Status and behavioural ecology of Sengis in the Boni-Dodori and Arabuko-Sokoke forests, Kenya, determined by camera traps

The biodiversity of northern coastal Kenya, east of the Tana River, is poorlyunderstood because security problems and poor infrastructure have discouraged accessto the area. However, the wooded areas in the region have great potential forharbouring endemic and rare species, including sengis or elephant-shrews (orderMacroscelidea), especially giant sengis in the genus Rhynchocyon. Based on extensivecamera-trap surveys of the Boni-Dodori forest, east of the Tana River near theSomalia border, and the Arabuko-Sokoke forest west of the Tana River, the goldenrumpedsengi Rhynchocyon chrysopygus appears to be limited to the Arabuko-Sokokearea, while the giant sengi in the Boni-Dodori forest is different. The Boni-Dodoriforest, the largest Kenyan coastal forest, with a potential forest and thicket area of atleast 3000 km2 is likely to hold a significant number of Rhynchocyon, making it veryimportant to sengi conservation. The study generated over 2700 images of giant sengiand 32 000 camera-trap images of soft-furred sengi in a total surveyed area ofapproximately 300 km2 providing the first detailed 24-hour behaviour data for thespecies. The circadian patterns have confirmed R. chrysopygus and Boni Rhynchocyonto be strictly diurnal while the soft-furred sengi were mostly nocturnal. Occupancy forRhynchocyon was over 80 percent for both the Boni forest thicket and Arabuko-Sokoke Cynometra forest thicket. Occupancy and trapping rates for the soft-furred sengi were significantly higher for the Arabuko-Sokoke forest than the Boni-Dodori forest. It was not possible in the camera trap images to reliably differentiate between the two soft-furred sengi species, four-toed sengi Petrodromus tetradactylus and rufous sengi Elephantulus rufescens, known to occur in the area.Keywords: Macroscelidea, elephant-shrew, Rhynchocyon, abundance, distribution,activity patter

Abundance, distribution, habitat, activity and conservation of Sokoke bushy-tailed mongoose Bdeogale omnivora in central and north coast forests of Kenya

The Sokoke dog or bushy-tailed mongoose Bdeogale omnivora is poorly known and considered to be endemic to the East African coastal forests. Systematic camera trap surveys, comprising 9229 camera trap days on grids at six study sites, were used to determine the distribution and relative abundance of the Sokoke bushy-tailed mongoose in the two largest Kenyan coastal forests: Boni-Dodori Forest Complex (ca. 4000 km²); and Arabuko-Sokoke Forest Reserve (416 km²). This species was captured in all surveyed forests with significantly more detections in Brachystegia woodland habitat (ca. 71 km2) of Arabuko-Sokoke and the Boni forest sectors (ca. 2000 km2) of the Boni-Dodori Forest Complex. Boni-Dodori Forest Complex, with an estimated occupancy of over 60% for this species, holds a significant population. The study generated over 1000 images of the Sokoke bushy-tailed mongoose in a total surveyed area of approximately 500 km2 providing the first 24-hour activity data for the species. The circadian patterns confirm this species to be strictly nocturnal. This study strongly recommends that its Red List status remains ‘Vulnerable’. The few remaining coastal forests continue to face human pressure. Recent proposals to find and extract hydrocarbons from under the Arabuko-Sokoke Forest, and the planned major development close to Boni-Dodori Forest Complex, raise serious conservation concerns for this exceptionally biodiverse ecosystem.Keywords: Arabuko-Sokoke forest, Boni forest, Dodori forest, camera trap, status, Bdeogale omnivor

Laying low: Rugged lowland rainforest preferred by feral cats in the Australian Wet Tropics

Invasive mesopredators are responsible for the decline of many species of native mammals worldwide. Feral cats have been causally linked to multiple extinctions of Australian mammals since European colonization. While feral cats are found throughout Australia, most research has been undertaken in arid habitats, thus there is a limited understanding of feral cat distribution, abundance, and ecology in Australian tropical rainforests. We carried out camera-trapping surveys at 108 locations across seven study sites, spanning 200 km in the Australian Wet Tropics. Single-species occupancy analysis was implemented to investigate how environmental factors influence feral cat distribution. Feral cats were detected at a rate of 5.09 photographs/100 days, 11 times higher than previously recorded in the Australian Wet Tropics. The main environmental factors influencing feral cat occupancy were a positive association with terrain ruggedness, a negative association with elevation, and a higher affinity for rainforest than eucalypt forest. These findings were consistent with other studies on feral cat ecology but differed from similar surveys in Australia. Increasingly harsh and consistently wet weather conditions at higher elevations, and improved shelter in topographically complex habitats may drive cat preference for lowland rainforest. Feral cats were positively associated with roads, supporting the theory that roads facilitate access and colonization of feral cats within more remote parts of the rainforest. Higher elevation rainforests with no roads could act as refugia for native prey species within the critical weight range. Regular monitoring of existing roads should be implemented to monitor feral cats, and new linear infrastructure should be limited to prevent encroachment into these areas. This is pertinent as climate change modeling suggests that habitats at higher elevations will become similar to lower elevations, potentially making the environment more suitable for feral cat populations

Leopard density and the ecological and anthropogenic factors influencing density in a mixed-use landscape in the Western Cape, South Africa

