Balancing bias and precision in capture‐recapture estimates of abundance

Abstract

Capture-recapture estimates of abundance using photographic identification data are sensitive to the quality of photographs used and distinctiveness of individuals in the population. Here analyses are presented for examining the effects of photographic quality and individual animal distinctiveness scores and for objectively selecting a subset of data to use for capture-recapture analyses using humpback whale (Megaptera novaeangliae) data from a 2-year study in the North Atlantic. Photographs were evaluated for their level of quality and whales for their level of individual distinctiveness. Photographic quality scores had a 0.21 probability of changing by a single-quality level, and there were no changes by two or more levels. Individual distinctiveness scores were not independent of photographic quality scores. Estimates of abundance decreased as poor-quality photographs were removed. An appropriate balance between precision and bias in abundance estimates was achieved by removing the lowest-quality photographs and those of incompletely photographed flukes given our assumptions about the true population abundance. A simulation of the selection process implied that, if the estimates are negatively biased by heterogeneity, the increase in bias produced by decreasing the sample size is not more than 2%. Capture frequencies were independent of individual distinctiveness scores.Key words: abundance estimation, capture-recapture, humpback whale, individual animal distinctiveness, individual identification, mark-recapture, Megaptera novaeangliae, North Atlantic, photographic identification, photographic quality.Photographs of natural markings are used to identify individual animals in a process known as photo-identification. Photo-identification has been used in a number of capture-recapture studies to estimate animal abundance and survival rates of several species (e.g., Buckland 1990, Hammond et al. 1990, Flatt et al. 1997, Langtimm et al. 1998, Baker 1999, Zeh et al. 2002, Calambokidis and Barlow 2004, Mizroch et al. 2004. When photo-identification is used in capture-recapture studies, the ability to accurately identify individuals from photographs needs to be examined. Accurate identification of individuals will depend on the quality of the photographs used and the distinctiveness of the natural markings of the individuals (Hammond 1986). Errors in identification can occur as false negatives and false positives and affect the accuracy of the resulting estimates.Photographic quality (hereafter referred to as quality) includes the clarity and contrast of the photograph, the angle of the markings to the plane of the photograph (angle), and the proportion of the animal or identifying feature that is photographed. Natural markings include color patterns, the shape of features, and scars. The distinctiveness of markings can depend on the complexity of a color pattern or a feature's shape and the number and size of scars.False-positive errors occur when different individuals are incorrectly identified as the same ...

Abundance, survival and temporary emigration of bottlenose dolphins (Tursiops sp.) off Useless Loop in the western gulf of Shark Bay, Western Australia

“…There are several special considerations when using photo-identification data for population demographic capture-recapture analyses (Gowans and Whitehead 2001;Friday et al 2008;Hammond 2010). First and foremost, individuals should be photographed so as to ensure sufficient quality to confirm identification, as well as to ensure the photograph passes the quality-grading process.…”

Current Knowledge on the Distribution and Relative Abundance of Humpback Whales (<I>Megaptera novaeangliae</I>) off the Cape Verde Islands, Eastern North Atlantic

“…Fluke photographs, which are used to identify individual humpbacks from the unique pattern of pigmentation and scars on the ventral surface, were obtained with a 35-mm digital camera. Only those fluke photographs for which quality and individual distinctiveness was 3-or better were used in this analysis (Friday et al, 2000(Friday et al, , 2008.…”

First time series of estimated humpback whale (Megaptera novaeangliae) abundance in Prince William Sound

“…Typically, in the case of photo identification of humpback whales, it is unlikely to have false positive errors; namely, instances where photos are wrongly designated as re-sightings. However, the occurrence of false negative errors-instances where photos are wrongly designated as new sightings when they are actually resightings-increases with the inclusion of poor quality photos (Friday et al 2000(Friday et al , 2008Stevick et al 2001). Efforts were taken to reduce the occurrence of this type of error by removing the photographs determined to be of poor quality.…”

“…A double tagging study by Stevick et al (2001) showed that false positive errors were absent altogether and false negative errors were negligible (0.1 %). Heterogeneity was assessed in a study by Friday et al (2008) where the authors concluded that the most accurate results could be found by simply removing poor quality photos. In the present study, we implemented a photo quality standard and built models including fluke distinctiveness covariates and found that they were not selected based on AICc values.…”

“…Fluke distinctiveness could also play a role in producing false negative errors, instances where photos are wrongly designated as new sightings, which would introduce positive bias in abundance in a mark-recapture analysis (Friday et al 2000(Friday et al , 2008Stevick et al 2001). Flukes bear wildly different patterns and markings, making some individuals more identifiable than others.…”