Philippa Kaur

Breed, M.D., Cook, C. & Krasnec, M.O. Cleptobiosis in social insects. Psyche 484765 (2012).Sakagami, S., Roubik, D. & Zucchi, R. Ethology of the robber stingless bee, Lestrimelitta limao (Hymenoptera: Apidae). Sociobiology 21, 237–277 (1993).
Google Scholar 
Rasmussen, C. & Cameron, S. A. Global stingless bee phylogeny supports ancient divergence, vicariance, and long distance dispersal. Biol. J. Lin. Soc. 99, 206–232 (2010).
Google Scholar 
Roubik, D. W. Ecology and Natural History of Tropical Bees (Cambridge University Press, 1989).
Google Scholar 
Camargo, J. M. F. & Pedro, S. R. M. Meliponini Lepeletier, 1836. in Catalogue of the Bees (Hymenoptera, Apoidea) in the Neotropical Region (ed Moure, J. S.). 272–578. (Sociedade Brasileira de Entomologia, 2007).Nogueira-Neto. P. Behavior problems related to the pillages made by some parasitic stingless bees (Meliponinae, Apidae). in Development and Evolution of Behavior: Essays in Memory of T.C. Schneirla (ed. Aronson, L.R.). 416–434. (W. H. Freeman, 1970).Quezada-Euán, J. J. G. & González-Acereto, J. Notes on the nest habits and host range of cleptobiotic Lestrimelitta niitkib (Ayala 1999) (Hymenoptera: Meliponini) from the Yucatan Peninsula, Mexico. Acta Zool. Mexicana 86, 245–249 (2002).
Google Scholar 
Rech, A. R., Schwade, M. A. & Schwade, M. R. M. Abelhas-sem-ferrão amazônicas defendem meliponarios contra saques de outras abelhas. Acta Amazon. 43, 389–394 (2013).
Google Scholar 
Grüter, C., von Zuben, L. G., Segers, F. H. I. D. & Cunningham, J. P. Warfare in stingless bees. Insect. Soc. 63, 223–236 (2016).
Google Scholar 
Cini, A., Bruschini, C., Poggi, L. & Cervo, R. Fight or fool? Physical strength, instead of sensory deception, matters in host nest invasion by a wasp social parasite. Anim. Behav. 81, 1139–1145 (2011).
Google Scholar 
Quezada-Euán, J. J. G. et al. Does sensory deception matter in eusocial obligate food robber systems? A study of Lestrimelitta and stingless bee hosts. Anim. Behav. 85, 817–823 (2013).
Google Scholar 
van Zweden, J. S. & D’Ettorre, P. Nestmate recognition in social insects and the role of hydrocarbons. In Insect hydrocarbons: biology, biochemistry, and chemical ecology (eds Blomquist, G. J. & Bagnères, A. G.) 222–243 (Cambridge University Press, 2010).
Google Scholar 
Blomquist, G. J. & Bagnères, A. G. Insect Hydrocarbons: Biology, Biochemistry and Chemical Ecology (Cambridge University Press, 2010).
Google Scholar 
Nash, D. R. & Boomsma, J. J. Communication between hosts and social parasites. In Sociobiology of Communication: An Interdisciplinary Perspective (eds d’Etorre, P. & Hughes, D. P.) 55–79 (Oxford University Press, 2008).
Google Scholar 
Martin, S. J., Shemilt, S., da S Lima, C. B. & de Carvalho, C. A. L. Are isomeric alkenes used in species recognition among neo-tropical stingless bees (Melipona spp). J. Chem. Ecol. 43, 1066–1072 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
Chung, H. & Carroll, S. B. Wax, sex and the origin of species: Dual roles of insect cuticular hydrocarbons in adaptation and mating. BioEssays 37, 822–830 (2015).CAS 
PubMed 
PubMed Central 

Google Scholar 
Finck, J., Berdan, E. L., Mayer, F., Ronacher, B. & Geiselhardt, S. Divergence of cuticular hydrocarbons in two sympatric grasshopper species and the evolution of fatty acid synthases and elongases across insects. Nat. Sci. Rep. 6, 33695 (2016).ADS 
CAS 

Google Scholar 
Buellesback, J., Vetter, S. G. & Schmitt, T. Differences in the reliance on cuticular hydrocarbons as sexual signaling and species discrimination cues in parasitoid wasps. Front. Zool. 15, 22 (2018).
Google Scholar 
Medina-Medina, L.A. & Gonzalez-Acereto, J.A. La respuesta defensiva de Scaptotrigona pectoralis como un contundente escudo de protección contra las incursiones de Lestrimelitta niitkib dirigidas a otras especies de abejas sin aguijón. in VI Congreso Iberoamericano de Apicultura. 171–173. (1998).National Institute of Standards and Technology. Mass Spectral Library. (NIST/EPA/NIH, 2011).Tabachnick, B. G. & Fidell, L. S. Using Multivariate Statistics (Harper Collins College, 1996).
Google Scholar 
SAS Institute. SAS/STAT 9.2 User’s Guide. (SAS Institute Cary, 2008).Rasband, W.S. ImageJ. (U.S. National Institutes of Health, 1997–2012).Quezada-Euán, J.J.G., Paxton, R.J., Palmer, K.A., May-Itzá, W.D.J., Tay, W.T. & Oldroyd, B.P. Morphological and molecular characters reveal differentiation in a Neotropical social bee, Melipona beecheii (Apidae: Meliponini). Apidologie 38, 247–258 (2007).Rohlf, F. J. TPSDIG: Version 2.12. (New York State University, 2008).Klingenberg, C. P. MorphoJ: An integrated software package for geometric morphometrics. Mol. Ecol. Resour. 11, 353–357 (2011).PubMed 

Google Scholar 
Francoy, T.M., Grassi, M.L., Imperatriz-Fonseca, V.L., May-Itzá, W.D.J. & Quezada-Euán, J.J.G. Geometric morphometrics of the wing as a tool for assigning genetic lineages and geographic origin to Melipona beecheii (Hymenoptera: Meliponini). Apidologie 42, 499–507 (2011).Ratnasingham, S. & Hebert, P. D. N. A DNA-based registry for all animal species: the Barcode Index Number (BIN) system. PLoS ONE 8, e66213 (2013).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Hurtado-Burillo, M., Ruiz, C., May-Itzá, W.D.J., Quezada-Eúan, J.J.G., & De la Rúa, P. Barcoding stingless bees: Genetic diversity of the economically important genus Scaptotrigona in Mesoamerica. Apidologie 44, 1–10 (2013).Folmer, O., Black, M., Hoeh, W., Lutz, R. & Vrigenhoek, R. DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. Mol. Mar. Biol. Biotech. 3, 294–299 (1994).CAS 

Google Scholar 
Packer, L., Sheffield, C.S., Gibbs, J., de Silva, N., Best, L.R. et al. The campaign to barcode the bees of the world: progress, problems and prognosis. in Memorias VI Congreso Mesoamericano Sobre Abejas Nativas, Guatemala. 178–180. (2009).Tamura, K., Stecher, G., & Kumar, S. MEGA11: Molecular evolutionary genetics analysis version 11. Mol. Biol. Evolut. https://doi.org/10.1093/molbev/msab120. (2021)Oliveira, F.F.d. & Marchi, P. Três espécies novas de Lestrimelitta Friese (Hymenoptera, Apidae) da Costa Rica, Panamá e Guiana Francesa. Rev. Bras. Entomol. 49, 1–6 (2005).González, V. H. & Griswold, T. L. New species and previously unknown males of neotropical cleptobiotic stingless bees (Hymenoptera, Apidae, Lestrimelitta). Caldasia 34, 227–245 (2012).
Google Scholar 
Marchi, P. & Melo, G.A.R. Revisão taxonômica das espêcies brasileiras do gênero Lestrimelitta Friese (Hymenoptera, Apidae, Meliponina). Rev. Bras. Entomol. 50, 6–30 (2006).Gonzalez, V., Rasmussen, C. & Velasquez, A. Una especie nueva de Lestrimelitta y un cambio de nombre en Lasioglossum (Hymenoptera: Apidae, Halictidae). Rev. Colomb. Entomol. 36, 319–324 (2010).
Google Scholar 
Ratnasingham, S. & Hebert, P. D. N. BOLD: The barcode of life data system (https://www.barcodinglife.org). Mol. Ecol. Notes 7, 355–364 (2007).Ayala, R. Revisión de las abejas sin aguijón de México (Hymenoptera: Apidae: Meliponini). Folia Entomol. Mexicana 106, 1–123 (1999).
Google Scholar 
Ruano, F. & Tinaut, A. The assault process of the slave-making ant Rossomyrmex minuchae (Hymenoptera: Formicidae). Sociobiology 43, 201–209 (2004).
Google Scholar 
Errard, C. et al. Coevolution-driven cuticular hydrocarbon variation between the slave-making ant Rossomyrmex minuchae and its host Proformica longiseta (Hymenoptera: Formicidae). Chemoecology 16, 235–240 (2006).CAS 

Google Scholar 
Dettner, K. & Liepert, C. Chemical mimicry and camouflage. Annu. Rev. Entomol. 39, 129–154 (1994).CAS 

Google Scholar 
Lenoir, A., d’Ettorre, P. & Errard, C. Chemical ecology and social parasitism in ants. Annu. Rev. Entomol. 46, 573–599 (2001).CAS 
PubMed 

Google Scholar 
Von Beeren, C., Pohl, S. & Witte, V. On the use of adaptive resemblance terms in chemical ecology. Psyche 2012, 635761 (2012).Lambardi, D., Dani, F. R., Turillazzi, S. & Boomsma, J. J. Chemical mimicry in an incipient leaf-cutting ant social parasite. Behav. Ecol. Sociobiol. 61, 843–851 (2007).
Google Scholar 
Uboni, A., Bagnères, A. G., Christidès, J. P. & Lorenzi, M. C. Cleptoparasites, social parasites and a common host: Chemical insignificance for visiting host nests, chemical mimicry for living in. J. Insect Physiol. 58, 1259–1264 (2012).CAS 
PubMed 

Google Scholar 
Quezada-Euán, J. J. G. et al. Body size differs in workers produced across time and is associated with variation in the quantity and composition of larval food in Nannotrigona perilampoides (Hymenoptera, Meliponini). Insect. Soc. 58, 31–38 (2011).
Google Scholar 
Nunes, T. M., Mateus, S., Turatti, I. C., Morgan, E. & Zucchi, R. Nestmate recognition in the stingless bee Frieseomelitta varia (Hymenoptera, Apidae, Meliponini): Sources of chemical signals. Anim. Behav. 81, 463–467 (2011).
Google Scholar 
Gutiérrez, E., Ruiz, D., Solís, T., May-Itzá, W.d.J., Moo-Valle, H. & Quezada-Euán, J.J.G. Does larval food affect cuticular profiles and recognition in eusocial bees? A test on Scaptotrigona gynes (Hymenoptera: Meliponini). Behav. Ecol. Sociobiol. 70, 871–879 (2016).Jones, S. M. et al. The role of wax and resin in the nestmate recognition system of a stingless bee, Tetragonisca angustula. Behav. Ecol. Sociobiol. 66, 1–12 (2012).
Google Scholar 
Leonhardt, S.D. Chemical ecology of stingless bees. J. Chem. Ecol. 43, 385–402 (2021).Akino, T. Chemical strategies to deal with ants: a review of mimicry, camouflage, propaganda, and phytomimesis by ants (Hymenoptera: Formicidae) and other arthropods. Myrmecol. News 11, 173–181 (2008).
Google Scholar 
Lenoir, A., Hefetz, A., Simon, T. & Soroker, V. Comparative dynamics of gestalt odour formation in two ant species Camponotus fellah and Aphaenogaster senilis (Hymenoptera: Formicidae). Physiol. Entomol. 26, 275–283 (2001).
Google Scholar 
Von Beeren, C. et al. Chemical and behavioral integration of army ant-associated rove beetles—A comparison between specialists and generalists. Front. Zool. 15, 8 (2018).
Google Scholar 
Kather, R. & Martin, S. J. Cuticular hydrocarbon profiles as a taxonomic tool: Advantages, limitations and technical aspects. Physiol. Entomol. 37, 25–32 (2012).CAS 

Google Scholar 
Menzel, F., Blaimer, B. B. & Schmitt, T. How do cuticular hydrocarbons evolve? Physiological constraints and climatic and biotic selection pressures act on a complex functional trait. Proc. R. Soc. B-Biol. Sci. 284, 20161727 (2017).
Google Scholar 
Savolainen, R. & Vepsäläinen, K. Sympatric speciation through intraspecific social parasitism. Proc. Nat. Acad. Sci. 100, 7169–7174 (2003).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Hartke, J., Sprenger, P.P., Sahm, J, Winterberg, H., Orivel, J. et al. Cuticular hydrocarbons as potential mediators of cryptic species divergence in a mutualistic ant association. Ecol. Evolut. 9, 9160–9176 (2019).Doebeli, M. & Dieckmann, U. Evolutionary branching and sympatric speciation caused by different types of ecological interactions. Am. Nat. 156, S77–S101 (2000).PubMed 

Google Scholar 
Thibert-Plante, X. & Gavrilets, S. Evolution of mate choice and the so-called magic traits in ecological speciation. Ecol. Lett. 16, 1004–1013 (2013).PubMed 
PubMed Central 

