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    Investigation into the communication between unheated and heat-stressed Caenorhabditis elegans via volatile stress signals

    Witzany, G. Biocommunication of Animals (Springer, 2014).Book 

    Google Scholar 
    Mothersill, C., Smith, R. W., Agnihotri, N. & Seymour, C. B. Characterization of a radiation-induced stress response communicated in vivo between zebrafish. Environ. Sci. Technol. 41, 3382–3387 (2007).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Matveev, V. An investigation of allelopathic effects of Daphnia. Freshw Biol. 29, 99–105 (1993).Article 

    Google Scholar 
    Surinov, B. P., Isaeva, V. G. & Dukhova, N. N. Post radiation immunosuppressive and attractive volatile secretions: The “bystander effect” or allelopathy in groups of animals. Dokl. Biol. Sci. 400, 28–30 (2005).Article 

    Google Scholar 
    Mothersill, C. et al. Communication of radiation-induced stress or bystander signals between fish in vivo. Environ. Sci. Technol. 40, 6859–6864 (2006).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Choi, V. W., Cheng, S. H. & Yu, K. N. Radioadaptive response induced by alpha-particle-induced stress communicated in vivo between zebrafish embryos. Environ. Sci. Technol. 44, 8829–8834 (2010).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Peng, Y. et al. Cysteine protease cathepsin B mediates radiation-induced bystander effects. Nature 547, 458–462 (2017).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    White, J. G., Southgate, E., Thomson, J. N. & Brenner, S. The Structure of the Nervous System of the Nematode Caenorhabditis elegans (Cambridge University Press, 1986).
    Google Scholar 
    Riddle, D. L., Blumenthal, T., Meyer, B. J. & Priess, J. R. C. Elegans (Spring Harbor Laboratory Press, 1997).
    Google Scholar 
    Bargmann, C. I. & Mori, I. Chemotaxis and thermotaxis. In C. elegans II (eds Riddle, D. L. et al.) (Cold Spring Harbor (NY): Cold Spring Harbor Laboratory Press, 1997).
    Google Scholar 
    Leung, M. C. K. et al. Caenorhabditis elegans: An emerging model in biomedical and environmental toxicology. Toxicol. Sci. 106, 5–28 (2008).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Zhang, C. et al. The olfactory signal transduction for attractive odorants in Caenorhabditis elegans. Biotechnol. Adv. 32, 290–295 (2014).Article 
    PubMed 

    Google Scholar 
    Starich, T. A. et al. Mutations affecting the chemosensory neurons of Caenorhabditis elegans. Genetics 139, 171–188 (1995).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Mori, I. & Ohshima, Y. Molecular neurogenetics of chemotaxis and thermotaxis in the nematode Caenorhabditis elegans. BioEssays 19, 1055–1064 (1997).Article 
    CAS 
    PubMed 

    Google Scholar 
    Simon, J. M. & Sternberg, P. W. Evidence of a mate-finding cue in the hermaphrodite nematode Caenorhabditis elegans. Proc. Natl. Acad. Sci. USA 99, 1598–1603 (2002).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    White, J. Q. et al. The sensory circuitry for sexual attraction in C. elegans males. Curr. Biol. 17, 1847–1857 (2007).Article 
    CAS 
    PubMed 

    Google Scholar 
    Chasnov, J. R., So, W. K., Chan, C. M. & Chow, K. L. The species, sex, and stage specificity of a Caenorhabditis sex pheromone. Proc. Natl. Acad. Sci. USA 104, 6730–6735 (2007).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Srinivasan, J. et al. A blend of small molecules regulates both mating and development in Caenorhabditis elegans. Nature 454, 1115–1118 (2008).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Pungaliya, C. et al. A shortcut to identifying small molecule signals that regulate behavior and development in Caenorhabditis elegans. Proc. Natl. Acad. Sci. USA 106, 7708–7713 (2009).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Srinivasan, J. et al. A modular library of small molecule signals regulates social behaviors in Caenorhabditis elegans. PLoS. Biol. 10, e1001237 (2012).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Leighton, D. H., Choe, A., Wu, S. Y. & Sternberg, P. W. Communication between oocytes and somatic cells regulates volatile pheromone production in Caenorhabditis elegans. Proc. Natl. Acad. Sci. USA 111, 17905–17910 (2014).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Macosko, E. Z. et al. A hub-and-spoke circuit drives pheromone attraction and social behaviour in C. elegans. Nature 458, 1171–1175 (2009).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    von Reuss, S. H. et al. Comparative metabolomics reveals biogenesis of ascarosides, a modular library of small-molecule signals in C. elegans. J. Am. Chem. Soc. 134, 1817–1824 (2012).Article 

    Google Scholar 
    Peckol, E. L., Troemel, E. R. & Bargmann, C. I. Sensory experience and sensory activity regulate chemosensory receptor gene expression in Caenorhabditis elegans. Proc. Natl. Acad. Sci. USA 98, 11032–11038 (2001).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Yamada, K. et al. Olfactory plasticity is regulated by pheromonal signaling in Caenorhabditis elegans. Science 329, 1647–1650 (2010).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ludewig, A. H. et al. Pheromone sensing regulates Caenorhabditis elegans lifespan and stress resistance via the deacetylase SIR-2.1. Proc. Natl. Acad. Sci. USA 110, 5522–5527 (2013).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Artyukhin, A. B. et al. Succinylated octopamine ascarosides and a new pathway of biogenic amine metabolism in Caenorhabditis elegans. J. Biol. Chem. 288, 18778–18783 (2013).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bargmann, C. I., Hartwieg, E. & Horvitz, H. R. Odorant-selective genes and neurons mediate olfaction in C. elegans. Cell 74, 515–527 (1993).Article 
    CAS 
    PubMed 

    Google Scholar 
    Troemel, E. R., Kimmel, B. E. & Bargmann, C. I. Reprogramming chemotaxis responses: Sensory neurons define olfactory preferences in C. elegans. Cell 91, 161–169 (1997).Article 
    CAS 
    PubMed 

    Google Scholar 
    Wes, P. D. & Bargmann, C. I. C. elegans odour discrimination requires asymmetric diversity in olfactory neurons. Nature 410, 698–701 (2001).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Tang, H. Q. et al. Enhancement of DNA damage repair potential in germ cells of Caenorhabditis elegans by a volatile signal from their irradiated partners. DNA Repair 86, 102755 (2020).Article 
    CAS 
    PubMed 

    Google Scholar 
    Byerly, L., Scherer, S. & Russell, R. L. The life cycle of the nematode Caenorhabditis elegans: ii. A simplified method for mutant characterization. Dev. Biol. 51, 34–48 (1976).Article 
    CAS 
    PubMed 

    Google Scholar 
    Grewal, P. S. & Wright, D. J. Migration of Caenorhabditis elegans (Nematoda: Rhabditidae) larvae towards bacteria and the nature of the bacterial stimulus. Fundam. Appl. Nematol. 15, 159–166 (1992).
    Google Scholar 
    Ludewig, A. H. & Schroeder, F. C. Ascaroside signaling in C. elegans. WormBook 18, 1–22 (2013).Article 

    Google Scholar 
    Hubbard, E. J. & Greenstein, D. Introduction to the germ line. WormBook 1, 1–4 (2005).
    Google Scholar 
    Metzstein, M. M., Stanfield, G. M. & Horvitz, H. R. Genetics of programmed cell death in C. elegans: Past, present and future. Trends. Genet. 14, 410–416 (1998).Article 
    CAS 
    PubMed 

    Google Scholar 
    Gumienny, T. L., Lambie, E., Hartwieg, E., Horvitz, H. R. & Hengartner, M. O. Genetic control of programmed cell death in the Caenorhabditis elegans hermaphrodite germline. Development 126, 1011–1022 (1999).Article 
    CAS 
    PubMed 

    Google Scholar 
    Takanami, T., Mori, A., Takahashi, H. & Higashitani, A. Hyper-resistance of meiotic cells to radiation due to a strong expression of a single recA-like gene in Caenorhabditis elegans. Nucleic. Acids. Res. 28, 4232–4236 (2000).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    O’Neil, N., Rose, A., DNA repair (January 13, 2006), WormBook, ed. The C. elegans Research Community, WormBook, https://doi.org/10.1895/wormbook.1.54.1, http://www.wormbook.org.Craig, A. L., Moser, S. C., Bailly, A. P. & Gartner, A. Methods for studying the DNA damage response in the Caenorhabdatis elegans germ line. Methods Cell Biol. 107, 321–352 (2012).Article 
    CAS 
    PubMed 

    Google Scholar 
    Joo, H. J., Park, S., Kim, K. Y., Kim, M. Y. & Paik, Y. K. HSF-1 is involved in regulation of ascaroside pheromone biosynthesis by heat stress in Caenorhabditis elegans. Biochem. J. 473, 789–796 (2016).Article 
    CAS 
    PubMed 

    Google Scholar 
    Prahlad, V., Cornelius, T. & Morimoto, R. I. Regulation of the cellular heat shock response in Caenorhabditis elegans by thermosensory neurons. Science 9, 811–814 (2008).Article 
    ADS 

    Google Scholar 
    Vakkayil, K. L. & Hoppe, T. Temperature-dependent regulation of proteostasis and longevity. Front. Aging 3, 853588 (2022).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Pagliuso, D. C., Bodas, D. M. & Pasquinelli, A. E. Recovery from heat shock requires the microRNA pathway in Caenorhabditis elegans. PLoS Genet. 17(8), e1009734 (2021).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Singh, V. & Aballay, A. Heat-shock transcription factor (HSF)-1 pathway required for Caenorhabditis elegans immunity. Proc. Natl. Acad. Sci. USA 103(35), 13092–13097 (2006).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kurop, M. K., Huyen, C. M., Kelly, J. H. & Blagg, B. S. J. The heat shock response and small molecule regulators. Eur. J. Med. Chem. 226, 113846 (2021).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Howard, A. C., Rollins, J., Snow, S., Castor, S. & Rogers, A. N. Reducing translation through eIF4G/IFG-1 improves survival under ER stress that depends on heat shock factor HSF-1 in Caenorhabditis elegans. Aging Cell 15(6), 1027–1038 (2016).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Jo, H., Shim, J., Lee, J. H., Lee, J. & Kim, J. B. IRE-1 and HSP-4 contribute to energy homeostasis via fasting-induced lipases in C. elegans. Cell Metab. 9(5), 440–448 (2009).Article 
    CAS 
    PubMed 

    Google Scholar 
    Al-Amin, M., Kawasaki, I., Gong, J. & Shim, Y. H. Caffeine induces the stress response and up-regulates heat shock proteins in Caenorhabditis elegans. Mol. Cells. 39(2), 163–168 (2016).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Dues, D. J. et al. Aging causes decreased resistance to multiple stresses and a failure to activate specific stress response pathways. Aging (Albany NY). 8(4), 777–795 (2016).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Prahlad, V. & Morimoto, R. I. Integrating the stress response: Lessons for neurodegenerative diseases from C. elegans. Trends. Cell. Biol. 19, 52–61 (2009).Article 
    CAS 
    PubMed 

    Google Scholar 
    Younis, A. E. et al. Stage-specific excretory-secretory small heat shock proteins from the parasitic nematode Strongyloides ratti–putative links to host’s intestinal mucosal defense system. FEBS. J. 278, 3319–3336 (2011).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Komarova, E. Y. et al. Downstream caspases are novel targets for the antiapoptotic activity of the molecular chaperone hsp70. Cell Stress Chaper. 9, 265–275 (2004).Article 
    CAS 

    Google Scholar 
    Edkins, A. L., Price, J. T., Pockley, A. G. & Blatch, G. L. Heat shock proteins as modulators and therapeutic targets of chronic disease: An integrated perspective. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 19, 1738 (2018).
    Google Scholar 
    Sancar, A., Lindsey-Boltz, L. A., Unsal-Kaccmaz, K. & Linn, S. Molecular mechanisms of mammalian DNA repair and the DNA damage checkpoints. Annu. Rev. Biochem. 73, 39–85 (2004).Article 
    CAS 
    PubMed 

    Google Scholar 
    Pierotti, M. A. & Dragani, T. A. Genetics and cancer. Curr. Opin. Oncol. 4, 127–133 (1992).Article 
    CAS 
    PubMed 

    Google Scholar 
    Roemer, K. Mutant p53: Gain-of-function oncoproteins and wild-type p53 inactivators. Biol. Chem. 380, 879–887 (1999).Article 
    CAS 
    PubMed 

    Google Scholar 
    Vogelstein, B., Lane, D. & Levine, A. J. Surfing the p53 network. Nature 408, 307–310 (2000).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Gartner, A., Milstein, S., Ahmed, S., Hodgkin, J. & Hengartner, M. O. A conserved checkpoint pathway mediates DNA damage-induced apoptosis and cell cycle arrest in C. elegans. Mol. Cell 5, 435–443 (2000).Article 
    CAS 
    PubMed 

    Google Scholar 
    Lettre, G. & Hengartner, M. O. Developmental apoptosis in C. elegans: A complex CEDnario. Nat. Rev. Mol. Cell Biol. 7, 97–108 (2006).Article 
    CAS 
    PubMed 

    Google Scholar 
    Conradt, B. & Xue, D. Programmed Cell Death 1–13 (WormBook, 2005).
    Google Scholar 
    Bartek, J. & Lukas, J. Chk1 and Chk2 kinases in checkpoint control and cancer. Cancer Cell 3, 421–429 (2003).Article 
    CAS 
    PubMed 

    Google Scholar 
    Sharpless, N. E. & DePinho, R. A. The INK4A/ARF locus and its two gene products. Curr. Opin. Genet. Dev. 9, 22–30 (1999).Article 
    CAS 
    PubMed 

    Google Scholar 
    Kaletta, T. & Hengartner, M. O. Finding function in novel targets: C. elegans as a model organism. Nat. Rev. Drug Discov. 5, 387–399 (2006).Article 
    CAS 
    PubMed 

    Google Scholar 
    Brenner, S. The genetics of Caenorhabditis elegans. Genetics 77, 71–94 (1974).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar  More

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    Environmental changes associated with drying climate are expected to affect functional groups of pro- and microeukaryotes differently in temporary saline waters

    Céréghino, R., Biggs, J., Oertli, B. & Declerck, S. The ecology of European ponds: Defining the characteristics of a neglected freshwater habitat. In Pond Conservation in Europe (eds Oertli, B. et al.) 1–6 (Springer Netherlands, 2007).
    Google Scholar 
    Olmo, C. et al. The environmental framework of temporary ponds: A tropical-Mediterranean comparison. CATENA 210, 105845 (2022).CAS 

    Google Scholar 
    Griffiths, R. A. Temporary ponds as amphibian habitats. Aquat. Conserv. Mar. Freshw. Ecosyst. 7, 119–126 (1997).
    Google Scholar 
    Boix, D. et al. Conservation of temporary wetlands. In Encyclopedia of the World’s Biomes 279–294 (Elsevier, 2020). https://doi.org/10.1016/B978-0-12-409548-9.12003-2.Chapter 

    Google Scholar 
    Fritz, K. A. & Whiles, M. R. Reciprocal subsidies between temporary ponds and riparian forests. Limnol. Oceanogr. 66, 3149–3161 (2021).ADS 

    Google Scholar 
    Jeffries, M. The spatial and temporal heterogeneity of macrophyte communities in thirty small, temporary ponds over a period of ten years. Ecography 31, 765–775 (2008).
    Google Scholar 
    Hassall, C. The ecology and biodiversity of urban ponds. WIREs Water 1, 187–206 (2014).
    Google Scholar 
    Lukács, B. A. et al. Macrophyte diversity of lakes in the Pannon Ecoregion (Hungary). Limnologica 53, 74–83 (2015).
    Google Scholar 
    Florencio, M., Díaz-Paniagua, C., Gómez-Rodríguez, C. & Serrano, L. Biodiversity patterns in a macroinvertebrate community of a temporary pond network. Insect Conserv. Divers. 7, 4–21 (2014).
    Google Scholar 
    Meland, S., Sun, Z., Sokolova, E., Rauch, S. & Brittain, J. E. A comparative study of macroinvertebrate biodiversity in highway stormwater ponds and natural ponds. Sci. Total Environ. 740, 140029 (2020).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Hahn, M. W. The microbial diversity of inland waters. Curr. Opin. Biotechnol. 17, 256–261 (2006).CAS 
    PubMed 

