More stories

  • in

    Genetic disruption of Arabidopsis secondary metabolite synthesis leads to microbiome-mediated modulation of nematode invasion

    van den Hoogen J, Geisen S, Routh D. Soil nematode abundance and functional group composition at a global scale. Nature 2019;572:194–98.PubMed 

    Google Scholar 
    Yeates GW, Bongers T, Degoede RGM, Freckman DW, Georgieva SS. Feeding habits in soil nematode families and genera – an outline for soil ecologists. J Nematol. 1993;25:315–31.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Nicol JM, Turner SJ, Coyne DL, Nijs Ld, Hockland S, Maafi ZT. Current nematode threats to world agriculture. In: Jones J, Gheysen G, Fenoll C, editors. Genomics and Molecular Genetics of Plant-Nematode Interactions. Dordrecht: Springer; 2011. p. 21–43.Decraemer W, Hunt D. Structure and Classification. In: R. N. Perry, M. Moens, Eds. Plant Nematology. CABI, Wallingford, Oxfordshire, UK and Boston, USA, 2005, pp. 26–27.Fleming TR, Maule AG, Fleming CC. Chemosensory responses of plant parasitic nematodes to selected phytochemicals reveal long-term habituation traits. J Nematol. 2017;49:462–71.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Murungi LK, Kirwa H, Coyne D, Teal PEA, Beck JJ, Torto B. Identification of key root volatiles signaling preference of tomato over spinach by the root knot nematode Meloidogyne incognita. J AgricFood Chem. 2018;66:7328–36.CAS 

    Google Scholar 
    Wang CL, Masler EP, Rogers ST. Responses of Heterodera glycines and Meloidogyne incognita infective juveniles to root tissues, root exudates, and root extracts from three plant species. Plant Dis. 2018;102:1733–40.CAS 
    PubMed 

    Google Scholar 
    Sikder MM, Vestergård M. Impacts of root metabolites on soil nematodes. Front Plant Sci. 2020;10:1792.PubMed 
    PubMed Central 

    Google Scholar 
    van Dam NM, Tytgat TOG, Kirkegaard JA. Root and shoot glucosinolates: A comparison of their diversity, function and interactions in natural and managed ecosystems. Phytochem Rev. 2009;8:171–86.CAS 

    Google Scholar 
    Bressan M, Roncato MA, Bellvert F, et al. Exogenous glucosinolate produced by Arabidopsis thaliana has an impact on microbes in the rhizosphere and plant roots. ISME J. 2009;3:1243–57.CAS 
    PubMed 

    Google Scholar 
    Mucha S, Heinzlmeir S, Kriechbaumer V, Strickland B, Kirchhelle C, Choudhary M, et al. The formation of a camalexin biosynthetic metabolon. Plant Cell. 2019;31:2697–710.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kettles GJ, Drurey C, Schoonbeek HJ, Maule AJ, Hogenhout SA. Resistance of Arabidopsis thaliana to the green peach aphid, Myzus persicae, involves camalexin and is regulated by microRNAs. N. Phytol. 2013;198:1178–90.CAS 

    Google Scholar 
    Tsuji J, Jackson EP, Gage DA, Hammerschmidt R, Somerville SC. Phytoalexin accumulation in Arabidopsis thaliana during the hypersensitive reaction to Pseudomonas syringae pv. syringae. Plant Physiol. 1992;98:1304–9.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Thomma BPHJ, Nelissen I, Eggermont K, Broekaert WF. Deficiency in phytoalexin production causes enhanced susceptibility of Arabidopsis thaliana to the fungus Alternaria brassicicola. Plant J 1999;19:163–71.CAS 
    PubMed 

    Google Scholar 
    Teixeira MA, Wei LH, Kaloshian I. Root-knot nematodes induce pattern-triggered immunity in Arabidopsis thaliana roots. N Phytol. 2016;211:276–87.CAS 

    Google Scholar 
    Shah SJ, Anjam MS, Mendy B, Anwer MA, Habash SS, Lozano-Torres JL, et al. Damage-associated responses of the host contribute to defence against cyst nematodes but not root-knot nematodes. J Exp Bot. 2017;68:5949–60.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ali MA, Wieczorek K, Kreil DP, Bohlmann H. The beet cyst nematode Heterodera schachtii modulates the expression of WRKY transcription factors in syncytia to favour its development in Arabidopsis roots. PLoS One. 2014;9:e102360.PubMed 
    PubMed Central 

    Google Scholar 
    Lazzeri L, Curto G, Leoni O, Dallavalle E. Effects of glucosinolates and their enzymatic hydrolysis products via myrosinase on the root-knot nematode Meloidogyne incognita (Kofoid et White) Chitw. J Agric Food Chem. 2004;52:6703–07.CAS 
    PubMed 

    Google Scholar 
    Avato P, D’Addabbo T, Leonetti P, Argentieri MP. Nematicidal potential of Brassicaceae. Phytochem Rev. 2013;12:791–802.CAS 

    Google Scholar 
    Mathesius U. Flavonoid functions in plants and their interactions with other organisms. Plants (Basel) 2018;7:30.
    Google Scholar 
    Weston LA, Mathesius U. Flavonoids: Their structure, biosynthesis and role in the rhizosphere, including allelopathy. J Chem Ecol. 2013;39:283–97.CAS 
    PubMed 

    Google Scholar 
    Badri DV, Loyola-Vargas VM, Broeckling CD, De-la-Pena C, Jasinski M, Santelia D, et al. Altered profile of secondary metabolites in the root exudates of Arabidopsis ATP-binding cassette transporter mutants. Plant Physiol. 2008;146:762–71.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Cesco S, Neumann G, Tomasi N, Pinton R, Weisskopf L. Release of plant-borne flavonoids into the rhizosphere and their role in plant nutrition. Plant Soil. 2010;329:1–25.CAS 

    Google Scholar 
    Drewnowski A, Gomez-Carneros C. Bitter taste, phytonutrients, and the consumer: A review. Am J Clin Nutr. 2000;72:1424–35.CAS 
    PubMed 

    Google Scholar 
    Chin S, Behm CA, Mathesius U. Functions of flavonoids in plant-nematode interactions. Plants (Basel) 2018;7:1–17.
    Google Scholar 
    Kaplan DT, Keen NT, Thomason IJ. Association of glyceollin with the incompatible response of soybean roots to Meloidogyne incognita. Physiol Plant Pathol. 1980;16:309–18.CAS 

    Google Scholar 
    Aoudia H, Ntalli N, Aissani N, Yahiaoui-Zaidi R, Caboni P. Nematotoxic phenolic compounds from Melia azedarach against Meloidogyne incognita. J AgricFood Chem. 2012;60:11675–80.CAS 

    Google Scholar 
    Kennedy MJ, Niblack TL, Krishnan HB. Infection by Heterodera glycines elevates isoflavonoid production and influences soybean nodulation. J Nematol. 1999;31:341–47.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Collingborn FMB, Gowen SR, Mueller-Harvey I. Investigations into the biochemical basis for nematode resistance in roots of three Musa cultivars in response to Radopholus similis infection. J Agric Food Chem. 2000;48:5297–301.CAS 
    PubMed 

    Google Scholar 
    Cook R, Tiller SA, Mizen KA, Edwards R. Isoflavonoid metabolism in resistant and susceptible cultivars of white clover infected with the stem nematode Ditylenchus dipsaci. J Plant Physiol. 1995;146:348–54.CAS 

    Google Scholar 
    Kirwa HK, Murungi LK, Beck JJ, Torto B. Elicitation of differential responses in the root-knot nematode Meloidogyne incognita to tomato root exudate cytokinin, flavonoids, and alkaloids. J AgricFood Chem. 2018;66:11291–300.CAS 

    Google Scholar 
    Wuyts N, Swennen R, De, Waele D. Effects of plant phenylpropanoid pathway products and selected terpenoids and alkaloids on the behaviour of the plant-parasitic nematodes Radopholus similis. Pratylenchus penetrans Meloidogyne Incogn Nematol. 2006;8:89–101.CAS 

    Google Scholar 
    Hartwig UA, Joseph CM, Phillips DA. Flavonoids released naturally from alfalfa seeds enhance growth rate of Rhizobium meliloti. Plant Physiol. 1991;95:797–803.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Hassan S, Mathesius U. The role of flavonoids in root-rhizosphere signalling: Opportunities and challenges for improving plant-microbe interactions. J Exp Bot. 2012;63:3429–44.CAS 
    PubMed 

    Google Scholar 
    Kudjordjie EN, Sapkota R, Nicolaisen M. Arabidopsis assemble distinct root-associated microbiomes through the synthesis of an array of defense metabolites. PLoS One. 2021;10:e0259171.
    Google Scholar 
    Rønn R, Vestergård M, Ekelund F. Interactions between bacteria, protozoa and nematodes in soil. Acta Protozool. 2012;51:223–35.
    Google Scholar 
    Thakur MP, Geisen S. Trophic regulations of the soil microbiome. Trends Microbiol. 2019;27:771–80.CAS 
    PubMed 

    Google Scholar 
    Elhady A, Gine A, Topalovic O, Jacquiod S, Sorensen SJ, Sorribas FJ, et al. Microbiomes associated with infective stages of root-knot and lesion nematodes in soil. PLoS One. 2017;12:e0177145.PubMed 
    PubMed Central 

    Google Scholar 
    Toju H, Tanaka Y. Consortia of anti-nematode fungi and bacteria in the rhizosphere of soybean plants attacked by root-knot nematodes. R Soc Open Sci. 2019;6:181693.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Topalović O, Bredenbruch S, Schleker ASS, Heuer H. Microbes attaching to endoparasitic phytonematodes in soil trigger plant defense upon root penetration by the nematode. Front Plant Sci 2020;11:138.PubMed 
    PubMed Central 

    Google Scholar 
    Schaad NW, Walker JT. The use of density-gradient centrifugation for the purification of eggs of Meloidogyne spp. J Nematol. 1975;7:203–04.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Hooper DJ, Hallmann J, Subbotin SA. Methods for extraction, processing and detection of plant and soil nematodes. In: Luc M, Sikora RA, Bridge J, editors. Plant parasitic nematodes in subtropical and tropical agriculture. Second ed. Wallingford, UK: CABI Publishing; 2005. p. 53.Topalovic O, Elhady A, Hallmann J, Richert-Poggeler KR, Heuer H. Bacteria isolated from the cuticle of plant-parasitic nematodes attached to and antagonized the root-knot nematode Meloidogyne hapla. Sci Rep. 2019;9:11477.PubMed 
    PubMed Central 

    Google Scholar 
    R Core Team. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2019.Porazinska DL, Giblin-Davis RM, Faller L, Farmerie W, Kanzaki N, Morris K, et al. Evaluating high-throughput sequencing as a method for metagenomic analysis of nematode diversity. Mol Ecol Resour. 2009;9:1439–50.CAS 
    PubMed 

    Google Scholar 
    Sapkota R, Nicolaisen M. High-throughput sequencing of nematode communities from total soil DNA extractions. BMC Ecol. 2015;15:3.PubMed 
    PubMed Central 

    Google Scholar 
    Sikder MM, Vestergård M, Sapkota R, Kyndt T, Nicolaisen M. Evaluation of metabarcoding primers for analysis of soil nematode communities. Diversity (Basel) 2020;12:388.CAS 

    Google Scholar 
    Ihrmark K, Bodeker ITM, Cruz-Martinez K, Friberg H, Kubartova A, Schenck J, et al. New primers to amplify the fungal ITS2 region – evaluation by 454-sequencing of artificial and natural communities. FEMS Microbiol Ecol. 2012;82:666–77.CAS 
    PubMed 

    Google Scholar 
    Klindworth A, Pruesse E, Schweer T, Peplies J, Quast C, Horn M, et al. Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Res. 2013;41:e1.CAS 
    PubMed 

    Google Scholar 
    Sapkota R, Skantar AM, Nicolaisen M. A TaqMan real-time PCR assay for detection of Meloidogyne hapla in root galls and in soil. Nematol. 2016;18:147–54.CAS 

    Google Scholar 
    Rognes T, Flouri T, Nichols B, Quince C, Mahe F. VSEARCH: A versatile open source tool for metagenomics. Peer J. 2016;4:e2584.PubMed 
    PubMed Central 

    Google Scholar 
    Bengtsson-Palme J, Ryberg M, Hartmann M, Branco S, Wang Z, Godhe A, et al. Improved software detection and extraction of ITS1 and ITS2 from ribosomal ITS sequences of fungi and other eukaryotes for analysis of environmental sequencing data. Methods Ecol Evol. 2013;4:914–19.
    Google Scholar 
    Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 2013;41:D590–D6.CAS 
    PubMed 

    Google Scholar 
    Yilmaz P, Parfrey LW, Yarza P, Gerken J, Pruesse E, Quast C, et al. The SILVA and “All-species Living Tree Project (LTP)” taxonomic frameworks. Nucleic Acids Res. 2014;42:D643–D8.CAS 
    PubMed 

    Google Scholar 
    UNITE. UNITE QIIME release for Fungi [Internet]. UNITE Community. 2020.Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods. 2010;7:335–36.CAS 
    PubMed 
    PubMed Central 

