Density of tiger and leopard in a tropical deciduous forest of Mudumalai Tiger Reserve,southern India,as estimated using photographic capture–recapture sampling

Density of tiger Panthera tigris and leopard Panthera pardus was estimated using photographic capture–recapture sampling in a tropical deciduous forest of Mudumalai Tiger Reserve, southern India, from November 2008 to February 2009. A total of 2,000 camera trap nights for 100 days yielded 19 tigers and 29 leopards within an intensive sampling area of 107 km². Population size of tiger from closed population estimator model M_b Zippin was 19 tigers (SE = ±0.9) and for leopards M_h Jackknife estimated 53 (SE = ±11) individuals. Spatially explicit maximum likelihood and Bayesian model estimates were 8.31 (SE = ±2.73) and 8.9 (SE = ±2.56) per 100 km² for tigers and 13.17 (SE = ±3.15) and 13.01 (SE = ±2.31) per 100 km² for leopards, respectively. Tiger density for MMDM models ranged from 6.07 (SE = ±1.74) to 9.72 (SE = ±2.94) per 100 km² and leopard density ranged from 13.41 (SE = ±2.67) to 28.91 (SE = ±7.22) per 100 km². Spatially explicit models were more appropriate as they handle information at capture locations in a more specific manner than some generalizations assumed in the classical approach. Results revealed high density of tiger and leopard in Mudumalai which is unusual for other high density tiger areas. The tiger population in Mudumalai is a part of the largest population at present in India and a source for the surrounding Reserved Forest.     

Low leopard populations in protected areas of Maputaland: a consequence of poaching,habitat condition,abundance of prey,and a top predator

Identifying the primary causes affecting population densities and distribution of flagship species are necessary in developing sustainable management strategies for large carnivore conservation. We modeled drivers of spatial density of the common leopard (Panthera pardus) using a spatially explicit capture–recapture—Bayesian approach to understand their population dynamics in the Maputaland Conservation Unit, South Africa. We camera‐trapped leopards in four protected areas (PAs) of varying sizes and disturbance levels covering 198 camera stations. Ours is the first study to explore the effects of poaching level, abundance of prey species (small, medium, and large), competitors (lion Panthera leo and spotted hyenas Crocuta crocuta), and habitat on the spatial distribution of common leopard density. Twenty‐six male and 41 female leopards were individually identified and estimated leopard density ranged from 1.6 ± 0.62/100 km² (smallest PA—Ndumo) to 8.4 ± 1.03/100 km² (largest PA—western shores). Although dry forest thickets and plantation habitats largely represented the western shores, the plantation areas had extremely low leopard density compared to native forest. We found that leopard density increased in areas when low poaching levels/no poaching was recorded in dry forest thickets and with high abundance of medium‐sized prey, but decreased with increasing abundance of lion. Because local leopard populations are vulnerable to extinction, particularly in smaller PAs, the long‐term sustainability of leopard populations depend on developing appropriate management strategies that consider a combination of multiple factors to maintain their optimal habitats.     

Occupancy,density, and activity patterns of a Critically Endangered leopard population on the Kawthoolei-Thailand border

Large carnivores have been largely extirpated from Southeast Asia due to deforestation, habitat fragmentation, and poaching. Estimating the density of endangered carnivore populations, and identifying relationships between species occupancy and both environmental and anthropogenic factors, is essential for effective conservation planning. Recently, the IUCN conservation status of the Indochinese leopard (Panthera pardus delacouri) was upgraded to “Critically Endangered.” We surveyed Kweekoh Wildlife Sanctuary in Kawthoolei, an area administered by the Karen ethnic group in eastern Myanmar, to quantify (1) leopard population density using spatially explicit mark-resight (SMR) models, (2) leopard occupancy as influenced by important ecological variables, and (3) potential differences in activity between melanistic and spotted leopard morphs. Leopard density was estimated to be 1.39 ± SE 0.22/100 km². Leopard occupancy (ψ = 0.43; 95% credible interval: 0.26–0.67) increased further from roads, at relatively higher elevations, and in areas with higher relative abundance of wild boar. Leopard activity was cathemeral, with higher activity during night hours, and significant overlap (Δ = 0.84; 95% confidence interval: 0.71–0.96) between melanistic and spotted morphs. However, melanistic leopards were more active during twilight hours than spotted individuals whose activity did not significantly vary throughout the day. Indochinese leopard density estimates in Kweekoh were among the lowest reported from Southeast Asia. Leopard occupancy was highest in the sanctuary's core areas, suggesting the presence of negative anthropogenic impacts along the sanctuary borders. We suggest our low density estimates warrant immediate and decisive conservation action, including better protection for leopards, their habitat, and their prey.     

