More stories

  • in

    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

  • in

    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

  • in

    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

  • 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

  • in

    The unequal burden of human-wildlife conflict

    Andrade, G. S. & Rhodes, J. R. Protected areas and local communities: an inevitable partnership toward successful conservation strategies? Ecol. Soc. 17, 14–23 (2012).Article 

    Google Scholar 
    UNHCR. United Nations High Commissioner for Refugees. The Sustainable Development Goals and Addressing Statelessness (2017). https://www.refworld.org/docid/58b6e3364.html [accessed 16 April 2021]Ngorima, A., Brown, A., Masunungure, C. & Biggs, D. Local community benefits from elephants: Can willingness to support anti-poaching efforts be strengthened? Conserv. Sci. Pract. 2, e303 (2020).
    Google Scholar 
    Ripple, W. J. et al. Status and ecological effects of the world’s largest carnivores. Science 343, 1241484 (2014).O’Bryan, C. J. et al. The contribution of predators and scavengers to human well-being. Nat. Ecol. Evol. 2, 229–236 (2018).Article 
    PubMed 

    Google Scholar 
    Levi, T. et al. Community ecology and conservation of bear-salmon ecosystems. Front. Ecol. Evol. 8, 433 (2020).Article 

    Google Scholar 
    Raynor, J. L., Grainger, C. A. & Parker, D. P. Wolves make roadways safer, generating large economic returns to predator conservation. Proc. Natl Acad. Sci. U.S.A. 118, e2023251118 (2021).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Tortato, F. R., Izzo, T. J., Hoogesteijn, R. & Peres, C. A. The numbers of the beast: Valuation of jaguar (Panthera onca) tourism and cattle depredation in the Brazilian Pantanal. Glob. Ecol. Conserv. 11, 106–114 (2017).Article 

    Google Scholar 
    Jacobsen, K. S. et al. What is a lion worth to local people—quantifying of the costs of living alongside a top predator. Ecol. Econ. 198, 107431 (2022).Article 

    Google Scholar 
    Thirgood, S., Woodroffe, R. & Rabinowitz, A. The impact of human-wildlife conflict on human lives and livelihoods. Conserv. Biol. Ser. 9, 13 (2005).
    Google Scholar 
    Mackenzie, C. A. & Ahabyona, P. Elephants in the garden: financial and social costs of crop raiding. Ecol. Econ. 75, 72–82 (2012).Article 

    Google Scholar 
    Anaya, F. C. & Espírito-Santo, M. M. Protected areas and territorial exclusion of traditional communities. Ecol. Soc. 23 (2018).Nsukwini, S. & Bob, U. Protected areas, community costs and benefits: a comparative study of selected conservation case studies from northern KwaZulu-Natal, South Africa. GeoJ. Tour. Geosites 27, 1377–1391 (2019).Article 

    Google Scholar 
    Heydinger, J. M., Packer, C. & Tsaneb, J. Desert-adapted lions on communal land: surveying the costs incurred by, and perspectives of, communal-area livestock owners in northwest Namibia. Biol. Conserv. 236, 496–504 (2019).Article 

    Google Scholar 
    Dickman, A. J., Macdonald, E. A. & Macdonald, D. W. A review of financial instruments to pay for predator conservation and encourage human–carnivore coexistence. Proc. Natl Acad. Sci. U.S.A. 108, 13937–13944 (2011).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Wang, S. W. & Macdonald, D. W. Livestock predation by carnivores in Jigme Singye Wangchuck National Park, Bhutan. Biol. Conserv. 129, 558–565 (2006).Article 

    Google Scholar 
    Holmern, T., Nyahongo, J. & Røskaft, E. Livestock loss caused by predators outside the Serengeti National Park, Tanzania. Biol. Conserv. 135, 518–526 (2007).Article 

    Google Scholar 
    Thornton, P. K. et al. Locating poor livestock keepers at the global level for research and development targeting. Land Use Policy 20, 311–322 (2003).Article 

    Google Scholar 
    McDermott, J. J., Staal, S. J., Freeman, H. A., Herrero, M. & Van de Steeg, J. A. Sustaining intensification of smallholder livestock systems in the tropics. Livest. Sci. 130, 95–109 (2010).Article 

    Google Scholar 
    Dyson-Hudson, N. & Dyson-Hudson, R. The structure of East African herds and the future of East African herders. Dev. Change 13, 213–238 (1982).Article 

    Google Scholar 
    Herrero, M. et al. Greenhouse gas mitigation potentials in the livestock sector. Nat. Clim. Change 6, 452–461 (2016).Article 

    Google Scholar 
    Kgathi, D. L., Ngwenya, B. N. & Wilk, J. Shocks and rural livelihoods in the Okavango Delta, Botswana. Dev. South. Afr. 24, 289–308 (2007).Article 

    Google Scholar 
    Letta, M., Montalbano, P. & Tol, R. S. Temperature shocks, short-term growth and poverty thresholds: evidence from rural Tanzania. World Dev. 112, 13–32 (2018).Article 

    Google Scholar 
    Cottrell, R. S. et al. Food production shocks across land and sea. Nat. Sustain. 2, 130–137 (2019).Article 

    Google Scholar 
    Li, J. et al. Role of Tibetan Buddhist monasteries in snow leopard conservation. Conserv. Biol. 28, 87–94 (2014).Article 
    PubMed 

    Google Scholar 
    Bhatia, S., Redpath, S. M., Suryawanshi, K. & Mishra, C. The relationship between religion and attitudes toward large carnivores in northern India? Hum. Dimens. Wildl. 22, 30–42 (2017).Article 

    Google Scholar 
    Gebresenbet, F., Baraki, B., Yirga, G., Sillero-Zubiri, C. & Bauer, H. A culture of tolerance: coexisting with large carnivores in the Kafa Highlands, Ethiopia. Oryx 52, 751–760 (2018).Article 

    Google Scholar 
    Cardillo, M. et al. Human population density and extinction risk in the world’s carnivores. PLoS Biol. 2, e197 (2004).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Hazzah, L., Mulder, M. B. & Frank, L. Lions and warriors: social factors underlying declining African lion populations and the effect of incentive-based management in Kenya. Biol. Conserv. 142, 2428–2437 (2009).Article 

    Google Scholar 
    Plaza, P. I., Martínez-López, E. & Lambertucci, S. A. The perfect threat: pesticides and vultures. Sci. Total Environ. 687, 1207–1218 (2019).Article 
    CAS 
    PubMed 

    Google Scholar 
    Mateo-Tomás, P. & López-Bao, J. V. Poisoning poached megafauna can boost trade in African vultures. Biol. Conserv. 241, 108389 (2020).Article 

    Google Scholar 
    Tumenta, P. N. et al. Threat of rapid extermination of the lion (Panthera leo leo) in Waza National Park, Northern Cameroon. Afr. J. Ecol. 48, 888–894 (2010).Article 

    Google Scholar 
    Braczkowski, A. et al. Detecting early warnings of pressure on an African lion (Panthera leo) population in the Queen Elizabeth Conservation Area, Uganda. Ecol. Solut. Evid. 1, e12015 (2020b).Article 

    Google Scholar 
    Ickes, K. Hyper-abundance of Native Wild Pigs (Sus scrofa) in a Lowland Dipterocarp Rain Forest of Peninsular Malaysia 1. Biotropica 33, 682–690 (2001).Article 

    Google Scholar 
    Ripple, W. J. et al. Widespread mesopredator effects after wolf extirpation. Biol. Conserv. 160, 70–79 (2013).Article 

    Google Scholar 
    Ripple, W. J. & Beschta, R. L. Linking a cougar decline, trophic cascade, and catastrophic regime shift in Zion National Park. Biol. Conserv. 133, 397–408 (2006).Article 

    Google Scholar 
    Ripple, W. J. & Beschta, R. L. Trophic cascades involving cougar, mule deer, and black oaks in Yosemite National Park. Biol. Conserv. 141, 1249–1256 (2008).Article 

    Google Scholar 
    Gilbert, S. L. et al. Socioeconomic benefits of large carnivore recolonization through reduced wildlife-vehicle collisions. Conserv. Lett. 10, 431–439 (2017).Article 

    Google Scholar 
    ILRI. Rangelands Atlas. (ILRI, IUCN, FAO, WWF, UNEP and ILC, 2021). Nairobi Kenya: ILRI.Williams, D. R. et al. Proactive conservation to prevent habitat losses to agricultural expansion. Nat. Sustain. 4, 314–322 (2021).Article 

    Google Scholar 
    McManus, J. S. et al. Dead or alive? Comparing costs and benefits of lethal and non-lethal human-wildlife conflict mitigation on livestock farms. Oryx 49, 687–695 (2015).Article 

    Google Scholar 
    Broekhuis, F. et al. Identification of human-carnivore conflict hotspots to prioritize mitigation efforts. Ecol. Evol. 7, 10630–10639 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lozano, J. et al. Human-carnivore relations: a systematic review. Biol. Conserv. 237, 480–492 (2019).Article 

    Google Scholar 
    Khorozyan, I. & Waltert, M. A global view on evidence-based effectiveness of interventions used to protect livestock from wild cats. Conserv. Sci. Pract. 3, e317 (2021).
    Google Scholar 
    Di Minin, E., Slotow, R., Fink, C., Bauer, H. & Packer, C. A pan-African spatial assessment of human conflicts with lions and elephants. Nat. Commun. 12, 1–10 (2021).Article 

