More stories

  • 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

  • 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

    Public interest in individual study animals can bolster wildlife conservation

    Benson, E. S. Sci. Context 29, 107–128 (2016).Article 
    PubMed 

    Google Scholar 
    Buckmaster, C. A. Lab Anim. 44, 237 (2015).Article 

    Google Scholar 
    Kelly, M. J. et al. J. Zool. 244, 473–488 (1998).Article 

    Google Scholar 
    Spagnuolo, O. S. B., Lemerle, M. A., Holekamp, K. E. & Wiesel, I. Mamm. Biol. https://doi.org/10.1007/s42991-022-00309-4 (2022).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    California Department of Fish and Wildlife. Mountain lion P-22 compassionately euthanized following complete health evaluation results. wildlife.ca.gov, https://wildlife.ca.gov/News/mountain-lion-p-22-compassionately-euthanized-following-complete-health-evaluation-results (17 December 2022).Road Ecology Center, UC Davis. California roadkill observation system, https://www.wildlifecrossing.net/california/ (accessed 19 December 2022).Wong-Parodi, G. & Feygina, I. Environ. Commun. 15, 571–593 (2021).Article 

    Google Scholar 
    Carmi, N., Arnon, S. & Orion, N. J. Environ. Educ. 46, 183–201 (2015).Article 

    Google Scholar 
    Manfredo, M. J., Urquiza-Haas, E. G., Don Carlos, A. W., Bruskotter, J. T. & Dietsch, A. M. Biol. Conserv. 241, 108297 (2020).Article 

    Google Scholar 
    Schueler, D. S. & Newberry, M. G. III Appl. Environ. Educ. Commun. 19, 259–273 (2020).Article 

    Google Scholar 
    Jennings, L. Public gets to name Dallas Zoo’s baby giraffe. Dallas Zoo https://zoohoo.dallaszoo.com/2014/11/05/public-gets-to-name-dallas-zoos-baby-giraffe/ (5 November 2014).Verma, A., van der Wal, R. & Fischer, A. Ambio 44(Suppl 4), 648–660 (2015).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Macdonald, D. W., Jacobsen, K. S., Burnham, D., Johnson, P. J. & Loveridge, A. J. Animals 6, 26 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Jones, M. D., Shanahan, E. A. & McBeth, M. K. The Science of Stories: Applications of the Narrative Policy Framework in Public Policy Analysis (Palgrave MacMillan, 2014). More

  • in

    Taxonomic composition, community structure and molecular novelty of microeukaryotes in a temperate oligomesotrophic lake as revealed by metabarcoding

    Pawlowski, J. et al. CBOL Protist working group: barcoding eukaryotic richness beyond the animal, plant, and fungal kingdoms. PLOS Biol. 10, e1001419 (2012).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    del Campo, J. et al. The others: our biased perspective of eukaryotic genomes. Trends Ecol. Evol. 29, 252–259 (2014).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Handbook of the Protists (Springer, 2017). https://doi.org/10.1007/978-3-319-28149-0.Lang, B. F., O’Kelly, C., Nerad, T., Gray, M. W. & Burger, G. The closest unicellular relatives of animals. Curr. Biol. 12, 1773–1778 (2002).Article 
    CAS 
    PubMed 

    Google Scholar 
    del Campo, J. et al. Ecological and evolutionary significance of novel protist lineages. Eur. J. Protistol. 55, 4–11 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Grau-Bové, X. et al. Dynamics of genomic innovation in the unicellular ancestry of animals. Life 6, e26036 (2017).
    Google Scholar 
    Gawryluk, R. M. R. et al. Non-photosynthetic predators are sister to red algae. Nature 572, 240–243 (2019).Article 
    CAS 
    PubMed 

    Google Scholar 
    Gabr, A., Grossman, A. R. & Bhattacharya, D. Paulinella, a model for understanding plastid primary endosymbiosis. J. Phycol. 56, 837–843 (2020).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Gao, Z., Karlsson, I., Geisen, S., Kowalchuk, G. & Jousset, A. Protists: Puppet masters of the rhizosphere microbiome. Trends Plant Sci. 24, 165–176 (2019).Article 
    CAS 
    PubMed 

    Google Scholar 
    Caron, D. A. New accomplishments and approaches for assessing protistan diversity and ecology in natural ecosystems. Bioscience 59, 287–299 (2009).Article 

    Google Scholar 
    Gooday, A. J., Schoenle, A., Dolan, J. R. & Arndt, H. Protist diversity and function in the dark ocean: Challenging the paradigms of deep-sea ecology with special emphasis on foraminiferans and naked protists. Eur. J. Protistol. 75, 125721 (2020).Article 
    PubMed 

    Google Scholar 
    Stoecker, D. K., Johnson, M. D., de Vargas, C. & Not, F. Acquired phototrophy in aquatic protists. Aquat. Microb. Ecol. 57, 279–310 (2009).Article 

    Google Scholar 
    Strom, S. L., Benner, R., Ziegler, S. & Dagg, M. J. Planktonic grazers are a potentially important source of marine dissolved organic carbon. Limnol. Oceanogr. 42, 1364–1374 (1997).Article 
    ADS 
    CAS 

    Google Scholar 
    Orsi, W. D. et al. Identifying protist consumers of photosynthetic picoeukaryotes in the surface ocean using stable isotope probing. Environ. Microbiol. 20, 815–827 (2018).Article 
    CAS 
    PubMed 

    Google Scholar 
    Corno, G. & Jürgens, K. Direct and indirect effects of protist predation on population size structure of a bacterial strain with high phenotypic plasticity. Appl. Environ. Microbiol. 72, 78–86 (2006).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Mahé, F. et al. Parasites dominate hyperdiverse soil protist communities in Neotropical rainforests. Nat. Ecol. Evol. 1, 91 (2017).Article 
    PubMed 

    Google Scholar 
    Ruppert, K. M., Kline, R. J. & Rahman, M. S. Past, present, and future perspectives of environmental DNA (eDNA) metabarcoding: A systematic review in methods, monitoring, and applications of global eDNA. Glob. Ecol. Conserv. 17, e00547 (2019).Article 

    Google Scholar 
    Epstein, S. & López-García, P. “Missing” protists: a molecular prospective. Biodivers. Conserv. 17, 261–276 (2008).Article 

    Google Scholar 
    López-García, P., Rodríguez-Valera, F., Pedrós-Alió, C. & Moreira, D. Unexpected diversity of small eukaryotes in deep-sea Antarctic plankton. Nature 409, 603–607 (2001).Article 
    ADS 
    PubMed 

    Google Scholar 
    Lovejoy, C., Massana, R. & Pedrós-Alió, C. Diversity and distribution of marine microbial eukaryotes in the Arctic Ocean and adjacent seas. Appl. Environ. Microbiol. 72, 3085–3095 (2006).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Worden, A. Z., Cuvelier, M. L. & Bartlett, D. H. In-depth analyses of marine microbial community genomics. Trends Microbiol. 14, 331–336 (2006).Article 
    CAS 
    PubMed 

    Google Scholar 
    Countway, P. D. et al. Distinct protistan assemblages characterize the euphotic zone and deep sea (2500 m) of the western North Atlantic (Sargasso Sea and Gulf Stream). Environ. Microbiol. 9, 1219–1232 (2007).Article 
    CAS 
    PubMed 

    Google Scholar 
    Massana, R. & Pedrós-Alió, C. Unveiling new microbial eukaryotes in the surface ocean. Curr. Opin. Microbiol. 11, 213–218 (2008).Article 
    PubMed 

    Google Scholar 
    Alexander, E. et al. Microbial eukaryotes in the hypersaline anoxic L’Atalante deep-sea basin. Environ. Microbiol. 11, 360–381 (2009).Article 
    CAS 
    PubMed 

    Google Scholar 
    Stoeck, T. et al. Multiple marker parallel tag environmental DNA sequencing reveals a highly complex eukaryotic community in marine anoxic water. Mol. Ecol. 19, 21–31 (2010).Article 
    CAS 
    PubMed 

    Google Scholar 
    Logares, R. et al. Patterns of rare and abundant marine microbial eukaryotes. Curr. Biol. 24, 813–821 (2014).Article 
    CAS 
    PubMed 

    Google Scholar 
    de Vargas, C. et al. Eukaryotic plankton diversity in the sunlit ocean. Science 348, 150 (2015).Article 

    Google Scholar 
    Fell, J. W., Scorzetti, G., Connell, L. & Craig, S. Biodiversity of micro-eukaryotes in Antarctic Dry Valley soils with More

