Ongoing surveillance protects tanoak whilst conserving biodiversity: applying optimal control theory to a spatial simulation model of sudden oak death
Ongoing surveillance protects tanoak whilst conserving biodiversity: applying optimal control theory to a spatial simulation model of sudden oak death
复制标题
持续监测保护橡树，同时保护生物多样性：将最优控制理论应用于橡树突然死亡的空间模拟模型
DOI：
10.1101/773424
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Bussell E
中科院分区：
文献类型：
--
作者：
Bussell E
加州的橡树猝死病正在失控地蔓延。一段时间以来，大规模根除是不可能的。然而，小规模的疾病管理仍然可以减缓疾病的传播。尽管经验证据表明，局部控制可能是成功的，但数学模型对这种管理几乎没有说明。通过近似一个详细的，空间上明确的模拟模型的橡木猝死与一个更简单的，易于处理的模型，我们演示了如何最优控制理论可以用来明确地解释有效的时间依赖性疾病管理策略。我们专注于保护tanoak，这是一种在文化和生态上具有重要意义的树种，但也极易受到橡树突然死亡的影响。我们确定了管理策略，以保护新入侵的林分中的tanoak，同时也保护生物多样性。我们发现，稀疏的月桂是必不可少的流行病的早期。我们应用模型预测控制，一种反馈策略，其中近似模型和控制都随着流行病的进展而反复更新。以这种方式调整最佳控制策略对于有效的疾病管理至关重要。这种反馈策略对参数不确定性具有鲁棒性，在最坏情况下限制了tanoak的损失。然而，该方法需要持续的监测，以重新优化近似模型。这引入了最佳水平的监测，以平衡密集调查的高成本与更好地估计疾病进展所带来的更好管理。我们的研究表明，详细的仿真模型可以与最优控制理论和模型预测控制相结合，找到有效的控制策略，突然橡树死亡。我们表明，控制策略，橡树猝死必须依赖于当地的管理目标，并成功地依赖于适应性战略，通过不断的疾病监测更新。广泛的框架，允许使用最优控制理论对复杂的仿真模型适用于广泛的系统。
The sudden oak death epidemic in California is spreading uncontrollably. Large-scale eradication has been impossible for some time. However, small-scale disease management could still slow disease spread. Although empirical evidence suggests localised control could potentially be successful, mathematical models have said little about such management. By approximating a detailed, spatially-explicit simulation model of sudden oak death with a simpler, mathematically-tractable model, we demonstrate how optimal control theory can be used to unambiguously characterise effective time-dependent disease management strategies. We focus on protection of tanoak, a tree species which is culturally and ecologically important, but also highly susceptible to sudden oak death. We identify management strategies to protect tanoak in a newly-invaded forest stand, whilst also conserving biodiversity. We find that thinning of bay laurel is essential early in the epidemic. We apply model predictive control, a feedback strategy in which both the approximating model and the control are repeatedly updated as the epidemic progresses. Adapting optimal control strategies in this way is vital for effective disease management. This feedback strategy is robust to parameter uncertainty, limiting loss of tanoak in the worst-case scenarios. However, the methodology requires ongoing surveillance to re-optimise the approximating model. This introduces an optimal level of surveillance to balance the high costs of intensive surveys against improved management resulting from better estimates of disease progress. Our study shows how detailed simulation models can be coupled with optimal control theory and model predictive control to find effective control strategies for sudden oak death. We demonstrate that control strategies for sudden oak death must depend on local management goals, and that success relies on adaptive strategies that are updated via ongoing disease surveillance. The broad framework allowing the use of optimal control theory on complex simulation models is applicable to a wide range of systems.
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影响因子：
3.2
作者：
Davidson, J. M.;Patterson, H. A.;Rizzo, D. M.
通讯作者：
Rizzo, D. M.
影响因子：
3.5
作者：
Alexander, Janice;Lee, Christopher A.
通讯作者：
Lee, Christopher A.
美国西北太平洋地区大型硬木的最新趋势
影响因子：
2.9
作者：
J. Long;A. Gray;Frank K. Lake
通讯作者：
Frank K. Lake
影响因子：
4.3
作者：
Cunniffe NJ;Laranjeira FF;Neri FM;DeSimone RE;Gilligan CA
通讯作者：
Gilligan CA
前言：创新和奉献是加州和俄勒冈州森林橡树猝死（Phytophthora ramorum）管理的基础
DOI：
--
发表时间：
2017
期刊：
影响因子：
--
作者：
S. Frankel
通讯作者：
S. Frankel