Ecology

Kelemen PB, Manning CE. Reevaluating carbon fluxes in subduction zones, what goes down, mostly comes up. Proc Natl Acad Sci USA. 2015;112:E3997–4006.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Vitale Brovarone A, Sverjensky DA, Piccoli F, Ressico F, Giovannelli D, Daniel I. Subduction hides high-pressure sources of energy that may feed the deep subsurface biosphere. Nat Commun. 2020;11:1–1.Article 

Google Scholar 
Harris RN, Wang K. Thermal models of the middle America trench at the Nicoya Peninsula, Costa Rica. Geophys Res Lett. 2002;29:6–1.Article 

Google Scholar 
Plümper O, King HE, Geisler T, Liu Y, Pabst S, Savov IP, et al. Subduction zone forearc serpentinites as incubators for deep microbial life. Proc Natl Acad Sci USA. 2017;114:4324–9.PubMed 
PubMed Central 
Article 

Google Scholar 
Lee H, Fischer TP, de Moor JM, Sharp ZD, Takahata N, Sano Y. Nitrogen recycling at the Costa Rican subduction zone: the role of incoming plate structure. Sci Rep. 2017;7:1–10.
Google Scholar 
Stern RJ. Subduction zones. Rev Geophys. 2002;40:3–38.Article 

Google Scholar 
Fullerton KM, Schrenk MO, Yücel M, Manini E, Basili M, Rogers TJ, et al. Effect of tectonic processes on biosphere–geosphere feedbacks across a convergent margin. Nat Geosci. 2021;14:301–6.CAS 
Article 

Google Scholar 
Barry PH, de Moor JM, Giovannelli D, Schrenk M, Hummer DR, Lopez T, et al. Forearc carbon sink reduces long-term volatile recycling into the mantle. Nature. 2019;568:487–92.CAS 
PubMed 
Article 

Google Scholar 
Moore EK, Jelen BI, Giovannelli D, Raanan H, Falkowski PG. Metal availability and the expanding network of microbial metabolisms in the Archaean eon. Nat Geosci. 2017;10:629–36.CAS 
Article 

Google Scholar 
Barnes JD, Cullen J, Barker S, Agostini S, Penniston-Dorland S, Lassiter JC, et al. The role of the upper plate in controlling fluid-mobile element (Cl, Li, B) cycling through subduction zones: Hikurangi forearc, New Zealand. Geosphere. 2019;15:642–58.Article 

Google Scholar 
Clift P, Vannucchi P. Controls on tectonic accretion versus erosion in subduction zones: Implications for the origin and recycling of the continental crust. Rev Geophys. 2004;42:1–31.Article 

Google Scholar 
Rüpke LH, Morgan JP, Hort M, Connolly JA. Serpentine and the subduction zone water cycle. Earth Planet Sci Lett. 2004;223:17–34.Article 

Google Scholar 
Carr MJ, Feigenson MD, Bennett EA. Incompatible element and isotopic evidence for tectonic control of source mixing and melt extraction along the Central American arc. Contrib Miner Pet. 1990;105:369–80.CAS 
Article 

Google Scholar 
Gazel E, Carr MJ, Hoernle K, Feigenson MD, Szymanski D, Hauff F, et al. Galapagos‐OIB signature in southern Central America: mantle refertilization by arc–hot spot interaction. Geochem Geophys Geosyst. 2009;10:1–32.Article 

Google Scholar 
Trembath-Reichert E, Butterfield DA, Huber JA. Active subseafloor microbial communities from Mariana back-arc venting fluids share metabolic strategies across different thermal niches and taxa. ISME J. 2019;13:2264–79. https://doi.org/10.1038/s41396-019-0431-y.Power JF, Carere CR, Lee CK, Wakerley GL, Evans DW, Button M, et al. Microbial biogeography of 925 geothermal springs in New Zealand. Nat Commun. 2018;9:1–2.CAS 
Article 

Google Scholar 
Acocella V, Spinks K, Cole J, Nicol A. Oblique back arc rifting of Taupo Volcanic zone. NZ Tecton. 2003;22:1–18.
Google Scholar 
Curtis AC, Wheat CG, Fryer P, Moyer CL. Mariana forearc serpentinite mud volcanoes harbor novel communities of extremophilic archaea. Geomicrobiol J. 2013;30:430–41.Article 

Google Scholar 
Inskeep WP, Jay ZJ, Herrgard MJ, Kozubal MA, Rusch DB, Tringe SG, et al. Phylogenetic and functional analysis of metagenome sequence from high-temperature archaeal habitats demonstrate linkages between metabolic potential and geochemistry. Front Microbiol. 2013;4:1–21.Article 

Google Scholar 
Colman DR, Lindsay MR, Amenabar MJ, Boyd ES. The intersection of geology, geochemistry, and microbiology in continental hydrothermal systems. Astrobiology. 2019;19:1505–22.CAS 
PubMed 
Article 

Google Scholar 
Inskeep WP, Jay ZJ, Tringe SG, Herrgård MJ, Rusch DB, YNP Metagenome Project Steering Committee and Working Group Members. The YNP metagenome project: environmental parameters responsible for microbial distribution in the Yellowstone geothermal ecosystem. Front Microbiol. 2013;4:1–15.Article 

Google Scholar 
Hou W, Wang S, Dong H, Jiang H, Briggs BR, Peacock JP, et al. A comprehensive census of microbial diversity in hot springs of Tengchong, Yunnan Province China using 16S rRNA gene pyrosequencing. PloS One. 2013;8:1–15.
Google Scholar 
Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–20.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Nurk S, Meleshko D, Korobeynikov A, Pevzner PA. metaSPAdes: a new versatile metagenomic assembler. Genome Res. 2017;27:824–34.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Bowers RM, Kyrpides NC, Stepanauskas R, Harmon-Smith M, Doud D, Reddy TB, et al. Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea. Nat Biotechnol. 2017;35:725–31.CAS 
PubMed 
PubMed Central 
Article 

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

Google Scholar 
Probst AJ, Castelle CJ, Singh A, Brown CT, Anantharaman K, Sharon I, et al. Genomic resolution of a cold subsurface aquifer community provides metabolic insights for novel microbes adapted to high CO2 concentrations. Environ Microbiol. 2017;19:459–74.CAS 
PubMed 
Article 

Google Scholar 
Probst AJ, Ladd B, Jarett JK, Geller-McGrath DE, Sieber CM, Emerson JB, et al. Differential depth distribution of microbial function and putative symbionts through sediment-hosted aquifers in the deep terrestrial subsurface. Nat Microbiol. 2018;3:328–36.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
He C, Keren R, Whittaker M, Farag IF, Doudna J, Cate JH, et al. Genome-resoled metagenomics reveals site-specific diversity of episymbiotic CPR bacteria and DPANN archaea in groundwater ecosystems. Nat. Microbiol. 2021;6:354–65.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Grettenberger CL, Hamilton TL. Metagenome-assembled genomes of novel taxa from an acid mine drainage environment. Appl Environ Microbiol. 2021;87:e0077221. https://doi.org/10.1101/2020.07.02.185728.Uritskiy GV, DiRuggiero J, Taylor J. MetaWRAP–a flexible pipeline for genome-resolved metagenomic data analysis. Microbiome. 2018;6:1–3.Article 

Google Scholar 
Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014;30:2068–9.CAS 
PubMed 
Article 

Google Scholar 
Garber AI, Nealson KH, Okamoto A, McAllister SM, Chan CS, Barco RA, et al. FeGenie: a comprehensive tool for the identification of iron genes and iron gene neighborhoods in genome and metagenome assemblies. Front Microbiol. 2020;11:37. https://doi.org/10.3389/fmicb.2020.00037.Kanehisa M, Sato Y, Morishima K. BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J Mol Biol. 2016;428:726–31.CAS 
PubMed 
Article 

Google Scholar 
Graham ED, Heidelberg JF, Tully BJ. Potential for primary productivity in a globally distributed bacterial phototroph. ISME J. 2018;12:1861–6.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Chaumeil PA, Mussig AJ, Hugenholtz P, Parks DH. GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database. Bioinformatics. 2020;36:1925–27.CAS 

Google Scholar 
Berg IA, Kockelkorn D, Ramos-Vera WH, Say RF, Zarzycki J, Hügler M, et al. Autotrophic carbon fixation in archaea. Nat Rev Microbiol. 2010;8:447–60.CAS 
PubMed 
Article 

Google Scholar 
Berg IA. Ecological aspects of the distribution of different autotrophic CO2 fixation pathways. Appl Environ Microbiol. 2011;77:1925–36.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Youssef NH, Farag IF, Hahn CR, Jarett J, Becraft E, Eloe-Fadrosh E, et al. Genomic characterization of candidate division LCP-89 reveals an atypical cell wall structure, microcompartment production, and dual respiratory and fermentative capacities. Appl Environ Microbiol. 2019;85:1–19.Article 

Google Scholar 
Nigro LM, King GM. Disparate distributions of chemolithotrophs containing form IA or IC large subunit genes for ribulose-1, 5-bisphosphate carboxylase/oxygenase in intertidal marine and littoral lake sediments. FEMS Microbiol Ecol. 2007;60:113–25.CAS 
PubMed 
Article 

Google Scholar 
Aminuddin M, Nicholas DJ. Electron transfer during sulphide and sulphite oxidation in Thiobacillus denitrificans. Microbiology. 1974;82:115–23.
Google Scholar 
Giovannelli D, Sievert SM, Hügler M, Markert S, Becher D, Schweder T, et al. Insight into the evolution of microbial metabolism from the deep-branching bacterium, Thermovibrio ammonificans. eLife. 2017;6:1–31.Article 

Google Scholar 
Nakagawa S, Shataih Z, Banta A, Beveridge TJ, Sako Y, Reysenbach AL. Sulfurihydrogenibium yellowstonense sp. nov., an extremely thermophilic, facultatively heterotrophic, sulfur-oxidizing bacterium from Yellowstone National Park, and emended descriptions of the genus Sulfurihydrogenibium, Sulfurihydrogenibium subterraneum. Int J Syst Evol Microbiol. 2005;55:2263–8.CAS 
PubMed 
Article 

Google Scholar 
Leclerque A, Kleespies RGA. Rickettsiella bacterium from the hard tick, Ixodes woodi: molecular taxonomy combining multilocus sequence typing (MLST) with significance testing. PLoS One. 2012;7:e38062. https://doi.org/10.1371/journal.pone.0038062.Quatrini R, Johnson DB. Acidithiobacillus ferrooxidans. Trends Microbiol. 2019;27:282–3.CAS 
PubMed 
Article 

Google Scholar 
Spang A, Poehlein A, Offre P, Zumbrägel S, Haider S, Rychlik N, et al. The genome of the ammonia‐oxidizing Candidatus Nitrososphaera gargensis: insights into metabolic versatility and environmental adaptations. Environ Microbiol. 2012;14:3122–45.CAS 
PubMed 
Article 

Google Scholar 
Chen CY, Chen PC, Weng FC, Shaw GT, Wang D. Habitat and indigenous gut microbes contribute to the plasticity of gut microbiome in oriental river prawn during rapid environmental change. PLoS One. 2017;12:e0181427. https://doi.org/10.1371/journal.pone.0181427.Garcia R, Müller R. The family Myxococcaceae. In: Rosenberg E, DeLong EF, Lory S, Stackebrandt E, Thompson F, editors. The prokaryotes: Deltaproteobacteria and Epsilonproteobacteria. Berlin: Springer; 2014. p. 191–212.Garcia R, Müller R. Simulacricoccus ruber gen. nov., sp. nov., a microaerotolerant, non-fruiting, myxospore-forming soil myxobacterium and emended description of the family Myxococcaceae. Int J Syst Evol Microbiol. 2018;68:3101–10.CAS 
PubMed 
Article 

