Interplay of competition and facilitation in grazing succession by migrant Serengeti herbivores

Competition, facilitation, and predation offer alternative explanations for successional patterns of migratory herbivores. However, these interactions are difficult to measure, leaving uncertainty about the mechanisms underlying body-size-dependent grazing-and even whether succession occurs at all. We used data from an 8-year camera-trap survey, GPS-collared herbivores, and fecal DNA metabarcoding to analyze the timing, arrival order, and interactions among migratory grazers in Serengeti National Park. Temporal grazing succession is characterized by a "push-pull" dynamic: Competitive grazing nudges zebra ahead of co-migrating wildebeest, whereas grass consumption by these large-bodied migrants attracts trailing, small-bodied gazelle that benefit from facilitation. "Natural experiments" involving intense wildfires and rainfall respectively disrupted and strengthened these effects. Our results highlight a balance between facilitative and competitive forces in co-regulating large-scale ungulate migrations.

Fear of the human "super predator" pervades the South African savanna

Lions have long been perceived as Africa's, if not the world's, most fearsome terrestrial predator,1,2,3,4,5,6,7,8,9 the "king of beasts". Wildlife's fear of humans may, however, be far more powerful and all-prevailing1,10 as recent global surveys show that humans kill prey at much higher rates than other predators,10,11,12 due partly to technologies such as hunting with dogs or guns.11,13,14,15 We comprehensively experimentally tested whether wildlife's fear of humans exceeds even that of lions, by quantifying fear responses1 in the majority of carnivore and ungulate species (n = 19) inhabiting South Africa`s Greater Kruger National Park (GKNP),9,15,16,17 using automated camera-speaker systems9,18 at waterholes during the dry season that broadcast playbacks of humans, lions, hunting sounds (dogs, gunshots) or non-predator controls (birds).9,19,20,21,22 Fear of humans significantly exceeded that of lions throughout the savanna mammal community. As a whole (n = 4,238 independent trials), wildlife were twice as likely to run (p < 0.001) and abandoned waterholes in 40% faster time (p < 0.001) in response to humans than to lions (or hunting sounds). Fully 95% of species ran more from humans than lions (significantly in giraffes, leopards, hyenas, zebras, kudu, warthog, and impala) or abandoned waterholes faster (significantly in rhinoceroses and elephants). Our results greatly strengthen the growing experimental evidence that wildlife worldwide fear the human "super predator" far more than other predators,1,19,20,21,22,23,24,25,26,27,28 and the very substantial fear of humans demonstrated can be expected to cause considerable ecological impacts,1,6,22,23,24,29,30,31,32,33,34,35 presenting challenges for tourism-dependent conservation,1,36,37 particularly in Africa,38,39 while providing new opportunities to protect some species.1,22,40.

A worldwide perspective on large carnivore attacks on humans

Large carnivores have long fascinated human societies and have profound influences on ecosystems. However, their conservation represents one of the greatest challenges of our time, particularly where attacks on humans occur. Where human recreational and/or livelihood activities overlap with large carnivore ranges, conflicts can become particularly serious. Two different scenarios are responsible for such overlap: In some regions of the world, increasing human populations lead to extended encroachment into large carnivore ranges, which are subject to increasing contraction, fragmentation, and degradation. In other regions, human and large carnivore populations are expanding, thus exacerbating conflicts, especially in those areas where these species were extirpated and are now returning. We thus face the problem of learning how to live with species that can pose serious threats to humans. We collected a total of 5,440 large carnivore (Felidae, Canidae, and Ursidae; 12 species) attacks worldwide between 1950 and 2019. The number of reported attacks increased over time, especially in lower-income countries. Most attacks (68%) resulted in human injuries, whereas 32% were fatal. Although attack scenarios varied greatly within and among species, as well as in different areas of the world, factors triggering large carnivore attacks on humans largely depend on the socioeconomic context, with people being at risk mainly during recreational activities in high-income countries and during livelihood activities in low-income countries. The specific combination of local socioeconomic and ecological factors is thus a risky mix triggering large carnivore attacks on humans, whose circumstances and frequencies cannot only be ascribed to the animal species. This also implies that effective measures to reduce large carnivore attacks must also consider the diverse local ecological and social contexts.

Stabilizing effects of group formation by Serengeti herbivores on predator-prey dynamics

Predator-prey theory often assumes that potential prey individuals are solitary and evenly distributed in space. This assumption is violated in social, mobile prey, such as many ungulates. Here we use data from 80 monthly field censuses to estimate the parameters for a power relationship between herd density and population density for eight species of large herbivores commonly found in the diet of Serengeti lions, confirming a power relationship proposed from a preliminary Serengeti dataset. Here we extend our analysis of that model to demonstrate how parameters of the power function relate to average herd size and density-dependent changes in herd size and evaluate how interspecific variation in these parameters shapes the group-dependent functional response by Serengeti lions for eight prey species. We apply the different prey-specific functional response models in a Rosenzweig-MacArthur framework to compare their impact on the stability of predator–prey dynamics. Model outcomes suggest that group formation plays a strong role in stabilizing lion–herbivore interactions in Serengeti by forcing lions to search over a larger area before each prey encounter. As a consequence of grouping by their prey, our model also suggests that Serengeti lions are forced to broaden their diets to include multiple species of prey in order to persist, potentially explaining the generalist foraging by lions routinely recorded across multiple ecosystems.

