Dear colleagues, My coauthors and I are pleased to share the following article recently published in *Ocean & Coastal Management*:
Keen, Eric M; Hendricks, Ben; Shine, Chenoah; Wray, Janie; Picard, Chris R; Alidina, Hussein M. (2022). A simulation-based tool for predicting whale-vessel encounter rates. In Ocean & Coastal Management (Vol. 224, p. 106183). Elsevier BV. https://doi.org/10.1016/j.ocecoaman.2022.106183 Abstract ============== To understand the threat of ship strikes for marine predators such as whales, quantitative tools are needed that measure specific impacts without ignoring the many uncertain and stochastic elements of whale-vessel interactions. We developed a tool that focuses on one particularly complex aspect of the ship-strike problem: the encounter rate, the fraction of co-occurrences (i.e., times that whales and vessels occur within the same 1-km2) that result in an imminent collision. This tool uses iterative simulations, based in R, and basic inputs regarding marine traffic and whale biology to predict the rate at which the precise courses of the whale and the vessel intersect in space and time. The result of this simulator is a spatially explicit probability distribution of encounter rates, which can be summarized for reports as well as integrated into subsequent stages of a ship-strike impact analysis. We explain the design of this tool, provide its source code, and demonstrate its utility with four case applications. First, we estimate encounter rates for fin whales (Balaenoptera physalus) in Gitga'at First Nation waters (British Columbia, BC, Canada) and quantify the differences in encounter rate between vessel classes. Second, we predict encounter rates for the same area in 2030, by which time a new shipping lane is slated to be established in Gitga'at territory, highlighting the impact of shifting traffic composition vs. traffic volume. Third, we assess the sensitivity of these estimates to changes in vessel and whale characteristics, finding that vessel length is the most important determinant of the encounter rate, followed by whale speed. Fourth, we integrate the encounter rate estimator into a shipping impact assessment for Gitga'at fin whales. Our predictions indicate that this decade's traffic increase in Gitga'at waters alone could match Potential Biological Removal for coastal BC fin whales. However, the assumptions underlying our prediction require validation and further study. The encounter rate simulator is available in the R package, “shipstrike”. The article may be accessed at the link below, or by contacting me. https://authors.elsevier.com/a/1ex4q3RKK-uDAk A demo for the corresponding R package 'shipstrike' (available on GitHub) can be found here: https://ericmkeen.github.io/shipstrike/ Our special thanks to the Gitga'at First Nation for their collaboration and support in this work. Best wishes, Eric Keen
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