  • in

    The spatio-temporal distribution of alkaline phosphatase activity and phoD gene abundance and diversity in sediment of Sancha Lake

    Smith, V. H. Eutrophication of freshwater and coastal marine ecosystems: A global problem. Environ. Sc. Pollut. R. Int. 10, 126–139 (2003).Article 
    CAS 

    Google Scholar 
    Jeppesen, E., Sondergaard, M. & Jensen, J. P. Lake responses to reduced nutrient loading an analysis of contemporary long term data from 35 case studies. Freshw. Biol. 50, 1747–1771 (2005).Article 
    CAS 

    Google Scholar 
    Kim, L. H., Choi, E. & Michal, K. S. Sediment characteristics, phosphorus types and phosphorus release rates between river and lake sediments. Chemosphere 50, 53–61 (2003).Article 
    ADS 
    CAS 

    Google Scholar 
    Jiang, X. J., Xiang, C. & Yao, Y. Effects of biological activity, light, temperature and oxygen on phosphorus release processes at the sediment and water interface of Taihu Lake, China. Water Res. 42, 2251–2259 (2008).Article 
    CAS 

    Google Scholar 
    Wang, S. R., Jin, X. C. & Bu, Q. Y. Effects of dissolved oxygen supply level on phosphorus release from lake sediments. Colloids Surf. A 316, 245–252 (2008).Article 
    CAS 

    Google Scholar 
    Miao, S. Y., De-Laune, R. D. & Jug-Sujinda, A. Influence of sediment redox conditions on release/solubility of metals and nutrients in a Louisiana Mississippi River deltaic plain freshwater lake. Sci. Total Environ. 371, 334–343 (2006).Article 
    ADS 
    CAS 

    Google Scholar 
    Smits, J. G. C. & Van Beek, J. K. L. ECO: A generic eutrophication model including comprehensive sediment-water interaction. PLoS ONE 8, e68104 (2013).Article 
    ADS 
    CAS 

    Google Scholar 
    Topcu, A. & Pulatsu, S. Phosphorus fractions and cycling in the sediment of a shallow eutrophic pond. Tarim Bilim. Derg. 20, 63–70 (2014).Article 

    Google Scholar 
    Jeppesen, E., Sondergaard, M. & Jensen, J. P. Lake responses to reduced nutrient loading-an analysis of contemporary long-term data from 35 case studies. Freshw. Biol. 50, 1747–1771 (2005).Article 
    CAS 

    Google Scholar 
    Song, C. L., Cao, X. Y. & Liu, Y. B. Seasonal variations in chlorophyll a concentrations in relation to potentials of sediment phosphate release by different mechanisms in a large chinese shallow eutrophic lake (Lake Taihu). Geomicrobiol. J. 26, 508–515 (2009).Article 
    CAS 

    Google Scholar 
    Pop, O., Martin, U., Abel, C. & Müller, J. P. The twin-arginine signal peptide of PhoD and the TatAd/Cd proteins of Bacillus subtilis form an autonomous tat translocation system. J. Biol. Chem. 277, 3268–3273 (2002).Article 
    CAS 

    Google Scholar 
    Luo, H. W., Zhang, H. M. & Long, R. A. Depth distributions of alkaline phosphatase and phosphonate utilization genes in the North Pacific Subtropical Gyre. Aquat. Microb. Ecol. 62, 61–69 (2011).Article 

    Google Scholar 
    Tan, H. et al. Long-term phosphorus fertilisation increased the diversity of the total bacterial community and the phoD phosphorus mineraliser group in pasture soils. Biol. Fertil. Soils 49, 661–672 (2012).Article 

    Google Scholar 
    Wan, W. J. et al. Spatial differences in soil microbial diversity caused by pH-driven organic phosphorus mineralization. Land Degrad. Dev. 32, 766–776 (2021).Article 

    Google Scholar 
    Chen, X. et al. Response of soil phoD phosphatase gene to long-term combined applications of chemical fertilizers and organic materials. Appl. Soil Ecol. 119, 197–204 (2017).Article 
    ADS 

    Google Scholar 
    Sagnon, A. et al. Amendment with Burkina Faso phosphate rock-enriched composts alters soil chemical properties and microbial structure, and enhances sorghum agronomic performance. Sci. Rep. 12, 13945 (2022).Article 
    ADS 
    CAS 

    Google Scholar 
    Chhabra, S. et al. Fertilization management affects the alkaline phosphatase bacterial community in barley rhizosphere soil. Biol. Fertil. Soils 49, 31–39 (2012).Article 

    Google Scholar 
    Luo, H. W., Benner, R., Long, R. A. & Hu, J. J. Subcellular localization of marine bacterial alkaline phosphatases. Proc. Natl. Acad. Sci. 106, 212–219 (2009).Article 

    Google Scholar 
    Zhang, T. X. et al. Suspended particles phoD alkaline phosphatase gene diversity in large shallow eutrophic Lake Taihu. Sci. Total Environ. 728, 138615 (2020).Article 
    ADS 
    CAS 

    Google Scholar 
    Li, H. et al. Nutrients regeneration pathway, release potential, transformation pattern and algal utilization strategies jointly drove cyanobacterial growth and their succession. J. Environ. Sci. 103, 255–267 (2021).Article 
    CAS 

    Google Scholar 
    Sun, T. T., Huang, T. & Liu, Y. X. Effects of cyanobacterial growth and decline on the phoD-harboring bacterial community structure in sediments of Lake Chaohu. J. Lake Sci. 34, 32 (2022).ADS 

    Google Scholar 
    Li, Y., Ai, M. J., Sun, Y., Zhang, Y. Q. & Zhang, J. Q. Spirosoma lacussanchae sp. nov., a phosphate-solubilizing bacterium isolated from a freshwater reservoir. Int. J. Syst. Evol. Microbiol. 67, 3144–3149 (2017).Article 
    CAS 

    Google Scholar 
    Li, Y., Zhang, J. J., Xu, W. L. & Mou, Z. S. Microbial community structure in the sediments and its relation to environmental factors in eutrophicated Sancha Lake. Int. J. Environ. Res. Public Health 16, 1931–1946 (2019).Article 
    CAS 

    Google Scholar 
    Jia, B. Y., Tang, Y. & Fu, W. L. Relationship among sediment characteristics, eutrophication process and human activities in the Sancha Lake. China Environ. Sci. 33, 1638–1644 (2013).CAS 

    Google Scholar 
    Li, Y., Zhang, J. J., Zhang, J. Q., Xu, W. L. & Mou, Z. S. Characteristics of inorganic phosphate-solubilizing bacteria from the sediments of a Eutrophic Lake. Int. J. Environ. Res. Public Health 16, 2141 (2019).Article 
    CAS 

    Google Scholar 
    Ruban, V., Brigault, S., Demare, D. & Philippe, A. M. An investigation of the origin and mobility of phosphorus in freshwater sediments from Bort-Les-Orgues reservoir, France. J. Environ. Monit. 1, 403–407 (1999).Article 
    CAS 

    Google Scholar 
    Ruban, V., López-Sánchez, J. F. & Pardo, P. Harmonized protocol and certified reference material for the determination of extractable contents of phosphorus in freshwater sediments: A synthesis of recent works. Fresenius J. Anal. Chem. 370, 224–228 (2001).Article 
    CAS 

    Google Scholar 
    Li, Y., Zhang, J. Q., Gong, Z. L., Fu, W. L. & Wu, D. M. Fractions and temporal and spatial distribution of phosphorus in the sediments of Sancha lake. Appl. Ecol. Environ. Res. 17, 11731–11743 (2019).Article 

    Google Scholar 
    Li, Y., Zhang, J. Q., Gong, Z. L., Xu, W. L. & Mou, Z. S. Gcd gene diversity of quinoprotein glucose dehydrogenase in the sediment of Sancha lake and its response to the environment. Int. J. Environ. Res. Public Health 16, 1–10 (2019).Article 

    Google Scholar 
    Luo, G. W. et al. Long-term fertilisation regimes affect the composition of the alkaline phosphomonoesterase encoding microbial community of a vertisol and its derivative soil fractions. Biol. Fertil. Soils 53, 375–388 (2017).Article 
    CAS 

    Google Scholar 
    Lagos, L. et al. Effect of phosphorus addition on total and alkaline phosphomonoesterase-harboring bacterial populations in ryegrass rhizosphere microsites. Biol. Fertil. Soils 52, 1007–1019 (2016).Article 
    CAS 

