[MARMAM] Ship-strike encounter rate simulator: new publication

Eric Keen ericmkeen at gmail.com
Sat Apr 23 09:13:19 PDT 2022

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.

A demo for the corresponding R package 'shipstrike' (available on GitHub)
can be found here:

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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