Author:
Alexandridis Nikolaos,Marion Glenn,Chaplin-Kramer Rebecca,Dainese Matteo,Ekroos Johan,Grab Heather,Jonsson Mattias,Karp Daniel S.,Meyer Carsten,O’Rourke Megan E.,Pontarp Mikael,Poveda Katja,Seppelt Ralf,Smith Henrik G.,Martin Emily A.,Clough Yann
Abstract
AbstractNatural control of crop pests has the potential to complement or replace intensive agricultural practices, but its mainstream application requires reliable predictions in diverse socioecological settings. In lack of a widely accepted model of natural pest control, we review existing modelling approaches and critically examine their potential to provide understanding and predictions across agricultural landscapes. Models that explicitly represent the underlying mechanisms are better positioned to represent the diversity and context sensitivity of natural pest control than correlative models. Such mechanistic models have used diverse techniques to represent crop-pest-enemy combinations at various spatiotemporal scales. However, certain regions of the world and socioeconomic aspects of natural pest control are underrepresented, while modelling approaches are restricted by a fundamental trade-off between generality and realism. We propose that modelling natural pest control across agroecosystems requires a framework of context-specific generalizations, based on empirical evidence and theoretical expectations. Reviewed models of natural pest control indicate potential attributes of such a general predictive framework.
Publisher
Cold Spring Harbor Laboratory