Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB, Canada.
BC Ministry of Environment and Climate Change Strategy, Conservation Science Section, Victoria, BC, Canada.
J Environ Manage. 2021 Apr 1;283:111923. doi: 10.1016/j.jenvman.2020.111923. Epub 2021 Jan 19.
Aquatic invasive species (AIS) cause significant ecological and economic damages around the world. A major spread mechanism for AIS is traffic of boaters transporting their watercraft from invaded to uninvaded waterbodies. To inhibit the spread of AIS, Canadian provinces and American states often set up watercraft inspection stations at roadsides, where potentially infested boats are screened for AIS and, if necessary, decontaminated. However, since budgets for AIS control are limited, watercraft inspection stations can only be operated at specific locations and daytimes. Though theoretical studies provide managers with general guidelines for AIS management, more specific results are needed to determine when and where watercraft inspections would be most effective. This is the subject of this paper. We show how linear integer programming techniques can be used to optimize watercraft inspection policies under budget constraints. We introduce our approach as a general framework and apply it to the prevention of the spread of zebra and quagga mussels (Dreissena spp.) to the Canadian province of British Columbia. We consider multiple scenarios and show how variations in budget constraints, propagule sources, and model uncertainty affect the optimal policy. Based on these results, we identify simple, generally applicable principles for optimal AIS management.
水生入侵物种（AIS）在全球范围内造成了重大的生态和经济损失。AIS 的主要传播机制是划船者将其船只从受入侵水域运送到未受入侵水域。为了抑制 AIS 的传播，加拿大各省和美国各州经常在路边设置船只检查站，对可能受感染的船只进行 AIS 筛查，如果有必要，对其进行消毒。然而，由于 AIS 控制的预算有限，船只检查站只能在特定地点和白天运行。尽管理论研究为管理人员提供了 AIS 管理的一般准则，但需要更具体的结果来确定何时何地进行船只检查最有效。这就是本文的主题。我们展示了如何在预算限制下使用线性整数规划技术来优化船只检查政策。我们将我们的方法介绍为一个通用框架，并将其应用于预防斑马和斑马贻贝（Dreissena spp.）传播到加拿大不列颠哥伦比亚省。我们考虑了多种情况，并展示了预算限制、繁殖体来源和模型不确定性的变化如何影响最优政策。基于这些结果，我们确定了用于优化 AIS 管理的简单、普遍适用的原则。