Google Scholar 
Cabej, N. R. Epigenetic Principles of Evolution (Elsevier, 2012).
Google Scholar 
Quezada-Euán, J. J. G. Stingless Bees of Mexico: The Biology, Management and Conservation of an Ancient Heritage (Springer, 2018).
Google Scholar 
Von Zuben, L. G. et al. Interspecific chemical communication in raids of the robber bee Lestrimelitta limao. Insect. Soc. 63, 339–347 (2016).
Google Scholar  More

Ley, R. E. et al. Evolution of mammals and their gut microbes. Science 320, 1647–1651 (2008).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Thaiss, C. A., Zmora, N., Levy, M. & Elinav, E. The microbiome and innate immunity. Nature 535, 65–74 (2016).ADS 
CAS 
PubMed 

Google Scholar 
Ezenwa, V. O., Gerardo, N. M., Inouye, D. W., Medina, M. & Xavier, J. B. Microbiology. Animal behavior and the microbiome. Science 338, 198–199 (2012).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Sampson, T. R. & Mazmanian, S. K. Control of brain development, function, and behavior by the microbiome. Cell Host Microbe. 17, 565–576 (2015).CAS 
PubMed 
PubMed Central 

Google Scholar 
Voigt, R. M., Forsyth, C. B., Green, S. J., Engen, P. A. & Keshavarzian, A. Circadian rhythm and the gut microbiome. Int. Rev. Neurobiol. 131, 193–205 (2016).CAS 
PubMed 

Google Scholar 
Backhed, F. Programming of host metabolism by the gut microbiota. Endocr. Abstr. https://doi.org/10.1530/endoabs.32.s20.2 (2013).Article 

Google Scholar 
Mallott, E. K., Borries, C., Koenig, A., Amato, K. R. & Lu, A. Reproductive hormones mediate changes in the gut microbiome during pregnancy and lactation in Phayre’s leaf monkeys. Sci. Rep. 10, 9961 (2020).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Miller, E. A., Livermore, J. A., Alberts, S. C., Tung, J. & Archie, E. A. Ovarian cycling and reproductive state shape the vaginal microbiota in wild baboons. Microbiome. 5, 8 (2017).PubMed 
PubMed Central 

Google Scholar 
Gomez-Arango, L. F. et al. Connections between the gut microbiome and metabolic hormones in early pregnancy in overweight and obese women. Diabetes 65, 2214–2223 (2016).CAS 
PubMed 

Google Scholar 
Shin, J.-H. et al. Serum level of sex steroid hormone is associated with diversity and profiles of human gut microbiome. Res. Microbiol. 170, 192–201 (2019).CAS 
PubMed 

Google Scholar 
Burokas, A., Moloney, R. D., Dinan, T. G. & Cryan, J. F. Microbiota regulation of the mammalian gut–brain axis. Adv. Appl. Microbiol. 91, 1–62. (2015).Sudo, N. The hypothalamic–pituitary–adrenal axis and gut microbiota. Gut–Brain Axis. https://doi.org/10.1016/b978-0-12-802304-4.00013-x (2016).Article 

Google Scholar 
Sapolsky, R. M., Romero, L. M. & Munck, A. U. How do glucocorticoids influence stress responses? Integrating permissive, suppressive, stimulatory, and preparative actions. Endocr. Rev. 21, 55–89 (2000).CAS 
PubMed 

Google Scholar 
Hau, M., Casagrande, S., Ouyang, J. Q. & Baugh, A. T. Glucocorticoid-mediated phenotypes in vertebrates: Multilevel variation and evolution. Adv. Stud. Behav. 48, 41–115 (2016).
Google Scholar 
Sprague, R. S. & Breuner, C. W. Timing of fledging is influenced by glucocorticoid physiology in Laysan Albatross chicks. Horm. Behav. 58, 297–305 (2010).CAS 
PubMed 

Google Scholar 
Fletcher, Q. E., Dantzer, B. & Boonstra, R. The impact of reproduction on the stress axis of free-living male northern red backed voles (Myodes rutilus). Gen. Comp. Endocrinol. 224, 136–147 (2015).CAS 
PubMed 

Google Scholar 
Romero, L. M. & Wikelski, M. Corticosterone levels predict survival probabilities of Galapagos marine iguanas during El Nino events. Proc. Natl. Acad. Sci. USA. 98, 7366–7370 (2001).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Chevalier, C. et al. Gut microbiota orchestrates energy homeostasis during cold. Cell 163, 1360–1374 (2015).CAS 
PubMed 

Google Scholar 
Amato, K. R. et al. Habitat degradation impacts black howler monkey (Alouatta pigra) gastrointestinal microbiomes. ISME J. 7, 1344–1353 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
Baniel, A. et al. Seasonal shifts in the gut microbiome indicate plastic responses to diet in wild geladas. Microbiome. 9, 26 (2021).PubMed 
PubMed Central 

Google Scholar 
Kohl, K. D., Amaya, J., Passement, C. A., Dearing, M. D. & McCue, M. D. Unique and shared responses of the gut microbiota to prolonged fasting: A comparative study across five classes of vertebrate hosts. FEMS Microbiol. Ecol. 90, 883–894 (2014).CAS 
PubMed 

Google Scholar 
Stecher, B. et al. Like will to like: Abundances of closely related species can predict susceptibility to intestinal colonization by pathogenic and commensal bacteria. PLoS Pathog. https://doi.org/10.1371/journal.ppat.1000711 (2010).Article 
PubMed 
PubMed Central 

Google Scholar 
Das, B. & Nair, G. B. Homeostasis and dysbiosis of the gut microbiome in health and disease. J. Biosci. 44(5), 1–8 (2019). https://www.ncbi.nlm.nih.gov/pubmed/31719226.CAS 

Google Scholar 
Noguera, J. C., Aira, M., Pérez-Losada, M., Domínguez, J. & Velando, A. Glucocorticoids modulate gastrointestinal microbiome in a wild bird. R. Soc. Open Sci. https://doi.org/10.1098/rsos.171743 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
UrenWebster, T. M., Rodriguez-Barreto, D., Consuegra, S. & GarciadeLeaniz, C. Cortisol-related signatures of stress in the fish microbiome. Front. Microbiol. 11, 1621 (2020).
Google Scholar 
Stothart, M. R., Palme, R. & Newman, A. E. M. It’s what’s on the inside that counts: stress physiology and the bacterial microbiome of a wild urban mammal. Proc. Biol. Sci. 286, 20192111 (2019).PubMed 
PubMed Central 

Google Scholar 
Vlčková, K. et al. Impact of stress on the gut microbiome of free-ranging western lowland gorillas. Microbiology 164, 40–44 (2018).PubMed 

Google Scholar 
Dantzer, B. et al. Density triggers maternal hormones that increase adaptive offspring growth in a wild mammal. Science 340, 1215–1217 (2013).ADS 
CAS 
PubMed 

Google Scholar 
Sarkar, A. et al. Microbial transmission in animal social networks and the social microbiome. Nat. Ecol. Evol. 4, 1020–1035 (2020).PubMed 

Google Scholar 
Kruuk, L. E. B., Merilä, J. & Sheldon, B. C. When environmental variation short-circuits natural selection. Trends Ecol. Evol. 18, 207–209 (2003).
Google Scholar 
Stinchcombe, J. R. et al. Testing for environmentally induced bias in phenotypic estimates of natural selection: Theory and practice. Am. Nat. 160, 511–523 (2002).PubMed 

Google Scholar 
Rausher, M. D. The measurement of selection on quantitative traits: Biases due to environmental covariances between traits and fitness. Evolution 46, 616–626 (1992).PubMed 

Google Scholar 
Lamontagne, J. M. & Boutin, S. Local-scale synchrony and variability in mast seed production patterns of Picea glauca. J. Ecol. https://doi.org/10.1111/j.1365-2745.2007.01266.x (2007).Article 

Google Scholar 
Fletcher, Q. E. et al. Reproductive timing and reliance on hoarded capital resources by lactating red squirrels. Oecologia https://doi.org/10.1007/s00442-013-2699-3 (2013).Article 
PubMed 

Google Scholar 
Fletcher, Q. E. et al. The functional response of a hoarding seed predator to mast seeding. Ecology 91, 2673–2683 (2010).PubMed 

Google Scholar 
Boutin, S. et al. Anticipatory reproduction and population growth in seed predators. Science 314, 1928–1930 (2006).ADS 
CAS 
PubMed 

Google Scholar 
Haines, J. A. et al. Sexually selected infanticide by male red squirrels in advance of a mast year. Ecology 99, 1242–1244 (2018).PubMed 

Google Scholar 
Dantzer, B., McAdam, A. G., Humphries, M. M., Lane, J. E. & Boutin, S. Decoupling the effects of food and density on life-history plasticity of wild animals using field experiments: Insights from the steward who sits in the shadow of its tail, the North American red squirrel. J. Anim. Ecol. 89, 2397–2414 (2020).PubMed 

Google Scholar 
Hestbeck, J. B. A Mathematical Model of Population Regulation in Cyclic Mammals. Population Biology 290–297 (Springer, 1983).
Google Scholar 
Dantzer, B., Boutin, S., Humphries, M. M. & McAdam, A. G. Behavioral responses of territorial red squirrels to natural and experimental variation in population density. Behav. Ecol. Sociobiol. 66, 865–878 (2012).
Google Scholar 
Siracusa, E. et al. Familiarity with neighbours affects intrusion risk in territorial red squirrels. Anim. Behav. 133, 11–20 (2017).
Google Scholar 
Guindre-Parker, S. et al. Individual variation in phenotypic plasticity of the stress axis. Biol. Lett. 15, 20190260 (2019).PubMed 
PubMed Central 

Google Scholar 
Laughlin, D. & Grace, J. Discoveries and novel insights in ecology using structural equation modeling. Ideas Ecol. Evol. https://doi.org/10.24908/iee.2019.12.5.c (2019).Article 

Google Scholar 
Pugesek, B. H., Tomer, A. & von Eye, A. Structural Equation Modeling: Applications in Ecological and Evolutionary Biology (Cambridge University Press, 2003).MATH 

Google Scholar 
Pearl, J. The causal foundations of structural equation modeling. (2012). https://doi.org/10.21236/ada557445Leftwich, P. T., Clarke, N. V. E., Hutchings, M. I. & Chapman, T. Gut microbiomes and reproductive isolation in Drosophila. Proc. Natl. Acad. Sci. USA. 114, 12767–12772 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
Markle, J. G. M. et al. Sex differences in the gut microbiome drive hormone-dependent regulation of autoimmunity. Science 339, 1084–1088 (2013).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Reveles, K. R., Patel, S., Forney, L. & Ross, C. N. Age-related changes in the marmoset gut microbiome. Am. J. Primatol. https://doi.org/10.1002/ajp.22960 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Dantzer, B. et al. Fecal cortisol metabolite levels in free-ranging North American red squirrels: Assay validation and the effects of reproductive condition. Gen. Comp. Endocrinol. 167, 279–286 (2010).CAS 
PubMed 

Google Scholar 
Fletcher, Q. E. et al. Seasonal stage differences overwhelm environmental and individual factors as determinants of energy expenditure in free-ranging red squirrels. Funct. Ecol. https://doi.org/10.1111/j.1365-2435.2012.01975.x (2012).Article 

Google Scholar 
Lane, J. E., Boutin, S., Gunn, M. R., Slate, J. & Coltman, D. W. Female multiple mating and paternity in free-ranging North American red squirrels. Anim. Behav. 75, 1927–1937 (2008).
Google Scholar 
Ren, T. et al. Seasonal, spatial, and maternal effects on gut microbiome in wild red squirrels. Microbiome. 5, 163 (2017).PubMed 
PubMed Central 

Google Scholar 
Backhans, A., Fellström, C. & Lambertz, S. T. Occurrence of pathogenic Yersinia enterocolitica and Yersinia pseudotuberculosis in small wild rodents. Epidemiol. Infect. 139, 1230–1238 (2011).CAS 
PubMed 

Google Scholar 
Bižanov, G. & Dobrokhotova, N. D. Experimental infection of ground squirrels (Citellus pygmaeus Pallas) with Yersinia pestis during hibernation. J. Infect. 54, 198–203 (2007).PubMed 

Google Scholar 
Stothart, M. R. et al. Stress and the microbiome: Linking glucocorticoids to bacterial community dynamics in wild red squirrels. Biol. Lett. 12, 20150875 (2016).PubMed 
PubMed Central 

Google Scholar 
Costello, E. K., Stagaman, K., Dethlefsen, L., Bohannan, B. J. M. & Relman, D. A. The application of ecological theory toward an understanding of the human microbiome. Science 336, 1255–1262 (2012).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Rocca, J. D., Simonin, M., Bernhardt, E. S., Washburne, A. D. & Wright, J. P. Rare microbial taxa emerge when communities collide: Freshwater and marine microbiome responses to experimental mixing. Ecology https://doi.org/10.1002/ecy.2956 (2020).Article 
PubMed 

Google Scholar 
Shade, A. et al. Conditionally rare taxa disproportionately contribute to temporal changes in microbial diversity. MBio https://doi.org/10.1128/mbio.01371-14 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
Dinan, T. G. & Cryan, J. F. The microbiome–gut–brain axis in health and disease. Gastroenterol. Clin. N. Am. 46, 77–89 (2017).
Google Scholar 
Claus, S. P. et al. Colonization-induced host–gut microbial metabolic interaction. MBio 2, e00271-e310 (2011).PubMed 
PubMed Central 

