Philippa Kaur

Brugiroux S, Beutler M, Pfann C, Garzetti D, Ruscheweyh HJ, Ring D, et al. Genome-guided design of a defined mouse microbiota that confers colonization resistance against Salmonella enterica serovar Typhimurium. Nat Microbiol. 2016;2:16215.CAS 
PubMed 

Google Scholar 
Buffie CG, Bucci V, Stein RR, McKenney PT, Ling L, Gobourne A, et al. Precision microbiome reconstitution restores bile acid mediated resistance to Clostridium difficile. Nature 2015;517:205–8.CAS 
PubMed 

Google Scholar 
He M, Shi B. Gut microbiota as a potential target of metabolic syndrome: the role of probiotics and prebiotics. Cell Biosci. 2017;7:54.PubMed 
PubMed Central 

Google Scholar 
Ma W, Mao Q, Xia W, Dong G, Yu C, Jiang F. Gut microbiota shapes the efficiency of cancer therapy. Front Microbiol. 2019;10:1050.PubMed 
PubMed Central 

Google Scholar 
Rodriguez J, Hiel S, Neyrinck AM, Le Roy T, Potgens SA, Leyrolle Q, et al. Discovery of the gut microbial signature driving the efficacy of prebiotic intervention in obese patients. Gut 2020;69:1975–87.CAS 
PubMed 

Google Scholar 
Schubert AM, Sinani H, Schloss PD. Antibiotic-induced alterations of the murine gut microbiota and subsequent effects on colonization resistance against Clostridium difficile. mBio 2015;6:e00974.CAS 
PubMed 
PubMed Central 

Google Scholar 
Vivarelli S, Salemi R, Candido S, Falzone L, Santagati M, Stefani S, et al. Gut microbiota and cancer: From pathogenesis to therapy. Cancers (Basel). 2019;11:38.Pasolli E, Truong DT, Malik F, Waldron L, Segata N. Machine learning meta-analysis of large metagenomic datasets: Tools and biological insights. PLoS Comput Biol. 2016;12:e1004977.PubMed 
PubMed Central 

Google Scholar 
Walters WA, Xu Z, Knight R. Meta-analyses of human gut microbes associated with obesity and IBD. FEBS Lett. 2014;588:4223–33.CAS 
PubMed 
PubMed Central 

Google Scholar 
Rastelli M, Knauf C, Cani PD. Gut microbes and health: A focus on the mechanisms linking microbes, obesity, and related disorders. Obes (Silver Spring) 2018;26:792–800.
Google Scholar 
Sonnenburg JL, Backhed F. Diet-microbiota interactions as moderators of human metabolism. Nature 2016;535:56–64.CAS 
PubMed 
PubMed Central 

Google Scholar 
Costello EK, Stagaman K, Dethlefsen L, Bohannan BJ, Relman DA. The application of ecological theory toward an understanding of the human microbiome. Science 2012;336:1255–62.CAS 
PubMed 
PubMed Central 

Google Scholar 
Koskella B, Hall LJ, Metcalf CJE. The microbiome beyond the horizon of ecological and evolutionary theory. Nat Ecol Evol. 2017;1:1606–15.PubMed 

Google Scholar 
Walter J, Ley R. The human gut microbiome: Ecology and recent evolutionary changes. Annu Rev Microbiol. 2011;65:411–29.CAS 
PubMed 

Google Scholar 
Walter J, Maldonado-Gomez MX, Martinez I. To engraft or not to engraft: An ecological framework for gut microbiome modulation with live microbes. Curr Opin Biotechnol. 2018;49:129–39.CAS 
PubMed 

Google Scholar 
Le Roy T, Debedat J, Marquet F, Da-Cunha C, Ichou F, Guerre-Millo M, et al. Comparative evaluation of microbiota engraftment following fecal microbiota transfer in mice models: Age, kinetic and microbial status matter. Front Microbiol. 2018;9:3289.PubMed 

Google Scholar 
Maldonado-Gomez MX, Martinez I, Bottacini F, O’Callaghan A, Ventura M, van Sinderen D, et al. Stable engraftment of Bifidobacterium longum AH1206 in the human gut depends on individualized features of the resident microbiome. Cell Host Microbe. 2016;20:515–26.CAS 
PubMed 

Google Scholar 
Martinez I, Maldonado-Gomez MX, Gomes-Neto JC, Kittana H, Ding H, Schmaltz R, et al. Experimental evaluation of the importance of colonization history in early-life gut microbiota assembly. Elife. 2018;7:e36521.Podlesny D, Durdevic M, Paramsothy S, Kaakoush NO, Högenauer C, Gorkiewicz G, et al. Intraspecies strain exclusion, antibiotic pretreatment, and donor selection control microbiota engraftment after fecal transplantation. medRxiv. 2021;08.18.21262200.Li SS, Zhu A, Benes V, Costea PI, Hercog R, Hildebrand F, et al. Durable coexistence of donor and recipient strains after fecal microbiota transplantation. Science 2016;352:586–89.CAS 
PubMed 

Google Scholar 
Seekatz AM, Aas J, Gessert CE, Rubin TA, Saman DM, Bakken JS, et al. Recovery of the gut microbiome following fecal microbiota transplantation. mBio 2014;5:e00893–00814.PubMed 
PubMed Central 

Google Scholar 
Shahinas D, Silverman M, Sittler T, Chiu C, Kim P, Allen-Vercoe E, et al. Toward an understanding of changes in diversity associated with fecal microbiome transplantation based on 16S rRNA gene deep sequencing. mBio. 2012;3:e00338–12.Hardin G. The competitive exclusion principle. Science 1960;131:1292–7.CAS 
PubMed 

Google Scholar 
Stecher B, Chaffron S, Kappeli R, Hapfelmeier S, Freedrich S, Weber TC, et al. Like will to like: Abundances of closely related species can predict susceptibility to intestinal colonization by pathogenic and commensal bacteria. PLoS Pathog. 2010;6:e1000711.PubMed 
PubMed Central 

Google Scholar 
Chesson P. Mechanisms of maintenance of species diversity. Annu Rev Ecol Syst. 2000;31:343–66.
Google Scholar 
Grainger TN, Letten AD, Gilbert B, Fukami T. Applying modern coexistence theory to priority effects. Proc Natl Acad Sci USA. 2019;116:6205–10.CAS 
PubMed 
PubMed Central 

Google Scholar 
Lee SM, Donaldson GP, Mikulski Z, Boyajian S, Ley K, Mazmanian SK. Bacterial colonization factors control specificity and stability of the gut microbiota. Nature 2013;501:426–9.CAS 
PubMed 
PubMed Central 

Google Scholar 
Onderdonk A, Marshall B, Cisneros R, Levy SB. Competition between congenic Escherichia coli K-12 strains in vivo. Infect Immun. 1981;32:74–9.CAS 
PubMed 
PubMed Central 

Google Scholar 
Everard A, Belzer C, Geurts L, Ouwerkerk JP, Druart C, Bindels LB, et al. Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity. Proc Natl Acad Sci USA. 2013;110:9066–71.CAS 
PubMed 
PubMed Central 

Google Scholar 
Shin NR, Lee JC, Lee HY, Kim MS, Whon TW, Lee MS, et al. An increase in the Akkermansia spp. population induced by metformin treatment improves glucose homeostasis in diet-induced obese mice. Gut 2014;63:727–35.CAS 

Google Scholar 
Dingemanse C, Belzer C, van Hijum SA, Gunthel M, Salvatori D, den Dunnen JT, et al. Akkermansia muciniphila and Helicobacter typhlonius modulate intestinal tumor development in mice. Carcinogenesis 2015;36:1388–96.CAS 
PubMed 

Google Scholar 
Png CW, Linden SK, Gilshenan KS, Zoetendal EG, McSweeney CS, Sly LI, et al. Mucolytic bacteria with increased prevalence in IBD mucosa augment in vitro utilization of mucin by other bacteria. Am J Gastroenterol. 2010;105:2420–8.CAS 
PubMed 

Google Scholar 
Zhai R, Xue X, Zhang L, Yang X, Zhao L, Zhang C. Strain-specific anti-inflammatory properties of two Akkermansia muciniphila strains on chronic colitis in mice. Front Cell Infect Microbiol. 2019;9:239.CAS 
PubMed 
PubMed Central 

Google Scholar 
Martens EC, Lowe EC, Chiang H, Pudlo NA, Wu M, McNulty NP, et al. Recognition and degradation of plant cell wall polysaccharides by two human gut symbionts. PLoS Biol. 2011;9:e1001221.CAS 
PubMed 
PubMed Central 

Google Scholar 
Pudlo NA, Urs K, Crawford R, Pirani A, Atherly T, Jimenez R, et al. Phenotypic and genomic diversification in complex carbohydrate-degrading human gut bacteria. mSystems. 2022;7:e0094721.Lagkouvardos I, Pukall R, Abt B, Foesel BU, Meier-Kolthoff JP, Kumar N, et al. The mouse intestinal bacterial collection (miBC) provides host-specific insight into cultured diversity and functional potential of the gut microbiota. Nat Microbiol. 2016;1:16131.CAS 
PubMed 

Google Scholar 
Weldon L, Abolins S, Lenzi L, Bourne C, Riley EM, Viney M. The gut microbiota of wild mice. PLoS One. 2015;10:e0134643.PubMed 
PubMed Central 

Google Scholar 
Segura Munoz RR, Quach T, Gomes-Neto JC, Xian Y, Pena PA, Weier S, et al. Stearidonic-enriched soybean oil modulates obesity, glucose metabolism, and fatty acid profiles independently of Akkermansia muciniphila. Mol Nutr Food Res. 2020;64:e2000162.PubMed 
PubMed Central 

