Philippa Kaur

1.Rothschild, L. J. & Mancinelli, R. L. Life in extreme environments. Nature 409, 1092–1101 (2001).CAS 
PubMed 

Google Scholar 
2.Schmid, A. K., Allers, T. & DiRuggiero, J. Snapshot: microbial extremophiles. Cell 180, 818–818.e1 (2020).CAS 
PubMed 

Google Scholar 
3.Denef, V. J., Mueller, R. S. & Banfield, J. F. AMD biofilms: using model communities to study microbial evolution and ecological complexity in nature. ISME J. 4, 599–610 (2010).PubMed 

Google Scholar 
4.Inskeep, W. P. et al. The YNP metagenome project: environmental parameters responsible for microbial distribution in the Yellowstone geothermal ecosystem. Front. Microbiol. 4, 67 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
5.Oren, A. Halophilic microbial communities and their environments. Curr. Opin. Microbiol. 33, 119–124 (2015).CAS 

Google Scholar 
6.Reysenbach, A. L., Wickham, G. S. & Pace, N. R. Phylogenetic analysis of the hyperthermophilic pink filament community in Octopus Spring, Yellowstone National Park. Appl. Environ. Microbiol. 60, 2113–2119 (1994).CAS 
PubMed 
PubMed Central 

Google Scholar 
7.Bond, P. L., Smriga, S. P. & Banfield, J. F. Phylogeny of microorganisms populating a thick, subaerial, predominantly lithotrophic biofilm at an extreme acid mine drainage site. Appl. Environ. Microbiol. 66, 3842–3849 (2000).CAS 
PubMed 
PubMed Central 

Google Scholar 
8.Huber, J. A. et al. Microbial population structures in the deep marine biosphere. Science 318, 97–100 (2007).CAS 
PubMed 

Google Scholar 
9.Kuang, J. L. et al. Contemporary environmental variation determines microbial diversity patterns in acid mine drainage. ISME J. 7, 1038–1050 (2013).CAS 
PubMed 

Google Scholar 
10.Power, J. F. et al. Microbial biogeography of 925 geothermal springs in New Zealand. Nat. Commun. 9, 2876 (2018). Extensive sampling and high-throughput 16S rRNA gene sequencing have provided deeper insights into the patterns and ecological drivers of microbial communities inhabiting geothermal springs.PubMed 
PubMed Central 

Google Scholar 
11.Podell, S. et al. Seasonal fluctuations in ionic concentrations drive microbial succession in a hypersaline lake community. ISME J. 8, 979–990 (2014).CAS 
PubMed 

Google Scholar 
12.Chen, L. X. et al. Comparative metagenomic and metatranscriptomic analyses of microbial communities in acid mine drainage. ISME J. 9, 1579–1592 (2015).PubMed 

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

Google Scholar 
14.Brown, C. T. et al. Unusual biology across a group comprising more than 15% of domain Bacteria. Nature 523, 208–211 (2015).CAS 
PubMed 

Google Scholar 
15.Castelle, C. J. et al. Genomic expansion of domain archaea highlights roles for organisms from new phyla in anaerobic carbon cycling. Curr. Biol. 25, 690–701 (2015). The cultivation-independent reconstruction of the first complete genomes for members of the DPANN archaea allowed confident prediction of incomplete or absent pathways for these enigmatic organisms.CAS 
PubMed 

Google Scholar 
16.Sharp, C. E. et al. Humboldt’s spa: microbial diversity is controlled by temperature in geothermal environments. ISME J. 8, 1166–1174 (2014).CAS 
PubMed 
PubMed Central 

Google Scholar 
17.Hedlund, B. P. et al. Uncultivated thermophiles: current status and spotlight on ‘Aigarchaeota’. Curr. Opin. Microbiol. 25, 136–145 (2015).CAS 
PubMed 

Google Scholar 
18.Hua, Z. S. et al. Ecological roles of dominant and rare prokaryotes in acid mine drainage revealed by metagenomics and metatranscriptomics. ISME J. 9, 1280–1294 (2015).CAS 
PubMed 

Google Scholar 
19.Tyson, G. W. et al. Community structure and metabolism through reconstruction of microbial genomes from the environment. Nature 428, 37–43 (2004). This is the first shotgun metagenomic sequencing study that enabled reconstruction of near-complete microbial genomes directly (without cultivation) from a natural community.CAS 
PubMed 

Google Scholar 
20.Castelle, C. J. & Banfield, J. F. Major new microbial groups expand diversity and alter our understanding of the tree of life. Cell 172, 1181–1197 (2018).CAS 
PubMed 

Google Scholar 
21.Chen, L. X. et al. Metabolic versatility of small archaea Micrarchaeota and Parvarchaeota. ISME J. 12, 756–775 (2018).CAS 
PubMed 

Google Scholar 
22.Baker, B. J. et al. Enigmatic, ultrasmall, uncultivated Archaea. Proc. Natl Acad. Sci. USA 107, 8806–8811 (2010).CAS 
PubMed 
PubMed Central 

Google Scholar 
23.Narasingarao, P. et al. De novo metagenomic assembly reveals abundant novel major lineage of Archaea in hypersaline microbial communities. ISME J. 6, 81–93 (2012).CAS 
PubMed 

Google Scholar 
24.Brock, T. D. Life at high temperatures. Science 158, 1012–1019 (1967).CAS 
PubMed 

Google Scholar 
25.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 
26.Colman, D. R. et al. Ecological differentiation in planktonic and sediment-associated chemotrophic microbial populations in Yellowstone hot springs. FEMS Microbiol. Ecol. 92, fiw137 (2016).PubMed 

Google Scholar 
27.Ward, D. M. et al. 16S rRNA sequences reveal numerous uncultured microorganisms in a natural community. Nature 345, 63–65 (1990).CAS 
PubMed 

Google Scholar 
28.Miller, S. R. et al. Bar-coded pyrosequencing reveals shared bacterial community properties along the temperature gradients of two alkaline hot springs in Yellowstone National Park. Appl. Environ. Microbiol. 75, 4565–4572 (2009).CAS 
PubMed 
PubMed Central 

Google Scholar 
29.Ward, L. et al. Microbial community dynamics in Inferno Crater Lake, a thermally fluctuating geothermal spring. ISME J. 11, 1158–1167 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
30.Barns, S. M., Fundyga, R. E., Jeffries, M. W. & Pace, N. R. Remarkable archaeal diversity detected in a Yellowstone National Park hot spring environment. Proc. Natl Acad. Sci. USA 91, 1609–1613 (1994).CAS 
PubMed 
PubMed Central 

Google Scholar 
31.Takai, K. & Yoshihiko, S. A molecular view of archaeal diversity in marine and terrestrial hot water environments. FEMS Microbiol. Ecol. 28, 177–188 (1999).CAS 

Google Scholar 
32.Elkins, J. G. et al. A korarchaeal genome reveals insights into the evolution of the Archaea. Proc. Natl Acad. Sci. USA 105, 8102–8107 (2008).CAS 
PubMed 
PubMed Central 

Google Scholar 
33.Dombrowski, N., Teske, A. P. & Baker, B. J. Expansive microbial metabolic versatility and biodiversity in dynamic Guaymas Basin hydrothermal sediments. Nat. Commun. 9, 4999 (2018).PubMed 
PubMed Central 

Google Scholar 
34.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 
35.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 (2011).CAS 
PubMed 

Google Scholar 
36.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 
37.Hua, Z. S. et al. Genomic inference of the metabolism and evolution of the archaeal phylum Aigarchaeota. Nat. Commun. 9, 2832 (2018).PubMed 
PubMed Central 

Google Scholar 
38.Takami, H. et al. A deeply branching thermophilic bacterium with an ancient acetyl-CoA pathway dominates a subsurface ecosystem. PLoS ONE 7, e30559 (2012).CAS 
PubMed 
PubMed Central 

Google Scholar 
39.Colman, D. R. et al. Novel, deep-branching heterotrophic bacterial populations recovered from thermal spring metagenomes. Front. Microbiol. 7, 304 (2016).PubMed 
PubMed Central 

Google Scholar 
40.Nobu, M. et al. Phylogeny and physiology of candidate phylum ‘Atribacteria’ (OP9/JS1) inferred from cultivation-independent genomics. ISME J. 10, 273–286 (2016).CAS 
PubMed 

Google Scholar 
41.Hugenholtz, P., Pitulle, C., Hershberger, K. L. & Pace, N. R. Novel division level bacterial diversity in a Yellowstone hot spring. J. Bacteriol. 180, 366–376 (1998).CAS 
PubMed 
PubMed Central 

Google Scholar 
42.Orcutt, B. N., Sylvan, J. B., Knab, N. J. & Edwards, K. J. Microbial ecology of the dark ocean above, at, and below the seafloor. Microbiol. Mol. Biol. Rev. 75, 361–422 (2011).CAS 
PubMed 
PubMed Central 

Google Scholar 
43.Eloe-Fadrosh, E. A. et al. Global metagenomic survey reveals a new bacterial candidate phylum in geothermal springs. Nat. Commun. 7, 10476 (2016). This is a good example of how analysis of the increasing wealth of metagenomic data collected from diverse environments may lead to the discovery of novel major lineages.CAS 
PubMed 
PubMed Central 

Google Scholar 
44.Kelley, D. S., Baross, J. A. & Delaney, J. R. Volcanoes, fluids, and life at Mid-Ocean Ridge spreading centers. Annu. Rev. Earth Planet. Sci. 30, 385–491 (2002).CAS 

Google Scholar 
45.Perner, M. et al. In situ chemistry and microbial community compositions in five deep-sea hydrothermal fluid samples from Irina II in the Logatchev field. Environ. Microbiol. 15, 1551–1560 (2013).CAS 
PubMed 

Google Scholar 
46.Flores, G. E. et al. Microbial community structure of hydrothermal deposits from geochemically different vent fields along the Mid-Atlantic Ridge. Environ. Microbiol. 13, 2158–2171 (2011).CAS 
PubMed 

Google Scholar 
47.Dick, G. J. et al. The microbiomes of deep-sea hydrothermal vents: distributed globally, shaped locally. Nat. Rev. Microbiol. 17, 271–283 (2019).CAS 
PubMed 

Google Scholar 
48.Campbell, B. J., Summers Engel, A., Porter, M. L. & Takai, K. The versatile ε-proteobacteria: key players in sulphidic habitats. Nat. Rev. Microbiol. 4, 458–468 (2006).CAS 
PubMed 

Google Scholar 
49.Reysenbach, A. L., Longnecker, K. & Kirshtein, J. Novel bacterial and archaeal lineages from an in situ growth chamber deployed at a Mid-Atlantic Ridge hydrothermal vent. Appl. Environ. Microbiol. 66, 3798–3806 (2000).CAS 
PubMed 
PubMed Central 

Google Scholar 
50.Takai, K., Komatsu, T., Inagaki, F. & Horikoshi, K. Distribution of archaea in a black smoker chimney structure. Appl. Environ. Microbiol. 67, 3618–3629 (2001).CAS 
PubMed 
PubMed Central 

Google Scholar 
51.Schrenk, M. O., Kelley, D. S., Bolton, S. A. & Baross, J. A. Low archaeal diversity linked to subseafloor geochemical processes at the Lost City Hydrothermal Field, Mid-Atlantic Ridge. Environ. Microbiol. 6, 1086–1095 (2004).CAS 
PubMed 

Google Scholar 
52.Brazelton, W. J., Schrenk, M. O., Kelley, D. S. & Baross, J. A. Methane- and sulfur-metabolizing microbial communities dominate the Lost City Hydrothermal Field ecosystem. Appl. Environ. Microbiol. 72, 6257–6270 (2006).CAS 
PubMed 
PubMed Central 

Google Scholar 
53.Reveillaud, J. et al. Subseafloor microbial communities in hydrogen-rich vent fluids from hydrothermal systems along the Mid-Cayman Rise. Environ. Microbiol. 18, 1970–1987 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
54.Brazelton, W. J. et al. Archaea and bacteria with surprising micro-diversity show shifts in dominance over 1000-year time scales in hydrothermal chimneys. Proc. Natl Acad. Sci. USA 107, 1612–1617 (2010).CAS 
PubMed 
PubMed Central 

Google Scholar 
55.Huber, H. et al. A new phylum of Archaea represented by a nanosized hyperthermophilic symbiont. Nature 417, 63–67 (2002).CAS 
PubMed 

Google Scholar 
56.Waters, E. et al. The genome of Nanoarchaeum equitans: insights into early archaeal evolution and derived parasitism. Proc. Natl Acad. Sci. USA 100, 12984–12988 (2003).CAS 
PubMed 
PubMed Central 

Google Scholar 
57.Casanueva, A. et al. Nanoarchaeal 16S rRNA gene sequences are widely dispersed in hyperthermophilic and mesophilic halophilic environments. Extremophiles 12, 651–656 (2008).CAS 
PubMed 

Google Scholar 
58.Wurch, L. et al. Genomics-informed isolation and characterization of a symbiotic Nanoarchaeota system from a terrestrial geothermal environment. Nat. Commun. 7, 12115 (2016). This is an interesting study demonstrating that insights from genomic studies may help develop effective cultivation strategies for the isolation of novel microbial species.CAS 
PubMed 
PubMed Central 

Google Scholar 
59.Spang, A. et al. Complex archaea that bridge the gap between prokaryotes and eukaryotes. Nature 521, 173–179 (2015). The discovery and genomic characterization of Lokiarchaeota have unveiled insights into eukaryogenesis.CAS 
PubMed 
PubMed Central 

Google Scholar 
60.Seitz, K. W., Lazar, C. S., Hinrichs, K. U., Teske, A. P. & Baker, B. J. Genomic reconstruction of a novel, deeply branched sediment archaeal phylum with pathways for acetogenesis and sulfur reduction. ISME J. 10, 1696–1705 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
61.Zaremba-Niedzwiedzka, K. et al. Asgard archaea illuminate the origin of eukaryotic cellular complexity. Nature 541, 353–358 (2017).CAS 
PubMed 

Google Scholar 
62.Imachi, H. et al. Isolation of an archaeon at the prokaryote-eukaryote interface. Nature 577, 519–525 (2020). This study reports the isolation of the first member of the superphylum Asgard, confirming the existence of these archaea and their close phylogenetic relatedness to eukaryotes.CAS 
PubMed 
PubMed Central 

Google Scholar 
63.Margesin, R. & Collins, T. Microbial ecology of the cryosphere (glacial and permafrost habitats): current knowledge. Appl. Microbiol. Biotechnol. 103, 2537–2549 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
64.Boetius, A., Anesio, A. M., Deming, J. W., Mikucki, J. A. & Rapp, J. Z. Microbial ecology of the cryosphere: sea ice and glacial habitats. Nat. Rev. Microbiol. 13, 677–690 (2015).CAS 
PubMed 

Google Scholar 
65.Hoham, R. W. & Duval, B. in Snow Ecology (eds Jones, H. et al.) 168–228 (Cambridge Univ. Press, 2001).66.Edwards, A. et al. Coupled cryoconite ecosystem structure-function relationships are revealed by comparing bacterial communities in alpine and Arctic glaciers. FEMS Microbiol. Ecol. 89, 222–237 (2014).CAS 
PubMed 

Google Scholar 
67.Jungblut, A. D., Lovejoy, C. & Vincent, W. F. Global distribution of cyanobacterial ecotypes in the cold biosphere. ISME J. 4, 191–202 (2010).CAS 
PubMed 

Google Scholar 
68.Franzetti, A. et al. Temporal variability of bacterial communities in cryoconite on an alpine glacier. Environ. Microbiol. Rep. 9, 71–78 (2017).CAS 
PubMed 

Google Scholar 
69.Anesio, A. M., Hodson, A. J., Fritz, A., Psenner, R. & Sattler, B. High microbial activity on glaciers: importance to the global carbon cycle. Glob. Chang. Biol. 15, 955–960 (2009).
Google Scholar 
70.Christner, B. C. et al. A microbial ecosystem beneath the West Antarctic ice sheet. Nature 512, 310–313 (2014).CAS 
PubMed 

Google Scholar 
71.Hultman, J. et al. Multi-omics of permafrost, active layer and thermokarst bog soil microbiomes. Nature 521, 208–212 (2015).CAS 
PubMed 

Google Scholar 
72.Mackelprang, R. et al. Metagenomic analysis of a permafrost microbial community reveals a rapid response to thaw. Nature 480, 368–371 (2011).CAS 
PubMed 

Google Scholar 
73.Frey, B. et al. Microbial diversity in European alpine permafrost and active layers. FEMS Microbiol. Ecol. 92, fiw018 (2016).PubMed 

Google Scholar 
74.Fernández, A. B. et al. Prokaryotic taxonomic and metabolic diversity of an intermediate salinity hypersaline habitat assessed by metagenomics. FEMS Microbiol. Ecol. 88, 623–635 (2014).PubMed 

Google Scholar 
75.Ventosa, A. et al. Microbial diversity of hypersaline environments: a metagenomic approach. Curr. Opin. Microbiol. 25, 80–87 (2015).CAS 
PubMed 

