Revisiting the effect of capture heterogeneity on survival estimates in capture-mark-recapture studies: does it matter?
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ABSTRACT:
SUBMITTER: Abadi F
PROVIDER: S-EPMC3639964 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Capture-mark-recapture (CMR) studies have been used extensively in ecology and evolution. While it is feasible to apply CMR in some animals, it is considerably more challenging in small fast-moving species such as insects. In these groups, low recapture rates can bias estimates of demographic parameters, thereby handicapping effective analysis and management of wild populations. Here, we use high-speed videos (HSV) to capture two large dragonfly species, Anax junius and Rhionaeschna multicolor, that rarely land and, thus, are particularly challenging for CMR studies. We test whether HSV, compared to conventional "eye" observations, increases the "resighting" rates and, consequently, improves estimates of both survival rates and the effects of demographic covariates on survival. We show that the use of HSV increases the number of resights by 64% in A. junius and 48% in R. multicolor. HSV improved our estimates of resighting and survival probability which were either under- or overestimated with the conventional observations. Including HSV improved credible intervals for resighting rate and survival probability by 190% and 130% in A. junius and R. multicolor, respectively. Hence, it has the potential to open the door to a wide range of research possibilities on species that are traditionally difficult to monitor with distance sampling, including within insects and birds.
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Project description: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 elephant seals.Including recycled individuals did not affect estimates of capture, survival, and tag-retention probabilities. However, with low tag-retention rates, high capture rates, and high survival rates, recycled individuals produced overestimates of population size. For the elephant seal case study, we found population size estimates to be between 8% and 53% larger when recycled individuals were ignored.Ignoring the effects of recycled individuals can cause large biases in population size estimates. These results are particularly noticeable in longer studies.
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Project description:Understanding age-dependent patterns of survival is fundamental to predicting population dynamics, understanding selective pressures, and estimating rates of senescence. However, quantifying age-specific survival in wild populations poses significant logistical and statistical challenges. Recent work has helped to alleviate these constraints by demonstrating that age-specific survival can be estimated using mark-recapture data even when age is unknown for all or some individuals. However, previous approaches do not incorporate auxiliary information that can improve age estimates of individuals. We introduce a survival estimator that combines a von Bertalanffy growth model, age-specific hazard functions, and a Cormack-Jolly-Seber mark-recapture model into a single hierarchical framework. This approach allows us to obtain information about age and its uncertainty based on size and growth for individuals of unknown age when estimating age-specific survival. Using both simulated and real-world data for two painted turtle (Chrysemys picta) populations, we demonstrate that this additional information substantially reduces the bias of age-specific hazard rates, which allows for the testing of hypotheses related to aging. Estimating patterns of senescence is just one practical application of jointly estimating survival and growth; other applications include obtaining better estimates of the timing of recruitment and improved understanding of life-history trade-offs between growth and survival.
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Project description:Capture-recapture (CR) models are an essential tool for estimating demographic parameters in most animal and some plant populations. To avoid drawing incorrect conclusions in any statistical inference, a crucial prerequisite is to assess the goodness of fit of a general model to the data. In CR models, a frequent cause of lack of fit, is the so-called transience effect, which is due to a lower expectation of re-observation of individuals marked for the first time as compared to other individuals. The transience effect may result either from different biological causes or from the sampling procedure. A transience effect is usually treated by distinguishing at least two age-classes in the survival probability, but other approaches may be more suitable. Here we develop a conceptual and analytical framework for including a transience effect in capture-recapture models. We show the implementation of two additional parametrizations that incorporate a transience effect. With these parametrizations, we can directly estimate the "transience probability" defined as the probability that a newly caught individual disappear from the population beyond what is expected based on the behavior of the previously caught individuals in the same sample. Additionally, these parametrizations allow testing biological hypotheses concerning drivers affecting this probability. Results from our case study show differences between parametrizations, with the parametrization most currently used giving different estimates, especially when including covariates. We advocate for a unifying framework for treating a transience effect, that helps clarifying the ideas and terminology, and where the biological reasons should be the rule for choosing the appropriate analytical procedure. This framework will also open new and powerful ways for the detection and exploration of ecological processes such as the costs of the first reproduction or the deleterious effects of some types of marking.
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Project description:BackgroundParasite evolution is hypothesized to select for levels of parasite virulence that maximise transmission success. When host population densities fluctuate, low levels of virulence with limited impact on the host are expected, as this should increase the likelihood of surviving periods of low host density. We examined the effects of Morogoro arenavirus on the survival and recapture probability of multimammate mice (Mastomys natalensis) using a seven-year capture-mark-recapture time series. Mastomys natalensis is the natural host of Morogoro virus and is known for its strong seasonal density fluctuations.ResultsAntibody presence was negatively correlated with survival probability (effect size: 5-8% per month depending on season) but positively with recapture probability (effect size: 8%).ConclusionsThe small negative correlation between host survival probability and antibody presence suggests that either the virus has a negative effect on host condition, or that hosts with lower survival probability are more likely to obtain Morogoro virus infection, for example due to particular behavioural or immunological traits. The latter hypothesis is supported by the positive correlation between antibody status and recapture probability which suggests that risky behaviour might increase the probability of becoming infected.
