Effects of temperature and resource variation on insect population dynamics: the bordered plant bug as a case study

In species with complex life cycles, population dynamics result from a combination of intrinsic cycles arising from delays in the operation of negative density‐dependent processes (e.g. intraspecific competition) and extrinsic fluctuations arising from seasonal variation in the abiotic environment. Abiotic variation can affect species directly through their life‐history traits and indirectly by modulating the species’ interactions with resources or natural enemies. We investigate how the interplay between density‐dependent dynamics and abiotic variability affects population dynamics of the bordered plant bug (Largus californicus), a Hemipteran herbivore inhabiting the California coastal sage scrub community. Field data show a striking pattern in abundance: adults are extremely abundant or nearly absent during certain periods of the year, leading us to predict that seasonal forcing plays a role in driving observed dynamics. We develop a stage‐structured population model with variable developmental delays, in which fecundity is affected by both intraspecific competition and temporal variation in resource availability and all life‐history traits (reproduction, development, mortality) are temperature‐dependent. We parameterize the model with experimental data on temperature responses of life‐history and competitive traits and validate the model with independent field census data. We find that intraspecific competition is strongest at temperatures optimal for reproduction, which theory predicts leads to more complex population dynamics. Our model predicts that while temperature or resource variability interacts with development‐induced delays in self‐limitation to generate population fluctuations, it is the interplay between all three factors that drive the observed dynamics. Considering how multiple abiotic factors interact with density‐dependent processes is important both for understanding how species persist in variable environments and predicting species’ responses to perturbations in their typical environment.