Predicting potential distributions of large carnivores in Kenya: An occupancy study to guide conservation

Abstract

Aim Species‐specific conservation strategies are frequently formulated based on species distribution maps, which are challenging to produce, especially at large spatial scales. Our aim was to use a novel empirical approach to predict the national distribution for all six large carnivore species found in Kenya to guide conservation and management decisions by identifying knowledge and conservation gaps. Location Kenya. Methods We collected data on carnivore presence and absence through questionnaire and sightings‐based surveys and analysed the combined data set using single‐season false‐positive occupancy models, which account for imperfect detections and false positives. To predict potential distributions and inform conservation strategies, we used the occupancy outputs to make predictions for unsampled areas and create occupancy‐based distribution maps where ψ > 0.50, to (1) quantify differences with IUCN Red List range maps, (2) quantify overlap with wildlife areas and (3) identify areas of high carnivore richness. Results Large carnivore occupancy was associated with land conversion, habitat and prey availability. Our results suggest that all six species are widely distributed across Kenya and reveal substantial differences to distribution maps compiled by the IUCN Red List. More specifically, our occupancy‐based distribution maps predict much larger distribution for African wild dog (5.09X), lion (4.77X) and leopard (1.46X), similar distribution for cheetah, and smaller distribution for spotted hyaena (0.84X) and striped hyaena (0.65X). For all large carnivores, the vast majority (~80%) of their predicted distribution falls outside wildlife areas and northern Kenya is predicted to have the highest large carnivore richness. Main conclusions Our results are encouraging as large carnivores may be widely distributed across Kenya, in some cases potentially more so than previously acknowledged. However, much of this range lies outside wildlife areas and represent areas of concern both for conservation and human livelihoods illustrating the challenges of conserving large carnivores across their range.

Historical and current distribution ranges of the Asiatic black bear (Ursus thibetanus)

“…Conservation strategies, often reliant on distribution maps, are crafted for specific species. However, the creation of these maps, especially on a large spatial scale, presents substantial challenges, as highlighted by 41 . This underscores the pressing need for conservation measures aimed at safeguarding and preserving these species for the future.…”

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

“…Kenya's lion populations face a myriad of threats such as conflicts with local communities, habitat loss, loss of wild prey (Ogutu et al., 2016 ), and disease (Kenya Wildlife Service, 2016 ). Despite these threats, lions are predicted to be widely distributed across the country (Broekhuis et al., 2022 ), with the largest population found in the Maasai Mara, followed by Tsavo, Laikipia, and Amboseli, with several other populations of less than 100 individuals (Elliot et al., 2021 ).…”

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

“…In addition, a wet season sampling session is recommended to gain an understanding of potential seasonal differences also noting that this is a multiple‐use landscape. At a landscape level, it is possible that lions are distributed across southern Kenya from the Maasai Mara to the Tsavo ecosystem (Broekhuis et al, in review). Population monitoring across this area is recommended and could be achieved using the methods presented in this paper, perhaps within a combined SCR approach (Gopalaswamy, Royle, Delampady, et al, 2012) that makes use of high‐quality camera traps, unstructured sampling to collect noninvasive DNA via fecal samples (e.g., Bischof, Milleret, et al, 2020), or by using sign‐based occupancy surveys (e.g., Karanth et al, 2011).…”