Google Scholar 
Bindels LB, Segura Munoz RR, Gomes-Neto JC, Mutemberezi V, Martinez I, Salazar N, et al. Resistant starch can improve insulin sensitivity independently of the gut microbiota. Microbiome 2017;5:12.PubMed 
PubMed Central 

Google Scholar 
Chen IA, Chu K, Palaniappan K, Pillay M, Ratner A, Huang J, et al. IMG/M v.5.0: an integrated data management and comparative analysis system for microbial genomes and microbiomes. Nucleic Acids Res. 2019;47:D666–D677.CAS 
PubMed 

Google Scholar 
Rozen S, Skaletsky H. Primer3 on the WWW for general users and for biologist programmers. Methods Mol Biol. 2000;132:365–86.CAS 
PubMed 

Google Scholar 
Mukherjee S, Stamatis D, Bertsch J, Ovchinnikova G, Katta HY, Mojica A, et al. Genomes OnLine database (GOLD) v.7: Updates and new features. Nucleic Acids Res.2019;47:D649–D659.CAS 
PubMed 

Google Scholar 
Schneeberger M, Everard A, Gomez-Valades AG, Matamoros S, Ramirez S, Delzenne NM, et al. Akkermansia muciniphila inversely correlates with the onset of inflammation, altered adipose tissue metabolism and metabolic disorders during obesity in mice. Sci Rep. 2015;5:16643.CAS 
PubMed 
PubMed Central 

Google Scholar 
Gomes-Neto JC, Mantz S, Held K, Sinha R, Segura Munoz RR, Schmaltz R, et al. A real-time PCR assay for accurate quantification of the individual members of the Altered Schaedler Flora microbiota in gnotobiotic mice. J Microbiol Methods. 2017;135:52–62.CAS 
PubMed 
PubMed Central 

Google Scholar 
Gomes-Neto JC, Kittana H, Mantz S, Segura Munoz RR, Schmaltz RJ, Bindels LB, et al. A gut pathobiont synergizes with the microbiota to instigate inflammatory disease marked by immunoreactivity against other symbionts but not itself. Sci Rep. 2017;7:17707.PubMed 
PubMed Central 

Google Scholar 
Wingett SW, Andrews S. FastQ Screen: A tool for multi-genome mapping and quality control. F1000Res. 2018;7:1338.PubMed 
PubMed Central 

Google Scholar 
Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 2009;25:1754–60.CAS 
PubMed 
PubMed Central 

Google Scholar 
Garcia-Alcalde F, Okonechnikov K, Carbonell J, Cruz LM, Gotz S, Tarazona S, et al. Qualimap: evaluating next-generation sequencing alignment data. Bioinformatics 2012;28:2678–79.CAS 
PubMed 

Google Scholar 
Thomsen MCF, Hasman H, Westh H, Kaya H, Lund O. RUCS: rapid identification of PCR primers for unique core sequences. Bioinformatics 2017;33:3917–21.PubMed 
PubMed Central 

Google Scholar 
Darling AC, Mau B, Blattner FR, Perna NT. Mauve: multiple alignment of conserved genomic sequence with rearrangements. Genome Res. 2004;14:1394–1403.CAS 
PubMed 
PubMed Central 

Google Scholar 
Kang DD, Li F, Kirton E, Thomas A, Egan R, An H, et al. MetaBAT 2: An adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies. PeerJ. 2019;7:e7359.PubMed 
PubMed Central 

Google Scholar 
Genome [Internet] (2004). National Library of Medicine (US), National Center for Biotechnology Information: Bethesda (MD). https://www.ncbi.nlm.nih.gov/genome/browse/#!/prokaryotes/1218/Genome [Internet] (2004). National Library of Medicine (US), National Center for Biotechnology Information: Bethesda (MD). https://www.ncbi.nlm.nih.gov/genome/browse/#!/prokaryotes/1598/Beghini F, McIver LJ, Blanco-Miguez A, Dubois L, Asnicar F, Maharjan S, et al. Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3. Elife. 2021;10:e65088.Asnicar F, Weingart G, Tickle TL, Huttenhower C, Segata N. Compact graphical representation of phylogenetic data and metadata with GraPhlAn. PeerJ 2015;3:e1029.PubMed 
PubMed Central 

Google Scholar 
Varghese NJ, Mukherjee S, Ivanova N, Konstantinidis KT, Mavrommatis K, Kyrpides NC, et al. Microbial species delineation using whole genome sequences. Nucleic Acids Res 2015;43:6761–71.CAS 
PubMed 
PubMed Central 

Google Scholar 
Mavromatis K, Chu K, Ivanova N, Hooper SD, Markowitz VM, Kyrpides NC. Gene context analysis in the Integrated Microbial Genomes (IMG) data management system. PLoS One 2009;4:e7979.PubMed 
PubMed Central 

Google Scholar 
El-Gebali S, Mistry J, Bateman A, Eddy SR, Luciani A, Potter SC, et al. The Pfam protein families database in 2019. Nucleic Acids Res 2019;47:D427–D432.CAS 
PubMed 

Google Scholar 
The UniProt Consortium. The universal protein resource (UniProt). Nucleic Acids Res 2008;36:D190–195.
Google Scholar 
Obadia B, Guvener ZT, Zhang V, Ceja-Navarro JA, Brodie EL, Ja WW, et al. Probabilistic invasion underlies natural gut microbiome stability. Curr Biol 2017;27:1999–2006 e1998.CAS 
PubMed 
PubMed Central 

Google Scholar 
Meszena G, Gyllenberg M, Pasztor L, Metz JA. Competitive exclusion and limiting similarity: A unified theory. Theor Popul Biol. 2006;69:68–87.PubMed 

Google Scholar 
Cavender-Bares J, Kozak KH, Fine PV, Kembel SW. The merging of community ecology and phylogenetic biology. Ecol Lett. 2009;12:693–715.PubMed 

Google Scholar 
Tramontano M, Andrejev S, Pruteanu M, Klunemann M, Kuhn M, Galardini M, et al. Nutritional preferences of human gut bacteria reveal their metabolic idiosyncrasies. Nat Microbiol 2018;3:514–22.CAS 
PubMed 

Google Scholar 
Derrien M, Vaughan EE, Plugge CM, de Vos WM. Akkermansia muciniphila gen. nov., sp. nov., a human intestinal mucin-degrading bacterium. Int J Syst Evol Microbiol 2004;54:1469–1476.CAS 
PubMed 

Google Scholar 
Walker AW, Lawley TD. Therapeutic modulation of intestinal dysbiosis. Pharm Res 2013;69:75–86.CAS 

Google Scholar 
Livanos AE, Greiner TU, Vangay P, Pathmasiri W, Stewart D, McRitchie S, et al. Antibiotic-mediated gut microbiome perturbation accelerates development of type 1 diabetes in mice. Nat Microbiol 2016;1:16140.CAS 
PubMed 
PubMed Central 

Google Scholar 
Perez-Cobas AE, Gosalbes MJ, Friedrichs A, Knecht H, Artacho A, Eismann K, et al. Gut microbiota disturbance during antibiotic therapy: A multi-omic approach. Gut 2013;62:1591–1601.CAS 
PubMed 

Google Scholar 
Adler PB, Hillerislambers J, Levine JM. A niche for neutrality. Ecol Lett. 2007;10:95–104.PubMed 

Google Scholar 
Levine JM, HilleRisLambers J. The importance of niches for the maintenance of species diversity. Nature 2009;461:254–57.CAS 
PubMed 

Google Scholar 
Forstner G. Signal transduction, packaging and secretion of mucins. Annu Rev Physiol. 1995;57:585–605.CAS 
PubMed 

Google Scholar 
Ottman N, Davids M, Suarez-Diez M, Boeren S, Schaap PJ, Martins Dos Santos VAP, et al. Genome-scale model and omics analysis of metabolic capacities of Akkermansia muciniphila reveal a preferential mucin-degrading lifestyle. Appl Environ Microbiol. 2017;83:e01014-17.Duar RM, Frese SA, Lin XB, Fernando SC, Burkey TE, Tasseva G et al. Experimental evaluation of host adaptation of Lactobacillus reuteri to different vertebrate species. Appl Environ Microbiol. 2017;83:e00132–17.Frese SA, Benson AK, Tannock GW, Loach DM, Kim J, Zhang M, et al. The evolution of host specialization in the vertebrate gut symbiont Lactobacillus reuteri. PLoS Genet. 2011;7:e1001314.CAS 
PubMed 
PubMed Central 

Google Scholar 
Rosshart SP, Vassallo BG, Angeletti D, Hutchinson DS, Morgan AP, Takeda K, et al. Wild mouse gut microbiota promotes host fitness and improves disease resistance. Cell 2017;171:1015–1028 e1013.CAS 
PubMed 
PubMed Central 

Google Scholar 
Karcher N, Nigro E, Puncochar M, Blanco-Miguez A, Ciciani M, Manghi P, et al. Genomic diversity and ecology of human-associated Akkermansia species in the gut microbiome revealed by extensive metagenomic assembly. Genome Biol. 2021;22:209.CAS 
PubMed 
PubMed Central 

Google Scholar 
Rosshart SP, Herz J, Vassallo BG, Hunter A, Wall MK, Badger JH, et al. Laboratory mice born to wild mice have natural microbiota and model human immune responses. Science. 2019;365.Mark Welch JL, Hasegawa Y, McNulty NP, Gordon JI, Borisy GG. Spatial organization of a model 15-member human gut microbiota established in gnotobiotic mice. Proc Natl Acad Sci USA. 2017;114:E9105–E9114.CAS 
PubMed 
PubMed Central 

Google Scholar 
Whitaker WR, Shepherd ES, Sonnenburg JL. Tunable expression tools enable single-cell strain distinction in the gut microbiome. Cell 2017;169:538–546. e512.CAS 
PubMed 
PubMed Central 

