School of Biological Sciences, Monash University, Clayton, Victoria, Australia.
School of BioSciences, The University of Melbourne, Parkville, Victoria, Australia.
Conserv Biol. 2021 Oct;35(5):1639-1649. doi: 10.1111/cobi.13748. Epub 2021 Apr 28.
Land managers decide how to allocate resources among multiple threats that can be addressed through multiple possible actions. Additionally, these actions vary in feasibility, effectiveness, and cost. We sought to provide a way to optimize resource allocation to address multiple threats when multiple management options are available, including mutually exclusive options. Formulating the decision as a combinatorial optimization problem, our framework takes as inputs the expected impact and cost of each threat for each action (including do nothing) and for each overall budget identifies the optimal action to take for each threat. We compared the optimal solution to an easy to calculate greedy algorithm approximation and a variety of plausible ranking schemes. We applied the framework to management of multiple introduced plant species in Australian alpine areas. We developed a model of invasion to predict the expected impact in 50 years for each species-action combination that accounted for each species' current invasion state (absent, localized, widespread); arrival probability; spread rate; impact, if present, of each species; and management effectiveness of each species-action combination. We found that the recommended action for a threat changed with budget; there was no single optimal management action for each species; and considering more than one candidate action can substantially increase the management plan's overall efficiency. The approximate solution (solution ranked by marginal cost-effectiveness) performed well when the budget matched the cost of the prioritized actions, indicating that this approach would be effective if the budget was set as part of the prioritization process. The ranking schemes varied in performance, and achieving a close to optimal solution was not guaranteed. Global sensitivity analysis revealed a threat's expected impact and, to a lesser extent, management effectiveness were the most influential parameters, emphasizing the need to focus research and monitoring efforts on their quantification.
土地管理者需要在多种威胁之间分配资源，这些威胁可以通过多种可能的行动来解决。此外，这些行动在可行性、有效性和成本方面存在差异。我们旨在提供一种方法，以便在有多种管理选择（包括互斥选项）时优化资源分配，以解决多种威胁。我们将决策制定为组合优化问题，该框架将每个行动（包括不作为）对每个威胁的预期影响和成本作为输入，对于每个总体预算，为每个威胁确定采取的最佳行动。我们将最优解与易于计算的贪婪算法近似值和多种合理的排序方案进行了比较。我们将该框架应用于澳大利亚高山地区多种引入植物物种的管理。我们开发了一种入侵模型，用于预测每种物种-行动组合在 50 年内的预期影响，该模型考虑了每个物种的当前入侵状态（不存在、局部存在、广泛存在）；到达概率；传播速度；如果存在，每种物种的影响；以及每种物种-行动组合的管理效果。我们发现，对于一个威胁，建议的行动会随着预算的变化而变化；对于每个物种，没有单一的最佳管理行动；并且考虑多个候选行动可以大大提高管理计划的整体效率。近似解（按边际成本效益排序的解）在预算与优先行动的成本相匹配时表现良好，这表明如果预算是优先排序过程的一部分，则该方法将是有效的。排序方案的性能存在差异，并不保证能获得接近最优的解决方案。全局敏感性分析显示，威胁的预期影响，以及在较小程度上，管理效果是最具影响力的参数，这强调了需要集中精力进行研究和监测工作，以量化这些参数。