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Project description:Population parameters of poorly marked gregarious species are difficult to estimate. This is the case for common dolphins (Delphinus sp.), a genus known for its lack of distinctive marks resulting in a low mark ratio. Furthermore, the widespread nature of common dolphins results in low recaptures. We developed reliable photo-identification protocols to ensure accurate identification of individuals in the Hauraki Gulf, New Zealand. These protocols combined the use of nicks and notches and pigmentation patterns for identification and included the development of a distinctiveness threshold. The data were further stratified by the level of distinctiveness of each individual (as distinctive or highly-distinctive). Photo-identification surveys were conducted from January 2010 to December 2013. Mark-recapture techniques were implemented through a POPAN super-population approach to estimate seasonal apparent survival, capture probability and abundance of dolphins. A total of 2,083 unique adult common dolphins were identified, 51.3% were classified as D1 (highly distinctive; n = 1,069) and 48.7% as D2 (distinctive; n = 1,014). Of all individuals identified, 34.3% (n = 704) were re-sighted over subsequent years. The proportion of marked dolphins (when compared to unmarked dolphins) was 26.3% for D1 and 46.4% for D1 & D2, respectively. Apparent survival was estimated at 0.767 (CI = 0.694-0.827) for D1 animals, and 0.796 (CI = 0.729-0.850) for D1 & D2 combined. For D1 only, seasonal abundance varied from 732 (CI = 460-1,177) in autumn 2010 to 5,304 (CI = 4,745-5,930) in spring 2013. While the inclusion of D2 individuals may offer a more precise estimate of total abundance, the inability to determine additional sources of bias (for example, arising from under or overestimated mark ratios) meant that estimates for D1 individuals were deemed the least biased for this population. The photo-identification protocol, stratification of the data and steps taken to eliminate potential model violations provided a useful and novel approach to estimate population parameters for common dolphins. These approaches could be implemented for other large gregarious populations (≥500 individuals) of animals with poor natural markings.
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Project description:The Cormack-Jolly-Seber (CJS) model assumes that all marked animals have equal recapture probabilities at each sampling occasion, but heterogeneity in capture often occurs and should be taken into account to avoid biases in parameter estimates. Although diagnostic tests are generally used to detect trap-dependence or transience and assess the overall fit of the model, heterogeneity in capture is not routinely tested for. In order to detect and identify this phenomenon in a CJS framework, we propose a test of positive association between previous and future encounters using Goodman-Kruskal's gamma. This test is based solely on the raw capture histories and makes no assumption on model structure. The development of the test is motivated by a dataset of Sandwich terns (Thalasseus sandvicensis), and we use the test to formally show that they exhibit heterogeneity in capture. We use simulation to assess the performance of the test in the detection of heterogeneity in capture, compared to existing and corrected diagnostic goodness-of-fit tests, Leslie's test of equal catchability and Carothers' extension of the Leslie test. The test of positive association is easy to use and produces good results, demonstrating high power to detect heterogeneity in capture. We recommend using this new test prior to model fitting as the outcome will guide the model-building process and help draw more accurate biological conclusions. Supplementary materials accompanying this paper appear online. Electronic Supplementary Material:Supplementary materials for this article are available at 10.1007/s13253-017-0315-4.
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Project description:Error-tolerant likelihood-based match calling presents a promising technique to accurately identify recapture events in genetic mark-recapture studies by combining probabilities of latent genotypes and probabilities of observed genotypes, which may contain genotyping errors. Combined with clustering algorithms to group samples into sets of recaptures based upon pairwise match calls, these tools can be used to reconstruct accurate capture histories for mark-recapture modelling. Here, we assess the performance of a recently introduced error-tolerant likelihood-based match-calling model and sample clustering algorithm for genetic mark-recapture studies. We assessed both biallelic (i.e. single nucleotide polymorphisms; SNP) and multiallelic (i.e. microsatellite; MSAT) markers using a combination of simulation analyses and case study data on Pacific walrus (Odobenus rosmarus divergens) and fishers (Pekania pennanti). A novel two-stage clustering approach is demonstrated for genetic mark-recapture applications. First, repeat captures within a sampling occasion are identified. Subsequently, recaptures across sampling occasions are identified. The likelihood-based matching protocol performed well in simulation trials, demonstrating utility for use in a wide range of genetic mark-recapture studies. Moderately sized SNP (64+) and MSAT (10-15) panels produced accurate match calls for recaptures and accurate non-match calls for samples from closely related individuals in the face of low to moderate genotyping error. Furthermore, matching performance remained stable or increased as the number of genetic markers increased, genotyping error notwithstanding.
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