Google Scholar 
76.Emerson, J. B. et al. Virus-host and CRISPR dynamics in Archaea-dominated hypersaline Lake Tyrrell, Victoria, Australia. Archaea 2013, 370871 (2013).PubMed 
PubMed Central 

Google Scholar 
77.Ley, R. E. et al. Unexpected diversity and complexity of the Guerrero Negro hypersaline microbial mat. Appl. Environ. Microbiol. 72, 3685–3695 (2006).CAS 
PubMed 
PubMed Central 

Google Scholar 
78.Harris, J. K. et al. Phylogenetic stratigraphy in the Guerrero Negro hypersaline microbial mat. ISME J. 7, 50–60 (2013). This study retrieves an unprecedented number of nearly full length 16S rRNA gene sequences from the microbial mats of the Guerrero Negro hypersaline environment, Mexico, demonstrating them to be among the most diverse, complex and novel microbial ecosystems known.PubMed 

Google Scholar 
79.Vavourakis, C. D. et al. Metagenomic insights into the uncultured diversity and physiology of microbes in four hypersaline soda lake brines. Front. Microbiol. 7, 211 (2016).PubMed 
PubMed Central 

Google Scholar 
80.Hamm, J. N. et al. Unexpected host dependency of Antarctic Nanohaloarchaeota. Proc. Natl Acad. Sci. USA. 116, 14661–14670 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
81.Nigro, L. M., Hyde, A. S., MacGregor, B. J. & Teske, A. Phylogeography, salinity adaptations and metabolic potential of the candidate division KB1 bacteria based on a partial single cell genome. Front. Microbiol. 7, 1266 (2016).PubMed 
PubMed Central 

Google Scholar 
82.Vavourakis, C. D. et al. A metagenomics roadmap to the uncultured genome diversity in hypersaline soda lake sediments. Microbiome 6, 168 (2018).PubMed 
PubMed Central 

Google Scholar 
83.Edwards, K. J., Becker, K. & Colwell, F. The deep, dark energy biosphere: intraterrestrial life on Earth. Annu. Rev. Earth Planet. Sci. 40, 551–568 (2012).CAS 

Google Scholar 
84.Parkes, R. J. et al. A review of prokaryotic populations and processes in sub-seafloor sediments, including biosphere: geosphere interactions. Mar. Geol. 352, 409–425 (2014).CAS 

Google Scholar 
85.Starnawski, P. et al. Microbial community assembly and evolution in subseafloor sediment. Proc. Natl Acad. Sci. USA 114, 2940–2945 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
86.Ciobanu, M. C. et al. Microorganisms persist at record depths in the subseafloor of the Canterbury Basin. ISME J. 8, 1370–1380 (2014).PubMed 
PubMed Central 

Google Scholar 
87.Inagaki, F. et al. Exploring deep microbial life in coal-bearing sediment down to ~2.5 km below the ocean floor. Science 349, 420–424 (2015).CAS 
PubMed 

Google Scholar 
88.D’Hondt, S., Pockalny, R., Fulfer, V. M. & Spivack, A. J. Subseafloor life and its biogeochemical impacts. Nat. Commun. 10, 3519 (2019).PubMed 
PubMed Central 

Google Scholar 
89.Petro, C., Starnawski, P., Schramm, A. & Kjeldsen, K. U. Microbial community assembly in marine sediments. Aquat. Microb. Ecol. 79, 177–195 (2017).
Google Scholar 
90.Teske, A. & Sørensen, K. B. Uncultured archaea in deep marine subsurface sediments: have we caught them all? ISME J. 2, 3–18 (2008).CAS 
PubMed 

Google Scholar 
91.Orsi, W. D. Ecology and evolution of seafloor and subseafloor microbial communities. Nat. Rev. Microbiol. 16, 671–683 (2018).CAS 
PubMed 

Google Scholar 
92.Sørensen, K. B. & Teske, A. Stratified communities of active Archaea in deep marine subsurface sediments. Appl. Environ. Microbiol. 72, 4596–4603 (2006).PubMed 
PubMed Central 

Google Scholar 
93.Walsh, E. A. et al. Relationship of bacterial richness to organic degradation rate and sediment age in subseafloor sediment. Appl. Environ. Microbiol. 82, 4994–4999 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
94.Petro, C. et al. Marine deep biosphere microbial communities assemble in near-surface sediments in Aarhus Bay. Front. Microbiol. 10, 758 (2019).PubMed 
PubMed Central 

Google Scholar 
95.Jorgensen, S. L. et al. Correlating microbial community profiles with geochemical data in highly stratified sediments from the Arctic Mid-Ocean Ridge. Proc. Natl Acad. Sci. USA 109, E2846–E2855 (2012).CAS 
PubMed 
PubMed Central 

Google Scholar 
96.Edwards, K. J., Wheat, C. G. & Sylvan, J. B. Under the sea: microbial life in volcanic oceanic crust. Nat. Rev. Microbiol. 9, 703–712 (2011).CAS 
PubMed 

Google Scholar 
97.Li, J. et al. Recycling and metabolic flexibility dictate life in the lower oceanic crust. Nature 579, 250–255 (2020). This is a multiple-approach exploration to provide the first insights into the ultralow-biomass microbial assemblages inhabiting the lithified lower oceanic crust.CAS 
PubMed 

Google Scholar 
98.Bar-On, Y. M., Phillips, R. & Milo, R. The biomass distribution on Earth. Proc. Natl Acad. Sci. USA 115, 6506–6511 (2018).CAS 
PubMed 
PubMed Central 

Google Scholar 
99.Nyyssönen, M. et al. Taxonomically and functionally diverse microbial communities in deep crystalline rocks of the Fennoscandian shield. ISME J. 8, 126–138 (2014).PubMed 

Google Scholar 
100.Lin, X., Kennedy, D., Fredrickson, J., Bjornstad, B. & Konopka, A. Vertical stratification of subsurface microbial community composition across geological formations at the Hanford Site. Environ. Microbiol. 14, 414–425 (2012).CAS 
PubMed 

Google Scholar 
101.Osburn, M. R. et al. Chemolithotrophy in the continental deep subsurface: Sanford Underground Research Facility (SURF), USA. Front. Microbiol. 5, 610 (2014).PubMed 
PubMed Central 

Google Scholar 
102.Magnabosco, C. et al. The biomass and biodiversity of the continental subsurface. Nat. Geosci. 11, 707–717 (2018).CAS 

Google Scholar 
103.Navarro-Noya, Y. E. et al. Pyrosequencing analysis of the bacterial community in drinking water wells. Microb. Ecol. 66, 19–29 (2013).PubMed 

Google Scholar 
104.Wrighton, K. C. et al. Fermentation, hydrogen, and sulfur metabolism in multiple uncultivated bacterial phyla. Science 337, 1661–1665 (2012).CAS 
PubMed 

Google Scholar 
105.Bagnoud, A. et al. Reconstructing a hydrogen driven microbial metabolic network in Opalinus Clay rock. Nat. Commun. 7, 12770 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
106.Magnabosco, C. et al. A metagenomic window into carbon metabolism at 3 km depth in Precambrian continental crust. ISME J. 10, 730–741 (2016).CAS 
PubMed 

Google Scholar 
107.Hernsdorf, A. W. et al. Potential for microbial H2 and metal transformations associated with novel bacteria and archaea in deep terrestrial subsurface sediments. ISME J. 11, 1915–1929 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
108.Anantharaman, K. et al. Thousands of microbial genomes shed light on interconnected biogeochemical processes in an aquifer system. Nat. Commun. 7, 13219 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
109.Kantor, R. S. et al. Small genomes and sparse metabolisms of sediment-associated bacteria from four candidate phyla. mBio 4, e00708–e00713 (2013).PubMed 
PubMed Central 

Google Scholar 
110.Wrighton, K. C. et al. Metabolic interdependencies between phylogenetically novel fermenters and respiratory organisms in an unconfined aquifer. ISME J. 8, 1452–1463 (2014).CAS 
PubMed 
PubMed Central 

Google Scholar 
111.Hallberg, K. B., Coupland, K., Kimura, S. & Johnson, D. B. Macroscopic streamer growths in acidic, metal-rich mine waters in north Wales consist of novel and remarkably simple bacterial communities. Appl. Environ. Microbiol. 72, 2022–2030 (2006).CAS 
PubMed 
PubMed Central 

Google Scholar 
112.Belnap, C. P. et al. Quantitative proteomic analyses of the response of acidophilic microbial communities to different pH conditions. ISME J. 5, 1152–1161 (2011).CAS 
PubMed 
PubMed Central 

Google Scholar 
113.Edwards, K. J. et al. Seasonal variations in microbial populations and environmental conditions in an extreme acid mine drainage environment. Appl. Environ. Microbiol. 65, 3627–3632 (1999).CAS 
PubMed 
PubMed Central 

Google Scholar 
114.Liu, J. et al. Correlating microbial diversity patterns with geochemistry in an extreme and heterogeneous environment of mine tailings. Appl. Environ. Microbiol. 80, 3677–3686 (2014).PubMed 
PubMed Central 

Google Scholar 
115.Golyshina, O. V. et al. ‘ARMAN’ archaea depend on association with euryarchaeal host in culture and in situ. Nat. Commun. 8, 60 (2017).PubMed 
PubMed Central 

Google Scholar 
116.Antony, C. P. et al. Microbiology of Lonar Lake and other soda lakes. ISME J. 7, 468–476 (2013).PubMed 

Google Scholar 
117.Sorokin, D. Y. et al. Microbial diversity and biogeochemical cycling in soda lakes. Extremophiles 18, 791–809 (2014).CAS 
PubMed 
PubMed Central 

Google Scholar 
118.Reynolds, J. F. et al. Global desertification: building a science for dryland development. Science 316, 847–851 (2007).CAS 
PubMed 

Google Scholar 
119.Maestre, F. T. et al. Increasing aridity reduces soil microbial diversity and abundance in global drylands. Proc. Natl Acad. Sci. USA. 112, 15684–15689 (2015).CAS 
PubMed 
PubMed Central 

Google Scholar 
120.Makhalanyane, T. P. et al. Microbial ecology of hot desert edaphic systems. FEMS Microbiol. Rev. 39, 203–221 (2015).CAS 
PubMed 

Google Scholar 
121.Reinthaler, T. et al. Prokaryotic respiration and production in the meso- and bathypelagic realm of the eastern and western North Atlantic basin. Limnol. Oceanogr. 51, 1262–1273 (2006).CAS 

Google Scholar 
122.Hewson, I., Steele, J. A., Capone, D. G. & Fuhrman, J. A. Remarkable heterogeneity in meso- and bathypelagic bacterioplankton assemblage composition. Limnol. Oceanogr. 51, 1274–1283 (2006).
Google Scholar 
123.DeLong, E. F. et al. Community genomics among stratified microbial assemblages in the ocean’s interior. Science 311, 496–503 (2006).CAS 
PubMed 

Google Scholar 
124.Pham, V. D., Konstantinidis, K. T., Palden, T. & DeLong, E. F. Phylogenetic analyses of ribosomal DNA-containing bacterioplankton genome fragments from a 4000 m vertical profile in the North Pacific Subtropical Gyre. Environ. Microbiol. 10, 2313–2330 (2008).CAS 
PubMed 

Google Scholar 
125.Karner, M. B., DeLong, E. F. & Karl, D. M. Archaeal dominance in the mesopelagic zone of the Pacific Ocean. Nature 409, 507–510 (2001).CAS 
PubMed 

Google Scholar 
126.Ziegler, S. et al. Oxygen-dependent niche formation of a pyrite-dependent acidophilic consortium built by archaea and bacteria. ISME J. 7, 1725–1737 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
127.Méndez-García, C. et al. Microbial stratification in low pH oxic and suboxic macroscopic growths along an acid mine drainage. ISME J. 8, 1259–1274 (2014).PubMed 
PubMed Central 

Google Scholar 
128.Klatt, C. G. et al. Temporal metatranscriptomic patterning in phototrophic Chloroflexi inhabiting a microbial mat in a geothermal spring. ISME J. 7, 1775–1789 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
129.Klatt, C. G. et al. Community structure and function of high-temperature chlorophototrophic microbial mats inhabiting diverse geothermal environments. Front. Microbiol. 4, 106 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
130.Inskeep, W. P. et al. Metagenomes from high-temperature chemotrophic systems reveal geochemical controls on microbial community structure and function. PLoS ONE 5, e9773 (2010).PubMed 
PubMed Central 

Google Scholar 
131.Swingley, W. D. et al. Coordinating environmental genomics and geochemistry reveals metabolic transitions in a hot spring ecosystem. PLoS ONE 7, e38108 (2012).CAS 
PubMed 
PubMed Central 

Google Scholar 
132.Liu, Z. et al. Metatranscriptomic analyses of chlorophototrophs of a hot-spring microbial mat. ISME J. 5, 1279–1290 (2011).CAS 
PubMed 
PubMed Central 

Google Scholar 
133.Woodcroft, B. J. et al. Genome-centric view of carbon processing in thawing permafrost. Nature 560, 49–54 (2018).CAS 
PubMed 

Google Scholar 
134.Ghai, R. et al. New abundant microbial groups in aquatic hypersaline environments. Sci. Rep. 1, 135 (2011).PubMed 
PubMed Central 

Google Scholar 
135.Uritskiy, G. et al. Halophilic microbial community compositional shift after a rare rainfall in the Atacama Desert. ISME J. 13, 2737–2749 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
136.Uritskiy, G. et al. Cellular life from the three domains and viruses are transcriptionally active in a hypersaline desert community. Environ. Microbiol. 23, 3401–3417 (2021).CAS 
PubMed 

Google Scholar 
137.Herrmann, M. et al. Large fractions of CO2-fixing microorganisms in pristine limestone aquifers appear to be involved in the oxidation of reduced sulfur and nitrogen compounds. Appl. Environ. Microbiol. 81, 2384–2394 (2015).CAS 
PubMed 
PubMed Central 

Google Scholar 
138.Probst, A. J. et al. Differential depth distribution of microbial function and putative symbionts through sediment-hosted aquifers in the deep terrestrial subsurface. Nat. Microbiol. 3, 328–336 (2018).CAS 
PubMed 
PubMed Central 

Google Scholar 
139.Mueller, R. S. et al. Ecological distribution and population physiology defined by proteomics in a natural microbial community. Mol. Syst. Biol. 6, 374 (2010).PubMed 
PubMed Central 

Google Scholar 
140.Chen, L. X. et al. Shifts in microbial community composition and function in the acidification of a lead/zinc mine tailings. Environ. Microbiol. 15, 2431–2444 (2013).CAS 
PubMed 

Google Scholar 
141.Mueller, R. S. et al. Proteome changes in the initial bacterial colonist during ecological succession in an acid mine drainage biofilm community. Environ. Microbiol. 13, 2279–2292 (2011).CAS 
PubMed 

Google Scholar 
142.Mosier, A. C. et al. Elevated temperature alters proteomic responses of individual organisms within a biofilm community. ISME J. 9, 180–194 (2015).CAS 
PubMed 

Google Scholar 
143.Papke, R. T., Koenig, J. E., Rodriguez-Valera, F. & Doolittle, W. F. Frequent recombination in a saltern population of Halorubrum. Science 306, 1928–1929 (2004).CAS 
PubMed 

Google Scholar 
144.Whitaker, R. J., Grogan, D. W. & Taylor, J. W. Recombination shapes the natural population structure of the hyperthermophilic archaeon Sulfolobus islandicus. Mol. Biol. Evol. 22, 2354–2361 (2005).CAS 
PubMed 

Google Scholar 
145.Naor, A., Lapierre, P., Mevarech, M., Papke, R. T. & Gophna, U. Low species barriers in halophilic archaea and the formation of recombinant hybrids. Curr. Biol. 22, 1444–1448 (2012).CAS 
PubMed 

Google Scholar 
146.Reno, M. L., Held, N. L., Fields, C. J., Burke, P. V. & Whitaker, R. J. Biogeography of the Sulfolobus islandicus pan-genome. Proc. Natl Acad. Sci. USA 106, 8605–8610 (2009).CAS 
PubMed 
PubMed Central 

Google Scholar 
147.Mongodin, E. F. et al. The genome of Salinibacter Ruber: convergence and gene exchange among hyperhalophilic bacteria and archaea. Proc. Natl Acad. Sci. USA 102, 18147–18152 (2005).CAS 
PubMed 
PubMed Central 

Google Scholar 
148.Nelson-Sathi, S. et al. Acquisition of 1,000 eubacterial genes physiologically transformed a methanogen at the origin of Haloarchaea. Proc. Natl Acad. Sci. USA 109, 20537–20542 (2012). Comparative genomics provides evidence that massive amounts of gene influx from bacterial sources may have led to the drastic change in lifestyle in the extremely salt tolerant Haloarchaea.CAS 
PubMed 
PubMed Central 

Google Scholar 
149.Wolf, Y. I., Makarova, K. S., Yutin, N. & Koonin, E. V. Updated clusters of orthologous genes for Archaea: a complex ancestor of the Archaea and the byways of horizontal gene transfer. Biol. Direct 7, 46 (2012).CAS 
PubMed 
PubMed Central 

Google Scholar 
150.Nelson-Sathi, S. et al. Origins of major archaeal clades correspond to gene acquisitions from bacteria. Nature 517, 77–80 (2015).CAS 
PubMed 

