A collaborative and near-comprehensive North Pacific humpback whale photo-ID dataset

We present an ocean-basin-scale dataset that includes tail fluke photographic identification (photo-ID) and encounter data for most living individual humpback whales (Megaptera novaeangliae) in the North Pacific Ocean. The dataset was built through a broad collaboration combining 39 separate curated photo-ID catalogs, supplemented with community science data. Data from throughout the North Pacific were aggregated into 13 regions, including six breeding regions, six feeding regions, and one migratory corridor. All images were compared with minimal pre-processing using a recently developed image recognition algorithm based on machine learning through artificial intelligence; this system is capable of rapidly detecting matches between individuals with an estimated 97-99% accuracy. For the 2001-2021 study period, a total of 27,956 unique individuals were documented in 157,350 encounters. Each individual was encountered, on average, in 5.6 sampling periods (i.e., breeding and feeding seasons), with an annual average of 87% of whales encountered in more than one season. The combined dataset and image recognition tool represents a living and accessible resource for collaborative, basin-wide studies of a keystone marine mammal in a time of rapid ecological change.

Automated summary

We provide an extensive dataset of humpback whales in the North Pacific Ocean, including photo identification records and encounter data. The dataset was created through collaboration and combines curated photo-ID catalogs with community science data. An image recognition algorithm based on machine learning was used to quickly and accurately match individuals with a 97-99% accuracy rate. Over the study period of 2001-2021, 27,956 unique individuals were documented in 157,350 encounters, with each individual encountered in an average of 5.6 sampling periods.