multimark: an R package for analysis of capture–recapture data consisting of multiple “noninvasive” marks

I describe an open‐source R package, multimark , for estimation of survival and abundance from capture–mark–recapture data consisting of multiple “noninvasive” marks. Noninvasive marks include natural pelt or skin patterns, scars, and genetic markers that enable individual identification in lieu of physical capture. multimark provides a means for combining and jointly analyzing encounter histories from multiple noninvasive sources that otherwise cannot be reliably matched (e.g., left‐ and right‐sided photographs of bilaterally asymmetrical individuals). The package is currently capable of fitting open population Cormack–Jolly–Seber (CJS) and closed population abundance models with up to two mark types using Bayesian Markov chain Monte Carlo (MCMC) methods. multimark can also be used for Bayesian analyses of conventional capture–recapture data consisting of a single‐mark type. Some package features include (1) general model specification using formulas already familiar to most R users, (2) ability to include temporal, behavioral, age, cohort, and individual heterogeneity effects in detection and survival probabilities, (3) improved MCMC algorithm that is computationally faster and more efficient than previously proposed methods, (4) Bayesian multimodel inference using reversible jump MCMC, and (5) data simulation capabilities for power analyses and assessing model performance. I demonstrate use of multimark using left‐ and right‐sided encounter histories for bobcats (Lynx rufus) collected from remote single‐camera stations in southern California. In this example, there is evidence of a behavioral effect (i.e., trap “happy” response) that is otherwise indiscernible using conventional single‐sided analyses. The package will be most useful to ecologists seeking stronger inferences by combining different sources of mark–recapture data that are difficult (or impossible) to reliably reconcile, particularly with the sparse datasets typical of rare or elusive species for which noninvasive sampling techniques are most commonly employed. Addressing deficiencies in currently available software, multimark also provides a user‐friendly interface for performing Bayesian multimodel inference using capture–recapture data consisting of a single conventional mark or multiple noninvasive marks.     

Survival and abundance of short‐finned pilot whales in the archipelago of Madeira,NE Atlantic

Estimates of population parameters for the short‐finned pilot whale, Globicephala macrorhynchus, are scarce in literature, contributing to an International Union for Conservation of Nature (IUCN) status of Data Deficient. In this study, photo‐identification data collected over 7 yr from Madeira were used to estimate for the first time survivorship, capture probability, and abundance in this species using mark‐recapture methodology. The Cormack‐Jolly‐Seber model estimated that the adult island‐associated (i.e., resident and regular visitor) whales had a constant survival rate of 0.960 (95% CI: 0.853–0.990) and an annual capture probability varying between 0.372 (CI: 0.178–0.619) and 0.843 (CI: 0.619–0.947). A parameterization of the Jolly‐Seber model estimated that 140 island‐associated whales (CI: 131–151) used the area throughout the course of the study. Based on a closed population model, the most precise (lower CV) annual estimate of the total number of pilot whales using the southern and eastern waters of Madeira (~900 km²) in a 3 mo period covering summer/autumn was 334 animals (CI: 260–437). No trend was observed. Despite including biases, the approach used in this study provided plausible estimates of population parameters, which can contribute to the regional conservation strategies.     

Cormack–Jolly–Seber model with environmental covariates: A P‐spline approach

In capture–recapture models, survival and capture probabilities can be modelled as functions of time‐varying covariates, such as temperature or rainfall. The Cormack–Jolly–Seber (CJS) model allows for flexible modelling of these covariates; however, the functional relationship may not be linear. We extend the CJS model by semi‐parametrically modelling capture and survival probabilities using a frequentist approach via P‐splines techniques. We investigate the performance of the estimators by conducting simulation studies. We also apply and compare these models with known semi‐parametric Bayesian approaches on simulated and real data sets.     

Trap‐shyness subsidence is a threshold function of mark–recapture interval in brown mudfish Neochanna apoda populations

The influence of capture interval on trap shyness, and temperature, rainfall and drought on capture probability (p) in 827 brown mudfish Neochanna apoda was quantified using mark–recapture models. In particular, it was hypothesized that the loss of trapping memory in marked N. apoda would lead to a capture‐interval threshold required to minimize trap shyness. Neochanna apoda trap shyness approximated a threshold response to capture interval, declining rapidly with increasing capture intervals up to 16·5 days, after which p remained constant. Tests for detecting trap‐dependent capture probability in Cormack–Jolly–Seber models failed to detect trap shyness in N. apoda capture histories with capture intervals averaging 16 days. This confirmed the applicability of the 16 day capture‐interval threshold for mark–recapture studies. Instead, N. apoda p was positively influenced by water temperature and rainfall during capture. These results imply that a threshold capture interval is required to minimize the trade‐off between the competing assumptions of population closure and p homogeneity between capture occasions in closed mark–recapture models. Moreover, environmental factors that influence behaviour could potentially confound abundance indices, and consequently abundance trends should be interpreted with caution in the face of long‐term climate change, such as with global warming.     

