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    Variation in the ratio of compounds in a plant volatile blend during transmission by wind

    Beyaert, I. & Hilker, M. Plant odour plumes as mediators of plant–insect interactions. Biol. Rev. 89, 68–81 (2014).
    Google Scholar 
    Simpraga, M., Takabayashi, J. & Holopainen, J. K. Language of plants: Where is the word?. J. Integr. Plant Biol. 58, 343–349 (2016).CAS 

    Google Scholar 
    Bruce, T. J. A., Wadhams, L. J. & Woodcock, C. M. Insect host location: A volatile situation. Trends Plant Sci. 10, 269–274 (2005).CAS 

    Google Scholar 
    Bruce, T. J. A. & Pickett, J. A. Perception of plant volatile blends by herbivorous insects—Finding the right mix. Phytochemistry 72, 1605–1611 (2011).CAS 

    Google Scholar 
    Raguso, R. A. Wake up and smell the roses: The ecology and evolution of floral scent. Annu. Rev. Ecol. Evol. S. 39, 549–569 (2008).
    Google Scholar 
    Schiestl, F. P. The evolution of floral scent and insect chemical communication. Ecol. Lett. 13, 643–656 (2010).
    Google Scholar 
    Arimura, G., Kost, C. & Boland, W. Herbivore-induced, indirect plant defences. Biochim. Biophys. Acta. 1734, 91–111 (2005).CAS 

    Google Scholar 
    Hare, J. D. Ecological role of volatiles produced by plants in response to damage by herbivorous insects. Annu. Rev. Entomol. 56, 161–180 (2011).CAS 

    Google Scholar 
    Laothawornkitkul, J., Taylor, J. E., Paul, N. D. & Hewitt, C. N. Biogenic volatile organic compounds in the earth system. New Phytol. 183, 27–51 (2009).CAS 

    Google Scholar 
    Dicke, M., van Loon, J. J. A. & Soler, R. Chemical complexity of volatiles from plant induced by multiple attack. Nature Chem. Biol. 5, 317–324 (2009).CAS 

    Google Scholar 
    Loreto, F. & Schnitzler, J. P. Abiotic stresses and induced BVOCs. Trends Plant Sci. 15, 154–166 (2010).CAS 

    Google Scholar 
    Tasin, M. et al. Synergism and redundancy in a plant volatile blend attracting grapevine moth females. Phytochemistry 68, 203–209 (2007).CAS 

    Google Scholar 
    Riffell, J. A., Lei, H., Christensen, T. A. & Hildebrand, J. G. Characterization and coding of behaviorally significant odor mixtures. Curr. Biol. 19, 335–340 (2009).CAS 

    Google Scholar 
    Riffell, J. A., Lei, H. & Hildebrand, J. G. Neural correlates of behavior in the moth Manduca sexta in response to complex odors. Proc. Natl. Acad. Sci. USA 106, 19219–19226 (2009).ADS 
    CAS 

    Google Scholar 
    Atema, J. Eddy chemotaxis and odor landscapes: Exploration of nature with animal sensors. Biol. Bull. 191, 129–138 (1996).CAS 

    Google Scholar 
    Conchou, L. et al. Insect odorscapes: From plant volatiles to natural olfactory scenes. Front. Physiol. 10, 972 (2019).
    Google Scholar 
    Riffell, J. A., Abrell, L. & Hildebrand, J. G. Physical processes and real-time chemical measurement of the insect olfactory environment. J. Chem. Ecol. 34, 837–853 (2008).CAS 

    Google Scholar 
    Mylne, K. R., Davidson, M. J. & Thomson, D. J. Concentration fluctuation measurements in tracer plumes using high and low frequency response detectors. Bound-Lay. Meteorol. 79, 225–242 (1996).ADS 

    Google Scholar 
    Finelli, C. M., Pentcheff, N. D., Zimmer-Faust, R. K. & Wethey, D. S. Odor transport in turbulent flows: Constraints on animal navigation. Limnol. Oceanogr. 44, 1056–1071 (1999).ADS 
    CAS 

    Google Scholar 
    Murlis, J., Elkinton, J. S. & Cardé, R. T. Odor plumes and how insects use them. Annu. Rev. Entomol. 37, 505–532 (1992).
    Google Scholar 
    Murlis, J., Willis, M. A. & Cardé, R. T. Spatial and temporal structures of pheromone plumes in fields and forests. Physiol. Entomol. 25, 211–222 (2000).CAS 

    Google Scholar 
    Kennedy, J. S. The visual response of flying mosquitoes. Proc. Zool. Soc. London Ser. A 109, 221–242 (1940).
    Google Scholar 
    Bursell, E. Observations on the orientation of tsetse flies (Glossina pallidipes) to wind-borne odours. Physio. Entomol. 9, 133–137 (1984).
    Google Scholar 
    Murlis, J., Elkinton, J. S. & Cardé, R. T. Odor plumes and how insects use them. Annu. Rev. Entomol. 37, 505–532 (1992).
    Google Scholar 
    Kennedy, J. S., Ludlow, A. R. & Sanders, C. J. Guidance of flying male moths by wind-borne sex-pheromone. Physiol. Entomol. 6, 395–412 (1981).
    Google Scholar 
    Koehl, M. A. R. The fluid mechanics of arthropod sniffing in turbulent odor plumes. Chem. Senses 31, 93–105 (2006).CAS 

    Google Scholar 
    Baker, T. C., Willis, M. A., Haynes, K. F. & Phelan, P. L. A pulsed cloud of sex pheromone elicits upwind flight in male moths. Physiol. Entomol. 10, 257–265 (1985).
    Google Scholar 
    Willis, M. A. & Baker, T. C. Effects of intermittent and continuous pheromone stimulation on the flight behavior of the oriental fruit moth, Grapholita molesta. Physiol. Entomol. 9, 341–358 (1984).
    Google Scholar 
    Mafraneto, A. & Cardé, R. T. Fine-scale structure of pheromone plumes modulates upwind orientation of flying moths. Nature 369, 142–144 (1994).ADS 
    CAS 

    Google Scholar 
    Mafraneto, A. & Cardé, R. T. Dissection of the pheromone-modulated flight of moths using single-pulse response as a template. Experientia 52, 373–379 (1996).CAS 

    Google Scholar 
    Vickers, N. J. & Baker, T. C. Reiterative responses to single strands of odor promote sustained upwind flight and odor source location by moths. Proc. Natl. Acad. Sci. USA 91, 5756–5760 (1994).ADS 
    CAS 

    Google Scholar 
    Lei, H., Riffell, J. A., Gage, S. L. & Hildebrand, J. G. Contrast enhancement of stimulus intermittency in a primary olfactory network and its behavioral significance. J. Biol. 8, 21 (2009).
    Google Scholar 
    Kuenen, L. & Carde, R. T. Strategies for recontacting a lost pheromone plume: Casting and upwind flight in the male gypsy moth. Physiol. Entomol. 19, 15–29 (1994).
    Google Scholar 
    Vickers, N. J. & Baker, T. C. Latencies of behavioral response to interception of filaments of sex pheromone and clean air influence flight track shape in Heliothis virescens (F.) males. J. Comp. Physiol. A. 178, 831–847 (1996).
    Google Scholar 
    Vickers, N. J. Mechanisms of animal navigation in odor plumes. Biol. Bull. 198, 203–212 (2000).CAS 

    Google Scholar 
    Cardé, R. T. & Willis, M. A. Navigational strategies used by insects to find distant, wind-borne sources of odor. J. Chem. Ecol. 34, 854–866 (2008).
    Google Scholar 
    Willis, M. A. & Baker, T. C. Effects of varying sex pheromone component ratios on the zigzagging flight movements of the oriental fruit moth, Grapholita molesta. J. Insect. Behav. 1, 357–371 (1988).
    Google Scholar 
    Voskamp, K. E., Den Otter, C. J. & Noorman, N. Electroantennogram responses of tsetse flies (Glossina pallidipes) to host odours in an open field and riverine woodland. Physiol. Entomol. 23, 176–183 (1998).
    Google Scholar 
    Cai, X. M., Xu, X. X., Bian, L., Luo, Z. X. & Chen, Z. M. Measurement of volatile plant compounds in field ambient air by thermal desorption–gas chromatography–mass spectrometry. Anal. Bioanal. Chem. 407, 9105–9114 (2015).CAS 

    Google Scholar 
    Zollner, G. E., Torr, S. J., Ammann, C. & Meixner, F. X. Dispersion of carbon dioxide plumes in African woodland: implications for host-finding by tsetse flies. Physiol. Entomol. 29, 381–394 (2004).
    Google Scholar 
    McFrederick, Q. S., Kathilankal, J. C. & Fuentes, J. D. Air pollution modifies floral scent trails. Atmos. Environ. 42, 2336–2348 (2008).ADS 
    CAS 

    Google Scholar 
    Yuan, J. S., Himanen, S. J., Holopainen, J. K., Chen, F. & NealStewart, C. Jr. Smelling global climate change: mitigation of function for plant volatile organic compounds. Trends Ecol. Evol. 24, 323–331 (2009).
    Google Scholar 
    Weissburg, M. J. The fluid dynamical context of chemosensory behavior. Biol. Bull. 198, 188–202 (2000).CAS 

    Google Scholar 
    Atkinson, R. & Arey, J. Gas-phase tropospheric chemistry of biogenic volatile organic compounds: A review. Atmos. Environ. 37, 197–219 (2003).ADS 

    Google Scholar 
    Helmig, D., Bocquet, F., Pollmann, J. & Revermann, T. Analytical techniques for sesquiterpene emission rate studies in vegetation enclosure experiments. Atmos. Environ. 38, 557–572 (2004).ADS 
    CAS 

    Google Scholar 
    Riffell, J. A, Shlizerman, E., Sanders, E., Abrell, L., Medina, B., Hinterwirth, A. J. & NathanKutz, J. Flower discrimination by pollinators in a dynamic chemical environment. Science 344, 1515–1518 (2014).Shorey, H. H. Animal communication by pheromones (Academic Press, 1976).Cardé, R. T. & Charlton, R. E. Olfactory sexual communication in Lepidoptera: Strategy, sensitivity and selectivity In Insect communication (ed. Lewis, T.) 241–265 (Academic Press, 1984).Elkinton, J. S., Schal, C., Ono, T. & Carde, R. T. Pheromone puff trajectory and upwind flight of male gypsy moths in a forest. Physiol. Entomol. 12, 399–406 (1987).
    Google Scholar 
    Baker, T. C., Fadamiro, H. Y. & Cosse, A. A. Moth uses fine tuning for odour resolution. Nature 393, 530 (1998).ADS 
    CAS 

    Google Scholar 
    Szyszka, P., Stierle, J. S., Biergans, S. & Galizia, C. G. The speed of smell: Odor-object segregation within milliseconds. PLoS One 7, e36096 (2012).ADS 
    CAS 

    Google Scholar 
    Hildebrand, J. G. Analysis of chemical signals by nervous systems. Proc. Natl. Acad. Sci. USA 92, 67–74 (1995).ADS 
    CAS 

    Google Scholar 
    Cai, X. M. et al. Field background odour should be taken into account when formulating a pest attractant based on plant volatiles. Sci. Rep. 7, 41818 (2017).ADS 
    CAS 

    Google Scholar 
    Xu, X. X. et al. Does background odor in tea gardens mask attractants? Screening and application of attractants for Empoasca onukii Matsuda. J. Econ. Entomol. 110, 2357–2363 (2017).CAS 

    Google Scholar 
    Hare, J. D. & Sun, J. J. Production of induced volatiles by Datura wrightii in response to damage by insects: Effect of herbivore species and time. J. Chem. Ecol. 37, 751–764 (2011).CAS 

    Google Scholar 
    Mumm, R., Tiemann, T., Schulz, S. & Hilker, M. Analysis of volatiles from black pine (Pinus nigra): Significance of wounding and egg deposition by a herbivorous sawfly. Phytochemistry 65, 3221–3230 (2004).CAS 

    Google Scholar  More

  • in

    Mutualism promotes insect fitness by fungal nutrient compensation and facilitates fungus propagation by mediating insect oviposition preference

    Franco FP, Túler AC, Gallan DZ, Gonçalves FG, Favaris AP, Peñaflor MFGV, et al. Fungal phytopathogen modulates plant and insect responses to promote its dissemination. ISME J. 2021;15:3522–33.CAS 

    Google Scholar 
    Huang H, Ren L, Li H, Schmidt A, Gershenzon J, Lu Y, et al. The nesting preference of an invasive ant is associated with the cues produced by actinobacteria in soil. PLoS Pathog. 2020;16:e1008800.CAS 

    Google Scholar 
    Angleró-Rodríguez YI, Blumberg BJ, Dong Y, Sandiford SL, Pike A, Clayton AM, et al. A natural Anopheles-associated Penicillium chrysogenum enhances mosquito susceptibility to Plasmodium infection. Sci Rep. 2016;6:34084.
    Google Scholar 
    Davis TS, Landolt PJ. A survey of insect assemblages responding to volatiles from a ubiquitous fungus in an agricultural landscape. J Chem Ecol. 2013;39:860–8.CAS 

    Google Scholar 
    Flury P, Vesga P, Dominguez-Ferreras A, Tinguely C, Ullrich CI, Kleespies RG, et al. Persistence of root-colonizing Pseudomonas protegens in herbivorous insects throughout different developmental stages and dispersal to new host plants. ISME J. 2018;13:860–72.
    Google Scholar 
    Kandasamy D, Gershenzon J, Andersson MN, Hammerbacher A. Volatile organic compounds influence the interaction of the Eurasian spruce bark beetle (Ips typographus) with its fungal symbionts. ISME J. 2019;13:1788–800.CAS 

    Google Scholar 
    Keesey IW, Koerte S, Khallaf MA, Retzke T, Guillou A, Grosse-Wilde E, et al. Pathogenic bacteria enhance dispersal through alteration of Drosophila social communication. Nat Commun. 2017;8:265.
    Google Scholar 
    Paul GB, Gerhard F, Elżbieta R, Alexandra S, Arne H, Sébastien L, et al. Yeast, not fruit volatiles mediate Drosophila melanogaster attraction, oviposition and development. Funct Ecol. 2012;26:1365–2435.
    Google Scholar 
    Ganter PF. Yeast and invertebrate associations. In: Gábor P, Carlos R, editors. Biodiversity and ecophysiology of yeasts. Berlin, Heidelberg: Springer; 2006. pp 303–70.Anagnostou C, Legrand EA, Rohlfs M. Friendly food for fitter flies?—Influence of dietary microbial species on food choice and parasitoid resistance in Drosophila. Oikos. 2010;119:533–41.
    Google Scholar 
    Günther CS, Knight SJ, Jones R, Goddard MR. Are Drosophila preferences for yeasts stable or contextual? Ecol Evol. 2019;9:8075–86.
    Google Scholar 
    Luo Y, Johnson JC, Chakraborty TS, Piontkowski A, Gendron CM, Pletcher SD. Yeast volatiles double starvation survival in Drosophila. Sci Adv. 2021;7:eabf8896.CAS 

    Google Scholar 
    Fogleman S. Coadaptation of Drosophila and yeasts in their natural habitat. J Chem Ecol. 1986;12:1037–55.
    Google Scholar 
    Droby S, Eick A, Macarisin D, Cohen L, Rafael G, Stange R, et al. Role of citrus volatiles in host recognition, germination and growth of Penicillium digitatum and Penicillium italicum. Postharvest Biol Tec. 2008;49:386–96.CAS 

    Google Scholar 
    Stensmyr MC, Dweck HK, Farhan A, Ibba I, Strutz A, Mukunda L, et al. A conserved dedicated olfactory circuit for detecting harmful microbes in Drosophila. Cell. 2012;151:1345–57.CAS 

    Google Scholar 
    Melo N, Wolff GH, Costa-da-Silva AL, Arribas R, Triana MF, Gugger M, et al. Geosmin attracts Aedes aegypti mosquitoes to oviposition sites. Curr Biol. 2020;30:127–34.CAS 

    Google Scholar 
    Wei DD, He W, Lang N, Miao ZQ, Xiao LF, Dou W, et al. Recent research status of Bactrocera dorsalis: Insights from resistance mechanisms and population structure. Arch Insect Biochem. 2019;102:e21601.CAS 

    Google Scholar 
    Han P, Wang X, Niu CY, Dong YC, Zhu JQ, Desneux N. Population dynamics, phenology, and overwintering of Bactrocera dorsalis (Diptera: Tephritidae) in Hubei Province, China. J Pest Sci. 2011;84:289–95.
    Google Scholar 
    Duyck PF, David P, Quilici S. A review of relationships between interspecific competition and invasions in fruit flies (Diptera: Tephritidae). Ecol Entomol. 2004;29:511–20.
    Google Scholar 
    Wen T, Zheng L, Dong S, Gong Z, Sang M, Long X, et al. Rapid detection and classification of citrus fruits infestation by Bactrocera dorsalis (Hendel) based on electronic nose. Postharvest Biol Tec. 2019;147:156–65.
    Google Scholar 
    Li X, Yang H, Wang T, Wang J, Wei H. Life history and adult dynamics of Bactrocera dorsalis in the citrus orchard of Nanchang, a subtropical area from China: implications for a control timeline. ScienceAsia. 2019;45:212–20.
    Google Scholar 
    Chalupowicz D, Veltman B, Droby S, Eltzov E. Evaluating the use of biosensors for monitoring of Penicillium digitatum infection in citrus fruit. Sens Actuat B-Chem. 2020;311:127896.CAS 

