Spatially Explicit Capture-recapture Research Articles

A new dawn? Population baselines of snow leopards and other mammals of the Kishtwar High Altitude National Park, India

AbstractAccurately assessing the status of threatened species requires reliable population estimates. Despite this necessity, only a small proportion of the global distribution range of the vulnerable snow leopard (Panthera uncia) has been systematically sampled. The Indian section of the Greater Himalayas, which includes Kishtwar High Altitude National Park (KHANP), harbours potential snow leopard habitat. Nevertheless, there has been limited ecological and conservation research focusing on species that are specific to KHANP, as well as limited research on the broader biodiversity of the Greater Himalayas. We used Spatially Explicit Capture‐Recapture (SECR) models to provide—to our knowledge—the first robust snow leopard population density and abundance estimates from KHANP. We also provide a Relative Abundance Index (RAI) for non‐volant mammals (excluding small rodents). Our study sampled three catchments within the Dachhan region of KHANP—Kibber, Nanth and Kiyar—using 44 cameras over a 45‐day period between May and June 2023. We identified four unique snow leopard individuals across 15 detections in nine camera locations. SECR analysis estimated a density of 0.50 snow leopards per 100 km2 (95% confidence interval: 0.13–1.86), corresponding to an abundance of four individual (4–9) adults. Camera trapping revealed a total of 16 mammal species, including the endangered Kashmir musk deer (Moschus cupreus). Marmots (Marmota caudata) had the highest RAI of 21.3 (±0.2). Although the estimated density and abundance of snow leopards in our study area had relatively wide 95% confidence intervals, our combined results of snow leopard densities and RAIs of prey species such as ibex and marmots indicate that KHANP is a potentially important area for snow leopards. Given the geopolitical history of Jammu and Kashmir in India, the region where KHANP is located, wildlife research remains a low priority. We hope our study encourages authorities to support further research. This study is an initial step towards evaluating the potential of KHANP as a conservation landscape under the Government of India's Project Snow Leopard.

Density matters: How population dynamics of house mice (Mus musculus) inform the epidemiology of Leptospira

Abstract Rodents are maintenance hosts of numerous pathogens, and both their density and the pathogen prevalence determine the risk they pose to other animals or humans. However, density is often overlooked. We investigated a capture‐mark‐recapture‐sampling strategy to study introduced mice (Mus musculus) and Leptospira as a model and demonstrate the advantages of a combined approach. We estimated population density and Leptospira prevalence in mice in a replicated longitudinal survey conducted between 2016 and 2018. Capture‐mark‐recapture sessions were undertaken at two sites in Spring and Autumn and blood and kidney samples were collected at the end of each session. Mouse density and areas of activity were estimated using spatially explicit capture–recapture (SECR) models and both were compared between Leptospira positive and negative mice. Leptospira exposure and shedding status were estimated using Microscopic Agglutination Test, and a combination of culture and lipL32 PCR on kidneys. Leptospira prevalence was higher in spring (83%–86%) than in autumn (31%–37%) and mouse densities simultaneously varied from 3.6 to 55.9/ha. However, despite these variations in prevalence and density, the density of infected animals remained relatively constant over time (3–8/ha). Shedding or being seropositive was also associated with the activity of mice. Shedding or seropositive mice had a larger activity area, and seropositive mice were trapped on average 1 day earlier than seronegative mice. Synthesis and applications: Our results show how understanding the population dynamics of pathogen‐carrying rodents is critical in epidemiology. The wider movement patterns and easier encounters of positive mice highlight the possibility of biases in classical prevalence surveys and have implications for disease transmission within and between species. Importantly, and quite counter‐intuitively, Leptospira prevalence was negatively associated with mouse density, resulting in a constant density of shedders that contradicts the conventional view of higher exposure risk at high rodent density. More broadly, such sampling designs can improve animal and disease control policies and better inform modelling studies by providing more parameter estimates than classical prevalence surveys.

Density of a cryptic Australian small mammal: The threatened Julia Creek dunnart (Sminthopsis douglasi).