Assessing Estimators of Snow Leopard Abundance

Abstract: The secretive nature of snow leopards (Uncia uncia) makes them difficult to monitor, yet conservation efforts require accurate and precise methods to estimate abundance. We assessed accuracy of Snow Leopard Information Management System (SLIMS) sign surveys by comparing them with 4 methods for estimating snow leopard abundance: predator:prey biomass ratios, capture-recapture density estimation, photo-capture rate, and individual identification through genetic analysis. We recorded snow leopard sign during standardized surveys in the SaryChat Zapovednik, the Jangart hunting reserve, and the Tomur Strictly Protected Area, in the Tien Shan Mountains of Kyrgyzstan and China. During June-December 2005, adjusted sign averaged 46.3 (SaryChat), 94.6 (Jangart), and 150.8 (Tomur) occurrences/km. We used counts of ibex (Capra ibex) and argali (Ovis ammon) to estimate available prey biomass and subsequent potential snow leopard densities of 8.7 (SaryChat), 1.0 (Jangart), and 1.1 (Tomur) snow leopards/100 km². Photo capture-recapture density estimates were 0.15 (n = 1 identified individual/1 photo), 0.87 (n = 4/13), and 0.74 (n = 5/6) individuals/100 km² in SaryChat, Jangart, and Tomur, respectively. Photo-capture rates (photos/100 trap-nights) were 0.09 (SaryChat), 0.93 (Jangart), and 2.37 (Tomur). Genetic analysis of snow leopard fecal samples provided minimum population sizes of 3 (SaryChat), 5 (Jangart), and 9 (Tomur) snow leopards. These results suggest SLIMS sign surveys may be affected by observer bias and environmental variance. However, when such bias and variation are accounted for, sign surveys indicate relative abundances similar to photo rates and genetic individual identification results. Density or abundance estimates based on capture-recapture or ungulate biomass did not agree with other indices of abundance. Confidence in estimated densities, or even detection of significant changes in abundance of snow leopard, will require more effort and better documentation.     

Do fences constrain predator movements on an evolutionary scale? Home range, food intake and movement patterns of large predators reintroduced to Addo Elephant National Park, South Africa

Fencing conservation areas is ubiquitous in South Africa, however, the impact of these on predator ecology has not been tested. We used relationships between prey abundance and predator space use to create equations to predict the home range size of lions Panthera leo and leopards Panthera pardus. We then successfully tested these predictions using published data (Phinda, Makalali) and home range estimates from radio collared individuals reintroduced to Addo Elephant National Park. Spotted hyaena Crocuta crocuta ranges also seem food dependent. Lion home ranges in Addo (114 ± 5 km²) required 180 fixes to be accurately estimated, spotted hyaena ranges (91 ± 10 km²) required 200 fixes, and the solitary leopard had 295 fixes for a range of 38 km². There were no sexual differences in home range sizes of lions or hyaenas. The daily food intake rate of lions, measured during continuous follows, was 9.8 kg per female equivalent unit. Dominant male lions (14.3 km for 8.3 kg) traveled furthest but obtained the least amount of food per day compared to subordinate males (8.9 km for 16.0 kg) and females (5.8 km for 17.9 kg). Subordinate males traveled the fastest and during the day, to avoid competition and harassment from the dominant males. From an evolutionary viewpoint, the use of fences for conservation has not affected the natural behaviour of the predators as they still conform to predictions derived from unfenced reserves; that is, prey abundance is the key factor in determining space use of large predators.     

