Reliable Population Density Estimates Research Articles

How abundant is a species at the limit of its distribution range? Crested porcupine Hystrix cristata and its northern population.

The crested porcupine (Hystrix cristata) is a rodent present in Africa and southern Europe (Italy exclusively). The Italian population is expanding from the centre to the north and south, but little is known about the species' abundance. Reliable population density estimates are important for monitoring trends in wildlife populations and for developing effective conservation and management strategies. In this context, we aimed to first report crested porcupine population density on the northern limit of its current distribution range using a non-invasive approach. Specifically, we randomly placed 38 camera traps in an area of 242 km2 in north Italy (Lombardy region), and we applied camera trap distance sampling. We estimated a porcupine density of 0.49 ind·km-2 (±0.33, standard error). The results presented here are the first crested porcupine density estimate accounting for imperfect detection (i.e. species present but not detected). The abundance estimate reported here is fundamental for a better understanding of the species status in Europe and for implementing conservation and management plans.

Spatial capture-recapture and LiDAR-derived vegetation metrics reveal high densities of ocelots on Texas ranchlands

Reliable estimates of population density and size are crucial to wildlife conservation, particularly in the context of the Endangered Species Act. In the United States, ocelots (Leopardus pardalis pardalis) were listed as endangered in 1982, and to date, only one population density estimate has been reported in Texas. In this study, we integrated vegetation metrics derived from LiDAR and spatial capture-recapture models to discern factors of ocelot encounter rates and estimated localized population estimates on private ranchlands in coastal southern Texas. From September 2020 to May 2021, we conducted a camera trap study across 42 camera stations on the East Foundation’s El Sauz Ranch, which was positioned within a larger region of highly suitable woody and herbaceous cover for ocelots. We observed a high density of ocelots (17.6 ocelots/100 km2) and a population size of 36.3 ocelots (95% CI: 26.1–58.6) with the 206.25 km2 state space area of habitat. The encounter probability of ocelots increased with greater canopy cover at 1-2 m height and decreasing proximity to woody cover. These results suggest that the incorporation of LiDAR-derived vegetative canopy metrics allowed us to understand where ocelots are likely to be detected, which may aid in current and future population monitoring efforts. These population estimates reflect the first spatially explicit and most recent estimates in a portion of the northernmost population of ocelots in southern Texas. This study further demonstrates the importance of private working lands for the recovery of ocelots in Texas.

Estimating the density of a small population of leopards (Panthera pardus) in central Iran using multi-session photographic\u2010sampling data

West Asian drylands host a number of threatened large carnivores, including the leopard (Panthera pardus) which is limited generally to areas with low primary productivity. While conservation efforts have focused on these areas for several decades, reliable population density estimates are missing for many of them. Spatially explicit capture–recapture (SECR) methodology is a widely accepted population density estimation tool to monitor populations of large carnivores and it incorporates animal movement in the statistical estimation process. We employed multi-session maximum-likelihood SECR modeling to estimate the density of a small population of leopard in a mountainous environment surrounded by deserts in central Iran. During 6724 camera trap nights, we detected 8 and 5 independent leopards in 2012 and 2016 sessions, respectively. The top-performing model produced density estimates of 1.6 (95% CI = 0.9–2.9) and 1.0 (95% CI = 0.6–1.6) independent leopards/100 km2 in 2012 and 2016, respectively. Both sex and season had substantial effects on spatial scale (σ), with larger movements recorded for males, and during winter. The estimates from our density estimation exercise represent some of the lowest densities across the leopard global range and strengthen the notion that arid habitats support low densities of the species. These small populations are vulnerable to demographic stochasticity, and monitoring temporal changes in their population density and composition is a critical tool in assisting conservation managers to better understand their population performance.

Density of leopard in a moist-temperate forest of western Himalaya, India

Widespread conversion of the biodiversity rich habitats into land for cultivation and human habitation has resulted in extensive habitat loss for wildlife including leopard. In order to prioritize investments and assess conservation intervention and effectiveness reliable estimates of population density are required. We carried out camera-trapping and line-transect surveys to estimate the predator and prey densities in moist-temperate forest of Dachigam National Park, north-western Himalaya. Density estimate for leopard (Panthera pardus) obtained from programme CAPTURE was 2.8 ± SE 1.18/100 km2 and the SECR density obtained from software SPACECAP was 0.744 ± SE 0.18/100 km2. Density estimate obtained using software DISTANCE for the two principal prey species was 5.11 ± 0.51/km2 and 16.32 ± 1.87/km2 for hangul (Cervus hanglu ssp. hanglu) and langur (Semnopithecus ajax), respectively. The leopard density estimates, which are a first record from the study area, turned out to be the lowest in the country. The low densities of prey represent an alarming status of the species as well as of forest ecosystems of the study area. Our baseline estimates for the leopard and prey species will help future research, conservation and management strategies.

