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Drivers of change and their indicators Scaling of fragmentation Microclimate
 

Microclimate

Existing global climate models can predict average air temperatures at coarse resolutions, but the survival of organisms depends on very fine-scale local conditions. The SCALES microclimate tool uses fine-scale topographic data, along with climate data, to predict local ground temperatures.

Downscaling climate data and forecasts across European landscapes


Plants and animals have the greatest chances of survival at environmental temperatures to which they are adapted. Both air and ground temperatures can vary widely between nearby points in a landscape because of effects of altitude, vegetation cover and varying exposure to the Sun's rays. Ground temperature in particular may vary widely among microsites, and is particularly important for ecosystem functions because of its effect on plant roots and soil-dwelling animals. This variation will alter the survival of organisms and the distribution of suitable habitat at fine spatial scales. Temperatures can also fluctuate rapidly, reaching maxima and minima not described in mean climatic records or forecasts.



Differential frost cover on uneven ground in sunny conditions, photographed around 10am on 6 March at 53.78°N, 1.61°W. (Picture credit: Richard Gunton)

Existing global weather models can predict average air temperatures at coarse resolutions (e.g. 0.25-degree cells or coarser) but topographic data are available for the entire Earth's land surface at very fine resolutions, suggesting a way to down-scale model predictions insofar as they depend on topography. We developed a downscaling tool called micEuroclim that provides a method to do this: a set of formulas that can be used to predict monthly mean, maximum and minimum temperatures, and daily afternoon temperatures, for a depth of 2 cm into the soil at either open grassland or tree covered sites. The formulas were derived using a year's temperature data from 83 sites around Europe, combined with publicly-available topographic and climate data.

We find that terrain, combined with sunshine data, is most important for down-scaling monthly maximum temperatures, followed by monthly mean and noon temperatures at open sites; it contributes little for down-scaling monthly minimum temperatures, or noon temperatures at tree-covered sites. Typical weather data forecasted for future climate scenarios could thus be used to generate fine-scale predictions of the areas that will be suitable for species whose ranges are limited by mean or maximum soil temperatures. Such predictions could be used to model species' ranges and habitat connectivity, which can in turn be used for predicting the potential for migration and changes in biodiversity under predicted climate change. For sessile organisms and animals with limited mobility, knowledge about the likely microclimate at fine spatial and temporal scales should be valuable for understanding climatic niches, individual dispersal possibilities and community dynamics.

An R package implementing our models for predicting monthly mean and daily afternoon temperatures is available at www.microclim.org.uk. Further details are provided in SCALESBOOK.

Microclimate maps


Microclimates of central-western Europe: predicted soil temperature (degrees Celsius) at 13:40 in mid-July. Click on any of the squares in this map to see a map of microclimate for that square. These maps were generated using function "micEuroclim" in the R package "microclim", with argument pred=3.


Maps based on topographic data from Jarvis A., H.I. Reuter, A. Nelson, E. Guevara (2008): Hole-filled seamless SRTM data V4, International Centre for Tropical Agriculture (CIAT), available from http://srtm.csi.cgiar.org.

References

Gunton, R.M., Lehsten, V., Kunin, W.E. (2014) Downscaling climate data to predict species' ranges, pp. 25-30. In: Henle, K., Potts, S.G., Kunin, W.E., Matsinos, Y.G., Similä, J., Pantis, J.D., Grobelnik, V., Penev, L., Settele, S. (eds.): Scaling in Ecology and Biodiversity Conservation. Pensoft Publishers, Sofia.
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