Google Scholar 
Becken B, Davey L, Middleton DR, Mueller KD, Sharma A, Holmes ZC, et al. Genotypic and phenotypic diversity among human isolates of Akkermansia muciniphila. mBio. 2021;12:e00478–21.Truong DT, Tett A, Pasolli E, Huttenhower C, Segata N. Microbial strain-level population structure and genetic diversity from metagenomes. Genome Res. 2017;27:626–38.
Google Scholar 
Faith JJ, Guruge JL, Charbonneau M, Subramanian S, Seedorf H, Goodman AL, et al. The long-term stability of the human gut microbiota. Science 2013;341:1237439.PubMed 
PubMed Central 

Google Scholar 
Mehta RS, Abu-Ali GS, Drew DA, Lloyd-Price J, Subramanian A, Lochhead P, et al. Stability of the human faecal microbiome in a cohort of adult men. Nat Microbiol. 2018;3:347–355.CAS 
PubMed 
PubMed Central 

Google Scholar 
Ferretti P, Pasolli E, Tett A, Asnicar F, Gorfer V, Fedi S, et al. Mother-to-infant microbial transmission from different body sites shapes the developing infant gut microbiome. Cell Host Microbe. 2018;24:133–45 e135.CAS 
PubMed 
PubMed Central 

Google Scholar 
Korpela K, Costea P, Coelho LP, Kandels-Lewis S, Willemsen G, Boomsma DI, et al. Selective maternal seeding and environment shape the human gut microbiome. Genome Res. 2018;28:561–8.CAS 
PubMed 
PubMed Central 

Google Scholar 
Freitag TL, Hartikainen A, Jouhten H, Sahl C, Meri S, Anttila VJ, et al. Minor effect of antibiotic pre-treatment on the engraftment of donor microbiota in fecal transplantation in mice. Front Microbiol. 2019;10:2685.PubMed 
PubMed Central 

Google Scholar 
Ji SK, Yan H, Jiang T, Guo CY, Liu JJ, Dong SZ, et al. Preparing the gut with antibiotics enhances gut microbiota reprogramming efficiency by promoting xenomicrobiota colonization. Front Microbiol. 2017;8:1208.PubMed 
PubMed Central 

Google Scholar 
Divya Ganeshan S, Hosseinidoust Z. Phage therapy with a focus on the human microbiota. Antibiotics (Basel). 2019;8:131.Ramachandran G, Bikard D. Editing the microbiome the CRISPR way. Philos Trans R Soc Lond B Biol Sci. 2019;374:20180103.CAS 
PubMed 
PubMed Central 

Google Scholar  More

.readcube-buybox { display: none !important;}

The unprecedented fires that devastated parts of Australia in 2020 can be attributed in part to colonialism1.

Access options

Access through your institution

Change institution

Buy or subscribe

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

Additional access options:

Log in

Learn about institutional subscriptions

doi: https://doi.org/10.1038/d41586-022-00509-5

ReferencesMariani, M. et al. Front. Ecol. Environ. https://doi.org/10.1002/fee.2395 (2022).Article 

Google Scholar 
Download references

Subjects

Ecology

Latest on:

Ecology

Apply Singapore Index on Cities’ Biodiversity at scale
Correspondence 22 FEB 22

Marching in the streets for climate-crisis action
Career Q&A 22 FEB 22

From the archive
News & Views 22 FEB 22

Jobs

PhD position (m/f/d) – Metabolomics

Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. (ISAS)
Dortmund, Germany

PhD position (m/f/d) – Computational Mass spectrometry and Metabolomics

Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. (ISAS)
Dortmund, Germany

Laboratory technician – Metabolomics Platform

University of Luxembourg
Luxembourg, Luxembourg

PhD Position – Protein Phase Separation and Microbiology

The University of British Columbia (UBC)
Vancouver, Canada More

Anderegg, W. R. L. AGU Advances 2, e2021AV000490 (2021).Article 

Google Scholar 
Goldstein, A. et al. Nat. Clim. Chang. 10, 287–295 (2020).CAS 
Article 

Google Scholar 
Tanneberger, F. et al. Adv. Sustain. Syst. 5, 2000146 (2021).CAS 
Article 

Google Scholar 
Paustian, K. et al. Nature 532, 49–57 (2016).CAS 
Article 

Google Scholar 
Magill, B. Biden climate plan to save forests pivots on swamps, wetland (1). Bloomberg Law, https://go.nature.com/3gzaYKM (2 November 2021).Meier, J. Designating Dark Sky Areas: Actors and Interests (Routledge, 2014).Climate Action Reserve. Key Accounting Principles for Improved Forest Management Projects within the Forest Protocol (Climate Action Reserve, 2019).Verified Carbon Standard. VM0007 REDD+ Methodology Framework (REDD+ MF), v1.6. verra.org, https://go.nature.com/3GCEKbZ (8 September 2020).PCAF. The Global GHG Accounting and Reporting Standard for the Financial Industry (Partnership for Carbon Accounting Financials, 2021).Xu, J., Morris, P. J., Liu, J. & Holden, J. Catena 160, 134–140 (2018).Article 

Google Scholar 
Yu, Z., Loisel, J., Brosseau, D. P., Beilman, D. W. & Hunt, S. J. Geophys. Res. Lett. 37, L13402 (2010).
Google Scholar 
Loisel, J. et al. Nat. Clim. Chang. 11, 70–77 (2021).Article 

Google Scholar 
Leifeld, J., Wüst-Galley, C. & Page, S. Nat. Clim. Chang. 9, 945–947 (2019).CAS 
Article 

Google Scholar 
Leifeld, J. & Menichetti, L. Nat. Commun. 9, 1071 (2018).CAS 
Article 

Google Scholar 
Juffe-Bignoli, D. et al. Protected Planet Report 2014 (UNEP-WCMC: 2014).Hoyos-Santillan, J., Miranda, A., Lara, A., Rojas, M. & Sepulveda-Jauregui, A. Science 366, 1207–1208 (2019).Article 

Google Scholar 
von Unger, M. & Emmer, I. Carbon Market Incentives to Conserve, Restore and Enhance Soil Carbon. (The Nature Conservancy, 2018).Bonn, A. et al. (eds). Peatland Restoration and Ecosystem Services: Science, Policy and Practice (Cambridge Univ. Press, 2016).Buotte, P. C., Law, B. E., Ripple, W. J. & Berner, L. T. Ecol. Appl. 30, e02039 (2020).Article 

Google Scholar 
Soto-Navarro, C. et al. Phil. Trans. R. Soc. Lond. B 375, 20190128 (2020).CAS 
Article 

Google Scholar  More

Chemical and pathogenic hazards in aquaculture supply chains threaten the provision of safe aquatic food. The Seafood Risk Tool is an integrated, semi-quantitative system that develops bespoke supply chain and risk management strategies.Although wild fish catches have plateaued globally, the aquaculture sector continues to expand in response to increasing demand for fish and other aquatic foods. Economic progress and the growing consumer awareness of aquatic foods in sustainable, healthy and nutritious diets are contributing to sector expansion1. However, rapid expansion must be achieved in a socially responsible and environmentally sustainable manner. Aquaculture produces over 400 different species across marine and freshwater fish, crustaceans, molluscs, plants and algae2 — all presenting complex and unique risk profiles to the environment, the industry, investors and consumers. Measures to mitigate these risks, including aquaculture certification and legislation, are inconsistent across nations and regions, and cohesive risk management has been difficult to manage and implement. More