In the shadows of snow leopards and the Himalayas: density and habitat selection of blue sheep in Manang,Nepal

There is a growing agreement that conservation needs to be proactive and pay increased attention to common species and to the threats they face. The blue sheep (Pseudois nayaur) plays a key ecological role in sensitive high‐altitude ecosystems of Central Asia and is among the main prey species for the globally vulnerable snow leopard (Panthera uncia). As the blue sheep has been increasingly exposed to human pressures, it is vital to estimate its population dynamics, protect the key populations, identify important habitats, and secure a balance between conservation and local livelihoods. We conducted a study in Manang, Annapurna Conservation Area (Nepal), to survey blue sheep on 60 transects in spring (127.9 km) and 61 transects in autumn (134.7 km) of 2019, estimate their minimum densities from total counts, compare these densities with previous estimates, and assess blue sheep habitat selection by the application of generalized additive models (GAMs). Total counts yielded minimum density estimates of 6.0–7.7 and 6.9–7.8 individuals/km² in spring and autumn, respectively, which are relatively high compared to other areas. Elevation and, to a lesser extent, land cover indicated by the normalized difference vegetation index (NDVI) strongly affected habitat selection by blue sheep, whereas the effects of anthropogenic variables were insignificant. Animals were found mainly in habitats associated with grasslands and shrublands at elevations between 4,200 and 4,700 m. We show that the blue sheep population size in Manang has been largely maintained over the past three decades, indicating the success of the integrated conservation and development efforts in this area. Considering a strong dependence of snow leopards on blue sheep, these findings give hope for the long‐term conservation of this big cat in Manang. We suggest that long‐term population monitoring and a better understanding of blue sheep–livestock interactions are crucial to maintain healthy populations of blue sheep and, as a consequence, of snow leopards.     

Population density and abundance of sympatric large carnivores in the lowland tropical evergreen forest of Indian Eastern Himalayas

Low density occurrence of large carnivore species and direct hunting of predators and prey make carnivore conservation complex. Vital baseline information on population status of large carnivores is still deficient in most forests of eastern Himalaya, which are known to be the biodiversity hotspots. To fill this information gap, we estimated the large carnivore population status and abundance in an intricate eastern Himalayan lowland tropical forest in Pakke Tiger Reserve, Arunachal Pradesh. Population status and abundance estimates of tigers and leopards were made through individual identification using closed capture-recapture sampling. To estimate the dhole abundance photographic encounter rate was used. For individually non-identifiable species photographic rate seemed to correlate well with animal abundance. The estimated tiger and leopard density through 1/2 MMDM was 2.14 ± 0.04/100 km² and 2.99 ± 1.13/100 km² respectively. Maximum likelihood estimates shows density of tiger 1.86 ± 0.7 and for leopard 2.82 ± 1.2.The estimated dhole abundance was (N) 10.6 ± 0.94, and density 6.62 ± 0.58 individuals in 100 km². Further, occupancy estimation of large carnivores may be tried along with assessing the comparative efficacy of other population estimation methods to establish better monitoring methods for this region.     

Big cats at large: Density,structure, and spatio-temporal patterns of a leopard population free of anthropogenic mortality

Human impact is near pervasive across the planet and studies of wildlife populations free of anthropogenic mortality are increasingly scarce. This is particularly true for large carnivores that often compete with and, in turn, are killed by humans. Accordingly, the densities at which carnivore populations occur naturally, and their role in shaping and/or being shaped by natural processes, are frequently unknown. We undertook a camera-trap survey in the Sabi Sand Game Reserve (SSGR), South Africa, to examine the density, structure and spatio-temporal patterns of a leopard Panthera pardus population largely unaffected by anthropogenic mortality. Estimated population density based on spatial capture–recapture models was 11.8 ± 2.6 leopards/100 km². This is likely close to the upper density limit attainable by leopards, and can be attributed to high levels of protection (particularly, an absence of detrimental edge effects) and optimal habitat (in terms of prey availability and cover for hunting) within the SSGR. Although our spatio-temporal analyses indicated that leopard space use was modulated primarily by “bottom-up” forces, the population appeared to be self-regulating and at a threshold that is unlikely to change, irrespective of increases in prey abundance. Our study provides unique insight into a naturally-functioning carnivore population at its ecological carrying capacity. Such insight can potentially be used to assess the health of other leopard populations, inform conservation targets, and anticipate the outcomes of population recovery attempts.     

