Location: Location not imported yet.Title: Simulating migration of wind-borne pests: “Deconstructing” representation of the emigration process
|WANG, HSIAO-HSUAN - Texas A&M University|
|GRANT, WILLIAM - Texas A&M University|
|KORALEWSKI, TOMASZ - Texas A&M University|
|BREWER, MICHAEL - Texas A&M University|
|Elliott, Norman - Norm|
Submitted to: Ecological Modelling
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/31/2021
Publication Date: 11/15/2021
Citation: Wang, H., Grant, W.E., Koralewski, T.E., Brewer, M.J., Elliott, N.C. 2021. Simulating migration of wind-borne pests: “Deconstructing” representation of the emigration process. Ecological Modelling. https://doi.org/10.1016/j.ecolmodel.2021.109742.
Interpretive Summary: Models capable of simulating both local population dynamics and long-range dispersal of wind-borne pests show promise as components of areawide pest management programs. However, modeling causes of emigration (and, hence, subsequent infestation of fields by pest insects) remains a primary source of uncertainty limiting use of models for pest prediction. We present results of a robustness analysis in which we systematically “deconstructed” the representation of emigration in a recent model that forecasts regional infestations of North American sorghum fields by sugarcane aphids. Results of robustness analysis suggest that our forecasts of emigration timing were robust, whereas our forecasts of emigration magnitude were not. The take-home message from robustness analysis is that we should shift our modeling focus from details of the representation of interactions among sorghum growth stage, aphid density, and aphid developmental stage as causes of emigration to aspects of aphid aeroecology affecting long-range migration. This requires shift in modeling priorities from quantitatively accurate representation of local population dynamics to qualitatively accurate representation of the dispersion and deposition of migrating aphids. This will lead to progress in the use of simulation models as tools for forecasting pest insect infestations geographically.
Technical Abstract: Models capable of simulating both local population dynamics and long-range dispersal of wind-borne pests show promise as components of adaptive areawide pest management programs. Local life cycles and long-range wind-borne transport patterns, especially for small weak fliers, are relatively well-understood. However, modelling proximate causes of emigration from crop fields (and, hence, subsequent infestation of remote crop fields) remains a challenge. We present results of a robustness analysis (RA) in which we systematically “deconstructed” the representation of emigration in a recent model that forecasts regional infestations of North American sorghum (Sorghum bicolor ) fields by the sugarcane aphid ( Melanaphis sacchari ). Results of RA suggested that forecasts of emigration timing were robust, whereas forecasts of emigration magnitude were not. For all deconstructed versions of the model, the time lag between initial infestation of a sorghum field and first emigration of aphids from that field was consistently (in ˜83% of the simulations) less than a week. However, total magnitude of emigration from any given sorghum field differed among model versions by as much as 4- or 5-fold, or by hundreds of thousands of aphids. Placing these RA results within the context of areawide aphid management, they suggest a shift in modelling priorities from further refinement of details representing local population dynamics and magnitudes of emigration events to accurate representation of the dispersion and deposition of migrating aphids. Since (1) forecasted time lags between initial infestation and first emigration were both robust to changes in representation of the emigration process and of short duration, and (2) time lags between a small initial infestation and populations reaching the lower action threshold for pesticide application also can be of short duration, forecasted magnitudes of emigration, in addition to being non-robust, were of marginal utility within an areawide forecasting context. (We hasten to note that details of the terrestrial portion of the aphid life cycle are of the utmost importance from the perspective of modelling local population increase and means of suppression, but that is not our focus here.) Placing our results within the broader context of simulating long-range migration of wind-borne pests as a component of adaptive areawide pest management programs, we advocate the systematic deconstruction of local-scale insect pest models as a matter of habit. Systematic deconstruction could identify robust simplifications that could facilitate linking localscale models to existing atmospheric transport models, thus increasing transferability of local-levels models from one system to another.