Barcoding of Pseudomonas isolates and experimental designTo test possible host–commensal–pathogen dynamics in a local population, we spray inoculated six A. thaliana accessions with synthetic bacterial communities composed of pathogenic and commensal Pseudomonas candidates. Because we wanted to study interactions that are likely to occur in nature, we used A. thaliana genotypes that originated from the same plant populations near Tübingen, Germany28, from which the Pseudomonas strains had been isolated (Fig. 1a). Classification of Pseudomonas lineages as pathogenic or commensal was based on observed effects in axenic infections11. Only one lineage, previously named OTU5, which dominated local plant populations, was associated with pathogenicity, both based on negative impact on rosette weight and visible disease symptoms11. We henceforth call this lineage ATUE5 (isolates sampled from ‘Around TUEbingen, group 5’) and all other Pseudomonas lineages from the Karasov collection non-ATUE5. We interchangeably use the terms ‘pathogens’ or ‘ATUE5’, and ‘commensals’ or ‘non-ATUE5’.Fig. 1: Study system.a, Location of original a. thaliana and Pseudomonas sampling sites around Tübingen. b, Taxonomic representation of the 14 Pseudomonas isolates used and the prevalence of closely related strains (divergence 0.99 and P value |± 0.2| shown. Node colours indicate the bacterial isolate classification, ATUE5 or non-ATUE5. e, In planta abundance change of the seven ATUE5 isolates in non-ATUE5 inclusive treatments in comparison with PathoCom. Abundance mean difference was estimated with the model [log10(isolate load) ~ treatment × experiment + treatment + experiment + error] for each individual strain. Thus, the treatment coefficient was estimated per isolate. Dots indicate the median estimates, and vertical lines represent 95% Bayesian credible intervals of the fitted parameter. ‘Combi’ indicates combination of the isolates C3,C4,C5 and C7, and n = 23.Full size imageEach of the 14 isolates was examined for growth inhibition against all other isolates, covering all possible combinations of binary interactions. In total, three strains out of the 14 had inhibitory activity; all were non-ATUE5 (Fig. 4c). Specifically, C4 and C5 showed the same pattern: both inhibited all pathogenic isolates but P1, and both inhibited the same two commensals, C6 and weakly C3. C3 inhibited three ATUE5 isolates: P5, P6 and P7. In summary, the in vitro assay provides evidence that among the tested Pseudomonas isolates, direct inhibition was a trait unique to commensals, and susceptible bacteria were primarily pathogens. This supports the notion that ATUE5 and non-ATUE5 isolates employ divergent competition strategies, or that if they use the same mechanism, they differ in the effectiveness of such a mechanism.The in vitro results recapitulated the general trend of pathogen inhibition found among treatments in planta. Nevertheless, we observed major discrepancies between the two assays. First, P1 was not inhibited by any isolate in the host-free assay (Fig. 4c), though it was the most inhibited member in planta among the communities (Fig. 4b). Second, no commensal isolate was inhibited in planta among communities (Fig. 4b), while two commensals, C3 and C6, were inhibited in vitro (Fig. 4c). Both observations are compatible with an effect of the host on microbe–microbe interactions. To explore such effects, we analysed all pairwise microbe–microbe abundance correlations within MixedCom-infected hosts. When we used absolute abundances, all pairwise correlations were positive, also in CommenCom and PathoCom (Extended Data Fig. 8a), consistent with there being a positive correlation between absolute abundance of individual isolates and total abundance of the entire community (Supplementary Fig. 7), that is, no isolate was less abundant in highly colonized plants than in sparsely colonized plants. This indicates that there does not seem to be active killing of competitors in planta in the CommenCom, which is probably not surprising. With relative abundances, however, a clear pattern emerged with a cluster of commensals that were positively correlated, possibly reflecting mutual growth promotion, and several commensal strains being negatively correlated with both P6 and C7, possibly reflecting unidirectional growth inhibition (Fig. 4d). We did not observe the same correlations within CommenCom among commensals and within PathoCom among pathogens as we did for either subgroup in MixedCom, reflecting higher-order interactions. Thus, interactions among pathogens were constrained by the presence of commensals and vice versa (Extended Data Fig. 8b).The in planta patterns measured in complex communities did not fully recapitulate what we had observed in vitro with pairwise interactions. We therefore investigated individual commensal isolates for their ability to suppress pathogens in planta and also tested the entourage effect. We focused on the three commensals C3, C4 and C5, which had directly inhibited pathogens in vitro, and as a control C7, which had not shown any inhibition activity in vitro. We infected plants with mixtures of PathoCom and each of the four individual commensals and also with PathoCom mixed with all four commensals. Because pathogen inhibition seemed to be independent of the host genotype, we arbitrarily chose HE-1. Regardless of the commensal isolate, only P1 was suppressed with high probability in all commensal-including treatments (Fig. 4e), with P2, P3 and P4 being substantially inhibited only by the mixture of all four commensals. Together with the lack of meaningful differences between individual commensals, this indicates that pathogen inhibition is either a function of commensal dose or a result of interaction among commensals.An important finding was that four commensal strains had much more similar inhibitory activity in planta than in vitro and that the combined action was greater than the individual effects. Together, this suggested that the host contributes to the observed interactions between commensal and pathogenic Pseudomonas isolates. To begin to investigate this possibility, we next studied potential host immune responses with RNA sequencing.Defensive response elicited by non-ATUE5For the RNA-sequencing experiment, we treated plants of the genotype Lu3-30 with the three synthetic communities and also used a bacteria-free control treatment. We sampled the treated plants 3 DPI and 4 DPI, thus increasing the ability to pinpoint differentially expressed genes (DEGs) between treatments that are not highly time specific. Exploratory analysis indicated that the two time points behaved similarly, and they were combined for further in-depth analysis.We first looked at DEGs in a comparison between infected plants and control (Supplementary Table 5); with PathoCom, there were only 14 DEGs; with CommenCom, there were 1,112 DEGs; and with MixedCom, there were 1,949 DEGs, suggesting that the CommenCom isolates, which are also present in the MixedCom, elicited a stronger host response than the PathoCom members. Furthermore, the high number of DEGs in MixedCom, higher than both PathoCom and CommenCom together, suggested a synergistic response derived from inclusion of both PathoCom and CommenCom members. Alternatively, this could also be a consequence of the higher initial inoculum in the 14-member MixedCom than either the 7-member PathoCom or 7-member CommenCom, or a combination of the two effects (Fig. 5a,b and Extended Data Fig. 9). The genes induced by the MixedCom fell into two classes: Group 5 (Fig. 5a,b) was also induced, albeit more weakly, by the CommenCom but not by the PathoCom. This group was overrepresented for non-redundant gene ontology (GO) categories linked to defence (Fig. 5c) and most likely explains the protective effects of commensals in the MixedCom. Specifically, among the top ten enriched GO categories in the shared MixedCom and CommenCom set, eight relate to immune response or response to another organism (‘defence response’, ‘multi-organism process’, ‘immune response’, ‘response to stimulus’, ‘response to biotic stimulus’, ‘response to other organism’, ‘immune system process’, ‘response to stress’; Fig. 5c).Fig. 5: Only commensal members elicit a strong host-defensive response.a, Relative expression (RE) pattern of 2,727 DEGs found in at least one of the comparisons of CommenCom, PathoCom and MixedCom with Control. DEGs were hierarchically clustered. b, Euler diagram of DEGs in PathoCom-, CommenCom- and MixedCom-treated plants compared with Control (log2[fold change]  >|± 1|; false discovery rate (FDR) 0.05); n = 4.Full size imageGroup 4 was only induced in MixedCom, either indicating synergism between commensals and pathogens or reflecting a consequence of the higher initial inoculum. This group included a small number of redundant GO categories indicative of defence, such as ‘salicylic acid mediated signalling pathway’, ‘multi-organism process’, ‘response to other organism’ and ‘response to biotic stimulus’ (Supplementary Table 6). Moreover, the MixedCom response cannot simply be explained by synergistic effects or commensals suppressing pathogen effects because there was a prominent class, Group 2, which included genes that were induced in the CommenCom but to a much lesser extent in the PathoCom or MixedCom. From their annotation, it was unclear how they can be linked to infection (Fig. 5c). About 500 genes (Group 1) that were downregulated by all bacterial communities are unlikely to contain candidates for commensal protection (Fig. 5a).Cumulatively, these results imply that the CommenCom members elicited a defensive response in the host regardless of PathoCom members, while the mixture of both led to additional responses. To better understand if selective suppression of ATUE5 in MixedCom infections may have resulted from the recognition of both non-ATUE5 and ATUE5 (reflected by a unique MixedCom set of DEGs) or solely non-ATUE5 (a set of DEGs shared by MixedCom and CommenCom), we examined the expression of key genes related to the salicylic acid pathway and downstream immune responses. Activation of the salicylic acid pathway was previously related to increased fitness of A. thaliana in the presence of wild bacterial pathogens, a phenomenon which was attributed to an increased systemic acquired resistance32.We observed a general trend of higher expression in MixedCom- and CommenCom-infected hosts for several such genes (Fig. 5d). Examples are PR1 and PR5, marker genes for systemic acquired resistance and resistance execution. Therefore, according to the marker genes we tested, non-ATUE5 elicited a defensive response in the host, regardless of ATUE5 presence.We conclude that the expression profiles of non-ATUE5-infected Lu3-30 plants point to an increased defensive status, supporting our hypothesis regarding host-mediated ATUE5 suppression. We note that ATUE5 suppression was not associated with full plant protection and thus control-like weight levels in all plant genotypes. One accession, Ey15-2, was only partially protected in the MixedCom (Fig. 2), despite levels of pathogen inhibition being not very different from other host genotypes (Extended Data Fig. 7).Lack of protection explained by a single pathogenic isolateThe fact that Ey15-2 was only partially protected by MixedCom (Fig. 2) underlines the importance of the host genotype in plant–microbe–microbe interactions, apparently reflecting the dynamics between microbes and plants in wild populations. We therefore wanted to reveal the cause for this differential interaction.Our first aim was to rank compositional variables in MixedCom according to their impact on plant weight, regardless of host genotype. Next, we asked whether any of the top-ranked variables could explain the lack of protection in Ey15-2. With Random Forest analysis, we estimated the weight-predictive power of all individual isolates in MixedCom and three cumulative variables: total bacterial abundance, total ATUE5 abundance and total non-ATUE5 abundance. We found that the best weight-predictive variable was the abundance of pathogenic isolate P6, followed by total bacterial load and total ATUE5 load, which were probably confounded by the abundance of P6 (Fig. 6a). In agreement, P6 was the dominant ATUE5 in MixedCom (Fig. 6b and Extended Data Fig. 10a). We thus hypothesized that the residual pathogenicity in MixedCom-infected Ey15-2 was caused by P6. Although P6 grew best in Ey15-2, the difference to most other genotypes was unlikely to be important (Extended Data Fig. 10b). However, P6 was particularly dominant in Ey15-2 (Fig. 6b).Fig. 6: The effect of isolate P6 on weight in MixedCom-infected hosts and particularly on accession Ey15-2.a, Relative importance (mean decrease accuracy; ‘MSE’) of 20 examined variables in weight prediction of MixedCom-infected hosts as determined by Random Forest analysis. The best predictor was the abundance of isolate P6. ‘Total bacterial’, ‘Total ATUE5’ and ‘Total non-ATUE5’ indicate the cumulative abundances of the 14 isolates, seven ATUE5 isolates and seven non-ATUE5 isolates, respectively. b, Abundance of P6 compared with the other 13 barcoded isolates in MixedCom-infected hosts across the six A. thaliana genotypes used in this study. Dots indicate the median estimates, and vertical lines represent 95% Bayesian credible intervals of the fitted parameter, following the model [log10(isolate load) ~ isolate × experiment + isolate + experiment + error]. Each genotype was analysed individually, thus the model was utilized for each genotype separately. The shaded area denotes the 95% Bayesian credible intervals for the isolate P6. c, Fresh rosette weight of Ey15-2 plants treated with Control, MixedCom and MixedCom without P6 (MixedCom ΔP6). Fresh rosette weight was measured 12 DPI. The top panel presents the raw data, with the breaks in the vertical black lines denoting the mean value of each group, and the vertical lines indicating standard deviation. The lower panel presents the mean difference to control, plotted as bootstrap sampling55,56, indicating the distribution of effect size that is compatible with the data. The 95% confidence intervals are indicated by the black vertical bars, and n = 19.Full size imageGiven that pathogen load in Ey15-2 was driven to a substantial extent by P6, we assumed that this isolate had a stronger impact on the weight of Ey15-2 than on other accessions. We experimentally validated that removal of P6 restored protection when Ey15-2 was infected with the MixedCom (Fig. 6c). To confirm that restored protection was due to the interaction of commensals with the five other pathogenic isolates (P1–P5), rather than simply removal of P6, we also treated Ey15-2 with PathoCom only, but not P6. The removal of P6 did not diminish the negative weight impact of PathoCom (P1–P5, Supplementary Fig. 8), implying that it was indeed the interaction between commensals with five out of six pathogenic isolates that mitigated the harmful effect of pathogens in Ey15-2 plants. More

