Scaling pairwise β‐diversity and α‐diversity with area

Abstract

Aim The relationship between species richness (α‐diversity) and area is well studied; however, the way in which compositional dissimilarity between pairs of sites (β‐diversity) scales with area has only recently attracted research attention. The aim of this study was to improve the understanding of how both α‐ and β‐diversity scale with area, to illuminate ecological processes structuring the distribution of biodiversity and enable prediction of α‐ and β‐diversity for large regions from much smaller samples. Location We examined both simulated spatial community data and measurements from tropical forest tree plots in Panama. Methods We applied the simulated and measured community data to assess how both α‐ and β‐diversity scale with area. Then we examined how accurately community α‐diversity and pairwise β‐diversity can be extrapolated from small sample areas of different size within each community, using the species–area power relationship. Results For both the simulated and tree plot data, pairwise β‐diversity scaled with area in a corresponding manner to the much more familiar species–area relationship. By altering the attributes of the simulated communities, we found that α‐ and β‐diversity saturated at smaller areas where abundances were more even, species distributions were less aggregated and regional richness was lower. Estimates of α‐ and β‐diversity for a pair of communities generally increased in accuracy with the size of the local sample areas from which extrapolations were made. Main conclusions These analyses suggest that the most robust estimates of α‐ and β‐diversity for a larger area will be obtained by local samples that are greater than 10% the size of that larger area. Our results emphasize the fundamental link in how both α‐ and β‐diversity scale with area, and demonstrate how simple knowledge of these scaling relationships can be used to predict the diversity of larger areas from smaller samples.

The compositional similarity of urban forests among the world's cities is scale dependent

“…This finding supports Olden & Poff's (2003) conclusion that biotic homogenization is a scale-dependent phenomenon. However, contrary to other studies that have examined compositional similarity among plant assemblages (Mokany et al, 2013), our results indicate that similarity among urban forests is greater at smaller spatial scales, suggesting a unique scale dependence for these particular urban systems. We also found evidence that these scaledependent patterns did not differ between native and nonnative species.…”

Potential Global-Local Inconsistency in Species-Area Relationships Fitting

“…As showed in a generalized schematic diagram of the SARs (Figures 5A,B ), species abundance distributions largely affect the shape of SAR curves, which is in accordance with the findings in previous studies (Allen and White, 2003 ; Green and Ostling, 2003 ; Šizling and Storch, 2004 ; Dengler, 2008 ; Tjørve and Tjørve, 2008 ; Tjørve et al, 2008 ; Mokany et al, 2013 ; Rybicki and Hanski, 2013 ; Guo, 2015 ; Harte and Kitzes, 2015 ). The curve of the logarithm SAR sampling [i.e., log 10 (Area)–Number of Species] showed a sigmoid shape that can be divided into two sections, concave section when the sampling area is small until the inflection point, and convex section.…”

Identifying Priority Areas for Conservation and Management in Diverse Tropical Forests

“…However, for the purposes of the present study, our objective was to generate predictions of species richness and compositional dissimilarity that are relevant to the spatial grain of the 250 m grid cells (62,500 m 2 ) rather than the much smaller area that the survey plots occupy (500–1,000 m 2 ). To transform our community diversity data so that they were relevant to the spatial grid cell resolution, we applied a recently developed biodiversity scaling method [35].…”

“…We then calculate the predicted Sorensen’s compositional dissimilarity between the two grid cells ( β ij  = 1– [2 S com,ij /( S i + S j )]) using the predicted species richness of each grid cell ( S i , S j ) and the predicted number of species in common between the two grid cells ( S com,ij ). We applied a single scaling factor for species richness ( z  = 0.25) and for the number of species shared between a pair of communities ( z com  = 0.42), as derived previously [35]. This scaling approach retains the underlying gradients in species richness and compositional dissimilarity that are observed across the community survey plots, but scales the absolute values so that they better represent those of the grid cells being modelled.…”