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Compared to emblematic large carnivores, most species of the order Carnivora receive little conservation attention despite increasing anthropogenic pressure and poor understanding of their status across much of their range. We employed systematic camera trapping and spatially explicit capture-recapture modelling to estimate variation in population density of serval, striped hyaena and aardwolf across the mixed-use Ruaha-Rungwa landscape in southern Tanzania. We selected three sites representative of different habitat types, management strategies, and levels of anthropogenic pressure: Ruaha National Park’s core tourist area, dominated by Acacia-Commiphora bushlands and thickets; the Park’s miombo woodland; and the neighbouring community-run MBOMIPA Wildlife Management Area, also covered in Acacia-Commiphora . The Park’s miombo woodlands supported a higher serval density (5.56 [Standard Error = ±2.45] individuals per 100 km 2 ) than either the core tourist area (3.45 [±1.04] individuals per 100 km 2 ) or the Wildlife Management Area (2.08 [±0.74] individuals per 100 km 2 ). Taken together, precipitation, the abundance of apex predators, and the level of anthropogenic pressure likely drive such variation. Striped hyaena were detected only in the Wildlife Management Area and at low density (1.36 [±0.50] individuals per 100 km 2 ), potentially due to the location of the surveyed sites at the edge of the species’ global range, high densities of sympatric competitors, and anthropogenic edge effects. Finally, aardwolf were captured in both the Park’s core tourist area and the Wildlife Management Area, with a higher density in the Wildlife Management Area (13.25 [±2.48] versus 9.19 [±1.66] individuals per 100 km 2 ), possibly as a result of lower intraguild predation and late fire outbreaks in the area surveyed. By shedding light on three understudied African carnivore species, this study highlights the importance of miombo woodland conservation and community-managed conservation, as well as the value of by-catch camera trap data to improve ecological knowledge of lesser-studied carnivores.

In East Africa, community-based conservation models (CBCMs) have been established to support the conservation of wildlife in fragmented landscapes like the Tarangire Ecosystem, Tanzania. To assess how different management approaches maintained large herbivore populations, we conducted line distance surveys and estimated seasonal densities of elephant, giraffe, zebra, and wildebeest in six management units, including three CBCMs, two national parks (positive controls), and one area with little conservation interventions (negative control). Using a Monte-Carlo approach to propagate uncertainties from the density estimates and trend analysis, we analyzed the resulting time series (2011–2019). Densities of the target species were consistently low in the site with little conservation interventions. In contrast, densities of zebra and wildebeest in CBCMs were similar to national parks, providing evidence that CBCMs contributed to the stabilization of these migratory populations in the central part of the ecosystem. CBCMs also supported giraffe and elephant densities similar to those found in national parks. In contrast, the functional connectivity of Lake Manyara National Park has not been augmented by CBCMs. Our analysis suggests that CBCMs can effectively conserve large herbivores, and that maintaining connectivity through CBCMs should be prioritized.

Efforts to identify suitable habitat for wildlife conservation are crucial for safeguarding biodiversity, facilitating management, and promoting sustainable coexistence between wildlife and communities. Our study focuses on identifying potential black rhino (Diceros bicornis) habitat within the Ngorongoro Conservation Area (NCA), Tanzania, across wet and dry seasons. To achieve this, we used remote sensing data with and without field data. We employed a comprehensive approach integrating Sentinel-2 and PlanetScope images, vegetation indices, and human activity data. We employed machine learning recursive feature elimination (RFE) and random forest (RF) algorithms to identify the most relevant features that contribute to habitat suitability prediction. Approximately 36% of the NCA is suitable for black rhinos throughout the year; however, there are seasonal shifts in habitat suitability. Anthropogenic factors increase land degradation and limit habitat suitability, but this depends on the season. This study found a higher influence of human-related factors during the wet season, with suitable habitat covering 53.6% of the NCA. In the dry season, browse availability decreases and rhinos are forced to become less selective of the areas where they move to fulfil their nutritional requirements, with anthropogenic pressures becoming less important. Furthermore, our study identified specific areas within the NCA that consistently offer suitable habitat across wet and dry seasons. These areas, situated between Olmoti and the Crater, exhibit minimal disturbance from human activities, presenting favourable conditions for rhinos. Although the Oldupai Gorge only has small suitable patches, it used to sustain a large population of rhinos in the 1960s. Land cover changes seem to have decreased the suitability of the Gorge. This study highlights the importance of combining field data with remotely sensed data. Remote sensing-based assessments rely on the importance of vegetation covers as a proxy for habitat and often overlook crucial field variables such as shelter or breeding locations. Overall, our study sheds light on the imperative of identifying suitable habitat for black rhinos within the NCA and underscores the urgency of intensified conservation efforts. Our findings underscore the need for adaptive conservation strategies to reverse land degradation and safeguard black rhino populations in this dynamic multiple land-use landscape as environmental and anthropogenic pressures evolve.

