dispersal limits). Even with dispersal limits, these first encounters are predicted to produce al-207 most one hundred new viral sharing events (RCP 2.6: 96 ± 2.3; RCP 8.5: 86 ± 3.9) that might 208 include ZEBOV, and which cover a much broader part of Africa than the current zoonotic niche 209 of Ebola 68 . Human spillover risk aside, this could expose several new wildlife species to a 210 deadly virus historically responsible for sizable primate die-offs 69 . Moreover, for zoonoses like emerging threats like ranavirus causing conservation concern, pathogen exchange among am-271 phibians may be especially important for conservation practitioners to understand 82 . Finally, 272 marine mammals are an important target given their exclusion here, especially after a recent 273 study implicating reduced Arctic sea ice in novel viral transmission between pinnipeds and sea 274 otters-a result that may be the first proof of concept for our proposed climate-disease link 83 .
Because hotspots of cross-species transmission are predictable, our study provides the first 276 template for how surveillance could target future hotspots of viral emergence in wildlife. In the 277 next decade alone, billions could be spent on virological work trying to identify and counteract 278 zoonotic threats before they spread from wildlife reservoirs into human populations 2 . These 
To implement the Grubb outlier tests for a given species we defined a distance matrix between 322 each record and the centroid of all records (in both environmental or geographic space, respec-323 tively) and determined whether the record with the largest distance was an outlier with respect 324 to all other distances, at a given statistical significance (p = 1e − 3, in order to exclude only 325 extreme outliers). If an outlier was detected it was removed and the test was repeated until no 326 additional outliers were detected. The WorldClim dataset is widely used in ecology, biodiversity, and agricultural projections 331 of potential climate change impacts. WorldClim makes data available for current and future 
For herbivores and omnivores, the maximum is estimated as D = 3.31M 0.65 . 514 We used mammalian diet data from the EltonTraits database 113 , and used the same cutoff as 515 Schloss to identify carnivores as any species with 10% or less plants in their diet. We used body 516 mass data from EltonTraits in the Schloss formula to estimate maximum generational dispersal, 517 and converted estimates to annual maximum dispersal rates by dividing by generation length, formula performs notably poorly for bats: for example, it would assign the largest bat in our 527 study, the Indian flying fox (Pteropus giganteus), a dispersal capacity lower than that of the gray 528 dwarf hamster (Cricetulus migratorius). Bats were instead given full dispersal in all scenarios: 529 14 given significant evidence that some bat species regularly cover continental distances 46,47 , and 530 that isolation by distance is uncommon within many bats' ranges 49 , we felt this was a defensible 531 assumption for modeling purposes. Moving forward, the rapid range shifts already observed 532 in many bat species (see main text) could provide an empirical reference point to fit a new allo-533 metric scaling curve (after standardizing those results for the studies' many different method-534 ologies). A different set of functional traits likely govern the scaling of bat dispersal, chiefly the 535 aspect ratio (length:width) of wings, which is a strong predictor of population genetic differ-536 entiation 49 . Migratory status would also be important to include as a predictor although here, 537 we exclude information on long-distance migration for all species (due to a lack of any real 538 framework for adding that information to species distribution models in the literature). . Using a linear model, we show that elevation (C), species richness (D), and land use (E) influence the number of new overlaps for bats and non-bats. Slopes for the elevation effect were generally steeply positive: a log 10 -increase in elevation was associated with between a 0.4-1.41 log 10 -increase in first encounters. Results are averaged across nine global climate models. Legends refer to scenarios: CL gives climate and land use change, while CLD add adds dispersal limits. 20
A. B. Extended Data Figure 8 : Projected viral sharing from suspected Ebola reservoirs is dominated by bats. Node size is proportional to (left) the number of suspected Ebola host species in each order, which connect to (middle) first encounters with potentially naive host species; and (right) the number of projected viral sharing events in each receiving group. (Node size denotes proportions out of 100% within each column total.) While Ebola hosts will encounter a much wider taxonomic range of mammal groups than current reservoirs, the vast majority of viral sharing will occur disproportionately in bats.
Extended Data Figure 9 : Data processing workflow. Summary of species inclusion across the modeling pipeline for species distributions and viral sharing models. The final analyses in the main text use 3,139 species of placental mammals across all scenarios.
Extended Data Figure 10 : Species distribution modeling workflow for a single species. A focal species (the sand cat, Felis margarita) is displayed as an illustrative example. The present day climate prediction (top left) was clipped to the same continent according to the IUCN distribution (top right). This was then clipped according to Cervus elaphus land use (second row, left). The known dispersal distance of the red deer was used to buffer the climate distribution (second row, right). The future distribution predictions (RCP 2.6 shown as an example) are displayed in the bottom four panels, for each of the four pipelines: only climate (third row, left); climate + dispersal clip (third row, right); climate + land use clip (bottom row, left) and climate + land use + dispersal clip (bottom row, right). The four distributions clearly display the limiting effect of the dispersal filter (bottom right panels) in reducing the probability of novel species interactions (bottom left panels). The land use clip had little effect on this species as the entire distribution area was habitable for the red deer.