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Coupled Human-Environment Dynamics of Forest Pest Spread and Control in a Multi-Patch, Stochastic Setting.

Ali Q, Bauch CT, Anand M - PLoS ONE (2015)

Bottom Line: In particular, modest increases in the tree removal rate, modest increases in public concern for infestation, and modest decreases in the cost of locally purchased firewood, relative to baseline (current) values, cause very large increases in the average time until a patch becomes infested due to firewood transport from other patches, thereby better preventing long-distance spread.Patches that experience lower visitor volumes benefit more from firewood movement restrictions than patches that experience higher visitor volumes.Also, cross-patch infestations not only seed new infestations, they can also worsen existing infestations to a surprising extent: long-term infestations are more intense in the high volume patches than the low volume patches, even when infestation is already endemic everywhere.

View Article: PubMed Central - PubMed

Affiliation: Department of Applied Mathematics, Western University, London, Ontario, Canada.

ABSTRACT

Background: The transportation of camp firewood infested by non-native forest pests such as Asian long-horned beetle (ALB) and emerald ash borer (EAB) has severe impacts on North American forests. Once invasive forest pests are established, it can be difficult to eradicate them. Hence, preventing the long-distance transport of firewood by individuals is crucial.

Methods: Here we develop a stochastic simulation model that captures the interaction between forest pest infestations and human decisions regarding firewood transportation. The population of trees is distributed across 10 patches (parks) comprising a "low volume" partition of 5 patches that experience a low volume of park visitors, and a "high volume" partition of 5 patches experiencing a high visitor volume. The infestation spreads within a patch--and also between patches--according to the probability of between-patch firewood transportation. Individuals decide to transport firewood or buy it locally based on the costs of locally purchased versus transported firewood, social norms, social learning, and level of concern for observed infestations.

Results: We find that the average time until a patch becomes infested depends nonlinearly on many model parameters. In particular, modest increases in the tree removal rate, modest increases in public concern for infestation, and modest decreases in the cost of locally purchased firewood, relative to baseline (current) values, cause very large increases in the average time until a patch becomes infested due to firewood transport from other patches, thereby better preventing long-distance spread. Patches that experience lower visitor volumes benefit more from firewood movement restrictions than patches that experience higher visitor volumes. Also, cross-patch infestations not only seed new infestations, they can also worsen existing infestations to a surprising extent: long-term infestations are more intense in the high volume patches than the low volume patches, even when infestation is already endemic everywhere.

Conclusions: The success of efforts to prevent long-distance spread of forest pests may depend sensitively on the interaction between outbreak dynamics and human social processes, with similar levels of effort producing very different outcomes depending on where the coupled human and natural system exists in parameter space. Further development of such modeling approaches through better empirical validation should yield more precise recommendations for ways to optimally prevent the long-distance spread of invasive forest pests.

No MeSH data available.


Related in: MedlinePlus

Average of 100 realizations over 100 years’ simulated time.Error bars represent two standard deviations from the mean and have been drawn for only Patch 3 (results are similar for other patches). Patches 1–5 are in Partition 1 while patches 6–10 are in Partition 2.The parameters used to generate the results are given in Table 2. Panels show (a) the impact of social norms n; (b) the impact of social learning σ; and (c) the impact of changing the volume of visitors in high volume patches dH on the average time-to-first-cross–patch-infestation tcross.
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pone.0139353.g005: Average of 100 realizations over 100 years’ simulated time.Error bars represent two standard deviations from the mean and have been drawn for only Patch 3 (results are similar for other patches). Patches 1–5 are in Partition 1 while patches 6–10 are in Partition 2.The parameters used to generate the results are given in Table 2. Panels show (a) the impact of social norms n; (b) the impact of social learning σ; and (c) the impact of changing the volume of visitors in high volume patches dH on the average time-to-first-cross–patch-infestation tcross.

Mentions: In most cases, a change to any of these parameters causes a nonlinear response in the time-to-first-cross–patch-infestation (Figs 4 and 5, data available in the supplementary materials: S2, S3, S4, S5, S6 and S7 Matlab Data Files). In other words, there are many cases where tcross does not respond to changes in a parameter’s value, until the parameter value exceeds a threshold, beyond which tcross changes dramatically. This has implications for how much effort must be expended to prevent long–range infestation spread, since some changes to control parameters will cause enormous changes in control success, while other changes to control parameters will have little effect on control success. Also, the variability in outcomes (standard deviations) across the 100 model realizations is often significant, meaning that stochasticity could influence whether or not firewood movement restrictions are successful.