Reactive anti-predator behavioral strategy shaped by predator characteristics

Large mammalian herbivores use a diverse array of strategies to survive predator encounters including flight, grouping, vigilance, warning signals, and fitness indicators. While anti-predator strategies appear to be driven by specific predator traits, no prior studies have rigorously evaluated whether predator hunting characteristics predict reactive anti-predator responses. We experimentally investigated behavioral decisions made by free-ranging impala, wildebeest, and zebra during encounters with model predators with different functional traits. We hypothesized that the choice of response would be driven by a predator’s hunting style (i.e., ambush vs. coursing) while the intensity at which the behavior was performed would correlate with predator traits that contribute to the prey’s relative risk (i.e., each predator’s prey preference, prey-specific capture success, and local predator density). We found that the choice and intensity of anti-predator behaviors were both shaped by hunting style and relative risk factors. All prey species directed longer periods of vigilance towards predators with higher capture success. The decision to flee was the only behavior choice driven by predator characteristics (capture success and hunting style) while intensity of vigilance, frequency of alarm-calling, and flight latency were modulated based on predator hunting strategy and relative risk level. Impala regulated only the intensity of their behaviors, while zebra and wildebeest changed both type and intensity of response based on predator traits. Zebra and impala reacted to multiple components of predation threat, while wildebeest responded solely to capture success. Overall, our findings suggest that certain behaviors potentially facilitate survival under specific contexts and that prey responses may reflect the perceived level of predation risk, suggesting that adaptive functions to reactive anti-predator behaviors may reflect potential trade-offs to their use. The strong influence of prey species identity and social and environmental context suggest that these factors may interact with predator traits to determine the optimal response to immediate predation threat.

The long lives of primates and the 'invariant rate of ageing' hypothesis

Is it possible to slow the rate of ageing, or do biological constraints limit its plasticity? We test the 'invariant rate of ageing' hypothesis, which posits that the rate of ageing is relatively fixed within species, with a collection of 39 human and nonhuman primate datasets across seven genera. We first recapitulate, in nonhuman primates, the highly regular relationship between life expectancy and lifespan equality seen in humans. We next demonstrate that variation in the rate of ageing within genera is orders of magnitude smaller than variation in pre-adult and age-independent mortality. Finally, we demonstrate that changes in the rate of ageing, but not other mortality parameters, produce striking, species-atypical changes in mortality patterns. Our results support the invariant rate of ageing hypothesis, implying biological constraints on how much the human rate of ageing can be slowed.

Contrasting levels of social distancing between the sexes in lions

Understanding sexual segregation is crucial to comprehend sociality. A comparative analysis of long-term lion data from Serengeti and Ngorongoro in Tanzania, and Gir in India, reveals that male-female associations are contingent upon male and female group size, prey-size and availability, and the number of prides that each male coalition currently resides. Males maintain proximity with females, whereas females are responsible for segregation except at large kills. Lions feed on the largest prey in Ngorongoro and the smallest in Gir, and females spend the most time with males in Ngorongoro and the least in Gir. Females roar less often in prey-scarce circumstances in Serengeti and throughout the year in Gir possibly to prevent being tracked by males that parasitize on female kills. However, females readily associate with males when available prey is large and abundant. Contrasting availability of resources between Gir and Serengeti/Ngorongoro helps explain the varying degrees of sexual segregation and appears to drive differences in mating systems between these lion populations.

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Sexual segregation in lion populations is driven by resource availability

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Females are responsible for segregating from males, except at large kills

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When prey is scarce, females reduce detection by males by roaring less frequently

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Contrasting proximity between the sexes has led to variation in mating strategies in these populations of African and Asian lions

A pan-African spatial assessment of human conflicts with lions and elephants

African lions (Panthera leo) and African savanna (Loxodonta africana) and forest (L. cyclotis) elephants pose threats to people, crops, and livestock, and are themselves threatened with extinction. Here, we map these human-wildlife conflicts across Africa. Eighty-two percent of sites containing lions and elephants are adjacent to areas with considerable human pressure. Areas at severe risk of conflict (defined as high densities of humans, crops, and cattle) comprise 9% of the perimeter of these species' ranges and are found in 18 countries hosting, respectively, ~ 74% and 41% of African lion and elephant populations. Although a variety of alternative conflict-mitigation strategies could be deployed, we focus on assessing the potential of high-quality mitigation fences. Our spatial and economic assessments suggest that investments in the construction and maintenance of strategically located mitigation fences would be a cost-effective strategy to support local communities, protect people from dangerous wildlife, and prevent further declines in lion and elephant populations.

