Effects of regime shifts on the population dynamics of the grey-sided vole in Hokkaido, Japan

Abstract

We explored the effects of regime shifts (drastic changes usually observed in marine ecosystems, corresponding to climatic variability) in a terrestrial system focusing on a key event that occurred in 1976-77. We used data on the gray-sided vole Clethrionomys rufocanus (Sundevall, 1846) from 89 time series covering 31 yr , recorded in Asahikawa, Hokkaido, Japan, where both cyclic and non-cyclic populations occur. Wavelet analyses demonstrated a clear shift of dynamic patterns in the mid-1970s, presumably resulting from the Aleutian Low Pressure (as measured by the Aleutian Low Pressure Index). The vole populations exhibited erratic fluctuations until the mid1970s, and then changed their pattern to cyclic fluctuations at a 4 yr interval. The structure of density dependence changed during the regime shift. Although the strength of direct density dependence was similar, delayed density dependence became stronger after the shift. Altogether these findings suggest that changing climate may affect the ecological interactions among voles, predators and resources.

Density dependence: an ecological Tower of Babel

“…In contrast, others differentiate direct and delayed DD in terms of whether the density feedback is immediate or retarded (e.g. Bjørnstad et al 1995;Brook and Bradshaw 2006;Holyoak and Lawton 1992;Saitoh et al 2006;Williams et al 2004;Yoccoz et al 2001). As a result, the term direct DD has become pervasively polysemous.…”

Analysing multiple time series and extending significance testing in wavelet analysis

“…nonlinearity in time series, recurrence patterns, similarity of rhythms between time series, phase analysis), as several null models can be chosen according to the different algorithms employed to create the surrogates (Schreiber & Schmitz 2000, Cazelles & Stone 2003, Cazelles 2004, Royer & Fromentin 2006. The surrogate approach has also been used to test the wavelet spectrum using a hidden Markov process as a null model (Klvana et al 2004, Saitoh et al 2006. Other null models are the 'Type 0' surrogates, equivalent to a white noise assumption, whereas the null model referred to as 'Type 1' surrogates (or Fourier surrogates), preserves the autocorrelation structure of the time series (or equivalently its power-spectrum).…”

Constraints to projecting the effects of climate change on mammals

“…First, observed patterns generate testable hypotheses and thus seed predictive models (see this issue, Saitoh et al 2006, Tkadlec et al 2006. Second, observed patterns can be used to test ecological hypotheses through natural experiments.…”