    Google Scholar 
    Lybbert, T. J. et al. Stochastic wealth dynamics and risk management among a poor population. Econ. J. 114, 750–777 (2004).Article 

    Google Scholar 
    Otte, M. J. & Chilonda, P. Cattle and Small Ruminant Production Systems in Sub-Saharan. Africa – Systematic Rev. (FAO, Rome, Italy, 2002).
    Google Scholar 
    Maystadt, J. F. & Ecker, O. Extreme weather and civil war: Does drought fuel conflict in Somalia through livestock price shocks? Am. J. Agric. Econ. 96, 1157–1182 (2014).Article 

    Google Scholar 
    Galvin, K. A. Transitions: pastoralists living with change. Annu. Rev. Anthropol. 38, 185–198 (2009).Article 

    Google Scholar 
    Stavi, I. et al. Food security among dryland pastoralists and agropastoralists: The climate, land-use change, and population dynamics nexus. Anthropocene Rev. (2021). 20530196211007512.Ogra, M. V. Human–wildlife conflict and gender in protected area borderlands: a case study of costs, perceptions, and vulnerabilities from Uttarakhand (Uttaranchal), India. Geoforum 39, 1408–1422 (2008).Article 

    Google Scholar 
    Botreau, H., & Cohen, M. J. Gender Inequalities and Food Insecurity: Ten Years After The Food Price Crisis, Why Are Women Farmers Still Food-Insecure? Oxfam:Oxford, UK (2019).Salerno, J. et al. Wildlife impacts and changing climate pose compounding threats to human food security. Curr. Biol. 31, 5077–5085 (2021).Article 
    CAS 
    PubMed 

    Google Scholar 
    Prado, E. L. & Dewey, K. G. Nutrition and brain development in early life. Nutr. Rev. 72, 267–284 (2014).Article 
    PubMed 

    Google Scholar 
    Madhusudan, M. D. The global village: linkages between international coffee markets and grazing by livestock in a south Indian wildlife reserve. Conserv. Biol. 19, 411–420 (2005).Article 

    Google Scholar 
    Margulies, J. D. & Karanth, K. K. The production of human-wildlife conflict: A political animal geography of encounter. Geoforum 95, 153–164 (2018).Article 

    Google Scholar 
    Simoons, F. J., Simoons, F. I. & Lodrick, D. O. Background to understanding the cattle situation of India: The sacred cow concept in Hindu religion and folk culture. Zeitschrift Für Ethnologie 106, 121–137 (1981).Good, C., Burnham, D. & Macdonald, D. W. A cultural conscience for conservation. Animals 7, 52 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Courchamp, F. et al. The paradoxical extinction of the most charismatic animals. PLoS Biol. 16, e2003997 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bond, J. & Mkutu, K. Exploring the hidden costs of human–wildlife conflict in northern Kenya. Afr. Stud. Rev. 61, 33–54 (2018).Article 

    Google Scholar 
    Di Minin, E., Leader-Williams, N. & Bradshaw, C. J. Banning trophy hunting will exacerbate biodiversity loss. Trends Ecol. Evol. 31, 99–102 (2016).Article 
    PubMed 

    Google Scholar 
    Dickman, A. et al. Trophy hunting bans imperil biodiversity. Science 365, 874–874 (2019).Article 
    PubMed 

    Google Scholar 
    Bruskotter, J. T., Vucetich, J. A., Gilbert, S. L., Carter, N. H. & George, K. A. Tragic trade‐offs accompany carnivore coexistence in the modern world. Conserv. Lett. 15, e412841 (2022).Dempsey, J. et al. Biodiversity targets will not be met without debt and tax justice. Nat. Ecol. Evol. 6, 237–239 (2022).Hallegatte, S. & Rozenberg, J. Climate change through a poverty lens. Nat. Clim. Change 7, 250–256 (2017).Article 

    Google Scholar 
    Islam, S. N., and Winkel, J. Climate change and social inequality. DESA Working Paper No. 152. New York, NY: United Nations Department of Economic & Social Affairs (2017).Platteau, J. P. Monitoring elite capture in community-driven development. Dev. Change 35, 223–246 (2004).Article 

    Google Scholar 
    Karanth, K. K. & DeFries, R. Nature-based tourism in Indian protected areas: new challenges for park management. Conserv. Lett. 4, 137–149 (2011).Article 

    Google Scholar 
    Ament, J. M., Collen, B., Carbone, C., Mace, G. M. & Freeman, R. Compatibility between agendas for improving human development and wildlife conservation outside protected areas: insights from 20 years of data. People Nat. 1, 305–316 (2019).Article 

    Google Scholar 
    Geldmann, J., Manica, A., Burgess, N. D., Coad, L. & Balmford, A. A global-level assessment of the effectiveness of protected areas at resisting anthropogenic pressures. Proc. Natl Acad. Sci. U.S.A. 116, 23209–23215 (2019).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Naidoo, R. et al. Evaluating the impacts of protected areas on human well-being across the developing world. Sci. Adv. 5, eaav3006 (2019).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lichtenfeld, L. L., Trout, C. & Kisimir, E. L. Evidence-based conservation: predator-proof bomas protect livestock and lions. Biodivers. Conserv. 24, 483–491 (2015).Article 

    Google Scholar 
    Persson, J., Rauset, G. R. & Chapron, G. Paying for an endangered predator leads to population recovery. Conserv. Lett. 8, 345–350 (2015).Article 

    Google Scholar 
    Barichievy, C. et al. A demographic model to support an impact financing mechanism for black rhino metapopulations. Biol. Conserv. 257, 109073 (2021).Article 

    Google Scholar 
    Maingi, S. W. Safari tourism and its role in sustainable poverty eradication in East Africa: the case of Kenya. Worldwide Hosp. Tour. Themes 13, 81–94 (2021).Homewood, K. M., Trench, P. C. & Brockington, D. Pastoralist livelihoods and wildlife revenues in East Africa: a case for coexistence? Pastoralism: Res. Pol. Pract. 2, 1–23 (2012).Article 

    Google Scholar 
    Thornton, P., Nelson, G., Mayberry, D. & Herrero, M. Impacts of heat stress on global cattle production during the 21st century: a modelling study. Lancet Planet. Health 6, e192–e201 (2022).Article 
    PubMed 

    Google Scholar 
    Lessmann, C. & Seidel, A. Regional inequality, convergence, and its determinants–a view from outer space. Eur. Econ. Rev. 92, 110–132 (2017).Article 

    Google Scholar 
    Brooks, T. M. et al. Measuring terrestrial area of habitat (AOH) and its utility for the IUCN Red List. Trends Ecol. Evol. 34, 977–986 (2019).Article 
    PubMed 

    Google Scholar 
    Miller, J. R. Mapping attack hotspots to mitigate human–carnivore conflict: approaches and applications of spatial predation risk modeling. Biodivers. Conserv. 24, 2887–2911 (2015).Article 

    Google Scholar 
    Gastineau, A., Robert, A., Sarrazin, F., Mihoub, J. B. & Quenette, P. Y. Spatiotemporal depredation hotspots of brown bears, Ursus arctos, on livestock in the Pyrenees, France. Biol. Conserv. 238, 108210 (2019).Article 

    Google Scholar 
    Kruuk, H. Surplus killing by carnivores. J. Zool. 166, 233–244 (1972).Article 

    Google Scholar 
    Khorozyan, I. et al. Effects of shepherds and dogs on livestock depredation by leopards (Panthera pardus) in north-eastern Iran. PeerJ 5, e3049 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lucherini, M., Guerisoli, M. D. L. M. & Luengos Vidal, E. M. Surplus killing by pumas Puma concolor: rumours and facts. Mammal. Rev. 48, 277–283 (2018).Article 

    Google Scholar 
    Ocaido, M., Muwazi, R. T. & Opuda-Asibo, J. Financial analysis of livestock production systems around Lake Mburo National Park, in South Western Uganda. Livest. Res. Rural Dev. 21, 70 (2009).
    Google Scholar 
    Dyson-Hudson, R. & Dyson-Hudson, N. Nomadic pastoralism. Annu. Rev. Anthropol. 9, 15–61 (1980).Barber, J. P. The Karamoja District of Uganda: a pastoral people under colonial rule. J. Afr. Hist. 3, 111–124 (1962).Article 

    Google Scholar 
    Oberg, K. Analysis of the Bahima marriage ceremony. Africa 19, 107–120 (1949).Article 

    Google Scholar 
    Purseglove, J. W. Banyankole Agriculture. East Afr. Agric. J. 5, 198–207 (1939).
    Google Scholar 
    Canonici, N. N. Food in Zulu folktales. South. Afr. J. Folk. Stud. 2, 24–36 (1991).
    Google Scholar 
    United Nations. World Population Prospects 2022: Summary of Results. UN DESA/POP/2022/TR/NO. 3 (2022).Tomas, W. M. et al. Sustainability agenda for the Pantanal Wetland: perspectives on a collaborative interface for science, policy, and decision-making. Trop. Conserv. Sci. 12, 1940082919872634 (2019).Article 