No silver bullet? Snow leopard prey selection in Mt. Kangchenjunga,Nepal

In this study, we investigated the impact of domestic and wild prey availability on snow leopard prey preference in the Kangchenjunga Conservation Area of eastern Nepal—a region where small domestic livestock are absent and small wild ungulate prey are present. We took a comprehensive approach that combined fecal genetic sampling, macro‐ and microscopic analyses of snow leopard diets, and direct observation of blue sheep and livestock in the KCA. Out of the collected 88 putative snow leopard scat samples from 140 transects (290 km) in 27 (4 × 4 km²) sampling grid cells, 73 (83%) were confirmed to be from snow leopard. The genetic analysis accounted for 19 individual snow leopards (10 males and 9 females), with a mean population size estimate of 24 (95% CI: 19–29) and an average density of 3.9 snow leopards/100 km² within 609 km². The total available prey biomass of blue sheep and yak was estimated at 355,236 kg (505 kg yak/km² and 78 kg blue sheep/km²). From the available prey biomass, we estimated snow leopards consumed 7% annually, which comprised wild prey (49%), domestic livestock (45%), and 6% unidentified items. The estimated 47,736 kg blue sheep biomass gives a snow leopard‐to‐blue sheep ratio of 1:59 on a weight basis. The high preference of snow leopard to domestic livestock appears to be influenced by a much smaller available biomass of wild prey than in other regions of Nepal (e.g., 78 kg/km² in the KCA compared with a range of 200–300 kg/km² in other regions of Nepal). Along with livestock insurance scheme improvement, there needs to be a focus on improved livestock guarding, predator‐proof corrals as well as engaging and educating local people to be citizen scientists on the importance of snow leopard conservation, involving them in long‐term monitoring programs and promotion of ecotourism.     

Evaluating Methods for Counting Cryptic Carnivores

ABSTRACT Numerous techniques have been proposed to estimate carnivore abundance and density, but few have been validated against populations of known size. We used a density estimate established by intensive monitoring of a population of radiotagged leopards (Panthera pardus) with a detection probability of 1.0 to evaluate efficacy of track counts and camera-trap surveys as population estimators. We calculated densities from track counts using 2 methods and compared performance of 10 methods for calculating the effectively sampled area for camera-trapping data. Compared to our reference density (7.33 ± 0.44 leopards/100 km²), camera-trapping generally produced more accurate but less precise estimates than did track counts. The most accurate result (6.97 ± 1.88 leopards/100 km²) came from camera-trap data with a sampled area buffered by a boundary strip representing the mean maximum distance moved by leopards outside the survey area (MMDMOSA) established by telemetry. However, contrary to recent suggestions, the traditional method of using half the mean maximum distance moved from photographic recaptures did not result in gross overestimates of population density (6.56 ± 1.92 leopards/100 km²) but rather displayed the next best performance after MMDMOSA. The only track-count method comparable to reference density employed a capture-recapture framework applied to data when individuals were identified from their tracks (6.45 ± 1.43 leopards/100 km²) but the underlying assumptions of this technique limit more widespread application. Our results demonstrate that if applied correctly, camera-trap surveys represent the best balance of rigor and cost-effectiveness for estimating abundance and density of cryptic carnivore species that can be identified individually.     

