Ecology

Huxley, J. Evolution. The Modern Synthesis (Allen & Unwin, 1942).Bay, R. A. & Palumbi, S. R. Rapid acclimation ability mediated by transcriptome changes in reef-building corals. Genome Biol. Evol. 7, 1602–1612 (2015).CAS 
PubMed 
PubMed Central 

Google Scholar 
Palumbi, S. R., Barshis, D. J., Traylor-Knowles, N. & Bay, R. A. Mechanisms of reef coral resistance to future climate change. Science 344, 895–898 (2014).CAS 
PubMed 

Google Scholar 
Bang, C. et al. Metaorganisms in extreme environments: do microbes play a role in organismal adaptation? Zoology 127, 1–19 (2018).PubMed 

Google Scholar 
Fraune, S., Forêt, S. & Reitzel, A. M. Using Nematostella vectensis to study the interactions between genome, epigenome, and bacteria in a changing environment. Front. Mar. Sci. 3, 1–8 (2016).
Google Scholar 
Kolodny, O. & Schulenburg, H. Opinion piece Microbiome-mediated plasticity directs host evolution along several distinct time scales. Phil. Trans. R. Soc. B 375, 20190589 (2020).Reshef, L., Koren, O., Loya, Y., Zilber-Rosenberg, I. & Rosenberg, E. The coral probiotic hypothesis. Environ. Microbiol. 8, 2068–2073 (2006).CAS 
PubMed 

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

Google Scholar 
Totton, A. K. The British sea anemones. Nature 135, 977–978 (1935).
Google Scholar 
Hand, C. & Uhlinger, K. R. The unique, widely distributed, estuarine sea anemone, Nematostella vectensis Stephenson: a review, new facts, and questions. Estuaries 17, 501–501 (1994).
Google Scholar 
Darling, J. A., Reitzel, A. M. & Finnerty, J. R. Regional population structure of a widely introduced estuarine invertebrate: Nematostella vectensis Stephenson in New England. Mol. Ecol. 13, 2969–2981 (2004).CAS 
PubMed 

Google Scholar 
Darling, J. A. et al. Rising starlet: the starlet sea anemone, Nematostella vectensis. BioEssays 27, 211–221 (2005).CAS 
PubMed 

Google Scholar 
Hand, C. & Uhlinger, K. R. The culture, sexual and asexual reproduction, and growth of the sea anemone Nematostella vectensis. Biol. Bull. 182, 169–176 (1992).CAS 
PubMed 

Google Scholar 
Pearson, C. V. M., Rogers, A. D. & Sheader, M. The genetic structure of the rare lagoonal sea anemone, Nematostella vectensis Stephenson (Cnidaria; Anthozoa) in the United Kingdom based on RAPD analysis. Mol. Ecol. 11, 2285–2293 (2002).CAS 
PubMed 

Google Scholar 
Reitzel, A. M., Darling, J. A., Sullivan, J. C. & Finnerty, J. R. Global population genetic structure of the starlet anemone Nematostella vectensis: multiple introductions and implications for conservation policy. Biol. Invasions 10, 1197–1213 (2008).
Google Scholar 
Stefanik, D. J., Friedman, L. E. & Finnerty, J. R. Collecting, rearing, spawning and inducing regeneration of the starlet sea anemone, Nematostella vectensis. Nat. Protoc. 8, 916–923 (2013).PubMed 

Google Scholar 
Fritzenwanker, J. H. & Technau, U. Induction of gametogenesis in the basal cnidarian Nematostella vectensis (Anthozoa). Dev. Genes Evol. 212, 99–103 (2002).PubMed 

Google Scholar 
Mortzfeld, B. M. et al. Response of bacterial colonization in Nematostella vectensis to development, environment, and biogeography. Environ. Microbiol. 18, 1764–1781 (2016).PubMed 

Google Scholar 
Baldassarre, L. et al. Contribution of maternal and paternal transmission to bacterial colonization in Nematostella vectensis. Front. Microbiol. 12, 2892 (2021).
Google Scholar 
Domin, H. et al. Predicted bacterial interactions affect in vivo microbial colonization dynamics in Nematostella. Front. Microbiol. 9, 728 (2018).Guest, J. J. R. et al. Contrasting patterns of coral bleaching susceptibility in 2010 suggest an adaptive response to thermal stress. PLoS ONE 7, e33353–e33353 (2012).CAS 
PubMed 
PubMed Central 

Google Scholar 
Puisay, A., Pilon, R., Goiran, C. & Hédouin, L. Thermal resistances and acclimation potential during coral larval ontogeny in Acropora pulchra. Mar. Environ. Res. 135, 1–10 (2018).CAS 
PubMed 

Google Scholar 
Van Oppen, M. J. H., Oliver, J. K., Putnam, H. M. & Gates, R. D. Building coral reef resilience through assisted evolution. Proc. Natl Acad. Sci. USA 112, 2313 (2015).
Google Scholar 
Torda, G. et al. Rapid adaptive responses to climate change in corals. Nat. Clim. Change 7, 627–636 (2017).
Google Scholar 
Yu, Xiaopeng et al. Thermal acclimation increases heat tolerance of the scleractinian coral Acropora pruinosa,. Sci. Total Environ. 733, 139319–139319 (2020).CAS 
PubMed 

Google Scholar 
Jury, C. P. & Toonen, R. J. Adaptive responses and local stressor mitigation drive coral resilience in warmer, more acidic oceans. Proc. R. Soc. B Biol. Sci. 286, 20190614–20190614 (2019).
Google Scholar 
Sully, S., Burkepile, D. E., Donovan, M. K., Hodgson, G. & van Woesik, R. A global analysis of coral bleaching over the past two decades. Nat. Commun. 10, 5 (2019).
Google Scholar 
Thomas, L. et al. Mechanisms of thermal tolerance in reef-building corals across a fine-grained environmental mosaic: lessons from Ofu,. Am. Samoa. Front. Mar. Sci. 4, 434 (2018).
Google Scholar 
Oliver, T. A. & Palumbi, S. R. Many corals host thermally resistant symbionts in high-temperature habitat. Coral Reefs 30, 241–250 (2011).
Google Scholar 
Kenkel, C. D. & Matz, M. V. Gene expression plasticity as a mechanism of coral adaptation to a variable environment. Nat. Ecol. Evol. 1, 14 (2017).Barker, V. Exceptional thermal tolerance of coral reefs in American Samoa a review. Curr. Clim. Change Rep. 4, 427 (2018).
Google Scholar 
Bourne, D., Iida, Y., Uthicke, S. & Smith-Keune, C. Changes in coral-associated microbial communities during a bleaching event. ISME J. 2, 350–63 (2008).CAS 
PubMed 

Google Scholar 
Carrier, T. J. & Reitzel, A. M. The hologenome across environments and the implications of a host-associated microbial repertoire. Front. Microbiol. 8, 802 (2017).Koren, O. & Rosenberg, E. Bacteria associated with mucus and tissues of the coral Oculina patagonica in summer and winter. Appl. Environ. Microbiol. 72, 5254–5259 (2006).CAS 
PubMed 
PubMed Central 

Google Scholar 
Littman, R., Willis, B. L. & Bourne, D. G. Metagenomic analysis of the coral holobiont during a natural bleaching event on the Great Barrier Reef. Environ. Microbiol. Rep. 3, 651–60 (2011).CAS 
PubMed 

Google Scholar 
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, 14213–14213 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
Thurber, R. V. et al. Metagenomic analysis of stressed coral holobionts. Environ. Microbiol. 11, 2148–2163 (2009).CAS 

Google Scholar 
van Oppen, M. J. H. & Blackall, L. L. Coral microbiome dynamics, functions and design in a changing world. Nat. Rev. Microbiol. 17, 557–567 (2019).PubMed 

Google Scholar 
Moran, N. A. & Yun, Y. Experimental replacement of an obligate insect symbiont. Proc. Natl Acad. Sci. USA 112, 2093–2096 (2015).CAS 
PubMed 
PubMed Central 

Google Scholar 
Ainsworth, T. D. T. et al. The coral core microbiome identifies rare bacterial taxa as ubiquitous endosymbionts. ISME J. 9, 2261–2274 (2015).CAS 

Google Scholar 
Hester, E. R., Barott, K. L., Nulton, J., Vermeij, M. J. A. & Rohwer, F. L. Stable and sporadic symbiotic communities of coral and algal holobionts. ISME J. 10, 1157–1169 (2016).CAS 
PubMed 

Google Scholar 
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, 340 (2016).
Google Scholar 
Pollock, F. J. et al. Reduced diversity and stability of coral-associated bacterial communities and suppressed immune function precedes disease onset in corals. R. Soc. Open Sci. 6, 31312497 (2019).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 

Google Scholar 
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 

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

Google Scholar 
Bourne, D. G. Microbiological assessment of a disease outbreak on corals from Magnetic Island (Great Barrier Reef, Australia). Coral Reefs 24, 304–312 (2005).
Google Scholar 
Leach, W. B., Carrier, T. J. & Reitzel, A. M. Diel patterning in the bacterial community associated with the sea anemone Nematostella vectensis. Ecol. Evol. 9, 9935–9947 (2019).PubMed 
PubMed Central 

Google Scholar 
Pootakham, W. et al. Heat-induced shift in coral microbiome reveals several members of the Rhodobacteraceae family as indicator species for thermal stress in Porites lutea. MicrobiologyOpen 8, e935 (2019).Webster, N. Host-associated coral reef microbes respond to the cumulative pressures of ocean warming and ocean acidification. Sci. Rep. 6, 19324 (2016).Van, K. L., Ae, A., Schupp, P. & Slattery, M. The distribution of dimethylsulfoniopropionate in tropical Pacific coral reef invertebrates. Coral Reefs 25, 321–327 (2006).
Google Scholar 
Rypien, K. L., Ward, J. R. & Azam, F. Antagonistic interactions among coral-associated bacteria. Environ. Microbiol. 12, 28–39 (2010).CAS 
PubMed 

Google Scholar 
Blazejak, A., Erséus, C., Amann, R. & Dubilier, N. Coexistence of bacterial sulfide oxidizers, sulfate reducers, and spirochetes in a gutless worm (oligochaeta) from the Peru margin. Appl. Environ. Microbiol. 71, 1553–1561 (2005).CAS 
PubMed 
PubMed Central 

Google Scholar 
Dubilier, N. et al. Phylogenetic diversity of bacterial endosymbionts in the gutless marine oligochete Olavius loisae (Annelida). Mar. Ecol. Prog. Ser. 178, 271–280 (1999).
Google Scholar 
Rincón-Rosales, R., Lloret, L., Ponce, E. & Martínez-Romero, E. Erratum: Rhizobia with different symbiotic efficiencies nodulate Acaciella angustissima in Mexico, including Sinorhizobium chiapanecum sp. nov. which has common symbiotic genes with Sinorhizobium mexicanum (FEMS Microbiology Ecology (2009) 67 (103-117)). FEMS Microbiol. Ecol. 68, 255–255 (2009).
Google Scholar 
Rosenberg, E. & DeLong, E. F., Stackebrandt, E., Lory, S., Thompson, F. The Prokaryotes—Prokaryotic Biology and Symbiotic Associations. (Springer, 2013).Kimura, H., Higashide, Y. & Naganuma, T. Endosymbiotic microflora of the Vestimentiferan Tubeworm (Lamellibrachia sp.) from a Bathyal Cold Seep. Mar. Biotechnol. 5, 593–603 (2003).CAS 

Google Scholar 
Melillo, A. A., Bakshi, C. S. & Melendez, J. A. Francisella tularensis antioxidants harness reactive oxygen species to restrict macrophage signaling and cytokine production. J. Biol. Chem. 285, 27553–27560 (2010).CAS 
PubMed 
PubMed Central 

Google Scholar 
Rabadi, S. M. et al. Antioxidant defenses of Francisella tularensis modulate macrophage function and production of proinflammatory cytokines. J. Biol. Chem. 291, 5009–5021 (2016).CAS 
PubMed 

Google Scholar 
McBride, M. J. in The Prokaryotes: Other Major Lineages of Bacteria and The Archaea. Vol. 9783642389542, 643–676 (Springer-Verlag Berlin Heidelberg, 2014).Augustin, R., Fraune, S. & Bosch, T. C. G. How Hydra senses and destroys microbes. Semin. Immunol. 22, 54–58 (2010).CAS 
PubMed 

Google Scholar 
Augustin, R. et al. A secreted antibacterial neuropeptide shapes the microbiome of Hydra. Nat. Commun. 8, 698 (2017).Franzenburg, S. et al. Distinct antimicrobial peptide expression determines host species-specific bacterial associations. Proc. Natl Acad. Sci. USA 110, E3730–E3738 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
Fraune, S., Abe, Y. & Bosch, T. C. G. G. Disturbing epithelial homeostasis in the metazoan Hydra leads to drastic changes in associated microbiota. Environ. Microbiol. 11, 2361–9 (2009).CAS 
PubMed 

Google Scholar 
Brennan, J. J. et al. Sea anemone model has a single Toll-like receptor that can function in pathogen detection, NF-κB signal transduction, and development. Proc. Natl Acad. Sci. USA 114, E10122–E10131 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
Sullivan, J. C. et al. Two alleles of NF-κB in the sea anemone Nematostella vectensis are widely dispersed in nature and encode proteins with distinct activities. PLoS ONE 4, e7311 (2009).Wolenski, F. S. et al. Characterization of the core elements of the NF-B signaling pathway of the sea anemone Nematostella vectensis. Mol. Cell. Biol. 31, 1076–1087 (2011).CAS 
PubMed 

Google Scholar 
Gáliková, M., Klepsatel, P., Senti, G. & Flatt, T. Steroid hormone regulation of C. elegans and Drosophila aging and life history. Exp. Gerontol. 46, 141–147 (2011).PubMed 

Google Scholar 
Taubenheim, J., Kortmann, C. & Fraune, S. Function and evolution of nuclear receptors in environmental-dependent postembryonic development. Front. Cell Dev. Biol. 9, 653792 (2021).PubMed 
PubMed Central 

Google Scholar 
Becker, P. B. & Workman, J. L. Nucleosome remodeling and epigenetics. Cold Spring Harb. Perspect. Biol. 5, a017905–a017905 (2013).PubMed 
PubMed Central 

Google Scholar 
Barno, A. R., Villela, H. D. M., Aranda, M., Thomas, T. & Peixoto, R. S. Host under epigenetic control: a novel perspective on the interaction between microorganisms and corals. BioEssays 43, 2100068.Reitzel, A. M. et al. Physiological and developmental responses to temperature by the sea anemone Nematostella vectensis. Mar. Ecol. Prog. Ser. 484, 115–130 (2013).
Google Scholar 
Chua, C. M., Leggat, W., Moya, A. & Baird, A. H. Temperature affects the early life history stages of corals more than near future ocean acidification. Mar. Ecol. Prog. Ser. 475, 85–92 (2013).
Google Scholar 
Ericson, J. A. et al. Combined effects of two ocean change stressors, warming and acidification, on fertilization and early development of the Antarctic echinoid Sterechinus neumayeri. Polar Biol. 35, 1027–1034 (2012).
Google Scholar 
Sheppard Brennand, H., Soars, N., Dworjanyn, S. A., Davis, A. R. & Byrne, M. Impact of ocean warming and ocean acidification on larval development and calcification in the sea urchin Tripneustes gratilla. PLoS ONE 5, e11372 (2010).Bernal, M. A. et al. Phenotypic and molecular consequences of stepwise temperature increase across generations in a coral reef fish. Mol. Ecol. 27, 4516–4528 (2018).CAS 
PubMed 

Google Scholar 
Clark, M. S. et al. Molecular mechanisms underpinning transgenerational plasticity in the green sea urchin Psammechinus miliaris. Sci. Rep. 9, 1–12 (2019).
Google Scholar 
Donelson, J. et al. Rapid transgenerational acclimation of a tropical reef fish to climate change. Nat. Clim. Change 2, 30–32 (2012).
Google Scholar 
Miller, G. M., Watson, S. A., Donelson, J. M., McCormick, M. I. & Munday, P. L. Parental environment mediates impacts of increased carbon dioxide on a coral reef fish. Nat. Clim. Change 2, 858–861 (2012).CAS 