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

    Google Scholar 
    Oksanen J, Blanchet FG, Kindt R, Friendly M, Legendre P, McGlinn D, et al. Vegan: Community Ecology Package. Ordination methods, diversity analysis and other functions for community and vegetation ecologists. R Package Version 2.5-5 ed: The Comprehensive R Archive Network; 2019.Love MI, Huber W, Anders S. Moderated estimation of fold change anddispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550.PubMed 
    PubMed Central 

    Google Scholar 
    Parks DH, Tyson GW, Hugenholtz P, Beiko RG. STAMP: Statistical analysis of taxonomic and functional profiles. Bioinformatics 2014;30:3123–24.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kudjordjie EN, Sapkota R, Steffensen SK, Fomsgaard IS, Nicolaisen M. Maize synthesized benzoxazinoids affect the host associated microbiome. Microbiome 2019;7:59.PubMed 
    PubMed Central 

    Google Scholar 
    McCarthy DJ, Chen YS, Smyth GK. Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation. Nucleic Acids Res. 2012;40:4288–97.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Robinson MD, McCarthy DJ, Smyth GK. edgeR: A Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 2010;26:139–40.CAS 
    PubMed 

    Google Scholar 
    Frerigmann H, Gigolashvili T. MYB34, MYB51, and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsis thaliana. Mol Plant. 2014;7:814–28.CAS 
    PubMed 

    Google Scholar 
    Schulz E, Tohge T, Zuther E, Fernie AR, Hincha DK. Flavonoids are determinants of freezing tolerance and cold acclimation in Arabidopsis thaliana. Sci Rep. 2016;6:34027.Borevitz JO, Xia Y, Blount J, Dixon RA, Lamb C. Activation tagging identifies a conserved MYB regulator of phenylpropanoid biosynthesis. Plant Cell. 2000;12:2383–94.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Du SS, Zhang HM, Bai CQ, Wang CF, Liu QZ, Liu ZL, et al. Nematocidal flavone-C-glycosides against the root-knot nematode (Meloidogyne incognita) from Arisaema erubescens tubers. Molecules 2011;16:5079–86.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Zhou DM, Feng H, Schuelke T, De Santiago A, Zhang QM, Zhang JF, et al. Rhizosphere microbiomes from root knot nematode non-infested plants suppress nematode Infection. Micro Ecol. 2019;78:470–81.CAS 

    Google Scholar 
    Topalović O, Vestergård M. Can microorganisms assist the survival and parasitism of plant-parasitic nematodes? Trends Parasitol. 2021;37:947–58.PubMed 

    Google Scholar 
    De Mesel I, Derycke S, Moens T, Van der Gucht K, Vincx M, Swings J. Top-down impact of bacterivorous nematodes on the bacterial community structure: a microcosm study. Environ Microbiol. 2004;6:733–44.PubMed 

    Google Scholar 
    Adam M, Westphal A, Hallmann J, Heuer H. Specific microbial attachment to root knot nematodes in suppressive soil. Appl Environ Microbiol. 2014;80:2679–86.PubMed 
    PubMed Central 

    Google Scholar 
    Ramyabharathi S, Sankari Meena K, Rajendran L, Karthikeyan G, Jonathan EI, Raguchander T. Biocontrol of wilt-nematode complex infecting gerbera by Bacillus subtilis under protected cultivation. Egypt J Biol Pest Co. 2018;28:21.
    Google Scholar 
    Jamal Q, Cho JY, Moon JH, Munir S, Anees M, Kim KY. Identification for the first time of cyclo (D-Pro-L-Leu) produced by Bacillus amyloliquefaciens y1 as a nematocide for control of Meloidogyne incognita. Molecules 2017;22:1839.PubMed Central 

    Google Scholar 
    Moosavi MR, Zare R. Fungi as biological control agents of plant-parasitic nematodes. In: Mérillon J-M, Ramawat KG, editors. Plant Defence: Biological Control. Progress in Biological Control 22. 2nd Edition ed. Switzerland: Springer; 2020. p. 333–84.Ashrafi S, Stadler M, Dababat AA, Richert-Poggeler KR, Finckh MR, Maier W. Monocillium gamsii sp nov and Monocillium bulbillosum: two nematode-associated fungi parasitising the eggs of Heterodera filipjevi. Mycokeys. 2017;27:21–38.
    Google Scholar 
    Nuaima RH, Ashrafi S, Maier W, Heuer H. Fungi isolated from cysts of the beet cyst nematode parasitized its eggs and counterbalanced root damages. J Pest Sci. 2021;94:563–72.
    Google Scholar 
    Iqbal M, Dubey M, McEwan K, Menzel U, Franko MA, Viketoft M, et al. Evaluation of Clonostachys rosea for control of plant parasitic nematodes in soil and in roots of carrot and wheat. Phytopathology 2018;108:52–59.CAS 
    PubMed 

    Google Scholar 
    DiLegge MJ, Manter DK, Vivanco JM. A novel approach to determine generalist nematophagous microbes reveals Mortierella globalpina as a new biocontrol agent against Meloidogyne spp. nematodes. Sci Rep. 2019;9:7521.PubMed 
    PubMed Central 

    Google Scholar 
    Goswami J, Pandey RK, Tewari JP, Goswami BK. Management of root knot nematode on tomato through application of fungal antagonists, Acremonium strictum and Trichoderma harzianum. J Environ Sci Health. 2008;43:237–40.CAS 

    Google Scholar 
    Chen Q, Peng D. Nematode chitin and application. In: Yang Q, Fukamizo T, editors. Targeting Chitin-containing Organisms. Advances in Experimental Medicine and Biology. 1142. Singapore: Springer; 2019. pp. 209–219.Zhou WQ, Verma VC, Wheeler TA, Woodward JE, Starr JL, Sword GA. Tapping into the cotton fungal phytobiome for novel nematode biological control tools. Phytobiomes J 2020;4:19–26.
    Google Scholar 
    Alcazar R, von Reth M, Bautor J, Chae E, Weigel D, Koornneef M, et al. Analysis of a plant complex resistance gene locus underlying immune-related hybrid incompatibility and its occurrence in nature. PLoS Genet. 2014;10:e1004848.PubMed 
    PubMed Central 

    Google Scholar 
    Mikkelsen MD, Hansen CH, Wittstock U, Halkier BA. Cytochrome P450CYP79B2 from Arabidopsis catalyzes the conversion of tryptophan to indole-3-acetaldoxime, a precursor of indole glucosinolates and indole-3-acetic acid. J Biol Chem. 2000;275:33712–17.CAS 
    PubMed 

    Google Scholar 
    Hull AK, Vij R, Celenza JL. Arabidopsis cytochrome P450s that catalyze the first step of tryptophan-dependent indole-3-acetic acid biosynthesis. Proc Natl Acad Sci USA. 2000;97:2379–84.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Zhao YD, Hull AK, Gupta NR, Goss KA, Alonso J, Ecker JR, et al. Trp-dependent auxin biosynthesis in Arabidopsis: involvement of cytochrome P450s CYP79B2 and CYP79B3. GenesDev. 2002;16:3100–12.CAS 

    Google Scholar 
    Schlaeppi K, Bodenhausen N, Buchala A, Mauch F, Reymond P. The glutathione-deficient mutant pad2-1 accumulates lower amounts of glucosinolates and is more susceptible to the insect herbivore Spodoptera littoralis. Plant J. 2008;55:774–86.CAS 
    PubMed 

    Google Scholar 
    Schuhegger R, Nafisi M, Mansourova M, Petersen BL, et al. CYP71B15 (PAD3) catalyzes the final step in camalexin biosynthesis. Plant Physiol. 2006;141:1248–54.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Glawischnig E. The role of cytochrome P450 enzymes in the biosynthesis of camalexin. Biochem Soc Trans. 2006;34:1206–8.CAS 
    PubMed 

    Google Scholar 
    Haughn GW, Davin L, Giblin M, Underhill EW. Biochemical genetics of plant secondary metabolites in Arabidopsis thaliana: The glucosinolates. Plant Physiol. 1991;97:217–26.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kroymann J, Textor S, Tokuhisa JG, Falk KL, Bartram S, Gershenzon J, et al. A gene controlling variation in Arabidopsis glucosinolate composition is part of the methionine chain elongation pathway. Plant Physiol. 2001;127:1077–88.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Textor S, de Kraker JW, Hause B, Gershenzon J, Tokuhisa JG. MAM3 catalyzes the formation of all aliphatic glucosinolate chain lengths in Arabidopsis. Plant Physiol. 2007;144:60–71.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Barth C, Jander G. Arabidopsis myrosinases TGG1 and TGG2 have redundant function in glucosinolate breakdown and insect defense. Plant J. 2006;46:549–62.CAS 
    PubMed 

    Google Scholar 
    Dong XY, Braun EL, Grotewold E. Functional conservation of plant secondary metabolic enzymes revealed by complementation of Arabidopsis flavonoid mutants with maize genes. Plant Physiol. 2001;127:46–57.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Peer WA, Brown DE, Tague BW, Muday GK, Taiz L, Murphy AS. Flavonoid accumulation patterns of transparent testa mutants of Arabidopsis. Plant Physiol. 2001;126:536–48.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Gonzalez A, Brown M, Hatlestad G, Akhavan N, Smith T, Hembd A, et al. TTG2 controls the developmental regulation of seed coat tannins in Arabidopsis by regulating vacuolar transport steps in the proanthocyanidin pathway. Dev Biol. 2016;419:54–63.CAS 
    PubMed 

    Google Scholar 
    Walker AR, Davison PA, Bolognesi-Winfield AC, James CM, Srinivasan N, Blundell TL, et al. The TRANSPARENT TESTA GLABRA1 locus, which regulates trichome differentiation and anthocyanin biosynthesis in Arabidopsis, encodes a WD40 repeat protein. Plant Cell. 1999;11:1337–49.CAS 
    PubMed 
    PubMed Central 

    Google Scholar  More

  • in

    Biodiversity mediates ecosystem sensitivity to climate variability

    Scheffers, B. R. et al. The broad footprint of climate change from genes to biomes to people. Science 354, aaf7671 (2016).PubMed 

    Google Scholar 
    IPBES. Global Assessment Report on Biodiversity and Ecosystem Service. Debating Nature’s Value (IPBES, 2019).Harrison, S. Plant community diversity will decline more than increase under climatic warming. Philos. Trans. R. Soc. B Biol. Sci. 375, 20190106 (2020).
    Google Scholar 
    Díaz, S. et al. Pervasive human-driven decline of life on Earth points to the need for transformative change. Science (80-.). 1327, eaax3100 (2019).Chapin, F. S. et al. Consequences of changing biodiversity. Nature 405, 234–242 (2000).CAS 
    PubMed 

    Google Scholar 
    Isbell, F. et al. Linking the influence and dependence of people on biodiversity across scales. Nature 546, 65–72 (2017).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Craven, D. et al. Multiple facets of biodiversity drive the diversity–stability relationship. Nat. Ecol. Evol. 2, 1579–1587 (2018).PubMed 

    Google Scholar 
    Hautier, Y. et al. Anthropogenic environmental changes affect ecosystem stability via biodiversity. Science (80-.). 348, 336–340 (2015).CAS 

    Google Scholar 
    Díaz, S., Fargione, J., Chapin, F. S. & Tilman, D. Biodiversity loss threatens human well-being. PLoS Biol. 4, e277 (2006).PubMed 
    PubMed Central 

    Google Scholar 
    Pennekamp, F. et al. Biodiversity increases and decreases ecosystem stability. Nature 563, 109–112 (2018).CAS 
    PubMed 

    Google Scholar 
    Valencia, E. et al. Synchrony matters more than species richness in plant community stability at a global scale. Proc. Natl Acad. Sci. USA 117, 24345–24351 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Wang, Y. et al. Global evidence of positive biodiversity effects on spatial ecosystem stability in natural grasslands. Nat. Commun. 10, 1–9 (2019).
    Google Scholar 
    Poorter, L. et al. Diversity enhances carbon storage in tropical forests. Glob. Ecol. Biogeogr. 24, 1314–1328 (2015).
    Google Scholar 
    Schnabel, F. et al. Drivers of productivity and its temporal stability in a tropical tree diversity experiment. Glob. Chang. Biol. 25, 4257–4272 (2019).PubMed 

    Google Scholar 
    Reichstein, M., Bahn, M., Mahecha, M. D., Kattge, J. & Baldocchi, D. D. Linking plant and ecosystem functional biogeography. Proc. Natl Acad. Sci. USA 111, 13697–13702 (2014).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Mori, A. S. Advancing nature-based approaches to address the biodiversity and climate emergency. Ecol. Lett. 23, 1729–1732 (2020).PubMed 