    Google Scholar 
    Turlings TC, Lengwiler UB, Bernasconi ML, Wechsler D. Timing of induced volatile emissions in maize seedlings. Planta. 1998;207:146–52.CAS 

    Google Scholar 
    Wang B, Dong W, Li H, D’Onofrio C, Bai P, Chen R, et al. Molecular basis of (E)-β-farnesene-mediated aphid location in the predator Eupeodes corollae. Curr Biol. 2022;32:951–62.CAS 

    Google Scholar 
    Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2− ΔΔCT method. Methods. 2001;25:402–8.CAS 

    Google Scholar 
    Cellar NA, De Nison JE, Seipelt CT, Twohig M, Burgess JA. Title of subordinate document. In: Dramatic improvements in assay reproducibility for water-soluble vitamins using ACQUITY UPLC and the Ultra-Sensitive Xevo TQ-S Mass Spectrometer. 2013. https://www.waters.com/webassets/cms/library/docs/720004690en.pdf.Ren FR, Sun X, Wang TY, Yan JY, Yao YL, Li CQ, et al. Pantothenate mediates the coordination of whitefly and symbiont fitness. ISME J. 2021;15:1655–67.CAS 

    Google Scholar 
    Batta YA. Quantitative postharvest contamination and transmission of Penicillium expansum (Link) conidia to nectarine and pear fruit by Drosophila melanogaster (Meig.) adults. Postharvest Biol Tec. 2006;40:190–6.
    Google Scholar 
    Rohlfs M. Clash of kingdoms or why Drosophila larvae positively respond to fungal competitors. Front Zool. 2005;2:2.
    Google Scholar 
    Becher PG, Bengtsson M, Hansson BS, Witzgall P. Flying the fly: long-range flight behavior of Drosophila melanogaster to attractive odors. J Chem Ecol. 2010;36:599–607.CAS 

    Google Scholar 
    Dionigi C, Ahten T, Wartelle L. Effects of several metals on spore, biomass, and geosmin production by Streptomyces tendae and Penicillium expansum. J Ind Microbiol Biot. 1996;17:84–88.CAS 

    Google Scholar 
    Jin S, Zhou X, Gu F, Zhong G, Yi X. Olfactory plasticity: variation in the expression of chemosensory receptors in Bactrocera dorsalis in different physiological states. Front Physiol. 2017;8:672.
    Google Scholar 
    Li H, Ren L, Xie M, Gao Y, He M, Hassan B, et al. Egg-surface bacteria are indirectly associated with oviposition aversion in Bactrocera dorsalis. Curr Biol. 2020;30:4432–40.CAS 

    Google Scholar 
    Liu Y, Cui Z, Si P, Liu Y, Zhou Q, Wang G. Characterization of a specific odorant receptor for linalool in the Chinese citrus fly Bactrocera minax (Diptera: Tephritidae). Insect Biochem Molec. 2020;122:103389.CAS 

    Google Scholar 
    Ju JF, Bing XL, Zhao DS, Guo Y, Hong XY. Wolbachia supplement biotin and riboflavin to enhance reproduction in planthoppers. ISME J. 2019;14:1–12.
    Google Scholar 
    Liu F, Wickham JD, Cao Q, Lu M, Sun J. An invasive beetle–fungus complex is maintained by fungal nutritional-compensation mediated by bacterial volatiles. ISME J. 2020;14:2829–42.CAS 

    Google Scholar 
    Douglas AE. The B vitamin nutrition of insects: the contributions of diet, microbiome and horizontally acquired genes. Curr Opin Insect Sci. 2017;23:65–69.
    Google Scholar 
    Honda K, Ômura H, Hayashi N, Abe F, Yamauchi T. Conduritols as oviposition stimulants for the danaid butterfly, Parantica sita, identified from a host plant, Marsdenia tomentosa. J Chem Ecol. 2004;30:2285–96.CAS 

    Google Scholar 
    Soldano A, Alpizar YA, Boonen B, Franco L, Lopez-Requena A, Liu G, et al. Gustatory-mediated avoidance of bacterial lipopolysaccharides via TRPA1 activation in Drosophila. Elife. 2016;5:e13133.
    Google Scholar 
    Hussain A, Üçpunar HK, Zhang M, Loschek LF, Grunwald Kadow IC. Neuropeptides modulate female chemosensory processing upon mating in Drosophila. PLoS Biol. 2016;14:e1002455.
    Google Scholar 
    Stötefeld L, Holighaus G, Schütz S, Rohlfs M. Volatile-mediated location of mutualist host and toxic non-host microfungi by Drosophila larvae. Chemoecology. 2015;5:271–83.
    Google Scholar 
    Gou B, Liu Y, Guntur A, Stern U, Yang HC. Mechanosensitive neurons on the internal reproductive tract contribute to egg-laying-induced acetic acid attraction in Drosophila. Cell Rep. 2014;9:522–30.CAS 

    Google Scholar 
    Mezzera C, Brotas M, Gaspar M, Pavlou HJ, Goodwin SF, Vasconcelos ML. Ovipositor extrusion promotes the transition from courtship to copulation and signals female acceptance in Drosophila melanogaster. Curr Biol. 2020;30:3736–48.CAS 

    Google Scholar 
    Teimoori-Boghsani Y, Ganjeali A, Cernava T, Müller H, Asili J, Berg G. Endophytic fungi of native Salvia abrotanoides plants reveal high taxonomic diversity and unique profiles of secondary metabolites. Front Microbiol. 2020;10:3013–20.
    Google Scholar 
    Holden JT, Furman C, Snell EE. D-alanine and the vitamin B6 content of microorganisms. J Biol Chem. 1949;178:789–97.CAS 

    Google Scholar 
    Michalkova V, Benoit JB, Weiss BL, Attardo GM, Aksoy S. Vitamin B6 generated by obligate symbionts is critical for maintaining proline homeostasis and fecundity in tsetse flies. Appl Environ Micro. 2014;80:5844–53.
    Google Scholar 
    Ren FR, Sun X, Wang TY, Yao YL, Huang YZ, Zhang X, et al. Biotin provisioning by horizontally transferred genes from bacteria confers animal fitness benefits. ISME J. 2020;14:2542–53.CAS 

    Google Scholar 
    Salem H, Bauer E, Strauss AS, Vogel H, Marz M, Kaltenpoth M. Vitamin supplementation by gut symbionts ensures metabolic homeostasis in an insect host. Proc Biol Sci. 2014;281:20141838.
    Google Scholar  More

  • in

    Metabarcoding the Antarctic Peninsula biodiversity using a multi-gene approach

    Meredith M, Sommerkorn M, Cassotta S, Derksen C, Ekaykin A, Hollowed A. IPCC special report on the ocean and cryosphere in a changing climate In: Pörtner H-O, Roberts D, Masson-Delmotte V, Zhai P, Tignor M, Poloczanska Eea, editors. 2022; chapter 3: https://doi.org/10.1017/9781009157964 (in press).Rozema PD, Venables HJ, van de Poll WH, Clarke A, Meredith MP, Buma AGJ. Interannual variability in phytoplankton biomass and species composition in northern Marguerite Bay (West Antarctic Peninsula) is governed by both winter sea ice cover and summer stratification. Limnol Oceanogr. 2017;62:235–52.Article 

    Google Scholar 
    Venables HJ, Clarke A, Meredith MP. Wintertime controls on summer stratification and productivity at the western Antarctic Peninsula. Limnol Oceanogr. 2013;58:1035–47.Article 

    Google Scholar 
    Barnes DKA, Souster T. Reduced survival of Antarctic benthos linked to climate-induced iceberg scouring. Nat Clim Change. 2011;1:365–8.Article 

    Google Scholar 
    Grange L, Tyler P, Peck L, Cornelius N. Long-term interannual cycles of the gametogenic ecology of the Antarctic brittle star Ophionotus victoriae. Mar Ecol Prog Ser. 2004;278:141–55.Article 

    Google Scholar 
    Schratzberger M, Ingels J. Meiofauna matters: The roles of meiofauna in benthic ecosystems. J Exp Mar Biol Ecol. 2018;502:12–25.Article 

    Google Scholar 
    Mayor D, Thornton B, Jenkins H, Felgate S. Microbiota: the living foundation. In: Beninger P, editor. Mudflat ecology. Switzerland AG: Springer Nature 2018. p. 43–61.Fonseca VG, Sinniger F, Gaspar JM, Quince C, Creer S, Power DM, et al. Revealing higher than expected meiofaunal diversity in Antarctic sediments: a metabarcoding approach. Sci Rep. 2017;7:6094.CAS 
    Article 

    Google Scholar 
    Vause BJ, Morley SA, Fonseca VG, Jazdzewska A, Ashton GV, Barnes DKA, et al. Spatial and temporal dynamics of Antarctic shallow soft-bottom benthic communities: ecological drivers under climate change. BMC Ecol. 2019;19:27.Article 

    Google Scholar 
    Danovaro R, Scopa M, Gambi C, Fraschetti S. Trophic importance of subtidal metazoan meiofauna: evidence from in situ exclusion experiments on soft and rocky substrates. Mar Biol. 2007;152:339–50.Article 

    Google Scholar 
    Watzin MC. The effects of meiofauna on settling macrofauna: meiofauna may structure macrofaunal communities. Oecologia. 1983;59:163–6.Article 

    Google Scholar 
    Schmidt JL, Deming JW, Jumars PA, Keil RG. Constancy of bacterial abundance in surficial marine sediments. Limnol Oceanogr. 1998;43:976–82.Article 

    Google Scholar 
    Whitman WB, Coleman DC, Wiebe WJ. Prokaryotes: the unseen majority. Proc Natl Acad Sci USA. 1998;95:6578–83.CAS 
    Article 

    Google Scholar 
    Burdige DJ. Preservation of organic matter in marine sediments: controls, mechanisms, and an imbalance in sediment organic carbon budgets? Chem Rev. 2007;107:467–85.CAS 
    Article 

    Google Scholar 
    Zou K, Thébault E, Lacroix G, Barot S. Interactions between the green and brown food web determine ecosystem functioning. Funct Ecol. 2016;30:1454–65.Article 

    Google Scholar 
    Anderson TR, Pond DW, Mayor DJ. The role of microbes in the nutrition of detritivorous invertebrates: a stoichiometric analysis. Front Microbiol. 2016;7:2113.
    Google Scholar 
    Lacoste E, Piot A, Archambault P, McKindsey CW, Nozais C. Bioturbation activity of three macrofaunal species and the presence of meiofauna affect the abundance and composition of benthic bacterial communities. Mar Environ Res. 2018;136:62–70.CAS 
    Article 

    Google Scholar 
    Bonaglia S, Nascimento FJ, Bartoli M, Klawonn I, Bruchert V. Meiofauna increases bacterial denitrification in marine sediments. Nat Commun. 2014;5:5133.CAS 
    Article 

    Google Scholar 
    Riemann F, Helmke E. Symbiotic relations of sediment-agglutinating nematodes and bacteria in detrital habitats: the enzyme-sharing concept. Mar Ecol. 2002;23:93–113.CAS 
    Article 

    Google Scholar 
    dos Santos GAP, Derycke S, Fonseca-Genevois VG, Coelho LCBB, Correia MTS, Moens T. Differential effects of food availability on population growth and fitness of three species of estuarine, bacterial-feeding nematodes. J Exp Mar Biol Ecol. 2008;355:27–40.Article 

    Google Scholar 
    Zeppilli D, Sarrazin J, Leduc D, Arbizu PM, Fontaneto D, Fontanier C, et al. Is the meiofauna a good indicator for climate change and anthropogenic impacts? Mar Biodivers. 2015;45:505–35.Article 

    Google Scholar 
    Moens T, Beninger PG. Meiofauna: an inconspicuous but important player in Mudflat ecology. In: Beninger P, editor. Mudflat ecology aquatic ecology series. 7. Switzerland: Springer; 2018.Webb AL, Hughes KA, Grand MM, Lohan MC, Peck LS. Sources of elevated heavy metal concentrations in sediments and benthic marine invertebrates of the western Antarctic Peninsula. Sci Total Environ. 2020;698:134268.CAS 
    Article 

    Google Scholar 
    Brown KM, Fraser KP, Barnes DK, Peck LS. Links between the structure of an Antarctic shallow-water community and ice-scour frequency. Oecologia. 2004;141:121–9.Article 

    Google Scholar 
    Stoeck T, Bass D, Nebel M, Christen R, Jones MDM, Breiner H-W, et al. Multiple marker parallel tag environmental DNA sequencing reveals a highly complex eukaryotic community in marine anoxic water. Mol Ecol. 2010;19:21–31.CAS 
    Article 

    Google Scholar 
    Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Huntley J, Fierer N, et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 2012;6:1621–4.CAS 
    Article 

    Google Scholar 
    Leray M, Yang JY, Meyer CP, Mills SC, Agudelo N, Ranwez V, et al. A new versatile primer set targeting a short fragment of the mitochondrial COI region for metabarcoding metazoan diversity: application for characterizing coral reef fish gut contents. Front Zool. 2013;10:34.Article 

    Google Scholar 
    Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 2011;17:10–2.Article 

    Google Scholar 
    Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJ, Holmes SP. DADA2: high-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13:581–3.CAS 
    Article 

    Google Scholar 
    Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, et al. BLAST+: architecture and applications. BMC Bioinform. 2009;10:421.Article 

    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 
    Article 

    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:D590–6.CAS 
    Article 

    Google Scholar 
    Benson DA, Karsch-Mizrachi I, Lipman DJ, Ostell J, Wheeler DL. GenBank. Nucleic Acids Res. 2005;33:D34–8.CAS 
    Article 

    Google Scholar 
    Wentworth CK. A scale of grade and class terms for clastic sediments. J Geol. 1922;30:377–92.Article 

    Google Scholar 
    Dean WE. Determination of carbonate and organic matter in calcareous sediments and sedimentary rocks by loss on ignition; comparison with other methods. J Sediment Res. 1974;44:242–8.CAS 

    Google Scholar 
    Tatzber M, Stemmer M, Spiegel H, Katzlberger C, Haberhauer G, Gerzabek MH. An alternative method to measure carbonate in soils by FT-IR spectroscopy. Environ Chem Lett. 2007;5:9–12.CAS 
    Article 

    Google Scholar 
    Hsieh CH, Reiss CS, Hunter JR, Beddington JR, May RM, Sugihara G. Fishing elevates variability in the abundance of exploited species. Nature. 2006;443:859–62.CAS 
    Article 

    Google Scholar 
    Elbrecht V, Braukmann TWA, Ivanova NV, Prosser SWJ, Hajibabaei M, Wright M, et al. Validation of COI metabarcoding primers for terrestrial arthropods. Peer J. 2019;7:e7745–e.Article 

    Google Scholar 
    Kirse A, Bourlat SJ, Langen K, Fonseca VG. Unearthing the potential of Soil eDNA metabarcoding—towards best practice advice for invertebrate biodiversity assessment. Front. Ecol. Evol. 2021;9:630560.Article 

    Google Scholar 
    Zhang GK, Chain FJJ, Abbott CL, Cristescu ME. Metabarcoding using multiplexed markers increases species detection in complex zooplankton communities. Evolut Appl. 2018;11:1901–14.CAS 
    Article 

    Google Scholar 
    Marquina D, Andersson AF, Ronquist F. New mitochondrial primers for metabarcoding of insects, designed and evaluated using in silico methods. Mol Ecol Resour. 2019;19:90–104.CAS 
    Article 

    Google Scholar 
    Leasi F, Sevigny JL, Laflamme EM, Artois T, Curini-Galletti M, de Jesus Navarrete A, et al. Biodiversity estimates and ecological interpretations of meiofaunal communities are biased by the taxonomic approach. Commun Biol. 2018;1:112.Article 

    Google Scholar 
    Giebner H, Langen K, Bourlat SJ, Kukowka S, Mayer C, Astrin JJ, et al. Comparing diversity levels in environmental samples: DNA sequence capture and metabarcoding approaches using 18S and COI genes. Mol Ecol Resour. 2020;20:1333–45.CAS 
    Article 

    Google Scholar 
    Vanhove S, Lee HJ, Beghyn M, Gansbeke DV, Brockington S, Vincx M. The Metazoan Meiofauna in its biogeochemical environment: the case of an Antarctic coastal sediment. J Mar Biol Assoc UK. 1998;78:411–34.Article 

    Google Scholar 
    Pasotti F, Saravia LA, De Troch M, Tarantelli MS, Sahade R, Vanreusel A. Benthic Trophic Interactions in an Antarctic Shallow Water Ecosystem Affected by Recent Glacier Retreat. PLoS ONE. 2015;10:e0141742.Article 

    Google Scholar 
    Griffiths JR, Kadin M, Nascimento FJA, Tamelander T, Tornroos A, Bonaglia S, et al. The importance of benthic-pelagic coupling for marine ecosystem functioning in a changing world. Global Change Biology. 2017;23:2179–96.Article 

    Google Scholar 
    Virta L, Gammal J, Järnström M, Bernard G, Soininen J, Norkko J, et al. The diversity of benthic diatoms affects ecosystem productivity in heterogeneous coastal environments. Ecology. 2019;100:e02765.Article 

    Google Scholar 
    Malviya S, Scalco E, Audic S, Vincent F, Veluchamy A, Poulain J, et al. Insights into global diatom distribution and diversity in the world’s ocean. Proc Natl Acad Sci USA. 2016;113:E1516–25.CAS 
    Article 

    Google Scholar 
    Forster D, Dunthorn M, Mahe F, Dolan JR, Audic S, Bass D, et al. Benthic protists: the under-charted majority. Fems Microbiol Ecol. 2016;92:fiw120.Article 

