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Insects 2018, 9(3), 115; https://doi.org/10.3390/insects9030115

An Advanced Numerical Trajectory Model Tracks a Corn Earworm Moth Migration Event in Texas, USA

1
Department of Entomology, Nanjing Agricultural University, Nanjing 210095, China
2
Department of Entomology, Texas A&M University, College Station, TX 77843-2475, USA
3
Insect Control and Cotton Disease Research Unit, US Department of Agriculture, Agricultural Research Service, College Station, TX 77845, USA
These authors contributed equally to this work.
*
Authors to whom correspondence should be addressed.
Received: 26 July 2018 / Revised: 31 August 2018 / Accepted: 3 September 2018 / Published: 5 September 2018
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Abstract

Many methods for trajectory simulation, such as Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT), have been developed over the past several decades and contributed greatly to our knowledge in insect migratory movement. To improve the accuracy of trajectory simulation, we developed a new numerical trajectory model, in which the self-powered flight behaviors of insects are considered and trajectory calculation is driven by high spatio-temporal resolution weather conditions simulated by the Weather Research and Forecasting (WRF) model. However, a rigorous evaluation of the accuracy of different trajectory models on simulated long-distance migration is lacking. Hence, in this study our trajectory model was evaluated by a migration event of the corn earworm moth, Helicoverpa zea, in Texas, USA on 20–22 March 1995. The results indicate that the simulated migration trajectories are in good agreement with occurrences of all pollen-marked male H. zea immigrants monitored in pheromone traps. Statistical comparisons in the present study suggest that our model performed better than the popularly-used HYSPLIT model in simulating migration trajectories of H. zea. This study also shows the importance of high-resolution atmospheric data and a full understanding of migration behaviors to the computational design of models that simulate migration trajectories of highly-flying insects. View Full-Text
Keywords: numerical simulation; migration; Weather Research and Forecasting (WRF) model; three-dimensional trajectory analysis program; valuation; Helicoverpa zea numerical simulation; migration; Weather Research and Forecasting (WRF) model; three-dimensional trajectory analysis program; valuation; Helicoverpa zea
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Wu, Q.-L.; Hu, G.; Westbrook, J.K.; Sword, G.A.; Zhai, B.-P. An Advanced Numerical Trajectory Model Tracks a Corn Earworm Moth Migration Event in Texas, USA. Insects 2018, 9, 115.

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