Google Scholar 
Iino T. The family Ignavibacteriaceae. In: Rosenberg E, DeLong EF, Lory S, Stackebrandt E, Thompson F, editors. The prokaryotes: other major lineages of bacteria and the archaea. New York, NY: Springer Science + Business Media; 2014. p. 701–3.Petrie L, North NN, Dollhopf SL, Balkwill DL, Kostka JE. Enumeration and characterization of iron (III)-reducing microbial communities from acidic subsurface sediments contaminated with uranium (VI). Appl Environ Microbiol. 2003;69:7467–79.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Fincker M, Huber JA, Orphan VJ, Rappé MS, Teske A, Spormann AM. Metabolic strategies of marine subseafloor Chloroflexi inferred from genome reconstructions. Environ Microbiol. 2020;22:3188–204.CAS 
PubMed 
Article 

Google Scholar 
Chen YJ, Leung PM, Wood JL, Bay SK, Hugenholtz P, Kessler AJ, et al. Metabolic flexibility allows bacterial habitat generalists to become dominant in a frequently disturbed ecosystem. ISME J. 2021;15:2986–3004.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Flieder M, Buongiorno J, Herbold CW, Hausmann B, Rattei T, Lloyd KG, et al. Novel taxa of Acidobacteriota implicated in seafloor sulfur cycling. ISME J. 2021;15:3159–80.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Kim M, Wilpiszeski RL, Wells M, Wymore AM, Gionfriddo CM, Brooks SC, et al. Metagenome-assembled genome sequences of novel prokaryotic species from the mercury-contaminated East Fork Poplar Creek, Oak Ridge, Tennessee, USA. Microbiol Resour Announc. 2021;10:e00153–21. https://doi.org/10.1128/MRA.00153-21.Santos‐Júnior CD, Logares R, Henrique‐Silva F. Microbial population genomes from the Amazon River reveal possible modulation of the organic matter degradation process in tropical freshwaters. Mol Ecol. 2022;31:206–19.PubMed 
Article 

Google Scholar 
Yamada T, Sekiguchi Y. Cultivation of uncultured Chloroflexi subphyla: significance and ecophysiology of formerly uncultured Chloroflexi ‘subphylum I’ with natural and biotechnological relevance. Microbes Environ. 2009;24:205–16.PubMed 
Article 

Google Scholar 
Sheik CS, Reese BK, Twing KI, Sylvan JB, Grim SL, Schrenk MO, et al. Identification and removal of contaminant sequences from ribosomal gene databases: lessons from the census of deep life. Front Microbiol. 2018;9:840. https://doi.org/10.3389/fmicb.2018.00840.Doughari HJ, Ndakidemi PA, Human IS, Benade S. The ecology, biology and pathogenesis of Acinetobacter spp.: an overview. Microbes Environ. 2011;26:101–12.PubMed 
Article 

Google Scholar 
Han XY, Han FS, Segal J. Chromobacterium haemolyticum sp. nov., a strongly haemolytic species. Int J Syst Evol Microbiol. 2008;58:1398–403.CAS 
PubMed 
Article 

Google Scholar 
Lau MC, Kieft TL, Kuloyo O, Linage-Alvarez B, Van Heerden E, Lindsay MR, et al. An oligotrophic deep-subsurface community dependent on syntrophy is dominated by sulfur-driven autotrophic denitrifiers. Proc Natl Acad Sci USA. 2016;113:E7927–36.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Momper L, Jungbluth SP, Lee MD, Amend JP. Energy and carbon metabolisms in a deep terrestrial subsurface fluid microbial community. ISME J. 2017;11:2319–33.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Worzewski T, Jegen M, Kopp H, Brasse H, Taylor Castillo W. Magnetotelluric image of the fluid cycle in the Costa Rican subduction zone. Nat Geosci. 2011;4:108–11.CAS 
Article 

Google Scholar 
Hensen C, Wallmann K, Schmidt M, Ranero CR, Suess E. Fluid expulsion related to mud extrusion off Costa Rica—a window to the subducting slab. Geology. 2004;32:201–4.CAS 
Article 

Google Scholar 
Simpson DR. Aluminum phosphate variants of feldspar. Am Miner. 1977;62:351–5.CAS 

Google Scholar 
London DA, Cerny P, Loomis J, Pan JJ. Phosphorus in alkali feldspars of rare-element granitic pegmatites. Can Miner. 1990;28:771–86.CAS 

Google Scholar 
Petrillo C, Castaldi S, Lanzilli M, Selci M, Cordone A, Giovannelli D, et al. Genomic and physiological characterization of Bacilli isolated from salt-pans with plant growth promoting features. Front Microbiol. 2021;12:715678. https://doi.org/10.3389/fmicb.2021.715678.Ghiorse WC, Wilson JT. Microbial ecology of the terrestrial subsurface. Adv Appl Microbiol. 1988;33:107–72.CAS 
PubMed 
Article 

Google Scholar 
Barker WW, Welch SA, Chu S, Banfield JF. Experimental observations of the effects of bacteria on aluminosilicate weathering. Am Miner. 1998;83:1551–63.CAS 
Article 

Google Scholar 
Bennett PC, Rogers JR, Choi WJ, Hiebert FK. Silicates, silicate weathering, and microbial ecology. Geomicrobiol J. 2001;18:3–19.CAS 
Article 

Google Scholar 
Hügler M, Sievert SM. Beyond the Calvin cycle: autotrophic carbon fixation in the ocean. Ann Rev Mar Sci. 2011;3:261–89.PubMed 
Article 

Google Scholar 
Markert S, Arndt C, Felbeck H, Becher D, Sievert SM, Hügler M, et al. Physiological proteomics of the uncultured endosymbiont of Riftia pachyptila. Science. 2007;315:247–50.CAS 
PubMed 
Article 

Google Scholar 
Bar-Even A, Noor E, Milo R. A survey of carbon fixation pathways through a quantitative lens. J Exp Bot. 2012;63:2325–42.CAS 
PubMed 
Article 

Google Scholar 
Stevens TO, McKinley JP. Lithoautotrophic microbial ecosystems in deep basalt aquifers. Science. 1995;270:450–5.CAS 
Article 

Google Scholar 
Barker WW, Welch SA, Banfield JF. Biogeochemical weathering of silicate minerals. Rev Miner Geochem. 1997;35:391–428.CAS 

Google Scholar 
Frank YA, Kadnikov VV, Lukina AP, Banks D, Beletsky AV, Mardanov AV, et al. Characterization and genome analysis of the first facultatively alkaliphilic Thermodesulfovibrio isolated from the deep terrestrial subsurface. Front Microbiol. 2016;7:2000. https://doi.org/10.3389/fmicb.2016.02000.Woycheese KM, Meyer-Dombard DA, Cardace D, Argayosa AM, Arcilla CA. Out of the dark: transitional subsurface-to-surface microbial diversity in a terrestrial serpentinizing seep (Manleluag, Pangasinan, the Philippines). Front Microbiol. 2015;6:1–12.Article 

Google Scholar 
Brazelton WJ, Morrill PL, Szponar N, Schrenk MO. Bacterial communities associated with subsurface geochemical processes in continental serpentinite springs. Appl Environ Microbiol. 2013;79:3906–16.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Moser DP, Gihring TM, Brockman FJ, Fredrickson JK, Balkwill DL, Dollhopf ME, et al. Desulfotomaculum and Methanobacterium spp. dominate a 4-to 5-kilometer-deep fault. Appl Environ Microbiol. 2005;71:8773–83.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Schwarzenbach EM, Gill BC, Gazel E, Madrigal P. Sulfur and carbon geochemistry of the Santa Elena peridotites: comparing oceanic and continental processes during peridotite alteration. Lithos. 2016;252:92–108.Article 

Google Scholar 
Sánchez‐Murillo R, Gazel E, Schwarzenbach EM, Crespo‐Medina M, Schrenk MO, Boll J, et al. Geochemical evidence for active tropical serpentinization in the Santa Elena Ophiolite, Costa Rica: an analog of a humid early Earth? Geochem Geophys Geosyst. 2014;15:1783–800.Article 

Google Scholar 
Crespo-Medina M, Twing KI, Sánchez-Murillo R, Brazelton WJ, McCollom TM, Schrenk MO. Methane dynamics in a tropical serpentinizing environment: the Santa Elena Ophiolite, Costa Rica. Front Microbiol. 2017;8:916. https://doi.org/10.3389/fmicb.2017.00916.DeShon HR, Schwartz SY. Evidence for serpentinization of the forearc mantle wedge along the Nicoya Peninsula, Costa Rica. Geophys Res Lett. 2004;31. https://doi.org/10.1029/2004GL021179.Delmelle P, Stix J. Volcanic gases. In: Sigurdsson H, Houghton B, McNutt S, Rymer H, Stix J, editors. Encyclopedia of volcanoes. New York, NY: Elsevier; 2000. p 803–15.Kharaka YK, Mariner RH. Geothermal systems. In: Sigurdsson H, Houghton B, McNutt S, Rymer H, Stix J, editors. Encyclopedia of volcanoes. New York, NY: Elsevier; 2000. p. 817–34.Badger MR, Bek EJ. Multiple Rubisco forms in proteobacteria: their functional significance in relation to CO2 acquisition by the CBB cycle. J Exp Bot. 2008;59:1525–41.CAS 
PubMed 
Article 

Google Scholar 
West-Roberts JA, Carnevali PB, Scholmerich MC, Al-Shayeb B, Thomas A, Sharrar AM, et al. The Chloroflexi supergroup is metabolically diverse and representatives have novel genes for non-photosynthesis based CO2 fixation. bioRxiv [Preprint]. 2021. Available from: https://doi.org/10.1101/2020.05.14.094862.Lloyd KG, Steen AD, Ladau J, Yin J, Crosby L. Phylogenetically novel uncultured microbial cells dominate earth microbiomes. mSystems. 2018;3:1–12.Article 

Google Scholar 
Colman DR, Lindsay MR, Boyd ES. Mixing of meteoric and geothermal fluids supports hyperdiverse chemosynthetic hydrothermal communities. Nat Commun. 2019;10:1–3.Article 

Google Scholar  More

The Asiatic cheetah (Acinonyx jubatus venaticus) once roamed throughout the Middle East and central India. Today there remain only an estimated 20 free-ranging individuals in central Iran and 5 in captivity. International economic sanctions against Iran have had devastating effects on its cheetah conservation and management (see go.nature.com/3suohzb; in Farsi). To help overcome these effects, we suggest that Iran work with the Indian government, which is conducting a rewilding programme for cheetahs.
Competing Interests
The authors declare no competing interests. More

Liu, X. Q. et al. Geographic differentiation and phylogeographic relationships among world soybean populations. Crop J. 8(2), 260–272 (2020).Article 

Google Scholar 
Coleman, K. et al. The potential for soybean to diversify the production of plant-based protein in the UK. Sci. Total Environ. 767(3), 144903 (2021).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Zhang, W. W., Feng, Z. Z., Wang, X. K., Liu, X. B. & Hu, E. Z. Quantification of ozone exposure- and stomatal uptake-yield response relationships for soybean in Northeast China. Sci. Total Environ. 599–600, 710–720 (2017).ADS 
PubMed 
Article 

Google Scholar 
Strom, N., Hu, W. M., Haarith, D. & Chen, S. Y. Interactions between soil properties, fungal communities, the soybean cyst nematode, and crop yield under continuous corn and soybean monoculture. Appl. Soil Ecol. 147, 103388 (2019).Article 

Google Scholar 
Fernandez-Gnecco, G. et al. Microbial community analysis of soils under different soybean cropping regimes in the Argentinean south-eastern Humid Pampas. Fems Microbiol. Ecol. 97(3), 007 (2021).Article 

Google Scholar 
Bai, L., Cui, J. Q., Jie, W. G. & Cai, B. Y. Analysis of the community compositions of rhizosphere fungi in soybeans continuous cropping fields. Microbiol. Res. 180, 49–56 (2015).PubMed 
Article 