    Google Scholar 
    Felföldi, T. Microbial communities of soda lakes and pans in the Carpathian Basin: A review. Biol. Futura 71, 393–404 (2020).
    Google Scholar 
    Grossart, H., Massana, R., McMahon, K. D. & Walsh, D. A. Linking metagenomics to aquatic microbial ecology and biogeochemical cycles. Limnol. Oceanogr. 65, S2–S20 (2020).CAS 

    Google Scholar 
    Marrone, F., Fontaneto, D. & Naselli-Flores, L. Cryptic diversity, niche displacement and our poor understanding of taxonomy and ecology of aquatic microorganisms. Hydrobiologia https://doi.org/10.1007/s10750-022-04904-x (2022).Article 

    Google Scholar 
    Ducklow, H. Microbial services: Challenges for microbial ecologists in a changing world. Aquat. Microb. Ecol. 53, 13–19 (2008).ADS 

    Google Scholar 
    Bodelier, P. L. E. Toward understanding, managing, and protecting microbial ecosystems. Front. Microbiol. 2, 80 (2011).PubMed 
    PubMed Central 

    Google Scholar 
    Bell, T., Newman, J. A., Silverman, B. W., Turner, S. L. & Lilley, A. K. The contribution of species richness and composition to bacterial services. Nature 436, 1157–1160 (2005).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Trivedi, C. et al. Losses in microbial functional diversity reduce the rate of key soil processes. Soil Biol. Biochem. 135, 267–274 (2019).CAS 

    Google Scholar 
    Wellborn, G. A., Skelly, D. K. & Werner, E. E. Mechanisms creating community structure across freshwater habitat gradient. Annu. Rev. Ecol. Syst. 27, 337–363 (1996).
    Google Scholar 
    Chase, J. M. Drought mediates the importance of stochastic community assembly. Proc. Natl. Acad. Sci. 104, 17430–17434 (2007).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Tweed, S., Grace, M., Leblanc, M., Cartwright, I. & Smithyman, D. The individual response of saline lakes to a severe drought. Sci. Total Environ. 409, 3919–3933 (2011).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Aguilar, P., Acosta, E., Dorador, C. & Sommaruga, R. Large differences in bacterial community composition among three nearby extreme waterbodies of the High Andean Plateau. Front. Microbiol. 7, 976 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Boros, E., Balogh, K., Vörös, L. & Horváth, Z. Multiple extreme environmental conditions of intermittent soda pans in the Carpathian Basin (Central Europe). Limnologica 62, 38–46 (2017).CAS 
    PubMed 

    Google Scholar 
    Lengyel, E., Pálmai, T., Padisák, J. & Stenger-Kovács, C. Annual hydrological cycle of environmental variables in astatic soda pans (Hungary). J. Hydrol. 575, 1188–1199 (2019).ADS 
    CAS 

    Google Scholar 
    Vieira-Silva, S. & Rocha, E. P. C. The Systemic imprint of growth and its uses in ecological (Meta)genomics. PLoS Genet. 6, e1000808 (2010).PubMed 
    PubMed Central 

    Google Scholar 
    Cunillera-Montcusí, D. et al. Freshwater salinisation: A research agenda for a saltier world. Trends Ecol. Evol. 37, 440–453 (2022).PubMed 

    Google Scholar 
    Šolić, M. et al. Structure of microbial communities in phosphorus-limited estuaries along the eastern Adriatic coast. J. Mar. Biol. Assoc. U.K. 95, 1565–1578 (2015).
    Google Scholar 
    Traving, S. J. et al. The Effect of increased loads of dissolved organic matter on estuarine microbial community composition and function. Front. Microbiol. 8, 351 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    Zhang, G. et al. Salinity controls soil microbial community structure and function in coastal estuarine wetlands. Environ. Microbiol. 23, 1020–1037 (2021).CAS 
    PubMed 

    Google Scholar 
    Tkavc, R. et al. Bacterial communities in the ‘petola’ microbial mat from the Sečovlje salterns (Slovenia): Bacterial communities in the ‘petola’. FEMS Microbiol. Ecol. 75, 48–62 (2011).CAS 
    PubMed 

    Google Scholar 
    Ali, I. et al. Comparative study of physical factors and microbial diversity of four man-made extreme ecosystems. Proc. Natl. Acad. Sci. India Sect. B Biol. Sci. 86, 767–778 (2016).
    Google Scholar 
    Paul, V., Banerjee, Y., Ghosh, P. & Busi, S. B. Depthwise microbiome and isotopic profiling of a moderately saline microbial mat in a solar saltern. Sci. Rep. 10, 20686 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Stenger-Kovács, C. et al. Vanishing world: Alkaline, saline lakes in Central Europe and their diatom assemblages. Inland Waters 4, 383–396 (2014).
    Google Scholar 
    Stenger-Kovács, C., Hajnal, É., Lengyel, E., Buczkó, K. & Padisák, J. A test of traditional diversity measures and taxonomic distinctness indices on benthic diatoms of soda pans in the Carpathian basin. Ecol. Indic. 64, 1–8 (2016).
    Google Scholar 
    Szabó, B., Lengyel, E., Padisák, J., Vass, M. & Stenger-Kovács, C. Structuring forces and β-diversity of benthic diatom metacommunities in soda pans of the Carpathian Basin. Eur. J. Phycol. 53, 219–229 (2018).
    Google Scholar 
    Szabó, A. et al. Soda pans of the Pannonian steppe harbor unique bacterial communities adapted to multiple extreme conditions. Extremophiles 21, 639–649 (2017).PubMed 

    Google Scholar 
    Szabó, A. et al. Grazing pressure-induced shift in planktonic bacterial communities with the dominance of acIII-A1 actinobacterial lineage in soda pans. Sci. Rep. 10, 19871 (2020).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Benlloch, S. et al. Prokaryotic genetic diversity throughout the salinity gradient of a coastal solar saltern. Environ. Microbiol. 4, 349–360 (2002).PubMed 

    Google Scholar 
    Horváth, Z. et al. Opposing patterns of zooplankton diversity and functioning along a natural stress gradient: When the going gets tough, the tough get going. Oikos 123, 461–471 (2014).
    Google Scholar 
    Mo, Y. et al. Low shifts in salinity determined assembly processes and network stability of microeukaryotic plankton communities in a subtropical urban reservoir. Microbiome 9, 128 (2021).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    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 
    PubMed 

    Google Scholar 
    Gómez-Rodríguez, C., Bustamante, J. & Díaz-Paniagua, C. Evidence of hydroperiod shortening in a preserved system of temporary ponds. Remote Sens. 2, 1439–1462 (2010).ADS 

    Google Scholar 
    Finger Higgens, R. A. et al. Changing lake dynamics indicate a drier arctic in western greenland. J. Geophys. Res. Biogeosciences 124, 870–883 (2019).ADS 

    Google Scholar 
    Zacharias, I. & Zamparas, M. Mediterranean temporary ponds. A disappearing ecosystem. Biodivers. Conserv. 19, 3827–3834 (2010).
    Google Scholar 
    Horváth, Z., Ptacnik, R., Vad, C. F. & Chase, J. M. Habitat loss over six decades accelerates regional and local biodiversity loss via changing landscape connectance. Ecol. Lett. 22, 1019–1027 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Grillas, P., Rhazi, L., Lefebvre, G., El Madihi, M. & Poulin, B. Foreseen impact of climate change on temporary ponds located along a latitudinal gradient in Morocco. Inland Waters 11, 492–507 (2021).CAS 

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

    Google Scholar 
    Zhong, Y. et al. Shrinking habitats and native species loss under climate change: a multifactorial risk Assessment of China’s inland wetlands. 28 (2022).Atkinson, S. T. et al. Substantial long-term loss of alpha and gamma diversity of lake invertebrates in a landscape exposed to a drying climate. Glob. Change Biol. 27, 6263–6279 (2021).CAS 

    Google Scholar 
    Whiting, G. J. & Chanton, J. P. Greenhouse carbon balance of wetlands: Methane emission versus carbon sequestration: Greenhouse carbon balance of wetlands. Tellus B 53, 521–528 (2001).ADS 

    Google Scholar 
    Mitsch, W. J. et al. Wetlands, carbon, and climate change. Landsc. Ecol. 28, 583–597 (2013).
    Google Scholar 
    Ardón, M., Helton, A. M. & Bernhardt, E. S. Salinity effects on greenhouse gas emissions from wetland soils are contingent upon hydrologic setting: A microcosm experiment. Biogeochemistry 140, 217–232 (2018).
    Google Scholar 
    Jeppesen, E., Beklioğlu, M., Özkan, K. & Akyürek, Z. Salinization increase due to climate change will have substantial negative effects on inland waters: A call for multifaceted research at the local and global scale. Innovation 1, 100030 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    Boros, E., Horváth, Z., Wolfram, G. & Vörös, L. Salinity and ionic composition of the shallow astatic soda pans in the Carpathian Basin. Ann. Limnol. Int. J. Limnol. 50, 59–69 (2014).
    Google Scholar 
    Sorokin, D. Y. et al. Microbial diversity and biogeochemical cycling in soda lakes. Extremophiles 18, 791–809 (2014).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Horváth, Z., Vad, C. F., Vörös, L. & Boros, E. The keystone role of anostracans and copepods in European soda pans during the spring migration of waterbirds: The keystone trophic role of crustaceans in European soda pans. Freshw. Biol. 58, 430–440 (2013).
    Google Scholar 
    Stenger-Kovács, C. & Lengyel, E. Taxonomical and distribution guide of diatoms in soda pans of Central Europe. Stud. Bot. Hung. 46, 3–203 (2015).
    Google Scholar 
    Szabó, B. et al. Microbial stowaways: Waterbirds as dispersal vectors of aquatic pro- and microeukaryotic communities. J. Biogeogr. 49, 1286–1298 (2022).
    Google Scholar 
    Williams, D. D. The Ecology of Temporary Waters (Springer Netherlands, 1987).
    Google Scholar 
    Hammer, U. T. The effects of climate change on the salinity, water levels and biota of Canadian prairie saline lakes. SIL Proc. 1922–2010(24), 321–326 (1990).
    Google Scholar 
    Schallenberg, M., Hall, C. & Burns, C. Consequences of climate-induced salinity increases on zooplankton abundance and diversity in coastal lakes. Mar. Ecol. Prog. Ser. 251, 181–189 (2003).ADS 

    Google Scholar 
    Felföldi, T., Somogyi, B., Márialigeti, K. & Vörös, L. Characterization of photoautotrophic picoplankton assemblages in turbid, alkaline lakes of the Carpathian Basin (Central Europe). J. Limnol. 68, 385 (2009).
    Google Scholar 
    Somogyi, B. et al. Winter bloom of picoeukaryotes in Hungarian shallow turbid soda pans and the role of light and temperature. Aquat. Ecol. 43, 735–744 (2009).CAS 

    Google Scholar 
    Pálffy, K. et al. Unique picoeukaryotic algal community under multiple environmental stress conditions in a shallow, alkaline pan. Extremophiles 18, 111–119 (2014).PubMed 

    Google Scholar 
    Padisák, J. & Naselli-Flores, L. Phytoplankton in extreme environments: Importance and consequences of habitat permanency. Hydrobiologia 848, 157–176 (2021).
    Google Scholar 
    Olli, K., Ptacnik, R., Klais, R. & Tamminen, T. Phytoplankton species richness along coastal and estuarine salinity continua. Am. Nat. 194, E41–E51 (2019).PubMed 

    Google Scholar 
    Olli, K., Tamminen, T. & Ptacnik, R. Predictable shifts in diversity and ecosystem function in phytoplankton communities along coastal salinity continua. Limnol. Oceanogr. Lett. https://doi.org/10.1002/lol2.10242 (2022).Article 

    Google Scholar 
    Tikhonenkov, D. V., Burkovsky, I. V. & Mazei, Y. A. Is there a relation between the distribution of heterotrophic flagellates and the zonation of a marine intertidal flat?. Oceanology 55, 13 (2015).
    Google Scholar 
    Arndt, H. et al. Functional diversity of heterotrophic flagellates in aquatic ecosystems. In Flagellates 252–280 (CRC Press, 2000). https://doi.org/10.1201/9781482268225-18.Chapter 

    Google Scholar 
    JeLee, W. & Patterson, D. J. Diversity and geographic distribution of free-living heterotrophic flagellates—Analysis by PRIMER. Protist 149, 229–244 (1998).CAS 

    Google Scholar 
    Azovsky, A. I., Tikhonenkov, D. V. & Mazei, Y. A. An estimation of the global diversity and distribution of the smallest eukaryotes: Biogeography of marine benthic heterotrophic flagellates. Protist 167, 411–424 (2016).PubMed 

    Google Scholar 
    Tikhonenkov, D. V., Mazei, Y. A. & Mylnikov, A. P. Species diversity of heterotrophic flagellates in White Sea littoral sites. Eur. J. Protistol. 42, 191–200 (2006).PubMed 

    Google Scholar 
    Van der Gucht, K. et al. The power of species sorting: Local factors drive bacterial community composition over a wide range of spatial scales. Proc. Natl. Acad. Sci. 104, 20404–20409 (2007).PubMed 
    PubMed Central 

    Google Scholar 
    Vanschoenwinkel, B. et al. Species sorting in space and time—The impact of disturbance regime on community assembly in a temporary pool metacommunity. J. North Am. Benthol. Soc. 29, 1267–1278 (2010).
    Google Scholar 
    Datry, T. et al. Metacommunity patterns across three neotropical catchments with varying environmental harshness. Freshw. Biol. 61, 277–292 (2016).
    Google Scholar 
    Hansen, H. P. & Koroleff, F. Determination of nutrients. In Methods of Seawater Analysis (eds Grasshoff, K. et al.) 159–228 (Wiley-VCH Verlag GmbH, 1999).
    Google Scholar 
    Clesceri, L. S., Greenberg, A. E. & Eaton, A. D. Standard methods for examination of water and wastewater. 20th ed. http://ipkosar.ir/jspui/handle/961944/280820 (1999).Parada, A. E., Needham, D. M. & Fuhrman, J. A. Every base matters: Assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples: Primers for marine microbiome studies. Environ. Microbiol. 18, 1403–1414 (2016).CAS 
    PubMed 

    Google Scholar 
    Apprill, A., McNally, S., Parsons, R. & Weber, L. Minor revision to V4 region SSU rRNA 806R gene primer greatly increases detection of SAR11 bacterioplankton. Aquat. Microb. Ecol. 75, 129–137 (2015).
    Google Scholar 
    Ray, J. L. et al. Metabarcoding and metabolome analyses of copepod grazing reveal feeding preference and linkage to metabolite classes in dynamic microbial plankton communities. Mol. Ecol. 25, 5585–5602 (2016).CAS 
    PubMed 

    Google Scholar 
    Hadziavdic, K. et al. Characterization of the 18S rRNA gene for designing universal eukaryote specific primers. PLoS One 9, e87624 (2014).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Schloss, P. D. et al. Introducing mothur: Open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl. Environ. Microbiol. 75, 7537–7541 (2009).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kozich, J. J., Westcott, S. L., Baxter, N. T., Highlander, S. K. & Schloss, P. D. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence sata on the MiSeq Illumina sequencing platform. Appl. Environ. Microbiol. 79, 5112–5120 (2013).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kunin, V., Engelbrektson, A., Ochman, H. & Hugenholtz, P. Wrinkles in the rare biosphere: Pyrosequencing errors can lead to artificial inflation of diversity estimates. Environ. Microbiol. 12, 118–123 (2010).CAS 
    PubMed 

    Google Scholar 
    Quast, C. et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2012).PubMed 
    PubMed Central 

    Google Scholar 
    Rohwer, R. R., Hamilton, J. J., Newton, R. J. & McMahon, K. D. TaxAss: Leveraging a custom freshwater database achieves fine-scale taxonomic resolution. mSphere 3, e00327-18 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Guillou, L. et al. The Protist Ribosomal Reference database (PR2): A catalog of unicellular eukaryote Small Sub-Unit rRNA sequences with curated taxonomy. Nucleic Acids Res. 41, D597–D604 (2012).PubMed 
    PubMed Central 

    Google Scholar 
    McMurdie, P. J. & Holmes, S. phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One 8, e61217 (2013).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Oksanen, J. et al. vegan: Community Ecology Package. R package version 2.5-7. https://CRAN.R-project.org/package=vegan (2020).Martinez Arbizu, P. pairwiseAdonis: Pairwise multilevel comparison using Adonis. Pairwise Adonis R package version 0.4. R package. https://cran.r-project.org/web/packages/pairwise/index.html (2017).Kassambara, A. ggpubr: ‘ggplot2’ based publication ready plots. ggpubr R package version 0.4.0. https://CRAN.R-project.org/package=ggpubr (2020).Burian, A. et al. Predation increases multiple components of microbial diversity in activated sludge communities. ISME J. 16, 1086–1094 (2022).CAS 
    PubMed 