Google Scholar 
Bangsgaard Bendtsen, K. M. et al. Gut microbiota composition is correlated to grid floor induced stress and behavior in the BALB/c mouse. PLoS ONE 7, e46231 (2012).ADS 
PubMed 
PubMed Central 

Google Scholar 
Amato, K. R. et al. The gut microbiota appears to compensate for seasonal diet variation in the wild black howler monkey (Alouatta pigra). Microb. Ecol. 69, 434–443 (2015).CAS 
PubMed 

Google Scholar 
McLaren, M. R. & Callahan, B. J. Pathogen resistance may be the principal evolutionary advantage provided by the microbiome. Philos. Trans. R Soc. Lond. B Biol. Sci. 375, 20190592 (2020).PubMed 
PubMed Central 

Google Scholar 
Donohoe, D. R. et al. The microbiome and butyrate regulate energy metabolism and autophagy in the mammalian colon. Cell Metab. 13, 517–526 (2011).CAS 
PubMed 
PubMed Central 

Google Scholar 
Rivera-Chávez, F. et al. Depletion of butyrate-producing clostridia from the gut microbiota drives an aerobic luminal expansion of salmonella. Cell Host Microbe. 19, 443–454 (2016).PubMed 
PubMed Central 

Google Scholar 
Meerburg, B. G. & Kijlstra, A. Role of rodents in transmission of Salmonella and Campylobacter. J. Sci. Food Agric. https://doi.org/10.1002/jsfa.3004 (2007).Article 

Google Scholar 
Jalal, M. S. et al. Antibiotic resistant zoonotic bacteria in Irrawaddy squirrel (Callosciurus pygerythrus). Vet. Med. Sci. 5, 260–268 (2019).CAS 
PubMed 

Google Scholar 
Petrosus, E., Silva, E. B., Lay, D. Jr. & Eicher, S. D. Effects of orally administered cortisol and norepinephrine on weanling piglet gut microbial populations and Salmonella passage. J. Anim. Sci. 96, 4543–4551 (2018).PubMed 
PubMed Central 

Google Scholar 
Lefcheck, J. S. piecewiseSEM: Piecewise structural equation modelling in r for ecology, evolution, and systematics. Methods Ecol. Evol. https://doi.org/10.1111/2041-210X.12512 (2016).Article 

Google Scholar 
Raulo, A. et al. Social networks strongly predict the gut microbiota of wild mice. ISME J. https://doi.org/10.1038/s41396-021-00949-3 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Phillips, C. D. et al. Microbiome structural and functional interactions across host dietary niche space. Integr. Comp. Biol. 57, 743–755 (2017).CAS 
PubMed 

Google Scholar 
Galley, J. D. et al. Exposure to a social stressor disrupts the community structure of the colonic mucosa-associated microbiota. BMC Microbiol. 14, 189 (2014).PubMed 
PubMed Central 

Google Scholar 
Wu, C.-S. et al. Age-dependent remodeling of gut microbiome and host serum metabolome in mice. Aging 13, 6330–6345 (2021).CAS 
PubMed 
PubMed Central 

Google Scholar 
Altmann, J., Gesquiere, L., Galbany, J., Onyango, P. O. & Alberts, S. C. Life history context of reproductive aging in a wild primate model. Ann. NY Acad. Sci. https://doi.org/10.1111/j.1749-6632.2010.05531.x (2010).Article 
PubMed 

Google Scholar 
Sylvia, K. E., Jewell, C. P., Rendon, N. M., St John, E. A. & Demas, G. E. Sex-specific modulation of the gut microbiome and behavior in Siberian hamsters. Brain Behav. Immun. 60, 51–62 (2017).PubMed 

Google Scholar 
Grieneisen, L. E., Livermore, J., Alberts, S., Tung, J. & Archie, E. A. Group living and male dispersal predict the core gut microbiome in wild baboons. Integr. Comp. Biol. 57, 770–785 (2017).PubMed 
PubMed Central 

Google Scholar 
Peckett, A. J., Wright, D. C. & Riddell, M. C. The effects of glucocorticoids on adipose tissue lipid metabolism. Metabolism 60, 1500–1510 (2011).CAS 
PubMed 

Google Scholar 
Wu, T. et al. Chronic glucocorticoid treatment induced circadian clock disorder leads to lipid metabolism and gut microbiota alterations in rats. Life Sci. 192, 173–182 (2018).CAS 
PubMed 

Google Scholar 
Deaver, J. A., Eum, S. Y. & Toborek, M. Circadian disruption changes gut microbiome taxa and functional gene composition. Front. Microbiol. 9, 737 (2018).PubMed 
PubMed Central 

Google Scholar 
Schroeder, B. O. Fight them or feed them: How the intestinal mucus layer manages the gut microbiota. Gastroenterol. Rep. 7, 3–12 (2019).
Google Scholar 
Huang, E. Y. et al. Using corticosteroids to reshape the gut microbiome: Implications for inflammatory bowel diseases. Inflamm. Bowel Dis. 21, 963–972 (2015).PubMed 

Google Scholar 
Carabotti, M., Scirocco, A., Maselli, M. A. & Severi, C. The gut–brain axis: Interactions between enteric microbiota, central and enteric nervous systems. Ann. Gastroenterol. Hepatol. 28, 203–209 (2015).
Google Scholar 
de Weerth, C. Do bacteria shape our development? Crosstalk between intestinal microbiota and HPA axis. Neurosci. Biobehav. Rev. 83, 458–471 (2017).PubMed 

Google Scholar 
Luo, Y. et al. Gut microbiota regulates mouse behaviors through glucocorticoid receptor pathway genes in the hippocampus. Transl. Psychiatry. 8, 187 (2018).PubMed 
PubMed Central 

Google Scholar 
Cryan, J. F. et al. The microbiota–gut–brain axis. Physiol. Rev. 99, 1877–2013 (2019).CAS 
PubMed 

Google Scholar 
McAdam, A. G., Boutin, S., Sykes, A. K. & Humphries, M. M. Life histories of female red squirrels and their contributions to population growth and lifetime fitness. Ecoscience 14, 362–369 (2007).
Google Scholar 
Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods. 7, 335–336 (2010).CAS 
PubMed 
PubMed Central 

Google Scholar 
Edgar, R. C., Haas, B. J., Clemente, J. C., Quince, C. & Knight, R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194–2200 (2011).CAS 
PubMed 
PubMed Central 

Google Scholar 
Edgar, R. C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26, 2460–2461 (2010).CAS 

Google Scholar 
Sheriff, M. J., Dantzer, B., Delehanty, B., Palme, R. & Boonstra, R. Measuring stress in wildlife: Techniques for quantifying glucocorticoids. Oecologia 166, 869–887 (2011).ADS 
PubMed 

Google Scholar 
Touma, C., Sachser, N., Möstl, E. & Palme, R. Effects of sex and time of day on metabolism and excretion of corticosterone in urine and feces of mice. Gen. Comp. Endocrinol. 130, 267–278 (2003).CAS 
PubMed 
PubMed Central 

Google Scholar 
Van Kesteren, F. et al. Experimental increases in glucocorticoids alter function of the HPA axis in wild red squirrels without negatively impacting survival and reproduction. Physiol. Biochem. Zool. 92, 445–458 (2019).PubMed 

Google Scholar 
Paradis, E., Claude, J. & Strimmer, K. APE: Analyses of phylogenetics and evolution in R language. Bioinformatics 20, 289–290 (2004).CAS 
PubMed 
PubMed Central 

Google Scholar 
McMurdie, P. J. & Holmes, S. Package, “phyloseq”. Gan. 2, 7 (2013).
Google Scholar 
Kembel, S. W. et al. Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26, 1463–1464 (2010).CAS 

Google Scholar 
Zhang, X. & Yi, N. NBZIMM: Negative binomial and zero-inflated mixed models, with application to microbiome/metagenomics data analysis. BMC Bioinform. 21, 488 (2020).CAS 

Google Scholar 
Jones, S. E. & Lennon, J. T. Dormancy contributes to the maintenance of microbial diversity. Proc. Natl. Acad. Sci. USA. 107, 5881–5886 (2010).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar  More

Mogollón JM, Bouwman AF, Beusen AH, Lassaletta L, van Grinsven HJ, Westhoek H. More efficient phosphorus use can avoid cropland expansion. Nat Food. 2021;2:509–18.Article 

Google Scholar 
Goldhammer T, Brüchert V, Ferdelman TG, Zabel M. Microbial sequestration of phosphorus in anoxic upwelling sediments. Nat Geosci. 2010;3:557–61.CAS 
Article 

Google Scholar 
Oliverio AM, Bissett A, McGuire K, Saltonstall K, Turner BL, Fierer N. The role of phosphorus limitation in shaping soil bacterial communities and their metabolic capabilities. mBio. 2020;11:e01718–20.CAS 
Article 

Google Scholar 
Wu X, Rensing C, Han D, Xiao KQ, Dai Y, Tang Z, et al. Genome-resolved metagenomics reveals distinct phosphorus acquisition strategies between soil microbiomes. mSystems. 2022;7:e01107–21.PubMed Central 

Google Scholar 
Long XE, Yao H, Huang Y, Wei W, Zhu YG. Phosphate levels influence the utilisation of rice rhizodeposition carbon and the phosphate-solubilizing microbial community in a paddy soil. Soil Bio Biochem. 2018;118:103–14.CAS 
Article 

Google Scholar 
Dai Z, Liu G, Chen H, Chen C, Wang J, Ai S, et al. Long-term nutrient inputs shift soil microbial functional profiles of phosphorus cycling in diverse agroecosystems. ISME J. 2020;14:757–70.CAS 
Article 

Google Scholar 
Liang J, Liu J, Jia P, Yang T, Zeng Q, Zhang S, et al. Novel phosphate-solubilizing bacteria enhance soil phosphorus cycling following ecological restoration of land degraded by mining. ISME J. 2020;14:1600–13.CAS 
Article 

Google Scholar 
Willsky GR, Bennett RL, Malamy MH. Inorganic phosphate transport in Escherichia coli: involvement of two genes which play a role in alkaline phosphatase regulation. J Bacteriol. 1973;113:529–39.CAS 
Article 

Google Scholar 
Wanner BL. Gene regulation by phosphate in enteric bacteria. J Cell Biochem. 1993;51:47–54.CAS 
Article 

Google Scholar 
Li J, Lu J, Wang H, Fang Z, Wang X, Feng S, et al. A comprehensive synthesis unveils the mysteries of phosphate‐solubilizing microbes. Biol Rev. 2021;96:2771–93.Article 

Google Scholar 
Hessen DO, Jeyasingh PD, Neiman M, Weider LJ. Genome streamlining and the elemental costs of growth. Trends Ecol Evol. 2010;25:75–80.Article 

Google Scholar 
Li J, Mau RL, Dijkstra P, Koch BJ, Schwartz E, Liu XA, et al. Predictive genomic traits for bacterial growth in culture versus actual growth in soil. ISME J. 2019;13:2162–72.Article 

Google Scholar 
Giovannoni SJ, Cameron Thrash J, Temperton B. Implications of streamlining theory for microbial ecology. ISME J. 2014;8:1553–65.Article 

Google Scholar 
Ye L, Mei R, Liu WT, Ren H, Zhang XX. Machine learning-aided analyses of thousands of draft genomes reveal specific features of activated sludge processes. Microbiome. 2020;8:1–13.Article 

Google Scholar 
Farhat MB, Boukhris I, Chouayekh H. Mineral phosphate solubilization by Streptomyces sp. CTM396 involves the excretion of gluconic acid and is stimulated by humic acids. FEMS Microbiol Lett. 2015;362:1–8.Article 

Google Scholar 
Bücking H, Shachar-Hill Y. Phosphate uptake, transport and transfer by the arbuscular mycorrhizal fungus Glomus intraradices is stimulated by increased carbohydrate availability. New Phytol. 2005;165:899–912.Article 

Google Scholar 
Zhang L, Xu M, Liu Y, Zhang F, Hodge A, Feng G. Carbon and phosphorus exchange may enable cooperation between an arbuscular mycorrhizal fungus and a phosphate‐solubilizing bacterium. New Phytol. 2016;210:1022–32.CAS 
Article 

Google Scholar 
Spohn M, Kuzyakov Y. Phosphorus mineralization can be driven by microbial need for carbon. Soil Biol Biochem. 2013;61:69–75.CAS 
Article 

Google Scholar 
Huang Y, Dai Z, Lin J, Li D, Ye H, Dahlgren RA, et al. Labile carbon facilitated phosphorus solubilization as regulated by bacterial and fungal communities in Zea mays. Soil Biol Biochem. 2021;163:108465.CAS 
Article 

Google Scholar 
Yao Q, Li Z, Song Y, Wright SJ, Guo X, Tringe SG, et al. Community proteogenomics reveals the systemic impact of phosphorus availability on microbial functions in tropical soil. Nat Ecol Evol. 2018;2:499–509.Article 