    Google Scholar 
    Vale, P. et al. Mapping the cattle industry in Brazil’s most dynamic cattle-ranching state: Slaughterhouses in Mato Grosso, 1967-2016. PLOS One 14, e0215286 (2019).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    De Leeuw, P. N., Bekure, S., & Grandin, B. E. Aspects of livestock productivity in Maasai group ranches in Kenya. ILCA Bull. (1984).Barua, M., Bhagwat, S. A. & Jadhav, S. The hidden dimensions of human–wildlife conflict: health impacts, opportunity and transaction costs. Biol. Conserv. 157, 309–316 (2013).Article 

    Google Scholar 
    Choudhury, A. Human–elephant conflicts in Northeast India. Hum. Dimens. Wildl. 9, 261–270 (2004).Article 

    Google Scholar 
    Sherman, P. B., & Dixon, J. A. Economics of protected areas: a new look at benefits and costs. Earthscan Publications Limited (1990).Braczkowski, A. et al. Evidence for increasing human‐wildlife conflict despite a financial compensation scheme on the edge of a Ugandan National Park. Conserv. Sci. Pract. 2, e309 (2020c).
    Google Scholar 
    Gulati, S., Karanth, K., Nguyet Anh Le, N. & Noack, F. Human casualties are the dominant cost of human–wildlife conflict in India. Proc. Natl Acad. Sci. 118, e1921338118 (2021).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Rondinini, C. et al. Global habitat suitability models of terrestrial mammals. Philos. Trans. R. Soc. 366, 2633–2641 (2011).Article 

    Google Scholar 
    Lewis, J. S. et al. Biotic and abiotic factors predicting the global distribution and population density of an invasive large mammal. Sci. Rep. 7, 44152 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Strassburg, B. et al. Global priority areas for ecosystem restoration. Nature 586, 724–729 (2020).Article 
    CAS 
    PubMed 

    Google Scholar 
    O’Bryan, C. J. et al. The importance of indigenous peoples’ lands for the conservation of terrestrial mammals. Conserv. Biol. 35, 1002–1008 (2021).Article 
    PubMed 

    Google Scholar 
    Rondinini, C., Wilson, K. A., Boitani, L., Grantham, H. & Possingham, H. P. Tradeoffs of different types of species occurrence data for use in systematic conservation planning. Ecol. Lett. 9, 1136–1145 (2006).Article 
    PubMed 

    Google Scholar 
    Henderson, J. V., Storeygard, A. & Weil, D. N. Measuring economic growth from outer space. Am. Econ. Rev. 102, 994–1028 (2012).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ebener, S., Murray, C., Tandon, A. & Elvidge, C. C. From wealth to health: modelling the distribution of income per capita at the sub-national level using night-time light imagery. Int. J. Health Geographics 4, 5 (2005).Article 

    Google Scholar 
    Chen, X. & Nordhaus, W. D. Using luminosity data as a proxy for economic statistics. Proc. Natl Acad. Sci. 108, 8589–8594 (2011).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Jean, N. et al. Combining satellite imagery and machine learning to predict poverty. Science 353, 790–794 (2016).Article 
    CAS 
    PubMed 

    Google Scholar 
    FAO Meat live weight, cattle database. License: CC BY-NC-SA 3.0 IGO. http://www.fao.org/faostat/en/#search/cattle (2021). Accessed 24 April 2021.Gilbert, M. et al. Global distribution data for cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in 2010. Sci. Data 5, 1–11 (2018).Article 

    Google Scholar 
    United Nations University & World Health Organization. Human Energy Requirements: Report of a Joint FAO/WHO/UNU Expert Consultation: Rome, 17–24 October 2001 (Vol. 1) Food & Agriculture Org (2004). More

  • in

    Seasonal activities of the phyllosphere microbiome of perennial crops

    Robertson, G. P. et al. Cellulosic biofuel contributions to a sustainable energy future: Choices and outcomes. Sci. (80-.) 356, 1–9 (2017).Article 

    Google Scholar 
    Ma, L. et al. The impact of stand age and fertilization on the soil microbiome of Miscanthus × giganteus. Phytobiomes J. 5, 51–59 (2021).Article 

    Google Scholar 
    Hestrin, R., Lee, M. R., Whitaker, B. K. & Pett-Ridge, J. The switchgrass microbiome: a review of structure, function, and taxonomic distribution. Phytobiomes J. 5, 14–28 (2021).Article 

    Google Scholar 
    Heaton, E. A., Dohleman, F. G. & Long, S. P. Meeting US biofuel goals with less land: The potential of Miscanthus. Glob. Chang. Biol. 14, 2000–2014 (2008).Article 
    ADS 

    Google Scholar 
    Langholtz, M., Stokes, B. & Eaton, L. 2016 billion-ton report: Advancing domestic resources for a thriving bioeconomy (Executive Summary). Ind. Biotechnol. 12, 282–289 (2016).Article 

    Google Scholar 
    Roley, S. S. et al. Associative nitrogen fixation (ANF) across a nitrogen input gradient. PLoS One 13, 1–19 (2018).Article 

    Google Scholar 
    Toju, H. et al. Core microbiomes for sustainable agroecosystems. Nat. Plants 4, 247–257 (2018).Article 
    PubMed 

    Google Scholar 
    Busby, P. E. et al. Research priorities for harnessing plant microbiomes in sustainable agriculture. PLoS Biol. 15, 1–14 (2017).Article 

    Google Scholar 
    Wang, N. R. & Haney, C. H. Harnessing the genetic potential of the plant microbiome. Biochem. (Lond.) 42, 20–25 (2020).Article 
    CAS 

    Google Scholar 
    Haskett, T. L., Tkacz, A. & Poole, P. S. Engineering rhizobacteria for sustainable agriculture. ISME J. 15, 949–964 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Hacquard, S. et al. Microbiota and host nutrition across plant and animal kingdoms. Cell Host Microbe 17, 603–616 (2015).Article 
    CAS 
    PubMed 

    Google Scholar 
    Gopal, M. & Gupta, A. Microbiome selection could spur next-generation plant breeding strategies. Front. Microbiol. 7, 1971 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Hardoim, P. R. et al. The hidden world within plants: Ecological and evolutionary considerations for defining functioning of microbial endophytes. Microbiol. Mol. Biol. Rev. 79, 293–320 (2015).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Andrews, J. H. & Harris, R. F. The ecology and biogeography of microorganisms on plant surfaces. Annu. Rev. Phytopathol. 38, 145–180 (2000).Article 
    PubMed 

    Google Scholar 
    Bulgarelli, D., Schlaeppi, K., Spaepen, S., van Themaat, E. V. L. & Schulze-Lefert, P. Structure and functions of the bacterial microbiota of plants. Annu. Rev. Plant Biol. 64, 807–838 (2013).Article 
    CAS 
    PubMed 

    Google Scholar 
    Müller, D. B., Vogel, C., Bai, Y. & Vorholt, J. A. The Plant Microbiota: Systems-Level Insights and Perspectives. Annu. Rev. Genet. 50, 120215–034952 (2016).Article 

    Google Scholar 
    Kuzyakov, Y. & Razavi, B. S. Rhizosphere size and shape: Temporal dynamics and spatial stationarity. Soil Biol. Biochem. 135, 343–360 (2019).Article 
    CAS 

    Google Scholar 
    Bell, T. H. et al. Manipulating wild and tamed phytobiomes: Challenges and opportunities. Phytobiomes J. 3, 3–21 (2019).Article 

    Google Scholar 
    Chen, T. et al. A plant genetic network for preventing dysbiosis in the phyllosphere. Nature 580, 653–657 (2020).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Vorholt, J. A. Microbial life in the phyllosphere. Nat. Rev. Microbiol. 10, 828–840 (2012).Article 
    CAS 
    PubMed 

    Google Scholar 
    Koskella, B. The phyllosphere. Curr. Biol. 30, R1143–R1146 (2020).Article 
    CAS 
    PubMed 

    Google Scholar 
    Lindow, S. E. & Brandl, M. T. Microbiology of the phyllosphere. Appl. Environ. Microbiol. 69, 1875–1883 (2003).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bringel, F. & Couée, I. Pivotal roles of phyllosphere microorganisms at the interface between plant functioning and atmospheric trace gas dynamics. Front. Microbiol. 6, 486 (2015).Dorokhov, Y. L., Sheshukova, E. V. & Komarova, T. V. Methanol in plant life. Front. Plant Sci. 871, 1–6 (2018).
    Google Scholar 
    Cavicchioli, R. et al. Scientists’ warning to humanity: microorganisms and climate change. Nat. Rev. Microbiol. 17, 569–586 (2019).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Peñuelas, J. & Terradas, J. The foliar microbiome. Trends Plant Sci. 19, 278–280 (2014).Article 
    PubMed 

    Google Scholar 
    Edwards, J. et al. Structure, variation, and assembly of the root-associated microbiomes of rice. Proc. Natl Acad. Sci. USA. 112, E911–E920 (2015).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Zhalnina, K. et al. Dynamic root exudate chemistry and microbial substrate preferences drive patterns in rhizosphere microbial community assembly. Nat. Microbiol. 3, 470 (2018).Article 
    CAS 
    PubMed 

    Google Scholar 
    Xu, L. et al. Drought delays development of the sorghum root microbiome and enriches for monoderm bacteria. Proc. Natl Acad. Sci. 115, E4284–E4293 (2018).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Shade, A. & Stopnisek, N. Abundance-occupancy distributions to prioritize plant core microbiome membership. Curr. Opin. Microbiol. 49, 50–58 (2019).Article 
    PubMed 