    Google Scholar 
    Acuña, J. et al. Bacterial alkaline phosphomono-esterase in the rhizospheres of plants grown in chilean extreme environments. Biol. Fertil. Soils 52, 763–773 (2016).Article 

    Google Scholar 
    Nicholas, A. B. et al. Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing. Nat. Methods. 10, 57–59 (2013).Article 

    Google Scholar 
    Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree: Computing large minimum evolution trees with profiles instead of a distance matrix. Mol. Biol. Evol. 26, 1641–1650 (2009).Article 
    CAS 

    Google Scholar 
    Fan, X. F. & Xing, P. The vertical distribution of sediment archaeal community in the (black bloom) disturbing Zhushan Bay of Lake Taihu. Archaea 2016, 201–208 (2016).Article 

    Google Scholar 
    White, J. R., Nagarajan, N. & Pop, M. O. Statistical methods for detecting differentially abundant features in clinical metagenomic samples (differential abundance in clinical metagenomics). PLoS Comput. Biol. 5, 1–11 (2009).Article 

    Google Scholar 
    Hu, H., Chen, X. J., Hou, F. J., Wu, Y. P. & Cheng, Y. X. Bacterial and fungal community structures in loess plateau grasslands with different grazing intensities. Front. Microbiol. 8, 606 (2017).Article 

    Google Scholar 
    Dai, J. Y. et al. Bacterial alkaline phosphatases and affiliated encoding genes in natural waters: A review. J. Lake Sci. 28, 1153–1166 (2016).Article 

    Google Scholar 
    Chróst, R. J. & Overbeck, J. Kinetics of alkaline phosphatase activity and phosphorus availability for phytoplankton and bacterio-plankton in lake plusee (North German Eutrophic Lake). Microb. Ecol. 13, 229–248 (1987).Article 

    Google Scholar 
    Margalef, O. et al. Global patterns of phosphatase activity in natural soils. Sci. Rep. 7, 1337 (2017).Article 
    ADS 
    CAS 

    Google Scholar 
    Zhao, D. D., Luo, J. F., Huang, X. Y. & Lin, W. T. Diversity of bacterial APase phoD gene in the Pearl River water. Acta Sci. Circum. 35, 722–728 (2015).CAS 

    Google Scholar 
    Valdespino-Castillo, P. M. et al. Alkaline phosphatases in microbialites and bacterioplankton from Alchichica soda lake, Mexico. FEMS Microbiol. Ecol. 90, 504–519 (2014).CAS 

    Google Scholar 
    Ni, Z. K., Li, Y. & Wang, S. R. Cognizing and characterizing the organic phosphorus in lake sediments: Advances and challenges. Water Res. 220, 118663 (2022).Article 
    CAS 

    Google Scholar 
    Han, S. S. & Wen, T. M. Phosphorus release and affecting factors in the sediments of eutrophic water. J. Ecol. 23, 98–101 (2004).
    Google Scholar 
    Wang, F. F., Qu, J. H. & Hu, Y. S. Spatio-temporal characteristics and correlation of phosphate, pH and alkaline phosphatase on water-sediment interface of Lake Taihu. Ecol. Environ. Sci. 21, 907–912 (2012).
    Google Scholar 
    Lu, Y. M. et al. Bioavailability of organic phosphorus in Lake Chaohu sediments. J. Environ. Eng. Technol. 10, 197–204 (2020).
    Google Scholar 
    LeBrun, E. S., King, R. S., Back, J. A. & Kang, S. Microbial community structure and function decoupling across a phosphorus gradient in streams. Microb. Ecol. 75, 64–73 (2018).Article 
    CAS 

    Google Scholar 
    Zhang, J. et al. Connecting sources, fractions and algal availability of sediment phosphorus in shallow lakes: An approach to the criteria for sediment phosphorus concentrations. J. Environ. Sci. 25, 798–810 (2023).Article 

    Google Scholar 
    Hu, Y. J. et al. Effects of long-term fertilization on phoD-harboring bacterial community in Karst soils. Sci. Total Environ. 628–629, 53–63 (2018).Article 
    ADS 

    Google Scholar  More

  • in

    Pathways of degradation in rangelands in Northern Tanzania show their loss of resistance, but potential for recovery

    Asner, G. P., Elmore, A. J., Olander, L. P., Martin, R. E. & Harris, A. T. Grazing systems, ecosystem responses, and global change. Annu. Rev. Environ. Resour. 29, 261–299 (2004).Article 

    Google Scholar 
    Millenium Ecosystem Assessment Board. Ecosystems and Human Well-Being: Wetlands and Water: Synthesis (Island Press, Washington, DC, 2005).Lind, J., Sabates-Wheeler, R., Caravani, M., Kuol, L. B. D. & Nightingale, D. M. Newly evolving pastoral and post-pastoral rangelands of Eastern Africa. Pastoralism 10, 24 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Hoffman, T. & Vogel, C. Climate change impacts on African rangelands. Rangelands 30, 12–17 (2008).Article 

    Google Scholar 
    Joyce, L. A. et al. Climate change and North American rangelands: Assessment of mitigation and adaptation strategies. Rangeland Ecol. Manage. 66, 512–528 (2013).Article 

    Google Scholar 
    Stringer, L. C., Reed, M. S., Dougill, A. J., Seely, M. K. & Rokitzki, M. Implementing the UNCCD: Participatory challenges. Nat. Resour. Forum 31, 198–211 (2007).Article 

    Google Scholar 
    Vågen, T.-G., Winowiecki, L. A., Tondoh, J. E., Desta, L. T. & Gumbricht, T. Mapping of soil properties and land degradation risk in Africa using MODIS reflectance. Geoderma 263, 216–225 (2016).Article 
    ADS 

    Google Scholar 
    Stevens, N., Lehmann, C. E. R., Murphy, B. P. & Durigan, G. Savanna woody encroachment is widespread across three continents. Glob. Chang. Biol. 23, 235–244 (2017).Article 
    ADS 
    PubMed 

    Google Scholar 
    Muñoz, P. et al. Land degradation, poverty and inequality (2019).Bond, W. & Keeley, J. Fire as a global ‘herbivore’: the ecology and evolution of flammable ecosystems. Trends Ecol. Evol. 20, 387–394 (2005).Article 
    PubMed 

    Google Scholar 
    Lehmann, C. E. R., Archibald, S. A., Hoffmann, W. A. & Bond, W. J. Deciphering the distribution of the savanna biome. New Phytol. 191, 197–209 (2011).Article 
    PubMed 

    Google Scholar 
    Staver, A. C., Archibald, S. & Levin, S. A. The global extent and determinants of savanna and forest as alternative biome states. Science 334, 230–232 (2011).Article 
    ADS 
    CAS 
    MATH 
    PubMed 

    Google Scholar 
    Fuhlendorf, S. D., Fynn, R. W. S., McGranahan, D. A. & Twidwell, D. Heterogeneity as the basis for rangeland management in Rangeland Systems: Processes, Management and Challenges, Springer Series on Environmental Management (ed. Briske, D. D.), 169–196 (Springer International Publishing, 2017).Liao, C., Agrawal, A., Clark, P. E., Levin, S. A. & Rubenstein, D. I. Landscape sustainability science in the drylands: mobility, rangelands and livelihoods. Landsc. Ecol. 35, 2433–2447 (2020).Article 

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

    Google Scholar 
    López-i Gelats, F., Fraser, E. D. G., Morton, J. F. & Rivera-Ferre, M. G. What drives the vulnerability of pastoralists to global environmental change? A qualitative meta-analysis. Glob. Environ. Change 39, 258–274 (2016).Obiri, J. F. Invasive plant species and their disaster-effects in dry tropical forests and rangelands of Kenya and Tanzania. Jàmbá: Journal of Disaster Risk Studies 3, 417–428 (2011).Kioko, J., Kiringe, J. W. & Seno, S. O. Impacts of livestock grazing on a savanna grassland in Kenya. J. Arid Land 4, 29–35 (2012).Article 

    Google Scholar 
    Kotiaho, J. S. et al. The IPBES assessment report on land degradation and restoration. Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem (2018).Western, D., Mose, V. N., Worden, J. & Maitumo, D. Predicting extreme droughts in savannah Africa: A comparison of proxy and direct measures in detecting biomass fluctuations, trends and their causes. PLoS One 10, e0136516 (2015).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Dai, A. Drought under global warming: a review. WIREs Climate Change 2, 45–65 (2011).Article 

