Morse, S. S. et al. Prediction and prevention of the next pandemic zoonosis. Lancet 380, 1956–1965 (2012).
Google Scholar
Jones, K. E. et al. Global trends in emerging infectious diseases. Nature 451, 990–993 (2008).
Google Scholar
Keesing, F. et al. Impacts of biodiversity on the emergence and transmission of infectious diseases. Nature 468, 647–652 (2010).
Google Scholar
Carlson, C. J. et al. Climate change will drive novel cross-species viral transmission. Preprint at bioRxiv https://doi.org/10.1101/2020.01.24.918755 (2020).
Gibb, R. et al. Zoonotic host diversity increases in human-dominated ecosystems. Nature https://doi.org/10.1038/s41586-020-2562-8 (2020).
Loh, E. H. et al. Targeting transmission pathways for emerging zoonotic disease surveillance and control. Vector Borne Zoonotic Dis. 15, 432–437 (2015).
Google Scholar
Hassell, J. M., Begon, M., Ward, M. J. & Fèvre, E. M. Urbanization and disease emergence: dynamics at the wildlife–livestock–human interface. Trends Ecol. Evol. 32, 55–67 (2017).
Google Scholar
Cohen, J. M., Sauer, E. L., Santiago, O., Spencer, S. & Rohr, J. R. Divergent impacts of warming weather on wildlife disease risk across climates. Science 370, eabb1702 (2020).
Google Scholar
Murray, M. H. et al. City sicker? A meta-analysis of wildlife health and urbanization. Front. Ecol. Environ. 17, 575–583 (2019).
Google Scholar
Becker, D. J., Hall, R. J., Forbes, K. M., Plowright, R. K. & Altizer, S. Anthropogenic resource subsidies and host–parasite dynamics in wildlife. Phil. Trans. R. Soc. B 373, 20170086 (2018).
Google Scholar
Werner, C. S. & Nunn, C. L. Effect of urban habitat use on parasitism in mammals: a meta-analysis. Proc. Biol. Sci. 287, 20200397 (2020).
Google Scholar
Becker, D. J., Streicker, D. G. & Altizer, S. Linking anthropogenic resources to wildlife–pathogen dynamics: a review and meta-analysis. Ecol. Lett. 18, 483–495 (2015).
Google Scholar
Becker, D. J. et al. Macroimmunology: the drivers and consequences of spatial patterns in wildlife immune defense. J. Anim. Ecol. 89, 972–995 (2020).
Google Scholar
Albery, G. F. & Becker, D. J. Fast-lived hosts and zoonotic risk. Trends Parasitol. https://doi.org/10.1016/j.pt.2020.10.012 (2021).
Seto, K. C., Güneralp, B. & Hutyra, L. R. Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools. Proc. Natl Acad. Sci. USA 109, 16083–16088 (2012).
Google Scholar
Chen, G. et al. Global projections of future urban land expansion under shared socioeconomic pathways. Nat. Commun. 11, 537 (2020).
Google Scholar
Gao, J. & O’Neill, B. C. Mapping global urban land for the twenty-first century with data-driven simulations and shared socioeconomic pathways. Nat. Commun. 11, 2302 (2020).
Google Scholar
Santini, L. et al. One strategy does not fit all: determinants of urban adaptation in mammals. Ecol. Lett. 22, 365–376 (2019).
Google Scholar
Ostfeld, R. S. et al. Life history and demographic drivers of reservoir competence for three tick-borne zoonotic pathogens. PLoS ONE 9, e107387 (2014).
Google Scholar
Olival, K. J. et al. Host and viral traits predict zoonotic spillover from mammals. Nature 546, 646–650 (2017).
Google Scholar
Mollentze, N. & Streicker, D. G. Viral zoonotic risk is homogenous among taxonomic orders of mammalian and avian reservoir hosts. Proc. Natl Acad. Sci. USA 117, 9423–9430 (2020).
Google Scholar
Gutiérrez, J. S., Piersma, T. & Thieltges, D. W. Micro- and macroparasite species richness in birds: the role of host life history and ecology. J. Anim. Ecol. 88, 1226–1239 (2019).
Google Scholar
Teitelbaum, C. S. et al. A comparison of diversity estimators applied to a database of host–parasite associations. Ecography 43, 1316–1328 (2019).
Google Scholar
Jorge, F. & Poulin, R. Poor geographical match between the distributions of host diversity and parasite discovery effort. Proc. R. Soc. B 285, 20180072 (2018).
Google Scholar
Allen, T. et al. Global hotspots and correlates of emerging zoonotic diseases. Nat. Commun. 8, 1124 (2017).
Google Scholar
Gibb, R. et al. Mammal virus diversity estimates are unstable due to accelerating discovery effort. Biol. Lett. https://doi.org/10.1098/rsbl.2021.0427 (2022).
Hughes, A. et al. Sampling biases shape our view of the natural world. Ecography 44, 1259–1269 (2021).
Google Scholar
Estes, L. et al. The spatial and temporal domains of modern ecology. Nat. Ecol. Evol. 2, 819–826 (2018).
Google Scholar
Titley, M. A., Snaddon, J. L. & Turner, E. C. Scientific research on animal biodiversity is systematically biased towards vertebrates and temperate regions. PLoS ONE 12, e0189577 (2017).
Google Scholar
Lloyd-Smith, J. O. et al. Should we expect population thresholds for wildlife disease? Trends Ecol. Evol. 20, 511–519 (2005).