Google Scholar  More

Geoffrey, E. Sur les Phyllostomes et les Megadermes, deux Genres de la famille des Chauve-souris. in Annales du Museum d’histoire (ed. Dufour, G.) vol. 15, 181 (d’Ocagne, 1810).Wilson, D. E. & Mittermeier, R. A. Bats. in Handbook of the Mammals of the World. Vol. 9. (eds. Wilson, D. E. & Mittermeier, R. A.) 1008 (Springer International Publishing, 2019).Hilaire, É. G. S., Pupuya, I. D. E., Del, R. & Higgins, L. B. O. Ampliación del rango de distribución sur de Desmodus rotundus. Boletín del Mus. Nac. Hist. Nat. 68, 5–12 (2019).
Google Scholar 
Kwon, M. & Gardner, A. L. Subfamily Desmodontinae. in Mammals of South America, Volume 1: Marsupials, Xenarthrans, Shrews and Bats (ed. Gardner, A. L.) 218–223 (The University of Chicago Press, 2008).Arellano-Sota, C. Vampire bat-transmitted rabies in cattle. Rev. Infect. Dis. 10, 707–709 (1988).
Google Scholar 
Fernandes, M. E. B., Da Costa, L. J. C., De Andrade, F. A. G. & Silva, L. P. Rabies in humans and non-human in the state of Pará, Brazilian Amazon. Brazilian J. Infect. Dis. 17, 251–253 (2013).
Google Scholar 
Andrade, F. A. G., Franca, E. S., Souza, V. P., Barreto, M. S. O. D. & Fernandes, M. E. B. Spatial and temporal analysis of attacks by common vampire bats (Desmodus rotundus) on humans in the rural Brazilian Amazon basin. Acta Chiropterologica 17, 393–400 (2015).
Google Scholar 
Greenhall, A. M., Joermann, G. & Schmidt, U. Desmodus rotundus. Mamm. Species 202, 1–6 (1983).
Google Scholar 
Herrera, L. G., Fleming, T. H. & Sternberg, L. S. Trophic relationships in a neotropical bat community: A preliminary study using carbon and nitrogen isotopic signatures. Trop. Ecol. 39, 23–29 (1998).
Google Scholar 
Dantas Torres, F., Valença, C. & De Andrade Filho, G. V. First record of Desmodus rotundus in urban area from the city of Olinda, Pernambuco, Northeastern Brazil: A case report. Rev. Inst. Med. Trop. Sao Paulo 47, 107–108 (2005).PubMed 

Google Scholar 
Flores-Crespo, R. & Arellano-Sota, C. Biology and control of the vampire bat. in The natural history of rabies (ed. Baer, G. M.) 461–476 (CRC Press Inc, 1991).Flores-Crespo, R. & Arellano-Sota, C. Biology and control of the vampire bat. Nat. Hist. Rabies, 2nd Ed. 10, 461–476 (2017).
Google Scholar 
Bolívar-Cimé, B., Flores-Peredo, R., García-Ortíz, S. A., Murrieta-Galindo, R. & Laborde, J. Influence of landscape structure on the abundance of Desmodus rotundus (Geoffroy 1810) in Northeastern Yucatan, Mexico. Ecosistemas y Recur. Agropecu. 6, 263 (2019).
Google Scholar 
Koopman, K. F. Systematics and distribution. in Natural History of Vampire Bats (eds. Greenhall, A. M. & Schmidt, U.) 4–28 (CRC Press, 1988).Dalquest, W. W. Natural history of the vampire bats of Eastern Mexico. Am. Midl. Nat. 53, 79–87 (1955).
Google Scholar 
Kalko, E. K. V. & Handley, C. O. Neotropical bats in the canopy: Diversity, community structure, and implications for conservation. Plant Ecol. 153, 319–333 (2001).
Google Scholar 
García-Morales, R., Badano, E. I. & Moreno, C. E. Response of neotropical bat assemblages to human land use. Conserv. Biol. 27, 1096–1106 (2013).PubMed 

Google Scholar 
Barquez, R.M., Perez, S., Miller, B. & Diaz, M. M. Desmodus rotundus. The IUCN Red List of Threatened Species 2015 e.T6510A21979045, https://doi.org/10.2305/IUCN.UK.2015-4.RLTS.T6510A21979045.en (2015).Becker, D. J. et al. Genetic diversity, infection prevalence, and possible transmission routes of Bartonella spp. in vampire bats. PLoS Negl. Trop. Dis. 12, e0006786 (2018).PubMed 
PubMed Central 

Google Scholar 
Brandão, P. E. et al. A coronavirus detected in the vampire bat Desmodus rotundus. Brazilian J. Infect. Dis. 12, 466–468 (2008).
Google Scholar 
Alves, R. S. et al. Detection of coronavirus in vampire bats (Desmodus rotundus) in southern Brazil. Transbound. Emerg. Dis. 00, 1–6 (2021).
Google Scholar 
Rocha, F. & Dias, R. A. The common vampire bat Desmodus rotundus (Chiroptera: Phyllostomidae) and the transmission of the rabies virus to livestock: A contact network approach and recommendations for surveillance and control. Prev. Vet. Med. 174, e104809 (2020).
Google Scholar 
Raoult, D. et al. Diagnosis of 22 new cases of Bartonella endocarditis. Ann. Intern. Med. 125, 646–652 (1996).CAS 
PubMed 

Google Scholar 
Raoult, D. et al. Outcome and treatment of Bartonella endocarditis. Arch. Int. Med. 163, 226–230 (2003).
Google Scholar 
Neely, B. A. et al. Surveying the vampire bat (Desmodus rotundus) serum proteome: A resource for identifying immunological proteins and detecting pathogens. J. Proteome Res. 20, 2547–2559 (2021).CAS 
PubMed 

Google Scholar 
Rupprecht, C. E., Hanlon, C. A. & Hemachudha, T. Rabies re-examined. Lancet Infect. Dis. 2, 327–343 (2002).PubMed 

Google Scholar 
World Health Organization. Rabies. WHO https://www.who.int/news-room/fact-sheets/detail/rabies (2020).Lee, D. N., Papeş, M. & Van Den Bussche, R. A. Present and potential future distribution of common vampire bats in the Americas and the associated risk to cattle. PLoS One 7, e42466 (2012).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Acha, P. N. & Malaga-Alba, A. Economic losses due to Desmodus rotundus. in Natural History of Vampire Bats (eds. Greenhall, A. M. & Schmidt, U.) 207–214 (CRC Press, 1968).Kotait, I. & Gonçalves, C. Manual Técnico MAPA – Controle da raiva dos herbívoros in Manual técnico dos herbívoros (Ministério da Agricultura, Pecuária e Abastecimento, 2009).Johnson, N., Aréchiga-Ceballos, N. & Aguilar-Setien, A. Vampire bat rabies: Ecology, epidemiology and control. Viruses 6, 1911–1928 (2014).PubMed 
PubMed Central 

Google Scholar 
Blackwood, J. C., Streicker, D. G., Altizer, S. & Rohani, P. Resolving the roles of immunity, pathogenesis, and immigration for rabies persistence in vampire bats. Proc. Natl. Acad. Sci. 110, 20837–20842 (2013).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Streicker, D. G. et al. Host-pathogen evolutionary signatures reveal dynamics and future invasions of vampire bat rabies. Proc. Natl. Acad. Sci. USA 113, 10926–10931 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
Zarza, H., Martínez-Meyer, E., Suzán, G. & Ceballos, G. Geographic distribution of Desmodus rotundus in Mexico under current and future climate change scenarios: Implications for bovine paralytic rabies infection. Vet. Mex. 4, 3–16 (2017).
Google Scholar 
Hayes, M. A. & Piaggio, A. J. Assessing the potential impacts of a changing climate on the distribution of a rabies virus vector. PLoS One 13, e0192887 (2018).PubMed 
PubMed Central 

Google Scholar 
Nunez, G. B., Becker, D. J., Lawrence, R. L. & Plowright, R. K. Synergistic effects of grassland fragmentation and temperature on bovine rabies emergence. EcoHealth 17, 203–216 (2020).PubMed Central 

Google Scholar 
da Rosa, E. S. T. et al. Bat-transmitted human rabies outbreaks, Brazilian Amazon. Emerg. Infect. Dis. 12, 1197–1202 (2006).PubMed 
PubMed Central 

Google Scholar 
Rocha, S. M., de Oliveira, S. V., Heinemann, M. B. & Gonçalves, V. S. P. Epidemiological profile of wild rabies in Brazil (2002–2012). Transbound. Emerg. Dis. 64, 624–633 (2017).CAS 
PubMed 

Google Scholar 
Schneider, M. C. et al. Rabies transmitted by vampire bats to humans: An emerging zoonotic disease in Latin America? Pan Am. J. Public Health. 25, 260–269 (2009).
Google Scholar 
VERA. Vigilancia epidemiológica de la rabia en las Américas. Organ. Panam. la Salud. 34, 14–42 (2020).
Google Scholar 
World Health Organization. WHO expert consultation on rabies, second report. WHO Tech. Rep. Ser. 982, 1–139 (2013).
Google Scholar 
Gilbert, A. T. et al. Evidence of rabies virus exposure among humans in the Peruvian Amazon. Am. J. Trop. Med. Hyg. 87, 206–215 (2012).
Google Scholar 
Fahl, W. O. et al. Desmodus rotundus and Artibeus spp. bats might present distinct rabies virus lineages. Brazilian J. Infect. Dis. 16, 545–551 (2012).
Google Scholar 
Berger, F. et al. Rabies risk: Difficulties encountered during management of grouped cases of bat bites in 2 isolated villages in French Guiana. PLoS Negl. Trop. Dis. 7, e2258 (2013).PubMed 
PubMed Central 

Google Scholar 
Linhart, S. B., Flores Crespo, R. & Mitchell, G. C. Control de murciélagos vampiros por medio de un anticoagulante. Bull Pan Am Health Organ. 73, 100–109 (1972).CAS 

Google Scholar 
Streicker, D. G. et al. Ecological and anthropogenic drivers of rabies exposure in vampire bats: Implications for transmission and control. Proc. R. Soc. B Biol. Sci. 279, 3384–3392 (2012).
Google Scholar 
Henry, M., Cosson, J. F. & Pons, J. M. Modelling multi-scale spatial variation in species richness from abundance data in a complex neotropical bat assemblage. Ecol. Modell. 221, 2018–2027 (2010).
Google Scholar 
Bárcenas-Reyes, I. et al. Comportamiento epidemiológico de la rabia paralítica bovina en la región central de México, 2001-2013. Pan Am. J. Public Health. 38, 396–402 (2015).
Google Scholar 
Benavides, J. A., Valderrama, W. & Streicker, D. G. Spatial expansions and travelling waves of rabies in vampire bats. Proc. R. Soc. B 283, e20160328 (2016).
Google Scholar 
Van de Vuurst, P. et al. Desmodus rotundus Occurrence Record Database. figshare https://doi.org/10.6084/m9.figshare.15025296.v6 (2021).Wieczorek, J. et al. Darwin core: An evolving community-developed biodiversity data standard. PLoS One 7, e29715 (2012).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Robertson, T. et al. The GBIF integrated publishing toolkit: Facilitating the efficient publishing of biodiversity data on the internet. PLoS One 9, e102623 (2014).ADS 
PubMed 
PubMed Central 

Google Scholar 
Marcial, L. H. & Hemminger, B. M. Scientific data repositories on the web: An initial survey. J. Am. Soc. Inf. Sci. Technol. 61, 2029–2048 (2010).
Google Scholar 
GBIF.org. GBIF Occurrence Download. Global Biodiversity Information Facility. GBIF https://doi.org/10.15468/dl.my64ap (2020).Grattarola, F. et al. Biodiversidata: An open-access biodiversity database for Uruguay. Biodivers. Data J. 7, e36226 (2019).PubMed 
PubMed Central 

Google Scholar 
CRIA. speciesLink Data Download. Centro de Referência em Informação Ambiental. https://specieslink.net/search/download/20210909104533-0016416 (2021).Cambon, J. Package ‘ tidygeocoder’. CRAN 2–13 (2021).Wickham, H., Francois, R., Henry, L. & Muller, K. Package ‘ dplyr’: A grammar of data manipulation. CRAN 3–88 (2020).R Core Team. R: A language and environment for statisitical computing. https://www.R-project.org/ (2019).Zizka, A. et al. Package ‘ CoordinateCleaner’. CRAN 13-152 (2019).Wickham, H. ggplot2: Elegant graphics for data analysis. (Springer-Verlag, 2016).ESRI Inc. ArcGIS Desktop Pro, version 2.4.3. https://www.esri.com/en-us/arcgis/products/arcgis-pro/overview (2019). More

Skarpe, C. Dynamics of savanna ecosystems. J. Veg. Sci. 3, 293–300 (1992).
Google Scholar 
Solbrig, O. T. The diversity of the savanna ecosystem. In Biodiversity and Savanna Ecosystem Processes: A Global Perspective Vol. 21 (eds Solbrig, O. T. et al.) 1–27 (Springer, Berlin, 1996).
Google Scholar 
Fynn, R. W. S., Augustine, D. J., Peel, M. J. S. & de Garine-Wichatitsky, M. Strategic management of livestock to improve biodiversity conservation in African savannahs: A conceptual basis for wildlife–livestock coexistence. J Appl Ecol 53, 388–397 (2016).
Google Scholar 
Turner, M. D. & Schlecht, E. Livestock mobility in sub-Saharan Africa: A critical review. Pastoralism 9, 13 (2019).
Google Scholar 
Moreno, G. et al. Exploring the causes of high biodiversity of Iberian dehesas: The importance of wood pastures and marginal habitats. Agrofor. Syst. 90, 87–105 (2015).
Google Scholar 
Spiegel, O. et al. Moving beyond curve fitting: Using complementary data to assess alternative explanations for long movements of three vulture species. Am. Nat. 185, E44–E54 (2015).
Google Scholar 
Houston, D. C. Food searching behaviour in griffon vultures. Afr. J. Ecol. 12, 63–77 (1974).
Google Scholar 
Fryxell, J. M. & Sinclair, A. R. E. Causes and Consequences of Migration by Large Herbivores. Trens Ecol. Evol. 3, 237–241 (1988).CAS 