Google Scholar 
Liu, J. J., Yu, Z. H., Yao, Q. & Hu, X. J. Distinct soil bacterial communities in response to the cropping system in a Mollisol of northeast China. Appl. Soil Ecol. 119, 407–416 (2017).Article 

Google Scholar 
Zeng, H. L. et al. The influence of Bt maize cultivation on communities of arbuscular mycorrhizal fungi revealed by MiSeq sequencing. Front. Microbiol. 9, 3275 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
Barbosa, M. V. et al. Aggregation of a ferruginous nodular gleysol in a pasture area in Cuba under the influence of Arbuscular mycorrhizal fungi associated with hybrid Urochloa. Soil Till. Res. 208(1), 104905 (2021).Article 

Google Scholar 
Zhang, F. G., Liu, M. H., Li, Y., Che, Y. & Xiao, Y. Effects of arbuscular mycorrhizal fungi, biochar and cadmium on the yield and element uptake of Medicago sativa. Sci. Total Environ. 655, 1150–1158 (2019).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Kokkoris, V. et al. Host identity influences nuclear dynamics in arbuscular mycorrhizal fungi. Curr. Biol. 31(7), 1531–1538 (2021).CAS 
PubMed 
Article 

Google Scholar 
Prates, J. P. et al. Agroecological coffee management increases arbuscular mycorrhizal fungi diversity. PLoS ONE 14(1), e0209093 (2019).Article 

Google Scholar 
Silvana, V. B., Longo, S., Marro, N. & Urcelay, C. The global invader Ligustrum lucidum accumulates beneficial arbuscular mycorrhizal fungi in a novel range. Plant Ecol. 222, 397–408 (2021).Article 

Google Scholar 
Chang, Q. et al. Effects of arbuscular mycorrhizal symbiosis on growth, nutrient and metal uptake by maize seedlings (Zea mays L.) grown in soils spiked with Lanthanum and Cadmium. Environ. Pollut. 2018(241), 607 (2018).Article 

Google Scholar 
Bi, Y. et al. Arbuscular mycorrhizal fungi alleviate root damage stress induced by simulated coal mining subsidence ground fissures. Sci. Total Environ. 652, 398–405 (2019).ADS 
PubMed 
Article 

Google Scholar 
Ma, X. N., Luo, W. Q., Li, J. & Wu, F. Arbuscular mycorrhizal fungi increase both concentrations and bioavilability of Zn in wheat (Triticum aestivum L.) grain on Zn-spiked soils. Appl. Soil Ecol. 135, 91–97 (2019).Article 

Google Scholar 
Srivastava, S., Johny, L. & Adholeya, A. Review of patents for agricultural use of arbuscular mycorrhizal fungi. Mycorrhiza 31(2), 127–136 (2021).PubMed 
Article 

Google Scholar 
Kabdwal, B. C., Sharma, R. & Tewari, R. Field efficacy of different combinations of Trichoderma harzianum, Pseudomonas fluorescens, and arbuscular mycorrhiza fungus against the major diseases of tomato in Uttarakhand (India). Egypt. J. Biol. Pest Control 29, 1 (2019).Article 

Google Scholar 
Jie, W. G., Bai, L., Yu, W. J. & Cai, B. Y. Analysis of interspecific relationships between Funneliformis mosseae and Fusarium oxysporum in the continuous cropping of soybean rhizosphere soil during the branching period. Biocontrol Sci. Technol. 25(9), 1036–1051 (2015).Article 

Google Scholar 
Jie, W. G., Lin, J. X., Guo, N., Cai, B. Y. & Yan, X. F. Community composition of rhizosphere fungi as affected by Funneliformis mosseae in soybean continuous cropping soil during seedling period. Chil. J. Agric. Res. 79(3), 356–365 (2019).Article 

Google Scholar 
Jie, W. G., Lin, J. X., Guo, N., Cai, B. Y. & Yan, X. F. Effects of Funneliformis mosseae on mycorrhizal colonization, plant growth and the composition of bacterial community in the rhizosphere of continuous cropping soybean at seedling stage. Int. J. Agric. Biol. 22(5), 1173–1180 (2019).CAS 

Google Scholar 
Jie, W. G., Yao, Y. X., Guo, N., Zhang, Y. Z. & Qiao, W. Effects of Rhizophagus intraradices on plant growth and the composition of microbial communities in the roots of continuous cropping soybean at maturity. Sustainability 13, 6623 (2021).CAS 
Article 

Google Scholar 
Yang, Y. R. et al. Interactive effects of exogenous melatonin and Rhizophagus intraradices on saline-alkaline stress tolerance in Leymus chinensis. Mycorrhiza 30(2), 357–371 (2020).CAS 
PubMed 
Article 

Google Scholar 
Phillips, J. M. & Hayman, D. S. Improved procedures for clearing roots and staining parasitic and vesicula-arbuscular mycorrhizal fungi for rapid assessment of infection. Trans. Br. Mycol. Soc. 55(1), 158–161 (1970).Article 

Google Scholar 
Geng, Y. F., Qiu, Q., Mao, J. H. & Jing, Y. B. Effects of arbuscular mycorrhizal fungi inoculation and different inoculation amount on seedlings of Mesua ferrea. J. Fujian For. Sci. Technol. 43(03), 67–71 (2016).
Google Scholar 
Schütz, L., Saharan, K., Mäder, P., Boller, T. & Mathimaran, N. Rate of hyphal spread of arbuscular mycorrhizal fungi from pigeon pea to finger millet and their contribution to plant growth and nutrient uptake in experimental microcosms. Appl. Soil Ecol. 169(248), 104156 (2022).Article 

Google Scholar 
Fehr, W. R. & Caviness, C. E. Stages of Soybean Development. Special Report 80. Ames Cooperative Extension Service, Agriculture and Home Economic Experiment Station 1–11 (Iowa State University Press, 1977).
Google Scholar 
Zhou, N., Liu, P., Wang, Z. Y. & Xu, G. D. The effects of rapeseed root exudates on the forms of aluminum in aluminum stressed rhizosphere soil. Crop Prot. 30(6), 631–636 (2011).CAS 
Article 

Google Scholar 
Dorn-In, S., Bassitta, R., Schwaiger, K., Bauer, J. & Holzel, C. S. Specific amplification of bacterial DNA by optimized so-called universal bacterial primers in samples rich of plant DNA. J. Microbiol. Methods 113, 50–56 (2015).CAS 
PubMed 
Article 

Google Scholar 
Smith, D. P. & Peay, K. G. Sequence depth, not PCR replication, improves ecological inference from next generation DNA sequencing. PLoS ONE 9(2), e90234 (2014).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7(5), 335–336 (2010).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Magoc, T. & Salzberg, S. L. FLASH: Fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27(21), 2957–2963 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Edgar, R. C., Haas, B. J., Quince, C. & Knight, R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27(16), 2194–2200 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Edgar, R. C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26(19), 2460–2461 (2010).CAS 
PubMed 
Article 

Google Scholar 
Chen, H. B. & Boutros, P. C. VennDiagram: A package for the generation of highly-customizable Venn and Euler diagrams in R. BMC Bioinform. 12, 35 (2011).Article 

Google Scholar 
Spagnoletti, F. N., Balestrasse, K., Lavado, R. S. & Giacometti, R. Arbuscular mycorrhiza detoxifying response against arsenic and pathogenic fungus in soybean. Ecotoxicol. Environ. Safe 133(11), 47–56 (2016).CAS 
Article 

Google Scholar 
Song, Y. Y., Chen, D. M., Lu, K., Sun, Z. X. & Zeng, R. S. Enhanced tomato disease resistance primed by arbuscular mycorrhizal fungus. Front. Plant Sci. 6, 786 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
Ramadan, A., Muroi, A. & Arimura, G. Herbivore-induced maize volatiles serve as priming cues for resistance against post-attack by the specialist armyworm Mythimna separata. J. Plant Interact. 6(2–3), 155–158 (2011).CAS 
Article 

Google Scholar 
Spagnoletti, F. N., Leiva, M., Chiocchio, V. & Lavado, R. S. Phosphorus fertilization reduces the severity of charcoal rot (Macrophomina phaseolina) and the arbuscular mycorrhizal protection in soybean. J. Plant Nutr. Soil Sci. 181, 855–860 (2018).CAS 
Article 

Google Scholar 
Wehner, J., Antunes, P. M., Powell, J. R., Mazukatow, J. & Rillig, M. C. Plant pathogen protection by arbuscular mycorrhizas: A role for fungal diversity? Pedobiologia 53(3), 197–201 (2010).Article 

Google Scholar 
Al-Askar, A. A. & Rashad, Y. M. Arbuscular mycorrhizal fungi: A biocontrol agent against common. Plant Pathol. 9, 31–38 (2010).Article 

Google Scholar 
Marschner, P. M., Crowley, D. E. & Lieberei, R. L. Arbuscular mycorrhizal infection changes the bacterial 16s rDNA community composition in the rhizosphere of maize. Mycorrhiza 11(6), 297–302 (2001).CAS 
PubMed 
Article 

Google Scholar 
Turrini, A., Avio, L., Giovannetti, M. & Agnolucci, M. Functional complementarity of arbuscular mycorrhizal fungi and associated microbiota: The challenge of translational research. Front. Plant Sci. 9, 1407 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Giovannetti, M., Avio, L. & Sbrana, C. Fungal spore germination and pre-symbiotic mycelial growth-physiological and genetic aspects. In Arbuscular Mycorrhizas Physiology and Function (eds Koltai, H. & Kapulnik, Y.) 3–32 (Springer, 2010).Chapter 

Google Scholar 
Linderman, R. G. Mycorrhizal interactions with the rhizosphere microflora-the mycorrhizosphere effect. Phytopathology 78(3), 366–371 (1988).
Google Scholar 
Lugtenberg, B. & Kamilova, F. Plant-growth-promoting rhizobacteria. Annu. Rev. Microbiol. 1, 541–556 (2009).Article 

Google Scholar 
Shoresh, M., Harman, G. E. & Mastouri, F. Induced systemic resistance and plant responses to fungal biocontrol agents. Annu. Rev. Phytopathol. 48(1), 21–43 (2010).CAS 
PubMed 
Article 

Google Scholar 
Wang, E. et al. A common signaling process that promotes mycorrhizal and oomycete colonization of plants. Curr. Biol. 22(23), 2242–2246 (2012).CAS 
PubMed 
Article 

Google Scholar 
Zamioudis, C. & Pieterse, C. M. J. Modulation of host immunity by beneficial microbes. Mol. Plant Microbe 25(2), 139–150 (2012).CAS 
Article 

Google Scholar 
Haichar, F. Z. et al. Plant host habitat and root exudates shape soil bacterial community structure. ISME J. 2(12), 1221–1230 (2008).CAS 
PubMed 
Article 

Google Scholar 
Linderman, R. G. Vesicular arbuscular mycorrhizae and soil microbial interactions, in Mycorrhizae in sustainable agriculture. ASA Spec. Publ. 54, 45–70 (1992).
Google Scholar 
Harrier Lucy, A. & Watson, C. A. The potential role of arbuscular mycorrhizal (AM) fungi in the bioprotection of plants against soil-borne pathogens in organic and/or other sustainable farming systems. Pest Manag. Sci. 60(2), 149–157 (2004).CAS 
PubMed 
Article 

Google Scholar 
Smith, G. S. The role of phosphorous nutrition in interactions of vesicular arbuscular mycorrhizal fungi with soilborne nematodes and fungi. Phytopathology 78(3), 371–374 (1988).CAS 

Google Scholar 
Schwob, I., Ducher, M. & Coudret, A. Effects of climatic factors on native arbuscular mycorrhizae and Meloidogyne exigua in a Brazilian rubber tree (Hevea brasilensis) plantation. Plant Pathol. 48(1), 19–25 (2010).Article 

