Chapter 1: General Introduction 1
3.4 Discussion 112
3.4.1 The effects of C. volutator on sediment and overlying water column
Turbidity increased linearly with C. volutator biomass on all three days (see Figure
3.8. day 3: 9.2 ± 2.0, p < 0.0001; day6: 12.8 ± 2.2, p < 0.0001; day 8: 25.7 ± 2.2, p <
0.0001) and turbidity g
‐1also increased linearly with day (Figure 3.9, ‐0.5 + 3.5*day,
p=0.05). In similar experiments with increasing C. volutator biomasses in aquaria
without flow, de Deckere and colleagues (2000) found an exponential increase in
suspended sediment with increasing C. volutator biomass (y = 50 + 0.43x
0.45), whereas
Biles and colleagues (2002) found a sigmoidal relationship, where the suspended
sediment in the 1 g biomass group (surface area same as in this experiment) hardly
varied from 0 g biomass group but the 2 g treatment was 8 fold higher than the 1 g
treatment. However, both studies had much higher maximum biomasses than this
one (5x and 4x, respectively), so possibly, had this experiment included a 8 or 10 g
group, the relationship would eventually no longer have been linear but flattened
off. With respect to the C. volutator presence/absence treatments in this experiment,
the pumps distributed the overlying water effectively as there were no significant
differences in turbidity between the tanks within each unit after they were switched
on (see Table 3.2, Model 3.1.1: on days 6 & 8 p‐values = 0.082 & 0.724, respectively).
Lastly, if C. volutator pumping rate increases with temperature (as per Møller & Riis‐
gård 2006) then turbidity should also increase with temperature, however, the 1.6 °C
range in evening temperatures did not correlate with turbidity on any day (Pearson
correlations day 3, 6, and 8, respectively: ‐0.044, 0.168, and 0.294; p‐values: 0.608,
0.431, and 0.162). This suggests that a temperature difference of < 2 °C is not suffi‐
In contrast to multiple studies, on both laboratory reconstructed sediment micro‐
cosms and in the field, which have demonstrated C. volutator presence increasing
ammonium flux from the sediment to the overlying water column (Henriksen et al
1980; Henriksen et al 1983; Emmerson et al 2001; Biles 2002; Mermillod‐Blondin et al
2004, Bulling et al 2010), in this study the ammonium flux to the overlying water col‐
umn did not significantly increase with increasing biomass (Figure 3.11 and Table
3.3, Model 3.2.2a, slope = 2.9 ± 6.7, p = 0.670). There are several possible reasons why
there was not much distinction in ammonium levels in the overlying water. First,
coupled nitrification‐denitrification could have simultaneously depleted ammonia
and nitrate levels leading to lower ammonium levels in the overlying water column.
The source of the increased ammonia is partially C. volutator excretion and partially
ammonia release from lower depths in the sediment, due to bioturbation, where
ammonia concentrations are higher (Henriksen et al 1980, 1983). However, in con‐
junction with the release of ammonium, there can also be an increase in nitrification,
mediated by aerobic bacteria, and denitrification mediated by anaerobic bacteria liv‐
ing along in the oxic‐anoxic boundary – the surface areas of both of these habitats are
increased substantially by burrow building and irrigation (Pelegri & Blackburn 1994;
Pelegri et al 1994; Rysgaard et al 1995). In Pelegri and Blackburn’s experiment (1994)
ammonium from overlying water fluxed into the sediment but ammonium levels in
the sediment also decreased and this was due to enhanced coupled nitrification‐
denitrification in the sediment with C. volutator burrows. However, it has also been
shown that coupled nitrification‐denitrification increases with increasing nitrate lev‐
els in the overlying water column (Pelegri et al 1994; Rysgaard et al 1995) and as ni‐
trate levels were almost nil from the start of this experiment, coupled nitrification‐
denitrification probably was not the reason for the lack of relationship between C.
