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Abstract Characterizing genetically distinct populations of primates is important for protecting biodiversity and effectively allocating conservation resources. Skywalker gibbons (Hoolock tianxing) were first described in 2017, with the only confirmed population consisting of 150 individuals in Mt. Gaoligong, Yunnan Province, China. Based on river geography, the distribution of the skywalker gibbon has been hypothesized to extend into Myanmar between the N’Mai Kha and Ayeyarwaddy Rivers to the west, and the Salween River (named the Thanlwin River in Myanmar and Nujiang River in China) to the east. We conducted acoustic point-count sampling surveys, collected noninvasive samples for molecular mitochondrial cytochromebgene identification, and took photographs for morphological identification at six sites in Kachin State and three sites in Shan State to determine the presence of skywalker gibbons in predicted suitable forest areas in Myanmar. We also conducted 50 semistructured interviews with members of communities surrounding gibbon range forests to understand potential threats. In Kachin State, we audio-recorded 23 gibbon groups with group densities ranging between 0.57 and 3.6 group/km². In Shan State, we audio-recorded 21 gibbon groups with group densities ranging between 0.134 and 1.0 group/km². Based on genetic data obtained from skin and saliva samples, the gibbons were identified as skywalker gibbons (99.54–100% identity). Although these findings increase the species’ known population size and confirmed distribution, skywalker gibbons in Myanmar are threatened by local habitat loss, degradation, and fragmentation. Most of the skywalker gibbon population in Myanmar exists outside protected areas. Therefore, the IUCN Red List status of the skywalker gibbon should remain as Endangered. 

Pairwise host–parasite relationships are typically embedded in broader networks of ecological interactions, which have the potential to shape parasite evolutionary trajectories. Understanding this ‘community context’ of pathogen evolution is vital for wildlife, agricultural and human systems alike, as pathogens typically infect more than one host—and these hosts may have independent ecological relationships. Here, we introduce an eco-evolutionary model examining ecological feedback across a range of host–host interactions. Specifically, we analyse a model of the evolution of virulence of a parasite infecting two hosts exhibiting competitive, mutualistic or exploitative relationships. We first find that parasite specialism is necessary for inter-host interactions to impact parasite evolution. Furthermore, we find generally that increasing competition between hosts leads to higher shared parasite virulence while increasing mutualism leads to lower virulence. In exploitative host–host interactions, the particular form of parasite specialization is critical—for instance, specialization in terms of onward transmission, host tolerance or intra-host pathogen growth rate lead to distinct evolutionary outcomes under the same host–host interactions. Our work provides testable hypotheses for multi-host disease systems, predicts how changing interaction networks may impact virulence evolution and broadly demonstrates the importance of looking beyond pairwise relationships to understand evolution in realistic community contexts. 

The management of future pandemic risk requires a better understanding of the mechanisms that determine the virulence of emerging zoonotic viruses. Meta-analyses suggest that the virulence of emerging zoonoses is correlated with but not completely predictable from reservoir host phylogeny, indicating that specific characteristics of reservoir host immunology and life history may drive the evolution of viral traits responsible for cross-species virulence. In particular, bats host viruses that cause higher case fatality rates upon spillover to humans than those derived from any other mammal, a phenomenon that cannot be explained by phylogenetic distance alone. In order to disentangle the fundamental drivers of these patterns, we develop a nested modeling framework that highlights mechanisms that underpin the evolution of viral traits in reservoir hosts that cause virulence following cross-species emergence. We apply this framework to generate virulence predictions for viral zoonoses derived from diverse mammalian reservoirs, recapturing trends in virus-induced human mortality rates reported in the literature. Notably, our work offers a mechanistic hypothesis to explain the extreme virulence of bat-borne zoonoses and, more generally, demonstrates how key differences in reservoir host longevity, viral tolerance, and constitutive immunity impact the evolution of viral traits that cause virulence following spillover to humans. Our theoretical framework offers a series of testable questions and predictions designed to stimulate future work comparing cross-species virulence evolution in zoonotic viruses derived from diverse mammalian hosts.