Microclimate modelling at macro scales: a test of a general microclimate model integrated with gridded continental-scale soil and weather data
Article first published online: 18 JAN 2014
© 2013 The Authors. Methods in Ecology and Evolution © 2013 British Ecological Society
Methods in Ecology and Evolution
Volume 5, Issue 3, pages 273–286, March 2014
How to Cite
Kearney, M. R., Shamakhy, A., Tingley, R., Karoly, D. J., Hoffmann, A. A., Briggs, P. R., Porter, W. P. (2014), Microclimate modelling at macro scales: a test of a general microclimate model integrated with gridded continental-scale soil and weather data. Methods in Ecology and Evolution, 5: 273–286. doi: 10.1111/2041-210X.12148
- Issue published online: 11 MAR 2014
- Article first published online: 18 JAN 2014
- Accepted manuscript online: 9 DEC 2013 05:05AM EST
- Manuscript Accepted: 28 NOV 2013
- Manuscript Received: 20 SEP 2013
- University of Melbourne Science Faculty Seed Grant
- Australian Research Council (ARC) Fellowship
- ARC Laureate Fellowship
- ARC Federation Fellowship
- ARC Centre of Excellence for Environmental Decisions
- biophysical ecology;
- mechanistic model;
- soil temperature;
- The microclimate experienced by organisms is determined by local weather conditions. Yet the environmental data available for predicting the effect of climate on the distribution and abundance of organisms are typically in the form of long-term average monthly climate measured at standardized heights above the ground.
- Here, we demonstrate how hourly microclimates can be modelled mechanistically over decades at the continental scale with biologically suitable accuracy.
- We extend the microclimate model of the software package niche mapper to capture spatial and temporal variation in soil thermal properties and integrate it with gridded soil and weather data for Australia at 0·05° resolution.
- When tested against historical observations of soil temperature, the microclimate model predicted 85% of the variation in hourly soil temperature across 10 years from the surface to 1 m deep with an accuracy of 2–3·3 °C (c. 10% of the temperature range at a given depth) across an extremely climatically diverse range of sites.
- This capacity to accurately and mechanistically predict hourly local microclimates across continental scales creates new opportunities for understanding how organisms respond to changes in climate.