Google Scholar 
Munday, P. L. Transgenerational acclimation of fishes to climate change and ocean acidification. F1000Prime Rep. 6, 99–99 (2014).PubMed 
PubMed Central 

Google Scholar 
Ryu, T. et al. An epigenetic signature for within-generational plasticity of a reef fish to ocean warming. Front. Mar. Sci. 7, 284 (2020).Veilleux, H. et al. Molecular processes of transgenerational acclimation to a warming ocean. Nat. Clim. Change 5, 1074–1078 (2015).CAS 

Google Scholar 
Zhao, C. et al. Transgenerational effects of ocean warming on the sea urchin Strongylocentrotus intermedius. Ecotoxicol. Environ. Saf. 151, 212–219 (2018).CAS 
PubMed 

Google Scholar 
Eirin-Lopez, J. M. & Putnam, H. M. Marine Environmental Epigenetics. Annu. Rev. Mar. Sci. 11, 335–368 (2019).
Google Scholar 
Fallet, M., Luquet, E., David, P. & Cosseau, C. Epigenetic inheritance and intergenerational effects in mollusks. Gene 729, 144166–144166 (2020).CAS 
PubMed 

Google Scholar 
Putnam, H. M. & Gates, R. D. Preconditioning in the reef-building coral Pocillopora damicornis and the potential for trans-generational acclimatization in coral larvae under future climate change conditions. J. Exp. Biol. 218, 2365–2372 (2015).PubMed 

Google Scholar 
Daxinger, L. & Whitelaw, E. Transgenerational epigenetic inheritance: more questions than answers. Genome Res. 20, 1623–1628 (2010).CAS 
PubMed 
PubMed Central 

Google Scholar 
Ptashne, M. Epigenetics: core misconcept. Proc. Natl Acad. Sci. USA 110, 7101–7103 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
Rivera, H. E., Chen, C.-Y., Gibson, M. C. & Tarrant, A. M. Plasticity in parental effects confers rapid larval thermal tolerance in the estuarine anemone Nematostella vectensis. J. Exp. Biol. 224, jeb236745 (2021).Hirose, E. & Fukuda, T. Vertical transmission of photosymbionts in the colonial ascidian Didemnum molle: The larval tunic prevents symbionts from attaching to the anterior part of larvae. Zool. Sci. 23, 669–674 (2006).
Google Scholar 
Padilla-Gamiño, J. L., Pochon, X., Bird, C., Concepcion, G. T. & Gates, R. D. From parent to gamete: vertical transmission of Symbiodinium (Dinophyceae) ITS2 sequence assemblages in the reef building coral Montipora capitata. PLoS ONE 7, e38440–e38440 (2012).PubMed 
PubMed Central 

Google Scholar 
Sharp, K. H., Eam, B., John Faulkner, D. & Haygood, M. G. Vertical transmission of diverse microbes in the tropical sponge Corticium sp. Appl. Environ. Microbiol. 73, 622–629 (2007).CAS 
PubMed 

Google Scholar 
Sipkema, D. et al. Similar sponge-associated bacteria can be acquired via both vertical and horizontal transmission. Environ. Microbiol. 17, 3807–3821 (2015).CAS 
PubMed 

Google Scholar 
Apprill, A., Marlow, H. Q., Martindale, M. Q. & Rappé, M. S. The onset of microbial associations in the coral Pocillopora meandrina. ISME J. 3, 685–699 (2009).PubMed 

Google Scholar 
Sharp, K. H., Distel, D. & Paul, V. J. Diversity and dynamics of bacterial communities in early life stages of the Caribbean coral Porites astreoides. ISME J. 6, 790–801 (2012).CAS 
PubMed 

Google Scholar 
Lesser, M. P., Stat, M. & Gates, R. D. The endosymbiotic dinoflagellates (Symbiodinium sp.) of corals are parasites and mutualists. Coral Reefs 32, 603–611 (2013).
Google Scholar 
Ceh, J., Raina, J. B., Soo, R. M., van Keulen, M. & Bourne, D. G. Coral-bacterial communities before and after a coral mass spawning event on Ningaloo Reef. PLoS ONE 7, e36920 (2012).Ricardo, G. F., Jones, R. J., Negri, A. P. & Stocker, R. That sinking feeling: suspended sediments can prevent the ascent of coral egg bundles. Sci. Rep. 6, 21567 (2016).Leite, D. C. A. D. et al. Broadcast spawning coral Mussismilia Hispida can vertically transfer its associated bacterial core. Front. Microbiol. 8, 176–176 (2017).PubMed 
PubMed Central 

Google Scholar 
Epstein, H. E. et al. Microbiome engineering: enhancing climate resilience in corals. Front. Ecol. Environ. 17, 108 (2019).
Google Scholar 
Peixoto, R. S. et al. Beneficial microorganisms for corals (BMC) Proposed mechanisms for coral health and resilience. Front. Microbiol. 8, 341 (2017).PubMed 
PubMed Central 

Google Scholar 
Chakravarti, L. J., Beltran, V. H. & van Oppen, M. J. H. Rapid thermal adaptation in photosymbionts of reef-building corals. Glob. Change Biol. 23, 4675–4688 (2017).
Google Scholar 
Damjanovic, K., Blackall, L. L., Webster, N. S. & van Oppen, M. J. H. H. The contribution of microbial biotechnology to mitigating coral reef degradation. Microb. Biotechnol. 10, 1236–1243 (2017).PubMed 
PubMed Central 

Google Scholar 
Damjanovic, K., Van Oppen, M. J. H., Menéndez, P. & Blackall, L. L. Experimental inoculation of coral recruits with marine bacteria indicates scope for microbiome manipulation in Acropora tenuis and Platygyra daedalea. Front. Microbiol. 10, 1702 (2019).Rosado, P. M. et al. Marine probiotics: increasing coral resistance to bleaching through microbiome manipulation. ISME J. 13, 921–936 (2019).CAS 
PubMed 

Google Scholar 
Fraune, S. et al. Bacteria-bacteria interactions within the microbiota of the ancestral metazoan Hydra contribute to fungal resistance. ISME J. 9, 1543–1556 (2015).CAS 
PubMed 

Google Scholar 
Fadrosh, D. W. et al. An improved dual-indexing approach for multiplexed 16 S rRNA gene sequencing on the Illumina MiSeq platform. Microbiome 2, 6 (2014).PubMed 
PubMed Central 

Google Scholar 
Rausch, P. et al. Analysis of factors contributing to variation in the C57BL/6 J fecal microbiota across German animal facilities. Int. J. Med. Microbiol. 306, 343–355 (2016).PubMed 

Google Scholar 
Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7, 335–336 (2010).CAS 
PubMed 
PubMed Central 

Google Scholar 
Faith, J. J. et al. The long-term stability of the human gut microbiota. Science 341, 1237439–1237439 (2013).PubMed 
PubMed Central 

Google Scholar 
Segata, N. et al. Metagenomic biomarker discovery and explanation. Genome Biol. 12, R60–R60 (2011).PubMed 
PubMed Central 

Google Scholar 
Andrews, S. FastQC: A Quality Control Tool for High Throughput Sequence Data [Online]. Available online at: http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ (2010).Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).CAS 
PubMed 
PubMed Central 

Google Scholar 
Kim, D., Langmead, B. & Salzberg, S. L. HISAT: a fast spliced aligner with low memory requirements. Nat. Methods 12, 357–360 (2015).CAS 
PubMed 
PubMed Central 

Google Scholar 
Pertea, M. et al. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat. Biotechnol. 33, 290–295 (2015).CAS 
PubMed 
PubMed Central 

Google Scholar 
Shao, M. & Kingsford, C. accurate assembly of transcripts through phase-preserving graph decomposition. Nat. Biotechnol. 35, 1167–1169 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
Niknafs, Y. S., Pandian, B., Iyer, H. K., Chinnaiyan, A. M. & Iyer, M. K. TACO produces robust multisample transcriptome assemblies from RNA-seq. Nat. Methods 14, 68–70 (2016).PubMed 
PubMed Central 

Google Scholar 
Pertea, M. & Pertea, G. GFF Utilities: GffRead and GffCompare. F1000Research 9, 304–304 (2020).
Google Scholar 
Manni, M., Berkeley, M. R., Seppey, M., Simão, F. A. & Zdobnov, E. M. BUSCO update: novel and streamlined workflows along with broader and deeper phylogenetic coverage for scoring of eukaryotic, prokaryotic, and viral genomes. Mol. Biol. Evol. 38, 4647–4654 (2021).PubMed 
PubMed Central 

Google Scholar 
Liao, Y., Smyth, G. K. & Shi, W. FeatureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014).CAS 
PubMed 

Google Scholar 
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550–550 (2014).PubMed 
PubMed Central 

Google Scholar 
Law, C. W., Chen, Y., Shi, W. & Smyth, G. K. Voom: Precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol. 15, R29–R29 (2014).PubMed 
PubMed Central 

Google Scholar  More

RESEARCH HIGHLIGHT
01 July 2022

Rock doves on some Scottish islands show almost no sign of having interbred with domestic pigeons.

The relatively long, slender bill of this rock dove from the Outer Hebridean islands of Scotland are characteristic of feral pigeons’ ancestors. Credit: W. J. Smith et al./iScience

.readcube-buybox { display: none !important;}
Charles Darwin developed his theory of natural selection in part by studying a form of artificial selection: the nineteenth-century rage for pigeon breeding, which created a wealth of fantastical varieties of pigeon (Columba livia). So widespread was pigeon fancying that it seeded the world with escaped domestic birds and their feral descendants, which then hybridized with their wild ancestors, the rock doves.

Access options

/* style specs start */
style{display:none!important}.LiveAreaSection-193358632 *{align-content:stretch;align-items:stretch;align-self:auto;animation-delay:0s;animation-direction:normal;animation-duration:0s;animation-fill-mode:none;animation-iteration-count:1;animation-name:none;animation-play-state:running;animation-timing-function:ease;azimuth:center;backface-visibility:visible;background-attachment:scroll;background-blend-mode:normal;background-clip:borderBox;background-color:transparent;background-image:none;background-origin:paddingBox;background-position:0 0;background-repeat:repeat;background-size:auto auto;block-size:auto;border-block-end-color:currentcolor;border-block-end-style:none;border-block-end-width:medium;border-block-start-color:currentcolor;border-block-start-style:none;border-block-start-width:medium;border-bottom-color:currentcolor;border-bottom-left-radius:0;border-bottom-right-radius:0;border-bottom-style:none;border-bottom-width:medium;border-collapse:separate;border-image-outset:0s;border-image-repeat:stretch;border-image-slice:100%;border-image-source:none;border-image-width:1;border-inline-end-color:currentcolor;border-inline-end-style:none;border-inline-end-width:medium;border-inline-start-color:currentcolor;border-inline-start-style:none;border-inline-start-width:medium;border-left-color:currentcolor;border-left-style:none;border-left-width:medium;border-right-color:currentcolor;border-right-style:none;border-right-width:medium;border-spacing:0;border-top-color:currentcolor;border-top-left-radius:0;border-top-right-radius:0;border-top-style:none;border-top-width:medium;bottom:auto;box-decoration-break:slice;box-shadow:none;box-sizing:border-box;break-after:auto;break-before:auto;break-inside:auto;caption-side:top;caret-color:auto;clear:none;clip:auto;clip-path:none;color:initial;column-count:auto;column-fill:balance;column-gap:normal;column-rule-color:currentcolor;column-rule-style:none;column-rule-width:medium;column-span:none;column-width:auto;content:normal;counter-increment:none;counter-reset:none;cursor:auto;display:inline;empty-cells:show;filter:none;flex-basis:auto;flex-direction:row;flex-grow:0;flex-shrink:1;flex-wrap:nowrap;float:none;font-family:initial;font-feature-settings:normal;font-kerning:auto;font-language-override:normal;font-size:medium;font-size-adjust:none;font-stretch:normal;font-style:normal;font-synthesis:weight style;font-variant:normal;font-variant-alternates:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-variant-position:normal;font-weight:400;grid-auto-columns:auto;grid-auto-flow:row;grid-auto-rows:auto;grid-column-end:auto;grid-column-gap:0;grid-column-start:auto;grid-row-end:auto;grid-row-gap:0;grid-row-start:auto;grid-template-areas:none;grid-template-columns:none;grid-template-rows:none;height:auto;hyphens:manual;image-orientation:0deg;image-rendering:auto;image-resolution:1dppx;ime-mode:auto;inline-size:auto;isolation:auto;justify-content:flexStart;left:auto;letter-spacing:normal;line-break:auto;line-height:normal;list-style-image:none;list-style-position:outside;list-style-type:disc;margin-block-end:0;margin-block-start:0;margin-bottom:0;margin-inline-end:0;margin-inline-start:0;margin-left:0;margin-right:0;margin-top:0;mask-clip:borderBox;mask-composite:add;mask-image:none;mask-mode:matchSource;mask-origin:borderBox;mask-position:0 0;mask-repeat:repeat;mask-size:auto;mask-type:luminance;max-height:none;max-width:none;min-block-size:0;min-height:0;min-inline-size:0;min-width:0;mix-blend-mode:normal;object-fit:fill;object-position:50% 50%;offset-block-end:auto;offset-block-start:auto;offset-inline-end:auto;offset-inline-start:auto;opacity:1;order:0;orphans:2;outline-color:initial;outline-offset:0;outline-style:none;outline-width:medium;overflow:visible;overflow-wrap:normal;overflow-x:visible;overflow-y:visible;padding-block-end:0;padding-block-start:0;padding-bottom:0;padding-inline-end:0;padding-inline-start:0;padding-left:0;padding-right:0;padding-top:0;page-break-after:auto;page-break-before:auto;page-break-inside:auto;perspective:none;perspective-origin:50% 50%;pointer-events:auto;position:static;quotes:initial;resize:none;right:auto;ruby-align:spaceAround;ruby-merge:separate;ruby-position:over;scroll-behavior:auto;scroll-snap-coordinate:none;scroll-snap-destination:0 0;scroll-snap-points-x:none;scroll-snap-points-y:none;scroll-snap-type:none;shape-image-threshold:0;shape-margin:0;shape-outside:none;tab-size:8;table-layout:auto;text-align:initial;text-align-last:auto;text-combine-upright:none;text-decoration-color:currentcolor;text-decoration-line:none;text-decoration-style:solid;text-emphasis-color:currentcolor;text-emphasis-position:over right;text-emphasis-style:none;text-indent:0;text-justify:auto;text-orientation:mixed;text-overflow:clip;text-rendering:auto;text-shadow:none;text-transform:none;text-underline-position:auto;top:auto;touch-action:auto;transform:none;transform-box:borderBox;transform-origin:50% 50%0;transform-style:flat;transition-delay:0s;transition-duration:0s;transition-property:all;transition-timing-function:ease;vertical-align:baseline;visibility:visible;white-space:normal;widows:2;width:auto;will-change:auto;word-break:normal;word-spacing:normal;word-wrap:normal;writing-mode:horizontalTb;z-index:auto;-webkit-appearance:none;-moz-appearance:none;-ms-appearance:none;appearance:none;margin:0}.LiveAreaSection-193358632{width:100%}.LiveAreaSection-193358632 .login-option-buybox{display:block;width:100%;font-size:17px;line-height:30px;color:#222;padding-top:30px;font-family:Harding,Palatino,serif}.LiveAreaSection-193358632 .additional-access-options{display:block;font-weight:700;font-size:17px;line-height:30px;color:#222;font-family:Harding,Palatino,serif}.LiveAreaSection-193358632 .additional-login >li:not(:first-child)::before{transform:translateY(-50%);content:””;height:1rem;position:absolute;top:50%;left:0;border-left:2px solid #999}.LiveAreaSection-193358632 .additional-login >li:not(:first-child){padding-left:10px}.LiveAreaSection-193358632 .additional-login >li{display:inline-block;position:relative;vertical-align:middle;padding-right:10px}.BuyBoxSection-683559780{display:flex;flex-wrap:wrap;flex:1;flex-direction:row-reverse;margin:-30px -15px 0}.BuyBoxSection-683559780 .box-inner{width:100%;height:100%}.BuyBoxSection-683559780 .readcube-buybox{background-color:#f3f3f3;flex-shrink:1;flex-grow:1;flex-basis:255px;background-clip:content-box;padding:0 15px;margin-top:30px}.BuyBoxSection-683559780 .subscribe-buybox{background-color:#f3f3f3;flex-shrink:1;flex-grow:4;flex-basis:300px;background-clip:content-box;padding:0 15px;margin-top:30px}.BuyBoxSection-683559780 .subscribe-buybox-nature-plus{background-color:#f3f3f3;flex-shrink:1;flex-grow:4;flex-basis:100%;background-clip:content-box;padding:0 15px;margin-top:30px}.BuyBoxSection-683559780 .title-readcube{display:block;margin:0;margin-right:20%;margin-left:20%;font-size:24px;line-height:32px;color:#222;padding-top:30px;text-align:center;font-family:Harding,Palatino,serif}.BuyBoxSection-683559780 .title-buybox{display:block;margin:0;margin-right:29%;margin-left:29%;font-size:24px;line-height:32px;color:#222;padding-top:30px;text-align:center;font-family:Harding,Palatino,serif}.BuyBoxSection-683559780 .title-asia-buybox{display:block;margin:0;margin-right:5%;margin-left:5%;font-size:24px;line-height:32px;color:#222;padding-top:30px;text-align:center;font-family:Harding,Palatino,serif}.BuyBoxSection-683559780 .asia-link{color:#069;cursor:pointer;text-decoration:none;font-size:1.05em;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:1.05em6}.BuyBoxSection-683559780 .access-readcube{display:block;margin:0;margin-right:10%;margin-left:10%;font-size:14px;color:#222;padding-top:10px;text-align:center;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:20px}.BuyBoxSection-683559780 .access-asia-buybox{display:block;margin:0;margin-right:5%;margin-left:5%;font-size:14px;color:#222;padding-top:10px;text-align:center;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:20px}.BuyBoxSection-683559780 .access-buybox{display:block;margin:0;margin-right:30%;margin-left:30%;font-size:14px;color:#222;opacity:.8px;padding-top:10px;text-align:center;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:20px}.BuyBoxSection-683559780 .usps-buybox{display:block;margin:0;margin-right:30%;margin-left:30%;font-size:14px;color:#222;opacity:.8px;text-align:center;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:20px}.BuyBoxSection-683559780 .price-buybox{display:block;font-size:30px;color:#222;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;padding-top:30px;text-align:center}.BuyBoxSection-683559780 .price-from{font-size:14px;padding-right:10px;color:#222;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:20px}.BuyBoxSection-683559780 .issue-buybox{display:block;font-size:13px;text-align:center;color:#222;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:19px}.BuyBoxSection-683559780 .no-price-buybox{display:block;font-size:13px;line-height:18px;text-align:center;padding-right:10%;padding-left:10%;padding-bottom:20px;padding-top:30px;color:#222;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif}.BuyBoxSection-683559780 .vat-buybox{display:block;margin-top:5px;margin-right:20%;margin-left:20%;font-size:11px;color:#222;padding-top:10px;padding-bottom:15px;text-align:center;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:17px}.BuyBoxSection-683559780 .button-container{display:flex;padding-right:20px;padding-left:20px;justify-content:center}.BuyBoxSection-683559780 .button-container >*{flex:1px}.BuyBoxSection-683559780 .button-container >a:hover,.Button-505204839:hover,.Button-1078489254:hover,.Button-2808614501:hover{text-decoration:none}.BuyBoxSection-683559780 .readcube-button{background:#fff;margin-top:30px}.BuyBoxSection-683559780 .button-asia{background:#069;border:1px solid #069;border-radius:0;cursor:pointer;display:block;padding:9px;outline:0;text-align:center;text-decoration:none;min-width:80px;margin-top:75px}.BuyBoxSection-683559780 .button-label-asia,.ButtonLabel-3869432492,.ButtonLabel-3296148077,.ButtonLabel-1566022830{display:block;color:#fff;font-size:17px;line-height:20px;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;text-align:center;text-decoration:none;cursor:pointer}.Button-505204839,.Button-1078489254,.Button-2808614501{background:#069;border:1px solid #069;border-radius:0;cursor:pointer;display:block;padding:9px;outline:0;text-align:center;text-decoration:none;min-width:80px;max-width:320px;margin-top:10px}.Button-505204839 .readcube-label,.Button-1078489254 .readcube-label,.Button-2808614501 .readcube-label{color:#069}
/* style specs end */Subscribe to Nature+Get immediate online access to the entire Nature family of 50+ journals$29.99monthlySubscribe to JournalGet full journal access for 1 year$199.00only $3.90 per issueAll prices are NET prices.VAT will be added later in the checkout.Tax calculation will be finalised during checkout.Buy articleGet time limited or full article access on ReadCube.$32.00All prices are NET prices.

