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ARS Home » Plains Area » El Reno, Oklahoma » Oklahoma and Central Plains Agricultural Research Center » Peanut and Small Grains Research Unit » Research » Research Project #443940

Research Project: Sorghum Aphid Ecological Model for Improved Areawide Pest Management

Location: Peanut and Small Grains Research Unit

Project Number: 3070-22000-017-006-S
Project Type: Non-Assistance Cooperative Agreement

Start Date: Jun 1, 2023
End Date: Dec 31, 2024

Objective:
The insufficiently understood process of aphid migration presents an impediment to effective sorghum aphid integrated areawide pest management. The primary purpose of the modeling effort is to use a model in conjunction with empirically obtained data to better understand migration and within field population dynamics in order to predict sorghum aphid population dynamics in relation to spatial and temporal environmental heterogeneity. An existing simulation model of sorghum aphid regional migration and population dynamics will be the starting point for this project. Briefly, the model simulates sorghum aphid regional population dynamics using the NOAA Air Resources Laboratory (ARL) Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model (HYSPLIT PC version 4.9) that was previously developed and evaluated by the Cooperator, colleagues, and the ARS PI. Based on comparison to field collected data from 2017 and 2018, the model simulates some aspects of sorghum aphid regional population dynamics well but lacks precision in fine scale spatial and temporal prediction. Therefore, for objective 1 the model will be modified to incorporate spatially explicit geographical and meteorological data with the aim of improving fine scale spatial and temporal prediction, to produce a model with utility for predicting sorghum aphid population outbreaks and assessing strategies for areawide pest management. For objective 2, the Cooperator will interface the model with geographic data bases, such as USDA-NASS Cropland Data and NOAA geographical archived meteorological data to consult with developers of a model of the effects of weather on sorghum aphid infestation. The model evaluates the effect of spatial and temporal patterns of weather variables on sorghum aphid dispersal at a finer scale than the HYSPLIT based mode. Econometric methods identified north-westerly wind direction to cause persistent aphid movements and accurately simulates spatial patterns of aphid infestation within Oklahoma. The Cooperator will conduct a detailed evaluation of this model, its assumptions, and structure to determine aspects of the model that can be integrated with the HYSPLIT based model to improve fine scale infestation predictions. Once integration of models and/or incorporating aspects of model structure and integration of fine scale geographical and meteorologic data have been completed and the resulting model tested it will be used to evaluate areawide pest management scenarios, such as deployment strategies for sorghum aphid resistant sorghum varieties. Predictions will be validated by ongoing field monitoring using field collected data from 2019-2023 and ground-truthing at locations where model predictions indicate sorghum aphid population outbreaks.

Approach:
The cooperator will address the following objectives: (1) evaluate an existing individual-based mathematical simulation model of sorghum aphid, Melonaphis sorghi (previously named surgarcane aphid), for accuracy at describing sorghum aphid population dynamics, dispersal, and regional migration, insufficiently understood ecological processes that present impediments to optimal sorghum aphid areawide pest management; 2) modify and improve the mathematical model by interfacing with geographical databases of agricultural land use and meteorology; and 3) compare the model to a second existing model of sorghum aphid fine scale dispersal to determine similarities and differences in model structure that can be exploited to improve model accuracy for determining sorghum aphid migration patterns at coarse and fine scales and simulating population dynamics for the purpose of understanding and quantifying sorghum aphid ecology and pest population dynamics.