Coupled Human-Environment Dynamics of Forest Pest Spread and Control in a Multi-Patch, Stochastic Setting.

Ali Q, Bauch CT, Anand M - PLoS ONE (2015)

Average of 100 realizations over 100 years’ simulated time.Error bars represent two standard deviations from the mean and have been drawn for only Patch 3 (results are similar for other patches). Patches 1–5 are in Partition 1 while patches 6–10 are in Partition 2.The parameters used to generate the results are given in Table 2. Panels show (a) the impact of social norms n; (b) the impact of social learning σ; and (c) the impact of changing the volume of visitors in high volume patches dH on the average time-to-first-cross–patch-infestation tcross.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4592071&req=5

pone.0139353.g005: Average of 100 realizations over 100 years’ simulated time.Error bars represent two standard deviations from the mean and have been drawn for only Patch 3 (results are similar for other patches). Patches 1–5 are in Partition 1 while patches 6–10 are in Partition 2.The parameters used to generate the results are given in Table 2. Panels show (a) the impact of social norms n; (b) the impact of social learning σ; and (c) the impact of changing the volume of visitors in high volume patches dH on the average time-to-first-cross–patch-infestation tcross.
Mentions: In most cases, a change to any of these parameters causes a nonlinear response in the time-to-first-cross–patch-infestation (Figs 4 and 5, data available in the supplementary materials: S2, S3, S4, S5, S6 and S7 Matlab Data Files). In other words, there are many cases where tcross does not respond to changes in a parameter’s value, until the parameter value exceeds a threshold, beyond which tcross changes dramatically. This has implications for how much effort must be expended to prevent long–range infestation spread, since some changes to control parameters will cause enormous changes in control success, while other changes to control parameters will have little effect on control success. Also, the variability in outcomes (standard deviations) across the 100 model realizations is often significant, meaning that stochasticity could influence whether or not firewood movement restrictions are successful.

Bottom Line: In particular, modest increases in the tree removal rate, modest increases in public concern for infestation, and modest decreases in the cost of locally purchased firewood, relative to baseline (current) values, cause very large increases in the average time until a patch becomes infested due to firewood transport from other patches, thereby better preventing long-distance spread.Patches that experience lower visitor volumes benefit more from firewood movement restrictions than patches that experience higher visitor volumes.Also, cross-patch infestations not only seed new infestations, they can also worsen existing infestations to a surprising extent: long-term infestations are more intense in the high volume patches than the low volume patches, even when infestation is already endemic everywhere.

View Article: PubMed Central - PubMed

Affiliation: Department of Applied Mathematics, Western University, London, Ontario, Canada.

ABSTRACT

Background: The transportation of camp firewood infested by non-native forest pests such as Asian long-horned beetle (ALB) and emerald ash borer (EAB) has severe impacts on North American forests. Once invasive forest pests are established, it can be difficult to eradicate them. Hence, preventing the long-distance transport of firewood by individuals is crucial.

Methods: Here we develop a stochastic simulation model that captures the interaction between forest pest infestations and human decisions regarding firewood transportation. The population of trees is distributed across 10 patches (parks) comprising a "low volume" partition of 5 patches that experience a low volume of park visitors, and a "high volume" partition of 5 patches experiencing a high visitor volume. The infestation spreads within a patch--and also between patches--according to the probability of between-patch firewood transportation. Individuals decide to transport firewood or buy it locally based on the costs of locally purchased versus transported firewood, social norms, social learning, and level of concern for observed infestations.

Results: We find that the average time until a patch becomes infested depends nonlinearly on many model parameters. In particular, modest increases in the tree removal rate, modest increases in public concern for infestation, and modest decreases in the cost of locally purchased firewood, relative to baseline (current) values, cause very large increases in the average time until a patch becomes infested due to firewood transport from other patches, thereby better preventing long-distance spread. Patches that experience lower visitor volumes benefit more from firewood movement restrictions than patches that experience higher visitor volumes. Also, cross-patch infestations not only seed new infestations, they can also worsen existing infestations to a surprising extent: long-term infestations are more intense in the high volume patches than the low volume patches, even when infestation is already endemic everywhere.

Conclusions: The success of efforts to prevent long-distance spread of forest pests may depend sensitively on the interaction between outbreak dynamics and human social processes, with similar levels of effort producing very different outcomes depending on where the coupled human and natural system exists in parameter space. Further development of such modeling approaches through better empirical validation should yield more precise recommendations for ways to optimally prevent the long-distance spread of invasive forest pests.

No MeSH data available.


Related in: MedlinePlus