Google Scholar  More

Benthic organism exudate collectionsExudate collections from benthic organisms were conducted on board the R/V Walton Smith in November 2018 in Lameshur Bay, St. John, U.S. Virgin Islands within the Virgin Islands National Park. In brief, we collected six species of benthic organisms (n = 6 specimens), incubated these organisms in separate containers for 8 h, and harvested the incubation water to characterize the composition of dissolved metabolites in their exudates. A description of the exudate collections is included below (additional details available in Supplementary Methods).Before each organism experiment, 58 l of surface (non-reef) seawater was collected ~1 mile offshore (18 17.127° N, 064 44.312° W, 31.6 m depth). Cells and particles were removed using peristaltic pressure through a 0.2 µm filter (47 mm, Omnipore, EMD Millipore Corporation, Billerica, MA, USA) using metabolomics-grade tubing and this filtrate (filtered seawater) was collected for the incubations. Additionally, two to three, 2 l filtrate subsets per experiment were acidified with concentrated hydrochloric acid (final concentration 1% volume/volume) and subjected to solid-phase-extraction (SPE) using a negative vacuum pressure of –3.7 to –5 100xkPA in Hg, to serve as controls. Before SPE, 6 ml, 1 gm Bond Elut PPL cartridges (Agilent, Santa Clara, CA, USA) were pre-conditioned with 6 ml of 100% HPLC-grade methanol.For the experiments, six species of benthic organisms were collected from reefs around Lameshur Bay by SCUBA divers. Experiments were completed on three stony corals (Porites astreoides, Siderastrea siderea, and Psuedodiploria strigosa), two octocorals (Plexaura homomalla and Gorgonia ventalina), and one encrusting alga (Ramicrusta textilis) (Table S1). P. astreoides, S. siderea, and R. textilis were held in a seawater table for 24 h (hrs) before the incubations and colonies from the other three species were held for 2-3 h due to timing constraints. Coral and algal fragments were generally small (2.5-5.0 cm in length).For each incubation, nine, acid-washed, 10 l polycarbonate bins (with lids) containing filtered seawater (4 l) were secured into an illuminated aquarium table (Prime HD, Aqua illumination, Bethlehem, PA, USA) (Photosynthetically Active Radiation = ~350–600 µmol quanta m−2 s−1). Air bubblers with sterilized Fluorinated Ethylene Propylene (FEP) tubing (890 Tubing, Nalgene, Thermo Scientific, Waltham, MA, USA) were used to inject air into each bin. Surface seawater was circulated through the aquarium table to maintain reef seawater temperature (29.5 °C). Six colonies/fragments of one species were randomly placed into 6 bins. The other 3 bins were reserved for control incubations containing filtered seawater only. A sensor (8 K HOBO/PAR loggers; Onset, Wareham, MA) monitored temperature and light conditions (data not shown). At the end of each 8 h experiment, colonies/fragments were wrapped in combusted aluminum foil and flash frozen in a charged dry shipper. The water in all incubations was re-filtered (as outlined above) and 2 l of each filtrate were acidified and subjected to SPE as described above. SPE cartridges were wrapped in combusted aluminum foil, placed in Whirl-Pak (Nasco, Madison, WI, USA) bags, and frozen at –20 °C.Metabolomics analyses and data processingAt the Woods Hole Oceanographic Institution (WHOI), metabolites were eluted from the thawed cartridges into combusted, borosilicate test tubes using 100% methanol (Optima grade) within 3 months of collection. The eluents were transferred into combusted amber 8 ml vials and nearly dried using a vacuum centrifuge. Samples were reconstituted in 200 µL of 95:5 (v/v) Milli-Q (MQ, Millipore Sigma, Burlington, MA, USA) water: acetonitrile with a deuterated standard mix added as an internal control (Table S2), vortexed, and prepared for targeted and untargeted metabolomics analyses in both positive and negative ion modes as described previously [16]. Samples prepared for untargeted analyses were further diluted (1:200) with the reconstitution solvent. A pooled sample (technical replicate) was made by combining aliquots from all samples and was injected repeatedly to assess instrument drift over the course of the run and for downstream sample processing. Samples prepared for targeted metabolomics were analyzed using an ultra-high performance liquid chromatography system (UHPLC; Accela Open Autosampler and Accela 1250 Pump, Thermo Scientific, Waltham, MA, USA) coupled to a heated electrospray ionization source (H-ESI) and a triple stage quadrupole mass spectrometer (TSQ Vantage, Thermo Scientific), operated in selected reaction monitoring (SRM) mode. Samples prepared for untargeted metabolomics were analyzed with a UHPLC system (Vanquish UHPLC, Thermo Scientific) coupled to an ultra-high resolution mass spectrometer (Orbitrap Fusion Lumos, Thermo Scientific). MS/MS spectra were collected in a data-dependent manner using higher energy collisional dissociation (HCD) with a normalized collision energy of 35% (detailed methods provided in [16]). A Waters Acquity HSS T3 column (2.1 × 100 mm, 1.8 μm) equipped with a Vanguard pre-column was used for chromatographic separation at 40 °C for targeted and untargeted analyses. Sample order was randomized and the pooled sample was analyzed after every six samples.For targeted metabolomics analysis, tandem MS/MS data files were converted into .mzML files using msconvert and processed with El-MAVEN [49]. Calibration curves for each compound (8 points each) were constructed based on the integrated peak areas using El-MAVEN. The concentrations of metabolites in the original samples were determined by dividing each concentration by the volume of the filtrate that passed through each PPL column. Finally, metabolite concentrations above the limits of detection and quantification were corrected for extraction efficiency using in-house values determined using standard protocols [50]. Statistical analyses of targeted metabolite concentrations were conducted using Welch’s independent t-tests and ANOVAs or Wilcoxon rank sum tests if data were not normally distributed (additional details in Supplementary Methods). We determined the mass of each colony and conducted Pearson correlations to investigate if colony size significantly correlated with concentrations of targeted metabolites, but no correlations were found.For the untargeted metabolomics analyses, raw files containing MS1 and MS/MS data were converted into .mzML files using msconvert and processed using XCMS [51]. Ion modes were analyzed separately. Before processing with XCMS, the R package AutoTuner [52] was used to find XCMS processing parameters appropriate for the data. In XCMS, the CentWave algorithm picked peaks using a gaussian fit. The specific parameters for peak picking for both ion modes were: noise = 10,000, peak-width = 3–15, ppm = 15, prefilter = c(2,168.600), integrate = 2, mzdiff = –0.005, snthresh = 10. Obiwarp was used to adjust retention times and this step was followed by correspondence analysis. For statistical analyses, including permutational PERMANOVA adonis tests and non-metric multidimensional scaling analysis (NMDS), MS1 features (defined as unique pairings of mass-to-charge (m/z) values with retention times) in both ion modes were culled following XCMS if they: (1) had >1 average fold change in the MQ blanks compared to the other samples, (2) occurred in less than 20% of samples (excluding pooled controls), and/or (3) were invariant (relative standard deviation of More

IPCC Climate Change 2022: Summary for Policymakers. (eds Pörtner, H. et al.) (Cambridge Univ. Press, 2022).Lewis, S. L. & Maslin, M. A. The human planet: How we created the Anthropocene. (Yale University Press, 2018).Lenzner, B. et al. Nat. Ecol. Evol. https://doi.org/s41559-022-01865-1 (2022).van Kleunen, M. et al. Nature 525, 100–103 (2015).Article 

Google Scholar 
Dawson, W. et al. Nat. Ecol. Evol. 1, 0186 (2017).Article 

Google Scholar 
Dyer, E. E. et al. PLoS Biol. 15, e2000942 (2017).Article 

Google Scholar 
Mohammed, R. S. et al. Am. Nat. 200, 140–155 (2022).Article 

Google Scholar 
Rodrigues, A. S. L. et al. Phil. Trans. R. Soc. Lond. B 374, 20190220 (2019).Article 

Google Scholar 
Reddin, C. J., Aberhan, M., Raja, N. B. & Kocsis, Á. T. Glob. Change Biol. 28, 5793–5807 (2022).CAS 
Article 

Google Scholar 
Elton, C. S. The Ecology of Invasions by Animals and Plants. (University of Chicago Press, 1958).Goode, E. Invasive Species Aren’t Always Unwanted. The New York Times https://www.nytimes.com/2016/03/01/science/invasive-species.html (2016).Reo, N. J. & Ogden, L. A. Sustain. Sci. 13, 1443–1452 (2018).Article 

Google Scholar 
Simberloff, D. Nature 475, 36 (2011).CAS 
Article 

Google Scholar  More

Bardgett, R. D. & van der Putten, W. H. Belowground biodiversity and ecosystem functioning. Nature 515, 505–511 (2014).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Fierer, N. Embracing the unknown: Disentangling the complexities of the soil microbiome. Nat. Rev. Microbiol. https://doi.org/10.1038/nrmicro.2017.87 (2017).Article 
PubMed 

Google Scholar 
Frouz, J. Effects of soil macro- and mesofauna on litter decomposition and soil organic matter stabilization. Geoderma 332, 161–172 (2018).ADS 
CAS 
Article 

Google Scholar 
Hicks Pries, C. E., Castanha, C., Porras, R., Phillips, C. & Torn, M. S. Response to comment on “The whole-soil carbon flux in response to warming”. Science 359, 1420–1423 (2018).Article 

Google Scholar 
Lavelle, P. et al. Soil function in a changing world: The role of invertebrate ecosystem engineers. Eur. J. Soil Biol. 33, 159–193 (1997).CAS 

Google Scholar 
Frouz, J., Špaldoňová, A., Fričová, K. & Bartuška, M. The effect of earthworms (Lumbricus rubellus) and simulated tillage on soil organic carbon in a long-term microcosm experiment. Soil. Biol. Biochem. 78, 58–64 (2014).CAS 
Article 

Google Scholar 
Lavelle, P., Blanchart, E., Martin, A., Martin, S. & Schaefer, R. A hierarchical model for decomposition in terrestrial ecosystems: Application to soils of the humid tropics. Assoc. Trop. Biol. 25, 130–150 (2016).
Google Scholar 
Lavelle, P. et al. Earthworms as a resource in tropical agroecosystems. Nat. Res. 34, 26–41 (1998).
Google Scholar 
Lavelle, P. Diversity of soil fauna and ecosystem function. Biol. Int. J. 33, 3–16 (1996).
Google Scholar 
Ruiz, N., Lavelle, P. & Jiménez, J. Soil macrofauna field manual. Recherche 113 (2008).Xiong, W. et al. Soil protist communities form a dynamic hub in the soil microbiome. ISME J. 12, 634–638 (2018).PubMed 
Article 

Google Scholar 
Fierer, N., Strickland, M. S., Liptzin, D., Bradford, M. A. & Cleveland, C. C. Global patterns in belowground communities. Ecol. Lett. 12, 1238–1249 (2009).PubMed 
Article 

Google Scholar 
Nielsen, U. N. et al. Global-scale patterns of assemblage structure of soil nematodes in relation to climate and ecosystem properties. Glob. Ecol. Biogeogr. 23, 968–978 (2014).Article 

Google Scholar 
Špaldoňová, A. & Frouz, J. The role of Armadillidium vulgare (Isopoda: Oniscidea) in litter decomposition and soil organic matter stabilization. Appl. Soil. Ecol. https://doi.org/10.1016/j.apsoil.2014.04.012 (2014).Article 

Google Scholar 
McCay, T. S., Cardelus, C. L. & Neatrour, M. A. Rate of litter decay and litter macroinvertebrates in limed and unlimed forests of the Adirondack Mountains, USA. For. Ecol. Manag. 304, 254–260 (2013).Article 

Google Scholar 
Slade, E. M. & Riutta, T. Interacting effects of leaf litter species and macrofauna on decomposition in different litter environments. Basic Appl. Ecol. 13, 423–431 (2012).Article 

Google Scholar 
Joly, F.-X., Coq, S., Coulis, M., Nahmani, J. & Hättenschwiler, S. Litter conversion into detritivore faeces reshuffles the quality control over C and N dynamics during decomposition. Funct. Ecol. https://doi.org/10.1111/1365-2435.13178 (2018).Article 