Seasonal abundance and adult survival of bottlenose dolphins (Tursiops truncatus) in a community that cooperatively forages with fishermen in southern Brazil

A subgroup of a population of Tursiops truncatus in southern Brazil is known for a cooperative behavior with artisanal fishermen whereby the dolphins shoal fish towards net‐casting fishermen. Combining photo‐identification data collected between September 2007 and 2009 with mark‐recapture and Pollock's robust design models, we assessed abundance within seasons and survival and temporary emigration rates of dolphins between seasons. We also reanalyzed a previous data set collected during 1989–1991, and Cormack‐Jolly‐Seber models were applied to estimate survival rates for each of the study periods. The abundance of marked “cooperative” dolphins varied between seasons from 18 (CI: 17–24) to 21 (CI: 20–24). The total abundance varied from 59 in the winter of 2008 (CI: 49–72) to 50 in the autumn of 2009 (CI: 40–62). The annual adult survival was estimated to be 0.917 (CI: 0.876–0.961), close to that estimated from data collected in the 1990s (0.941; CI: 0.888–0.998). The emigration probability was low (0.031; CI: 0.011–0.084) and different capture probabilities between the “cooperative” and “noncooperative” dolphins indicated a degree of behavioral segregation. The precision of our estimates is likely to provide sufficient power to detect population change, but we recommend a precautionary management approach to protect this vulnerable dolphin community and its unique cooperative feeding tradition.     

A temporally stratified extension of space-for-time Cormack–Jolly–Seber for migratory animals

Understanding drivers of temporal variation in demographic parameters is a central goal of mark-recapture analysis. To estimate the survival of migrating animal populations in migration corridors, space-for-time mark–recapture models employ discrete sampling locations in space to monitor marked populations as they move past monitoring sites, rather than the standard practice of using fixed sampling points in time. Because these models focus on estimating survival over discrete spatial segments, model parameters are implicitly integrated over the temporal dimension. Furthermore, modeling the effect of time-varying covariates on model parameters is complicated by unknown passage times for individuals that are not detected at monitoring sites. To overcome these limitations, we extended the Cormack–Jolly–Seber (CJS) framework to estimate temporally stratified survival and capture probabilities by including a discretized arrival time process in a Bayesian framework. We allow for flexibility in the model form by including temporally stratified covariates and hierarchical structures. In addition, we provide tools for assessing model fit and comparing among alternative structural models for the parameters. We demonstrate our framework by fitting three competing models to estimate daily survival, capture, and arrival probabilities at four hydroelectric dams for over 200 000 individually tagged migratory juvenile salmon released into the Snake River, USA.     

Assessing the abundance of Bristol Bay belugas with genetic mark‐recapture methods

The Bristol Bay stock of beluga whales (Delphinapterus leucas) is genetically distinct and resides in Bristol Bay year‐round. We estimated the abundance of this population using genetic mark‐recapture, whereby genetic markers from skin biopsies, collected between 2002 and 2011, were used to identify individuals. We identified 516 individual belugas in two inner bays, 468 from Kvichak Bay and 48 from Nushagak Bay, and recaptured 75 belugas in separate years. Using a POPAN Jolly‐Seber model, abundance was estimated at 1,928 belugas (95% CI = 1,611–2,337), not including calves, which were not sampled. Most belugas were sampled in Kvichak Bay at a time when belugas are also known to occur in Nushagak Bay. The pattern of genetic recaptures and data from belugas with satellite transmitters suggested that belugas in the two bays regularly mix. Hence, the estimate of abundance likely applies to all belugas within Bristol Bay. Simulations suggested that POPAN estimates of abundance are robust to most forms of emigration, but that emigration causes negative bias in both capture and survival probabilities. Because it is likely that some belugas do not enter the sampling area during sampling, our estimate of abundance is best considered a minimum population size.     

