The same data was used for Hodin (2015) Royal Society Open Science, Figs 4, 5, 6.

Figure 4. Sand dollar larvae show substantial batch-to-batch variation in the turbulence response across ontogeny. (a) Larval batch A, fertilized 27 May 2014. (b) Larval batch B, fertilized 28 May 2014. Each of the data points in (a) and (b) are results from single runs of 25 larvae, with the exception of the day 9 batch A data, which we replicated once (data points on day 9 in (a) show the mean of the two runs; error bars are s.e.m). (c) Larval batch C, fertilized 22 August 2014. Each of these data points aremeans of four runs at each speed with 20–25 larvae each; error bars are s.e.m. Note that in (a–c), we do not indicate the error along the x-axis in each of the Taylor–Couette cell rotation rates that we employed, which we estimate to be approximately±25 r.p.m. Each graph shows the energy dissipation rates (in W kg−1) on the lower x-axis, and the corresponding rotation rates (spin speeds in r.p.m.) along the upper x-axis. We only tested day 7 larvae from batch A and day 10 larvae from batches A and B.

Figure 5. Precompetent sand dollar larvae showincreasing responsiveness to turbulence as ontogeny proceeds. Shown are themaximal proportion of larvae in each of our three batches (A, B and C; figure 4) that settled on a given daywith the background level of settlement in that batch subtracted out (thus excluding larvae that were nominally competent); error bars are s.e.m. (note that the data from batch A days 10 and 11 and batch B days 9, 10 and 11 were unreplicated, thus show no error bars). This analysis reveals a marked and steady increase in the proportion of nominally precompetent larvae that responded to turbulence as ontogeny proceeds. The estimated slope (±s.e.m.) for the regression is 0.24 (±0.07) maximum proportion settled per age (unpaired t-test: t7.9 =3.25, p<0.02), and the estimated intercept (±s.e.m.) is−1.90 (±0.74; t7.9=−2.56, p<0.04).

Figure 6. Precompetent sand dollar larvae show evidence of increasing sensitivity to turbulence as ontogeny proceeds. (a) Shown are the best-fit curves (solid curves)±95% CIs (dashed curves) generated by our best-supported general mixed linear model (see Material and methods for details and comparisons with other models). The lines and symbols (batch A, squares; batch B, circles; batch C, crosses) show the data from day 9 (black) and day 11 (grey). Error bars are s.e.m (note that the data from batch A day 11 and batch B days 9 and 11 were unreplicated, thus show no error bars). The inflection points of the best-fit curves for day 9 (black arrow) and day 11 (grey arrow) are shown along the x-axis and indicated by the black and grey vertical dotted lines, respectively. The shaded areas within the day 9 and day 11 CI curves indicate the range of 95% CIs in our respective inflection point estimates based upon 10 000 non-parametric bootstrap samples. (b) The range of inflection point estimates (and 8.5% overlap) from these bootstrap samples on days 9 and 11. Arrows as in (a).

Note that the y-axis units of density are linearly related to the proportion of bootstrap samples showing a given range of inflection point estimates.

Related Reference:
Hodin J, Ferner MC, Ng G, Lowe CJ, Gaylord B. 2015. Rethinking competence in marine life cycles: ontogenetic changes in the settlement response of sand dollar larvae exposed to turbulence. Royal Society Open Science. 2: 150114. doi: 10.1098/rsos.150114.

Related Datasets:
Turbulence settlement: fig.3
Turbulence settlement: fig.4-6_Batch C
Turbulence settlement: fig.6b
Turbulence settlement: fig.7
Turbulence settlement: fig.8
Turbulence settlement: fig.8 bootstrap

fig4-6_batch-ab.csv