Google Scholar 
151.Simmons, S. L. et al. Population genomic analysis of strain variation in Leptospirillum group II bacteria involved in acid mine drainage formation. PLoS Biol. 6, e177 (2008).PubMed 
PubMed Central 

Google Scholar 
152.Lo, I. et al. Strain-resolved community proteomics reveals recombining genomes of acidophilic bacteria. Nature 446, 537–541 (2007).CAS 
PubMed 

Google Scholar 
153.Denef, V. J. et al. Proteomics-inferred genome typing (PIGT) demonstrates inter-population recombination as a strategy for environmental adaptation. Environ. Microbiol. 11, 313–325 (2009).CAS 
PubMed 

Google Scholar 
154.Denef, V. J. et al. Proteogenomic basis for ecological divergence of closely related bacteria in natural acidophilic microbial communities. Proc. Natl Acad. Sci. USA 107, 2383–2390 (2010).CAS 
PubMed 
PubMed Central 

Google Scholar 
155.Denef, V. J. & Banfield, J. F. In situ evolutionary rate measurements show ecological success of recently emerged bacterial hybrids. Science 336, 462–466 (2012). This study provides a time-series population metagenomic analysis of microorganisms in exceptionally low diversity AMD biofilms, allowing for the first time measurement of evolutionary rates for wild populations.CAS 
PubMed 

Google Scholar 
156.Brochier-Armanet, C., Boussau, B., Gribaldo, S. & Forterre, P. Mesophilic Crenarchaeota: proposal for a third archaeal phylum, the Thaumarchaeota. Nat. Rev. Microbiol. 6, 245–252 (2008).CAS 
PubMed 

Google Scholar 
157.Kelly, S., Wickstead, B. & Gull, K. Archaeal phylogenomics provides evidence in support of a methanogenic origin of the Archaea and a thaumarchaeal origin for the eukaryotes. Proc. Biol. Sci. 278, 1009–1018 (2011).CAS 
PubMed 

Google Scholar 
158.Sorokin, D. Y. et al. Discovery of extremely halophilic, methyl-reducing euryarchaea provides insights into the evolutionary origin of methanogenesis. Nat. Microbiol. 2, 17081 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
159.Baker, B. J. et al. Diversity, ecology and evolution of archaea. Nat. Microbiol. 5, 887–900 (2020).CAS 
PubMed 

Google Scholar 
160.Paul, B. G. et al. Targeted diversity generation by intraterrestrial archaea and archaeal viruses. Nat. Commun. 6, 6585 (2015).CAS 
PubMed 

Google Scholar 
161.Paul, B. G. et al. Retroelement-guided protein diversification abounds in vast lineages of Bacteria and Archaea. Nat. Microbiol. 2, 17045 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
162.Burstein, D. et al. New CRISPR-Cas systems from uncultivated microbes. Nature 542, 237–241 (2017).CAS 
PubMed 

Google Scholar 
163.Anderson, R. E. et al. Genomic variation in microbial populations inhabiting the marine subseafloor at deep-sea hydrothermal vents. Nat. Commun. 8, 1114 (2017).PubMed 
PubMed Central 

Google Scholar 
164.Brazelton, W. J. & Baross, J. A. Abundant transposases encoded by the metagenome of a hydrothermal chimney biofilm. ISME J. 3, 1420–1424 (2009).CAS 
PubMed 

Google Scholar 
165.Jansson, J. K. & Taş, N. The microbial ecology of permafrost. Nat. Rev. Microbiol. 12, 414–425 (2014).CAS 
PubMed 

Google Scholar 
166.Kuang, J. et al. Predicting taxonomic and functional structure of microbial communities in acid mine drainage. ISME J. 10, 1527–1539 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
167.Clark, D. R. et al. Biogeography at the limits of life: do extremophilic microbial communities show biogeographical regionalization? Glob. Ecol. Biogeogr. 26, 1435–1446 (2017).
Google Scholar 
168.Atanasova, N. S., Roine, E., Oren, A., Bamford, D. H. & Oksanen, H. M. Global network of specific virus-host interactions in hypersaline environments. Environ. Microbiol. 14, 426–440 (2012).CAS 
PubMed 

Google Scholar 
169.Wilkins, D. et al. Key microbial drivers in Antarctic aquatic environments. FEMS Microbiol. Rev. 37, 303–335 (2013).CAS 
PubMed 

Google Scholar 
170.Cavicchioli, R. Microbial ecology of Antarctic aquatic systems. Nat. Rev. Microbiol. 13, 691–706 (2015).CAS 
PubMed 

Google Scholar 
171.López-Bueno, A. et al. High diversity of the viral community from an Antarctic lake. Science 326, 858–861 (2009).PubMed 

Google Scholar 
172.Aguirre de Cárcer, D., López-Bueno, A., Pearce, D. A. & Alcamí, A. Biodiversity and distribution of polar freshwater DNA viruses. Sci. Adv. 1, e1400127 (2015).PubMed 
PubMed Central 

Google Scholar 
173.Yau, S. et al. Virophage control of Antarctic algal host–virus dynamics. Proc. Natl Acad. Sci. USA 108, 6163–6168 (2011). This is the first study to reveal the important ecological roles of virophages and their regulation of host–virus interactions.CAS 
PubMed 
PubMed Central 

Google Scholar 
174.Al-Shayeb, B. et al. Clades of huge phages from across Earth’s ecosystems. Nature 578, 425–431 (2020). Analysis of massive metagenomic datasets revealed clades of huge phages from diverse habitats, including extreme environments.CAS 
PubMed 
PubMed Central 

Google Scholar 
175.Tschitschko, B. et al. Antarctic archaea-virus interactions: metaproteome-led analysis of invasion, evasion and adaptation. ISME J. 9, 2094–2107 (2015).CAS 
PubMed 
PubMed Central 

Google Scholar 
176.Mosier, A. C. et al. Fungi contribute critical but spatially varying roles in nitrogen and carbon cycling in acid mine drainage. Front. Microbiol. 7, 238 (2016).PubMed 
PubMed Central 

Google Scholar 
177.Quemener, M. et al. Meta-omics highlights the diversity, activity and adaptations of fungi in deep oceanic crust. Environ. Microbiol. 22, 3950–3967 (2020).CAS 
PubMed 

Google Scholar 
178.Fredrickson, J. K. Ecological communities by design. Science 348, 1425–1427 (2015).CAS 
PubMed 

Google Scholar 
179.Fuhrman, J. A. et al. Annually reoccurring bacterial communities are predictable from ocean conditions. Proc. Natl Acad. Sci. USA 103, 13104–13109 (2006).CAS 
PubMed 
PubMed Central 

Google Scholar 
180.Sunagawa, S. et al. Structure and function of the global ocean microbiome. Science 348, 1261359 (2015).PubMed 

Google Scholar 
181.Lozupone, C. A. & Knight, R. Global patterns in bacterial diversity. Proc. Natl Acad. Sci. USA 104, 11436–11440 (2007).CAS 
PubMed 
PubMed Central 

Google Scholar 
182.Fierer, N. & Jackson, R. B. The diversity and biogeography of soil bacterial communities. Proc. Natl Acad. Sci. USA 103, 626–631 (2006).CAS 
PubMed 
PubMed Central 

Google Scholar 
183.López-Pérez, M., Haro-Moreno, J. M., Coutinho, F. H., Martinez-Garcia, M. & Rodriguez-Valera, F. The evolutionary success of the marine bacterium SAR11 analyzed through a metagenomic perspective. mSystems 5, e00605-20 (2020).PubMed 
PubMed Central 

Google Scholar 
184.Altshuler, I., Goordial, J. & Whyte, L. G. in Psychrophiles: From Biodiversity to Biotechnology (ed. Margesin, R.) 153–180 (Springer International Publishing, 2017).185.Huang, L. N., Kuang, J. L. & Shu, W. S. Microbial ecology and evolution in the acid mine drainage model system. Trends Microbiol. 24, 581–593 (2016).CAS 
PubMed 

Google Scholar 
186.Klatt, C. G. et al. Community ecology of hot spring cyanobacterial mats: predominant populations and their functional potential. ISME J. 5, 1262–1278 (2011).CAS 
PubMed 
PubMed Central 

Google Scholar 
187.Menzel, P. et al. Comparative metagenomics of eight geographically remote terrestrial hot springs. Microb. Ecol. 70, 411–424 (2015).PubMed 

Google Scholar 
188.Stokke, R. et al. Functional interactions among filamentous Epsilonproteobacteria and Bacteroidetes in a deep-sea hydrothermal vent biofilm. Environ. Microbiol. 17, 4063–4077 (2015).CAS 
PubMed 

Google Scholar 
189.Zeng, Y. et al. Potential rhodopsin- and bacteriochlorophyll-based dual phototrophy in a High Arctic glacier. mBio 11, e02641–20 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
190.Simon, C., Wiezer, A., Strittmatter, A. W. & Daniel, R. Phylogenetic diversity and metabolic potential revealed in a glacier ice metagenome. Appl. Environ. Microbiol. 75, 7519–7526 (2009).CAS 
PubMed 
PubMed Central 

Google Scholar 
191.Lipson, D. A. et al. Metagenomic insights into anaerobic metabolism along an Arctic peat soil profile. PLoS ONE 8, e64659 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
192.Podell, S. et al. Assembly-driven community genomics of a hypersaline microbial ecosystem. PLoS ONE 8, e61692 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
193.DeMaere, M. Z. et al. High level of intergenera gene exchange shapes the evolution of haloarchaea in an isolated Antarctic lake. Proc. Natl Acad. Sci. USA. 110, 16939–16944 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
194.Smith, A. R. et al. Carbon fixation and energy metabolisms of a subseafloor olivine biofilm. ISME J. 13, 1737–1749 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
195.Zhao, R. et al. Geochemical transition zone powering microbial growth in subsurface sediments. Proc. Natl Acad. Sci. USA. 117, 32617–32626 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
196.Luo, Z. H. et al. Diversity and genomic characterization of a novel Parvarchaeota family in acid mine drainage sediments. Front. Microbiol. 11, 612257 (2020).PubMed 
PubMed Central 

Google Scholar 
197.Lewin, A., Wentzel, A. & Valla, S. Metagenomics of microbial life in extreme temperature environments. Curr. Opin. Biotechnol. 24, 516–525 (2013).CAS 
PubMed 

Google Scholar 
198.Schlesinger, M. J. Heat-shock proteins. J. Biol. Chem. 265, 12111–12114 (1990).CAS 
PubMed 

Google Scholar 
199.D’Amico, S., Collins, T., Marx, J.-C., Feller, G. & Gerday, C. Psychrophilic microorganisms: challenges for life. EMBO Rep. 7, 385–389 (2006).PubMed 
PubMed Central 

Google Scholar 
200.Bakermans, C., Bergholz, P. W., Ayala-del-Río, H. & Tiedje, J. in Permafrost Soils (ed. Margesin, R.) 159–168 (Springer, 2009).201.Gunde-Cimerman, N., Plemenitaš, A. & Oren, A. Strategies of adaptation of microorganisms of the three domains of life to high salt concentrations. FEMS Microbiol. Rev. 42, 353–375 (2018).CAS 
PubMed 

Google Scholar 
202.Baker-Austin, C. & Dopson, M. Life in acid: pH homeostasis in acidophiles. Trends Microbiol. 15, 165–171 (2007).CAS 
PubMed 

Google Scholar 
203.Dopson, M., Baker-Austin, C., Koppineedi, P. R. & Bond, P. L. Growth in sulfidic mineral environments: metal resistance mechanisms in acidophilic micro-organisms. Microbiology 149, 1959–1970 (2003).CAS 
PubMed 

Google Scholar 
204.Dopson, M., Ossandon, F. J., Lövgren, L. & Holmes, D. S. Metal resistance or tolerance? Acidophiles confront high metal loads via both abiotic and biotic mechanisms. Front. Microbiol. 5, 157 (2014).PubMed 
PubMed Central 

Google Scholar 
205.Allen, E. E. & Banfield, J. F. Community genomics in microbial ecology and evolution. Nat. Rev. Microbiol. 3, 489–498 (2005).CAS 
PubMed 

Google Scholar 
206.Sakowski, E. et al. Current state of and future opportunities for prediction in microbiome research: report from the Mid-Atlantic Microbiome Meet-up in Baltimore on 9 January 2019. mSystems 4, e00392–19 (2019).PubMed 
PubMed Central 

Google Scholar 
207.Lima-Mendez, G. et al. Determinants of community structure in the global plankton interactome. Science 348, 1262073 (2015).PubMed 

Google Scholar  More

1.Sims, D. W., Queiroz, N., Doyle, T. K., Houghton, J. D. R. & Hays, G. C. Satellite tracking of the world’s largest bony fish, the ocean sunfish (Mola mola L.) in the North East Atlantic. J. Exp. Mar. Biol. Ecol. 370, 127–133 (2009a)2.Sims, D. W., Queiroz, N., Humphries, N. E., Lima, F. P. & Hays, G. C. Long-term GPS tracking of ocean sunfish Mola mola offers a new direction in fish monitoring. PLoS ONE 4, e7351 (2009b).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
3.Dewar, H. et al. Satellite tracking the world’s largest jelly predator, the ocean sunfish, Mola mola, in the Western Pacific. J. Exp. Mar. Biol. Ecol. 393, 32–42 (2010).Article 

Google Scholar 
4.Thys, T. M. et al. Ecology of the ocean sunfish, Mola mola, in the southern California current system. J. Exp. Mar. Biol. Ecol. 471, 64–76 (2015).Article 

Google Scholar 
5.Sousa, L. L., Queiroz, N., Mucientes, G., Humphries, N. E. & Sims, D. W. Environmental influence on the seasonal movements of satellite-tracked ocean sunfish Mola mola in the north-east Atlantic. Anim. Biotelemetry 4, 7 (2016a).Article 

Google Scholar 
6.Sousa, L. L. et al. Integrated monitoring of Mola mola behaviour in space and time. PLoS ONE 11, e0160404 (2016b).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
7.Chang, C. T. et al. Horizontal and vertical movement patterns of sunfish off eastern Taiwan. Deep-Sea Res. Part II Top. Stud. Oceanogr. 175, 104683 (2020).8.Sawai, E., Yamanoue, Y., Yoshita, Y., Sakai, Y. & Hashimoto, H. Seasonal occurrence patterns of Mola sunfishes (Mola spp. A and B; Molidae) in waters off the Sanriku region, eastern Japan. Japan. J. Ichthyol. 58, 181–187 (2011).
Google Scholar 
9.Thys, T. M., Ryan, J. P., Weng, K. C., Erdmann, M. & Tresnati, J. Tracking a marine ecotourism star: Movements of the short ocean sunfish Mola ramsayi in Nusa Penida, Bali, Indonesia. J. Mar. Biol. 2016, 8750193 (2016).Article 

Google Scholar 
10.Thys, T. M., Hearn, A. R., Weng, K. C., Ryan, J. P. & Peñaherrera-Palma, C. Satellite tracking and site fidelity of short ocean sunfish, Mola ramsayi, in the Galapagos Islands. J. Mar. Biol. 2017, 7097965 (2017).Article 

Google Scholar 
11.Aspillaga, E. et al. Thermal stratification drives movement of a coastal apex predator. Sci. Rep. 7, 526 (2017).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
12.Gaube, P. et al. Mesoscale eddies influence the movements of mature female white sharks in the Gulf Stream and Sargasso Sea. Sci. Rep. 8, 7363 (2018).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
13.Nakamura, I., Goto, Y. & Sato, K. Ocean sunfish rewarm at the surface at the surface after deep excursion to forage for siphonophores. J. Anim. Ecol. 84, 590–603 (2015).PubMed 
Article 
PubMed Central 

Google Scholar 
14.Tolotti, M. et al. Fine-scale vertical movements of oceanic whitetip sharks (Carcharhinus longimanus). Fish. Bull. 115, 380–395 (2017).Article 

Google Scholar 
15.Musyl, M. K. et al. Postrelease survival, vertical and horizontal movements, and thermal habitats of five species of pelagic sharks in the central Pacific Ocean. Fish. Bull. 109, 341–368 (2011).
Google Scholar 
16.Furukawa, S. et al. Vertical movements of Pacific bluefin tuna (Thunnus orientalis) and dolphinfish (Coryphaena hippurus) relative to the thermocline in the northern East China Sea. Fish. Res. 149, 86–91 (2014).Article 

Google Scholar 
17.Gaube, P. et al. The use of mesoscale eddies by juvenile loggerhead sea turtles (Caretta caretta) in the southwestern Atlantic. PloS ONE 12, e0172839 (2017).18.Braun, C. D., Gaube, P., Sinclair-Taylor, T. H., Skomal, G. B. & Thorrold, S. R. Mesoscale eddies release pelagic sharks from thermal constraints to foraging in the ocean twilight zone. PNAS 116, 17187–17192 (2019).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
19.Sawai, E., Yamanoue, Y., Nyegaard, M. & Sakai, Y. Redescription of the bump-head sunfish Mola alexandrini (Ranzani 1839), senior synonym of Mola ramsayi (Giglioli 1883), with designation of a neotype for Mola mola (Linnaeus 1758) (Tetraodontiformes: Molidae). Ichthyol. Res. 65, 142–160 (2018).Article 