Globally, hundreds of mammal species face the threat of extinction in the coming decades, and in many cases, their ecology remains poorly understood. Fundamental ecological knowledge is crucial for effective conservation management of these species, but it is particularly lacking for small, cryptic mammals. The Julia Creek dunnart (Sminthopsis douglasi), a threatened, cryptic carnivorous marsupial that occurs in scattered populations in the central west of Queensland, Australia, was once so poorly studied that it was believed extinct. Sporadic research since its rediscovery in the early 1990s has revealed that S. douglasi is distributed across land at risk from many threats. Fundamental knowledge of S. douglasi population density is urgently required to inform conservation management at key sites, yet the species has historically proven hard to detect. Indeed, the status of the largest known population of S. douglasi, in Bladensburg National Park, is unknown. Here, we conducted a population study on S. douglasi at two sites within Bladensburg National Park via live mark-recapture surveys during 2022 and 2023. From likelihood-based spatially explicit capture-recapture (SECR) modelling we provide the first estimates of density and population size for S. douglasi. Live trapping resulted in captures of 49 individual S. douglasi (with 83 captures total, including recaptures). We estimated S. douglasi to occur at a density of 0.38 individuals ha-1 (0.25-0.58) at one site and 0.16 individuals ha-1 (0.09-0.27) at another site, with an estimated mean population size in suitable habitat at Bladensburg National Park of 1211 individuals (776-1646). Our S. douglasi density estimates were similar to that reported for other threatened small mammals in Australia. We also found evidence of extreme S. douglasi population fluctuations over time at Bladensburg National Park, which is of concern for its future conservation. Our study has provided the first estimate of density for S. douglasi, a threatened dasyurid species from the Mitchell Grass Downs of central western Queensland, Australia. Our research provides crucial population data to assist the management of this poorly studied species. We demonstrate a method that can be applied to species with low detection probability to ultimately help address the mammal extinction crisis faced by Australia and the rest of the world.

Moderate anthropogenic impacts alter temporal niche without affecting spatial distribution of ocelots in the Amazon rainforest

AbstractThe Amazon rainforest faces escalating human disturbances such as logging, mining, agriculture, and urbanization, leading to the conversion of primary forest into matrix habitat. This transformation's impact on mesocarnivores, specifically ocelots (Leopardus pardalis), is still largely unknown. In 2021, we deployed camera traps across a 174 km2 study area in Las Piedras, Madre de Dios, Peru, containing mixed land use and protected forests. Utilizing kernel density functions, we compared temporal activity patterns and employed spatially explicit capture‐recapture (SECR) models to assess density, encounter probability, and movement by habitat and trail type, as well as sex. Of the 293 captures, we identified 39 ocelots (21 females, 18 males), estimating an average density of 31.46 (SE 5.15) individuals per 100 km2 with no significant difference between protected and mixed‐use areas. Baseline detection and movement varied by sex, with male and female home ranges estimated at 17.14 and 4.10 km2, respectively. Ocelot temporal activity patterns differed between the protected area and the mixed‐use area, with increased nocturnality in areas of higher human impact. Our SECR results highlight that matrix habitats can support ocelot populations, emphasizing the need for further research on ocelot demographics in human‐modified Amazon rainforest areas facing varying degrees of anthropogenic disturbance.Abstract in Spanish is available with online material.

The Recolonisation of the Piketberg Leopard Population: A Model for Human–Wildlife Coexistence in a Changing Landscape

