• Other Authors: The Pennsylvania State University CiteSeerX Archives
• Format: Text
• Language: English
• Subjects: Key words; Spatial autocorrelation; Measurement error; Voles; Norway; North Norway
• Online Access: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.472.129; http://www.bcn.cat/museuciencies_fitxers/imatges/FitxerContingut4249.pdf

Spatial population dynamics of small mammals: some methodological and practical issues. — Small mammals have been widely used to further our understanding of spatial and temporal population dynamical patterns, because their dynamics exhibit large variations, both in time (multi–annual cycles vs. seasonal variation only) and space (regional synchrony, travelling waves). Small mammals have therefore been the focus of a large number of empirical and statistical (analysis of time–series) studies, mostly based on trapping indices. These studies did not take into account sampling variability associated with the use of counts or estimates of population size. In this paper, we use our field study focusing on population dynamics and demography of small mammals in North Norway at three spatial scales (0.1, 10 and 100 km) to illustrate some methodological and practical issues. We first investigate the empirical patterns of spatial population dynamics, focusing on correlation among time–series of population abundance at increasing spatial scales. We then assess using simulated data the bias of estimates of spatial correlation induced by using either population indices such as the number of individuals captured (i.e., raw counts) or estimates of population size derived from statistical modeling of capture–recapture data. The problems encountered are similar to those described when assessing density–dependence in time-series —a special case of the consequence of measurement error for estimates of regression coefficients — but are to our knowledge ignored in the ecological literature. We suggest some empirical solutions as well as more rigorous approaches.