Explicit Capture-recapture Models Research Articles

Abundance of the northernmost jaguar Panthera onca breeding population

Jaguars are the apex predators of tropical and subtropical ecosystems in the Americas but their conservation is threatened due to habitat loss, poaching, and conflicts over predation. The Northern Jaguar Reserve (NJR) was created by Naturalia A.C. as a project to protect the northernmost jaguar population within an area of 59.3 thousand acres (24.4 ha) of private property. The property also includes other protected species. The present study was conducted to verify the status of this jaguar population in order to evaluate the effectiveness of the NJR, and to contribute to knowledge regarding its ecology. We estimated density using mark-resight and spatially explicit capture-recapture (SERC) models, and evaluated home range through a survey with 56 camera-trap stations over 12 bimonthly periods. In total, we obtained a sampling effort of 40,880 camera-days, registering 2.32 records from 1,000 camera-days. Jaguar density, calculated using the capture-recapture models, ranged from 0.3 to 1.44 indiv./100 km2, while the SERC model estimated a density of between 0.21 and 3.04 indiv./100 km2. The home range was 78.9 km2 for males and 45.1 km2 for females. Long-term population monitoring together with the establishment of Areas Voluntarily Assigned to Conservation, an initiative recently created by the Mexican government, such as the NJR, could be a valid strategy to strengthen jaguar conservation and thereby maintain key ecological processes for other species and their habitat in northwestern Mexico.

Can genetic rescue help save Arabia's last big cat?

Genetic diversity underpins evolutionary potential that is essential for the long-term viability of wildlife populations. Captive populations harbor genetic diversity potentially lost in the wild, which could be valuable for release programs and genetic rescue. The Critically Endangered Arabian leopard (Panthera pardus nimr) has disappeared from most of its former range across the Arabian Peninsula, with fewer than 120 individuals left in the wild, and an additional 64 leopards in captivity. We (i) examine genetic diversity in the wild and captive populations to identify global patterns of genetic diversity and structure; (ii) estimate the size of the remaining leopard population across the Dhofar mountains of Oman using spatially explicit capture-recapture models on DNA and camera trap data, and (iii) explore the impact of genetic rescue using three complementary computer modeling approaches. We estimated a population size of 51 (95% CI 32-79) in the Dhofar mountains and found that 8 out of 25 microsatellite alleles present in eight loci in captive leopards were undetected in the wild. This includes two alleles present only in captive founders known to have been wild-sourced from Yemen, which suggests that this captive population represents an important source for genetic rescue. We then assessed the benefits of reintroducing novel genetic diversity into the wild population as well as the risks of elevating the genetic load through the release of captive-bred individuals. Simulations indicate that genetic rescue can improve the long-term viability of the wild population by reducing its genetic load and realized load. The model also suggests that the genetic load has been partly purged in the captive population, potentially making it a valuable source population for genetic rescue. However, the greater loss of its genetic diversity could exacerbate genomic erosion of the wild population during a rescue program, and these risks and benefits should be carefully evaluated. An important next step in the recovery of the Arabian leopard is to empirically validate these conclusions, implement and monitor a genomics-informed management plan, and optimize a strategy for genetic rescue as a tool to recover Arabia's last big cat.

Estimating distribution and abundance of wide-ranging species with integrated spatial models: Opportunities revealed by the first wolf assessment in south-central Italy.

