Studying the mechanisms that enable coral populations to inhabit spatially varying thermal environments can help evaluate how they will respond in time to the effects of global climate change and elucidate the evolutionary forces that enable or constrain adaptation. Inshore reefs in the Florida Keys experience higher temperatures than offshore reefs for prolonged periods during the summer. We conducted a common garden experiment with heat stress as our selective agent to test for local thermal adaptation in corals from inshore and offshore reefs. We show that inshore corals are more tolerant of a 6-week temperature stress than offshore corals. Compared with inshore corals, offshore corals in the 31 °C treatment showed significantly elevated bleaching levels concomitant with a tendency towards reduced growth. In addition, dinoflagellate symbionts (Symbiodinium sp.) of offshore corals exhibited reduced photosynthetic efficiency. We did not detect differences in the frequencies of major (>5%) haplotypes comprising Symbiodinium communities hosted by inshore and offshore corals, nor did we observe frequency shifts ('shuffling') in response to thermal stress. Instead, coral host populations showed significant genetic divergence between inshore and offshore reefs, suggesting that in Porites astreoides, the coral host might play a prominent role in holobiont thermotolerance. Our results demonstrate that coral populations inhabiting reefs <10-km apart can exhibit substantial differences in their physiological response to thermal stress, which could impact their population dynamics under climate change.

Although the approach of contact network epidemiology has been increasing in popularity for studying transmission of infectious diseases in human populations, it has generally been an underutilized approach for investigating disease outbreaks in wildlife populations. In this paper we explore the differences between the type of data that can be collected on human and wildlife populations, provide an update on recent advances that have been made in wildlife epidemiology by using a network approach, and discuss why networks might have been underutilized and why networks could and should be used more in the future. We conclude with ideas for future directions and a call for field biologists and network modelers to engage in more cross-disciplinary collaboration.

Many endangered wildlife populations are vulnerable to infectious diseases for which vaccines exist; yet, pragmatic considerations often preclude largescale vaccination efforts. These barriers could be reduced by focusing on individuals with the highest contact rates. However, the question then becomes whether targeted vaccination is sufficient to prevent large outbreaks. To evaluate the efficacy of targeted wildlife vaccinations, we simulate pathogen transmission and control on monthly association networks informed by behavioural data from a wild chimpanzee community (Kanyawara N ¼ 37, Kibale National Park, Uganda). Despite considerable variation across monthly networks, our simulations indicate that targeting the most connected individuals can prevent large outbreaks with up to 35% fewer vaccines than random vaccination. Transmission heterogeneities might be attributed to biological differences among individuals (e.g. sex, age, dominance and family size). Thus, we also evaluate the effectiveness of a trait-based vaccination strategy, as trait data are often easier to collect than interaction data. Our simulations indicate that a trait-based strategy can prevent large outbreaks with up to 18% fewer vaccines than random vaccination, demonstrating that individual traits can serve as effective estimates of connectivity. Overall, these results suggest that fine-scale behavioural data can help optimize pathogen control efforts for endangered wildlife.

WOS:000239127800009International audience[No abstract

Since the 1980s, the Virunga mountain gorilla population has almost doubled, now reaching 480 individuals living in a 430-km(2) protected area. Analysis of the gorillas' ranging patterns can provide critical information on the extent and possible effects of competition for food and space. We analyzed 12 years of daily ranging data and inter-group encounter data collected on 11 gorilla groups monitored by the Karisoke Research Center in Rwanda. During that period, the study population increased in size by almost 50% and the number of groups tripled. Groups had small yearly home ranges compared to other known gorilla populations, with an average 90% kernel density estimate of 8.07 km2 and large between-group variations (3.17-23.59 km2). Most groups had consistent home range location over the course of the study but for some, we observed gradual range shifts of up to 4 km. Neighboring groups displayed high home range overlap, which increased dramatically after the formation of new groups. On average, each group used only 28.6% of its 90% kernel home range exclusively, and in some areas up to six different groups had overlapping home ranges with little or no exclusive areas. We found a significant intra-group positive relationship between the number of weaned individuals in a group and the home range size, but the fitted models only explained 17.5% and 13.7% of the variance in 50% and 90% kernel home range size estimates, respectively. This suggests that despite the increase in size, the study population is not yet experiencing marked effects of feeding competition. However, the increase in home range overlap resulting from the formation of new groups led to a sixfold increase in the frequency of inter-group encounters, which exposes the population to elevated risks of fight-related injuries and infanticide.