    Google Scholar 
    Mazzochini, G. G. et al. Plant phylogenetic diversity stabilizes large-scale ecosystem productivity. Glob. Ecol. Biogeogr. 28, 1430–1439 (2019).
    Google Scholar 
    Manhães, A. P., Mazzochini, G. G., Oliveira-Filho, A. T., Ganade, G. & Carvalho, A. R. Spatial associations of ecosystem services and biodiversity as a baseline for systematic conservation planning. Divers. Distrib. 22, 932–943 (2016).
    Google Scholar 
    García-Palacios, P., Gross, N., Gaitán, J. & Maestre, F. T. Climate mediates the biodiversity–ecosystem stability relationship globally. Proc. Natl Acad. Sci. USA 115, 8400–8405 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    De Keersmaecker, W. et al. A model quantifying global vegetation resistance and resilience to short-term climate anomalies and their relationship with vegetation cover. Glob. Ecol. Biogeogr. 24, 539–548 (2015).
    Google Scholar 
    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).CAS 
    PubMed 

    Google Scholar 
    Linscheid, N. et al. Towards a global understanding of vegetation-climate dynamics at multiple timescales. Biogeosciences 17, 945–962 (2020).
    Google Scholar 
    Nemani, R. R. et al. Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science (80-.). 300, 1560–1563 (2003).CAS 

    Google Scholar 
    Quetin, G. R. & Swann, A. L. S. Empirically derived sensitivity of vegetation to climate across global gradients of temperature and precipitation. J. Clim. 30, 5835–5849 (2017).
    Google Scholar 
    Cavender-bares, J. et al. The role of diversification in community assembly of the oaks (Quercus L.) across the continental U. S. Am. J. Bot. 105, 565–586 (2018).PubMed 

    Google Scholar 
    Woodward, F. I., Lomas, M. R. & Kelly, C. K. Global climate and the distribution of plant biomes. Philos. Trans. R. Soc. Lond. Ser. B Biol. Sci. 359, 1465–1476 (2004).CAS 

    Google Scholar 
    Maurer, G. E., Hallmark, A. J., Brown, R. F., Sala, O. E. & Collins, S. L. Sensitivity of primary production to precipitation across the United States. Ecol. Lett. 23, 527–536 (2020).PubMed 

    Google Scholar 
    Cavender-Bares, J., Ackerly, D. D., Hobbie, S. E. & Townsend, P. A. Evolutionary legacy effects on ecosystems: biogeographic origins, plant traits, and implications for management in the era of global change. Annu. Rev. Ecol. Evol. Syst. 47, 433–462 (2016).
    Google Scholar 
    Harrison, S., Spasojevic, M. J. & Li, D. Climate and plant community diversity in space and time. Proc. Natl Acad. Sci. USA 117, 4464–4470 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Šímová, I. et al. Spatial patterns and climate relationships of major plant traits in the New World differ between woody and herbaceous species. J. Biogeogr. 45, 895–916 (2018).
    Google Scholar 
    Lamanna, C. et al. Functional trait space and the latitudinal diversity gradient. Proc. Natl Acad. Sci. USA 111, 13745–13750 (2014).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Craven, D. et al. A cross-scale assessment of productivity–diversity relationships. Glob. Ecol. Biogeogr. 29, 1940–1955 (2020).
    Google Scholar 
    White, H. J. et al. Ecosystem stability at the landscape scale is primarily associated with climatic history. Funct. Ecol. 1–13 https://doi.org/10.1111/1365-2435.13957 (2021).Enquist, B. J. et al. Scaling from Traits to Ecosystems: Developing a General Trait Driver Theory via Integrating Trait-Based and Metabolic Scaling Theories. Advances in Ecological Research. Vol. 52 (Elsevier Ltd., 2015).Gonzalez, A. et al. Scaling-up biodiversity-ecosystem functioning research. Ecol. Lett. 23, 757–776 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    Barry, K. E. et al. A graphical null model for scaling biodiversity–ecosystem functioning relationships. J. Ecol. 109, 1549–1560 (2021).
    Google Scholar 
    Mori, A. S., Furukawa, T. & Sasaki, T. Response diversity determines the resilience of ecosystems to environmental change. Biol. Rev. 88, 349–364 (2013).PubMed 

    Google Scholar 
    Tilman, D., Reich, P. B. & Knops, J. M. H. Biodiversity and ecosystem stability in a decade-long grassland experiment. Nature 441, 629–632 (2006).CAS 
    PubMed 

    Google Scholar 
    Isbell, F. et al. Quantifying effects of biodiversity on ecosystem functioning across times and places. Ecol. Lett. 21, 763–778 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Bond, E. M. & Chase, J. M. Biodiversity and ecosystem functioning at local and regional spatial scales. Ecol. Lett. 5, 467–470 (2002).
    Google Scholar 
    Delsol, R., Loreau, M. & Haegeman, B. The relationship between the spatial scaling of biodiversity and ecosystem stability. Glob. Ecol. Biogeogr. 27, 439–449 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Price, G. R. The nature of selection. J. Theor. Biol. 175, 389-396 (1995).Fonseca, C. R. & Ganade, G. Species functional redundancy, random extinctions and the stability of ecosystems. J. Ecol. 89, 118–125 (2001).
    Google Scholar 
    Le Bagousse-Pinguet, Y. et al. Phylogenetic, functional, and taxonomic richness have both positive and negative effects on ecosystem multifunctionality. Proc. Natl Acad. Sci. USA 116, 8419–8424 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Cadotte, M., Dinnage, R. & Tilman, D. Phylogenetic diversity promotes ecosytem stability. Ecology 93, S223–S233 (2012).
    Google Scholar 
    Veron, S., Davies, T. J., Cadotte, M. W., Clergeau, P. & Pavoine, S. Predicting loss of evolutionary history: Where are we? Biol. Rev. 92, 271–291 (2017).PubMed 

    Google Scholar 
    Tucker, C. M., Davies, T. J., Cadotte, M. W. & Pearse, W. D. On the relationship between phylogenetic diversity and trait diversity. Ecology 99, 1473–1479 (2018).PubMed 

    Google Scholar 
    Faith, D. P. Systematics and conservation: on predicting the feature diversity of subsets of taxa. Cladistics 8, 361–373 (1992).PubMed 

    Google Scholar 
    Hisano, M., Searle, E. B. & Chen, H. Y. H. Biodiversity as a solution to mitigate climate change impacts on the functioning of forest ecosystems. Biol. Rev. 93, 439–456 (2018).PubMed 

    Google Scholar 
    Flynn, D. F. B., Mirotchnick, N., Jain, M., Palmer, M. I. & Naeem, S. Functional and phylogenetic diversity as predictors of biodiversity–ecosystem-function relationships. Ecology 92, 1573–1581 (2011).PubMed 

    Google Scholar 
    Cadotte, M. W., Cardinale, B. J. & Oakley, T. H. Evolutionary history and the effect of biodiversity on plant productivity. Proc. Natl Acad. Sci. USA 105, 17012–17017 (2008).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Venail, P. et al. Species richness, but not phylogenetic diversity, influences community biomass production and temporal stability in a re-examination of 16 grassland biodiversity studies. Funct. Ecol. 29, 615–626 (2015).
    Google Scholar 
    Enquist, B., Condit, R., Peet, R., Schildhauer, M. & Thiers, B. Cyberinfrastructure for an integrated botanical information network to investigate the ecological impacts of global climate change on plant biodiversity. PeerJ Prepr. 4, e2615v2 (2016).Maitner, B. S. et al. The bien R package: a tool to access the Botanical Information and Ecology Network (BIEN) database. Methods Ecol. Evol. 9, 373–379 (2018).
    Google Scholar 
    Mori, A. S. Resilience in the studies of biodiversity–ecosystem functioning. Trends Ecol. Evol. 31, 87–89 (2016).PubMed 

    Google Scholar 
    Holling, C. S. Resilience and stability of ecological systems. Annu. Rev. Ecol. Syst. 4, 1–23 (1973).
    Google Scholar 
    Oliver, T. H. et al. Biodiversity and resilience of ecosystem functions. Trends Ecol. Evol. 30, 673–684 (2015).PubMed 

    Google Scholar 
    Huete, A., Chris, J. & Leeuwen, W. Van. MODIS vegetation index (MOD 13). Algorithm theoretical basis document vol. 3 https://modis.gsfc.nasa.gov/data/atbd/atbd_mod13.pdf (1999).Abatzoglou, J. T., Dobrowski, S. Z., Parks, S. A. & Hegewisch, K. C. TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015. Sci. Data 5, 170191 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    MacIas-Fauria, M., Forbes, B. C., Zetterberg, P. & Kumpula, T. Eurasian Arctic greening reveals teleconnections and the potential for structurally novel ecosystems. Nat. Clim. Chang. 2, 613–618 (2012).
    Google Scholar 
    Garcia, R. A., Cabeza, M., Rahbek, C. & Araújo, M. B. Multiple dimensions of climate change and their implications for biodiversity. Science (80-.). 344, 1247579 (2014).Zhang, Y. et al. Precipitation and carbon-water coupling jointly control the interannual variability of global land gross primary production. Sci. Rep. 6, 39748 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Poulter, B. et al. Contribution of semi-arid ecosystems to interannual variability of the global carbon cycle. Nature 509, 600–603 (2014).CAS 
    PubMed 

    Google Scholar 
    Olson, D. M. et al. Terrestrial ecoregions of the world: a new map of life on earth. Bioscience 51, 933 (2001).
    Google Scholar 
    Srivastava, D. S. et al. Phylogenetic diversity and the functioning of ecosystems. Ecol. Lett. 15, 637–648 (2012).PubMed 

    Google Scholar 
    Parker, I. M. et al. Phylogenetic structure and host abundance drive disease pressure in communities. Nature 520, 542–544 (2015).CAS 
    PubMed 

    Google Scholar 
    Díaz, S. et al. The global spectrum of plant form and function. Nature 529, 167–171 (2015).PubMed 

    Google Scholar 
    Brun, P. et al. Plant community impact on productivity: Trait diversity or key(stone) species effects? Ecol. Lett. 25, 913–925 (2022).PubMed 

    Google Scholar 
    Aubin, I. et al. Traits to stay, traits to move: a review of functional traits to assess sensitivity and adaptive capacity of temperate and boreal trees to climate change. Environ. Rev. 24, 164–186 (2016).
    Google Scholar 
    Reichstein, M., Bahn, M., Mahecha, M. D., Kattge, J. & Baldocchi, D. D. Linking plant and ecosystem functional biogeography. Proc. Natl. Acad. Sci. USA https://doi.org/10.1073/pnas.1216065111 (2014).Díaz, S. & Cabido, M. Vive la différence: plant functional diversity matters to ecosystem processes. Trends Ecol. Evol. 16, 646–655 (2001).
    Google Scholar 
    Poorter, L. et al. Biomass resilience of Neotropical secondary forests. Nature 530, 211–214 (2016).CAS 
    PubMed 

    Google Scholar 
    Ye, J. S., Pei, J. Y. & Fang, C. Under which climate and soil conditions the plant productivity–precipitation relationship is linear or nonlinear? Sci. Total Environ. 616–617, 1174–1180 (2018).PubMed 

    Google Scholar 
    Allan, E. et al. More diverse plant communities have higher functioning over time due to turnover in complementary dominant species. Proc. Natl Acad. Sci. U. S. A. 108, 17034–17039 (2011).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Hurlbert, A. H. & Jetz, W. Species richness, hotspots, and the scale dependence of range maps in ecology and conservation. Proc. Natl Acad. Sci. 104, 13384–13389 (2007).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Mori, A. S. et al. Biodiversity–productivity relationships are key to nature-based climate solutions. Nat. Clim. Chang. 11, 543–550 (2021).
    Google Scholar 
    Kattge, J. et al. TRY plant trait database–enhanced coverage and open access. Glob. Chang. Biol. 26, 119–188 (2020).PubMed 

    Google Scholar 
    Feeley, K. J., Bravo-Avila, C., Fadrique, B., Perez, T. M. & Zuleta, D. Climate-driven changes in the composition of New World plant communities. Nat. Clim. Chang. 10, 965–970 (2020).CAS 

    Google Scholar 
    Li, D., Miller, J. E. D. & Harrison, S. Climate drives loss of phylogenetic diversity in a grassland community. Proc. Natl Acad. Sci. USA 116, 19989–19994 (2019).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Madani, N. et al. Future global productivity will be affected by plant trait response to climate. Sci. Rep. 8, 2870 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    R Core Team. R: A Language and Environment for Statistical Computing Version 3.5.2. (R Core Team, 2018).Ammer, C. Diversity and forest productivity in a changing climate. N. Phytol. 221, 50–66 (2019).
    Google Scholar 
    Hooper, D. U. et al. A global synthesis reveals biodiversity loss as a major driver of ecosystem change. Nature 486, 105–108 (2012).CAS 
    PubMed 