Group density, disease, and season shape territory size and overlap of social carnivores

The spatial organization of a population can influence the spread of information, behaviour and pathogens. Group territory size and territory overlap and components of spatial organization, provide key information as these metrics may be indicators of habitat quality, resource dispersion, contact rates and environmental risk (e.g. indirectly transmitted pathogens). Furthermore, sociality and behaviour can also shape space use, and subsequently, how space use and habitat quality together impact demography. Our study aims to identify factors shaping the spatial organization of wildlife populations and assess the impact of epizootics on space use. We further aim to explore the mechanisms by which disease perturbations could cause changes in spatial organization. Here we assessed the seasonal spatial organization of Serengeti lions and Yellowstone wolves at the group level. We use network analysis to describe spatial organization and connectivity of social groups. We then examine the factors predicting mean territory size and mean territory overlap for each population using generalized additive models. We demonstrate that lions and wolves were similar in that group-level factors, such as number of groups and shaped spatial organization more than population-level factors, such as population density. Factors shaping territory size were slightly different than factors shaping territory overlap; for example, wolf pack size was an important predictor of territory overlap, but not territory size. Lion spatial networks were more highly connected, while wolf spatial networks varied seasonally. We found that resource dispersion may be more important for driving territory size and overlap for wolves than for lions. Additionally, canine distemper epizootics may have altered lion spatial organization, highlighting the importance of including infectious disease epizootics in studies of behavioural and movement ecology. We provide insight about when we might expect to observe the impacts of resource dispersion, disease perturbations, and other ecological factors on spatial organization. Our work highlights the importance of monitoring and managing social carnivore populations at the group level. Future research should elucidate the complex relationships between demographics, social and spatial structure, abiotic and biotic conditions and pathogen infections.

Identifying Candidate Genetic Markers of CDV Cross-Species Pathogenicity in African Lions

Canine distemper virus (CDV) is a multi-host pathogen with variable clinical outcomes of infection across and within species. We used whole-genome sequencing (WGS) to search for viral markers correlated with clinical distemper in African lions. To identify candidate markers, we first documented single-nucleotide polymorphisms (SNPs) differentiating CDV strains associated with different clinical outcomes in lions in East Africa. We then conducted evolutionary analyses on WGS from all global CDV lineages to identify loci subject to selection. SNPs that both differentiated East African strains and were under selection were mapped to a phylogenetic tree representing global CDV diversity to assess if candidate markers correlated with documented outbreaks of clinical distemper in lions (n = 3). Of 54 SNPs differentiating East African strains, ten were under positive or episodic diversifying selection and 20 occurred in the clinical strain despite strong purifying selection at those loci. Candidate markers were in functional domains of the RNP complex (n = 19), the matrix protein (n = 4), on CDV glycoproteins (n = 5), and on the V protein (n = 1). We found mutations at two loci in common between sequences from three CDV outbreaks of clinical distemper in African lions; one in the signaling lymphocytic activation molecule receptor (SLAM)-binding region of the hemagglutinin protein and another in the catalytic center of phosphodiester bond formation on the large polymerase protein. These results suggest convergent evolution at these sites may have a functional role in clinical distemper outbreaks in African lions and uncover potential novel barriers to pathogenicity in this species.

Mixed-species groups of Serengeti grazers: a test of the stress gradient hypothesis

Understanding the role of species interactions within communities is a central focus of ecology. A key challenge is to understand variation in species interactions along environmental gradients. The stress gradient hypothesis posits that positive interactions increase and competitive interactions decrease with increasing consumer pressure or environmental stress. This hypothesis has received extensive attention in plant community ecology, but only a handful of tests in animals. Furthermore, few empirical studies have examined multiple co‐occurring stressors. Here we test predictions of the stress gradient hypothesis using the occurrence of mixed‐species groups in six common grazing ungulate species within the Serengeti‐Mara ecosystem. We use mixed‐species groups as a proxy for potential positive interactions because they may enhance protection from predators or increase access to high‐quality forage. Alternatively, competition for resources may limit the formation of mixed‐species groups. Using more than 115,000 camera trap observations collected over 5 yr, we found that mixed‐species groups were more likely to occur in risky areas (i.e., areas closer to lion vantage points and in woodland habitat where lions hunt preferentially) and during time periods when resource levels were high. These results are consistent with the interpretation that stress from high predation risk may contribute to the formation of mixed‐species groups, but that competition for resources may prevent their formation when food availability is low. Our results are consistent with support for the stress gradient hypothesis in animals along a consumer pressure gradient while identifying the potential influence of a co‐occurring stressor, thus providing a link between research in plant community ecology on the stress gradient hypothesis, and research in animal ecology on trade‐offs between foraging and risk in landscapes of fear.

