Spatial partial identity model reveals low densities of leopard and spotted hyaena in a miombo woodland

Decline in global carnivore populations has led to increased demand for assessment of carnivore densities in understudied habitats. Spatial capture–recapture (SCR) is used increasingly to estimate species densities, where individuals are often identified from their unique pelage patterns. However, uncertainty in bilateral individual identification can lead to the omission of capture data and reduce the precision of results. The recent development of the two-flank spatial partial identity model (SPIM) offers a cost-effective approach, which can reduce uncertainty in individual identity assignment and provide robust density estimates. We conducted camera trap surveys annually between 2016 and 2018 in Kasungu National Park, Malawi, a primary miombo woodland and a habitat lacking baseline data on carnivore densities. We used SPIM to estimate density for leopard (Panthera pardus) and spotted hyaena (Crocuta crocuta) and compared estimates with conventional SCR methods. Density estimates were low across survey years, when compared to estimates from sub-Saharan Africa, for both leopard (1.9±0.19 sd adults/100km2) and spotted hyaena (1.15±0.42 sd adults/100km2). Estimates from SPIM improved precision compared with analytical alternatives. Lion (Panthera leo) and wild dog (Lycaon pictus) were absent from the 2016 survey, but lone dispersers were recorded in 2017 and 2018, and both species appear limited to transient individuals from within the wider transfrontier conservation area. Low densities may reflect low carrying capacity in miombo woodlands or be a result of reduced prey availability from intensive poaching. We provide the first leopard density estimates from Malawi and a miombo woodland habitat, whilst demonstrating that SPIM is beneficial for density estimation in surveys where only one camera trap per location is deployed. The low density of large carnivores requires urgent management to reduce the loss of the carnivore guild in Kasungu National Park and across the wider transfrontier landscape

Using camera trap bycatch data to assess habitat use and the influence of human activity on African elephants (Loxodonta africana) in Kasungu National Park, Malawi

African elephants (Loxodonta africana) are increasingly exposed to high levels of human disturbance and are threatened by poaching and human–elephant conflict. As anthropogenic pressures continue to increase, both inside and outside protected areas, understanding elephant behavioural responses to human activity is required for future conservation management. Here, we use bycatch data from camera trap surveys to provide inferences on elephant habitat use and temporal activity in Kasungu National Park (KNP), Malawi. The KNP elephant population has declined by ~ 95% since the late 1970s, primarily because of intensive poaching, and information on elephant ecology and behaviour can assist in the species’ recovery. Using occupancy modelling, we show that proximity to water is the primary driver of elephant habitat use in KNP, with sites closer to water having a positive effect on elephant site use. Our occupancy results suggest that elephants do not avoid sites of higher human activity, while results from temporal activity models show that elephants avoid peak times of human activity and exhibit primarily nocturnal behaviour when using the KNP road network. As key park infrastructure is located near permanent water sources, elephant spatiotemporal behaviour may represent a trade-off between resource utilisation and anthropogenic-risk factors, with temporal partitioning used to reduce encounter rates. Increased law enforcement activity around permanent water sources could help to protect the KNP elephant population during the dry season. Our findings highlight that camera trap bycatch data can be a useful tool for the conservation management of threatened species beyond the initial scope of research