volutator biomass and ammonium in the overlying water column. Second, MPB
biofilms themselves influence biogeochemical fluxes: phosphate and dissolved inor‐
ganic nitrogen release tends to be low or negative (going into the sediment) in the
light, when photosynthesis is presumably sequestering resources, and becomes more
positive when in the dark or with increased respiration in the sediment (Henriksen et
al 1980; Andersen & Kristensen 1988; Rizzo 1990) whereas others have found that ni‐
trogen dynamics are seasonal and whereas slight nitrate uptake prevails in spring
ammonium release prevails in summer (Feuillet‐Girard et al 1997). As each tank
containing a C. volutator biomass treatment was coupled to a tank containing only
sediment and MPB and measurements were only made from single samples from
each tank on days 1 and 8 it is impossible to tell which tank had a stronger effect on
the overlying water column and whether a negative or positive flux of one tank
could have cancelled out the negative or positive flux in the other tank. This uncer‐
tainty would have been avoided by measuring the fluxes within the two tanks of
each unit independently of each other: stopping the pumps, plugging the tanks, and
then sampling the water immediately, at 3 hours, and at 6 hours before draining the
water. Daily net fluxes could have then been calculated for each day to establish
(independent) trends for C. volutator presence and biomass treatments. Finally, it is
possible that ammonium was flushed from the mud because, due to a delay in start‐
ing the experiment, mud previously collected, sifted, and stored outdoors had to be
aerated to prevent it from becoming completely anoxic prior to starting the experi‐
ment – water was poured off every 3 days and fresh oxygenated seawater stirred in.
Not only could this have washed away porewater nutrients but it is also possible that
the sediment had not stabilized by day 1, hence the large outlier (see Figure 3.10).
Experiments on nutrient fluxes by other researchers have allowed mesocosms to be
established from anywhere from 2 – 9 weeks before making flux measurements
Blackburn 1994; Emmerson et al 2001; Mermillod‐Blondin 2004), although there have
been experiments where significant differences in fluxes between treatments have
been found after just 5 – 7 days and with a similar setting‐up procedure (Biles et al
2002; Bulling et al 2010). Also, the variability in nutrient levels is quite large so possi‐
bly a larger sample size was required to detect relatively small differences. A power
analysis by Ieno and colleagues (2006) concluded that a minimum sample size of 5
was required to detect a significant nutrient release from sediments bioturbated by
different macrofauna, although Biles and colleagues (2002) found significant differ‐
ences with only 3 replicates. Phosphates fluxes between days 1 and 8 also did not
vary significantly between C. volutator biomass treatments (Figure 3.13 and Table 3.3,
Model 3.2.2b, slope = ‐0.04 ± 0.43, p = 0.930). The reasons are probably similar to
those discussed for ammonium release above. However, interestingly phosphate
was released (fluxes from day 1 to 8 are mostly positive) across all treatments, includ‐
ing the control, which suggests that phosphate flux is either purely diffusive or that it
is mediated by MPB rather than macrofauna. As water samples for flux measure‐
ments were taken in the morning after only maximum 2 hours of light, it is possible
that it is simply the release of phosphate in the dark as described by previous authors
(Henriksen et al 1980; Andersen & Kristensen 1988; Rizzo 1990) that is being detected.
Water content over the top 2 mm of sediment varied substantially within and be‐
tween C. volutator treatments (on both days) but no relationship was apparent be‐
cause while water contents on day 8 were mostly higher than on day 1 this was also
true for the control treatment (see Figure 3.14). Meadows and Tait (1989) found a
significant negative correlation between sediment water content and C. volutator
biomass in their laboratory cores, which they reasoned was due to burrows provid‐
ing increased drainage from surface sediment, whereas Gerdol and Hughes (1994b)
other infauna were excluded from patches of sediment found that water content in‐
creased in the presence of burrowing infauna. In contrast one would expect the or‐
ganic content in the top 2 mm of sediment to decrease with increasing C. volutator
density because they feed on MPB as well as EPS. However, although while there
were no real differences in sediment organic content between C. volutator presence
and biomass treatments, organic content in the MA treatments of the 1 and 2 g treat‐
ments were higher than those in the corresponding MP treatments by 1 and 0.8 %
(Figure 3.15). De Deckere and colleagues (2000) found lower organic content in
sediment where C. volutator was present (but found no further decreasing relation‐
ship at increasing densities) and higher percentages of organic content in the sus‐
pended sediment, which increased with increasing C. volutator density. It is possible
that suspended sediment with organic content from the MP tanks settled on the sur‐
face in the MA tanks whereas it was more likely to remain suspended in the MP
tanks. However, if that were the case, then the organic contents in the MA tanks
should be correspondingly lower, which they were not. For both sediment assays,
larger samples or pooling of sample cores from the same tanks instead of measuring
them separately could possibly have reduced the variance within tanks and within
treatments. Also freeze drying rather than oven drying is a more accurate as it is
immediately apparent when there is moisture remaining after the standard drying
time. Slight variations in residual moisture content in the samples following drying
and prior to incineration would lead to both inaccurate estimation of water and or‐
ganic content.
