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Gathering species population data from local people is growing in popularity in conservation, as a cost-effective way to rapidly collect information over spatiotemporal scales that are not always feasible using conventional surveys. However, few studies exist that assess the bias when incorporating local ecological knowledge (LEK) into wildlife population monitoring. In this thesis, I use a mixed-method approach to gain a better understanding of the uncertainty that can affect observational data and explore how local ecological knowledge can be better incorporated into wildlife population monitoring, using two wild meat hunting villages adjacent to the Dja Faunal Reserve in Cameroon as a case study. I explore patterns of hunting offtake and intensity within a socioecological system framework, to identify the drivers of hunting and threats to hunted species in both hunting systems. I find clear village level differences in species depletion, as a result of differing geographical characteristics and hunter-level methods and motivations to hunt. I then triangulate estimates of species occupancy obtained from daily hunter diaries, seasonal interviews and camera traps, to better understands the sources of uncertainty when using each monitoring method. Estimates from LEK-informed methods were broadly comparable with camera trap data at the village level, but with species level differences. I explore the use of modern expert elicitation methods as a tool to better understand uncertainty around estimates of species occupancy and density from local people. Gender plays an important predictive role in the type of knowledge held. Further, those predicted to be the most knowledgeable by their peers (i.e. local experts) do not always provide the most robust estimates. Finally, power analysis that account for species detectability reveal that the cost and effort required to ensure power to detect trends in species occupancy over time is often prohibitive. The thesis highlights the value that LEK-informed methods have for providing monitoring data on species hunted for wild meat, and how an improved understanding of LEK-informed data and integration into wildlife population monitoring can result in more ethical and just conservation efforts. However, conservation actors must account for species detectability when designing monitoring programmes and consider whether they have the logistical and financial resources required for effective and sustainable monitoring of trends over time.

Changes in the timings of seasonality as a result of anthropogenic climate change are predicted to occur over the coming decades. While this is expected to have widespread impacts on the dynamics of infectious disease through environmental forcing, empirical data are lacking. Here, we investigated whether seasonality, specifically the timing of spring ice-thaw, affected susceptibility to infection by the emerging pathogenic fungus Batrachochytrium dendrobatidis (Bd) across a montane community of amphibians that are suffering declines and extirpations as a consequence of this infection. We found a robust temporal association between the timing of the spring thaw and Bd infection in two host species, where we show that an early onset of spring forced high prevalences of infection. A third highly susceptible species (the midwife toad, Alytes obstetricans) maintained a high prevalence of infection independent of time of spring thaw. Our data show that perennially overwintering midwife toad larvae may act as a year-round reservoir of infection with variation in time of spring thaw determining the extent to which infection spills over into sympatric species. We used future temperature projections based on global climate models to demonstrate that the timing of spring thaw in this region will advance markedly by the 2050s, indicating that climate change will further force the severity of infection. Our findings on the effect of annual variability on multi-host infection dynamics show that the community-level impact of fungal infectious disease on biodiversity will need to be re-evaluated in the face of climate change.

The trade in wildlife products can represent an important source of income for poor people, but also threaten wildlife locally, regionally and internationally. Bushmeat provides livelihoods for hunters, traders and sellers, protein to rural and urban consumers, and has depleted the populations of many tropical forest species. Management interventions can be targeted towards the consumers or suppliers of wildlife products. There has been a general assumption in the bushmeat literature that the urban trade is driven by consumer demand with hunters simply fulfilling this demand. Using the urban bushmeat trade in the city of Kumasi, Ghana, as a case study, we use a range of datasets to explore the processes driving the urban bushmeat trade. We characterise the nature of supply and demand by explicitly considering three market attributes: resource condition, hunter behaviour, and consumer behaviour. Our results suggest that bushmeat resources around Kumasi are becoming increasingly depleted and are unable to meet demand, that hunters move in and out of the trade independently of price signals generated by the market, and that, for the Kumasi bushmeat system, consumption levels are driven not by consumer choice but by shortfalls in supply and consequent price responses. Together, these results indicate that supply-side processes dominate the urban bushmeat trade in Kumasi. This suggests that future management interventions should focus on changing hunter behaviour, although complementary interventions targeting consumer demand are also likely to be necessary in the long term. Our approach represents a structured and repeatable method to assessing market dynamics in information-poor systems. The findings serve as a caution against assuming that wildlife markets are demand driven, and highlight the value of characterising market dynamics to inform appropriate management.

We previously reported that African (Loxodonta africana) and Asian (Elephas maximus) female elephants in European zoos have shorter adult lifespans than protected conspecifics in range countries. This effect was the cause of greatest concern in Asian elephants, and risk factors within this species included being zoo-born, transferred between zoos, and possibly removed early from the mother. Here, we investigate these risk factors further; assess fecundity and sustainability in European zoos; and propose testable hypotheses as to the causes of these animals’ problems. Although imported wild-born Asian elephants live longer than zoo-born conspecifics, being imported when juvenile or adult appears no more protective than being imported in infancy, suggesting that the benefits of being wild- rather than zoo-born are conferred early in life. Zoo-born Asian neonates are significantly heavier than those born to working animals in range countries, with a possible tendency to be fatter. In zoos, African elephants have tended to be removed from their mothers at older ages than young Asians, and were also transferred between zoos significantly less often: factors that could possibly underlie this species’ lower calf losses and improving adult survivorship in Europe. Both species have low fecundity in European zoos compared to in situ populations, and are not self-sustaining, declining at approximately 10% per annum if reliant on captive-bred females under historically prevailing conditions. Data from other species suggest that stress and/or obesity are parsimonious explanations for the suite of problems seen. We recommend specific screens for testing these hypotheses, and for potentially identifying vulnerable individuals within the extant zoo populations.