Estimating demographic parameters for wide-ranging and elusive species living at low density is challenging, especially at the scale of an entire country. To produce wolf distribution and abundance estimates for the whole south-central portion of the Italian wolf population, we developed an integrated spatial model, based on the data collected during a 7-month sampling campaign in 2020-2021. Data collection comprised an extensive survey of wolf presence signs, and an intensive survey in 13 sampling areas, aimed at collecting non-invasive genetic samples (NGS). The model comprised (i) a single-season, multiple data-source, multi-event occupancy model and (ii) a spatially explicit capture-recapture model. The information about species' absence was used to inform local density estimates. We also performed a simulation-based assessment, to estimate the best conditions for optimizing sub-sampling and population modelling in the future. The integrated spatial model estimated that 74.2% of the study area in south-central Italy (95% CIs = 70.5% to 77.9%) was occupied by wolves, for a total extent of the wolf distribution of 108,534 km2 (95% CIs = 103,200 to 114,000). The estimate of total population size for the Apennine wolf population was of 2557 individuals (SD = 171.5; 95% CIs = 2127 to 2844). Simulations suggested that the integrated spatial model was associated with an average tendency to slightly underestimate population size. Also, the main contribution of the integrated approach was to increase precision in the abundance estimates, whereas it did not affect accuracy significantly. In the future, the area subject to NGS should be increased to at least 30%, while at least a similar proportion should be sampled for presence-absence data, to further improve the accuracy of population size estimates and avoid the risk of underestimation. This approach could be applied to other wide-ranging species and in other geographical areas, but specific a priori evaluations of model requirements and expected performance should be made.

Where the small things are: Modelling edge effects on mouse lemur population density and distribution in northwestern Madagascar.

Edge effects result from the penetration to varying depths and intensities, of abiotic and biotic conditions from the surrounding non-forest matrix into the forest interior. Although 70% of the world's forests are within 1 km of a forest edge, making edge effects a dominant feature of most forest habitats, there are few empirical data on inter-site differences in edge responses in primates. We used spatially explicit capture-recapture (SECR) models to determine spatial patterns of density for two species of mouse lemurs (Microcebus murinus and Microcebus ravelobensis) in two forest landscapes in northwestern Madagascar. The goal of our study was to determine if mouse lemurs displayed spatially variable responses to edge effects. We trapped animals using Sherman live traps in the Mariarano Classified Forest (MCF) and in the Ambanjabe Forest Fragment Site (AFFS) site within Ankarafantsika National Park. We trapped 126 M. murinus and 79 M. ravelobensis at MCF and 78 M. murinus and 308 M. ravelobensis at AFFS. For M. murinus, our top model predicted a positive edge response, where density increased towards edge habitats. In M. ravelobensis, our top model predicted a negative edge response, where density was lower near the forest edges and increased towards the forest interior. At regional and landscape-specific scales, SECR models estimated different density patterns between M. murinus and M. ravelobensis as a result of variation in edge distance. The spatial variability of our results using SECR models indicate the importance of studying the population ecology of primates at varying scales that are appropriate to the processes of interest. Our results lend further support to the theory that some lemurs exhibit a form of ecological flexibility in their responses to forest loss, forest fragmentation, and associated edge effects.

First density estimates for a recovering bobcat population in Ohio using DNA from scat

AbstractThe recovery of mammalian species in the US Midwest through natural recolonization constitutes a conservation success story, yet management remains challenging due to many unknowns related to population dynamics and numeric trends. Abundance is a critical parameter for management decisions, and estimating the density and abundance of elusive species, such as terrestrial carnivores, remains challenging despite recent technological advances. In this study, we evaluated density and abundance of a recovering carnivore species, the bobcat (Lynx rufus) in two areas of Ohio using non‐invasive DNA from scat. The target areas in eastern and southern Ohio have been shown to have uneven dynamics and recolonization success and we expected that this would be reflected in differences in density and abundance. We collected 298 bobcat scats between July 2018 and April 2019 on 150 km of repeated transects. Of these, 102 scats were successfully genotyped, and 55 individuals were identified (33 in eastern Ohio and 22 in southern Ohio). Using Spatially Explicit Capture–Recapture models, we estimated 18.9 ± 4.1 and 10.9 ± 2.7 bobcats/100 km2 in eastern and southern Ohio study areas, respectively. Our results support prior telemetry data which indicated that bobcats in eastern Ohio had smaller home‐ranges than bobcats in southern Ohio, and thus could support a higher density of individuals. The higher densities were similar to other eastern US populations and are much higher than other Midwestern recovering populations. Our results provide a snapshot of the population status and can be used to determine sustainable management strategies for Ohio's bobcat population.

Exploring patterns of female house mouse spatial organisation among outbreaking and stable populations.