Google Scholar 
20.Sawai, E. & Yamada, M. Bump-head sunfish Mola alexandrini photographed in the north-west Pacific Ocean mesopelagic zone. J. Fish Biol. 96, 278–280 (2020).PubMed 
Article 
PubMed Central 

Google Scholar 
21.Kiyofuji, H. et al. Northward migration dynamics of skipjack tuna (Katsuwonus pelamis) associated with the lower thermal limit in the western Pacific Ocean. Progr. Oceanogr. 175, 55–67 (2019).ADS 
Article 

Google Scholar 
22.Fujioka, K. et al. Spatial and temporal variability in the trans-Pacific migration of Pacific bluefin tuna (Thunnus orientalis) revealed by archival tags. Progr. Oceanogr. 162, 52–65 (2018).23.Kobari, T. et al. Variability in taxonomic composition, standing stock, and productivity of the plankton community in the Kuroshio and its neighboring waters in Kuroshio Current: Physical, Biogeochemical, and Ecosystem Dynamics (ed. Nagai, T., Saito, H., Suzuki, K., Takahashi, M.) 223–243 (Hoboken, 2019).24.Queiroz, N., Humphries, N. E., Noble, L. R., Santos, A. M. & Sims, D. W. Short-term movements and diving behaviour of satellite-tracked blue sharks Prionace glauca in the northeastern Atlantic Ocean. Mar. Ecol. Progress Ser. 406, 265–279 (2010).ADS 
Article 

Google Scholar 
25.McMahon, C. R. & Hays, G. C. Thermal niche, large-scale movements and implications of climate change for a critically endangered marine vertebrate. Glob. Change Biol. 12, 1330–1338 (2006).ADS 
Article 

Google Scholar 
26.Nakatsubo, T., Kawachi, M., Mano, N. & Hirose, H. Spawning period of ocean sunfish Mola mola in waters of the eastern Kanto region, Japan. Aquacult. Sci. 55, 613–618 (2007).
Google Scholar 
27.Ashida, H., Suzuki, N., Tanabe, T., Suzuki, N. & Aonuma, Y. Reproductive condition, batch fecundity, and spawning fraction of large Pacific bluefin tuna Thunnus orientalis landed at Ishigaki Island, Okinawa, Japan. Environ. Biol. Fish. 98, 1173–1183 (2015).Article 

Google Scholar 
28.Watai, M. et al. Comparative analysis of the early growth history of Pacific bluefin tuna Thunnus orientalis from different spawning grounds. Mar. Ecol. Progress Ser. 607, 207–220 (2018).ADS 
Article 

Google Scholar 
29.Stevens, J. D., Bradford, R. W. & West, G. J. Satellite tagging of blue sharks (Prionace glauca) and other pelagic sharks off eastern Australia: Depth behaviour, temperature experience and movements. Mar. Biol. 157, 575–591 (2010).Article 

Google Scholar 
30.Musyl, M. K. et al. Vertical movements of bigeye tuna (Thunnus obesus) associated with islands, buoys, and seamounts near the main Hawaiian Islands from archival tagging data. Fish. Oceanogr. 12, 152–169 (2003).Article 

Google Scholar 
31.Lin, S. J. et al. Vertical and horizontal movements of bigeye tuna (Thunnus obesus) in southeastern Taiwan. Mar. Freshw. Behav. Physiol. 54, 1–21 (2021).Article 

Google Scholar 
32.Yasuda, I. & Kitagawa, D. Locations of early fishing grounds of saury in the northwestern Pacific. Fish. Oceanogr. 5, 63–69 (1996).Article 

Google Scholar 
33.Godø, O. R. et al. Mesoscale eddies are oases for higher trophic marine life. PloS ONE 7, e30161 (2012). 34.Polovina, J. J. et al. Forage and migration habitat of loggerhead (Caretta caretta) and olive ridley (Lepidochelys olivacea) sea turtles in the central North Pacific Ocean. Fish. Oceanogr. 13, 36–51 (2004).Article 

Google Scholar 
35.Sbragaglia, V. et al. Annual rhythms of temporal niche partitioning in the Sparidae family are correlated to different environmental variables. Sci. Rep. 9, 1708 (2019).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
36.Nakamura, I., Mastumoto, R. & Sato, K. Body temperature stability in the whale shark, the world’s largest fish. J. Exp. Biol. 223, jeb210286 (2020).PubMed 
Article 
PubMed Central 

Google Scholar 
37.Brill, R. W., Bigelow, K. A., Musyl, M. K., Fritsches, K. A. & Warrant, E. J. Bigeye tuna (Thunnus obesus) behavior and physiology and their relevance to stock assessments and fishery biology. Col. Vol. Sci. Pap. ICCAT 57, 142–161 (2005).
Google Scholar 
38.Stramma, L. et al. Expansion of oxygen minimum zones may reduce available habitat for tropical pelagic fishes. Nat. Clim. Change 2, 33–37 (2012).ADS 
CAS 
Article 

Google Scholar 
39.Brill, R. W. A review of temperature and oxygen tolerance studies of tunas pertinent to fisheries oceanography, movement models and stock assessments. Fish. Oceanogr. 3, 204–216 (1994).Article 

Google Scholar 
40.Lam, C. H., Kiefer, D. A. & Domeier, M. L. Habitat characterization for striped marlin in the Pacific Ocean. Fish. Res. 166, 80–91 (2015).Article 

Google Scholar 
41.Carlisle, A. B. et al. Influence of temperature and oxygen on the distribution of blue marlin (Makaira nigricans) in the Central Pacific. Fish. Oceanogr. 26, 34–48 (2017).Article 

Google Scholar 
42.Madigan D. J. et al. Water column structure defines vertical habitat of twelve pelagic predators in the South Atlantic. ICES J. Mar. Sci. 78, 867–883 (2021).Article 

Google Scholar 
43.Schlitzer, R. Export production in the equatorial and North Pacific derived from dissolved oxygen, nutrient and carbon data. J. Oceanogr. 60, 53–62 (2004).CAS 
Article 

Google Scholar 
44.Thomsen, S. et al. The formation of a subsurface anticyclonic eddy in the Peru-Chile Undercurrent and its impact on the near-coastal salinity, oxygen, and nutrient distributions. J. Geophys. Res. 121, 476–501 (2016).ADS 
Article 

Google Scholar 
45.Nakamura, I. & Sato, K. Ontogenetic shift in foraging habit of ocean sunfish Mola mola from dietary and behavioral studies. Mar. Biol. 161, 1263–1273 (2014).Article 

Google Scholar 
46.QGIS Development Team. Quantum GIS geographic information system. Open Source Geospatial Foundation Project. http://www.qgis.org/en/site/ (2016).47.Chelton, D. B., Gaube, P., Schlax, M. G., Early, J. J. & Samelson, R. M. The influence of nonlinear mesoscale eddies on near-surface oceanic chlorophyll. Science 334, 328–332 (2011).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
48.Fiedler, P. C. Comparison of objective descriptions of the thermocline. Limnol. Oceanogr. Methods 8, 313–325 (2010).Article 

Google Scholar 
49.Zar, J. H. Biostatistical Analysis 4th edn. (Prentice Hall, 1999).
Google Scholar 
50.Clarke, K. R., & Gorley, R. N. PRIMER v6: User manual/tutorial. PRIMER-E, Plymouth.51.Wood, S. N. On p-values for smooth components of an extended generalized additive model. Biometrika 100, 221–228 (2013).MathSciNet 
MATH 
Article 

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Reproductive successThe production of urinary pheromones correlated with male but not female reproductive success (RS; defined in “Materials and methods” section). The most important predictors of male RS were total urinary protein concentration (75%) and social status (69%; Table 1; based on conditional model average sum of weights). The relative importance of age, creatinine, and mass ranged from 23 to 39%; PC ratio (protein:creatinine concentration) was excluded from the model due to collinearity (VIF = 6.97). Total urinary protein concentration during the enclosure phase was positively correlated with RS for males (Spearman R = 0.52, p = 0.01; Fig. 1a), but not females (Fig. 1b). This correlation is explained by the low protein concentration in the urine of non-reproductive males, as it is no longer significant after removing these males from the analysis (R = 0.12, p = 0.62; Supplementary Fig. S2). The median total urinary protein concentration was 5512 µg mL−1 and 5028 µg mL−1 for reproductive and non-reproductive males, respectively (Wilcoxon rank sum test W = 5, p  More