Positive correlation between biosynthetic gene cluster (BGC) and phylogenetic distance in the genus Bacillus
BGCs are responsible for the synthesis of secondary metabolites involved in microbial interference competition. To investigate the relationship between BGC and phylogenetic distance within the genus Bacillus, we collected 4268 available Bacillus genomes covering 139 species from the NCBI database (Supplementary Data 1). Phylogenetic analysis based on the sequences of 120 ubiquitous single-copy proteins27 showed that the 139 species could be generally clustered into four clades (Fig. 1 and Supplementary Data 2; the phylogenetic tree including all the detailed species information is shown in Supplementary Fig. 1), including a subtilis clade that includes species from diverse niches and can be further divided into the subtilis and pumilus subclades, a cereus clade that contains typical pathogenic species (B. cereus, B. anthracis, B. thuringiensis, etc.), a megaterium clade, and a circulans clade.Fig. 1: Phylogram of the tested Bacillus genomes.The maximum likelihood (ML) phylogram of 4268 Bacillus genomes was based on the sequences of 120 ubiquitous single-copy proteins27. The phylogenetic tree shows that Bacillus species can be generally clustered into the subtilis (light green circle; further includes subtilis (dark green) and pumilus (blue) subclades as shown in the branches), cereus (red), megaterium (yellow), and circulans (gray) clades. For detailed information of the species, please refer to the phylogenetic tree in Supplementary Fig. 1.Full size imagePrediction using the bioinformatic tool antiSMASH15 detected 49,671 putative BGCs in the 4268 genomes, corresponding to an average of 11.6 BGCs per genome (Supplementary Data 3). The subtilis clade had the most BGCs, 13.1 BGCs per genome (Fig. 2a); the subtilis subclade especially accommodates a high abundance of BGCs as 13.6 per genome (Supplementary Fig. 2a), which corresponds to their adaptation in diverse competitive habitats such as plant rhizosphere. The cereus and megaterium clades possessed moderate number of BGCs as 11.7 and 7.4 per genome, respectively; while the circulans clade only had 4.3 BGCs/genome (Fig. 2a and Supplementary Table 1), suggesting a distinct physiological feature and niche adaptation strategy. The two most abundant BGC classes were nonribosomal peptide-synthetase (NRPS) and RiPPs, which had an abundance of 3.7 and 3.1 per genome on average, respectively (Supplementary Fig. 2b and Supplementary Table 1). Interestingly, subtilis clade accommodated significantly higher abundance of BGCs in another polyketide synthase (PKSother; 2.0 per genome vs. 0.0–1.1 per genome) and PKS-NRPS Hybrids (0.7 vs. 0.0–0.2) classes, as compared with the three other clades (Supplementary Table 1); while cereus clade had more BGCs in RiPPs than other clades on average (Supplementary Table 1). Overall, the profile of BGC products and classification was generally consistent with the phylogenetic tree (Supplementary Fig. 3).Fig. 2: Biosynthetic gene cluster (BGC) distribution is correlated with phylogeny in the genus Bacillus.a The numbers of BGCs in the 4268 Bacillus genomes from different clades as defined by antiSMASH15. In the violin plot, the centre line represents the median, violin edges show the 25th and 75th percentiles, and whiskers extend to 1.5× the interquartile range. b Hierarchal clustering among the 545 representative Bacillus genomes based on the abundance of the different biosynthesis gene cluster families (GCFs). Each column represents a GCF, which was classified through BiG-SCAPE by calculating the Jaccard index (JI), adjacency index (AI), and domain sequence similarity (DSS) of each BGC28; the color bar on the top of the heatmap represents the BGC class of each GCF, where PKS includes classes of PKSother and PKSI, PKS-NRPS means PKS-NRPS Hybrids, Others includes classes of saccharides, terpene, and others. Each row represents a Bacillus genome, and the abundance of each GCF in different genomes is shown in the heatmap. The left tree was constructed based on the distribution pattern of GCFs, which showes a similar pattern to the phylogram in Fig. 1. c The correlation between the BGC and phylogenetic distance of the 545 representative Bacillus genomes (P  More

Meredith, M. et al. Polar regions. IPCC Intergov. Panel Clim. Chang. Geneva, Switz. 3, 203–320 (2019).Raftery, A. E., Zimmer, A., Frierson, D. M. W., Startz, R. & Liu, P. Less than 2 °C warming by 2100 unlikely. Nat. Clim. Chang. 7, 637–641 (2017).CAS 
PubMed 
PubMed Central 
ADS 

Google Scholar 
Ernakovich, J. G. et al. Predicted responses of arctic and alpine ecosystems to altered seasonality under climate change. Glob. Chang. Biol. 20, 3256–3269 (2014).PubMed 
ADS 

Google Scholar 
Parmesan, C. & Yohe, G. A globally coherent fingerprint of climate change impacts across natural systems. Nature 421, 37–42 (2003).CAS 
PubMed 
ADS 

Google Scholar 
Myers-Smith, I. H. & Hik, D. S. Climate warming as a driver of tundra shrubline advance. J. Ecol. 106, 547–560 (2018).
Google Scholar 
Martin, A. C., Jeffers, E. S., Petrokofsky, G., Myers-Smith, I. & Macias-Fauria, M. Shrub growth and expansion in the Arctic tundra: An assessment of controlling factors using an evidence-based approach. Environ. Res. Lett. 12, (2017).Myers-Smith, I. H. et al. Climate sensitivity of shrub growth across the tundra biome. Nat. Clim. Chang. 5, 887–891 (2015).ADS 

Google Scholar 
Myers-Smith, I. H. et al. Complexity revealed in the greening of the Arctic. Nat. Clim. Chang. 10, 106–117 (2020).ADS 

Google Scholar 
Epstein, H. E., Myers-Smith, I. & Walker, D. A. Recent dynamics of arctic and sub-arctic vegetation. Environ. Res. Lett. 8, 015040 (2013).ADS 

Google Scholar 
Ackerman, D., Griffin, D., Hobbie, S. E. & Finlay, J. C. Arctic shrub growth trajectories differ across soil moisture levels. Glob. Chang. Biol. 23, 4294–4302 (2017).PubMed 

Google Scholar 
Carrer, M., Pellizzari, E., Prendin, A. L., Pividori, M. & Brunetti, M. Winter precipitation – not summer temperature – is still the main driver for Alpine shrub growth. Sci. Total Environ. 682, 171–179 (2019).CAS 
PubMed 
ADS 

Google Scholar 
Xu, Y., Ramanathan, V. & Washington, W. M. Observed high-altitude warming and snow cover retreat over Tibet and the Himalayas enhanced by black carbon aerosols. Atmos. Chem. Phys. 16, 1303–1315 (2016).CAS 
ADS 

Google Scholar 
Francon, L. et al. Assessing the effects of earlier snow melt-out on alpine shrub growth: The sooner the better? Ecol. Indic. 115, (2020).López-Blanco, E. et al. Exchange of CO2 in Arctic tundra: impacts of meteorological variations and biological disturbance. Biogeosciences 14, 4467–4483 (2017).ADS 

Google Scholar 
Lund, M. et al. Larval outbreaks in West Greenland: Instant and subsequent effects on tundra ecosystem productivity and CO2 exchange. Ambio 46, 26–38 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
Prendin, A. L. et al. Immediate and carry-over effects of insect outbreaks on vegetation growth in West Greenland assessed from cells to satellite. J. Biogeogr. 47, 87–100 (2020).
Google Scholar 
Hobbie, S. E., Nadelhoffer, K. J. & Högberg, P. A synthesis: The role of nutrients as constraints on carbon balances in boreal and arctic regions. Plant Soil 242, 163–170 (2002).CAS 

Google Scholar 
Bret-Harte, M. S., Shaver, G. R. & Chapin, F. S. Primary and secondary stem growth in arctic shrubs: Implications for community response to environmental change. J. Ecol. 90, 251–267 (2002).
Google Scholar 
Sullivan, P. F., Ellison, S. B. Z., McNown, R. W., Brownlee, A. H. & Sveinbjörnsson, B. Evidence of soil nutrient availability as the proximate constraint on growth of treeline trees in northwest Alaska. Ecology 96, 716–727 (2015).PubMed 

Google Scholar 
Craine, J. M. et al. Global patterns of foliar nitrogen isotopes and their relationships with climate, mycorrhizal fungi, foliar nutrient concentrations, and nitrogen availability. New Phytol. 183, 980–992 (2009).CAS 
PubMed 

Google Scholar 
Shaver, G. R. & Chapin, F. S. Long-term responses to factorial, NPK fertilizer treatment by Alaskan wet and moist tundra sedge species. Ecography (Cop.) 18, 259–275 (1995).
Google Scholar 
Choudhary, S., Blaud, A., Osborn, A. M., Press, M. C. & Phoenix, G. K. Nitrogen accumulation and partitioning in a High Arctic tundra ecosystem from extreme atmospheric N deposition events. Sci. Total Environ. 554–555, 303–310 (2016).PubMed 
ADS 