    Google Scholar 
    Stopnisek, N. & Shade, A. Persistent microbiome members in the common bean rhizosphere: an integrated analysis of space, time, and plant genotype. ISME J. 15, 2708–2722 (2021).Grady, K. L., Sorensen, J. W., Stopnisek, N., Guittar, J. & Shade, A. Assembly and seasonality of core phyllosphere microbiota on perennial biofuel crops. Nat. Commun. 10, 4135 (2019).Singer, E., Bonnette, J., Kenaley, S. C., Woyke, T. & Juenger, T. E. Plant compartment and genetic variation drive microbiome composition in switchgrass roots. Environ. Microbiol. Rep. 11, 185–195 (2019).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lundberg, D. S. et al. Defining the core Arabidopsis thaliana root microbiome. Nature 488, 86–90 (2012).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bulgarelli, D. et al. Revealing structure and assembly cues for Arabidopsis root-inhabiting bacterial microbiota. Nature 488, 91–95 (2012).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Bahulikar, R. A., Torres-Jerez, I., Worley, E., Craven, K. & Udvardi, M. K. Diversity of nitrogen-fixing bacteria associated with switchgrass in the native tallgrass prairie of Northern Oklahoma. Appl. Environ. Microbiol. 80, 5636–5643 (2014).Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Roley, S. S., Xue, C., Hamilton, S. K., Tiedje, J. M. & Robertson, G. P. Isotopic evidence for episodic nitrogen fixation in switchgrass (Panicum virgatum L.). Soil Biol. Biochem. 129, 90–98 (2019).Article 
    CAS 

    Google Scholar 
    Bowers, R. M. et al. Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea. Nat. Biotechnol. 35, 725–731 (2017).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Yoon, S. H., Ha, S. M., Lim, J., Kwon, S. & Chun, J. A large-scale evaluation of algorithms to calculate average nucleotide identity. Antonie van. Leeuwenhoek, Int. J. Gen. Mol. Microbiol. 110, 1281–1286 (2017).Article 
    CAS 

    Google Scholar 
    Julsing, M. K., Rijpkema, M., Woerdenbag, H. J., Quax, W. J. & Kayser, O. Functional analysis of genes involved in the biosynthesis of isoprene in Bacillus subtilis. Appl. Microbiol. Biotechnol. 75, 1377–1384 (2007).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Carlström, C. I. et al. Synthetic microbiota reveal priority effects and keystone strains in the Arabidopsis phyllosphere. Nat. Ecol. Evol. 3, 1445–1454 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Laskowska, E. & Kuczyńska-Wiśnik, D. New insight into the mechanisms protecting bacteria during desiccation. Curr. Genet. 66, 313–318 (2020).Article 
    CAS 
    PubMed 

    Google Scholar 
    Zou, H. et al. The metabolism and biotechnological application of betaine in microorganism. Appl. Microbiol. Biotechnol. 100, 3865–3876 (2016).Article 
    CAS 
    PubMed 

    Google Scholar 
    Rastogi, G., Coaker, G. L. & Leveau, J. H. J. New insights into the structure and function of phyllosphere microbiota through high-throughput molecular approaches. FEMS Microbiol. Lett. 348, 1–10 (2013).Article 
    CAS 
    PubMed 

    Google Scholar 
    Urrejola, C. et al. Genomic features for desiccation tolerance and sugar biosynthesis in the extremophile gloeocapsopsis sp. UTEX B3054. Front. Microbiol. 10, 1–11 (2019).Article 

    Google Scholar 
    Lacerda-Júnior, G. V. et al. Land use and seasonal effects on the soil microbiome of a Brazilian dry forest. Front. Microbiol. 10, 1–14 (2019).Article 

    Google Scholar 
    Dai, J. et al. Unraveling adaptation of Pontibacter korlensis to radiation and infertility in desert through complete genome and comparative transcriptomic analysis. Sci. Rep. 5, 1–9 (2015).Article 

    Google Scholar 
    Harty, C. E. et al. Ethanol stimulates trehalose production through a SpoT-DksA-AlgU-dependent pathway in Pseudomonas aeruginosa. J. Bacteriol. 201, 1–21 (2019).Kimmerer, T. W. & MacDonald, R. C. Acetaldehyde and ethanol biosynthesis in leaves of plants. Plant Physiol. 84, 1204–1209 (1987).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ferner, E., Rennenberg, H. & Kreuzwieser, J. Effect of flooding on C metabolism of flood-tolerant (Quercus robur) and non-tolerant (Fagus sylvatica) tree species. Tree Physiol. 32, 135–145 (2012).Article 
    CAS 
    PubMed 

    Google Scholar 
    Kimmerer, T. W. & Kozlowski, T. T. Ethylene, ethane, acetaldehyde, and ethanol production by plants under stress. Plant Physiol. 69, 840–847 (1982).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Liu, Y. et al. Assessment of drought tolerance of 49 switchgrass (Panicum virgatum) genotypes using physiological and morphological parameters. Biotechnol. Biofuels 8, 1–18 (2015).Article 

    Google Scholar 
    Wingler, A. et al. Trehalose 6-phosphate is required for the onset of leaf senescence associated with high carbon availability. Plant Physiol. 158, 1241–1251 (2012).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Gottschlich, L., Geiser, P., Bortfeld-Miller, M., Field, C. M. & Vorholt, J. A. Complex general stress response regulation in Sphingomonas melonis Fr1 revealed by transcriptional analyses. Sci. Rep. 9, 1–13 (2019).Article 
    CAS 

    Google Scholar 
    Chen, C., Li, S., McKeever, D. R. & Beattie, G. A. The widespread plant-colonizing bacterial species Pseudomonas syringae detects and exploits an extracellular pool of choline in hosts. Plant J. 75, 891–902 (2013).Article 
    CAS 
    PubMed 

    Google Scholar 
    Valenzuela-Soto, E. M. & Figueroa-Soto, C. G. Biosynthesis and degradation of glycine betaine and its potential to control plant growth and development. in Osmoprotectant-Mediated Abiotic Stress Tolerance in Plants (eds. Anwar Hossain, M., Kumar, V., Burritt, D. J., Fujita, M. & Makela, P. S. A.) 241–256 (Springer, 2019). https://doi.org/10.1007/978-3-030-27423-8_5.Kerchev, P., De Smet, B., Waszczak, C., Messens, J. & Van Breusegem, F. Redox strategies for crop improvement. Antioxid. Redox Signal 23, 1186–1205 (2015).Article 
    CAS 
    PubMed 

    Google Scholar 
    Considine, M. J. & Foyer, C. H. Redox regulation of plant development. Antioxid. Redox Signal. 21, 1305–1326 (2014).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Spaepen, S., Vanderleyden, J. & Remans, R. Indole-3-acetic acid in microbial and microorganism-plant signaling. FEMS Microbiol. Rev. 31, 425–448 (2007).Article 
    CAS 
    PubMed 

    Google Scholar 
    Egamberdieva, D., Wirth, S. J., Alqarawi, A. A., Abd-Allah, E. F. & Hashem, A. Phytohormones and beneficial microbes: Essential components for plants to balance stress and fitness. Front. Microbiol. 8, 1–14 (2017).Article 

    Google Scholar 
    Lajoie, G., Maglione, R. & Kembel, S. W. Adaptive matching between phyllosphere bacteria and their tree hosts in a neotropical forest. Microbiome 8, 1–10 (2020).Article 

    Google Scholar 
    McGenity, T. J., Crombie, A. T. & Murrell, J. C. Microbial cycling of isoprene, the most abundantly produced biological volatile organic compound on Earth. ISME J. 12, 931–941 (2018).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Sharkey, T. D., Wiberley, A. E. & Donohue, A. R. Isoprene emission from plants: Why and how. Ann. Bot. 101, 5–18 (2008).Article 
    CAS 
    PubMed 

    Google Scholar 
    Zuo, Z. et al. Isoprene acts as a signaling molecule in gene networks important for stress responses and plant growth. Plant Physiol. 180, 124–152 (2019).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Sharkey, T. D. & Yeh, S. Isoprene emission from plants. Plant Mol. Biol. 52, 407–436 (2001).CAS 

    Google Scholar 
    Sharkey, T. D., Loreto, F. & Delwiche, C. High carbon dioxide and sun/shade effects on isoprene emission from oak and aspen tree leaves. Plant, Cell Environ. 14, 333–338 (1991).Article 
    CAS 

    Google Scholar 
    Eller, A. S. D. et al. Volatile organic compound emissions from switchgrass cultivars used as biofuel crops. Atmos. Environ. 45, 3333–3337 (2011).Article 
    ADS 
    CAS 

    Google Scholar 
    Morrison, E. C., Drewer, J. & Heal, M. R. A comparison of isoprene and monoterpene emission rates from the perennial bioenergy crops short-rotation coppice willow and Miscanthus and the annual arable crops wheat and oilseed rape. GCB Bioenergy 8, 211–225 (2016).Article 
    CAS 

    Google Scholar 
    Sivy, T. L., Shirk, M. C. & Fall, R. Isoprene synthase activity parallels fluctuations of isoprene release during growth of Bacillus subtilis. Biochem. Biophys. Res. Commun. 294, 71–75 (2002).Article 
    CAS 
    PubMed 