Summary1. Heterogeneity in host association patterns can alter pathogen transmission and strategies for control. Great apes are highly social and endangered animals that have experienced substantial population declines from directly transmitted pathogens; as such, network approaches to quantify contact heterogeneity could be crucially important for predicting infection probability and outbreak size following pathogen introduction, especially owing to challenges in collecting real-time infection data for endangered wildlife. 2. We present here the first study using network analysis to quantify contact heterogeneity in wild apes, with applications for predicting community-wide infectious disease risk. Specifically, within a wild chimpanzee community, we ask how associations between individuals vary over time, and we identify traits of highly connected individuals that might contribute disproportionately to pathogen spread. 3. We used field observations of behavioural encounters in a habituated wild chimpanzee community in Kibale National Park, Uganda to construct monthly party level (i.e. subgroup) and close-contact (i.e. 5 m) association networks over a 9-month period. 4. Network analysis revealed that networks were highly dynamic over time. In particular, oestrous events significantly increased pairwise party associations, suggesting that communitywide disease outbreaks should be more likely to occur when many females are in oestrus. 5. Bayesian models and permutation tests identified traits of chimpanzees that were highly connected within the network. Individuals with large families (i.e. mothers and their juveniles) that range in the core of the community territory and to a lesser extent high-ranking males were central to association networks, and thus represent the most important individuals to target for disease intervention strategies. 6. Overall, we show striking temporal variation in network structure and traits that predict association patterns in a wild chimpanzee community. These empirically-derived networks can inform dynamic models of pathogen transmission and have practical applications for infectious disease management of endangered wildlife species.

The western lowland gorilla (Gorilla gorilla gorilla) is one of the most sexually dimorphic primate species. Mature males are twice the size of females and have grey fur on their backs and a fibrous, adipose crest on their heads. Such traits are likely to have evolved by sexual selection, either because they confer advantages during male-male fights or because females prefer males with more dimorphic traits. We developed photogrammetric methods for distance collection of morphological data from silverback males frequenting the Lokoué forest clearing in Odzala-Kokoua National Park, Republic of the Congo. Body length, head-crest size, musculature development, and extent of the grey color on the back were assessed in 87 nonbreeding and breeding mature males. Behavioral data were also collected during 312 male-male encounters involving 67 mature males in order to estimate their level of aggressiveness. The number of females belonging to a mature male positively correlated with the male crest size, body length, and musculature. Whereas morphological variables did not significantly affect the intensity of male-male encounters, the number of females attending male-male encounters strongly affected the number of agonistic displays by the two males. We discuss the mechanisms through which males with more exaggerated traits could obtain a mating advantage, namely male-male fights or female mate choice.

Density-dependent processes such as competition for resources, migration, predation, and disease outbreaks limit the growth of natural populations. The analysis of 50 years of mountain gorilla data reveals that social behavior changes observed at high group density may also affect population growth in social species. A sudden increase in social group density observed in 2007 caused a threefold increase in the rate of violent encounters between social units (groups and solitary males). A fivefold increase in the rate of infanticide and seven cases of lethal fights among mature males were subsequently recorded, and the annual subpopulation growth rate declined by half between 2000 and 2017. The increase in infanticide alone explains 57% of this decline. These findings highlight the complex relationship between population density and growth in social species and hold important implications for the management of island populations.