State–space mark–recapture estimates reveal a recent decline in abundance of North Atlantic right whales

North Atlantic right whales (Eubalaena glacialis Müller 1776) present an interesting problem for abundance and trend estimation in marine wildlife conservation. They are long lived, individually identifiable, highly mobile, and one of the rarest of cetaceans. Individuals are annually resighted at different rates, primarily due to varying stay durations among several principal habitats within a large geographic range. To date, characterizations of abundance have been produced that use simple accounting procedures with differing assumptions about mortality. To better characterize changing abundance of North Atlantic right whales between 1990 and 2015, we adapted a state–space formulation with Jolly‐Seber assumptions about population entry (birth and immigration) to individual resighting histories and fit it using empirical Bayes methodology. This hierarchical model included accommodation for the effect of the substantial individual capture heterogeneity. Estimates from this approach were only slightly higher than published accounting procedures, except for the most recent years (when recapture rates had declined substantially). North Atlantic right whales' abundance increased at about 2.8% per annum from median point estimates of 270 individuals in 1990 to 483 in 2010, and then declined to 2015, when the final estimate was 458 individuals (95% credible intervals 444–471). The probability that the population's trajectory post‐2010 was a decline was estimated at 99.99%. Of special concern was the finding that reduced survival rates of adult females relative to adult males have produced diverging abundance trends between sexes. Despite constraints in recent years, both biological (whales' distribution changing) and logistical (fewer resources available to collect individual photo‐identifications), it is still possible to detect this relatively recent, small change in the population's trajectory. This is thanks to the massive dataset of individual North Atlantic right whale identifications accrued over the past three decades. Photo‐identification data provide biological information that allows more informed inference on the status of this species.     

A local evaluation of the individual state‐space to scale up Bayesian spatial capture–recapture

Spatial capture–recapture models (SCR) are used to estimate animal density and to investigate a range of problems in spatial ecology that cannot be addressed with traditional nonspatial methods. Bayesian approaches in particular offer tremendous flexibility for SCR modeling. Increasingly, SCR data are being collected over very large spatial extents making analysis computational intensive, sometimes prohibitively so. To mitigate the computational burden of large‐scale SCR models, we developed an improved formulation of the Bayesian SCR model that uses local evaluation of the individual state‐space (LESS). Based on prior knowledge about a species’ home range size, we created square evaluation windows that restrict the spatial domain in which an individual's detection probability (detector window) and activity center location (AC window) are estimated. We used simulations and empirical data analyses to assess the performance and bias of SCR with LESS. LESS produced unbiased estimates of SCR parameters when the AC window width was ≥5σ (σ: the scale parameter of the half‐normal detection function), and when the detector window extended beyond the edge of the AC window by 2σ. Importantly, LESS considerably decreased the computation time needed for fitting SCR models. In our simulations, LESS increased the computation speed of SCR models up to 57‐fold. We demonstrate the power of this new approach by mapping the density of an elusive large carnivore—the wolverine (Gulo gulo)—with an unprecedented resolution and across the species’ entire range in Norway (> 200,000 km²). Our approach helps overcome a major computational obstacle to population and landscape‐level SCR analyses. The LESS implementation in a Bayesian framework makes the customization and fitting of SCR accessible for practitioners working at scales that are relevant for conservation and management.     

Species richness estimation and determinants of species detectability in butterfly monitoring programmes

Abstract 1. Species richness is the most widely used biodiversity index, but can be hard to measure. Many species remain undetected, hence raw species counts will often underestimate true species richness. In contrast, capture–recapture methods estimate true species richness and correct for imperfect and varying detectability. 2. Detectability is a crucial quantity that provides the link between a species count and true species richness. For insects, it has hardly ever been estimated, although this is required for the interpretation of species counts. 3. In the Swiss butterfly monitoring programme about 100 transect routes are surveyed seven times a year using a highly standardised protocol. In July 2003, control observers made two additional surveys on 38 transects. Data from these 38 quadrats were analysed to see whether currently available capture–recapture models can provide quadrat‐specific estimates of species richness, and to estimate species detectability in relation to transect, observer, survey, region, and abundance. 4. Species richness over the entire season cannot be estimated using current capture–recapture methods. The species pool was open, preventing use of closed population models, and detectability varied by species, preventing use of current open population models. Assuming a closed species pool during two mid‐season (July) surveys, a Jackknife capture–recapture method was used that accounts for heterogeneity to estimate mean detectability and species richness. 5. In every case, more species were present than were counted. Mean species detectability was 0.61 (SE 0.01) with significant differences between observers (range 0.37–0.83). Species‐specific detection at time t+ 1 was then modelled for those species seen at t for three mid‐season surveys. Detectability averaged 0.50 (range 0.17–0.81) for individual species and 0.65, 0.44, and 0.42 for surveys. Abundant species were detected more easily, although this relationship explained only 5% of variation in species detectability. 6. These are important, although not entirely unexpected, results for species richness estimation of short‐lived animals. Raw counts of species may be misleading species richness indicators unless many surveys are conducted. Monitoring programmes should be calibrated, i.e. the assumption of constant detectability over dimensions of interest needs to be tested. The development of capture–recapture or similar models that can cope with both open populations and heterogeneous species detectability to estimate species richness should be a research priority.     