The size and distribution of home ranges reflect how individuals within a population use, defend, and share space and resources, and may thus be an important predictor of population-level dynamics. Eruptive species, such as the house mouse in Australian grain-growing regions, are an ideal species in which to investigate variations in space use and home range overlap between stable and outbreaking populations. In this study, we use spatially explicit capture-recapture models to explore if space use and home range overlap among female mice could serve as indicators of changes in population density leading into summer. Additionally, we assess the sensitivity of space use and home range estimates to reduced recapture rates. Our analysis did not reveal variations in the spring spatial organisation of female mice based on existing capture-mark-recapture data. However, our study highlights the need to balance monitoring efforts within regions, emphasising the importance of exploring studies that can improve spatial recaptures by optimising trapping efforts. This is particularly important in Australian agricultural systems, where varying farm management practices may drive differences in population dynamics.

Jaguar density in the Argentine Yungas: Overcoming camera trap failure

The Yungas ecoregion supports an important jaguar population, of particular conservation relevance due to its location in the extreme SW of the species distribution, with potential for range extension and population recovery. Detailed population estimates are lacking. To evaluate jaguar density in the Argentine Yungas we conducted a camera trap survey in Baritú National Park and surrounding private lands. We deployed 32 sampling stations with a pair of camera traps each, obtaining a sampling effort of 2,080 trap/nights. Camera malfunction translated in several individual jaguars’ photo-captured only from one side, thus preventing unequivocal identification to apply traditional spatially explicit capture-recapture models. We used 2-flank SPIM, a partial identity spatially explicit capture-recapture model, we estimated a density of 0.75 jaguars per 100 km2, with a probability of detecting one side and both sides of 0.01 and 0.02 respectively. Our density estimates are low, but within the range of other studies, especially those on the fringes of the species distribution and support the idea of Yungas offering a stronghold for Argentina’s jaguars. This study offers a baseline for a monitoring program, much needed in a priority jaguar population.

Density and ecological drivers of free‐ranging cat abundance and activity in Madeira Island, Macaronesia

AbstractMammalian predators introduced to oceanic islands pose a significant threat to biodiversity and have led to numerous extinctions. Free‐ranging cats are particularly problematic due to their predatory habits and negative impact on conservation. However, there is limited information on the ecology and population status of free‐ranging cats in insular ecosystems, where they often represent the apex terrestrial predator. Using a peri‐urban protected area in the subtropical island of Madeira as a case study, we employed camera traps to assess the density of free‐ranging cats and investigate the ecological drivers influencing their abundance and activity in nonurban insular habitats. Based on 582 trapping‐nights, we identified 25 individual cats from 156 cat detections. Spatially explicit capture–recapture models revealed a density of 1.4 cats per km2. Cat activity was positively affected by both the proportion of rocky areas in the landscape and the distance to human resource subsidies, whereas no significant driver was found for abundance. Our results indicate that cats are highly abundant throughout the protected area and suggest that their core home ranges are associated with rocky terrain, away from the most humanized sections of the park. Free‐ranging cats do not appear to heavily rely on anthropogenic food sources, signaling that they may rely mostly on wild prey to fulfill their dietary needs. Their preference for rocky areas could be explained by the increased availability of shelter and prey, such as the Madeira wall lizard (Teira dugesii). Notably, cat abundance and activity were particularly high in the vicinity of the only known breeding colony of the locally threatened Manx shearwater (Puffinus puffinus) on Madeira Island. Our findings suggest that cats pose a significant threat to the native vertebrate fauna of the protected area and thus their management, particularly during the breeding season of the Manx shearwater, should be considered.

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.

Status of the snow leopard Panthera uncia in the Qilian Mountains, Gansu Province, China

AbstractPopulation density estimation is integral to the effective conservation and management of wildlife. The snow leopard Panthera uncia is categorized as Vulnerable on the IUCN Red List, and reliable information on its density is a prerequisite for its conservation and management. Little is known about the status of the snow leopard in the central and eastern Qilian Mountains, China. To address this, we estimated the population density of the snow leopard using a spatially explicit capture–recapture model based on camera trapping in Machang in the central and eastern Qilian Mountains during January–March 2019. We set up 40 camera traps and recorded 84 separate snow leopard captures over 3,024 trap-days. We identified 18 individual snow leopards and estimated their density to be 2.26/100 km2. Our study provides baseline information on the snow leopard and the first population estimate for the species in the central and eastern Qilian Mountains.

