In most cases, successive durations with the standard walker appear not to be related, having a random distribution similar to the data given by other forms of bistable display (see [6] for a sample lag plot analysis with slant rivalry).
In our sample, LAG spacing is variable between different elements within a single individual.
To assess the degree of spatial autocorrelation, the (semi -variogram isemi -variogramat descrises the spatial pattern ofunctionriable withatncreasing inter-sample (lag) describes
Most of the Spearman's correlation coefficients of mosquito captures between consecutive samples (lag = 1) in VC were highly significant (P < 0.01).
Nugget values greater than zero represent a combination of experimental error and of unresolved spatial variability occurring at scales smaller than inter-sampling lag distance.
Fluorescence intensities detected in the samples during lag were compared with the intensities of the sample obtained in stationary phase used as the inoculum (time 0).
Since stump extraction in the study area started just six years prior to sampling, time-lags in population-level responses could be expected.
Due to lack of statistical power in a small sample, distributed lag models were not considered.
To test for spatial stability, a Spearman rank correlation coefficient of trap captures between consecutive samples (forward lag = 1) was calculated.
The medians of the within-individual interquartile ranges (IQR) for the entire study sample on lag 0, lag 0 1, lag 0 2, lag 0 3, and lag 0 4 PM2.5 concentration were 6.38 μg/m, 6.57 μg/m, 5.97 μg/m, 5.83 μg/m, and 6.06 μg/m, respectively, which indicates no substantial variation in the IQRs across the window of exposure.
