Geostatistical Tools for Modeling and Interpreting Ecological Spatial Dependence

Abstract

Abstract. Geostatistics brings to ecology novel tools for the interpretation of spatial patterns of organisms, of the numerous environmental components with which they interact, and of the joint spatial dependence between organisms and their environment. The purpose of this paper is to use data from the ecological literature as well as from original research to provide a comprehensive and easily understood analysis ofgeostatistics' manner of modeling and methods. The traditional geostatistical tool, the variogram, a tool that is beginning to be used in ecology, is shown to provide an incomplete and misleading summary of spatial pattern when local means and variances change. Use of the non-ergodic covariance and correlogram provides a more effective description of lag-to-lag spatial dependence because the changing local means and variances are accounted for. Indicator transformations capture the spatial patterns of nominal ecological variables like gene frequencies and the presence/absence of an organism and of subgroups of a population like large or small individuals. Robust variogram measures are shown to be useful in data sets that contain many data outliers. Appropriate removal of outliers reveals latent spatial dependence and patterns. Cross-variograms, cross-covariances, and cross-correlograms define the joint spatial dependence between co-occurring organisms. The results of all of these analyses bring new insights into the spatial relations of organisms in their environment.

Spatial patterns of seed dispersal, their determinants and consequences for recruitment

“…partial Mantel tests 41 , geostatistics 42 and other spatial statistics to evaluate the concordance between spatial patterns among arriving seeds and among established seedlings 9 . Genetic demography studies of changes in the spatial patterns of genotypes through the life cycle can also reveal genotype-or phenotype-specific effects, which might cause the sources and dispersal distances of seeds recruited into the adult population to vary considerably from those at earlier life stages 43 .…”

On the Nature of Environmental Gradients: Temporal and Spatial Variability of Soils and Vegetation in the New Jersey Pinelands

“…Because the samples were not collected on a regular two-dimensional array of points, but were grouped according to the location of the blocks, conventional methods of spatial analysis (Rossi et al 1992) could not be used. Rather, analyses of variance (both parametric and non-parametric) comparing the sample blocks ( Fig.…”

Geostatistical tools for the study of insect spatial distribution: practical implications in the integrated management of orchard and vineyard pests

“…To evaluate the spatial variation, different tools can be used, analyzing correlation coefficient (in correlograms), covariance (in covariance functions) or variance (in semivariograms). On choosing between these methods in ecological applications, see Rossi et al (1992). Next, we will refer mainly to semivariograms, the most commonly used method in geostatistics.…”