Capture–Recapture When Time and Behavioral Response Affect Capture Probabilities

Chao, Anne; Chu, Wenten; Hsu, Chiu Hsieh

doi:10.1111/j.0006-341x.2000.00427.x

Cited by 36 publications

(55 citation statements)

References 25 publications

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“…The capture probability for this whale at time t À 1 is therefore s 1 p t-1 . This treatment is similar to the M b model for behavioral response to capture (Chao et al 2000); however, s 1 only applies to the capture probability in the year prior to capture as a breeder, rather than to all years subsequent to capture as in model M b . Similarly, we describe the reduction in capture probability in the year after calving as the ''postcalf'' effect, incorporating the parameter s 2 into the model.…”

Section: Evaluating Assumptions Of Capture-recapture Modelsmentioning

confidence: 99%

Accounting for female reproductive cycles in a superpopulation capture–recapture framework

Carroll

Childerhouse²,

Fewster

et al. 2013

Ecological Applications

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Abstract. Superpopulation capture-recapture models are useful for estimating the abundance of long-lived, migratory species because they are able to account for the fluid nature of annual residency at migratory destinations. Here we extend the superpopulation POPAN model to explicitly account for heterogeneity in capture probability linked to reproductive cycles (POPAN-s). This extension has potential application to a range of species that have temporally variable life stages (e.g., non-annual breeders such as albatrosses and baleen whales) and results in a significant reduction in bias over the standard POPAN model. We demonstrate the utility of this model in simultaneously estimating abundance and annual population growth rate (k) in the New Zealand (NZ) southern right whale (Eubalaena australis) from 1995 to 2009. DNA profiles were constructed for the individual identification of more than 700 whales, sampled during two sets of winter expeditions in 1995-1998 and 2006-2009. Due to differences in recapture rates between sexes, only sex-specific models were considered. The POPAN-s models, which explicitly account for a decrease in capture probability in non-calving years, fit the female data set significantly better than do standard superpopulation models (DAIC . 25). The best POPAN-s model (AIC) gave a superpopulation estimate of 1162 females for 1995-2009 (95% CL 921, 1467 and an estimated annual increase of 5% (95% CL À2%, 13%). The best model (AIC) gave a superpopulation estimate of 1007 males (95% CL 794, 1276) and an estimated annual increase of 7% (95% CL 5%, 9%) for 1995-2009. Combined, the total superpopulation estimate for 1995-2009 was 2169 whales (95% CL 1836, 2563). Simulations suggest that failure to account for the effect of reproductive status on the capture probability would result in a substantial positive bias (þ19%) in female abundance estimates.

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Section: Evaluating Assumptions Of Capture-recapture Modelsmentioning

confidence: 99%

Accounting for female reproductive cycles in a superpopulation capture–recapture framework

Carroll

Childerhouse²,

Fewster

et al. 2013

Ecological Applications

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“…Thus, the usual likelihood method cannot be easily extended to models incorporating covariates. (iv) The CMLE is scale invariant whereas the UMLE is not (Chao et al, 2000). (ii) For large population sizes, the two types of MLEs are asymptotically equivalent (Sanathanan, 1972) and lead to close estimates and variances, though for finite population sizes they might differ to some extent (Chao, Chu, and Hsu, 2000).…”

Section: Model MM 2 (B): With Both Enduring and Ephemeralmentioning

confidence: 99%

“…(ii) For large population sizes, the two types of MLEs are asymptotically equivalent (Sanathanan, 1972) and lead to close estimates and variances, though for finite population sizes they might differ to some extent (Chao, Chu, and Hsu, 2000). Thus, the usual likelihood method cannot be easily extended to models incorporating covariates.…”

Section: Model MM 2 (B): With Both Enduring and Ephemeralmentioning

confidence: 99%

Modeling Animals' Behavioral Response by Markov Chain Models for Capture–Recapture Experiments

Yang

Chao

2005

Biometrics

Self Cite

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A bivariate Markov chain approach that includes both enduring (long-term) and ephemeral (short-term) behavioral effects in models for capture-recapture experiments is proposed. The capture history of each animal is modeled as a Markov chain with a bivariate state space with states determined by the capture status (capture/noncapture) and marking status (marked/unmarked). In this framework, a conditional-likelihood method is used to estimate the population size and the transition probabilities. The classical behavioral model that assumes only an enduring behavioral effect is included as a special case of the bivariate Markovian model. Another special case that assumes only an ephemeral behavioral effect reduces to a univariate Markov chain based on capture/noncapture status. The model with the ephemeral behavioral effect is extended to incorporate time effects; in this model, in contrast to extensions of the classical behavioral model, all parameters are identifiable. A data set is analyzed to illustrate the use of the Markovian models in interpreting animals' behavioral response. Simulation results are reported to examine the performance of the estimators.

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“…We rewrite c as c = ϕp for some ϕ (>0), which is termed as the behavioural response effect characterizing the behavioural dependency of an individual at the time of second capture attempt (Chao, Chu, & Chiu, ). Note that the dimension of the parameters cannot be reduced by any reparameterization of likelihood , and therefore, the estimability problem persists.…”

Section: Analyses On Dual‐record System: Preliminariesmentioning

confidence: 99%

“…Note that the dimension of the parameters cannot be reduced by any reparameterization of likelihood , and therefore, the estimability problem persists. However, the reparameterized likelihood in terms of ϕ and p may be of interest in lieu of likelihood (Chao, Chu, & Chiu, ); ϕ and p are not estimable separately but their product c is. We will use the ϕ in Section 4.1 to construct various simulated populations as ϕ has a clear interpretation about the direction of behavioural dependence in DRS (i.e.…”

Section: Analyses On Dual‐record System: Preliminariesmentioning

confidence: 99%

A new integrated likelihood for estimating population size in dependent dual‐record system

Chatterjee¹,

Mukherjee

2018

Can J Statistics

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Efficient estimation of the population size from dependent dual‐record system (DRS) remains a statistical challenge in the capture‐recapture type experiment. Owing to the non‐identifiability of the suitable time‐behavioural response variation model (denoted as Mtb) under DRS, few methods are developed in the Bayesian paradigm based on informative priors. Our contribution in this article is to develop a new integrated likelihood function from model Mtb motivated by a novel approach developed by Severini (2007). A suitable weight function on the nuisance parameter is derived with the knowledge of the direction of behavioural dependency. A pseudo‐likelihood function is constructed so that the resulting estimator possess some desirable properties including negligible prior (or weight) sensitiveness. Extensive simulations show the superior performance of our proposed method to that of the existing Bayesian methods. Moreover, the proposed estimator is easy to implement from the computational perspective. Applications to two real data sets are presented. The Canadian Journal of Statistics 46: 577–592; 2018 © 2018 Société statistique du Canada

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Capture–Recapture When Time and Behavioral Response Affect Capture Probabilities

Cited by 36 publications

References 25 publications

Accounting for female reproductive cycles in a superpopulation capture–recapture framework

Accounting for female reproductive cycles in a superpopulation capture–recapture framework

Modeling Animals' Behavioral Response by Markov Chain Models for Capture–Recapture Experiments

A new integrated likelihood for estimating population size in dependent dual‐record system

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