Google Scholar 
Joly, K. et al. Longest terrestrial migrations and movements around the world. Sci. Rep. 9, 15333 (2019).ADS 
PubMed 
PubMed Central 

Google Scholar 
Naveh, Z. Mediterranean ecosystems and vegetation types in California and Israel. In Transdisciplinary Challenges in Landscape Ecology and Restoration Ecology. Landscape Series, vol 6. (Springer, Dordrecht, 1967), vol 48, pp. 445–459.Pereira, P. M. & Pires da Fonseca, M. Nature vs. nurture: The making of the montado ecosystem. Conserv. Ecol. 7, 7 (2003).
Google Scholar 
Blondel, J. The ‘design’ of Mediterranean landscapes: A millennial story of humans and ecological systems during the historic period. Hum. Ecol. 34, 713–729 (2006).
Google Scholar 
Díaz, M., Campos, P. & Pulido, F. J. The Spanish dehesas: A diversity of land use and wildlife. In Farming and birds in Europe: The Common Agricultural Policy and its implications for bird conservation (eds Pain, D. & Pienkowski, M.) 178–209 (Academic Press, London, 1997).
Google Scholar 
Campos, P. et al. Mediterranean Oak Woodland Working Landscapes: Dehesas of Spain and Ranchlands of California (Springer, 2013).
Google Scholar 
Plieninger, T. & Bieling, C. Resilience and the Cultural Landscape: Understanding and Managing Change in Human-Shaped Environments (Cambridge University Press, 2012).
Google Scholar 
Lomba, A. et al. Back to the future: Rethinking socioecological systems underlying high nature value farmlands. Front. Ecol. Environ. 18, 36–42 (2020).
Google Scholar 
Ogada, D. et al. Another continental vulture crisis: Africa’s vultures collapsing toward extinction. Conserv. Lett. 9, 89–97 (2016).ADS 

Google Scholar 
Buechely, E. & Şekercioğlu, Ç. H. The avian scavenger crisis: Looming extinctions, trophic cascades, and loss of critical ecosystem functions. Biol. Conserv. 198, 220–228 (2016).
Google Scholar 
Safford, R. et al. Vulture conservation: The case for urgent action. Bird Conserv. Int. 29, 1–9 (2019).
Google Scholar 
García-Alfonso, M., Donázar, J. A., Serrano, D. Individual and environmental drivers of resource use in endangered vulture: Integrating movement, spatial and social ecology. PhD Thesis. Universidad de Sevilla, Seville, Spain.Ogada, D. L., Keesing, F. & Virani, M. Z. Dropping dead: Causes and consequences of vulture population declines worldwide. Ann. NY Acad. Sci. 1249, 57–71 (2012).ADS 
PubMed 

Google Scholar 
Blanco, G., Cortés-Avizanda, A., Frías, Ó., Arrondo, E. & Donázar, J. A. Livestock farming practices modulate vulture diet-disease interactions. Glob. Ecol. 17, e00518 (2019).
Google Scholar 
Olea, P. P., Mateo-Tomas, P. & Sánchez Zapata, J. A. Carrion Ecology and Management (Springer Nature, 2019).
Google Scholar 
Montsarrat, S. et al. How predictability of feeding patches affects home range and foraging habitat selection in avian social scavengers?. PLoS ONE 8, e53077 (2013).ADS 

Google Scholar 
Arrondo, E. et al. Invisible barriers: Differential sanitary regulations constrain vulture movements across country borders. Biol. Conserv. 219, 46–52 (2018).
Google Scholar 
Houston, D. C. Breeding of the white-backed and Rüppell’s griffon vultures, Gyps africanus and G. rueppellii. Ibis 118, 14–40 (1976).
Google Scholar 
Houston, D. C. A change in the breeding season of Rüppell’s griffon vultures Gyps rueppellii in the Serengeti in response to changes in ungulate populations. Ibis 132, 36–41 (1990).
Google Scholar 
Kendall, C. J., Virani, M. Z., Hopcraft, J. G. C., Bildstein, K. L. & Rubenstein, D. I. African vultures don’t follow migratory herds: Scavenger habitat use is not mediated by prey abundance. PLoS ONE 9, e83470 (2014).ADS 
PubMed 
PubMed Central 

Google Scholar 
Carrete, M. & Donázar, J. A. Application of central-place foraging theory shows the importance of Mediterranean dehesas for the conservation of the cinereous vulture, Aegypius monachus. Biol. Conserv. 126, 582–590 (2005).
Google Scholar 
Martín-Díaz, P. et al. Rewilding processes shape the use of Mediterranean landscapes by an avian top scavenger. Sci. Rep. 10, 2853 (2020).ADS 
PubMed 
PubMed Central 

Google Scholar 
Botha, A. et al. Multi-species action plan to conserve African-Eurasian vultures (vulture MSAP). CMS Raptors MOU Technical Publication 5, 2–162 (2017).
Google Scholar 
Cortés-Avizanda, A. et al. Supplementary feeding and endangered avian scavengers: Benefits, caveats, and controversies. Front. Ecol. Environ. 14, 191–199 (2016).
Google Scholar 
Fluhr, J., Benhamou, S., Riotte-Lambert, L. & Duriez, O. Assessing the risk for an obligate scavenger to be dependent on predictable feeding sources. Biol. Conserv. 215, 92–98 (2017).
Google Scholar 
Schabo, D. G. et al. Long-term data indicates that supplementary food enhances the number of breeding pairs in a Cape Vulture Gyps coprotheres colony. Bird Conserv. Int. 27, 1–13 (2016).
Google Scholar 
Louzao, M. et al. Conserving pelagic habitats: Seascape modelling of an oceanic predator. J. Appl. Ecol. 48, 121–132 (2011).
Google Scholar 
Buechley, E. R. et al. Identifying critical migratory bottlenecks and high-use areas for an endangered migratory soaring bird across three continents. J. Avian Biol. 49, e01629 (2018).
Google Scholar 
Morales-Reyes, Z. et al. Supplanting ecosystem services provided by scavengers raises greenhouse gas emissions. Sci. Rep. 5, 7811 (2015).CAS 
PubMed 
PubMed Central 

Google Scholar 
Mateo-Tomás, P., Olea, P. P., Moleón, M., Selva, N. & Sánchez-Zapata, J. A. Both rare and common species support ecosystem services in scavenger communities. Glob. Ecol. 26, 1459–1470 (2017).
Google Scholar 
Aguilera-Alcalá, N., Morales-Reyes, Z., Martín-López, B., Moléon, M. & Sánchez-Zapata, J. A. Role of scavengers in providing non-material contributions to people. Ecol. Indic. 117, 106643 (2020).
Google Scholar 
Margalida, A. et al. Uneven large-scale movement patterns in wild and reintroduced pre-adult bearded vultures: Conservation implications. PLoS ONE 8, e65857 (2013).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Griesinger, J. Juvenile dispersion and migration among Griffon Vultures Gyps fulvus in Spain. Holartic Birds of Prey (1998).Plieninger, T. et al. Dehesas as high nature value farming systems: A social-ecological synthesis of drivers, pressures, state, impacts, and responses. Ecology 26, 23 (2021).
Google Scholar 
Virani, M. Z., Monadjem, A., Thomsett, S. & Kendall, C. Seasonal variation in breeding Rüppell’s Vultures Gyps rueppellii at Kwenia, southern Kenya and implications for conservation. Bird. Conserv. Int. 22, 260–269 (2012).
Google Scholar 
Morales-Reyes, Z. et al. Evaluation of the network of protection areas for the feeding of scavengers in Spain: From biodiversity conservation to greenhouse gas emission savings. J. Appl. Ecol. 54, 1120–1129 (2017).CAS 

Google Scholar 
Mateo-Tomás, P. & Olea, P. When hunting benefits raptors: A case study of game species and vultures. Eur. J. Wildl. Res. 56, 519–528 (2010).
Google Scholar 
Pereira, H. M. & Navarro, L. M. Rewilding European Landscapes (Springer, 2015).
Google Scholar 
Margalida, A., Carrete, M., Sánchez-Zapata, J. A. & Donázar, J. A. Good news for European vultures. Science 335, 284 (2012).ADS 
CAS 
PubMed 

Google Scholar 
Paredes, R. et al. Proximity to multiple foraging habitats enhances seabirds’ resilience to local food shortages. Mar. Ecol. Prog. Ser. 471, 253–269 (2012).ADS 

Google Scholar 
Gomo, G., Mattisson, J., Hagen, B. R., Moa, P. F. & Willebrand, T. Scavenging on a pulsed resource. Quality matters for corvids but density for mammals. BMC Ecol. 17, 22 (2017).PubMed 
PubMed Central 

Google Scholar 
Navarro, L. M. & Pereira, H. M. Rewilding abandoned landscapes in Europe. Ecosystems 15, 900–912 (2012).
Google Scholar 
Arrondo, E. et al. Rewilding traditional grazing areas affects scavenger assemblages and carcass consumption patterns. Basic Appl. Ecol. 41, 56–66 (2019).
Google Scholar 
Cortés-Avizanda, A., Donázar, J. A. & Pereira, H. M. Top scavengers in a wilder Europe. In Rewilding European Landscapes (eds Pereira, H. M. & Navarro, L.) 85–106 (Springer, Berlin, 2015).
Google Scholar 
Harel, R. et al. Decision-making by a soaring bird: Time, energy and risk considerations at different spatio-temporal scales. Philos. Trans. R. Soc. B 371, 20150397 (2016).
Google Scholar 
Austin, R. E. et al. A sex-influenced flexible foraging strategy in a tropical seabird, the magnificent frigatebird. Mar. Ecol. Prog. Ser. 611, 203–214 (2019).ADS 

Google Scholar 
Weimerskirch, H., Cherel, Y., Cuenot-Chaillet, F. & Ridoux, V. Alternative foraging strategies and resource allocation by maIe and female wandering albatrosses. Ecology 78, 2051–2063 (1997).
Google Scholar 
Gangoso, L. et al. Avian scavengers living in anthropized landscapes have shorter telomeres and higher levels of glucocorticoid hormones. Sci. Total Environ. 782, 146920 (2021).ADS 
CAS 

Google Scholar 
Lambertucci, S. A., Carrete, M., Donázar, J. A. & Hiraldo, F. Large-scale age-dependent skewed sex ratio in a sexually dimorphic avian scavenger. PLoS ONE 7, e46347 (2012).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Jackson, A. L., Ruxton, G. D. & Houston, D. C. The effect of social facilitation on foraging success in vultures: A modelling study. Biol. Lett. 4, 311–313 (2008).PubMed 
PubMed Central 

Google Scholar 
Deygout, C., Gault, A., Duriez, O., Sarrazin, F. & Bessa-Gomes, C. Impact of food predictability on social facilitation by foraging scavengers. Behav. Ecol. 21, 1131–1139 (2010).
Google Scholar 
Harel, R., Spiegel, O., Getz, W. M. & Nathan, R. Social foraging and individual consistency in following behaviour: Testing the information centre hypothesis in free-ranging vultures. Proc. R. Soc. B 284, 20162654 (2017).PubMed 
PubMed Central 

Google Scholar 
van Overveld, T. et al. Integrating vulture social behavior into conservation practice. The Condor 122, 1–20 (2020).
Google Scholar 
Genero, F., Franchini, M., Fanin, Y. & Filacorda, S. Spatial ecology of non-breeding Eurasian Griffon Vultures Gyps fulvus in relation to natural and artificial food availability. Bird Study 67, 1–18 (2020).
Google Scholar 
Sherub, S., Fiedler, W., Duriez, O. & Wikelski, M. Bio-Logging – New Technologies to study conservation physiology on the move: A case study on annual survival of Himalayan Vultures. J. Comp. Physiol. 203, 531–542 (2017).
Google Scholar 
Olea, P. P. & Mateo-Tomás, P. The role of traditional farming practices in ecosystem conservation: The case of transhumance and vultures. Biol. Conserv. 142, 1844–1853 (2009).
Google Scholar 
Aguilera-Alcalá, N. et al. The value of transhumance for biodiversity conservation: Vulture foraging in relation to livestock movements. (Ambio, 2021).
Google Scholar 
Clement, V. Spanish wood pasture: Origin and durability of an historical wooded landscape in Mediterranean Europe. Environ. Hist. Camb. 14, 67–87 (2008).
Google Scholar 
Arrondo, E. et al. Landscape anthropization shapes the survival of a top avian scavenger. Biodivers. Conserv. 29, 1411–1425 (2020).
Google Scholar 
Block, T. A., Lyon, B. E., Mikalonis, Z., Chaine, A. S. & Shizuka, D. Social migratory connectivity: Do birds that socialize in winter breed together?. BioRxiv 17, 76 (2021).
Google Scholar 
Thaxter, C. B. et al. Seabird foraging ranges as a preliminary tool for identifying candidate Marine Protected Areas. Biol. Conserv. 156, 53–61 (2012).
Google Scholar 
Santangeli, A. et al. Priority areas for conservation of Old World vultures. Conserv. Biol. 33, 1056–1065 (2019).PubMed 
PubMed Central 