Google Scholar
Cummings, C. R. et al. Foraging in urban environments increases bactericidal capacity in plasma and decreases corticosterone concentrations in white ibises. Front. Ecol. Evol. 8, 575980 (2020).
Google Scholar
Hwang, J. et al. Anthropogenic food provisioning and immune phenotype: association among supplemental food, body condition, and immunological parameters in urban environments. Ecol. Evol. 8, 3037–3046 (2018).
Google Scholar
Strandin, T., Babayan, S. A. & Forbes, K. M. Reviewing the effects of food provisioning on wildlife immunity. Phil. Trans. R. Soc. B 373, 20170088 (2018).
Google Scholar
Downs, C. J., Dochtermann, N. A., Ball, R., Klasing, K. C. & Martin, L. B. The effects of body mass on immune cell concentrations of mammals. Am. Nat. 195, 107–114 (2020).
Google Scholar
Downs, C. J. et al. Extreme hyperallometry of mammalian antibacterial defenses. Preprint at bioRxiv https://doi.org/10.1101/2020.09.04.242107 (2020).
Becker, D. J., Seifert, S. N. & Carlson, C. J. Beyond infection: integrating competence into reservoir host prediction. Trends Ecol. Evol. 35, 1062–1065 (2020).
Google Scholar
Hanson, D. A., Britten, H. B., Restani, M. & Washburn, L. R. High prevalence of Yersinia pestis in black-tailed prairie dog colonies during an apparent enzootic phase of sylvatic plague. Conserv. Genet. 8, 789–795 (2007).
Google Scholar
Gecchele, L. V., Pedersen, A. B. & Bell, M. Fine-scale variation within urban landscapes affects marking patterns and gastrointestinal parasite diversity in red foxes. Ecol. Evol. 10, 13796–13809 (2020).
Google Scholar
Albery, G. F., Sweeny, A. R., Becker, D. J. & Bansal, S. Fine-scale spatial patterns of wildlife disease are common and understudied. Funct. Ecol. https://doi.org/10.1111/1365-2435.13942 (2021).
Jones, K. E. et al. PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90, 2648–2648 (2009).
Google Scholar
Fritz, S. A., Bininda-Emonds, O. R. P. & Purvis, A. Geographical variation in predictors of mammalian extinction risk: big is bad, but only in the tropics. Ecol. Lett. 12, 538–549 (2009).
Google Scholar
Albery, G. F., Eskew, E. A., Ross, N. & Olival, K. J. Predicting the global mammalian viral sharing network using phylogeography. Nat. Commun. https://doi.org/10.1038/s41467-020-16153-4 (2020).
IUCN Red List of Threatened Species Version 2019-2 (IUCN, 2019); https://www.iucnredlist.org
Becker, D. J. et al. Optimising predictive models to prioritise viral discovery in zoonotic reservoirs. Lancet Microbe https://doi.org/10.1016/S2666-5247(21)00245-7 (2022).
Mason, P. Parasites of deer in New Zealand. N. Zeal. J. Zool. 21, 39–47 (1994).
Google Scholar
Wilman, H. et al. EltonTraits 1.0: species-level foraging attributes of the world’s birds and mammals. Ecology 95, 2027 (2014).
Google Scholar
Plourde, B. T. et al. Are disease reservoirs special? Taxonomic and life history characteristics. PLoS ONE 12, e0180716 (2017).
Google Scholar
Gibb, R. et al. Data proliferation, reconciliation, and synthesis in viral ecology. Bioscience https://doi.org/10.1101/2021.01.14.426572 (2021).
Stephens, P. R. et al. Global mammal parasite database version 2.0. Ecology 98, 1476 (2017).
Google Scholar
Wardeh, M., Risley, C., Mcintyre, M. K., Setzkorn, C. & Baylis, M. Database of host–pathogen and related species interactions, and their global distribution. Sci. Data 2, 150049 (2015).
Google Scholar
Shaw, L. P. et al. The phylogenetic range of bacterial and viral pathogens of vertebrates. Mol. Ecol. 29, 3361–3379 (2020).
Google Scholar
Chamberlain, S. A. & Szöcs, E. taxize: taxonomic search and retrieval in R. F1000Res https://doi.org/10.12688/f1000research.2-191.v2 (2013).
Carlson, C. J. et al. The Global Virome in One Network (VIRION): an atlas of vertebrate–virus associations. mBio 13, e0298521 (2022).
Google Scholar
Lindgren, F. & Rue, H. Bayesian spatial modelling with R-INLA. J. Stat. Softw. 63, 1–25 (2015).
Google Scholar
Lindgren, F., Rue, H. & Lindstrom, J. An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach. J. R. Stat. Soc. B 73, 423–498 (2011).
Google Scholar
Hadfield, J. D. MCMC methods for multi-response generalized linear mixed models: the MCMCglmm R package. J. Stat. Softw. 33, 1–22 (2010).
Google Scholar
Winter, D. J. rentrez: an R package for the NCBI eUtils API. R J. 9, 520–526 (2017).
Google Scholar
Shipley, B. Confirmatory path analysis in a generalized multilevel context. Ecology 90, 363–368 (2009).
Google Scholar
Carlson, C. J., Dallas, T. A., Alexander, L. W., Phelan, A. L. & Phillips, A. J. What would it take to describe the global diversity of parasites? Proc. R. Soc. B 287, 20201841 (2020).
Google Scholar
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