Important metapopulation dynamics are disrupted by factors such as habitat loss, climate change, and human-induced mortality, culminating in isolated wildlife populations and threatening species survival. Source populations, where birth rates exceed mortality and connectivity facilitates dispersal, contrast with sink populations, where mortality outstrips births, risking localised extinction. Recolonisation by individuals from source populations is pivotal for species survival. The leopard is the last free-roaming apex predator in South Africa and plays an important ecological role. In the Eastern and Western Cape provinces in South Africa, leopard populations have low densities and fragmented population structures. We identified a leopard population that, after being locally extinct for a century, appeared to recolonise an ‘island’ of mountainous habitat. We aimed to understand potential factors driving this recolonisation using recent camera trapping surveys and historical statutory destruction permits. We employed spatially explicit capture–recapture (SECR) methods to estimate the leopard density and explore potential factors which best explain density. We found that the recently recolonised Piketberg population now exhibits some of the highest densities reported in the region (~1.8 leopards/100 km2; CI 1.4–2.5). Livestock, human presence, elevation, and the camera trap grid appeared to explain leopard detection rates. When considering the historic data, the re-emergence of leopards in the Piketberg coincided with the cessation of the extensive state-sponsored and state-enabled culling of the species, and the change in land use from livestock production to crop agriculture, which likely contributed to the recolonisation. Elucidating these factors deepens our understanding of leopard metapopulation dynamics in relation to land use and species management and highlights the crucial role of private land and state agencies and associated policies in species persistence.

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.

Density estimation of the globally threatened fishing cat Prionailurus viverrinus through a participatory science approach in the Chilika lagoon, eastern India

The fishing cat Prionailurus viverrinus is an Indo-Malayan wetland-dependent felid which is listed as Vulnerable on the IUCN Red List. Its main prey, fish, has low energetic demands and is abundant in productive aquatic habitats. This facilitates high piscivore densities and potentially alters expected scaling patterns that link population density to the body mass of small cats. With local community participation, we estimated the density of the fishing cat in Chilika, Asia’s largest brackish water lagoon, located in the state of Odisha, eastern India, with community participation. The study was carried out in 2 phases in different habitats during 2021 and 2022: a homogeneous marshy habitat and its buffer (Northern Block), and a heterogeneous matrix of different land-use types (Southern Block). We deployed a total of 144 camera traps across 4380 trap nights. Using spatially explicit capture-recapture (SECR), we estimated mean (±SE) fishing cat density to be 0.69 ± 0.1 ind. km-2 in the Northern Block and 0.67 ± 0.33 ind. km-2 in the Southern Block. The population abundance estimates for the Northern and the Southern Blocks were 159 ± 23 and 185 ± 91 respectively. In the former, SECR modelling indicated an effect of anthropogenic habitat modification upon the species’ home range extent. Our density estimates are amongst the highest reported for the species outside protected areas. The results imply that Chilika holds an abundant population of the fishing cat, the continued persistence of which requires mitigation of local and external threats to fish populations. Furthermore, our study, with its inclusive approach, sets a precedent for the use of camera trapping for obtaining robust density estimates of species with uniquely marked individuals in wetland habitats.

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.

Using photo by-catch data to reliably estimate spotted hyaena densities over time

Abstract Protected areas are becoming increasingly isolated refugia for large carnivores but remain critical for their survival. Spotted hyaenas (Crocuta crocuta) are important members of the African large carnivore guild but, like other members of the guild, routinely come into conflict with people because of their large home ranges that are not always confined to protected areas. To effectively conserve spotted hyaena populations, it is paramount to monitor their abundance through reliable and cost-effective techniques. We estimated the density of spotted hyaenas in Hluhluwe–iMfolozi Park (HiP), South Africa using camera trap images and a spatially explicit capture-recapture (SECR) framework between 2013 and 2018. We estimated an average of 18.29 ± 3.27 spotted hyaenas per 100 km2 between 2013 and 2018, with an annual estimated high of 20.83/100 km2 in 2014 and a low of 11.98/100 km2 in 2015. Our results demonstrate that camera trap by-catch data can be used for estimating spotted hyaena densities over time. We believe that given the widespread use and deployment of camera traps across Africa, collaborative efforts to use existing data to improve regional and continental estimates and population trends for spotted hyaenas should be a priority.