Google Scholar 
Hättenschwiler, S. Isopod effects on decomposition of litter produced under elevated CO2, N deposition and different soil types Isopod effects on decomposition of litter produced under elevated CO2, N deposition and different soil types. Glob. Change Biol. https://doi.org/10.1046/j.1365-2486.2001.00402.x (2015).Article 

Google Scholar 
Wall, D. H. et al. Global decomposition experiment shows soil animal impacts on decomposition are climate-dependent. Glob. Change Biol. 14, 2661–2677 (2008).ADS 
Article 

Google Scholar 
Brussaard, L., Pulleman, M. M., Ouédraogo, É., Mando, A. & Six, J. Soil fauna and soil function in the fabric of the food web. Pedobiologia (Jena) 50, 447–462 (2007).Article 

Google Scholar 
Frouz, J., Elhottová, D., Kuráž, V. & Šourková, M. Effects of soil macrofauna on other soil biota and soil formation in reclaimed and unreclaimed post mining sites: Results of a field microcosm experiment. Appl. Soil Ecol. 33, 308–320 (2006).Article 

Google Scholar 
García-Palacios, P., Maestre, F. T., Kattge, J. & Wall, D. H. Climate and litter quality differently modulate the effects of soil fauna on litter decomposition across biomes. Ecol. Lett. 16, 1045–1053 (2013).PubMed 
PubMed Central 
Article 

Google Scholar 
Melguizo-Ruiz, N. et al. Field exclusion of large soil predators impacts lower trophic levels and decreases leaf-litter decomposition in dry forests. J. Anim. Ecol. 89, 334–346 (2020).PubMed 
Article 

Google Scholar 
Lavelle, P. et al. Soil macroinvertebrate communities: A world-wide assessment. Glob. Ecol. Biogeogr. https://doi.org/10.1111/geb.13492 (2022).Article 

Google Scholar 
Coq, S. et al. Faeces traits as unifying predictors of detritivore effects on organic matter turnover. Geoderma 422, 115940 (2022).ADS 
CAS 
Article 

Google Scholar 
Lavelle, P. et al. Soil aggregation, ecosystem engineers and the C cycle. Act Oecol. 105, 103561 (2020).Article 

Google Scholar 
Filser, J. et al. Soil fauna: Key to new carbon models. Soil 2, 565–582 (2016).ADS 
CAS 
Article 

Google Scholar 
Wardle, D. A. et al. Ecological linkages between aboveground and belowground biota. Science 304, 1629–1633 (2004).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Joly, F. X. et al. Detritivore conversion of litter into faeces accelerates organic matter turnover. Commun. Biol. 3, 1–9 (2020).MathSciNet 
Article 

Google Scholar 
Frouz, J., Roubíčková, A., Heděnec, P. & Tajovský, K. Do soil fauna really hasten litter decomposition? A meta-analysis of enclosure studies. Eur. J. Soil Biol. 68, 18 (2015).CAS 
Article 

Google Scholar 
Lavelle, P., Blanchart, E., Martin, A., Martin, S. & Spain, A. A hierarchical model for decomposition in terrestrial ecosystems: Application to soils of the humid tropics. Biotropica 25, 130–150 (1993).Article 

Google Scholar 
Crowther, T. W. & A’Bear, A. D. Impacts of grazing soil fauna on decomposer fungi are species-specific and density-dependent. Fungal Ecol. 5, 277–281 (2012).Article 

Google Scholar 
Decaëns, T. Macroecological patterns in soil communities. Glob. Ecol. Biogeogr. 19, 287–302 (2010).Article 

Google Scholar 
Tordoff, G. M., Boddy, L. & Jones, T. H. Species-specific impacts of collembola grazing on fungal foraging ecology. Soil. Biol. Biochem. 40, 434–442 (2008).CAS 
Article 

Google Scholar 
Meysman, F. J. R., Middelburg, J. J. & Heip, C. H. R. Bioturbation: A fresh look at Darwin’s last idea. Trends Ecol. Evol. 21, 688–695 (2006).PubMed 
Article 

Google Scholar 
Frouz, J. et al. Soil food web changes during spontaneous succession at post mining sites: A possible ecosystem engineering effect on food web organization? PLoS ONE 8, e79694 (2013).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Frouz, J., Moradi, J., Püschel, D. & Rydlová, J. Earthworms affect growth and competition between ectomycorrhizal and arbuscular mycorrhizal plants. Ecosphere 10, e02736 (2019).Article 

Google Scholar 
Marichal, R. et al. Soil macroinvertebrate communities and ecosystem services in deforested landscapes of Amazonia. Appl. Soil. Ecol. 83, 177–185 (2014).Article 

Google Scholar 
Prescott, C. E. & Vesterdal, L. Forest ecology and management decomposition and transformations along the continuum from litter to soil organic matter in forest soils. For. Ecol. Manag. 498, 119522 (2021).Article 

Google Scholar 
Kampichler, C. & Bruckner, A. The role of microarthropods in terrestrial decomposition: A meta-analysis of 40 years of litterbag studies. Biol. Rev. Camb. Philos. Soc. 84, 375–389 (2009).PubMed 
Article 

Google Scholar 
Brennan, K. E. C., Christie, F. J. & York, A. Global climate change and litter decomposition: More frequent fire slows decomposition and increases the functional importance of invertebrates. Glob. Change. Biol. 15, 2958–2971 (2009).ADS 
Article 

Google Scholar 
Birkhofer, K. et al. General relationships between abiotic soil properties and soil biota across spatial scales and different land-use types. PLoS ONE 7, e43292 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Wu, T., Ayres, E., Bardgett, R. D., Wall, D. H. & Garey, J. R. Molecular study of worldwide distribution and diversity of soil animals. PNAS 108, 17720–17725 (2011).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
James, S. W. et al. Comment on Global distribution of earthworm diversity. Science 371, 4629 (2021).Article 

Google Scholar 
Cesarz, S. et al. Tree species diversity versus tree species identity: Driving forces in structuring forest food webs as indicated by soil nematodes. Soil. Biol. Biochem. 62, 36–45 (2013).CAS 
Article 

Google Scholar 
Eppinga, M. B., Kaproth, M. A., Collins, A. R. & Molofsky, J. Litter feedbacks, evolutionary change and exotic plant invasion. J. Ecol. 99, 503–514 (2011).
Google Scholar 
Harrison, K. A., Bol, R. & Bardgett, R. D. Do plant species with different growth strategies vary in their ability to compete with soil microbes for chemical forms of nitrogen? Soil. Biol. Biochem. 40, 228–237 (2008).CAS 
Article 

Google Scholar 
Wardle, D. A., Yeates, G. W., Barker, G. M. & Bonner, K. I. The influence of plant litter diversity on decomposer abundance and diversity. Soil Biol. Biochem. 38, 1052–1062 (2006).CAS 
Article 

Google Scholar 
Zhang, D., Hui, D., Luo, Y. & Zhou, G. Rates of litter decomposition in terrestrial ecosystems: Global patterns and controlling factors. J. Plant Ecol. 1, 85–93 (2008).Article 

Google Scholar 
Preston, C. M. & Trofymow, J. A. Variability in litter quality and its relationship to litter decay in Canadian forests. Botany 78, 1269–1287 (2000).Article 

Google Scholar 
Bar-On, Y. M., Phillips, R. & Milo, R. The biomass distribution on Earth. PNAS 115, 6506–6511 (2018).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Phillips, H. R. P. et al. Global distribution of earthworm diversity. Science 366, 480–485 (2019).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Andersen, D. C. Below-ground herbivory in natural communities: A review emphasizing fossorial animals. Q. Rev. Biol. 62, 261–286 (1987).Article 

Google Scholar 
Cepáková, S. & Frouz, J. Changes in chemical composition of litter during decomposition: A review of published 13C NMR spectra. Plant Nutr. Soil Sci. 15, 805–815 (2015).
Google Scholar 
Pietsch, K. A. et al. Global relationship of wood and leaf litter decomposability: The role of functional traits within and across plant organs. Glob. Ecol. Biogeogr. 23, 1046–1057 (2014).Article 

Google Scholar 
Cornwell, W. K. et al. Plant species traits are the predominant control on litter decomposition rates within biomes worldwide. Ecol. Lett. 11, 1065–1071 (2008).PubMed 
Article 

Google Scholar 
Ponge, J.-F. Plant–soil feedbacks mediated by humus forms: A review. Soil. Biol. Biochem. 57, 1048–1060 (2013).CAS 
Article 

Google Scholar 
Salmon, S., Mantel, J., Frizzera, L. & Zanella, A. Changes in humus forms and soil animal communities in two developmental phases of Norway spruce on an acidic substrate. For. Ecol. Manag. 237, 47–56 (2006).Article 

Google Scholar 
Desie, E. et al. Positive feedback loop between earthworms, humus form and soil pH reinforces earthworm abundance in European forests. Funct. Ecol. 34, 2598–2610 (2020).Article 

Google Scholar 
Samson, F. B. & Knopf, F. L. (eds) Organisms as Ecosystem Engineers BT—Ecosystem Management: Selected Readings 130–147 (Springer, 1996).
Google Scholar 
Araujo, P. I., Yahdjian, L. & Austin, A. T. Do soil organisms affect aboveground litter decomposition in the semiarid Patagonian steppe, Argentina? Oecologia 168, 221–230 (2012).ADS 
PubMed 
Article 

Google Scholar 
Frouz, J. et al. Soil biota in post-mining sites along a climatic gradient in the USA: Simple communities in shortgrass prairie recover faster than complex communities in tallgrass prairie and forest. Soil. Biol. Biochem. 67, 212–225 (2013).CAS 
Article 

Google Scholar 
Hattenschwiler, S., Tiunov, A. V. & Scheu, S. Biodiversity and litter decomposition interrestrial ecosystems. Annu. Rev. Ecol. Evol. Syst. 36, 191–218 (2005).Article 

Google Scholar 
Deckmyn, G. et al. KEYLINK: Towards a more integrative soil representation for inclusion in ecosystem scale models I. Review and model concept. PeerJ 8, 1–69 (2020).Article 

Google Scholar 
Héry, M. et al. Effect of earthworms on the community structure of active methanotrophic bacteria in a landfill cover soil. SME J. 2, 92–104 (2008).
Google Scholar 
Roubickova, A., Mudrak, O. & Frouz, J. Effect of earthworm on growth of late succession plant species in postmining sites under laboratory and field conditions. Biol. Fert. Soils 45, 769–774 (2009).Article 

Google Scholar 
Bodine, M. C. & Ueckert, D. N. Effect litter in west of desert termites on herbage and in a shortgrass Texas. J. Range. Manag. 28, 353–358 (1975).Article 

Google Scholar 
Cebrian, J. Patterns in the fate of production in plant communities. Am. Nat. 154, 449–468 (1999).PubMed 
Article 

Google Scholar 
Petersen, H. & Luxton, M. A comparative analysis of soil fauna populations and their role in decomposition processes. Oikos 39, 288 (1982).Article 

Google Scholar 
Gongalsky, K. B., Persson, T. & Pokarzhevskii, A. D. Effects of soil temperature and moisture on the feeding activity of soil animals as determined by the bait-lamina test. Appl. Soil Ecol. 39, 84–90 (2008).Article 

Google Scholar 
Simpson, J. E., Slade, E., Riutta, T. & Taylor, M. E. Factors affecting soil fauna feeding activity in a fragmented lowland temperate deciduous woodland. PLoS ONE 7, 0029616 (2012).ADS 
Article 

Google Scholar 
Clarke, A. Is there a universal temperature dependence of metabolism? Funct. Ecol. 18, 252–256 (2004).Article 

Google Scholar 
Coq, S. & Ibanez, S. Soil fauna contribution to winter decomposition in subalpine grasslands. Soil Org. https://doi.org/10.25674/so91iss3pp107 (2019).Article 