Effects of temporary closure of a national park on leopard movement and behaviour in tropical Asia

Across Asia protected areas serve as refuges for carnivores inside human-dominated landscapes. However, the creation of hard edges around reserve boundaries where conflicts with humans arise and disturbance from human activities inside the reserves may affect carnivore behaviour and ecology. Thailand’s largest protected area, Kaeng Krachan National Park (2915 km²) receives >100,000 visitors annually while maintaining an intact assemblage of prey species for large carnivores, making it a potentially important site for population recovery of leopards (Panthera pardus), tigers (Panthera tigris) and dholes (Cuon alpinus). We assessed the abundance of leopards and their prey base, and their response to changes in levels of human activity after an unexpected flooding event that resulted in the park being closed to visitors for >6 months. Using camera-traps, we identified 6 individual leopards and used spatially explicit capture-recapture (SECR) methods, incorporating humans and prey as covariates, to test for factors affecting the detection probability of leopards before and after the park closure. Leopard density was unchanged between the two periods, however the movement and activity patterns were clearly different. In the absence of tourist activity, leopards tended to move more frequently, leopard detection rates increased by 70% and activity shifted towards being more diurnal. The consequences of these changes in behaviour may include improved health, reproduction and survival. A management strategy involving seasonal closure of parks may serve to alleviate pressure on leopards and other carnivores. We recommend using information on abundance of large carnivores and their prey species, and human disturbance as the key indicators for long-term monitoring and management of protected areas in Southeast Asia.     

Sampling bias in snow leopard population estimation studies

Accurate assessments of the status of threatened species and their conservation planning require reliable estimation of their global populations and robust monitoring of local population trends. We assessed the adequacy and suitability of studies in reliably estimating the global snow leopard (Panthera uncia) population. We compiled a dataset of all the peer-reviewed published literature on snow leopard population estimation. Metadata analysis showed estimates of snow leopard density to be a negative exponential function of area, suggesting that study areas have generally been too small for accurate density estimation, and sampling has often been biased towards the best habitats. Published studies are restricted to six of the 12 range countries, covering only 0.3–0.9% of the presumed global range of the species. Re-sampling of camera trap data from a relatively large study site (c.1684 km²) showed that small-sized study areas together with a bias towards good quality habitats in existing studies may have overestimated densities by up to five times. We conclude that current information is biased and inadequate for generating a reliable global population estimate of snow leopards. To develop a rigorous and useful baseline and to avoid pitfalls, there is an urgent need for (a) refinement of sampling and analytical protocols for population estimation of snow leopards (b) agreement and coordinated use of standardized sampling protocols amongst researchers and governments across the range, and (c) sampling larger and under-represented areas of the snow leopard's global range.     

新疆托木尔峰国家级自然保护区雪豹的种群密度

雪豹(Panthera uncia)是一种仅公布于中亚高山地区的珍稀濒危大型猫科动物,被IUCN红皮书列为濒危物种,并被收录入CITES公约附录Ⅰ,在中国雪豹被列为国家一级重点保护动物(杨奇森和冯祚建,1998).     

Leopard (Panthera pardus) occupancy in the Chure range of Nepal

Conservation of large carnivores such as leopards requires large and interconnected habitats. Despite the wide geographic range of the leopard globally, only 17% of their habitat is within protected areas. Leopards are widely distributed in Nepal, but their population status and occupancy are poorly understood. We carried out the sign‐based leopard occupancy survey across the entire Chure range (~19,000 km²) to understand the habitat occupancy along with the covariates affecting their occupancy. Leopard signs were obtained from in 70 out of 223 grids surveyed, with a naïve leopard occupancy of 0.31. The model‐averaged leopard occupancy was estimated to be 0.5732 (SE 0.0082) with a replication‐level detection probability of 0.2554 (SE 0.1142). The top model shows the additive effect of wild boar, ruggedness, presence of livestock, and human population density positively affecting the leopard occupancy. The detection probability of leopard was higher outside the protected areas, less in the high NDVI (normalized difference vegetation index) areas, and higher in the areas with livestock presence. The presence of wild boar was strong predictor of leopard occupancy followed by the presence of livestock, ruggedness, and human population density. Leopard occupancy was higher in west Chure (0.70 ± SE 0.047) having five protected areas compared with east Chure (0.46 ± SE 0.043) with no protected areas. Protected areas and prey species had positive influence on leopard occupancy in west Chure range. Similarly in the east Chure, the leopard occupancy increased with prey, NDVI, and terrain ruggedness. Enhanced law enforcement and mass awareness activities are necessary to reduce poaching/killing of wild ungulates and leopards in the Chure range to increase leopard occupancy. In addition, maintaining the sufficient natural prey base can contribute to minimize the livestock depredation and hence decrease the human–leopard conflict in the Chure range.     

