Análisis de interpretación de los resultados

C. helgolandicus egg hatch success and naupliar deformity proportion data were arcsine-square-root transformed before any regression analyses were performed to linearise the data. Egg and seston fatty acid proportion data were also arcsine- square-root transformed. Phyto-, micro- and zooplankton data were log transformed (as log10 x+1). Both simple and multiple regression models were generated using environmental, phyto/micro-plankton and FA data (see more on FA data below). Homogeneity, normality and independence of model residuals were examined. Where residuals displayed heterogeneity, variance-covariance structures were applied via a GLS (generalised least squares) model. Date was included in the regression models to account for temporal autocorrelation in residuals.

Seston fatty acid data were analysed using principal components analysis (PCA) to reduce the number of variables employed in multiple regression analyses. PCA arranges similar variables on components and calculates the relative loading

[eigenvectors on a scale of -1 (negative loading) to 1 (positive loading)], allowing key variables to be selected (Table 3.4). FA with the highest loadings (+ and –ve) from each principal component were included in multiple regression analysis (Table 3.5).

Fatty acid profiles of both egg and seston (relative proportion data) were subject to separate non-metric multidimensional scaling (MDS) analyses to investigate fatty acid composition of each sample. MDS is an ordination technique that represents samples as points in low-dimensional space, so that samples occurring close together in a plot are very similar in composition.

The analysis of the effects of potential toxic species on eggs involved an

exploration of toxic species (listed in Table 3.2) reported during the month prior to the timings of low EHS and high NA (using mean proportions as threshold low EHS/high NA levels), to ascertain if there was any co-occurrence.

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Egg mortality rates were both positive and negative values, therefore a log10[x + (min(x) +1)] transformation was undertaken to convert all data to positive values and normalise the distribution. Following Hirst et al. (2007), mortality rates were LOESS- smoothed (f=0.2) before further analysis for relationships with potential predators (C. helgolandicus copepodites, total copepods, total medusae, total meroplankton, etc.) and environmental variables (SST, SI and chlorophyll-a, etc.). All regression analyses were performed on the LOESS-smoothed mortality rates.

All regression analyses were performed in the R programming environment (R Development Core Team, 2012). Reduced major axis (RMA) regressions were

performed using the RMA Software of Bohonak and van def Linde (2004). All multivariate statistical analyses (MDS and PCA) were performed using PRIMER-E v6 (Clarke and Gorley, 2006).

Table 3.4. Eigenvectors from five principal components of Principal Components Analysis (PCA) of seston fatty acids (proportions); numbers in bold represent highest loadings.

Seston fatty acid PC1 PC2 PC3 PC4 PC5

C16:0 -0.36 -0.02 -0.24 0.07 -0.12 C16:1(n-7) -0.16 0.32 0.31 0.14 -0.15 C16:1/C16:0 ratio -0.02 0.32 0.39 0.10 -0.05 C16:4 (n-3) 0.27 0.11 -0.36 0.00 -0.18 C16:4 (n-1) 0.08 0.30 0.02 0.34 -0.06 C18:2(n-6) -0.15 -0.28 0.00 0.34 0.19 C18:3(n-6) 0.17 0.24 -0.21 -0.29 0.34 C18:3(n-3) 0.08 -0.31 -0.17 0.33 -0.26 C18:4(n-3) 0.32 -0.05 -0.24 0.22 -0.30 C20:4(n-6) 0.08 0.28 -0.23 0.14 0.14 C20:5(n-3) 0.30 0.24 0.10 0.22 0.03 C22:6 (n-3) 0.14 -0.25 0.31 -0.24 0.32 C22:6/C20:5 ratio 0.00 0.12 0.00 -0.40 -0.57 n-3/n-6 ratio 0.12 -0.26 0.34 -0.02 -0.35 Tot MUFA -0.28 0.11 0.25 0.30 -0.05 Tot PUFA 0.41 -0.07 0.06 0.11 0.10 Tot SFA -0.37 0.04 -0.17 -0.24 -0.10

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Table 3.5. Seston fatty acids included in multiple regressions with Calanus helgolandicus egg hatch success and naupliar abnormalities, following PCA of all seston fatty acids

(proportions) and expert knowledge.

Seston fatty acid C16:0 C16:1(n-7) C16:1/C16:0 ratio C16:4(n-3) C16:4(n-1) C18:2(n-6) C18:3(n-3) C18:4(n-3) C20:4(n-6) C20:5(n-3) C22:6(n-3)) C22:6/C20:5 ratio n-3/n-6 ratio Tot MUFA Tot PUFA Tot SFA 3.3 Results

The average L4 seasonal environment over the time periods analysed in this study is presented in Figure 3.1. Sea surface temperature ranged from ~7ºC in spring (low of 7.3ºC on 9th March 2013) to ~19ºC during late summer and autumn (high of 18.8ºC on 9th August 2004) with an annual mean of ~13ºC (Figure 3.1a). Thermal stratification occurred between May and September, with peak SI indices recorded August to September when surface temperatures were >4ºC greater than at depth (Figure 3.1a). Mean fortnightly chlorophyll-a concentrations ranged from 0.3-2.4 mg m- 3

and peaked from April to May (during the spring diatom bloom), and again in late summer to autumn (with the dinoflagellate bloom). Lowest concentrations occurred during winter and also in the summer stratified period (Figure 3.1b).

Phytoplankton biomass was low throughout November to March, and was superseded by the spring diatom bloom and an increase in flagellates. Dinoflagellates appeared in summer and obtained peak biomass in September (Figure 3.1c).

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and peaked in the summer (Figure 3.1d). Ciliate biomass increased in mid-winter and constituted between 50-75% of the biomass between February and May. Throughout June and July, heterotrophic flagellates dominated and peak microzooplankton biomass levels were reached. During the autumn, both heterotrophic dinoflagellate and ciliate biomass contributed ~50% to the biomass.

Predator biomass was generally high throughout March to October and was dominated by copepods (Figure 3.1e). Meroplankton biomass was greatest during the spring, whilst gelatinous zooplankton biomass was high during summer and autumn. Non-copepod holoplankton occurred mostly in the spring and fish larval biomass was greatest in spring and summer; both contributed little to total predator biomass.

Figure 3.1. Seasonal variation (fortnightly means and error bars representing standard deviation) of (a) sea surface temperature (SST) (ºC) and Stratification Index (difference in temperature between surface and 30m) (2002-04, 2013, 2015, Jan-Sep 2016); (b) chlorophyll-

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Figure 3.1 contd. Seasonal variation (fortnightly means and error bars representing standard deviation) of (c) phytoplankton biomass (2002–2004, 2013); (d) microzooplankton biomass (2002-2004, 2013), and (e) main predator groups biomass (2002–2004, 2013).

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The fatty acid profile of the seston was measured on a near-weekly basis throughout 2013. Total seston fatty acid concentrations ranged from 4 - ~50 µg L-1, with a mean of 15.4 µg L-1. Concentrations rose from background levels from May through to September, with a peak of 48.9 µg L-1 occurring in August 2013. The dominant fatty acids included C16:0 – mean of 23%, C22:6(n-3) docosahexaenoic acid (DHA) - mean of 12%, C14:0 - mean of 11%, C16:1(n-7) - mean of 8% and C20:5(n-3) eicosapentaenoic acid (EPA) - mean of 7.5% (Figure 3.2).

Figure 3.2. Dominant fatty acid concentrations in seston (2013), comprising ~60% of annual FA concentration (C16:0 – 23%; C22:6(n-3) – 12%; C14:0 – 11%; C16:1(n-7) – 8%; C20:5(n-3) – 7.5%).