Generic nameRavenala Adans.1 (1763: 67). (equiv) Urania Schreb.22 (1789: 212). –Ravenala Scop.23, nom. illeg. (1777: 96) as “Ravenalla Adans”.Type species Ravenala madagascariensis Sonn.24.Note: Dorr & Parkinson25 proposed to conserve the spelling Ravenala Scop. (and correct Scopoli’s original orthography “Ravenalla”) against Ravenala Adans. on the basis that Adanson’s generic names (using a uninominal nomenclature for species) were invalid. Brummitt26 rejected this proposal and considered that Adanson’s generic names were valid27 and thus that there was no need to use Scopoli’s Ravenala (Ravenalla). Moreover, the exact wording in Scopoli23 (1777: 96) is “Ravenalla Adans.”, citing Adanson explicitly, but with an incorrect spelling for the generic name (the double “l”).Typification and emended descriptionRavenala madagascariensis Sonn. (1782: 2[ed. qto.]: 223, tt. 124–126).(equiv) Ravenala madagascariensis J.F.Gmel.28 (1791: 567). (equiv) Urania madagascariensis (Sonn.) Schreb. ex Forsyth f.29 (1794: 212). (equiv) Heliconia ravenala Willemet30 (1796: 22). (equiv) Urania speciosa Willdenow31 (1799: 7). (equiv) Urania ravenalia (Willemet) A.Rich.32 (1831: 19). –Ravenala madagascariensis Adans.1 (1763: 597), nomen invalid., appearing on page 597, abbreviated in the final index of Adanson’s book as “Ravenala madag. 67”, which can also be construed as referring to Madagascar as a locality.Type Lectotype, here designated: The plate numbered 126, representing the typical lax mature infructescence, in Sonnerat24 (1782: plate 126). Epitype, here designated: MADAGASCAR (bullet) Fort-Dauphin, Forêt de Manantantely, [24°58′ 59.988″S, 46°55′0.012″E, calc. from label], 60–300 m elev., 15 September 1928, H. Humbert 5730 (Epitype: MNHN-P-P02234599!, Isoepitypes: MNHN-P-P02234602!, MNHN-P-P02234604!, MNHN-P-P02234605!).Additional specimen examined: MADAGASCAR (bullet) Toamasina: Foulpointe, Analalava Forest, plant growing close to the main forest station, 17°42.3′S, 49°27.38′E, 50 m elev., 20 March 2016, T.Haevermans, M. Vorontsova, S. Dransfield & J. Razanatsoa 821 (TAN!, P!, K !) (bullet) X. Aubriot et al. 45 (P00696168!, P00696167!, P00685124!, TAN!) (bullet) Along Route #5 from Fenerive to Maroantsetra, disturbed areas along road, 100 m elev., 28 February 1975, T. B. Croat 32540 (L-WAG.1111446!, L-WAG.1111447!, MO-358490!, MO-358491!, MO-358523!) (bullet) Toalagnaro, Ebakika, District de Fort-Dauphin, 12 July 1932, R. Decary 10107 (P02234596!) (bullet) Vondrozo (commune de Farafangana), 16 September 1926, R. Decary 5428 (P02234588!, P02234591!, P02234592!) (bullet) 2 km E of Ranomafana towards Brickaville, 18.965° S, 48.8564° E, 4 March 1992, J. Kress et al. 92-3412 (US00424302!, US00424299!, US00424300!, US00424301!, US00424303!) (bullet) 18 km E of Ranomafana, 25 km W of Brickaville, 18.9453° S, 48.9664° E, 4 March 1992, J. Kress et al. 92-3414 (US00424312!, US00424309!, US00424310!, US00424311!, US00424313!). MAURITIUS (bullet) Isle de France, s.dat., Commerson s.n. (P02234587!, P-JU!, P-LAM!).Identity of Ravenala madagascariensis Sonn. —Figs. 2d, 3d, 4d, 5d— In the absence of a specimen undoubtedly collected or seen by Sonnerat (Commerson’s specimens, collected in Mauritius and preserved in both Jussieu’s and Lamarck’s herbaria at the Paris herbarium (P-JU and P-LAM), might actually be part of original material), we decided to lectotypify from plates 124, 125 and 126 of the protologue in Sonnerat’s valid publication24 of the species. On page 225, Sonnerat24 mentions that the plant originated from Madagascar but was transported and established in Mauritius (known at the time as Isle de France) at the “Jardin des Pamplemousses”. We observed plants growing in this garden as well as naturalized plants occurring in the wild in Mauritius; all the plants we saw suckered and possessed the characteristic pointed conical fruits also observed in the Fort-Dauphin population. Sonnerat also specified that the original plant grew in marshy areas, which corresponds exactly to the coastal populations that can be found on the eastern coast of Madagascar (i.e. the “Horonorona” variant of Blanc et al.13). Plate 126 shows the typical mature infructescence of the species, with the space between bracts increasing before releasing the seeds (unlike other species of Ravenala). However, the “tree” pictured on plate 124 is a non-suckering plant, which in our opinion can be explained as artistic license on the part of the illustrator, as all the plants observed in Mauritius consistently sucker, like the plants growing in the south-eastern marshy areas. We also decided to designate an epitype with a documented locality in Madagascar (the material in P-JU and P-LAM does not bear a precise indication of locality) to fix the application of the name R. madagascariensis to the populations occurring in the marshy areas surrounding Fort-Dauphin, where only one morphotype is known.Figure 3Comparison of petiole bases. (a) R. agatheae. (b) R. blancii. (c) R. grandis. (d) R. madagascariensis. (e) R. menahirana. (f) R. hladikorum. Photographs Thomas Haevermans©.Full size imageFigure 4Comparison of inflorescences. (a) R. agatheae. (b) R. blancii. (c) R. grandis. (d) R. madagascariensis. (e) R. menahirana. (f) R. hladikorum. Photographs Thomas Haevermans©.Full size imageFigure 5Species of Ravenala in their natural habitat. (a) R. agatheae. (b) R. blancii. (c) R. grandis. (d) R. madagascariensis. (e) R. menahirana. (f) R. hladikorum. Photographs Thomas Haevermans©.Full size imageEmended description Plants suckering, 6–12 meters tall (adult), trunk circumference (d.b.h.) 20–30 cm, juvenile and adult laminae distributed in a perfect fan, 14–25 leaves simultaneously alive on the adult plant, 1–3 leaves between inflorescences. Leaves adult petiole 380–440 cm long, greenish-yellow, slightly waxy, sheath margin undeveloped to moderately developed (0–9 mm), entire, not drying, slightly splitting when aged (Fig. 3d), petiole/lamina ratio 1.9–(2.2)–2.3, adult lamina (200 times 100) cm, light green, juvenile lamina base non-decurrent. Inflorescences 4–6 live lateral inflorescences at a time, (100 times 100) cm (peduncle excluded), 8–16 bracts per inflorescence, bracts 200–(450 times 50)–100 mm, with some wax to very waxy, margin uniformly green (Fig. 4d), cincinnii of ca. 10 flowers per bract, flowering sequentially, bracteoles without a colored stripe. Flowers 240–280 mm long (ovary included), inferior ovary 40–50 mm long, perianth yellowish, sepals narrowly triangular 240–250 (times 10)–12 mm, sheathing (fused) petals narrowly triangular 220–230(times)ca. 10 mm, free petal acicular 180–190 (times 5) mm, slightly smaller than the remaining perianth with mean free petal/mean fused petal length ratio = 0.8, petal blotches absent, stamens (roughly) the same size as the perianth, 200–210 mm long, style 200–230 mm long, stigma 15–20 mm long, oblong ovoid with a basal constriction. Infructescences lax (bract bases not imbricate at maturity), stiff and coriaceous persisting bracts, old infructescences deciduous, 4–8 fruits per bract. Fruits 70–120 (times 30)–35 mm, trilocular septifragal capsule, apices conical (Fig. 2d), seeds 6–(8.5)–(11 times 5)–(6.4)–8 mm, shiny, dark brown, mostly globose, varying in shape according to their distribution in the capsule, ultramarine blue aril.Ecology Ravenala madagascariensis is a low-altitude species restricted to swampy areas of the eastern coast of Madagascar. Populations outside of Madagascar on nearby islands are reputedly non-indigenous24.Preliminary IUCN assessments We propose a Least Concern status for R. madagascariensis, having an E.O.O ( > 20,000) km2 and an A.O.O. ( > 2,000) km2 (criterion B)33.Note This emended description for R. madagascariensis was drawn up from our own observations and collections, and was made comparable point by point to the descriptions of the five new species presented below, along with a dichotomous identification key to all six species.New species descriptions
Ravenala agatheae Haev. & Razanats. sp. nov.—Figs. 2a, 3a, 4a, 5a, 6
Type MADAGASCAR (bullet) Antsiranana: Ambanja District, along R.N.6 road to Ankaramibe, 13°45′54.8″S, 48°21′27.7″E, 30 m elev., on degraded lateritic slopes, 28 October 2018, T. Haevermans, A. Haevermans & J. Razanatsoa 830 (Holotype: TAN!, Isotypes: K!, MO!, P!).Figure 6Ravenala agatheae. (a) young infructescence. (b) adult plant habit showing the suckers at the base and the persistent petioles and old infructescences. (c) fruit with a conical apex. (d) infructescence with remains of dried flowers and dried bracts. (e) style apex. (f) inflorescence with open flowers. (g) open flower. Ink drawings on (75 , upmu) polyester tracing paper by Agathe Haevermans© from specimen Haevermans et al. 830, and observations in-situ.Full size imageParatypes MADAGASCAR (bullet) Antsiranana: 57–58 km N of Ambanja, 13°22′59.9″S, 48°48′E, 22 May 1974, A.H. Gentry 11878 (L-WAG.1111448!, L-WAG.1111449!, MO-358489!, TAN) (bullet) Ampasindava, forêts d’Ambilanivy et Rangoty, 13°48′36″S, 48°10′48″E, 29 November 2007, L. Nusbaumer 2658 (G334213/1!, MO!, TAN) (bullet) Mahajanga: Morafenobe, Beravy, 15 km from Beravy, near the road from Orombato to Beravy, 18°3′50″S, 44°31′46″E, 09 June 2016, F. Rakotonasolo et al. 2772 (K, P00782931!, TAN).Diagnosis Similar to Ravenala madagascariensis but differs in its dark green narrower laminae, tricolor petioles with very developed dryish petiole sheath margins, very waxy petioles, the persistence of older infructescences for several years, a purple stripe on the bract margin, longer bracts, a whitish perianth, brown blotches on its mature fused petals, the bracteole apex tinged with pink, an ovoid pointed stigma, dense infructescences, smaller inflorescences, the free petal much shorter than the fused petals, and an end of year flowering period.Distribution Plants restricted to Madagascar, growing in the north-western part of the island. We observed it growing from the southern part of the Diego Suarez area (on the hills along the road leading to Tsingy Rouge and the city of Sadjoavato) in the north to the western part of the Mahajanga province down to the Melaky region, with most observations around Ambanja34. We also observed that the species was cultivated on Nosy Be.Preliminary IUCN assessments We propose a Least Concern status for R. agatheae, having an E.O.O ( > 20,000) km2 and an A.O.O. ( > 2,000) km2 (criterion B)33.Ecology This species is adapted to seasonally dry and warm coastal habitats, growing on slopes at low elevations in north-western coastal areas of Madagascar, from Antsiranana (Diego-Suarez) down to the Melaky region in the Mahajanga province.Etymology This species is named after to the first author’s wife, Agathe Haevermans, a botanical illustrator at the Muséum National d’Histoire Naturelle, who helped discover this species in the field with the collecting team and who contributes greatly to botany by producing illustrations of new taxa from biodiversity hotspots such as Madagascar.Description Plants suckering, 6–10 meters tall (adult), trunk circumference (d.b.h.) 20–30 cm, juvenile and adult laminae distributed like a regular fan, 9–22 leaves simultaneously alive on the adult plant, 1–3 leaves between inflorescences. Leaves adult petiole 300–460 cm long, tricolor (dark green with a waxy white strip and red petiole sheath margin subsequently drying out, Fig. 3a), very waxy, sheath margin very developed (10 mm and more), entire, dryish-papyraceous and protruding at 90 degrees, petiole/lamina ratio 1.7–(1.95)–2.2, adult lamina 174–(210 times 72)–86 cm, dark green, juvenile lamina base non-decurrent. Inflorescences 4–6 live lateral inflorescences at a time, 70–(90 times 90)–100 cm (peduncle excluded), 10–14 bracts per inflorescence, bracts 450–500 (times 80)– 90 mm, with some waxiness (Fig. 4a), margin bearing a purple stripe, cincinnii of 8–10 flowers per bract, flowering sequentially, some pink tinge at the apex of bracteoles. Flowers 260–310 mm long (ovary included), inferior ovary 40–60 mm long, perianth whitish, sepals narrowly triangular 220–250(times)ca. 10 mm, sheathing (fused) petals narrowly triangular 200–(220times)ca. 10 mm, free petal acicular 130–(140 times 5) mm, much smaller than the remaining perianth with a mean free petal / mean fused petal length ratio = 0.6, petal blotches present, stamens (roughly) the same size as the perianth, 210–220 mm long, style 220 mm long, stigma 15 mm long, ovoid-pointed with basal constriction. Infructescences compact (bracts bases imbricate at all stages of maturity), stiff and coriaceous persisting bracts on mature infructescence, persistence of old infructescences, 4–10 fruits per bract. Fruits 90–110 (times) 30–45 mm, trilocular septifragal capsule, apices conical (Fig. 2a), seeds shiny, dark brown, mostly globose, varying in shape according to their distribution in the capsule, ultramarine blue aril.
Ravenala blancii Haev., V. Jeannoda & A. Hladik sp. nov. —Figs. 2b, 3b, 4b, 5b, 7
Type MADAGASCAR (bullet) Andasibe; 18°56′00″S, 48°25′06″E; 940 m elev.; 01 December 2002; A. Hladik & C.-M. Hladik 6760 (Holotype: TAN!, Isotypes: K!, MO!, P!).Paratypes MADAGASCAR (bullet) Andasibe; 18°56′00″S, 48°25′06″E; 940 m elev., 23 Aug. 1998, A. Hladik & al. 6239 (P!, fruits) (bullet) June 2001, A. Hladik & al. 6650 (P!, leaves, fruits, bracts) (bullet) Andasibe-Mantadia area, Vakôna, Kalonora; 18°53′17.3″S, 48°25′51.3″E, 08 November 2018, 934 m elev., T. Haevermans & al. 832 (K!, MO!, P!, TAN!).Diagnosis Similar to Ravenala madagascariensis but differs in its non-suckering habit, decurrent juvenile lamina bases, toroidal distribution of juvenile laminae, smaller number of leaves simultaneously alive on the adult plant, dark green lamina and green non waxy petiole, smaller leaves, smaller number of live inflorescences, smaller number of bracts in an inflorescence, non-waxy bracts, sub-simultaneous flowering, smaller flowers, smaller inflorescences, non-persistence of entire bracts on dry infructescences, October/November flowering period.Distribution Andasibe-Mantadia, Ranomafana21. Restricted to Madagascar.Preliminary IUCN assessments We propose a Data Deficient status for R. blancii; further fieldwork is required to understand its precise distribution and the status of its populations33.Ecology High-elevation species found in eastern rainforests at elevations between 600 and 1,100 m. The species seems to favor cool tropical humid and shady conditions.Etymology This species is named after Dr. Patrick Blanc, world renowned botanist, plant ecologist and street artist, inventor of the planted vertical walls known as “Mur Végétal” and who first recognized the sheer originality of the juvenile phases of this peculiar taxon.Description Plants solitary (never suckering), 10–15 meters tall (adult), trunk circumference (d.b.h.) 20–30 cm, juvenile laminae distributed in a toroidal shape, adult laminae arranged in a regular fan, 9–16 leaves simultaneously alive on the adult plant, 2–4 leaves between inflorescences. Leaves adult petiole 240–310 cm long, green, not waxy, sheath margin undeveloped, entire, not drying, smooth with a worn-out irregular aspect (Fig. 3b), petiole/lamina ratio 1.8–(2.0)–2.2, adult lamina 120–160 (times) 90–104 cm, dark green, juvenile lamina base decurrent. Inflorescences 2–3 live lateral inflorescences at a time, (60 times 70) cm (peduncle excluded), 4–6 bracts per inflorescence, bracts 160–350 (times) 50–90 mm, no waxiness (Fig. 4b), margin color uniformly green, cincinnii of 5–14 flowers per bract, flowering sub-simultaneously, bracteoles sometimes pink colored. Flowers 165–280 mm long (ovary included), inferior ovary 40–50 mm long, perianth whitish-yellowish, sepals narrowly triangular 125–231 (times) 10–12 mm, sheathing (fused) petals narrowly triangular 105–190 (times 10) mm, free petal acicular 105–178 (times 3)–5 mm, free petal and fused petals of sub-equal size with a mean free petal / mean fused petal length ratio = 1.0, petal blotches absent or present, stamens (roughly) the same size as the perianth, 115–186 mm long, style 132–220 mm long, stigma 20-25 mm long, ovoid to ovoid-pointed with a basal constriction. Infructescences compact (bract bases imbricate at all stages of maturity), torn and degraded bracts on mature infructescence, old infructescences deciduous, 5–14 fruits per bract. Fruits 80–120 (times) 32–45 mm, trilocular septifragal capsule, apices conical (Fig. 2b), seeds 6–10 (times) 3.2–6 mm, shiny, dark brown, mostly globose, varying in shape according to their distribution in the capsule, ultramarine blue aril.Note The strong leaf dimorphism between juvenile and adult forms is characteristic of this species13, a phenomenon which is not present in the other taxa. The base of the juvenile plant usually grows buried in the leaf litter due to the action of traction roots13, its decurrent leaves (Fig. 7) giving it the aspect of a bird’s nest fern.Figure 7Ravenala blancii. (a) juvenile plant habit with roots. (b) juvenile plant showing the arrangement of laminae. (c) adult plant habit. (d) mature infructescence segment. (e) juvenile leaf showing the attenuate base of the lamina. (f) inflorescence with sub-simultaneous opening of the flowers. (g) young infructescence with already degraded bracts. (h) seeds with arilla. (i) open flower. (j) details of the stigma. (k) style. Ink drawings on (75 , upmu) polyester tracing paper by Agathe Haevermans© from specimens Hladik 6790, 6239, 6650, Haevermans et al. 832, and observations in-situ.Full size image
Ravenala grandis Haev., Razanats., A. Hladik & P. Blanc sp. nov.—Figs. 2c, 3c, 4c, 5cType. MADAGASCAR (bullet) Ampasimbe Commune, Maromaniry Fokontany, along Route Nationale, 18°57′41.8″S, 48°42′41.4″E, 258 m elev., 08 November 2018, T. Haevermans, A. Haevermans & J. Razanatsoa 831 (Holotype: TAN!, Isotypes: K!, MO!, P!).Paratypes MADAGASCAR (bullet) Varifoana, près d’Ambohimahasoa-sud, 15 May 1964, R. Capuron 26014SF (P02234597!) (bullet) Soanierana-Antasibe[Andasibe], 350 m elev., 10 December 1938, H.J. Lam & A.D.J. Meeuse 5867 (L-WAG.1111450!, L-WAG.1111451!, L-WAG.1111452!, L-WAG.1111453!, L-L.1477714!, L-L.1477715!).Diagnosis Similar to Ravenala madagascariensis but differs in its non-suckering habit, much larger dimensions, very thick leathery laminae, very waxy dark green-yellowish petioles, much larger bracts and overall dimensions, whitish/pure white perianth, strong reddish-pink stripes on its bracteoles, cylindrical stigma without basal constriction, stamens much shorter than perianth, and fruit with a truncated apex.Distribution Eastern rainforests at around 200–500 m elevation in Madagascar13,20.Preliminary IUCN assessments We propose a Data Deficient status for R. grandis; further fieldwork is required to understand its precise distribution and the status of its populations33.Ecology This species seems to favor growing in low discontinuous forests on inselbergs12 and thrives in secondary degraded vegetation on the slopes of eastern rain forests.Etymology The name of this species is in reference to its stature and habit, the most robust species of Ravenala known.Description Plants solitary (never suckering), 20–30 meters tall (adult), trunk circumference (d.b.h.) 30 cm, juvenile and adult laminae distributed in a perfect fan, 15–30 leaves simultaneously alive on the adult plant, usually 3 leaves between inflorescences. Leaves adult petiole 390–440 cm long, dark green/light green-yellowish, very waxy (Fig. 3c), sheath margin moderately developed to undeveloped (0–9 mm), entire on young leaves, splitting and dryish when old, petiole/lamina ratio 1.8–(2.2)–2.6, adult lamina 170–230 (times) 94–120 cm, light green, juvenile lamina base non-decurrent. Inflorescences 4–6 live lateral inflorescences at a time, 100–120 (times) 80–100 cm (peduncle excluded), 10–20 bracts per inflorescence, bracts 440–540 (times) 140–170 mm, some waxiness (Fig. 4c), margin color uniformly green, cincinnii of ca. 20 flowers per bract, flowering sequentially, bracteoles with a strong reddish-pink stripe. Flowers 300 mm long (ovary included), inferior ovary 50–70 mm long, perianth whitish/pure white, sepals narrowly triangular 220–240 (times) 10–15 mm, sheathing (fused) petals narrowly triangular 210–220 (times) 10–12 mm, free petal acicular 150–170 (times 3) mm, slightly smaller than the rest of the perianth with a mean free petal / mean fused petal length ratio = 0.8, petal blotches absent, stamens much shorter than the perianth, 180–200 mm long, style 180–210 mm long, stigma 14–16 mm long, oblong without basal constriction (almost indistinguishable from style). Infructescences lax (bract bases not imbricate at some stages of maturity), stiff and coriaceous persisting bracts on mature infructescence, old infructescences deciduous, 5–18 fruits per bract. Fruits 100–120 (times) 35–40 mm, trilocular septifragal capsule, apices truncate (Fig. 2c), seeds shiny, dark brown, mostly globose, varying in shape according to their distribution in the capsule, ultramarine blue aril.Note The leaves of this species are the most robust and tough of all Ravenala species, with a thick leathery texture, making it the material of choice for building roofs35.
Ravenala hladikorum Haev., Razanats., V. Jeannoda & P. Blanc sp. nov. — Figs. 2f, 3f, 4f, 5fType MADAGASCAR (bullet) Andasibe; 18°56′00″S, 48°25′06″E; 940 m elev.; 05 February 2004; A. Hladik & C.-M. Hladik 6842 (Holotype: TAN!, Isotype: P!). Paratypes. MADAGASCAR (bullet) Andasibe; 18°56′00″S, 48°25′06″E; 940 m elev.; 23 August 1998; A. Hladik & al. 6240 (fruit with seeds: P!). (bullet) Andasibe-Mantadia area, Vakôna, Kalonora; 18°53′17.3″S, 48°25′51.3″E; 934 m elev., 08 November 2018; T. Haevermans & al. 833 (TAN!, P!, K!, MO!).Diagnosis Similar to Ravenala madagascariensis but differs in its non-suckering habit, the alternate positioning of its adult laminae, its dark green leaves, non-waxy petioles with their very papyraceous petiole sheath margins, more than 1 cm long, smaller lamina dimensions, smaller number of simultaneously live inflorescences, purple stripe on bracts and on bracteoles, non-waxy inflorescences, smaller inflorescences, dense infructescences, truncated fruit apices, and short flowering period from November to December.Distribution Andasibe, Mantady, Ranomafana21. Restricted to Madagascar.Preliminary IUCN assessments We propose a Data Deficient status for R. hladikorum; further fieldwork is required to understand its precise distribution and the status of its populations33.Ecology High-elevation species found in eastern rainforests at elevations between 600 and 1100 m. The species seems to favor cool tropical humid and shady conditions.Etymology This species is named in honor of Annette and Claude-Marcel Hladik from the Muséum National d’Histoire Naturelle in Paris, who dedicated their lives to the study of Madagascan biodiversity and contributed greatly to the discovery of this species.Description Plants solitary (never suckering), 10–15 meters tall (adult), trunk circumference (d.b.h.) 20–30 cm, juvenile laminae distributed like a fan, adult laminae arranged in an irregular fan, 9–18 leaves simultaneously alive on the adult plant, 1–3 leaves between inflorescences. Leaves adult petiole 280–440 cm long, greenish-yellow, not waxy (Fig. 3f), sheath margin very developed (10 mm and more), split, very papyraceous with min. 1 cm brown dry expansions, petiole/lamina ratio 2.1–(2.42)–2.8, adult lamina 120–160 (times) 102–116 cm, dark green, juvenile lamina base non-decurrent. Inflorescences 2–3 live lateral inflorescences at a time, (60 times 90) cm (peduncle excluded), 4–7 bracts per inflorescence, bracts 150–510 (times) 64–100 mm, no waxiness (Fig. 4f), margin green with a purple stripe, cincinnii of 5–14 flowers per bract, sequentially flowering, bracteoles with a dark purple colored stripe. Flowers 240–320 mm long (ovary included), inferior ovary 40–60 mm long, perianth whitish, sepals narrowly triangular 210–265(times)ca. 10 mm, sheathing (fused) petals narrowly triangular 190–240(times)ca. 10 mm , free petal acicular 135–220 (times) 5 mm, almost the same size as the fused petals with a mean free petal / mean fused petal length ratio = 0.9, petal blotches unknown, stamens (roughly) the same size as the perianth, 170–230 mm long, style 187–250 mm long, stigma 20–25 mm long, ovoid with a basal constriction. Infructescences compact (bract bases imbricate at all stages of maturity), stiff and coriaceous persistent bracts on mature infructescences, old infructescences deciduous, 5–14 fruits per bract. Fruits 82–108 (times) 34–48 mm, trilocular septifragal capsule, apices truncate (Fig. 2f), seeds 4–9 (times) 3–6 mm, shiny, dark brown, mostly globose, varying in shape according to their distribution in the capsule, ultramarine blue aril.
Ravenala menahirana Haev. & Razanats. sp. nov.—Figs. 2e, 3e, 4e, 5eType MADAGASCAR (bullet) Foulpointe, Analalava Forest; 17°42.3′S, 49°27.38′E; 50 m elev.; 20 March 2016; T.Haevermans, M. Vorontsova, S. Dransfield & J. Razanatsoa 826 (Holotype: TAN!, Isotypes: P!, K !, MO!).Diagnosis Similar to Ravenala madagascariensis but differs in its non-suckering habit, the alternate dark green laminae tending not to form a perfect fan (Fig. 5e), dark red petioles with a zigzagging well developed dryish sheath margin, more strongly obovoid laminae, smaller number of simultaneously live inflorescences, smaller inflorescences tinged with red, pure white/whitish perianth, smaller flowers, dense infructescences, the fruit apices truncate with a mucro, and subequal free and fused petals.Distribution Appears to be restricted to the east coast in the area around Analalava-Foulpointe up to the Mananara-Avaratra area. Two human observations from Marojejy (North-East) and Tampolo (Masoala) seem also to be this species. Restricted to Madagascar.Preliminary IUCN assessments We propose a Data Deficient status for R. menahirana; further fieldwork is required to understand its precise distribution and the status of its populations33.Ecology This coastal forest-dwelling species favors low-elevation tropical humid conditions in the Analalava-Foulpointe area, extending north to Mananara-Avaratra area, and maybe up to Marojejy.Etymology The name of this species is in reference to one of its local names “menahirana”, given to the species in the Analalava-Foulpointe area and meaning “red ravenala”.Description Plants solitary (never suckering), 6–10 meters tall (adult), trunk circumference (d.b.h.) 20–30 cm, juvenile laminae distributed like a fan, adult laminae arranged in an irregular to regular fan, 12–18 leaves simultaneously alive on the adult plant, 3 leaves between inflorescences. Leaves adult petiole 200–230 cm long, dark red, slightly to very waxy, sheath margin very developed (10 mm and more), red, entire, forming a three dimensional zigzag pattern (Fig. 3e), then splitting and drying on old leaves, petiole/lamina ratio 1.4–(1.7)–1.9, adult lamina (350 times 120) cm, lamina color dark green, juvenile lamina base non-decurrent. Inflorescences 1–2 live lateral inflorescences at a time, (60 times 70) cm (peduncle excluded), 10–12 bracts per inflorescence, bracts 260–360 (times) 50–80 mm, very waxy (Fig. 4e), margin color uniformly reddish-green, cincinnii of 8–12 flowers per bract, flowering sequentially, no colored stripe on bracteoles (apices sometimes suffused with pink). Flowers 220–250 mm long (ovary included), inferior ovary 40–60 mm long, perianth pure white to whitish, sepals narrowly triangular 180–230 (times) 12–16 mm, sheathing (fused) petals narrowly triangular 160–180 (times) 5 mm, free petal acicular 160–170 (times) 5 mm, free petal the same size as the remaining perianth with a mean free petal / mean fused petal length ratio = 1.0, petal blotches absent, stamens the same size (roughly) as the perianth, stamen 150–160 mm long, style 150–200 mm long, stigma 10 mm long, oblong with a basal constriction. Infructescences compact (bract bases imbricate at all stages of maturity), stiff and coriaceous persisting bracts on mature infructescences, old infructescences deciduous, 8–12 fruits per bract. Fruits 80–100 (times) 30–35 mm, trilocular septifragal capsule, apices truncate with a mucro (Fig. 2e), seeds shiny, dark brown, mostly globose, varying in shape according to their distribution in the capsule, ultramarine blue aril.Note This species is similar to R. hladikorum but is easily distinguished by, in addition to its petioles and its ecology, its truncate mucronate fruit apices, the shape of the synflorescence bracts and the absence of a red stripe on the cyme bracteoles.Identification key to the species of genus Ravenala More