Additional access options:

doi: https://doi.org/10.1038/d41586-022-01780-2

References

Subjects

Conservation biology

Subjects

Conservation biology More

Hassani, M. A., Durán, P. & Hacquard, S. Microbial interactions within the plant holobiont. Microbiome 6(1), 58. https://doi.org/10.1186/s40168-018-0445-0 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Sapp, M., Ploch, S., Fiore-Donno, A. M., Bonkowski, M. & Rose, L. E. Protists are an integral part of the Arabidopsis thaliana microbiome. Environ Microbiol 20(1), 30–43. https://doi.org/10.1111/1462-2920.13941 (2018).CAS 
Article 
PubMed 

Google Scholar 
Herrera Paredes, S. & Lebeis, S. L. Giving back to the community: Microbial mechanisms of plant–soil interactions. Funct. Ecol. 30(7), 1043–1052. https://doi.org/10.1111/1365-2435.12684 (2016).Article 

Google Scholar 
Nath, A. & Sundaram, S. Microbiome community interactions with social forestry and agroforestry. In Microbial services in restoration ecology (eds Singh, J. S. & Vimal, S. R.) 71–82 (Elsevier, 2020).Chapter 

Google Scholar 
Rodriguez, P. A. et al. Systems biology of plant–microbiome interactions. Mol. Plant 12(6), 804–821. https://doi.org/10.1016/j.molp.2019.05.006 (2019).CAS 
Article 
PubMed 

Google Scholar 
Guttman, D. S., McHardy, A. C. & Schulze-Lefert, P. Microbial genome-enabled insights into plant–microorganism interactions. Nat. Rev. Genet. 15(12), 797–813. https://doi.org/10.1038/nrg3748 (2014).CAS 
Article 
PubMed 

Google Scholar 
Lewin, S., Francioli, D., Ulrich, A. & Kolb, S. Crop host signatures reflected by co-association patterns of keystone bacteria in the rhizosphere microbiota. Environ. Microb. 16(1), 18. https://doi.org/10.1186/s40793-021-00387-w (2021).CAS 
Article 

Google Scholar 
Trivedi, P., Leach, J. E., Tringe, S. G., Sa, T. & Singh, B. K. Plant–microbiome interactions: From community assembly to plant health. Nat. Rev. Microbiol. 18(11), 607–621. https://doi.org/10.1038/s41579-020-0412-1 (2020).CAS 
Article 
PubMed 

Google Scholar 
Bardelli, T. et al. Effects of slope exposure on soil physico-chemical and microbiological properties along an altitudinal climosequence in the Italian Alps. Sci. Total Environ. 575, 1041–1055. https://doi.org/10.1016/j.scitotenv.2016.09.176 (2017).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Francioli, D., van Ruijven, J., Bakker, L. & Mommer, L. Drivers of total and pathogenic soil-borne fungal communities in grassland plant species. Fungal Ecol. 48, 100987. https://doi.org/10.1016/j.funeco.2020.100987 (2020).Article 

Google Scholar 
Hamonts, K. et al. Field study reveals core plant microbiota and relative importance of their drivers. Environ. Microbiol. 20(1), 124–140. https://doi.org/10.1111/1462-2920.14031 (2018).CAS 
Article 
PubMed 

Google Scholar 
Trivedi, P., Batista, B. D., Bazany, K. E. & Singh, B. K. Plant–microbiome interactions under a changing world: Responses, consequences and perspectives. New Phytol. 234(6), 1951–1959. https://doi.org/10.1111/nph.18016 (2022).Article 
PubMed 

Google Scholar 
Hawkes, C. V. et al. Extension of plant phenotypes by the foliar microbiome. Annu. Rev. Plant Biol. 72(1), 823–846. https://doi.org/10.1146/annurev-arplant-080620-114342 (2021).CAS 
Article 
PubMed 

Google Scholar 
Hunter, P. The revival of the extended phenotype: After more than 30 years, Dawkins’ extended phenotype hypothesis is enriching evolutionary biology and inspiring potential applications. EMBO Rep. 19(7), e46477. https://doi.org/10.15252/embr.201846477 (2018).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Thapa, S. & Prasanna, R. Prospecting the characteristics and significance of the phyllosphere microbiome. Ann. Microbiol. 68(5), 229–245. https://doi.org/10.1007/s13213-018-1331-5 (2018).CAS 
Article 

Google Scholar 
Vacher, C. et al. The phyllosphere: Microbial jungle at the plant-climate interface. Annu. Rev. Ecol. Evol. Syst. 47(1), 1–24. https://doi.org/10.1146/annurev-ecolsys-121415-032238 (2016).Article 

Google Scholar 
Copeland, J. K., Yuan, L., Layeghifard, M., Wang, P. W. & Guttman, D. S. Seasonal community succession of the phyllosphere microbiome. Mol. Plant Microbe Interact. 28(3), 274–285. https://doi.org/10.1094/mpmi-10-14-0331-fi (2015).CAS 
Article 
PubMed 

Google Scholar 
Pérez-Bueno, M. L., Pineda, M., Díaz-Casado, E. & Barón, M. Spatial and temporal dynamics of primary and secondary metabolism in Phaseolus vulgaris challenged by Pseudomonas syringae. Physiol. Plant. 153(1), 161–174. https://doi.org/10.1111/ppl.12237 (2015).CAS 
Article 
PubMed 

Google Scholar 
Bodenhausen, N., Bortfeld-Miller, M., Ackermann, M. & Vorholt, J. A. A Synthetic community approach reveals plant genotypes affecting the phyllosphere microbiota. PLoS Genet. 10(4), e1004283. https://doi.org/10.1371/journal.pgen.1004283 (2014).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Giauque, H. & Hawkes, C. V. Climate affects symbiotic fungal endophyte diversity and performance. Am. J. Bot. 100(7), 1435–1444. https://doi.org/10.3732/ajb.1200568 (2013).Article 
PubMed 

Google Scholar 
Rodriguez, R. J. et al. Stress tolerance in plants via habitat-adapted symbiosis. ISME J. 2(4), 404–416. https://doi.org/10.1038/ismej.2007.106 (2008).Article 
PubMed 

Google Scholar 
Trivedi, P., Mattupalli, C., Eversole, K. & Leach, J. E. Enabling sustainable agriculture through understanding and enhancement of microbiomes. New Phytol. 230(6), 2129–2147. https://doi.org/10.1111/nph.17319 (2021).Article 
PubMed 

Google Scholar 
Delmotte, N. et al. Community proteogenomics reveals insights into the physiology of phyllosphere bacteria. Proc. Natl. Acad. Sci. 106(38), 16428–16433. https://doi.org/10.1073/pnas.0905240106%JProceedingsoftheNationalAcademyofSciences (2009).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Vorholt, J. A. Microbial life in the phyllosphere. Nat. Rev. Microbiol. 10(12), 828–840. https://doi.org/10.1038/nrmicro2910 (2012).CAS 
Article 
PubMed 

Google Scholar 
Kembel, S. W. et al. Relationships between phyllosphere bacterial communities and plant functional traits in a neotropical forest. Proc. Natl. Acad. Sci. 111(38), 13715–13720. https://doi.org/10.1073/pnas.1216057111 (2014).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Whipps, J. M., Hand, P., Pink, D. & Bending, G. D. Phyllosphere microbiology with special reference to diversity and plant genotype. J. Appl. Microbiol. 105(6), 1744–1755. https://doi.org/10.1111/j.1365-2672.2008.03906.x (2008).CAS 
Article 
PubMed 

Google Scholar 
Bai, Y. et al. Functional overlap of the Arabidopsis leaf and root microbiota. Nature 528(7582), 364–369. https://doi.org/10.1038/nature16192 (2015).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Laforest-Lapointe, I., Messier, C. & Kembel, S. W. Host species identity, site and time drive temperate tree phyllosphere bacterial community structure. Microbiome 4(1), 27. https://doi.org/10.1186/s40168-016-0174-1 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Sapkota, R., Knorr, K., Jørgensen, L. N., O’Hanlon, K. A. & Nicolaisen, M. Host genotype is an important determinant of the cereal phyllosphere mycobiome. New Phytol. 207(4), 1134–1144. https://doi.org/10.1111/nph.13418 (2015).CAS 
Article 
PubMed 

Google Scholar 
Grady, K. L., Sorensen, J. W., Stopnisek, N., Guittar, J. & Shade, A. Assembly and seasonality of core phyllosphere microbiota on perennial biofuel crops. Nat. Commun. 10(1), 4135. https://doi.org/10.1038/s41467-019-11974-4 (2019).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Latz, M. A. C. et al. Succession of the fungal endophytic microbiome of wheat is dependent on tissue-specific interactions between host genotype and environment. Sci. Total Environ. 759, 143804. https://doi.org/10.1016/j.scitotenv.2020.143804 (2021).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Rastogi, G. et al. Leaf microbiota in an agroecosystem: Spatiotemporal variation in bacterial community composition on field-grown lettuce. ISME J. 6(10), 1812–1822. https://doi.org/10.1038/ismej.2012.32 (2012).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Bao, L. et al. Seasonal variation of epiphytic bacteria in the phyllosphere of Gingko biloba, Pinus bungeana and Sabina chinensis. FEMS Microbiol. Ecol. 96, 3. https://doi.org/10.1093/femsec/fiaa017 (2020).CAS 
Article 

Google Scholar 
Ding, T. & Melcher, U. Influences of plant species, season and location on leaf endophytic bacterial communities of non-cultivated plants. PLoS ONE 11(3), e0150895. https://doi.org/10.1371/journal.pone.0150895 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Perreault, R. & Laforest-Lapointe, I. Plant-microbe interactions in the phyllosphere: Facing challenges of the anthropocene. ISME J. https://doi.org/10.1038/s41396-021-01109-3 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Redford, A. J. & Fierer, N. Bacterial succession on the leaf surface: A novel system for studying successional dynamics. Microb. Ecol. 58(1), 189–198. https://doi.org/10.1007/s00248-009-9495-y (2009).Article 
PubMed 

Google Scholar 
Campisano, A. et al. Temperature drives the assembly of endophytic communities’ seasonal succession. Environ. Microbiol. 19(8), 3353–3364. https://doi.org/10.1111/1462-2920.13843 (2017).Article 
PubMed 

Google Scholar 
Ren, G. et al. Response of soil, leaf endosphere and phyllosphere bacterial communities to elevated CO2 and soil temperature in a rice paddy. Plant Soil 392(1), 27–44. https://doi.org/10.1007/s11104-015-2503-8 (2015).CAS 
Article 

Google Scholar 
Konapala, G., Mishra, A. K., Wada, Y. & Mann, M. E. Climate change will affect global water availability through compounding changes in seasonal precipitation and evaporation. Nat. Commun. 11(1), 3044. https://doi.org/10.1038/s41467-020-16757-w (2020).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Parmesan, C. & Yohe, G. A globally coherent fingerprint of climate change impacts across natural systems. Nature 421(6918), 37–42. https://doi.org/10.1038/nature01286 (2003).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Donn, S., Kirkegaard, J. A., Perera, G., Richardson, A. E. & Watt, M. Evolution of bacterial communities in the wheat crop rhizosphere. Environ. Microbiol. 17(3), 610–621. https://doi.org/10.1111/1462-2920.12452 (2015).Article 
PubMed 

