The perils of linear thinking: modeling the effects of climate change on insect pest dynamics

How will climate change affect our food security? Although many of the effects of climate change on agriculture have been postulated, spatiotemporal prediction models for important crop pests have not been forthcoming. Pest prediction models are key components for developing agricultural management strategy. However, model inputs such as available climate data are at resolutions that do not readily synchronize with arthropod biology. Moreover, assumptions of a linear relationship between increasing temperature and increasing degree day accumulations can result in substantial errors. Thus, a modeling approach is required that incorporates temperature variation and pest-specific temperature development thresholds. Here we explain how multiple sources of climate data can be synthesized to quantify the effects of climate change on pest dynamics. To illustrate our method, we apply it to a pest of sunflower, the sunflower stem weevil, Cylindrocopturus adspersus (LeConte). Climate change simulations altered the duration of the crop at-risk window, with some areas, unexpectedly, experiencing longer at-risk windows. Our work details a biologically-relevant climate modeling approach for arthropod pest dynamics with results designed to help mitigate the effects of climate change, and thus improve our food supply resilience.