The cheetah Acinonyx jubatus has suffered considerable range contractions in recent decades. Despite the importance of up-to-date information on distribution to guide conservation, such information is lacking for large areas within the species’ remaining potential range. In Tanzania, the largest tract of potential cheetah habitat without such data is the Selous–Nyerere ecosystem. Although the cheetah is considered possibly extant in this landscape, the last confirmed sighting was in the late 1990s. During 2020–2022, we carried out sign-based (spoor) and camera-trap surveys across Selous Game Reserve and Nyerere National Park. We did not record any evidence of cheetah presence, and opportunistic enquiries with tourism operators and protected area management staff did not provide any evidence of current or recent presence. Our findings suggest that current cheetah presence is unlikely, and that Selous–Nyerere should not be treated as potential contemporary cheetah range. We discuss the possibility that Selous–Nyerere may have never hosted a resident cheetah population, and was either occasionally occupied by dispersers from other populations or represented the edge of populations that spanned areas now treated as corridors.

Under the dual pressures of climate change and human activities, the restrictions imposed by conservation policies, along with the increasing overlap between wildlife protected areas (PAs) and community living areas, have intensified the contradictions and conflicts between PAs and surrounding communities. Effective governance of such conflicts is particularly crucial to reconciling the contradictions between conservation and development. This study takes the Mikumi–Selous areas in Tanzania, Africa, as a case study. Through questionnaires and semi-structured interviews, it explores the current state of conflicts between PAs and communities in the study area and summarizes conflict governance measures. Moreover, this research focuses on identifying various factors that influence the conservation willingness and action of community residents, further validating the relationships between residents’ household characteristics, conservation costs and benefits, conservation cognition, willingness, and behaviors through empirical analysis methods. The results indicate that residents’ conservation cognition significantly positively impacts their conservation willingness and behaviors, while conservation willingness also positively affects their conservation behaviors. Additionally, it was found that conservation costs inhibit residents’ conservation willingness and behaviors. This study primarily explores, from a community governance perspective, the participation willingness and behaviors of core stakeholders in conflict governance, emphasizing the critical role of community involvement in achieving biodiversity conservation and coordinated community development and providing a new perspective for alleviating conservation and development issues.

For territorial advertisement and intra‐pride communication African lions emit a roaring bout, of which one component, is their iconic roar. The full‐throated roar of a lion has recently been shown to be a unique and individually identifiable signature. At the same time, the frequency of large‐scale passive acoustic monitoring surveys has increased. As such, a lion's roar may soon become a useful tool to count individuals and estimate population density, to supplement traditional survey techniques. Currently, selecting full‐throated roars is heavily dependent on expert inference and is therefore subject to human‐induced bias. We propose a data‐driven approach to automatically classify lions' full‐throated roars from the other vocalisations that constitute a roaring bout. By using two‐state Gaussian Hidden‐Markov Models, we also demonstrate that two types of roars exist within a lion's roaring bout—a full‐throated roar and a newly named intermediary roar—and these can be classified at an accuracy of 84.7%. We further demonstrate that using simple metrics to describe lion vocalisations—maximum frequency (Hz) and vocalisation length (s)—and K ‐means clustering is sufficient to classify lion call types, at a high accuracy (95.4%), and that using data‐driven predicted full‐throated roars results in an improved ability to identify individuals (F1‐score 0.87 vs. manual full‐throated roar classification 0.80). Here, we establish an easy‐to‐understand and implement process that will reduce the knowledge gap and make passive acoustic monitoring more accessible in a field currently dominated by other monitoring techniques (e.g., camera surveys), paving the way for novel research.