Identifying important conservation areas for the clouded leopard Neofelis nebulosa in a mountainous landscape: Inference from spatial modeling techniques

The survival of large carnivores is increasingly precarious due to extensive human development that causes the habitat loss and fragmentation. Habitat selection is influenced by anthropogenic as well as environmental factors, and understanding these relationships is important for conservation management. We assessed the environmental and anthropogenic variables that influence site use of clouded leopard Neofelis nebulosa in Bhutan, estimated their population density, and used the results to predict the species’ site use across Bhutan. We used a large camera‐trap dataset from the national tiger survey to estimate for clouded leopards, for the first time in Bhutan, (1) population density using spatially explicit capture–recapture models and (2) site‐use probability using occupancy models accounting for spatial autocorrelation. Population density was estimated at (0.10 SD) and (0.12 SE) per 100 km². Clouded leopard site use was positively associated with forest cover and distance to river while negatively associated with elevation. Mean site‐use probability (from the Bayesian spatial model) was (0.076 SD). When spatial autocorrelation was ignored, the probability of site use was overestimated, (0.066 SD). Predictive mapping allowed us to identify important conservation areas and priority habitats to sustain the future of these elusive, ambassador felids and associated guilds. Multiple sites in the south, many of them outside of protected areas, were identified as habitats suitable for this species, adding evidence to conservation planning for clouded leopards in continental South Asia.     

Modelling differential extinctions to understand big cat distribution on Indonesian islands

Aims To model differential extinction rates for island populations of tigers Panthera tigris and leopards P. pardus. Location Indonesia. Methods We built VORTEX population models of tiger and leopard populations on an island the size of Bali (3632 km²), using data from the literature. Results The tiger populations were less extinction prone than the leopard populations. This was unexpected as tigers had the smaller population sizes and, as such, might be assumed to be more extinction prone. We identified several aspects of tiger breeding biology that explain the result. Main conclusions Sea level reconstructions suggest that both tiger and leopard would have been present in Java, Sumatra and Bali at the end of the last glacial. Our model provides a plausible mechanism based on population ecology to explain why these leopard populations were more extinction prone than the tiger populations. In addition it illustrates the potential utility of population ecology models in understanding historical patterns in biogeography.     

Modelling potential habitat suitability for critically endangered Arabian leopards (Panthera pardus nimr) across their historical range in Saudi Arabia

Camera trapping can detect and monitor rare species in landscapes spanning thousands of square kilometres but placement of cameras in areas where the animals most likely occur will increase detection success. This vital information is lacking for the critically endangered Arabian leopard (Panthera pardus nimr) that has undergone a 90% decline across its range in Saudi Arabia. We aimed to identify suitable Arabian leopard habitat and potential population capacity in Saudi Arabia using data from leopards living in ecologically analogous habitat in South Africa and Oman. We developed a resource selection function (RSF) from 14 leopards’ GPS data in the Cederberg, South Africa, and validated the model using three leopards in the Little Karoo, and two Arabian leopards in Oman. We then projected the model to the historical range of Arabian leopards in Saudi Arabia to estimate likely leopard locations and potential population sizes based on home range metrics. The RSF successfully discriminated between used and available locations (specificity = 96.7%) and had high predictive ability (Rho > 0.9). Leopards selectively used areas away from human settlements and roads, with high enhanced vegetation index, and intermediate slopes and elevations. Saudi Arabia could theoretically host 4 distinct populations totalling 162–362 Arabian leopard females, depending on home range size. Camera traps deployed in the south-western mountains of Saudi Arabia may be most likely to detect remnant populations of Arabian leopards. Further research is needed into the local abundance of prey species and human activity to ensure the persistence of suitable leopard ranges and inform conservation actions.     

