Asian Gypsy Moth
Asian Gypsy Moth Phenology and Potential Distribution Modeling
Phenology is the study of the relationship between environmental factors (especially temperature, moisture, and nutrition) and cyclical/seasonal biological phenomena (e.g., flowering, insect emergence). To support effective eradication treatments, we are developing models to more accurately predict the timing of all Asian gypsy moth life stages.
Management of the European gypsy moth (Lymantria dispar dispar) in North America has benefited from more than a century of research. The Asian gypsy moth (AGM) strains bring new challenges including multiple subspecies (Lymantria dispar asiatica and Lymantria dispar japonica), broad distributions across diverse habitats, and limited data on the variation in the phenology of source populations, which may affect risk. Many additional factors can play a role in the phenology of the gypsy moth as the illustration suggests.
The Gypsy Moth Life Stage model (GLS) has been used to predict the invasive range of the European gypsy moth in North America and New Zealand. The GLS has also been used to model the invasive range of Asian subspecies, despite observed differences between the European and Asian populations. Either existing phenology models (like the GLS) for European gypsy moth need to be reparametrized for Asian populations or new models need to be developed to adequately predict the timing of key stages and potential range if they become established.
To address these issues, new models were developed as well as new parameters established for Asian populations in existing models.
First, the published phenology parameters for the eight populations of AGM were used to develop eight strain-specific, agent-based phenological models. These models were applied to 47 shipping ports in East Asia where the AGM is native. Model outputs were compared with available trap data to assess the role of population variation in predicting moth flight among varied locations, assess variation in the performance of models among years, and assess the importance of modeling phenology using parameters from a ‘local’ moth population.
Second, the results of temperature and exposure duration on the timing of gypsy moth egg hatch were used to develop phenology model parameters for the lower chill requirement that is present in some Asian populations.
Third, the potential distribution of Asian gypsy moth in Canada was assessed using two presence-only species distribution models, Maximum Entropy (MaxEnt) and Genetic Algorithm for Rule-set Prediction (GARP). In addition, AGM potential future distribution under two future climate change scenarios was mapped while implementing dispersal constraints.
The goal of this research is to develop models that can predict the timing of all life stages of gypsy moths from Asian origin, and the ability to predict the potential range of AGM in invaded areas.
Variation in phenological parameters among the eight populations yielded variation in predicted flight times among the 47 shipping ports analyzed, and the use of ‘local’ populations did not generally improve model fit. Model accuracy varied substantially among ports and among years within some ports. The larva-to-adult agent-based models have utility in estimating flight periods for some ports in their current form, but variation in model quality across the landscape suggests that there is potential for unsampled and unparameterized moth populations and factors that remain to be quantified. These models can also be used to predict when larvae are the right size to apply eradication treatments and when male moths occur to deploy traps for detecting the presence of the Asian populations.
Trotter, R. Talbot, III; Limbu, Samita; Hoover, Kelli; Nadel, Hannah; Keena, Melody A. 2020. Comparing Asian gypsy moth [Lymantria dispar asiatica (Lepidoptera: Erebidae) and L. dispar japonica] trap data from East Asian ports with lab parameterized phenology models: new tools and questions. Annals of the Entomological Society of America. 14 p. https//doi.org/10.1093/aesa/saz037.
Parameters for Hatch Phenology Model
The importance of AGM as a potential forest and urban pest in North America, and the ongoing threat of its introduction via international trade, make it vital to derive model parameters that can predict the phenological development leading to egg hatch for all the AGM populations. Egg hatch is arguably the most important life cycle event in gypsy moth population suppression/eradication interventions and in estimating their potential invasive range. By developing new model parameters, we are able to more accurately predict egg hatch for the Asian gypsy moth populations that have different requirements from those of the European gypsy moth.
Gray, David R; Keena, Melody A. 2019. A Phenology Model for Asian Gypsy Moth Egg Hatch. Environmental Entomology. 48(4): 903-910. https://doi.org/10.1093/ee/nvz051.
Predicting Potential Distribution
MaxEnt had higher model fit and sensitivity scores than the GARP model, indicating better discrimination of suitable versus unsuitable areas for AGM. The models indicated that suitable conditions for AGM were present in the provinces of British Columbia, Ontario, Quebec, Nova Scotia and New Brunswick. The human influence index was the variable found to contribute the most in predicting the distribution of AGM. These model results can be used to identify areas at risk for this pest, to inform strategic and tactical pest management decisions.
Srivastava, Vivek; Griess, Verena C.; Keena, Melody A. 2020. Assessing the Potential Distribution of Asian Gypsy Moth in Canada: A Comparison of Two Methodological Approaches. Scientific Reports. 10: 22. 10 p. https://doi.org/10.1038/s41598-019-57020-7
- Melody Keena, USDA Forest Service, Northern Research Station, Research Entomologist
- R. Talbot Trotter III, USDA Forest Service, Northern Research Station, Research Ecologist
- Samita Limbu, The Pennsylvania State University, Department of Entomology, previous doctoral student
- Hannah Nadel, USDA Animal and Plant Health Inspection Service, PPQ S & T, Buzzards Bay, MA
- Kelli Hoover, The Pennsylvania State University, Department of Entomology
- David Gray, Natural Resources Canada, Canadian Forest Service—Atlantic Forestry Centre, Fredericton, NB, Canada (retired)
- Vivek Srivastava, University of British Columbia, Department of Forest Resources Management, Vancouver, British Columbia, Canada, graduate student
- Verena Griess, University of British Columbia, Department of Forest Resources Management, Vancouver, British Columbia, Canada
- Last modified: May 29, 2020