    Google Scholar 
    Kembel, S. W. et al. Picante: R tools for integrating phylogenies and ecology, picante R package version 1.8.2. Bioinformatics 26, 1463–1464. https://cran.r-project.org/web/packages/picante/index.html (2010).Venables, W. N. & Ripley, B. D. Modern Applied Statistics with S. 4th ed. MASS R package version 7.3-54 (Springer, 2002). https://cran.r-project.org/web/packages/MASS/index.html. ISBN 0-387-95457-0.Wood, S. N. Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. mgcv R package version 1.8-38. J. R. Stat. Soc. B 73(1), 3–36. https://cran.r-project.org/web/packages/mgcv/index.html (2011).Gu, Z. Complex heatmap visualization. iMeta 1 (2022).R Core Team. R: A language and environment for statistical computing (R Foundation for Statistical Computing, 2022). https://www.R-project.org/. More

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    A thousand-genome panel retraces the global spread and adaptation of a major fungal crop pathogen

    Global genetic structure of the pathogen tracks the historical spread of wheatWe assessed the evolutionary trajectory of the pathogen in conjunction with the history of global wheat cultivation (Fig. 1a). For this, we assembled a worldwide collection of Z. tritici isolates from naturally infected fields (Fig. 1b). We selected isolates covering most wheat production areas, both in the center of origin of the crop (i.e., the Fertile Crescent in the Middle East), and in areas where wheat was introduced during the last millennia (i.e., Europe and North Africa), or last centuries (i.e., the Americas and Oceania; Fig. 1c). We called variants in a set of 1109 high-quality short-read resequencing datasets (Supplementary Data 1, 2) covering 42 countries and a broad range of climates. Using a joint genotyping approach, we produced raw variant calls mapped to the telomere-to-telomere assembled reference genome IPO323. To assess genotyping accuracy, we used eight isolates with replicate sequencing data to analyze discrepancies. We adjusted quality thresholds targeting specifically the type of genotyping errors observed in our data set (Fig. S1). The improved filtering yielded 8,406,818 high-confidence short variants (short indels and SNPs). The final variant set included 5,578,488 biallelic SNPs corresponding to 14.1% of the genome.Fig. 1: Global sampling of the wheat pathogen Zymoseptoria tritici retracing the historical spread of its host.a Schematic representation of the introduction of wheat across continents. b Septoria tritici blotch symptoms caused by Z. tritici on wheat leaves. Pictures taken by B. A. McDonald, ETH Zurich. c Map of the sampling scheme for the global collection of 1109 isolates for whole-genome sequencing.Full size imageWe tested whether global diversity patterns of pathogen populations are likely a consequence of the history of wheat cultivation. We first performed unsupervised clustering of genotypes and identified eleven well-supported clusters (Fig. 2a, Figs. S2,3). Over 90% of the genotypes were clearly assigned to a single cluster (Fig. 2a, Supplementary Data 3). Two clusters were identified among genotypes originating from the pathogen center of origin, distinguishing collections from Iran and Middle Eastern regions. Genotypes from Africa and Europe split into two distinct genetic clusters without any apparent secondary structure within clusters. This lack of any fine-scale structure is remarkable given the extensive geographic sampling of European genotypes and suggests extensive gene flow within the continent. Genotypes from Oceania grouped into three distinct clusters marked by collections from Tasmania, the Australian mainland, and New Zealand. Genotypes from North America formed two clusters along a North-South separation. Finally, South American genotypes formed two clusters split along the Andes (Chile versus Argentina and Uruguay). Some uncertainty exists in the assessment of regional population structure by low coverage of major wheat-producing countries such as Russia and Ukraine. Septoria tritici blotch is only sporadically reported in China. In complementary analyses, we found that a phylogenetic network accounting for the high frequency of recombination consistently reflected the global population structure (Fig. S4). A principal component analysis of all genotypes confirmed the nested genetic structure with differentiation at the continent level, subdivisions within some continents and the existence of admixed genotypes (Fig. 2b, Fig. S5).Fig. 2: Global genetic structure based on 1109 genomes.a Map of the genetic clustering based on a thinned genome-wide SNP dataset using sNMF. Each color represents a different genetic cluster, and the sizes of the slices represent the average attribution to the cluster across the isolates from each location. Fractions representing less than 10% of all genotypes of a location were colored in grey to improve clarity. The large pie chart outside of the map represents the proportion of isolates assigned clearly (≥75%) to a single genetic cluster (pure; in teal) and isolates identified as hybrids (admixed) between clusters (in yellow). Names of the clusters include an abbreviation of continents and a more precise geographical location (MEA: Middle East and Africa; NA: North America; SA: South America; OC: Oceania). b Principal component analysis, showing the first and second component (PCs) based on a subset of variants. Colors and shapes indicate the genomic clusters identified with the sNMF method (with hybrids in grey). The marginal distributions represent the distribution for each PC. PCs 1 to 8 are shown in Fig S4. c Population tree based on Treemix, rooted using two genomes from the sister species Z. passerinii and Z. ardabiliae. The colors are the same as in the previous panels and only samples which were fully assigned to a cluster were used. d Diversity estimated with using pi per genetic cluster. The boxplots are ordered according to the tree of panel. c. The lower and upper hinges correspond to the first and third quartiles, the whiskers to the largest value are within 1.5 times the inter-quartile range, and the central horizontal line defines the median. e Linkage disequilibrium (r2) between variants per genetic cluster. Colors are identical among panels.Full size imageWe analyzed the history of population splits and admixture using allele frequency information (Fig. 2c). The analyses largely supported a genetic structure shaped by the introduction of wheat across continents. The historical relationships between clusters show an early divergence of the Middle Eastern and North African clusters matching the early introduction of agriculture in these regions. Populations in Europe and the Americas share a similar time point of divergence consistent with extensive contributions of European genotypes to the Western hemisphere. Oceanian groups have diverged as a single branch from genotypes most closely related to extant European populations. Matching the introduction of wheat to Oceania from the European continent, the Australian and New Zealand pathogen populations share a common origin rooted in European genetic diversity. Populations from Australia show also a striking loss of diversity and higher linkage disequilibrium compared to European diversity consistent with a significant founder effect (Fig. 2d, e). Similarly, populations in South and North America have reduced genetic diversity compared to extant European populations as suggested previously based on Sanger sequencing16. The highest diversity was found in populations from Africa and the Middle East closest to the center of origin. Overall, the global genetic structure of the pathogen reveals multiple founder events associated with the introduction of wheat to new continents.Ongoing gene flow among regions should lead to admixed genotypes. We found that nearly 10% of all analyzed genotypes showed contributions from at least two clusters. The most significant recent gene flow was detected between Middle Eastern/North African clusters and European clusters in North Africa (i.e., Algeria and Tunisia) as well as Southern and Eastern Europe (i.e., France, Italy, Hungary, Ukraine, Portugal, and Spain; Supplementary Data 3). We found a particularly high incidence of recent immigration in a durum wheat population in the south of France. The population consisted only of hybrids or atypical genotypes suggesting either recent migration from North Africa or host specialization on durum wheat varieties. Additionally, we found hybrid genotypes with European ancestry in both North America and in Oceania. The relatively balanced ancestry proportions in these hybrids suggest very recent gene flow dating back to only a few generations. We further investigated past gene flow between clusters by allowing Treemix to infer migration events, thus creating a population network (Fig. S6a–d). Three distinct recent migration events were best explaining the data with specific migration routes from the Middle East/African clusters to North America, from an Australian cluster to South America and between two Oceanian clusters (Fig. S6d). However, the migration events did not affect the overall shape of the inferred population tree (Fig. 2c, Fig. S6b–d). To better understand effects of long-distance gene flow, we investigated the relationship between relatedness among genotypes (i.e., identity-by-state) and geographic distance. At the continent level, we observed a negative relationship between identity-by-state and geographic distance (Fig. S7). The wide distribution of identity-by-state values shows that although closely related isolates tend to be found at closer geographic distance, distantly related isolates can be found at both far and close geographic distances. Long-distance migration events are most likely caused by international trade similar as for other crop pathogens17,18,19. In combination, our findings show an important role of long-distance dispersal impacting the genetic make-up of populations from individual fields to continental scale genetic diversity.Relaxation of genomic defenses against transposable elements concurrent with global spreadTransposable elements (TEs) are drivers of genome evolution. In Z. tritici, TE activity created beneficial mutations for fungicide resistance and virulence on the wheat host20,21. Rapid recent adaptation of the pathogen has benefitted from the activity of TEs with consequences for genome size22. Unchecked transposition of TEs can be deleterious and an array of defenses mechanisms has evolved to counteract their activity both at the genomic and epigenetic level including targeted mutations and silencing23. To analyze the effectiveness of genomic defenses against active TEs, we screened all genomes for evidence of TE insertions. We mapped short-read sequencing data on the reference genome and a species-specific TE sequence library. We classified evidence for TEs in each of the analyzed isolates as reference TEs (i.e. also present in the reference genome) and non-reference TE (i.e. absent). Detected TEs among isolates were binned into loci (width 100 bp) to account for uncertainties about the precise mapping of the insertion point. We found that the frequency spectrum of TE insertions is heavily skewed towards low frequencies with 77% of TE insertions being found in single isolates (~0.1% frequency) and 96% of insertions were found in ten or fewer isolates ( More

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    Enzyme adaptation to habitat thermal legacy shapes the thermal plasticity of marine microbiomes