Spotted hyaena population density across habitat and land use types in southern Tanzania

AbstractAlthough the spotted hyaena (Crocuta crocuta) has been widely considered to be resilient to human disturbance, the species is now thought to be undergoing widespread population declines. Nevertheless, only a handful of population density estimates are available for the species, despite the importance of this information for informing conservation management. This is a consequence of both a lack of surveys and logistical challenges associated with processing spotted hyaena data. In this study, we collaborated with a cohort of students to process camera trap data from the Ruaha‐Rungwa landscape initially collected to estimate lion (Panthera leo) and leopard (Panthera pardus) population density. By doing so, we provide the first spatially explicit population density estimates for spotted hyaena in Tanzania, via spatially explicit capture‐recapture (SECR) modelling. We also examine the relationship between population densities of spotted hyaena, lion and leopard at each site. Spotted hyaena densities varied from 3.55 ± 0.72 adults and sub‐adults per 100 km2 in a miombo (Brachystegia‐Julbernardia) woodland area of Ruaha National Park, to 10.80 ± 1.08 per 100 km2 in a prey‐rich open woodland savannah habitat in Ruaha National Park, with intermediate densities recorded in Rungwa Game Reserve and MBOMIPA Wildlife Management Area. Our results suggest that spotted hyaena density is influenced by prey availability and protection, and the species may be less resilient to human pressures than widely thought. Spotted hyaena densities were generally positively correlated with densities of lion and leopard, suggesting that prey availability and anthropogenic disturbance had a greater impact than interspecific effects in shaping large carnivore densities in this system. Overall, our study provides some of the first insights into an under‐studied species in an under‐researched part of its range, while shedding light into the impact of anthropogenic versus interspecific effects in shaping population status of spotted hyaena in human‐impacted African systems.

Accounting for heterogeneous density and detectability in spatially explicit capture–recapture studies of carnivores

AbstractReliable estimates of population density are fundamental for managing and conserving wildlife. Spatially explicit capture–recapture (SECR) models in combination with information‐theoretic model selection criteria are frequently used to estimate population density. Variation in density and detectability is inevitable and, when unmodeled, can lead to erroneous estimates. Despite this knowledge, the performance of SECR models and information‐theoretic criteria remain relatively untested for populations with realistic levels of variation in density and detectability. We addressed this issue using simulations of American black bear (Ursus americanus) populations with variable density and detectability between sexes and across study areas. We first assessed the reliability of Akaike information criterion adjusted for small sample sizes (AICc) to correctly identify the true data generating model or a good approximating model. We then assessed the bias, accuracy, and precision of density estimates when such a model was selected or not. We demonstrated that unmodeled heterogeneity in detection and, more importantly, density can lead to pronounced bias. However, when a good approximating model is included in the candidate set, models with lower AICc included important forms of variation and yielded accurate estimates. We encourage researchers and practitioners to consider the impact of unmodeled variation in SECR models when making inferences and to strive to include covariates likely to be the most influential based on the species biology and ecology in candidate model sets. Doing so can improve the robustness of wildlife density estimation methods that can be leveraged to make more sound conservation and management decisions.

Estimating wolf (Canis lupus) densities using video camera traps and spatial capture–recapture analysis

AbstractEstimating population density is critical for effective species conservation, wildlife management planning, and long‐term monitoring. Obtaining accurate estimates is especially important for the wolf (Canis lupus), a widely distributed northern hemisphere apex predator whose management and conservation are highly controversial in most of its range, and whose presence usually generates high‐profile media coverage. The peculiarities of wolf social spatial organization and behavior can violate the assumptions of capture–recapture models (uniformity and independence, respectively) to a greater or lesser extent and make it difficult to obtain precise and reliable density estimates. This paper presents a case study, which estimated the population density of the Iberian wolf in the Dorsal Gallega mountain ridge (Galicia, NW Spain) based on the identification of individual wolves from their traits and behavior using video camera traps and spatially explicit capture–recapture (SCR) analyses. The study followed three phases. Firstly, field data were collected by installing camera traps and changing their location until the entire area was sampled. Second, a complete morphological and behavioral study of the wolves recorded was performed to facilitate individual recognition. Third, overdispersion due to gregariousness and other sources of heterogeneity was modeled in the SCR analyses comparing Poisson and negative binomial observation models with different random effects on the baseline detection probability. We estimated a density of 2.88 (SD: 0.37) wolves/100 km2 in the study area. We concluded that estimating wolf population size using camera trap videos, individual identification, and SCR provides a feasible method and can be used for estimating the density in similar species.