Considerations on effort, precision and accuracy for long-term monitoring of African lions (Panthera leo), when using Bayesian spatial explicit capture-recapture models, in fenced protected areas.

Intensive management is frequently required in fenced wildlife areas to reduce deleterious effects of isolation. Decisions on how best to manage such wildlife are ideally informed by regular and reliable estimates of spatiotemporal fluctuations in population size and structure. However, even in small, fenced areas, it is difficult and costly to regularly monitor key species using advanced methods. This is particularly the case for large carnivores, which typically occur at low density and are elusive yet are central to management decision-making due to their top-down effects in ecosystems and attracting tourism. In this study, we aimed to provide robust estimates of population parameters for African lions (Panthera leo) and use the data to inform a resource-efficient long-term monitoring programme. To achieve this, we used unstructured spatial sampling to collect data on lions in Pilanesberg National Park, a small (~550 km2) fenced protected area in South Africa. We used Bayesian spatial capture-recapture models to estimate density, abundance, sex ratio and home range size of lions over the age of 1 year. Finally, to provide guidance on resource requirements for regular monitoring, we rarefied our empirical data set incrementally and analysed the subsets. Lion density was estimated to be 8.8 per 100 km2 (posterior SD = 0.6), which was lower than anticipated by park management. Sex ratio was estimated close to parity (0.9♀:1♂), consistent with emerging evidence in fenced lion populations, yet discordant with unfenced populations, which are usually ~2♀:1♂ in healthy, source populations. Our rarefied data suggest that a minimum of 4000 km search effort needs to be invested in future monitoring to obtain accurate and precise estimates, while assuming similar detection rates. This study demonstrates an important utility of Bayesian spatial explicit capture-recapture methods for obtaining robust estimates of lion densities and other important parameters in fence-protected areas to inform decision-making.

Habitat destruction threatens jaguars in a mixed land-use region of eastern Bolivia

AbstractLarge carnivores such as the jaguar Panthera onca are particularly susceptible to population decline and local extinction as a result of habitat loss. Here we report on the long-term monitoring of a local jaguar population in a mixed land-use area in the eastern lowlands of Bolivia from March 2017 to December 2019. We recorded 15 jaguar individuals and four reproduction events (five offspring from three females), suggesting that our study area harbours a resident breeding population. Seven iterations of spatially explicit capture–recapture models provided density estimates of 1.32–3.57 jaguars per 100 km2. Jaguar capture rates were highest in forested areas, with few to no jaguar captures in pastures used for livestock. Massive deforestation after the survey period reduced the proportion of dense forest cover by 33%, shrinking the availability of suitable jaguar habitat and placing the resident jaguar population at risk. We use the jaguar as an indicator species to highlight the threat of habitat destruction in the Chiquitano region and we emphasize the importance of intact forest patches for jaguar conservation.

Individuality matters in human–wildlife conflicts: Patterns and fraction of damage‐making brown bears in the north‐eastern Carpathians