    Extraction of total active proteomes from sediment samplesWe sampled 14 sediments along the coastlines of the Irish Sea, the Mediterranean Sea, and the Red Sea (from 16°N to 53°N), applying uniform sampling and storage procedures. Location details and sediment temperature fluctuations are summarized in Supplementary Table S1. We collected sediments (5 Kg) in triplicate and extracted the total proteins using a well-established microbial detachment procedure67, with some modifications. We mixed 100 g of sediment with 300 ml of sterilized saline solution (5 mM sodium pyrophosphate and 35 g L−1 of NaCl) containing 150 mg L−1 of Tween 80 (from Merck Life Science S.L.U., Madrid, Spain) in an ice water bath. After re-suspension, samples were kept in a water bath ultra-sonicator (Bandelin SONOREX, Berlin, Germany) on ice and sonicated (60 W output) for 120 min. We repeated this procedure twice, with an ice water bath incubation of 60 min between each cycle. We then centrifuged the samples at 500 g for 15 min at 4 °C to remove the sediments in a centrifuge 5810 R (Eppendorf AG, Hamburg, Germany). Supernatants were carefully transferred to a new tube, minimizing disruption of the sediments, and the resulting supernatants were centrifuged at 13,000 g for 15 min at 4 °C to produce microbial cell pellets. We used the resulting cell mix to extract the total protein by mixing the cells with 1.2 ml BugBuster® Protein Extraction Reagent (Novagen, Darmstadt, Germany) for 30 min with shaking (250 rpm). Subsequently, samples were disrupted by sonication using a pin Sonicator® 3000 (Misonix, New Highway Farmingdale, NY, USA) for a total time of 2 min (10 watts) on ice (4 cycles × 0.5 min with 1 min ice-cooling between each cycle). Extracts were centrifuged for 10 min at 12,000 g at 4 °C to separate cellular debris and intact cells. Supernatants were carefully aspirated (to avoid disturbing the pellet), transferred to new tubes, and stored at –80 °C until use. The protein solution was filtered at 15 °C for 7 h using Vivaspin filters (Sartorius, Goettingen, Germany) with a molecular weight (MW) cut-off of 3,000 Da to concentrate the proteins up to a final concentration of 10 mg ml−1, according to the Bradford Protein Assay (Bio-Rad Laboratories, S.A., Madrid, Spain)68. The average total amount of proteins extracted per each 100 g of sediment was 612 µg (interquartile range, 31 µg, see details in Supplementary Fig. S2). In all cases, extensive dialysis of protein solutions against 40 mM 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES) buffer was performed using a Pur-A-LyzerTM Maxi 1200 dialysis kit (Merck Life Science S.L.U., Madrid, Spain)69, and active proteins stored at a concentration of 10 mg ml−1at –86 °C until use. As reported previously70, 2DE was performed using GE Healthcare reagents and equipment, 11 cm IPG strips in the pH range of 3–10 and molecular weight ranging from 10 to 250 kDa (Precision Plus Protein Dual Color Standards #1610374, Bio-Rad Laboratories, S.A., Madrid, Spain). The 2-DE was performed using a validated pooling strategy71, in which proteins extracted from three independent biological replicates (i.e., sediments) were mixed in equal amounts and a total of 150 µg of protein were further loaded per gel. Staining was performed with SYPRO Ruby Protein Gel Stain (Invitrogen, Waltham, MA, USA). The two-dimensional SDS-PAGE (12% acrylamide) gels of extracted proteins are reported in Supplementary Fig. S2 (original gels in Source Data). The same protocol was applied to extract and analyse by SDS-PAGE the total active proteins extracted from sediment samples with different temperature variability levels (HTV, ITV, and LTV) collected in the Red Sea (Supplementary Table S4). The total amount of protein extracted per each 100 g of sediment is given in Supplementary Table S8. Coomassie-stained one-dimension SDS-PAGE (1-DE) gels of extracted proteins are shown in Supplementary Fig. S9 (original gel in Source Data).Source, expression and purification of esterases and EXDOs from a wide geographical rangeWe recovered 83 enzymes (78 esterases and 5 EXDO) from microbial communities inhabiting marine sediments across ten distinct locations from the latitudinal transect described above: Ancona harbour (Anc), Priolo Gargallo (Pri), Gulf of Genoa, Messina harbour (Mes), Milazo harbour (Mil), Mar Chica lagoon (MCh), Bizerte lagoon (Biz), El-Max site (ElMax), Gulf of Aqaba (Aq), and Menai Strait (MS); further details are provided in Supplementary Data S3. Sources of the enzymes were the corresponding shotgun metagenomes (see Supplementary Table S3) and the metagenome clone libraries generated from the extracted DNA71. The sediment sample from the Gulf of Genoa was not used for activity tests and metaproteome analysis because no raw sample material was available; however, because of the possibility to access its shotgun metagenome (see Supplementary Table S3) and a metagenome clone library72, we used the sample for screening esterases to incorporate an additional latitude in our transect. In the case of Menai Strait (Irish Sea), five additional esterases were retrieved from a metagenome obtained from enriched cultures prepared with samples collected on 22nd June 2019 from Menai Strait (School of Ocean Sciences, Bangor University, St. George’s Pier, Menai Bridge, N53°13′31.3″; W4°09′33.3”). The water temperature was 14 °C and the salinity was 32 p.s.u. Two enrichment cultures were set up at 20 °C: (i) SW: seawater enrichment with 0.1% lignin; the enrichment was set up using 50 ml of the sample as inoculum with the addition of 0.1% lignin (Sigma-Aldrich, Gillingham, United Kingdom) (w/v); (ii) AW: algal surface wash-off in seawater, enriched with 0.1% lignin; the enrichment was set up using 50 ml of surface wash-off after mixing of ca. 10 g of Fucus (brown algae) in the seawater and removal of plant tissue, 0.1% lignin (w/v) was added. After 92 days of incubation, 5 ml of each enrichment cultures were transferred into the new flask containing 45 ml autoclaved and filtered seawater with 0.1% lignin. This procedure was repeated on days 185 and 260, and the incubation was stopped on day 365. The DNA was extracted using 12 months using MetaGnome extraction kit (EpiCentre, Biotechnologies, Madison, WI, USA), sequenced on Illumina MiSeq™ platform (Illumina Inc., San Diego, CA, USA) using paired-end 250 bp reads at the Centre for Environmental Biotechnology (Bangor, UK), and sequencing reads were processed and analysed as described previously73.The screening, cloning and activity of a subset of 35 identified esterases have been reported previously72. The remaining 48 enzymes are reported for the first time in this study and were identified using naive and in silico metagenomic approaches, as detailed below. The environmental site from which each enzyme originated and the method employed for its identification are detailed in Supplementary Data S3. For naive screens addressing the recovery of new sequences encoding esterases and EXDO, the large-insert pCCFOS1 fosmid libraries made using the corresponding DNA samples, the CopyControl Fosmid Library Kit (Epicentre Biotechnologies, Madison, WI, USA) and the Escherichia coli EPI300-T1R strain were used. The nucleic acid extraction, construction and the functional screens of such libraries have been previously described72. In brief, fosmid clones were plated onto large (22.5 × 22.5 cm) Petri plates with Luria Bertani (LB) agar containing chloramphenicol (12.5 µg ml−1) and induction solution (Epicentre Biotechnologies; WI, USA), at a quantity recommended by the supplier to induce a high fosmid copy number. Clones were scored by the ability to hydrolyze α-naphthyl acetate and tributyrin (for esterase activity), and catechol (for EXDO activity)72,74. Positive clones presumed to contain esterases and EXDOs were selected, and their DNA inserts were sequenced using a MiSeq Sequencing System (Illumina, San Diego, USA) with a 2 × 150-bp sequencing v2 kit at Lifesequencing S.L. (Valencia, Spain). After sequencing, the reads were quality-filtered and assembled to generate nonredundant meta-sequences, and genes were predicted and annotated via BLASTP and the PSI-BLAST tool72. For in silico screens, addressing the recovery of new sequences encoding esterases, the predicted protein-coding genes, obtained after the sequencing of DNA material from resident microbial communities in each of the samples, were used. The meta-sequences are available from the National Center for Biotechnology Information (NCBI) nonredundant public database (accession numbers reported in Supplementary Data S3). Protein-coding genes identified from the DNA inserts of positive clones (naive screen) or from the meta-sequences were screened for enzymes of interest using the Blastp algorithm via the DIAMOND v2.0.9 program with default parameters (percentage of identity ≥60%; alignment length ≥70; e-value ≤1e−5)29, against the Lipase Engineering sequence databases (to screen for esterases) and AromaDeg database (for EXDO)74. Since the collection of sediments across locations experiencing different MATs was limited by our sampling capacity, to expand our range of exploration at a global scale and to validate our dataset, we added our single enzyme analysis to the seawater metagenomes retrieved from the Tara Ocean Expedition database (accession number in Supplementary Data S4). Due to the volume of sequences generated, this database provides access to a large number of enzymes, including those studied here through homology search. Esterases were selected as target sequences, and the following pipeline was used. First, we selected a sequence encoding an esterase reported as one of the most substrate-ambiguous esterases out of 145 tested (EH1, Protein Data Bank acc. nr. 5JD4) and well-distributed in the marine environment72. Second, we performed a homology search of this sequence against the Tara Ocean metagenome21 to retrieve similar sequences, using the Blastp algorithm via the DIAMOND v2.0.9 program30 (e-value 98% using SDS-PAGE analysis in a Mini PROTEAN electrophoresis system (Bio-Rad Laboratories, S.A., Madrid, Spain). Purified protein was stored at –86 °C until use at a concentration of 10 mg ml−1 in 40 mM HEPES buffer (pH 7.0). A total of approximately 5–40 mg of total purified recombinant protein was obtained from 1 L of culture. Supplementary Fig. S1 illustrates a schematic representation of the pipeline implemented in this work to investigate enzyme activities in a large set of marine samples, starting from samples collected (sediments) and available metagenomes.Enzyme activity assessmentsAll substrates used for activity tests were of the highest purity and, if not indicated otherwise, were obtained from Merck Life Science S.L.U. (Madrid, Spain): 4-nitrophenyl-propionate (ref. MFCD00024664), 4-nitrophenyl phosphate (ref. 487663), 4-nitrophenyl β-D-galactose (ref. N1252), bis(p-nitrophenyl) phosphate (ref. 123943), benzaldehyde (ref. B1334), 2-(4-nitrophenyl)ethan-1-amine (ref. 184802-5G), pyridoxal phosphate (ref. P9255), acetophenone (ref. A10701), NADPH (ref. N5130) and catechol (ref. PHL82372). We directly tested total protein extracts for esterase, phosphatase, beta-galactosidase, and nuclease activity using 4-nitrophenyl-propionate, 4-nitrophenyl phosphate, 4-nitrophenyl β-D-galactose, and bis(p-nitrophenyl) phosphate, respectively, by following the production of 4-nitrophenol at 348 nm (extinction coefficient [ε], 4147 M−1 cm−1), as previously described69. For determination: [total protein]: 5 μg ml−1; [substrate]: 0.8 mM; reaction volume: 200 μl; T: 4–85 °C; and pH: 8.0 (50 mM Tris-HCl buffer). The hydrolysis of 4-nitrophenyl-propionate was used to determine, under these standard conditions, the effects of temperature on the purified esterase. Transaminase activity was determined using benzaldehyde as amine acceptor, 2-(4-nitrophenyl)ethan-1-amine as amine donor, and pyridoxal phosphate as a cofactor, by following the production of a colour amine at 600 nm (extinction coefficient, 537 M−1 cm−1), as previously described75. For determination, [total protein]: 5 μg ml−1; [substrates]: 25 mM; [pyridoxal phosphate]: 1 mM; reaction volume: 200 μL; T: 4-85 °C; and pH: 8.0 (50 mM Tris-HCl buffer). Aldo-keto reductase activity was determined using acetophenone as a substrate and NADPH as a cofactor, by following the consumption of NADPH at 340 nm (extinction coefficient, 6220 M−1 cm−1), as described76. For determination, [total protein]: 5 μg ml−1; [substrate]: 1 mM; [cofactor]: 1 mM; reaction volume: 200 μL; T: 4–85 °C; and pH: 8.0 (50 mM Tris-HCl buffer). We determined EXDO activity using catechol as substrate, by following the increase of absorbance at 375 nm of the ring fission products (extinction coefficient, 36000 M−1 cm−1), as previously described74. For determination, [protein]: 5 μg ml−1; [catechol]: 0.5 mM; reaction volume: 200 μL; T: 4–85 °C; and pH: 8.0 (50 mM Tris-HCl buffer). The hydrolysis of catechol was used to determine, under these standard conditions, the effects of temperature on the purified EXDOs. All measurements were performed in 96-well plates (ref. 655801, Greiner Bio-One GmbH, Kremsmünster, Austria), in biological triplicates over 180 min in a Synergy HT Multi-Mode Microplate Reader (Biotek Instruments, Winooski, VT, USA) in continuous mode (measurements every 30 s) and determining the absorbance per minute from the slopes generated and applying the formula (1). All values were corrected for nonenzymatic transformation.$${Rate}left(frac{mu {mol}}{{{min }}{mg},{protein}}right)= frac{frac{triangle {{{{{rm{Abs}}}}}}}{{{min }}}}{{{{{{rm{varepsilon }}}}}},{{{{{rm{M}}}}}}-1{{{{{rm{cm}}}}}}-1}*frac{1}{0.4,{cm}}*frac{{10}^{6},mu M}{1{{{{{rm{M}}}}}}}\ *0.0002,L*frac{1}{{mg},{protein}}$$
    (1)
    Shotgun proteomicsProteomics was performed by using total active proteins (extracted as above), which were then subjected to protein precipitation, protein digestion and Liquid Chromatography-Electrospray Ionization Tandem Mass Spectrometric (LC-ESI-MS/MS) analysis, as previously described77. High-quality reference metagenomes corresponding to each sample (BioProject number in Supplementary Table S3) were used for protein calling, with a threshold of only one identified peptide per protein identification because False Discovery Rates (FDR) controlled experiments counter-intuitively suffer from the two-peptide rule. The confidence interval for protein identification was set to ≥95% (p  50 °C for which the second phase transition was chosen to focus on the decomposition of the core. It is important to note that applying CNA to MD simulations at room temperature may lead to an evening out of Tp values for esterases that transition around this temperature, i.e., systems with a Tp at or below room temperature might all be influenced similarly by loosening their bonding network. By contrast, systems with a transition temperature at or above room temperature would still be discriminated against. The data generated in this study for analyzing Tp values have been deposited at researchdata.hhu.de under accession code DOI: 10.25838/d5p-42101 [https://doi.org/10.25838/d5p-42].Relationship of temperature-induced changes in enzymeRelationship between MAT and enzyme response to temperature (i.e., Topt, Td and Tp) were evaluated by performing linear regression in R. In the case of enzymes retrieved from the Tara ocean dataset we calculated first the break point (flexus) using the package segmented in R102 and then we computed separately the linear model describing the two linear regressions before and after the breakpoint. To evaluate the possible relation between enzyme thermal response and other environmental parameters, salinity and pH data were retrieved from Bio-ORACLE52 using GPS coordinates of each location.Environmental characterization and sediment collection from different temperature variability levels in the Red SeaWe recorded the temperatures of surface sediments from March 2015 to September 2016 along the coast of the Red Sea using HOBO data loggers (Onset, USA) in nine stations located at 3, 25, and 50 m depth. Details on the location, depth and temperature fluctuations of the studied sediments are reported in Supplementary Table S4 and Source Data. We first assess the differences in the homogeneity of the temperature variance in the three types of sediments to evaluate the magnitude of thermal variation and then we test the difference among their MATs using a non-parametric ANOVA (Dunnett’s multiple comparisons tests). We identified three different levels of temperature variability (Fig. 3a–c; Supplementary Table S5): high, intermediate, and low thermal variability (HTV, ITV, and LTV, respectively), where sediments experienced temperature variations of 12.8 °C, 8.8 °C, and 6.7 °C, respectively. From each station, we sampled 200 g of surface sediment (0–5 cm depth) in triplicate in August and December 2015 with a Van der Venn grab (1 dm3) equipped with a MicroCat 250 Seabird CTD (Conductivity, Temperature, Depth), which was assembled on board the research vessel R/V Explorer (KAUST). During sampling, we measured the temperature of the sediments and the water layer covering the sediments using a digital thermometer and the CTD, respectively. We conducted all sampling in compliance with the guidelines specified by KAUST and Saudi Arabian authorities.Sediment processing for analysis of bacterial communitiesFrom each sample (in triplicate), we immediately removed subsamples of sediment (n = 54, ~10 g) and stored them at –20 °C for molecular analysis. Separately, sediment 25 ± 1 g was transferred to 50 ml tubes and added 30 ml of filtered (0.2 µm) water from the Red Sea. The tubes were shaken at 500 rpm for one hour and then centrifuged them at 300 g for 15 min to detach the microbial cells in the sediments without affecting their vitality103,104. The supernatant containing the extracted cells was collected in sterile tubes and was immediately used to measure microbial growth rates.Evaluation of bacterial growth in sediments at different temperaturesWe evaluated the microbial growth rate of the heterotrophic community extracted from the sediments under HTV, ITV, and LTV at 10 °C, 20 °C, 30 °C, 40 °C and 50 °C, using Marine Broth as the cultivation medium (Zobell Marine Broth 2216) supplemented with 0.1 g/L cycloheximide; a rich-medium was selected to avoid the nutrient limitation effect that can affect bacterial physiology63,105. We inoculated 96-well plates with 200 µl of cultivation medium and 25 µl of the cell suspension extracted from the sediments. We inoculated the three biological replicates from each station and each level of temperature variability in eight wells, giving a total of 72 wells for each plate, with 24 wells used as a negative control inoculated with water. We assembled a total of three plates for each incubation temperature from August and December. Plates were spectrophotometrically measured at 3 h intervals using an optical density of 600 nm (Spectramax® M5) for 72 h. Wells with optical density 90%) for further analysis (Supplementary Tables S9 and S10). We calculated the compositional similarity matrix (Bray-Curtis of the log-transformed OTU table) with Primer 6109. Using the same software, canonical analysis of principal coordinates (CAP)110 was used to compare the temperature variability samples (temperature variability levels: HTV, ITV, and LTV; season levels: August and December) based on the compositional similarity matrix. We applied permutational multivariate analyses of variance to the matrix (PERMANOVA; main and multiple comparison tests). We tested the occurrence of thermal-decay patterns in sediments with different temperature variability levels using linear regression (Prism 9.2 software, La Jolla California USA, www.graphpad.com) between the bacterial community similarities (Bray-Curtis) and the temperature differences among sediments (∆T°C) at the time of sampling. We calculated alphadiversity indices (richness and evenness) using the paleontological statistics (PAST) software, and their correlation with temperature was modelled using linear regression in Prism 9.2. Spearman correlation among temperature and relative abundance of OTUs within each sediment sample was evaluated; OTUs were classified based on their positive (enriched) and negative (depleted) correlation with sediment temperature.Reporting summaryFurther information on research design is available in the Nature Portfolio Reporting Summary linked to this article. More

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    Malaria-driven adaptation of MHC class I in wild bonobo populations

    World Health Organization. World malaria report 2022. (2022).Kariuki, S. N. & Williams, T. N. Human genetics and malaria resistance. Hum. Gen. 139, 801–811 (2020).Article 

    Google Scholar 
    Watson, J. A., White, N. J. & Dondorp, A. M. Falciparum malaria mortality in sub-Saharan Africa in the pretreatment era. Trends Parasitol. 38, 11–14 (2022).Article 
    CAS 
    PubMed 

    Google Scholar 
    Sanchez-Mazas, A. A review of HLA allele and SNP associations with highly prevalent infectious diseases in human populations. Swiss Med. Wkly. 150, w20214 (2020).PubMed 

    Google Scholar 
    Heijmans, C. M. C., de Groot, N. G. & Bontrop, R. E. Comparative genetics of the major histocompatibility complex in humans and nonhuman primates. Int. J. Immunogenet. 47, 243–260 (2020).Article 
    CAS 
    PubMed 

    Google Scholar 
    Neefjes, J., Jongsma, M. L., Paul, P. & Bakke, O. Towards a systems understanding of MHC class I and MHC class II antigen presentation. Nat. Rev. Immunol. 11, 823–836 (2011).Article 
    CAS 
    PubMed 

    Google Scholar 
    Zinkernagel, R. M. & Doherty, P. C. Restriction of in vitro T cell-mediated cytotoxicity in lymphocytic choriomeningitis within a syngeneic or semiallogeneic system. Nature 248, 701–702 (1974).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Colonna, M. & Samaridis, J. Cloning of Immunoglobulin-Superfamily Members Associated with HLA-C and HLA-B Recognition by Human Natural Killer Cells. Science 268, 405–408 (1995).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Hill, A. V. et al. Common west African HLA antigens are associated with protection from severe malaria. Nature 352, 595–600 (1991).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Sanchez‐Mazas, A. et al. The HLA‐B landscape of Africa: signatures of pathogen‐driven selection and molecular identification of candidate alleles to malaria protection. Mol. Ecol. 26, 6238–6252 (2017).Article 
    PubMed 

    Google Scholar 
    Hill, A. V. et al. Molecular analysis of the association of HLA-B53 and resistance to severe malaria. Nature 360, 434–439 (1992).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Norman, P. J. et al. Co-evolution of human leukocyte antigen (HLA) class I ligands with killer-cell immunoglobulin-like receptors (KIR) in a genetically diverse population of sub-Saharan Africans. PLoS Genet. 9, e1003938 (2013).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Sharp, P. M., Plenderleith, L. J. & Hahn, B. H. Ape origins of human malaria. Annu. Rev. Microbiol. 74, 39–63 (2020).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Liu, W. et al. Wild bonobos host geographically restricted malaria parasites including a putative new Laverania species. Nat. Commun. 8, 1635 (2017).Liu, W. et al. African origin of the malaria parasite Plasmodium vivax. Nat. Commun. 5, 3346 (2014).Article 
    ADS 
    PubMed 

    Google Scholar 
    Liu, W. et al. Origin of the human malaria parasite Plasmodium falciparum in gorillas. Nature 467, 420–425 (2010).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Liu, W. et al. Multigenomic delineation of Plasmodium species of the Laverania subgenus infecting wild-living chimpanzees and gorillas. Genome Biol. Evol. 8, 1929–1939 (2016).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    De Nys, H. M. et al. Age-related effects on malaria parasite infection in wild chimpanzees. Biol. Lett. 9, 20121160 (2013).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    De Nys, H. M. et al. Malaria parasite detection increases during pregnancy in wild chimpanzees. Malar. J. 13, 1–6 (2014).
    Google Scholar 
    Mapua, M. I. et al. Ecology of malaria infections in western lowland gorillas inhabiting Dzanga Sangha Protected Areas, Central African Republic. Parasitology 142, 890–900 (2015).Article 
    PubMed 

    Google Scholar 
    Scully, E. J. et al. The ecology and epidemiology of malaria parasitism in wild chimpanzee reservoirs. Commun. Biol. 5, 1020 (2022).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Herbert, A. et al. Malaria-like symptoms associated with a natural Plasmodium reichenowi infection in a chimpanzee. Malar. J. 14, 1–8 (2015).Article 

