Scaling up: the statistical linkage between organismal abundance and geomorphology on rocky intertidal shorelines

Abstract Quantifying the distribution and abundance of intertidal organisms over large areas presents problems to scientists and resource managers limited by time, personnel, and funding. The objective of this study was to test for a statistical relationship between species abundance and a suite of physical factors so that inferences can be made about species distributions over large spatial scales if geomorphology is known. This has application to oil spill damage assessments, inventory and monitoring programs, global change and biodiversity studies where economical or logistical constraints dictate a reliance on data collected from relatively localized areas but there is a need to extrapolate to broad spatial scales. Complex shorelines can be partitioned into relatively distinct segments with generally homogenous abiotic characteristics. These segments can be characterized using common geomorphological parameters, thus differentiating horizontal (among-segment) and vertical (within-segment) characteristics. Shoreline segments with similar characteristics can then be statistically clustered into groups of like habitats. We applied this technique to 5 km of rocky shoreline on San Juan Island, Washington and then analyzed the relationship between 3 clusters of geomorphologically homogenous shoreline segments and local floral and faunal abundances. Using standard transect techniques at 3 elevations, we compared the variance in abundance of organisms (i) among 3 transects within one homogenous shoreline segment selected from a moderate-angle bedrock segment cluster; (ii) among 3 shoreline segments from the same moderate-angle bedrock cluster; and (iii) among 3 separate clusters representing low-angle, moderate-angle and high-angle bedrock segments. We hypothesized that variance in organismal abundance would be low among transects and among similar segments but high among segments from different clusters. Data were analyzed using parametric and non-parametric one-way ANOVAs for population level comparisons at each elevation. Community level comparisons were made using a quantitative similarity index (NESS) and a multivariate analysis of variance (MANOVA). From the within-segment ANOVAs, we found the population-level abundance was not significantly different among transects for 35 out of 42 comparisons. The among-segment (within cluster) ANOVAs also showed no significant differences in abundance for 43 out of 57 comparisons. However, abundances varied significantly among dissimilar clusters. Significant differences were found in 45 out of 58 comparisons. The NESS index indicated a higher similarity for communities within a segment, and within a cluster, than among samples from different clusters. The multivariate test also showed no significant difference among transects and among segments (except for a significant difference at the 1 meter sampling station), but a very significant difference was computed at all three stations for the among clusters analysis. These results suggest that by using a systematic approach based on a geomorphological classification of the intertidal zone and a limited series of transects, intertidal community composition for a complex rocky shoreline over a broad spatial scale can be statistically inferred.