Abstract Effective, evidence‐based management is required to ensure long‐term coexistence between people and wildlife in an increasingly humanized world. Although behavioural individuality is recognized as a key factor affecting evolutionary and ecological processes, it has rarely been explicitly assessed in relation to human–wildlife conflicts. The ‘problem individual’ paradigm states that some conspecifics within a given population have a disproportionately large contribution to conflicts. To the best of our knowledge, no studies have so far systematically tested this assumption in large carnivores. Here, we investigated the variation in conflict behaviour among brown bears Ursus arctos within the population inhabiting the Polish Eastern Carpathians. We inspected all sites notified as damaged by bears in 2014–2017 to determine the number and sex of the individuals involved. We conducted systematic noninvasive genetic sampling to estimate the size of the local population by spatially explicit capture–recapture models. We assessed the fraction and sex ratio of damage‐making bears in relation to the population, as well as the behavioural patterns by classifying and differentiating between occasional and repetitive damage‐makers. Approximately one‐third of the estimated 72 (95% CI 45.2–115.5) brown bears inhabiting the Polish Eastern Carpathians were responsible for damage occurrence in the region. The majority of damage‐makers were female (65% vs. 35% of male), which reflected the sex ratio of the local population (0.57). Thirty‐three per cent of the damage‐making bears (i.e. nine individuals) were classified as ‘problem individuals’, exhibiting repetitive conflict behaviour. Synthesis and applications. This study provides evidence of intraspecific differences in conflict behaviour in a large carnivore species, the brown bear, and indicates that damage‐making behaviour is not exhibited with the same frequency by all individuals within a population. Managers and policy‐makers should be aware that targeting individuals involved in conflicts without reference to the whole population may lead to misleading conclusions or an incomplete picture of the mechanisms underlying the conflicts, and thus, to mismanagement. Unravelling the behavioural patterns of individual engagement in damage through large‐scale and population‐wide studies is needed to accurately assess the magnitude of damage and enhance human–wildlife coexistence in areas experiencing conflicts.

Carbonated tiger-high above-ground biomass carbon stock in protected areas and corridors and its observed negative relationship with tiger population density and occupancy in the Terai Arc Landscape, Nepal.

Healthy natural forests maintain and/or enhances carbon stock while also providing potential habitat and an array of services to wildlife including large carnivores such as the tiger. This study is the first of its kind in assessing relationships between above-ground biomass carbon stock, tiger density and occupancy probability and its status in protected areas, corridors, and forest connectivity blocks. The dataset used to assess the relationship were: (1) Converged posterior tiger density estimates from camera trap data derived from Bayesian- Spatially Explicit Capture-Recapture model from Chitwan National Park; (2) Site wise probability of tiger occupancy estimated across the Terai Arc Landscape and (3) Habitat wise above-ground biomass carbon stock estimated across the Terai Arc Landscape. Carbon stock maps were derived based on eight habitat classes and conservation units linking satellite (Landsat 7 ETM+) images and field collected sampling data. A significant negative relationship (r = -0.20, p<0.01) was observed between above-ground biomass carbon stock and tiger density in Chitwan National Park and with tiger occupancy (r = -0.24, p = 0.023) in the landscape. Within protected areas, we found highest mean above-ground biomass carbon stock in high density mixed forest (~223 tC/ha) and low in degraded scrubland (~73.2 tC/ha). Similarly, we found: (1) highest tiger density ~ 0.06 individuals per 0.33 km2 in the riverine forest and lowest estimates (~0.00) in degraded scrubland; and (2) predictive tiger density of 0.0135 individuals per 0.33 km2 is equivalent to mean total of 43.7 tC/ha in Chitwan National Park. Comparatively, we found similar above-ground biomass carbon stock among corridors, large forest connectivity blocks (~117 tC/ha), and within in tiger bearing protected areas (~119 tC/ha). Carbon conservation through forest restoration particularly in riverine habitats (forest and grassland) and low transitional state forests (degraded scrubland) provides immense opportunities to generate win-win solutions, sequester more carbon and maintain habitat integrity for tigers and other large predators.

Evaluating predator control using two non-invasive population metrics: a camera trap activity index and density estimation from scat genotyping