Scat DNA as a non-invasive method for estimating the abundance of the vulnerable mala (Lagorchestes hirsutus)

Context Population-monitoring programs often use direct (e.g. live capture or spotlighting) or indirect (e.g. scats sightings) observations to estimate population abundance. Such methods, however, are often inadequate for rare, elusive, or cryptic species due to the difficulty in achieving sufficient encounters or detection rates. The mala (Lagorchestes hirsutus), a small native Australian macropod, listed as Vulnerable by the IUCN, is difficult to capture, susceptible to capture myopathy, and not easily sighted in their dense habitat; consequently, the population size cannot always be estimated. The use of molecular markers to identify individual genotypes from non-invasively collected samples is increasingly being used in wildlife conservation and may be an alternative approach for mala. Aim The aim of this study was to evaluate the efficacy of non-invasive scat DNA sampling to estimate the population abundance of mala. Methods A panel of microsatellite markers was developed for the identification of individual mala via profiling of their scats. Scats were systematically collected from a wild mala population located in an 1100-ha fenced reserve in Western Australia. Individual genotypes were determined using the microsatellite markers, and the abundance of mala was estimated using the genotypes with spatially explicit capture–recapture (SECR) and mark–resight analyses. Key results The genetic markers proved variable and with sufficient exclusionary power to confidently identify unique individuals (mean locus genotyping error rate: 3.1%). Individual genetic identification from scat sampling, when used with traditional mark–recapture/resight analytical models, provides feasible estimates of population abundance. This is the first reliable abundance estimate of this mala population, suggesting a >70% increase in population size since the initial reintroduction of 64 individuals in 2011–13. Conclusions Given the inherent difficulties in surveying mala, this approach would be valuable to ensure effective monitoring of the few remaining fenced and island mala populations to prevent further decline of this vulnerable species. Implications This is the first study to identify species-specific microsatellite markers for mala and use genetic-capture sampling with scat DNA to estimate the abundance of a mala population. The study provides an evaluation of a valuable species monitoring technique that can be applied to other rare, elusive, or cryptic threatened species.

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.

Count me in: Leopard population density in an area of mixed land‐use, Eastern Cape, South Africa

Count me in: Leopard population density in an area of mixed land‐use, Eastern Cape, South Africa

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.

Efficient Discretization of Movement Kernels for Spatiotemporal Capture–Recapture

Spatially explicit capture–recapture (SECR) models treat detection probability as a function of the distance between each animal and its notional activity centre. Open-population variants of these models (open SECR) are increasingly used to estimate the vital rates (survival and recruitment) of spatial populations subject to turnover between sampling times. If activity centres also move between sampling times then modelling the movement can reduce bias in estimates of vital rates. The usual movement model in open SECR is a random walk with step length governed by a probability kernel. Space is discretized in open SECR for computational convenience, and in some implementations this includes truncation of the probability kernel. Computations for the movement submodel are nevertheless very time-consuming owing to the repeated convolution steps and the need to manage boundary effects. A novel ‘sparse’ discretized kernel is proposed that greatly reduces fitting time. The sparse kernel was tested by simulation and applied to two datasets. Differences between models fitted using the sparse and full kernels were minor and unlikely to matter in practice. The sparse kernel extends the practical limits of the movement modelling in open SECR to greater dispersal distances and greater spatial resolution. Supplementary materials accompanying this paper appear online.

Assessing small-mammal trapping design using spatially explicit capture recapture (SECR) modeling on long-term monitoring data.

