Understanding how climate determines species geographic distributions is an important question in ecology with direct implications for predicting climate change-driven range shifts. For Lepidoptera, degree-days, a measure of growing season length, has been shown to be a limiting factor of species distributions in some cases. Most studies use a standardized base development temperature in their calculations of degree-days instead of a species-specific threshold so past estimates of the influence of degree-days on Lepidoptera distributions may not have been optimal. Theoretically, species-specific estimates of degree-days should improve the accuracy of species distribution models. In practise, this has not always been the case. Given the prevalence of species distribution models in fundamental and applied research, a better understanding of when and how lab-based physiological thresholds can be scaled up to inform broad-scale predictions is needed. We compare the predictive ability of correlative species distribution models, based on standardized calculations of degree-days, to hybrid models, based on species-specific degree-days, using 14 moth species native to North America to determine whether: a) degree-days are the best climatic predictor of Lepidoptera species’ distributions at broad scales; and b) physiological traits improve the predictions of these distributions.
Results/Conclusions:
Degree-days was the top contributor for the greatest number of species in the correlative and hybrid models (35%, 42% respectively). On average, degree-days accounted for ~45% of model contribution in the correlative model and ~46% of model contribution in the hybrid model. These results suggest that degree-days are the best climatic predictor of species distributions for this group of Lepidoptera. On average, there was no difference in model accuracy between the correlative and hybrid models, suggesting that thermal tolerance data may not improve Lepidoptera species’ distribution models at broad scales. Determining the ultimate factors that limit species’ distributions will be critical in accurately predicting species’ range shifts response to future climate change.
