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.

中文翻译：

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评估湖鳟海七鳃鳗伤口的分类一致性、准确性和可预测愈合时间的假设

摘要 Laurentian Great Lakes 的海七鳃鳗控制依赖于湖鳟海七鳃鳗的伤口记录来评估控制努力是否支持渔业管理目标。受伤记录已保存了 70 年，前提是它们可靠而准确地反映了海七鳃鳗对鱼类种群造成的损害。然而，支持使用这些数据的两个关键假设需要彻底评估：海七鳃鳗的伤口遵循可预测的愈合过程，个人对伤口进行准确可靠的分类。为了评估这些假设，我们举办了一个研讨会，在那里经验丰富的专业人员检查了已知海七鳃鳗伤口的湖鳟鱼。对于大多数湖鳟，在愈合过程中定期拍摄照片。我们对伤口图片的评估发现愈合时间和伤口进展的高度可变性不符合当前使用的分类系统。对于大多数伤口类型，参与者的伤口分类一致性和准确性较低，错误分类率较高。研讨会期间提供的培训并未显着改善这些指标。我们首次评估了伤口分类的准确性，发现不满足高精度和一致性的假设。我们建议将错误分类率纳入使用伤口数据的模型中，进行敏感性分析以评估伤口错误分类对关键指标（例如海七鳃鳗引起的湖鳟死亡率）估计的潜在影响，并开发替代生物标志物来量化伤口状态具有更高的准确度和精确度。