Archaea gene copy ratios (Fig. 4c). Bacterial always exceed archaeal gene copies at 45 °C. Between 10 and 45 °C, domain-level gene dominance varies with location. Despite the variability, Bacteria-to-Archaea gene copy ratios follow a highly significant, exponential relationship with temperature (R2 = 0.67, p  More