Towards improved pest management of the soybean aphid

TL;DR

This paper develops and compares mathematical models for controlling soybean aphids using biological agents and insecticides, highlighting the effectiveness of combined predator-parasitoid strategies over insecticides alone.

Contribution

It introduces empirically motivated models for pest control, incorporating predator, parasitoid, and insecticide interactions, and evaluates their dynamics and stability in soybean aphid management.

Findings

Parasitoids and predators together stabilize populations more effectively.

Combination of biological control and insecticides enhances suppression.

Models align with long-term field data from 2000-2013.

Abstract

The soybean aphid (\emph{Aphis glycines}) is an invasive insect pest that continues to cause large-scale damage to soybean crops in the North Central United States. The current manuscript proposes several mathematical models for the top-down bio-control of the aphid, as well as control via pesticides and neonicotinoids. The models are motivated empirically, and constructed based on laboratory experiments conducted to test control of aphids by Lacewing larvae, as well as by a parasitic wasp (\emph{Aphidius colemani}). The effectiveness of these models is compared by taking into account factors such as economic injury levels for soybeans, life history traits such as cannibalism amongst the predator, and intraguild predation between competing bio-control agents such as predators and parasitoids. The models predict multiple population peaks and transient chaotic dynamics when a predator and/or insecticides are used. It is observed that parasitoids, in conjunction with predators, are more efficient at stabilizing the population dynamics than insecticide use. They also suggest a combination of predators, parasitoids, and insecticides would be more efficient at suppressing aphid populations than using only predators or parasitoids. The models also qualitatively capture the features seen in long-time field data from 2000-2013. We discuss applications of our results to pest management strategies for soybean aphids in the context of a changing climate, as well as regime shifts.