    Google Scholar 
    Holechek, J. L., Cibils, A. F., Bengaly, K. & Kinyamario, J. I. Human population growth, African pastoralism, and rangelands: A perspective. Rangeland Ecol. Manage. 70, 273–280 (2017).Article 

    Google Scholar 
    Midgley, G. F. & Bond, W. J. Future of African terrestrial biodiversity and ecosystems under anthropogenic climate change. Nat. Clim. Chang. 5, 823–829 (2015).Article 
    ADS 

    Google Scholar 
    Hill, M. J. & Guerschman, J. P. The MODIS global vegetation fractional cover product 2001–2018: Characteristics of vegetation fractional cover in grasslands and savanna woodlands. Remote Sensing 12, 406 (2020).Article 
    ADS 

    Google Scholar 
    Lake, P. S. Resistance, resilience and restoration. Ecol. Manage. Restor. 14, 20–24 (2013).Article 

    Google Scholar 
    Hodgson, D., McDonald, J. L. & Hosken, D. J. What do you mean, ‘resilient’?. Trends Ecol. Evol. 30, 503–506 (2015).Article 
    PubMed 

    Google Scholar 
    Tilman, D. & Downing, J. A. Biodiversity and stability in grasslands. Nature 367, 363–365 (1994).Article 
    ADS 

    Google Scholar 
    Fedrigo, J. K. et al. Temporary grazing exclusion promotes rapid recovery of species richness and productivity in a long-term overgrazed Campos grassland. Restor. Ecol. 26, 677–685 (2018).Article 

    Google Scholar 
    Ruppert, J. C. et al. Quantifying drylands’ drought resistance and recovery: the importance of drought intensity, dominant life history and grazing regime. Glob. Chang. Biol. 21, 1258–1270 (2015).Article 
    ADS 
    PubMed 

    Google Scholar 
    Homewood, K. M. Policy, environment and development in African rangelands. Environ. Sci. Policy 7, 125–143 (2004).Article 

    Google Scholar 
    Caro, T. & Davenport, T. R. B. Wildlife and wildlife management in Tanzania. Conserv. Biol. 30, 716–723 (2016).Article 
    PubMed 

    Google Scholar 
    Bollig, M. & Schulte, A. Environmental change and pastoral perceptions: degradation and indigenous knowledge in two African pastoral communities. Hum. Ecol. 27, 493–514 (1999).Article 

    Google Scholar 
    Veldhuis, M. P. et al. Cross-boundary human impacts compromise the Serengeti-Mara ecosystem. Science 363, 1424–1428 (2019).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Nicholson, S. E. Climate and climatic variability of rainfall over Eastern Africa. Rev. Geophys. 55, 590–635 (2017).Article 
    ADS 

    Google Scholar 
    2012 Population and Housing Census (National Bureau of Statistics, Ministry of Finance, 2013).Kiffner, C., Nagar, S., Kollmar, C. & Kioko, J. Wildlife species richness and densities in wildlife corridors of Northern Tanzania. J. Nat. Conserv. 31, 29–37 (2016).Article 

    Google Scholar 
    Foley, C. A. H. & Faust, L. J. Rapid population growth in an elephant Loxodonta africana population recovering from poaching in Tarangire National Park, Tanzania. Oryx 44, 205–212 (2010).Article 

    Google Scholar 
    Kebacho, L. L. Large-scale circulations associated with recent interannual variability of the short rains over East Africa. Meteorol. Atmos. Phys. 134, 10 (2021).Article 
    ADS 

    Google Scholar 
    Wainwright, C. M., Finney, D. L., Kilavi, M., Black, E. & Marsham, J. H. Extreme rainfall in East Africa, October 2019-January 2020 and context under future climate change. Weather 76, 26–31 (2021).Article 
    ADS 

    Google Scholar 
    Abukari, H. & Mwalyosi, R. B. Comparing pressures on national parks in Ghana and Tanzania: The case of mole and Tarangire National Parks. Global Ecol. Conserv. 15, e00405 (2018).Article 

    Google Scholar 
    Kaswamila, A. An analysis of the contribution of community wildlife management areas on livelihood in Tanzania. Sustain. Natl. Res. Manag. 139–54 (2012).NTRI. Maps | NTRI – Northern Tanzania Rangelands Initiative. https://www.ntri.co.tz/maps/ (2016). Accessed: 2021-3-29.Mworia, J., Kinyamario, J. & John, E. Impact of the invader Ipomoea hildebrandtii on grass biomass, nitrogen mineralisation and determinants of its seedling establishment in Kajiado, Kenya. Afr. J. Range Forage Sci. 25, 11–16 (2008).Article 

    Google Scholar 
    Manyanza, N. M. & Ojija, F. Invasion, impact and control techniques for invasive Ipomoea hildebrandtii on Maasai steppe rangelands. NATO Adv. Sci. Inst. Ser. E Appl. Sci. 17, 12 (2021).Thaiyah, A. G. et al. Acute, sub-chronic and chronic toxicity of Solanum incanum L in sheep in Kenya. Kenya Veterinarian 35, 1–8 (2011).
    Google Scholar 
    Roques, K. G., O’Connor, T. G. & Watkinson, A. R. Dynamics of shrub encroachment in an African savanna: relative influences of fire, herbivory, rainfall and density dependence. J. Appl. Ecol. 38, 268–280 (2001).Article 

    Google Scholar 
    Riginos, C. & Herrick, J. E. Monitoring rangeland health: a guide for pastoralists and other land managers in Eastern Africa. Version II (2010).Farr, T. G. et al. The shuttle radar topography mission. Rev. Geophys. 45, RG2004 (2007).QGIS Development Team. QGIS Geographic Information System. QGIS Association (2022).Gorelick, N. et al. Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sens. Environ. 202, 18–27 (2017).Article 
    ADS 

    Google Scholar 
    Didan, K. MOD13Q1 MODIS/Terra Vegetation Indices 16-Day L3 Global 250m SIN Grid V006 [Data set] (NASA EOSDIS Land Processes DAAC, 2015).Friedl, M. & Sulla-Menashe, D. MCD12Q1 MODIS/Terra+ Aqua Land Cover Type Yearly L3 Global 500m SIN Grid V006 (NASA EOSDIS Land Processes DAAC, 2019).Vermote, E. MOD09A1 MODIS/Terra Surface Reflectance 8-day L3 Global 500m SIN Grid V006. NASA EOSDIS Land Processes DAAC 10 (2015).Funk, C. et al. The climate hazards infrared precipitation with stations–a new environmental record for monitoring extremes. Scientific Data 2, 1–21 (2015).Article 

    Google Scholar 
    Zeileis, A. & Grothendieck, G. zoo: S3 infrastructure for regular and irregular time series. arXiv:math/0505527 (2005).R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. (2016).Scaramuzza, P. & Barsi, J. Landsat 7 scan line corrector-off gap-filled product development in Proceeding of Pecora 16, 23–27 (2005).
    Google Scholar 
    Huete, A. et al. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sens. Environ. 83, 195–213 (2002).Article 
    ADS 

    Google Scholar 
    Rikimaru, A., Roy, P. S. & Miyatake, S. Tropical forest cover density mapping. Trop. Ecol. 39–47 (2002).Diek, S., Fornallaz, F., Schaepman, M. E. & De Jong, R. Barest pixel composite for agricultural areas using landsat time series. Remote Sensing 9, 1245 (2017).Article 
    ADS 

    Google Scholar 
    Qi, J., Chehbouni, A., Huete, A. R., Kerr, Y. H. & Sorooshian, S. A modified soil adjusted vegetation index. Remote Sens. Environ. 48, 119–126 (1994).Article 
    ADS 

    Google Scholar 
    Adams, B. et al. Mapping forest composition with Landsat time series: An evaluation of seasonal composites and harmonic regression. Remote Sensing 12, 610 (2020).Article 
    ADS 

    Google Scholar 
    Nwanganga, F. & Chapple, M. Practical machine learning in R (John Wiley and Sons, Indianapolis, 2020).Adam, E., Mutanga, O., Odindi, J. & Abdel-Rahman, E. M. Land-use/cover classification in a heterogeneous coastal landscape using RapidEye imagery: evaluating the performance of random forest and support vector machines classifiers. Int. J. Remote Sens. 35, 3440–3458 (2014).Article 

    Google Scholar 
    Mansour, K., Mutanga, O., Adam, E. & Abdel-Rahman, E. M. Multispectral remote sensing for mapping grassland degradation using the key indicators of grass species and edaphic factors. Geocarto Int. 31, 477–491 (2016).Article 