Cross-species transmission and evolutionary dynamics of canine distemper virus during a spillover in African lions of Serengeti National Park

The outcome of pathogen spillover from a reservoir to a novel host population can range from a "dead-end" when there is no onward transmission in the recipient population, to epidemic spread and even establishment in new hosts. Understanding the evolutionary epidemiology of spillover events leading to discrete outcomes in novel hosts is key to predicting risk and can lead to a better understanding of the mechanisms of emergence. Here we use a Bayesian phylodynamic approach to examine cross-species transmission and evolutionary dynamics during a canine distemper virus (CDV) spillover event causing clinical disease and population decline in an African lion population (Panthera leo) in the Serengeti Ecological Region between 1993 and 1994. Using 21 near-complete viral genomes from four species we found that this large-scale outbreak was likely  ignited by a single cross-species spillover event from a canid reservoir to noncanid hosts <1 year before disease detection and explosive spread of CDV in lions. Cross-species transmission from other noncanid species probably fuelled the high prevalence of CDV across spatially structured lion prides. Multiple lines of evidence suggest that spotted hyenas (Crocuta crocuta) could have acted as the proximate source of CDV exposure in lions. We report 13 nucleotide substitutions segregating CDV strains found in canids and noncanids. Our results are consistent with the hypothesis that virus evolution played a role in CDV emergence in noncanid hosts following spillover during the outbreak, suggest that host barriers to clinical infection can limit outcomes of CDV spillover in novel host species.

QUANTIFYING THE SEVERITY OF GIRAFFE SKIN DISEASE VIA PHOTOGRAMMETRY ANALYSIS OF CAMERA TRAP DATA

Developing techniques to quantify the spread and severity of diseases afflicting wildlife populations is important for disease ecology, animal ecology, and conservation. Giraffes (Giraffa camelopardalis) are in the midst of a dramatic decline, but it is not known whether disease is playing an important role in the broad-scale population reductions. A skin disorder referred to as giraffe skin disease (GSD) was recorded in 1995 in one giraffe population in Uganda. Since then, GSD has been detected in 13 populations in seven African countries, but good descriptions of the severity of this disease are not available. We photogrammetrically analyzed camera trap images from both Ruaha and Serengeti National parks in Tanzania to quantify GSD severity. Giraffe skin disease afflicts the limbs of giraffes in Tanzania, and we quantified severity by measuring the vertical length of the GSD lesion in relation to the total leg length. Applying the Jenks natural breaks algorithm to the lesion proportions that we derived, we classified individual giraffes into disease categories (none, mild, moderate, and severe). Scaling up to the population level, we predicted the proportion of the Ruaha and Serengeti giraffe populations with mild, moderate, and severe GSD. This study serves to demonstrate that camera traps presented an informative platform for examinations of skin disease ecology.

How to make more from exposure data? An integrated machine learning pipeline to predict pathogen exposure

Predicting infectious disease dynamics is a central challenge in disease ecology. Models that can assess which individuals are most at risk of being exposed to a pathogen not only provide valuable insights into disease transmission and dynamics but can also guide management interventions. Constructing such models for wild animal populations, however, is particularly challenging; often only serological data are available on a subset of individuals and nonlinear relationships between variables are common. Here we provide a guide to the latest advances in statistical machine learning to construct pathogen-risk models that automatically incorporate complex nonlinear relationships with minimal statistical assumptions from ecological data with missing data. Our approach compares multiple machine learning algorithms in a unified environment to find the model with the best predictive performance and uses game theory to better interpret results. We apply this framework on two major pathogens that infect African lions: canine distemper virus (CDV) and feline parvovirus. Our modelling approach provided enhanced predictive performance compared to more traditional approaches, as well as new insights into disease risks in a wild population. We were able to efficiently capture and visualize strong nonlinear patterns, as well as model complex interactions between variables in shaping exposure risk from CDV and feline parvovirus. For example, we found that lions were more likely to be exposed to CDV at a young age but only in low rainfall years. When combined with our data calibration approach, our framework helped us to answer questions about risk of pathogen exposure that are difficult to address with previous methods. Our framework not only has the potential to aid in predicting disease risk in animal populations, but also can be used to build robust predictive models suitable for other ecological applications such as modelling species distribution or diversity patterns.

Novel smacoviruses identified in the faeces of two wild felids: North American bobcat and African lion

Smacoviruses are small circular single-stranded DNA viruses that appear to be prevalent in faeces of a range of animals and have also been found in a few insect species. In this study, we report the first viral genomes from faeces of free-roaming wild felids on two continents. Two smacoviruses were recovered from the faeces of two North American bobcats (Lynx rufus), and one was recovered from an African lion (Panthera leo). All three genomes are genetically different, sharing 59-69% genome-wide sequence identity to other smacoviruses. These are the first full smacovirus genome sequences associated with a large top-end feline predator, and their presence in these samples suggests that feline faeces are a natural niche for the organisms that these viruses infect.

