The conditional ecology of pest suppression: A general mechanistic framework for predicting landscape effects on biological control

Landscape heterogeneity often increases natural enemy abundance, yet its effects on crop pest suppression are strikingly inconsistent across empirical studies. We developed a trait-based simulation framework to identify the general mechanisms linking landscape structure to realized pest load. Across >150 in silico experiments, we show that landscape attributes influence biological control by altering two early-season predator metrics: (i) the immigration rate from the surrounding landscape and (ii) the rate at which colonizing predators accumulate energy after arriving in the crop. These two conditions form universal causal pathways from landscape structure to pest suppression, but their relative importance depends on pest traits. Suppression of slow-growing, diffusely distributed pests requires high early-season energy accumulation by predators; rapidly growing and aggregated pests are controlled by increased predator immigration alone; suppression of rapid but diffuse pests requires both, and is weak even under favorable conditions. These three suppression fingerprints explain why landscape heterogeneity reliably increases natural enemy arrival yet only sometimes reduces pest load. Our results reveal a general, trait-mediated architecture—the conditional ecology of pest suppression—that reconciles inconsistent field findings, predicts when landscape heterogeneity should enhance biological control, and provides a mechanistic framework for using landscape management to support sustainable agriculture.