    Google Scholar 
    De Nys, H. M., Löhrich, T., Wu, D., Calvignac-Spencer, S. & Leendertz, F. H. Wild African great apes as natural hosts of malaria parasites: current knowledge and research perspectives. Primate Biol. 4, 47–59 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Takemoto, H., Kawamoto, Y. & Furuichi, T. How did bonobos come to range south of the congo river? Reconsideration of the divergence of Pan paniscus from other Pan populations. Evol. Anthropol. 24, 170–184 (2015).Article 
    PubMed 

    Google Scholar 
    Takemoto, H., Kawamoto, Y. & Furuichi, T. The formation of Congo River and the origin of bonobos: A new hypothesis. in Bonobos: unique in mind, brain, and behavior (eds. Hare, B. & Yamamoto, S.) 235-248 (Oxford University Press, 2017).Takemoto, H. et al. The mitochondrial ancestor of bonobos and the origin of their major haplogroups. PLoS One. 12, e0174851 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Pilbrow, V. & Groves, C. Evidence for divergence in populations of bonobos (Pan paniscus) in the Lomami-Lualaba and Kasai-Sankuru regions based on preliminary analysis of craniodental variation. Int. J. Primatol. 34, 1244–1260 (2013).Article 

    Google Scholar 
    de Groot, N. G., Stevens, J. M. & Bontrop, R. E. Does the MHC confer protection against malaria in bonobos? Trends Immunol. 39, 768–771 (2018).Article 
    PubMed 

    Google Scholar 
    Sidney, J., Peters, B., Frahm, N., Brander, C. & Sette, A. HLA class I supertypes: a revised and updated classification. BMC Immunol. 9, 1 (2008).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Wroblewski, E. E. et al. Bonobos maintain immune system diversity with three functional types of MHC-B. J. Immunol. 198, 3480–3493 (2017).Article 
    CAS 
    PubMed 

    Google Scholar 
    Bjorkman, P. et al. The foreign antigen binding site and T cell recognition regions of class I histocompatibility antigens. Nature 329, 512–518 (1987).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Guethlein, L. A., Norman, P. J., Hilton, H. G. & Parham, P. Co-evolution of MHC class I and variable NK cell receptors in placental mammals. Immunol. Rev. 267, 259–282 (2015).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Wroblewski, E. E. et al. Signature patterns of MHC diversity in three Gombe communities of wild chimpanzees reflect fitness in reproduction and immune defense against SIVcpz. PLoS. Biol. 13, e1002144 (2015).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Li, Y. et al. Eastern chimpanzees, but not bonobos, represent a simian immunodeficiency virus reservoir. J. Virol. 18, 10776–10791 (2012).Article 

    Google Scholar 
    Yang, C. et al. Sequence variations in the non-repetitive regions of the liver stage-specific antigen-1 (LSA-1) of Plasmodium falciparum from field isolates,. Mol. Biochem Parasitol. 71, 291–294 (1995).Article 
    CAS 
    PubMed 

    Google Scholar 
    Fidock, D. A. et al. Plasmodium falciparum liver stage antigen-1 is well conserved and contains potent B and T cell determinants. J. Immunol. 153, 190–204 (1994).Article 
    CAS 
    PubMed 

    Google Scholar 
    Aurrecoechea, C. et al. PlasmoDB: a functional genomic database for malaria parasites. Nucl. Acids Res. 37, D539–D543 (2009).Article 
    CAS 
    PubMed 

    Google Scholar 
    Hughes, A. L. & Yeager, M. Natural selection at major histocompatibility complex loci of vertebrates. Annu. Rev. Genet. 32, 415–435 (1998).Article 
    CAS 
    PubMed 

    Google Scholar 
    Trowsdale, J. The MHC, disease and selection. Immunol. Lett. 137, 1–8 (2011).Article 
    CAS 
    PubMed 

    Google Scholar 
    Crow, J. & Kimura, M. An Introduction To Population Genetics Theory. (Alpha Editions, 1970).Prado-Martinez, J. et al. Great ape genetic diversity and population history. Nature 499, 471 (2013).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Digitale, J. C. et al. HLA alleles B* 53:01 and C* 06:02 are associated with higher risk of P. falciparum parasitemia in a cohort in Uganda. Front. Immunol. 12, 650028 (2021).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lyke, K. E. et al. Association of HLA alleles with Plasmodium falciparum severity in Malian children. Tissue Antigens. 77, 562–571 (2011).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Osafo-Addo, A. D. et al. HLA-DRB1*04 allele is associated with severe malaria in northern Ghana. Am. J. Trop. Med. 78, 251–255 (2008).Article 

    Google Scholar 
    Jallow, M. et al. Genome-wide and fine-resolution association analysis of malaria in West Africa. Nat. Genet. 41, 657–665 (2009).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Malaria Genomic Epidemiology Network. Insights into malaria susceptibility using genome-wide data on 17,000 individuals from Africa, Asia and Oceania. Nat. Commun. 10, 5732 (2019).Article 
    ADS 
    CAS 

    Google Scholar 
    Ravenhall, M. et al. Novel genetic polymorphisms associated with severe malaria and under selective pressure in North-eastern Tanzania. PLoS Genet. 14, e1007172 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Damena, D., Denis, A., Golassa, L. & Chimusa, E. R. Genome-wide association studies of severe P. falciparum malaria susceptibility: progress, pitfalls and prospects. BMC Med. Genom. 12, 1–14 (2019).Article 
    CAS 

    Google Scholar 
    Kennedy, A. E., Ozbek, U. & Dorak, M. T. What has GWAS done for HLA and disease associations? Int. J. Immunogenet. 44, 195–211 (2017).Article 
    CAS 
    PubMed 

    Google Scholar 
    Tukwasibwe, S. et al. Variations in killer-cell immunoglobulin-like receptor and human leukocyte antigen genes and immunity to malaria. Cell. Mol. Immunol. 17, 799–806 (2020).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Leffler, E. M. et al. Multiple instances of ancient balancing selection shared between humans and chimpanzees. Science 339, 1578–1582 (2013).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Phillips, M. et al. Malaria. Nat. Rev. Dis. Prim. 3, 17050 (2017).Article 
    PubMed 

    Google Scholar 
    Samandary, S. et al. Associations of HLA-A, HLA-B and HLA-C alleles frequency with prevalence of herpes simplex virus infections and diseases across global populations: implication for the development of an universal CD8+ T-cell epitope-based vaccine. Hum. Immunol. 75, 715–729 (2014).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Miranda-Katz, M. et al. Novel HLA-B7-restricted human metapneumovirus epitopes enhance viral clearance in mice and are recognized by human CD8+ T cells. Sci. Rep. 11, 20769 (2021).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Appanna, R., Ponnampalavanar, S., Lum Chai See, L. & Sekaran, S. D. Susceptible and protective HLA class 1 alleles against dengue fever and dengue hemorrhagic fever patients in a Malaysian population. PloS One 5, e13029 (2010).Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Gao, X. et al. Effect of a single amino acid change in MHC class I molecules on the rate of progression to AIDS. NEJM 344, 1668–1675 (2001).Article 
    CAS 
    PubMed 

    Google Scholar 
    Sharp, P. M. & Hahn, B. H. Origins of HIV and the AIDS pandemic. Cold Spring Harb. Perspect. Med. 1, a006841 (2011).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Barbian, H. J. et al. CHIIMP: An automated high‐throughput microsatellite genotyping platform reveals greater allelic diversity in wild chimpanzees. Ecol. Evol. 8, 7946–7963 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Sullivan, K. M., Mannucci, A., Kimpton, C. P. & Gill, P. A rapid and quantitative DNA sex test: fluorescence-based PCR analysis of X-Y homologous gene amelogenin. Biotechniques 15, 636–638 (1993). 640-631.CAS 
    PubMed 

    Google Scholar 
    de Groot, N. G. et al. Nomenclature report 2019: major histocompatibility complex genes and alleles of Great and Small Ape and Old and New World monkey species. Immunogenet 72, 25–36 (2020).Article 

    Google Scholar 
    Zhang, J., Kobert, K., Flouri, T. & Stamatakis, A. PEAR: a fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics 30, 614–620 (2014).Article 
    CAS 
    PubMed 

    Google Scholar 
    Thomsen, M., Lundegaard, C., Buus, S., Lund, O. & Nielsen, M. MHCcluster, a method for functional clustering of MHC molecules. Immunogenet 65, 655–665 (2013).Article 
    CAS 

    Google Scholar 
    Maibach, V. & Vigilant, L. Reduced bonobo MHC class I diversity predicts a reduced viral peptide binding ability compared to chimpanzees. BMC Evol. Biol. 19, 1–15 (2019).Article 

    Google Scholar 
    Wroblewski, E. E., Parham, P. & Guethlein, L. A. Two to tango: co-evolution of hominid natural killer cell receptors and MHC. Front. Immunol. 10 https://doi.org/10.3389/fimmu.2019.00177 (2019).Raymond, M. GENEPOP (version 1.2): population genetics software for exact tests and ecumenicism. J. Hered. 86, 248–249 (1995).Article 

    Google Scholar 
    Rousset, F. GENEPOP’007: a complete re‐implementation of the GENEPOP software for Windows and Linux. Mol. Ecol. Resour. 8, 103–106 (2008).Article 
    PubMed 

    Google Scholar 
    Wilson, M. L. et al. Lethal aggression in Pan is better explained by adaptive strategies than human impacts. Nature 513, 414–417 (2014).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Cheng, L., Samuni, L., Lucchesi, S., Deschner, T. & Surbeck, M. Love thy neighbour: behavioural and endocrine correlates of male strategies during intergroup encounters in bonobos. Anim. Behav. 187, 319–330 (2022).Article 

    Google Scholar 
    Lucchesi, S. et al. Beyond the group: how food, mates, and group size influence intergroup encounters in wild bonobos. Behav. Ecol. 31, 519–532 (2020).Article 

    Google Scholar 
    Plumptre, A., Robbins, M. M. & Williamson, E. A. Gorilla beringei. The IUCN Red List of Threatened Species 2019: e.T39994A115576640. (2019).Maisels, F., Bergl, R. A. & Williamson, E. A. Gorilla gorilla (amended version of 2016 assessment). The IUCN Red List of Threatened Species 2018: e.T9404A136250858. (2018).Humle, T., Maisels, F., Oates, J.F., Plumptre, A. & Williamson, E.A. Pan troglodytes (errata version published in 2018). The IUCN Red List of Threatened Species 2016: e.T15933A129038584. (2016).Fruth, B. et al. Pan paniscus (errata version published in 2016). The IUCN Red List of Threatened Species 2016: e.T15932A102331567. (2016). More

  • in

    Modeling present and future distribution of plankton populations in a coastal upwelling zone: the copepod Calanus chilensis as a study case

    Tittensor, D. P. et al. Global patterns and predictors of marine biodiversity across taxa. Nature 466, 1098–1101 (2010).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    González, C. E., Medellín-Mora, J. & Escribano, R. Environmental gradients and spatial patterns of calanoid copepods in the southeast pacific. Front. Ecol. Evol. 8, 1–16 (2020).Article 

    Google Scholar 
    Rombouts, I. et al. Global latitudinal variations in marine copepod diversity and environmental factors. Proc. R. Soc. B Biol. Sci. 276, 3053–3062 (2009).Article 

    Google Scholar 
    Brandão, M. C. et al. Macroscale patterns of oceanic zooplankton composition and size structure. Sci. Rep. 11, 1–19 (2021).
    Google Scholar 
    Mcclain, C. R. & Barry, J. P. Habitat heterogeneity, disturbance, and productivity work in concert to regulate biodiversity in deep submarine canyons. Ecology 91, 964–976 (2010).Article 
    PubMed 

    Google Scholar 
    Escribano, R. & Rodriguez, L. Life cycle of Calanus chilensis Brodsky in Bay of San Jorge, Antofagasta Chile. Hydrobiologia 292–293, 289–294 (1994).Article 

    Google Scholar 
    Strub, P. T., Mesías, M. J., Montecino, V., Rutllant, J. & Salinas, S. Coastal ocean circulation off western South America coastal segment. Sea 11, 273–313 (1998).
    Google Scholar 
    Montecino, V. & Lange, C. The Humboldt current system: Ecosystem components and processes, fisheries, and sediment studies. Prog. Oceanogr. 83, 65–79 (2009).Article 
    ADS 

    Google Scholar 
    Miloslavich, P. et al. Marine biodiversity in the Atlantic and Pacific coasts of South America: Knowledge and gaps. PLoS ONE 6, e14631 (2011).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Marín, V., Espinoza, S. & Fleminger, A. Morphometric study of Calanus chilensis males along the Chilean coast. Hydrobiologia 292, 75–80 (1994).Article 

    Google Scholar 
    Escribano, R. & McLaren, I. Production of Calanus chilensis in the upwelling area of Antofagasta Northern Chile. Mar. Ecol. Prog. Ser. 177, 147–156 (1999).Article 
    ADS 

    Google Scholar 
    Escribano, R. & Hidalgo, P. Spatial distribution of copepods in the north of the Humboldt Current region off Chile during coastal upwelling. J. Mar. Biol. Assoc. U. K. 80, 283–290 (2000).Article 

    Google Scholar 
    Hirche, H. J., Barz, K., Ayon, P. & Schulz, J. High resolution vertical distribution of the copepod Calanus chilensis in relation to the shallow oxygen minimum zone off northern Peru using LOKI, a new plankton imaging system. Deep Res. I Oceanogr. Res. Pap. 88, 63–73 (2014).Article 
    ADS 
    CAS 

    Google Scholar 
    Sabatini, M., rez, F. & Martos, P. Distribution pattern and population structure of Calanus australis Brodsky, 1959 over the southern Patagonian Shelf off Argentina in summer. ICES J. Mar. Sci. 57, 1856–1866 (2000).Article 

    Google Scholar 
    Escribano, R. Population dynamics of Calanus chilensis in the Chilean Eastern Boundary Humboldt Current. Fish. Oceanogr. 7, 245–251 (1998).Article 

    Google Scholar 
    Hidalgo, P. et al. Patterns of copepod diversity in the Chilean coastal upwelling system. Deep Sea Res. Part II Top. Stud. Oceanogr. 57, 2089–2097 (2010).Article 
    ADS 

    Google Scholar 
    Hidalgo, P., Escribano, R., Fuentes, M., Jorquera, E. & Vergara, O. How coastal upwelling influences spatial patterns of size-structured diversity of copepods off central-southern Chile (summer 2009). Prog. Oceanogr. 92–95, 134–145 (2012).Article 
    ADS 

    Google Scholar 
    Giraldo, A., Escribano, R. & Marin, V. Spatial distribution of Calanus chilensis off Mejillones Peninsula (northern Chile): Ecological consequences upon coastal upwelling. Mar. Ecol. Prog. Ser. 230, 225–234 (2002).Article 
    ADS 

    Google Scholar 
    Gonzalez, A. & Marin, V. Distribution and life cycle of Calanus chilensis and Centropages brachiatus (Copepoda) in Chilean coastal waters: A GIS approach. Mar. Ecol. Prog. Ser. 165, 109–117 (1998).Article 
    ADS 

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

    Google Scholar 
    Parmesan, C. Influences of species, latitudes and methodologies on estimates of phenological response to global warming. Glob. Change Biol. 13, 1860–1872 (2007).Article 
    ADS 

    Google Scholar 
    Visser, M. E. & Both, C. Shifts in phenology due to global climate change: The need for a yardstick. Proc. R. Soc. B Biol. Sci. 272, 2561–2569 (2005).Article 

    Google Scholar 
    Chaudhary, C., Richardson, A. J., Schoeman, D. S. & Costello, M. J. Global warming is causing a more pronounced dip in marine species richness around the equator. Proc. Natl. Acad. Sci. 118, e2015094118 (2021).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ferrier, S., Drielsma, M., Manion, G. & Watson, G. Extended statistical approaches to modelling spatial pattern in biodiversity in northeast New South Wales. II. Community-level modelling. Biodivers. Conserv. 11, 2309–2338 (2002).Article 

    Google Scholar 
    Jetz, W., Wilcove, D. S. & Dobson, A. P. Projected impacts of climate and land-use change on the global diversity of birds. PLoS Biol. 5, e157 (2007).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Peterson, A. T. et al. Ecological Niches and Geographic Distributions (MPB-49) (Princeton University Press, 2011). https://doi.org/10.2307/j.ctt7stnh.Book 

    Google Scholar 
    Franklin, J. Spatial Inference and Prediction. Mapping Species Distributions Vol. 141 (Cambridge University Press, 2010).Book 

