TESTING FOR SPATIAL AUTOCORRELATION IN ECOLOGICAL-STUDIES

We describe a statistical method appropriate for the analysis of spati al autocorrelation in data varying in time as well as space. In partic ular, the technique was developed to address the issue of geographic s ynchrony in ecological variables that may change markedly from year to year such as population density of animals or seed production of tree s. The method yields ''modified correlograms'' that test for significa nt autocorrelation between sites located within any given range of dis tances apart. This technique facilitates detecting and understanding s patial processes in a variety of ecological phenomena, including testi ng the plausibility of causational hypotheses using cross-correlationa l analyses. Several examples are discussed, including population densi ties of squirrels in Finland, winter densities of two hawk species in California, and acorn production and radial growth by individual blue oak Quercus douglasii trees in central coastal California.