    Google Scholar 
    Hunter, F. D. L., Mitchard, E. T. A., Tyrrell, P. & Russell, S. Inter-Seasonal time series imagery enhances classification accuracy of grazing resource and land degradation maps in a savanna ecosystem. Remote Sensing 12, 198 (2020).Article 
    ADS 

    Google Scholar 
    Yang, L. et al. Estimating surface downward shortwave radiation over china based on the gradient boosting decision tree method. Remote Sensing 10, 185 (2018).Article 
    ADS 

    Google Scholar 
    Pham, T. D. et al. Estimating mangrove Above-Ground biomass using extreme gradient boosting decision trees algorithm with fused Sentinel-2 and ALOS-2 PALSAR-2 data in Can Gio biosphere reserve, Vietnam. Remote Sensing 12, 777 (2020).Article 
    ADS 

    Google Scholar 
    Adobe Inc. Adobe illustrator.Lenth, R. V. emmeans: Estimated marginal means, aka Least-Squares means. R package version 1.5.4 (2021).Royall, R. M. The effect of sample size on the meaning of significance tests. Am. Stat. 40, 313–315 (1986).MATH 

    Google Scholar 
    Rue, H., Martino, S. & Chopin, N. Approximate bayesian inference for latent Gaussian models by using integrated nested Laplace approximations. J. R. Stat. Soc. Series B Stat. Methodol. 71, 319–392 (2009).Lindgren, F. & Rue, H. Bayesian spatial modelling with R-INLA. J. Stat. Softw. 63, 1–25 (2015).Article 

    Google Scholar 
    Bakka, H. et al. Spatial modelling with R-INLA: A review. arXiv:1802.06350 [stat] (2018).Lobora, A. L. et al. Modelling habitat conversion in Miombo woodlands: Insights from Tanzania. J. Land Use Sci. 1747423X.2017.1331271 (2017).Bright, E. A., Rose, A. N., Urban, M. L. & McKee, J. LandScan 2017 High-Resolution global population data set. Tech. Rep., Oak Ridge National Lab.(ORNL), Oak Ridge, TN (United States) (2018).Gilbert, M. et al. Global distribution data for cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in 2010. Sci Data 5, 180227 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Yang, Y., Fang, J., Ma, W. & Wang, W. Relationship between variability in aboveground net primary production and precipitation in global grasslands. Geophys. Res. Lett. 35 (2008).Guo, Q. et al. Spatial variations in aboveground net primary productivity along a climate gradient in Eurasian temperate grassland: effects of mean annual precipitation and its seasonal distribution. Glob. Chang. Biol. 18, 3624–3631 (2012).Article 
    ADS 

    Google Scholar 
    Wang, X., Yue, Y. & Faraway, J. J. Bayesian Regression Modeling with INLA (Chapman and Hall/CRC, 2018).Côté, I. M. & Darling, E. S. Rethinking ecosystem resilience in the face of climate change. PLoS Biol. 8, e1000438 (2010).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    O’Loughlin, J. et al. Climate variability and conflict risk in East Africa, 1990–2009. Proc. Natl. Acad. Sci. 109, 18344–18349 (2012).Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ongoma, V., Chen, H., Gao, C., Nyongesa, A. M. & Polong, F. Future changes in climate extremes over Equatorial East Africa based on CMIP5 multimodel ensemble. Nat. Hazards 90, 901–920 (2018).Article 

    Google Scholar 
    Homewood, K. & Rodgers, W. A. Pastoralism, conservation and the overgrazing controversy. Conservation in Africa: People, policies and practice 111–128 (1987).Scoones, I. Exploiting heterogeneity: habitat use by cattle in dryland Zimbabwe. J. Arid Environ. 29, 221–237 (1995).Article 
    ADS 

    Google Scholar 
    Goldman, M. J. & Riosmena, F. Adaptive capacity in Tanzanian Maasailand: Changing strategies to cope with drought in fragmented landscapes. Glob. Environ. Change 23, 588–597 (2013).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Selemani, I. S. & Others. Communal rangelands management and challenges underpinning pastoral mobility in Tanzania: a review. Livestock Res. Rural Dev. 26, 1–12 (2014).Middleton, N. Rangeland management and climate hazards in drylands: dust storms, desertification and the overgrazing debate. Nat. Hazards 92, 57–70 (2018).Article 

    Google Scholar 
    Sallu, S. M., Twyman, C. & Stringer, L. C. Resilient or vulnerable livelihoods? Assessing livelihood dynamics and trajectories in rural Botswana. Ecology and Society 15 (2010).Oba, G. & Lusigi, W. J. An overview of drought strategies and land use in African pastoral systems (Agricultural Administration Unit, Overseas Development Institute, 1987).Russell, S., Tyrrell, P. & Western, D. Seasonal interactions of pastoralists and wildlife in relation to pasture in an African savanna ecosystem. J. Arid Environ. 154, 70–81 (2018).Article 
    ADS 

    Google Scholar 
    Girvetz, E. et al. Future climate projections in Africa: Where are we headed? In The Climate-Smart Agriculture Papers: Investigating the Business of a Productive, Resilient and Low Emission Future 15–27 (Springer International Publishing, 2019).Lyon, B. & DeWitt, D. G. A recent and abrupt decline in the East African long rains. Geophys. Res. Lett. 39 (2012).Liebmann, B. et al. Climatology and interannual variability of boreal spring wet season precipitation in the Eastern Horn of Africa and implications for its recent decline. J. Clim. 30, 3867–3886 (2017).Article 
    ADS 

    Google Scholar 
    Shongwe, M. E., van Oldenborgh, G. J., van den Hurk, B. & van Aalst, M. Projected changes in mean and extreme precipitation in Africa under global warming. part II: East Africa. J. Clim. 24, 3718–3733 (2011).Dunning, C. M., Black, E. & Allan, R. P. Later wet seasons with more intense rainfall over Africa under future climate change. J. Clim. 31, 9719–9738 (2018).Article 
    ADS 

    Google Scholar 
    Rowell, D. P., Booth, B. B. B., Nicholson, S. E. & Good, P. Reconciling past and future rainfall trends over East Africa. J. Clim. 28, 9768–9788 (2015).Article 
    ADS 

    Google Scholar 
    Vizy, E. K. & Cook, K. H. Mid-Twenty-First-Century changes in extreme events over Northern and Tropical Africa. J. Clim. 25, 5748–5767 (2012).Article 
    ADS 

    Google Scholar 
    Gebremeskel Haile, G. et al. Droughts in East Africa: Causes, impacts and resilience. Earth-Sci. Rev. 193, 146–161 (2019).Kendon, E. J. et al. Enhanced future changes in wet and dry extremes over Africa at convection-permitting scale. Nat. Commun. 10, 1794 (2019).Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Finney, D. L. et al. Effects of explicit convection on future projections of mesoscale circulations, rainfall, and rainfall extremes over Eastern Africa. J. Clim. 33, 2701–2718 (2020).Article 
    ADS 

    Google Scholar 
    Prins, H. H. T. & Loth, P. E. Rainfall patterns as background to plant phenology in Northern Tanzania. J. Biogeogr. 15, 451–463 (1988).Article 

    Google Scholar 
    Ngondya, I. B., Treydte, A. C., Ndakidemi, P. A. & Munishi, L. K. Invasive plants: ecological effects, status, management challenges in Tanzania and the way forward. J. Biodivers. Environ. Sci. (JBES) 10, 204–217 (2017).
    Google Scholar 
    Drusch, M. et al. Sentinel-2: ESA’s optical High-Resolution mission for GMES operational services. Remote Sens. Environ. 120, 25–36 (2012).Article 
    ADS 

    Google Scholar 
    Rapinel, S. et al. Evaluation of Sentinel-2 time-series for mapping floodplain grassland plant communities. Remote Sens. Environ. 223, 115–129 (2019).Article 
    ADS 

    Google Scholar 
    Li, W. et al. Accelerating savanna degradation threatens the Maasai Mara socio-ecological system. Glob. Environ. Change 60, 102030 (2020).Article 

    Google Scholar 
    Wonkka, C. L., Twidwell, D., Franz, T. E., Taylor, C. A. & Rogers, W. E. Persistence of a severe drought increases desertification but not woody dieback in semiarid savanna. Rangeland Ecol. Manage. 69, 491–498 (2016).Article 