Large carnivores face numerous threats, including habitat loss and fragmentation, direct killing, and prey depletion, leading to significant global range and population declines. Despite such threats, leopards (Panthera pardus) persist outside protected areas throughout most of their range, occupying diverse habitat types and land uses, including peri-urban and rural areas. Understanding of leopard population dynamics in mixed-use landscapes is limited, especially in South Africa, where the majority of leopard research has focused on protected areas. We use spatially explicit capture-recapture models to estimate leopard density across a mixed-use landscape of protected areas, farmland, and urban areas in the Overberg region of the Western Cape, South Africa. Data from 86 paired camera stations provided 221 independent captures of 25 leopards at 50 camera trap stations with a population density estimate of 0.64 leopards per 100 km2 (95% CI: 0.55–0.73). Elevation, terrain ruggedness, and vegetation productivity were important drivers of leopard density in the landscape, being highest on elevated remnants of natural land outside of protected areas. These results are similar to previous research findings in other parts of the Western Cape, where high-lying natural vegetation was shown to serve as both a refuge and a corridor for leopard movement in otherwise transformed landscapes. Given the low leopard density and the prevalence of transformed land intermixed with patches of more suitable leopard habitat, prioritising and preserving connectivity for leopards is vital in this shared landscape. Ecological corridors should be developed in partnership with private landowners through an inclusive and multifaceted conservation strategy which also incorporates monitoring of and rapid mitigation of emerging threats to leopards

Africa's forgotten forests: the conservation value of Kenya's Northern coastal forests for large mammals

There are two PFS for this article, one is the original article and the other is an Erratum specifying the errors in the original article.In comparison to other ecosystems in east Africa, the biodiversity of the coastal forests of Kenya’s northern coastline is poorly documented, even in the case of large terrestrial mammals. In response to this, we undertook a systematic survey of the Boni-Dodori forests using four camera trap grids with camera spacing of 2 km covering 300 km2 over 7020 camera trap days. We recorded 37 mammal species and derived camera trap rates and estimated occupancy for 31 medium-to-large terrestrial species, some of which represent range extensions. Remarkably, the critically endangered Aders’ duiker was the most frequently recorded species. A distinctive form of giant sengi and the vulnerable Sokoke bushy-tailed mongoose were also widely distributed and relatively abundant. Other significant records of threatened species included African wild dog, African lion and Pousargues’s monkey. Species richness and relative abundance of all species were higher than that recorded for Arabuko-Sokoke Forest, Kenya’s only other large coastal forest, using the same camera trap survey protocol.Keywords: Boni-Dodori forest, coastal forest, camera trapping, mammals, species richness, trap rates, occupanc

Software to facilitate and streamline camera trap data management: a review

Improving technology and increasing affordability mean that camera trapping—the use of remotely triggered cameras to photograph wildlife—is becoming an increasingly common tool in the monitoring and conservation of wild populations. Each camera trap study generates a vast amount of data, which need to be processed and labeled before analysis. Traditionally, processing camera trap data has been performed manually by entering data into a spreadsheet. This is time‐consuming, prone to human error, and data management may be inconsistent between projects, hindering collaboration. Recently, several programs have become available to facilitate and quicken data processing. Here, we review available software and assess their ability to better standardize camera trap data management and facilitate data sharing and collaboration. To identify available software for camera trap data management, we used internet searches and contacted researchers and practitioners working on large camera trap projects, as well as software developers. We tested all available programs against a range of software characteristics in addition to their ability to record a suite of important data variables extracted from images. We identified and reviewed 12 available programs for the management of camera trap data. These ranged from simple software assisting with the extraction of metadata from an image, through to comprehensive programs that facilitate data entry and analysis. Many of the programs tested were developed for use on specific studies and so do not cover all possible software or data collection requirements that different projects may have. We highlight the importance of a standardized software solution for camera trap data management. This approach would allow all possible data to be collected, enabling researchers to share data and contribute to other studies, as well as facilitating multi‐project comparisons. By standardizing camera trap data collection and management in this way, future studies would be better placed to guide conservation policy on a global level

Capacity building for wildlife health professionals: the Wildlife Health Bridge

The Wildlife Health Bridge was established in 2009 with the aim of improving the expertise and knowledge base of wildlife health professionals in biodiverse low- and middle-income countries. The Wildlife Health Bridge centres around partnerships among educational institutions: the Zoological Society of London, the Royal Veterinary College, the University of Edinburgh’s Royal (Dick) School of Veterinary Studies, the Wildlife Institute of India, and the University of Melbourne Veterinary School. The Wildlife Health Bridge provides quality education in wildlife health, ecosystem health, and wildlife biology, facilitates the interchange of students between collaborating countries for research studies and provides a global graduate network of wildlife health professionals. In addition to established Masters’ level wildlife health training programmes run by the partner organisations, the Wildlife Health Bridge has developed a collaborative field-based course, Interventions in Wild Animal Health, provided annually in India since 2016, which has trained 138 veterinarians to date, enhancing local and international capacity in managing emerging wildlife health issues and building global professional linkages. The Wildlife Health Bridge’s Wild Animal Alumni network facilitates networking and exchange between Wildlife Health Bridge institutions and graduates, with over 701 members from 67 countries, half of which are biodiverse low- and middle-income countries. Collaboration between educational institutions has enabled new ideas and ongoing developments in the delivery of materials and learning outcomes. The Wildlife Health Bridge is building global capacity in trained wildlife health professionals, through educational programmes and a synergised network, with the aim of impacting conservation practice to benefit human, domestic animal and wildlife health