Transmission ecology of canine parvovirus in a multi-host, multi-pathogen system

Understanding multi-host pathogen maintenance and transmission dynamics is critical for disease control. However, transmission dynamics remain enigmatic largely because they are difficult to observe directly, particularly in wildlife. Here, we investigate the transmission dynamics of canine parvovirus (CPV) using state-space modelling of 20 years of CPV serology data from domestic dogs and African lions in the Serengeti ecosystem. We show that, although vaccination reduces the probability of infection in dogs, and despite indirect enhancement of population seropositivity as a result of vaccine shedding, the vaccination coverage achieved has been insufficient to prevent CPV from becoming widespread. CPV is maintained by the dog population and has become endemic with approximately 3.5-year cycles and prevalence reaching approximately 80%. While the estimated prevalence in lions is lower, peaks of infection consistently follow those in dogs. Dogs exposed to CPV are also more likely to become infected with a second multi-host pathogen, canine distemper virus. However, vaccination can weaken this coupling, raising questions about the value of monovalent versus polyvalent vaccines against these two pathogens. Our findings highlight the need to consider both pathogen- and host-level community interactions when seeking to understand the dynamics of multi-host pathogens and their implications for conservation, disease surveillance and control programmes.

Endemic infection can shape exposure to novel pathogens: Pathogen co-occurrence networks in the Serengeti lions

Pathogens are embedded in a complex network of microparasites that can collectively or individually alter disease dynamics and outcomes. Endemic pathogens that infect an individual in the first years of life, for example, can either facilitate or compete with subsequent pathogens thereby exacerbating or ameliorating morbidity and mortality. Pathogen associations are ubiquitous but poorly understood, particularly in wild populations. We report here on 10 years of serological and molecular data in African lions, leveraging comprehensive demographic and behavioural data to test if endemic pathogens shape subsequent infection by epidemic pathogens. We combine network and community ecology approaches to assess broad network structure and characterise associations between pathogens across spatial and temporal scales. We found significant non‐random structure in the lion‐pathogen co‐occurrence network and identified both positive and negative associations between endemic and epidemic pathogens. Our results provide novel insights on the complex associations underlying pathogen co‐occurrence networks.

The use of contraceptive techniques in managed wild African lion (Panthera leo) populations to mimic open system cub recruitment

Context Managed wild lions (Panthera leo) are lions found in smaller (&lt;1000 km2), fenced protected areas that hold a substantial portion of South Africa’s wild lion population. Because the natural population control mechanisms are compromised within these properties, managers must actively control population growth rates. Fecundity control is used by wildlife managers, but long-term, empirical data on the impact and consequences of such interventions in lions are lacking. Aims The aim of the present study was to assess the effectiveness of two methods of contraception (deslorelin implant and unilateral hysterectomy) in reducing cub recruitment of managed wild lions. Methods Survey data spanning 14 years from 94 managed wild lions on 19 protected areas were used to evaluate the effectiveness of deslorelin implant treatments and unilateral hysterectomies on population growth rates through mimicking open system cub recruitment. Key results Deslorelin implants were effective at increasing the age of first reproduction and lengthening inter-birth intervals. There was also an unexpected decrease in litter size. Behavioural side-effects were recorded in 40% of individuals: 19% pride fragmentation; 13% lack of receptiveness towards males; 8% other. The more successive deslorelin implants a lioness had, the more likely it was that weight gain was reported. Unilateral hysterectomy resulted in a decrease in litter size post-surgery, but this was not statistically significant. No behavioural or physiological side-effects were noted after unilateral hysterectomy. Conclusions Deslorelin treatment was more effective in reducing the reproductive output of managed wild lionesses than unilateral hysterectomy surgery. While more side-effects were associated with deslorelin implants than unilateral hysterectomies, a single deslorelin treatment is currently a good option for fecundity reduction. More research is required on unilateral hysterectomy surgery. Implications Neither deslorelin implants nor unilateral hysterectomies offer a ‘silver bullet’ solution for reducing rapid population growth in managed wild lions. Reproductive control should be integrated with other best-practice approaches.

The diversity of population responses to environmental change

The current extinction and climate change crises pressure us to predict population dynamics with ever‐greater accuracy. Although predictions rest on the well‐advanced theory of age‐structured populations, two key issues remain poorly explored. Specifically, how the age‐dependency in demographic rates and the year‐to‐year interactions between survival and fecundity affect stochastic population growth rates. We use inference, simulations and mathematical derivations to explore how environmental perturbations determine population growth rates for populations with different age‐specific demographic rates and when ages are reduced to stages. We find that stage‐ vs. age‐based models can produce markedly divergent stochastic population growth rates. The differences are most pronounced when there are survival‐fecundity‐trade‐offs, which reduce the variance in the population growth rate. Finally, the expected value and variance of the stochastic growth rates of populations with different age‐specific demographic rates can diverge to the extent that, while some populations may thrive, others will inevitably go extinct.

