The continual development of ecological models and availability of high-resolution gridded climate surfaces have stimulated studies that link climate variables to functional traits of organisms. A primary constraint of these studies is the ability to reliably predict the microclimate that an organism experiences using macroscale climate inputs. This is particularly important in regions where access to empirical information is limited. Here, we contrast correlative models based on both ambient and sea surface temperatures to mechanistic modelling approaches to predict beach sand temperatures at depths relevant to sea turtle nesting. We show that mechanistic models are congruent with correlative models at predicting sand temperatures. We used these predictions to explore thermal variation across 46 mainland and island beaches that span the geographical range of sea turtle nesting in Western Australia. Using high resolution gridded climate surfaces and site-specific soil reflectance, we predict almost 9 °C variation in average annual temperatures between beaches, and nearly 10 °C variation in average temperatures during turtle nesting seasons. Validation of models demonstrated that predictions were typically within 2 °C of observations and, although most sites had high correlations (r2 > 0.7), predictive capacity varied between sites. An advantage of the mechanistic model demonstrated here is that it can be used to explore the impacts of climate change on sea turtle nesting beach temperatures as, unlike correlative models, it can be forced with novel combinations of environmental variables.
Keywords: Beach; Mechanistic model; Microclimate; Rookery; Sea turtle; Thermal environment.
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