Details:

Journal Title:
Biometrics
Personal Author:
McClintock, Brett T. ; White, Gary C. ; Pryde, Moira A.
McClintock, Brett T. ; White, Gary C. ; Pryde, Moira A. Less -
NOAA Program & Office:
NMFS (National Marine Fisheries Service) ; AFSC (Alaska Fisheries Science Center)
NMFS (National Marine Fisheries Service) ; AFSC (Alaska Fisheries Science Center) Less -
Description:
Over the past decade, there has been much methodological development for the estimation of abundance and related demographic parameters using mark-resight data. Often viewed as a less-invasive and less-expensive alternative to conventional mark recapture, mark-resight methods jointly model marked individual encounters and counts of unmarked individuals, and recent extensions accommodate common challenges associated with imperfect detection. When these challenges include both individual detection heterogeneity and an unknown marked sample size, we demonstrate several deficiencies associated with the most widely used mark-resight models currently implemented in the popular capture-recapture freeware Program MARK. We propose a composite likelihood solution based on a zero-inflated Poisson log-normal model and find the performance of this new estimator to be superior in terms of bias and confidence interval coverage. Under Pollock's robust design, we also extend the models to accommodate individual-level random effects across sampling occasions as a potentially more realistic alternative to models that assume independence. As a motivating example, we revisit a previous analysis of mark-resight data for the New Zealand Robin (Petroica australis) and compare inferences from the proposed estimators. For the all-too-common situation where encounter rates are low, individual detection heterogeneity is non-negligible, and the number of marked individuals is unknown, we recommend practitioners use the zero-inflated Poisson log-normal mark-resight estimator as now implemented in Program MARK.
Source:
Biometrics. 2019 Sep; 75(3): 799–809.
DOI:
https://doi.org/10.1111/biom.13058
Pubmed ID:
31004437
Pubmed Central ID:
PMC6850357
Document Type:
Journal Article
Rights Information:
CC BY
Compliance:
PMC
Main Document Checksum:
[+]
urn:sha256:517860e4bb7904628e8f3531012e7aa0e2291e8c40352c9cfbb9a61eb74fa7c6
Download URL:
https://repository.library.noaa.gov/view/noaa/26056/noaa_26056_DS1.pdf
File Type:

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