Google Scholar 
Francioli, D., Schulz, E., Buscot, F. & Reitz, T. Dynamics of soil bacterial communities over a vegetation season relate to both soil nutrient status and plant growth phenology. Microb. Ecol. 75(1), 216–227. https://doi.org/10.1007/s00248-017-1012-0 (2018).CAS 
Article 
PubMed 

Google Scholar 
Breitkreuz, C., Buscot, F., Tarkka, M. & Reitz, T. Shifts between and among populations of wheat rhizosphere Pseudomonas, Streptomyces and Phyllobacterium suggest consistent phosphate mobilization at different wheat growth stages under abiotic stress. Front. Microbiol. 10, 3109–3109. https://doi.org/10.3389/fmicb.2019.03109 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Na, X. et al. Plant stage, not drought stress, determines the effect of cultivars on bacterial community diversity in the rhizosphere of broomcorn millet (Panicum miliaceum L.). Front. Microbiol. 10, 828. https://doi.org/10.3389/fmicb.2019.00828 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Ad-hoc-AG-Boden. Bodenkundliche Kartieranleitung 438 (Schweizerbart, 2005).
Google Scholar 
Zadoks, J. C., Chang, T. T. & Konzak, C. F. A decimal code for the growth stages of cereals. Weed Res. 14(6), 415–421. https://doi.org/10.1111/j.1365-3180.1974.tb01084.x (1974).Article 

Google Scholar 
Cannell, R. Q., Belford, R. K., Gales, K., Dennis, C. W. & Prew, R. D. Effects of waterlogging at different stages of development on the growth and yield of winter wheat. J. Sci. Food Agric. 31(2), 117–132. https://doi.org/10.1002/jsfa.2740310203 (1980).Article 

Google Scholar 
Drew, M. C. Soil aeration and plant root metabolism. Soil Sci. 154(4), 259–268 (1992).ADS 
Article 

Google Scholar 
Meyer, W. et al. Effect of irrigation on soil oxygen status and root and shoot growth of wheat in a clay soil. Aust. J. Agric. Res. https://doi.org/10.1071/AR9850171 (1985).Article 

Google Scholar 
Riehm, H. Bestimmung der laktatlöslichen Phosphorsäure in karbonathaltigen Böden. Phosphorsäure 1, 167–178. https://doi.org/10.1002/jpln.19420260107 (1943).Article 

Google Scholar 
Murphy, J., & Riley, J. P. A modified single solution method for the determination of phosphate in natural waters. Anal. Chim. Acta 27, 31–36. https://doi.org/10.1016/S0003-2670(00)88444-5 (1962).CAS 
Article 

Google Scholar 
Francioli, D., Lentendu, G., Lewin, S. & Kolb, S. DNA metabarcoding for the characterization of terrestrial microbiota—pitfalls and solutions. Microorganisms 9(2), 361 (2021).CAS 
Article 

Google Scholar 
Chelius, M. K. & Triplett, E. W. The diversity of archaea and bacteria in association with the roots of Zea mays L. Microb. Ecol. 41(3), 252–263. https://doi.org/10.1007/s002480000087 (2001).CAS 
Article 
PubMed 

Google Scholar 
Redford, A. J., Bowers, R. M., Knight, R., Linhart, Y. & Fierer, N. The ecology of the phyllosphere: Geographic and phylogenetic variability in the distribution of bacteria on tree leaves. Environ. Microbiol. 12(11), 2885–2893. https://doi.org/10.1111/j.1462-2920.2010.02258.x (2010).Article 
PubMed 
PubMed Central 

Google Scholar 
Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 17, 1. https://doi.org/10.14806/ej.17.1.200 (2011).Article 

Google Scholar 
Callahan, B. J. et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 13(7), 581. https://doi.org/10.1038/Nmeth.3869 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Francioli, D. et al. Flooding causes dramatic compositional shifts and depletion of putative beneficial bacteria on the spring wheat microbiota. Front. Microbiol. 12, 3371. https://doi.org/10.3389/fmicb.2021.773116 (2021).Article 

Google Scholar 
Anderson, M. J. Permutational multivariate analysis of variance (PERMANOVA). In Wiley StatsRef: Statistics Reference Online 1–15 (Wiley, 2017).
Google Scholar 
Dray, S., Legendre, P. & Blanchet, G. Packfor: Forward Selection with Permutation. R package version 0.0‐8/r100 ed. (2011).Oksanen, J. et al. vegan: Community Ecology Package. R package version 2.5-2. ed. (2018).Segata, N. et al. Metagenomic biomarker discovery and explanation. Genome Biol. 12(6), R60. https://doi.org/10.1186/gb-2011-12-6-r60 (2011).Article 
PubMed 
PubMed Central 

Google Scholar 
Lahti, L. & Sudarshan, S. Tools for Microbiome Analysis in R. Version 2.1.28. ed. (2020).R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020).
Google Scholar 
Chen, S. et al. Root-associated microbiomes of wheat under the combined effect of plant development and nitrogen fertilization. Microbiome 7(1), 136. https://doi.org/10.1186/s40168-019-0750-2 (2019).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Wang, J. et al. Wheat and rice growth stages and fertilization regimes alter soil bacterial community structure, but not diversity. Front. Microbiol. 7, 1207. https://doi.org/10.3389/fmicb.2016.01207 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Comby, M., Lacoste, S., Baillieul, F., Profizi, C. & Dupont, J. Spatial and temporal variation of cultivable communities of co-occurring endophytes and pathogens in wheat. Front. Microbiol. 7, 403. https://doi.org/10.3389/fmicb.2016.00403 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Robinson, R. J. et al. Endophytic bacterial community composition in wheat (Triticum aestivum) is determined by plant tissue type, developmental stage and soil nutrient availability. Plant Soil 405(1), 381–396. https://doi.org/10.1007/s11104-015-2495-4 (2016).CAS 
Article 

Google Scholar 
Sapkota, R., Jørgensen, L. N. & Nicolaisen, M. Spatiotemporal variation and networks in the mycobiome of the wheat canopy. Front. Plant Sci. https://doi.org/10.3389/fpls.2017.01357 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Chaudhry, V. et al. Shaping the leaf microbiota: Plant–microbe–microbe interactions. J. Exp. Bot. 72(1), 36–56. https://doi.org/10.1093/jxb/eraa417 (2020).CAS 
Article 
PubMed Central 

Google Scholar 
Liu, Z., Cheng, R., Xiao, W., Guo, Q. & Wang, N. Effect of off-season flooding on growth, photosynthesis, carbohydrate partitioning, and nutrient uptake in Distylium chinense. PLoS ONE 9(9), e107636. https://doi.org/10.1371/journal.pone.0107636 (2014).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Rosa, M. et al. Soluble sugars. Plant Signal. Behav. 4(5), 388–393. https://doi.org/10.4161/psb.4.5.8294 (2009).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Chen, H., Qualls, R. G. & Blank, R. R. Effect of soil flooding on photosynthesis, carbohydrate partitioning and nutrient uptake in the invasive exotic Lepidium latifolium. Aquat. Bot. 82(4), 250–268. https://doi.org/10.1016/j.aquabot.2005.02.013 (2005).CAS 
Article 

Google Scholar 
Bacanamwo, M. & Purcell, L. C. Soybean dry matter and N accumulation responses to flooding stress, N sources and hypoxia. J. Exp. Bot. 50(334), 689–696. https://doi.org/10.1093/jxb/50.334.689 (1999).CAS 
Article 

Google Scholar 
Boem, F. H. G., Lavado, R. S. & Porcelli, C. A. Note on the effects of winter and spring waterlogging on growth, chemical composition and yield of rapeseed. Field Crop. Res. 47(2), 175–179. https://doi.org/10.1016/0378-4290(96)00025-1 (1996).Article 

Google Scholar 
Kozlowski, T. T. Plant responses to flooding of soil. Bioscience 34(3), 162–167. https://doi.org/10.2307/1309751 (1984).Article 

Google Scholar 
Topa, M. A. & Cheeseman, J. M. 32P uptake and transport to shoots in Pinuus serotina seedlings under aerobic and hypoxic growth conditions. Physiol. Plant. 87(2), 125–133. https://doi.org/10.1111/j.1399-3054.1993.tb00134.x (1993).CAS 
Article 

Google Scholar 
Colmer, T. D. & Flowers, T. J. Flooding tolerance in halophytes. New Phytol. 179(4), 964–974. https://doi.org/10.1111/j.1469-8137.2008.02483.x (2008).CAS 
Article 
PubMed 

Google Scholar 
Gibbs, J. & Greenway, H. Mechanisms of anoxia tolerance in plants. I. Growth, survival and anaerobic catabolism. Funct. Plant Biol. 30(1), 1–47. https://doi.org/10.1071/PP98095 (2003).CAS 
Article 
PubMed 

Google Scholar 
Board, J. E. Waterlogging effects on plant nutrient concentrations in soybean. J. Plant Nutr. 31(5), 828–838. https://doi.org/10.1080/01904160802043122 (2008).CAS 
Article 

Google Scholar 
Smethurst, C. F., Garnett, T. & Shabala, S. Nutritional and chlorophyll fluorescence responses of lucerne (Medicago sativa) to waterlogging and subsequent recovery. Plant Soil 270(1), 31–45. https://doi.org/10.1007/s11104-004-1082-x (2005).CAS 
Article 

Google Scholar 
Thomson, C. J., Atwell, B. J. & Greenway, H. Response of wheat seedlings to low O2 concentrations in nutrient solution: II. K+/Na+ selectivity of root tissues. J. Exp. Bot. 40(9), 993–999. https://doi.org/10.1093/jxb/40.9.993 (1989).Article 

Google Scholar 
Barrett-Lennard, E. G. The interaction between waterlogging and salinity in higher plants: Causes, consequences and implications. Plant Soil 253(1), 35–54. https://doi.org/10.1023/A:1024574622669 (2003).CAS 
Article 

Google Scholar 
Granzow, S. et al. The effects of cropping regimes on fungal and bacterial communities of wheat and faba bean in a greenhouse pot experiment differ between plant species and compartment. Front. Microbiol. 8, 902. https://doi.org/10.3389/fmicb.2017.00902 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Gdanetz, K. & Trail, F. The wheat microbiome under four management strategies, and potential for endophytes in disease protection. Phytobiomes J. 1(3), 158–168. https://doi.org/10.1094/PBIOMES-05-17-0023-R (2017).Article 

Google Scholar 
Shade, A., McManus, P. S., Handelsman, J. & Zhou, J. Unexpected diversity during community succession in the apple flower microbiome. MBio 4(2), e00602-00612. https://doi.org/10.1128/mBio.00602-12 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
Guo, J. et al. Seed-borne, endospheric and rhizospheric core microbiota as predictors of plant functional traits across rice cultivars are dominated by deterministic processes. New. Phytol. 230(5), 2047–2060. https://doi.org/10.1111/nph.17297 (2021).Article 
PubMed 

Google Scholar 
Allwood, J. W. et al. Profiling of spatial metabolite distributions in wheat leaves under normal and nitrate limiting conditions. Phytochemistry 115, 99–111. https://doi.org/10.1016/j.phytochem.2015.01.007 (2015).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Li, Y. et al. Plant phenotypic traits eventually shape its microbiota: A common garden test. Front. Microbiol. 9, 2479. https://doi.org/10.3389/fmicb.2018.02479 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Xiong, C. et al. Plant developmental stage drives the differentiation in ecological role of the maize microbiome. Microbiome 9(1), 171. https://doi.org/10.1186/s40168-021-01118-6 (2021).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Schlechter, R. O., Miebach, M. & Remus-Emsermann, M. N. P. Driving factors of epiphytic bacterial communities: A review. J. Adv. Res. 19, 57–65. https://doi.org/10.1016/j.jare.2019.03.003 (2019).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Mathur, P., Mehtani, P. & Sharma, C. (2021). Leaf Endophytes and Their Bioactive Compounds. In Symbiotic Soil Microorganisms: Biology and Applications, (eds Shrivastava, N. et al.) 147–159 (Cham, Springer International Publishing, 2021).Aquino, J., Junior, F. L. A., Figueiredo, M., De Alcântara Neto, F. & Araujo, A. Plant growth-promoting endophytic bacteria on maize and sorghum1. Pesq. Agrop. Trop. https://doi.org/10.1590/1983-40632019v4956241 (2019).Article 

Google Scholar 
Gamalero, E. et al. Screening of bacterial endophytes able to promote plant growth and increase salinity tolerance. Appl. Sci. 10(17), 5767 (2020).CAS 
Article 

Google Scholar 
Borah, A. & Thakur, D. Phylogenetic and functional characterization of culturable endophytic actinobacteria associated with Camellia spp. for growth promotion in commercial tea cultivars. Front. Microbiol. 11, 318. https://doi.org/10.3389/fmicb.2020.00318 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Haidar, B. et al. Population diversity of bacterial endophytes from jute (Corchorus olitorius) and evaluation of their potential role as bioinoculants. Microbiol. Res. 208, 43–53. https://doi.org/10.1016/j.micres.2018.01.008 (2018).Article 
PubMed 

Google Scholar 
Bind, M. & Nema, S. Isolation and molecular characterization of endophytic bacteria from pigeon pea along with antimicrobial evaluation against Fusarium udum. J. Appl. Microbiol. Open Access 5, 163 (2019).
Google Scholar 
de Almeida Lopes, K. B. et al. Screening of bacterial endophytes as potential biocontrol agents against soybean diseases. J. Appl. Microbiol. 125(5), 1466–1481. https://doi.org/10.1111/jam.14041 (2018).CAS 
Article 
PubMed 

Google Scholar 
Müller, T. & Behrendt, U. Exploiting the biocontrol potential of plant-associated pseudomonads: A step towards pesticide-free agriculture?. Biol. Control 155, 104538. https://doi.org/10.1016/j.biocontrol.2021.104538 (2021).CAS 
Article 

Google Scholar 
Safin, R. I. et al. Features of seeds microbiome for spring wheat varieties from different regions of Eurasia. In: International Scientific and Practical Conference “AgroSMART: Smart Solutions for Agriculture”, 766–770 (Atlantis Press).Adler, P. B. & Drake, J. Environmental variation, stochastic extinction, and competitive coexistence. Am. Nat. 172(5), E186–E195. https://doi.org/10.1086/591678 (2008).Article 

Google Scholar 
Gilbert, B. & Levine, J. M. Ecological drift and the distribution of species diversity. Proc. R. Soc. B 284(1855), 20170507. https://doi.org/10.1098/rspb.2017.0507 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Fitzpatrick, C. R. et al. Assembly and ecological function of the root microbiome across angiosperm plant species. Proc. Natl. Acad. Sci. 115(6), E1157–E1165. https://doi.org/10.1073/pnas.1717617115 (2018).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Freschet, G. T. et al. Root traits as drivers of plant and ecosystem functioning: Current understanding, pitfalls and future research needs. New Phytol. 232(3), 1123–1158. https://doi.org/10.1111/nph.17072 (2021).Article 
PubMed 

Google Scholar 
Kembel, S. W. & Mueller, R. C. Plant traits and taxonomy drive host associations in tropical phyllosphere fungal communities. Botany 92(4), 303–311. https://doi.org/10.1139/cjb-2013-0194 (2014).Article 

Google Scholar 
Leff, J. W. et al. Predicting the structure of soil communities from plant community taxonomy, phylogeny, and traits. ISME J. 12(7), 1794–1805. https://doi.org/10.1038/s41396-018-0089-x (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Ulbrich, T. C., Friesen, M. L., Roley, S. S., Tiemann, L. K. & Evans, S. E. Intraspecific variability in root traits and edaphic conditions influence soil microbiomes across 12 switchgrass cultivars. Phytobiom. J. 5(1), 108–120. https://doi.org/10.1094/pbiomes-12-19-0069-fi (2021).Article 

Google Scholar 
Arduini, I., Orlandi, C., Pampana, S. & Masoni, A. Waterlogging at tillering affects spike and spikelet formation in wheat. Crop Pasture Sci. 67(7), 703–711. https://doi.org/10.1071/CP15417 (2016).CAS 
Article 

