The variance between temporal samples was slightly higher (0.13%, FSC = 0.0013).
Pairwise genetic differentiation between temporal samples was very low with Weir and Cockerham's θ ST ranging between 0.002 and 0.008, suggesting a high level of temporal stability among cohorts within the ten year sampling period (Additional file 5).
When significant differences between temporal samples were indicated, these were found between samples taken in subsequent years (2009 vs. 2010 in FIF, NET, DKR and DKV) as well as between samples from longer time periods (2008 vs. 2010 in FIA).
No pairwise FST or Dest comparisons between migrant Padre Island temporal samples were significant across sampling periods, indicating stable allele frequency distributions over a 22-year period.
We answer the following questions: (i) which indicator is most sensitive to the decline, (ii) how many temporal samples are needed, (iii) what temporal sampling pattern (interval between time points) is most appropriate, (iv) is power of an indicator dependent on the type of population decline, and (v) what is the effect of sample size and marker number on power?
Genetic differentiation among the spatial and temporal samples was investigated using analysis of molecular variance (AMOVA) [ 40, 41] and by estimating pairwise FST values between samples using Arlequin.
Furthermore, adaptive temporal sampling is applied, that is, frame skipping and up-sampling in terms of motion characteristics between the frames, which can achieve better rate distortion performance.
In these analyses, significant differences were found between temporal samples in some but not all populations, and the FST and Dest values were generally low.
Excluding Utsjoki(T) samples, the spatial component accounted for 9.2% of the total genetic variation among tributary samples and only 0.7% of the genetic variation was observed between temporal samples.
This method uses changes in allele frequencies between temporal samples to estimate N e, assuming that these are due to genetic drift.