Google Scholar 
Bergström, A. K. & Jansson, M. Atmospheric nitrogen deposition has caused nitrogen enrichment and eutrophication of lakes in the northern hemisphere. Glob. Chang. Biol. 12, 635–643 (2006).ADS 

Google Scholar 
Wild, B. et al. Plant-derived compounds stimulate the decomposition of organic matter in arctic permafrost soils. Sci. Rep. 6, 25607 (2016).CAS 
PubMed 
PubMed Central 
ADS 

Google Scholar 
Pedersen, E. P., Elberling, B. & Michelsen, A. Foraging deeply: Depth-specific plant nitrogen uptake in response to climate-induced N-release and permafrost thaw in the High Arctic. Glob. Chang. Biol. 26, 6523–6536 (2020).PubMed 
ADS 

Google Scholar 
Mack, M. C., Schuur, E. A. G. & Bret-harte, M. S. Ecosystem carbon storage in arctic tundra reduced by long-term nutrient fertilization. 431, 658–661 (2004).
Google Scholar 
Zamin, T. J. & Grogan, P. Birch shrub growth in the low Arctic: the relative importance of experimental warming, enhanced nutrient availability, snow depth and caribou exclusion. Environ. Res. Lett. 7, 034027 (2012).ADS 

Google Scholar 
DeMarco, J., MacK, M. C., Bret-Harte, M. S., Burton, M. & Shaver, G. R. Long-term experimental warming and nutrient additions increase productivity in tall deciduous shrub tundra. Ecosphere 5, 1–22 (2014).
Google Scholar 
Zamin, T. J., Bret-Harte, M. S. & Grogan, P. Evergreen shrubs dominate responses to experimental summer warming and fertilization in Canadian mesic low arctic tundra. J. Ecol. 102, 749–766 (2014).
Google Scholar 
Fenger-Nielsen, R. et al. Footprints from the past: The influence of past human activities on vegetation and soil across five archaeological sites in Greenland. Sci. Total Environ. 654, 895–905 (2019).CAS 
PubMed 
ADS 

Google Scholar 
Forbes, B. C., Ebersole, J. J. & Strandberg, B. Anthropogenic disturbance and patch dynamics in Circumpolar Arctic ecosystems. Conserv. Biol. 15, 954–969 (2001).
Google Scholar 
Andersen, E. A. S. et al. Nitrogen isotopes reveal high N retention in plants and soil of old Norse and Inuit deposits along a wet-dry arctic fjord transect in Greenland. Plant Soil 455, 241–255 (2020).CAS 

Google Scholar 
Normand, S. et al. Legacies of historical human activities in Arctic woody plant dynamics. Annu. Rev. Environ. Resour. 42, 541–567 (2017).
Google Scholar 
Walker, D. A. et al. The Circumpolar Arctic vegetation map. J. Veg. Sci. 16, 267–282 (2005).
Google Scholar 
Cappelen, J., Vinther, B. M., Kern-Hansen, C., Laursen, E. V. & Jørgensen, P. V. Greenland-DMI Historical Climate Data Collection 1784–2020 (Danish Meteorological Institute, 2021).
Google Scholar 
Hollesen, J. et al. Predicting the loss of organic archaeological deposits at a regional scale in Greenland. Sci. Rep. 9, 9097 (2019).PubMed 
PubMed Central 
ADS 

Google Scholar 
Fenger-Nielsen, R. et al. Arctic archaeological sites threatened by climate change: A regional multi-threat assessment of sites in south-west Greenland. Archaeometry 62, 1280–1297 (2020).CAS 

Google Scholar 
Fettweis, X. et al. Reconstructions of the 1900–2015 Greenland ice sheet surface mass balance using the regional climate MAR model. Cryosphere 11, 1015–1033 (2017).ADS 

Google Scholar 
Berner, L. T. et al. Summer warming explains widespread but not uniform greening in the Arctic tundra biome. Nat. Commun. 11, 1–12 (2020).ADS 

Google Scholar 
Assmann, J. J. et al. Local snow melt and temperature—but not regional sea ice—explain variation in spring phenology in coastal Arctic tundra. Glob. Chang. Biol. 25, 2258–2274 (2019).PubMed 
ADS 

Google Scholar 
Bhatt, U. S. et al. Climate drivers of Arctic tundra variability and change using an indicators framework. Environ. Res. Lett. 16, (2021).Hollesen, J., Matthiesen, H. & Elberling, B. The impact of Climate Change on an archaeological site in the Arctic. Archaeometry 59, 1175–1189 (2017).CAS 

Google Scholar 
Tolvanen, A. & Henry, G. H. R. Responses of carbon and nitrogen concentrations in high arctic plants to experimental warming. Can. J. Bot. 79, 711–718 (2001).CAS 

Google Scholar 
Oppen, J. et al. Annual air temperature variability and biotic interactions explain tundra shrub species abundance. J. Veg. Sci. 32, (2021).Hobbie, S. E. Temperature and plant species control over litter decomposition in Alaskan tundra. Ecol. Monogr. 66, 503–522 (1996).
Google Scholar 
Nadelhoffer, K. J., Giblin, A. E., Shaver, G. R. & Laundre, J. A. Effects of temperature and substrate quality on element mineralization in six Arctic soils. Ecology 72, 242–253 (1991).
Google Scholar 
Arens, S. J. T., Sullivan, P. F. & Welker, J. M. Nonlinear responses to nitrogen and strong interactions with nitrogen and phosphorus additions drastically alter the structure and function of a high Arctic ecosystem. J. Geophys. Res. Biogeosciences 113, 1–10 (2008).
Google Scholar 
Baddeley, J. A., Woodin, S. J. & Alexander, I. J. Effects of increased nitrogen and phosphorus availability on the photosynthesis and nutrient relations of three Arctic dwarf shrubs from Svalbard. Funct. Ecol. 8, 676 (1994).
Google Scholar 
Anadon-Rosell, A. et al. Xylem anatomical and growth responses of the dwarf shrub Vaccinium myrtillus to experimental CO2 enrichment and soil warming at treeline. Sci. Total Environ. 642, 1172–1183 (2018).CAS 
PubMed 
ADS 

Google Scholar 
Dawes, M. A. et al. Soil warming and CO2 enrichment induce biomass shifts in alpine tree line vegetation. Glob. Chang. Biol. 21, 2005–2021 (2015).PubMed 
ADS 

Google Scholar 
Walker, M. D. et al. Plant community responses to experimental warming across the tundra biome. Proc. Natl. Acad. Sci. 103, 1342–1346 (2006).CAS 
PubMed 
PubMed Central 
ADS 

Google Scholar 
Matthiesen, H., Fenger-Nielsen, R. F., Harmsen, H., Madsen, C. K. & Hollesen, J. The impact of vegetation on archaeological sites in the low arctic in light of climate change. Arctic 73, 141–152 (2020).
Google Scholar 
Dahl, M. B. et al. Warming, shading and a moth outbreak reduce tundra carbon sink strength dramatically by changing plant cover and soil microbial activity. Sci. Rep. 7, 1–13 (2017).CAS 

Google Scholar 
Westergaard-Nielsen, A., Karami, M., Hansen, B. U., Westermann, S. & Elberling, B. Contrasting temperature trends across the ice-free part of Greenland. Sci. Rep. 8, 1586 (2018).PubMed 
PubMed Central 
ADS 

Google Scholar 
Schweingruber, F. H., Börner, A. & Schulze, E.-D. Atlas of Stem Anatomy in Herbs, Shrubs and Trees. (Springer, Berlin, 2013). https://doi.org/10.1007/978-3-642-20435-7Pellizzari, E., Camarero, J. J., Gazol, A., Sangüesa-Barreda, G. & Carrer, M. Wood anatomy and carbon-isotope discrimination support long-term hydraulic deterioration as a major cause of drought-induced dieback. Glob. Chang. Biol. 22, 2125–2137 (2016).PubMed 
ADS 

Google Scholar 
Myers-Smith, I. H. et al. Methods for measuring arctic and alpine shrub growth: A review. Earth-Science Rev. 140, 1–13 (2015).ADS 

Google Scholar 
Stokes, M. A. & Smiley, T. L. Introduction to Tree-Ring Dating. (University of Chicago Press, 1968).Cook, E. R., Briffa, K., Shiyatov, S. & Mazepa, V. Methods of Dendrochronology: Applications in the Environmental Sciences. (Kluwer Academic Publisher, 1990).Gärtner, H. & Schweingruber, F. H. Microscopic preparation techniques for plant stem analysis. Kessel 95, 132–150 (2013).
Google Scholar 
von Arx, G., Crivellaro, A., Prendin, A. L., Čufar, K. & Carrer, M. Quantitative wood anatomy—practical guidelines. Front. Plant Sci. 7, 781 (2016).
Google Scholar 
Holmes, R. L. Computer-assisted quality control in tree- ring dating and measurement. Tree-ring Bulletin 43, 69–78 (1983).
Google Scholar 
Belokopytova, L. V, Babushkina, E. A., Zhirnova, D. F., Panyushkina, I. P. & Vaganov, E. A. Pine and larch tracheids capture seasonal variations of climatic signal at moisture-limited sites. Trees 33, 227–242 (2019).Büntgen, U. et al. Temperature-induced recruitment pulses of Arctic dwarf shrub communities. J. Ecol. 103, 489–501 (2015).
Google Scholar 
Fritts., H. C. Dendrochronology and Dendroclimatology. in Tree Rings and Climate 1–54 (1976). https://doi.org/10.1016/B978-0-12-268450-0.50006-9Briffa, K. & Jones, P. Basic chronology statistics and assessment. in Methods of Dendrochronology: Applications in the Environmental Sciences 137–152 (Kluwer Academic Publishers, 1990).Zuur, A. F., Ieno, E. N., Walker, N., Saveliev, A. A. & Smith, G. M. Mixed effects models and extensions in ecology with R. (Springer New York, 2009). https://doi.org/10.1007/978-0-387-87458-6Gazol, A. & Camarero, J. J. Mediterranean dwarf shrubs and coexisting trees present different radial-growth synchronies and responses to climate. Plant Ecol. 213, 1687–1698 (2012).
Google Scholar 
Crawley, M. J. Mixed-Effects Models. in R Book Second edition 681–714 (2007).Zar, J. H. Biostatistical analysis Fifth edition. USA Prentice Hall 4165 4159–4165, (1999).Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting Linear Mixed-Effects Models Using lme4. J. Stat. Softw. 67, arXiv:1406.5823 (2015).Pinheiro, J. C. & Bates, D. M. Linear Mixed-Effects Models: Basic Concepts and Examples. in Mixed-Effects Models in S and S-PLUS 3–56 (Springer-Verlag, 2000). https://doi.org/10.1007/0-387-22747-4_1Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. B. lmerTest Package: Tests in Linear Mixed Effects Models. J. Stat. Softw. 82, (2017).R Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/. More

