The genetic structure of Avena barbata, the slender wild oat, has been reported to be correlated with geographic variations in temperature and degree of moisture in both California and Israeli populations. This study observes the effect of temporal changes in moisture and temperature on the genetic structure of populations of A. barbata in California. Two natural populations, CSA and Jasper Ridge, both located in the polymorphic region of A. barbata, were studied. They were sampled at the end of a dry growing season (1976-77), a very wet season (1977-78), and a season with a moderate amount of rainfall (1978-79). Five enzymes (ACPH, EST, LAP, PRX, and 6PGD) as well as two morphological markers were studied on 20 to 40 families (8 to 10 individuals per family) per site each year (total of 31 samples studied). Formal genetics studies have not been completed for all of the enzyme systems used as markers in this study, consequently population analyses in the present study are based mainly on electrophoretic phenotypic band frequencies rather than on genotypic frequencies. Nei's measure of genetic identity for each sample and a hypothetical monomorphic mesic" population was calculated. In wet years higher genetic identity values were observed. Also, a measure of the extent of polymorphism was calculated by the method of Kahler et al. (1980). Samples studied showed different degrees of polymorphism for different marker loci. A measure of non-random association, D', between pairs of loci was also calculated. Averaged over all sites, D' value was greater for the CSA population than for Jasper Ridge in each year. In both populations non-random association between pairs of loci fluctuated over years as a function of environmental variability, in particular the amount of rainfall in the growing season. The rates of change in allelic frequencies, polymorphic index, and gametic disequilibrium are far too rapid to be explained by any force except selection. Outcrossing rates were estimated for each marker in each sample. More than 90% of the estimated values of outcrossing were less than eight percent. There were no noticeable differences between the estimates from the "mesic" and the "xeric" locations. In order to study the relationship between phenotypic frequencies and environmental variables,principal component analysis was performed on the arcsin square root transformed phenotypic frequencies of each locus, as well as on the arcsin square root transformed of the "mesic" and the "xeric" phenotypes over the entire collection for all years. The first principal component in each case was then predicted from eight rainfall and temperature variables using step-wise regression analysis. Among the nine "Best Regression Equations" (BRE) six had the amount of rainfall in the growing season as well as in the flowering season as important factors. In five BRE (equations for "mesic" phenotype, lemma color, PRX, LAP, and 6PGD), rainfall was the only factor. In seven ..."