    Google Scholar 
    Larue, E. A., Hardiman, B. S., Elliott, J. M. & Fei, S. Structural diversity as a predictor of ecosystem function. Environ. Res. Lett. 14, 114011 (2019).Phillips, S. J. & Dudìk, M. Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography (Cop.). 31, 161–175 (2008).
    Google Scholar 
    Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978 (2005).
    Google Scholar 
    Diniz-Filho, J. A. F. & Bini, L. M. Modelling geographical patterns in species richness using eigenvector-based spatial filters. Glob. Ecol. Biogeogr. 14, 177–185 (2005).
    Google Scholar 
    Merow, C., Smith, M. J. & Silander, J. a. A practical guide to MaxEnt for modeling species’ distributions: what it does, and why inputs and settings matter. Ecography (Cop.). 36, 1058–1069 (2013).
    Google Scholar 
    Merow, C. BIEN range methods description. http://bien.nceas.ucsb.edu/bien/wp-content/uploads/2017/06/BIEN3RangeMethodsSummary.pdf (2017).Schrodt, F. et al. BHPMF-a hierarchical Bayesian approach to gap-filling and trait prediction for macroecology and functional biogeography. Glob. Ecol. Biogeogr. 24, 1510–1521 (2015).
    Google Scholar 
    Bruelheide, H. et al. Global trait–environment relationships of plant communities. Nat. Ecol. Evol. 2, 1906–1917 (2018).PubMed 

    Google Scholar 
    Guo, W. Y. et al. Half of the world’s tree biodiversity is unprotected and is increasingly threatened by human activities. Preprint at bioRxiv https://doi.org/10.1101/2020.04.21.052464 (2020).Guo, W., Serra-diaz, J. M., Schrodt, F. & Eiserhardt, W. L. Paleoclimate and current climate collectively shape the phylogenetic and functional diversity of trees worldwide. Preprint at bioRxiv https://doi.org/10.1101/2020.06.02.128975 (2020).Diniz-Filho, J. A. F. et al. On the selection of phylogenetic eigenvectors for ecological analyses. Ecography (Cop.). 35, 239–249 (2012).
    Google Scholar 
    Penone, C. et al. Imputation of missing data in life-history trait datasets: which approach performs the best? Methods Ecol. Evol. 5, 961–970 (2014).
    Google Scholar 
    Santos, T. PVR: Phylogenetic eigenvectors regression and phylogentic signal-representation curve. R package version 0.3. Available at: http://CRAN.R-project.org/package=PVR (2018).Brum, F. T. et al. Global priorities for conservation across multiple dimensions of mammalian diversity. Proc. Natl Acad. Sci. USA 114, 7641–7646 (2017).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Gerhold, P., Cahill, J. F., Winter, M., Bartish, I. V. & Prinzing, A. Phylogenetic patterns are not proxies of community assembly mechanisms (they are far better). Funct. Ecol. 29, 600–614 (2015).
    Google Scholar 
    Kendall, M. & Stuart, A. The Advanced Theory of Statistics (Macmillan, 1983).Pavoine, S. & Bonsall, M. B. Measuring biodiversity to explain community assembly: a unified approach. Biol. Rev. Camb. Philos. Soc. 86, 792–812 (2011).CAS 
    PubMed 

    Google Scholar 
    Tucker, C. M. et al. A guide to phylogenetic metrics for conservation, community ecology and macroecology. Biol. Rev. 92, 698–715 (2017).PubMed 

    Google Scholar 
    Schliep, K. P. phangorn: phylogenetic analysis in R. Bioinformatics 27, 592–593 (2011).CAS 
    PubMed 

    Google Scholar 
    Cornwell, W. K., Schwilk, L. D. W. & Ackerly, D. D. A trait-based test for habitat filtering: convex hull volume. Ecology 87, 1465–1471 (2006).PubMed 

    Google Scholar 
    Villéger, S., Maire, E. & Leprieur, F. On the risks of using dendrograms to measure functional diversity and multidimensional spaces to measure phylogenetic diversity: a comment on Sobral et al. (2016). Ecol. Lett. 20, 554–557 (2017).PubMed 

    Google Scholar 
    Laliberté, E., Legendre, P. & Shipley, B. FD: measuring functional diversity from multiple traits, an other tools for functional ecology. R package version 1.0-12 (Comprehensive R Archive Network, Vienna, Austria, 2015).Podani, J. & Schmera, D. On dendrogram-based measures of functional diversity. Oikos 115, 179–185 (2006).
    Google Scholar 
    Poos, M. S., Walker, S. C. & Jackson, D. A. Functional-diversity indices can be driven by methodological choices and species richness. Ecology 90, 341–347 (2009).PubMed 

    Google Scholar 
    Gotelli, N. J. & Graves, G. R. Null Models in Ecology (Smithsonian Institution Press, 1996).Swenson, N. G. Functional and Phylogenetic Ecology in R. (Springer, 2014).Dormann, C. F. et al. Methods to account for spatial autocorrelation in the analysis of species distributional data: a review. Ecography (Cop.). 30, 609–628 (2007).
    Google Scholar 
    Kissling, W. D. & Carl, G. Spatial autocorrelation and the selection of simultaneous autoregressive models. Glob. Ecol. Biogeogr. 17, 59–71 (2008).
    Google Scholar 
    Bivand, R. spatialreg: Spatial Regression Analysis (R package version 1.1-5, 2019). More

  • in

    Meta-analysis shows that plant mixtures increase soil phosphorus availability and plant productivity in diverse ecosystems

    Vitousek, P. M., Porder, S., Houlton, B. Z. & Chadwick, O. A. Terrestrial phosphorus limitation: mechanisms, implications, and nitrogen–phosphorus interactions. Ecol. Appl. 20, 5–15 (2010).PubMed 
    Article 

    Google Scholar 
    Hou, E. Q. et al. Global meta-analysis shows pervasive phosphorus limitation of aboveground plant production in natural terrestrial ecosystems. Nat. Commun. 11, 637 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Cordell, D., Drangert, J.-O. & White, S. The story of phosphorus: global food security and food for thought. Glob. Environ. Change 19, 292–305 (2009).Article 

    Google Scholar 
    Newbold, T. et al. Global effects of land use on local terrestrial biodiversity. Nature 520, 45–50 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    Chen, X. L., Chen, H. Y. H., Searle, E. B., Chen, C. & Reich, P. B. Negative to positive shifts in diversity effects on soil nitrogen over time. Nat. Sustain. 4, 225–234 (2021).Article 

    Google Scholar 
    Oelmann, Y. et al. Plant diversity effects on aboveground and belowground N pools in temperate grassland ecosystems: development in the first 5 years after establishment. Glob. Biogeochem. Cy. 25, GB2014 (2011).Article 
    CAS 

    Google Scholar 
    Fornara, D. A. et al. Plant effects on soil N mineralization are mediated by the composition of multiple soil organic fractions. Ecol. Res. 26, 201–208 (2011).CAS 
    Article 

    Google Scholar 
    Wright, A. J., Wardle, D. A., Callaway, R. & Gaxiola, A. The overlooked role of facilitation in biodiversity experiments. Trends Ecol. Evol. 32, 383–390 (2017).PubMed 
    Article 

    Google Scholar 
    Oelmann, Y. et al. Above- and belowground biodiversity jointly tighten the P cycle in agricultural grasslands. Nat. Commun. 12, 4431 (2021).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Li, L. et al. Diversity enhances agricultural productivity via rhizosphere phosphorus facilitation on phosphorus-deficient soils. Proc. Natl Acad. Sci. USA 104, 11192–11196 (2007).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Li, L., Tilman, D., Lambers, H. & Zhang, F. S. Plant diversity and overyielding: insights from belowground facilitation of intercropping in agriculture. New Phytol. 203, 63–69 (2014).PubMed 
    Article 
    CAS 

    Google Scholar 
    Hacker, N. et al. Plant diversity shapes microbe–rhizosphere effects on P mobilisation from organic matter in soil. Ecol. Lett. 18, 1356–1365 (2015).PubMed 
    Article 

    Google Scholar 
    Vance, C. P., Uhde-Stone, C. & Allan, D. L. Phosphorus acquisition and use: critical adaptations by plants for securing a nonrenewable resource. New Phytol. 157, 423–447 (2003).CAS 
    PubMed 
    Article 

    Google Scholar 
    Chen, J. et al. Long-term nitrogen loading alleviates phosphorus limitation in terrestrial ecosystems. Glob. Change Biol. 26, 5077–5086 (2020).Article 

    Google Scholar 
    Hinsinger, P. et al. P for two, sharing a scarce resource: soil phosphorus acquisition in the rhizosphere of intercropped species. Plant Physiol. 156, 1078–1086 (2011).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Liu, X. J. et al. Plant diversity and species turnover co-regulate soil nitrogen and phosphorus availability in Dinghushan forests, southern China. Plant Soil 464, 257–272 (2021).CAS 
    Article 

    Google Scholar 
    Hooper, D. U. & Vitousek, P. M. Effects of plant composition and diversity on nutrient cycling. Ecol. Monogr. 68, 121–149 (1998).Article 

    Google Scholar 
    Alberti, G. et al. Tree functional diversity influences belowground ecosystem functioning. Appl. Soil Ecol. 120, 160–168 (2017).Article 

    Google Scholar 
    Maddhesiya, P. K., Singh, K. & Singh, R. P. Effects of perennial aromatic grass species richness and microbial consortium on soil properties of marginal lands and on biomass production. Land Degrad. Dev. 32, 1008–1021 (2021).Article 

    Google Scholar 
    Zhang, C. B. et al. Effects of plant diversity on nutrient retention and enzyme activities in a full-scale constructed wetland. Bioresour. Technol. 101, 1686–1692 (2010).CAS 
    PubMed 
    Article 

    Google Scholar 
    Štursová, M. & Baldrian, P. Effects of soil properties and management on the activity of soil organic matter transforming enzymes and the quantification of soil-bound and free activity. Plant Soil 338, 99–110 (2011).Article 
    CAS 

    Google Scholar 
    Wu, H. et al. Linkage between tree species richness and soil microbial diversity improves phosphorus bioavailability. Funct. Ecol. 33, 1549–1560 (2019).Article 

    Google Scholar 
    Steinauer, K. et al. Plant diversity effects on soil microbial functions and enzymes are stronger than warming in a grassland experiment. Ecology 96, 99–112 (2015).PubMed 
    Article 

    Google Scholar 
    Zhang, D. S. et al. Increased soil phosphorus availability induced by faba bean root exudation stimulates root growth and phosphorus uptake in neighbouring maize. New Phytol. 209, 823–831 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Berendse, F., van Ruijven, J., Jongejans, E. & Keesstra, S. Loss of plant species diversity reduces soil erosion resistance. Ecosystems 18, 881–888 (2015).CAS 
    Article 

    Google Scholar 
    Forrester, D. I. & Bauhus, J. A review of processes behind diversity–productivity relationships in forests. Curr. Rep. 2, 45–61 (2016).Article 
    CAS 

    Google Scholar 
    Batterman, S. A. et al. Phosphatase activity and nitrogen fixation reflect species differences, not nutrient trading or nutrient balance, across tropical rainforest trees. Ecol. Lett. 21, 1486–1495 (2018).PubMed 
    Article 

    Google Scholar 
    Chen, C., Chen, H. Y. H., Chen, X. & Huang, Z. Meta-analysis shows positive effects of plant diversity on microbial biomass and respiration. Nat. Commun. 10, 1332 (2019).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Hisano, M., Chen, H. Y. H., Searle, E. B. & Reich, P. B. Species-rich boreal forests grew more and suffered less mortality than species-poor forests under the environmental change of the past half-century. Ecol. Lett. 22, 999–1008 (2019).PubMed 
    Article 

    Google Scholar 
    Chen, X. & Chen, H. Y. H. Plant diversity loss reduces soil respiration across terrestrial ecosystems. Glob. Change Biol. 25, 1482–1492 (2019).Article 

    Google Scholar 
    Chen, X. & Chen, H. Y. H. Plant mixture balances terrestrial ecosystem C:N:P stoichiometry. Nat. Commun. 12, 4562 (2021).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Reich, P. B. et al. Species and functional group diversity independently influence biomass accumulation and its response to CO2 and N. Proc. Natl Acad. Sci. USA 101, 10101–10106 (2004).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Chen, X. et al. Effects of plant diversity on soil carbon in diverse ecosystems: a global meta-analysis. Biol. Rev. 95, 167–183 (2020).Article 

    Google Scholar 
    Zhang, Y., Chen, H. Y. H. & Reich, P. B. Forest productivity increases with evenness, species richness and trait variation: a global meta-analysis. J. Ecol. 100, 742–749 (2012).Article 

    Google Scholar 
    Alewell, C. et al. Global phosphorus shortage will be aggravated by soil erosion. Nat. Commun. 11, 4546 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Mueller, K. E., Tilman, D., Fornara, D. A. & Hobbie, S. E. Root depth distribution and the diversity–productivity relationship in a long-term grassland experiment. Ecology 94, 787–793 (2013).Article 

    Google Scholar 
    Tang, X. Y. et al. Intercropping legumes and cereals increases phosphorus use efficiency; a meta-analysis. Plant Soil 460, 89–104 (2021).CAS 
    Article 

    Google Scholar 
    Karanika, E. D., Alifragis, D. A., Mamolos, A. P. & Veresoglou, D. S. Differentiation between responses of primary productivity and phosphorus exploitation to species richness. Plant Soil 297, 69–81 (2007).CAS 
    Article 

