Complete tag loss in capture-recapture studies affects abundance estimates: An elephant seal case study.
Ontology highlight
ABSTRACT:
SUBMITTER: Malcolm-White E
PROVIDER: S-EPMC7069293 | biostudies-literature | 2020 Mar
REPOSITORIES: biostudies-literature
Publications
Complete tag loss in capture-recapture studies affects abundance estimates: An elephant seal case study.
Malcolm-White Emily E McMahon Clive R CR Cowen Laura L E LLE
Ecology and evolution 20200130 5
In capture-recapture studies, recycled individuals occur when individuals lose all of their tags and are recaptured as though they were new individuals. Typically, the effect of these recycled individuals is assumed negligible.Through a simulation-based study of double-tagging experiments, we examined the effect of recycled individuals on parameter estimates in the Jolly-Seber model with tag loss (Cowen & Schwarz, 2006). We validated the simulation framework using long-term census data of elepha ...[more]
Similar Datasets
Project description:Information about how animal abundance varies across landscapes is needed to inform management action but is costly and time-consuming to obtain; surveys of a single population distributed over a large area can take years to complete. Surveys employing small, spatially replicated sampling units improve efficiency, but statistical estimators rely on assumptions that constrain survey design or become less reasonable as larger areas are sampled. Efficient methods that avoid assumptions about similarity of detectability or density among replicates are therefore appealing. Using simulations and data from >3500 black bears sampled on 73 independent study areas in Ontario, Canada, we (1) quantified bias induced by unmodeled spatial heterogeneity in detectability and density; (2) evaluated novel, design-based estimators of average density across replicate study areas; and (3) evaluated two estimators of the variance of average density across study areas: an analytic estimator that assumed an underlying homogeneous spatial Poisson point process for the distribution of animals' activity centers, and an empirical estimator of variance across study areas. In simulations where detectability varied in space, assuming spatially constant detectability yielded density estimates that were negatively biased by 20% to 30%; estimating local detectability and density from local data and treating study areas as independent, equal replicates when estimating average density across study areas using the design-based estimator yielded unbiased estimates at local and landscape scales. Similarly, detectability of black bears varied among study areas and estimates of bear density at landscape scales were higher when no information was shared across study areas when estimating detectability. This approach also maximized precision (relative SEs of estimates of average black bear density ranged from 7% to 18%) and computational efficiency. In simulations, the analytic variance estimator was robust to threefold variation in local densities but the empirical estimator performed poorly. Conducting multiple, similar SECR surveys and treating them as independent replicates during analyses allowed us to efficiently estimate density at multiple scales and extents while avoiding biases caused by pooling spatially heterogeneous data. This approach enables researchers to address a wide range of ecological or management-related questions and is applicable with most types of SECR data.
| S-EPMC9788300 | biostudies-literature
Project description:An increasing number of studies employ spatial capture-recapture models to estimate population size, but there has been limited research on how different spatial sampling designs and trap configurations influence parameter estimators. Spatial capture-recapture models provide an advantage over non-spatial models by explicitly accounting for heterogeneous detection probabilities among individuals that arise due to the spatial organization of individuals relative to sampling devices. We simulated black bear (Ursus americanus) populations and spatial capture-recapture data to evaluate the influence of trap configuration and trap spacing on estimates of population size and a spatial scale parameter, sigma, that relates to home range size. We varied detection probability and home range size, and considered three trap configurations common to large-mammal mark-recapture studies: regular spacing, clustered, and a temporal sequence of different cluster configurations (i.e., trap relocation). We explored trap spacing and number of traps per cluster by varying the number of traps. The clustered arrangement performed well when detection rates were low, and provides for easier field implementation than the sequential trap arrangement. However, performance differences between trap configurations diminished as home range size increased. Our simulations suggest it is important to consider trap spacing relative to home range sizes, with traps ideally spaced no more than twice the spatial scale parameter. While spatial capture-recapture models can accommodate different sampling designs and still estimate parameters with accuracy and precision, our simulations demonstrate that aspects of sampling design, namely trap configuration and spacing, must consider study area size, ranges of individual movement, and home range sizes in the study population.