Open Capture–Recapture Models with Heterogeneity: II. Jolly–Seber Model

Summary Estimation of abundance is important in both open and closed population capture–recapture analysis, but unmodeled heterogeneity of capture probability leads to negative bias in abundance estimates. This article defines and develops a suite of open population capture–recapture models using finite mixtures to model heterogeneity of capture and survival probabilities. Model comparisons and parameter estimation use likelihood‐based methods. A real example is analyzed, and simulations are used to check the main features of the heterogeneous models, especially the quality of estimation of abundance, survival, recruitment, and turnover. The two major advances in this article are the provision of realistic abundance estimates that take account of heterogenetiy of capture, and an appraisal of the amount of overestimation of survival arising from conditioning on the first capture when heterogeneity of survival is present.     

NOTES ON THE BREEDING OF THE BOKMAKIRI

Counting Saddle-billed Storks in a study area the size of the Kruger National Park, at 2.2 million ha, is difficult because the birds are long-lived, sparse in the landscape and have large home ranges. Aerial surveys conducted to date provide an estimate with no measure of data dispersion, thence precision. The aim of this study was to estimate the population size within associated confidence limits using a modified mark–recapture field method. The vehicle survey, conducted shortly after rainfall in the area, did not produce results with known precision under these conditions. A repeat of this census in spring, after the peak breeding season and when surface water is confined to the larger rivers and dams, should yield different results. A photographic census technique yielded sufficient information to construct a population registration database. Individual identification profiles indicate that there are at least 40 adult Saddle-billed Storks in the southern part of the Kruger National Park. This is considered the minimum number of known-to-be-alive individuals in this area. In this paper, the Cormack–Jolly–Seber mark– recapture model was used to return an estimate of the population size for each capture occasion.     

Using dynamic N‐mixture models to test cavity limitation on northern flying squirrel demographic parameters using experimental nest box supplementation

Dynamic N‐mixture models have been recently developed to estimate demographic parameters of unmarked individuals while accounting for imperfect detection. We propose an application of the Dail and Madsen ( 2011 : Biometrics, 67 , 577–587) dynamic N‐mixture model in a manipulative experiment using a before‐after control‐impact design (BACI). Specifically, we tested the hypothesis of cavity limitation of a cavity specialist species, the northern flying squirrel, using nest box supplementation on half of 56 trapping sites. Our main purpose was to evaluate the impact of an increase in cavity availability on flying squirrel population dynamics in deciduous stands in northwestern Québec with the dynamic N‐mixture model. We compared abundance estimates from this recent approach with those from classic capture–mark–recapture models and generalized linear models. We compared apparent survival estimates with those from Cormack–Jolly–Seber (CJS) models. Average recruitment rate was 6 individuals per site after 4 years. Nevertheless, we found no effect of cavity supplementation on apparent survival and recruitment rates of flying squirrels. Contrary to our expectations, initial abundance was not affected by conifer basal area (food availability) and was negatively affected by snag basal area (cavity availability). Northern flying squirrel population dynamics are not influenced by cavity availability at our deciduous sites. Consequently, we suggest that this species should not be considered an indicator of old forest attributes in our study area, especially in view of apparent wide population fluctuations across years. Abundance estimates from N‐mixture models were similar to those from capture–mark–recapture models, although the latter had greater precision. Generalized linear mixed models produced lower abundance estimates, but revealed the same relationship between abundance and snag basal area. Apparent survival estimates from N‐mixture models were higher and less precise than those from CJS models. However, N‐mixture models can be particularly useful to evaluate management effects on animal populations, especially for species that are difficult to detect in situations where individuals cannot be uniquely identified. They also allow investigating the effects of covariates at the site level, when low recapture rates would require restricting classic CMR analyses to a subset of sites with the most captures.     

