Daily activity schedules and time budgets reveal how animals cope with changing environmental conditions in securing food and evading enemies. Theory suggests that animals in populations limited by food availability should be energy maximizers in their foraging time allocation, while those regulated by predation should minimize their mobile activity levels. We compared daily and seasonal variation in activity states among three species of grazing ungulates coexisting in the same region of Kruger National Park, South Africa, and for one of these species between regions differing in rainfall. These grazers differed in body size and digestive physiology, potentially affecting their activity patterns. Hourly movement rates recorded by GPS telemetry were partitioned among activity states by applying independent mixture models. All three species showed activity peaks during the early morning and late afternoon, while resting prevailed pre-dawn as well as through midday. African buffalo showed the strongest diel variation in activity and greatest depression of midday activity, consistent with their large body size. Buffalo maintained similar levels of activity through the day and night, while zebra and sable antelope showed higher levels of diurnal than nocturnal activity. During the late dry season, zebra and coexisting sable, but not buffalo, showed elevated foraging and total mobile activity. Zebra devoted more time to foraging than both ruminants, consistent with greater food intake requirements for hindgut digestion. Sable antelope inhabiting the region with higher rainfall showed similar activity levels to the sable herd in the drier area, but slower rates of movement while foraging and travelling and less elevation in foraging time towards the end of the dry season. Observed patterns indicated subtly changing interplay among different constraints bearing on activity patterns over the diel and seasonal cycles, especially those related to digestive physiology. Simplistic concepts of energy maximization or time minimization were not supported. Additional time is also required to digestively process the food consumed, especially for ruminants reliant upon remastication to facilitate digestive efficiency (Owen

Air temperatures have increased globally over the past decades, while rainfall changes have been more variable, but are taking place. In South Africa, substantial climate-related impacts are predicted, and protected area management agencies will need to respond actively to impacts. It is critical for management agencies to understand the way in which climate is changing locally to predict impacts and respond appropriately. Here, for the first time, we quantify observable changes in temperature and rainfall in South African national parks over the past five to ten decades. Our results show significant increases in temperatures in most parks, with increases being most rapid in the arid regions of the country. Increases in the frequency of extreme high temperature events were also most pronounced in these regions. These results are consistent with other climate studies conducted in these areas. Similar increases were identified for both minimum and maximum temperatures, though absolute minimum temperatures increased at greater rates than absolute maxima. Overall, rainfall trends were less obvious, but a decrease in rainfall was observed for the southern Cape (in three parks), and an increase was detected in one park. The observed temperature changes over the last 20-50 years have in several instances already reached those predicted for near future scenarios (2035), indicating that change scenarios are conservative. These results provide individual parks with evidence-based direction for managing impacts under current and projected changes in local climate. They also provide the management agency with sub-regional information to tailor policy and impact monitoring. Importantly, our results highlight the critical role that individual weather stations play in informing local land management and the concerns for parks that have no local information on changes in climate.

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Human activities in the oceans increase the extinction risk of marine megafauna. Interventions require an understanding of movement patterns and the spatiotemporal overlap with threats. We analysed the movement patterns of 33 white sharks (Carcharodon carcharias) satellite-tagged in South Africa between 2012 and 2014 to investigate the influence of size, sex and season on movement patterns and the spatial and temporal overlap with longline and gillnet fisheries and marine protected areas (MPAs). We used a hidden Markov model to identify ‘resident’ and ‘transient’ movement states and investigate the effect of covariates on the transition probabilities between states. A model with sex, total length and season had the most support. Tagged sharks were more likely to be in a resident state near the coast and a transient state away from the coast, while the probability of finding a shark in the transient state increased with size. White sharks moved across vast areas of the southwest Indian Ocean, emphasising the need for a regional management plan. White sharks overlapped with longline and gillnet fisheries within 25% of South Africa’s Exclusive Economic Zone and spent 15% of their time exposed to these fisheries during the study period. The demersal shark longline fishery had the highest relative spatial and temporal overlap, followed by the pelagic longline fishery and the KwaZulu-Natal (KZN) shark nets and drumlines. However, the KZN shark nets and drumlines reported the highest white shark catches, emphasising the need to combine shark movement and fishing effort with reliable catch records to assess risks to shark populations accurately. White shark exposure to shark nets and drumlines, by movement state, sex and maturity status, corresponded with the catch composition of the fishery, providing support for a meaningful exposure risk estimate. White sharks spent significantly more time in MPAs than expected by chance, likely due to increased prey abundance or less disturbance, suggesting that MPAs can benefit large, mobile marine megafauna. Conservation of white sharks in Southern Africa can be improved by implementing non-lethal solutions to beach safety, increasing the observer coverage in fisheries, and continued monitoring of movement patterns and existing and emerging threats.

Context Direct observations of animals are the most reliable way to define their behavioural characteristics; however, to obtain these observations is costly and often logistically challenging. GPS tracking allows finer-scale interpretation of animal responses by measuring movement patterns; however, the true behaviour of the animal during the period of observation is seldom known. Aims The aim of our research was to draw behavioural inferences for a lioness with a hidden Markov model and to validate the predicted latent-state sequence with field observations of the lion pride. Methods We used hidden Markov models to model the movement of a lioness in the Kruger National Park, South Africa. A three-state log-normal model was selected as the most suitable model. The model outputs are related to collected data by using an observational model, such as, for example, a distribution for the average movement rate and/or direction of movement that depends on the underlying model states that are taken to represent behavioural states of the animal. These inferred behavioural states are validated against direct observation of the pride’s behaviour. Key results Average movement rate provided a useful alternative for the application of hidden Markov models to irregularly spaced GPS locations. The movement model predicted resting as the dominant activity throughout the day, with a peak in the afternoon. The local-movement state occurred consistently throughout the day, with a decreased proportion during the afternoon, when more resting takes place, and an increase towards the early evening. The relocating state had three peaks, namely, during mid-morning, early evening and about midnight. Because of the differences in timing of the direct observations and the GPS locations, we had to compare point observations of the true behaviour with an interval prediction of the modelled behavioural state. In 75% of the cases, the model-predicted behaviour and the field-observed behaviour overlapped. Conclusions Our data suggest that the hidden Markov modelling approach is successful at predicting a realistic behaviour of lions on the basis of the GPS location coordinates and the average movement rate between locations. The present study provided a unique opportunity to uncover the hidden states and compare the true behaviour with the inferred behaviour from the predicted state sequence. Implications Our results illustrated the potential of using hidden Markov models with movement rate as an input to understand carnivore behavioural patterns that could inform conservation management practices.