Thompson Brielle K, Olden Julian D, Converse Sarah J
Washington Cooperative Fish and Wildlife Research Unit, Quantitative Ecology and Resource Management Program University of Washington Seattle Washington USA.
School of Aquatic and Fishery Sciences University of Washington Seattle Washington USA.
Ecol Evol. 2025 Apr 1;15(4):e71176. doi: 10.1002/ece3.71176. eCollection 2025 Apr.
Efficient allocation of managers' limited resources is necessary to effectively control invasive species, but determining how to allocate effort between monitoring and management over space and time remains a challenge. In an adaptive management context, monitoring data are key for gaining knowledge and iteratively improving management, but monitoring costs money. Community science or other opportunistic monitoring data present an opportunity for managers to gain critical knowledge without a substantial reduction in management funds. We designed a management strategy evaluation to investigate optimal spatial allocation of resources to monitoring and management, while also exploring the potential for community science data to improve decision-making, using adaptive management of invasive flowering rush () in the Columbia River, USA, as a case study. We evaluated management and monitoring alternatives under two invasion conditions, a well-established invasion and an emerging invasion, for both risk-neutral and risk-averse decision makers. Simulations revealed that regardless of invasion condition or managers' risk tolerance, allocating effort outward from the estimated center of invasion ( prioritization) resulted in the lowest overall level of infestation at the end of management. This allocation outperformed alternatives in which management occurred in fixed areas ( prioritization) and alternatives that targeted patchily distributed areas with the highest estimated infestation level of the invasive species ( prioritization). Additionally, management outcomes improved when more resources were allocated toward removal effort than monitoring effort, and the addition of community science data improved outcomes only under certain scenarios. Finally, actions that led to the best outcomes often did not produce the most accurate and precise estimates of parameters describing system function, emphasizing the importance of using value of information principles to guide monitoring. Our adaptive management approach is adaptable to many invasive species management contexts in which ongoing monitoring allows management strategies to be updated over time.
有效分配管理者的有限资源对于有效控制入侵物种至关重要，但确定如何在空间和时间上在监测和管理之间分配精力仍然是一项挑战。在适应性管理背景下，监测数据是获取知识和迭代改进管理的关键，但监测需要资金。社区科学或其他机会性监测数据为管理者提供了一个机会，使其能够在不大量削减管理资金的情况下获得关键知识。我们设计了一项管理策略评估，以研究资源在监测和管理之间的最佳空间分配，同时还探讨社区科学数据改善决策的潜力，以美国哥伦比亚河对入侵性开花灯心草（）的适应性管理为例进行研究。我们针对风险中性和风险规避型决策者，在两种入侵情况下评估了管理和监测方案，即已确立的入侵和新出现的入侵。模拟结果显示，无论入侵情况或管理者的风险承受能力如何，从估计的入侵中心向外分配精力（优先级排序）在管理结束时导致的总体侵染水平最低。这种分配方式优于在固定区域进行管理的方案（优先级排序）以及针对入侵物种估计侵染水平最高的零散分布区域的方案（优先级排序）。此外，当分配更多资源用于清除工作而非监测工作时，管理效果会得到改善，并且仅在某些情况下，添加社区科学数据才会改善效果。最后，导致最佳结果的行动往往并未产生对描述系统功能的参数最准确和精确的估计，这强调了使用信息价值原则来指导监测的重要性。我们的适应性管理方法适用于许多入侵物种管理背景，在这些背景下，持续监测可使管理策略随时间更新。
