Models of natural pest control: Towards predictions across agricultural landscapes

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