3.4.2 Effects of C. volutator on MPB biomass
There were differences in light and temperature across the bench: temperatures were
generally higher in the back row (Figure 3.26) and light intensities were higher under
in such a way that meant that light and temperature differences were confounded
with C. volutator presence and biomass treatments: MP tanks had higher tempera‐
tures than MA tanks and the 0.5 and 1 g biomass treatments had, on average, up to
100 μmol m
‐2s
‐1more light than the 0 and 2 g treatment.
As with other sediment assays, cores for chlorophyll a extraction probably had too
small a surface area (57 mm
2) and should have been pooled prior to assaying to pro‐
vide a more accurate measure of chlorophyll a content of sediment. Chlorophyll a
values also varied greatly within treatment (though more so on day 1) and did not
present any obvious patterns with C. volutator presence or biomass treatments (Fig‐
ure 3.16). However, when regressed against the environmental variables in each
tank (Table 3.4, Model 3.4), both turbidity and incident light intensity had a signifi‐
cant negative effect on chlorophyll a concentration (‐2.5 ± 0.6 μg cm
‐2ntu
‐1, p = 0.001
and ‐0.04 ± 0.004 μg cm
‐2μ
‐1, p = 8.5*10
‐9, respectively), while phosphate in the water
column and, oddly, the biomass of feeding C. volutator in the tank both had a signifi‐
cant positive effect on chlorophyll a concentration (3.8 ± 0.4 μg cm
‐2μmol
‐1, p = 0.007
and 13.8 ± 4.5 μg cm
‐2g
‐1, p = 9.6*10
‐9, respectively). Turbidity was certainly caused
by C. volutator and reduced light penetration to sediment and this seemed to deplete
MPB biomass. Phosphate flux is discussed in conjunction with F
0model below. The
effects of light intensity and C. volutator feeding, though, are counter‐intuitive and
slightly suspect: one would expect increased light intensity to have a positive effect
on photosynthetic biomass rather than a negative one and vice versa for C. volutator
feeding. Bootstrapped predictions and confidence intervals of chlorophyll a concen‐
tration over the mean turbidity range (Figure 3.21) shows that while significant ef‐
fects are predicted by the model, the confidence intervals on the predictions for each
scenario (low biomass – low phosphate, low biomass ‐ high phosphate, high biomass
tween C. volutator presence and biomass treatments or between the maximum and
minimum turbidity. The only variable for which the model predicts a marked differ‐
ence on chlorophyll levels, where the confidence levels of the predictions for high
and low levels do not overlap, is phosphate. It is likely that the large uncertainty in
chlorophyll a estimation is caused either by too small a sample area or interference of
chlorophyll degradation products such as pheophytin a and pheophorbide a in the
chlorophyll a signal as measured by fluorescence (Lorenzen 1967). Some studies
have shown that these pigments increase with grazing of sediment biofilms (Lucas &
Holligan 1999; Cartaxana et al 2003) although other studies have found a decrease in
pheopigments in grazed sediment and do not recommend inference of grazing inten‐
sity from phaeopigment quantification (Ford & Honeywill 2002). Concentration of
pheopigments in a solution can be detected by acidification of the pigment solution
(Lorenzen 1967) and this step should probably be performed as a caution for inter‐
preting chlorophyll a content of grazed sediment.