    Google Scholar 
    Guisan, A., Thuiller, W. & Zimmermann, N. E. Habitat Suitability and Distribution Models: With Applications in R. Ecology Biodiversity and Conservation (Cambridge University Press, 2017). https://doi.org/10.1017/9781139028271.Book 

    Google Scholar 
    Freer, J. J., Partridge, J. C., Tarling, G. A., Collins, M. A. & Genner, M. J. Predicting ecological responses in a changing ocean: The effects of future climate uncertainty. Mar. Biol. 165, 7 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Robinson, N. M., Nelson, W. A., Costello, M. J., Sutherland, J. E. & Lundquist, C. J. A systematic review of marine-based species distribution models (SDMs) with recommendations for best practice. Front. Mar. Sci. 4, 421 (2017).Article 

    Google Scholar 
    Pennino, M. G. et al. Accounting for preferential sampling in species distribution models. Ecol. Evol. 9, 653–663 (2019).Article 
    PubMed 

    Google Scholar 
    Coll, M., Pennino, M. G., Steenbeek, J., Sole, J. & Bellido, J. M. Predicting marine species distributions: Complementarity of food-web and Bayesian hierarchical modelling approaches. Ecol. Model. 405, 86–101 (2019).Article 

    Google Scholar 
    Stock, B. C. et al. Comparing predictions of fisheries bycatch using multiple spatiotemporal species distribution model frameworks. Can. J. Fish. Aquat. Sci. 77, 146–163 (2019).Article 

    Google Scholar 
    Lezama-Ochoa, N. et al. Spatio-temporal distribution of the spinetail devil ray mobula mobular in the Eastern tropical Atlantic ocean. Endanger. Species Res. 43, 447–460 (2020).Article 

    Google Scholar 
    Marshall, C. E., Glegg, G. A. & Howell, K. L. Species distribution modelling to support marine conservation planning: The next steps. Mar. Policy 45, 330–332 (2014).Article 

    Google Scholar 
    Hunt, T. N., Allen, S. J., Bejder, L. & Parra, G. J. Identifying priority habitat for conservation and management of Australian humpback dolphins within a marine protected area. Sci. Rep. 10, 1–14 (2020).Article 

    Google Scholar 
    Champion, C., Brodie, S. & Coleman, M. A. Climate-driven range shifts are rapid yet variable among recreationally important coastal-pelagic fishes. Front. Mar. Sci. 8, 1–13 (2021).Article 

    Google Scholar 
    Przeslawski, R., Falkner, I., Ashcroft, M. B. & Hutchings, P. Using rigorous selection criteria to investigate marine range shifts. Estuar. Coast. Shelf Sci. 113, 205–212 (2012).Article 
    ADS 

    Google Scholar 
    Januario, S. M., Estay, S. A., Labra, F. A. & Lima, M. Combining environmental suitability and population abundances to evaluate the invasive potential of the tunicate Ciona intestinalis along the temperate South American coast. PeerJ 3, e1357. https://doi.org/10.7717/peerj.1357 (2015).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Pinochet, J., Rivera, R., Neill, P. E., Brante, A. & Hernández, C. E. Spread of the non-native anemone Anemonia alicemartinae Häussermann & Försterra, 2001 along the Humboldt-current large marine ecosystem: An ecological niche model approach. PeerJ https://doi.org/10.7717/peerj.7156 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lh, G., Rj, R. & Brante, A. One step ahead of sea anemone invasions with ecological niche modeling: Potential distributions and niche dynamics of three successful invasive species. Mar. Ecol. Prog. Ser. 690, 83–95 (2022).Article 

    Google Scholar 
    Allynid, A. J. et al. Comparing and synthesizing quantitative distribution models and qualitative vulnerability assessments to project marine species distributions under climate change. PLoS ONE 15, 1–28 (2020).
    Google Scholar 
    Pennino, M. G. et al. Current and future influence of environmental factors on small pelagic fish distributions in the northwestern mediterranean sea. Front. Mar. Sci. 7, 1–20 (2020).Article 

    Google Scholar 
    Melo-Merino, S. M., Reyes-Bonilla, H. & Lira-Noriega, A. Ecological niche models and species distribution models in marine environments: A literature review and spatial analysis of evidence. Ecol. Model. 415, 108837 (2020).Article 

    Google Scholar 
    Rosa, R., Dierssen, H. M., Gonzalez, L. & Seibel, B. A. Ecological biogeography of cephalopod molluscs in the Atlantic Ocean: Historical and contemporary causes of coastal diversity patterns. Glob. Ecol. Biogeogr. 17, 600–610 (2008).Article 

    Google Scholar 
    Barton, A. D., Dutkiewicz, S., Flierl, G., Bragg, J. & Follows, M. J. Patterns of diversity in marine phytoplankton. Science 327, 1509–1511 (2010).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Rodríguez-Ramos, T., Marañón, E. & Cermeño, P. Marine nano- and microphytoplankton diversity: Redrawing global patterns from sampling-standardized data. Glob. Ecol. Biogeogr. 24, 527–538 (2015).Article 

    Google Scholar 
    Righetti, D., Vogt, M., Gruber, N., Psomas, A. & Zimmermann, N. E. Global pattern of phytoplankton diversity driven by temperature and environmental variability. Sci. Adv. 5, eaau6253 (2022).Article 
    ADS 

    Google Scholar 
    Busseni, G. et al. Large scale patterns of marine diatom richness: Drivers and trends in a changing ocean. Glob. Ecol. Biogeogr. 29, 1915–1928 (2020).Article 

    Google Scholar 
    Ruz, P. M., Hidalgo, P., Yáñez, S., Escribano, R. & Keister, J. E. Egg production and hatching success of Calanus chilensis and Acartia tonsa in the northern Chile upwelling zone (23°S) Humboldt Current System. J. Mar. Syst. 148, 200–212 (2015).Article 

    Google Scholar 
    Ashlock, L., García-Reyes, M., Gentemann, C., Batten, S. & Sydeman, W. Temperature and patterns of occurrence and abundance of key copepod taxa in the Northeast Pacific. Front. Mar. Sci. 8, 1–10 (2021).
    Article 
    ADS 

    Google Scholar 
    Campbell, M. D. et al. Testing Bergmann’s rule in marine copepods. Ecography 44, 1283–1295 (2021).Article 

    Google Scholar 
    Soberón, J. Grinnellian and Eltonian niches and geographic distributions of species. Ecol. Lett. 10, 1115–1123 (2007).Article 
    PubMed 

    Google Scholar 
    Soberón, J. & Nakamura, M. Niches and distributional areas: Concepts, methods, and assumptions. Proc. Natl. Acad. Sci. U. S. A. 106, 19644–19650 (2009).Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Morales, C. E. et al. Mesoscale structure of copepod assemblages in the coastal transition zone and oceanic waters off central-southern Chile. Prog. Oceanogr. 84, 158–173 (2010).Article 
    ADS 

    Google Scholar 
    Gonzalez, R. R. & Quiñones, R. A. Ldh activity in Euphausia mucronata and Calanus chilensis: Implications for vertical migration behaviour. J. Plankton Res. 24, 1349–1356 (2002).Article 
    CAS 

    Google Scholar 
    Escribano, R., Hidalgo, P. & Krautz, C. Zooplankton associated with the oxygen minimum zone system in the northern upwelling region of Chile during March 2000. Deep Sea Res. Part II Top. Stud. Oceanogr. 56, 1083–1094 (2009).Article 
    ADS 

    Google Scholar 
    Fernández-Urruzola, I. et al. Plankton respiration in the Atacama Trench region: Implications for particulate organic carbon flux into the hadal realm. Limnol. Oceanogr. 66, 3134–3148 (2021).Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Steinberg, D. K. & Landry, M. R. Zooplankton and the ocean carbon cycle. Ann. Rev. Mar. Sci. 9, 413–444 (2017).Article 
    PubMed 

    Google Scholar 
    Tutasi, P. & Escribano, R. Zooplankton diel vertical migration and downward~C flux into the oxygen minimum zone in the highly productive upwelling region off northern Chile. Biogeosciences 17, 455–473 (2020).Article 
    ADS 
    CAS 

    Google Scholar 
    Gonzalez, A. & Marín, V. H. Distribution and life cycle of Calanus chilensis and Centropages brachiatus (Copepoda) in chilean coastal waters: A GIS approach. Mar. Ecol. Prog. Ser. 165, 109–117 (1998).Article 
    ADS 

    Google Scholar 
    Pulliam, H. R. Sources, sinks, and population regulation. Am. Nat. 132, 652–661 (1988).Article 

    Google Scholar 
    Dias, P. C. Sources and sinks in population biology. Trends Ecol. Evol. 11, 326–330 (1996).Article 
    CAS 
    PubMed 

    Google Scholar 
    Ding, M., Lin, P., Liu, H., Hu, A. & Liu, C. Lagrangian eddy kinetic energy of ocean mesoscale eddies and its application to the Northwestern Pacific. Sci. Rep. 10, 12791 (2020).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Morales, C. E. et al. The distribution of chlorophyll-a and dominant planktonic components in the coastal transition zone off Concepción, central Chile, during different oceanographic conditions. Prog. Oceanogr. 75, 452–469 (2007).Article 
    ADS 

    Google Scholar 
    Escribano, R. & Rodriguez, L. Life cycle of Calanus chilensis Brodsky in Bay of San Jorge, Antofagasta Chile. Hydrobiologia 292, 289–294 (1994).Article 

    Google Scholar 
    Hidalgo, P. & Escribano, R. Coupling of life cycles of the copepods Calanus chilensis and Centropages brachiatus to upwelling induced variability in the central-southern region of Chile. Prog. Oceanogr. 75, 501–517 (2007).Article 
    ADS 

    Google Scholar 
    Sobarzo, M., Bravo, L., Donoso, D., Garcés-Vargas, J. & Schneider, W. Coastal upwelling and seasonal cycles that influence the water column over the continental shelf off central Chile. Prog. Oceanogr. 75, 363–382 (2007).Article 
    ADS 

    Google Scholar 
    Carlson, C. J. embarcadero: Species distribution modelling with Bayesian additive regression trees in r. Methods Ecol. Evol. 11, 850–858 (2020).Article 

    Google Scholar 
    Gelfand, A. et al. Explaining species distribution patterns through hierarchical modeling. Bayesian Anal. https://doi.org/10.1214/06-BA102 (2006).Article 
    MathSciNet 
    MATH 

    Google Scholar 
    Hortal, J. et al. Seven shortfalls that beset large-scale knowledge of biodiversity. Annu. Rev. Ecol. Evol. Syst. 46, 523–549 (2015).Article 

    Google Scholar 
    Wisz, M. S. et al. Effects of sample size on the performance of species distribution models. Divers. Distrib. 14, 763–773 (2008).Article 

    Google Scholar 
    van Proosdij, A. S. J., Sosef, M. S. M., Wieringa, J. J. & Raes, N. Minimum required number of specimen records to develop accurate species distribution models. Ecography 39, 542–552 (2016).Article 

    Google Scholar 
    Gaul, W. et al. Data quantity is more important than its spatial bias for predictive species distribution modelling. PeerJ 8, e10411 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Beck, J., Böller, M., Erhardt, A. & Schwanghart, W. Spatial bias in the GBIF database and its effect on modeling species’ geographic distributions. Ecol. Inform. 19, 10–15 (2014).Article 

    Google Scholar 
    Breiner, F. T., Guisan, A., Bergamini, A. & Nobis, M. P. Overcoming limitations of modelling rare species by using ensembles of small models. Methods Ecol. Evol. 6, 1210–1218 (2015).Article 

    Google Scholar 
    Breiner, F. T., Nobis, M. P., Bergamini, A. & Guisan, A. Optimizing ensembles of small models for predicting the distribution of species with few occurrences. Methods Ecol. Evol. 9, 802–808 (2018).Article 

    Google Scholar 
    Yasuhara, M. et al. Past and future decline of tropical pelagic biodiversity. Proc. Natl. Acad. Sci. 117, 12891–12896 (2020).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Richardson, A., Schoeman, D., Richardson, A. J. & Schoeman, D. S. Climate impact on plankton ecosystems in the Northeast Atlantic. Science 305, 1609–1612 (2004).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Chiba, S., Sugisaki, H., Nonaka, M. & Saino, T. Geographical shift of zooplankton communities and decadal dynamics of the Kuroshio-Oyashio currents in the western North Pacific. Glob. Change Biol. 15, 1846–1858 (2009).Article 
    ADS 

    Google Scholar 
    Reygondeau, G. & Beaugrand, G. Future climate-driven shifts in distribution of Calanus finmarchicus. Glob. Change Biol. 17, 756–766 (2011).Article 
    ADS 

    Google Scholar 
    Beaugrand, G., Lindley, J. A., Helaouet, P. & Bonnet, D. Macroecological study of Centropages typicus in the North Atlantic Ocean. Prog. Oceanogr. 72, 259–273 (2007).Article 
    ADS 

    Google Scholar 
    Hirche, H. J., Barz, K., Ayon, P. & Schulz, J. High resolution vertical distribution of the copepod Calanus chilensis in relation to the shallow oxygen minimum zone off northern Peru using LOKI, a new plankton imaging system. Deep Sea Res. I Oceanogr. Res. Pap. 88, 63–73 (2014).Article 
    ADS 
    CAS 

    Google Scholar 
    Spalding, M. D. et al. Marine ecoregions of the world: A bioregionalization of coastal and shelf areas. Bioscience 57, 573–583 (2007).Article 

    Google Scholar 
    Barve, N. et al. The crucial role of the accessible area in ecological niche modeling and species distribution modeling. Ecol. Model. 222, 1810–1819 (2011).Article 

    Google Scholar 
    Riquelme-Bugueño, R. et al. The influence of upwelling variation on the spatially-structured euphausiid community off central-southern Chile in 2007–2008. Prog. Oceanogr. 92–95, 146–165 (2012).Article 
    ADS 

    Google Scholar 
    Soberón, J. & Peterson, A. Interpretation of models of fundamental ecological niches and species’ distributional areas. Biodivers. Inform. https://doi.org/10.17161/bi.v2i0.4 (2005).Article 

    Google Scholar 
    Provoost, P. & Bosch, S. robis: Ocean Biodiversity Information System (OBIS) Client (2020).Chamberlain, S. & Oldoni, D. rgbif: Interface to the Global Biodiversity Information Facility API (2021).R Core Team. R: A Language and Environment for Statistical Computing (2021).Aiello-Lammens, M. E., Boria, R. A., Radosavljevic, A., Vilela, B. & Anderson, R. P. spThin: An R package for spatial thinning of species occurrence records for use in ecological niche models. Ecography 38, 541–545 (2015).Article 

    Google Scholar 
    ESRI. ArcGIS Desktop: Release 10.4.1 (Envrionmental Systems Research Institute, 2016).
    Google Scholar 
    De Marco, P. & Nóbrega, C. C. Evaluating collinearity effects on species distribution models: An approach based on virtual species simulation. PLoS ONE 13, e202403 (2018).Article 

    Google Scholar 
    Feng, X. et al. A checklist for maximizing reproducibility of ecological niche models. Nat. Ecol. Evol. 3, 1382–1395 (2019).Article 
    PubMed 

    Google Scholar 
    Naimi, B., Hamm, N. A. S., Groen, T. A., Skidmore, A. K. & Toxopeus, A. G. Where is positional uncertainty a problem for species distribution modelling?. Ecography 37, 191–203 (2014).Article 

    Google Scholar 
    Zuur, A. F., Ieno, E. N. & Elphick, C. S. A protocol for data exploration to avoid common statistical problems. Methods Ecol. Evol. 1, 3–14 (2010).Article 

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

    Google Scholar 
    Pinto-Ledezma, J. N. & Cavender-Bares, J. Predicting species distributions and community composition using satellite remote sensing predictors. Sci. Rep. 11, 16448 (2021).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ellison, A. M. Bayesian inference in ecology. Ecol. Lett. 7, 509–520 (2004).Article 

    Google Scholar 
    Pennino, M. G., Muñoz, F., Conesa, D., López-Quílez, A. & Bellido, J. M. Bayesian spatio-temporal discard model in a demersal trawl fishery. J. Sea Res. 90, 44–53 (2014).Article 

    Google Scholar 
    Di Cola, V. et al. ecospat: An R package to support spatial analyses and modeling of species niches and distributions. Ecography 40, 774–787 (2017).Article 

    Google Scholar 
    Engler, R., Guisan, A. & Rechsteiner, L. An improved approach for predicting the distribution of rare and endangered species from occurrence and pseudo-absence data. J. Appl. Ecol. 41, 263–274 (2004).Article 