    Google Scholar 
    Fonseca VG, Carvalho GR, Nichols B, Quince C, Johnson HF, Neill SP, et al. Metagenetic analysis of patterns of distribution and diversity of marine meiobenthic eukaryotes. Glob Ecol Biogeogr. 2014;23:1293–302.Article 

    Google Scholar 
    O’Malley MA. The nineteenth century roots of ‘everything is everywhere’. Nat Rev Microbiol. 2007;5:647–51.Article 

    Google Scholar 
    Pasotti F, Manini E, Giovannelli D, Wölfl A-C, Monien D, Verleyen E, et al. Antarctic shallow water benthos in an area of recent rapid glacier retreat. Mar Ecol. 2015;36:716–33.Article 

    Google Scholar 
    Molari M, Janssen F, Vonnahme TR, Wenzhöfer F, Boetius A. The contribution of microbial communities in polymetallic nodules to the diversity of the deep-sea microbiome of the Peru Basin (4130–4198 m depth). Biogeosciences. 2020;17:3203–22.CAS 
    Article 

    Google Scholar 
    Signori CN, Thomas F, Enrich-Prast A, Pollery RCG, Sievert SM. Microbial diversity and community structure across environmental gradients in Bransfield Strait, Western Antarctic Peninsula. Front Microbiol. 2014;5:647.Article 

    Google Scholar 
    Ozturk RC, Feyzioglu AM, Altinok I. Prokaryotic community and diversity in coastal surface waters along the Western Antarctic Peninsula. Pol Sci. 2021;31:100764.Article 

    Google Scholar 
    Ghiglione JF, Murray AE. Pronounced summer to winter differences and higher wintertime richness in coastal Antarctic marine bacterioplankton. Environ Microbiol. 2012;14:617–29.CAS 
    Article 

    Google Scholar 
    Luria CM, Ducklow HW, Amaral-Zettler LA. Marine bacterial, archaeal and eukaryotic diversity and community structure on the continental shelf of the western Antarctic Peninsula. Aquat Microbial Ecol. 2014;73:107–21.Article 

    Google Scholar 
    Cao S, He J, Zhang F, Lin L, Gao Y, Zhou Q. Diversity and community structure of bacterioplankton in surface waters off the northern tip of the Antarctic Peninsula. Pol Res. 2019;38:3491.Article 

    Google Scholar 
    Walsh EA, Kirkpatrick JB, Rutherford SD, Smith DC, Sogin M, D’Hondt S. Bacterial diversity and community composition from seasurface to subseafloor. ISME J. 2016;10:979–89.Article 

    Google Scholar 
    Kiko R, Werner I, Wittmann A. Osmotic and ionic regulation in response to salinity variations and cold resistance in the Arctic under-ice amphipod Apherusa glacialis. Pol Biol. 2009;32:393–8.Article 

    Google Scholar 
    Zeppilli D, Leduc D, Fontanier C, Fontaneto D, Fuchs S, Gooday AJ, et al. Characteristics of meiofauna in extreme marine ecosystems: a review. Mar Biodivers. 2018;48:35–71.Article 

    Google Scholar 
    Arnosti C, Joergensen BB, Sagemann J, Thamdrup B. Temperature dependence of microbial degradation of organic matter in marine sediments: polysaccharide hydrolysis, oxygen consumption, and sulfate reduction. Mar Ecol Prog Ser. 1998;165:59–70.CAS 
    Article 

    Google Scholar 
    Fabiano M, Danovaro R. Enzymatic activity, bacterial distribution, and organic matter composition in sediments of the ross sea (Antarctica). Appl Environ Microbiol. 1998;64:3838–45.CAS 
    Article 

    Google Scholar 
    Kujawinski EB, Longnecker K, Barott KL, Weber RJM, Kido Soule, MC. Microbial community structure affects marine dissolved organic matter composition. Front Mar Sci. 2016;3:45.Article 

    Google Scholar 
    Barrett JE, Virginia RA, Hopkins DW, Aislabie J, Bargagli R, Bockheim JG, et al. Terrestrial ecosystem processes of Victoria Land, Antarctica. Soil Biol Biochem. 2006;38:3019–34.CAS 
    Article 

    Google Scholar 
    Ganzert L, Lipski A, Hubberten H-W, Wagner D. The impact of different soil parameters on the community structure of dominant bacteria from nine different soils located on Livingston Island, South Shetland Archipelago, Antarctica. Fems Microbiol Ecol. 2011;76:476–91.CAS 
    Article 

    Google Scholar 
    Rusch A, Huettel M, Reimers CE, Taghon GL, Fuller CM. Activity and distribution of bacterial populations in Middle Atlantic Bight shelf sands. Fems Microbiol Ecol. 2003;44:89–100.CAS 
    Article 

    Google Scholar 
    Hemkemeyer M, Dohrmann AB, Christensen BT, Tebbe CC. Bacterial preferences for specific soil particle size fractions revealed by community analyses. Front Microbiol. 2018;9:149.Article 

    Google Scholar 
    Giere O. Meiobenthology: the microscopic motile fauna of aquatic sediments. 2nd ed: Springer-Verlag Berlin Heidelberg; 2009. 527 p.Fonseca VG, Carvalho GR, Sung W, Johnson HF, Power DM, Neill SP, et al. Second-generation environmental sequencing unmasks marine metazoan biodiversity. Nat Commun. 2010;1:98.Article 

    Google Scholar 
    Pitcher RC, Lawton P, Ellis N, Smith SJ, Incze LS, Wei C-L, et al. Exploring the role of environmental variables in shaping patterns of seabed biodiversity composition in regional-scale ecosystems. J Appl Ecol. 2012;49:670–9.Article 

    Google Scholar 
    Rose A, Ingels J, Raes M, Vanreusel A, Arbizu PM. Long-term iceshelf-covered meiobenthic communities of the Antarctic continental shelf resemble those of the deep sea. Heidelberg: Springer; 2014. 743–62 p.Gonçalves-Araujo R, de Souza MS, Tavano VM, Garcia CAE. Influence of oceanographic features on spatial and interannual variability of phytoplankton in the Bransfield Strait, Antarctica. J Mar Syst. 2015;142:1–15.Article 

    Google Scholar 
    Learman DR, Henson MW, Thrash JC, Temperton B, Brannock PM, Santos SR, et al. Biogeochemical and microbial variation across 5500 km of Antarctic surface sediment implicates organic matter as a driver of benthic community structure. Front Microbiol. 2016;7:284.Article 

    Google Scholar 
    Ghiglione JF, Galand PE, Pommier T, Pedros-Alio C, Maas EW, Bakker K, et al. Pole-to-pole biogeography of surface and deep marine bacterial communities. Proc Natl Acad Sci USA. 2012;109:17633–8.CAS 
    Article 

    Google Scholar 
    Rosli N, Leduc D, Rowden A, Probert P. Review of recent trends in ecological studies of deep-sea meiofauna, with focus on patterns and processes at small to regional spatial scales. Mar Biodivers. 2017;48:13–34.Article 

    Google Scholar 
    Ruff SE, Probandt D, Zinkann A-C, Iversen M, Klaas C, Schwabe L, et al. Indications for algae-degrading benthic microbial communities in deep-sea sediments along the Antarctic Polar Front. Deep Sea Res Part II: Top Stud Oceanogr. 2014;108:6–16.Article 

    Google Scholar 
    El-Serehy HA, Al-Rasheid KA, Al-Misned FA, Al-Talasat AA, Gewik MM. Microbial-meiofaunal interrelationships in coastal sediments of the Red Sea. Saudi J Biol Sci. 2016;23:327–34.CAS 
    Article 

    Google Scholar 
    Danovaro R, Company JB, Corinaldesi C, D’Onghia G, Galil B, Gambi C, et al. Deep-sea biodiversity in the Mediterranean Sea: the known, the unknown, and the unknowable. PLoS ONE. 2010;5:e11832.Article 

    Google Scholar 
    Mussmann M, Pjevac P, Kruger K, Dyksma S. Genomic repertoire of the Woeseiaceae/JTB255, cosmopolitan and abundant core members of microbial communities in marine sediments. ISME J. 2017;11:1276–81.CAS 
    Article 

    Google Scholar 
    Hinger I, Pelikan C, Mußmann M. Role of the ubiquitous bacterial family Woeseiaceae for N2O production in marine sediments. Geophys Res Abstracts. 2019;21:17441.
    Google Scholar 
    Hoffmann K, Bienhold C, Buttigieg PL, Knittel K, Laso-Pérez R, Rapp JZ, et al. Diversity and metabolism of Woeseiales bacteria, global members of marine sediment communities. ISME J. 2020;14:1042–56.CAS 
    Article 

    Google Scholar 
    Mare MF. A study of a marine benthic community with special reference to the microorganisms. J Mar Biol Assoc UK. 1942;25:517–54.Article 

    Google Scholar 
    Bott TL, Borchardt MA. Grazing of protozoa, bacteria, and diatoms by Meiofauna in lotic epibenthic communities. J North Am Bentholog Soc. 1999;18:499–513.Article 

    Google Scholar 
    Griffiths HJ. Antarctic marine biodiversity-what do we know about the distribution of life in the Southern Ocean? PLoS ONE. 2010;5:e11683.Article 

    Google Scholar 
    Convey P, Chown SL, Clarke A, Barnes DKA, Bokhorst S, Cummings V, et al. The spatial structure of Antarctic biodiversity. Ecol Monogr. 2014;84:203–44.Article 

    Google Scholar 
    Li L, Ma ZS. Species sorting and neutral theory analyses reveal archaeal and bacterial communities are assembled differently in hot springs. Front Bioeng Biotechnol. 2020;8:464.Article 

    Google Scholar 
    Lee JE, Buckley HL, Etienne RS, Lear G. Both species sorting and neutral processes drive assembly of bacterial communities in aquatic microcosms. Fems Microbiol Ecol. 2013;86:288–302.CAS 
    Article 

    Google Scholar 
    Gansfort B, Fontaneto D, Zhai M. Meiofauna as a model to test paradigms of ecological metacommunity theory. Hydrobiologia. 2020;847:2645–63.Article 

    Google Scholar 
    Convey P, Peck LS. Antarctic environmental change and biological responses. Sci Adv. 2019;5:eaaz0888.CAS 
    Article 

    Google Scholar  More

  • in

    Contrasting diversity patterns of prokaryotes and protists over time and depth at the San-Pedro Ocean Time series

    Brown MV, Philip GK, Bunge JA, Smith MC, Bissett A, Lauro FM, et al. Microbial community structure in the North Pacific ocean. ISME J. 2009;3:1374–86.CAS 
    Article 

    Google Scholar 
    Chénard C, Wijaya W, Vaulot D, dos Santos AL, Martin P, Kaur A, et al. Temporal and spatial dynamics of Bacteria, Archaea and protists in equatorial coastal waters. Sci Rep. 2019;9:1–13.Article 

    Google Scholar 
    Yeh YC, McNichol J, Needham DM, Fichot EB, Berdjeb L, Fuhrman JA. Comprehensive single‐PCR 16S and 18S rRNA community analysis validated with mock communities, and estimation of sequencing bias against 18S. Environ Microbiol. 2021;23:2340–3250.Article 

    Google Scholar 
    Needham DM, Fuhrman JA. Pronounced daily succession of phytoplankton, archaea and bacteria following a spring bloom. Nat. Microbiol. 2016;1:16005.CAS 
    Article 

    Google Scholar 
    Parada AE, Needham DM, Fuhrman JA. Every base matters: assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples. Environ Microbiol. 2016;18:1403–14.CAS 
    Article 

    Google Scholar 
    Needham DM, Fichot EB, Wang E, Berdjeb L, Cram JA, Fichot CG, et al. Dynamics and interactions of highly resolved marine plankton via automated high-frequency sampling. ISME J. 2018;12:2417.CAS 
    Article 

    Google Scholar 
    Steinberg DK, Carlson CA, Bates NR, Johnson RJ, Michaels AF, Knap AH. Overview of the US JGOFS Bermuda Atlantic Time-series Study (BATS): a decade-scale look at ocean biology and biogeochemistry. Deep Sea Res Part II Top Stud Oceanogr. 2001;48:1405–47.CAS 
    Article 

    Google Scholar 
    Karl DM, Church MJ. Microbial oceanography and the Hawaii Ocean Time-series programme. Nat Rev Microbiol. 2014;12:699–713.CAS 
    Article 

    Google Scholar 
    Mestre M, Höfer J, Sala MM, Gasol JM. Seasonal variation of bacterial diversity along the marine particulate matter continuum. Front Microbiol. 2020;11:1590.Article 

    Google Scholar 
    Cram JA, Chow C-ET, Sachdeva R, Needham DM, Parada AE, Steele JA, et al. Seasonal and interannual variability of the marine bacterioplankton community throughout the water column over ten years. ISME J. 2015;9:563–80.Article 

    Google Scholar 
    Berelson WM. The flushing of two deep‐sea basins, southern California borderland. Limnol Oceanogr. 1991;36:1150–66.CAS 
    Article 

    Google Scholar 
    Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. DADA2: high-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13:581–3.CAS 
    Article 

    Google Scholar 
    Traving SJ, Kellogg CT, Ross T, McLaughlin R, Kieft B, Ho GY, et al. Prokaryotic responses to a warm temperature anomaly in northeast subarctic Pacific waters. Commun Biology. 2021;4:1–12.Article 

    Google Scholar 
    Butler TM, Wilhelm A-C, Dwyer AC, Webb PN, Baldwin AL, Techtmann SM. Microbial community dynamics during lake ice freezing. Scient Rep. 2019;9:1–11.
    Google Scholar 
    LeBrun ES, King RS, Back JA, Kang S. Microbial community structure and function decoupling across a phosphorus gradient in streams. Microb Ecol. 2018;75:64–73.CAS 
    Article 

    Google Scholar 
    McNichol J, Berube PM, Biller SJ, Fuhrman JA. Evaluating and improving small subunit rRNA PCR primer coverage for bacteria, archaea, and eukaryotes using metagenomes from global ocean surveys. Msystems. 2021;6:e00565–21.CAS 
    Article 

    Google Scholar 
    De Bie T, De Meester L, Brendonck L, Martens K, Goddeeris B, Ercken D, et al. Body size and dispersal mode as key traits determining metacommunity structure of aquatic organisms. Ecol Lett. 2012;15:740–7.Article 

    Google Scholar 
    Soininen J, Korhonen JJ, Karhu J, Vetterli A. Disentangling the spatial patterns in community composition of prokaryotic and eukaryotic lake plankton. Limnol. Oceanogr. 2011;56:508–20.Article 

    Google Scholar 
    Wu W, Lu H-P, Sastri A, Yeh Y-C, Gong G-C, Chou W-C, et al. Contrasting the relative importance of species sorting and dispersal limitation in shaping marine bacterial versus protist communities. ISME J. 2018;12:485–94.Article 

    Google Scholar 
    Kraemer S, Ramachandran A, Colatriano D, Lovejoy C, Walsh DA. Diversity and biogeography of SAR11 bacteria from the Arctic Ocean. ISME J. 2020;14:79–90.Article 

    Google Scholar 
    Tsementzi D, Wu J, Deutsch S, Nath S, Rodriguez-R LM, Burns AS, et al. SAR11 bacteria linked to ocean anoxia and nitrogen loss. Nature. 2016;536:179–83.CAS 
    Article 

    Google Scholar 
    Brown MV, Lauro FM, DeMaere MZ, Muir L, Wilkins D, Thomas T, et al. Global biogeography of SAR11 marine bacteria. Mol Syst Biol. 2012;8:595.Article 

    Google Scholar 
    Giovannoni SJ. SAR11 bacteria: the most abundant plankton in the oceans. Ann Rev Mar Sci. 2017;9:231–55.Article 

    Google Scholar 
    Thrash JC, Temperton B, Swan BK, Landry ZC, Woyke T, DeLong EF, et al. Single-cell enabled comparative genomics of a deep ocean SAR11 bathytype. ISME J. 2014;8:1440–51.Article 

    Google Scholar 
    Fernández-Gomez B, Richter M, Schüler M, Pinhassi J, Acinas SG, González JM, et al. Ecology of marine Bacteroidetes: a comparative genomics approach. ISME J. 2013;7:1026–37.Article 

    Google Scholar 
    Countway PD, Vigil PD, Schnetzer A, Moorthi SD, Caron DA. Seasonal analysis of protistan community structure and diversity at the USC Microbial Observatory (San Pedro Channel, North Pacific Ocean). Limnol Oceanogr. 2010;55:2381–96.Article 

    Google Scholar 
    Kim DY, Countway PD, Jones AC, Schnetzer A, Yamashita W, Tung C, et al. Monthly to interannual variability of microbial eukaryote assemblages at four depths in the eastern North Pacific. ISME J. 2014;8:515–30.Article 

    Google Scholar 
    Parris DJ, Ganesh S, Edgcomb VP, DeLong EF, Stewart FJ. Microbial eukaryote diversity in the marine oxygen minimum zone off northern Chile. Front Microbiol. 2014;5:543.Article 

    Google Scholar 
    Orsi W, Song YC, Hallam S, Edgcomb V. Effect of oxygen minimum zone formation on communities of marine protists. ISME J. 2012;6:1586–601.CAS 
    Article 

    Google Scholar 
    Leibold MA, Holyoak M, Mouquet N, Amarasekare P, Chase JM, Hoopes MF, et al. The metacommunity concept: a framework for multi‐scale community ecology. Ecol Lett. 2004;7:601–13.Article 

    Google Scholar 
    Fuhrman JA, Hewson I, Schwalbach MS, Steele JA, Brown MV, Naeem S. Annually reoccurring bacterial communities are predictable from ocean conditions. Proc Natl Acad Sci USA. 2006;103:13104–9.CAS 
    Article 

