Mortality was highest during the first week (3.6%, range 0-7%, Table 1), but decreased throughout the experiment. Mortality was less than 2.5% in all sieves on 28 August, and less than 0.5% on 2 and 7 September (Appendix 6). When sorting the unattached spat, in average 80% were alive.

One of the sieves in the LL group had significantly higher mortality than the other LL replicates, both the first week, for the rest of the experiment and in total mortality (chi-square test, p=0.0003, p<10-6 and p<10-6, respectively, Appendix 6). Mortality in this sieve was as high as 18.4% the first week (Table 1), hence this replicate was excluded from further analysis of mortality and growth. However, mortality in this sieve observed in the last registration on 7 September was reduced to 1.7%, which is comparable to the other sieves.

For the first week (20 Aug), both the chi-square goodness of fit test and a one-way ANOVA on arcsine transformed proportions showed significant differences in mortality between the groups (chi-square, p=0.03; ANOVA, p<0.01), which was due to a significant higher mortality in the SL group compared to the DD group (multiple chi-square analysis with Bonferroni correction, p=0.003; Tukey HSD, p<0.01). Pooling the mortality from the rest of the experiment (28 August, 2 September and 7 September, Table 1) gave no significant differences between the groups with neither chi-square analysis (p=0.31) nor one-way ANOVA on arcsine transformed proportions (p=0.99), though large variation among the experimental units lead to significant differences between the replicates in the SL and NL groups. There was no significant correlation between mortality the first week and mortality in the rest of the experiment for each experimental unit (p=0.68, r2=0.02) when excluding the LL sieve with significant higher mortality.
Table 1. Mortality (%) during the experiment and number of live spat at the end of the experiment.
% mort. first week*
% mort. rest of exp.
Live spat, end of exp.
% total mortality
*The numbers are estimated for the whole sieves from mortality observed in samples from the populations (see Appendix 6)

Mortality pooled from all groups was size-dependent for all dates of mortality registrations. Significantly different sizes were found both between the dead spat and the live spat on the date of mortality registration (t-tests, p<0.001 for all comparisons) and also compared to the live spat from the preceding date of size measurement (t-tests, p<0.0001 for all comparisons), except for dead 20 Aug compared to live 13 Aug (p=0.06). Mean sizes of dead spat were between 73 and 77% of mean sizes of live spat throughout the experiment (Appendix 6, Table 22, see also Appendix 2). The size of dead spat increased significantly between the three first registrations on 20 August, 28 August and 2 September (Unequal N HSD, p 0.001), but not from 2 to 7 September (p=0.75). There was no significant difference in size of dead spat between the groups at any of the dates (one-way ANOVAs, 0.08<p=<0.53, 1-<0.25). Since there was higher mortality among the smaller spat and mortality varied between the groups, it was necessary to test for the impact of this on the shell height ANOVAs. Hence, the measurements of the dead spat from 20 August were added to the shell height data (raw data, before adjusting the numbers) from the same date, where mortality was highest and significant differences in mortality were found between the groups. A new ANOVA was then performed. The result was a decreased difference between the groups which increased the p-value for the group effect from 0.25 with the data for the live spat to 0.49 with the combined data.

At the end of the experiment, the LL sieve with highest mortality had 73% of the average number of spat for the other sieves, and the DD group had just below 10% more spat than the other groups (Table 1). There was a highly significant inverse correlation (p<0.0001, R2=0.86) between number of spat in the sieves at the end of the experiment and total mortality for the whole experiment. Adding the estimated total number of dead spat to the number of spat in each experimental unit counted at the end of the experiment, gave an estimated average density of 421 ± 14 (SD) spat per sieve at the beginning of the experiment (13 August).


No significant differences in shell height were found between the four groups at any of the dates of sampling (one-way ANOVA, 0.12<p<0.78, 1-=0.80 with =5% of the at each date, Figure 6 and Appendix 7).

Figure 6. Mean shell heights of spat of Pecten maximus reared under different photoperiods. DD = continuous darkness, SL = 7 ½ h light and 16 ½ h darkness, NL = simulated natural photoperiod changing from 18h light and 6h darkness to 16h light and 8h darkness, and LL = continuous light. Vertical bars indicate 95% confidence intervals, n=180-225 (120-150 in LL).

Growth was stable throughout the experiment, but growth was lower during the acclimation period than for the rest of the experiment. There was a twofold increase in shell height during the experiment (Figure 6). Regressions on untransformed (R2=0.67) and ln transformed (R2=0.69) data showed that exponential growth was slightly better fit to the data than linear growth (Appendix 7, Table 27 and Table 28). Regression on ln transformed data gave an instantaneous growth rate of 0.028, which gave an average SGR of 2.8% during the experiment. For comparison with literature, average linear growth rate throughout the experiment was 0.14 mmday­1. Coefficient of variation (CV) showed no significant regression with time (R2=0.02, p=0.22) and was in average 0.15 ± 0.015 (SD) (Figure 7). There was no significant correlation between density and growth (p=0.34, r2=0.09).

Figure 7. Coefficient of variation for all replicate units throughout the experiment.


The spat was observed to detach themselves from the mesh or other substrate and crawl around by extending the foot and pulling the shell along the mesh. They were also able to climb the sieve walls and attach themselves with byssus threads. 50-100 spat were removed from the walls the day before each recording, but on average 90% were returned on the days of recording. There was no difference in number of spat on the walls between the groups on most of the dates (one-way ANOVA, 0.09<p<0.32, 1-<0.5). The only differences were found at the last date of recording (p<0.001) with significant differences between several of the groups, but with no obvious pattern according to the length of the day.

Feeding rate

The data from the first time of sampling (4 a.m.) were not used, as the flow from the feeding tank was disturbed prior to sampling. Hence, the sampling represented the period from 10 a.m. to 10 p.m., which included the shifts from light to darkness in the SL and NL groups. There was a significant increase in feeding rate from 10 a.m. to 4.30 p.m. (3-way nested ANOVA, p<0.0001) but no significant changes from 4.30 p.m. to 10 p.m. (3-way nested ANOVA, p=0.68). However, the pattern was the same for all the groups (Figure 8), and there were no differences in feeding rate between the groups (three-way nested ANOVA, p=0.24, 1-­<0.3).

Figure 8. Feeding rate as number of algae cellsindividual-1minute-1, of four groups of spat of Pecten maximus reared under different photoperiods. DD = continuous darkness, SL = 7 ½ h light and 16 ½ h darkness NL = simulated natural photoperiod changing from 18h light and 6h darkness to 16h light and 8h darkness, and LL = continuous light. The 3 replicates are shown for each group. Vertical bars indicate 95% confidence intervals, n=3 (2). Dotted area above x-axis indicate period of light, dark area indicate period of darkness.

The pattern of feeding rate over time varied between the replicates (Figure 8). Though not significant, the average feeding rate of group DD was lower than the three other groups at all times of sampling. The least detectable difference () was 889 algae cellsindividual-1minute-1 (12% of average feeding rate), while the largest difference was
695 algae cellsindividual-1minute-1. The average coefficient of variation within each group at the different sampling times was 7.5% (range 2-22%).


Large variability was observed in the data for oxygen consumption with sporadic deviant measurements (Appendix 9). In four cases the values for oxygen concentration in the outlet water were higher than for the inlet water. The SD of the replicates in this experiment was 0.2 mgl­1, which is a tenfold increase from preliminary measurements (SD=0.018 mgl­1, range 0­0.04). The data were therefore not considered as adequate for analysis.

ropp LOGO ropp LOGO rneste LOGO