Reconciling corruption with conservation triage: Should investments shift from the last best places?

Considerable outside funding will be required to overcome the financial shortfalls faced by most of Africa's protected areas. Given limited levels of external support, it will be essential to allocate these funds wisely. While most recent studies on conservation triage have recommended prioritizing reserves with the highest remaining conservation value (the "last best places"), such investments are complicated by the fact that these same reserves often attract the greatest revenues from ecotourism and thus the most attention from corrupt local governments. Alternatively, philanthropic organizations might achieve greater returns from investing in the management of neglected areas with lower current conservation value but with less financial leakage from corruption. We outline here how high levels of corruption could favor a strategy that shifts investments away from the last best places.

The spatial distribution of African savannah herbivores: species associations and habitat occupancy in a landscape context

Herbivores play an important role in determining the structure and function of tropical savannahs. Here, we (i) outline a framework for how interactions among large mammalian herbivores, carnivores and environmental variation influence herbivore habitat occupancy in tropical savannahs. We then (ii) use a Bayesian hierarchical model to analyse camera trap data to quantify spatial patterns of habitat occupancy for lions and eight common ungulates of varying body size across an approximately 1100 km(2) landscape in the Serengeti ecosystem. Our results reveal strong positive associations among herbivores at the scale of the entire landscape. Lions were positively associated with migratory ungulates but negatively associated with residents. Herbivore habitat occupancy differed with body size and migratory strategy: large-bodied migrants, at less risk of predation and able to tolerate lower quality food, were associated with high NDVI, while smaller residents, constrained to higher quality forage, avoided these areas. Small herbivores were strongly associated with fires, likely due to the subsequent high-quality regrowth, while larger herbivores avoided burned areas. Body mass was strongly related to herbivore habitat use, with larger species more strongly associated with riverine and woodlands than smaller species. Large-bodied migrants displayed diffuse habitat occupancy, whereas smaller species demonstrated fine-scale occupancy reflecting use of smaller patches of high-quality habitat. Our results demonstrate the emergence of strong positive spatial associations among a diverse group of savannah herbivores, while highlighting species-specific habitat selection strongly determined by herbivore body size.This article is part of the themed issue 'Tropical grassy biomes: linking ecology, human use and conservation'.

Evaluating empirical contact networks as potential transmission pathways for infectious diseases

Networks are often used to incorporate heterogeneity in contact patterns in mathematical models of pathogen spread. However, few tools exist to evaluate whether potential transmission pathways in a population are adequately represented by an observed contact network. Here, we describe a novel permutation-based approach, the network k-test, to determine whether the pattern of cases within the observed contact network are likely to have resulted from transmission processes in the network, indicating that the network represents potential transmission pathways between nodes. Using simulated data of pathogen spread, we compare the power of this approach to other commonly used analytical methods. We test the robustness of this technique across common sampling constraints, including undetected cases, unobserved individuals and missing interaction data. We also demonstrate the application of this technique in two case studies of livestock and wildlife networks. We show that the power of the k-test to correctly identify the epidemiologic relevance of contact networks is substantially greater than other methods, even when 50% of contact or case data are missing. We further demonstrate that the impact of missing data on network analysis depends on the structure of the network and the type of missing data.

Linking social and spatial networks to viral community phylogenetics reveals subtype-specific transmission dynamics in African lions

Heterogeneity within pathogen species can have important consequences for how pathogens transmit across landscapes; however, discerning different transmission routes is challenging. Here, we apply both phylodynamic and phylogenetic community ecology techniques to examine the consequences of pathogen heterogeneity on transmission by assessing subtype-specific transmission pathways in a social carnivore. We use comprehensive social and spatial network data to examine transmission pathways for three subtypes of feline immunodeficiency virus (FIV_Ple ) in African lions (Panthera leo) at multiple scales in the Serengeti National Park, Tanzania. We used FIV_Ple molecular data to examine the role of social organization and lion density in shaping transmission pathways and tested to what extent vertical (i.e., father- and/or mother-offspring relationships) or horizontal (between unrelated individuals) transmission underpinned these patterns for each subtype. Using the same data, we constructed subtype-specific FIV_Ple co-occurrence networks and assessed what combination of social networks, spatial networks or co-infection best structured the FIV_Ple network. While social organization (i.e., pride) was an important component of FIV_Ple transmission pathways at all scales, we find that FIV_Ple subtypes exhibited different transmission pathways at within- and between-pride scales. A combination of social and spatial networks, coupled with consideration of subtype co-infection, was likely to be important for FIV_Ple transmission for the two major subtypes, but the relative contribution of each factor was strongly subtype-specific. Our study provides evidence that pathogen heterogeneity is important in understanding pathogen transmission, which could have consequences for how endemic pathogens are managed. Furthermore, we demonstrate that community phylogenetic ecology coupled with phylodynamic techniques can reveal insights into the differential evolutionary pressures acting on virus subtypes, which can manifest into landscape-level effects.