Google Scholar 
Frouz, J., Špaldoňová, A., Lhotáková, Z. & Cajthaml, T. Major mechanisms contributing to the macrofauna-mediated slow down of litter decomposition. Soil. Biol. Biochem. 91, 23–31 (2015).CAS 
Article 

Google Scholar 
Frouz, J., Šustr, V. & Kalčík, J. Energetic budget of three species of bibionid larvae. In Contributions to Soil Zoology in Central Europe I. ISB AS CR, České Budějovice, 15–18 (2005).Frouz, J., Jedlička, P., Šimáčková, H. & Lhotáková, Z. The life cycle, population dynamics, and contribution to litter decomposition of Penthetria holosericea (Diptera: Bibionidae) in an alder forest. Eur. J. Soil Biol. 71, 21–27 (2015).Article 

Google Scholar 
Brovkin, V. et al. Plant-driven variation in decomposition rates improves projections of global litter stock distribution. Biogeosciences 9, 565–576 (2012).ADS 
CAS 
Article 

Google Scholar 
Buis, G. M. et al. Controls of aboveground net primary production in mesic savanna grasslands: An inter-hemispheric comparison. Ecosystems 12, 982–995 (2009).CAS 
Article 

Google Scholar 
O’Neill, D. W. & Abson, D. J. To settle or protect? A global analysis of net primary production in parks and urban areas. Ecol. Econ. 69, 319–327 (2009).Article 

Google Scholar 
Pan, S. et al. Impacts of climate variability and extremes on global net primary production in the first decade of the 21st century. J. Geogr. Sci. 25, 1027–1044 (2015).Article 

Google Scholar 
Yanai, R. D. et al. Litterfall and litter chemistry change over time in an old-growth temperate forest, northeastern China. For. Ecol. Manag. 43, 279–287 (1999).
Google Scholar 
Shchelchkova, M., Davydov, S., Fyodorov-Davydov, D., Davydova, A. & Boeskorov, G. The characteristics of a relic steppe of Northeast Asia: Refuges of the Pleistocene Mammoth steppe (an example from the Lower Kolyma area). IOP Conf. Ser. Earth Environ. Sci. 438, 012025 (2020).Article 

Google Scholar 
Ayuke, F. O. et al. Soil fertility management: Impacts on soil macrofauna, soil aggregation and soil organic matter allocation. Appl. Soil Ecol. 48, 53–62 (2011).Article 

Google Scholar 
Blanchart, E. et al. Effect of direct seeding mulch-based systems on soil carbon storage and macrofauna in Central Brazil. Agric. Conspec. Sci. 72, 81–87 (2007).
Google Scholar 
Korboulewsky, N., Perez, G. & Chauvat, M. How tree diversity affects soil fauna diversity: A review. Soil Biol. Biochem. 94, 94–106 (2016).CAS 
Article 

Google Scholar 
Frouz, J., Pizl, V., Cienciala, E. & Kalcik, J. Carbon storage in post-mining forest soil, the role of tree biomass and soil bioturbation. Biogeochemistry 94, 111–121 (2009).CAS 
Article 

Google Scholar 
Milton, Y. & Kaspari, M. Bottom-up and top-down regulation of decomposition in a tropical forest. Oecologia 153, 163–172 (2007).ADS 
PubMed 
Article 

Google Scholar 
Öpik, M., Moora, M., Liira, J. & Zobel, M. Composition of root-colonizing arbuscular mycorrhizal fungal communities in different ecosystems around the globe. J. Ecol. 94, 778–790 (2006).Article 

Google Scholar 
Portela, M. B. et al. Do ecological corridors increase the abundance of soil fauna? Écoscience 27, 45–57 (2020).Article 

Google Scholar 
Prieto, I., Almagro, M., Bastida, F. & Querejeta, J. I. Altered leaf litter quality exacerbates the negative impact of climate change on decomposition. J. Ecol. 107, 2364–2382 (2019).CAS 
Article 

Google Scholar 
Van der Putten, W. H. et al. Plant-soil feedbacks: The past, the present and future challenges. J. Ecol. 101, 265–276 (2013).Article 

Google Scholar 
Artz, R. et al. European atlas of soil. Biodiversity. https://doi.org/10.13140/RG.2.1.3178.2880 (2010).Article 

Google Scholar 
Orgiazzi, A. et al. Global Soil Biodiversity Atlas (European Soil Data Centre, 2016).
Google Scholar 
Peng, Y. et al. Litter quality, mycorrhizal association, and soil properties regulate effects of tree species on the soil fauna community. Geoderma 407, 115570 (2022).ADS 
CAS 
Article 

Google Scholar 
Bardgett, R. D. The Biology of Soil: A Community and Ecosystem Approach 255 (Oxford University Press, 2005).Book 

Google Scholar 
Jackson, R. B. et al. A global analysis of root distributions for terrestrial biomes. Oecologia 108, 389–411 (1996).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Jackson, R. B., Mooney, H. A. & Schulze, E.-D. A global budget for fine root biomass, surface area, and nutrient contents. PNAS 94, 7362–7366 (1997).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Sanchez, G. PLS Path Modeling with R, 235 (2013).Holland, E. A. et al. A global database of litterfall mass and litter pool carbon and nutrients. 10.3334/ORNLDAAC/1244 (2014).Palpurina, S. et al. The type of nutrient limitation affects the plant species richness–productivity relationship: Evidence from dry grasslands across Eurasia. J. Ecol. 107, 1038–1050 (2019).CAS 
Article 

Google Scholar 
Green, C. & Byrne, K. A. Biomass: Impact on carbon cycle and greenhouse gas emissions. In Encyclopedia of Energy (ed. Cleveland, C. J.) 223–236 (Elsevier, 2004).Chapter 

Google Scholar 
Liang, W. et al. Analysis of spatial and temporal patterns of net primary production and their climate controls in China from 1982 to 2010. Agric. For. Meteorol. 204, 22–36 (2015).ADS 
Article 

Google Scholar 
Ise, T., Litton, C. M., Giardina, C. P. & Ito, A. Comparison of modeling approaches for carbon partitioning: Impact on estimates of global net primary production and equilibrium biomass of woody vegetation from MODIS GPP. J. Geo. Res. Biogeosci. 115, 1–11 (2010).
Google Scholar 
Ni, J. Net primary production, carbon storage and climate change in Chinese biomes. Nord. J. Bot. 20, 415–426 (2000).Article 

Google Scholar 
Jandl, R. et al. How strongly can forest management influence soil carbon sequestration? Geoderma 137, 253–268 (2007).ADS 
CAS 
Article 

Google Scholar 
Reeves, M. C., Moreno, A. L., Bagne, K. E. & Running, S. W. Estimating climate change effects on net primary production of rangelands in the United States. Clim. Change 126, 429–442 (2014).ADS 
Article 

Google Scholar 
Cappai, C. et al. Small-scale spatial variation of soil organic matter pools generated by cork oak trees in Mediterranean agro-silvo-pastoral systems. Geoderma 304, 59–67 (2017).ADS 
CAS 
Article 

Google Scholar 
Clark, D. A. et al. Net primary production in tropical forests: An evaluation and synthesis of existing field data. Ecol. Appl. 11, 371–384 (2001).Article 

Google Scholar 
Yanai, R. D., Arthur, M. A., Acker, M., Levine, C. R. & Park, B. B. Variation in mass and nutrient concentration of leaf litter across years and sites in a northern hardwood forest. Can. J. For. Res. 42, 1597–1610 (2012).CAS 
Article 

Google Scholar  More

Richardson, D. M. et al. Naturalization and invasion of alien plants: concepts and definitions. Divers. Distrib. 6, 93–107 (2000).
Google Scholar 
Winter, M. et al. Plant extinctions and introductions lead to phylogenetic and taxonomic homogenization of the European flora. Proc. Natl Acad. Sci. USA 106, 21721–21725 (2009).CAS 
PubMed 
PubMed Central 

Google Scholar 
Pyšek, P. et al. Naturalized alien flora of the world: species diversity, taxonomic and phylogenetic patterns, geographic distribution and global hotspots of plant invasion. Preslia 89, 203–274 (2017).
Google Scholar 
Daru, B. H. et al. Widespread homogenization of plant communities in the Anthropocene. Nat. Commun. 12, 6983 (2021).Yang, Q. et al. The global loss of floristic uniqueness. Nat. Commun. 12, 7290 (2021).van Kleunen, M. et al. Global exchange and accumulation of non-native plants. Nature 525, 100–103 (2015).PubMed 

Google Scholar 
Dawson, W. et al. Global hotspots and correlates of alien species richness across taxonomic groups. Nat. Ecol. Evol. 1, 0186 (2017).Essl, F. et al. Drivers of the relative richness of naturalized and invasive plant species on Earth. AoB Plants 11, plz051 (2019).Pyšek, P. & Richardson, D. M. The biogeography of naturalization in alien plants. J. Biogeogr. 33, 2040–2050 (2006).
Google Scholar 
Moser, D. et al. Remoteness promotes biological invasions on islands worldwide. Proc. Natl Acad. Sci. USA 115, 9270–9275 (2018).CAS 
PubMed 
PubMed Central 

Google Scholar 
Guo, Q. et al. Latitudinal patterns of alien plant invasions. J. Biogeogr. 48, 253–262 (2021).
Google Scholar 
Pyšek, P. et al. Disentangling the role of environmental and human pressures on biological invasions across Europe. Proc. Natl Acad. Sci. USA 107, 12157–12162 (2010).PubMed 
PubMed Central 

Google Scholar 
Essl, F. et al. Socioeconomic legacy yields an invasion debt. Proc. Natl Acad. Sci. USA 108, 203–207 (2011).CAS 
PubMed 

Google Scholar 
Helmus, M. R., Mahler, D. L. & Losos, J. B. Island biogeography of the Anthropocene. Nature 513, 543–546 (2014).CAS 
PubMed 

Google Scholar 
di Castri, F. in Biological Invasions: A Global Perspective (ed. Drake, J. et al.), Ch. 1 (Wiley, 1989).Crosby, A. W. Ecological Imperialism: The Biological Expansion of Europe, 900–1900 2nd edn (Cambridge Univ. Press, 2004).Diamond, J. M. Guns, Germs, and Steel: The Fates of Human Societies (Norton, 2005).Nunn, N. & Qian, N. The Columbian exchange: a history of disease, food, and ideas. J. Econ. Perspect. 24, 163–188 (2010).
Google Scholar 
Beinart, W. & Middleton, K. Plant transfers in historical perspective: a review article. Environ. Hist. Camb. 10, 3–29 (2004).
Google Scholar 
Mrozowski, S. A. in Historical Archaeology (eds Hall, M. & Silliman, S. W.) Ch. 2 (Blackwell, 2006).Brockway, L. H. Science and colonial expansion: the role of the British Royal Botanic Gardens. Am. Ethnol. 6, 449–465 (1979).
Google Scholar 
Hulme, P. E. Addressing the threat to biodiversity from botanic gardens. Trends Ecol. Evol. 26, 168–174 (2011).PubMed 

Google Scholar 
Baas, P. The golden age of Dutch colonial botany and its impact on garden and herbarium collections. In Proc. Int. Symp. held by The Royal Danish Academy of Sciences and Letters in Copenhagen (eds Friis, I. & Balselv, H.), 53–62 (2017).Anderson, W. Climates of opinion: acclimatization in nineteenth-century France and England. Vic. Stud. 35, 135–157 (1992).CAS 
PubMed 

Google Scholar 
Osborne, M. A. Acclimatizing the world: a history of the paradigmatic colonial science. Osiris 15, 135–151 (2000).CAS 
PubMed 