    Google Scholar 
    Vierich, H. I. D. & Stoop, W. A. Changes in West African savanna agriculture in response to growing population and continuing low rainfall. Agric. Ecosyst. Environ. 31, 115–132 (1990).Article 

    Google Scholar 
    Fynn, R. W. S. & O’Connor, T. G. Effect of stocking rate and rainfall on rangeland dynamics and cattle performance in a semi-arid savanna, South Africa. J. Appl. Ecol. 37, 491–507 (2000).Article 

    Google Scholar 
    Wang, S., Chen, W., Xie, S. M., Azzari, G. & Lobell, D. B. Weakly supervised deep learning for segmentation of remote sensing imagery. Remote Sensing 12, 207 (2020).Article 
    ADS 

    Google Scholar 
    Alananga, S., Makupa, E. R., Moyo, K. J., Matotola, U. C. & Mrema, E. F. Land administration practices in Tanzania: A replica of past mistakes. Journal of Property, Planning and Environmental Law (2019).Huggins, C. Village land use planning and commercialization of land in Tanzania. LANDac Research Brief 1 (2016).Stein, H., Maganga, F. P., Odgaard, R., Askew, K. & Cunningham, S. The formal divide: Customary rights and the allocation of credit to agriculture in Tanzania. J. Dev. Stud. 52, 1306–1319 (2016).Article 

    Google Scholar 
    Hall, D. G. M., Reeve, M. J., Thomasson, A. J. & Wright, V. F. Water retention, porosity and density of field soils (No. Tech. Monograph N9, 1977).Moore, D. C. & Singer, M. J. Crust formation effects on soil erosion processes. Soil Sci. Soc. Am. J. 54, 1117–1123 (1990).Article 
    ADS 

    Google Scholar 
    Cotler, H. & Ortega-Larrocea, M. P. Effects of land use on soil erosion in a tropical dry forest ecosystem, Chamela watershed, Mexico. Catena 65, 107–117 (2006).Article 

    Google Scholar 
    Bach, E. M., Baer, S. G., Meyer, C. K. & Six, J. Soil texture affects soil microbial and structural recovery during grassland restoration. Soil Biol. Biochem. 42, 2182–2191 (2010).Article 
    CAS 

    Google Scholar 
    Butz, R. J. Traditional fire management: historical fire regimes and land use change in pastoral East Africa. Int. J. Wildland Fire 18, 442–450 (2009).Article 

    Google Scholar  More

  • in

    Diverse flower-visiting responses among pollinators to multiple weather variables in buckwheat pollination

    Mooney, H. et al. Biodiversity, climate change, and ecosystem services. Curr. Opin. Environ. Sustain. 1, 46–54 (2009).Article 

    Google Scholar 
    Perrings, C., Duraiappah, A., Larigauderie, A. & Mooney, H. The biodiversity and ecosystem services science-policy interface. Science 331, 1139–1140 (2011).Article 
    ADS 
    CAS 

    Google Scholar 
    Yachi, S. & Loreau, M. Biodiversity and ecosystem productivity in a fluctuating environment: The insurance hypothesis. Proc. Natl. Acad. Sci. USA 96, 1463–1468 (1999).Article 
    ADS 
    CAS 

    Google Scholar 
    Elmqvist, T. et al. Response diversity, ecosystem change, and resilience. Front. Ecol. Environ. 1, 488–494 (2003).Article 

    Google Scholar 
    Gonzalez, A. & Loreau, M. The causes and consequences of compensatory dynamics in ecological communities. Annu. Rev. Ecol. Evol. Syst. 40, 393–414 (2009).Article 

    Google Scholar 
    Blüthgen, N. & Klein, A.-M. Functional complementarity and specialisation: The role of biodiversity in plant–pollinator interactions. Basic Appl. Ecol. 12, 282–291 (2011).Article 

    Google Scholar 
    Brittain, C., Kremen, C. & Klein, A. M. Biodiversity buffers pollination from changes in environmental conditions. Glob. Change Biol. 19, 540–547 (2013).Article 
    ADS 

    Google Scholar 
    Rader, R., Reilly, J., Bartomeus, I. & Winfree, R. Native bees buffer the negative impact of climate warming on honey bee pollination of watermelon crops. Glob. Chang. Biol. 19, 3103–3110 (2013).Article 
    ADS 

    Google Scholar 
    Rogers, S. R., Tarpy, D. R. & Burrack, H. J. Bee species diversity enhances productivity and stability in a perennial crop. PLoS ONE 9, e97307 (2014).Article 
    ADS 

    Google Scholar 
    Kühsel, S. & Blüthgen, N. High diversity stabilizes the thermal resilience of pollinator communities in intensively managed grasslands. Nat. Commun. 6, 1–10 (2015).Article 

    Google Scholar 
    Knop, E. et al. Rush hours in flower visitors over a day-night cycle. Insect Conserv. Divers. 11, 267–275 (2018).Article 

    Google Scholar 
    Goodwin, E. K., Rader, R., Encinas-Viso, F. & Saunders, M. E. Weather conditions affect the visitation frequency, richness and detectability of insect flower visitors in the Australian Alpine zone. Environ. Entomol. 50, 348–358 (2021).Article 

    Google Scholar 
    Feit, B. et al. Landscape complexity promotes resilience of biological pest control to climate change. Proc. Biol. Sci. 288, 20210547 (2021).
    Google Scholar 
    Tomas, F., Martínez-Crego, B., Hernán, G. & Santos, R. Responses of seagrass to anthropogenic and natural disturbances do not equally translate to its consumers. Glob. Chang. Biol. 21, 4021–4030 (2015).Article 
    ADS 

    Google Scholar 
    Mori, A. S., Furukawa, T. & Sasaki, T. Response diversity determines the resilience of ecosystems to environmental change. Biol. Rev. 88, 349–364 (2013).Article 

    Google Scholar 
    Cariveau, D. P., Williams, N. M., Benjamin, F. E. & Winfree, R. Response diversity to land use occurs but does not consistently stabilise ecosystem services provided by native pollinators. Ecol. Lett. 16, 903–911 (2013).Article 

    Google Scholar 
    Garibaldi, L. A. et al. Wild pollinators enhance fruit set of crops regardless of honey bee abundance. Science 339, 1608. https://doi.org/10.1126/science.1230200 (2013).Article 
    ADS 
    CAS 

    Google Scholar 
    Kennedy, C. M. et al. A global quantitative synthesis of local and landscape effects on wild bee pollinators in agroecosystems. Ecol. Lett. 16, 584–599 (2013).Article 

    Google Scholar 
    Rader, R. et al. Non-bee insects are important contributors to global crop pollination. Proc. Natl. Acad. Sci. 113, 146–151 (2016).Article 
    ADS 
    CAS 

    Google Scholar 
    Klein, A.-M. et al. Importance of pollinators in changing landscapes for world crops. Proc. R. Soc. B Biol. Sci. 274, 303–313 (2007).Article 

    Google Scholar 
    Smith, M. R., Singh, G. M., Mozaffarian, D. & Myers, S. S. Effects of decreases of animal pollinators on human nutrition and global health: A modelling analysis. Lancet 386, 1964–1972 (2015).Article 

    Google Scholar 
    González-Varo, J. P. et al. Combined effects of global change pressures on animal-mediated pollination. Trends Ecol. Evol. 28, 524–530 (2013).Article 

    Google Scholar 
    Marshall, L. et al. The interplay of climate and land use change affects the distribution of EU bumblebees. Glob. Change Biol. 24, 101–116 (2018).Article 
    ADS 

    Google Scholar 
    Millard, J. et al. Global effects of land-use intensity on local pollinator biodiversity. Nat. Commun. 12, 1–11 (2021).Article 
    ADS 

    Google Scholar 
    Vasiliev, D. & Greenwood, S. The role of climate change in pollinator decline across the Northern Hemisphere is underestimated. Sci. Total Environ. 775, 145788 (2021).Article 
    ADS 
    CAS 

    Google Scholar 
    Steffan-Dewenter, I., Münzenberg, U., Bürger, C., Thies, C. & Tscharntke, T. Scale-dependent effects of landscape context on three pollinator guilds. Ecology 83, 1421–1432 (2002).Article 

    Google Scholar 
    Hass, A. L. et al. Landscape configurational heterogeneity by small-scale agriculture, not crop diversity, maintains pollinators and plant reproduction in western Europe. Proc. R. Soc. B Biol. Sci. https://doi.org/10.1098/rspb.2017.2242 (2018).Article 