Natural resource managers and policymakers need actionable climate data to guide conservation decisions. Conserving climate change refugia, areas relatively buffered from contemporary climate change, is increasingly considered an effective strategy for adaptation. Despite tropical species facing heightened vulnerability to climate change, the tropics remain underserved in climate adaptation research. We coproduced with Tanzanian partners the first comprehensive assessment of climate change refugia across Tanzania through extensive consultation, in‐person conversations, and field visits to priority ecosystems, ensuring our analysis addressed local conservation needs and decision‐making contexts. We developed species distribution models for 33 terrestrial animal species using maximum entropy and boosted regression tree algorithms. We projected future suitable habitats for SSP126 and SSP585, for 2011–2040 and 2071–2100, using GFDL Earth System and the UK Earth System models. More than half under SSP126 and 79% of focal species under SSP585 lost their suitable habitat by 2100. Serengeti National Park, Northern Highlands Forest Reserve, and the Eastern Arc Mountains emerged as key climate change refugia, while other protected areas, including Kigosi and Ugalla River National Parks, had no climate change refugia. This assessment provides actionable insights for Tanzania's conservation prioritization while identifying critical research gaps in western and montane ecosystems. We coproduced the first comprehensive assessment of climate change refugia across Tanzania with Tanzanian partners through extensive consultation, in‐person interviews, and field visits to priority ecosystems, ensuring our analysis addressed local conservation needs and decision‐making contexts. We developed species distribution models for 33 terrestrial animal species using maximum entropy and boosted regression tree algorithms.

Strawberry or red leopards are a rare colour morph of leopard (Panthera pardus) characterised by spot markings that are red or brown instead of black, thought to be a result of a mutation in the tyrosinase‐related protein (TYRP1) gene. We report the first record of this phenotype on the African continent outside of South Africa, from Selous Game Reserve in southern Tanzania. One female leopard with strawberry colouration was documented out of 373 individual leopards (0.3%) identified through camera trap surveys conducted from 2020 to 2022 over a combined area of more than 4600 km2 in the Nyerere‐Selous landscape. Strawberry leopards are a rare colour morph of leopard (Panthera pardus) characterised by spot markings that are red or brown instead of black. We report the first record of this phenotype for the African continent outside of South Africa, from Selous Game Reserve in southern Tanzania. One female leopard with strawberry colouration was documented out of 373 individual leopards (0.3%) identified through camera trap surveys conducted in the Nyerere‐Selous ecosystem from 2020 to 2022.

Remarkably little is still understood about how the leopard (Panthera pardus) is faring in much of its remaining African range, despite the species' importance for ecosystem function and generating funding for conservation via tourism. In this study, we address this knowledge gap in southern Tanzania's Selous–Nyerere ecosystem, one of the largest intact wilderness areas on the continent, by estimating leopard population density via spatially explicit capture–recapture (SECR) modelling of data from seven camera trap surveys. Population density was highest in Nyerere National Park's Matambwe sector (8.08 ± SE 1.54 adult and subadult leopards per 100 km2), followed by Selous Game Reserve's Miguruwe sector (7.38 ± 1.26 per 100 km2); Nyerere NP's Msolwa sector (6.05 ± 0.78 per 100 km2); Selous GR's Liwale sector (5.93 ± 0.88 per 100 km2), western Kingupira sector (5.58 ± 0.87 per 100 km2) and eastern Kingupira sector (5.22 ± 0.71 per 100 km2); and Nyerere NP's Kalulu sector (3.80 ± 0.64 per 100 km2). Together, our surveys covered an important component of extant leopard range in Tanzania, and our findings highlight the importance of the Selous–Nyerere ecosystem as a leopard stronghold. The estimates include the highest leopard densities yet documented in miombo woodland, which represents nearly one fifth of the species' remaining African range. Unlike lion, leopard population density was highly correlated with relative abundance of preferred prey. Although limited by a small number of data points, this suggests that the two species may not be uniformly affected by anthropogenic threats. Threats to leopard in Selous–Nyerere include accelerating habitat conversion in boundary areas and bushmeat poaching, which impacts leopard indirectly by suppressing prey populations and directly via accidental snaring. Practical implication. Placed in the context of range‐wide leopard monitoring, this study highlights the need to address persistent knowledge gaps on the species' continental status and prioritise sites for monitoring based on their potential to inform evidence‐based conservation management. This study uses spatially explicit capture–recapture modelling of camera trap data to shed light on the status of leopard in Tanzania's Selous–Nyerere ecosystem, one of the largest remaining wilderness areas in Africa. The results highlight the ecosystem as a leopard stronghold, with population densities ranging from 3.80 (±0.64) to 8.08 (±1.54) adult and subadult leopards per 100 km2. While this study makes an important contribution to our knowledge of the species, it is unrealistic to survey the species' entire range in this way, and we advocate for a more strategic approach to leopard monitoring that prioritises sites based on their potential to inform evidence‐based conservation.