Google Scholar 
Costa, A., Pereira, H. & Madeira, M. Landscape dynamics in endangered cork oak woodlands in Southwestern Portugal (1958–2005). Agrofor. Syst. 77, 83–96 (2009).
Google Scholar 
Del Moral, J. C. & Molina, B. (eds) El buitre leonado en España, población reproductora en 2018 y método de censo (SEO/BirdLife, 2018).
Google Scholar 
Zuberogoitia, I. et al. The flight feather molt of griffon vultures (Gyps fulvus) and associated biological consequences. J. Raptor Res. 47, 292–304 (2013).
Google Scholar 
Fluhr, J., Benhamou, S., Peyrusque, D. & Duriez, O. Space use and time budget in two populations of Griffon Vultures in contrasting landscapes. J. Raptor Res. 55, 13 (2021).
Google Scholar 
Arrondo, E. et al. Use of avian GPS tracking to mitigate human fatalities from bird strikes caused by large soaring birds. J. Appl. Ecol. 58, 1411–1420 (2021).
Google Scholar 
Serrano, D. Dispersal in raptors. In Birds of Prey. Biology and Conservation in the XXI Century (eds HernánSarasola, J. et al.) 95–121 (Springer, 2018).
Google Scholar 
Williams, H. J. et al. Vultures respond to challenges of near-ground thermal soaring by varying bank angle. J. Exp. Biol. 221, 174995 (2018).
Google Scholar 
García-Barón, I. et al. How to fit the distribution of apex scavengers into land-abandonment scenarios? The Cinereous vulture in the Mediterranean biome. Divers. Distrib. 24, 1018–1031 (2018).
Google Scholar 
Donázar, J. A., Ceballos, O. & Cortés-Avizanda, A. Tourism in protected areas: Disentangling road and traffic effects on intra-guild scavenging processes. Sci. Total Environ. 630, 600–608 (2018).ADS 
PubMed 

Google Scholar 
Daoud, J. I. Multicollinearity and Regression Analysis. J. Phys. Conf. Ser. 949, 012009 (2017).
Google Scholar 
Burnham, K. P., Anderson, D. R. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach (2002).Symonds, M. R. E. & Moussalli, A. A brief guide to model selection, multimodel inference and model averaging in behavioural ecology using Akaike’s information criterion. Behav. Ecol. Sociobiol. 65, 13–21 (2011).
Google Scholar 
Hartig, F. DHARMa: Residual Diagnostics for Hierarchical (Multi-Level/Mixed) Regression Models (2020).R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria, (2018), https://www.r-project.org/Venables, W. N. & Ripley, B. D. Modern Applied Statistics with S 4th edn. (Springer, New York, 2002).MATH 

Google Scholar 
Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).
Google Scholar 
Warnes, G. R., Bolker, B., Lumley, T., Johnson, R. C. gmodels: Various R programming tools for model fitting (2018).Mazerolle, M. J. AICcmodavg: Model selection and multimodel inference based on (Q)AIC(c). R package version 2.2-2 (2019).K. Barton, MuMIn: Multimodel inference. R package version 1.43.6.557. (2019).QGIS.org, QGIS Geographic Information System. QGIS Association, (2019), http://www.qgis.orgBouten, W., Baaij, E. W., Shammoun-Baranes, J. & Camphuysen, K. C. J. A flexible GPS tracking system for studying bird behaviour at multiple scales. J. Ornithol. 154, 571–580 (2012).
Google Scholar 
ASTER GDEM Validation Team, ASTER Global Digital Elevation Model Version 2 ‐ Summary of Validation Results (2011).Ruiz de la Torre, J. Mapa Forestal de España, 1:200.000, Memoria General, (ICONA, Madrid, 1990).INE, Anuario estadístico. Madrid, Spain: Instituto Nacional de Estadística, Ministerio de Economía y Hacienda (2006). More

Zald, H. S. J. & Dunn, C. J. Severe fire weather and intensive forest management increase fire severity in a multi-ownership landscape. Ecol. Appl. 2, 1–13 (2018).
Google Scholar 
Schoennagel, T. et al. Adapt to more wildfire in western North American forests as climate changes. Proc. Natl. Acad. Sci. 114, 4582–4590 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
Johnstone, J. F. et al. Changing disturbance regimes, ecological memory, and forest resilience. Front. Ecol. Environ. 14, 369–378 (2016).
Google Scholar 
Radeloff, V. C., Helmers, D. P., Kramer, H. A., Mockrin, M. H. & Alexandre, P. M. Rapid growth of the US wildland-urban interface raises wildfire risk. Proc. Natl. Acad. Sci. https://doi.org/10.1073/pnas.1718850115 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Westerling, A. L., Hidalgo, H. G., Cayan, D. R. & Swetnam, T. W. Warming and earlier spring increase western U.S. forest wildfire activity. Science (80-.). 313, 940–943 (2006).ADS 
CAS 

Google Scholar 
Jolly, W. M. et al. Climate-induced variations in global wildfire danger from 1979 to 2013. Nat. Commun. 6, 1–11 (2015).CAS 

Google Scholar 
Abatzoglou, J. T. & Williams, A. P. Impact of anthropogenic climate change on wildfire across western US forests. Proc. Natl. Acad. Sci. U. S. A. 113, 11770–11775 (2016).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Agee, J. K. The landscape ecology of western forest fire regimes. Northwest Sci. 72, 7569 (1993).
Google Scholar 
Whitehair, L., Fulé, P. Z., Meador, A. S., Azpeleta, T. A. & Kim, Y. S. Fire regime on a cultural landscape: Navajo Nation. Ecol. Evol. 8, 9848–9858 (2018).PubMed 
PubMed Central 

Google Scholar 
Hessburg, P. F. et al. Restoring fire-prone Inland Pacific landscapes: seven core principles. Landsc. Ecol. 30, 1805–1835 (2015).
Google Scholar 
Calkin, D. E., Thompson, M. P. & Finney, M. A. Negative consequences of positive feedbacks in US wildfire management. For. Ecosyst. 2, 1–10 (2015).
Google Scholar 
Mietkiewicz, N. et al. In the line of fire: consequences of human-ignited wildfires to homes in the U.S. (1992–2015). Fire 3, 1–20 (2020).
Google Scholar 
USDA Forest Service & Department of the Interior. 2014 Quadrennial Fire Review: Final Report. (2015).Fischer, A. P. et al. Wildfire risk as a socioecological pathology. Front. Ecol. Environ. 14, 276–284 (2016).
Google Scholar 
Hamilton, M., Fischer, A. P. & Ager, A. A social-ecological network approach for understanding wildfire risk governance. Glob. Environ. Chang. 54, 113–123 (2019).
Google Scholar 
Syphard, A. D. et al. Human influence on California fire regimes. Ecol. Appl. 17, 1388–1402 (2007).PubMed 

Google Scholar 
Balch, J. K. et al. Human-started wildfires expand the fire niche across the USA. Proc. Natl. Acad. Sci. U. S. A. 114, 2946–2951 (2017).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Hoover, K. Federal wildfire management: Ten-year funding trends and issues (FY2011-FY2020). Congressional Research Service (2020).Brown, H. The Camp Fire tragedy of 2018 in California. Fire Manag. Today 78, 11–22 (2020).
Google Scholar 
Wang, D., Guan, D., Kinnon, M. M., Geng, G. & Davis, S. J. Economic footprint of California wildfires in 2018. Nat. Sustain. https://doi.org/10.1038/s41893-020-00646-7 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Higuera, P. E. & Abatzoglou, J. T. Record-setting climate enabled the extraordinary 2020 fire season in the western USA. Glob. Chang. Biol. 27, 1–2 (2021).ADS 
PubMed 

Google Scholar 
NIFC. National Report of Wildland Fires and Acres Burned by State. Natl. Interag. Fire Cent. 64–75 (2018).Ager, A. A. et al. Wildfire exposure to the wildland urban interface in the western US. Appl. Geogr. 111, 102059 (2019).
Google Scholar 
Palaiologou, P., Ager, A. A., Evers, C. R., Nielsen-Pincus, M. & Day, M. A. Fine-scale assessment of cross-boundary wildfire events in the western USA. Nat. Hazards Earth Syst. Sci. 6, 1755–1777 (2019).ADS 

Google Scholar 
Evers, C. R., Ager, A. A., Nielsen-pincus, M., Palaiologou, P. & Bunzel, K. Archetypes of community wildfire exposure from national forests of the western USA. Landsc. Urban Plan. 182, 55–66 (2019).
Google Scholar 
Artley, D. K. Wildland fire protection and response in the United States: the responsibilities, authorities, and roles of federal, state, local, and tribal government. Int. Assoc. Fire Chiefs 5, 1–117 (2009).
Google Scholar 
USDA Forest Service. National action plan: An implementation framework for the National Cohesive Wildland Fire Management Strategy. USDA For. Serv. (2014).Ager, A. A. et al. Network analysis of wildfire transmission and implications for risk governance. PLoS One https://doi.org/10.1371/journal.pone.0172867 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Fleming, C. J., Mccartha, E. B. & Steelman, T. A. Conflict and collaboration in wildfire management: the role of mission alignment. Public Adm. Rev. 75, 445–454 (2015).
Google Scholar 
Dunn, C. J. et al. Wildfire risk science facilitates adaptation of fire-prone social-ecological systems to the new fire reality. Environ. Res. Lett. 15, 25001 (2020).
Google Scholar 
Calkin, D. E., Cohen, J. D., Finney, M. A. & Thompson, M. P. How risk management can prevent future wildfire disasters in the wildland-urban interface. Proc. Natl. Acad. Sci. U. S. A. 111, 746–751 (2014).ADS 
CAS 
PubMed 

Google Scholar 
Whitman, E. et al. The climate space of fire regimes in north-western North America. J. Biogeogr. 42, 1736–1749 (2015).
Google Scholar 
Littell, J. S., Mckenzie, D., Peterson, D. L. & Westerling, A. L. Climate and wildfire area burned in western U.S.A ecoprovinces, 1916–2003. Ecol. Appl. 19, 1003–1021 (2009).PubMed 

Google Scholar 
Syphard, A. D., Keeley, J. E., Pfaff, A. H. & Ferschweiler, K. Human presence diminishes the importance of climate in driving fire activity across the USA. Proc. Natl. Acad. Sci. U. S. A. 114, 13750–13755 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
Parisien, M. A. et al. The spatially varying influence of humans on fire probability in North America. Environ. Res. Lett. 11, 1089 (2016).
Google Scholar 
Scott, J. H. et al. Wildfire risk to communities: spatial datasets of landscape-wide widlfire risk components for the USA. Fort Collins CO For. Serv. Res. Data Arch. 3, 159–1089 (2020).
Google Scholar 
Smith, A. M. S. et al. The science of firescapes: achieving fire-resilient communities. Bioscience 66, 130–146 (2016).PubMed 
PubMed Central 

Google Scholar 
Moritz, M. A. et al. Learning to coexist with wildfire. Nature 515, 58–66 (2014).ADS 
CAS 
PubMed 

Google Scholar 
Ager, A. A. et al. Predicting paradise: modeling future wildfire disasters in the western USA. Sci. Total Environ. 784, 147057 (2021).ADS 
CAS 
PubMed 

Google Scholar 
Ager, A. A. et al. Wildfire exposure and fuel management on western USA national forests. J. Environ. Manag. 145, 54–70 (2014).
Google Scholar 
Haas, J. R., Calkin, D. E. & Thompson, M. P. Wildfire risk transmission in the Colorado Front Range, USA. Risk Anal. 35, 226–240 (2015).PubMed 

Google Scholar 
Stephens, S. L. & Ruth, L. W. Federal forest-fire policy in the USA. Ecol. Appl. 15, 532–542 (2005).
Google Scholar 
Harrell, A. All California’s national forests, including Tahoe’s, to close as fires rage (San Francisco Chronicle, 2020).Thompson, M. P., Gannon, B. M. & Caggiano, M. D. Forest roads and operational wildfire response planning. Forests 12, 1–11 (2021).
Google Scholar 
Parks, S. A., Parisien, M. A., Miller, C. & Dobrowski, S. Z. Fire activity and severity in the western US vary along proxy gradients representing fuel amount and fuel moisture. PLoS ONE 9, 1–8 (2014).
Google Scholar 
Scott, J. H. & Burgan, R. E. Standard fire behavior fuel models: a comprehensive set for use with Rothermel’s surface fire spread model. USDA For. Serv. Gen. Tech. Rep. RMRS GTR 2, 1–76. https://doi.org/10.2737/RMRS-GTR-153 (2005).Article 

