Forest stand conditions after Phytophthora ramorum management in northern California: post-treatment observations inform future responses

Frankel, Susan J.

doi:10.5399/osu/fp.7.1.4018

Cited by 8 publications

(3 citation statements)

References 18 publications

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“…Only one model captures dynamics at a small enough scale to show the decline of overstorey tanoak at the forest stand level ( 20 ha) [21]. Studies have used this model to demonstrate the effectiveness of one-off interventions [23,28], but have not assessed time-dependent controls, and strategies have not been optimised in order to protect tanoak.…”

Section: Introductionmentioning

confidence: 99%

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Applying optimal control theory to a spatial simulation model of sudden oak death: ongoing surveillance protects tanoak while conserving biodiversity

Bussell

Cunniffe

2020

J. R. Soc. Interface.

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Sudden oak death has devastated tree populations across California. However, management might still slow disease spread at local scales. We demonstrate how to unambiguously characterize effective, local management strategies using a detailed, spatially explicit simulation model of spread in a single forest stand. This pre-existing, parameterized simulation is approximated here by a carefully calibrated, non-spatial model, explicitly constructed to be sufficiently simple to allow optimal control theory (OCT) to be applied. By lifting management strategies from the approximate model to the detailed simulation, effective time-dependent controls can be identified. These protect tanoak—a culturally and ecologically important species—while conserving forest biodiversity within a limited budget. We also consider model predictive control, in which both the approximating model and optimal control are repeatedly updated as the epidemic progresses. This allows management which is robust to both parameter uncertainty and systematic differences between simulation and approximate models. Including the costs of disease surveillance then introduces an optimal intensity of surveillance. Our study demonstrates that successful control of sudden oak death is likely to rely on adaptive strategies updated via ongoing surveillance. More broadly, it illustrates how OCT can inform effective real-world management, even when underpinning disease spread models are highly complex.

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Section: Introductionmentioning

confidence: 99%

“…20 ha) [21]. Studies have used this model to demonstrate the effectiveness of one-off interventions [23,28], but have not assessed timedependent controls, and strategies have not been optimized in order to protect tanoak.…”

Section: Introductionmentioning

confidence: 99%

Applying optimal control theory to a spatial simulation model of sudden oak death: ongoing surveillance protects tanoak while conserving biodiversity

Bussell

Cunniffe

2020

J. R. Soc. Interface.

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“…Only one model captures 64 dynamics at a small enough scale to show the decline of overstorey tanoak at the forest stand level ( 20 ha) [16]. 65 Studies have used this model to demonstrate the effectiveness of one-off interventions [18,23], but do not assess 66 time-dependent controls, and strategies have not been optimised in order to protect tanoak. Whilst a clear objective for control is to protect tanoak, this must not be at the cost of the overall health of the 68 forest.…”

Section: Introductionmentioning

confidence: 99%

Ongoing surveillance protects tanoak whilst conserving biodiversity: applying optimal control theory to a spatial simulation model of sudden oak death

Bussell

Cunniffe

2019

Preprint

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AbstractThe 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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Forest community structure and composition following containment treatments for the fungal pathogen oak wilt

et al. 2021

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Forest stand conditions after Phytophthora ramorum management in northern California: post-treatment observations inform future responses

Cited by 8 publications

References 18 publications

Applying optimal control theory to a spatial simulation model of sudden oak death: ongoing surveillance protects tanoak while conserving biodiversity

Applying optimal control theory to a spatial simulation model of sudden oak death: ongoing surveillance protects tanoak while conserving biodiversity

Ongoing surveillance protects tanoak whilst conserving biodiversity: applying optimal control theory to a spatial simulation model of sudden oak death

Forest community structure and composition following containment treatments for the fungal pathogen oak wilt

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