    Google Scholar 
    Crombie, A. T. et al. Poplar phyllosphere harbors disparate isoprene-degrading bacteria. Proc. Natl Acad. Sci. USA. 115, 13081–13086 (2018).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    El Khawand, M. et al. Isolation of isoprene degrading bacteria from soils, development of isoA gene probes and identification of the active isoprene-degrading soil community using DNA-stable isotope probing. Environ. Microbiol. 18, 2743–2753 (2016).Article 
    CAS 
    PubMed 

    Google Scholar 
    Nowicka, B. & Kruk, J. Occurrence, biosynthesis and function of isoprenoid quinones. Biochim. Biophys. Acta – Bioenerg. 1797, 1587–1605 (2010).Article 
    CAS 

    Google Scholar 
    Kałużna, M. et al. Pseudomonas cerasi sp. nov. (non Griffin, 1911) isolated from diseased tissue of cherry. Syst. Appl. Microbiol. 39, 370–377 (2016).Article 
    PubMed 

    Google Scholar 
    El-Tarabily, K. A., Nassar, A. H., Hardy, G. E. S. J. & Sivasithamparam, K. Plant growth promotion and biological control of Pythium aphanidermatum, a pathogen of cucumber, by endophytic actinomycetes. J. Appl. Microbiol 106, 13–26 (2009).Article 
    CAS 
    PubMed 

    Google Scholar 
    Javed, Z., Tripathi, G. D., Mishra, M. & Dashora, K. Actinomycetes – the microbial machinery for the organic-cycling, plant growth, and sustainable soil health. Biocatal. Agric. Biotechnol. 31, 101893 (2021).Article 
    CAS 

    Google Scholar 
    Anwar, S., Ali, B. & Sajid, I. Screening of rhizospheric actinomycetes for various in-vitro and in-vivo plant growth promoting (PGP) traits and for agroactive compounds. Front. Microbiol. 7, 1–11 (2016).Article 

    Google Scholar 
    Bao, L. et al. Microbial community overlap between the phyllosphere and rhizosphere of three plants from Yongxing Island, South China Sea. Microbiologyopen 9, 1–18 (2020).Article 

    Google Scholar 
    Remus-Emsermann, M. N. P. & Schlechter, R. O. Phyllosphere microbiology: at the interface between microbial individuals and the plant host. N. Phytol. 218, 1327–1333 (2018).Article 

    Google Scholar 
    Beilsmith, K. et al. Genome-wide association studies on the phyllosphere microbiome: embracing complexity in host–microbe interactions. Plant J. 97, 164–181 (2019).Article 
    CAS 
    PubMed 

    Google Scholar 
    Levy, A., Conway, J. M., Dangl, J. L. & Woyke, T. Elucidating bacterial gene functions in the plant microbiome. Cell Host Microbe 24, 475–485 (2018).Article 
    CAS 
    PubMed 

    Google Scholar 
    Trivedi, P., Leach, J. E., Tringe, S. G., Sa, T. & Singh, B. K. Plant–microbiome interactions: from community assembly to plant health. Nat. Rev. Microbiol. 18, 607–621 (2020).Article 
    CAS 
    PubMed 

    Google Scholar 
    Choi, H. et al. Identification of viruses and viroids infecting tomato and pepper plants in vietnam by metatranscriptomics. Int. J. Mol. Sci. 21, 1–16 (2020).Article 
    ADS 

    Google Scholar 
    Marzano, S. Y. L. & Domier, L. L. Novel mycoviruses discovered from metatranscriptomics survey of soybean phyllosphere phytobiomes. Virus Res 213, 332–342 (2016).Article 
    CAS 
    PubMed 

    Google Scholar 
    Chao S, et al. Metatranscriptomic sequencing suggests the presence of novel RNA viruses in rice rransmitted by brown planthopper. Viruses. 13, 2464 (2021).Delmotte, N. et al. Community proteogenomics reveals insights into the physiology of phyllosphere bacteria. Proc. Natl Acad. Sci. 106, 16428–16433 (2009).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Suzuki, Y., Makino, A. & Mae, T. An efficient method for extraction of RNA from rice leaves at different ages using benzyl chloride. J. Exp. Bot. 52, 1575–1579 (2001).Article 
    CAS 
    PubMed 

    Google Scholar 
    Caporaso, J. G. et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc. Natl Acad. Sci. 108, 4516–4522 (2011).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Druzhinina, I. S. et al. Massive lateral transfer of genes encoding plant cell wall-degrading enzymes to the mycoparasitic fungus Trichoderma from its plant-associated hosts. PLoS Genet. 14, e1007322 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Haridas, S. et al. 101 Dothideomycetes genomes: A test case for predicting lifestyles and emergence of pathogens. Stud. Mycol. 96, 141–153 (2020).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Gostinčar, C. et al. Genome sequencing of four Aureobasidium pullulans varieties: Biotechnological potential, stress tolerance, and description of new species. BMC Genomics 15, 549 (2014).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Gill, U. S. et al. Draft genome sequence resource of switchgrass rust pathogen, puccinia novopanici isolate ard-01. Phytopathology 109, 1513–1515 (2019).Article 
    CAS 
    PubMed 

    Google Scholar 
    Bowsher, A. W., Benucci, G. M. N., Bonito, G. & Shade, A. Seasonal dynamics of core fungi in the switchgrass phyllosphere, and co-occurrence with leaf bacteria. Phytobiomes J. 5, 60–68 (2021).Li, D., Liu, C. M., Luo, R., Sadakane, K. & Lam, T. W. MEGAHIT: An ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics 31, 1674–1676 (2015).Article 
    CAS 
    PubMed 

    Google Scholar 
    Kang, D. D. et al. MetaBAT 2: An adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies. PeerJ 2019, 1–13 (2019).
    Google Scholar 
    Nayfach, S., Shi, Z. J., Seshadri, R., Pollard, K. S. & Kyrpides, N. C. New insights from uncultivated genomes of the global human gut microbiome. Nature 568, 505–510 (2019).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Parks, D. H., Imelfort, M., Skennerton, C. T., Hugenholtz, P. & Tyson, G. W. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 25, 1043–1055 (2015).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Swan, B. K. et al. Prevalent genome streamlining and latitudinal divergence of planktonic bacteria in the surface ocean. Proc. Natl Acad. Sci. USA. 110, 11463–11468 (2013).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Eren, A. M. et al. Anvi’o: an advanced analysis and visualization platform for’omics data. PeerJ. 2015, 1–29 (2015).
    Google Scholar 
    Lee, M. D. GToTree: a user-friendly workflow for phylogenomics. Bioinformatics 35, 4162–4164 (2019).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Shaffer, M. et al. DRAM for distilling microbial metabolism to automate the curation of microbiome function. Nucleic Acids Res. 48, 8883–8900 (2020).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Parks, D. H. et al. A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life. Nat. Biotechnol. 36, 996 (2018).Article 
    CAS 
    PubMed 

    Google Scholar 
    Suzuki, R. & Shimodaira, H. Pvclust: an R package for assessing the uncertainty in hierarchical clustering. Bioinformatics 22, 1540–1542 (2006).Article 
    CAS 
    PubMed 

    Google Scholar 
    Blin, K. et al. AntiSMASH 6.0: improving cluster detection and comparison capabilities. Nucleic Acids Res. 49, W29–W35 (2021).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Navarro-Muñoz, J. C. et al. A computational framework to explore large-scale biosynthetic diversity. Nat. Chem. Biol. 16, 60–68 (2020).Article 
    PubMed 

    Google Scholar 
    Zimmermann, J., Kaleta, C. & Waschina, S. Gapseq: informed prediction of bacterial metabolic pathways and reconstruction of accurate metabolic models. Genome Biol. 22, 1–35 (2021).Article 

    Google Scholar 
    Tseng, T. T., Tyler, B. M. & Setubal, J. C. Protein secretion systems in bacterial-host associations, and their description in the Gene Ontology. BMC Microbiol 9, 1–9 (2009).Article 

    Google Scholar 
    Lucke, M., Correa, M. G. & Levy, A. The role of secretion systems, effectors, and secondary metabolites of beneficial rhizobia in interactions with plants and microbes. Front. Plant Sci. 11, 589416 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Palmer, J. L., Hilton, S., Picot, E., Bending, G. D. & Schäfer, H. Tree phyllospheres are a habitat for diverse populations of CO-oxidizing bacteria. Environ. Microbiol. 23, 6309–6327 (2021).Article 
    CAS 
    PubMed 

    Google Scholar 
    Bay, S. K. et al. Trace gas oxidizers are widespread and active members of soil microbial communities. Nat. Microbiol. 6, 246–256 (2021).Article 
    CAS 
    PubMed 

    Google Scholar  More

  • in

    Brown bear skin-borne secretions display evidence of individuality and age-sex variation

    Zala, S. M., Potts, W. K. & Penn, D. J. Scent-marking displays provide honest signals of health and infection. Behav. Ecol. 15, 338–344 (2004).Article 

    Google Scholar 
    Allen, M. L., Wallace, C. F. & Wilmers, C. C. Patterns in bobcat (Lynx rufus) scent marking and communication behaviors. J. Ethol. 33, 9–14 (2014).Article 

    Google Scholar 
    White, A. M., Swaisgood, R. R. & Zhang, H. The highs and lows of chemical communication in giant pandas (Ailuropoda melanoleuca): Effect of scent deposition height on signal discrimination. Behav. Ecol. Sociobiol. 51, 519–529 (2002).Article 

