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◆ Marine Mammal Science2025-10-14· Probabilistic logic

Deriving Probabilistic Age Estimates Using Common Photo‐Identification Catalog Information: An Application to Endangered Hawaiian False Killer Whales ( <scp> <i>Pseudorca crassidens</i> </scp> )

Michaela A. Kratofil, Sabre D. Mahaffy, Karen K. Martien, Frederick I. Archer, Kristi L. West, Susan J. Chivers, Robin W. Baird

原始摘要(英文原文)· Original abstract
ABSTRACT Age is important for studying population dynamics, but it is difficult to obtain reasonably accurate age estimates and associated uncertainty of free‐ranging individuals, especially for cetaceans. We developed a protocol for deriving probabilistic age estimates using information commonly curated in marine mammal photo‐identification catalogs and applied the approach to 81 biopsy‐sampled and genetically sexed false killer whales ( Pseudorca crassidens ) from the endangered main Hawaiian Islands insular population. The protocol integrates qualitative evidence into a quantitative framework for deriving age estimates and plausible age ranges. Confidence ratings reflecting the strength of available evidence were developed to account for uncertainty. Estimates were then translated to statistical distributions to depict probabilistic age estimates that can be used in further analyses. Age estimates ranged from 3 to 40 years (minimum: 1–33; maximum: 5–65) and were strongly influenced by the estimated age when first seen and length of sighting history. Sensitivity analyses show that population‐level age distribution estimates are robust to age class misclassifications and lack of auxiliary information, including sex. This protocol may provide a guide for aging individuals of some species from photo‐identification catalogs and for which other aging methods from biological samples are not yet feasible or available.
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Deriving Probabilistic Age Estimates Using Common Photo‐Identification Catalog Information: An Application to Endangered Hawaiian False Killer Whales ( <scp> <i>Pseudorca crassidens</i> </scp> ) — 科研速览 Science Skim