Topographical wave exposure indices allow objective assessment of the degree of wave action at coastal sites. We present a grid-based method for rapidly calculating indices at fine spatial resolutions along whole coastlines, and evaluate the power of candidate indices in predicting composition of rocky shore communities. The method has 3 stages: (1) a grid is created from a vector-based digital coastline using geographical information systems (GIS) software; (2) for every coastal cell, wave fetch is determined as the distance to the nearest land cell in 16 angular sectors, using coarse-, medium- and fine-resolution searches of the surrounding cells up to a distance of 200 km; (3) wind energy (average wind speed and proportional occurrence) in each sector is calculated for nearby coastal sites. We calculated the average fetch in each sector (F) and the sum of products of fetch and wind energy (W). A total of 57 species were surveyed at 185 sites in west Scotland for determination of trends with wave indices. Average wave fetch with a 200 m scale grid explained >50% of the variation in the first principal component of the species-sites abundance matrix, with shore extent explaining another 10%. Incorporating wind data in the indices had a negligible effect on predictive power. Species diversity explained 61% of the variance in the second principal component and declined from low to high pelagic primary productivity. Separating direct physical effects from biological effects, such as food supply or grazing could potentially help us better understand the processes structuring biological communities on rocky shores.
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