Document: HEL-3-40-13

Modeling spatial autocorrelation in plant species composition with the community variogram.

WAGNER, H.H.*, J.M.BOSSENBROEK, M.M.HAWKS, B.VAN HORNE and J.A.WIENS

Colorado State University, Fort Collins, CO 80521 USA ¹

Abstract:
Species composition is influenced by a number of biotic and abiotic processes. Their spatial structure and interaction creates what we observe as spatial autocorrelation in species composition. Spatial autocorrelation can pose severe problems to the estimation of community - environment relationships and of interspecific associations. We show how variogram modeling can be used to separate the effects of environmental heterogeneity, species-specific characteristics and interspecific interactions on plant species composition. We define the Community Variogram as an extension of the ordinary semi-variogram to multivariate binary data such as a vector of presence-absence data of species in a sampling unit. Point-wise division by the expected value leads to the definition of a Standard Community Variogram, which can be used to account for environmental heterogeneity. By fitting an appropriate variogram model, the distance-dependent coefficients of autocorrelation and of interspecific association can be estimated and graphically interpreted. Partial variograms can be fitted for individual species or for functional groups to derive group-specific parameters. We outline how the method can be applied in community and landscape ecology to address questions about the independence of sampling units, estimation in the presence of spatial dependence, the effect of landscape structure on species distribution, differences in spatial autocorrelation between functional groups of species, and the existence of assembly rules.

Keywords: geostatistics, environmental heterogeneity, functional types, interspecific association

This abstract is being presented at: 8:45 AM in session:
Oral Session #59: Plant Communities: Vegetative Analysis.