The slope and aspect of a vegetated surface strongly affects the amount of solar radiation intercepted by that surface. Solar radiation is the dominant component of the surface energy balance and influences ecologically critical factors of microclimate, including near-surface temperatures, evaporative demand and soil moisture content. It also determines the exposure of vegetation to photosynthetically active and ultra-violet wavelengths. Spatial variation in slope and aspect is therefore a key determinant of vegetation pattern, species distribution and ecosystem processes in many environments. Slope and aspect angle may vary considerably over distances of a few metres, and fine-scale species' distribution patterns frequently follow these topographic patterns. The availability of suitable microclimate at such scales may be critical for the response of species distributions to climatic change at much larger spatial scales. However, quantifying the relevant microclimatic gradients is not straightforward, as the potential variation in solar radiation flux under clear-sky conditions is modified by local and regional variations in cloud cover, and interacts with long-wave radiation exchange, local meteorology and surface characteristics. We tested simple models of near-surface temperature and potential evapotranspiration driven by meteorological data with the incoming solar radiation flux adjusted for topography against measurements of temperature and soil moisture at two chalk grassland field sites in contrasting regional climates of the United Kingdom. We then estimated the cumulative distribution function of three key ecological variables (monthly temperature sums above 5 and 30 degrees C, plus potential evapotranspiration) across areas of complex topography at each site using two separate approaches: a spatially explicit and a spatially implicit method. The spatially explicit method uses digital elevation models of the sites to calculate the solar radiation at each grid cell and hence determines the spatial distribution of environmental variables. The second, less computationally intensive, method uses estimated statistical distributions of slope and aspect within the field sites to calculate the proportion of the surface area of each site predicted to exceed a given threshold of temperature sum or potential evapotranspiration. The spatially implicit model reproduces the range of the explicit model reasonably well but is limited by the parameterisation of slope and aspect, underlining the importance of variation in topography in determining the microclimatic conditions of a site
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