Decision support for pest management: Using field data for optimizing temperature-dependent population dynamics models

Mortality dynamics of a polyphagous invasive herbivore reveal clues in its agroecosystem success

BACKGROUND

The population dynamics of polyphagous pests such as Bemisia argentifolii (B. tabaci MEAM1) are governed by complex, interacting factors involving its cultivated and wild host plants, seasonality, movement and demography. To understand mechanisms contributing to population development and pest success within the agroecosystem, contiguous multi-host field sites were established in three environmentally distinct areas in Arizona. Life tables quantified and partition models described mortality sources and rates for immature insect stages on each host plant.

RESULTS

Predation and dislodgement were the largest sources of marginal mortality, supplied the highest irreplaceable mortality and predation was the key factor. Rates of mortality were best predicted, in order, by source, temperature, host plant and season. Marginal mortality was highest for fourth-stage nymphs followed by eggs. Mortality rates were predicted in descending order by stage, temperature and season. Survivorship patterns varied among host plants, and generational mortality averaged 70% on spring cantaloupes but nearly 95% on all other hosts. Population density varied seasonally, persisting at low levels on winter hosts and expanding beginning in the spring; perennial hosts and weeds bridge populations year-round.

CONCLUSION

Survival on winter hosts such as broccoli, albeit low, enables population continuity, whereas unusually high survivorship on spring crops like cantaloupe is an ecological release propelling population growth and driving regional dynamics in the summer and fall. This detailed understanding of mortality dynamics provides clues to the success of this invasive pest in our agroecosystems and facilitates opportunities for improved pest management at a broader landscape scale. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Towards a Knowledge-Based Decision Support System for Integrated Control of Woolly Apple Aphid, Eriosoma lanigerum, with Maximal Biological Suppression by the Parasitoid Aphelinus mali

Simple Summary

The woolly apple aphid Eriosoma lanigerum is an important pest in apple orchards worldwide. At present, effective limitation of woolly aphid populations relies on a good synergy between chemical control treatments and biological suppression by beneficial insects, especially by its main specific natural enemy, the parasitic wasp (parasitoid) Aphelinus mali. In order to reach maximum control levels on woolly apple aphids and avoid negative side effects on A. mali, decision support for the optimal timing and positioning of control treatments is needed. In this study, we developed prediction models that based on the weather conditions (temperature data) can reasonably accurately predict crucial development/activity phases of both insects in the orchard. These prediction models can be utilized to target insecticide sprayings at the most sensitive stage of the pest (woolly apple aphids) and/or to avoid insecticide sprayings with detrimental side effects at the vulnerable stage of the beneficial insect (parasitoid A. mali), as was demonstrated by the outcomes of a field trial in this study.

Abstract

The woolly apple aphid Eriosoma lanigerum (Homoptera: Aphidiae) is an important pest in apple orchards worldwide. Since the withdrawal or restricted use of certain broad-spectrum insecticides, E. lanigerum has become one of the most severe pests in apple growing areas across Western Europe. At present, effective limitation of woolly aphid populations relies on a good synergy between chemical control treatments and biological suppression by beneficial arthropods, especially by its main specific natural enemy, the parasitoid Aphelinus mali (Hymenoptera: Aphelinidae). To develop a knowledge-based decision support system, detailed monitoring data of both species were collected in the field (region of Sint-Truiden, Belgium) for a period of ten years (2010–2020). Aphelinus mali flights were monitored in the field, starting before flowering until the end of the second-generation flight at minimum. The seasonal occurrence of the most important management stages of E. lanigerum, e.g., start of wool production or activity on aerial parts in spring and migration of crawlers from colonies towards flower clusters or shoots, were thoroughly monitored. All obtained data were compared with historical and literature data and analysed in a population dynamics phenological model. Our outcomes showed that the emergence of first-generation A. mali adults (critical for the first parasitation activity and the basis for following A. mali generations in the continuation of the season) can be accurately predicted by the developed model. Hence, this information can be utilized to avoid insecticide sprayings with detrimental side effects at this particular moment as demonstrated by the outcomes of a field trial. In addition, the start of migration of E. lanigerum crawlers towards flower clusters or shoots is accurately predicted by the model. In conclusion, our results demonstrate that the model can be used as decision support system for the optimal timing of control treatments in order to achieve effective control of E. lanigerum with maximal biological suppression by its main natural enemy.