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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

Statistics on number and timing of cross-patch infestation events.The results are averaged across 100 realizations. Patches 1 to 5 are in Partition 1 while patches 6 to 10 are in Partition 2. The parameter values are taken from Table 2. (a) Number of cross–patch infestations experienced by each patch due to the transportation of firewood during the first 10 years of the simulation, in 100s; (b) total number of cross–patch infestations occurring during the 300 years’ simulation time in each patch; (c) mean and two standard deviation (error bars) of the time-to-first-cross–patch-infestation occurring in each patch during the 300 years’ simulation time. Horizontal axis represents the patch number while vertical axis represents the time-to-first-cross–patch-infestation.
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pone.0139353.g003: Statistics on number and timing of cross-patch infestation events.The results are averaged across 100 realizations. Patches 1 to 5 are in Partition 1 while patches 6 to 10 are in Partition 2. The parameter values are taken from Table 2. (a) Number of cross–patch infestations experienced by each patch due to the transportation of firewood during the first 10 years of the simulation, in 100s; (b) total number of cross–patch infestations occurring during the 300 years’ simulation time in each patch; (c) mean and two standard deviation (error bars) of the time-to-first-cross–patch-infestation occurring in each patch during the 300 years’ simulation time. Horizontal axis represents the patch number while vertical axis represents the time-to-first-cross–patch-infestation.

Mentions: The temporal patterns of cross–patch infestation are clarified by plotting the number of cross–patch infestation events experienced by each patch versus time, for all 10 patches in the first 10 years, and including all 100 realizations (Fig 3A, data available in the supplementary material: S1 Matlab Data File), as well as the total number of cross–patch infestations experienced by each patch over 300 years, averaged over all 100 realizations (Fig 3B).


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)

Statistics on number and timing of cross-patch infestation events.The results are averaged across 100 realizations. Patches 1 to 5 are in Partition 1 while patches 6 to 10 are in Partition 2. The parameter values are taken from Table 2. (a) Number of cross–patch infestations experienced by each patch due to the transportation of firewood during the first 10 years of the simulation, in 100s; (b) total number of cross–patch infestations occurring during the 300 years’ simulation time in each patch; (c) mean and two standard deviation (error bars) of the time-to-first-cross–patch-infestation occurring in each patch during the 300 years’ simulation time. Horizontal axis represents the patch number while vertical axis represents the time-to-first-cross–patch-infestation.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0139353.g003: Statistics on number and timing of cross-patch infestation events.The results are averaged across 100 realizations. Patches 1 to 5 are in Partition 1 while patches 6 to 10 are in Partition 2. The parameter values are taken from Table 2. (a) Number of cross–patch infestations experienced by each patch due to the transportation of firewood during the first 10 years of the simulation, in 100s; (b) total number of cross–patch infestations occurring during the 300 years’ simulation time in each patch; (c) mean and two standard deviation (error bars) of the time-to-first-cross–patch-infestation occurring in each patch during the 300 years’ simulation time. Horizontal axis represents the patch number while vertical axis represents the time-to-first-cross–patch-infestation.
Mentions: The temporal patterns of cross–patch infestation are clarified by plotting the number of cross–patch infestation events experienced by each patch versus time, for all 10 patches in the first 10 years, and including all 100 realizations (Fig 3A, data available in the supplementary material: S1 Matlab Data File), as well as the total number of cross–patch infestations experienced by each patch over 300 years, averaged over all 100 realizations (Fig 3B).

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