Google Scholar 
Keeley, J. E. & Syphard, A. D. Climate change and future fire regimes: examples from California. Geosciences 6, 129 (2016).
Google Scholar 
Thompson, M. P., Dunn, C. J. & Calkin, D. E. Wildfire: systemic changes required. Science (80-.) 20, 63 (2015).
Google Scholar 
North, M. et al. Reform forest fire management. Science (80-.) 3, 7–1459 (2015).
Google Scholar 
Williams, J. Exploring the onset of high-impact mega-fires through a forest land management prism. For. Ecol. Manag. 294, 4–10 (2013).
Google Scholar 
Safford, H. D., Stevens, J. T., Merriam, K., Meyer, M. D. & Latimer, A. M. Fuel treatment effectiveness in California yellow pine and mixed conifer forests. For. Ecol. Manag. 274, 17–28 (2012).
Google Scholar 
Prichard, S. J., Povak, N. A., Kennedy, M. C. & Peterson, D. W. Fuel treatment effectiveness in the context of landform, vegetation, and large, wind-driven wildfires. Ecol. Appl. 30, 1–22 (2020).
Google Scholar 
Thompson, M. P., Riley, K. L., Loeffler, D. & Haas, J. R. Modeling fuel treatment leverage: encounter rates, risk reduction, and suppression cost impacts. Forests 8, 1–26 (2017).
Google Scholar 
Boer, M. M., Price, O. F. & Bradstock, R. A. Wildfires: weigh policy effectiveness. Science (80-.) 250, 919 (2015).
Google Scholar 
Barnett, K., Parks, S. A., Miller, C. & Naughton, H. T. Beyond fuel treatment effectiveness: characterizing interactions between fire and treatments in the USA. Forests 7, 7569 (2016).
Google Scholar 
Brenkert-Smith, H., Champ, P. A. & Flores, N. Insights into wildfire mitigation decisions among wildland-urban interface residents. Soc. Nat. Resour. 19, 759–768 (2006).
Google Scholar 
Reams, M. A., Haines, T. K., Renner, C. R., Wascom, M. W. & Kingre, H. Goals, obstacles and effective strategies of wildfire mitigation programs in the Wildland-Urban Interface. For. Policy Econ. 7, 818–826 (2005).
Google Scholar 
Cohen, J. The wildland-urban interface fire problem: a consequence of the fire exclusion paradigm. For. Hist. Today 2008, 20–26 (2008).
Google Scholar 
Caggiano, M. D., Hawbaker, T. J., Gannon, B. M. & Hoffman, C. M. Building loss in WUI disasters: evaluating the core components of the wildland–urban interface definition. Fire 3, 1–17 (2020).
Google Scholar 
Steelman, T. A. & Burke, C. A. Is wildfire policy in the USA sustainable?. J. For. 105, 67–72 (2007).
Google Scholar 
Syphard, A. D. & Keeley, J. E. Factors associated with structure loss in the 2013–2018 California wildfires. Fire 2, 1–15 (2019).
Google Scholar 
Keeley, J. E. & Syphard, A. D. Historical patterns of wildfire ignition sources in California ecosystems. Int. J. Wildl. Fire 27, 781–799 (2018).
Google Scholar 
Scott, J. H., Thompson, M. P. & Calkin, D. E. A wildfire risk assessment framework for land and resource management. Gen. Tech. Rep. RMRS-GTR-315 US. Dep. Agric. For. Serv. Rocky Mt. Res. Stn. P 83, 59–67 (2013).
Google Scholar 
Rodrıguez y Silva, F., O’Connor, C. D., Thompson, M. P., Ramon Molina Martinez, J. & Calkin, D. E. Modelling suppression difficulty: current and future applications. Int. J. Wildl. Fire (2020).O’Connor, C. D., Calkin, D. E. & Thompson, M. P. An empirical machine learning method for predicting potential fire control locations for pre-fire planning and operational fire management. Int. J. Wildl. Fire 2, 587–597 (2017).
Google Scholar 
Thompson, M. P. et al. Application of wildfire risk assessment results to wildfire response planning in the Southern Sierra Nevada, California, USA. Forests 7, 542 (2016).
Google Scholar 
Thompson, M. P. et al. Prototyping a geospatial atlas for wildfire planning and management. Forests 2, 1–17 (2020).
Google Scholar 
Paveglio, T. B. et al. Urban interface: adaptive capacity for wildfire. For. Sci. 61, 298–310 (2015).
Google Scholar 
Haas, J. R., Calkin, D. E. & Thompson, M. P. A national approach for integrating wildfire simulation modeling into Wildland Urban Interface risk assessments within the USA. Landsc. Urban Plan. 119, 44–53 (2013).
Google Scholar 
Mockrin, M. H., Stewart, S. I., Radeloff, V. C., Hammer, R. B. & Alexandre, P. M. Adapting to wildfire: rebuilding after home loss. Soc. Nat. Resour. 28, 839–856 (2015).
Google Scholar 
Haire, S. L. & McGarigal, K. Effects of landscape patterns of fire severity on regenerating ponderosa pine forests (Pinus ponderosa) in New Mexico and Arizona, USA. Landsc. Ecol. 25, 1055–1069 (2010).
Google Scholar 
Coop, J. D. et al. Wildfire-driven forest conversion in western North American landscapes. Bioscience 70, 659–673 (2020).PubMed 
PubMed Central 

Google Scholar 
Syphard, A. D., Brennan, T. J. & Keeley, J. E. Drivers of chaparral type conversion to herbaceous vegetation in coastal Southern California. Sci. Rep. 2, 90–101. https://doi.org/10.1111/ddi.12827 (2019).Article 

Google Scholar 
Steelman, T. U. S. wildfire governance as a socio-ecological problem. Ecol. Soc. 21, 386–408 (2016).
Google Scholar 
Short, K. C. Spatial wildfire occurrence data for the United States, 1992-2018 [FPA_FOD_20210617], 5th edn. https://doi.org/10.2737/RDS-2013-0009.5 (Forest Service Research Data Archive, Fort Collins, CO, 2021).
Google Scholar 
Short, K. C. A spatial database of wildfires in the USA, 1992–2011. Earth Syst. Sci. Data 6, 1–27 (2014).ADS 

Google Scholar 
PRISM. (PRISM Climate Group, Oregon State University. http://www.prism.oregonstate.edu, 2020).USGS. Protected areas database of the United States (PAD-US) 2.1: U.S. Geological Survey data release. (2020). https://doi.org/10.5066/P92QM3NT. Accessed 15 Nov 2020.Crase, B., Liedloff, A. C. & Wintle, B. A. A new method for dealing with residual spatial autocorrelation in species distribution models. Ecography (Cop.) 35, 879–888 (2012).
Google Scholar 
Elith, J., Leathwick, J. R. & Hastie, T. A working guide to boosted regression trees. J. Anim. Ecol. 2, 802–813. https://doi.org/10.1111/j.1365-2656.2008.01390.x (2008).Article 

Google Scholar 
Dormann, C. F. et al. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography (Cop.) 36, 27–46 (2013).
Google Scholar 
Greenwell, B., Boehmke, B., Cunningham, J. & GBM-developers. gmb: Generalized boosted regression models. R Packag. version 2.1.8. https//CRAN.R-project.org/package=gbm (2020).Hijmans, R. J., Philips, S., Leathwick, J. & Elith, J. dismo: Species distribution modeling. R Packag. version 1.3–3. https//CRAN.R-project.org/package=dismo (2020). More

CORRESPONDENCE
15 February 2022

Brazil opens highly protected caves to mining, risking fauna

Hernani Fernandes Magalhaes de Oliveira

 ORCID: http://orcid.org/0000-0001-7040-8317

0
,

Daiana Cardoso Silva

 ORCID: http://orcid.org/0000-0003-1612-6452

1
,

Priscilla Lora Zangrandi

 ORCID: http://orcid.org/0000-0003-1406-944X

2
&

Fabricius Maia Chaves Bicalho Domingos

 ORCID: http://orcid.org/0000-0003-2069-9317

3

Hernani Fernandes Magalhaes de Oliveira

Federal University of Paraná, Curitiba, Brazil.

View author publications

You can also search for this author in PubMed
 Google Scholar

Daiana Cardoso Silva

Mato Grosso State University, Nova Xavantina, Brazil.

View author publications

You can also search for this author in PubMed
 Google Scholar

Priscilla Lora Zangrandi

Toronto, Canada.

View author publications

You can also search for this author in PubMed
 Google Scholar

Fabricius Maia Chaves Bicalho Domingos

Federal University of Paraná, Curitiba, Brazil.

View author publications

You can also search for this author in PubMed
 Google Scholar

Twitter

Facebook

Email

Brazil’s government has changed the designation of caves that warrant top priority for conservation (see go.nature.com/3gy5). Constituting some 13–30% of the country’s 22,000 protected caves, these will now be open to commercial exploitation, which could seriously affect their vulnerable fauna.