    Google Scholar 
    Scordato, E. S., Dubay, G. & Drea, C. M. Chemical composition of scent marks in the ringtailed lemur (Lemur catta): Glandular differences, seasonal variation, and individual signatures. Chem. Senses 32, 493–504 (2007).Article 
    CAS 
    PubMed 

    Google Scholar 
    Maynard Smith, J. & Harper, D. Animal Signals (Oxford University Press, 2003).
    Google Scholar 
    Stockley, P., Bottell, L. & Hurst, J. L. Wake up and smell the conflict: Odour signals in female competition. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 368, 20130082 https://doi.org/10.1098/rstb.2013.0082 (2013).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Petrulis, A. Chemosignals, hormones and mammalian reproduction. Horm. Behav. 63, 723–741 (2013).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Coombes, H. A., Stockley, P. & Hurst, J. L. Female chemical signalling underlying reproduction in mammals. J. Chem. Ecol. 44, 851–873 (2018).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Harmsen, B. J., Foster, R. J., Gutierrez, S. M., Marin, S. Y. & Patrick, C. Scrape-marking behavior of jaguars (Panthera onca) and pumas (Puma concolor). J. Mammal. 91, 1225–1234 (2010).Article 

    Google Scholar 
    Lamb, C. T. et al. Density-dependent signaling: An alternative hypothesis on the function of chemical signaling in a non-territorial solitary carnivore. PLoS ONE 12, e0184176 https://doi.org/10.1371/journal.pone.0184176 (2017).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Woodmansee, K. B., Zabel, C. J., Glickman, S. E., Frank, L. G. & Keppel, G. Scent marking (pasting) in a colony of immature spotted hyenas (Crocuta crocuta): A developmental study. J. Comp. Psychol. 105, 10–14 (1991).Article 
    CAS 
    PubMed 

    Google Scholar 
    Rasmussen, L. E. L., Riddle, H. S. & Krishnamurthy, V. Mellifluous matures to malodorous in musth. Nature 415, 975–976 (2002).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Surov, A. V. & Maltsev, A. N. Analysis of chemical communication in mammals: Zoological and ecological aspects. Biol. Bull. 43, 1175–1183 (2016).Article 

    Google Scholar 
    Hurst, J. L. Female recognition and assessment of males through scent. Behav. Brain Res. 200, 295–303 (2009).Article 
    CAS 
    PubMed 

    Google Scholar 
    Mills, M. G. L. & Gorman, M. L. The scent-marking behaviour of the spotted hyaena Crocuta crocuta in the southern Kalahari. J. Zool. 212, 483–497 (1987).Article 

    Google Scholar 
    Gassett, J. W. et al. Volatile compounds from interdigital gland of male white-tailed deer (Odocoileus virginianus). J. Chem. Ecol. 22, 1689–1696 (1996).Article 
    CAS 
    PubMed 

    Google Scholar 
    Stoeckelhuber, M., Sliwa, A. & Welsch, U. Histo-physiology of the scent-marking glands of the penile pad, anal Pouch, and the forefoot in the aardwolf (Proteles cristatus). Anat. Rec. 259, 312–326 (2000).Article 
    CAS 

    Google Scholar 
    Begg, C. M., Begg, K. S., Du Toit, J. T. & Mills, M. G. L. Scent-marking behaviour of the honey badger, Mellivora capensis (Mustelidae), in the southern Kalahari. Anim. Behav. 66, 917–929 (2003).Article 

    Google Scholar 
    Yasui, T., Tsukise, A. & Meyer, W. Histochemical analysis of glycoconjugates in the eccrine glands of the raccoon digital pads. Eur. J. Histochem. 48, 393–402 (2004).CAS 
    PubMed 

    Google Scholar 
    Johnston, R. E. Scent marking by male golden hamsters (Mesocricetus aurutus) I. Effects of odors and social encounters. Z. Tierpsychol. 37, 75–98 (1975).Article 
    CAS 
    PubMed 

    Google Scholar 
    Caspers, B., Wibbelt, G. & Voigt, C. C. Histological examinations of facial glands in Saccopteryx bilineata (Chiroptera, Emballonuridae), and their potential use in territorial marking. Zoomorphology 128, 37–43 (2008).Article 

    Google Scholar 
    Lawson, R. E., Putnam, R. J. & Fielding, A. H. Individual signatures in scent gland secretions of Eurasian deer. J. Zool. 251, 399–410 (2000).Article 

    Google Scholar 
    Smith, T. E., Tomlinson, A. J., Mlotkiewicz, J. A. & Abbott, D. H. Female marmoset monkeys (Callithrix jacchus) can be identified from the chemical composition of their scent marks. Chem. Senses 26, 449–458 (2001).Article 
    CAS 
    PubMed 

    Google Scholar 
    del Barco-Trillo, J., LaVenture, A. B. & Johnston, R. E. Male hamsters discriminate estrous state from vaginal secretions and individuals from flank marks. Behav. Process. 82, 18–24 (2009).Article 

    Google Scholar 
    Sun, L. & Müller-Schwarze, D. Anal gland secretion codes for family membership in the beaver. Behav. Ecol. Sociobiol. 44, 199–208 (1998).Article 

    Google Scholar 
    Zhang, J. X. et al. Possible coding for recognition of sexes, individuals and species in anal gland volatiles of Mustela eversmanni and M. sibirica. Chem. Senses 28, 381–388 (2003).Article 
    PubMed 

    Google Scholar 
    Kean, E. F., Müller, C. T. & Chadwick, E. A. Otter scent signals age, sex, and reproductive status. Chem. Senses 36, 555–564 (2011).Article 
    CAS 
    PubMed 

    Google Scholar 
    Rosell, F. et al. Brown bears possess anal sacs and secretions may code for sex. J. Zool. 283, 143–152 (2011).Article 

    Google Scholar 
    Buesching, C. D., Waterhouse, J. S. & Macdonald, D. W. Gas-chromatographic analyses of the subcaudal gland secretion of the European badger (Meles meles) part I: Chemical differences related to individual parameters. J. Chem. Ecol. 28, 41–56 (2002).Article 
    CAS 
    PubMed 

    Google Scholar 
    Yuan, H. et al. Anogenital gland secretions code for sex and age in the giant panda, Ailuropoda melanoleuca. Can. J. Zool. 82, 1596–1604 (2004).Article 

    Google Scholar 
    Kent, L. & Tang-Martínez, Z. Evidence of individual odors and individual discrimination in the raccoon, Procyon lotor. J. Mammal. 95, 1254–1262 (2014).Article 

    Google Scholar 
    Woodley, S. K. & Baum, M. J. Differential activation of glomeruli in the ferret’s main olfactory bulb by anal scent gland odours from males and females: An early step in mate identification. Eur. J. Neurosci. 20, 1025–1032 (2004).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Allen, M. L. et al. The role of scent marking in mate selection by female pumas (Puma concolor). PLoS ONE 10, e0139087 https://doi.org/10.1371/journal.pone.0139087 (2015).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Latour, P. Interactions between free-ranging, adult male polar bears (Ursus maritimus Phipps): A case of adult social play. Can. J. Zool. 59, 1775–1783 (1981).Article 

    Google Scholar 
    Nie, Y., Swaisgood, R. R., Zhang, Z., Liu, X. & Wei, F. Reproductive competition and fecal testosterone in wild male giant pandas (Ailuropoda melanoleuca). Behav. Ecol. Sociobiol. 66, 721–730 (2012).Article 

    Google Scholar 
    Clapham, M. & Kitchin, J. Social play in wild brown bears of varying age-sex class. Acta Ethol. 19, 181–188 (2016).Article 

    Google Scholar 
    Stonorov, D. & Stokes, A. W. Social behavior of the Alaska brown bear. Int. Conf. Bear Res. Manag. 2, 232–242 (1972).
    Google Scholar 
    Clapham, M., Nevin, O. T., Ramsey, A. D. & Rosell, F. A hypothetico-deductive approach to assessing the social function of chemical signalling in a non-territorial solitary carnivore. PLoS ONE 7, e35404 https://doi.org/10.1371/journal.pone.0035404 (2012).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Clapham, M., Nevin, O. T., Ramsey, A. D. & Rosell, F. The function of strategic tree selectivity in the chemical signalling of brown bears. Anim. Behav. 85, 1351–1357 (2013).Article 

    Google Scholar 
    Owen, M. A. et al. An experimental investigation of chemical communication in the polar bear. J. Zool. 295, 36–43 (2015).Article 

    Google Scholar 
    Sergiel, A. et al. Histological, chemical and behavioural evidence of pedal communication in brown bears. Sci. Rep. 7, 1052 https://doi.org/10.1038/s41598-017-01136-1 (2017).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Tomiyasu, J. et al. Morphological and histological features of the vomeronasal organ in the brown bear. J. Anat. 231, 749–757 (2017).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Tomiyasu, J. et al. Testicular regulation of seasonal change in apocrine glands in the back skin of the brown bear (Ursus arctos). J. Vet. Med. Sci. 80, 1034–1040 (2018).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Tomiyasu, J. et al. Testosterone-related and seasonal changes in sebaceous glands in the back skin of adult male brown bears (Ursus arctos). Can. J. Zool. 96, 205–211 (2018).Article 
    CAS 

