Models of natural pest control: Towards predictions across agricultural landscapes

authored by

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.

Organisation(s)

Institute of Geobotany

External Organisation(s)

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
German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig
Leipzig University
Martin Luther University Halle-Wittenberg
Virginia Polytechnic Institute and State University (Virginia Tech)
Helmholtz Centre for Environmental Research (UFZ)

Type

Review article

Journal

Biological control

Volume

163

ISSN

1049-9644

Publication date

11.2021

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

Insect Science, Agronomy and Crop Science

Sustainable Development Goals

SDG 15 - Life on Land, SDG 3 - Good Health and Well-being, SDG 2 - Zero Hunger, SDG 12 - Responsible Consumption and Production

Electronic version(s)

https://doi.org/10.1016/j.biocontrol.2021.104761 (Access: Open)