Models of natural pest control: Towards predictions across agricultural landscapes

verfasst von
N. Alexandridis, G. Marion, R. Chaplin-Kramer, M. Dainese, J. Ekroos, H. Grab, M. Jonsson, D.S. Karp, C. Meyer, M.E. O'Rourke, M. Pontarp, K. Poveda, R. Seppelt, H.G. Smith, E.A. Martin, Y. Clough
Abstract

Natural control of invertebrate crop pests has the potential to complement or replace conventional insecticide-based practices, but its mainstream application is hampered by predictive unreliability across agroecosystems. Inconsistent responses of natural pest control to changes in landscape characteristics have been attributed to ecological complexity and system-specific conditions. Here, we review agroecological models and their potential to provide predictions of natural pest control across agricultural landscapes. Existing models have used a multitude of techniques to represent specific crop-pest-enemy systems at various spatiotemporal scales, but less wealthy regions of the world are underrepresented. A realistic representation of natural pest control across systems appears to be hindered by a practical trade-off between generality and realism. Nonetheless, observations of context-sensitive, trait-mediated responses of natural pest control to land-use gradients indicate the potential of ecological models that explicitly represent the underlying mechanisms. We conclude that modelling natural pest control across agroecosystems should exploit existing mechanistic techniques towards a framework of contextually bound generalizations. Observed similarities in causal relationships can inform the functional grouping of diverse agroecosystems worldwide and the development of the respective models based on general, but context-sensitive, ecological mechanisms. The combined use of qualitative and quantitative techniques should allow the flexible integration of empirical evidence and ecological theory for robust predictions of natural pest control across a wide range of agroecological contexts and levels of knowledge availability. We highlight challenges and promising directions towards developing such a general modelling framework.

Organisationseinheit(en)
Institut für Geobotanik
Externe Organisation(en)
Lund University
Biomathematics and Statistics Scotland
Stanford University
University of Minnesota
Eurac Research
Cornell University
Swedish University of Agricultural Sciences
University of California at Davis
Deutsches Zentrum für integrative Biodiversitätsforschung (iDiv) Halle-Jena-Leipzig
Universität Leipzig
Martin-Luther-Universität Halle-Wittenberg
Virginia Polytechnic Institute and State University (Virginia Tech)
Helmholtz-Zentrum für Umweltforschung (UFZ)
Typ
Übersichtsarbeit
Journal
Biological control
Band
163
ISSN
1049-9644
Publikationsdatum
11.2021
Publikationsstatus
Veröffentlicht
Peer-reviewed
Ja
ASJC Scopus Sachgebiete
Insektenkunde, Agronomie und Nutzpflanzenwissenschaften
Ziele für nachhaltige Entwicklung
SDG 15 – Lebensraum Land, SDG 3 – Gute Gesundheit und Wohlergehen, SDG 2 – Kein Hunger, SDG 12 – Verantwortungsvoller Konsum und Produktion
Elektronische Version(en)
https://doi.org/10.1016/j.biocontrol.2021.104761 (Zugang: Offen)