Synchrony In Dynamics Research Articles

SYNCHRONY AND SCALING IN DYNAMICS OF VOLES AND MICE IN NORTHERN JAPAN

One hundred and seventy-six time series of the Japanese wood mouse (Apodemus speciosus) and 185 time series of the grey-sided vole (Clethrionomys rufocanus) spanning 31 years (1962–1992) were studied with respect to synchrony and spatial correlation in population dynamics. The time series were collected at fixed sites as part of the rodent census program of the Japanese Forestry Agency. The survey locations cover a region of 115 by 270 km in northern Hokkaido, Japan. The average correlation between the time series was 0.34 (ci95% = [0.31, 0.36]) for the grey-sided vole and 0.16 (ci95% = [0.13, 0.18]) for the Japanese wood mouse. This average correlation was decomposed spatially using spatial autocorrelation techniques and the nonparametric covariance function. The lower region-wide correlation in the latter species was found to be due to the spatial covariance dropping more rapidly with distance. The spatial scale of the dynamics was measured by the L0 correlation length (the distance at which the covariance is equal to that between two randomly chosen sites within the region). This distance was estimated to be ∼50 km for the grey-sided vole and 20–30 km for the Japanese wood mouse. The L0 correlation length was linked to the scaling of the underlying ecological processes through a simple epiphenomenological model motivated by diffusion theory (the exponential covariance model). A review of the ecology of the rodent species indicates that the spatial scale of the pattern of fluctuation of the grey-sided vole is more extensive than can be accounted for by a process of dispersal of voles. Predator movement and regulation of the vole by predators are possible causes of the pattern of spatial covariance. The Japanese wood mouse has a scale of dynamics slightly larger than what may be accounted for by the movement of individuals. This species constitutes a negligible part of predators’ diet. Food resource dynamics may be an important regulatory factor and a source of spatial covariance. We interpret the results as indicating that the natural scales of regulation are species specific and can be large relative to the scale of local populations.

Noise Colour, Synchrony and Extinctions in Spatially Structured Populations

I analyse the importance and influence of noise with positive autocorrelation ('red noise') to extinction risk in spatially structured populations using a set of simple population dynamical simulation models. Noise colour has a major influence on both local and global extinction risk, level of synchrony in population dynamics, and spatial patterns of the synchrony. Generally, the stronger the autocorrelation in the noise is, the higher is the global extinction risk even though local extinction risk may decrease. Populations with high intrinsic growth rate are more prone to global extinction than populations with low growth rate. The influence of autocorrelated noise on population synchrony depends strongly on the way in which environmental noise is introduced into the model.

The effects of large– and small–scale random events on the synchrony of metapopulation dynamics: a theoretical analysis

We present an analysis of the conditions under which migration and global random factors may determine large scale synchrony in the dynamics of spatially structured populations. We derive an analytic approximation which describes how the desynchronizing influence of local environmental stochasticity combines with the synchronizing influences of larger scale environmental stochastic variation and migration to determine population cross correlation coefficients. Despite the simplifications made by this analysis, computer simulations show that the behaviour of more complicated models is well described by our approximation over considerable regions of parameter space. We conclude that population synchrony is largely determined by the coefficients of variation ( CV s) of the local and larger scale stochastic processes, and that migration alone is only likely to maintain population synchrony when the CV of the local stochastic process is very small.

Synchrony and Clustering in Two and Three Synaptically Coupled Hodgkin–Huxley Neurons with a Time Delay

Synchrony and clustering in phase dynamics of two and three Hodgkin–Huxley neurons coupled globally by excitatory synapses with a time delay have been studied by numerical simulations and bifurcation analysis. In particular, we have obtained phase diagrams for the synchronous state and various cluster states in the parameter space of the synaptic coupling strength, G syn , and the synaptic time delay, τd, by computing the phase shifts of action potential spikes. In the weak coupling limit the computed phase diagrams are found to be consistent with the results of phase model analysis. The bifurcation analysis shows the phase model predictions break down at G syn ~ 0.3 and new complex phase dynamics appear. For all numbers of neurons explored, the critical time delay at which the nature of synaptic coupling changes completely is found to be typically about 2–4 msec, which may have some implications in modeling cortical dynamics.

The Moran Effect and Synchrony in Population Dynamics

Our approach is twofold. First, with 1964-1983 data on red squirrel (Sciurus vulgaris) in 11 provinces in Finland we show that population fluctuations in different parts of the country are largely synchronous. Second, using two differing model types for producing the dynamics of populations we set up to examine the synchronizing effect of an extrinsic disturbing factor, the Moran effect. We show that in a spatially structured population system a randomly occurring stochastic perturbation reducing reproduction success is indeed capable of synchronizing subpopulations. The synchronizing effect is achievable with a wide range of probabilities of occurrence and strengths. However, when the Moran effect occurs in most years its synchronizing power wanes, despite the strength of the effect. Allowing regionality in the variance of the strength of the Moran effect reduces the synchronizing capacity of the perturbation. The Moran effect is also capable of producing a wide range of population dynamics from very simple premises.

Spatial and Temporal Patterns of Small‐Rodent Population Dynamics at a Regional Scale

Many species exhibit regional synchrony in population dynamics, and different influential biotic and abiotic factors can be indicated by the observed scale of spatial synchrony. Here, we present analyses of spatial patterns of bank vole Clethrionomys glareolus population fluctuations, based on a 5—yr (1990—1994) trapping series obtained from 31 trap stations regularly spaced along a 256—km transect in the boreal forest in southeastern Norway. The bank vole was known to exhibit typically cyclic population dynamics in this region prior to this study. Bank vole fall densities exhibited fluctuations with little year—to—year variation; all $s$—indices (a measure of temporal variability) were below 0.5. There was a large scale trend in the temporal variability of the populations, with highest variability at the south end and lowest in the middle of the transect. Analysis (Mantel correlogram) of the year—to—year rate of change of local populations showed that the opposite ends of the transect appeared to be most out of phase. At a smaller spatial scale (up to 30—40 km), local populations exhibited statistically significant synchrony in growth patterns. Spatiotemporal patterns in the dynamics of local populations were not related to habitat quality. We suggest that the scale domain of population synchrony is related to intrinsic population scaling properties such as dispersal capacity.

Synchrony in Tetraonid Population Dynamics

We studied temporal and spatial synchrony of population fluctuations in the capercaillie (Tetrao urogallus), the black grouse (Tetrao tetrix) and the hazel grouse (Bonasa bonasia) in Finland. The data consist of route censuses (20 000-30 000 km annually) performed in 11 provinces during 1964-83. The population data for the three species in each province were standardized to zero mean and unit variance. Cross-correlation analysis indicates that population dynamics of the three species in every area are in rather good temporal synchrony. Moreover, with the aid of k-means clustering, the 11 provinces could be merged into four regions, indicating large-scale synchrony in dynamics of the three tetraonid species. Because it is obvious that this synchrony cannot be due only to the similar life histories of these species, we explored whether it could be influenced by a common synchronizing factor affecting all the species simultaneously. In order to do this we used a Leslie matrix-based simulation approach. In this model there is a stochastic hit of breeding failure at a given average interval. This failure was shown to synchronize the population dynamics of the species with primarily different life tables.