Lawler, J.J. Climate change adaptation strategies for resource management and conservation planning. The year in ecology and conservation biology. Ann. N.Y. Acad. Sci. 1162, 79–98. https://doi.org/10.1111/j.1749-6632.2009.04147.x (2009).Dawson, T. P., Jackson, S. T., House, J. I., Prentice, I. C. & Mace, G. M. Beyond predictions: biodiversity conservation in a changing climate. Science 332(6025), 53–58. https://doi.org/10.1126/science.1200303 (2011).CAS 
Article 
PubMed 
ADS 

Google Scholar 
Walsworth, T. E. et al. Management for network diversity speeds evolutionary adaptation to climate change. Nat. Clim. Change 9(8), 632–636. https://doi.org/10.1038/s41558-019-0518-5 (2019).Article 

Google Scholar 
Morelli, T. L. et al. Climate-change refugia: Biodiversity in the slow lane. Front Ecol. Environ. 18(5), 228–234. https://doi.org/10.1002/fee.2189 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Vincent, H., Bornand, C. N., Kempel, A. & Fischer, M. Rare species perform worse than widespread species under changed climate. Biol. Conserv. 246, 108586. https://doi.org/10.1016/j.biocon.2020.108586 (2020).Article 

Google Scholar 
Corlett, R. T. & Westcott, D. A. Will plant movements keep up with climate change?. Trends Ecol. Evol. 28(8), 482–488. https://doi.org/10.1016/j.tree.2013.04.003 (2013).Article 
PubMed 

Google Scholar 
Janssen, J. & Bijlsma, R.J. Molinia meadows on calcareous, peaty or clayey-silt-laden soils (Molinion caeruleae) (6410) in the Netherlands, in: Bijlsma, R.J. et al. Defining and applying the concept of favourable reference values for species habitats under the EU Birds and Habitats Directives: examples of setting favourable reference values. Wageningen Environmental Research, Wageningen, 2929, pp. 201–203 (2019).Arnell, M., Cousins, S. A. O. & Eriksson, O. Does historical land use affect the regional distribution of fleshy-fruited woody plants?. PLoS ONE 14(12), e0225791. https://doi.org/10.1371/journal.pone.0225791 (2019).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Welk, A., Welk, E., Baudis, M., Böckelmann, J. & Bruelheide, H. Plant species range type determines local responses to biotic interactions and land use. Ecology 100(12), e02890. https://doi.org/10.1002/ecy.2890 (2019).Article 
PubMed 

Google Scholar 
Caissy, P., Klemet-N’Guessan, S., Jackiw, R., Eckert, C.G. & Hargreaves, A.L. High conservation priority of range-edge plant populations not matched by habitat protection or research effort. Biol. Conserv. 249, 108732. https://doi.org/10.1101/682823 (2020).Kreyling, J. et al. Rewetting does not return drained fen peatlands to their old selves. Nat. Commun. 12, 5693. https://doi.org/10.1038/s41467-021-25619-y (2021).CAS 
Article 
PubMed 
PubMed Central 
ADS 

Google Scholar 
Sotek, Z. Distribution patterns, history, and dynamics of peatland vascular plants in Pomerania (NW Poland). Biodiv. Res. Conserv. 18, 1–82. https://doi.org/10.2478/v10119-010-0020-4 (2010).Article 

Google Scholar 
Hultén, E. & Fries, M. Atlas of north European vascular plants, North of the tropic of cancer, I, Introduction, taxonomic index to the maps (Koeltz Scientific Books, 1986).
Google Scholar 
Buse, J., Boch, S., Hilgers, J. & Griebeler, E. M. Conservation of threatened habitat types under future climate change—lessons from plant-distribution models and current extinction trends in southern Germany. J. Nat. Conserv. 27, 18–25. https://doi.org/10.1016/j.jnc.2015.06.001 (2015).Article 

Google Scholar 
Dítě, D., Melečková, Z. & Eliáš, P. jun. Flea sedge (Carex pulicaris)—a new species in the Great Fatra. Acta Carpathica Occidentalis 6, 23–27, (in Slovak) (2015).Sotek, Z. et al. Distribution and habitat properties of Carex pulicaris and Pedicularis sylvatica at their range margin in NW Poland. Acta Soc. Bot. Pol. 85(3), 3507. https://doi.org/10.5586/asbp.3507 (2016).Article 

Google Scholar 
Kukk, T., Kull, T., Luuk, O., Mesipuu, M. & Saar, P. Atlas of the Estonian flora 2020. Tartu, Estonia (2020).Grulich, V. Red list of vascular plants of the Czech Republic, 3rd ed. Preslia 84, 631–645 (2012).Eliáš, P. jun, Dítě, D., Kliment, J., Hrivnák, R. & Feráková, V. Red list of ferns and flowering plants of Slovakia, 5th edition (October 2014). Biologia 70(2), 218–228. https://doi.org/10.1515/biolog-2015-0018 (2015).Kaźmierczakowa, R. et al. Polish red list of pteridophytes and flowering plants. Institute of Nature Conservation of the Polish Academy of Sciences, Cracow (2016).Aronsson, M. et al. Kärlväxter—vascular plants (Tracheophyta). In The 2010 Red List of Swedish Species (ed. Gärdenfors, U.) 201–221 (ArtDatabanken, Uppsala, 2010).
Google Scholar 
Kalliovirta, M. et al. Vascular plants, in: Rassi, P., Hyvärinen, E., Juslén, A. & Mannerkoski, I. (Eds.), The 2010 red list of Finnish species. Ministry of the Environment and Finnish Environment Institute, Helsinki, pp. 183–203 (2010).Kull, T. et al. Kokkuvõte soontaimede ohustatuse hindamistulemustest 2017–2018. Liikide ohustatuse hindamine riigihanke 183098 osa nr 15 – Õistaimed (Anthophyta), okaspuutaimed (Coniferophyta), lehtsooneostaimed (Monilophyta) ja pärisraigastaimed (Lycopodiophyta) vastavalt lepingule nr 7–27/17/59 (16. juuni 2017.a.). Lõpparuanne Keskkonnaametile. Eesti Maaülikool. Lk 1–6 + lisa, (in Estonian). Available from https://infoleht.keskkonnainfo.ee/GetFile.aspx?id=1947479558 (2018).Bartoszek, W., Mirek, Z. & Koczur, A. Flea sedge – Carex pulicaris L., in: Kaźmierczakowa, R., Zarzycki, K. & Mirek, Z., (Eds), Polish red data book of plants. Pteridophytes and flowering plants, 3rd ed. Polish Academy of Sciences, Institute of Nature Conservation, Cracow, pp. 737–739, (in Polish) (2014).Matuszkiewicz, W. Guide to the identification of plant communities in Poland. Scientific Publisher Warsaw, Poland, (in Polish) (2006).Hájek, M., Horsák, M., Hájková, P. & Dítě, D. Habitat diversity of central European fens in relation to environmental gradients and an effort to standardise fen terminology in ecological studies. Perspect. Plant Ecol. Evol. Syst. 8, 97–114. https://doi.org/10.1016/j.ppees.2006.08.002 (2006).Article 

Google Scholar 
Šefferová-Stanová, V., Šeffer, J. & Janák, M. Management of Natura 2000 habitats. 7230 Alkaline fens. Technical Report 2008 20/24. European Commission. Available from http://ec.europa.eu/environment/nature/natura2000/management/habitats/pdf/7230_Alkaline_fens.pdf. Accessed 15 June 2018 (2008).O’Connell, M., Ryan, J. B. & Macgowran, B. A. Wetland communities in Ireland: a phytosociological review. In European Mires (ed. Moore, P. D.) 303–364 (Academic Press INC, LTD, 1984).Chapter 

Google Scholar 
Dítě, D., Kubandová, M. & Pukajová, D. Chorological, ecological and phytocenological notes on the occurrence of flea sedge (Carex pulicaris L.) in Slovakia. Bull. Slovak Bot. Soc. 27, 77–84, (in Slovak) (2005).Hällfors, M. H. et al. Assessing the need and potential of assisted migration using species distribution models. Biol. Conserv. 196(7), 60–68. https://doi.org/10.1016/j.biocon.2016.01.031 (2016).Article 

Google Scholar 
Emsens, W.-J., Aggenbach, C. J. S., Rydin, H., Smolders, A. J. P. & van Diggelen, R. Competition for light as a bottleneck for endangered fen species: an introduction experiment. Biol. Conserv. 220, 76–83. https://doi.org/10.1016/j.biocon.2018.02.002 (2018).Article 