Few studies have evaluated the optimal sampling design for tracking small mammal population trends, especially for rare or difficult to detect species. Spatially explicit capture-recapture (SECR) models present an advancement over non-spatial models by accounting for individual movement when estimating density. The salt marsh harvest mouse (SMHM; Reithrodontomys raviventris) is a federal and California state listed endangered species endemic to the San Francisco Bay-Delta estuary, California, USA; where a population in a subembayment has been continually monitored over an 18-year period using mark-recapture methods. We analyzed capture data within a SECR modeling framework that allowed us to account for differences in detection and movement between sexes. We compared the full dataset to subsampling scenarios to evaluate how the grid size (area) of the trap design, trap density (spacing), and number of consecutive trapping occasions (duration) influenced density estimates. To validate the subsampling methods, we ran Monte Carlo simulations based on the true parameter estimates for each specific year. We found that reducing the area of the trapping design by more than 36% resulted in the inability of the SECR model to replicate density estimates within the SE of the original density estimates. However, when trapping occasions were reduced from 4 to 3-nights the density estimates were indistinguishable from the full dataset. Furthermore, reducing trap density by 50% also resulted in density estimates comparable to the full dataset and was a substantially better model than reducing the trap area by 50%. Overall, our results indicated that moderate reductions in the number of trapping occasions or trap density could yield similar density estimates when using a SECR approach. This approach allows the optimization of field trapping efforts and designs by reducing field efforts while maintaining the same population estimate compared to the full dataset. Using a SECR approach may help other wildlife programs identify sampling efficiencies without sacrificing data integrity for long term monitoring of population densities.

Comparison of methods for estimating density and population trends for low-density Asian bears

Populations of bears in Asia are vulnerable to extinction and effective monitoring is critical to measure and direct conservation efforts. Population abundance (local density) or growth (λ) are the most sensitive metrics to change. We discuss the value in implementing spatially explicit capture-recapture (SCR), the current gold standard for density estimation, and open population SCR (OPSCR) to monitor changes in density over time. We provide guidance for designing studies to provide estimates with sufficient power to detect changes. Because of the wide availability of camera traps and interest in their use, we consider six density estimation methods and their extensions developed for use with camera traps, with specific consideration of assumptions and applications for monitoring Asian bears. We conducted a power analysis to calculate the precision in estimates needed to detect changes in populations with reference to IUCN Red List criteria. We performed a systematic review of empirical studies implementing camera trap abundance estimation methods and considered sample sizes, effort, and model assumptions required to achieve adequate precision for population monitoring. We found SCR and OPSCR, reliant on “marked” individuals, are currently the only methods with enough power to reliably detect even moderate to major (20–80%) declines. Camera trap methods with unmarked individuals rarely achieved precision sufficient to detect even large declines (80–90%), although with some exceptions (e.g., situations with moderate population densities, large number of sampling sites, or inclusion of ancillary local telemetry data. We describe additional estimation options including line transects, direct observations, monitoring age-specific survival and reproductive rates, and hybrid/integrated methodologies that may have potential to work for some Asian bear populations. We conclude monitoring changes in abundance or density is possible for most Asian bear populations but will require collaboration among researchers over broad spatial extents and extensive financial investment to overcome biological and logistical constraints. We strongly encourage practitioners to consider study design and sampling effort required to meet objectives by conducting simulations, power analyses, and assumption checks prior to implementing monitoring efforts, and reporting standardized dispersion measures such as coefficients of variation to allow for assessment of precision. Our guidance is relevant to other low-density and wide-ranging species.

Monitoring sitatunga (Tragelaphus spekii) populations using camera traps

AbstractPopulation densities are an important consideration for wildlife management. For hunted species, estimates of population size are essential for establishing quotas. There are limited data regarding sitatunga (Tragelaphus spekii) abundance, and few studies have used camera traps for estimating population densities. We estimated sitatunga density in the Mayanja River area of central Uganda using the time in front of the camera (TIFC) method, which yields population density estimates using camera‐trap data without having to identify each individual. Density estimates from the TIFC method averaged 11.1 sitatunga/km2, similar to estimates from a spatially explicit capture–recapture (SECR) study, which requires perfect identification of individuals. These results suggest that TIFC methods accurately estimate population densities and might be an alternative for species where individual identity cannot be determined, or in habitats where typically identifiable species might not be accurately identified to meet the requirements of SECR. In addition, the resulting density estimates can influence management decisions and quotas for hunting.