Google Scholar 
Musgrave, T., Gardner, C. & Musgrave, W. The Plant Hunters Two Hundred Years of Adventure and Discovery (Seven Dials, 1999).Stoner, A. & Hummer, K. 19th and 20th century plant hunters. HortScience 42, 197–199 (2007).
Google Scholar 
Williams, K. A. An overview of the U.S. National Plant Germplasm System’s Exploration Program. HortScience 40, 297–301 (2005).
Google Scholar 
McCracken, D. P. Gardens of Empire: Botanical Institutions of the Victorian British Empire Garden History Vol. 26 (Leicester Univ. Press, 1997).Mitchener, K. J. & Weidenmier, M. Trade and empire. Econ. J. 118, 1805–1834 (2008).
Google Scholar 
World Trade Report 2007: Six Decades of Multilateral Trade Cooperation: What Have We Learnt? (World Trade Organization, 2007).Seebens, H. et al. No saturation in the accumulation of alien species worldwide. Nat. Commun. 8, 14435 (2017).Seebens, H. et al. Global rise in emerging alien species results from increased accessibility of new source pools. Proc. Natl Acad. Sci. USA 115, E2264–E2273 (2018).CAS 
PubMed 
PubMed Central 

Google Scholar 
Essl, F. et al. Historical legacies accumulate to shape future biodiversity in an era of rapid global change. Divers. Distrib. 21, 534–547 (2015).
Google Scholar 
van Kleunen, M. et al. The Global Naturalized Alien Flora (GloNAF) database. Ecology 100, e02542 (2019).PubMed 

Google Scholar 
Soininen, J., McDonald, R. & Hillebrand, H. The distance decay of similarity in ecological communities. Ecography 30, 3–12 (2007).
Google Scholar 
Blackburn, T. M. et al. A proposed unified framework for biological invasions. Trends Ecol. Evol. 26, 333–339 (2011).PubMed 

Google Scholar 
Colautti, R. I., Grigorovich, I. A. & MacIsaac, H. J. Propagule pressure: a null model for biological invasions. Biol. Invasions 8, 1023–1037 (2006).
Google Scholar 
Cassey, P., Delean, S., Lockwood, J. L., Sadowski, J. S. & Blackburn, T. M. Dissecting the null model for biological invasions: a meta-analysis of the propagule pressure effect. PLoS Biol. 16, e2005987 (2018).PubMed 
PubMed Central 

Google Scholar 
Blackburn, T. M., Cassey, P. & Duncan, R. P. Colonization pressure: a second null model for invasion biology. Biol. Invasions 22, 1221–1233 (2020).
Google Scholar 
Nekola, J. C. & White, P. S. The distance decay of similarity in biogeography and ecology. J. Biogeogr. 26, 867–878 (1999).
Google Scholar 
Liu, C., Wolter, C., Xian, W. & Jeschke, J. M. Most invasive species largely conserve their climatic niche. Proc. Natl Acad. Sci. USA 117, 23643–23651 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
Panton, K. J. Historical Dictionary of the British Empire (Rowman & Littlefield, 2015).Brendon, P. The Decline and Fall of the British Empire, 1781–1997 (Cape, 2007).Hulme, P. E. Unwelcome exchange: international trade as a direct and indirect driver of biological invasions worldwide. One Earth 4, 666–679 (2021).
Google Scholar 
Levinson, M. The Box: How the Shipping Container Made the World Smaller and the World Economy Bigger (Princeton Univ. Press, 2010).Liebhold, A. M., Brockerhoff, E. G. & Kimberley, M. Depletion of heterogeneous source species pools predicts future invasion rates. J. Appl. Ecol. 54, 1968–1977 (2017).
Google Scholar 
Theoharides, K. A. & Dukes, J. S. Plant invasion across space and time: factors affecting nonindigenous species success during four stages of invasion. New Phytol. 176, 256–273 (2007).PubMed 

Google Scholar 
Maltby, W. S. The Rise and Fall of the Spanish Empire (Palgrave Macmillan, 2008).Disdier, A. C. & Head, K. The puzzling persistence of the distance effect on bilateral trade. Rev. Econ. Stat. 90, 37–48 (2008).
Google Scholar 
Jiménez, A., Pauchard, A., Cavieres, L. A., Marticorena, A. & Bustamante, R. O. Do climatically similar regions contain similar alien floras? A comparison between the Mediterranean areas of central Chile and California. J. Biogeogr. 35, 614–624 (2008).
Google Scholar 
Epanchin-Niell, R., McAusland, C., Liebhold, A., Mwebaze, P. & Springborn, M. R. Biological invasions and international trade: managing a moving target. Rev. Environ. Econ. Policy 15, 180–190 (2021).
Google Scholar 
Bakewell, P. A History of Latin America (Wiley-Blackwell, 2003).Disney, A. R. A History of Portugal and the Portuguese Empire (Cambridge Univ. Press, 2009).De Zwart, P. Globalization in the early modern era: new evidence from the Dutch-Asiatic Trade, c. 1600–1800. J. Econ. Hist. 76, 520–558 (2016).
Google Scholar 
Emmer, P. C. & Gommans, J. J. L. The Dutch Overseas Empire, 1600–1800 (Cambridge Univ. Press, 2021).Melitz, J. & Toubal, F. Native language, spoken language, translation and trade. J. Int. Econ. 93, 351–363 (2014).
Google Scholar 
Becker, B. Introducing COLDAT: the colonial dates dataset. Preprint at OSF https://doi.org/10.31219/osf.io/apvqm (2019).Pyšek, P., Richardson, D. M. & Williamson, M. Predicting and explaining plant invasions through analysis of source area floras: some critical considerations. Divers. Distrib. 10, 179–187 (2004).
Google Scholar 
R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2021).Hui, C. & McGeoch, M. A. Zeta diversity as a concept and metric that unifies incidence-based biodiversity patterns. Am. Nat. 184, 684–694 (2014).PubMed 

Google Scholar 
McGeoch, M. A. et al. Measuring continuous compositional change using decline and decay in zeta diversity. Ecology 100, e02832 (2019).Latombe, G., Richardson, D. M., Pyšek, P., Kučera, T. & Hui, C. Drivers of species turnover vary with species commonness for native and alien plants with different residence times. Ecology 99, 2763–2775 (2018).PubMed 

Google Scholar 
Latombe, G., McGeoch, M. A., Nipperess, D. A. & Hui, C. zetadiv: an R package for computing compositional change across multiple sites, assemblages or cases. Preprint at bioRxiv https://doi.org/10.1101/324897 (2018).Latombe, G., McGeoch, M. A., Nipperess, D. A. & Hui, C. zetadiv: Functions to compute compositional turnover using zeta diversity. R package version 1.2.0 (2020).Baselga, A. Partitioning the turnover and nestedness components of beta diversity. Glob. Ecol. Biogeogr. 19, 134–143 (2010).
Google Scholar 
Latombe, G., Hui, C. & McGeoch, M. A. Multi-site generalised dissimilarity modelling: using zeta diversity to differentiate drivers of turnover in rare and widespread species. Methods Ecol. Evol. 8, 431–442 (2017).
Google Scholar 
Newman, M. E. J. & Girvan, M. Finding and evaluating community structure in networks. Phys. Rev. E 69, 026113 (2004).Clauset, A., Newman, M. E. J. & Moore, C. Finding community structure in very large networks. Phys. Rev. E 70, 066111 (2004).
Google Scholar 
Csardi, G. & Nepusz, T. The igraph software package for complex network research. InterJournal, Complex Systems, 1695 (2006).Bonacich, P. Power and centrality: a family of neasures. Am. J. Sociol. 92, 1170–1182 (1987).
Google Scholar 
Delmas, E. et al. Analysing ecological networks of species interactions. Biol. Rev. 94, 16–36 (2019).
Google Scholar  More

Bowman, D. M. J. S. et al. Fire in the Earth system. Science 324, 481–484 (2009).Article 

Google Scholar 
Bowman, D. M. J. S. et al. Human exposure and sensitivity to globally extreme wildfire events. Nat. Ecol. Evol. 1, 0058 (2017).Article 

Google Scholar 
Hamilton, D. S. et al. Earth, wind, fire, and pollution: aerosol nutrient sources and impacts on ocean biogeochemistry. Ann. Rev. Mar. Sci. 14, 303–330 (2022).Article 

Google Scholar 
Barkley, A. E. et al. African biomass burning is a substantial source of phosphorus deposition to the Amazon, tropical Atlantic Ocean, and Southern Ocean. Proc. Natl Acad. Sci. USA 116, 16216–16221 (2019).Article 

Google Scholar 
Schlosser, J. S. et al. Analysis of aerosol composition data for western United States wildfires between 2005 and 2015: dust emissions, chloride depletion, and most enhanced aerosol constituents. J. Geophys. Res. Atmos. 122, 8951–8966 (2017).Article 

Google Scholar 
Wagner, R., Schepanski, K. & Klose, M. The dust emission potential of agricultural-like fires—theoretical estimates from two conceptually different dust emission parameterizations. J. Geophys. Res. Atmos. 126, e2020JD034355 (2017).
Google Scholar 
Ichoku, C. et al. Biomass burning, land-cover change, and the hydrological cycle in northern sub-Saharan Africa. Environ. Res. Lett. 11, 095005 (2016).Article 

Google Scholar 
Bowman, D. M. J. S. et al. Vegetation fires in the Anthropocene. Nat. Rev. Earth Environ. 1, 500–515 (2020).Article 

Google Scholar 
Duniway, M. C. et al. Wind erosion and dust from US drylands: a review of causes, consequences, and solutions in a changing world. Ecosphere 10, e02650 (2019).Article 

Google Scholar 
Okin, G. S., Gillette, D. A. & Herrick, J. E. Multi-scale controls on and consequences of aeolian processes in landscape change in arid and semi-arid environments. J. Arid. Environ. 65, 253–275 (2006).Article 

Google Scholar 
Raupach, M. R. Drag and drag partition on rough surfaces. Boundary Layer Meteorol. 60, 375–395 (1992).Article 

Google Scholar 
Webb, N. P. et al. Vegetation canopy gap size and height: critical indicators for wind erosion monitoring and management. Rangel. Ecol. Manag. 76, 78–83 (2021).Article 

Google Scholar 
Ellis, T. M., Bowman, D. M. J. S., Jain, P., Flannigan, M. D. & Williamson, G. J. Global increase in wildfire risk due to climate-driven declines in fuel moisture. Glob. Change Biol. 28, 1544–1559 (2022).Article 

Google Scholar 
Ravi, S. et al. Aeolian processes and the biosphere. Rev. Geophys. 49, RG3001 (2011).Article 

Google Scholar 
Wagenbrenner, N. S., Germino, M. J., Lamb, B. K., Robichaud, P. R. & Foltz, R. B. Wind erosion from a sagebrush steppe burned by wildfire: Measurements of PM10 and total horizontal sediment flux. Aeolian Res. 10, 25–36 (2013).Article 

Google Scholar 
Wagenbrenner, N. S. A large source of dust missing in Particulate Matter emission inventories? Wind erosion of post-fire landscapes. Elementa 5, 2 (2017).
Google Scholar 
Jeanneau, A. C., Ostendorf, B. & Herrmann, T. Relative spatial differences in sediment transport in fire-affected agricultural landscapes: a field study. Aeolian Res. 39, 13–22 (2019).Article 

Google Scholar 
Deb, P. et al. Causes of the widespread 2019–2020 Australian bushfire season. Earths Future 8, e2020EF001671 (2020).Article 

Google Scholar 
Nogrady, B. & Nicky, B. The climate link to Australia’s fires. Nature 577, 610–612 (2020).Yu, Y. & Ginoux, P. Assessing the contribution of the ENSO and MJO to Australian dust activity based on satellite- and ground-based observations. Atmos. Chem. Phys. 21, 8511–8530 (2021).Article 

Google Scholar 
Ginoux, P., Prospero, J. M., Gill, T. E., Hsu, N. C. & Zhao, M. Global-scale attribution of anthropogenic and natural dust sources and their emission rates based on MODIS Deep Blue aerosol products. Rev. Geophys. 50, RG3005 (2012).Article 