    Google Scholar 
    Bünemann, E. K., Prusisz, B. & Ehlers, K. in Phosphorus in Action: Biological Processes in Soil Phosphorus Cycling (eds Bünemann, E. et al.) 37–57 (Springer, 2011).Ma, Z. L. & Chen, H. Y. H. Effects of species diversity on fine root productivity in diverse ecosystems: a global meta-analysis. Glob. Ecol. Biogeogr. 25, 1387–1396 (2016).Article 

    Google Scholar 
    Mellado-Vazquez, P. G. et al. Plant diversity generates enhanced soil microbial access to recently photosynthesized carbon in the rhizosphere. Soil Biol. Biochem. 94, 122–132 (2016).CAS 
    Article 

    Google Scholar 
    Qin, Y. et al. Arbuscular mycorrhizal fungus differentially regulates P mobilizing bacterial community and abundance in rhizosphere and hyphosphere. Appl. Soil Ecol. 170, 104294 (2022).Article 

    Google Scholar 
    Rojo, M. J., Carcedo, S. G. & Mateos, M. P. Distribution and characterization of phosphatase and organic phosphorus in soil fractions. Soil Biol. Biochem. 22, 169–174 (1990).CAS 
    Article 

    Google Scholar 
    Barrow, N. The effects of pH on phosphate uptake from the soil. Plant Soil 410, 401–410 (2017).CAS 
    Article 

    Google Scholar 
    Button, K. S. et al. Power failure: why small sample size undermines the reliability of neuroscience. Nat. Rev. Neurosci. 14, 365–376 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    Yu, R. P., Li, X. X., Xiao, Z. H., Lambers, H. & Li, L. Phosphorus facilitation and covariation of root traits in steppe species. New Phytol. 226, 1285–1298 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G. & PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Medicine 6, e1000097 (2009).Jenkins, D. G. & Quintana-Ascencio, P. F. A solution to minimum sample size for regressions. PLoS ONE 15, e0229345 (2020)..Rohatgi, A. WebPlotDigitizer v.4.5 (Automeris, 2021); https://automeris.io/WebPlotDigitizerJobbagy, E. G. & Jackson, R. B. The distribution of soil nutrients with depth:global patterns and the imprint of plants. Biogeochemistry 53, 51–77 (2001).CAS 
    Article 

    Google Scholar 
    Trabucco, A. & Zomer, R. Global Aridity Index (Global-Aridity) and Global Potential Evapo-Transpiration (Global-PET) Geospatial Database (CGIAR, 2009); http://www.cgiar-csi.org/data/global-aridity-and-pet-databaseBridgham, S. D., Pastor, J., Mcclaugherty, C. A. & Richardson, C. J. Nutrient-use efficiency: a litterfall index, a model, and a test along a nutrient-availability gradient in North Carolina peatlands. Am. Nat. 145, 1–21 (1995).Article 

    Google Scholar 
    Hedges, L. V., Gurevitch, J. & Curtis, P. S. The meta-analysis of response ratios in experimental ecology. Ecology 80, 1150–1156 (1999).Article 

    Google Scholar 
    Loreau, M. & Hector, A. Partitioning selection and complementarity in biodiversity experiments. Nature 412, 72–76 (2001).CAS 
    PubMed 
    Article 

    Google Scholar 
    Pittelkow, C. M. et al. Productivity limits and potentials of the principles of conservation agriculture. Nature 517, 365–368 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    Bates, D. et al. lme4: Linear mixed-effects models using Eigen and S4. R package version 1.1-10 https://cran.r-project.org/web/packages/lme4/index.html (2017).Zuur, A. F., Ieno, E. N. & Elphick, C. S. A protocol for data exploration to avoid common statistical problems. Methods Ecol. Evol. 1, 3–14 (2010).Article 

    Google Scholar 
    Johnson, J. B. & Omland, K. S. Model selection in ecology and evolution. Trends Ecol. Evol. 19, 101–108 (2004).PubMed 
    Article 

    Google Scholar 
    MuMIn: Multi-model inference. R package version 1.42.1 (2018).Zuur, A. F., Ieno, E. N., Walker, N., Saveliev, A. A. & Smith, G. M. Mixed Effects Models and Extensions in Ecology with R (Springer, 2009).Koricheva, J., Gurevitch, J. & Mengersen, K. Handbook of Meta-analysis in Ecology and Evolution (Princeton Univ. Press, 2013).Graham, M. H. Confronting multicollinearity in ecological multiple regression. Ecology 84, 2809–2815 (2003).Article 

    Google Scholar 
    Lefcheck, J. S. piecewiseSEM: piecewise structural equation modelling in R for ecology, evolution, and systematics. Methods Ecol. Evol. 7, 573–579 (2016).Article 

    Google Scholar 
    Long, J. A. Interactions: comprehensive, user-friendly toolkit for probing interactions. R package version 1.1.5 https://cran.r-project.org/package=interactions (2021).Adams, D. C., Gurevitch, J. & Rosenberg, M. S. Resampling tests for meta-analysis of ecological data. Ecology 78, 1277–1283 (1997).Article 

    Google Scholar 
    R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2021). More

  • in

    Warming-induced increase in carbon uptake is linked to earlier spring phenology in temperate and boreal forests

    Chuine, I. Why does phenology drive species distribution? Philos. Trans. 365, 3149–3160 (2010).
    Google Scholar 
    Chuine, I. & Beaubien, E. G. Phenology is a major determinant of tree species range. Ecol. Lett. 4, 500–510 (2001).
    Google Scholar 
    Richardson, D. A. et al. Climate change, phenology, and phenological control of vegetation feedbacks to the climate system. Agric. For. Meteorol. 169, 156–173 (2013).ADS 

    Google Scholar 
    Tang, J. et al. Emerging opportunities and challenges in phenology: a review. Ecosphere 7, e01436 (2016).
    Google Scholar 
    Piao, S. et al. Plant phenology and global climate change: current progresses and challenges. Glob. Chang. Biol. 25, 1922–1940 (2019).ADS 
    MathSciNet 
    PubMed 

    Google Scholar 
    Fu, Y. H. et al. Three times greater weight of daytime than of night‐time temperature on leaf unfolding phenology in temperate trees. N. Phytol. 212, 590–597 (2016).CAS 

    Google Scholar 
    Menzel, A. et al. European phenological response to climate change matches the warming pattern. Glob. Chang. Biol. 12, 1969–1976 (2006).ADS 

    Google Scholar 
    Piao, S. et al. Leaf onset in the northern hemisphere triggered by daytime temperature. Nat. Commun. 6, 6911 (2015).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Penuelas, J., Rutishauser, T. & Filella, I. Phenology feedbacks on climate change. Science 324, 887–888 (2009).CAS 
    PubMed 

    Google Scholar 
    Fu, Y. H. et al. Declining global warming effects on the phenology of spring leaf unfolding. Nature 526, 104–107 (2015).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Lang, G. A. Dormancy: a new universal terminology. HortScience 22, 817–820 (1987).
    Google Scholar 
    Perry, T. O. Dormancy of trees in winter. Science 171, 29–36 (1971).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Huang, J. et al. Intra-annual wood formation of subtropical Chinese red pine shows better growth in dry season than wet season. Tree Physiol. 38, 1225–1236 (2018).PubMed 

    Google Scholar 
    Knowles, J. F. et al. Montane forest productivity across a semi-arid climatic gradient. Glob. Chang. Biol. 26, 6945–6958 (2020).ADS 
    PubMed 

    Google Scholar 
    Richard, S., Kjellsen, T. D., Schaberg, P. G. & Murakami, P. F. Dynamics of low-temperature acclimation in temperate and boreal conifer foliage in a mild winter climate. Tree Physiol. 28, 1365–1374 (2008).
    Google Scholar 
    Roxas, A. A., Orozco, J., Guzmán-Delgado, P. & Zwieniecki, M. A. Spring phenology is affected by fall non-structural carbohydrate concentration and winter sugar redistribution in three Mediterranean nut tree species. Tree Physiol. 41, 1425–1438 (2021).CAS 

    Google Scholar 
    Palacio, S., Martínez, M. M. & Montserrat-Martí, G. Seasonal dynamics of non-structural carbohydrates in two species of mediterranean sub-shrubs with different leaf phenology. Environ. Exp. Bot. 59, 34–42 (2007).CAS 

    Google Scholar 
    Fierravanti, A., Rossi, S., Kneeshaw, D., Grandpré, L. D. & Deslauriers, A. Low non-structural carbon accumulation in spring reduces growth and increases mortality in conifers defoliated by spruce budworm. Front. For. Glob. Change. 2, 1–13 (2019).
    Google Scholar 
    Oberhuber, W., Gruber, A., Lethaus, G., Winkler, A. & Wieser, G. Stem girdling indicates prioritized carbon allocation to the root system at the expense of radial stem growth in Norway spruce under drought conditions. Environ. Exp. Bot. 138, 109–118 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    Pérez-de-Lis, G., Rossi, S., Vázquez-Ruiz, R. A., Rozas, V. & García-González, I. Do changes in spring phenology affect earlywood vessels? Perspective from the xylogenesis monitoring of two sympatric ring-porous oaks. N. Phytol. 209, 521–530 (2016).
    Google Scholar 
    Weber, R., Gessler, A. & Hoch, G. High carbon storage in carbon-limited trees. N. Phytol. 222, 171–182 (2019).CAS 

    Google Scholar 
    Zani, D., Crowther, T. W., Lidong, M., Renner, S. S. & Zohner, C. M. Increased growing-season productivity drives earlier autumn leaf senescence in temperate trees. Science 370, 1066–1071 (2020).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Dusenge, M. E., Duarte, A. G. & Way, D. A. Plant carbon metabolism and climate change: elevated CO2 and temperature impacts on photosynthesis, photorespiration and respiration. N. Phytol. 221, 32–49 (2019).CAS 

    Google Scholar 
    Lin, Y.-S., Medlyn, B. E. & Ellsworth, D. Temperature responses of leaf net photosynthesis: the role of component processes. Tree Physiol. 32, 219–231 (2012).CAS 
    PubMed 

    Google Scholar 
    Huang, M. et al. Air temperature optima of vegetation productivity across global biomes. Nat. Ecol. Evol. 3, 772–779 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Terashima, I. & Hikosaka, K. Comparative ecophysiology of leaf and canopy photosynthesis. Plant Cell Environ. 18, 1111–1128 (1995).
    Google Scholar 
    Liang, J., Xia, J., Liu, L. & Wan, S. Global patterns of the responses of leaf-level photosynthesis and respiration in terrestrial plants to experimental warming. J. Plant. Ecol. 6, 437–447 (2013).
    Google Scholar 
    Duffy, K. A. et al. How close are we to the temperature tipping point of the terrestrial biosphere? Sci. Adv. 7, eaay1052 (2021).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Güsewell, S., Furrer, R., Gehrig, R. & Pietragalla, B. Changes in temperature sensitivity of spring phenology with recent climate warming in Switzerland are related to shifts of the preseason. Glob. Chang. Biol. 23, 5189–5202 (2017).ADS 
    PubMed 

    Google Scholar 
    Keenan, T. F., Richardson, A. D. & Hufkens, K. On quantifying the apparent temperature sensitivity of plant phenology. N. Phytol. 225, 1033–1040 (2020).
    Google Scholar 
    Klein, T., Vitasse, Y. & Hoch, G. Coordination between growth, phenology and carbon storage in three coexisting deciduous tree species in a temperate forest. Tree Physiol. 36, 847–855 (2016).CAS 
    PubMed 

    Google Scholar 
    Kagawa, A., Sugimoto, A. & Maximov, T. C. Seasonal course of translocation, storage and remobilization of 13C pulse-labeled photoassimilate in naturally growing Larix gmelinii saplings. N. Phytol. 171, 793–804 (2010).
    Google Scholar 
    Rinne, K. T. et al. Examining the response of needle carbohydrates from Siberian larch trees to climate using compound-specific δ(13) C and concentration analyses. Plant Cell Environ. 38, 2340–2352 (2015).CAS 
    PubMed 

    Google Scholar 
    Schädel, C., Blöchl, A., Richter, A. & Hoch, G. Short-term dynamics of nonstructural carbohydrates and hemicelluloses in young branches of temperate forest trees during bud break. Tree Physiol. 29, 901–911 (2009).PubMed 

    Google Scholar 
    Kaurin, A., Junttila, O. & Hanson, J. Seasonal changes in frost hardiness in cloudberry (Rubus chamaemorus) in relation to carbohydrate content with special reference to sucrose. Physiol. Plant. 52, 310–314 (1981).CAS 

    Google Scholar 
    Shahba, M. A., Qian, Y. L., Hughes, H. G., Koski, A. J. & Christensen, D. Relationships of soluble carbohydrates and freeze tolerance in saltgrass. Crop Sci. 43, 2148–2153 (2003).CAS 

    Google Scholar 
    Wang, J. et al. Contrasting temporal variations in responses of leaf unfolding to daytime and nighttime warming. Glob. Chang. Biol. 27, 5084–5093 (2021).PubMed 

