The proportional scallop shell height frequency distribution from the AUV survey with a 90% confidence bound (312 data points), the annual dredge tow (106 data points) and the small-scale dredge tow (112 data points).

<p>The proportional scallop shell height frequency distribution from the AUV survey with a 90% confidence bound (312 data points), the annual dredge tow (106 data points) and the small-scale dredge tow (112 data points).</p

A undistorted reference grid (black) and prediction (red) from the distorted matrix extracted from the image of the checkered frame in <b>Figure 3</b>.

<p>A undistorted reference grid (black) and prediction (red) from the distorted matrix extracted from the image of the checkered frame in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0109369#pone-0109369-g003" target="_blank"><b>Figure 3</b></a>.</p

Iceland scallops photographed with a AUV camera at 1.94 m above the bottom, from the water surface.

<p>Approximate size scales, 6.0 and 6.5 cm, for known scallop sizes are also displayed.</p

The Gavia autonomous underwater vehicle used for this study.

<p>Modules include nosecone with camera, battery module, doppler velocity log, control unit with tower and side-scan sonar, and propulsion module. The strobe is located under the control module.</p

A checkered frame photographed underwater with the AUV camera for lens distortion correction where each square represents 15×15 cm.

<p>A checkered frame photographed underwater with the AUV camera for lens distortion correction where each square represents 15×15 cm.</p

Regions selected in first two experiments.

<p>The loci of the 20 regions selected in first and second experiments, according to hg18 and hg19 and the genes reported at these loci.</p

The proportion of regions that were selected in both Experiment 1 and Experiment 2.

<p>The underlying region was split up into equally sized regions and a fixed number of regions with the highest ratio of probes, within the region, expressed above the median, was selected. The proportion of regions that were selected in both Experiment 1 and Experiment 2 was calculated for varying length of each underlying region (y-axis) and the total number of regions to be selected (x-axis). The numbers within each cell show the exact proportions for the corresponding criteria.</p

The number of Monte Carlo simulations for which each region is chosen by the selection method using arrays with the same sample.

<p>The genomic location of the regions on 8q24 is on the x-axis. The proportion of Monte Carlo simulations for which the region was chosen is on the y-axis. The graph is shown with two different colourings, representing whether the region was among the previously experiment-wise selected regions (cyan) or not (pink). Those who were selected previously in Experiment 1 are shown at the top graph, Experiment 2 in the middle and Experiment 3 at the bottom. The simulations are done on the ten repeated spots for each probe for the three arrays in Experiment 3 that contained the same sample.</p

The number of Monte Carlo simulations for which each region is chosen by the selection method using arrays with different samples.

<p>The genomic location of the regions on 8q24 is on the x-axis. The proportion of Monte Carlo simulations for which the region was chosen is on the y-axis. The graph is shown with two different colourings, representing whether the region was among the previously experiment-wise selected regions (cyan) or not (pink). Those who were selected previously in Experiment 1 are shown at the top graph, Experiment 2 in the middle and Experiment 3 at the bottom. The simulations are done on the ten repeated spots for each probe for all nine arrays in Experiment 3.</p

Simulation of Lake Victoria Circulation Patterns Using the Regional Ocean Modeling System (ROMS)

<div><p>Lake Victoria provides important ecosystem services including transport, water for domestic and industrial uses and fisheries to about 33 million inhabitants in three East African countries. The lake plays an important role in modulating regional climate. Its thermodynamics and hydrodynamics are also influenced by prevailing climatic and weather conditions on diel, seasonal and annual scales. However, information on water temperature and circulation in the lake is limited in space and time. We use a Regional Oceanographic Model System (ROMS) to simulate these processes from 1^st January 2000 to 31^st December 2014. The model is based on real bathymetry, river runoff and atmospheric forcing data using the bulk flux algorithm. Simulations show that the water column exhibits annual cycles of thermo-stratification (September–May) and mixing (June–August). Surface water currents take different patterns ranging from a lake-wide northward flow to gyres that vary in size and number. An under flow exists that leads to the formation of upwelling and downwelling regions. Current velocities are highest at the center of the lake and on the western inshore waters indicating enhanced water circulation in those areas. However, there is little exchange of water between the major gulfs (especially Nyanza) and the open lake, a factor that could be responsible for the different water quality reported in those regions. Findings of the present study enhance understanding of the physical processes (temperature and currents) that have an effect on diel, seasonal, and annual variations in stratification, vertical mixing, inshore—offshore exchanges and fluxes of nutrients that ultimately influence the biotic distribution and trophic structure. For instance information on areas/timing of upwelling and vertical mixing obtained from this study will help predict locations/seasons of high primary production and ultimately fisheries productivity in Lake Victoria.</p></div