Google Scholar 
Ding, J. et al. Effects of waterlogging on grain yield and associated traits of historic wheat cultivars in the middle and lower reaches of the Yangtze River, China. Field Crops Res. 246, 107695. https://doi.org/10.1016/j.fcr.2019.107695 (2020).Article 

Google Scholar 
Malik, I., Colmer, T., Lambers, H. & Schortemeyer, M. Changes in physiological and morphological traits of roots and shoots of wheat in response to different depths of waterlogging. Austral. J. Plant Physiol. 28, 1121–1131. https://doi.org/10.1071/PP01089 (2001).Article 

Google Scholar 
Pampana, S., Masoni, A. & Arduini, I. Grain yield of durum wheat as affected by waterlogging at tillering. Cereal Res. Commun. 44(4), 706–716. https://doi.org/10.1556/0806.44.2016.026 (2016).Article 

Google Scholar 
Xu, L. et al. Drought delays development of the sorghum root microbiome and enriches for monoderm bacteria. Proc. Natl. Acad. Sci. 115(18), E4284–E4293. https://doi.org/10.1073/pnas.1717308115%JProceedingsoftheNationalAcademyofSciences (2018).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Angel, R. et al. The root-associated microbial community of the world’s highest growing vascular plants. Microb. Ecol. 72(2), 394–406. https://doi.org/10.1007/s00248-016-0779-8 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Edwards, J. A. et al. Compositional shifts in root-associated bacterial and archaeal microbiota track the plant life cycle in field-grown rice. PLoS Biol. 16(2), e2003862. https://doi.org/10.1371/journal.pbio.2003862 (2018).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Kuźniar, A. et al. Culture-independent analysis of an endophytic core microbiome in two species of wheat: Triticum aestivum L. (cv. ‘Hondia’) and the first report of microbiota in Triticum spelta L. (cv. ‘Rokosz’). Syst. Appl. Microbiol. 43(1), 126025. https://doi.org/10.1016/j.syapm.2019.126025 (2020).CAS 
Article 
PubMed 

Google Scholar 
Soldan, R. et al. Bacterial endophytes of mangrove propagules elicit early establishment of the natural host and promote growth of cereal crops under salt stress. Microbiol. Res. 223–225, 33–43. https://doi.org/10.1016/j.micres.2019.03.008 (2019).CAS 
Article 
PubMed 

Google Scholar 
Truyens, S., Weyens, N., Cuypers, A. & Vangronsveld, J. Bacterial seed endophytes: Genera, vertical transmission and interaction with plants. Environ. Microbiol. Rep. 7(1), 40–50. https://doi.org/10.1111/1758-2229.12181 (2015).Article 

Google Scholar 
Chimwamurombe, P. M., Grönemeyer, J. L. & Reinhold-Hurek, B. Isolation and characterization of culturable seed-associated bacterial endophytes from gnotobiotically grown Marama bean seedlings. FEMS Microbiol. Ecol. 92, 6. https://doi.org/10.1093/femsec/fiw083 (2016).CAS 
Article 

Google Scholar 
Eid, A. M. et al. Harnessing bacterial endophytes for promotion of plant growth and biotechnological applications: An overview. Plants 10(5), 935 (2021).CAS 
Article 

Google Scholar 
Mareque, C. et al. The endophytic bacterial microbiota associated with sweet sorghum (Sorghum bicolor) is modulated by the application of chemical N fertilizer to the field. Int. J. Genom. 2018, 7403670. https://doi.org/10.1155/2018/7403670 (2018).CAS 
Article 

Google Scholar 
Francioli, D. et al. Mineral vs organic amendments: Microbial community structure, activity and abundance of agriculturally relevant microbes are driven by long-term fertilization strategies. Front. Microbiol. 7, 1446. https://doi.org/10.3389/fmicb.2016.01446 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Schrey, S. D. & Tarkka, M. T. Friends and foes: Streptomycetes as modulators of plant disease and symbiosis. Antonie Van Leeuwenhoek 94(1), 11–19. https://doi.org/10.1007/s10482-008-9241-3 (2008).Article 
PubMed 

Google Scholar 
Patel, J. K., Madaan, S. & Archana, G. Antibiotic producing endophytic Streptomyces spp. colonize above-ground plant parts and promote shoot growth in multiple healthy and pathogen-challenged cereal crops. Microbiol. Res. 215, 36–45. https://doi.org/10.1016/j.micres.2018.06.003 (2018).CAS 
Article 
PubMed 

Google Scholar 
Yi, Y.-S. et al. Antifungal activity of Streptomyces sp. against Puccinia recondita causing wheat leaf rust. J. Microbiol. Biotechnol. 14(2), 422–425 (2004).CAS 

Google Scholar 
Sperdouli, I. & Moustakas, M. Leaf developmental stage modulates metabolite accumulation and photosynthesis contributing to acclimation of Arabidopsis thaliana to water deficit. J. Plant. Res. 127(4), 481–489. https://doi.org/10.1007/s10265-014-0635-1 (2014).CAS 
Article 
PubMed 

Google Scholar  More

Weiss, S. et al. Correlation detection strategies in microbial data sets vary widely in sensitivity and precision. ISME J. 10, 1669–1681 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
Djokic, T., Kranendonk, M. J. V., Campbell, K. A., Walter, M. R. & Ward, C. R. Earliest signs of life on land preserved in ca. 3.5 Ga hot spring deposits. Nat. Commun. 8, 1–9 (2017).
Google Scholar 
Damer, B. & Deamer, D. The Hot Spring Hypothesis for an origin of life. Astrobiology 20, 429–452 (2020).ADS 
PubMed 
PubMed Central 

Google Scholar 
Van Kranendonk, M. J. et al. Elements for the origin of life on land: a deep-time perspective from the Pilbara Craton of Western Australia. Astrobiology 21, 39–59 (2021).ADS 
PubMed 

Google Scholar 
Colman, D. R. et al. Phylogenomic analysis of novel Diaforarchaea is consistent with sulfite but not sulfate reduction in volcanic environments on early Earth. ISME J. 14, 1316–1331 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
Anbar, A. D. & Knoll, A. H. Proterozoic ocean chemistry and evolution: a bioinorganic bridge? Science 297, 1137–1142 (2002).ADS 
CAS 
PubMed 

Google Scholar 
Lloyd, K. G. et al. Phylogenetically novel uncultured microbial cells dominate Earth microbiomes. mSystems 3, 431 (2018).
Google Scholar 
Hedlund, B. P. et al. Uncultivated thermophiles: current status and spotlight on ‘Aigarchaeota’. Curr. Opin. Microbiol. 25, 136–145 (2015).CAS 
PubMed 

Google Scholar 
Nunoura, T. et al. Genetic and functional properties of uncultivated thermophilic crenarchaeotes from a subsurface gold mine as revealed by analysis of genome fragments. Environ. Microbiol. 7, 1967–1984 (2005).CAS 
PubMed 

Google Scholar 
Nunoura, T. et al. Insights into the evolution of Archaea and eukaryotic protein modifier systems revealed by the genome of a novel archaeal group. Nucleic Acids Res. 39, 3204–3223 (2010).PubMed 
PubMed Central 

Google Scholar 
Rinke, C. et al. A standardized archaeal taxonomy for the Genome Taxonomy Database. Nat. Microbiol. 6, 946–959 (2021).CAS 
PubMed 

Google Scholar 
Hua, Z.-S. et al. Genomic inference of the metabolism and evolution of the archaeal phylum Aigarchaeota. Nat. Commun. 9, 1–11 (2018).ADS 

Google Scholar 
Takami, H., Arai, W., Takemoto, K., Uchiyama, I. & Taniguchi, T. Functional classification of uncultured ‘Candidatus Caldiarchaeum subterraneum’ using the Maple system. PLoS ONE 10, e0132994 (2015).PubMed 
PubMed Central 

Google Scholar 
Beam, J. P. et al. Ecophysiology of an uncultivated lineage of Aigarchaeota from an oxic, hot spring filamentous ‘streamer’ community. ISME J. 10, 210–224 (2016).CAS 
PubMed 

Google Scholar 
Rinke, C. et al. Insights into the phylogeny and coding potential of microbial dark matter. Nature 499, 431–437 (2013).ADS 
CAS 
PubMed 

Google Scholar 
Cole, J. K. et al. Sediment microbial communities in Great Boiling Spring are controlled by temperature and distinct from water communities. ISME J. 7, 718–729 (2013).CAS 
PubMed 

Google Scholar 
Peacock, J. P. et al. Pyrosequencing reveals high-temperature cellulolytic microbial consortia in Great Boiling Spring after in situ lignocellulose enrichment. PLoS ONE 8, e59927 (2013).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Kletzin, A. & Adams, M. W. W. Tungsten in biological systems. FEMS Microbiol. Rev. 18, 5–63 (1996).CAS 
PubMed 

Google Scholar 
Hagedoorn, P. L. et al. Purification and characterization of the tungsten enzyme aldehyde:ferredoxin oxidoreductase from the hyperthermophilic denitrifier Pyrobaculum aerophilum. J. Biol. Inorg. Chem. 10, 259–269 (2005).CAS 
PubMed 

Google Scholar 
de Vries, S. et al. Adaptation to a high-tungsten environment: Pyrobaculum aerophilum contains an active tungsten nitrate reductase. Biochemistry 49, 9911–9921 (2010).PubMed 

Google Scholar 
Bräsen, C., Esser, D., Rauch, B. & Siebers, B. Carbohydrate metabolism in Archaea: current insights into unusual enzymes and pathways and their regulation. Microbiol. Mol. Biol. Rev. 78, 89–175 (2014).Kato, S. et al. Long-term cultivation and metagenomics reveal ecophysiology of previously uncultivated thermophiles involved in biogeochemical nitrogen cycle. Microbes Environ. 33, 107–110 (2018).PubMed 
PubMed Central 

Google Scholar 
Costa, K. C. et al. Microbiology and geochemistry of great boiling and mud hot springs in the United States Great Basin. Extremophiles 13, 447–459 (2009).CAS 
PubMed 

Google Scholar 
Mukund, S. & Adams, M. W. The novel tungsten-iron-sulfur protein of the hyperthermophilic archaebacterium, Pyrococcus furiosus, is an aldehyde ferredoxin oxidoreductase. Evidence for its participation in a unique glycolytic pathway. J. Biol. Chem. 266, 14208–14216 (1991).CAS 
PubMed 

Google Scholar 
Mukund, S. & Adams, M. W. W. Glyceraldehyde-3-phosphate ferredoxin oxidoreductase, a novel tungsten-containing enzyme with a potential glycolytic role in the hyperthermophilic archaeon Pyrococcus furiosus. J. Biol. Chem. 270, 8389–8392 (1995).CAS 
PubMed 

Google Scholar 
Roy, R. et al. Purification and molecular characterization of the tungsten-containing formaldehyde ferredoxin oxidoreductase from the hyperthermophilic archaeon Pyrococcus furiosus: the third of a putative five-member tungstoenzyme family. J. Bacteriol. 181, 1171–1180 (1999).CAS 
PubMed 
PubMed Central 

Google Scholar 
Roy, R. & Adams, M. W. W. Characterization of a fourth tungsten-containing enzyme from the hyperthermophilic archaeon Pyrococcus furiosus. J. Bacteriol. 184, 6952–6956 (2002).CAS 
PubMed 
PubMed Central 

Google Scholar 
Bevers, L. E., Bol, E., Hagedoorn, P.-L. & Hagen, W. R. WOR5, a novel tungsten-containing aldehyde oxidoreductase from Pyrococcus furiosus with a broad substrate specificity. J. Bacteriol. 187, 7056–7061 (2005).CAS 
PubMed 
PubMed Central 

Google Scholar 
Habib, U. & Hoffman, M. Effect of molybdenum and tungsten on the reduction of nitrate in nitrate reductase, a DFT study. Chem. Cent. J. 11, 1–12 (2017).
Google Scholar 
Liao, R.-Z. Why is the molybdenum-substituted tungsten-dependent formaldehyde ferredoxin oxidoreductase not active? A quantum chemical study. J. Biol. Inorg. Chem. 18, 175–181 (2013).CAS 
PubMed 

Google Scholar 
Qian, H.-X. & Liao, R.-Z. QM/MM study of tungsten-dependent benzoyl-coenzyme A reductase: rationalization of regioselectivity and predication of W vs Mo selectivity. Inorg. Chem. 57, 10667–10678 (2018).CAS 
PubMed 

Google Scholar 
Liu, Y.-F., Liao, R.-Z., Ding, W.-J., Yu, J.-G. & Liu, R.-Z. Theoretical investigation of the first-shell mechanism of acetylene hydration catalyzed by a biomimetic tungsten complex. JBIC 16, 745–752 (2011).CAS 
PubMed 

Google Scholar 
Kerr, P. F. Tungsten-bearing manganese deposit at Golconda, Nevada. Geol. Soc. Am. Bull. 51, 1359–1390 (1940).ADS 
CAS 

Google Scholar 
Mukund, S. & Adams, M. W. W. Molybdenum and vanadium do not replace tungsten in the catalytically active forms of the three tungstoenzymes in the hyperthermophilic archaeon Pyrococcus furiosus. J. Bacteriol. 178, 163–167 (1996).CAS 
PubMed 
PubMed Central 

Google Scholar 
Debnar-Daumler, C., Seubert, A., Schmitt, G. & Heider, J. Simultaneous involvement of a tungsten-containing aldehyde:ferredoxin oxidoreductase and a phenylacetaldehyde dehydrogenase in anaerobic phenylalanine metabolism. J. Bacteriol. 196, 483–492 (2014).PubMed 
PubMed Central 

Google Scholar 
Scott, I. M. et al. A new class of tungsten-containing oxidoreductase in Caldicellulosiruptor, a genus of plant biomass-degrading thermophilic bacteria. Appl. Environ. Microbiol. 81, 7339–7347 (2015).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Scott, I. M. et al. The thermophilic biomass-degrading bacterium Caldicellulosiruptor bescii utilizes two enzymes to oxidize glyceraldehyde 3-phosphate during glycolysis. J. Biol. Chem. 294, 9995–10005 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
Johnson, J. L., Rajagopalan, K. V., Mukund, S. & Adams, M. W. Identification of molybdopterin as the organic component of the tungsten cofactor in four enzymes from hyperthermophilic Archaea. J. Biol. Chem. 268, 4848–4852 (1993).CAS 
PubMed 

Google Scholar 
Chan, M. K., Mukund, S., Kletzin, A., Adams, M. W. & Rees, D. C. Structure of a hyperthermophilic tungstopterin enzyme, aldehyde ferredoxin oxidoreductase. Science 267, 1463–1469 (1995).ADS 
CAS 
PubMed 

Google Scholar 
Glass, J. B. et al. Geochemical, metagenomic and metaproteomic insights into trace metal utilization by methane‐oxidizing microbial consortia in sulphidic marine sediments. Environ. Microbiol. 16, 1592–1611 (2014).CAS 
PubMed 

Google Scholar 
Li, G.-W., Burkhardt, D., Gross, C. & Weissman, J. S. Quantifying absolute protein synthesis rates reveals principles underlying allocation of cellular resources. Cell 157, 624–635 (2014).CAS 
PubMed 
PubMed Central 

Google Scholar 
Behrens, S. et al. Linking microbial phylogeny to metabolic activity at the single-cell level by using enhanced element labeling-catalyzed reporter deposition fluorescence in situ hybridization (EL-FISH) and NanoSIMS. Appl. Environ. Microbiol. 74, 3143–3150. https://doi.org/10.1128/AEM.00191-08 (2008).Knapik, K., Becerra, M. & González-Siso, M.-I. Microbial diversity analysis and screening for novel xylanase enzymes from the sediment of the Lobios Hot Spring in Spain. Sci. Rep. 9, 11195 (2019).ADS 
PubMed 
PubMed Central 

Google Scholar 
Roy, R., Dhawan, I. K., Johnson, M. K., Rees, D. C. & Adams, M. W. Aldehyde Ferredoxin Oxidoreductase. 266 (American Cancer Society, 2011).Sevcenco, A.-M. et al. The tungsten metallome of Pyrococcus furiosus. Metallomics 1, 395–402 (2009).CAS 
PubMed 