1.Gelfand, I. et al. Sustainable bioenergy production from marginal lands in the US Midwest. Nature 493, 514–517 (2013).CAS 
PubMed 
Article 

Google Scholar 
2.Sprunger, C. D. & Philip Robertson, G. Early accumulation of active fraction soil carbon in newly established cellulosic biofuel systems. Geoderma 318, 42–51 (2018).CAS 
Article 

Google Scholar 
3.DuPont, S. T. et al. Root traits and soil properties in harvested perennial grassland, annual wheat, and never-tilled annual wheat. Plant Soil 381, 405–420 (2014).CAS 
Article 

Google Scholar 
4.Robertson, G. P. et al. Cellulosic biofuel contributions to a sustainable energy future: Choices and outcomes. Science 356, 6375. https://doi.org/10.1126/science.aal2324 (2017).CAS 
Article 

Google Scholar 
5.Kravchenko, A. N. et al. Microbial spatial footprint as a driver of soil carbon stabilization. Nat. Commun. https://doi.org/10.1038/s41467-019-11057-4 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
6.Yang, Y., Tilman, D., Furey, G. & Lehman, C. Soil carbon sequestration accelerated by restoration of grassland biodiversity. Nat. Commun. 10, 1–7 (2019).Article 

Google Scholar 
7.Lange, M. et al. Plant diversity increases soil microbial activity and soil carbon storage. Nat. Commun. 6, 1–8 (2015).
Google Scholar 
8.Young, I. M. & Crawford, J. W. Interactions and self-organization in the soil-microbe complex. Science 304, 1634–1637 (2004).CAS 
PubMed 
Article 

Google Scholar 
9.Rabot, E., Wiesmeier, M., Schlüter, S. & Vogel, H. J. Soil structure as an indicator of soil functions: A review. Geoderma 314, 122–137 (2018).Article 

Google Scholar 
10.Pohl, M., Alig, D., Körner, C. & Rixen, C. Higher plant diversity enhances soil stability in disturbed alpine ecosystems. Plant Soil 324, 91–102 (2009).CAS 
Article 

Google Scholar 
11.Bodner, G., Leitner, D. & Kaul, H. P. Coarse and fine root plants affect pore size distributions differently. Plant Soil 380, 133–151 (2014).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
12.Bacq-Labreuil, A., Crawford, J., Mooney, S. J., Neal, A. L. & Ritz, K. Cover crop species have contrasting influence upon soil structural genesis and microbial community phenotype. Sci. Rep. 9, 1–9 (2019).CAS 
Article 

Google Scholar 
13.Kravchenko, A. N. et al. X-ray computed tomography to predict soil N2O production via bacterial denitrification and N2O emission in contrasting bioenergy cropping systems. GCB Bioenergy 10, 894–909 (2018).CAS 
Article 

Google Scholar 
14.Cambardella, C. A. & Elliott, E. T. Particulate soil organic-matter changes across a grassland cultivation sequence. Soil Sci. Soc. Am. J. 56, 777–783 (1992).Article 

Google Scholar 
15.Gregorich, E. G., Beare, M. H., McKim, U. F. & Skjemstad, J. O. Chemical and biological characteristics of physically uncomplexed organic matter. Soil Sci. Soc. Am. J. 70, 975–985 (2006).CAS 
Article 

Google Scholar 
16.Besnard, E., Chenu, C., Balesdent, J., Puget, P. & Arrouays, D. Fate of particulate organic matter in soil aggregates during cultivation. Eur. J. Soil Sci. 47, 495–503 (1996).CAS 
Article 

Google Scholar 
17.Haddix, M. L. et al. Climate, carbon content, and soil texture control the independent formation and persistence of particulate and mineral-associated organic matter in soil. Geoderma 363, 114160 (2020).CAS 
Article 

Google Scholar 
18.Kuzyakov, Y. & Blagodatskaya, E. Microbial hotspots and hot moments in soil: Concept & review. Soil Biol. Biochem. 83, 184–199 (2015).CAS 
Article 

Google Scholar 
19.Moeslund, J. E. et al. Topographically controlled soil moisture drives plant diversity patterns within grasslands. Biodivers. Conserv. 22, 2151–2166 (2013).Article 

Google Scholar 
20.Shi, P. et al. The effects of ecological construction and topography on soil organic carbon and total nitrogen in the Loess Plateau of China. Environ. Earth Sci. 78, 1–8 (2019).Article 

Google Scholar 
21.Cnudde, V. & Boone, M. N. High-resolution X-ray computed tomography in geosciences: A review of the current technology and applications. Earth-Science Rev. 123, 1–17 (2013).Article 

Google Scholar 
22.Wang, W., Kravchenko, A. N., Smucker, A. J. M., Liang, W. & Rivers, M. L. Intra-aggregate pore characteristics: X-ray computed microtomography analysis. Soil Sci. Soc. Am. J. 76, 1159–1171 (2012).CAS 
Article 

Google Scholar 
23.Diel, J., Vogel, H. J. & Schlüter, S. Impact of wetting and drying cycles on soil structure dynamics. Geoderma 345, 63–71 (2019).CAS 
Article 

Google Scholar 
24.Pires, L. F., Auler, A. C., Roque, W. L. & Mooney, S. J. X-ray microtomography analysis of soil pore structure dynamics under wetting and drying cycles. Geoderma 362, 114103 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
25.Negassa, W. C. et al. Properties of soil pore space regulate pathways of plant residue decomposition and community structure of associated bacteria. PLoS ONE 10, 1–22 (2015).Article 

Google Scholar 
26.Quigley, M. Y., Negassa, W. C., Guber, A. K., Rivers, M. L. & Kravchenko, A. N. Influence of pore characteristics on the fate and distribution of newly added carbon. Front. Environ. Sci. 6, 1–13 (2018).Article 

Google Scholar 
27.Juyal, A., Otten, W., Baveye, P. C. & Eickhorst, T. Influence of soil structure on the spread of Pseudomonas fluorescens in soil at microscale. Eur. J. Soil Sci. 72, 141–153 (2021).CAS 
Article 

Google Scholar 
28.Kravchenko, A. N., Negassa, W., Guber, A. K. & Schmidt, S. New approach to measure soil particulate organic matter in intact samples using X-ray computed microtomography. Soil Sci. Soc. Am. J. 78, 1177–1185 (2014).Article 

Google Scholar 
29.Peth, S. et al. Localization of soil organic matter in soil aggregates using synchrotron-based X-ray microtomography. Soil Biol. Biochem. 78, 189–194 (2014).CAS 
Article 

Google Scholar 
30.Gee, G. W. & Or, D. 2.4 Particle-Size Analysis (Soil Science Society of America, 2018).
Google Scholar 
31.Schindelin, J. et al. Fiji: An open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).CAS 
PubMed 
Article 

Google Scholar 
32.Münch, B. & Holzer, L. Contradicting geometrical concepts in pore size analysis attained with electron microscopy and mercury intrusion. J. Am. Ceram. Soc. 91, 4059–4067 (2008).Article 

Google Scholar 
33.Houston, A. N., Otten, W., Baveye, P. C. & Hapca, S. Adaptive-window indicator kriging: A thresholding method for computed tomography images of porous media. Comput. Geosci. 54, 239–248 (2013).Article 

Google Scholar 
34.Doube, M. et al. BoneJ: Free and extensible bone image analysis in ImageJ. Bone 47, 1076–1079 (2010).PubMed 
PubMed Central 
Article 

Google Scholar 
35.Houston, A. N. et al. Effect of scanning and image reconstruction settings in X-ray computed microtomography on quality and segmentation of 3D soil images. Geoderma 207–208, 154–165 (2013).Article 

Google Scholar 
36.Milliken, G. A. & Johnson, D. E. Analysis of Messy Data, Volume II: Nonreplicated experiments. Analysis of Messy Data, Volume II: Nonreplicated Experiments (Chaoman/CRC Press, 2017).Book 

Google Scholar 
37.Ladoni, M., Basir, A., Robertson, P. G. & Kravchenko, A. N. Scaling-up: Cover crops differentially influence soil carbon in agricultural fields with diverse topography. Agric. Ecosyst. Environ. 225, 93–103 (2016).Article 

Google Scholar 
38.Ontl, T. A., Hofmockel, K. S., Cambardella, C. A., Schulte, L. A. & Kolka, R. K. Topographic and soil influences on root productivity of three bioenergy cropping systems. New Phytol. 199, 727–737 (2013).CAS 
PubMed 
Article 

Google Scholar 
39.Zhu, M. et al. Effects of topography on soil organic carbon stocks in grasslands of a semiarid alpine region, northwestern China. J. Soils Sediments 19, 1640–1650 (2019).CAS 
Article 

Google Scholar 
40.Shi, P. et al. Land-use types and slope topography affect the soil labile carbon fractions in the Loess hilly-gully area of Shaanxi, China. Arch. Agron. Soil Sci. 66, 638–650 (2020).CAS 
Article 

Google Scholar 
41.Ontl, T. A., Cambardella, C. A., Schulte, L. A. & Kolka, R. K. Factors influencing soil aggregation and particulate organic matter responses to bioenergy crops across a topographic gradient. Geoderma 255–256, 1–11 (2015).Article 

Google Scholar 
42.Kravchenko, A. N. et al. Spatial patterns of extracellular enzymes: Combining X-ray computed micro-tomography and 2D zymography. Soil Biol. Biochem. 135, 411–419 (2019).CAS 
Article 

Google Scholar 
43.Cotrufo, M. F., Wallenstein, M. D., Boot, C. M., Denef, K. & Paul, E. The Microbial Efficiency-Matrix Stabilization (MEMS) framework integrates plant litter decomposition with soil organic matter stabilization: Do labile plant inputs form stable soil organic matter?. Glob. Change Biol. 19, 988–995 (2013).Article 

Google Scholar 
44.Oades, J. M. The role of biology in the formation, stabilization and degradation of soil structure. Geoderma 56, 377–400 (1993).Article 

Google Scholar 
45.Kravchenko, A. N. & Guber, A. K. Soil pores and their contributions to soil carbon processes. Geoderma 287, 31–39 (2017).CAS 
Article 

Google Scholar 
46.Wickings, K., Grandy, A. S. & Kravchenko, A. N. Going with the flow: Landscape position drives differences in microbial biomass and activity in conventional, low input, and organic agricultural systems in the Midwestern U.S. Agric. Ecosyst. Environ. 218, 1–10 (2016).Article 

Google Scholar 
47.da Jesus, E. C. et al. Influence of corn, switchgrass, and prairie cropping systems on soil microbial communities in the upper Midwest of the United States. GCB Bioenergy 8, 481–494 (2016).CAS 
Article 

Google Scholar 
48.Poirier, V., Roumet, C. & Munson, A. D. The root of the matter: Linking root traits and soil organic matter stabilization processes. Soil Biol. Biochem. 120, 246–259 (2018).CAS 
Article 

Google Scholar 
49.Toosi, E. R., Kravchenko, A. N., Guber, A. K. & Rivers, M. L. Pore characteristics regulate priming and fate of carbon from plant residue. Soil Biol. Biochem. 113, 219–230 (2017).CAS 
Article 