Modelling the effect of covariates on the detectability and density of native blackbucks and invasive feral-horse using Multiple Covariate Distance Sampling at Point Calimere Wildlife Sanctuary, Southern India

Reliable estimates of population size and a knowledge of determinants of detectability and density estimates are crucial for effective conservation of species. Using Multiple Covariate Distance Sampling (MCDS), we modelled the influence of covariates on detection probability and density estimates of native blackbuck Antilope cervicapra and the invasive feral-horse Equus caballus at Point Calimere Wildlife Sanctuary. Grids of 1 × 1 km size were overlaid on the study area with a 1-km line transect in alternate grid cells. Sixteen transects were walked four times each, which detected 199 blackbuck and 152 feral-horse clusters. On each sighting, the climatic, habitat and anthropogenic covariates were recorded, which are likely to affect detection probability. At first, exploratory analyses were made using Conventional Distance Sampling (CDS) to arrive at estimates. Later, in Multiple Covariate Distance Sampling (MCDS), key models were fit into the dataset after selecting the potential covariates that had a significant effect on detection distances obtained from FAMD/PCA, and the best one was selected based on AIC. The MCDS analysis in blackbuck included covariates, viz., distance to water in the best model (29 individuals/km2; CI 22–36; detection probability = 0.58), followed by distance to feral-horse, sampling time and principal diet. The covariate distance to water emerged as the best model for feral-horse as well (13 individuals/km2; CI 9–18; detection probability = 0.36), followed by distance to cattle and principal diet. While the MCDS approach outperformed the CDS global and survey-strata estimates in blackbuck, both the approaches had a marginal difference in feral-horse. Post-stratification analysis showed that blackbuck density increased significantly with distance to water and feral-horse, but insignificantly with the absence of principal diet; whereas, the density of the feral-horse increased significantly with distance to water and cattle in the presence of principal diet. These findings suggest the ability of feral-horse to keep the blackbuck away from optimal areas, where the principal diet is abundant. Our study, thus, illustrates the need for the use of MCDS approach that ascertained (i) reliable population density estimates, (ii) spatiotemporal constraint on large herbivores caused by overabundance of water during the wet season, and (iii) competitive interaction of the invasive feral-horse with the native blackbuck and its likely effect on the latter keeping away from the former and the principal diet to overcome competition. Thus, the study highlights the impact of feral-horse on the native species and suggests measures for the long-term conservation of the blackbuck.

A paradox of local abundance amidst regional rarity: the value of montane refugia for Persian leopard conservation

The population densities of leopards vary widely across their global range, influenced by prey availability, intraguild competition and human persecution. In Asia, particularly the Middle East and the Caucasus, they generally occur at the lower extreme of densities recorded for the species. Reliable estimates of population density are important for understanding their ecology and planning their conservation. We used a photographic spatial capture-recapture (SCR) methodology incorporating animal movement to estimate density for the endangered Persian leopard Panthera pardus saxicolor in three montane national parks, northeastern Iran. We combined encounter history data arising from images of bilaterally asymmetrical left- and right-sided pelage patterns using a Bayesian spatial partial identity model accommodating multiple “non-invasive” marks. We also investigated the effect of camera trap placement on detection probability. Surprisingly, considering the subspecies’ reported low abundance and density based on previous studies, we found relatively high population densities in the three national parks, varying between 3.10 ± SD 1.84 and 8.86 ± SD 3.60 individuals/100 km2. The number of leopards detected in Tandoureh National Park (30 individuals) was larger than estimated during comparable surveys at any other site in Iran, or indeed globally. Capture and recapture probabilities were higher for camera traps placed near water resources compared with those placed on trails. Our results show the benefits of protecting even relatively small mountainous areas, which accommodated a high density of leopards and provided refugia in a landscape with substantial human activity.

