Evaluation of Areawide Forecasts of Wind-borne Crop Pests: Sugarcane Aphid (Hemiptera: Aphididae) Infestations of Sorghum in the Great Plains of North America

Author:

Koralewski Tomasz E1,Wang Hsiao-Hsuan1,Grant William E1,Brewer Michael J2,Elliott Norman C3

Affiliation:

1. Ecological Systems Laboratory, Department of Ecology and Conservation Biology, Texas A&M University , 2258 TAMU, College Station, TX , USA

2. Texas AgriLife Research, Department of Entomology, Texas AgriLife Research and Extension Center , 10345 State Highway 44, Corpus Christi, TX , USA

3. USDA, Agricultural Research Service , 1301 North Western Road, Stillwater, OK , USA

Abstract

Abstract Airborne pests pose a major challenge in agriculture. Integrated pest management programs have been considered a viable response to this challenge, and pest forecasting can aid in strategic management decisions. Annually recurrent areawide sugarcane aphid [Melanaphis sacchari (Zehntner) (Hemiptera: Aphididae)] infestations of sorghum [Sorghum bicolor (L.) Moench (Poales: Poaceae)] in the Great Plains of North America is one of such challenges. As part of the response, a spatially-explicit individual-based model was developed that simulates sugarcane aphid infestations over the southern-to-central part of the region. In this work, we evaluated model forecasts using 2015–2018 field data. The ranges of forecasted days of first infestation significantly overlapped with those observed in the field. The average days of first infestation observed in the field were approximated by the model with differences of less than 28 days in Texas and southern Oklahoma (2015–2018), and in northern Oklahoma (2016–2017). In half of these cases the difference was less than 14 days. In general, the modeled average day of first infestation was earlier than the observed one. As conceptual modeling decisions may impact model forecasts and as various socio-environmental factors may impact spatio-temporal patterns of field data collection, agreement between the forecasts and the observed estimates may vary between locations and seasons. Predictive modeling has the potential to occupy a central position within areawide integrated pest management programs. More detailed consideration of local agricultural practices and local environmental conditions could improve forecasting accuracy, as could broader participation of producers in field monitoring efforts.

Funder

U.S. Department of Agriculture

Publisher

Oxford University Press (OUP)

Subject

Insect Science,Ecology,General Medicine

Reference33 articles.

1. EDDMapS – Early Detection and Distribution Mapping System for the Southeast Exotic Pest Plant Council;Bargeron;Wildland Weeds,2007

2. Sugarcane aphid (Hemiptera: Aphididae): a new pest on sorghum in North America;Bowling;J. Integr. Pest Manag,2016

3. Invasive cereal aphids of North America: ecology and pest management;Brewer;Annu. Rev. Entomol,2019

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