Applying generic landscape-scale models of natural pest control to real data

Associations between crops, pests and biocontrol agents make the difference

verfasst von

Marta Bonato, Emily A. Martin, Anna F. Cord, Ralf Seppelt, Michael Beckmann, Michael Strauch

Abstract

Managing agricultural land to maximize the supply of natural pest control can help reduce pesticide use. Tools that are able to represent the relationship between landscape structure, field management and natural pest control can help in deciding which management practices should be used and where. However, the reliability and the predictive power of generic models of natural pest control is largely unknown. We applied an existing generic model of natural pest control potential based on landscape structure to nine sites in five European countries and tested the resulting values against field measurements of natural pest control. Subsequently, we added information on local level factors to test the possibility of improving model performance and predictive power. The results showed that there is generally little or no evidence of correlation between modeled and field-measured values of natural pest control. Moreover, we found high variability in the results, depending on the associations of crops, pests and biocontrol agents considered (e.g. Oilseed rape-Pollen beetle-Parasitoids) and on the different case studies. Factors at the local level, such as conservation tillage, had an overall positive effect on natural pest control, and their inclusion in the models typically increased their predictive power. Our results underline the importance of developing predictive models of natural pest control which are tailored towards specific associations between crops, pests and biocontrol agents, consider local level factors and are trained using field measurements. They would serve as important tools within farmers' decision making, ultimately supporting the shift toward a low-pesticide agriculture.

Organisationseinheit(en)

Institut für Geobotanik

Externe Organisation(en)

Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt
Technische Universität Dresden
Martin-Luther-Universität Halle-Wittenberg
Deutsches Zentrum für integrative Biodiversitätsforschung (iDiv) Halle-Jena-Leipzig

Typ

Artikel

Journal

Agriculture, Ecosystems and Environment

Band

342

Anzahl der Seiten

11

ISSN

0167-8809

Publikationsdatum

01.02.2023

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Ökologie, Nutztierwissenschaften und Zoologie, Agronomie und Nutzpflanzenwissenschaften

Ziele für nachhaltige Entwicklung

SDG 2 – Kein Hunger

Elektronische Version(en)

https://doi.org/10.1016/j.agee.2022.108215 (Zugang: Offen)