    Google Scholar 
    Chow C-ET, Sachdeva R, Cram JA, Steele JA, Needham DM, Patel A, et al. Temporal variability and coherence of euphotic zone bacterial communities over a decade in the Southern California Bight. ISME J. 2013;7:2259–73.CAS 
    Article 

    Google Scholar 
    Parada AE, Fuhrman JA. Marine archaeal dynamics and interactions with the microbial community over 5 years from surface to seafloor. ISME J. 2017;11:2510–25.Article 

    Google Scholar 
    Mestre M, Ruiz-González C, Logares R, Duarte CM, Gasol JM, Sala MM. Sinking particles promote vertical connectivity in the ocean microbiome. Proc Natl Acad Sci USA. 2018;115:E6799–E807.CAS 
    Article 

    Google Scholar 
    Mestre M, Ferrera I, Borrull E, Ortega‐Retuerta E, Mbedi S, Grossart HP, et al. Spatial variability of marine bacterial and archaeal communities along the particulate matter continuum. Mol Ecol. 2017;26:6827–40.CAS 
    Article 

    Google Scholar 
    Wilson B, Müller O, Nordmann E-L, Seuthe L, Bratbak G, Øvreås L. Changes in marine prokaryote composition with season and depth over an Arctic polar year. Front Mar Sci. 2017;4:95.
    Google Scholar 
    Treusch AH, Vergin KL, Finlay LA, Donatz MG, Burton RM, Carlson CA, et al. Seasonality and vertical structure of microbial communities in an ocean gyre. ISME J. 2009;3:1148–63.Article 

    Google Scholar 
    Zinger L, Amaral-Zettler LA, Fuhrman JA, Horner-Devine MC, Huse SM, Welch DBM, et al. Global patterns of bacterial beta-diversity in seafloor and seawater ecosystems. PLoS ONE. 2011;6:e24570.CAS 
    Article 

    Google Scholar 
    DeLong EF, Preston CM, Mincer T, Rich V, Hallam SJ, Frigaard N-U, et al. Community genomics among stratified microbial assemblages in the ocean’s interior. Science. 2006;311:496–503.CAS 
    Article 

    Google Scholar 
    Agogué H, Lamy D, Neal PR, Sogin ML, Herndl GJ. Water mass‐specificity of bacterial communities in the North Atlantic revealed by massively parallel sequencing. Mol. Ecol. 2011;20:258–74.Article 

    Google Scholar 
    Walsh EA, Kirkpatrick JB, Rutherford SD, Smith DC, Sogin M, D’Hondt S. Bacterial diversity and community composition from seasurface to subseafloor. ISME J. 2016;10:979–89.Article 

    Google Scholar 
    Reji L, Tolar BB, Chavez FP, Francis CA. Depth-differentiation and seasonality of planktonic microbial assemblages in the Monterey Bay upwelling system. Front Microbiol. 2020;11:1075.Article 

    Google Scholar 
    Milici M, Vital M, Tomasch J, Badewien TH, Giebel HA, Plumeier I, et al. Diversity and community composition of particle‐associated and free‐living bacteria in mesopelagic and bathypelagic Southern Ocean water masses: Evidence of dispersal limitation in the Bransfield Strait. Limnol Oceanogr. 2017;62:1080–95.Article 

    Google Scholar 
    Crespo BG, Pommier T, Fernández‐Gómez B, Pedrós‐Alió C. Taxonomic composition of the particle‐attached and free‐living bacterial assemblages in the Northwest Mediterranean Sea analyzed by pyrosequencing of the 16S rRNA. Microbiologyopen. 2013;2:541–52.CAS 
    Article 

    Google Scholar 
    Ganesh S, Parris DJ, DeLong EF, Stewart FJ. Metagenomic analysis of size-fractionated picoplankton in a marine oxygen minimum zone. ISME J. 2014;8:187–211.CAS 
    Article 

    Google Scholar 
    Ghiglione J-F, Galand PE, Pommier T, Pedrós-Alió C, Maas EW, Bakker K, et al. Pole-to-pole biogeography of surface and deep marine bacterial communities. Proc Natl Acad Sci USA. 2012;109:17633–8.CAS 
    Article 

    Google Scholar 
    Murillo AA, Ramírez-Flandes S, DeLong EF, Ulloa O. Enhanced metabolic versatility of planktonic sulfur-oxidizing γ-proteobacteria in an oxygen-deficient coastal ecosystem. Front Mar Sci. 2014;1:18.Article 

    Google Scholar 
    Hawley AK, Nobu MK, Wright JJ, Durno WE, Morgan-Lang C, Sage B, et al. Diverse Marinimicrobia bacteria may mediate coupled biogeochemical cycles along eco-thermodynamic gradients. Nat Commun. 2017;8:1–10.CAS 
    Article 

    Google Scholar 
    Santoro AE, Buchwald C, McIlvin MR, Casciotti KL. Isotopic signature of N2O produced by marine ammonia-oxidizing archaea. Science. 2011;333:1282–5.CAS 
    Article 

    Google Scholar 
    Aldunate M, De la Iglesia R, Bertagnolli AD, Ulloa O. Oxygen modulates bacterial community composition in the coastal upwelling waters off central Chile. Deep Sea Res Part II Top Stud Oceanogr. 2018;156:68–79.CAS 
    Article 

    Google Scholar 
    Duret MT, Lampitt RS, Lam P. Prokaryotic niche partitioning between suspended and sinking marine particles. Environ Microbiol Rep. 2019;11:386–400.CAS 
    Article 

    Google Scholar 
    Lindh MV, Sjöstedt J, Andersson AF, Baltar F, Hugerth LW, Lundin D, et al. Disentangling seasonal bacterioplankton population dynamics by high‐frequency sampling. Environ Microbiol. 2015;17:2459–76.Article 

    Google Scholar 
    Teeling H, Fuchs BM, Bennke CM, Krueger K, Chafee M, Kappelmann L, et al. Recurring patterns in bacterioplankton dynamics during coastal spring algae blooms. elife. 2016;5:e11888.Article 

    Google Scholar 
    Buchan A, LeCleir GR, Gulvik CA, González JM. Master recyclers: features and functions of bacteria associated with phytoplankton blooms. Nat Rev Microbiol. 2014;12:686–98.CAS 
    Article 

    Google Scholar 
    Giovannoni SJ, Tripp HJ, Givan S, Podar M, Vergin KL, Baptista D, et al. Genome streamlining in a cosmopolitan oceanic bacterium. Science. 2005;309:1242–5.CAS 
    Article 

    Google Scholar 
    Cram JA, Xia LC, Needham DM, Sachdeva R, Sun F, Fuhrman JA. Cross-depth analysis of marine bacterial networks suggests downward propagation of temporal changes. ISME J. 2015;9:2573–86.Article 

    Google Scholar 
    Salazar G, Cornejo‐Castillo FM, Borrull E, Díez‐Vives C, Lara E, Vaqué D, et al. Particle‐association lifestyle is a phylogenetically conserved trait in bathypelagic prokaryotes. Mol Ecol. 2015;24:5692–706.Article 

    Google Scholar 
    Mohit V, Archambault P, Toupoint N, Lovejoy C. Phylogenetic differences in attached and free-living bacterial communities in a temperate coastal lagoon during summer, revealed via high-throughput 16S rRNA gene sequencing. Appl Environ Microbiol. 2014;80:2071–83.Article 

    Google Scholar 
    Rieck A, Herlemann DP, Jürgens K, Grossart H-P. Particle-associated differ from free-living bacteria in surface waters of the Baltic Sea. Front Microbiol. 2015;6:1297.Article 

    Google Scholar 
    Pachiadaki MG, Brown JM, Brown J, Bezuidt O, Berube PM, Biller SJ, et al. Charting the complexity of the marine microbiome through single-cell genomics. Cell. 2019;179:1623–35. e11.CAS 
    Article 

    Google Scholar 
    Giner CR, Pernice MC, Balagué V, Duarte CM, Gasol JM, Logares R, et al. Marked changes in diversity and relative activity of picoeukaryotes with depth in the world ocean. ISME J. 2020;14:437–49.Article 

    Google Scholar 
    Countway PD, Gast RJ, Dennett MR, Savai P, Rose JM, Caron DA. Distinct protistan assemblages characterize the euphotic zone and deep sea (2500 m) of the western North Atlantic (Sargasso Sea and Gulf Stream). Environ Microbiol. 2007;9:1219–32.CAS 
    Article 

    Google Scholar 
    Ollison GA, Hu SK, Mesrop LY, DeLong EF, Caron DA. Come rain or shine: depth not season shapes the active protistan community at station ALOHA in the North Pacific Subtropical Gyre. Deep Sea Res Part I Oceanogr Res Pap. 2021;170:103494.Article 

    Google Scholar 
    Schnetzer A, Moorthi SD, Countway PD, Gast RJ, Gilg IC, Caron DA. Depth matters: microbial eukaryote diversity and community structure in the eastern North Pacific revealed through environmental gene libraries. Deep Sea Res Part I Oceanogr Res Pap. 2011;58:16–26.Article 

    Google Scholar 
    Martin P, Allen JT, Cooper MJ, Johns DG, Lampitt RS, Sanders R, et al. Sedimentation of acantharian cysts in the Iceland Basin: strontium as a ballast for deep ocean particle flux, and implications for acantharian reproductive strategies. Limnol Oceanogr. 2010;55:604–14.CAS 
    Article 

    Google Scholar 
    Lampitt R, Salter I, Johns D. Radiolaria: Major exporters of organic carbon to the deep ocean. Glob Biogeochem Cycle. 2009;23:GB1010.Article 

    Google Scholar 
    Skovgaard A, Massana R, Balague V, Saiz E. Phylogenetic position of the copepod-infesting parasite Syndinium turbo (Dinoflagellata, Syndinea). Protist. 2005;156:413–23.CAS 
    Article 

    Google Scholar 
    Bachvaroff TR, Kim S, Guillou L, Delwiche CF, Coats DW. Molecular diversity of the syndinean genus Euduboscquella based on single-cell PCR analysis. Appl Environ Microbiol. 2012;78:334–45.CAS 
    Article 

    Google Scholar 
    Guillou L, Viprey M, Chambouvet A, Welsh R, Kirkham A, Massana R, et al. Widespread occurrence and genetic diversity of marine parasitoids belonging to Syndiniales (Alveolata). Environ Microbiol. 2008;10:3349–65.CAS 
    Article 

    Google Scholar 
    Berdjeb L, Parada A, Needham DM, Fuhrman JA. Short-term dynamics and interactions of marine protist communities during the spring–summer transition. ISME J. 2018;12:1907.Article 

    Google Scholar 
    Hu SK, Connell PE, Mesrop LY, Caron DA. A hard day’s night: diel shifts in microbial eukaryotic activity in the north pacific subtropical gyre. Front Mar Sci. 2018;5:351.Article 

    Google Scholar 
    Clarke LJ, Bestley S, Bissett A, Deagle BE. A globally distributed Syndiniales parasite dominates the Southern Ocean micro-eukaryote community near the sea-ice edge. ISME J. 2019;13:734–7.CAS 
    Article 

    Google Scholar 
    De Vargas C, Audic S, Henry N, Decelle J, Mahé F, Logares R, et al. Eukaryotic plankton diversity in the sunlit ocean. Science. 2015;348:1261605.Article 

    Google Scholar 
    Pernice MC, Giner CR, Logares R, Perera-Bel J, Acinas SG, Duarte CM, et al. Large variability of bathypelagic microbial eukaryotic communities across the world’s oceans. ISME J. 2016;10:945–58.Article 

    Google Scholar 
    Crutsinger GM, Collins MD, Fordyce JA, Gompert Z, Nice CC, Sanders NJ. Plant genotypic diversity predicts community structure and governs an ecosystem process. Science. 2006;313:966–8.CAS 
    Article 

    Google Scholar 
    Hawkins BA, Porter EE. Does herbivore diversity depend on plant diversity? The case of California butterflies. Am Nat. 2003;161:40–9.Article 

    Google Scholar 
    Scherber C, Eisenhauer N, Weisser WW, Schmid B, Voigt W, Fischer M, et al. Bottom-up effects of plant diversity on multitrophic interactions in a biodiversity experiment. Nature. 2010;468:553–6.CAS 
    Article 

    Google Scholar 
    Yang JW, Wu W, Chung C-C, Chiang K-P, Gong G-C, Hsieh C-h Predator and prey biodiversity relationship and its consequences on marine ecosystem functioning—interplay between nanoflagellates and bacterioplankton. ISME J. 2018;12:1532–42.Article 

    Google Scholar 
    Fuhrman JA, Comeau DE, Hagström Å, Chan AM. Extraction from natural planktonic microorganisms of DNA suitable for molecular biological studies. Appl Environ Microbiol. 1988;54:1426–9.CAS 
    Article 

    Google Scholar 
    Lie AA, Kim DY, Schnetzer A, Caron DA. Small-scale temporal and spatial variations in protistan community composition at the San Pedro Ocean Time-series station off the coast of southern California. Aquat Microb Ecol. 2013;70:93–110.Article 

    Google Scholar 
    Yeh Y-C, Needham DM, Sieradzki ET, Fuhrman JA. Taxon disappearance from microbiome analysis reinforces the value of mock communities as a standard in every sequencing run. MSystems. 2018;3:e00023–18.Article 

    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. Nucl Acids Res. 2013;41:D590–D6.CAS 
    Article 

    Google Scholar 
    Guillou L, Bachar D, Audic S, Bass D, Berney C, Bittner L, et al. The Protist Ribosomal Reference database (PR2): a catalog of unicellular eukaryote small sub-unit rRNA sequences with curated taxonomy. Nucl Acids Res. 2013;41:D579–D604.
    Google Scholar 
    Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol. 2019;37:852–7.CAS 
    Article 

    Google Scholar 
    Decelle J, Romac S, Stern RF, Bendif EM, Zingone A, Audic S, et al. Phyto REF: a reference database of the plastidial 16S rRNA gene of photosynthetic eukaryotes with curated taxonomy. Mol Ecol Resour. 2015;15:1435–45.CAS 
    Article 

    Google Scholar 
    Oksanen J, Blanchet F, Friendly M, Kindt R, Legendre P, McGlinn D, et al. Vegan: community ecology package. R package version 2.5-7. 2020. https://CRAN.R-project.org/package=vegan.Wickham H. ggplot2-elegant graphics for data analysis. Cham, Switzerland: Springer International Publishing; 2016.Kolde R. Pheatmap: pretty heatmaps. R Package Version. 2012;1:726.
    Google Scholar 
    Schloerke B, Crowley J, Cook D. Package ‘GGally’. Extension to ‘ggplot2’See. 2018;713. More

  • in

    Deforestation-induced climate change reduces carbon storage in remaining tropical forests

    Saatchi, S. S. et al. Benchmark map of forest carbon stocks in tropical regions across three continents. Proc. Natl Acad. Sci. USA 108, 9899–9904 (2011).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Baccini, A. et al. Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps. Nat. Clim. Chang 2, 182–185 (2012).ADS 
    CAS 

    Google Scholar 
    Santoro, M. et al. The global forest above-ground biomass pool for 2010 estimated from high-resolution satellite observations. Earth Syst. Sci. Data 13, 3927–3950 (2021).Cox, P. M. et al. Sensitivity of tropical carbon to climate change constrained by carbon dioxide variability. Nature 494, 341–344 (2013).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Davidson, E. A. et al. The Amazon basin in transition. Nature 481, 321–328 (2012).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Ramankutty, N. & Foley, J. A. Estimating historical changes in global land cover: croplands from 1700 to 1992. Glob. Biogeochem. Cy. 13, 997–1027 (1999).ADS 
    CAS 

    Google Scholar 
    Pongratz, J., Reick, C., Raddatz, T. & Claussen, M. A reconstruction of global agricultural areas and land cover for the last millennium. Glob. Biogeochem. Cy. 22, GB3018 (2008).ADS 

    Google Scholar 
    Kaplan, J. O. et al. Holocene carbon emissions as a result of anthropogenic land cover change. Holocene 21, 775–791 (2011).ADS 

    Google Scholar 
    Fearnside, P. M. Deforestation in Brazilian Amazonia: history, rates, and consequences. Conserv Biol. 19, 680–688 (2005).
    Google Scholar 
    van Marle, M. J. et al. Fire and deforestation dynamics in Amazonia (1973–2014). Glob. Biogeochem. Cy 31, 24–38 (2017).
    Google Scholar 
    Houghton, R. A. & Nassikas, A. A. Global and regional fluxes of carbon from land use and land cover change 1850–2015. Glob. Biogeochem. Cy 31, 456–472 (2017).ADS 
    CAS 

    Google Scholar 
    Houghton, R. A. Aboveground forest biomass and the global carbon balance. Glob. Change Biol. 11, 945–958 (2005).ADS 

    Google Scholar 
    Friedlingstein, P. et al. Global carbon budget 2020. Earth Syst. Sci. Data 12, 3269–3340 (2020).ADS 

    Google Scholar 
    Xu, L. et al. Changes in global terrestrial live biomass over the 21st century. Sci. Adv. 7, eabe9829 (2021).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Brando, P. M. et al. The gathering firestorm in southern Amazonia. Sci. Adv. 6, eaay1632 (2020).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Qin, Y. et al. Carbon loss from forest degradation exceeds that from deforestation in the Brazilian Amazon. Nat. Clim. Chang. 11, 442–448 (2021).ADS 