| S-EPMC3914876 | biostudies-literature
Project description:Population estimates are a fundamental requirement of ecology and conservation. While capture-recapture models are an established method for producing such estimates, their assumption of homogeneous capture probabilities is problematic given that heterogeneity in individual capture probability is inherent to most species. Such variation must be accounted for by abundance models; otherwise, biased estimates are risked.Here, we investigate the performance of four types of heterogeneity models for estimating abundance of male cheetah Acinonyx jubatus, a species with two distinct spatial tactics of territorial and nonterritorial (floater) males. The differences in spatial movements of territory holders and floaters are expected to result in intrasexual heterogeneous capture probabilities. Four heterogeneity models were used to model male abundance at five territories in central Namibia; (a) a spatial tactic model, (b) a finite mixture model, both run in program MARK, (c) a floater-only model, and (d) a heterogeneity Mh model, both run in the program CAPTURE. Camera trap data of cheetah, taken at frequently visited marking trees, were used to derive true abundance. Model results were compared to the true abundance to assess the accuracy of estimates.Only models (a), (b), and (c) were able to consistently produce accurate results. Mixture models do not require prior knowledge regarding spatial tactic of males, which might not always be available. Therefore, we recommend such models as the preferred model type for cheetahs.Results highlight the potential for mixture models in overcoming the challenges of capture probability heterogeneity and in particular their use with species where intrasexual behavioral differences exist.
| S-EPMC6194303 | biostudies-literature
Project description:When estimating population density from data collected on non-invasive detector arrays, recently developed spatial capture-recapture (SCR) models present an advance over non-spatial models by accounting for individual movement. While these models should be more robust to changes in trapping designs, they have not been well tested. Here we investigate how the spatial arrangement and size of the trapping array influence parameter estimates for SCR models. We analysed black bear data collected with 123 hair snares with an SCR model accounting for differences in detection and movement between sexes and across the trapping occasions. To see how the size of the trap array and trap dispersion influence parameter estimates, we repeated analysis for data from subsets of traps: 50% chosen at random, 50% in the centre of the array and 20% in the South of the array. Additionally, we simulated and analysed data under a suite of trap designs and home range sizes. In the black bear study, we found that results were similar across trap arrays, except when only 20% of the array was used. Black bear density was approximately 10 individuals per 100 km(2). Our simulation study showed that SCR models performed well as long as the extent of the trap array was similar to or larger than the extent of individual movement during the study period, and movement was at least half the distance between traps. SCR models performed well across a range of spatial trap setups and animal movements. Contrary to non-spatial capture-recapture models, they do not require the trapping grid to cover an area several times the average home range of the studied species. This renders SCR models more appropriate for the study of wide-ranging mammals and more flexible to design studies targeting multiple species.
| S-EPMC3335117 | biostudies-literature
Project description:Recently developed capture-mark-recapture methods allow us to account for capture heterogeneity among individuals in the form of discrete mixtures and continuous individual random effects. In this article, we used simulations and two case studies to evaluate the effectiveness of continuously distributed individual random effects at removing potential bias due to capture heterogeneity, and to evaluate in what situation the added complexity of these models is justified. Simulations and case studies showed that ignoring individual capture heterogeneity generally led to a small negative bias in survival estimates and that individual random effects effectively removed this bias. As expected, accounting for capture heterogeneity also led to slightly less precise survival estimates. Our case studies also showed that accounting for capture heterogeneity increased in importance towards the end of study. Though ignoring capture heterogeneity led to a small bias in survival estimates, such bias may greatly impact management decisions. We advocate reducing potential heterogeneity at the sampling design stage. Where this is insufficient, we recommend modelling individual capture heterogeneity in situations such as when a large proportion of the individuals has a low detection probability (e.g. in the presence of floaters) and situations where the most recent survival estimates are of great interest (e.g. in applied conservation).
| S-EPMC3639964 | biostudies-literature
Project description:Estimating eco-epidemiological parameters in free-ranging populations can be challenging. As known individuals may be undetected during a field session, or their health status uncertain, the collected data are typically "imperfect". Multi-event capture-mark-recapture (MECMR) models constitute a substantial methodological advance by accounting for such imperfect data. In these models, animals can be "undetected" or "detected" at each time step. Detected animals can be assigned an infection state, such as "susceptible" (S), "infected" (I), or "recovered" (R), or an "unknown" (U) state, when for instance no biological sample could be collected. There may be heterogeneity in the assignment of infection states, depending on the manifestation of the disease in the host or the diagnostic method. For example, if obtaining the samples needed to prove viral infection in a detected animal is difficult, this can result in a low chance of assigning the I state. Currently, it is unknown how much uncertainty MECMR models can tolerate to provide reliable estimates of eco-epidemiological parameters and whether these parameters are sensitive to heterogeneity in the assignment of infection states. We used simulations to assess how estimates of the survival probability of individuals in different infection states and the probabilities of infection and recovery responded to (1) increasing infection state uncertainty (i.e., the proportion of U) from 20 to 90%, and (2) heterogeneity in the probability of assigning infection states. We simulated data, mimicking a highly virulent disease, and used SIR-MECMR models to quantify bias and precision. For most parameter estimates, bias increased and precision decreased gradually with state uncertainty. The probabilities of survival of I and R individuals and of detection of R individuals were very robust to increasing state uncertainty. In contrast, the probabilities of survival and detection of S individuals, and the infection and recovery probabilities showed high biases and low precisions when state uncertainty was >50%, particularly when the assignment of the S state was reduced. Considering this specific disease scenario, SIR-MECMR models are globally robust to state uncertainty and heterogeneity in state assignment, but the previously mentioned parameter estimates should be carefully interpreted if the proportion of U is high.