    Google Scholar 
    Marchand, L. J. et al. Inter-individual variability in spring phenology of temperate deciduous trees depends on species, tree size and previous year autumn phenology. Agric Meteorol. 290, 108031 (2020).
    Google Scholar 
    Shen, M. et al. Can changes in autumn phenology facilitate earlier green-up date of northern vegetation? Agric Meteorol. 291, 108077 (2020).
    Google Scholar 
    Chen, L. et al. Long-term changes in the impacts of global warming on leaf phenology of four temperate tree species. Glob. Chang. Biol. 25, 997–1004 (2019).ADS 
    PubMed 

    Google Scholar 
    Hanninen, H. Boreal and temperate trees in a changing climate: modelling the ecophysiology of seasonality. (Springer, 2016).Dreyer, E., Le Roux, X., Montpied, P., Daudet, F. A. & Masson, F. Temperature response of leaf photosynthetic capacity in seedlings from seven temperate tree species. Tree Physiol. 21, 223–232 (2001).CAS 
    PubMed 

    Google Scholar 
    Devi, A. F. & Garkoti, S. C. Variation in evergreen and deciduous species leaf phenology in Assam. India Trees 27, 985–997 (2013).
    Google Scholar 
    Bai, K., He, C., Wan, X. & Jiang, D. Leaf economics of evergreen and deciduous tree species along an elevational gradient in a subtropical mountain. AoB PLANTS 7, plv064 (2015).PubMed 
    PubMed Central 

    Google Scholar 
    Qi, J., Fan, Z., Fu, P., Zhang, Y. & Sterck, F. Differential determinants of growth rates in subtropical evergreen and deciduous juvenile trees: carbon gain, hydraulics and nutrient-use efficiencies. Tree Physiol. 41, 12–23 (2021).CAS 
    PubMed 

    Google Scholar 
    Fyllas, N. M. et al. Functional trait variation among and within species and plant functional types in mountainous mediterranean forests. Front. Plant Sci. 11, 1–18 (2020).
    Google Scholar 
    Templ, B. et al. Pan European Phenological database (PEP725): a single point of access for European data. Int J. Biometeorol. 62, 1109–1113 (2018).ADS 
    PubMed 

    Google Scholar 
    Leys, C., Ley, C., Klein, O., Bernard, P. & Licata, L. Detecting outliers: do not use standard deviation around the mean, use absolute deviation around the median. J. Exp. Soc. Psychol. 49, 764–766 (2013).
    Google Scholar 
    Richardson, A. D. et al. Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery. Sci. Data. 5, 180028 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Klosterman, S. et al. Evaluating remote sensing of deciduous forest phenology at multiple spatial scales using PhenoCam imagery. Biogeosciences 11, 4305–4320 (2014).ADS 

    Google Scholar 
    Zhang, Y. et al. Seasonal and interannual changes in vegetation activity of tropical forests in Southeast Asia. Agric. For. Meteorol. 224, 1–10 (2016).ADS 

    Google Scholar 
    Pinzon, J. E. & Tucker, C. J. A non-stationary 1981–2012 AVHRR NDVI3g time series. Remote Sens. 6, 6929–6960 (2014).ADS 

    Google Scholar 
    Wang, X. et al. No trends in spring and autumn phenology during the global warming hiatus. Nat. Commun. 10, 2389 (2019).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Wang, X. et al. Validation of MODIS-GPP product at 10 flux sites in northern China. Int. J. Remote Sens. 34, 587–599 (2013).
    Google Scholar 
    Julien, Y. & Sobrino, J. Global land surface phenology trends from GIMMS database. Int J. Remote Sens. 30, 3495–3513 (2009).
    Google Scholar 
    Zhang, X. et al. Monitoring vegetation phenology using MODIS. Remote Sens Environ. 84, 471–475 (2003).ADS 

    Google Scholar 
    Dinerstein, E. et al. An ecoregion-based approach to protecting half the terrestrial realm. Bioscience 67, 534–545 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    Pastorello, G. et al. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data. Sci. Data. 7, 1–27 (2020).
    Google Scholar 
    Huang, K. et al. Enhanced peak growth of global vegetation and its key mechanisms. Nat. Ecol. Evol. 2, 1897–1905 (2018).PubMed 

    Google Scholar 
    Tang, Y., Xu, X., Zhou, Z., Qu, Y. & Sun, Y. Estimating global maximum gross primary productivity of vegetation based on the combination of MODIS greenness and temperature data. Ecol. Inform. 63, 101307 (2021).
    Google Scholar 
    Xia, J. et al. Joint control of terrestrial gross primary productivity by plant phenology and physiology. Proc. Natl. Acad. Sci. U.S.A. 112, 2788–2793 (2015).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kalman, D. A singularly valuable decomposition: The SVD of a matrix. Coll. Math. J. 27, 2–23 (1996).MathSciNet 

    Google Scholar 
    Biriukova, K. et al. Performance of singular spectrum analysis in separating seasonal and fast physiological dynamics of solar-induced chlorophyll fluorescence and PRI optical signals. J. Geophys. Res. Biogeosci. 126, e2020JG006158 (2021).ADS 
    CAS 

    Google Scholar 
    Richardson, A. D. et al. Influence of spring and autumn phenological transitions on forest ecosystem productivity. Philos. Trans. R. Soc. Lond. B Biol. Sci. 365, 3227–3246 (2010).PubMed 
    PubMed Central 

    Google Scholar 
    Wu, C. et al. Interannual variability of net carbon exchange is related to the lag between the end-dates of net carbon uptake and photosynthesis: Evidence from long records at two contrasting forest stands. Agric. For. Meteorol. 164, 29–38 (2012).ADS 

    Google Scholar 
    Cornes, R., der Schrier, G. V., den Besselaar, E. J. M. V. & Jones, P. An ensemble version of the E-OBS temperature and precipitation data sets. J. Geophys. Res. Atmos. 123, 9391–9409 (2018).
    Google Scholar 
    Hijmans, R. J. et al. raster: Geographic data analysis and modeling. https://CRAN.R-project.org/package=raster. R package version 3.5-15 (2022).R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria (2021).Erb, I. Partial correlations in compositional data analysis. Comput. Geosci. 6, 100026 (2020).
    Google Scholar 
    Vitasse, Y., Signarbieux, C. & Fu, Y. H. Global warming leads to more uniform spring phenology across elevations. Proc. Natl Acad. Sci. U.S.A. 115, 1004–1008 (2018).CAS 
    PubMed 

    Google Scholar 
    Kim, S. ppcor: Partial and semi-partial (part) correlation. https://CRAN.R-project.org/package=ppcor. R package version 1.1 (2015).Lefcheck, J. S. piecewiseSEM: piecewise structural equation modeling in R for ecology, evolution, and systematics. Methods Ecol. Evol. 7, 573–579 (2016).
    Google Scholar 
    Breiman, L. Random forests. Mach. Learn. 45, 5–32 (2001).MATH 

    Google Scholar 
    Valavi, R., Elith, J., Lahoz-Monfort, J. J. & Guillera-Arroita, G. Modelling species presence-only data with random forests. Ecography 44, 1731–1742 (2021).
    Google Scholar 
    Freeman, E. A., Moisen, G. G., Coulston, J. W. & Wilson, B. T. Random forests and stochastic gradient boosting for predicting tree canopy cover: comparing tuning processes and model performance. Can. J. For. Res. 46, 323–339 (2016).
    Google Scholar 
    Liaw, A. & Wiener, M. Classification and regression by randomForest. R. N. 2, 18–22 (2002).
    Google Scholar 
    Cutler, D. et al. Random forests for classification in ecology. Ecology 88, 2783–2792 (2007).PubMed 

    Google Scholar  More

  • in

    Archiving the genomic and genetic resources of glaciers

    Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.This is a summary of: Liu, Y. et al. A genome and gene catalog of glacier microbiomes. Nat. Biotechnol. https://doi.org/10.1038/s41587-022-01367-2 (2022). More

  • in

    Long-term evidence for ecological intensification as a pathway to sustainable agriculture

    Rockström, J. et al. Sustainable intensification of agriculture for human prosperity and global sustainability. Ambio 46, 4–17 (2017).Article 

    Google Scholar 
    Steffen, W. et al. Planetary boundaries: guiding human development on a changing planet. Science 347, 1259855 (2015).Article 
    CAS 

    Google Scholar 
    Campbell, B. M. et al. Agriculture production as a major driver of the Earth system exceeding planetary boundaries. Ecol. Soc. 22, 8 (2017).Article 

    Google Scholar 
    Hazell, P. & Wood, S. Drivers of change in global agriculture. Philos. Trans. R. Soc. B 363, 495–515 (2008).Article 

    Google Scholar 
    Lehmann, P. et al. Complex responses of global insect pests to climate warming. Front. Ecol. Environ. 18, 141–150 (2020).Article 

    Google Scholar 
    Foley, J. A. et al. Solutions for a cultivated planet. Nature 478, 337–342 (2011).CAS 
    Article 

    Google Scholar 
    Springmann, M. et al. Options for keeping the food system within environmental limits. Nature 562, 519–525 (2018).CAS 
    Article 

    Google Scholar 
    Hunter, M. C., Smith, R. G., Schipanski, M. E., Atwood, L. W. & Mortensen, D. A. Agriculture in 2050: recalibrating targets for sustainable intensification. Bioscience 67, 386–391 (2017).Article 

    Google Scholar 
    Ecosystems and Human Well-being: Synthesis (Millenium Ecosystem Assessment, 2005); http://www.millenniumassessment.org/documents/document.356.aspx.pdfBommarco, R., Kleijn, D. & Potts, S. G. Ecological intensification: harnessing ecosystem services for food security. Trends Ecol. Evol. 28, 230–238 (2013).Article 

    Google Scholar 
    Kleijn, D. et al. Ecological intensification: bridging the gap between science and practice. Trends Ecol. Evol. 34, 154–166 (2018).Article 

    Google Scholar 
    Pingali, P. L. Green revolution: impacts, limits, and the path ahead. Proc. Natl Acad. Sci. USA 109, 12302–12308 (2012).CAS 
    Article 

    Google Scholar 
    Wezel, A. et al. Agroecology as a science, a movement and a practice. Sustain. Agric. 2, 27–43 (2009).
    Google Scholar 
    Garnett, T. et al. Sustainable intensification in agriculture: premises and policies. Science 341, 33–34 (2013).CAS 
    Article 

    Google Scholar 
    Lipper, L. et al. Climate-smart agriculture for food security. Nat. Clim. Change 4, 1068–1072 (2014).Article 

    Google Scholar 
    Tittonell, P. Ecological intensification of agriculture—sustainable by nature. Curr. Opin. Environ. Sustain. 8, 53–61 (2014).Article 

    Google Scholar 
    Jenkinson, D. S. The impact of humans on the nitrogen cycle, with focus on temperate arable agriculture. Plant Soil 228, 3–15 (2001).CAS 
    Article 

    Google Scholar 
    Verheijen, F. G. A., Jones, R. J. A., Rickson, R. J. & Smith, C. J. Tolerable versus actual soil erosion rates in Europe. Earth Sci. Rev. 94, 23–38 (2009).Article 

    Google Scholar 
    Peoples, M. B. et al. in Agroecosystem Diversity: Reconciling Contemporary Agriculture and Environmental Quality (eds Lemaire, G. et al.) 123–142 (Academic Press, 2019); https://doi.org/10.1016/B978-0-12-811050-8.00008-XStorkey, J., Bruce, T., McMillan, V. & Neve, P. in Agroecosystem Diversity: Reconciling Contemporary Agriculture and Environmental Quality (eds Lemaire, G. et al.) 199–209 (Academic Press, 2019); https://doi.org/10.1016/B978-0-12-811050-8.00012-1Schröder, J. Revisiting the agronomic benefits of manure: a correct assessment and exploitation of its fertilizer value spares the environment. Bioresour. Technol. 96, 253–261 (2005).Article 
    CAS 

    Google Scholar 
    Mhlanga, B., Ercoli, L., Pellegrino, E., Onofri, A. & Thierfelder, C. The crucial role of mulch to enhance the stability and resilience of cropping systems in southern Africa. Agron. Sustain. Dev. 41, 29–43 (2021).Article 

    Google Scholar 
    Barrett, C. B. & Bevis, L. E. M. The self-reinforcing feedback between low soil fertility and chronic poverty. Nat. Geosci. 8, 907–912 (2015).CAS 
    Article 

    Google Scholar 
    Tittonell, P. & Giller, K. E. When yield gaps are poverty traps: the paradigm of ecological intensification in African smallholder agriculture. Field Crops Res. 143, 76–90 (2013).Article 

    Google Scholar 
    Sandén, T. et al. European long-term field experiments: knowledge gained about alternative management practices. Soil Use Manage. 34, 167–176 (2018).Article 

    Google Scholar 
    Storkey, J. et al. The unique contribution of Rothamsted to ecological research at large temporal scales. Adv. Ecol. Res. 55, 3–42 (2016).Article 

    Google Scholar 
    Johnston, A. E. & Poulton, P. R. The importance of long-term experiments in agriculture: their management to ensure continued crop production and soil fertility; the Rothamsted experience. Eur. J. Soil Sci. 69, 113–125 (2018).CAS 
    Article 