Access options

Access through your institution

Change institution

Buy or subscribe

/* style specs start */
style{display:none!important}.LiveAreaSection-193358632 *{align-content:stretch;align-items:stretch;align-self:auto;animation-delay:0s;animation-direction:normal;animation-duration:0s;animation-fill-mode:none;animation-iteration-count:1;animation-name:none;animation-play-state:running;animation-timing-function:ease;azimuth:center;backface-visibility:visible;background-attachment:scroll;background-blend-mode:normal;background-clip:borderBox;background-color:transparent;background-image:none;background-origin:paddingBox;background-position:0 0;background-repeat:repeat;background-size:auto auto;block-size:auto;border-block-end-color:currentcolor;border-block-end-style:none;border-block-end-width:medium;border-block-start-color:currentcolor;border-block-start-style:none;border-block-start-width:medium;border-bottom-color:currentcolor;border-bottom-left-radius:0;border-bottom-right-radius:0;border-bottom-style:none;border-bottom-width:medium;border-collapse:separate;border-image-outset:0s;border-image-repeat:stretch;border-image-slice:100%;border-image-source:none;border-image-width:1;border-inline-end-color:currentcolor;border-inline-end-style:none;border-inline-end-width:medium;border-inline-start-color:currentcolor;border-inline-start-style:none;border-inline-start-width:medium;border-left-color:currentcolor;border-left-style:none;border-left-width:medium;border-right-color:currentcolor;border-right-style:none;border-right-width:medium;border-spacing:0;border-top-color:currentcolor;border-top-left-radius:0;border-top-right-radius:0;border-top-style:none;border-top-width:medium;bottom:auto;box-decoration-break:slice;box-shadow:none;box-sizing:border-box;break-after:auto;break-before:auto;break-inside:auto;caption-side:top;caret-color:auto;clear:none;clip:auto;clip-path:none;color:initial;column-count:auto;column-fill:balance;column-gap:normal;column-rule-color:currentcolor;column-rule-style:none;column-rule-width:medium;column-span:none;column-width:auto;content:normal;counter-increment:none;counter-reset:none;cursor:auto;display:inline;empty-cells:show;filter:none;flex-basis:auto;flex-direction:row;flex-grow:0;flex-shrink:1;flex-wrap:nowrap;float:none;font-family:initial;font-feature-settings:normal;font-kerning:auto;font-language-override:normal;font-size:medium;font-size-adjust:none;font-stretch:normal;font-style:normal;font-synthesis:weight style;font-variant:normal;font-variant-alternates:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-variant-position:normal;font-weight:400;grid-auto-columns:auto;grid-auto-flow:row;grid-auto-rows:auto;grid-column-end:auto;grid-column-gap:0;grid-column-start:auto;grid-row-end:auto;grid-row-gap:0;grid-row-start:auto;grid-template-areas:none;grid-template-columns:none;grid-template-rows:none;height:auto;hyphens:manual;image-orientation:0deg;image-rendering:auto;image-resolution:1dppx;ime-mode:auto;inline-size:auto;isolation:auto;justify-content:flexStart;left:auto;letter-spacing:normal;line-break:auto;line-height:normal;list-style-image:none;list-style-position:outside;list-style-type:disc;margin-block-end:0;margin-block-start:0;margin-bottom:0;margin-inline-end:0;margin-inline-start:0;margin-left:0;margin-right:0;margin-top:0;mask-clip:borderBox;mask-composite:add;mask-image:none;mask-mode:matchSource;mask-origin:borderBox;mask-position:0% 0%;mask-repeat:repeat;mask-size:auto;mask-type:luminance;max-height:none;max-width:none;min-block-size:0;min-height:0;min-inline-size:0;min-width:0;mix-blend-mode:normal;object-fit:fill;object-position:50% 50%;offset-block-end:auto;offset-block-start:auto;offset-inline-end:auto;offset-inline-start:auto;opacity:1;order:0;orphans:2;outline-color:initial;outline-offset:0;outline-style:none;outline-width:medium;overflow:visible;overflow-wrap:normal;overflow-x:visible;overflow-y:visible;padding-block-end:0;padding-block-start:0;padding-bottom:0;padding-inline-end:0;padding-inline-start:0;padding-left:0;padding-right:0;padding-top:0;page-break-after:auto;page-break-before:auto;page-break-inside:auto;perspective:none;perspective-origin:50% 50%;pointer-events:auto;position:static;quotes:initial;resize:none;right:auto;ruby-align:spaceAround;ruby-merge:separate;ruby-position:over;scroll-behavior:auto;scroll-snap-coordinate:none;scroll-snap-destination:0 0;scroll-snap-points-x:none;scroll-snap-points-y:none;scroll-snap-type:none;shape-image-threshold:0;shape-margin:0;shape-outside:none;tab-size:8;table-layout:auto;text-align:initial;text-align-last:auto;text-combine-upright:none;text-decoration-color:currentcolor;text-decoration-line:none;text-decoration-style:solid;text-emphasis-color:currentcolor;text-emphasis-position:over right;text-emphasis-style:none;text-indent:0;text-justify:auto;text-orientation:mixed;text-overflow:clip;text-rendering:auto;text-shadow:none;text-transform:none;text-underline-position:auto;top:auto;touch-action:auto;transform:none;transform-box:borderBox;transform-origin:50% 50% 0;transform-style:flat;transition-delay:0s;transition-duration:0s;transition-property:all;transition-timing-function:ease;vertical-align:baseline;visibility:visible;white-space:normal;widows:2;width:auto;will-change:auto;word-break:normal;word-spacing:normal;word-wrap:normal;writing-mode:horizontalTb;z-index:auto;-webkit-appearance:none;-moz-appearance:none;-ms-appearance:none;appearance:none;margin:0}.LiveAreaSection-193358632{width:100%}.LiveAreaSection-193358632 .login-option-buybox{display:block;width:100%;font-size:17px;line-height:30px;color:#222;padding-top:30px;font-family:Harding,Palatino,serif}.LiveAreaSection-193358632 .additional-access-options{display:block;font-weight:700;font-size:17px;line-height:30px;color:#222;font-family:Harding,Palatino,serif}.LiveAreaSection-193358632 .additional-login >li:not(:first-child)::before{transform:translateY(-50%);content:”;height:1rem;position:absolute;top:50%;left:0;border-left:2px solid #999}.LiveAreaSection-193358632 .additional-login >li:not(:first-child){padding-left:10px}.LiveAreaSection-193358632 .additional-login >li{display:inline-block;position:relative;vertical-align:middle;padding-right:10px}.BuyBoxSection-683559780{display:flex;flex-wrap:wrap;flex:1;flex-direction:row-reverse;margin:-30px -15px 0}.BuyBoxSection-683559780 .box-inner{width:100%;height:100%}.BuyBoxSection-683559780 .readcube-buybox{background-color:#f3f3f3;flex-shrink:1;flex-grow:1;flex-basis:255px;background-clip:content-box;padding:0 15px;margin-top:30px}.BuyBoxSection-683559780 .subscribe-buybox{background-color:#f3f3f3;flex-shrink:1;flex-grow:4;flex-basis:300px;background-clip:content-box;padding:0 15px;margin-top:30px}.BuyBoxSection-683559780 .subscribe-buybox-nature-plus{background-color:#f3f3f3;flex-shrink:1;flex-grow:4;flex-basis:100%;background-clip:content-box;padding:0 15px;margin-top:30px}.BuyBoxSection-683559780 .title-readcube{display:block;margin:0;margin-right:20%;margin-left:20%;font-size:24px;line-height:32px;color:#222;padding-top:30px;text-align:center;font-family:Harding,Palatino,serif}.BuyBoxSection-683559780 .title-buybox{display:block;margin:0;margin-right:29%;margin-left:29%;font-size:24px;line-height:32px;color:#222;padding-top:30px;text-align:center;font-family:Harding,Palatino,serif}.BuyBoxSection-683559780 .title-asia-buybox{display:block;margin:0;margin-right:5%;margin-left:5%;font-size:24px;line-height:32px;color:#222;padding-top:30px;text-align:center;font-family:Harding,Palatino,serif}.BuyBoxSection-683559780 .asia-link{color:#069;cursor:pointer;text-decoration:none;font-size:1.05em;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:1.05em6}.BuyBoxSection-683559780 .access-readcube{display:block;margin:0;margin-right:10%;margin-left:10%;font-size:14px;color:#222;padding-top:10px;text-align:center;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:20px}.BuyBoxSection-683559780 .access-asia-buybox{display:block;margin:0;margin-right:5%;margin-left:5%;font-size:14px;color:#222;padding-top:10px;text-align:center;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:20px}.BuyBoxSection-683559780 .access-buybox{display:block;margin:0;margin-right:30%;margin-left:30%;font-size:14px;color:#222;opacity:.8px;padding-top:10px;text-align:center;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:20px}.BuyBoxSection-683559780 .usps-buybox{display:block;margin:0;margin-right:30%;margin-left:30%;font-size:14px;color:#222;opacity:.8px;text-align:center;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:20px}.BuyBoxSection-683559780 .price-buybox{display:block;font-size:30px;color:#222;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;padding-top:30px;text-align:center}.BuyBoxSection-683559780 .price-from{font-size:14px;padding-right:10px;color:#222;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:20px}.BuyBoxSection-683559780 .issue-buybox{display:block;font-size:13px;text-align:center;color:#222;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:19px}.BuyBoxSection-683559780 .no-price-buybox{display:block;font-size:13px;line-height:18px;text-align:center;padding-right:10%;padding-left:10%;padding-bottom:20px;padding-top:30px;color:#222;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif}.BuyBoxSection-683559780 .vat-buybox{display:block;margin-top:5px;margin-right:20%;margin-left:20%;font-size:11px;color:#222;padding-top:10px;padding-bottom:15px;text-align:center;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:17px}.BuyBoxSection-683559780 .button-container{display:flex;padding-right:20px;padding-left:20px;justify-content:center}.BuyBoxSection-683559780 .button-container >*{flex:1px}.BuyBoxSection-683559780 .button-container >a:hover,.Button-505204839:hover,.Button-1078489254:hover,.Button-2808614501:hover{text-decoration:none}.BuyBoxSection-683559780 .readcube-button{background:#fff;margin-top:30px}.BuyBoxSection-683559780 .button-asia{background:#069;border:1px solid #069;border-radius:0;cursor:pointer;display:block;padding:9px;outline:0;text-align:center;text-decoration:none;min-width:80px;margin-top:75px}.BuyBoxSection-683559780 .button-label-asia,.ButtonLabel-3869432492,.ButtonLabel-3296148077,.ButtonLabel-1566022830{display:block;color:#fff;font-size:17px;line-height:20px;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;text-align:center;text-decoration:none;cursor:pointer}.Button-505204839,.Button-1078489254,.Button-2808614501{background:#069;border:1px solid #069;border-radius:0;cursor:pointer;display:block;padding:9px;outline:0;text-align:center;text-decoration:none;min-width:80px;max-width:320px;margin-top:10px}.Button-505204839 .readcube-label,.Button-1078489254 .readcube-label,.Button-2808614501 .readcube-label{color:#069}
/* style specs end */Subscribe to nature+Get immediate online access to the entire Nature family of 50+ journals$29.99monthlySubscribeSubscribe to JournalGet full journal access for 1 year$199.00only $3.90 per issueSubscribeAll prices are NET prices. VAT will be added later in the checkout.Tax calculation will be finalised during checkout.Buy articleGet time limited or full article access on ReadCube.$32.00BuyAll prices are NET prices.

Additional access options:

Log in

Learn about institutional subscriptions

Nature 602, 386 (2022)
doi: https://doi.org/10.1038/d41586-022-00406-x

Competing Interests
The authors declare no competing interests.

Related Articles

See more letters to the editor

Subjects

Conservation biology

Government

Industry

Latest on:

Government

China: reform research-evaluation criteria
Correspondence 15 FEB 22

Biden needs scientists with policy chops
World View 11 FEB 22

Africa is bringing vaccine manufacturing home
Editorial 09 FEB 22

Industry

Start-ups create career opportunities for scientists
Career Feature 07 FEB 22

Climate pledges from top companies crumble under scrutiny
News 07 FEB 22

Theranos’s lesson for investors: speak to lab workers
Correspondence 25 JAN 22

Jobs

Hodi Research Fellow

Dana-Farber Cancer Institute (DFCI)
Boston, MA, United States

Research Associate / Postdoctoral Researcher-Carbon

Woodwell Climate Research Center
Falmouth, MA, United States

Postdoc Bioinformatics in (single cell) transcriptomic and (epi)genomic analyses of pediatric brain tumors

Prinses Máxima Centrum
Utrecht, Netherlands

Chief Editor, Nature Reviews Cancer

Springer Nature
London, United Kingdom More

Study sitesThe paired 15N-tracer experiments were conducted in 13 forest sites, of which nine were in China, two in Europe and two in the USA. These sites vary in mean annual precipitation (MAP) from 700 to 2500 mm, in mean annual temperature (MAT) from 3 to > 20 °C, and in soil types (Fig. 1, Supplementary Table 1, Supplementary Table 2). Ambient N deposition (bulk/throughfall NH4+ plus NO3−) at the sites ranged from 6 to 54 kg N ha−1 yr−1. Forest types at the experimental sites include tropical forests in southern China, subtropical forests in central China, and temperate forests in northeastern China, Europe, and the USA. Data from the sites in Europe, the USA, and six of the nine sites in China have been reported previously. Detailed descriptions of these sites and the related data source references are summarized in Supplementary Table 1. Data for forests at the other three sites in China (Xishuangbanna, Wuyishan, and Maoershan) are originally presented here. The Xishuangbanna sites, which is located Xishuangbanna National Forest Reserve in Menglun, Mengla County, Yunnan Province, is a primary mixed forest dominated by the typical tropical forest tree species Terminalia myriocarpa and Pometia tomentosa. The Wuyishan forest, which is located in the Wuyi mountains in Jiangxi Province, is also a mature subtropical forest with Tsuga chinensis var. tchekiangensis as the dominant tree species in the canopy layer. Other common tree species in the forest include Betula luminifera and Cyclobalanopsis multinervis. Maoershan is a relatively young (45 years) larch (Larix gmelinii) plantation located at Laoshan Forest Research Station of Northeast Forestry University, Heilongjiang Province. A few tree species- Juglans mandshurica, Quercus mongolica, and Betula platyphylla- coexist with Larix gmelinii in the canopy. More information about these sites is also presented in Supplementary Table 1.
15N-tracer experimentAt all sites, small amounts of 15NH4+ or 15NO3− tracers (generally  20% in a 1-km pixel was defined as forest. Based on this, we estimated the total global forest area to be ≈42 million km2.Calculation of N-induced C sinkThe N-induced C sink was estimated via the stoichiometric upscaling method19, i.e., by multiplying the N retention in woody tissues of stems, branches, and coarse roots and in the soil with the C/N ratios in these compartments. The C sink due to NHx and or NOy deposition was calculated separately using Eq. (4) as follows:$${{{{{{mathrm{C}}}}}}}_{{{{{{mathrm{sink}}}}}}}={{{{{{mathrm{N}}}}}}}_{{{{{{mathrm{dep}}}}}}}times left(,{!}^{15}{{{{{{{mathrm{N}}}}}}}_{{{{{{mathrm{org}}}}}}}^{{{{{{mathrm{R}}}}}}}}times frac{{{{{{mathrm{C}}}}}}}{{{{{{mathrm{N}}}}}}}_{{{{{{mathrm{org}}}}}}}+{{,}^{15}}{{{{{{{mathrm{N}}}}}}}_{{{min }}}^{{{{{{mathrm{R}}}}}}}}times frac{{{{{{mathrm{C}}}}}}}{{{{{{mathrm{N}}}}}}}_{{{min }}}+{{,}^{15}}{{{{{{{mathrm{N}}}}}}}_{{{{{{mathrm{wood}}}}}}}^{{{{{{mathrm{R}}}}}}}}times frac{{{{{{mathrm{C}}}}}}}{{{{{{mathrm{N}}}}}}}_{{{{{{mathrm{wood}}}}}}}times {{{{{mathrm{f}}}}}}right)$$
(4)
where Ndep is NHx or NOy deposition (kg N ha−1 yr−1); ({}^{15}{{{{{{rm{N}}}}}}}_{{{{{{rm{org}}}}}}}^{{{{{{rm{R}}}}}}}), ({}^{15}{{{{{{rm{N}}}}}}}_{{{min }}}^{{{{{{rm{R}}}}}}}) and ({}^{15}{{{{{{rm{N}}}}}}}_{{{{{{rm{wood}}}}}}}^{{{{{{rm{R}}}}}}}) indicate the fraction of deposited NHx or NOy allocated to organic layer, mineral soil, and woody biomass, respectively; and ({frac{{{{{{rm{C}}}}}}}{{{{{{rm{N}}}}}}}}_{{{{{{rm{org}}}}}}}), ({frac{{{{{{rm{C}}}}}}}{{{{{{rm{N}}}}}}}}_{{{min }}}), and ({frac{{{{{{rm{C}}}}}}}{{{{{{rm{N}}}}}}}}_{{{{{{rm{wood}}}}}}}) indicate C/N ratios in the soil organic layer, soil mineral layer and woody plant biomass, respectively. f is the fraction we applied to account for flexible C/N in response to elevated N deposition. At elevated N deposition, wood C/N ratio may decrease, and N accumulates without stimulating additional ecosystem C storage. To account for this scenario, we adopted a flexible stoichiometry51, in which the effects of N deposition on wood C/N ratios are accounted for by multiplying the C/N ratios of wood with a fraction f (from 1 to 0) depending on plant growth response to different rates of N deposition level (kg N ha−1 yr−1). Results of growth responses to experimental N addition and field N gradient studies show plant growth increased with increasing N deposition, flattening near 15–30 kg N ha−1 yr−1 and a reversal toward no enhanced growth response at about 100 kg N ha−1 yr−1 (ref. 36,52). Therefore, for N deposition More