    Google Scholar 
    Erb, K. H. et al. Unexpectedly large impact of forest management and grazing on global vegetation biomass. Nature 553, 73–76 (2018).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Bonan, G. B. Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320, 1444–1449 (2008).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Davin, E. L. & de Noblet-Ducoudré, N. Climatic impact of global-scale deforestation: radiative versus nonradiative processes. J. Clim. 23, 97–112 (2010).ADS 

    Google Scholar 
    Li, Y. et al. Local cooling and warming effects of forests based on satellite observations. Nat. Commun. 6, 1–8 (2015).ADS 

    Google Scholar 
    Silvério, D. V. et al. Agricultural expansion dominates climate changes in southeastern Amazonia: the overlooked non-GHG forcing. Environ. Res. Lett. 10, 104015 (2015).
    Google Scholar 
    Betts, R. Implications of land ecosystem-atmosphere interactions for strategies for climate change adaptation and mitigation. Tellus Ser. B-Chem. Phys. Meteorol. 59, 602–615 (2007).ADS 

    Google Scholar 
    Gibbard, S., Caldeira, K., Bala, G., Phillips, T. J. & Wickett, M. Climate effects of global land cover change. Geophys. Res. Lett. 32, L23705 (2005).ADS 

    Google Scholar 
    Bala, G. et al. Combined climate and carbon-cycle effects of large-scale deforestation. Proc. Natl Acad. Sci. USA 104, 6550–6555 (2007).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bathiany, S., Claussen, M., Brovkin, V., Raddatz, T. & Gayler, V. Combined biogeophysical and biogeochemical effects of large-scale forest cover changes in the MPI earth system model. Biogeosciences 7, 1383–1399 (2010).ADS 
    CAS 

    Google Scholar 
    Devaraju, N., Bala, G. & Modak, A. Effects of large-scale deforestation on precipitation in the monsoon regions: Remote versus local effects. Proc. Natl Acad. Sci. USA 112, 3257–3262 (2015).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Devaraju, N., Bala, G. & Nemani, R. Modelling the influence of land‐use changes on biophysical and biochemical interactions at regional and global scales. Plant Cell Environ. 38, 1931–1946 (2015).CAS 
    PubMed 

    Google Scholar 
    Henderson-Sellers, A. & Gornitz, V. Possible climatic impacts of land cover transformations, with particular emphasis on tropical deforestation. Clim. Change 6, 231–257 (1984).ADS 

    Google Scholar 
    Dickinson, R. E. & Henderson‐Sellers, A. Modelling tropical deforestation: a study of GCM land‐surface parametrizations. Q. J. R. Meteorol. Soc. 114, 439–462 (1988).ADS 

    Google Scholar 
    Zhang, H., Henderson-Sellers, A. & McGuffie, K. Impacts of tropical deforestation. Part I: process analysis of local climatic change. J. Clim. 9, 1497–1517 (1996).ADS 

    Google Scholar 
    Costa, M. H. & Foley, J. A. Combined effects of deforestation and doubled atmospheric CO2 concentrations on the climate of Amazonia. J. Clim. 13, 18–34 (2000).ADS 

    Google Scholar 
    Lawrence, D. & Vandecar, K. Effects of tropical deforestation on climate and agriculture. Nat. Clim. Chang. 5, 27–36 (2015).ADS 

    Google Scholar 
    Nobre, C. A., Sellers, P. J. & Shukla, J. Amazonian deforestation and regional climate change. J. Clim. 4, 957–988 (1991).ADS 

    Google Scholar 
    Gedney, N. & Valdes, P. J. The effect of Amazonian deforestation on the northern hemisphere circulation and climate. Geophys. Res. Lett. 27, 3053–3056 (2000).ADS 

    Google Scholar 
    Nobre, P., Malagutti, M., Urbano, D. F., de Almeida, R. A. & Giarolla, E. Amazon deforestation and climate change in a coupled model simulation. J. Clim. 22, 5686–5697 (2009).ADS 

    Google Scholar 
    Snyder, P. K. The influence of tropical deforestation on the Northern Hemisphere climate by atmospheric teleconnections. Earth Interact. 14, 1–34 (2010).
    Google Scholar 
    Spracklen, D. V., Baker, J. C. A., Garcia-Carreras, L. & Marsham, J. H. The effects of tropical vegetation on rainfall. Annu. Rev. Environ. Resour. 43, 193–218 (2018).
    Google Scholar 
    Leite-Filho, A. T., Soares-Filho, B. S., Davis, J. L., Abrahão, G. M. & Börner, J. Deforestation reduces rainfall and agricultural revenues in the Brazilian Amazon. Nat. Commun. 12, 1–7 (2021).
    Google Scholar 
    Baidya Roy, S. & Avissar, R. Impact of land use/land cover change on regional hydrometeorology in Amazonia. J. Geophys. Res. Atmos. 107, LBA-4 (2002).
    Google Scholar 
    Khanna, J., Medvigy, D., Fisch, G. & de Araújo Tiburtino Neves, T. T. Regional hydroclimatic variability due to contemporary deforestation in southern Amazonia and associated boundary layer characteristics. J. Geophys. Res. Atmos. 123, 3993–4014 (2018).ADS 

    Google Scholar 
    McGuffie, K., Henderson-Sellers, A., Zhang, H., Durbidge, T. B. & Pitman, A. J. Global climate sensitivity to tropical deforestation. Glob. Planet. Change 10, 97–128 (1995).ADS 

    Google Scholar 
    Zhang, H., Henderson-Sellers, A. & McGuffie, K. The compounding effects of tropical deforestation and greenhouse warming on climate. Clim. Change 49, 309–338 (2001).CAS 

    Google Scholar 
    Voldoire, A. & Royer, J. F. Climate sensitivity to tropical land surface changes with coupled versus prescribed SSTs. Clim. Dyn. 24, 843–862 (2005).
    Google Scholar 
    Mahmood, R. et al. Land cover changes and their biogeophysical effects on climate. Int. J. Climatol. 34, 929–953 (2014).
    Google Scholar 
    Kooperman, G. J. et al. Forest response to rising CO2 drives zonally asymmetric rainfall change over tropical land. Nat. Clim. Chang. 8, 434–440 (2018).ADS 

    Google Scholar 
    Doughty, C. E. & Goulden, M. L. Are tropical forests near a high temperature threshold? J. Geophys. Res. Biogeosci. 113, G00B07 (2008).ADS 

    Google Scholar 
    Sullivan, M. J. et al. Long-term thermal sensitivity of Earth’s tropical forests. Science 368, 869–874 (2020).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Wu, C. et al. Historical and future global burned area with changing climate and human demography. One Earth 4, 517–530 (2021).ADS 

    Google Scholar 
    Brando, P. M. et al. Abrupt increases in Amazonian tree mortality due to drought–fire interactions. Proc. Natl Acad. Sci. USA 111, 6347–6352 (2014).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Nobre, C. A. et al. Land-use and climate change risks in the Amazon and the need of a novel sustainable development paradigm. Proc. Natl Acad. Sci. USA 113, 10759–10768 (2016).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Trumbore, S., Brando, P. & Hartmann, H. Forest health and global change. Science 349, 814–818 (2015).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Green, J. K., Berry, J., Ciais, P., Zhang, Y. & Gentine, P. Amazon rainforest photosynthesis increases in response to atmospheric dryness. Sci. Adv. 6, eabb7232 (2020).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Numata, I. et al. Biomass collapse and carbon emissions from forest fragmentation in the Brazilian Amazon. J. Geophys. Res. Biogeosci. 115, G03027 (2010).ADS 

    Google Scholar 
    Junior, C. H. S. et al. Persistent collapse of biomass in Amazonian forest edges following deforestation leads to unaccounted carbon losses. Sci. Adv. 6, eaaz8360 (2020).ADS 

    Google Scholar 
    Lawrence, D. M. et al. The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6: rationale and experimental design. Geosci. Model Dev. 9, 2973–2998 (2016).ADS 

    Google Scholar 
    Friedlingstein, P. et al. Climate–carbon cycle feedback analysis: results from the C4MIP model intercomparison. J. Clim. 19, 3337–3353 (2006).ADS 

    Google Scholar 
    Wu, T. et al. The Beijing Climate Center climate system model (BCC-CSM): the main progress from CMIP5 to CMIP6. Geosci. Model Dev. 12, 1573–1600 (2019).ADS 

    Google Scholar 
    Swart, N. C. et al. The Canadian Earth System Model version 5 (CanESM5. 0.3). Geosci. Model Dev. 12, 4823–4873 (2019).ADS 
    CAS 

    Google Scholar 
    Danabasoglu, G. et al. The Community Earth System Model version 2 (CESM2). J. Adv. Model Earth Syst. 12, e2019MS001916 (2020).ADS 

    Google Scholar 
    Séférian, R. et al. Evaluation of CNRM Earth System Model, CNRM‐ESM2‐1: role of earth system processes in present‐day and future climate. J. Adv. Model Earth Syst. 11, 4182–4227 (2019).ADS 

    Google Scholar 
    Boucher, O. et al. Presentation and evaluation of the IPSL-CM6A-LR climate model. J. Adv. Model Earth Syst. 12, 1–52 (2020).
    Google Scholar 
    Kelley, M. et al. GISS‐E2. 1: configurations and climatology. J. Adv. Model Earth Syst. 12, e2019MS002025 (2020).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Sellar, A. A. et al. Implementation of UK Earth system models for CMIP6. J. Adv. Model Earth Syst. 12, e2019MS001946 (2020).ADS 

    Google Scholar 
    Mauritsen, T. et al. Developments in the MPI‐M Earth System Model version 1.2 (MPI‐ESM1. 2) and its response to increasing CO2. J. Adv. Model Earth Syst. 11, 998–1038 (2019).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Boysen, L. et al. Global climate response to idealized deforestation in CMIP6 models. Biogeosciences 17, 5615–5638 (2020).ADS 
    CAS 

    Google Scholar 
    Malhi, Y. et al. Exploring the likelihood and mechanism of a climate-change-induced dieback of the Amazon rainforest. Proc. Natl Acad. Sci. USA 106, 20610–20615 (2009).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Novick, K. A. et al. The increasing importance of atmospheric demand for ecosystem water and carbon fluxes. Nat. Clim. Chang. 6, 1023–1027 (2016).ADS 
    CAS 

    Google Scholar 
    Hurtt, G. C. et al. Harmonization of global land use change and management for the period 850–2100 (LUH2) for CMIP6. Geosci. Model Dev. 13, 5425–5464 (2020).ADS 
    CAS 

    Google Scholar 
    Ciais, P. et al. Carbon and other biogeochemical cycles. In Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. (eds Stocker et al.) 465–570 (Cambridge Univ Press, UK and USA, 2013).Arora, V. K. et al. Carbon–concentration and carbon–climate feedbacks in CMIP6 models and their comparison to CMIP5 models. Biogeosciences 17, 4173–4222 (2020).ADS 
    CAS 

    Google Scholar 
    Jones, C. D. et al. C4MIP–The coupled climate–carbon cycle model intercomparison project: experimental protocol for CMIP6. Geosci. Model Dev. 9, 2853–2880 (2016).ADS 
    CAS 

    Google Scholar 
    UNFCCC. Background paper for the Workshop on Reducing Emissions from Deforestation in Developing Countries, Part 1: Scientific, Socio-economic, Technical, and Methodological Issues Related to Deforestation in Developing Countries 30 August to 1 September, Rome, Italy. Working paper No. 1(a) (2006).Asner, G. P. Tropical forest carbon assessment: integrating satellite and airborne mapping approaches. Environ. Res. Lett. 4, 034009 (2009).ADS 

    Google Scholar 
    Mahowald, N. M. et al. Interactions between land use change and carbon cycle feedbacks. Glob. Biogeochem. Cy 31, 96–113 (2017).CAS 

    Google Scholar 
    Hubau, W. et al. Asynchronous carbon sink saturation in African and Amazonian tropical forests. Nature 579, 80–87 (2020).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Gibbs, H. K., Brown, S., Niles, J. O. & Foley, J. A. Monitoring and estimating tropical forest carbon stocks: making REDD a reality. Environ. Res. Lett. 2, 045023 (2007).ADS 

    Google Scholar 
    Zhao, Z. et al. Fire enhances forest degradation within forest edge zones in Africa. Nat. Geosci. 14, 479–483 (2021).ADS 
    CAS 

    Google Scholar 
    Ordway, E. M. & Asner, G. P. Carbon declines along tropical forest edges correspond to heterogeneous effects on canopy structure and function. Proc. Natl Acad. Sci. USA117, 7863–7870 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Fischer, R. et al. Accelerated forest fragmentation leads to critical increase in tropical forest edge area. Sci. Adv. 7, eabg7012 (2021).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    McDowell, N. et al. Drivers and mechanisms of tree mortality in moist tropical forests. N. Phytol. 219, 851–869 (2018).
    Google Scholar 
    Staver, A. C., Archibald, S. & Levin, S. A. The global extent and determinants of savanna and forest as alternative biome states. Science 334, 230–232 (2011).ADS 
    CAS 
    MATH 

    Google Scholar 
    Fu, R. et al. Increased dry-season length over southern Amazonia in recent decades and its implication for future climate projection. Proc. Natl Acad. Sci. USA 110, 18110–18115 (2013).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bagley, J. E., Desai, A. R., Harding, K. J., Snyder, P. K. & Foley, J. A. Drought and deforestation: has land cover change influenced recent precipitation extremes in the Amazon? J. Clim. 27, 345–361 (2014).ADS 

    Google Scholar 
    Arora, V. K. et al. Carbon–concentration and carbon–climate feedbacks in CMIP5 Earth system models. J. Clim. 26, 5289–5314 (2013).ADS 

    Google Scholar 
    Duveiller, G. et al. Biophysics and vegetation cover change: a process-based evaluation framework for confronting land surface models with satellite observations. Earth Syst. Sci. Data 10, 1265–1279 (2018).ADS 

    Google Scholar 
    Schulzweida, U. Climate data operators (CDO) user guide (Version 1.9.8). https://doi.org/10.5281/zenodo.3539275 (2019).Tropical Rainfall Measuring Mission (TRMM) TRMM (TMPA/3B43) Rainfall Estimate L3 1 month 0.25 degree x 0.25 degree V7, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC). https://doi.org/10.5067/TRMM/TMPA/MONTH/7 (2011).Harris, I., Osborn, T. J., Jones, P. & Lister, D. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset. Sci. Data 7, 1–18 (2020).
    Google Scholar 
    Yang, H. et al. Comparison of forest above‐ground biomass from dynamic global vegetation models with spatially explicit remotely sensed observation‐based estimates. Glob. Chang. Biol. 26, 3997–4012 (2020).ADS 
    PubMed 

    Google Scholar 
    Schneider, U. et al. GPCC Full Data Reanalysis Version 6.0 at 1.0o: Monthly Land-Surface Precipitation from Rain-Gauges built on GTS-based and Historic Data. https://doi.org/10.5676/DWD_GPCC/FD_M_V7_100 (2011).Liu, Y. Y. et al. Recent reversal in loss of global terrestrial biomass. Nat. Clim. Chang 5, 470–474 (2015).ADS 

    Google Scholar 
    Spracklen, D. V. & Garcia‐Carreras, L. The impact of Amazonian deforestation on Amazon basin rainfall. Geophys. Res. Lett. 42, 9546–9552 (2015).ADS 

    Google Scholar  More

  • in

    High genomic diversity in the endangered East Greenland Svalbard Barents Sea stock of bowhead whales (Balaena mysticetus)

    Kovacs, K. M. et al. The endangered Spitsbergen bowhead whales’ secrets revealed after hundreds of years in hiding. Biol. Lett. https://doi.org/10.1098/rsbl.2020.0148 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Cooke, J. & Reeves, R. Balaena mysticetus (East Greenland-Svalbard-Barents Sea subpopulation). The IUCN Red List of Threatened Species 2018, e.T2472A50348144 (2018). https://doi.org/10.2305/IUCN.UK.2018-1.RLTS.T2472A50348144.enAllen, R. C. & Keay, I. Bowhead whales in the eastern Arctic, 1611–1911: Population reconstruction with historical whaling records. Environ. Hist. 12, 89–113 (2006).Article 

    Google Scholar 
    Reeves, R. R. Spitsbergen bowhead stock: A short review. Mar. Fish. Rev. 42, 65–69 (1980).
    Google Scholar 
    Shelden, K. E. W. & Rugh, D. J. The Bowhead Whale, Balaena mysticetus: Its Historic and Current Status. Mar. Fish. Rev. 57, 1–20 (1995).
    Google Scholar 
    Gilg, O. & Born, E. W. Recent sightings of the bowhead whale (Balaena mysticetus) in Northeast Greenland and the Greenland Sea. Polar Biol. 28, 796–801. https://doi.org/10.1007/s00300-005-0001-9 (2005).Article 

    Google Scholar 
    Boertmann, D., Kyhn, L. A., Witting, L. & Heide-Jørgensen, M. P. A hidden getaway for bowhead whales in the Greenland Sea. Polar Biol. 38, 1315–1319. https://doi.org/10.1007/s00300-015-1695-y (2015).Article 

    Google Scholar 
    Wiig, Ø., Bachmann, L., Janik, V., Kovac, K. & Lydersen, C. Spitsbergen bowhead whales revisited. Mar. Mamm. Sci. 23, 688–693. https://doi.org/10.1111/j.1748-7692.2007.02373.x (2007).Article 

    Google Scholar 
    Wiig, Ø., Bachmann, L., Øien, N., Kovacs, K. & Lydersen, C. Observations of bowhead whales (Balaena mysticetus) in the Svalbard area 1940–2009. Polar Biol. 33, 979–984. https://doi.org/10.1007/s00300-010-0776-1 (2010).Article 