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

    Google Scholar 
    Boyce, M. S., Vernier, P. R., Nielsen, S. E. & Schmiegelow, F. K. A. Evaluating resource selection functions. Ecol. Model. 157, 281–300 (2002).Article 

    Google Scholar 
    Hirzel, A. H., Le Lay, G., Helfer, V., Randin, C. & Guisan, A. Evaluating the ability of habitat suitability models to predict species presences. Ecol. Model. 199, 142–152 (2006).Article 

    Google Scholar 
    Warren, D. & Dinnage, R. ENMTools: Analysis of Niche Evolution using Niche and Distribution Models (2020).Assis, J. et al. Bio-ORACLE v2.0: Extending marine data layers for bioclimatic modelling. Glob. Ecol. Biogeogr. 27, 277–284 (2018).Article 

    Google Scholar 
    Elith, J., Kearney, M. & Phillips, S. The art of modelling range-shifting species. Methods Ecol. Evol. 1, 330–342 (2010).Article 

    Google Scholar 
    Osorio-Olvera, L. et al. ntbox: An r package with graphical user interface for modelling and evaluating multidimensional ecological niches. Methods Ecol. Evol. 11, 1199–1206 (2020).Article 

    Google Scholar 
    Bosch, S., Tyberghein, L. & De Clerck, O. ‘sdmpredictors’: Species distribution modelling predictor datasets. R package version 0.2.6. R Packag. version 0.2.6 (2018).Thuiller, W., Georges, D., Engler, R. & Breiner, F. biomod2: Ensemble platform for species distribution modeling (2020).Zurell, D. et al. A standard protocol for reporting species distribution models. Ecography 43, 1261–1277 (2020).Article 

    Google Scholar  More

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    Novel plant–frugivore network on Mauritius is unlikely to compensate for the extinction of seed dispersers

    Whittaker, R. J., Fernández-Palacios, J. M., Matthews, T. J., Borregaard, M. K. & Triantis, K. A. Island biogeography: taking the long view of nature’s laboratories. Science 357, eaam8326 (2017).Article 
    PubMed 

    Google Scholar 
    Boyer, A. G. & Jetz, W. Biogeography of body size in Pacific island birds. Ecography 33, 369–379 (2010).
    Google Scholar 
    Heinen, J. H., van Loon, E. E., Hansen, D. M. & Kissling, W. D. Extinction‐driven changes in frugivore communities on oceanic islands. Ecography 41, 1245–1255 (2018).Article 

    Google Scholar 
    Sayol, F., Steinbauer, M. J., Blackburn, T. M., Antonelli, A. & Faurby, S. Anthropogenic extinctions conceal widespread evolution of flightlessness in birds. Sci. Adv. 6, eabb6095 (2020).Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Steadman, D. W. & Martin, P. S. The late quaternary extinction and future resurrection of birds on Pacific islands. Earth Sci. Rev. 61, 133–147 (2003).Article 
    ADS 

    Google Scholar 
    Blackburn, T. M., Cassey, P., Duncan, R. P., Evans, K. L. & Gaston, K. J. Avian extinction and mammalian introductions on oceanic islands. Science 305, 1955–1958 (2004).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Blackburn, T. M., Lockwood, J. L., & Cassey, P. (2009). Avian Invasions: The Ecology and Evolution of Exotic Birds (Oxford University Press, 2009).Steadman, D. W. Extinction and Biogeography of Tropical Pacific Birds (University of Chicago Press, 2006).Boyer, A. G. & Jetz, W. Extinctions and the loss of ecological function in island bird communities. Glob. Ecol. Biogeogr. 23, 679–688 (2014).Article 

    Google Scholar 
    Fritts, T. H. & Rodda, G. H. The role of introduced species in the degradation of island ecosystems: a case history of Guam. Annu. Rev. Ecol. Syst. 29, 113–140 (1998).Article 

    Google Scholar 
    Vidal, M. M. et al. Frugivores at higher risk of extinction are the key elements of a mutualistic network. Ecology 95, 3440–3447 (2014).Article 

    Google Scholar 
    Pires, M. M. et al. Reconstructing past ecological networks: the reconfiguration of seed-dispersal interactions after megafaunal extinction. Oecologia 175, 1247–1256 (2014).Article 
    ADS 
    PubMed 

    Google Scholar 
    Heinen, J. H., Rahbek, C. & Borregaard, M. K. Conservation of species interactions to achieve self-sustaining ecosystems. Ecography 43, 1603–1611 (2020).Article 

    Google Scholar 
    Moreno-Mateos, D. et al. The long-term restoration of ecosystem complexity. Nat. Ecol. Evol. 4, 676–685 (2020).Article 
    PubMed 

    Google Scholar 
    Galetti, M. et al. Functional extinction of birds drives rapid evolutionary changes in seed size. Science 340, 1086–1090 (2013).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Dunn, R. R. Coextinction: anecdotes, models, and speculation. In Holocene Extinctions (ed. Turvey, S. T.) 167–180 (Oxford University Press, 2009).Rezende, E. L., Lavabre, J. E., Guimarães, P. R., Jordano, P. & Bascompte, J. Non-random coextinctions in phylogenetically structured mutualistic networks. Nature 448, 925–928 (2007).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Wotton, D. M. & Kelly, D. Do larger frugivores move seeds further? Body size, seed dispersal distance, and a case study of a large, sedentary pigeon. J. Biogeogr. 39, 1973–1983 (2012).Article 

    Google Scholar 
    Anderson, S. H., Kelly, D., Ladley, J. J., Molloy, S. & Terry, J. Cascading effects of bird functional extinction reduce pollination and plant density. Science 331, 1068–1071 (2011).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Pérez-Méndez, N., Jordano, P., García, C. & Valido, A. The signatures of Anthropocene defaunation: cascading effects of the seed dispersal collapse. Sci. Rep. 6, 1–9 (2016).Article 

    Google Scholar 
    Wotton, D. M. & Kelly, D. Frugivore loss limits recruitment of large-seeded trees. Proc. R. Soc. B Biol. Sci. 278, 3345–3354 (2011).Article 

    Google Scholar 
    Traveset, A. Effect of seed passage through vertebrate frugivores’ guts on germination: a review. Perspect. Plant Ecol. Evol. Syst. 1, 151–190 (1998).Article 

    Google Scholar 
    Janzen, D. H. Herbivores and the number of tree species in tropical forests. Am. Nat. 104, 501–528 (1970).Article 

    Google Scholar 
    Connell, J. H. On the role of natural enemies in preventing competitive exclusion in some marine animals and in rain forest trees. In Dynamics of Populations (eds Den Boer, P. J. & Gradwell, G. R.) 298–312 (Centre for Agricultural Publishing and Documentation, 1971).Farwig, N. & Berens, D. G. Imagine a world without seed dispersers: a review of threats, consequences and future directions. Basic Appl. Ecol. 13, 109–115 (2012).Article 

    Google Scholar 
    Meehan, H. J., McConkey, K. R. & Drake, D. R. Potential disruptions to seed dispersal mutualisms in Tonga, Western Polynesia. J. Biogeogr. 29, 695–712 (2002).Article 

    Google Scholar 
    Pérez-Méndez, N., Jordano, P. & Valido, A. Downsized mutualisms: consequences of seed dispersers’ body-size reduction for early plant recruitment. Perspect. Plant Ecol. Evol. Syst. 17, 151–159 (2015).Article 

    Google Scholar 
    Rodriguez, L. F. Can invasive species facilitate native species? Evidence of how, when, and why these impacts occur. Biol. Invasions 8, 927–939 (2006).Article 

    Google Scholar 
    Griffiths, C. J., Hansen, D. M., Jones, C. G., Zuël, N. & Harris, S. Resurrecting extinct interactions with extant substitutes. Curr. Biol. 21, 762–765 (2011).Article 
    CAS 
    PubMed 

    Google Scholar 
    Thibault, J.-C. & Cibois, A. Birds Of Eastern Polynesia: A Biogeographic Atlas (Lynx Edicions, 2017).Vizentin-Bugoni, J. et al. Structure, spatial dynamics, and stability of novel seed dispersal mutualistic networks in Hawaiʻi. Science 364, 78–82 (2019).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Case, S. B. & Tarwater, C. E. Functional traits of avian frugivores have shifted following species extinction and introduction in the Hawaiian Islands. Funct. Ecol. 34, 2467–2476 (2020).Article 

    Google Scholar 
    Albert, S., Flores, O. & Strasberg, D. Collapse of dispersal trait diversity across a long‐term chronosequence reveals a strong negative impact of frugivore extinctions on forest resilience. J. Ecol. 108, 1386–1397 (2020).Article 

    Google Scholar 
    Cheke, A. S. & Hume, J. P. Lost Land of the Dodo: The Ecological History of Mauritius, Réunion & Rodrigues 464 (T. & A. D. Poyser, 2008).Hammond, D. S. et al. Threats to environmentally sensitive areas from peri-urban expansion in Mauritius. Environ. Conserv. 42, 256–267 (2015).Article 

    Google Scholar 
    Florens, F. V., Baider, C., Seegoolam, N. B., Zmanay, Z. & Strasberg, D. Long‐term declines of native trees in an oceanic island’s tropical forests invaded by alien plants. Appl. Veg. Sci. 20, 94–105 (2017b).Article 

    Google Scholar 
    McConkey, K. R. & O’Farrill, G. Cryptic function loss in animal populations. Trends Ecol. Evol. 30, 182–189 (2015).Article 
    PubMed 

    Google Scholar 
    Carpenter, J. K. et al. The forgotten fauna: Native vertebrate seed predators on islands. Funct. Ecol. 34, 1802–1813 (2020).Article 

    Google Scholar 
    Perea, R., Delibes, M., Polko, M., Suárez-Esteban, A. & Fedriani, J. M. Context‐dependent fruit–frugivore interactions: partner identities and spatio‐temporal variations. Oikos 122, 943–951 (2013).Article 

    Google Scholar 
    Dracxler, C. M. & Kissling, W. D. The mutualism–antagonism continuum in Neotropical palm–frugivore interactions: from interaction outcomes to ecosystem dynamics. Biol. Rev. 97, 527–553 (2022).Article 

    Google Scholar 
    Baider, C. & Florens, F. B. V. Current decline of the ‘Dodo-tree’: a case of broken-down interactions with extinct species or the result of new interactions with alien invaders? In Emerging Threats to Tropical Forests (eds Laurance, W. & Peres, C.) 199–214 (Chicago University Press, 2006).Reinegger, R. D., Oleksy, R. Z., Bissessur, P., Naujeer, H. & Jones, G. First come, first served: fruit availability to keystone bat species is potentially reduced by invasive macaques. J. Mammal. 102, 428–439 (2021).Article 

    Google Scholar 
    Reinegger, R. D., Oleksy, R. Z., Gazagne, E. & Jones, G. Foraging strategies of invasive Macaca fascicularis may promote plant invasion in Mauritius. Int. J. Primatol. 44, 1–31 (2022).O’Connor, S. J. & Kelly, D. Seed dispersal of matai (Prumnopitys taxifolia) by feral pigs (Sus scrofa). N.Z. J. Ecol. 36, 228–231 (2012).
    Google Scholar 
    Shiels, A. B. & Drake, D. R. Are introduced rats (Rattus rattus) both seed predators and dispersers in Hawaii? Biol. Invasions 13, 883–894 (2011).Article 

    Google Scholar 
    Florens, F. B. V. et al. Disproportionately large ecological role of a recently mass-culled flying fox in native forests of an oceanic island. J. Nat. Conserv. 40, 85–93 (2017a).Article 

    Google Scholar 
    Bissessur, P., Bunsy, Y., Baider, C. & Florens, F. B. V. Non-intrusive systematic study reveals mutualistic interactions between threatened island endemic species and points to more impactful conservation. J. Nat. Conserv. 49, 108–117 (2019).Article 

    Google Scholar 
    Hume, J. P. & Winters, R. Captive birds on Dutch Mauritius: bad-tempered parrots, warty pigeons and notes on other native animals. Hist. Biol. 28, 812–822 (2016).Article 

    Google Scholar 
    Kingston, T., Florens, F. B. V., Oleksy, R., Ruhomaun, K. & Tatayah, V. Pteropus niger. The IUCN Red List of Threatened Species (2018).Hume, J. P. The history of the dodo Raphus cucullatus and the penguin of Mauritius. Hist. Biol. 18, 65–89 (2006).Article 

    Google Scholar 
    Hume, J. P. Reappraisal of the parrots (Aves: Psittacidae) from the Mascarene Islands, with comments on their ecology, morphology and affinities. Zootaxa 1513, 1–76 (2007).Article 

    Google Scholar 
    Hume, J. P. Systematics, morphology, and ecological history of the Mascarene starlings (Aves: Sturnidae) with the description of a new genus and species from Mauritius. Zootaxa 3849, 1–75 (2014).Article 
    PubMed 

    Google Scholar 
    Albert, S., Flores, O., Baider, C., Florens, F. B. V. & Strasberg, D. Differing severity of frugivore loss contrasts the fate of native forests on the land of the Dodo (Mascarene archipelago). Biol. Conserv. 257, 109–131 (2021).Article 

    Google Scholar 
    Florens, F. B. V. Conservation in Mauritius and Rodrigues: challenges and achievements from two ecologically devastated oceanic islands. In Conservation Biology: Voices from the Tropics (eds Raven, P. H., Sodhi, N. S. & Gibson, L.) 40–50 (Wiley-Blackwell, 2013).Krivek, G., Florens, F. B. V., Baider, C., Seegobin, V. O. & Haugaasen, T. Invasive alien plant control improves foraging habitat quality of a threatened island flying fox. J. Nat. Conserv. 54, 125805 (2020).Article 

    Google Scholar 
    Monty, M. F., Florens, F. B. V. & Baider, C. Invasive alien plants elicit reduced production of flowers and fruits in various native forest species on the tropical island of Mauritius (Mascarenes, Indian Ocean). Trop. Conserv. Sci. 6, 35–49 (2013).Article 

    Google Scholar 
    Florens, F. B. V. & Baider, C. Ecological restoration in a developing island nation: how useful is the science? Restor. Ecol. 21, 1–5 (2013).Article 

    Google Scholar 
    Nogués-Bravo, D., Simberloff, D., Rahbek, C. & Sanders, N. J. Rewilding is the new Pandora’s box in conservation. Curr. Biol. 26, R87–R91 (2016).Article 
    PubMed 

    Google Scholar 
    Linnebjerg, J. F., Hansen, D. M., Bunbury, N. & Olesen, J. M. Diet composition of the invasive red-whiskered bulbul Pycnonotus jocosus in Mauritius. J. Trop. Ecol. 26, 347–350 (2010).Article 

    Google Scholar 
    Sperry, J. H. et al. Fruit and seed traits of native and invasive plant species in Hawai’i: implications for seed dispersal by non-native birds. Biol. Invasions 23, 1819–1835 (2021).Article 

    Google Scholar 
    Hansen, D. M., Donlan, C. J., Griffiths, C. J. & Campbell, K. J. Ecological history and latent conservation potential: large and giant tortoises as a model for taxon substitutions. Ecography 33, 272–284 (2010).
    Google Scholar 
    Oleksy, R. Z. et al. The movement ecology of the Mauritian flying fox (Pteropus niger): a long-term study using solar-powered GSM/GPS tags. Mov. Ecol. 7, 1–12 (2019).Article 

    Google Scholar 
    Seegobin, V. O., Oleksy, R. Z. & Florens, F. B. V. Foraging and roosting patterns of a repeatedly mass-culled island flying fox offer avenues to mitigate human-wildlife conflict. Biodiversity 23, 49–60 (2022).Article 

    Google Scholar 
    Baider, C. et al. Status of plant conservation in oceanic islands of the Western Indian Ocean. In Proceedings of the 4th Global Botanic Gardens Congress (National Botanic Gardens of Ireland, Dublin, 2010).Humphreys, A. M., Govaerts, R., Ficinski, S. Z., Lughadha, E. N. & Vorontsova, M. S. Global dataset shows geography and life form predict modern plant extinction and rediscovery. Nat. Ecol. Evol. 3, 1043–1047 (2019).Article 
    PubMed 

    Google Scholar 
    BGCI. State of the World’s Trees (BGCI, 2021).Vázquez-Yanes, C. & Orozco-Segovia, A. Patterns of seed longevity and germination in the tropical rainforest. Annu. Rev. Ecol. Syst. 24, 69–87 (1993).Article 

    Google Scholar 
    Gallaher, T., Callmander, M. W., Buerki, S. & Keeley, S. C. A long distance dispersal hypothesis for the Pandanaceae and the origins of the Pandanus tectorius complex. Mol. Phylogenet. Evol. 83, 20–32 (2015).Article 
    PubMed 

