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Animal activity patterns vary on a daily, circalunar and seasonal scale in response to abiotic (e.g. light availability and temperature) and biotic factors (e.g. predation and competition). In the presence of humans and their livestock, carnivores, for example, have been found to become more nocturnal. The aim of this paper is to compare daily, circalunar and seasonal activity patterns of cheetah Acinonyx jubatus in the western Kalahari of Botswana between areas where there is no livestock present (i.e. game farms with a relatively low risk of cheetah mortality) and areas where livestock is present (i.e. cattle farms with a higher risk of cheetah mortality). Using two years of camera trap data, we recorded 88% of cheetah observations on game farms and 12% on cattle farms. Our results showed that cheetahs were more nocturnal in the absence of cattle and more crepuscular on cattle farms compared to game farms. Overall, cheetah activity on cattle farms showed a peak in activity after inferred cattle activity and before human activity during the day, specifically during the dry season. We recommend management strategies on a local scale such as temporal zoning of grazing activities during the different seasons or keeping cattle in an enclosure at night. This study sheds new light on our understanding of the impact of land use on free-ranging carnivores in the face of livestock expansion on the African continent.

Social carnivores frequently live in fission–fusion societies, where individuals that share a common territory or home range may be found alone, in subgroups, or altogether. Absolute group size and subgroup size is expected to vary according to resource distribution, but for species that are susceptible to anthropogenic pressures, other factors may be important drivers. African lions (Panthera leo) are the only truly social felid and lion prides are characterized by fission–fusion dynamics with social groups frequently splitting and reforming, and subgroup membership can change continuously and frequently. The number of individuals in a group can be reflective of social, ecological, and anthropogenic conditions. This dynamic behavior makes understanding lion grouping patterns crucial for tailoring conservation measures. The evolution of group living in lions has been the topic of numerous studies, and we drew on these to formulate hypotheses relating to group size and subgroup size variation. Based on data collected from 199 lion groups across eight sites in Kenya, we found that group sizes were smaller when lions were closer to human settlements, suggesting that edge effects are impacting lions at a national scale. Smaller groups were also more likely when they were far from water, and were associated with very low and very high levels of non-tree vegetation. We found significant differences between the study sites, with the Maasai Mara having the largest groups (mean ± SD = 7.7 ± 4.7, range = 1–19), and Amboseli conservation area the smallest (4.3 ± 3.5, range = 1–14). While long-term studies within a single site are well suited to thoroughly differentiate between absolute group size and subgroup size, our study provides unique insight into the correlates of grouping patterns in a vulnerable species at a national scale.

Conserving large carnivores requires protecting landscape spaces that encompass all spatiotemporal scales of their movement. Large carnivores normally roam widely, but habitat loss and fragmentation can constrain their movement in ways that restrict access to resources and increase encounters with humans and potential conflict. Facilitating carnivore population coexistence with humans across landscapes requires conservation plans informed by patterns of carnivore space use, particularly at the human–wildlife interface.We sought to understand lion space use in Laikipia, Kenya. We conducted a path-selection function analysis using GPS collar data from 16 lions to assess patterns of space use across a range of spatial scales (sedentary to home range expanses; 0, 12.5, 25 and 50 km) and temporal scales (day, dusk, night and dawn). Path-selection results were then incorporated into space use maps.We found that most landscape features influenced path-selection at the broadest spatial scale (50 km), representative of home range-wide movement, thereby demonstrating a landscape-wide human impact on lion space use. We also detected sub-diurnal variation in lion path-selection which revealed limited space use during daylight hours and increased space use overnight.Our results highlight that optimal support for human–lion coexistence should be temporally adaptive at sub-diurnal scales. Furthermore, spatial approaches to lion conservation may be better generalized at broad spatial scales so that land management plans can account for home range patterns in lion space use.

Coexistence between humans and carnivores enables the persistence or recovery of wildlife populations. In 2018, we conducted a survey in Kenya’s Greater Mara Ecosystem to explore community attitudes toward the reestablishment of African wild dogs (Lycaon pictus) following their regional disappearance. Analyzing data from 60 households, we found that proximity to protected areas, land lease to conservancies, and risk perception significantly influenced people’s tolerance of African wild dogs, as revealed by Generalized Linear Models. Notably, there were no instances of human attacks and 78% of respondents had not experienced livestock predation, indicating positive coexistence. Among those perceiving a risk, 37 out of 46 recognized livestock predation only occurred when livestock were unguarded during the day. These findings highlight the potential for coexistence and species recovery in this mixed-use landscape, emphasizing the importance of effective conservation education, livestock management, and economic incentives.