    Google Scholar 
    Winfree, R. & Kremen, C. Are ecosystem services stabilized by differences among species? A test using crop pollination. Proc. R. Soc. B Biol. Sci. 276, 229–237 (2009).Article 

    Google Scholar 
    Jauker, F., Diekoetter, T., Schwarzbach, F. & Wolters, V. Pollinator dispersal in an agricultural matrix: Opposing responses of wild bees and hoverflies to landscape structure and distance from main habitat. Landsc. Ecol. 24, 547–555 (2009).Article 

    Google Scholar 
    Weiner, C. N., Werner, M., Linsenmair, K. E. & Blüthgen, N. Land-use impacts on plant–pollinator networks: Interaction strength and specialization predict pollinator declines. Ecology 95, 466–474 (2014).Article 

    Google Scholar 
    Chain-Guadarrama, A., Martínez-Salinas, A., Aristizábal, N. & Ricketts, T. H. Ecosystem services by birds and bees to coffee in a changing climate: A review of coffee berry borer control and pollination. Agric. Ecosyst. Environ. 280, 53–67 (2019).Article 

    Google Scholar 
    Hegland, S. J., Nielsen, A., Lázaro, A., Bjerknes, A. L. & Totland, Ø. How does climate warming affect plant–pollinator interactions?. Ecol. Lett. 12, 184–195 (2009).Article 

    Google Scholar 
    Bartomeus, I. et al. Contribution of insect pollinators to crop yield and quality varies with agricultural intensification. PeerJ 2, e328 (2014).Article 

    Google Scholar 
    Albrecht, M., Schmid, B., Hautier, Y. & Müller, C. B. Diverse pollinator communities enhance plant reproductive success. Proc. R. Soc. B Biol. Sci. 279, 4845–4852 (2012).Article 

    Google Scholar 
    Ellis, C. R., Feltham, H., Park, K., Hanley, N. & Goulson, D. Seasonal complementary in pollinators of soft-fruit crops. Basic Appl. Ecol. 19, 45–55 (2017).Article 

    Google Scholar 
    Brittain, C., Williams, N., Kremen, C. & Klein, A.-M. Synergistic effects of non-Apis bees and honey bees for pollination services. Proc. R. Soc. B Biol. Sci. 280, 20122767 (2013).Article 

    Google Scholar 
    Miñarro, M. & Twizell, K. W. Pollination services provided by wild insects to kiwifruit (Actinidia deliciosa). Apidologie 46, 276–285 (2015).Article 

    Google Scholar 
    Senapathi, D., Goddard, M. A., Kunin, W. E. & Baldock, K. C. Landscape impacts on pollinator communities in temperate systems: Evidence and knowledge gaps. Funct. Ecol. 31, 26–37 (2017).Article 

    Google Scholar 
    Papanikolaou, A. D., Kuehn, I., Frenzel, M. & Schweiger, O. Landscape heterogeneity enhances stability of wild bee abundance under highly varying temperature, but not under highly varying precipitation. Landsc. Ecol. 32, 581–593 (2017).Article 

    Google Scholar 
    Papanikolaou, A. D., Kühn, I., Frenzel, M. & Schweiger, O. Semi-natural habitats mitigate the effects of temperature rise on wild bees. J. Appl. Ecol. 54, 527–536 (2017).Article 

    Google Scholar 
    Orford, K. A., Vaughan, I. P. & Memmott, J. The forgotten flies: The importance of non-syrphid Diptera as pollinators. Proc. R. Soc. B Biol. Sci. 282, 20142934 (2015).Article 

    Google Scholar 
    Settele, J., Bishop, J. & Potts, S. G. Climate change impacts on pollination. Nat. Plants 2, 1–3 (2016).Article 

    Google Scholar 
    Taki, H., Okabe, K., Makino, S. I., Yamaura, Y. & Sueyoshi, M. Contribution of small insects to pollination of common buckwheat, a distylous crop. Ann. Appl. Biol. 155, 121–129 (2009).Article 

    Google Scholar 
    Krkošková, B. & Mrazova, Z. Prophylactic components of buckwheat. Food Res. Int. 38, 561–568 (2005).Article 

    Google Scholar 
    Campbell, J. W., Irvin, A., Irvin, H., Stanley-Stahr, C. & Ellis, J. D. Insect visitors to flowering buckwheat, Fagopyrum esculentum (Polygonales: Polygonaceae), in north-central Florida. Fla. Entomol. 99, 264–268 (2016).Article 

    Google Scholar 
    Hadley, N. F. Water Relations of Terrestrial Arthropods (CUP Archive, 1994).
    Google Scholar 
    Sgolastra, F. et al. Temporal activity patterns in a flower visitor community of Dictamnus albus in relation to some biotic and abiotic factors. Bull. Insectol. 69, 291–300 (2016).
    Google Scholar 
    Vicens, N. & Bosch, J. Weather-dependent pollinator activity in an apple orchard, with special reference to Osmia cornuta and Apis mellifera (Hymenoptera: Megachilidae and Apidae). Environ. Entomol. 29, 413–420 (2000).Article 

    Google Scholar 
    Carlucci, M. B., Brancalion, P. H., Rodrigues, R. R., Loyola, R. & Cianciaruso, M. V. Functional traits and ecosystem services in ecological restoration. Restor. Ecol. 28, 1372–1383 (2020).Article 

    Google Scholar 
    Lavorel, S. Plant functional effects on ecosystem services. (2013).Defra. (ed Food and Rural Affairs Department for Environment) (2019).Agency, J. M. Amedas, https://tenki.jp/past/2019/09/amedas/ (2019).Jacquemart, A.-L., Gillet, C. & Cawoy, V. Floral visitors and the importance of honey bee on buckwheat (Fagopyrum esculentum Moench) in central Belgium. J. Hortic. Sci. Biotechnol. 82, 104–108 (2007).Article 

    Google Scholar 
    Taki, H. et al. Effects of landscape metrics on Apis and non-Apis pollinators and seed set in common buckwheat. Basic Appl. Ecol. 11, 594–602 (2010).Article 

    Google Scholar 
    Dray, S., Legendre, P. & Peres-Neto, P. R. Spatial modelling: A comprehensive framework for principal coordinate analysis of neighbour matrices (PCNM). Ecol. Model. 196, 483–493 (2006).Article 

    Google Scholar 
    Legendre, P. & Legendre, L. Numerical Ecology (Elsevier, 2012).MATH 

    Google Scholar 
    Dray S, et al. adespatial: Multivariate Multiscale Spatial Analysis. R package version 0.3-20, https://CRAN.R-project.org/package=adespatial. (2022).Benjamin, F. E., Reilly, J. R. & Winfree, R. Pollinator body size mediates the scale at which land use drives crop pollination services. J. Appl. Ecol. 51, 440–449 (2014).Article 

    Google Scholar 
    Földesi, R. et al. Relationships between wild bees, hoverflies and pollination success in apple orchards with different landscape contexts. Agric. For. Entomol. 18, 68–75 (2016).Article 

    Google Scholar 
    Oksanen J, et al. vegan: Community Ecology Package. R package version 2.6-4. https://CRAN.R-project.org/package=vegan. (2022)Bürkner, P.-C. brms: An R package for Bayesian multilevel models using Stan. J. Stat. Softw. 80, 1–28 (2017).Article 

    Google Scholar 
    Gelman, A., Carlin, J. B., Stern, H. S. & Rubin, D. B. Bayesian Data Analysis (Chapman and Hall/CRC, 1995).Book 
    MATH 

    Google Scholar 
    Team, R. C. R: A Language and Environment for Statistical Computing (2019).Sasaki, H. & Wagatsuma, T. Bumblebees (Apidae: Hymenoptera) are the main pollinators of common buckwheat, Fogopyrum esculentum, in Hokkaido, Japan. Appl. Entomol. Zool. 42, 659–661 (2007).Article 

    Google Scholar 
    Nagano, Y., Miyashita, T., Taki, H. & Yokoi, T. Diversity of co-flowering plants at field margins potentially sustains an abundance of insects visiting buckwheat, Fagopyrum esculentum, in an agricultural landscape. Ecol. Res. 36, 882–891 (2021).Article 

    Google Scholar 
    Samra, S., Samocha, Y., Eisikowitch, D. & Vaknin, Y. Can ants equal honeybees as effective pollinators of the energy crop Jatropha curcas L. under Mediterranean conditions?. Gcb Bioenergy 6, 756–767 (2014).Article 

