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Maxent species distribution modelling of 10 cetacean species in the northeastern Pacific from citizen science occurrence records

Dares, Lauren1; Robinson, Chloe1

Published Aug 18, 2025 on Dryad. https://doi.org/10.5061/dryad.sn02v6xfv

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Aug 18, 2025 version files 11.87 MB

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Abstract

Aim: Citizen science is an important source of biodiversity information, particularly for gathering information on species distributions over time. However, there are challenges with spatial and species biases, and variation in effort in citizen science data. We aimed to investigate seasonal habitat suitability for cetacean species reported within the Pacific Northwest by applying species distribution models (SDMs) to opportunistic sightings data submitted to the Ocean Wise Sightings Network (hereafter OWSN; formerly the British Columbia Cetacean Sightings Network, BCCSN) over two decades (2002-2022).

Location: British Columbia, Washington State, South Alaska.

Taxon: Order Cetacea

Methods: We employed MaxEnt SDMs for the 10 cetacean species most frequently reported to the OWSN between 2002 and 2022. We thinned the dataset to account for spatial bias in sighting locations, then best-performing models were selected based on continuous Boyce Index (CBI), and further evaluated against null models. Ensemble predictions were made using best-performing models on seasonal means of environmental variables across the study period to produce coast-wide maps of relative habitat suitability for each species.

Results: Across all 10 species, SDMs closely reflected the known seasonal species distribution across the Pacific Northwest. Summer habitat hotspots across all species include: the continental shelf offshore of Vancouver Island and Haida Gwaii and following the deep canyons of Queen Charlotte Sound; and winter hotspots encompassing nearshore waters within British Columbia and Washington, as well as much of Hecate Strait in the north and southern parts of Queen Charlotte Sound.

Main conclusions: Citizen science is an efficient mechanism for generating data on cetacean seasonal occurrence. Through applying SDMs and accounting for spatial biases in sampling, opportunistic data can be applied to investigate long-term trends in cetacean distribution, especially concerning the impacts of anthropogenic-mediated pressures such as climate change.