Improving estimation of puma (Puma concolor) population density: clustered camera-trapping, telemetry data, and generalized spatial mark-resight models

Obtaining reliable population density estimates for pumas (Puma concolor) and other cryptic, wide-ranging large carnivores is challenging. Recent advancements in spatially explicit capture-recapture models have facilitated development of novel survey approaches, such as clustered sampling designs, which can provide reliable density estimation for expansive areas with reduced effort. We applied clustered sampling to camera-traps to detect marked (collared) and unmarked pumas, and used generalized spatial mark-resight (SMR) models to estimate puma population density across 15,314 km2 in the southwestern USA. Generalized SMR models outperformed conventional SMR models. Integrating telemetry data from collars on marked pumas with detection data from camera-traps substantially improved density estimates by informing cryptic activity (home range) center transiency and improving estimation of the SMR home range parameter. Modeling sex of unmarked pumas as a partially identifying categorical covariate further improved estimates. Our density estimates (0.84–1.65 puma/100 km2) were generally more precise (CV = 0.24–0.31) than spatially explicit estimates produced from other puma sampling methods, including biopsy darting, scat detection dogs, and regular camera-trapping. This study provides an illustrative example of the effectiveness and flexibility of our combined sampling and analytical approach for reliably estimating density of pumas and other wildlife across geographically expansive areas.

Toward reliable population density estimates of partially marked populations using spatially explicit mark-resight methods.

Camera traps are used increasingly to estimate population density for elusive and difficult to observe species. A standard practice for mammalian surveys is to place cameras on roads, trails, and paths to maximize detections and/or increase efficiency in the field. However, for many species it is unclear whether track‐based camera surveys provide reliable estimates of population density.Understanding how the spatial arrangement of camera traps affects population density estimates is of key interest to contemporary conservationists and managers given the rapid increase in camera‐based wildlife surveys.We evaluated the effect of camera‐trap placement, using several survey designs, on density estimates of a widespread mesopredator, the red fox Vulpes vulpes, over a two‐year period in a semi‐arid conservation reserve in south‐eastern Australia. Further, we used the certainty in the identity and whereabouts of individuals (via GPS collars) to assess how resighting rates of marked foxes affect density estimates using maximum likelihood spatially explicit mark–resight methods.Fox detection rates were much higher at cameras placed on tracks compared with off‐track cameras, yet in the majority of sessions, camera placement had relatively little effect on point estimates of density. However, for each survey design, the precision of density estimates varied considerably across sessions, influenced heavily by the absolute number of marked foxes detected, the number of times marked foxes was resighted, and the number of detection events of unmarked foxes.Our research demonstrates that the precision of population density estimates using spatially explicit mark–resight models is sensitive to resighting rates of identifiable individuals. Nonetheless, camera surveys based either on‐ or off‐track can provide reliable estimates of population density using spatially explicit mark–resight models. This underscores the importance of incorporating information on the spatial behavior of the subject species when planning camera‐trap surveys.

Comparing clustered sampling designs for spatially explicit estimation of population density

AbstractSpatially explicit capture–recapture methods do not assume that animals have equal access to sampling devices (e.g., detectors), which allows for gaps in the sampling extent and nonuniform (e.g., clustered) sampling designs. However, the performance (i.e., relative root mean squared error [RRMSE], confidence interval coverage, relative bias and relative standard error) of clustered detector arrays has not been thoroughly evaluated. I used simulations to evaluate the performance of various detector and cluster spacings, cluster configurations (i.e., number of detectors arranged in a square grid), sampling extents and number of sampling occasions for estimating population density, the relationship between detection rate and distance to a detector from the animal's center of activity (σ) and base detection rates, using American black bears (Ursus americanus) as a case study. My simulations indicated that a wide range of detector configurations can provide reliable estimates if spacing between detectors in clusters is ≥1σ and ≤3σ. A number of cluster configurations and occasion lengths produced estimates that were unbiased, resulted in good spatial coverage, and were relatively precise. Moreover, increasing the duration of sampling, establishing large study areas, increasing detection rates and spacing clusters so that cross‐cluster sampling of individuals can occur could help ameliorate deficiencies in the detector layout. These results have application for a wide array of species and sampling methods (e.g., DNA sampling, camera trapping, mark‐resight and search‐encounter) and suggest that clustered sampling can significantly reduce the effort necessary to provide reliable estimates of population density across large spatial extents that previously would have been infeasible with nonclustered sampling designs.