| S-EPMC6121098 | biostudies-literature
Project description:In capture-recapture and mark-resight surveys, movements of individuals both within and between sampling periods can alter the susceptibility of individuals to detection over the region of sampling. In these circumstances spatially explicit capture-recapture (SECR) models, which incorporate the observed locations of individuals, allow population density and abundance to be estimated while accounting for differences in detectability of individuals. In this paper I propose two Bayesian SECR models, one for the analysis of recaptures observed in trapping arrays and another for the analysis of recaptures observed in area searches. In formulating these models I used distinct submodels to specify the distribution of individual home-range centers and the observable recaptures associated with these individuals. This separation of ecological and observational processes allowed me to derive a formal connection between Bayes and empirical Bayes estimators of population abundance that has not been established previously. I showed that this connection applies to every Poisson point-process model of SECR data and provides theoretical support for a previously proposed estimator of abundance based on recaptures in trapping arrays. To illustrate results of both classical and Bayesian methods of analysis, I compared Bayes and empirical Bayes esimates of abundance and density using recaptures from simulated and real populations of animals. Real populations included two iconic datasets: recaptures of tigers detected in camera-trap surveys and recaptures of lizards detected in area-search surveys. In the datasets I analyzed, classical and Bayesian methods provided similar - and often identical - inferences, which is not surprising given the sample sizes and the noninformative priors used in the analyses.
| S-EPMC3873963 | biostudies-literature
Project description:Past methods for estimating the population frequency of familial cancer syndromes have used cases and controls ignoring the familial nature of genetic disease. In this study we modified the capture-recapture method from ecology to estimate the number of families in central Ohio with Lynch syndrome (LS). We screened 1566 colorectal cancer cases and 545 endometrial cancer cases in central Ohio from 1999 to 2005 and identified 58 with LS. We screened an additional 3346 colorectal and 342 endometrial cancer cases from 2013 to 2016 and identified 149 with LS. We found 12 LS mutations shared between families observed in the first and second studies. We identified three individuals between studies who were closely related and eight who were more distantly related. We used identified family relationships and genetic test results to estimate family size and structure. Applying a modified capture-recapture method we estimate 1693 3-generation families in the area who have 288 unique LS causing mutations. Comprehensive colorectal and endometrial cancer screening will take about 20 years to identify 50% of families with LS. This is the first time that the capture-recapture method has been applied to estimate the burden of families with a specific heritable disease. Family structure reveals the potential extent of prevention and the time necessary to identify a proportion of families with LS.
| S-EPMC6324998 | biostudies-literature
Project description:It is necessary to estimate the population abundance of deer for managing their populations. However, most estimates are from high-density populations inhabiting the forests of North America or Europe; there is currently a lack of necessary knowledge regarding low-density deer populations in different forest habitats. In this article, we used fecal DNA based on the capture-mark-recapture method to estimate the population abundance of Siberian roe deer (Capreolus pygargus) in Liangshui National Nature Reserve in the Lesser Xing'an Mountains, northeast China, where the deer population was found to be of a low density by limited studies. We used a robust survey design to collect 422 fecal pellet groups in 2016 and extracted DNA from those samples, generating 265 different genotypes; we thus identified 77 deer individuals based on six microsatellite markers (Roe1, Roe8, Roe9, BM757, MB25 and OarFCB304). With capture and recapture records of these 77 individuals, the abundance of roe deer was estimated to be 87 deer (80-112, 95% CI) using the Program CAPTURE. Using an effective sampling area which resulted from the mean maximum recapture distance (MMRD), we converted the population abundance to a density of 2.9 deer/km2 (2.7-3.7, 95% CI). Our study estimated the roe deer population abundance by a feces-based capture-mark-recapture approach in northeast China, successfully demonstrating the applicability of non-invasive genetic sampling in monitoring populations of deer in this area, which contributes to the development of low-density deer population ecology and management.
| S-EPMC7401656 | biostudies-literature
Project description: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.
| S-EPMC5677501 | biostudies-literature