Patanasatienkul Thitiwan, Sanchez Javier, Davidson Jeff, Revie Crawford W
Department of Health Management, Atlantic Veterinary College, University of Prince Edward Island, Charlottetown, PE, Canada.
Department of Computer and Information Sciences, University of Strathclyde, Glasgow, United Kingdom.
Front Vet Sci. 2019 Aug 20;6:271. doi: 10.3389/fvets.2019.00271. eCollection 2019.
The Prince Edward Island (PEI) mussel industry has faced challenges associated with invasive tunicate species over the past two decades. Field experiments to find suitable mitigation strategies require considerable time and are resource intensive. This study demonstrates the application of a mathematical model to assess several control strategies against populations under different temperature conditions in a mussel production area in PEI. A temperature dependent compartmental model was used to model the total abundance of . Each mitigation strategy was defined in terms of a combination of timing and frequency of treatments. Various strategies were explored to obtain the combination that maximized the difference in predicted abundances between the control (untreated) and the different mitigation strategies. Treatment frequency was allowed to vary between one and four times over a given production year. The model was assessed under baseline conditions, which mimicked water temperatures from Georgetown Harbor, PEI, in 2008; as well as under scenarios that reflected prolonged summer or warm spring temperatures. Furthermore, the sensitivity of the model to variations in presumed treatment efficacy was evaluated. The use of all four available treatments, starting around the first week of July and correctly timed thereafter, provided the most effective strategy, assuming the baseline temperature scenario. However, the effectiveness of this mitigation strategy depended on temperature conditions. The mathematical model developed in this study allows decision makers to explore different strategies to control the abundance of in mussel production areas under different environmental conditions. In addition, the modeling framework developed could be adapted to simulate comparable ectoparasitic infestation in aquatic environments.
在过去二十年中，爱德华王子岛（PEI）的贻贝产业面临着与入侵被囊动物物种相关的挑战。寻找合适缓解策略的实地试验需要大量时间且资源密集。本研究展示了应用数学模型来评估针对PEI贻贝产区不同温度条件下种群的几种控制策略。使用了一个温度依赖的 compartmental 模型来模拟[具体物种]的总丰度。每种缓解策略都根据处理的时间和频率组合来定义。探索了各种策略以获得能使对照（未处理）与不同缓解策略之间预测丰度差异最大化的组合。在给定的生产年份中，处理频率允许在一到四次之间变化。该模型在基线条件下进行评估，基线条件模拟了2008年PEI乔治敦港的水温；以及在反映夏季延长或春季温暖温度的情景下进行评估。此外，还评估了模型对假定处理效果变化的敏感性。假设基线温度情景，从7月的第一周左右开始使用所有四种可用处理方法，并在此后正确安排时间，可以提供最有效的策略。然而，这种缓解策略的有效性取决于温度条件。本研究中开发的数学模型使决策者能够探索在不同环境条件下控制贻贝产区[具体物种]丰度的不同策略。此外，所开发的建模框架可适用于模拟水生环境中类似的体外寄生虫侵扰。