Estimating population densities of temperate, insectivorous bats based on automatically recorded calls

Estimating population density based on automatically recorded calls is a key topic in bioacoustics, as individual recognition of animals is impossible. Several recently developed models do not require individual recognition but nevertheless allow to estimate density. However, there is a need to test these models on empirical data. Here, we used generalized random encounter models (gREM) to estimate population densities based on automatically recorded bat calls. To check the validity of the derived estimates, we fit Royle-Nichols models to species detection/non-detection data. Estimates of the two models were compared to each other and to estimates from published studies. The estimates of both models and literature estimates were within the same order of magnitude. Both models give reliable estimates of population density. However, we provide some cautionary notes for practical use: Bats which enter the detection sphere from above might bias results of gREMs, as the model simplifies the detection sphere to a two-dimensional area. On the other hand, reduction to detection/non-detection data in Royle-Nichols models results in information loss, which could limit their applicability in common species. Finally, we recommend to consider species behaviour carefully when applying one of the tested models.Estimating population density based on automatically recorded calls is a key topic in bioacoustics, as individual recognition of animals is impossible. Several recently developed models do not require individual recognition but nevertheless allow to estimate density. However, there is a need to test these models on empirical data. Here, we used generalized random encounter models (gREM) to estimate population densities based on automatically recorded bat calls. To check the validity of the derived estimates, we fit Royle-Nichols models to species detection/non-detection data. Estimates of the two models were compared to each other and to estimates from published studies. The estimates of both models and literature estimates were within the same order of magnitude. Both models give reliable estimates of population density. However, we provide some cautionary notes for practical use: Bats which enter the detection sphere from above might bias results of gREMs, as the model simplifies the detection sphere to...

Genetic sampling for estimating density of common species.

Understanding population dynamics requires reliable estimates of population density, yet this basic information is often surprisingly difficult to obtain. With rare or difficult‐to‐capture species, genetic surveys from noninvasive collection of hair or scat has proved cost‐efficient for estimating densities. Here, we explored whether noninvasive genetic sampling (NGS) also offers promise for sampling a relatively common species, the snowshoe hare (Lepus americanus Erxleben, 1777), in comparison with traditional live trapping. We optimized a protocol for single‐session NGS sampling of hares. We compared spatial capture–recapture population estimates from live trapping to estimates derived from NGS, and assessed NGS costs. NGS provided population estimates similar to those derived from live trapping, but a higher density of sampling plots was required for NGS. The optimal NGS protocol for our study entailed deploying 160 sampling plots for 4 days and genotyping one pellet per plot. NGS laboratory costs ranged from approximately $670 to $3000 USD per field site. While live trapping does not incur laboratory costs, its field costs can be considerably higher than for NGS, especially when study sites are difficult to access. We conclude that NGS can work for common species, but that it will require field and laboratory pilot testing to develop cost‐effective sampling protocols.

Abundance and density estimates for common leopard Panthera pardus and clouded leopard Neofelis nebulosa in Manas National Park, Assam, India

AbstractEffective conservation of rare carnivores requires reliable estimates of population density for prioritizing investments and assessing the effectiveness of conservation interventions. We used camera traps and capture–recapture analysis to provide the first reliable abundance and density estimates for the common leopard Panthera pardus and clouded leopard Neofelis nebulosa in Manas National Park, India. In 57 days of camera trapping, with a total of 4,275 camera-trap days, we photo-captured 27 individually identified common leopards (11 males, 13 females and three unidentified), and 16 clouded leopards (four males, five females and seven unidentified). The abundance estimates using the Mh jackknife and Pledger model Mh were 47.0 and 35.6, respectively, for the common leopard, and 21.0 and 25.0, respectively, for the clouded leopard. Density estimates using maximum likelihood spatially-explicit capture–recapture were 3.4 ± SE 0.82 and 4.73 ± SE 1.43 per 100 km2 for the common and clouded leopards, respectively. Spatially-explicit capture–recapture provided more realistic density estimates compared with those obtained from conventional methods. Our data indicates that camera trapping using a capture–recapture framework is an effective tool for assessing population sizes of cryptic and elusive carnivores such as the common and clouded leopards. The study has established a baseline for the long-term monitoring programme for large carnivores in Manas National Park.