    Google Scholar 
    Lydersen, C. et al. Lost highway not forgotten: Satellite tracking of a bowhead whale (Balaena mysticetus) from the critically endangered Spitsbergen stock. Arctic 65, 76–86. https://doi.org/10.14430/arctic4167 (2012).Article 

    Google Scholar 
    Vacquié-Garcia, J. et al. Late summer distribution and abundance of ice-associated whales in the Norwegian High Arctic. Endang. Spec. Res. 32, 59–70. https://doi.org/10.3354/esr00791 (2017).Article 

    Google Scholar 
    Givens, G. H. & Heide-Jørgensen, M. P. Abundance. In The Bowhead Whale: Balaena Mysticetus: Biology and Human Interactions (eds George, J. C. & Thewissen, J. G. M.) 77–86 (Academic Press, 2020).
    Google Scholar 
    Rooney, A. P., Honeycutt, R. L. & Derr, J. N. Historical population size change of bowhead whales inferred from DNA sequence polymorphism data. Evolution 55, 1678–1685. https://doi.org/10.1111/j.0014-3820.2001.tb00687.x (2001).CAS 
    Article 
    PubMed 

    Google Scholar 
    Borge, T., Bachmann, L., Bjørnstad, G. & Wiig, Ø. Genetic variation in Holocene bowhead whales from Svalbard. Mol. Ecol. 16, 2223–2235. https://doi.org/10.1111/j.1365-294X.2007.03287.x (2007).CAS 
    Article 
    PubMed 

    Google Scholar 
    LeDuc, R. G. et al. Genetic analyses (mtDNA and microsatellites) of Okhotsk and Bering/Chukchi/Beaufort Seas populations of bowhead whales. J. Cetacean Res. Manag. 7, 107–111 (2005).
    Google Scholar 
    Meschersky, I. G., Chichkina, A. N., Shpak, O. V. & Rozhnov, V. V. Molecular genetic analysis of the Shantar Summer Group of bowhead whales (Balaena mysticetus L.) in the Okhotsk Sea. Russ. J. Genet. 50, 395–405. https://doi.org/10.1134/S1022795414040097 (2014).CAS 
    Article 

    Google Scholar 
    Bachmann, L. et al. Mitogenomics and the genetic differentiation of contemporary Balaena mysticetus (Cetacea) from Svalbard. Zool. J. Linn. Soc. 191, 1192–1203. https://doi.org/10.1093/zoolinnean/zlaa082 (2021).Article 

    Google Scholar 
    Grond, J., Płecha, M., Hahn, C., Wiig, Ø. & Bachmann, L. Mitochondrial genomes of ancient bowhead whales (Balaena mysticetus) from Svalbard. Mitochondrial DNA Part B 4, 4152–4154. https://doi.org/10.1080/23802359.2019.1693284 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Nyhus, E. S. et al. Mitogenomes of contemporary Spitsbergen stock bowhead whales (Balaena mysticetus). Mitochondrial DNA Part B 1, 898–900. https://doi.org/10.1080/23802359.2016.1258345 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Andrews, S. FastQC: A Quality Control Tool for High Throughput Sequence Data. http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ (2010).Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120. https://doi.org/10.1093/bioinformatics/btu170 (2014).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Keane, M. et al. Insights into the evolution of longevity from the bowhead whale genome. Cell Rep. 10, 112–122. https://doi.org/10.1016/j.celrep.2014.12.008) (2015).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Li, H. A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics 27, 2987–2993. https://doi.org/10.1093/bioinformatics/btr509 (2011).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Danecek, P. et al. The variant call format and VCFtools. Bioinformatics 27, 2156–2158. https://doi.org/10.1093/bioinformatics/btr330 (2011).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ortiz, E. M. vcf2phylip v2.0: Convert a VCF matrix into several matrix formats for phylogenetic analysis. zenodo.org, https://zenodo.org/record/2540861#.YDUOKy1Q0f0 (2019).Huson, D. H. & Bryant, D. Application of phylogenetic networks in evolutionary studies. Mol. Biol. Evol. 23, 254–267. https://doi.org/10.1093/molbev/msj030 (2006).CAS 
    Article 
    PubMed 

    Google Scholar 
    Purcell, S. et al. PLINK: A tool set for whole-genome and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–576. https://doi.org/10.1086/519795 (2007).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, https://www.R-project.org/ (2020).Knaus, B. J. & Grunwald, N. J. VcfR: An R package to manipulate and visualize VCF format data. bioRxiv, 041277 (2016). https://doi.org/10.1101/041277Jombart, T. & Ahmed, I. adegenet 1.3–1: New tools for the analysis of genome-wide SNP data. Bioinformatics 27, 3070–3071. https://doi.org/10.1093/bioinformatics/btr521 (2011).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Hanghøj, K., Moltke, I., Alstrup Andersen, P., Manica, A. & Korneliussen, T. S. Fast and accurate relatedness estimation from high-throughput sequencing data in the presence of inbreeding. GigaScience 8, giz034. https://doi.org/10.1093/gigascience/giz034 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Korneliussen, T. S., Albrechtsen, A. & Nielsen, R. ANGSD: Analysis of next generation sequencing data. BMC Bioinform. 15, 356. https://doi.org/10.1186/s12859-014-0356-4 (2014).Article 

    Google Scholar 
    Renaud, G., Hanghøj, K., Korneliussen, T. S., Willerslev, E. & Orlando, L. Joint estimates of heterozygosity and runs of homozygosity for modern and ancient samples. Genetics 212, 587–614. https://doi.org/10.1534/genetics.119.302057 (2019).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Grabherr, M. G. et al. Genome-wide synteny through highly sensitive sequence alignment: Satsuma. Bioinformatics 26, 1145–1151. https://doi.org/10.1093/bioinformatics/btq102 (2010).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079. https://doi.org/10.1093/bioinformatics/btp352 (2009).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Westbury, M. V. et al. Extended and continuous decline in effective population size results in low genomic diversity in the world’s rarest hyena species, the brown hyena. Mol. Biol. Evol. 35, 1225–1237. https://doi.org/10.1093/molbev/msy037 (2018).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Li, H. & Durbin, R. Inference of human population history from whole genome sequence of a single individual. Nature 475, 493–496. https://doi.org/10.1038/nature10231 (2011).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Westbury, M. V., Petersen, B., Garde, E., Heide-Jørgensen, M. P. & Lorenzen, E. D. Narwhal genome reveals long-term low genetic diversity despite current large abundance size. iScience 15, 592–599. https://doi.org/10.1016/j.isci.2019.03.023 (2019).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Taylor, B. et al. Synthesis of lines of evidence for population structure for bowhead whales in the Bering-Chukchi-Beaufort region. Paper SC/59/BRG35 presented to the IWC Scientific Committee, Anchorage, Alaska (2007).Phillips, C. D. et al. Molecular insights into the historic demography of bowhead whales: Understanding the evolutionary basis of contemporary management practices. Ecol. Evol. 3, 18–37. https://doi.org/10.1002/ece3.374 (2012).CAS 
    Article 
    PubMed 

    Google Scholar 
    Liu, X. & Fu, Y. X. Stairway Plot 2: Demographic history inference with folded SNP frequency spectra. Genome Biol. 21, 280. https://doi.org/10.1186/s13059-020-02196-9 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Westbury, M. V. et al. Speciation in the face of gene flow within the toothed whale superfamily Delphinoidea. bioRxiv, https://doi.org/10.1101/2020.10.23.352286 (2020).Westbury, M. V. et al. Ecological specialisation and evolutionary reticulation in extant Hyaenidae. Mol. Biol. Evol. https://doi.org/10.1093/molbev/msab055 (2021).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    IWC. Report of the Scientific Committee Virtual Meeting, 11–26 May 2020. J. Cetacean Res. Manag. (Supplement) 22, 1–122 (2021).Jonsgård, Å. A right whale (Balaena sp.), in all probability a Greenland right whale (Balaena mysticetus) observed in the Barents Sea. Norsk Hvalfangst-Tidende 53, 311–313 (1964).
    Google Scholar 
    De Jong, C. The hunt of the Greenland whale: A short history and statistical sources. Rep. Int. Whaling Comm. Spec. Issue 5, 83–106 (1983).
    Google Scholar 
    Weslawski, J. M., Hacquebord, L., Stempniewicz, L. & Malinga, M. Greenland whales and walruses in the Svalbard food web before and after exploitation. Oceanologia 2, 37–56 (2000).
    Google Scholar 
    George, J. C. et al. Age and growth estimates of bowhead whales (Balaena mysticetus) via aspartic acid racemization. Can. J. Zool. 77, 571–580. https://doi.org/10.1139/z99-015 (1999).Article 

    Google Scholar 
    de Jager, D. et al. High diversity, inbreeding and a dynamic Pleistocene demographic history revealed by African buffalo genomes. Sci. Rep. 11, 4540. https://doi.org/10.1038/s41598-021-83823-8 (2021).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Belikov, S. E., Gorbunov, Y. A. & Shil’nikov, V. I. Distribution of pinnipedia and cetacea in Soviet arctic seas and the Bering Sea in winter. Sov. J. Marine Biology 15, 251–257 (1989).
    Google Scholar 
    Gavrilo, M. V. Status of the bowhead whale Balaena mysticetus in the waters of Franz Josef Land Archipelago. Paper SC/66a/BRG20 Presented to the IWC Scientific Committee, May 2015, San Diego, USA (2015).Heide-Jorgensen, M. P., Hansen, R. G. & Shpak, O. V. Distribution, migrations, and ecology of the Atlantic and the Okhotsk Sea Populations. In The Bowhead Whale: Balaena Mysticetus: Biology and Human Interactions (eds George, J. C. & Thewissen, J. G. M.) 57–75 (Academic Press, 2020).
    Google Scholar 
    Petrov, S. A. et al. The results of marine mammal countins during the four expeditions in the Arctic in 2014 and 2015. Collection of scientific papers 9th International Conference ‘Marine mammals of the Holarctic’, Astrakhan, Russia, 2016. 91–102 (2018).Gavrilo, M. V. & Tretiakov V. Y. Observation of bowhead whales (Balaena mysticetus) in the East-Siberian Sea during 2007 season with record-low ice cover – Marine mammals of the Holarctic. In: Collection of Scientific Papers. Odessa, 191–194 (2008).Citta, J. J., Quakenbush, L. & George, J. C. Distribution and behavior of Bering-Chukchi-Beaufort bowhead whales as inferred by telemetry. In The Bowhead Whale: Balaena Mysticetus: Biology and Human Interactions (eds George, J. C. & Thewissen, J. G. M.) 31–56 (Academic Press, 2021). https://doi.org/10.1016/B978-0-12-818969-6.00004-2.Chapter 

    Google Scholar 
    Arnason, Ú., Lammers, F., Kumar, V., Nilsson, M. A. & Janke, A. Whole-genome sequencing of the blue whale and other rorquals finds signatures for introgressive gene flow. Sci. Adv. 4, eaap9873. https://doi.org/10.1126/sciadv.aap9873 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bazin, E., Glémin, S. & Galtier, N. Population size does not influence mitochondrial genetic diversity in animals. Science 312, 570–572. https://doi.org/10.1126/science.1122033 (2006).CAS 
    Article 
    PubMed 

    Google Scholar 
    Corbett-Detig, R., Hartl, D. L. & Sackton, T. B. Natural selection constrains neutral diversity across a wide range of species. PLoS Biol. 13, e1002112. https://doi.org/10.1371/journal.pbio.1002112 (2015).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Vachon, F., Whitehead, H. & Frasier, T. R. What factors shape genetic diversity in cetaceans?. Ecol. Evol. 8, 1554–1572. https://doi.org/10.1002/ece3.3727 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kumar, S. & Subramanian, S. Mutation rates in mammalian genomes. Proc. Natl. Acad. Sci. U.S.A. 99, 803–808. https://doi.org/10.1073/pnas.022629899 (2002).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bininda-Emonds, O. R. P. Fast genes and slow clades: Comparative rates of molecular evolution in mammals. Evol. Bioinf. 3, 59–85. https://doi.org/10.1177/117693430700300008 (2007).CAS 
    Article 

    Google Scholar 
    Jackson, J. A. et al. Big and slow: Phylogenetic estimates of molecular evolution in baleen whales (Suborder Mysticeti). Mol. Biol. Evol. 26, 2427–2440. https://doi.org/10.1093/molbev/msp169 (2009).CAS 
    Article 
    PubMed 

    Google Scholar 
    Foote, A. D. et al. Ancient DNA reveals that bowhead whale lineages survived Late Pleistocene climate change and habitat shifts. Nat. Commun. 4, 1667. https://doi.org/10.1038/ncomms2714 (2013).CAS 
    Article 

    Google Scholar 
    Wiig, Ø., Bachmann, L. & Hufthammer, A. K. Late Pleistocene and Holocene occurrence of bowhead whales (Balaena mysticetus) along the coasts of Norway. Polar Biol. 42, 645–656. https://doi.org/10.1007/s00300-019-02460-0 (2018).Article 

    Google Scholar 
    Alter, S. E. et al. Gene flow on ice: The role of sea ice and whaling in shaping Holarctic genetic diversity and population differentiation in bowhead whales (Balaena mysticetus). Ecol. Evol. 2, 2895–2911. https://doi.org/10.1093/zoolinnean/zlaa082 (2012).Article 

    Google Scholar  More

  • in

    Glycoside hydrolase from the GH76 family indicates that marine Salegentibacter sp. Hel_I_6 consumes alpha-mannan from fungi

    Field CB, Behrenfeld MJ, Randerson JT, Falkowski P. Primary production of the biosphere: integrating terrestrial and oceanic components. Science. 1998;281:237–40.CAS 
    PubMed 
    Article 

    Google Scholar 
    Falkowski PG, Barber RT, Smetacek V. Biogeochemical controls and feedbacks on ocean primary production. Science. 1998;281:200–6.CAS 
    PubMed 
    Article 

    Google Scholar 
    Schnepf E, Kühn S. Food uptake and fine structure of Cryothecomonas longipes sp. nov., a marine nanoflagellate incertae sedis feeding phagotrophically on large diatoms. Helgol Mar Res. 2000;54:18–32.Article 

    Google Scholar 
    Garvetto A, Nézan E, Badis Y, Bilien G, Arce P, Bresnan E, et al. Novel widespread marine oomycetes parasitising diatoms, including the toxic genus pseudo-nitzschia: genetic, morphological, and ecological characterisation. Front Microbiol. 2018;9:2918.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Gutiérrez MH, Jara AM, Pantoja S. Fungal parasites infect marine diatoms in the upwelling ecosystem of the Humboldt current system off central Chile. Environ Microbiol. 2016;18:1646–53.PubMed 
    Article 

    Google Scholar 
    Scholz B, Guillou L, Marano AV, Neuhauser S, Sullivan BK, Karsten U, et al. Zoosporic parasites infecting marine diatoms – A black box that needs to be opened. Fungal Ecol. 2016;19:59–76.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Hedges J, Baldock J, Gélinas Y, Lee C, Peterson M, Wakeham S. The biochemical and elemental compositions of marine plankton: A NMR perspective. Mar Chem. 2002;78:47–63.CAS 
    Article 

    Google Scholar 
    Hedges JI, Baldock JA, Gelinas Y, Lee C, Peterson M, Wakeham SG. Evidence for non-selective preservation of organic matter in sinking marine particles. Nature. 2001;409:801–4.CAS 
    PubMed 
    Article 

    Google Scholar 
    Laine RA. A calculation of all possible oligosaccharide isomers both branched and linear yields 1.05 x 10 (12) structures for a reducing hexasaccharide: the Isomer Barrier to development of single-method saccharide sequencing or synthesis systems. Glycobiology. 1994;4:759–67.CAS 
    PubMed 
    Article 

    Google Scholar 
    Chin W-C, Orellana MV, Verdugo P. Spontaneous assembly of marine dissolved organic matter into polymer gels. Nature. 1998;391:568–72.CAS 
    Article 

    Google Scholar 
    Passow U. Transparent exopolymer particles (TEP) in aquatic environments. Prog Oceanogr. 2002;55:287–333.Article 

    Google Scholar 
    Fangel JU, Pedersen HL, Vidal-Melgosa S, Ahl LI, Salmean AA, Egelund J, et al. Carbohydrate microarrays in plant science. Methods Mol Biol. 2012;918:351–62.CAS 
    PubMed 
    Article 

    Google Scholar 
    Vidal-Melgosa S, Pedersen HL, Schuckel J, Arnal G, Dumon C, Amby DB, et al. A new versatile microarray-based method for high throughput screening of carbohydrate-active enzymes. J Biol Chem. 2015;290:9020–36.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Vidal-Melgosa S, Sichert A, Francis TB, Bartosik D, Niggemann J, Wichels A, et al. Diatom fucan polysaccharide precipitates carbon during algal blooms. Nat Commun. 2021;12:1150.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Becker S, Scheffel A, Polz MF, Hehemann JH. Accurate quantification of laminarin in marine organic matter with enzymes from marine microbes. Appl Environ Microbiol. 2017;83:e03389-16.Krüger K, Chafee M, Francis TB, del Rio TG, Becher D, Schweder T, et al. In marine Bacteroidetes the bulk of glycan degradation during algae blooms is mediated by few clades using a restricted set of genes. ISME J. 2019;13:2800–16.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Teeling H, Fuchs BM, Bennke CM, Krüger K, Chafee M, Kappelmann L, et al. Recurring patterns in bacterioplankton dynamics during coastal spring algae blooms. eLife. 2016;5:e11888.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Kabisch A, Otto A, König S, Becher D, Albrecht D, Schüler M, et al. Functional characterization of polysaccharide utilization loci in the marine Bacteroidetes ‘Gramella forsetii’ KT0803. ISME J. 2014;8:1492–502.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Kappelmann L, Krüger K, Hehemann JH, Harder J, Markert S, Unfried F, et al. Polysaccharide utilization loci of North Sea Flavobacteriia as basis for using SusC/D-protein expression for predicting major phytoplankton glycans. ISME J. 2019;13:76–91.CAS 
    PubMed 
    Article 