Google Scholar 
Sakuraba, H. & Ohshima, T. Novel energy metabolism in anaerobic hyperthermophilic archaea: a modified Embden-Meyerhof pathway. J. Biosci. Bioeng. 93, 441–448 (2002).CAS 
PubMed 

Google Scholar 
Ma, K., Hutchins, A., Sung, S.-J. S. & Adams, M. W. W. Pyruvate ferredoxin oxidoreductase from the hyperthermophilic archaeon, Pyrococcus furiosus, functions as a CoA-dependent pyruvate decarboxylase. Proc. Natl Acad. Sci. USA 94, 9608–9613 (1997).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Mai, X. & Adams, M. W. Characterization of a fourth type of 2-keto acid-oxidizing enzyme from a hyperthermophilic archaeon: 2-ketoglutarate ferredoxin oxidoreductase from Thermococcus litoralis. J. Bacteriol. 178, 5890–5896 (1996).CAS 
PubMed 
PubMed Central 

Google Scholar 
Adams, M. W. W. & Kletzin, A. Oxidoreductase-type enzymes and redox proteins involved in fermentative metabolisms of hyperthermophilic archaea. Adv. Prot. Chem. 48, 101–180 (1996).CAS 

Google Scholar 
Mulkidjanian, A. Y., Galperin, M. Y., Makarova, K. S., Wolf, Y. I. & Koonin, E. V. Evolutionary primacy of sodium bioenergetics. Biol. Direct 3, 1–19 (2008).
Google Scholar 
Heider, J., Ma, K. & Adams, M. W. W. Purification, characterization, and metabolic function of tungsten-containing aldehyde ferredoxin oxidoreductase from the hyperthermophilic and proteolytic archaeon Thermococcus strain ES-1. J. Bacteriol. 177, 4757–4764 (1995).CAS 
PubMed 
PubMed Central 

Google Scholar 
Schut, G. J. et al. The modular respiratory complexes involved in hydrogen and sulfur metabolism by heterotrophic hyperthermophilic archaea and their evolutionary implications. FEMS Microbiol. Rev. 37, 182–203 (2013).CAS 
PubMed 

Google Scholar 
Kuhns, M., Trifunović, D., Huber, H. & Müller, V. The Rnf complex is a Na+ coupled respiratory enzyme in a fermenting bacterium, Thermotoga maritima. Commun. Biol. 3, 1–10 (2020).
Google Scholar 
Sapra, R., Verhagen, M. F. J. M. & Adams, M. W. W. Purification and characterization of a membrane-bound hydrogenase from the hyperthermophilic archaeon Pyrococcus furiosus. J. Bacteriol. 182, 3423–3428 (2000).CAS 
PubMed 
PubMed Central 

Google Scholar 
Sapra, R., Bagramyan, K. & Adams, M. W. W. A simple energy-conserving system: Proton reduction coupled to proton translocation. Proc. Natl Acad. Sci. USA 100, 7545–7550 (2003).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Schut, G. J. et al. The role of geochemistry and energetics in the evolution of modern respiratory complexes from a proton-reducing ancestor. Biochim. Biophys. Acta Bioenerg. 1857, 958–970 (2016).CAS 

Google Scholar 
Juszczak, A., Aono, S. & Adams, M. W. The extremely thermophilic eubacterium, Thermotoga maritima, contains a novel iron-hydrogenase whose cellular activity is dependent upon tungsten. J. Biol. Chem. 266, 13834–13841 (1991).CAS 
PubMed 

Google Scholar 
Selig, M., Xavier, K. B., Santos, H. & Schönheit, P. Comparative analysis of Embden-Meyerhof and Entner-Doudoroff glycolytic pathways in hyperthermophilic archaea and the bacterium Thermotoga. Arch. Microbiol. 167, 217–232 (1997).CAS 
PubMed 

Google Scholar 
Zhang, Y. & Gladyshev, V. N. Molybdoproteomes and evolution of molybdenum utilization. J. Mol. Biol. 379, 881–899 (2008).CAS 
PubMed 
PubMed Central 

Google Scholar 
Anbar, A. D. et al. A whiff of oxygen before the Great Oxidation Event? Science 317, 1903–1906 (2007).Neubert, N., Nägler, T. F. & Böttcher, M. E. Sulfidity controls molybdenum isotope fractionation into euxinic sediments: evidence from the modern Black Sea. Geology 36, 775–778 (2008).ADS 
CAS 

Google Scholar 
Helz, G. R. et al. Mechanism of molybdenum removal from the sea and its concentration in black shales: EXAFS evidence. Geochim. Cosmochim. Acta 60, 3631–3642 (1996).ADS 
CAS 

Google Scholar 
Shen, Y., Buick, R. & Canfield, D. E. Isotopic evidence for microbial sulphate reduction in the early Archaean era. Nature 410, 77–81 (2001).ADS 
CAS 
PubMed 

Google Scholar 
Dodsworth, J. A. et al. Thermoflexus hugenholtzii gen. nov., sp. nov., a thermophilic, microaerophilic, filamentous bacterium representing a novel class in the Chloroflexi, Thermoflexia classis nov., and description of Thermoflexaceae fam. nov. and Thermoflexales ord. nov. Int. J. Sys. Evol. Microbiol. 64, 2119–2127 (2014).CAS 

Google Scholar 
Hanada, S., Hiraishi, A., Shimada, K. & Matsuura, K. Chloroflexus aggregans sp. nov., a filamentous phototrophic bacterium which forms dense cell aggregates by active gliding movement. Int. J. Sys. Evol. Microbiol. 45, 676–681 (1995).CAS 

Google Scholar 
Murugapiran, S. K. et al. Thermus oshimai JL-2 and T. thermophilus JL-18 genome analysis illuminates pathways for carbon, nitrogen, and sulfur cycling. Stand. Genom. Sci. 7, 449–468 (2013).CAS 

Google Scholar 
Kozich, J. J., Westcott, S. L., Baker, N. T., Highlander, S. K. & Schloss, P. D. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina Sequencing Platform. Appl. Environ. Microbiol. 79, 5112–5120 (2013).Friel, A. D. et al. Microbiome shifts associated with the introduction of wild atlantic horseshoe crabs (Limulus polyphemus) into a touch-tank exhibit. Front. Microbiol. 11, 1398 (2020).Hamilton, T. L., Peters, J. W., Skidmore, M. L. & Boyd, E. S. Molecular evidence for an active endogenous microbiome beneath glacial ice. ISME J. 7, 1402–1412 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
Courtois, S. et al. Quantification of bacterial subgroups in soil: comparison of DNA extracted directly from soil or from cells previously released by density gradient centrifugation. Environ. Microbiol. 3, 431–439 (2001).CAS 
PubMed 

Google Scholar 
Pernthaler, A. & Pernthaler, J. In Protocols for Nucleic Acid Analysis by Nonradioactive Probes 353, 153–164 (Humana Press, 2007).Pett-Ridge, J. & Weber, P. K. In Microbial Systems Biology 91–136 (Humana, New York, NY, 2022). https://doi.org/10.1007/978-1-0716-1585-0_6Parks, D. H., Imelfort, M., Skennerton, C. T., Hugenholtz, P. & Tyson, G. W. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 25, 1043–1055 (2015).CAS 
PubMed 
PubMed Central 

Google Scholar 
Chaumeil, P. A., Mussig, A. J., Hugenholtz, P. & Parks, D. H. GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database. Bioinformatics 36, 1925–1927 (2020).CAS 

Google Scholar 
Hyatt, D. et al. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinform. 11, 1–11 (2010).
Google Scholar 
Cantalapiedra, C. P., Hernández-Plaza, A., Letunic, I., Bork, P. & Huerta-Cepas, J. eggNOG-mapper v2: functional annotation, orthology assignments, and domain prediction at the metagenomic scale. Mol. Biol. Evol. 38, 5825–5829 (2021).Aziz, R. K. et al. The RAST Server: Rapid Annotations using Subsystems Technology. BMC Genomics 9, 1–15 (2008).
Google Scholar 
Darriba, D., Taboada, G. L., Doallo, R. & Posada, D. ProtTest 3: fast selection of best-fit models of protein evolution. Bioinformatics 27, 1164–1165 (2011).CAS 
PubMed 

Google Scholar 
Kück, P. & Longo, G. C. FASconCAT-G: extensive functions for multiple sequence alignment preparations concerning phylogenetic studies. Front. Zool. 11, 1–8 (2014).
Google Scholar 
Stamatakis, A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313 (2014).CAS 
PubMed 
PubMed Central 

Google Scholar 
Jacox, E., Chauve, C., Szöllősi, G. J., Ponty, Y. & Scornavacca, C. ecceTERA: comprehensive gene tree-species tree reconciliation using parsimony. Bioinformatics 32, 2056–2058 (2016).CAS 
PubMed 

Google Scholar 
Chevenet, F. et al. SylvX: a viewer for phylogenetic tree reconciliations. Bioinformatics 32, 608–610 (2016).CAS 
PubMed 

Google Scholar 
Csűös, M. Count: evolutionary analysis of phylogenetic profiles with parsimony and likelihood. Bioinformatics 26, 1910–1912 (2010).
Google Scholar 
Yang, J. et al. The I-TASSER Suite: protein structure and function prediction. Nat. Methods 12, 7–8 (2015).CAS 
PubMed 
PubMed Central 

Google Scholar 
Wu, S., Skolnick, J. & Zhang, Y. Ab initio modeling of small proteins by iterative TASSER simulations. BMC Biol. 5, 17 (2007).PubMed 
PubMed Central 

Google Scholar 
Holm, L. & Rosenstrïm, P. I. Dali server: conservation mapping in 3D. Nucleic Acids Res. 38, W545–W549 (2010).CAS 
PubMed 
PubMed Central 

Google Scholar 
Holm, L. Benchmarking fold detection by DaliLite v.5. Bioinformatics 35, 5326–5327 (2019).CAS 
PubMed 

Google Scholar 
MacQueen, J. In Some Methods for Classification and Analysis of Multivariate Observations 1, 281–297 (1967).Ma, K. & Adams, M. W. W. Sulfide dehydrogenase from the hyperthermophilic archaeon Pyrococcus furiosus: a new multifunctional enzyme involved in the reduction of elemental sulfur. J. Bacteriol. 176, 6509–6517 (1994).CAS 
PubMed 
PubMed Central 

Google Scholar  More

Fink, D. et al. Crowdsourcing meets ecology: he misphere wide spatiotemporal species distribution models. AI Mag. 35, 19–30. https://doi.org/10.1609/aimag.v35i2.2533 (2014).Article 

Google Scholar 
Chandler, M. et al. Contribution of citizen science towards international biodiversity monitoring. Biol. Cons. 213, 280–294. https://doi.org/10.1016/j.biocon.2016.09.004 (2017).Article 

Google Scholar 
Schmeller, D. S. et al. Advantages of volunteer-based biodiversity monitoring in Europe. Conserv. Biol. 23, 307–316. https://doi.org/10.1111/j.1523-1739.2008.01125.x (2009).Article 
PubMed 

Google Scholar 
Boakes, E. H. et al. Distorted views of biodiversity: Spatial and temporal bias in species occurrence data. PLoS Biol. https://doi.org/10.1371/journal.pbio.1000385 (2010).Article 
PubMed 
PubMed Central 

Google Scholar 
Follett, R. & Strezov, V. An analysis of citizen science based research: Usage and publication patterns. PLoS ONE https://doi.org/10.1371/journal.pone.0143687 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
Zattara, E. E. & Aizen, M. A. Worldwide occurrence records suggest a global decline in bee species richness. One Earth 4, 114–123. https://doi.org/10.1016/j.oneear.2020.12.005 (2021).ADS 
Article 

Google Scholar 
Dickinson, J. L. et al. The current state of citizen science as a tool for ecological research and public engagement. Front. Ecol. Environ. 10, 291–297. https://doi.org/10.1890/110236 (2012).Article 

Google Scholar 
Kosmala, M., Wiggins, A., Swanson, A. & Simmons, B. Assessing data quality in citizen science. Front. Ecol. Environ. 14, 551–560. https://doi.org/10.1002/fee.1436 (2016).Article 

Google Scholar 
Bayraktarov, E. et al. Do big unstructured biodiversity data mean more knowledge?. Front. Ecol. Evol. https://doi.org/10.3389/fevo.2018.00239 (2019).Article 

Google Scholar 
Burgess, H. K. et al. The science of citizen science: Exploring barriers to use as a primary research tool. Biol. Cons. 208, 113–120. https://doi.org/10.1016/j.biocon.2016.05.014 (2017).Article 

Google Scholar 
Isaac, N. J. B. & Pocock, M. J. O. Bias and information in biological records. Biol. J. Lin. Soc. 115, 522–531. https://doi.org/10.1111/bij.12532 (2015).Article 

Google Scholar 
August, T., Fox, R., Roy, D. B. & Pocock, M. J. O. Data-derived metrics describing the behaviour of field-based citizen scientists provide insights for project design and modelling bias. Sci. Rep. https://doi.org/10.1038/s41598-020-67658-3 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Boakes, E. H. et al. Patterns of contribution to citizen science biodiversity projects increase understanding of volunteers’ recording behaviour. Sci. Rep. https://doi.org/10.1038/srep33051 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Di Cecco, G. J. et al. Observing the observers: How participants contribute data to iNaturalist and implications for biodiversity science. Bioscience 71, 1179–1188. https://doi.org/10.1093/biosci/biab093 (2021).Article 

Google Scholar 
Kamp, J., Oppel, S., Heldbjerg, H., Nyegaard, T. & Donald, P. F. Unstructured citizen science data fail to detect long-term population declines of common birds in Denmark. Divers. Distrib. 22, 1024–1035. https://doi.org/10.1111/ddi.12463 (2016).Article 

Google Scholar 
Altwegg, R. & Nichols, J. D. Occupancy models for citizen-science data. Methods Ecol. Evol. 10, 8–21. https://doi.org/10.1111/2041-210x.13090 (2019).Article 

Google Scholar 
Courter, J. R., Johnson, R. J., Stuyck, C. M., Lang, B. A. & Kaiser, E. W. Weekend bias in citizen science data reporting: Implications for phenology studies. Int. J. Biometeorol. 57, 715–720. https://doi.org/10.1007/s00484-012-0598-7 (2013).ADS 
Article 
PubMed 

Google Scholar 
Amano, T., Lamming, J. D. L. & Sutherland, W. J. Spatial gaps in global biodiversity information and the role of citizen science. Bioscience 66, 393–400. https://doi.org/10.1093/biosci/biw022 (2016).Article 

Google Scholar 
Geldmann, J. et al. What determines spatial bias in citizen science? Exploring four recording schemes with different proficiency requirements. Divers. Distrib. 22, 1139–1149. https://doi.org/10.1111/ddi.12477 (2016).Article 

Google Scholar 
Girardello, M. et al. Gaps in butterfly inventory data: A global analysis. Biol. Cons. 236, 289–295. https://doi.org/10.1016/j.biocon.2019.05.053 (2019).Article 

Google Scholar 
Husby, M., Hoset, K. S. & Butler, S. Non-random sampling along rural-urban gradients may reduce reliability of multi-species farmland bird indicators and their trends. Ibis https://doi.org/10.1111/ibi.12896 (2021).Article 

Google Scholar 
Petersen, T. K., Speed, J. D. M., Grøtan, V. & Austrheim, G. Species data for understanding biodiversity dynamics: The what, where and when of species occurrence data collection. Ecol. Solut. Evid. https://doi.org/10.1002/2688-8319.12048 (2021).Article 

Google Scholar 
Egerer, M., Lin, B. B. & Kendal, D. Towards better species identification processes between scientists and community participants. Sci. Total Environ. https://doi.org/10.1016/j.scitotenv.2019.133738 (2019).Article 
PubMed 

Google Scholar 
Jimenez, M. F., Pejchar, L. & Reed, S. E. Tradeoffs of using place-based community science for urban biodiversity monitoring. Conserv. Sci. Pract. https://doi.org/10.1111/csp2.338 (2021).Article 