Aim: Assessing the distribution and persistence of species across their range is a crucial component of wildlife conservation. It demands data at adequate spatial scales and over extended periods of time, which may only be obtained through collaborative efforts, and the development of methods that integrate heterogeneous datasets. We aimed to combine existing data on large carnivores to evaluate population dynamics and improve knowledge on their distribution nationwide. Location: Botswana Methods: Between 2010 – 2016, we collated data on African wild dog, cheetah, leopard, brown and spotted hyaena, and lion gathered with different survey methods by independent researchers across Botswana. We used a multi-species, multi-method dynamic occupancy model to analyse factors influencing occupancy, persistence, and colonisation, while accounting for imperfect detection. Lastly, we used the gained knowledge to predict the probability of occurrence of each species countrywide. Results: Wildlife areas and communal rangelands had similar occupancy probabilities for most species. Large carnivore occupancy was low in commercial farming areas and where livestock density was high, except for brown hyaena. Lion occupancy was negatively associated with human density; lion and spotted hyena occupancy was high where rainfall was high, while the opposite applied to brown hyaena. Lion and leopard occupancy remained constant countrywide over the study period. African wild dog and cheetah occupancy declined over time in the south and north, respectively, whereas both hyaena species expanded their ranges. Countrywide predictions identified the highest occupancy for leopards and lowest for the two hyaena species. Main Conclusions: We highlight the necessity of data sharing and propose a generalisable analytical method that addresses the challenges of heterogeneous data common in ecology. Our approach, which enables a comprehensive multi-species assessment at large spatial and temporal scales, Aim: Assessing the distribution and persistence of species across their range is a crucial component of wildlife conservation. It demands data at adequate spatial scales and over extended periods of time, which may only be obtained through collaborative efforts, and the development of methods that integrate heterogeneous datasets. We aimed to combine existing data on large carnivores to evaluate population dynamics and improve knowledge on their distribution nationwide. Location: Botswana Methods: Between 2010 – 2016, we collated data on African wild dog, cheetah, leopard, brown and spotted hyaena, and lion gathered with different survey methods by independent researchers across Botswana. We used a multi-species, multi-method dynamic occupancy model to analyse factors influencing occupancy, persistence, and colonisation, while accounting for imperfect detection. Lastly, we used the gained knowledge to predict the probability of occurrence of each species countrywide. Results: Wildlife areas and communal rangelands had similar occupancy probabilities for most species. Large carnivore occupancy was low in commercial farming areas and where livestock density was high, except for brown hyaena. Lion occupancy was negatively associated with human density; lion and spotted hyena occupancy was high where rainfall was high, while the opposite applied to brown hyaena. Lion and leopard occupancy remained constant countrywide over the study period. African wild dog and cheetah occupancy declined over time in the south and north, respectively, whereas both hyaena species expanded their ranges. Countrywide predictions identified the highest occupancy for leopards and lowest for the two hyaena species. Main Conclusions: We highlight the necessity of data sharing and propose a generalisable analytical method that addresses the challenges of heterogeneous data common in ecology. Our approach, which enables a comprehensive multi-species assessment at large spatial and temporal scales

This dataset contains key characteristics about the data described in the Data Descriptor Landscape Dynamics (landDX) an open-access spatial-temporal database for the Kenya-Tanzania borderlands.

Throughout Africa, lions are thought to have experienced dramatic population decline and range contraction. The greatest declines are likely occurring in human-dominated landscapes where reliably estimating lion populations is particularly challenging. By adapting a method that has thus far only been applied to animals that are habituated to vehicles, we estimate lion density in two community areas in Kenya's South Rift, located more than 100 km from the nearest protected area (PA). More specifically, we conducted an 89-day survey using unstructured spatial sampling coupled with playbacks, a commonly used field technique, and estimated lion density using spatial capture-recapture (SCR) models. Our estimated density of 5.9 lions over the age of 1 year per 100 km2 compares favorably with many PAs and suggests that this is a key lion population that could be crucial for connectivity across the wider landscape. We discuss the possible mechanisms supporting this density and demonstrate how rigorous field methods combined with robust analyses can produce reliable population estimates within human-dominated landscapes.