In the absence of a "landscape of fear": How lions, hyenas, and cheetahs coexist

Aggression by top predators can create a "landscape of fear" in which subordinate predators restrict their activity to low-risk areas or times of day. At large spatial or temporal scales, this can result in the costly loss of access to resources. However, fine-scale reactive avoidance may minimize the risk of aggressive encounters for subordinate predators while maintaining access to resources, thereby providing a mechanism for coexistence. We investigated fine-scale spatiotemporal avoidance in a guild of African predators characterized by intense interference competition. Vulnerable to food stealing and direct killing, cheetahs are expected to avoid both larger predators; hyenas are expected to avoid lions. We deployed a grid of 225 camera traps across 1,125 km² in Serengeti National Park, Tanzania, to evaluate concurrent patterns of habitat use by lions, hyenas, cheetahs, and their primary prey. We used hurdle models to evaluate whether smaller species avoided areas preferred by larger species, and we used time-to-event models to evaluate fine-scale temporal avoidance in the hours immediately surrounding top predator activity. We found no evidence of long-term displacement of subordinate species, even at fine spatial scales. Instead, hyenas and cheetahs were positively associated with lions except in areas with exceptionally high lion use. Hyenas and lions appeared to actively track each, while cheetahs appear to maintain long-term access to sites with high lion use by actively avoiding those areas just in the hours immediately following lion activity. Our results suggest that cheetahs are able to use patches of preferred habitat by avoiding lions on a moment-to-moment basis. Such fine-scale temporal avoidance is likely to be less costly than long-term avoidance of preferred areas: This may help explain why cheetahs are able to coexist with lions despite high rates of lion-inflicted mortality, and highlights reactive avoidance as a general mechanism for predator coexistence.

Dead or gone? Bayesian inference on mortality for the dispersing sex

Estimates of age‐specific mortality are regularly used in ecology, evolution, and conservation research. However, estimating mortality of the dispersing sex, in species where one sex undergoes natal dispersal, is difficult. This is because it is often unclear whether members of the dispersing sex that disappear from monitored areas have died or dispersed. Here, we develop an extension of a multievent model that imputes dispersal state (i.e., died or dispersed) for uncertain records of the dispersing sex as a latent state and estimates age‐specific mortality and dispersal parameters in a Bayesian hierarchical framework. To check the performance of our model, we first conduct a simulation study. We then apply our model to a long‐term data set of African lions. Using these data, we further study how well our model estimates mortality of the dispersing sex by incrementally reducing the level of uncertainty in the records of male lions. We achieve this by taking advantage of an expert's indication on the likely fate of each missing male (i.e., likely died or dispersed). We find that our model produces accurate mortality estimates for simulated data of varying sample sizes and proportions of uncertain male records. From the empirical study, we learned that our model provides similar mortality estimates for different levels of uncertainty in records. However, a sensitivity of the mortality estimates to varying uncertainty is, as can be expected, detectable. We conclude that our model provides a solution to the challenge of estimating mortality of the dispersing sex in species with data deficiency due to natal dispersal. Given the utility of sex‐specific mortality estimates in biological and conservation research, and the virtual ubiquity of sex‐biased dispersal, our model will be useful to a wide variety of applications.

A generalized approach for producing, quantifying, and validating citizen science data from wildlife images

Citizen science has the potential to expand the scope and scale of research in ecology and conservation, but many professional researchers remain skeptical of data produced by nonexperts. We devised an approach for producing accurate, reliable data from untrained, nonexpert volunteers. On the citizen science website www.snapshotserengeti.org, more than 28,000 volunteers classified 1.51 million images taken in a large-scale camera-trap survey in Serengeti National Park, Tanzania. Each image was circulated to, on average, 27 volunteers, and their classifications were aggregated using a simple plurality algorithm. We validated the aggregated answers against a data set of 3829 images verified by experts and calculated 3 certainty metrics-level of agreement among classifications (evenness), fraction of classifications supporting the aggregated answer (fraction support), and fraction of classifiers who reported "nothing here" for an image that was ultimately classified as containing an animal (fraction blank)-to measure confidence that an aggregated answer was correct. Overall, aggregated volunteer answers agreed with the expert-verified data on 98% of images, but accuracy differed by species commonness such that rare species had higher rates of false positives and false negatives. Easily calculated analysis of variance and post-hoc Tukey tests indicated that the certainty metrics were significant indicators of whether each image was correctly classified or classifiable. Thus, the certainty metrics can be used to identify images for expert review. Bootstrapping analyses further indicated that 90% of images were correctly classified with just 5 volunteers per image. Species classifications based on the plurality vote of multiple citizen scientists can provide a reliable foundation for large-scale monitoring of African wildlife.