Spatial density estimates of Eurasian lynx (Lynx lynx) in the French Jura and Vosges Mountains

Obtaining estimates of animal population density is a key step in providing sound conservation and management strategies for wildlife. For many large carnivores however, estimating density is difficult because these species are elusive and wide‐ranging. Here, we focus on providing the first density estimates of the Eurasian lynx (Lynx lynx) in the French Jura and Vosges mountains. We sampled a total of 413 camera trapping sites (with two cameras per site) between January 2011 and April 2016 in seven study areas across seven counties of the French Jura and Vosges mountains. We obtained 592 lynx detections over 19,035 trap days in the Jura mountains and 0 detection over 6,804 trap days in the Vosges mountains. Based on coat patterns, we identified a total number of 92 unique individuals from photographs, including 16 females, 13 males, and 63 individuals of unknown sex. Using spatial capture–recapture (SCR) models, we estimated abundance in the study areas between 5 (SE = 0.1) and 29 (0.2) lynx and density between 0.24 (SE = 0.02) and 0.91 (SE = 0.03) lynx per 100 km². We also provide a comparison with nonspatial density estimates and discuss the observed discrepancies. Our study is yet another example of the advantage of combining SCR methods and noninvasive sampling techniques to estimate density for elusive and wide‐ranging species, like large carnivores. While the estimated densities in the French Jura mountains are comparable to other lynx populations in Europe, the fact that we detected no lynx in the Vosges mountains is alarming. Connectivity should be encouraged between the French Jura mountains, the Vosges mountains, and the Palatinate Forest in Germany where a reintroduction program is currently ongoing. Our density estimates will help in setting a baseline conservation status for the lynx population in France.     

Spotted in the News: Using Media Reports to Examine Leopard Distribution,Depredation, and Management Practices outside Protected Areas in Southern India

There is increasing evidence of large carnivore presence outside protected areas, globally. Although this spells conservation success through population recoveries, it makes carnivore persistence in human-use landscapes tenuous. The widespread distribution of leopards in certain regions of India typifies this problem. We obtained information on leopard-human interactions at a regional scale in Karnataka State, India, based on systematic surveys of local media reports. We applied an innovative occupancy modelling approach to map their distribution patterns and identify hotspots of livestock/human depredation. We also evaluated management responses like removals of ‘problem’ leopards through capture and translocations. Leopards occupied around 84,000 km² or 47% of the State’s geographic area, outside designated national parks and wildlife sanctuaries. Their presence was facilitated by extent of vegetative cover- including irrigated croplands, rocky escarpments, and prey base in the form of feral and free-ranging dogs. Higher probabilities of livestock/human attacks by leopards were associated with similar ecological features as well as with capture/removals of leopards. Of the 56 cases of leopard removals reported, 91% did not involve human attacks, but followed livestock predation or only leopard sightings. The lack of knowledge on leopard ecology in human-use areas has resulted in unscientific interventions, which could aggravate the problem rather than mitigating it. Our results establish the presence of resident, breeding leopards in human-use areas. We therefore propose a shift in management focus, from current reactive practices like removal and translocation of leopards, to proactive measures that ensure safety of human lives and livelihoods.     

Night and day: evaluating transect methodologies to monitor duikers in the Dzanga‐Sangha Protected Areas,Central African Republic

Across the Congo Basin, human hunting pressure poses the biggest threat to small‐ and medium‐bodied forest ungulates (genus Philantomba and Cephalophus, commonly known as duikers). The exploitation of these species has cascading effects on larger ecosystem processes, as well as on human subsistence practices. This study compares encounter rates and estimated population densities of duiker species, specifically Philantomba monticola (blue duiker) in the Dzanga‐Sangha Protected Areas (APDS), Central African Republic (CAR). Data were collected using direct observations of individual animals during diurnal (135 km) and nocturnal (150 km) transects in the APDS, with abundance estimates produced using DISTANCE software. Transect data demonstrate that within hunted forests similar to APDS, nocturnal rather than diurnal transects yield more individual observations of ungulates. Despite hunting pressure in the region, estimates presented for APDS suggest some of the highest density estimates reported for blue duikers in western and central Africa (58.6 blue duikers per km²). This study directly contributes current regional data on the status of duiker populations at APDS and in the larger Sangha Trinational Landscape (TNS, UNESCO). More broadly, we highlight the potential importance of nocturnal transect data to the development of adaptive management regimes in hunted forests.