    Google Scholar 
    Burst, T. L. & Pelton, M. R. Black bear mark trees in the Smoky mountains. Int. Conf. Bear Res. Manag. 5, 45–53 (1983).
    Google Scholar 
    Mattson, D. J. & Greene, G. I. Tree rubbing by Yellowstone grizzly bears Ursus arctos. Wildl. Biol. 1, 1–9 (2003).
    Google Scholar 
    Nie, Y. et al. Giant panda scent-marking strategies in the wild: Role of season, sex and marking surface. Anim. Behav. 84, 39–44 (2012).Article 

    Google Scholar 
    Revilla, E. et al. Brown bear communication hubs: Patterns and correlates of tree rubbing and pedal marking at a long-term marking site. PeerJ 9, 10447 https://doi.org/10.7717/peerj.10447 (2021).Article 

    Google Scholar 
    Clapham, M., Nevin, O. T., Ramsey, A. D. & Rosell, F. Scent-marking investment and motor patterns are affected by the age and sex of wild brown bears. Anim. Behav. 94, 107–116 (2014).Article 

    Google Scholar 
    Taylor, A. P., Gunther, M. S. & Allen, M. L. Black bear marking behaviour at rub trees during the breeding season in northern California. Behaviour 152, 1097–1111 (2015).Article 

    Google Scholar 
    Filipczyková, E., Heitkönig, I., Castellanos, A., Hantson, W. & Steyaert, S. Marking behavior of Andean bears in an Ecuadorian cloud forest: A pilot study. Ursus 27, 122–128 (2017).Article 

    Google Scholar 
    Stringham, S. F. Aggressive body language of bears and wildlife viewing: A response to Geist (2011). Hum.-Wildl. Interact. 5, 4 (2011).
    Google Scholar 
    Swaisgood, R. R., Lindburg, D. G. & Zhang, H. Discrimination of oestrous status in giant pandas (Ailuropoda melanoleuca) via chemical cues in urine. J. Zool. 257, 381–386 (2002).Article 

    Google Scholar 
    Wilson, A. E. et al. Behavioral, semiochemical and androgen responses by male giant pandas to the olfactory sexual receptivity cues of females. Theriogenology 114, 330–337 (2018).Article 
    CAS 
    PubMed 

    Google Scholar 
    Sillero-Zubiri, C. & Macdonald, D. W. Scent-marking and territorial behaviour of Ethiopian wolves Canis simensis. J. Zool. 245, 351–361 (1998).Article 

    Google Scholar 
    Stępniak, K. M., Niedźwiecka, N., Szewczyk, M. & Mysłajek, R. W. Scent marking in wolves Canis lupus inhabiting managed lowland forests in Poland. Mammal Res. 65, 629–638 (2020).Article 

    Google Scholar 
    Liu, D. et al. Do anogenital gland secretions of giant panda code for their sexual ability? Chin. Sci. Bull. 51, 1986–1995 (2006).Article 
    CAS 

    Google Scholar 
    Tattoni, C., Bragalanti, N., Groff, C. & Rovero, F. Patterns in the use of rub trees by the Eurasian brown bear. Hystrix 26, 118 (2015).
    Google Scholar 
    Zhang, J. X. et al. Potential chemosignals in the anogenital gland secretion of giant pandas, Ailuropoda melanoleuca, associated with sex and individual identity. J. Chem. Ecol. 34, 398–407 (2008).Article 
    CAS 
    PubMed 

    Google Scholar 
    Swaisgood, R. R., Lindburg, D. G., Zhou, X. & Owen, M. A. The effects of sex, reproductive condition and context on discrimination of conspecific odours by giant pandas. Anim. Behav. 60, 227–237 (2000).Article 
    CAS 
    PubMed 

    Google Scholar 
    Swaisgood, R., Lindburg, D. & Zhou, X. Giant pandas discriminate individual differences in conspecific scent. Anim. Behav. 57, 1045–1053 (1999).Article 
    CAS 
    PubMed 

    Google Scholar 
    Liu, D. et al. Do urinary chemosignals code for sex, age, and season in the giant panda, Ailuropoda melanoleuca? in Chemical Signals in Vertebrates. Vol. 12. 207–222 (eds. East, M. L. & Dehnhard, M.). https://doi.org/10.1007/978-1-4614-5927-9_16 (Springer, 2013).Hagey, L. & MacDonald, E. Chemical cues identify gender and individuality in giant pandas (Ailuropoda melanoleuca). J. Chem. Ecol. 29, 1479–1488 (2003).Article 
    CAS 
    PubMed 

    Google Scholar 
    Wilson, A. E., Sparks, D. L., Knott, K. K., Willard, S. & Brown, A. Implementing solid phase microextraction (SPME) as a tool to detect volatile compounds produced by giant pandas in the environment. PLoS ONE 13, e0208618 https://doi.org/10.1371/journal.pone.0208618 (2018).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Wilson, A. E. et al. Field air analysis of volatile compounds from free-ranging giant pandas. Ursus 29, 75–81 (2019).Article 

    Google Scholar 
    Crupi, A. P., Waite, J. N., Flynn, R. W. & Beier, L. Brown bear population estimation in Yakutat, Southeast Alaska. Alaska Department of Fish and Game https://doi.org/10.13140/RG.2.2.35947.54568 (2017).Article 

    Google Scholar 
    Sikes, R. S., Gannon, W. L. & The Animal Care and Use Committee of the American Society of Mammalogists. Guidelines of the American Society of Mammalogists for the use of wild mammals in research. J. Mammal. 92, 235–253 (2011).Matson, G. et al. A Laboratory Manual for Cementum Age Determination of Alaska Brown Bear First Premolar Teeth. Alaska Department of Fish and Game, Division of Wildlife Conservation https://www.adfg.alaska.gov/index.cfm?adfg=librarypublications.wildlifepublicationsdetails&pubidentifier=3374 (1993).Seryodkin, I. V. Marking activity of the Kamchatka brown bear (Ursus arctos piscator). Achiev. Life Sci. 8, 153–161 (2014).
    Google Scholar 
    Peralbo-Molina, A., Calderón-Santiago, M., Jurado-Gámez, B., Luque De Castro, M. D. & Priego-Capote, F. Exhaled breath condensate to discriminate individuals with different smoking habits by GC-TOF/MS. Sci. Rep. 7, 1421 https://doi.org/10.1038/s41598-017-01564-z (2017).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Liu, D. et al. Male panda (Ailuropoda melanoleuca) urine contains kinship information. Chin. Sci. Bull. 53, 2793–2800 (2008).CAS 

    Google Scholar 
    Kean, E. F., Chadwick, E. A. & Müller, C. T. Scent signals individual identity and country of origin in otters. Mamm. Biol. Z. Säugetierkd. 80, 99–105 (2015).Article 

    Google Scholar 
    R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.r-project.org/ (2020).Harris, R. L., Holland, B. R., Cameron, E. Z., Davies, N. W. & Nicol, S. C. Chemical signals in the echidna: Differences between seasons, sexes, individuals and gland types. J. Zool. 293, 171–180 (2014).Article 

    Google Scholar 
    Vaglio, S. et al. Sternal gland scent-marking signals sex, age, rank, and group identity in captive mandrills. Chem. Senses 41, 177–186 (2016).PubMed 

    Google Scholar 
    Knott, K. K. et al. Blood-based biomarkers of selenium and thyroid status indicate possible adverse biological effects of mercury and polychlorinated biphenyls in Southern Beaufort Sea polar bears. Environ. Res. 111, 1124–1136 (2011).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Wilson, A. E. et al. Development and validation of protein biomarkers of health in grizzly bears. Conserv. Physiol. 8, coaa056 https://doi.org/10.1093/conphys/coaa056 (2020).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Oksanen, J. et al. Vegan: community ecology package. R package version 2.6-4. https://CRAN.R-project.org/package=vegan (2020).Williams, C. L., Ybarra, A. R., Meredith, A. N., Durrant, B. S. & Tubbs, C. W. Gut microbiota and phytoestrogen-associated infertility in Southern White Rhinoceros. MBio 10, e00311-19 https://doi.org/10.1128/mBio.00311-19 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Dill-McFarland, K. A., Breaker, J. D. & Suen, G. Microbial succession in the gastrointestinal tract of dairy cows from 2 weeks to first lactation. Sci. Rep. 7, 40864 https://doi.org/10.1038/srep40864 (2017).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Williams, C. L. et al. Dietary changes during weaning shape the gut microbiota of red pandas (Ailurus fulgens). Conserv. Physiol. 6, cox075 https://doi.org/10.1093/conphys/cox075 (2018).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bolar, K. STAT: interactive document for working with basic statistical analysis. R package version 0.1.0. https://CRAN.R-project.org/package=STAT (2019).Gese, E. & Ruff, R. Scent-marking by coyotes, Canis latrans: The influence of social and ecological factors. Anim. Behav. 54, 1155–1166 (1997).Article 
    CAS 
    PubMed 

    Google Scholar 
    Thompson, C. L. et al. What smells? Developing in-field methods to characterize the chemical composition of wild mammalian scent cues. Ecol. Evol. 10, 4691–4701 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Charpentier, M. J. E., Barthes, N., Proffit, M., Bessière, J.-M. & Grison, C. Critical thinking in the chemical ecology of mammalian communication: Roadmap for future studies. Funct. Ecol. 26, 769–774 (2012).Article 

