Assessing the assumptions of classification agreement, accuracy, and predictable healing time of sea lamprey wounds on lake trout

Journal of Great Lakes Research
By: , and 

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Abstract

Sea lamprey control in the Laurentian Great Lakes relies on records of sea lamprey wounds on lake trout to assess whether control efforts are supporting fisheries management targets. Wounding records have been maintained for 70 years under the assumption that they are a reliable and accurate reflection of sea lamprey damage inflicted on fish populations. However, two key assumptions underpinning the use of these data need thorough evaluation: sea lamprey wounds follow a predictable healing progression, and individuals classify wounds accurately and reliably. To assess these assumptions, we conducted a workshop where experienced professionals examined lake trout with known sea lamprey wounds. For most lake trout, pictures were taken at regular intervals during the healing process. Our evaluation of wound pictures found high variability in healing times and wound progressions that did not conform to the currently used classification system. Participants’ wound classification agreement and accuracy were low and misclassification rates were high for most wound types. Training provided during the workshops did not markedly improve these metrics. We assessed wound classification accuracy for the first time and found assumptions of high accuracy and agreement are not met. We recommend misclassification rates be incorporated into models using wound data, sensitivity analyses be conducted to assess the potential impact of wound misclassification on estimates of key metrics (such as sea lamprey-induced mortality for lake trout), and alternative biomarkers be developed to quantify wound status with greater accuracy and precision.

Study Area

Publication type Article
Publication Subtype Journal Article
Title Assessing the assumptions of classification agreement, accuracy, and predictable healing time of sea lamprey wounds on lake trout
Series title Journal of Great Lakes Research
DOI 10.1016/j.jglr.2020.07.016
Volume 47
Issue Supp 1
Year Published 2021
Language English
Publisher Elsevier
Contributing office(s) Great Lakes Science Center
Description 10 p.
First page S368
Last page S377
Country Canada, United States
Other Geospatial Laurentian Great Lakes
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