    Google Scholar 
    Sugiura, N., Miyazaki, S. & Nagaishi, S. A supplementary contribution of ants in the pollination of an orchid, Epipactis thunbergii, usually pollinated by hover flies. Plant Syst. Evol. 258, 17–26 (2006).Article 

    Google Scholar 
    Natsume, K., Hayashi, S. & Miyashita, T. Ants are effective pollinators of common buckwheat Fagopyrum esculentum. Agric. For. Entomol. 24, 446–452 (2022).Article 

    Google Scholar 
    Carvalheiro, L. G., Seymour, C. L., Nicolson, S. W. & Veldtman, R. Creating patches of native flowers facilitates crop pollination in large agricultural fields: Mango as a case study. J. Appl. Ecol. 49, 1373–1383 (2012).Article 

    Google Scholar 
    Michiyama, H., Arikuni, M. & Hirano, T. Effect of air temperature on the growth, flowering and ripening in common buckwheat. In The Procceeding of the 8th ISB (2001)Isbell, F. et al. High plant diversity is needed to maintain ecosystem services. Nature 477, 199-U196. https://doi.org/10.1038/nature10282 (2011).Article 
    ADS 
    CAS 

    Google Scholar 
    McCain, C. M. & Colwell, R. K. Assessing the threat to montane biodiversity from discordant shifts in temperature and precipitation in a changing climate. Ecol. Lett. 14, 1236–1245 (2011).Article 

    Google Scholar 
    Choi, S.-W. Effects of weather factors on the abundance and diversity of moths in a temperate deciduous mixed forest of Korea. Zool. Sci. 25, 53–58 (2008).Article 

    Google Scholar 
    Feldmeier, S. et al. Climate versus weather extremes: Temporal predictor resolution matters for future rather than current regional species distribution models. Divers. Distrib. 24, 1047–1060 (2018).Article 

    Google Scholar  More

  • in

    Temperature, species identity and morphological traits predict carbonate excretion and mineralogy in tropical reef fishes

    Animal collection and holding for this project was conducted under Marine Research Permit RE-19–28 issued by the Ministry of Natural Resources, Environment, and Tourism of the Republic of Palau (10.03.2019), Marine Research/Collection Permit and Agreement 62 issued by the Koror State Government (08.10.2019), Queensland Government GBRMPA Marine Parks Permit G14/36689.1, Queensland Government DNPRSR Marine Parks Permits QS2014/MAN247 and QS2014/MAN247a, Queensland Government General Fisheries Permit 168991, Queensland Government DAFF Animal Ethics approval CA2013/11/733, approval by The Bahamas Department of Marine Resources, approval by the Animal Care Officer of both the University of Bremen and the Leibniz Centre for Tropical Marine Research (ZMT), and in accordance with UK and Germany animal care guidelines.Sample collectionWe collected fish carbonate samples at four study locations across three tropical and subtropical regions: Eleuthera (24°50’N, 76°20’W), The Bahamas, between 2009 and 201127,37; Heron Reef (23°27’S, 151°55’E) and Moreton Bay (27°29’S, 153°24’E) in Queensland, Australia, in 2014 and 201528; and Koror (7°20’N, 134°28’E), Palau, during November and December 2019. These are located within four distinct marine biogeographic provinces and three realms (Tropical Atlantic, Central Indo-Pacific, and Temperate Australasia)43. At each location fish were collected using barrier nets, dip nets, clove oil or hook and line, and immediately transferred to aquaria facilities at the Cape Eleuthera Institute, Heron Island and Moreton Bay Research Stations, and the Palau International Coral Reef Center. Fish were held in a range of tanks (60, 400, or 1400 L in the Bahamas, 10, 60, 100, 120, or 400 L in Heron Island and Moreton Bay, and 8, 80, 280, or 400 L in Palau) of suitable dimensions for different fish sizes ( 5). Each sample was titrated with 0.01–0.5 N HCl (with continuous aeration with CO2-free air) until the end point (grey-lavender; pH~4.80) was reached and stable for at least 10 min. If the sample was over-titrated (pink), 0.01–0.1 N NaOH was added to titrate back to the end point and the amount of base used was subtracted from the amount of acid. Acid and base were added using an electronic multi-dispenser pipette (Eppendorf Repeater ®E3X, Eppendorf, Hamburg, Germany) with a precision of  ± 1 ({{{{{rm{mu }}}}}})L. Additionally, the pH of several samples was monitored using a pH microelectrode (Mettler Toledo InLab Micro) to ascertain the correctness of the colorimetric end point. The amount of carbonate in the sample was then calculated using Eq. (1). The method was validated using certified reference material (Alkalinity Standard Solution, 25,000 mg/L as CaCO3, HACH) and the accuracy in the determination of solid samples was verified using certified CaCO3 powder (Suprapur, ≥ 99.95% purity, Merck) samples (60–500 ({{{{{rm{mu }}}}}})g) and resulted in 96.53 ± 1.94% accuracy (mean ± SE; n = 8).To compare values obtained with the two titration methods we further analysed 12 samples collected at Lizard Island, Australia, in February 2016. Samples were collected at 24 h intervals from one individual of Lethrinus atkinsoni (f. Lethrinidae, body mass: 245 g), a group of five Lutjanus fulvus (f. Lutjanidae, mean body mass: 21 g), and an individual of Cephalopholis cyanostigma (f. Serranidae, body mass: 295 g), following the procedures described above. During sample collection water temperature ranged from 29.1 °C during the night to 32.6 °C during the day, with an average of ~31 °C, mean salinity was 35.4, and pHNBS ranged from 8.13 to 8.21. To compare the amount of carbonate measured by the two methods we added carbonate samples to 20 ml ultrapure water and disaggregated crystals via sonication. We then used a Metrohm Titrando autotitrator and Metrohm Aquatrode pH electrode to measure initial pH of the suspension of carbonates, then titrated each sample of carbonate in two stages. Firstly, they were titrated down to pH 4.80 using 0.1 M HCl, adding 20 µl increments of acid until this was sufficient to keep pH below 4.80 for 10 min whilst bubbling with CO2-free air. This first stage was comparable to the single end point titration used for samples collected in Palau. Secondly, whilst continuing to bubble with CO2-free air, further acid was added to the sample until it reached pH 3.89 and was stable for 1 min. Then 0.1 M NaOH was added to the samples to return them to the initial pH. For all samples the first end point titration (to pH 4.80) yielded slightly higher values for carbonate content than the second double titration. The ratio between the two methods (single end point/double titration) was 1.08 ± 0.01 (mean ± SE; range: 1.04–1.14; Supplementary Table 2). As we found a small but consistent difference between the two methods, all following analyses were initially performed on the actual data obtained with the double titration for samples from Australia and The Bahamas, and the single end point titration for samples from Palau. Then, to assess the robustness of the results, we repeated the analyses after applying a correction factor of 1.08 to the excretion rates of Palauan fishes (that used the single end point titration method). All results were consistent and robust to the measured difference between the titration methods (Supplementary Figs. 8, 9).Finally, measurements of multiple samples from each individual collected over periods of 18–169 h (median: 64 h) were combined to produce an average individual excretion rate in ({{{{{rm{mu }}}}}})mol h−1. For fish held in groups, carbonate excretion rates per individual (of average biomass) were obtained by averaging the total excretion rate of the group across the sampling period and dividing it by the number of individuals in the tank. Excretion rates obtained from fish groups thus evened the intraspecific variability within tanks, and are therefore more robust than those directly obtained from fish held individually. This aspect was considered in our models by fitting weighted regressions (see the “Statistical modelling” section). In total, we measured the carbonate excretion rates of 382 individual fishes arranged in 192 groups (i.e., independent observations), representing 85 species from 35 families across three tropical regions (180 individuals from 29 species in Australia, 90 individuals from 10 species in the Bahamas, and 112 individuals from 46 species in Palau; Supplementary Table 1).We assume that during the sampling of carbonates fishes were close to their resting metabolic rate and that their carbonate excretion rates are representative of fish at rest. Although the ratio of tank volume to fish volume in our study (median ~660; inter-quartile range ~180–1700) typically greatly exceeds the guideline ideal range for measuring resting metabolic rate (20–50)85, fishes were fasted prior to and throughout sampling, and in most instances their movement was somewhat constrained by tank volume. Fasting reduces metabolic rate in all animals, including fish, as they do not undergo energy-intensive digestive processes and use energy reserves to support vital processes, triggering metabolic changes in many tissues and reducing activity levels86,87. Additionally, other than the carbonate syphoning ( More