Google Scholar 
Kącki, Z. & Śliwiński, M. The polish vegetation database: structure, resources and development. Acta Soc. Bot. Pol. 81(2), 75–79. https://doi.org/10.5586/asbp.2012.014 (2012).Article 

Google Scholar 
Ellenberg, H. et al. Indicator values of plants in Central Europe. 2nd ed. Scripta Geobotanica 18, 1–258 (in Germany) (1992).PN-R-04031. Chemical and agricultural analysis of soil. Sampling of soil. Polish Committee for Standardization (1997).PN-R-04024. Chemical and agricultural analysis of soil. Determination of the Content of Available P, K, Mg and Mn in organic soils. Polish Committee for Standardization (1997).PN-R-04016-21. Chemical and Agricultural Analysis of Soil. Determination of the Content of Available Zinc, Copper, Manganese, Iron. Polish Committee for Standardization. (1992).Ostrowska, A., Gawliński, S. & Szczubiałka, Z. Methods of analysis and evaluation of soil and plant properties. Institute of Environmental Protection, Warsaw, Poland, (in Polish) (1991).WRB, I.W.G. World reference base for soil resources 2014. International soil classification system for naming soils and creating legends for soil maps. World Soil Resources Report, 106 (2014).IUNG (Institute of Soil Science and Plant Cultivation). Fertiliser Recommendations Part I. Limits for Estimating Soil Macro- and Microelement Content. Series P (44), Puławy, Poland, pp. 26–28 (1990).IUNG (Institute of Soil Science and Plant Cultivation). Evaluation of heavy metal and sulfur contamination of soils and plants. Framework guidelines for agriculture. Series P (53), Puławy, Poland, pp. 1–22 (1993).Oksanen, J. et al. Vegan: community ecology package. R package version 2.3–0. Available from https://cran.r-project.org/web/packages/vegan/vegan.pdf. Accessed date: 4 January 2021 (2019).R Core Team. R: a Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria Accessed 30 May 2020. https://www.R-project.org (2020).Hammer, Ø., Harper, D.A.T. & Ryan, P.D. PAST: Paleontological Statistics Software Package for Education and Data Analysis. Palaeontol. Electron. 4 (1), 1–9; http://palaeo-electronica.org/2001_1/past/issue1_01.htm (2001).Zelnik, I. & Čarni, A. Wet meadows of the alliance Molinion and their environmental gradients in Slovenia. Biologia 63(2), 187–196. https://doi.org/10.2478/s11756-008-0042-y (2008).CAS 
Article 

Google Scholar 
Lindén, C. Local plant species diversity in coastal grasslands in the Stockholm archipelago. The effect of isostatic land-uplift, different management and future sea level rise. Stockholm University, Master’s thesis, Physical Geography and Quaternary Geology, 45 Credits, Stockholm, pp. 1–33 (2017).Muller, S. Diversity of management practices required to ensure conservation of rare and locally threatened plant species in grasslands: A case study at a regional scale (Lorraine, France). Biodiv. Conserv. 11(7), 1173–1184. https://doi.org/10.1023/A:1016049605021 (2002).Article 

Google Scholar 
Rodwell, J. S. (ed.) British plant communities. Grasslands and montane communities. Vol. 3 (Cambridge University Press. 1992).Rodwell, J.S., Morgan, V., Jefferson, R.G. & Moss, D. The European context of British Lowland Grasslands. JNCC Report No. 394, JNCC, Peterborough, UK (2007).Carter, S. P., Proctor, J. & Slingsby, D. R. Soil and vegetation of the Keen of Hamar serpentine. Shetland. J. Ecol. 75(1), 21–42. https://doi.org/10.2307/2260534 (1987).CAS 
Article 

Google Scholar 
de Vere, N. Biological flora of the British Isles: Cirsium dissectum (L.) Hill (Cirsium tuberosum (L.) All. subsp. anglicum (Lam.) Bonnier; Cnicus pratensis (Huds.) Willd., non Lam.; Cirsium anglicum (Lam.) DC.). J. Ecol. 95, 876–894. https://doi.org/10.1111/j.1365-2745.2007.01265.x (2007).Fernández-Pascual, E. Comparative seed germination traits in bog and fen mire wetlands. Aquat. Bot. 130, 21–26. https://doi.org/10.1016/j.aquabot.2016.01.001 (2016).Article 

Google Scholar 
Otsus, M., Kukk, D., Kattai, K. & Sammul, M. Clonal ability, height and growth form explain species’ response to habitat deterioration in Fennoscandian wooded meadows. Plant Ecol. 215(9), 953–962. https://doi.org/10.1007/s11258-014-0347-6 (2014).Article 

Google Scholar 
Meusel, H., Jäger, E. & Weinert, E. Comparative chorology of the Central European flora. VEB Gustav Fischer Verlag, Jena, Germany, (in German) (1965).Hill, M.O., Preston, C.D. & Roy, D.B. PLANTATT. Attributes of British and Irish Plants: Status, Size, Life History, Geography and Habits. Centre for Ecology and Hydrology, Huntingdon, UK (2004).Dahl, E. The phytogeography of Northern Europe (British Isles, Fennoscandia and adjacent areas). Cambridge University Press, Cambridge. https://doi.org/10.1017/CBO9780511565182 (1998).Bartoszek, W., Koczur, A., Mirek, Z. & Oklejewicz, K. Flea sedge Carex pulicaris L., in: Mirek, Z. & Piękoś-Mirkowa, H. (Eds.), Red data book of the Polish Carpathians. Vascular plants. Polish Academy of Sciences Institute of Botany W. Szafer, Cracow, pp. 523–525, (in Polish) (2008).Hereźniak, J. Carex pulicaris L. – flea sedge, in: Olaczek R. (Ed.), Red Book of Plants of the Lodzkie Voivodship. Botanical Garden in Łódź, University of Łódź, Łódź, pp. 50–51, (in Polish) (2012).Wołejko, L., Pawlaczyk, P. & Stańko, R. (Eds.). Alkaline fens in Poland—diversity, resources, conservation. Naturalists’ Club, Świebodzin, Poland (2019).Koopman, J., Timmerman, A., Hosper, U. & Więcław, H. Distribution, ecology and morphology of three Ceratocystis hybrids in the Province of Fryslân, the Netherlands (Carex, Cyperaceae). Gorteria 41(1), 14–20 (2019).
Google Scholar 
Laughlin, D. C. & Abella, S. R. Abiotic and biotic factors explain independent gradients of plant community composition in ponderosa pine forests. Ecol. Modell. 205(1–2), 231–240. https://doi.org/10.1016/j.ecolmodel.2007.02.018 (2007).Article 

Google Scholar 
Austrheim, G., Gunilla, E., Olsson, A. & Grøntvedt, E. Land-use impact on plant communities in semi-natural sub-alpine grasslands of Budalen, central Norway. Biol. Conserv. 87(3), 369–379. https://doi.org/10.1016/S0006-3207(98)00071-8 (1999).Article 

Google Scholar 
Gough, M. W. & Marrs, R. H. A comparison of soil fertility between semi-natural and agricultural plant communities: Implications for the creations of species-rich grassland on abandoned agricultural land. Biol. Conserv. 51(2), 83–96. https://doi.org/10.1016/0006-3207(90)90104-w (1990).Article 

Google Scholar 
Bobbink, R., Hornung, M. & Roelofs, J. G. M. The effects of air-borne nitrogen pollutants on species diversity in natural and semi-natural European vegetation. J. Ecol. 86(5), 717–738 (1998).CAS 
Article 

Google Scholar 
McCrea, A. R., Trueman, I. C., Fullen, M. A., Atkinson, M. D. & Besenyei, L. Relationships between soil characteristics and species richness in two botanically heterogeneous created meadows in the urban English West Midlands. Biol. Conserv. 97(2), 171–180 (2001).Article 

Google Scholar 
Wamelink, W., van Dobben, H.F., Goedhart, P.W. & Jones-Walters, L.M. The role of abiotic soil parameters as a factor in the success of invasive plant species. Emerg. Sci. J. 2(6), 308–365. https://doi.org/10.28991/esj-2018-01155 (2018).Janssens, F. et al. Relationship between soil chemical factors and grassland diversity. Plant Soil 202(1), 69–78. https://doi.org/10.1023/A:1004389614865 (1998).CAS 
Article 

Google Scholar 
Tallowin, J. R. B. & Smith, R. E. N. Restoration of a Cirsio-Molinietum fen meadow on an agriculturally improved pasture. Restor. Ecol. 9(2), 167–178. https://doi.org/10.1046/j.1526-100x.2001.009002167.x (2001).Article 

Google Scholar 
Venterink, H. O., van der Vliet, R. E. & Wassen, M. J. Nutrient limitation along a productivity gradient in wet meadows. Plant Soil 234(2), 171–179. https://doi.org/10.1023/A:1017922715903 (2001).Article 

Google Scholar 
Linderoth, E. Management of nature reserves—with Valön nature reserve in focus. Bachelor of Science with specialization in Environmental Analysis 15 hp, VT18. Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science, pp 1–26, (in Swedish) (2018).Jansen, A. M. & Roelofs, J. G. Restoration of Cirsio-Molinietum wet meadows by sod cutting. Ecol. Eng. 7(4), 279–298. https://doi.org/10.1016/S0925-8574(96)00022-5 (1996).Article 

Google Scholar 
Jurzyk, S. & Wrobel, M. Co-occurrence of two species Molinia caerulea L. and “red-list” species Carex pulicaris L. in western Pomerania (Poland). Pol. J. Ecol. 51 (3), 363–367 (2003).Boyer, M. L. H. & Wheeler, B. D. Vegetation patterns in spring-fed calcareous fens: Calcite precipitation and constraints on fertility. J. Ecol. 77(2), 597–609. https://doi.org/10.2307/2260772 (1989).CAS 
Article 

Google Scholar  More