Biology subjects

Bennitt, E.

Publications and source records attributed to Bennitt, E..

2 recordsLinked to original sources

bioRxiv2026

Simple soil eDNA sampling reveals terrestrial mammal diversity in the Central Kalahari and highlights waterholes as sampling hotspots

Remote and vast ecosystems present a challenge for biodiversity monitoring. The Central Kalahari Game Reserve in Botswana is one such ecosystem spanning 52,800 km2, a mosaic of fossilized rivers, clay pans, semi-arid sand dunes, scrub, and woodland. It is one of the last remaining untouched wildernesses in the world and hosts unique biodiversity, including populations of threatened mammals. Due to its extreme arid environment, size, and inaccessibility, surveying biodiversity across the reserve is both logistically and technically difficult. Here we demonstrate that a low-effort approach of sampling soil across the reserve is an efficient way to rapidly assess the terrestrial mammal biodiversity using eDNA metabarcoding. We found that eDNA from soil near waterholes performed better at capturing local biodiversity than soil from roads. eDNA metabarcoding detected 38 mammal species, 15 bird species and two amphibians and a simultaneously conducted camera trapping study detected 29 mammal species. eDNA was particularly powerful for detecting small-bodied taxa, including murids, mongooses and bats, which were largely missed by camera traps, while camera trapping was aimed at and performed well for detecting felids. Mammal species that had a higher activity nearby eDNA sampling points (i.e., a higher number of camera trapping recordings nearby) had a higher probability of being detected via eDNA. We propose that simple soil collection for eDNA metabarcoding, particularly close to animal congregation points such as savanna waterholes, offers a practical, scalable and cost-effective strategy for DNA-based biomonitoring in large, remote areas such those in Southern Africa.

ecology↗

bioRxiv2025

Combining artificial intelligence and local ecological knowledge to document the largest ever-counted Cape buffalo mega-herd

Large aggregations of wild mammals are declining globally, sometimes before they can be scientifically documented and their ecological value understood, although non-scientists may be aware of these phenomena. Video recording of wildlife by non-academics is becoming more frequent with increasing activities of humans in natural habitats. This opportunistically-collected material can document rare or ecologically-important events, such as large aggregations, and thus provide potentially valuable data for ecologists and conservationists. We used footage of a large herd of Cape buffalo recorded by a wildlife film producer in the Mababe Depression, northern Botswana, and applied automated detection and tracking techniques to count individuals as they moved across the video frame. To complement this demographic snapshot, we accessed local ecological knowledge from stakeholders to provide contextual information for a more complete understanding of the ecosystem processes potentially driving population movement and trends. Manual review of the automated count resulted in a minimum group size of 3676 buffalo and a total estimated herd size of 4131 (range 3828-4446), which matched herd size estimates provided by local stakeholders. To our knowledge, this is the largest documented group of Cape buffalo, which we identify as a mega-herd and recommend research into the costs, benefits and ecological consequences of forming such large groups. This study represents an opportunistic collaboration among wildlife filmmakers, computer scientists, lay experts and ecologists, and highlights the value of combining contributions from different fields to generate information that can be used in conservation practice.

ecology↗