    Google Scholar 
    Unfried F, Becker S, Robb CS, Hehemann J-H, Markert S, Heiden SE, et al. Adaptive mechanisms that provide competitive advantages to marine bacteroidetes during microalgal blooms. ISME J. 2018;12:2894–906.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Xing P, Hahnke RL, Unfried F, Markert S, Huang S, Barbeyron T, et al. Niches of two polysaccharide-degrading Polaribacter isolates from the North Sea during a spring diatom bloom. ISME J. 2015;9:1410–22.CAS 
    PubMed 
    Article 

    Google Scholar 
    Bjursell MK, Martens EC, Gordon JI. Functional genomic and metabolic studies of the adaptations of a prominent adult human gut symbiont, Bacteroides thetaiotaomicron, to the suckling period. J Biol Chem. 2006;281:36269–79.CAS 
    PubMed 
    Article 

    Google Scholar 
    Martens EC, Chiang HC, Gordon JI. Mucosal glycan foraging enhances fitness and transmission of a saccharolytic human gut bacterial symbiont. Cell Host Microbe. 2008;4:447–57.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Hehemann JH, Correc G, Barbeyron T, Helbert W, Czjzek M, Michel G. Transfer of carbohydrate-active enzymes from marine bacteria to Japanese gut microbiota. Nature. 2010;464:908–12.CAS 
    PubMed 
    Article 

    Google Scholar 
    Larsbrink J, Rogers TE, Hemsworth GR, McKee LS, Tauzin AS, Spadiut O. et al. A discrete genetic locus confers xyloglucan metabolism in select human gut Bacteroidetes. Nature. 2014;506:498–502.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Larsbrink J, Thompson AJ, Lundqvist M, Gardner JG, Davies GJ, Brumer H. A complex gene locus enables xyloglucan utilization in the model saprophyte Cellvibrio japonicus. Mol Microbiol. 2014;94:418–33.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Cuskin F, Lowe EC, Temple MJ, Zhu Y, Cameron E, Pudlo NA, et al. Human gut Bacteroidetes can utilize yeast mannan through a selfish mechanism. Nature. 2015;517:165–9.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Ndeh D, Rogowski A, Cartmell A, Luis AS, Basle A, Gray J, et al. Complex pectin metabolism by gut bacteria reveals novel catalytic functions. Nature. 2017;544:65–70.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Reisky L, Préchoux A, Zühlke MK, Bäumgen M, Robb CS, Gerlach N, et al. A marine bacterial enzymatic cascade degrades the algal polysaccharide ulvan. Nat Chem Biol. 2019;15:803–12.CAS 
    PubMed 
    Article 

    Google Scholar 
    Hahnke RL, Harder J. Phylogenetic diversity of Flavobacteria isolated from the North Sea on solid media. Syst Appl Microbiol. 2013;36:497–504.CAS 
    PubMed 
    Article 

    Google Scholar 
    Chen J, Robb CS, Unfried F, Kappelmann L, Markert S, Song T, et al. Alpha- and beta-mannan utilization by marine Bacteroidetes. Environ Microbiol. 2018;20:4127–40.CAS 
    PubMed 
    Article 

    Google Scholar 
    Bågenholm V, Reddy SK, Bouraoui H, Morrill J, Kulcinskaja E, Bahr CM, et al. Galactomannan catabolism conferred by a polysaccharide utilization locus of Bacteroides ovatus: enzyme synergy and crystal structure of a β-mannanase. J Biol Chem. 2017;292:229–43.PubMed 
    Article 
    CAS 

    Google Scholar 
    Le Costaouëc T, Unamunzaga C, Mantecon L, Helbert W. New structural insights into the cell-wall polysaccharide of the diatom Phaeodactylum tricornutum. Algal Res. 2017;26:172–9.Article 

    Google Scholar 
    Matulewicz M, Cerezo A. Water-soluble sulfated polysaccharides from the red seaweed Chaetangium fastigiatum. Analysis of the system and the structures of the α-D-(1→ 3)-linked mannans. Carbohydr Polym. 1987;7:121–32.CAS 
    Article 

    Google Scholar 
    Tabarsa M, Karnjanapratum S, Cho M, Kim JK, You S. Molecular characteristics and biological activities of anionic macromolecules from Codium fragile. Int J Biol Macromol. 2013;59:1–12.CAS 
    PubMed 
    Article 

    Google Scholar 
    Chen Y, Mao WJ, Yan MX, Liu X, Wang SY, Xia Z, et al. Purification, chemical characterization, and bioactivity of an extracellular polysaccharide produced by the marine sponge endogenous fungus Alternaria sp. SP-32. Mar Biotechnol. 2016;18:301–13.CAS 
    Article 

    Google Scholar 
    Gimenez-Abian MI, Bernabe M, Leal JA, Jimenez-Barbero J, Prieto A. Structure of a galactomannan isolated from the cell wall of the fungus Lineolata rhizophorae. Carbohydr Res. 2007;342:2599–603.CAS 
    PubMed 
    Article 

    Google Scholar 
    Teeling H, Fuchs BM, Becher D, Klockow C, Gardebrecht A, Bennke CM, et al. Substrate-controlled succession of marine bacterioplankton populations induced by a phytoplankton bloom. Science. 2012;336:608–11.CAS 
    PubMed 
    Article 

    Google Scholar 
    Bennke CM, Krüger K, Kappelmann L, Huang S, Gobet A, Schüler M, et al. Polysaccharide utilisation loci of Bacteroidetes from two contrasting open ocean sites in the North Atlantic. Environ Microbiol. 2016;18:4456–70.CAS 
    PubMed 
    Article 

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

    Google Scholar 
    Li D, Liu CM, Luo R, Sadakane K, Lam TW. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics. 2015;31:1674–6.CAS 
    PubMed 
    Article 

    Google Scholar 
    Hyatt D, Chen GL, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinform. 2010;11:119.Article 
    CAS 

    Google Scholar 
    Yin Y, Mao X, Yang J, Chen X, Mao F, Xu Y. dbCAN: a web resource for automated carbohydrate-active enzyme annotation. Nucleic Acids Res. 2012;40(W1):W445–51.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Lombard V, Golaconda Ramulu H, Drula E, Coutinho PM, Henrissat B. The carbohydrate-active enzymes database (CAZy) in 2013. Nucleic Acids Res. 2014;42(D1):D490–5.CAS 
    PubMed 
    Article 

    Google Scholar 
    Fu L, Niu B, Zhu Z, Wu S, Li W. CD-HIT: accelerated for clustering the next-generation sequencing data. Bioinformatics. 2012;28:3150–2.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Gilchrist CLM, Chooi YH. Clinker & clustermap.js: automatic generation of gene cluster comparison figures. Bioinformatics. 2021;37:2473–75.CAS 
    Article 

    Google Scholar 
    Kumar S, Stecher G, Li M, Knyaz C, Tamura K. MEGA X: molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol. 2018;35:1547–9.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Stecher G, Tamura K, Kumar S. Molecular evolutionary genetics analysis (MEGA) for macOS. Mol Biol Evol. 2020;37:1237–9.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Letunic I, Bork P. Interactive Tree Of Life (iTOL) v4: recent updates and new developments. Nucleic Acids Res. 2019;47(W1):W256–W9.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Liu H, Naismith JH. An efficient one-step site-directed deletion, insertion, single and multiple-site plasmid mutagenesis protocol. BMC Biotechnol. 2008;8:91.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Hehemann JH, Smyth L, Yadav A, Vocadlo DJ, Boraston AB. Analysis of keystone enzyme in agar hydrolysis provides insight into the degradation (of a polysaccharide from) red seaweeds. J Biol Chem. 2012;287:13985–95.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Wilkins MR, Gasteiger E, Bairoch A, Sanchez JC, Williams KL, Appel RD, et al. Protein identification and analysis tools in the ExPASy server. Methods Mol Biol. 1999;112:531–52.CAS 
    PubMed 

    Google Scholar 
    Plante OJ, Palmacci ER, Seeberger PH. Automated solid-phase synthesis of oligosaccharides. Science. 2001;291:1523–7.CAS 
    PubMed 
    Article 

    Google Scholar 
    Kabsch W. Xds. Acta Crystallogr D Biol Crystallogr. 2010;66:125–32.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Kabsch W. Integration, scaling, space-group assignment and post-refinement. Acta Crystallogr D Biol Crystallogr. 2010;66:133–44.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    McCoy AJ, Grosse-Kunstleve RW, Adams PD, Winn MD, Storoni LC, Read RJ. Phaser crystallographic software. J Appl Crystallogr. 2007;40:658–74.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Cohen SX, Ben Jelloul M, Long F, Vagin A, Knipscheer P, Lebbink J. et al. ARP/wARP and molecular replacement: the next generation. Acta Crystallogr D Biol Crystallogr. 2008;64:49–60.CAS 
    PubMed 
    Article 

    Google Scholar 
    Afonine PV, Grosse-Kunstleve RW, Echols N, Headd JJ, Moriarty NW, Mustyakimov M. et al. Towards automated crystallographic structure refinement with phenix.refine. Acta Crystallogr D Biol Crystallogr. 2012;68:352–67.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Emsley P, Lohkamp B, Scott WG, Cowtan K. Features and development of Coot. Acta Crystallogr D Biol Crystallogr. 2010;66:486–501.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Battye TG, Kontogiannis L, Johnson O, Powell HR, Leslie AG. iMOSFLM: a new graphical interface for diffraction-image processing with MOSFLM. Acta Crystallogr D Biol Crystallogr. 2011;67(Pt 4):271–81.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Terwilliger TC, Grosse-Kunstleve RW, Afonine PV, Moriarty NW, Zwart PH, Hung LW, et al. Iterative model building, structure refinement and density modification with the PHENIX AutoBuild wizard. Acta crystallogr D Biol Crystallogr. 2008;64:61–9.CAS 
    PubMed 
    Article 

    Google Scholar 
    Murshudov GN, Skubak P, Lebedev AA, Pannu NS, Steiner RA, Nicholls RA. et al. REFMAC5 for the refinement of macromolecular crystal structures. Acta Crystallogr D Biol Crystallogr. 2011;67:355–67.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Murshudov GN, Vagin AA, Dodson EJ. Refinement of macromolecular structures by the maximum-likelihood method. Acta Crystallogr D Biol Crystallogr. 1997;53:240–55.CAS 
    PubMed 
    Article 

    Google Scholar 
    Mystkowska AA, Robb C, Vidal-Melgosa S, Vanni C, Fernandez-Guerra A, Hohne M, et al. Molecular recognition of the beta-glucans laminarin and pustulan by a SusD-like glycan-binding protein of a marine. Bacteroidetes FEBS J. 2018;285:4465–81.CAS 
    PubMed 
    Article 

    Google Scholar 
    Jones DR, Xing X, Tingley JP, Klassen L, King ML, Alexander TW, et al. Analysis of active site architecture and reaction product linkage chemistry reveals a conserved cleavage substrate for an endo-alpha-mannanase within diverse yeast mannans. J Mol Biol. 2020;432:1083–97.CAS 
    PubMed 
    Article 

    Google Scholar 
    Starr CM, Masada RI, Hague C, Skop E, Klock JC. Fluorophore-assisted carbohydrate electrophoresis in the separation, analysis, and sequencing of carbohydrates. J Chromatogr A. 1996;720:295–321.CAS 
    PubMed 
    Article 

    Google Scholar 
    Ivanova EP, Bowman JP, Christen R, Zhukova NV, Lysenko AM, Gorshkova NM, et al. Salegentibacter flavus sp. nov. Int J Syst Evol Microbiol. 2006;56:583–6.CAS 
    PubMed 
    Article 

    Google Scholar 
    Liang QY, Xu ZX, Zhang J, Chen GJ, Du ZJ. Salegentibacter sediminis sp. nov., a marine bacterium of the family Flavobacteriaceae isolated from coastal sediment. Int J Syst Evol Microbiol. 2018;68:2375–80.CAS 
    PubMed 
    Article 

    Google Scholar 
    Nedashkovskaya OI, Kim SB, Lysenko AM, Mikhailov VV, Bae KS, Kim IS. Salegentibacter mishustinae sp. nov., isolated from the sea urchin Strongylocentrotus intermedius. Int J Syst Evol Microbiol. 2005;55:235–8.CAS 
    PubMed 
    Article 

    Google Scholar 
    Nedashkovskaya OI, Kim SB, Vancanneyt M, Shin DS, Lysenko AM, Shevchenko LS, et al. Salegentibacter agarivorans sp. nov., a novel marine bacterium of the family Flavobacteriaceae isolated from the sponge Artemisina sp. Int J Syst Evol Microbiol. 2006;56:883–7.CAS 
    PubMed 
    Article 

    Google Scholar 
    Nedashkovskaya OI, Suzuki M, Vancanneyt M, Cleenwerck I, Zhukova NV, Vysotskii MV, et al. Salegentibacter holothuriorum sp. nov., isolated from the edible holothurian Apostichopus japonicus. Int J Syst Evol Microbiol. 2004;54:1107–10.CAS 
    PubMed 
    Article 

    Google Scholar 
    Xia HF, Li XL, Liu QQ, Miao TT, Du ZJ, Chen GJ. Salegentibacter echinorum sp. nov., isolated from the sea urchin Hemicentrotus pulcherrimus. Antonie Van Leeuwenhoek. 2013;104:315–20.CAS 
    PubMed 
    Article 

    Google Scholar 
    Yoon JH, Jung SY, Kang SJ, Jung YT, Oh TK. Salegentibacter salarius sp. nov., isolated from a marine solar saltern. Int J Syst Evol Microbiol. 2007;57:2738–42.CAS 
    PubMed 
    Article 

    Google Scholar 
    Regmi A, Boyd EF. Carbohydrate metabolic systems present on genomic islands are lost and gained in Vibrio parahaemolyticus. BMC Microbiol. 2019;19:112-.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Kelley LA, Mezulis S, Yates CM, Wass MN, Sternberg MJ. The Phyre2 web portal for protein modeling, prediction and analysis. Nat Protoc. 2015;10:845–58.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Shi H, Zhang Y, Xu B, Tu M, Wang F. Characterization of a novel GH2 family alpha-L-arabinofuranosidase from hyperthermophilic bacterium Thermotoga thermarum. Biotechnol Lett. 2014;36:1321–8.CAS 
    PubMed 
    Article 

    Google Scholar 
    Zhu Y, Suits MD, Thompson AJ, Chavan S, Dinev Z, Dumon C, et al. Mechanistic insights into a Ca2+-dependent family of alpha-mannosidases in a human gut symbiont. Nat Chem Biol. 2010;6:125–32.CAS 
    PubMed 
    Article 

    Google Scholar 
    Gregg KJ, Zandberg WF, Hehemann JH, Whitworth GE, Deng L, Vocadlo DJ, et al. Analysis of a new family of widely distributed metal-independent alpha-mannosidases provides unique insight into the processing of N-linked glycans. J Biol Chem. 2011;286:15586–96.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Thompson AJ, Speciale G, Iglesias-Fernandez J, Hakki Z, Belz T, Cartmell A, et al. Evidence for a boat conformation at the transition state of GH76 alpha-1,6-mannanases-key enzymes in bacterial and fungal mannoprotein metabolism. Angew Chem. 2015;54:5378–82.CAS 
    Article 

    Google Scholar 
    Thompson AJ, Cuskin F, Spears RJ, Dabin J, Turkenburg JP, Gilbert HJ, et al. Structure of the GH76 α-mannanase homolog, BT2949, from the gut symbiont Bacteroides thetaiotaomicron. Acta Crystallogr D Biol Crystallogr. 2015;71:408–15.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Eklöf JM, Shojania S, Okon M, McIntosh LP, Brumer H. Structure-function analysis of a broad specificity Populus trichocarpa endo-β-glucanase reveals an evolutionary link between bacterial licheninases and plant XTH gene products. J Biol Chem. 2013;288:15786–99.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Venugopal V. Marine polysaccharides: food applications. Boca Raton: CRC Press; 2016.Ferrer-González FX, Widner B, Holderman NR, Glushka J, Edison AS, Kujawinski EB, et al. Resource partitioning of phytoplankton metabolites that support bacterial heterotrophy. ISME J. 2021;15:762–73.PubMed 
    Article 
    CAS 

    Google Scholar 
    Comeau AM, Vincent WF, Bernier L, Lovejoy C. Novel chytrid lineages dominate fungal sequences in diverse marine and freshwater habitats. Sci Rep. 2016;6:30120.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Hassett BT, Gradinger R. Chytrids dominate arctic marine fungal communities. Environ Microbiol. 2016;18:2001–9.CAS 
    PubMed 
    Article 

    Google Scholar 
    Duan Y, Xie N, Song Z, Ward CS, Yung C-M, Hunt DE, et al. A high-resolution time series reveals distinct seasonal patterns of planktonic fungi at a temperate coastal ocean site (Beaufort, North Carolina, USA). Appl Environ Microbiol. 2018;84:e00967–18.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Priest T, Fuchs B, Amann R, Reich M. Diversity and biomass dynamics of unicellular marine fungi during a spring phytoplankton bloom. Environ Microbiol. 2021;23:448–63.CAS 
    PubMed 
    Article 