    Google Scholar 
    Martín, J., Carranza, J., López, P., Alarcos, S. & Pérez-González, J. A new sexual signal in rutting male red deer: Age related chemical scent constituents in the belly black spot. Mamm. Biol. 79, 362–368 (2014).Article 

    Google Scholar 
    Carranza, J. et al. The dark ventral patch: A bimodal flexible trait related to male competition in red deer. PLoS ONE 15, 0241374 https://doi.org/10.1371/journal.pone.0241374 (2020).Article 
    CAS 

    Google Scholar 
    Kean, E. F., Bruford, M. W., Russo, I. R. M., Müller, C. T. & Chadwick, E. A. Odour dialects among wild mammals. Sci. Rep. 7, 13593 https://doi.org/10.1038/s41598-017-12706-8 (2017).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Marneweck, C., Jürgens, A. & Shrader, A. M. The role of middens in white rhino olfactory communication. Anim. Behav. 140, 7–18 (2018).Article 

    Google Scholar 
    Linklater, W. L., Mayer, K. & Swaisgood, R. R. Chemical signals of age, sex and identity in black rhinoceros. Anim. Behav. 85, 671–677 (2013).Article 

    Google Scholar 
    White, A. M., Swaisgood, R. R. & Zhang, H. Chemical communication in the giant panda (Ailuropoda melanoleuca): The role of age in the signaller and assessor. J. Zool. 259, 171–178 (2003).Article 

    Google Scholar 
    Steiger, S., Schmitt, T. & Schaefer, H. M. The origin and dynamic evolution of chemical information transfer. Proc. R. Soc. B Biol. Sci. 278, 970–979 https://doi.org/10.1098/rspb.2010.2285 (2011).Article 

    Google Scholar 
    Williams, C. L. et al. Wildlife-microbiome interactions and disease: Exploring opportunities for disease mitigation across ecological scales. Drug Discov. Today Dis. Models 28, 105–115 (2018).Article 

    Google Scholar 
    Chiang, Y. R., Wei, S. T. S., Wang, P. H., Wu, P. H. & Yu, C. P. Microbial degradation of steroid sex hormones: Implications for environmental and ecological studies. Microb. Biotechnol. 13, 926–949 (2020).Article 
    CAS 
    PubMed 

    Google Scholar 
    Williams, C. L., Garcia-Reyero, N., Martyniuk, C. J., Tubbs, C. W. & Bisesi, J. H. Regulation of endocrine systems by the microbiome: Perspectives from comparative animal models. Gen. Comp. Endocrinol. 292, 113437 (2020).Article 
    CAS 
    PubMed 

    Google Scholar 
    Theis, K. R., Venkataraman, A., Wagner, A. P., Holekamp, K. E. & Schmidt, T. M. Age-related variation in the scent pouch bacterial communities of striped hyenas (Hyaena hyaena). Chem. Signals Vertebr. 13, 87–103 (2016).Article 

    Google Scholar 
    Steyaert, S. M. J. G., Endrestøl, A., Hackländer, K., Swenson, J. E. & Zedrosser, A. The mating system of the brown bear Ursus arctos. Mammal Rev. 42, 12–34 (2012).Article 

    Google Scholar 
    Bellemain, E. et al. The dilemma of female mate selection in the brown bear, a species with sexually selected infanticide. Proc. R. Soc. B Biol. Sci. 273, 283–291 https://doi.org/10.1098/rspb.2005.3331 (2006).Article 

    Google Scholar 
    Zedrosser, A., Bellemain, E., Taberlet, P. & Swenson, J. E. Genetic estimates of annual reproductive success in male brown bears: The effects of body size, age, internal relatedness and population density. J. Anim. Ecol. 76, 368–375 (2007).Article 
    PubMed 

    Google Scholar 
    Schwartz, C. C. et al. Reproductive maturation and senescence in the female brown bear. Ursus 14, 109–119 (2003).
    Google Scholar 
    Schulte, B. A., Freeman, E. W., Goodwin, T. E., Hollister-Smith, J. & Rasmussen, L. E. L. Honest signalling through chemicals by elephants with applications for care and conservation. Appl. Anim. Behav. Sci. 102, 344–363 (2007).Article 

    Google Scholar 
    Støen, O.-G., Bellemain, E., Sæbø, S. & Swenson, J. E. Kin-related spatial structure in brown bears Ursus arctos. Behav. Ecol. Sociobiol. 59, 191–197 (2005).Article 

    Google Scholar 
    Egbert, A. L. & Stokes, A. W. The social behaviour of brown bears on an Alaskan salmon stream. Int. Conf. Bear Res. Manag. 3, 41–56 (1976).
    Google Scholar 
    Craighead, J. J., Sumner, J. S. & Mitchell, J. A. The Grizzly Bears of Yellowstone: Their Ecology in the Yellowstone Ecosystem, 1959–1992 (Island Press, 1995).
    Google Scholar 
    Burgener, N., Dehnhard, M., Hofer, H. & East, M. L. Does anal gland scent signal identity in the spotted hyaena? Anim.
    Behav. 77, 707–715 (2009).Article 

    Google Scholar 
    Noonan, M. J. et al. Knowing me, knowing you: Anal gland secretion of European badgers (Meles meles) codes for individuality, sex and social group membership. J. Chem. Ecol. 45, 823–837 (2019).Article 
    CAS 
    PubMed 

    Google Scholar 
    Sun, L. & Müller-Schwarze, D. Sibling recognition in the beaver: A field test for phenotype matching. Anim. Behav. 54, 493–502 (1997).Article 
    CAS 
    PubMed 

    Google Scholar 
    Thom, M. D. & Hurst, J. L. Individual recognition by scent. Ann. Zool. Fenn. 41, 765–787 (2004).
    Google Scholar 
    Roberts, S. A. et al. Individual odour signatures that mice learn are shaped by involatile major urinary proteins (MUPs). BMC Biol. 16, 1–19 https://doi.org/10.1186/s12915-018-0512-9 (2018).Article 
    CAS 

    Google Scholar 
    Henkel, S. & Setchell, J. M. Group and kin recognition via olfactory cues in chimpanzees (Pan troglodytes). Proc. R. Soc. B Biol. Sci. 285, 20181527 https://doi.org/10.1098/rspb.2018.1527 (2018).Article 

    Google Scholar 
    Vogt, K., Boos, S., Breitenmoser, U. & Kölliker, M. Chemical composition of Eurasian lynx urine conveys information on reproductive state, individual identity, and urine age. Chemoecology 26, 205–217 (2016).Article 
    CAS 

    Google Scholar 
    Wyatt, T. D. Pheromones and signature mixtures: Defining species-wide signals and variable cues for identity in both invertebrates and vertebrates. J. Comp. Physiol. A Neuroethol. Sens. Neural. Behav. Physiol. 196, 685–700 (2010).Article 
    CAS 
    PubMed 

    Google Scholar 
    Johnston, R. E. Chemical communication in rodents: From pheromones to individual recognition. J. Mammal. 84, 1141–1162 (2003).Article 

    Google Scholar 
    Dehnhard, M. Mammal semiochemicals: Understanding pheromones and signature mixtures for better zoo-animal husbandry and conservation. Int. Zoo Yearb. 45, 55–79 (2011).Article 

    Google Scholar 
    Brennan, P. A. & Kendrick, K. M. Mammalian social odours: Attraction and individual recognition. Philos. Trans. R. Soc. B Biol. Sci. 361, 2061–2078 https://doi.org/10.1098/rstb.2006.1931 (2006).Article 
    CAS 

    Google Scholar 
    Bellemain, E., Swenson, J. E. & Taberlet, P. Mating strategies in relation to sexually selected infanticide in a non-social carnivore: The brown bear. Ethology 112, 238–246 (2006).Article 

    Google Scholar 
    Rogers, L. L. Effects of food supply and kinship on social behavior, movements, and population growth of black bears in northeastern Minnesota. Wildl. Monogr. 97, 72 (1987).
    Google Scholar 
    Noyce, K. V. & Garshelis, D. L. Follow the leader: Social cues help guide landscape-level movements of American black bears (Ursus americanus). Can. J. Zool. 92, 1005–1017 (2014).Article 

    Google Scholar 
    Hansen, J. E., Hertel, A. G., Frank, S. C., Kindberg, J. & Zedrosser, A. Social environment shapes female settlement decisions in a solitary carnivore. Behav. Ecol. 33, 137–146 (2022).Article 
    CAS 
    PubMed 

    Google Scholar 
    Morehouse, A. T., Loosen, A. E., Graves, T. A. & Boyce, M. S. The smell of success: Reproductive success related to rub behavior in brown bears. PLoS ONE 16, 247964 https://doi.org/10.1371/journal.pone.0247964 (2021).Article 
    CAS 

    Google Scholar 
    Tschanz, B., Meyer-Holzapfel, M. & Bachmann, S. Das informationssystem bei Braunbären. Z. Tierpsychol. 27, 47–72 (1970).Article 

    Google Scholar 
    Tattoni, C., Bragalanti, N., Ciolli, M., Groff, C. & Rovero, F. Behavior of the European brown bear at rub trees. Ursus 32e9, 1–11https://doi.org/10.2192/URSUS-D-20-00022.3 (2021).Article 

    Google Scholar 
    Alberts, A. C. Constraints on the design of chemical communication systems in terrestrial vertebrates. Am. Nat. 139, S62–S89 (1992).Article 

    Google Scholar  More

  • in

    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