Estimating wildlife disease dynamics in complex systems using an Approximate Bayesian Computation framework

Emerging infectious diseases of wildlife are of increasing concern to managers and conservation policy makers, but are often difficult to study and predict due to the complexity of host-disease systems and a paucity of empirical data. We demonstrate the use of an Approximate Bayesian Computation statistical framework to reconstruct the disease dynamics of bovine tuberculosis in Kruger National Park's lion population, despite limited empirical data on the disease's effects in lions. The modeling results suggest that, while a large proportion of the lion population will become infected with bovine tuberculosis, lions are a spillover host and long disease latency is common. In the absence of future aggravating factors, bovine tuberculosis is projected to cause a lion population decline of ~3% over the next 50 years, with the population stabilizing at this new equilibrium. The Approximate Bayesian Computation framework is a new tool for wildlife managers. It allows emerging infectious diseases to be modeled in complex systems by incorporating disparate knowledge about host demographics, behavior, and heterogeneous disease transmission, while allowing inference of unknown system parameters.

Does pregnancy coloration reduce female conspecific aggression in the presence of maternal kin?

Colour signals arise in a variety of sexual contexts, including advertising reproductive status. Despite potentially attracting negative attention from unrelated competitors, bright pregnancy coloration may communicate gestation to kin and potential fathers, thereby garnering aid during agonistic encounters and reducing the overall amount of aggression received by pregnant females. To establish whether this 'pregnancy sign' influences rates of aggression in the presence versus absence of maternal kin, we conducted behavioural observations of wild olive baboons, Papio anubis, in Gombe National Park, Tanzania, in groups composed of maternal kin and nonkin, and of captive baboons at the Southwest National Primate Research Center (SNPRC, San Antonio, TX, U.S.A.), in group enclosures that were unlikely to include close kin. At SNPRC, we also experimentally obscured the coloration of the pregnancy sign, and we performed playback experiments to measure male responses to the distress calls of pregnant females. Free-ranging female baboons experienced significantly less aggression from nonkin females after the onset of the pregnancy sign compared to the pre-pregnancy sign. In contrast, captive pregnant females whose pregnancy coloration was obscured with paint experienced significantly lower aggression rates from female conspecifics compared to pre-painting. Male aggression towards females did not differ in the presence versus absence of the pregnancy sign in either the wild or the captive population, although captive fathers paid significantly more attention to distress calls of pregnant cage-mates than they did to those of cycling cage-mates, suggesting a willingness to aid mothers that were carrying their unborn offspring.

Snapshot Serengeti, high-frequency annotated camera trap images of 40 mammalian species in an African savanna

Camera traps can be used to address large-scale questions in community ecology by providing systematic data on an array of wide-ranging species. We deployed 225 camera traps across 1,125 km² in Serengeti National Park, Tanzania, to evaluate spatial and temporal inter-species dynamics. The cameras have operated continuously since 2010 and had accumulated 99,241 camera-trap days and produced 1.2 million sets of pictures by 2013. Members of the general public classified the images via the citizen-science website www.snapshotserengeti.org. Multiple users viewed each image and recorded the species, number of individuals, associated behaviours, and presence of young. Over 28,000 registered users contributed 10.8 million classifications. We applied a simple algorithm to aggregate these individual classifications into a final ‘consensus’ dataset, yielding a final classification for each image and a measure of agreement among individual answers. The consensus classifications and raw imagery provide an unparalleled opportunity to investigate multi-species dynamics in an intact ecosystem and a valuable resource for machine-learning and computer-vision research.

Applying a random encounter model to estimate lion density from camera traps in Serengeti National Park, Tanzania

The random encounter model (REM) is a novel method for estimating animal density from camera trap data without the need for individual recognition. It has never been used to estimate the density of large carnivore species, despite these being the focus of most camera trap studies worldwide. In this context, we applied the REM to estimate the density of female lions (Panthera leo) from camera traps implemented in Serengeti National Park, Tanzania, comparing estimates to reference values derived from pride census data. More specifically, we attempted to account for bias resulting from non-random camera placement at lion resting sites under isolated trees by comparing estimates derived from night versus day photographs, between dry and wet seasons, and between habitats that differ in their amount of tree cover. Overall, we recorded 169 and 163 independent photographic events of female lions from 7,608 and 12,137 camera trap days carried out in the dry season of 2010 and the wet season of 2011, respectively. Although all REM models considered over-estimated female lion density, models that considered only night-time events resulted in estimates that were much less biased relative to those based on all photographic events. We conclude that restricting REM estimation to periods and habitats in which animal movement is more likely to be random with respect to cameras can help reduce bias in estimates of density for female Serengeti lions. We highlight that accurate REM estimates will nonetheless be dependent on reliable measures of average speed of animal movement and camera detection zone dimensions. © 2015 The Authors. Journal of Wildlife Management published by Wiley Periodicals, Inc. on behalf of The Wildlife Society.