Estimation of capture probabilities using generalized estimating equations and mixed effects approaches

Modeling individual heterogeneity in capture probabilities has been one of the most challenging tasks in capture–recapture studies. Heterogeneity in capture probabilities can be modeled as a function of individual covariates, but correlation structure among capture occasions should be taking into account. A proposed generalized estimating equations (GEE) and generalized linear mixed modeling (GLMM) approaches can be used to estimate capture probabilities and population size for capture–recapture closed population models. An example is used for an illustrative application and for comparison with currently used methodology. A simulation study is also conducted to show the performance of the estimation procedures. Our simulation results show that the proposed quasi‐likelihood based on GEE approach provides lower SE than partial likelihood based on either generalized linear models (GLM) or GLMM approaches for estimating population size in a closed capture–recapture experiment. Estimator performance is good if a large proportion of individuals are captured. For cases where only a small proportion of individuals are captured, the estimates become unstable, but the GEE approach outperforms the other methods.     

An evaluation of multiple‐pass seining to monitor blackstripe topminnow Fundulus notatus (Rafinesque, 1820) in the Sydenham River (Ontario,Canada)

Multiple‐pass (i.e. removal) sampling and mark‐recapture experiments were undertaken in the Sydenham River (Ontario, Canada) to assess the effectiveness of seining to detect and estimate the local abundance of blackstripe topminnow, Fundulus notatus (Rafinesque, 1820) as well as to compare catch characteristics from closed and open (with and without block nets) sample units. Probability of species detection using three‐pass seining was estimated to be 0.58 in closed units, and 0.51 in open units. To be 95% confident of occupancy status, a minimum of five repeat surveys is required. A decline in catch occurred in only half of the sample units, population size estimates were often imprecise, and attempts to generate mark‐recapture population estimates were unsuccessful. Mean capture probabilities were 0.48 in closed units and 0.65 in open units, when depletion occurred. For blackstripe topminnow and other fishes encountered, there were no significant differences between closed and open units in the frequency of depletion or capture probability. Compared to single‐pass surveys, monitoring programs that employ three seine hauls are more likely to detect the presence of the blackstripe topminnow and any decline in local abundance.     

Geographic variation and environmental correlates of apparent survival rates in adult tree swallows Tachycineta bicolor

Determining demographic rates in wild animal populations and understanding why rates vary are important challenges in population ecology and conservation. Whereas reproductive success is reported frequently for many songbird species, there are relatively few corresponding estimates of annual survival for widespread populations of the same migratory species. We incorporated mark–recapture data into Cormack–Jolly–Seber models to estimate annual apparent survival and recapture rates of adult male and female tree swallows Tachycineta bicolor in eight local breeding populations across North America for periods of 7–33 yr. We found strong site‐specific and annual variation in apparent survival rates of adult swallows, and evidence of higher survival or site fidelity among males than females. There were no strong associations between putative overwintering region and survival. Strength and patterns of winter climate‐apparent survival relationships varied across four sites monitored for >15 yr; at one site, spring pond conditions, local spring precipitation and, to a lesser extent, winter North Atlantic Oscillation Index were credible predictors of annual apparent survival. Further work is needed to evaluate how survival is related to environmental conditions throughout the annual cycle and how these factors affect population dynamics of swallows and related species of conservation concern.     

Movement patterns and study area boundaries: influences on survival estimation in capture–mark–recapture studies

The inability to account for the availability of individuals in the study area during capture–mark–recapture (CMR) studies and the resultant confounding of parameter estimates can make correct interpretation of CMR model parameter estimates difficult. Although important advances based on the Cormack–Jolly–Seber (CJS) model have resulted in estimators of true survival that work by unconfounding either death or recapture probability from availability for capture in the study area, these methods rely on the researcher's ability to select a method that is correctly matched to emigration patterns in the population. If incorrect assumptions regarding site fidelity (non‐movement) are made, it may be difficult or impossible as well as costly to change the study design once the incorrect assumption is discovered. Subtleties in characteristics of movement (e.g. life history‐dependent emigration, nomads vs territory holders) can lead to mixtures in the probability of being available for capture among members of the same population. The result of these mixtures may be only a partial unconfounding of emigration from other CMR model parameters. Biologically‐based differences in individual movement can combine with constraints on study design to further complicate the problem. Because of the intricacies of movement and its interaction with other parameters in CMR models, quantification of and solutions to these problems are needed. Based on our work with stream‐dwelling populations of Atlantic salmon Salmo salar, we used a simulation approach to evaluate existing CMR models under various mixtures of movement probabilities. The Barker joint data model provided unbiased estimates of true survival under all conditions tested. The CJS and robust design models provided similarly unbiased estimates of true survival but only when emigration information could be incorporated directly into individual encounter histories. For the robust design model, Markovian emigration (future availability for capture depends on an individual's current location) was a difficult emigration pattern to detect unless survival and especially recapture probability were high. Additionally, when local movement was high relative to study area boundaries and movement became more diffuse (e.g. a random walk), local movement and permanent emigration were difficult to distinguish and had consequences for correctly interpreting the survival parameter being estimated (apparent survival vs true survival).     