Google Scholar  More

Eukaryote composition (V9_PR2)Using V9_PR2 we were able to assign a total of 15 668 (shotgun) and 90 689 reads for the shotgun and amplicon data, respectively. These reads represented 14%, 54%, 0 and 32% (shotgun), and 0%, 29%, 0 and 71% (amplicon) unassigned cellular organisms, Bacteria, Archaea and Eukaryota, respectively. Within the eukaryotes, we determined 51 and 64 taxa for shotgun and amplicon data, respectively. Abundant taxa (average abundance >0.1% across all samples; 31 and 27 taxa in shotgun and amplicon, respectively) are shown in Fig. 2. The latter includes 23 taxa (including assignments made on “Eukaryota” level) that were shared between shotgun and amplicon, and four taxa only detected in the amplicon data (Fig. 2C).Fig. 2: Eukaryote composition in five Santa Barbara Basin sediment samples post-alignment with V9_PR2 database.Composition is shown in relative abundances for (A) shotgun, and (B) amplicon data (phylum-level). The surface sample should be considered with caution in both (A) and (B) due to the possibility of contamination (see “Methods”). C Venn diagram showing eukaryote taxa richness (phylum level) in the shotgun and amplicon data after alignment with the V9_PR2 database (diagram areas are proportional to the total number of taxa included, for a list of shared/non-shared taxa see Supplementary Material Fig. 1). Only taxa abundant on average >0.1% are included, as they make up >99% of the eukaryote composition.Full size imageWithin shotgun, the most abundant eukaryotes were Ascomycota (53%), Telonemia (11%), Eukaryota (not further determined, 8%), Polycystinea (4%), Dinophyceae (3.8%), Streptophyta (3.2%), Amoebozoa (3%), Cercozoa (1.6%), Bacillariophyta (1.6%), Arthropoda (1%). In the amplicon data, the most abundant eukaryotes were Ascomycota (33%), Apicomplexa (30%), Dinophyceae (9.5%), Stramenopiles (6.3%), Eukaryota (4.9%), Polycystinea (3.5%), Foraminifera (3.2%), Cercozoa (1.1%) and Chordata (1%). Thus, a total of 10 and 9 taxa were abundant with >1% (average across all samples) in the shotgun and amplicon data, including only five taxa (Ascomycota, Eukaryota, Dinophyceae, Polycystinea, Cercozoa) that were picked up by both methods (i.e., are amongst the shared taxa in Fig. 2C, Supplementary Material Fig. 1). Taxa detected by one method or the other were slightly rarer species (between 0.1 and 1% average relative abundance across all samples; Supplementary Material Table 3).The shotgun EBC detected two taxonomic groups, one prokaryotic (Gammaproteobacteria) and one eukaryotic (Poacea). The amplicon EBC detected 46 taxa, of which 12 were prokaryotes and 34 were eukaryotes, including dinoflagellate taxa (Dinophysis and Alexandrium), Calanoida and Bacillariophyta (copepods and diatoms, respectively; Supplementary Material Table 1). While any reads assigned to EBC taxa were removed from samples, including reads assigned to the Bacillariophyta node, reads assigned to Bacillariophyta at lower taxonomic levels (e.g., Bacillariophycidae, Bacillariaceae, etc.) remain summarised under the phylum-level Bacillariophyta node (Fig. 2).Relationship between Eukaryota composition and V9_PR2 reference sequence lengthV9_PR2 reference sequence-lengths for the relatively abundant taxa ( >0.1% across all samples, including all taxa that were shared and assigned below eukaryote-level, i.e., 22 taxa, see Supplementary Material Table 3) were around the overall average sequence length of the V9_PR2 database (121 bp) (Fig. 3). However, considerable length variation was observed, with most of the abundant taxa being represented by shorter than average reference sequences in the V9_PR2 database, and a few taxa (e.g., Arthropoda, Opisthokonta and Amoebozoa) with a number of reference sequences longer than average (Fig. 3).Fig. 3: Average sequence lengths for individual eukaryote taxa as per in the V9_PR2 database (A) and read counts for these taxa in shotgun (SG) and amplicon (Ampl) data (B).Listed are all taxa that occurred on average >0.1% across all samples in either the shotgun or amplicon dataset, or both. Only taxa that were determined in both shotgun and amplicon data are included.Full size imageWe determined a negative correlation between the average V9_PR2 reference sequence length (V9PR2AL) and the A:SG read counts ratio per taxon for all samples (rV9PR2AL,A:SG_1.2 = −0.27269, rV9PR2AL,A:SG_4.3 = −0.33233, rV9PR2AL,A:SG_7.3 = −0.28064, rV9PR2AL,A:SG_11.8 = −0.32559, rV9PR2AL,A:SG_16.4 = −0.30078). This means that shorter V9_PR2 reference sequences for our abundant taxa were associated with an overamplification of these taxa in the amplicon data (for average V9_PR2 reference sequence length of the abundant taxa and A:SG ratios see Supplementary Material Table 4).Eukaryota and Bacillariophyta sequence length and coverage post-V9_PR2 alignmentSequences assigned to Eukaryota in shotgun were on average 112 bp and in amplicon data 161 bp, i.e., shotgun reads were around ~50 bp shorter than amplicon reads (Table 2). Bases covered in shotgun were ~40 bp shorter than in amplicon data (Table 2). Similarly, sequences assigned to Bacillariophyta were on average 124 and 167 bp in shotgun and amplicon data, respectively, so showed an ~40 bp difference. For Eukaryota, there was a difference of ~23 bp and 29 bp between sequence length and coverage in shotgun and amplicon data, respectively. For Bacillariophyta, we found a ~36 and ~37 bp difference between sequence length and coverage in shotgun and amplicon data, respectively.Table 2 Lengths and coverage of sequences assigned to Eukaryota and Bacillariophyta in shotgun and amplicon data.Full size tableBacillariophyta read lengths and coverage were similar to those of Eukaryota, for both shotgun and amplicon data (Table 2). Variation in sequence lengths and coverage was much higher in shotgun than in amplicon data. We found no trend towards shorter (i.e., more fragmented) sequences with increasing subseafloor depth for either Eukaryota or Bacillariophyta in the shotgun data. Eukaryota shotgun read lengths were on average ~9 bp shorter (112 bp) than the average reference sequences in the V9_PR2 database (121 bp).Diatom composition detected via diat-rbcL and read length characteristicsA total of 60 (shotgun) and 80 674 (amplicon) reads were assigned to diatoms (Fig. 4). In total, 27 taxa were determined in the shotgun, and 140 in the amplicon dataset. When considering the “abundant” taxa (on average >0.1%), 27 and 49 diatoms were determined in the shotgun and amplicon data, respectively (Fig. 4). A total of 10 taxa were shared between the two datasets Bacillariophyta, Bacillariophycidae, Chaetoceros, C. cf. pseudobrevis 2 SEH-2013, Pseudo-nitzschia, P. fryxelliana, Thalassiosiraceae, Thalassiosirales, Thalassiosira and T. oceanica (Fig. 4C, Supplementary Material Fig. 2). Sequences assigned to diatoms via diat-rbcL were shorter (by ~16 bp) in the shotgun than in the amplicon data, with amplicon read lengths and coverage all 76 + 1 bases (Table 3).Fig. 4: Diatom composition in the Santa Barbara Basin sediment samples post-alignment with diat-rbcL database.Diatom composition is shown as relative abundance for (A) shotgun and (B) amplicon data. The surface sample should be considered with caution in both (A) and (B) due to the possibility of contamination (see “Methods”). C Venn diagram showing diatom taxa richness (species level) in the shotgun and amplicon data after alignment with the diat-rbcL database (diagram areas are proportional to the total number of taxa included, for a list of shared/non-shared taxa see Supplementary Material Fig. 2). Only taxa abundant on average >0.1% are included (in A, B, C).Full size imageTable 3 Bacillariophyta sequence lengths in shotgun and amplicon datasets.Full size tableNo diatoms were detected in the shotgun EBC, however, 45 taxa were determined in the amplicon EBC with most reads assigned to Chaetoceros spp. (especially, Chaetoceros debilis, C. socialis and C. radicans), several Thalassiosira and Pseudo-nitzschia species, as well as others (Supplementary Material Table 2).Comparison of V9_PR2 vs. diat-rbcL derived diatom compositionIn the shotgun data, 79 and 60 sequences were assigned to diatoms using V9_PR2 and diat-rbcL as the reference database, respectively, and composition differed considerably (Fig. 5). Using V9_PR2, diatoms were mostly assigned on relatively high taxonomic levels (e.g., Bacillariophyta) with few taxa being differentiated sporadically in the different samples (Fig. 5A, Supplementary Material Fig. 3). Using diat-rbcL, Chaetoceros, Thalassiosira and Pseudo-nitzschia were more prominent (Fig. 5B).Fig. 5: Comparison of diatom composition in Santa Barbara Basin sediment samples determined in shotgun and amplicon data using the V9_PR2 and diat-rbcL databases.Relative abundance of diatoms (genus level) in the shotgun data after aligning to (A) V9_PR2 and (B) diat-rbcL. Relative abundance of diatoms (genus level) in the amplicon data after aligning to (C) V9_PR2 and (D) diat-rbcL. The surface sample should be considered with caution in (A–D) due to the possibility of contamination (see “Methods”). Venn diagrams of shared and non-shared diatom taxa after alignment to the V9_PR2 (18S-V9) and diat-rbcL databases for the shotgun (E) and amplicon (F) data (species level, diagram areas are proportional to the total number of species included). For a complete species list and their read counts per sample see Supplementary Material Fig. 3, Supplementary Material Table 5.Full size imageIn the amplicon data, 329 sequences were assigned to diatoms using V9_PR2, and 80 674 using diat-rbcL. Using V9_PR2, few taxa were detected in the two top samples (Leptocylindrus and Fragilariaceae at 1.2 mbsf, Bacillariophycidae and Bacillariaceae at 4.3 mbsf) while the lowermost samples were more diverse (Fig. 5C). Using diat-rbcL, most reads were assigned to Thalassiosira, Chaetoceros, and Pseudo-nitzschia, with other taxa sporadically occurring at different depths (Fig. 5D). For a complete species list and their read counts see Supplementary Material Fig. 3, and Supplementary Material Table 5.We found large differences in the number of shared vs. non-shared taxa between shotgun and amplicon data, and V9_PR2 and diat-rbcL alignments (Fig. 5E, F). Database inspections showed that all taxa detected via V9_PR2 were also represented in the diat-rbcL database, except Rhizosoleniaceae. However, out of the 22 taxa exclusively detected via diat-rbcL in shotgun (Fig. 5E, F), 10 are only represented in the diat-rbcL database (Pseudo-nitzschia caciantha, P. dolorosa, Chaetoceros cf. contortus 1 SEH-2013, C. cf. lorenzianus 2 SEH-2013, C. cf. pseudobrevis 2 SEH-2013, Thalassiosirales, Thalassiosiraceae, Coscinodiscus wailesii, Arcocellulus mammifer, Meuniera membranacea, Supplementary Material Fig. 3). Similarly, out of the 134 taxa exclusively detected via diat-rbcl in amplicon, 84 were in this database only, noticeably including several species and strains of Chaetoceros, Pseudo-nitzschia, Thalassiosira and Cylindrotheca (eg., additions SHE-2013, BOF in species names), amongst others (see Supplementary Material Fig. 3, Supplementary Material Table 5). More

The Wuikinuxv, Kitasoo/Xai’xais, Heiltsuk and Nuxalk First Nations hold Indigenous rights to their territories, where all data were collected. Scientific staff who are members of these Nations or who work directly for them had direct approvals from Indigenous rights holders and were exempt from other research permit requirements. Collaborating DFO scientists worked in partnership with the First Nations to collect data in their territories..Sampling targeted rocky reefs, the preferred habitat for most Sebastidae38, which we located through local Indigenous knowledge or a bathymetric model49. Data were collected by four fishery-independent methods—shallow diver transects, mid-depth video transects, deep video transects, and hook-and-line sampling—detailed in earlier publications32,33,34,35,50,51 and summarized in Table 1. Data had a spatial resolution of ≤ 130 m2 and each sampling location (N = 2936 for Sebastidae, 2654 for sponges, 2321 for corals) was ascribed to a 1-km2 planning unit within the standardized grid used to design the MPA network (N = 632 for Sebastidae, 525 for sponges, 529 for corals, 516 inclusive of surveys for all taxonomic groups).Table 1 Survey methods used for data collection.Full size tableAlthough sampling encompassed 11 years (2006–2007, 2013–2021: Table 1), 84% of 1-km2 planning units were sampled during only one year (Appendix S2). Analyses, therefore, focus on spatial variability in species distributions and do not address temporal variability within planning units. When all years and methods are combined, 1-km2 planning units had a median of 3 samples (range = 1 to 80, Q1 = 2, Q3 = 6) (i.e., sum of dive transects, video sub-transects, and hook-and-line sessions). Supplementary Data Set 1 reports sampling effort by 1-km2 planning unit, survey type, and year (see Data Availability for link to these data).For each 1-km2 planning unit, u, we calculated hotspot indices for Sebastidae (BSEB,u), structural corals (BCor,u), and large-bodied sponges (BSp,u). These indices did not consider cup corals, whip-like corals or encrusting corals or sponges.As detailed below (Eqs. 1–4), each species of Sebastidae or genera of corals contributed to BSEB,u or BCor,u, according to their abundance weighted by Wt: a conservation prioritization score based on taxon characteristics. For the 26 species of Sebastidae that we observed, Wt equaled the sum of scores for (1) fishery vulnerability, using intrinsic population growth rate, r, as a proxy variable52,53, (2) depletion level, using the ratio of recent biomass to unfished biomass as a proxy variable, (3) ecological role, with trophic level as proxy, and (4) evolutionary distinctiveness14 (Table 2; Appendix S3). Because several rockfishes are very long-lived (i.e., have low values for r) and depleted, maximum potential scores were twice as large for fishery vulnerability and depletion level than for ecological role and evolutionary distinctiveness. Data for depletion level and evolutionary distinctiveness were unavailable for some species, and score calculations (detailed in Table 2) account for missing values (Appendix S3).Table 2 Criteria and equations used to calculate the conservation prioritization score, Wt, for each species of Sebastidae and for each taxa of structural corals.Full size tableFor the 6 genera of structural corals analyzed (Appendix S4), Wt depended on mean height (estimated from video transect images: Table 1), which correlates positively with vulnerability to physical damage from bottom-contact fishing gear (including longer time to recovery)20,54,55 and with strength of ecological role (e.g., amount of biogenic habitat and carbon sequestration increases with height)44,56 (Table 2, Appendix S4). Wt for corals did not include depletion level due to lack of data.The hotspot index for large-bodied sponges, BSp,u did not differentiate between species characteristics (i.e., ({W}_{t}=1)) and we pooled the abundances of all observed species of Hexactinellidae (Aphrocallistes vastus, Farrea occa, Heterochone calyx, Rhabdocalyptus dawsoni, Staurocalyptus dowlingi) and Demospongiae (Mycale cf loveni). This approach is consistent with regional fishery bodies worldwide, which treat large-bodied sponges as a single functional group57.To derive hotspot indices for each taxonomic group (Sebastidae, structural corals, or large-bodied sponges), we first developed a set of candidate generalized linear mixed models (GLMM) to explain relative abundance data for rockfish, corals, and sponges. For each GLMM, we estimated ({lambda }_{t,i,l}), the expected counts (or expected percent cover) for taxa t obtained with survey method i at point location l. (Point locations are individual dive transects, video transect bins, or hook-and-line timed sessions: Table 1.) Specifically,$${lambda }_{t,i,l}=gleft(beta {X}_{t,i,l}right)$$
(1)
$${C}_{t,i,l}mathrm {, or ,} {D}_{t,i,l}sim fleft({lambda }_{t,i,l}right)$$
(2)
where g was the link function for the GLMM and f the distribution for the likelihood function modelling either the observed counts C (negative binomial) for Sebastidae and structural corals or a combination of counts (negative binomial) and percent cover D (beta distribution) for large-bodied sponges. We used multiple GLMMs to model large-bodied sponges because deep video transects recorded actual counts whereas dive or mid-depth video transects recorded percent cover categories (Table 1).For each taxonomic group, we estimated a set of coefficients (beta) for the vector of X covariates that best estimated counts or percent cover. Our hypothesized covariates included the 1-km2 planning unit (modelled as a random intercept to control for repeated measures within a given planning unit), survey method, depth (including both linear or a 2nd order polynomial), and taxa. Each GLMM controlled for sample effort as an offset—effort was measured either as area covered by dive transects or video bins, or the duration of hook-and-line sessions. We also tested for possible covariate’s effects on the dispersion parameter (for the negative binomial GLMMs) and zero-inflation terms (for both the negative binomial and beta GLMMs). The best set of covariates to predict counts or percent cover were then chosen based on AIC model selection criteria. All models were fitted using ‘glmmTMB’58 in R version 4.0.259, and simulated residuals and diagnostic tests performed for each best-fit model using the package ‘DHARMa’60. For example, our best model for Sebastidae counts predicted 2% fewer zero counts than were observed.We applied depth and survey method selectivity criteria to reduce excessive zeroes in the count data that may be biologically unjustified (Appendix S5). For all taxon, if i detected t, then the method was valid for that taxon. If i did not detect t and t is a Sebastidae, then the method was valid (i.e., count = 0) only if the overall 10th and 90th percentiles of depths sampled by that method encompassed the expected depth range of t (Appendix S5). If i did not detect t and t is a coral or sponge (which are rarer than Sebastidae), then the method is valid only if the depth of the sampling event exceeded or equaled the minimum expected depth of t. Also, hook-and-line gear cannot systematically sample sessile benthic organisms or planktivores and this method was valid only for non-planktivorous Sebastidae (Appendix S5).Using the best-fit models from above, we calculated the expected count (or percent cover) per unit of effort, (mu), for taxa t observed with method i at each planning unit u:$${mu }_{t,i,u}=frac{{sum }_{l=1}^{{n}_{i,u}}left({lambda }_{t,i,l}right)}{{sum }_{l=1}^{{n}_{i,u}}left({mathrm{E}}_{t,i,l}right)}$$
(3)
where ({n}_{i,u}) was the total number of point locations sampled by that method within the planning unit and effort was either the cumulative area covered by dive or video surveys or the cumulative duration of hook-and-line sampling sessions within the planning unit. Because survey methods differed in their maximum values and potential biases (e.g., field of view is greater for divers than for video cameras; hook-and-line gear samples one fish at a time while visual methods can observe multiple fish simultaneously),({mu }_{t,i,u}) was rescaled as a min–max normalization,({mu }_{t,i,u}^{^{prime}}) (i.e., difference between the observed value and the minimum value across all u, divided by the range of values across all u).The hotspot index for each of Sebastidae, structural corals, and large-bodied sponges (denoted as taxonomic group g) was then calculated for each planning unit as:$${B}_{g,u }={sum }_{t=1}^{{n}_{s,g}}{sum }_{i=1}^{{n}_{m,g}}{mu }_{t,i,u}^{^{prime}}{W}_{t}$$
(4)
where Wt was the taxon-specific weighing factor (Table 2, Appendices S3, S4), ({n}_{s,g}) was the number of species in taxonomic group g, and ({n}_{m,g}) was the number of valid methods to sample group g.For each 1-km2 planning unit where all taxonomic groups were surveyed (N = 518), we then calculated the overall hotspot index:$${B}_{o,u }=H{sum }_{g=1}^{G}{B}_{g,u}.$$
(5)
where H is Shannon’s evenness index, with proportional abundance of each taxonomic group represented by BSEB,u, BCor,u, and BSp,u.Hotspot index values were normalized as the proportion of the maximum value and converted to decile ranks. Relationships between decile ranks and index values were nonlinear (Appendix S6).For Sebastidae, large-bodied sponges, and the overall hotspot index, we defined hotspots as planning units containing decile ranks 9 or 10: criterion which we deemed appropriate for the small spatial scales of conservation planning being used for the central portion of the Northern Shelf Bioregion (16-km2 planning units in Fig. 2). We are aware that other studies define hotspots based on a narrower range of values (e.g., top 10%26; top 2.5%28) but their context is generally one in which conservation planning is done at a much greater scale (e.g., ≈50,000-km2 grid cells26;1° latitude × 1° longitude grid cells28). For structural corals, which had near-zero index values in all but the top-ranking planning units (Appendix S6), we defined hotspots as planning units containing decile rank 10.Maximum depths sampled within planning units were deepest in the Mainland Fjord and shallowest in the Aristazabal Banks Upwelling Upper Ocean Subregion (Appendix S7). Accordingly, we used multiple logistic regression implemented with the ‘glm’ function in R to estimate the probabilities hotspot occurrence within 1-km2 planning units in relation to maximum depth sampled (including a 2nd-order polynomial) and Upper Ocean Subregion. Competing models were compared with AIC model selection procedures.Following the directive of Central Coast First Nations, decile rank distributions were mapped as 16-km2 planning units, u16 (N = 283 for Sebastidae, 264 for sponges, 263 for corals, 260 inclusive of surveys for all taxonomic groups), thereby protecting sensitive locations that would be revealed at smaller scales. To do so, we took the average between the maximum index value and the mean of the remainder of index values among the 1-km2 planning units, u, contained within each u16, and converted these values into decile ranks. This approach balances conservation prioritization among u16 that may have good average index values for multiple u, and u16 with a single high-ranking u among multiple low-scoring u. Relationships between decile ranks and hotspot index values also were nonlinear at this scale (Appendix S6). The same hotspot definitions developed for u apply to u16.Eighty one percent of 16-km2 planning units were sampled during only one or two years (Appendix S2). When all years and methods are combined, 16-km2 planning units had a median of 6 samples (range = 1 to 110, Q1 = 3, Q3 = 13). Supplementary Data Set 2 reports sampling effort by 16-km2 planning unit, survey type, and year (see Data Availability for link to these data). More