Google Scholar 
Branchini, S. et al. Using a citizen science program to monitor coral reef biodiversity through space and time. Biodivers. Conserv. 24, 319–336. https://doi.org/10.1007/s10531-014-0810-7 (2015).Article 

Google Scholar 
Snall, T., Kindvall, O., Nilsson, J. & Part, T. Evaluating citizen-based presence data for bird monitoring. Biol. Cons. 144, 804–810. https://doi.org/10.1016/j.biocon.2010.11.010 (2011).Article 

Google Scholar 
Gardiner, M. M. et al. Lessons from lady beetles: Accuracy of monitoring data from US and UK citizen-science programs. Front. Ecol. Environ. 10, 471–476. https://doi.org/10.1890/110185 (2012).Article 

Google Scholar 
Troudet, J., Grandcolas, P., Blin, A., Vignes-Lebbe, R. & Legendre, F. Taxonomic bias in biodiversity data and societal preferences. Sci. Rep. https://doi.org/10.1038/s41598-017-09084-6 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Johansson, F. et al. Can information from citizen science data be used to predict biodiversity in stormwater ponds?. Sci. Rep. https://doi.org/10.1038/s41598-020-66306-0 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Everett, G. & Geoghegan, H. Initiating and continuing participation in citizen science for natural history. BMC Ecol. https://doi.org/10.1186/s12898-016-0062-3 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Richter, A. et al. The social fabric of citizen science drivers for long-term engagement in the German butterfly monitoring scheme. J. Insect Conserv. 22, 731–743. https://doi.org/10.1007/s10841-018-0097-1 (2018).Article 

Google Scholar 
MacPhail, V. J., Gibson, S. D. & Colla, S. R. Community science participants gain environmental awareness and contribute high quality data but improvements are needed: Insights from Bumble Bee Watch. PeerJ https://doi.org/10.7717/peerj.9141 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Maund, P. R. et al. What motivates the masses: Understanding why people contribute to conservation citizen science projects. Biol. Conserv. https://doi.org/10.1016/j.biocon.2020.108587 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Moczek, N., Nuss, M. & Kohler, J. K. Volunteering in the citizen science project “Insects of Saxony”—The larger the island of knowledge, the longer the bank of questions. Insects https://doi.org/10.3390/insects12030262 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Branchini, S. et al. Participating in a citizen science monitoring program: Implications for environmental education. PLoS ONE https://doi.org/10.1371/journal.pone.0131812 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
Kelemen-Finan, J., Scheuch, M. & Winter, S. Contributions from citizen science to science education: An examination of a biodiversity citizen science project with schools in Central Europe. Int. J. Sci. Educ. 40, 2078–2098. https://doi.org/10.1080/09500693.2018.1520405 (2018).Article 

Google Scholar 
Deguines, N., Prince, K., Prevot, A. C. & Fontaine, B. Assessing the emergence of pro-biodiversity practices in citizen scientists of a backyard butterfly survey. Sci. Total Environ. https://doi.org/10.1016/j.scitotenv.2020.136842 (2020).Article 
PubMed 

Google Scholar 
Peter, M., Diekötter, T., Höffler, T. & Kremer, K. Biodiversity citizen science: Outcomes for the participating citizens. People Nat. 3, 294–311. https://doi.org/10.1002/pan3.10193 (2021).Article 

Google Scholar 
Phillips, T. B., Bailey, R. L., Martin, V., Faulkner-Grant, H. & Bonter, D. N. The role of citizen science in management of invasive avian species: What people think, know, and do. J. Environ. Manage. https://doi.org/10.1016/j.jenvman.2020.111709 (2021).Article 
PubMed 

Google Scholar 
Parrish, J. K. et al. Hoping for optimality or designing for inclusion: Persistence, learning, and the social network of citizen science. Proc. Natl. Acad. Sci. U.S.A. 116, 1894–1901. https://doi.org/10.1073/pnas.1807186115 (2019).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Mac Domhnaill, C., Lyons, S. & Nolan, A. The citizens in citizen science: Demographic, socioeconomic, and health characteristics of biodiversity recorders in Ireland. Citiz. Sci.: Theory Pract. 5, 16. https://doi.org/10.5334/cstp.283 (2020).Article 

Google Scholar 
van der Wal, R., Sharma, N., Mellish, C., Robinson, A. & Siddharthan, A. The role of automated feedback in training and retaining biological recorders for citizen science. Conserv. Biol. 30, 550–561. https://doi.org/10.1111/cobi.12705 (2016).Article 
PubMed 

Google Scholar 
Bloom, E. H. & Crowder, D. W. Promoting data collection in pollinator citizen science projects. Citiz. Sci.: Theory Pract. 5, 3. https://doi.org/10.5334/cstp.217 (2020).Article 

Google Scholar 
Johnston, A., Fink, D., Hochachka, W. M. & Kelling, S. Estimates of observer expertise improve species distributions from citizen science data. Methods Ecol. Evol. 9, 88–97. https://doi.org/10.1111/2041-210x.12838 (2018).Article 

Google Scholar 
Kelling, S. et al. Using semistructured surveys to improve citizen science data for monitoring biodiversity. Bioscience 69, 170–179. https://doi.org/10.1093/biosci/biz010 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Koen, B., Loosveldt, G., Vandenplas, C. & Stoop, I. Response rates in the european social survey: Increasing, decreasing, or a matter of fieldwork efforts?. Surv. Methods: Insights Field https://doi.org/10.13094/SMIF-2018-00003 (2018).Article 

Google Scholar 
Gideon, L. Handbook of Survey Methodology for the Social Sciences (Springer, 2012).Book 

Google Scholar 
Wolf, C., Joye, D., Smith, T. W. & Fu, Y. C. The SAGE Handbook of Survey Methodology (SAGE Publications Ltd, 2016).Book 

Google Scholar 
Richter, A. et al. Motivation and support services in citizen science insect monitoring: A cross-country study. Biol. Conserv. 263, 109325. https://doi.org/10.1016/j.biocon.2021.109325 (2021).Article 

Google Scholar 
Johnston, A., Moran, N., Musgrove, A., Fink, D. & Baillie, S. R. Estimating species distributions from spatially biased citizen science data. Ecol. Model. https://doi.org/10.1016/j.ecolmodel.2019.108927 (2020).Article 

Google Scholar 
Isaac, N. J. B., van Strien, A. J., August, T. A., de Zeeuw, M. P. & Roy, D. B. Statistics for citizen science: Extracting signals of change from noisy ecological data. Methods Ecol. Evol. 5, 1052–1060. https://doi.org/10.1111/2041-210x.12254 (2014).Article 

Google Scholar 
Liao, H.-I., Yeh, S.-L. & Shimojo, S. Novelty vs. familiarity principles in preference decisions: Task context of past experience matters. Front. Psychol. https://doi.org/10.3389/fpsyg.2011.00043 (2011).Article 
PubMed 
PubMed Central 

Google Scholar 
Park, J., Shimojo, E. & Shimojo, S. Roles of familiarity and novelty in visual preference judgments are segregated across object categories. Proc. Natl. Acad. Sci. U.S.A. 107, 14552–14555. https://doi.org/10.1073/pnas.1004374107 (2010).ADS 
Article 
PubMed 

Google Scholar 
Tiago, P., Gouveia, M. J., Capinha, C., Santos-Reis, M. & Pereira, H. M. The influence of motivational factors on the frequency of participation in citizen science activities. Nat. Conserv.-Bulg. https://doi.org/10.3897/natureconservation.18.13429 (2017).Article 

Google Scholar 
Davis, A., Taylor, C. E. & Martin, J. M. Are pro-ecological values enough? Determining the drivers and extent of participation in citizen science programs. Hum. Dimens. Wildl. 24, 501–514. https://doi.org/10.1080/10871209.2019.1641857 (2019).Article 

Google Scholar 
Bell, S. et al. What counts? Volunteers and their organisations in the recording and monitoring of biodiversity. Biodivers. Conserv. 17, 3443–3454. https://doi.org/10.1007/s10531-008-9357-9 (2008).Article 

Google Scholar 
Toomey, A. H. & Domroese, M. C. Can citizen science lead to positive conservation attitudes and behaviors?. Hum. Ecol. Rev. 20, 50–62 (2013).Article 

Google Scholar 
Dennis, E. B., Morgan, B. J. T., Brereton, T. M., Roy, D. B. & Fox, R. Using citizen science butterfly counts to predict species population trends. Conserv. Biol. 31, 1350–1361. https://doi.org/10.1111/cobi.12956 (2017).Article 
PubMed 

Google Scholar 
Callaghan, C. T., Poore, A. G. B., Major, R. E., Rowley, J. J. L. & Cornwell, W. K. Optimizing future biodiversity sampling by citizen scientists. Proc. R. Soc. B-Biol. Sci. https://doi.org/10.1098/rspb.2019.1487 (2019).Article 

Google Scholar 
Outhwaite, C. L., Gregory, R. D., Chandler, R. E., Collen, B. & Isaac, N. J. B. Complex long-term biodiversity change among invertebrates, bryophytes and lichens. Nat. Ecol. Evol. 4, 384. https://doi.org/10.1038/s41559-020-1111-z (2020).Article 
PubMed 

Google Scholar 
Bowler, D. E. et al. Winners and losers over 35 years of dragonfly and damselfly distributional change in Germany. Divers. Distrib. https://doi.org/10.1111/ddi.13274 (2021).Article 

Google Scholar  More

A strawberry poison-dart frog (Oophaga pumilio) in Guatemala. Biodiversity is at risk as talks on a deal to protect it founder.Credit: Yuri Cortez/AFP via Getty

Some conservation scientists are warning that a global deal to protect the environment is under threat after negotiations stalled during international talks in Nairobi last week. They are calling on global leaders to rescue the talks — and biodiversity — from the brink. Others are more hopeful that, although progress has been slow, a deal will be struck by the end of the year.Negotiators from around 200 countries that have signed up to the United Nations Convention on Biological Diversity (CBD) met in Nairobi from 21 to 26 June to thrash out key details of the deal, known as the post-2020 global biodiversity framework. But the talks made such little progress that many scientists are worried that nations will be unable to finalize the deal at the UN biodiversity summit in Montreal, Canada, in December. A key sticking point is how much funding rich nations will provide to low-income nations. Failure to agree on the framework at this summit — the 15th meeting of the Conference of the Parties (COP15) — will be devastating for the natural world, they say.“This is a huge missed opportunity and puts the framework in jeopardy,” says Brian O’Donnell, director of the Campaign for Nature in Washington DC, a partnership of private charities and conservation organizations advocating a deal to safeguard biodiversity.The framework consists of 4 broad goals, including reining in species extinction, and 21 targets — most of them quantitative — such as protecting at least 30% of the world’s land and seas. Without a deal, estimates say, one million plant and animal species could go extinct in the next few decades because of climate change, disease and human actions, among other triggers.Researchers were relieved when the CBD announced earlier this month that COP15 would take place in Montreal instead of Kunming, China, where lockdowns to quash SARS-CoV-2 infections could have prevented the meeting. The COVID-19 pandemic has already delayed in-person CBD meetings for two years, and threatened to derail the summit.Stalling tacticsSome conservation groups said that a few nations bore most of the responsibility for impeding progress. Marco Lambertini, head of conservation organization WWF International, based in Gland, Switzerland, referred in a statement to “a small number of countries, Brazil first and foremost, that are actively working to undermine the talks”.Others who were at the conference spoke on the condition of anonymity because parts of the negotiations are confidential. They say that Brazil asked for changes to the text simply to slow down the process, and argued against essential elements.Nature contacted representatives of Brazil for a response but did not receive a reply by the time of publication.Francis Ogwal, co-chair of the framework negotiations working group, acknowledged that the talks had not advanced as much as had been hoped. But he is buoyed by some headway gained on targets to improve access to nature in urban areas and to increase scientific and technological capacity in lower-income nations. Ogwal is hopeful that countries will iron out further differences at an extra meeting scheduled for just days before COP15.“There are still some big disagreements. We are not yet at the level we expected. But come December, we shall have a framework in good shape,” Ogwal told reporters at a press briefing on 26 June.Lack of leadershipBut scientists and conservation groups say political leadership is urgently needed to save the deal. In an open letter to UN secretary-general António Guterres and heads of state of CBD member nations, a group of eight organizations that support conservation and Indigenous people’s rights said that a lack of management is stalling the negotiations.“There is a notable absence of the high level political engagement, will and leadership to drive through compromise and to guide and inspire the commitments that are required,” the letter says.Some countries have restated that they back the biodiversity talks. On 26 June, UK Prime Minister Boris Johnson assured Canadian Prime Minister Justin Trudeau of his support for the December summit in Montreal. The two were speaking before the meeting of the G7 group of industrialized nations in Krün, Germany.In addition, some “hero” countries including Costa Rica and Columbia worked particularly hard in Nairobi to drive agreement, says O’Donnell.Speaking on condition of anonymity so as not to offend the CBD, others criticized the structure and organization of the Nairobi meeting, which they say didn’t help negations to move forwards. “The session facilitators were not able to shepherd negotiations towards consensus,” they say. Nature contacted the CBD for a response but did not hear back in time for publication.But despite the setbacks, some scientists are still hopeful that countries can strike a deal. “The negotiations are typically well-spirited. There is even a sense of collaboration arising,” says Juha Siikamäki, chief economist at the International Union for Conservation of Nature in Gland, who attended the Nairobi meeting.Elizabeth Mrema, executive secretary of the CBD, says countries will have to compromise. “Biodiversity is too important to fail,” she says. More