U‐CARE: Utilities for performing goodness of fit tests and manipulating CApture–REcapture data

In any statistical analysis, assessing the goodness of fit of a model to the data is crucial to avoid drawing incorrect conclusions. U‐CARE is a computer application that deals with the mandatory first steps of the analyses of capture–recapture data: the preparation of the data set and the assessment of the fit of a general model (Cormack‐Jolly‐Seber and variants for single‐state data; Jolly‐Move and variants for multi‐state data). U‐CARE implements the current state of the art in goodness‐of‐fit testing by incorporating components aimed at detecting the most likely departures from assumptions ( Pradel et al. 2003, 2005 ). It is a free and stand‐alone application for Windows.     

Updated assessment of hatchery‐reared pallid sturgeon (Forbes & Richardson, 1905) survival in the lower Missouri River

As pallid sturgeon, Scaphirhynchus albus (Forbes & Richardson, 1905), natural reproduction and recruitment remains very minimal in the lower Missouri River from Gavins Point Dam (river kilometer [rkm] 1305.2) to the confluence with the Mississippi River (rkm 0.0), hatchery supplementation and river‐wide monitoring efforts have continued. Annual survival estimates of hatchery‐reared pallid sturgeon stocked in the lower Missouri River were previously estimated during 1994–2008. Low recapture rates prior to 2006 limited the data available to estimate survival, which resulted in considerable uncertainty for the estimate of annual survival of age‐1 fish. Therefore, the objective was to provide more precise estimates of annual survival of pallid sturgeon using five additional years of stocking and sampling. The Cormack‐Jolly‐Seber model structure provided in program MARK was used to estimate the age‐specific survival estimates. Over 135 000 hatchery‐reared pallid sturgeon were released during 1994–2011 and recaptured at a rate of 1.9%, whereby estimates for the annual survival of age‐0 (Ø = 0.048) and >age‐1 (Ø = 0.931) were similar to those previously reported, but the age‐1 (Ø = 0.403) survival estimate was 52% lower. Post hoc analysis using time‐specific survival estimates indicated lower survival for age‐1 fish post‐2003 year classes, relative to the pre‐2002 year classes. An analysis confirms that hatchery‐reared pallid sturgeon continue to survive in the wild. However, low survival during the first 2 years of life is a management concern as efforts are aimed at maximizing genetic diversity and population growth. A follow‐up analysis also demonstrated the variability of capture rates and survival over time, which reinforces the need to continue to monitor and evaluate mark‐recapture data. The mark‐recapture efforts have provided demographic parameter estimates that remain a critical component for species recovery as these data are incorporated into population models.     

Abundance of rare and elusive species: Empirical investigation of closed versus spatially explicit capture–recapture models with lynx as a case study

Effective conservation and management require reliable monitoring methods and estimates of abundance to prioritize human and financial investments. Camera trapping is a non-invasive sampling method allowing the use of capture–recapture (CR) models to estimate abundance while accounting for the difficulty of detecting individuals in the wild. We investigated the relative performance of standard closed CR models and spatially explicit CR models (SECR) that incorporate spatial information in the data. Using simulations, we considered 4 scenarios comparing low versus high detection probability and small versus large populations and contrasted abundance estimates obtained from both approaches. Standard CR and SECR models both provided minimally biased abundance estimates, but precision was improved when using SECR models. The associated confidence intervals also provided better coverage than their non-spatial counterpart. We concluded SECR models exhibit better statistical performance than standard closed CR models and allow for sound management strategies based on density maps of activity centers. To illustrate the comparison, we considered the Eurasian lynx (Lynx lynx) as a case study that provided the first abundance estimates of a local population in France. © 2012 The Wildlife Society.