Effect of ecological and anthropogenic factors on grouping patterns in African lions across Kenya.

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.

Deep learning enables satellite-based monitoring of large populations of terrestrial mammals across heterogeneous landscape.

New satellite remote sensing and machine learning techniques offer untapped possibilities to monitor global biodiversity with unprecedented speed and precision. These efficiencies promise to reveal novel ecological insights at spatial scales which are germane to the management of populations and entire ecosystems. Here, we present a robust transferable deep learning pipeline to automatically locate and count large herds of migratory ungulates (wildebeest and zebra) in the Serengeti-Mara ecosystem using fine-resolution (38-50 cm) satellite imagery. The results achieve accurate detection of nearly 500,000 individuals across thousands of square kilometers and multiple habitat types, with an overall F1-score of 84.75% (Precision: 87.85%, Recall: 81.86%). This research demonstrates the capability of satellite remote sensing and machine learning techniques to automatically and accurately count very large populations of terrestrial mammals across a highly heterogeneous landscape. We also discuss the potential for satellite-derived species detections to advance basic understanding of animal behavior and ecology.

Lions in a coexistence landscape: Repurposing a traditional field technique to monitor an elusive carnivore.

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.

Wildlife roadkill in the Tsavo Ecosystem, Kenya: identifying hotspots, potential drivers, and affected species.

Roadkill is one of the highest causes of wildlife mortality and is of global conservation concern. Most roadkill studies have focused on wildlife in developed countries such as the United States of America and temperate biomes, but there are limited data for the impacts of roads on wildlife in the African tropics, where road infrastructure development is projected to grow rapidly in natural environments and conservation areas. The Tsavo Conservation Area is an important biodiversity hotspot in eastern Kenya and is bisected by a major highway and railways that connect the port of Mombasa to the interior. Along this infrastructure corridor, roadkill was recorded for 164 days over an 11-year period (2007-2018). In total, 1,436 roadkill were recorded from 13,008 km driven of a 164.42 km Nairobi-Mombasa road representing 0.11 collisions per kilometer. The majority of roadkill were small to medium sized mammals (<15kg) (53%; n = 756), whereas birds comprised 32% (n = 460), reptiles 10% (n = 143), with the remaining 5% (n = 77) being large mammals (>15kg). Of the 460 birds recorded, 264 were identifiable represented by 62 species. All large mammals comprising 10 species were identified, including the African elephant, Loxodonta africana and the endangered African wild dog, Lycaon pictus. Thirteen species of small mammal were also identified dominated by Kirk's dik-dik (Madoqua kirkii). Reptiles were represented by 11 species which were identified to the species level. Roadkill hotspots were identified using a kernel density method. The spatial distribution of roadkill was associated with adjacent shrub vegetation and proximity to permanent and seasonal rivers, and differences in seasonality and habitats were observed. Roadkill was lowest on road sections that traversed settled areas as opposed to roads adjacent to the protected areas. The results demonstrate that roadkill for two of the taxonomic groups - mammals and birds - appear high with numerous species detected in the Tsavo Conservation Area. These results can be used to focus efforts to reduce wildlife mortality by guiding future mitigation efforts.

Using Poaching Levels and Elephant Distribution to Assess the Conservation Efficacy of Private, Communal and Government Land in Northern Kenya.

Efforts to curb elephant poaching have focused on reducing demand, confiscating ivory and boosting security patrols in elephant range. Where land is under multiple uses and ownership, determining the local poaching dynamics is important for identifying successful conservation models. Using 2,403 verified elephant, Loxodonta africana, mortality records collected from 2002 to 2012 and the results of aerial total counts of elephants conducted in 2002, 2008 and 2012 for the Laikipia-Samburu ecosystem of northern Kenya, we sought to determine the influence of land ownership and use on diurnal elephant distribution and on poaching levels. We show that the annual proportions of illegally killed (i.e., poached) elephants increased over the 11 years of the study, peaking at 70% of all recorded deaths in 2012. The type of land use was more strongly related to levels of poaching than was the type of ownership. Private ranches, comprising only 13% of land area, hosted almost half of the elephant population and had significantly lower levels of poaching than other land use types except for the officially designated national reserves (covering only 1.6% of elephant range in the ecosystem). Communal grazing lands hosted significantly fewer elephants than expected, but community areas set aside for wildlife demonstrated significantly higher numbers of elephants and lower illegal killing levels relative to non-designated community lands. While private lands had lower illegal killing levels than community conservancies, the success of the latter relative to other community-held lands shows the importance of this model of land use for conservation. This work highlights the relationship between illegal killing and various land ownership and use models, which can help focus anti-poaching activities.

Elephant movement closely tracks precipitation-driven vegetation dynamics in a Kenyan forest-savanna landscape.

BACKGROUND: This study investigates the ranging behavior of elephants in relation to precipitation-driven dynamics of vegetation. Movement data were acquired for five bachelors and five female family herds during three years in the Marsabit protected area in Kenya and changes in vegetation were mapped using MODIS normalized difference vegetation index time series (NDVI). In the study area, elevations of 650 to 1100 m.a.s.l experience two growth periods per year, while above 1100 m.a.s.l. growth periods last a year or longer. RESULTS: We find that elephants respond quickly to changes in forage and water availability, making migrations in response to both large and small rainfall events. The elevational migration of individual elephants closely matched the patterns of greening and senescing of vegetation in their home range. Elephants occupied lower elevations when vegetation activity was high, whereas they retreated to the evergreen forest at higher elevations while vegetation senesced. Elephant home ranges decreased in size, and overlapped less with increasing elevation. CONCLUSIONS: A recent hypothesis that ungulate migrations in savannas result from countervailing seasonally driven rainfall and fertility gradients is demonstrated, and extended to shorter-distance migrations. In other words, the trade-off between the poor forage quality and accessibility in the forest with its year-round water sources on the one hand and the higher quality forage in the low-elevation scrubland with its seasonal availability of water on the other hand, drives the relatively short migrations (the two main corridors are 20 and 90 km) of the elephants. In addition, increased intra-specific competition appears to influence the animals' habitat use during the dry season indicating that the human encroachment on the forest is affecting the elephant population.