Morphologically complex flowers are characterized by bilateral symmetry, tube-like shapes, deep corolla tubes, fused petals, and/or poricidal anthers, all of which constrain the access of insect visitors to floral nectar and pollen rewards. Only a subset of potential pollinators, mainly large bees, learn to successfully forage on such flowers. Thus, complexity may comprise a morphological filter that restricts the range of visitors and thereby increases food intake for successful foragers. Such pollinator specialization, in turn, promotes flower constancy and reduces cross-species pollen transfer, providing fitness benefits to plants with complex flowers. Since visual signals associated with floral morphological complexity are generally honest (i.e., indicate food rewards), pollinators need to perceive and process them. Physiological studies show that bees detect distant flowers through long-wavelength sensitive photoreceptors. Bees effectively perceive complex shapes and learn the positions of contours based on their spatial frequencies. Complex flowers require long handling times by naive visitors, and become highly profitable only for experienced foragers. To explore possible pathways towards the evolution of floral complexity, we discuss cognitive mechanisms that potentially allow insects to persist on complex flowers despite low initial foraging gains, suggest experiments to test these mechanisms, and speculate on their adaptive value.

Identifying traits that are associated with success of introduced natural enemies in establishing and controlling pest insects has occupied researchers and biological control practitioners for decades. Unfortunately, consistent general relationships have been difficult to detect, preventing a priori ranking of candidate biological control agents based on their traits. We summarise previous efforts and propose a series of potential explanations for the lack of clear patterns. We argue that the quality of current datasets is insufficient to detect complex trait-efficacy relationships and suggest several measures by which current limitations may be overcome. We conclude that efforts to address this elusive issue have not yet been exhausted and that further explorations are likely to be worthwhile.

In Integrated Pest Management programs, insecticides are applied to agricultural crops when pest densities exceed a predetermined economic threshold. Under conditions of high natural enemy density, however, the economic threshold can be increased, allowing for fewer insecticide applications. These adjustments, called ‘dynamic thresholds’, allow farmers to exploit existing biological control interactions without economic loss. Further, the ability of natural enemies to disperse from, and subsequently immigrate into, insecticide-sprayed areas can affect their biological control potential. We develop a theoretical approach to incorporate both pest and natural enemy movement across field borders into dynamic thresholds and explore how these affect insecticide applications and farmer incomes. Our model follows a pest and its specialist natural enemy over one growing season. An insecticide that targets the pest also induces mortality of the natural enemy, both via direct toxicity and reduced resource pest densities. Pest and natural enemy populations recover after spraying through within-field reproduction and by immigration from neighboring unsprayed areas. The number of insecticide applications and per-season farmer revenues are calculated for economic thresholds that are either fixed (ignoring natural enemy densities) or dynamic (incorporating them). The model predicts that using dynamic thresholds always leads to reduced insecticide application. The benefit of dynamic thresholds in reducing insecticide use is highest when natural enemies rapidly recolonize sprayed areas, and when insecticide efficacy is low. We discuss real-life situations in which monitoring of natural enemies would substantially reduce insecticide use and other scenarios where the presence of beneficial organisms may lead to threshold modifications.