Integrating Models of Atmospheric Dispersion and Crop-Pest Dynamics: Linking Detection of Local Aphid Infestations to Forecasts of Region-Wide Invasion of Cereal Crops

Author:

Koralewski Tomasz E1,Wang Hsiao-Hsuan1,Grant William E1,Brewer Michael J2ORCID,Elliott Norman C3,Westbrook John K4,Szczepaniec Adrianna5ORCID,Knutson Allen6,Giles Kristopher L7,Michaud J P8

Affiliation:

1. Ecological Systems Laboratory, Department of Wildlife and Fisheries Sciences, Texas A&M University, TAMU, College Station, TX

2. Texas AgriLife Research, Department of Entomology, Texas AgriLife Research and Extension Center, Corpus Christi, TX

3. Plant Science Research Laboratory, USDA-ARS, Stillwater, OK

4. USDA, Agricultural Research Service (Retired), College Station, TX

5. Texas A&M AgriLife Research, Department of Entomology, Texas A&M AgriLife Research and Extension Center, Amarillo, TX

6. Texas A&M AgriLife Extension, Department of Entomology, Texas A&M AgriLife Research and Extension Center, Dallas, TX

7. Entomology and Plant Pathology, Oklahoma State University, 127 Noble Research Center, Stillwater, OK

8. Department of Entomology, Kansas State University, Agricultural Research Center–Hays, Hays, KS

Abstract

Abstract Invasive airborne insects pose major challenges in natural resource and agriculture management, as they can rapidly spread over large distances and cross physical boundaries. Field monitoring and local management are important tools to prevent and control infestations but require additional coordination to be operative region-wide. Computational modeling techniques have been effective in simulating local population dynamics and in capturing spread of invasive species on a regional scale. We use an integrated ecological model to simulate local and regional infestation dynamics of sugarcane aphids, Melanaphis sacchari (Zehntner) (Hemiptera: Aphididae), on sorghum, Sorghum bicolor (L.) Moench (family Poaceae), in the southern to central Great Plains of the United States. Local dynamics of aphid populations on sorghum are simulated by a spatially explicit, individual-based model, whereas regional aphid migration is simulated by an atmospheric model that computes inert air particle (aphid) transport, dispersion, and deposition. Simulation results indicate timing of initial infestations in the south affects spatiotemporal patterns of infestation throughout the region. Probability of local infestations is a function of both percentage of land occupied by growing sorghum and prevailing winds. Thus, due to availability of sorghum, relatively later dates of initial infestation in the south will probably lead to infestations farther north that become established more quickly following the first appearance of aphids in the south. The model we present, in coordination with field monitoring schemes, could be applied as a forecasting tool in region-wide pest management systems.

Funder

USDA-ARS

Publisher

Oxford University Press (OUP)

Subject

Insect Science

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