Mangrove forests thrive along tropical and subtropical shorelines and their distribution extends to warm temperate regions1. They are globally recognized for the valuable ecosystem services they provide2 but are expected to be substantially influenced by climate change-related physical processes in the future3,4. Under warming winter temperatures, poleward expansion is predicted for mangroves5,6, with potential implications for ecosystem structure and functioning, as well as human livelihoods and well-being7,8. The global distribution, abundance and species richness of mangroves is governed by a broad range of biotic and environmental factors, including temperature and precipitation9 and diverse geomorphological and hydrological gradients10. Climate and aspects related to coastal geography (for example, floodplain area) determine the availability of suitable habitat for establishment11,12. However, the potential for mangroves to track changing environmental conditions and expand their distributions ultimately depends on dispersal11,13. The importance of dispersal in controlling mangrove distributions has been demonstrated by mangrove distributional responses to historical climate variability14, past mangrove (re)colonization of oceanic islands15 and from the long-term survival of mangrove seedlings planted beyond natural range limits16. As such, quantifying changes in the factors that influence dispersal is important for understanding climate-driven distributional responses of mangroves under future climate conditions.In mangroves, dispersal is accomplished by buoyant seeds and fruits (hereafter referred to as ‘propagules’). In combination with prevailing currents, the spatial scale of this process, ranging from local retention to transoceanic dispersal over thousands of kilometres13, is determined by propagule buoyancy17, that is, the density difference between that of propagules and the surrounding water. Hence, the course of dispersal trajectories for propagules from these species depends on the interaction between spatiotemporal changes in both propagule density and that of the surrounding water, rendering this process sensitive to climate-driven changes in coastal and open-ocean water properties. The biogeographic implications of such density differences were recognized more than a century ago by Henry Brougham Guppy, who discussed18 ‘the far-reaching influence on plant-distribution and on plant-development that the relation between the specific weight of seeds and fruits and the density of sea-water must possess’.Since the time of Guppy’s early observations, climate change from human activities has driven pronounced changes in ocean temperature and salinity, with further changes predicted throughout the twenty-first century19. Ocean density is a nonlinear function of temperature, salinity and pressure20; therefore, these changes may influence dispersal patterns of mangrove propagules by altering their buoyancy and floating orientation. As Guppy noted18, ‘[for] plants whose seeds or fruits are not much lighter than seawater […] the effect of increased density of the water is to extend the flotation period’ or ‘to increase the number that floated for a given period’. Guppy also reported that the seedlings of the widespread mangrove genera Rhizophora and Bruguiera present exceptional examples of propagules with densities somewhere between seawater and freshwater18. Previous studies of the impacts of climate change on mangroves have focused on factors such as sea level rise, altered precipitation regimes and increasing temperature and storm frequency4,21,22,23 but the potential impact of climate-driven changes in seawater properties on mangroves has not yet been examined. This is somewhat surprising, as the ocean is the primary dispersal medium of this ‘sea-faring’ coastal vegetation and dispersal is a key process that governs a species’ response to climate change by changing its geographical range. This knowledge gap contrasts with recent efforts to expose links between climate change and dispersal in other ecologically important marine taxa such as zooplankton and fish species24,25,26,27.In this study, we investigate predicted changes in sea surface temperature (SST), sea surface salinity (SSS) and sea surface density (SSD) for coastal waters bordering mangrove forests (hereafter referred to as ‘coastal mangrove waters’), over the next century. Using a biogeographic classification system for coastal and shelf areas28, we examine spatiotemporal changes in these surface ocean properties, with a particular focus on the world’s two major mangrove diversity hotspots: (1) the Atlantic East Pacific (AEP) region, including all of the Americas, West and Central Africa and (2) the Indo West Pacific (IWP) region, extending from East Africa eastwards to the islands of the central Pacific1. Finally, we synthesize available data on the density of mangrove propagules for different mangrove species and explore the potential impact of climate-driven changes in SSD on propagule dispersal.To assess changes in SST and SSS throughout the global range of mangrove forests, we used present (2000–2014) and future (2090–2100) surface ocean properties from the Bio-ORACLE database29,30. SSD estimates were derived from these variables using the UNESCO EOS-80 equation of state polynomial for seawater31. Changes in SST, SSS and SSD (Fig. 1) were calculated for four representative concentration pathways (RCPs) and derived for coastal waters closest to the 583,578 polygon centroids from the 2015 Global Mangrove Watch (GMW) database32. After removing duplicates, our dataset contained 10,108 unique mangrove occurrence locations, with corresponding present conditions and predicted future changes in mean SST, SSS and SSD. Under the low-warming scenario RCP 2.6, mean SST of coastal mangrove waters is predicted to change by +0.64 (±0.11) °C and mean SSS by −0.06 (±0.25) practical salinity units (PSU). Combined, this results in an average change in mean SSD of −0.25 (±0.20) kg m−3 in coastal mangrove waters by the late twenty-first century (Supplementary Table 1). These values roughly double under RCP 4.5 (Supplementary Table 2), while under RCP 6.0, a change of +1.69 (±0.14) °C in mean SST, −0.21 (±0.42) PSU in mean SSS and −0.71 (±0.32) kg m−3 in mean SSD is predicted (Supplementary Table 3). Under RCP 8.5, our study predicts a change in SST of +2.84 (±0.21) °C (range 2.11–4.01 °C), a change in SSS of −0.30 (±0.74) PSU (−2.01–1.26 PSU) and a corresponding change in SSD of −1.17 (±0.56) kg m−3 (−2.53–0.03 kg m−3) (Supplementary Table 4).Fig. 1: Global map showing the change in sea surface variables across mangrove bioregions under RCP 8.5.a–c, Change in SST (a), SSS (b) and SSD (c). Changes in SST and SSS are based on present-day (2000–2014) and future (2090–2100) marine fields from the Bio-ORACLE database29,30, from which SSD data were derived. The vertical line (19° E) separates the two major mangrove bioregions: the AEP and IWP.Full size imageSpatial variability in predicted surface ocean property changes was examined by considering the two major mangrove bioregions (AEP and IWP) (Fig. 2) and using the Marine Ecoregions of the World (MEOW) biogeographic classification28 (Fig. 3). Both the range and changes in mean SST were comparable for the AEP and IWP mangrove bioregions, for all respective RCP scenarios (Fig. 2a and Supplementary Tables 1–4). Under RCP 8.5, mean SST in both mangrove bioregions is predicted to warm ~2.8 °C by 2100, which is roughly 4.5 times the predicted increase in mean SST under RCP 2.6 (Supplementary Tables 1 and 4). Predictions for the RCP 8.5 scenario are generally consistent with reported global ocean temperature trends33 and show that the greatest warming occurs in coastal waters near the Galapagos Islands (change in mean SST of 3.92 ± 0.06 °C). Pronounced SST increases are also predicted for Hawaii (change in mean SST of 3.36 ± 0.05 °C), the Southeast Australian Shelf (3.30 ± 0.25 °C), Northern and Southern New Zealand (3.25 ± 0.07 °C and 3.34 ± 0.02 °C, respectively), Warm Temperate Northwest Pacific (3.27 ± 0.16 °C), the Red Sea and Gulf of Aden (3.24 ± 0.08 °C), Somali/Arabian Coast (3.23 ± 0.15 °C), South China Sea (3.07 ± 0.10 °C), the Tropical East Pacific (3.09 ± 0.15 °C) and the Warm Temperate Northwest Atlantic (3.14 ± 0.13 °C) (Fig. 3b and Supplementary Tables 4).Fig. 2: Change in surface ocean properties for coastal waters bordering mangrove forests and in the two major mangrove bioregions, the AEP and IWP, for different RCPs.a–c, Variation in SST (a), SSS (b) and SSD (c) under various RCP scenarios. Grey indicates global distribution (n = 10,108), orange denotes AEP (n = 3,190) and green represents IWP (n = 6,918). Data for SST and SSS consist of present-day (2000–2014) and future (2090–2100) marine fields from the Bio-ORACLE database29,30, from which SSD data were derived. The cat-eye plots50 show the distribution of the data. Median and mean values are indicated with black and white circles, respectively, and the vertical lines represent the interquartile range.Full size imageFig. 3: Global spatial variability in SST, SSS and SSD for coastal waters bordering mangrove forests under RCP 8.5.a, Global map showing the provinces (colour code and numbers) from the MEOW database28 used to investigate spatial patterns in mangrove coastal ocean water changes by 2100. b–d, Longitudinal gradient of the change in SST (b), SSS (c) and SSD (d) under RCP 8.5 in the AEP and the IWP mangrove bioregions; circles are coloured according to the MEOW province in which respective mangrove sites are located.Full size imagePredicted SSS changes exhibit an opposite trend in the AEP and IWP bioregions, with increased salinity in the AEP and reduced salinity in the IWP under global warming (RCP 2.6–RCP 8.5; Fig. 2b); this is reflected in contrasting SSD changes in both mangrove bioregions (Fig. 2c) and associated with predicted global changes in precipitation, with extensions of the rainy season over most of the monsoon domains, except for the American monsoon34. Under RCP 8.5, the spatially averaged change in mean SSS is +0.51 (±0.57) PSU in the AEP and −0.68 (±0.44) PSU in the IWP region. The maximum decrease in mean SSS (−2.01 PSU) is predicted for the Gulf of Guinea in the AEP bioregion (Fig. 3c and Supplementary Table 4). Within the IWP, the Western Indian Ocean region shows little or no changes in SSS, which contrasts with the pronounced freshening trends predicted in the eastern part of this ocean basin and the Tropical West Pacific (Figs. 1b and 3c). Increased freshening is predicted in the Bay of Bengal (SSS change: −1.17 ± 0.43 PSU), the Sunda Shelf (SSS change: −1.21 ± 0.29 PSU) and the Western Coral Triangle province (mean SSS change: −0.80 ± 0.17 PSU) (Fig. 3c and Supplementary Table 4). Within the AEP, salinity increases exceed +0.96 PSU in the Tropical Northwestern Atlantic, +0.80 in the Warm Temperate Northwest Atlantic and +0.68 in the West African Transition (Fig. 3c and Supplementary Table 4). The spatial heterogeneity in SSS across the global range of mangrove forests corresponds with observed changes in SSS35. Trends in SSD (Fig. 3d) strongly track changes in SSS (Fig. 3c) rather than SST. All RCP scenarios predict an overall decrease in SSD for both mangrove bioregions; however, the predicted decrease in SSD in the IWP region was a factor of 2 (RCP 6.0) and 2.5 (RCP 2.6, RCP 4.5 and RCP 8.5) stronger than in the AEP (Figs. 2 and 3d and Supplementary Tables 1–4).Propagule density values from our literature survey range from 1,080 kg m−3 for different mangrove species (Fig. 4 and Supplementary Table 5). The low densities reported for Heritiera littoralis propagules provide a strong contrast with the near-seawater propagule densities reported for Avicennia and members of the Rhizophoraceae (Bruguiera, Rhizophora and Ceriops). Floating characteristics of the latter may be particularly sensitive to changes in SSD. To illustrate the potential influence of changing ocean conditions on mangrove propagule dispersal, we considered threshold water density values (1,020 and 1,022 kg m−3) that are within the range where elongated propagules of important mangrove genera tend to change floating orientation (Fig. 4a). More specifically, we determined the ocean surface area with an SSD below or equal to these thresholds under different climate change scenarios (Fig. 5). Under RCP 8.5, the ocean surface covered by mangrove coastal waters (coastal waters bordering present mangrove forests) with a density ≤1,020 kg m−3 increases ~27% by 2100, notably more so in the IWP (~37%) than in the AEP (~6%) (Supplementary Table 6). A threshold of 1,022 kg m−3 results in increases of roughly +11% (global), +12% (IWP) and +8% (AEP) (Supplementary Table 7). Similar spatial patterns are observed for open-ocean waters within the global latitudinal range of mangroves (Fig. 5 and Supplementary Figs. 1 and 2).Fig. 4: Potential effect of future declines in SSD on mangrove propagule dispersal.a, Range of reported propagule density values for wide-ranging mangrove species and present and future range of SSD for coastal waters along the range of those mangrove species. Mangrove propagule data are extracted from the literature (Supplementary Table 5). H. lit, Heritiera littoralis; X. gra, Xylocarpus granatum; A. ger, Avicennia germinans; A. mar, Avicennia marina; B. gym, Bruguiera gymnorrhiza; C. tag, Ceriops tagal; R. man, Rhizophora mangle; R. muc, Rhizophora mucronata. Bottom part adapted from ref. 51. b, Conceptual figure of the potential effects of ocean warming and freshening on mangrove propagule dispersal. Ocean warming and freshening drive changes in SSD and may reduce the timeframe for opportunistic colonization. For a propagule with a specific density and floating profile under present surface ocean conditions, reduced SSD of coastal and open-ocean waters may reduce floatation time (shaded area) and hence, reduce the proportion of long-distance dispersers. For simplicity, the density of propagules is assumed to increase linearly over time, although the actual increase may be nonlinear.Full size imageFig. 5: Future changes in SSD.a–d, Spatial extent of coastal and open-ocean surface waters with a density ≤1,020 kg m−3 (a,b) and 1,022 kg m−3 (c,d), for present (2000–2014) (a,c) and future (2090–2100; RCP 8.5) (b,d) scenarios. Data are shown for surface ocean waters within the global latitudinal range of mangrove forests (between 32° N and 38° S). The two density thresholds considered are within the range of densities at which mangrove propagule buoyancy and floating orientation of several mangrove genera change, as reported in available literature. Black dots along the coast represent the global mangrove extent from the 2015 GMW dataset32. Magenta-coloured circles represent SSD values More

McClain ME, Boyer EW, Dent CL, Gergel SE, Grimm NB, Groffman PM, et al. Biogeochemical hot spots and hot moments at the interface of terrestrial and aquatic ecosystems. Ecosystems. 2003;6:301–12.CAS 
Article 

Google Scholar 
Borch T, Kretzschmar R, Kappler A, Van Cappellen P, Ginder-Vogel M, Voegelin A, et al. Biogeochemical redox processes and their impact on contaminant dynamics. Environ Sci Technol. 2010;44:15–23.CAS 
Article 

Google Scholar 
Stegen JC, Lin XJ, Konopka AE, Fredrickson JK. Stochastic and deterministic assembly processes in subsurface microbial communities. ISME J. 2012;6:1653–64.CAS 
Article 

Google Scholar 
Dini-Andreote F, Stegen JC, van Elsas JD, Salles JF. Disentangling mechanisms that mediate the balance between stochastic and deterministic processes in microbial succession. Proc Natl Acad Sci USA. 2015;112:E1326–32.CAS 
Article 

Google Scholar 
Behrendt L, Larkum AWD, Trampe E, Norman A, Sorensen SJ, Kuhl M. Microbial diversity of biofilm communities in microniches associated with the didemnid ascidian Lissoclinum patella. ISME J. 2012;6:1222–37.CAS 
Article 

Google Scholar 
Becker KW, Elling FJ, Schroder JM, Lipp JS, Goldhammer T, Zabel M, et al. Isoprenoid quinones resolve the stratification of redox processes in a biogeochemical continuum from the photic zone to deep anoxic sediments of the Black Sea. Appl Environ Microbiol. 2018;84:e02736–17.CAS 
Article 

Google Scholar 
Locey KJ, Muscarella ME, Larsen ML, Bray SR, Jones SE, Lennon JT. Dormancy dampens the microbial distance-decay relationship. Phil Trans R Soc B. 2020;375:20190243.CAS 
Article 

Google Scholar 
Blagodatskaya E, Kuzyakov Y. Active microorganisms in soil: critical review of estimation criteria and approaches. Soil Biol Biochem. 2013;67:192–211.CAS 
Article 

Google Scholar 
Meyer KM, Memiaghe H, Korte L, Kenfack D, Alonso A, Bohannan BJM. Why do microbes exhibit weak biogeographic patterns? ISME J. 2018;12:1404–13.Article 

Google Scholar 
Xue R, Zhao KK, Yu XL, Stirling E, Liu S, Ye SD, et al. Deciphering sample size effect on microbial biogeographic patterns and community assembly processes at centimeter scale. Soil Biol Biochem. 2021;156:108218.CAS 
Article 

Google Scholar 
Morriss A, Meyer K, Bohannan B. Linking microbial communities to ecosystem functions: what we can learn from genotype-phenotype mapping in organisms. Phil Trans R Soc B. 2020;375:20190244.Article 

Google Scholar 
Armitage DW, Jones SE. How sample heterogeneity can obscure the signal of microbial interactions. ISME J. 2019;13:2639–46.Article 

Google Scholar 
Dini-Andreote F, Kowalchuk GA, Prosser JI, Raaijmakers JM. Towards meaningful scales in ecosystem microbiome research. Environ Microbiol. 2021;23:1–4.Article 

Google Scholar 
Meyerhof MS, Wilson JM, Dawson MN, Beman JM. Microbial community diversity, structure and assembly across oxygen gradients in meromictic marine lakes, Palau. Environ Microbiol. 2016;18:4907–19.CAS 
Article 

Google Scholar 
Zhou ZC, Meng H, Liu Y, Gu JD, Li M. Stratified bacterial and archaeal community in mangrove and intertidal wetland mudflats revealed by high throughput 16S rRNA gene sequencing. Front Microbiol. 2017;8:02148.Article 

Google Scholar 
Gutierrez-Preciado A, Saghai A, Moreira D, Zivanovic Y, Deschamps P, Lopez-Garcia P. Functional shifts in microbial mats recapitulate early Earth metabolic transitions. Nat Ecol Evol. 2018;2:1700–8.Article 

Google Scholar 
Louca S, Parfrey LW, Doebeli M. Decoupling function and taxonomy in the global ocean microbiome. Science. 2016;353:1272–7.CAS 
Article 

Google Scholar 
Murase J, Frenzel P. A methane-driven microbial food web in a wetland rice soil. Environ Microbiol. 2007;9:3025–34.CAS 
Article 

Google Scholar 
Reim A, Lüke C, Krause S, Pratscher J, Frenzel P. One millimetre makes the difference: high-resolution analysis of methane-oxidizing bacteria and their specific activity at the oxic-anoxic interface in a flooded paddy soil. ISME J. 2012;6:2128–39.CAS 
Article 

Google Scholar 
Peiffer S, Kappler A, Haderlein SB, Schmidt C, Byrne JM, Kleindienst S, et al. A biogeochemical–hydrological framework for the role of redox-active compounds in aquatic systems. Nat Geosci. 2021;14:264–72.CAS 
Article 

Google Scholar  More