1.BirdLife International. Neophron percnopterus, Egyptian vulture. http://www.iucnredlist.org/details/22695180/0 (2017) https://doi.org/10.2305/IUCN.UK.2017-3.RLTS.T22695180A118600142.en2.Gradev, G., Garcia, V., Ivanov, I., Zhelev, P. & Kmetova, E. Data from Egyptian vultures (Neophron percnopterus) tagged with GPS/GSM transmitters in Bulgaria. Acta Zool. Bulg. 64, 141–146 (2012).
Google Scholar 
3.Green, R. E. et al. Diclofenac poisoning as a cause of vulture population declines across the Indian subcontinent. J. Appl. Ecol. 41, 793–800 (2004).CAS 
Article 

Google Scholar 
4.Arkumarev, V., Dobrev, V., Abebe, Y. D., Popgeorgiev, G. & Nikolov, S. C. Congregations of wintering Egyptian Vultures Neophron percnopterus in Afar, Ethiopia: Present status and implications for conservation. Ostrich 85, 139–145 (2014).Article 

Google Scholar 
5.Grubač, B., Velevski, M. & Avukatov, V. Long-term population decrease and recent breeding performance of the Egyptian vulture Neophron percnopterus in Macedonia. North. West. J. Zool. 10, 25–35 (2014).
Google Scholar 
6.Angelov, I., Hashim, I. & Oppel, S. Persistent electrocution mortality of Egyptian vultures neophron percnopterus over 28 years in East Africa. Bird Conserv. Int. 23, 1–6 (2013).Article 

Google Scholar 
7.Zuberogoitia, I., Zabala, J., Martínez, J. A., Martínez, J. E. & Azkona, A. Effect of human activities on Egyptian vulture breeding success. Anim. Conserv. 11, 313–320 (2008).Article 

Google Scholar 
8.Sen, B., Avares, J. P. & Bilgin, C. C. Nest site selection patterns of a local Egyptian Vulture Neophron percnopterus population in Turkey. Bird Conserv. Int. 27, 568–581 (2017).Article 

Google Scholar 
9.Ceballos, O. & Donázar, J. A. Factors influencing the breeding density and nest-site selection of the Egyptian vulture (Neophron percnopterus). J. Ornithol. 130, 353–359 (1989).Article 

Google Scholar 
10.Sarà, M. & Vittorio, M. Factors influencing the distribution, abundance and nest-site selection of an endangered Egyptian vulture (Neophron percnopterus) population in Sicily. Anim. Conserv. 6, 317–328 (2003).Article 

Google Scholar 
11.KC, K. B. et al. Factors influencing the presence of the endangered Egyptian vulture Neophron percnopterus in Rukum, Nepal. Glob. Ecol. Conserv. 20, e00727 (2019).Article 

Google Scholar 
12.Mateo-Tomás, P. & Olea, P. P. Livestock-driven land use change to model species distributions: Egyptian vulture as a case study. Ecol. Indic. 57, 331–340 (2015).Article 

Google Scholar 
13.García-RIPOLLÉS, C., López-LÓPEZ, P. & Urios, V. First description of migration and wintering of adult Egyptian vultures neophron percnopterus tracked by GPS satellite telemetry. Bird Study 57, 261–265 (2010).Article 

Google Scholar 
14.Oppel, S. et al. Landscape factors affecting territory occupancy and breeding success of Egyptian vultures on the Balkan Peninsula. J. Ornithol. 158, 443–457 (2017).Article 

Google Scholar 
15.Bhusal, K. Population status and breeding success of Himalayan Griffon, Egyption vulture and Lammergeier in Gherabhir, Arghakhanchi, Nepal. (MSc thesis. Institute of Science and Technology, Tribuvan University, Kritipur, Nepal, 2011). https://doi.org/10.13140/RG.2.2.18494.69447.16.López-lópez, A. P. et al. Food predictability determines space use of endangered vultures: Implications for management of supplementary feeding. Ecol. Appl. 24, 938–949 (2014).PubMed 
Article 

Google Scholar 
17.Cortés-avizanda, A., Ceballos, O. & Donázar, J. Long-term trends in population size and breeding success in the Egyptian Vulture (Neophron percnopterus) in Northern Spain. J. Raptor Res. 43, 43–49 (2009).Article 

Google Scholar 
18.Rosenblatt, E. Neophron percnopterus Egyptian vulture. Animal Diversity Web https://animaldiversity.org/accounts/Neophron_percnopterus/ (2007).19.ESRI. ArcGIS Desktop: Release 10.5. Environmental systems research Redlands, California, USA https://www.arcgis.com/features/index.html (2017).20.Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978 (2005).Article 

Google Scholar 
21.USGS/EarthExplorer. Data Sets. United States Geological Survey https://earthexplorer.usgs.gov/ (2017).22.JAXA EORC. Global PALSAR-2/PALSAR/JERS-1 Mosaic and Forest/Non-forest Map. Earth Observation Research Center https://www.eorc.jaxa.jp/ALOS/en/palsar_fnf/data/index.htm (2017).23.CIESIN. Gridded population of the world (GPW), v4. http://sedac.ciesin.columbia.edu/data/collection/gpw-v4 (2000).24.Robinson, T. P. et al. Mapping the global distribution of livestock. PLoS ONE 9, e96084 (2014).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
25.FAO/GeoNetwork. Global land cover share database. http://www.fao.org/geonetwork/srv/en/main.home (2014).26.Elith, J. et al. Novel methods improve prediction of species’ distributions from occurrence data. Ecography (Cop.) 29, 129–151 (2006).Article 

Google Scholar 
27.Phillips, S. J., Anderson, R. P. & Schapire, R. E. Maximum entropy modelling of species geographic distributions. Ecol. Modell. 190, 231–259 (2006).Article 

Google Scholar 
28.Lobo, J. M., Jiménez-valverde, A. & Real, R. AUC: a misleading measure of the performance of predictive distribution models. Glob. Ecol. Biogeogr. 17, 145–151 (2008).Article 

Google Scholar 
29.Allouche, O., Tsoar, A. & Kadmon, R. Assessing the accuracy of species distribution models : Prevalence, kappa and the true skill statistic (TSS). J. Appl. Ecol. 43, 1223–1232 (2006).Article 

Google Scholar 
30.Pearce, J. & Ferrier, S. Evaluating the predictive performance of habitat models developed using logistic regression. Ecol. Modell. 133, 225–245 (2000).Article 

Google Scholar 
31.Barbet-Massin, M., Jiguet, F., Albert, C. H. & Thuiller, W. Selecting pseudo-absences for species distribution models: how, where and how many?. Methods Ecol. Evol. 3, 327–338 (2012).Article 

Google Scholar 
32.Liu, C., White, M. & Newell, G. Selecting thresholds for the prediction of species occurrence with presence-only data. J. Biogeogr. 40, 778–789 (2013).Article 

Google Scholar 
33.Cortés-Avizanda, A., Martín-López, B., Ceballos, O. & Pereira, H. M. Stakeholders perceptions of the endangered Egyptian vulture: Insights for conservation. Biol. Conserv. 218, 173–180 (2018).Article 

Google Scholar 
34.Hernández, M. & Margalida, A. Poison-related mortality effects in the endangered Egyptian vulture (Neophron percnopterus) population in Spain. Eur. J. Wildl. Res. 55, 415–423 (2009).Article 

Google Scholar 
35.Mateo-Tomás, P., Olea, P. P. & Fombellida, I. Status of the Endangered Egyptian vulture Neophron percnopterus in the Cantabrian Mountains, Spain, and assessment of threats. Oryx 44, 434–440 (2010).Article 

Google Scholar 
36.Carrete, M. et al. Habitat, human pressure, and social behavior : Partialling out factors affecting large-scale territory extinction in an endangered vulture. Biol. Conserv. https://doi.org/10.1016/j.biocon.2006.11.025 (2007).Article 

Google Scholar 
37.Zuberogoitia, I., Zabala, J., Martínez, J. E., González-Oreja, J. A. & López-López, P. Effective conservation measures to mitigate the impact of human disturbances on the endangered Egyptian vulture. Anim. Conserv. 17, 410–418 (2014).Article 

Google Scholar 
38.Garcia-Ripolles, C. & Lopez-Lopez, P. Population size and breeding performance of Egyptian vultures (Neophron percnopterus) in eastern Iberian Peninsula. J. Raptor Res. 40, 217–221 (2006).Article 

Google Scholar 
39.Velevski, M., Grubac, B. & Tomovic, L. Population viability analysis of the Egyptian vulture Neophron percnopterus in Macedonia and Implications for Its Conservation. Acta Zool. Bulg. 66, 43–58 (2014).
Google Scholar 
40.Arkumarev, V. et al. Breeding performance and population trend of the Egyptian vulture Neophron percnopterus in Bulgaria conservation implications. Ornis Fenn. 95, 115–127 (2018).
Google Scholar 
41.Dobrev, V. et al. Habitat of the Egyptian vulture (Neophron percnopterus) in Bulgaria and Greece (2003–2014). (2016).42.Milchev, B., Spassov, N. & Popov, V. Diet of the Egyptian vulture (Neophron percnopterus) after livestock reduction in Eastern Bulgaria. N. West. J. Zool. 8, 315–323 (2012).
Google Scholar 
43.Milchev, B. & Georgiev, V. Extinction of the globally endangered Egyptian vulture Neophron percnopterus breeding in SE Bulgaria. N. West. J. Zool. 10, 266–272 (2014).
Google Scholar 
44.Poirazidis, K., Goutner, V., Skartsi, T. & Stamou, G. Modelling nesting habitat as a conservation tool for the Eurasian black vulture (Aegypius monachus) in Dadia Nature Reserve, northeastern Greece. Biol. Conserv. 118, 235–248 (2004).Article 

Google Scholar 
45.Sanchis Serra, A. et al. Towards the identification of a new taphonomic agent: An analysis of bone accumulations obtained from modern Egyptian vulture (Neophron percnopterus) nests. Quat. Int. 330, 136–149 (2014).Article 

Google Scholar 
46.Vittorio, M. D., Lopez-Lopez, P., Cortone, G. & Luiselli, L. The diet of the Egyptian vulture (Neophron percnopterus) in Sicily: Temporal variation and conservation implications. Vie Milieu Life Environ. 67, 1–8 (2017).
Google Scholar 
47.Di Vittorio, M. et al. Successful fostering of a captive-born Egyptian Vulture (Neophron Percnopterus) in Sicily. J. Raptor Res. 40, 247–248 (2006).Article 

Google Scholar 
48.Sarà, M., Grenci, S. & Vittorio, M. D. Status of Egyptian vulture (Neophron percnopterus) in Sicily. J. Raptor Res. 43, 66–69 (2009).Article 

Google Scholar 
49.Vittorio, M. D. et al. Dispersal of Egyptian vultures Neophron percnopterus: the first case of long-distance relocation of an individual from France to Sicily. Ringing Migr. 31, 111–114 (2016).Article 

Google Scholar 
50.García-Heras, M. S., Cortés-Avizanda, A. & Donázar, J. A. Who are we feeding? Asymmetric individual use of surplus food resources in an insular population of the endangered Egyptian vulture Neophron percnopterus. PLoS ONE 8, e80523 (2013).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
51.Gangoso, L. et al. Susceptibility to infection and immune response in insular and continental populations of Egyptian vulture: Implications for conservation. PLoS ONE 4, e6333 (2009).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
52.Donazar, J. A. et al. Conservation status and limiting factors in the endangered population of Egyptian vulture (Neophron percnopterus) in the Canary Islands Conservation status and limiting factors in the endangered population of Egyptian vulture ( Neophron percnopterus ) in. Biol. Conserv. 107, 89–97 (2002).Article 

Google Scholar 
53.Rodríguez, B., Rodríguez, A., Siverio, F. & Siverio, M. Factors affecting the spatial distribution and breeding habitat of an insular cliff-nesting raptor community. Curr. Zool. 64, 173–181 (2018).PubMed 
Article 

Google Scholar 
54.Kret, E. et al. First documented case of the killing of an egyptian vulture (Neophron Percnopterus) for belief-based practices in Western Africa. Life Environ. 68, 45–50 (2018).
Google Scholar 
55.Thouless, C. R., Fanshawe, J. H. & Bertram, B. C. R. Egyptian vultures Neophron percnopterus and Ostrich Struthio camelus eggs: the origins of stone-throwing behaviour. Ibis (Lond.) 131, 9–15 (1989).Article 

Google Scholar 
56.Cuthbert, R. et al. Rapid population declines of Egyptian vulture (Neophron percnopterus) and red-headed vulture (Sarcogyps calvus) in India. Anim. Conserv. 9, 349–354 (2006).Article 

Google Scholar 
57.Samson, A. & Ramakarishnan, B. Observation of a population of Egyptian Vultures Neophron percnopterus in Ramanagaram Hills, Karnataka, southern India. Vulture News 71, 36–49 (2016).Article 

Google Scholar 
58.Farashi, A. & Alizadeh-Noughani, M. Niche modelling of the potential distribution of the Egyptian Vulture Neophron percnopterus during summer and winter in Iran, to identify gaps in protected area coverage. Bird Conserv. Int. 29, 423–436 (2019).Article 

Google Scholar 
59.Tauler-Ametller, H., Hernández-Matías, A., Pretus, J. L. L. & Real, J. Landfills determine the distribution of an expanding breeding population of the endangered Egyptian vulture Neophron percnopterus. Ibis (Lond). 159, 757–768 (2017).Article 

Google Scholar 
60.Mateo-Tomás, P. & Olea, P. P. Diagnosing the causes of territory abandonment by the Endangered Egyptian vulture Neophron percnopterus: The importance of traditional pastoralism and regional conservation. Oryx 44, 424–433 (2010).Article 

Google Scholar 
61.Galligan, T. H. et al. Have population declines in Egyptian vulture and Red-headed vulture in India slowed since the 2006 ban on veterinary diclofenac?. Bird Conserv. Int. 24, 272–281 (2014).Article 

Google Scholar 
62.Lieury, N., Gallardo, M., Ponchon, C., Besnard, A. & Millon, A. Relative contribution of local demography and immigration in the recovery of a geographically-isolated population of the endangered Egyptian vulture. Biol. Conserv. 191, 349–356 (2015).Article 

Google Scholar 
63.Porter, R. F. & Suleiman, A. S. the Egyptian Vulture Neophron percnopterus on Socotra, Yemen: Population, ecology, conservation and ethno-ornithology. Sandgrouse 34, 44–62 (2012).
Google Scholar  More