1. Abundance estimation is a pervasive goal in ecology. The rate of detection by motion-sensitive camera traps can, in principle, provide information on the abundance of many species of terrestrial vertebrates that are otherwise difficult to survey. The random encounter model (REM, Rowcliffe et al. 2008) provides a means estimating abundance from camera trap rate but requires camera sensitivity to be quantified. 2. Here, we develop a method to estimate the area effectively monitored by cameras, which is one of the most important codeterminants of detection rate. Our method borrows from distance sampling theory, applying detection function models to data on the position (distance and angle relative to the camera) where the animals are first detected. Testing the reliability of this approach through simulation, we find that bias depends on the effective detection angle assumed but was generally low at less than 5% for realistic angles typical of camera traps. 3. We adapted standard detection functions to allow for the possibility of smaller animals passing beneath the field of view close to the camera, resulting in reduced detection probability within that zone. Using a further simulation to test this approach, we find that detection distance can be estimated with little or no bias if detection probability is certain for at least some distance from the camera. 4. Applying this method to a 1-year camera trapping data set from Barro Colorado Island, Panama, we show that effective detection distance is related strongly positively to species body mass and weakly negatively to species average speed of movement. There was also a strong seasonal effect, with shorter detection distance during the wet season. Effective detection angle is related more weakly to species body mass, and again strongly to season, with a wider angle in the wet season. 5. This method represents an important step towards practical application of the REM, including abundance estimation for relatively small (

Societal, economic and scientific interests in knowing where biodiversity is, how it is faring and what can be done to efficiently mitigate further biodiversity loss and the associated loss of ecosystem services are at an all-time high. So far, however, biodiversity monitoring has primarily focused on structural and compositional features of ecosystems despite growing evidence that ecosystem functions are key to elucidating the mechanisms through which biological diversity generates services to humanity. This monitoring gap can be traced to the current lack of consensus on what exactly ecosystem functions are and how to track them at scales beyond the site level. This contribution aims to advance the development of a global biodiversity monitoring strategy by proposing the adoption of a set of definitions and a typology for ecosystem functions, and reviewing current opportunities and potential limitations for satellite remote sensing technology to support the monitoring of ecosystem functions worldwide. By clearly defining ecosystem processes, functions and services and their interrelationships, we provide a framework to improve communication between ecologists, land and marine managers, remote sensing specialists and policy makers, thereby addressing a major barrier in the field.

Organisms are frequently faced with uncertainty regarding how best to exploit vital resources, and may benefit from collecting information about their distribution through space and time. However, the ways in which competition over resources might systematically facilitate or constrain an individual's ability to use information has been largely overlooked. In this thesis, I develop a conceptual framework for considering how the distribution of limited resources might underpin interdependencies between competition and information use. I focus on the evolutionary ecology of relationships between social dominance and social information use. I begin with an observational study of wild chacma baboons (Papio ursinus) suggesting that, when resources can be monopolised, individuals with low competitive ability are limited in their ability to use social information. Building on these findings, I then develop a general model exploring selection on social information use in a competitive context across three axes of 'resource ecology' (scarcity, depletion rate, monopolisability). This study makes predictions regarding the resource conditions under which competitive ability might constrain social information use, and the potential importance of social information use in the evolution of social dominance. I go on to test these predictions in chacma baboons using a field experiment. This experiment also explores whether the predictability of resource distribution might facilitate the decoupling of social information use from the competitive context in which it was collected. Taken together, these findings provide general insights into the combinations of ecological conditions and behavioural mechanisms that should underpin the benefits of social dominance. I end by building a simple population matrix model to study social dominance using an eco-evolutionary approach, in which feedback loops between ecological and evolutionary processes are considered. By modelling relationships between dominance rank and survival, reproduction, inheritance, and development, I am able to derive estimates of long-term fitness associated with dominance. Using these estimates, I generate predictions regarding how dominance hierarchies should impact the dynamics of group stability, viability, and fission.

The deployment of camera traps, which automatically take pictures of wild animals moving in front of them, is now routinely used to survey terrestrial mammal communities worldwide. The resulting photographic data are used to answer questions relating to the richness and structure of mammal communities, the density of their component species, and how the latter might interact. This thesis fills key methodological gaps in how these questions are addressed. My first data chapter assesses how the exact placement of camera traps on natural game trails influences the characterisation of community richness, composition and structure in an east African savannah landscape. I find that a trail-based placement strategy leads to more species being detected more rapidly relative to a random one, and increases capture rates for carnivore species in particular. In contrast, I reveal in Chapter 3 how a non-random camera trap placement strategy can bias estimates of absolute density for an unmarked large carnivore, the lion Panthera leo, obtained using an ideal gas model approach. Chapter 4 considers spatiotemporal patterns in camera trap data, and to what extent they can be used to infer on the kleptoparasitic and predatory tendencies of spotted hyenas and lions, respectively, in Tanzania’s Ruaha landscape. I find patterns to be generally uninformative, and so, in Chapter 5, turn to another method of collecting spatiotemporal data, Global Positioning Satellite telemetry, to make inferences on the spatial response of elk to wolves in Yellowstone National park. I find no evidence for a significant spatial avoidance of wolves by elk, suggesting that species interactions may not always lead to measurable spatial patterns. Nevertheless, in my final chapter, I use an individual-based modelling framework to simulate different types of prey responses to predator movement in the absence of confounding factors, and find that a huge amount of camera trapping effort would be required to distinguish between them. This thesis highlights how camera trap placement can affect the description of mammal communities and the estimation of species density. It also shows that we cannot rely solely on spatiotemporal patterns derived from camera traps to make inferences on complex interactive processes.