    Google Scholar 
    Bowles, T. M. et al. Long-term evidence shows that crop-rotation diversification increases agricultural resilience to adverse growing conditions in North America. One Earth 2, 284–293 (2020).Marini, L. et al. Crop rotations sustain cereal yields under a changing climate. Environ. Res. Lett. 15, 124011 (2020).Article 

    Google Scholar 
    Lal, R. Carbon emission from farm operations. Environ. Int. 30, 981–990 (2004).CAS 
    Article 

    Google Scholar 
    Cordell, D., Drangert, J. O. & White, S. The story of phosphorus: global food security and food for thought. Glob. Environ. Change 19, 292–305 (2009).Article 

    Google Scholar 
    Lechenet, M., Dessaint, F., Py, G., Makowski, D. & Munier-Jolain, N. Reducing pesticide use while preserving crop productivity and profitability on arable farms. Nat. Plants 3, 17008 (2017).Article 

    Google Scholar 
    Bedoussac, L. et al. Ecological principles underlying the increase of productivity achieved by cereal-grain legume intercrops in organic farming. A review. Agron. Sustain. Dev. 35, 911–935 (2015).Article 

    Google Scholar 
    Storkey, J., Mead, A., Addy, J. & MacDonald, A. J. Agricultural intensification and climate change have increased the threat from weeds. Glob. Change Biol. 27, 2416–2425 (2021).Article 

    Google Scholar 
    Vanlauwe, B. et al. in Integrated Plant Nutrient Management in Sub-Saharan Africa: From Concept to Practice (eds Vanlauwe, B. et al.) 173–184 (CABI, 2002).Hijbeek, R. et al. Do organic inputs matter—a meta-analysis of additional yield effects for arable crops in Europe. Plant Soil 411, 293–303 (2017).CAS 
    Article 

    Google Scholar 
    Thierfelder, C. & Wall, P. C. Effects of conservation agriculture techniques on infiltration and soil water content in Zambia and Zimbabwe. Soil Tillage Res. 105, 217–227 (2009).Article 

    Google Scholar 
    Gentile, R., Vanlauwe, B., Chivenge, P. & Six, J. Interactive effects from combining fertilizer and organic residue inputs on nitrogen transformations. Soil Biol. Biochem. 40, 2375–2384 (2008).CAS 
    Article 

    Google Scholar 
    Mupangwa, W. et al. Maize yields from rotation and intercropping systems with different legumes under conservation agriculture in contrasting agro-ecologies. Agric. Ecosyst. Environ. 306, 107170 (2021).Article 

    Google Scholar 
    Pittelkow, C. M. et al. Productivity limits and potentials of the principles of conservation agriculture. Nature 517, 365–368 (2015).CAS 
    Article 

    Google Scholar 
    Steward, P. R. et al. The adaptive capacity of maize-based conservation agriculture systems to climate stress in tropical and subtropical environments: a meta-regression of yields. Agric. Ecosyst. Environ. 251, 194–202 (2018).Article 

    Google Scholar 
    Pittelkow, C. M. et al. When does no-till yield more? A global meta-analysis. Field Crops Res. 183, 156–168 (2015).Article 

    Google Scholar 
    Sun, W. et al. Climate drives global soil carbon sequestration and crop yield changes under conservation agriculture. Glob. Change Biol. 26, 3325–3335 (2020).Article 

    Google Scholar 
    Kirkegaard, J. A. et al. Sense and nonsense in conservation agriculture: principles, pragmatism and productivity in Australian mixed farming systems. Agric. Ecosyst. Environ. 187, 133–145 (2014).Article 

    Google Scholar 
    Thierfelder, C. et al. Complementary practices supporting conservation agriculture in southern Africa. A review. Agron. Sustain. Dev. 38, 16–37 (2018).Article 

    Google Scholar 
    Alignier, A. et al. Configurational crop heterogeneity increases within-field plant diversity. J. Appl. Ecol. 57, 654–663 (2020).Article 

    Google Scholar 
    Liebman, M. et al. Ecologically sustainable weed management: how do we get from proof-of-concept to adoption? Ecol. Appl. 26, 1352–1369 (2016).Article 

    Google Scholar 
    Giller, K. E. The food security conundrum of sub-Saharan Africa. Glob. Food Sec. 26, 100431 (2020).Article 

    Google Scholar 
    Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).Article 

    Google Scholar 
    Addy, J. W. G., Ellis, R. H., Macdonald, A. J., Semenov, M. A. & Mead, A. Changes in agricultural climate in South-Eastern England from 1892 to 2016 and differences in cereal and permanent grassland yield. Agric. For. Meteorol. 308–309, 108560 (2021).Article 

    Google Scholar 
    Bates, D., Kliegl, R., Vasishth, S. & Baayen, H. Parsimonious mixed models. Preprint at https://arXiv.org/abs/1506.04967v2 (2018).MacLaren, C., Glendining, M., Poulton, P., Macdonald, A. & Clark, S. Woburn Ley-Arable Experiment: Yields of Wheat as First Test Crop, 1976–2018 (e-RA Rothamsted, 2022); https://doi.org/10.23637/wrn3-wheat7618-01 .Lenth, R. emmeans: Estimated Marginal Means, aka Least-Squares Means: R package version 1.7.2 https://CRAN.R-project.org/package=emmeans (2020).Viechtbauer, W. Conducting meta-analyses in R with the metafor package. J. Stat. Softw. 36, 1–48 (2010).Article 

    Google Scholar 
    Lajeunesse, M. J. On the meta-analysis of response ratios for studies with correlated and multi-group designs. Ecology 92, 2049–2055 (2011).Article 

    Google Scholar 
    Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer-Verlag, 2016).Crain, C. M., Kroeker, K. & Halpern, B. S. Interactive and cumulative effects of multiple human stressors in marine systems. Ecol. Lett. 11, 1304–1315 (2008).Article 

    Google Scholar  More

  • in

    A nitrite-oxidising bacterium constitutively consumes atmospheric hydrogen

    Daims H, Lücker S, Wagner M. A new perspective on microbes formerly known as nitrite-oxidizing bacteria. Trends Microbiol. 2016;24:699–712.CAS 
    Article 

    Google Scholar 
    Ehrich S, Behrens D, Lebedeva E, Ludwig W, Bock E. A new obligately chemolithoautotrophic, nitrite-oxidizing bacterium, Nitrospira moscoviensis sp. nov. and its phylogenetic relationship. Arch Microbiol. 1995;164:16–23.CAS 
    Article 

    Google Scholar 
    Koch H, Galushko A, Albertsen M, Schintlmeister A, Gruber-Dorninger C, Lücker S, et al. Growth of nitrite-oxidizing bacteria by aerobic hydrogen oxidation. Science. 2014;345:1052–4.CAS 
    Article 

    Google Scholar 
    Koch H, Lücker S, Albertsen M, Kitzinger K, Herbold C, Spieck E, et al. Expanded metabolic versatility of ubiquitous nitrite-oxidizing bacteria from the genus Nitrospira. Proc Natl Acad Sci USA. 2015;112:11371–6.CAS 
    Article 

    Google Scholar 
    Daims H, Lebedeva EV, Pjevac P, Han P, Herbold C, Albertsen M, et al. Complete nitrification by Nitrospira bacteria. Nature. 2015;528:504–9.CAS 
    Article 

    Google Scholar 
    van Kessel MAHJ, Speth DR, Albertsen M, Nielsen PH, Op den Camp HJM, Kartal B, et al. Complete nitrification by a single microorganism. Nature. 2015;528:555–9.Article 

    Google Scholar 
    Lücker S, Wagner M, Maixner F, Pelletier E, Koch H, Vacherie B, et al. A Nitrospira metagenome illuminates the physiology and evolution of globally important nitrite-oxidizing bacteria. Proc Natl Acad Sci USA. 2010;107:13479–84.Article 

    Google Scholar 
    Mundinger AB, Lawson CE, Jetten MSM, Koch H, Lücker S. Cultivation and transcriptional analysis of a canonical Nitrospira under stable growth conditions. Front Microbiol. 2019;10:1325.Morita RY. Is H2 the universal energy source for long-term survival? Micro Ecol. 1999;38:307–20.CAS 
    Article 

    Google Scholar 
    Bay SK, Dong X, Bradley JA, Leung PM, Grinter R, Jirapanjawat T, et al. Trace gas oxidizers are widespread and active members of soil microbial communities. Nat Microbiol. 2021;6:246–56.CAS 
    Article 

    Google Scholar 
    Constant P, Poissant L, Villemur R. Isolation of Streptomyces sp. PCB7, the first microorganism demonstrating high-affinity uptake of tropospheric H2. ISME J. 2008;2:1066–76.CAS 
    Article 

    Google Scholar 
    Greening C, Carere CR, Rushton-Green R, Harold LK, Hards K, Taylor MC, et al. Persistence of the dominant soil phylum Acidobacteria by trace gas scavenging. Proc Natl Acad Sci USA. 2015;112:10497–502.CAS 
    Article 

    Google Scholar 
    Islam ZF, Cordero PRF, Feng J, Chen Y-J, Bay SK, Jirapanjawat T, et al. Two Chloroflexi classes independently evolved the ability to persist on atmospheric hydrogen and carbon monoxide. ISME J. 2019;13:1801.CAS 
    Article 

    Google Scholar 
    Islam ZF, Welsh C, Bayly K, Grinter R, Southam G, Gagen EJ, et al. A widely distributed hydrogenase oxidises atmospheric H2 during bacterial growth. ISME J. 2020;14:2649–58.CAS 
    Article 

    Google Scholar 
    Schmitz RA, Pol A, Mohammadi SS, Hogendoorn C, van Gelder AH, Jetten MSM, et al. The thermoacidophilic methanotroph Methylacidiphilum fumariolicum SolV oxidizes subatmospheric H2 with a high-affinity, membrane-associated [NiFe] hydrogenase. ISME J. 2020;14:1223–32.CAS 
    Article 

    Google Scholar 
    Ortiz M, Leung PM, Shelley G, Jirapanjawat T, Nauer PA, Van Goethem M, et al. Multiple energy sources and metabolic strategies sustain microbial diversity in Antarctic desert soils. Proc Natl Acad Sci. 2021;118:e2025322118.CAS 
    Article 

    Google Scholar 
    Greening C, Berney M, Hards K, Cook GM, Conrad R. A soil actinobacterium scavenges atmospheric H2 using two membrane-associated, oxygen-dependent [NiFe] hydrogenases. Proc Natl Acad Sci USA. 2014;111:4257–61.CAS 
    Article 

    Google Scholar 
    Myers MR, King GMY. Isolation and characterization of Acidobacterium ailaaui sp. nov., a novel member of Acidobacteria subdivision 1, from a geothermally heated Hawaiian microbial mat. Int J Syst Evol Microbiol. 2016;66:5328–35.CAS 
    Article 

    Google Scholar 
    Cordero PRF, Grinter R, Hards K, Cryle MJ, Warr CG, Cook GM, et al. Two uptake hydrogenases differentially interact with the aerobic respiratory chain during mycobacterial growth and persistence. J Biol Chem. 2019;294:18980–91.CAS 
    Article 

    Google Scholar 
    Sander R. Compilation of Henry’s law constants (version 4.0) for water as solvent. Atmos Chem Phys. 2015;15:4399–981.CAS 
    Article 

    Google Scholar 
    Cox J, Mann M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat Biotechnol. 2008;26:1367–72.CAS 
    Article 

    Google Scholar 
    Cox J, Neuhauser N, Michalski A, Scheltema RA, Olsen JV, Mann M. Andromeda: a peptide search engine integrated into the MaxQuant environment. J Proteome Res. 2011;10:1794–805.CAS 
    Article 

    Google Scholar 
    Shah AD, Goode RJA, Huang C, Powell DR, Schittenhelm RB. LFQ-Analyst: an easy-to-use interactive web platform to analyze and visualize label-free proteomics data preprocessed with MaxQuant. J Proteome Res. 2020;19:204–11.CAS 
    Article 

    Google Scholar 
    Nowka B, Daims H, Spieck E. Comparative oxidation kinetics of nitrite-oxidizing bacteria: nitrite availability as key factor for niche differentiation. Appl Environ Microbiol. 2014;81:745–53.Thauer RK, Jungermann K, Decker K. Energy conservation in chemotrophic anaerobic bacteria. Bacteriol Rev. 1977;41:809.Article 

    Google Scholar 
    Greening C, Villas-Bôas SG, Robson JR, Berney M, Cook GM. The growth and survival of Mycobacterium smegmatis is enhanced by co-metabolism of atmospheric H2. PLoS ONE. 2014;9:e103034.Article 

    Google Scholar 
    Constant P, Chowdhury SP, Pratscher J, Conrad R. Streptomycetes contributing to atmospheric molecular hydrogen soil uptake are widespread and encode a putative high-affinity [NiFe]-hydrogenase. Environ Microbiol. 2010;12:821–9.CAS 
    Article 