    Google Scholar 
    Picard KT. Coastal marine habitats harbor novel early-diverging fungal diversity. Fungal Ecol. 2017;25:1–13.Article 

    Google Scholar 
    Taylor JD, Cunliffe M. Multi-year assessment of coastal planktonic fungi reveals environmental drivers of diversity and abundance. ISME J. 2016;10:2118–28.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Banos S, Gysi DM, Richter-Heitmann T, Glöckner FO, Boersma M, Wiltshire KH, et al. Seasonal dynamics of pelagic mycoplanktonic communities: interplay of taxon abundance, temporal occurrence, and biotic interactions. Front Microbiol. 2020;11:1305.Tisthammer KH, Cobian GM, Amend AS. Global biogeography of marine fungi is shaped by the environment. Fungal Ecol. 2016;19:39–46.Article 

    Google Scholar 
    Tian T, Merico A, Su J, Staneva J, Wiltshire K, Wirtz K. Importance of resuspended sediment dynamics for the phytoplankton spring bloom in a coastal marine ecosystem. J Sea Res. 2009;62:214–28.Article 

    Google Scholar 
    Gutiérrez MH, Pantoja S, Tejos E, Quiñones RA. The role of fungi in processing marine organic matter in the upwelling ecosystem off Chile. Mar Biol. 2011;158:205–19.Article 

    Google Scholar 
    Cunliffe M, Hollingsworth A, Bain C, Sharma V, Taylor JD. Algal polysaccharide utilisation by saprotrophic planktonic marine fungi. Fungal Ecol. 2017;30:135–8.Article 

    Google Scholar 
    Chambouvet A, Monier A, Maguire F, Itoïz S, del Campo J, Elies P, et al. Intracellular infection of diverse diatoms by an evolutionary distinct relative of the fungi. Curr Biol. 2019;29:4093–101.e4.CAS 
    PubMed 
    Article 

    Google Scholar 
    Buaya AT, Ploch S, Hanic L, Nam B, Nigrelli L, Kraberg A, et al. Phylogeny of Miracula helgolandica gen. et sp. nov. and Olpidiopsis drebesii sp. nov., two basal oomycete parasitoids of marine diatoms, with notes on the taxonomy of Ectrogella-like species. Mycol Prog. 2017;16:1041–50.Article 

    Google Scholar 
    Meyers SP, Ahearn DG, Gunkel W, Roth FJ. Yeasts from the North Sea. Mar Biol. 1967;1:118–23.Article 

    Google Scholar 
    Grossart H-P, Van den Wyngaert S, Kagami M, Wurzbacher C, Cunliffe M, Rojas-Jimenez K. Fungi in aquatic ecosystems. Nat Rev Microbiol. 2019;17:339–54.CAS 
    PubMed 
    Article 

    Google Scholar  More

  • in

    Trade-off between tree planting and wetland conservation in China

    Griscom, B. W. et al. Natural climate solutions. Proc. Natl Acad. Sci. USA 114, 11645–11650 (2017).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    MacDicken, K. G. Global forest resources assessment 2015: what, why and how? For. Ecol. Manag. 352, 3–8 (2015).
    Google Scholar 
    Li, M.-M. et al. An overview of the “Three-North” Shelterbelt project in China. Forestry Stud. China 14, 70–79 (2012).ADS 

    Google Scholar 
    Zhang, P. et al. China’s forest policy for the 21st century. Science 288, 2135–2136 (2000).CAS 
    PubMed 

    Google Scholar 
    Chen, Y. et al. Balancing green and grain trade. Nat. Geosci. 8, 739–741 (2015).ADS 

    Google Scholar 
    Xu, J., Yin, R., Li, Z. & Liu, C. China’s ecological rehabilitation: unprecedented efforts, dramatic impacts, and requisite policies. Ecol. Econ. 57, 595–607 (2006).
    Google Scholar 
    Piao, S., Fang, J., Liu, H. & Zhu, B. NDVI-indicated decline in desertification in China in the past two decades. Geophys. Res. Lett. 32, L06402 (2005).ADS 

    Google Scholar 
    Wang, X., Chen, F., Hasi, E. & Li, J. Desertification in China: an assessment. Earth Sci. Rev. 88, 188–206 (2008).ADS 

    Google Scholar 
    Ouyang, Z. et al. Improvements in ecosystem services from investments in natural capital. Science 352, 1455–1459 (2016).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Bryan, B. A. et al. China’s response to a national land-system sustainability emergency. Nature 559, 193–204 (2018).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Feng, X. et al. Revegetation in China’s Loess Plateau is approaching sustainable water resource limits. Nat. Clim. Chang. 6, 1019–1022 (2016).ADS 

    Google Scholar 
    Cao, S., Zhang, J., Chen, L. & Zhao, T. Ecosystem water imbalances created during ecological restoration by afforestation in China, and lessons for other developing countries. J. Environ. Manag. 183, 843–849 (2016).
    Google Scholar 
    Liu, Y. et al. Recent trends in vegetation greenness in China significantly altered annual evapotranspiration and water yield. Environ. Res. Lett. 11, 094010 (2016).ADS 

    Google Scholar 
    Yao, Y. et al. The effect of afforestation on soil moisture content in Northeastern China. PLoS ONE 11, e0160776 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    An, W. et al. Exploring the effects of the “Grain for Green” program on the differences in soil water in the semi-arid Loess Plateau of China. Ecol. Eng. 107, 144–151 (2017).
    Google Scholar 
    Li, Y. et al. Divergent hydrological response to large-scale afforestation and vegetation greening in China. Sci. Adv. 4, eaar4182 (2018).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Global Wetland Outlook: State of the World’s Wetlands and their Services to People (Ramsar Convention Secretariat, 2018).Baumgartner, R. J. Sustainable development goals and the forest sector—a complex relationship. Forests 10, 152 (2019).
    Google Scholar 
    15-year Comprehensive Plan for Ecological System Protection and Recovery Work (National Development and Reform Commission, 2020).Prigent, C., Jimenez, C. & Bousquet, P. Satellite-derived global surface water extent and dynamics over the last 25 years (GIEMS-2). J. Geophys. Res. Atmos. 125, e2019JD030711 (2020).ADS 

    Google Scholar 
    Krinner, G. et al. A dynamic global vegetation model for studies of the coupled atmosphere-biosphere system. Glob. Biogeochem. Cy. 19, GB1015 (2005).ADS 

    Google Scholar 
    Tootchi, A. Development of a global wetland map and application to describe hillslope hydrology in the ORCHIDEE land surface model. Sorbonne Université, https://www.metis.upmc.fr/~ducharne/documents/These_Tootchi_revised_11Sep2019.pdf (2019).Beven, K. J. & Kirkby, M. J. A physically based, variable contributing area model of basin hydrology / Un modèle à base physique de zone d’appel variable de l’hydrologie du bassin versant. Hydrol. Sci. B. 24, 43–69 (1979).
    Google Scholar 
    Stocker, B. D., Spahni, R. & Joos, F. DYPTOP: a cost-efficient TOPMODEL implementation to simulate sub-grid spatio-temporal dynamics of global wetlands and peatlands. Geosci. Model Dev. 7, 3089–3110 (2014).ADS 

    Google Scholar 
    Xi, Y., Peng, S., Ciais, P. & Chen, Y. Future impacts of climate change on inland Ramsar wetlands. Nat. Clim. Chang. 11, 45–51 (2021).ADS 

    Google Scholar 
    Kim, H. Global soil wetness project phase 3 atmospheric boundary conditions (Experiment 1). Data Integration and Analysis System (DIAS). (2017).Cucchi, M. et al. WFDE5: bias-adjusted ERA5 reanalysis data for impact studies. Earth Syst. Sci. Data 12, 2097–2120 (2020).ADS 

    Google Scholar 
    Donchyts, G. et al. Earth’s surface water change over the past 30 years. Nat. Clim. Chang. 6, 810–813 (2016).ADS 

    Google Scholar 
    Zhu, Q. et al. Climate-driven increase of natural wetland methane emissions offset by human-induced wetland reduction in China over the past three decades. Sci. Rep. 6, 38020 (2016).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Mao, D. et al. Remote observations in China’s Ramsar Sites: wetland dynamics, anthropogenic threats, and implications for sustainable development goals. J. Remote Sens. 2021, 9849343 (2021).ADS 

    Google Scholar 
    Budyko, M. I. Climate and Life (Academic Press, 1974).Zhang, L., Dawes, W. R. & Walker, G. R. Response of mean annual evapotranspiration to vegetation changes at catchment scale. Water Resour. Res. 37, 701–708 (2001).ADS 

    Google Scholar 
    Woodward, C., Shulmeister, J., Larsen, J., Jacobsen, G. E. & Zawadzki, A. The hydrological legacy of deforestation on global wetlands. Science 346, 844–847 (2014).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Zhang, Z., Zimmermann, N. E., Kaplan, J. O. & Poulter, B. Modeling spatiotemporal dynamics of global wetlands: comprehensive evaluation of a new sub-grid TOPMODEL parameterization and uncertainties. Biogeosciences 13, 1387–1408 (2016).ADS 

    Google Scholar 
    Ringeval, B. et al. Modelling sub-grid wetland in the ORCHIDEE global land surface model: evaluation against river discharges and remotely sensed data. Geosci. Model Dev. 5, 941 (2012).ADS 

    Google Scholar 
    Tootchi, A., Jost, A. & Ducharne, A. Multi-source global wetland maps combining surface water imagery and groundwater constraints. Earth Syst. Sci. Data 11, 189–220 (2019).ADS 

    Google Scholar 
    List of Protected Wetlands in China. http://www.zrbhq.cn/web/confirm.html (National Forestry and Grassland Administration, 2011).Lehner, B. & Grill, G. Global river hydrography and network routing: baseline data and new approaches to study the world’s large river systems. Hydrol. Process. 27, 2171–2186 (2013).ADS 

    Google Scholar 
    Lu, F. et al. Effects of national ecological restoration projects on carbon sequestration in China from 2001 to 2010. Proc. Natl Acad. Sci. USA 115, 4039–4044 (2018).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Warszawski, L. et al. The inter-sectoral impact model intercomparison project (ISI–MIP): project framework. Proc. Natl Acad. Sci. USA 111, 3228–3232 (2014).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Levia, D. F. et al. Homogenization of the terrestrial water cycle. Nat. Geosci. 13, 656–658 (2020).ADS 
    CAS 

    Google Scholar 
    Zhang, J., Fu, B., Stafford-Smith, M., Wang, S. & Zhao, W. Improve forest restoration initiatives to meet sustainable development goal 15. Nat. Ecol. Evol. 5, 10–13 (2020).
    Google Scholar 
    Zeng, Z. et al. Impact of earth greening on the terrestrial water cycle. J. Clim. 31, 2633–2650 (2018).ADS 

    Google Scholar 
    Lewis, S. L., Wheeler, C. E., Mitchard, E. T. A. & Koch, A. Restoring natural forests is the best way to remove atmospheric carbon. Nature 568, 25–28 (2019).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Bastin, J.-F. et al. The global tree restoration potential. Science 365, 76–79 (2019).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Meier, R. et al. Empirical estimate of forestation-induced precipitation changes in Europe. Nat. Geosci. 14, 473–478 (2021).ADS 
    CAS 

    Google Scholar 
    Bosch, J. M. & Hewlett, J. D. A review of catchment experiments to determine the effect of vegetation changes on water yield and evapotranspiration. J. Hydrol. 55, 3–23 (1982).ADS 

    Google Scholar 
    Teuling, A. J. & Hoek van Dijke, A. J. Forest age and water yield. Nature 578, E16–E18 (2020).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Doelman, J. C. et al. Afforestation for climate change mitigation: Potentials, risks and trade-offs. Glob. Change Biol. 26, 1576–1591 (2020).ADS 

    Google Scholar 
    Peng, S. et al. Afforestation in China cools local land surface temperature. Proc. Natl Acad. Sci. USA 111, 2915–2919 (2014).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Seddon, N., Turner, B., Berry, P., Chausson, A. & Girardin, C. A. J. Grounding nature-based climate solutions in sound biodiversity science. Nat. Clim. Chang. 9, 84–87 (2019).ADS 

    Google Scholar 
    Brown, I. Challenges in delivering climate change policy through land use targets for afforestation and peatland restoration. Environ. Sci. Policy 107, 36–45 (2020).
    Google Scholar 
    The 2nd – 9th National Forest Resource Inventory Report (State Forestry Administration of the People’s Republic of China, 1973–2018).Fang, J. et al. Forest biomass carbon sinks in East Asia, with special reference to the relative contributions of forest expansion and forest growth. Glob. Change Biol. 20, 2019–2030 (2014).ADS 

    Google Scholar 
    Hou, X. Vegetation atlas of China. Chinese Academy of Science, the editorial board of vegetation map of China (2001).Xi, Y. et al. Contributions of climate change, CO2, land-use change, and human activities to changes in river flow across 10 Chinese Basins. J. Hydrometeorol. 19, 1899–1914 (2018).ADS 

    Google Scholar 
    Song, X.-P. et al. Global land change from 1982 to 2016. Nature 560, 639–643 (2018).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Klein Goldewijk, K., Beusen, A., Doelman, J. & Stehfest, E. Anthropogenic land use estimates for the Holocene – HYDE 3.2. Earth Syst. Sci. Data 9, 927–953 (2017).ADS 

    Google Scholar 
    Fluet-Chouinard, E., Lehner, B., Rebelo, L.-M., Papa, F. & Hamilton, S. K. Development of a global inundation map at high spatial resolution from topographic downscaling of coarse-scale remote sensing data. Remote Sens. Environ. 158, 348–361 (2015).ADS 

    Google Scholar 
    Herold, M., Van Groenestijn, A., Kooistra, L., Kalogirou, V. & Arino, O. Land cover CCI, product user guide version 2.0. https://maps.elie.ucl.ac.be/CCI/viewer/download/ESACCI-LC-Ph2-PUGv2_2.0.pdf (2015).Pekel, J. F., Cottam, A., Gorelick, N. & Belward, A. S. High-resolution mapping of global surface water and its long-term changes. Nature 540, 418–422 (2016).ADS 
    CAS 

    Google Scholar 
    Zhou, G. et al. Global pattern for the effect of climate and land cover on water yield. Nat. Commun. 6, 5918 (2015).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Yang, H. et al. Changing retention properties of catchments and their influence on runoff under climate change. Environ. Res. Lett. 13, 094019 (2018).ADS 

    Google Scholar 
    Berghuijs, W. R., Larsen, J. R., van Emmerik, T. H. M. & Woods, R. A. A global assessment of runoff sensitivity to changes in precipitation, potential evaporation, and other factors. Water Resour. Res. 53, 8475–8486 (2017).ADS 

    Google Scholar 
    Piao, S. et al. Changes in climate and land use have a larger direct impact than rising CO2 on global river runoff trends. Proc. Natl Acad. Sci. USA 104, 15242 (2007).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Guimberteau, M. et al. Testing conceptual and physically based soil hydrology schemes against observations for the Amazon Basin. Geosci. Model Dev. 7, 1115–1136 (2014).ADS 

    Google Scholar 
    Traore, A. K. et al. Evaluation of the ORCHIDEE ecosystem model over Africa against 25 years of satellite-based water and carbon measurements. J. Geophys. Res. Biogeosci. 119, 1554–1575 (2014).
    Google Scholar 
    de Rosnay, P. & Polcher, J. Impact of a physically based soil water flow and soil‐plant interaction representation for modeling large‐scale land surface processes. J. Geophys. Res. Atmos. 107, ACL 3-1–ACL 3-19 (2002).
    Google Scholar 
    Campoy, A. et al. Influence of soil bottom hydrological conditions on land surface fluxes and climate in a general circulation model. J. Geophys. Res. Atmos. 118, 10725–10739 (2013).ADS 

    Google Scholar 
    Guimberteau, M. et al. Discharge simulation in the sub-basins of the Amazon using ORCHIDEE forced by new datasets. Hydrol. Earth Syst. Sci. 16, 11171–11232 (2012).
    Google Scholar 
    Boucher, O. et al. Presentation and evaluation of the IPSL-CM6A-LR climate model. J. Adv. Model. Earth Sy. 12, e2019MS002010 (2020).ADS 

    Google Scholar 
    Fan, Y. et al. Hillslope hydrology in global change research and earth system modeling. Water Resour. Res. 55, 1737–1772 (2019).ADS 

    Google Scholar 
    Rayner, P. J. et al. Two decades of terrestrial carbon fluxes from a carbon cycle data assimilation system (CCDAS). Glob. Biogeochem. Cy. 19, GB2026 (2005).ADS 

    Google Scholar 
    Ducharne, A. Reducing scale dependence in TOPMODEL using a dimensionless topographic index. Hydrol. Earth Syst. Sci. 13, 2399–2412 (2009).ADS 

    Google Scholar 
    Niu, G., Yang, Z., Dickinson, R. E. & Gulden, L. E. A simple TOPMODEL-based runoff parameterization (SIMTOP) for use in global climate models. J. Geophys. Res. 110, D21106 (2005).ADS 

    Google Scholar 
    Xi, Y. et al. Monthly inundated fraction over China for 2000-2015 from GIEMS-2 (Version v1.0). Zenodo https://doi.org/10.5281/zenodo.5750962 (2021).Xi, Y. et al. Code of wetland simulation for trade-off between tree planting and wetland conservation in China (Version v1.0). Zenodo https://doi.org/10.5281/zenodo.4435082 (2021). More