Context Invasive mammalian predators are a threat to biodiversity and agriculture globally, yet management outcomes for lethal predator control remain difficult to monitor and evaluate. Understanding whether changes in activity indices correspond to true changes in population density will help inform effective monitoring and management programs. Aims The aim of this study was to evaluate the effect of poison baiting on invasive red fox (Vulpes vulpes) populations using two alternative population metrics: fox activity from camera trap surveys and density estimation from scat genetic analysis. Methods We conducted before–after control–impact studies in two regions of semi-arid Australia (Wimmera and Mallee) by monitoring paired non-treatment and treatment sites during unbaited and baited periods. We estimated the effects of poison baiting on: (1) a monthly fox activity index, derived from an array of 10 off-road camera traps per site; and (2) fox density. To estimate density, we collected fox scats along 14-km transects, identified individuals using polymorphic microsatellite DNA markers and fitted spatially explicit capture–recapture models. Key results Fox activity remained consistently low at all sites except the Mallee non-treatment. The top-ranked models of fox activity and density contained an interaction between treatment and period, with an interactive and additive effect of region, respectively. However, there was little evidence that baiting reduced fox activity or density. In the unbaited period, fox densities ranged from 0.69 (95% CI: 0.47–1.0) to 1.06 (95% CI: 0.74–1.51) foxes km−2 and were similar across regions. Conclusions Camera traps have the potential to provide continuous index-based measures of fox populations but may not record sufficient observations to detect change. Indices can also be confounded by variations in animal behaviour. Scat genetic analysis is a viable option for providing direct estimates of population change at specific snapshots in time; however, this approach is considerably more expensive, and large sample sizes may be required if genotyping success is low. Implications Our study presents a rare example of multiple concurrent – and non-invasive – monitoring techniques to evaluate the effectiveness of predator control. We highlight the value of rigorous study designs and high-quality density information for designing predator management and monitoring programs.

Population status and density estimate of Leopard Panthera pardus fusca in dry thorn forests of southern India

The study aims to assess the population status and density of the Leopard (Panthera pardus fusca) in the Erode Forest Division, Tamil Nadu. The Erode Forest division has numerous villages within its boundaries and is exposed to associated biotic pressures. In order to improve the management practices of the wildlife in the area and to enhance its conservation, it is relevant to assess its status. In 2018 and 2020, we estimated the population density of the leopard in the entire forest division using 2 km2 sample grids and the camera trapping method. In each grid, we deployed a pair of camera traps, the cumulative number of trap-nights being 22983 (10732 trap nights in 2018 and 12251 in 2020). We analysed the obtained data using spatially explicit capture-recapture models (SECR). The surveys yielded 198 images of the leopard in 2018 and 272 images in 2020, of which 48 and 44 leopard individuals were identified in the respective years based on the rosette pattern. The density estimates were 5.16 (SE = ±0.89) and 4.00 (SE ± 0.72) individuals/100 km2 in 2018 and 2020, respectively. We found that in some regions overlapping with the human-use area, leopard densities were high, indicating that the species successfully exploits areas near human habitation and highlighting its high potential for interaction with humans. This baseline estimate and insights will help prioritize management actions, strengthen large mammal conservation beyond the boundaries of protected areas (PA), and plan human-wildlife conflict mitigation measures to enable the persistence of large carnivores in multi-use forests.

Application of genetic and Spatially Explicit Capture-Recapture analyses to design adaptive feral cat control in a large inhabited island

Faunas of oceanic islands have a high proportion of endemic species which contribute to the uniqueness of island communities. Island species are particularly naïve and vulnerable to alien predators, such as cats (Felis catus). On large, inhabited islands, where the complete eradication of feral cat populations is not considered feasible, control represents the best management option to lower their detrimental effects on native fauna. The first objective of our study was to investigate population genetics of feral cats of Réunion Island. The second objective was to understand the space use of feral cats established near the breeding colonies of the two endemic and endangered seabirds of Réunion Island, the Barau’s Petrel (Pterodroma baraui) and the Mascarene Petrel (Pseudobulweria aterrima). We evaluated genetic diversity, population structure and gene flow amongst six groups of feral cats located at a maximum of 10 km from known petrel colonies. We also analysed the behaviour and space use of one of these feral cat groups using camera-trap data and Spatially Explicit Capture-Recapture (SECR) models. Genetic analyses revealed that feral cats were structured in three genetic clusters explained mostly by the island topography. Two clusters were observed at five sampled sites, suggesting high connectivity amongst these sites. The last cluster was found in only one site, suggesting high isolation. This site was a remote mountain area located in the vicinity of one of the main Barau’s Petrel colonies. The behavioural study was conducted on this isolated feral cat population. Mark recapture analysis suggested that feral cats were present at low density and had large home ranges, which is probably explained by reduced food availability. Finally, we make several recommendations for refining feral cat management programmes on inhabited islands.