    Google Scholar 
    Häring V, Conrad R. Demonstration of two different H2-oxidizing activities in soil using an H2 consumption and a tritium exchange assay. Biol Fertil Soils. 1994;17:125–8.Article 

    Google Scholar 
    Yang Y, Daims H, Liu Y, Herbold CW, Pjevac P, Lin J-G, et al. Activity and metabolic versatility of complete ammonia oxidizers in full-scale wastewater treatment systems. mBio. 2020;11:e03175–19.Chadwick GL, Hemp J, Fischer WW, Orphan VJ. Convergent evolution of unusual complex I homologs with increased proton pumping capacity: energetic and ecological implications. ISME J. 2018;12:2668–80.CAS 
    Article 

    Google Scholar 
    Alberty RA. Standard apparent reduction potentials of biochemical half reactions and thermodynamic data on the species involved. Biophys Chem. 2004;111:115–22.CAS 
    Article 

    Google Scholar 
    Burns LC, Stevens RJ, Smith RV, Cooper JE. The occurrence and possible sources of nitrite in a grazed, fertilized, grassland soil. Soil Biol Biochem. 1995;27:47–59.CAS 
    Article 

    Google Scholar 
    Zhang M, Yuan D, Chen G, Li Q, Zhang Z, Liang Y. Simultaneous determination of nitrite and nitrate at nanomolar level in seawater using on-line solid phase extraction hyphenated with liquid waveguide capillary cell for spectrophotometric detection. Microchim Acta. 2009;165:427–35.CAS 
    Article 

    Google Scholar 
    Daims H, Nielsen JL, Nielsen PH, Schleifer K-H, Wagner M. In situ characterization of Nitrospira-like nitrite-oxidizing bacteria active in wastewater treatment plants. Appl Environ Microbiol. 2001;67:5273–84.CAS 
    Article 

    Google Scholar 
    Lebedeva EV, Alawi M, Maixner F, Jozsa P-G, Daims H, Spieck E. Physiological and phylogenetic characterization of a novel lithoautotrophic nitrite-oxidizing bacterium, ‘Candidatus Nitrospira bockiana’. Int J Syst Evol Microbiol. 2008;58:242–50.CAS 
    Article 

    Google Scholar 
    Lebedeva EV, Off S, Zumbrägel S, Kruse M, Shagzhina A, Lücker S, et al. Isolation and characterization of a moderately thermophilic nitrite-oxidizing bacterium from a geothermal spring. FEMS Microbiol Ecol. 2011;75:195–204.CAS 
    Article 

    Google Scholar 
    Watson SW, Bock E, Valois FW, Waterbury JB, Schlosser U. Nitrospira marina gen. nov. sp. nov.: a chemolithotrophic nitrite-oxidizing bacterium. Arch Microbiol. 1986;144:1–7.Article 

    Google Scholar 
    Maixner F, Noguera DR, Anneser B, Stoecker K, Wegl G, Wagner M, et al. Nitrite concentration influences the population structure of Nitrospira-like bacteria. Environ Microbiol. 2006;8:1487–95.CAS 
    Article 

    Google Scholar 
    Sorokin DY, Lucker S, Vejmelkova D, Kostrikina NA, Kleerebezem R, Rijpstra WIC, et al. Nitrification expanded: discovery, physiology and genomics of a nitrite-oxidizing bacterium from the phylum Chloroflexi. ISME J. 2012;6:2245–56.CAS 
    Article 

    Google Scholar 
    Greening C, Biswas A, Carere CR, Jackson CJ, Taylor MC, Stott MB, et al. Genomic and metagenomic surveys of hydrogenase distribution indicate H2 is a widely utilised energy source for microbial growth and survival. ISME J. 2016;10:761–77.CAS 
    Article 

    Google Scholar 
    Daebeler A, Kitzinger K, Koch H, Herbold CW, Steinfeder M, Schwarz J, et al. Exploring the upper pH limits of nitrite oxidation: diversity, ecophysiology, and adaptive traits of haloalkalitolerant. Nitrospira ISME J. 2020;14:2967–79.CAS 
    Article 

    Google Scholar 
    Suarez C, Sedlacek CJ, Gustavsson DJI, Eiler A, Modin O, Hermansson M, et al. Disturbance-based management of ecosystem services and disservices in partial nitritation anammox biofilms. 2021. https://www.biorxiv.org/content/10.1101/2021.07.05.451122v1. More

  • in

    ORMEF: a Mediterranean database of exotic fish records

    Edelist, D., Rilov, G., Golani, D., Carlton, J. T. & Spanier, E. Restructuring the Sea: profound shifts in the world’s most invaded marine ecosystem. Divers. Distrib. 19, 69–77, https://doi.org/10.1111/ddi.12002 (2013).Article 

    Google Scholar 
    Parravicini, V., Azzurro, E., Kulbicki, M. & Belmaker, J. Niche shift can impair the ability to predict invasion risk in the marine realm: an illustration using Mediterranean fish invaders. Ecol. Lett. 18, 246–253, https://doi.org/10.1111/ele.12401 (2015).Article 
    PubMed 

    Google Scholar 
    Galil, B. S. et al. International arrivals: widespread bioinvasions in European Seas. Ethol. Ecol. Evol. 26, 152–171, https://doi.org/10.1080/03949370.2014.897651 (2014).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Golani, D. & Fricke, R. Checklist of the Red Sea Fishes with delineation of the Gulf of Suez, Gulf of Aqaba, endemism and Lessepsian migrants. Zootaxa 4509, 1–215, https://doi.org/10.11646/zootaxa.4509.1.1 (2018).Article 
    PubMed 

    Google Scholar 
    Zenetos, A. et al. Uncertainties and validation of alien species catalogues: The Mediterranean as an example. Estuar. Coast. Shelf Sci. 191, 171–187, https://doi.org/10.1016/j.ecss.2017.03.031 (2017).Article 

    Google Scholar 
    Katsanevakis, S. et al. Advancing marine conservation in European and contiguous seas with the MarCons Action. Res. Ideas Outcomes 3, e11884, https://doi.org/10.3897/rio.3.e11884 (2017).Article 

    Google Scholar 
    Schroeder, K., Chiggiato, J., Bryden, H. L., Borghini, M. & Ben Ismail, S. Abrupt climate shift in the Western Mediterranean Sea. Sci. Rep. 6, 23009, https://doi.org/10.1038/srep23009 (2016).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Vargas-Yáñez, M. et al. Warming trends and decadal variability in the Western Mediterranean shelf. Glob. Planet. Change 63, 177–184, https://doi.org/10.1016/j.gloplacha.2007.09.001 (2008).Article 

    Google Scholar 
    D’Amen, M. & Azzurro, E. Lessepsian fish invasion in Mediterranean marine protected areas: a risk assessment under climate change scenarios. ICES J. Mar. Sci. 77, 388–397, https://doi.org/10.1093/icesjms/fsz207 (2020).Article 

    Google Scholar 
    Golani, D., Azzurro, E., Dulčić, J., Massutí, E. & Orsi-Relini, L. Atlas of Exotic Species in the Mediterranean Sea. F. Briand, Ed. 365 pages. CIESM Publishers, Paris, Monaco (2021).Editorial Board. AquaNIS. Information system on Aquatic Non-Indigenous and Cryptogenic Species. World Wide Web electronic publication. Version 2.36+ (2015).Roy, D. et al. DAISIE – Inventory of alien invasive species in Europe. https://doi.org/10.15468/ybwd3x (2020).European Commission – Joint Research Centre – European Alien Species Information Network (EASIN).Uludag, A, Scalera, R., Trichkova, T., Tomov, R. & Rat, M. East and South European Network for Invasive Alien Species (ESENIAS): Development, networking and role in the invasive alien species research and policy-making in Europe. (2016).Zenetos, A. et al. ELNAIS: A collaborative network on Aquatic Alien Species in Hellas (Greece). REABIC 6, 185–196, https://doi.org/10.3391/mbi.2015.6.2.09 (2015).Article 

    Google Scholar 
    European Network on Invasive Alien Species. NOBANIS (Gateway to information on Invasive Alien species in North and Central Europe) (2013).MAMIAS – Marine Mediterranean Invasive Alien Species. (2014).MedMIS – Mediterranean Marine Invasive SpeciesKatsanevakis, S. et al. Identifying where vulnerable species occur in a data-poor context: combining satellite imaging and underwater occupancy surveys. Mar. Ecol. Prog. Ser. 577, 17–32, https://doi.org/10.3354/meps12232 (2017).Article 

    Google Scholar 
    Galil, B. S. Alien species in the Mediterranean Sea—which, when, where, why? In Challenges to Marine Ecosystems (eds. Davenport, J. et al.) 105–116, https://doi.org/10.1007/978-1-4020-8808-7_10 (Springer Netherlands (2008).Galil, B. S. Taking stock: inventory of alien species in the Mediterranean sea. Biol. Invasions 11, 359–372, https://doi.org/10.1007/s10530-008-9253-y (2009).Article 

    Google Scholar 
    Nunes, A. L., Orizaola, G., Laurila, A. & Rebelo, R. Rapid evolution of constitutive and inducible defenses against an invasive predator. Ecology 95, 1520–1530, https://doi.org/10.1890/13-1380.1 (2014).Article 
    PubMed 

    Google Scholar 
    Zenetos, A. et al. Annotated list of marine alien species in the Mediterranean with records of the worst invasive species. Mediterr. Mar. Sci. 6, 63–118, https://doi.org/10.12681/mms.186 (2005).Article 

    Google Scholar 
    Zenetos, A. et al. Additions to the annotated list of marine alien biota in the Mediterranean with special emphasis on Foraminifera and Parasites. Mediterr. Mar. Sci. 9, 119–166, https://doi.org/10.12681/mms.146 (2008).Article 

    Google Scholar 
    Zenetos, A. et al. Alien species in the Mediterranean sea by 2010. A contribution to the application of european union’s marine strategy framework directive (MSFD). Part I. Spatial distribution. https://doi.org/10.12681/mms.87 (2010)Zenetos, Α et al. Alien species in the Mediterranean Sea by 2012. A contribution to the application of European Union’s Marine Strategy Framework Directive (MSFD). Part 2. Introduction trends and pathways. Mediterr. Mar. Sci. 13, 328–352, https://doi.org/10.12681/mms.327 (2012).Article 

    Google Scholar 
    Dimitriadis, C. et al. Updating the occurrences of Pterois miles in the Mediterranean Sea, with considerations on thermal boundaries and future range expansion. Mediterr. Mar. Sci. 21, 62–69, https://doi.org/10.12681/mms.21845 (2020).Article 

    Google Scholar 
    Carlton, J. T. Pattern, process, and prediction in marine invasion ecology. Biol. Conserv. 78, 97–106, https://doi.org/10.1016/0006-3207(96)00020-1 (1996).Article 

    Google Scholar 
    Olenin, S., Minchin, D., Daunys, D. & Zaiko, A. Pathways of aquatic invasions in Europe. Atlas of biodiversity risk 138–139 (2010).Essl, F. et al. A Conceptual Framework for Range-Expanding Species that Track Human-Induced Environmental Change. BioScience 69, 908–919 (2019).Article 

    Google Scholar 
    Golani, D., Orsi-Relini, L., Massuti, E. & Quignard, J. P. CIESM Atlas of Exotic Species in the Mediterranean. vol. 1 (2002).D’Amen, M. & Azzurro, E. Integrating univariate niche dynamics in species distribution models: A step forward for marine research on biological invasions. J. Biogeogr. 47, 686–697, https://doi.org/10.1111/jbi.13761 (2020).Article 

    Google Scholar 
    Azzurro, E., Smeraldo, S. & D’Amen, M. ORMEF: Occurrence Records of Mediterranean Exotic Fishes database. SEANOE. https://doi.org/10.17882/84182 (2021).Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data 3, 160018, https://doi.org/10.1038/sdata.2016.18 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Fricke, R., Eschmeyer, W. N. & Van Der Laan, R. Eschmeyer’s Catalog of Fishes: genera, species, references. California Academy of Sciences (2022).Azzurro, E., Goren, M., Diamant, A., Galil, B. & Bernardi, G. Establishing the identity and assessing the dynamics of invasion in the Mediterranean Sea by the dusky sweeper, Pempheris homboidei Kossmann & Räuber, 1877 (Pempheridae, Perciformes). Biol. Invasions 17, 815–826, https://doi.org/10.1007/s10530-014-0836-5 (2015).Article 

    Google Scholar 
    Evans, J. & Schembri, P. On the occurrence of Cephalopholis hemistiktos and C. taeniops (Actinopterygii, Perciformes, Serranidae) in Malta, with corrections of previous misidentifications. Acta Ichthyol. Piscat. 47, 197–200, https://doi.org/10.3750/AIEP/02064 (2017).Article 

    Google Scholar 
    Dragicevic, B. et al. New Mediterranean Biodiversity Records (December 2019). https://doi.org/10.12681/mms.20913 (2019).UNEP/MAP – United Nation Environment Programme – Mediterranean Action Plan. Integrated Monitoring and Assessment Programme of the Mediterranean Sea and Coast and Related Assessment Criteria (IMAP). (2016). More