Leopard density in post‐conflict landscape, Cambodia: Evidence from spatially explicit capture–recapture

AbstractEffective conservation of large carnivores requires reliable estimates of population density, often obtained through capture–recapture analysis, in order to prioritize investments and assess conservation intervention effectiveness. Recent statistical advances and development of user‐friendly software for spatially explicit capture–recapture (SECR) circumvent the difficulties in estimating effective survey area, and hence density, from capture–recapture data. We conducted a camera‐trapping study on leopards (Panthera pardus) in Mondulkiri Protected Forest, Cambodia. We compared density estimates using SECR with those obtained from conventional approaches in which the effective survey area is estimated using a boundary strip width based on observed animal movements. Density estimates from Chao heterogeneity models (3.8 ± SE 1.9 individuals/100 km2) and Pledger heterogeneity models and models accounting for gender‐specific capture and recapture rates (model‐averaged density 3.9 ± SE 2.9 individuals/100 km2) were similar to those from SECR in program DENSITY (3.6 ± SE 1.0/100 km2) but higher than estimates from Jack‐knife heterogeneity models (2.9 ± SE 0.9 individuals/100 km2). Capture probabilities differed between male and female leopards probably resulting from differences in the use of human‐made trails between sexes. Given that there are a number of biologically plausible reasons to expect gender‐specific variation in capture probabilities of large carnivores, we recommend exploratory analysis of data using models in which gender can be included as a covariate affecting capture probabilities particularly given the demographic importance of breeding females for population recovery of threatened carnivores. © 2011 The Wildlife Society.

Evaluating exuvia collection as a management tool for the federally endangered Hine’s emerald dragonfly, Somatochlora hineana Williamson (Odonata: Cordulidae)

Reliable population density estimates are crucial for monitoring endangered species. Many species are difficult to capture or range over large areas, making direct monitoring of populations through capture or observation extremely challenging. In such cases, indirect methods of assessing populations can be the only source of reliable information. We examined whether the discarded exoskeleton of the last larval instar (exuvia), left behind when dragonflies emerge into the adult stage, could be used to predict larval densities and provide life history information for the federally listed endangered, Hine’s Emerald Dragonfly ( Somatochlora hineana). Using standardized protocols, we collected exuvia within six 2 × 2 m plots in an ephemeral wetland in Door County, Wisconsin during spring and summer of 1999 and 2000. S. hineana is a “summer emerger”, with more than 95% of the emergence occurring from late June until mid-July. Based on time of emergence and the flight period, adults appear to live a month or longer. The sex ratio at emergence did not differ significantly from a 1:1 ratio and emergence was synchronous between the sexes. Estimates of larval population density using exuvial data were similar to those obtained through intensive direct sampling for larvae. Exuvial collections provide a reliable estimate of larval population density, help link larval ecology to adult ecology and are a useful tool for assessing habitat suitability. Although sampling exuviae requires repeated searching on particular sites, less expertise and fewer people are required for this type of sampling, indicating that exuvial surveys can be a very effective tool for monitoring populations of endangered dragonflies.

Spoor counts as indices of large carnivore populations: the relationship between spoor frequency, sampling effort and true density

1. Studies of large carnivore populations and, particularly, reliable estimates of population density are necessary for effective conservation management. However, these animals are difficult to study, and direct methods of assessing population size and density are often expensive and time‐consuming. 2. Indirect sampling, by counting spoor, could provide repeatable and inexpensive measures of some population parameters. The relationship between true population density and indirect sampling results has seldom been described in large carnivore studies. 3. In northern Namibia the population densities of leopards, lions and wild dogs were measured through recognition of individuals and groups. Spoor counts were then conducted independently, to assess the relationship between true density and the distribution of spoor. 4. Sampling effort, both in terms of the number of roads and total road distance in a sample zone, and the intensity of sampling, had a marked effect on the accuracy and precision of spoor frequency calculations. 5. In a homogeneous habitat, leopard spoor were evenly spread along different roads and spoor frequency was independent of road length. Taking into account very low sample sizes, the spoor density of leopards, lions and wild dogs showed a strong linear correlation with true density. The slope of the regression for leopards was different to that of lions and wild dogs.

Macroinvertebrate Subsampling: A Simplified Apparatus and Approach

A simple, inexpensive, volumetric, subsampling apparatus for processing macroinvertebrate samples is described. Random mixing of the macroinvertebrates was consistently achieved with the subsampler when applied to either lotic or lentic samples. Protocols for the use of the subsampler are forwarded for the situations when either reliable population density estimates or only general trends in community composition and abundance are required.Key words: subsampling, macroinvertebrates