Spatial density estimate of the snow leopard, Panthera uncia, in the Central Tibetan Plateau, China.

Knowledge of large carnivore population abundance is essential for wildlife management and conservation, but these data are often difficult to obtain in inherently low-density species. In particular, the snow leopard, Panthera uncia, an enigmatic cat occupying remote mountains in Central Asia, has received insufficient assessments of its population abundance because of logistical and methodological challenges. Here, we aimed to develop a robust density estimation of snow leopards based on 81 days of camera trapping within a contiguous and previously unsurveyed 1950 km2 area of habitat on the Tibetan Plateau (Mayue Township, Shenzha County, Tibet Autonomous Region, China). By applying spatially explicit capture-recapture models, we produced an estimate of 1.40 (95%CI: 1.06-1.84) individuals per 100 km2 . Results also suggested sex-specific variation in the range of movement around activity centers, with male (N = 10, σ = 4.02) movement considerably greater than female (N = 8, σ = 1.84) movement. The findings can serve as a reliable baseline reference for assessing the population trends of this endangered felid species with future estimates. This study will provide context to contribute toward a better understanding of ecological factors shaping the distribution and abundance of snow leopards and the related conservation measures needed to sustain their long-term survival on the Tibetan Plateau.

Occupancy data improves parameter precision in spatial capture-recapture models.

Population size is one of the basic demographic parameters for species management and conservation. Among different estimation methods, spatially explicit capture–recapture (SCR) models allow the estimation of population density in a framework that has been greatly developed in recent years. The use of automated detection devices, such as camera traps, has impressively extended SCR studies for individually identifiable species. However, its application to unmarked/partially marked species remains challenging, and no specific method has been widely used. We fitted an SCR‐integrated model (SCR‐IM) to stone marten Martes foina data, a species for which only some individuals are individually recognizable by natural marks, and estimate population size based on integration of three submodels: (1) individual capture histories from live capture and transponder tagging; (2) detection/nondetection or “occupancy” data using camera traps in a bigger area to extend the geographic scope of capture–recapture data; and (3) telemetry data from a set of tagged individuals. We estimated a stone marten density of 0.352 (SD: 0.081) individuals/km2. We simulated four dilution scenarios of occupancy data to study the variation in the coefficient of variation in population size estimates. We also used simulations with similar characteristics as the stone marten case study, comparing the accuracy and precision obtained from SCR‐IM and SCR, to understand how submodels' integration affects the posterior distributions of estimated parameters. Based on our simulations, we found that population size estimates using SCR‐IM are more accurate and precise. In our stone marten case study, the SCR‐IM density estimation increased the precision by 37% when compared to the standard SCR model as regards to the coefficient of variation. This model has high potential to be used for species in which individual recognition by natural markings is not possible, therefore limiting the need to rely on invasive sampling procedures.

A review of movement models in open population capture–recapture

AbstractUnderstanding rates of survival and recruitment is critical to population management, and capture–recapture methods of estimation are widely used. Spatial models allow for a spatial detection process and can include the movement of activity centres between sampling times. Movement is often treated as a random walk with the step length governed by a probability kernel. However, the movement component of open population spatially explicit capture–recapture models (open SECR) has evolved haphazardly and comparison among studies is difficult.We review published studies, document suitable probability kernels and address the issues of scale and buffer dependence in open SECR by a combination of simulation and case studies on ovenbirdsSeiurus aurocapillaand tigersPanthera tigris.Flexible 2‐parameter kernels, such as the bivariate ‐distribution, fit better than the popular bivariate normal and resulted in higher estimates of survival. We reconcile different parameterizations of the bivariate ‐distribution and identify a problem when the kernel is defined in terms of its margins.Movement models failed to separate mortality and emigration in simulated data when the data were a random mixture of long and short movements. Our estimates of ovenbird survival were buffer‐dependent, and we interpret this as a sign that the data are inadequate for joint modelling of survival and movement. Estimates of tiger survival were more nearly asymptotic on buffer width.We repeat the warning of earlier authors that movement models are effective for separating mortality and emigration only when the data span the range of movement. We appeal for more complete and consistent reporting of movement models and identify topics for future research.