Tatiana A. Rynearson

Background: Marine phytoplankton drift passively with currents, have high dispersal potentials and can be comprised of morphologically cryptic species. To examine molecular subdivision in the marine diatom Thalassiosira rotula, variations in rDNA sequence, genome size, and growth rate were examined among isolates collected from the Atlantic and Pacific Ocean basins. Analyses of rDNA included T. gravida because morphological studies have argued that T. rotula and T. gravida are conspecific. Results: Culture collection isolates of T. gravida and T. rotula diverged by 7.0 ± 0.3% at the ITS1 and by 0.8 ± 0.03% at the 28S. Within T. rotula, field and culture collection isolates were subdivided into three lineages that diverged by 0.6 ± 0.3% at the ITS1 and 0% at the 28S. The predicted ITS1 secondary structure revealed no compensatory base pair changes among lineages. Differences in genome size were observed among isolates, but were not correlated with ITS1 lineages. Maximum acclimated growth rates of isolates revealed genotype by environment effects, but these were also not correlated with ITS1 lineages. In contrast, intra-individual variation in the multi-copy ITS1 revealed no evidence of recombination amongst lineages, and molecular clock estimates indicated that lineages diverged 0.68 Mya. The three lineages exhibited different geographic distributions and, with one exception, each field sample was dominated by a single lineage. Conclusions: The degree of inter- and intra-specific divergence between T. gravida and T. rotula suggests they should continue to be treated as separate species. The phylogenetic distinction of the three closely-related T. rotula lineages was unclear. On the one hand, the lineages showed no physiological differences, no consistent genome size differences and no significant changes in the ITS1 secondary structure, suggesting there are no barriers to interbreeding among lineages. In contrast, analysis of intra-individual variation in the multicopy ITS1 as well as molecular clock estimates of divergence suggest these lineages have not interbred for significant periods of time. Given the current data, these lineages should be considered a single species. Furthermore, these T. rotula lineages may be ecologically relevant, given their differential abundance over large spatial scales.

Probability distribution functions of displacement are central to Lagrangian statistics and the study of fluid dispersal. A method for computing marginal probability distributions of passive tracer dispersal from Lagrangian observations is developed. Using a pseudotrack approach, probability distributions for the domain of occupation and transit time are developed, complimenting more frequently used bulk statistics for average transit time and overall crossing probability. To demonstrate application of this technique to observations, likelihoods and time scales of dispersal from the Gulf Stream to the Azores are quantified using World Ocean Circulation Experiment (WOCE) Surface Velocity Program (SVP) near-surface drifter data for the years 1992–2008. Over observable time scales, the transit of a particle in the near-surface ocean from the Gulf Stream to the Azores occurs across a spectrum of time scales, from tens to hundreds of days, with an overall likelihood of 42% ± 4% and a mean time scale of 321 ± 41 days. The exclusion of measurements from drifters released after 1 January 2004 (which have been shown to potentially exhibit bias) slightly increases the overall likelihood of connection (49% ± 6%), consistent with recent surface current shifts in the northern North Atlantic, and increases the mean connection time scale (371 ± 52 days), potentially reflecting spurious acceleration of drifters in recent years. The method presented is general and applicable to a wide range of applications in physical and ecological oceanography.

Recent technological advancements have made high throughput sequencing an increasingly popular approach for transcriptome analysis. Advantages of sequencing-based transcriptional profiling over microarrays have been reported, including lower technical variability. However, advances in technology do not remove biological variation between replicates and this variation is often neglected in many analyses.