Google Scholar 
Yu, Y., Kalashnikova, O. V., Garay, M. J., Lee, H. & Notaro, M. Identification and characterization of dust source regions across North Africa and the Middle East using MISR satellite observations. Geophys. Res. Lett. 45, 6690–6701 (2018).Article 

Google Scholar 
Brianne, P., Rebecca, H. & David, L. The fate of biological soil crusts after fire: a meta-analysis. Glob. Ecol. Conserv. 24, e01380 (2020).Article 

Google Scholar 
Rodriguez-Caballero, E. et al. Global cycling and climate effects of aeolian dust controlled by biological soil crusts. Nat. Geosci. 15, 458–463 (2022).Article 

Google Scholar 
Goudie, A. S. & Middleton, N. J. Desert Dust in the Global System (Springer, 2006).Ginoux, P. Atmospheric chemistry: warming or cooling dust? Nat. Geosci. 10, 246–247 (2017).Article 

Google Scholar 
DeMott, P. J. et al. Predicting global atmospheric ice nuclei distributions and their impacts on climate. Proc. Natl Acad. Sci. USA 107, 11217–11222 (2010).Article 

Google Scholar 
Yu, H. et al. The fertilizing role of African dust in the Amazon rainforest: a first multiyear assessment based on data from cloud–aerosol lidar and infrared Pathfinder satellite observations. Geophys. Res. Lett. 42, 1984–1991 (2015).Article 

Google Scholar 
Tang, W. et al. Widespread phytoplankton blooms triggered by 2019–2020 Australian wildfires. Nature 597, 370–375 (2021).Article 

Google Scholar 
Sarangi, C. et al. Dust dominates high-altitude snow darkening and melt over high-mountain Asia. Nat. Clim. Change 10, 1045–1051 (2020).Article 

Google Scholar 
Cook, B. I. et al. Twenty-first century drought projections in the CMIP6 forcing scenarios. Earths Future 8, e2019EF001461 (2020).Article 

Google Scholar 
Zheng, B. et al. Increasing forest fire emissions despite the decline in global burned area. Sci. Adv. 7, eabh2646 (2021).Article 

Google Scholar 
Abatzoglou, J. T. & Williams, A. P. Impact of anthropogenic climate change on wildfire across western US forests. Proc. Natl Acad. Sci. USA 113, 11770–11775 (2016).Article 

Google Scholar 
Abram, N. J. et al. Connections of climate change and variability to large and extreme forest fires in southeast Australia. Commun. Earth Environ. 2, 1–17 (2021).Article 

Google Scholar 
Yu, Y. et al. Machine learning–based observation-constrained projections reveal elevated global socioeconomic risks from wildfire. Nat. Commun. 13, 1250 (2022).Article 

Google Scholar 
Pu, B. & Ginoux, P. How reliable are CMIP5 models in simulating dust optical depth? Atmos. Chem. Phys. 18, 12491–12510 (2018).Article 

Google Scholar 
Pu, B. & Ginoux, P. Climatic factors contributing to long-term variations in surface fine dust concentration in the United States. Atmos. Chem. Phys. 18, 4201–4215 (2018).Article 

Google Scholar 
Bodí, M. B. et al. Wildland fire ash: production, composition and eco-hydro-geomorphic effects. Earth Sci. Rev. 130, 103–127 (2014).Article 

Google Scholar 
NCAR Command Language v.6.6.2 (NCAR, 2019); https://doi.org/10.5065/D6WD3XH5Giglio, L., Schroeder, W. & Justice, C. O. The collection 6 MODIS active fire detection algorithm and fire products. Remote Sens. Environ. 178, 31–41 (2016).Article 

Google Scholar 
Ramo, R. et al. African burned area and fire carbon emissions are strongly impacted by small fires undetected by coarse resolution satellite data. Proc. Natl Acad. Sci. USA 118, 1–7 (2021).Article 

Google Scholar 
Diner, D. J. et al. Multi-angle imaging spectroradiometer (MISR) instrument description and experiment overview. IEEE Trans. Geosci. Remote Sens. 36, 1072–1087 (1998).Article 

Google Scholar 
Pu, B. et al. Retrieving the global distribution of the threshold of wind erosion from satellite data and implementing it into the Geophysical Fluid Dynamics Laboratory land–atmosphere model (GFDL AM4.0/LM4.0). Atmos. Chem. Phys. 20, 55–81 (2020).Article 

Google Scholar 
Sayer, A. M., Hsu, N. C., Bettenhausen, C. & Jeong, M. J. Validation and uncertainty estimates for MODIS collection 6 ‘Deep Blue’ aerosol data. J. Geophys. Res. Atmos. 118, 7864–7872 (2013).Article 

Google Scholar 
Hsu, N. C. et al. Enhanced Deep Blue aerosol retrieval algorithm: the second generation. J. Geophys. Res. Atmos. 118, 9296–9315 (2013).Article 

Google Scholar 
Ginoux, P., Garbuzov, D. & Hsu, N. C. Identification of anthropogenic and natural dust sources using moderate resolution imaging spectroradiometer (MODIS) Deep Blue level 2 data. J. Geophys. Res. 115, D05204 (2010).Article 

Google Scholar 
Eck, T. F. et al. Wavelength dependence of the optical depth of biomass burning, urban, and desert dust aerosols. J. Geophys. Res. Atmos. 104, 31333–31349 (1999).Article 

Google Scholar 
Anderson, T. L. et al. Testing the MODIS satellite retrieval of aerosol fine-mode fraction. J. Geophys. Res. 110, 1–16 (2005).Article 

Google Scholar 
Baddock, M. C., Bullard, J. E. & Bryant, R. G. Dust source identification using MODIS: a comparison of techniques applied to the Lake Eyre Basin, Australia. Remote Sens. Environ. 113, 1511–1528 (2009).Article 

Google Scholar 
Baddock, M. C., Ginoux, P., Bullard, J. E. & Gill, T. E. Do MODIS-defined dust sources have a geomorphological signature? Geophys. Res. Lett. 43, 2606–2613 (2016).Article 

Google Scholar 
Pu, B. & Ginoux, P. Projection of American dustiness in the late 21st century due to climate change. Sci. Rep. 7, 5553 (2017).Article 

Google Scholar 
Pu, B., Ginoux, P., Kapnick, S. B. & Yang, X. Seasonal prediction potential for springtime dustiness in the United States. Geophys. Res. Lett. 46, 9163–9173 (2019).Article 

Google Scholar 
Garay, M. J. et al. Introducing the 4.4 km spatial resolution multi-angle imaging spectroradiometer (MISR) aerosol product. Atmos. Meas. Tech. 13, 593–628 (2020).Article 

Google Scholar 
Kalashnikova, O. V., Kahn, R., Sokolik, I. N. & Li, W.-H. Ability of multiangle remote sensing observations to identify and distinguish mineral dust types: optical models and retrievals of optically thick plumes. J. Geophys. Res. 110, D18S14 (2005).Article 

Google Scholar 
Yu, Y. et al. Assessing temporal and spatial variations in atmospheric dust over Saudi Arabia through satellite, radiometric, and station data. J. Geophys. Res. Atmos. 118, 13253–13264 (2013).Article 

Google Scholar 
Yu, Y., Notaro, M., Kalashnikova, O. V. & Garay, M. J. Climatology of summer Shamal wind in the Middle East. J. Geophys. Res. Atmos. 121, 289–305 (2016).Article 

Google Scholar 
Yu, Y. et al. Disproving the Bodélé depression as the primary source of dust fertilizing the Amazon rainforest. Geophys. Res. Lett. 47, e2020GL088020 (2020).Article 

Google Scholar 
Giles, D. M. et al. Advancements in the Aerosol Robotic Network (AERONET) version 3 database—automated near-real-time quality control algorithm with improved cloud screening for Sun photometer aerosol optical depth (AOD) measurements. Atmos. Meas. Tech. 12, 169–209 (2019).Article 

Google Scholar 
O’Neill, N. T., Eck, T. F., Smirnov, A., Holben, B. N. & Thulasiraman, S. Spectral discrimination of coarse and fine mode optical depth. J. Geophys. Res. Atmos. 108, 1–15 (2003).
Google Scholar 
Winker, D. M. et al. Overview of the CALIPSO mission and CALIOP data processing algorithms. J. Atmos. Ocean. Technol. 26, 2310–2323 (2009).Article 

Google Scholar 
Esselborn, M. et al. Spatial distribution and optical properties of Saharan dust observed by airborne high spectral resolution lidar during SAMUM 2006. Tellus B 61, 131–143 (2009).Article 

Google Scholar 
Kim, M. H. et al. The CALIPSO version 4 automated aerosol classification and lidar ratio selection algorithm. Atmos. Meas. Tech. 11, 6107–6135 (2018).Article 

Google Scholar 
Didan, K., Munoz, A. B., Solano, R. & Huete, A. MODIS Vegetation Index User’s Guide (Collection 6) (Univ. Arizona, 2015).Seddon, A. W. R., Macias-Fauria, M., Long, P. R., Benz, D. & Willis, K. J. Sensitivity of global terrestrial ecosystems to climate variability. Nature 531, 229–232 (2016).Article 

Google Scholar 
Saleska, S. R. et al. Dry-season greening of Amazon forests. Nature 531, E4–E5 (2016).Article 

Google Scholar 
Remer, L. A., Kaufman, Y. J., Holben, B. N., Thompson, A. M. & McNamara, D. Biomass burning aerosol size distribution and modeled optical properties. J. Geophys. Res. Atmos. 103, 31879–31891 (1998).Article 

Google Scholar 
Tegen, I. & Lacis, A. A. Modeling of particle size distribution and its influence on the radiative properties of mineral dust aerosol. J. Geophys. Res. Atmos. 101, 19237–19244 (1996).Article 

Google Scholar 
Friedl, M. A. & Sulla-Menashe, D. User Guide to Collection 6 MODIS Land Cover (MCD12Q1 and MCD12C1) Product 6 (USGS, 2018).Sulla-Menashe, D., Gray, J. M., Abercrombie, S. P. & Friedl, M. A. Hierarchical mapping of annual global land cover 2001 to present: the MODIS collection 6 land cover product. Remote Sens. Environ. 222, 183–194 (2019).Article 

Google Scholar 
Dorigo, W. et al. ESA CCI Soil Moisture for improved Earth system understanding: state-of-the art and future directions. Remote Sens. Environ. 203, 185–215 (2017).Article 

Google Scholar 
Hersbach, H. et al. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146, 1999–2049 (2020).Article 

Google Scholar 
Preimesberger, W., Scanlon, T., Su, C.-H., Gruber, A. & Dorigo, W. Homogenization of structural breaks in the global ESA CCI Soil Moisture multisatellite climate data record. IEEE Trans. Geosci. Remote Sens. 59, 2845–2862 (2021).Article 

Google Scholar 
Minola, L. et al. Near-surface mean and gust wind speeds in ERA5 across Sweden: towards an improved gust parametrization. Clim. Dyn. 55, 887–907 (2020).Article 

Google Scholar 
Molina, M. O., Gutiérrez, C. & Sánchez, E. Comparison of ERA5 surface wind speed climatologies over Europe with observations from the HadISD dataset. Int. J. Climatol. 41, 4864–4878 (2021).Article 

Google Scholar 
Klose, M. et al. Mineral dust cycle in the Multiscale Online Nonhydrostatic Atmosphere Chemistry model (MONARCH) version 2.0. Geosci. Model Dev. 14, 6403–6444 (2021).Article 

Google Scholar 
Mondal, A., Kundu, S. & Mukhopadhyay, A. Rainfall trend analysis by Mann–Kendall test: a case study of north-eastern part of Cuttack District, Orissa. Int. J. Geol. Earth Environ. Sci. 2, 2277–208170 (2012).
Google Scholar 
Yu, Y. & Ginoux, P. Dust emission following large wildfires. figshare. 2022. https://doi.org/10.6084/m9.figshare.20648055.v2 More