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Improving invasive species management using predictive phenology models: an example from brown marmorated stink bug (Halyomorpha halys) in Japan

BACKGROUND In order to better understand the population dynamics of invasive species in their native range, we developed two predictive phenological models using the ubiquitous invasive insect pest, Halyomorpha halys (Stål) (Hemiptera: Pentatomidae), as the model organism. Our work establishes a zer...

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Published in:Pest management science 2021-12, Vol.77 (12), p.5489-5497
Main Authors: Kamiyama, Matthew T, Matsuura, Kenji, Yoshimura, Tsuyoshi, Yang, Chin‐Cheng Scotty
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description BACKGROUND In order to better understand the population dynamics of invasive species in their native range, we developed two predictive phenological models using the ubiquitous invasive insect pest, Halyomorpha halys (Stål) (Hemiptera: Pentatomidae), as the model organism. Our work establishes a zero‐inflated negative binomial regression (ZINB) model, and a general additive mixed model (GAMM) based on 11 years of black light trap monitoring of H. halys at three locations in Japan. RESULTS The ZINB model indicated that degree days (DD) have a significant effect on the trap catch of adult H. halys, and that precipitation has no effect. A dataset generated by 1000 simulations from the ZINB suggested that higher predicted trap catches equated to a lower probability of encountering a zero‐count. The GAMM produced a cubic regression smooth curve which forecasts the seasonal phenology of H. halys as following a bell‐shaped trend in Japan. Critical DD points during the field season in Japan included 261 DD for first H. halys adult detection and 1091 DD for peak activity. CONCLUSIONS This study establishes the first models capable of forecasting native H. halys population dynamics based on DD. These robust models practically improve population forecasting of H. halys in the future and help fill gaps in knowledge pertaining to its native phenology, thus ultimately contributing to the progression of efficient management of this globally invasive species. © 2021 Society of Chemical Industry. The population dynamics of Halyomorpha halys follow a single peaked trend throughout the field season in Japan, as estimated by predictive degree day‐based phenology models.
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Our work establishes a zero‐inflated negative binomial regression (ZINB) model, and a general additive mixed model (GAMM) based on 11 years of black light trap monitoring of H. halys at three locations in Japan. RESULTS The ZINB model indicated that degree days (DD) have a significant effect on the trap catch of adult H. halys, and that precipitation has no effect. A dataset generated by 1000 simulations from the ZINB suggested that higher predicted trap catches equated to a lower probability of encountering a zero‐count. The GAMM produced a cubic regression smooth curve which forecasts the seasonal phenology of H. halys as following a bell‐shaped trend in Japan. Critical DD points during the field season in Japan included 261 DD for first H. halys adult detection and 1091 DD for peak activity. CONCLUSIONS This study establishes the first models capable of forecasting native H. halys population dynamics based on DD. These robust models practically improve population forecasting of H. halys in the future and help fill gaps in knowledge pertaining to its native phenology, thus ultimately contributing to the progression of efficient management of this globally invasive species. © 2021 Society of Chemical Industry. 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Our work establishes a zero‐inflated negative binomial regression (ZINB) model, and a general additive mixed model (GAMM) based on 11 years of black light trap monitoring of H. halys at three locations in Japan. RESULTS The ZINB model indicated that degree days (DD) have a significant effect on the trap catch of adult H. halys, and that precipitation has no effect. A dataset generated by 1000 simulations from the ZINB suggested that higher predicted trap catches equated to a lower probability of encountering a zero‐count. The GAMM produced a cubic regression smooth curve which forecasts the seasonal phenology of H. halys as following a bell‐shaped trend in Japan. Critical DD points during the field season in Japan included 261 DD for first H. halys adult detection and 1091 DD for peak activity. CONCLUSIONS This study establishes the first models capable of forecasting native H. halys population dynamics based on DD. These robust models practically improve population forecasting of H. halys in the future and help fill gaps in knowledge pertaining to its native phenology, thus ultimately contributing to the progression of efficient management of this globally invasive species. © 2021 Society of Chemical Industry. 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subjects Black light
Forecasting
Halyomorpha halys
Indigenous species
Insects
integrated pest management
Introduced species
Invasive insects
Invasive species
Nonnative species
pentatomidae
pest monitoring
Phenology
Population dynamics
Population forecasting
Regression models
Statistical analysis
zero‐inflation
title Improving invasive species management using predictive phenology models: an example from brown marmorated stink bug (Halyomorpha halys) in Japan
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