    Google Scholar 
    Hansen, D. M., Kaiser, C. N. & Müller, C. B. Seed dispersal and establishment of endangered plants on oceanic islands: the Janzen-Connell model, and the use of ecological analogues. PLoS ONE 3, e2111 (2008).Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Albert, S., Flores, O., Stahl, M., Guilhabert, F. & Strasberg, D. Tree recruitment after native frugivore extinction? A field experiment to test the impact of fruit flesh persistence in a tropical oceanic island. J. Trop. Ecol. 38, 370–376 (2022).Article 

    Google Scholar 
    Witmer, M. C. & Cheke, A. S. The dodo and the tambalacoque tree: an obligate mutualism reconsidered. Oikos 61, 133–137 (1991).Bosser, J., Cadet, T., Guého, J. & Marais, W. Flore des Mascareignes: La Réunion, Maurice, Rodrigues (MSIRI/ORSTOM-IRD/Kew, Mauritius, 1976-onwards).Jordano, P. Fruits and frugivory. In Seeds: The Ecology of Regeneration in Plant Communities (ed. Fenner, N.) 125–165 (CABI Publishing, 2000).van der Pijl, L. Principles of Dispersal in Higher Plants 218 (Springer-Verlag, 1969).Dominy, N. J., Svenning, J. C. & Li, W. H. Historical contingency in the evolution of primate color vision. J. Hum. Evol. 44, 25–45 (2003).Article 
    PubMed 

    Google Scholar 
    Oba, S. et al. A Bayesian missing value estimation method for gene expression profile data. Bioinformatics 19, 2088–2096 (2003).Article 
    CAS 
    PubMed 

    Google Scholar 
    Stekhoven, D. J. & Bühlmann, P. MissForest—non-parametric missing value imputation for mixed-type data. Bioinformatics 28, 112–118 (2012).Article 
    CAS 
    PubMed 

    Google Scholar 
    Qian, H. & Jin, Y. An updated megaphylogeny of plants, a tool for generating plant phylogenies and an analysis of phylogenetic community structure. J. Plant Ecol. 9, 233–239 (2016).Article 

    Google Scholar 
    Jin, Y. & Qian, H. V.PhyloMaker: an R package that can generate very large phylogenies for vascular plants. Ecography 42, 1353–1359 (2019).Article 

    Google Scholar 
    Santos, T., Diniz-Filho, J. A., e Luis, T. R., Bini, M., & Santos, M. T. Package ‘PVR’. Phylogenetic Eigenvectors Regression and Phylogentic Signal-Representation, 3274 (2018).Hume, J. P. Extinct Birds 2nd edn (Bloomsbury, 2017).Safford, R. & Hawkins, F. The Birds of Africa: Volume VIII: The Malagasy Region: Madagascar, Seychelles, Comoros, Mascarenes 960 (Bloomsbury Publishing, 2013).Albert, S., Flores, O., Ah-Peng, C. & Strasberg, D. Forests without frugivores and frugivores without forests—an investigation into the causes of a paradox in one of the last archipelagos colonized by humans. Front. Ecol. Evol. 9, 539 (2021).Albert, S. et al. Rediscovery of the mistletoe Bakerella hoyifolia subsp. bojeri (Loranthaceae) on Reunion Island: population status assessment for its conservation. Bot. Lett. 164, 229–236 (2017).Article 

    Google Scholar 
    Atkinson, R. & Sevathian, J.-C. A Guide to the Plants in Mauritius 188 (Mauritian Wildlife Foundation, 2005).Austin, J. J. & Arnold, E. N. Using ancient and recent DNA to explore relationships of extinct and endangered Leiolopisma skinks (Reptilia: Scincidae) in the Mascarene islands. Mol. Phylogenet. Evol. 39, 503–511 (2006).Article 
    CAS 
    PubMed 

    Google Scholar 
    Bissessur, P., Probst, J.-M. & Florens, F. B. V. Le Merle noir ou Bulbul de Maurice Hypsipetes olivaceus. Bull. Phaethon 46, 86–90 (2017).
    Google Scholar 
    Bullock, D. J. The ecology and conservation of reptiles on Round Island and Gunner’s Quion, Mauritius. Biol. Conserv. 37, 135–156 (1986).Article 

    Google Scholar 
    Cadet, L. J. T. La végétation de l’ile de La Réunion. Etude phytoécologique et phytosociologique. PhD thesis, Université Aix-Marseille, France, 362 (1977).Cheke, A. S. The ecology of the smaller land-birds of Mauritius. In Studies of Mascarene Islands Birds (ed. Diamond, A. W.) 151–207 (Cambridge University Press, 1987).Cole, R., Ladkoo, A., Tatayah, V. & Jones, C. Mauritius Olive White-eye Recovery Programme 2007-08 (Mauritian Wildlife Foundation, Vacoas, Mauritius, 2008).Falcón, W., Moll, D. & Hansen, D. M. Frugivory and seed dispersal by chelonians: a review and synthesis. Biol. Rev. 95, 142–166 (2020).Article 
    PubMed 

    Google Scholar 
    Guérin, R. Faune ornithologique ancienne et actuelle des îles Mascareignes, Seychelles, Comores et des îles avoisinantes, Vol. 3 (General Printing & Stationery Co., 1940–53).Günther, A. C. L. G. The Gigantic Land-tortoises (Living and Extinct) in the Collection of the British Museum 96 (Order of the Trustees, London, 1877).Hansen, D. M. Ecology, Evolution, and Conservation of Plant-Animal Interactions in Islands. PhD thesis, University of Zurich, 192 (2006).Hansen, D. M. & Müller, C. B. Invasive ants disrupt gecko pollination and seed dispersal of the endangered plant Roussea simplex in Mauritius. Biotropica 41, 202–208 (2009).Article 

    Google Scholar 
    Harper, G. A. & Bunbury, N. Invasive rats on tropical islands: their population biology and impacts on native species. Glob. Ecol. Conserv. 3, 607–627 (2015).Article 

    Google Scholar 
    Henkel, F. W. & Schmidt, W. Amphibians and Reptiles of Madagascar and the Mascarene, Seychelles, and Comoro Islands 316 (Krieger Publishing, 2000).Hume, J. P. Systematics, morphology, and ecology of pigeons and doves (Aves: Columbidae) of the Mascarene Islands, with three new species. Zootaxa 3124, 1–62 (2011).Article 

    Google Scholar 
    Hume, J. P. Systematics, morphology, and ecology of rails (Aves: Rallidae) of the Mascarene Islands, with one new species. Zootaxa 4626, 001–107 (2019).Article 

    Google Scholar 
    Jones, C. G. The larger land-birds of Mauritius. In Studies of Mascarene Island birds (ed. Diamond, A. W.) 208–300 (Cambridge University Press, 1987).Jones, C. G. Studies on the Biology of the Pink Pigeon. Columba mayeri. PhD thesis, University College of Swansea, University of Wales, UK (1995).Larosa, A. M., Smith, C. W. & Gardner, D. E. Role of alien and native birds in the dissemination of firetree (Myrica faya Ait.-Myriacaceae) and associated plants in Hawaii. Pac. Sci. 39, 372–378 (1985).
    Google Scholar 
    Leguat de la Fougère, F. Voyage et aventures de François Leguat et de ses compagnons en deux iles désertes des Indes Orientales, Vol. 2 (J.J. Delorme, Amsterdam, 1707).Linnebjerg, J. F., Hansen, D. M. & Olesen, J. M. Gut passage effect of the introduced red-whiskered bulbul (Pycnonotus jocosus) on germination of invasive plant species in Mauritius. Austral. Ecol. 34, 272–277 (2009).Article 

    Google Scholar 
    Lorence, D. H. A monograph of the Monimiaceae (Laurales) in the Malagasy region (southwest Indian Ocean). Ann. Mo. Bot. Gard. 72, 1–165 (1985).Article 

    Google Scholar 
    Maggs, G. et al. Quantifying drivers of supplementary food use by a reintroduced, critically endangered passerine to inform management and habitat restoration. Biol. Conserv. 238, 108240 (2019).Article 

    Google Scholar 
    Meyer, J. Y. & Butaud, J. F. The impacts of rats on the endangered native flora of French Polynesia (Pacific Islands): drivers of plant extinction or coup de grâce species? Biol. Invasions 11, 1569–1585 (2009).Article 

    Google Scholar 
    Moorhouse-Gann, R. J. et al. New universal ITS2 primers for high-resolution herbivory analyses using DNA metabarcoding in both tropical and temperate zones. Sci. Rep. 8, 1–15 (2018).Article 
    CAS 

    Google Scholar 
    Nyhagen, D. F., Kragelund, C., Olesen, J. M. & Jones, C. G. Insular interactions between lizards and flowers: flower visitation by an endemic Mauritian gecko. J. Trop. Ecol. 17, 755–761 (2001).Article 

    Google Scholar 
    Nyhagen, D. F., Turnbull, S. D., Olesen, J. M. & Jones, C. G. An investigation into the role of the Mauritian flying fox, Pteropus niger, in forest regeneration. Biol. Conserv. 122, 491–497 (2005).Article 

    Google Scholar 
    Probst, J.-M. Les Bulbuls du genre Hypsipetes dans les Mascareignes (Océan Indien). Observations Mascarines 1, 34–36 (1988).
    Google Scholar 
    Probst, J. M. Capacité de vol étonnante du Bulbul orphée Pycnonotus jocosus (Ile aux Aigrettes–Ile Maurice). Bull. Phaethon 1, 14–17 (1995).
    Google Scholar 
    Safford, R. Conservation of the Forest-living Native Birds of Mauritius. PhD thesis, University of Kent at Canterbury, 265 (1994).Sengupta, S. Food and feeding ecology of the common myna, Acridotheres tristis (Linn.). J. Proc. Indian Natl Sci. Acad. Part B Biol. Sci. 42, 338–345 (1976).
    Google Scholar 
    Staub, F. Evolutionary trends in some Mauritian phanerogams in relation to their pollinators. Proc. R. Soc. Arts Sci. Maurit. 5, 7–78 (1988).
    Google Scholar 
    Strahm, W. A. The Conservation and Restoration of the Flora of Mauritius and Rodrigues, Vol. 2. PhD thesis, University of Reading (1993) .Sussman, R. W. & Tattersall, I. Behavior and ecology of Macaca fascicularis in Mauritius: a preliminary study. Primates 22, 192–205 (1981).Article 

    Google Scholar 
    Sussman, R. W. & Tattersall, I. Distribution, abundance, and putative ecological strategy of Macaca fascicularis on the island of Mauritius, southwestern Indian Ocean. Folia Primatol. 46, 28–43 (1986).Article 

    Google Scholar 
    Valido, A. & Olesen, J. M. The importance of lizards as frugivores and seed dispersers. In Seed Dispersal: Theory and Its Application in a Changing World (eds Dennis, A. J. et al.) 124–147 (CAB International, 2007).Vinson, J. & Vinson, J. M. Notes on the reptiles of Round Island. Maurit. Inst. Bull. 8, 49–67 (1975).
    Google Scholar 
    von Bethlenfalvy, G. Vertebrate Seed Dispersers in Mauritius: Fruit Traits and Fruit Traits Preferences. MSc thesis, Institute of Zoology, University of Zurich, Switzerland (2006).Wilman, H. et al. EltonTraits 1.0: species-level foraging attributes of the world’s birds and mammals: ecological archives E095-178. Ecology 95, 2027–2027 (2014).Article 

    Google Scholar 
    Winters, R. & Hume, J. P. The dodo, the deer and a 1647 voyage to Japan. Historical. Biology 27, 258–264 (2015).
    Google Scholar 
    Zuël, N. Ecology and Conservation of an Endangered Reptile Community on Round Island, Mauritius. Doctoral dissertation, University of Zurich (2009).Zuël, N. et al. Ingestion by an endemic frugivore enhances seed germination of endemic plant species but decreases seedling survival of exotics. J. Biogeogr. 39, 2021–2030 (2012).Article 

    Google Scholar 
    Kissling, W. D., Böhning–Gaese, K. & Jetz, W. The global distribution of frugivory in birds. Glob. Ecol. Biogeogr. 18, 150–162 (2009).Article 

    Google Scholar 
    Sandom, C. et al. Mammal predator and prey species richness are strongly linked at macroscales. Ecology 94, 1112–1122 (2013).Article 
    PubMed 

    Google Scholar 
    Hume, J. P. A new subfossil bulbul (Aves: Passerines: Pycnonotidae) from Rodrigues Island, Mascarenes, southwestern Indian Ocean. Ostrich 86, 247–260 (2015).Article 

    Google Scholar 
    Austin, J. J., Arnold, E. N. & Jones, C. G. Reconstructing an island radiation using ancient and recent DNA: the extinct and living day geckos (Phelsuma) of the Mascarene islands. Mol. Phylogenet. Evol. 31, 109–122 (2004).Article 
    CAS 
    PubMed 

    Google Scholar 
    Paradis, E. & Schliep, K. ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics 35, 526–528 (2019).Article 
    CAS 
    PubMed 

    Google Scholar  More

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    Big dino, little dino: how T. rex’s relatives changed their size

    Theropod dinosaurs such as Tarbosaurus bataar grew large or small in a range of ways.Credit: Marco Ansaloni/SPL

    A sweeping analysis of shin bones has given researchers a glimpse into how some dinosaurs evolved into mega-beasts such as Tyrannosaurus, and others into smaller, bird-like creatures. The work, published this week in Science1, reveals that dinosaurs used more than one evolutionary trick to become larger — or smaller — over time.Prevailing wisdom held that large-bodied animals are bigger than their smaller-bodied relatives because they grow faster during their most rapid period of growth. That trend holds true for modern animals including birds and mammals — elephants and ostriches grow faster than chihuahuas and sparrows, for example.It’s not the case for all animals. Crocodiles and alligators, for instance, become large because they grow for a long time. But palaeontologists had assumed that for theropod dinosaurs — a group that includes the iconic T. rex and which spawned modern birds — large species got big through rapid growth spurts. “It’s kind of become the established idea in dinosaurs,” says palaeontologist Michael D’Emic at Adelphi University in Garden City, New York.But that’s not what D’Emic found when he sawed into the bones of Majungasaurus, a 7-metre-long T. rex relative that lived 66 million years ago on what is now Madagascar. The speed of growth in dinosaurs is recorded in rings laid down each year in their bones. Instead of seeing wide rings corresponding to a rapid adolescent growth spurt, D’Emic found lots of narrow growth rings, suggesting that Majungasaurus had become large over a prolonged period.“I was very surprised,” he says. The next dinosaur he examined, a similar-sized beast called Ceratasaurus, was the opposite — a big dinosaur that grew fast during its growth spurt, says D’Emic.Bone growth ringsOver a decade, D’Emic and his colleagues amassed bone growth-ring measurements from 42 theropod species to see which strategies led to large and small bodies. They found that 31% of theropod species were larger than their ancestors because of faster growth and 28% because of prolonged growth. Meanwhile, 21% became smaller than their ancestors by shortening their growth spurts, and 19% by slowing growth.The study covered theropod species that lived between 230 million years ago and the end of the Cretaceous period 66 million years ago, when a mass-extinction event wiped out the non-avian dinosaurs. It’s “a huge evolutionary timescale”, to include in an analysis, says Vera Weisbecker, an evolutionary biologist at Flinders University in Adelaide, Australia. “That is really impressive,” she says. “It’s just fascinating that there are so many developmental ways to become big or small.”Palaeontologist Kevin Padian at the University of California, Berkeley, says the analysis is the kind of work that needs to be done, animal group by animal group, to understand how body size evolves.Drivers of changeBut Meike Köhler, an evolutionary palaeobiologist at the Catalan Institution for Research and Advanced Studies in Barcelona, Spain, says the findings are not surprising because previous work has shown a range of growth strategies across animal species. Köhler would like to see an analysis that considers what ecological circumstances influenced how animals changed in size over time.Weisbecker says that the growth strategy used might be related to evolutionary pressures. “If you looked at all the ones with explosive early growth, you might be able to test if they happen to be the ones that are more likely to be predated on, for example,” she says.For each species, the growth strategy that led to its individual body size probably related to its unique environment, says Padian. “It’s not a one-size-fits-all, which is a good thing for us to learn,” he says. “We might have thought that, but they’ve documented it.”D’Emic says he and his team are conducting similar analyses on other groups, including mammals — a group that contains many more species to sample — to see whether the diversity is found in other branches of the evolutionary tree. More