MODELING POPULATION VARIATION IN PEROMYSCUS-LEUCOPUS - AN EXPLORATORYANALYSIS

Time-series analysis was applied in an exploratory analysis of density estimates for Peromyscus leucopus obtained over 9 years by weekly nes t-box checks supplemented by live trapping. We developed a model that quantified the relationship between population density in a given mont h and density 1 month prior (1st-order autocorrelation), 12 months pri or (seasonal effects), and 36 months prior (multiannual effects). The remaining variation was examined to determine the influence of stochas tic variations in parameters of weather. In order of importance, predi ctors of density in a given month were density in the previous month ( 60.4% of variance explained), seasonality (6.1%), and multiannual effe cts (7.0%). Of the remaining 26.5% of variance, 3.4% was due to two we ather factors; deviation from mean precipitation with a 5-month lag an d high temperature with a 2-month lag. The population of P. leucopus w as relatively resilient to abiotic effects over the 9 years. Quantitat ive models of this type are rare in the literature because gathering a nd adequately analyzing long-term ecological data is a demanding task. However, quantitative descriptions of variations in population densit y are essential to assessment of the relative importance of various me chanisms contributing to population regulation.