Minimum fluorescence (F
0) is an estimation of surface biomass by proxy of the fluo‐
rescence emissions by pigments in the LHC complexes of chloroplasts in response to
light. F
0has been demonstrated to correlate with chlorophyll a content as they are
both proportional to biomass (Serôdio 2001; Honeywill et al 2002). However, that
was not the case in this study (Figure 3.23 A & B), where there was no significant cor‐
relation between these two biomass estimators at either the start or the end of the ex‐
periment (p = 0.914 and p = 0.660, respectively). This is more likely due to inaccuracy
in chlorophyll a quantification, discussed above, rather than inaccuracy in F
0meas‐
urement. Surface biomass clearly declined once C. volutator was added to the tanks
(Figure 3.18); the only treatments where there was an overall decline before C. voluta‐
tor were added were the 2
ndtanks (MA) of the 0 and 2 g treatments which had low
treatment (MP) had the lowest light and their biomass increased in this time. The
fact that decline also occurred in all 0 g treatments between days 6 and 8 suggests
that laboratory conditions were not suitable in the long term; perhaps this was be‐
cause MPB were from intertidal populations that were permanently submerged in
the laboratory. Defew and colleagues (2004) found that healthy biofilms could be
maintained in a tidal system in the laboratory for almost 3 weeks at 10 and 18 °C and
70, 175 and 350 μmol m
‐2s
‐1light, whereas Dyson and colleagues (2007), using per‐
manently submerged systems, also found a decline in F
0after 7 days even in the ab‐
sence of grazers, and also found no correlation between chlorophyll a biomass and F
0(Dyson 2008, personal communication). It should also be noted that F
0measures
only chlorophyll a biomass within about 100 ‐ 150 μmol of the sediment surface and
are therefore measuring only the proportion of the total productive biomass in the
sediment that is currently photosynthesising (Serôdio et al 2001). Diatoms migrate
during the tidal cycle and their in situ migratory rhythm is maintained for up to a
week in the laboratory in the absence of light and tidal stimuli (Consalvey et al 2004
and references therein); so even though F
0measurements were made at the same
time each day (9 – 10 am), they would not have been made at similar times in the in
situ tidal cycle. However, F
0measurements were made at the start of the low tide on
day 1 (when migration to the surface should be at peak levels), during high tide
(when most diatoms should be buried below 200 μm) on days 3 and 6, and towards
the end of the low tide (where diatoms should be migrating downwards) on day 8, so
it is unlikely that the low levels on day 8 are due to migratory rhythms. Since all
MPB assemblages in all tanks came from the same slurry, biomass levels across tanks
on the same day are still be comparable. On the final day of the experiment, there
was a clear pattern of surface biomass levels across treatments (Figure 3.17, round
where C. volutator was present (MP) had substantially lower biomasses than tanks
where C. volutator was absent (MA) and tanks that shared a water column with C.
volutator had much lower surface biomass than control tanks (with the exception of
one outlier in the 1 g – MA treatment). Overall, the pattern of decline was exponen‐
tial in both treatments, with the rate of decline decreasing with increasing biomass,
but with a steeper decline in the tanks where C. volutator was feeding. De Deckere
and colleagues (2001) also found and exponential decrease in their aquaria experi‐
ment with increasing C. volutator biomass.
In the regression of F
0against all the environmental variables measured for each tank
(Table 3.4, Model 3.5), turbidity, incident light intensity, and feeding C. volutator
presence (but not biomass) had a significant negative effect on surface biomass (‐3.9 ±
1.1 units ntu
‐1, p = 0.002; ‐0.699 ± 0.2 units μmol
‐1, p = 0.008; ‐42.4 ± 9.2 units g
‐1, p =
0.0003). That C. volutator feeding on diatoms reduced the biomass comes as no sur‐
prise and the fact that there was no increased MPB biomass loss with increased C.
volutator presence suggests that to some degree feeding rate is density dependent (al‐
though the 2 g ), which is also a common ecological phenomenon. The increase of
turbidity in the overlying water column is clearly linked to increased C. volutator
abundance and clearly reduced MPB biomass. However, light intensity also has a
negative effect on MPB biomass which would counteract the effect of turbidity; the
reason for this is to the fact that the biggest difference in light intensities occurred in
two tanks that had very similar turbidities, and the one with the lower light intensity
had a higher F
0. The significant positive interaction between turbidity and light in‐
tensity reduces both effects slightly. The bootstrapped predictions of the model over
the full range of turbidity, assuming mean temperature and light intensity, shows
that at low turbidities presence of C. volutator is more pronounced than at high con‐
Finally, it is interesting that the models for both biomass measurements estimated a
positive response to increasing phosphate levels in the overlying water (for F
09.0 ±
4.3 units μmol P ∙L
‐1, p = 0.050) and neither model estimated any significant effects of
increasing ammonium fluxes. The effect is significant in the F
0model due to the fact
that a positive outlier in the 1 g MA tank (std. res = 3.1) is from a unit with a high
phosphate content in the overlying water column; when the outlier is removed from
the model, phosphate no longer has a significant effect (Table 3.4, p = 0.078) and can
be removed from the model without AICc increase (AICc with = 197.66, without =
197.44). It is unlikely that higher phosphate in the overlying water caused higher
MPB levels for two reasons: (1) MPB is more likely to be DIN limited, and (2) if
higher phosphate levels did encourage MPB proliferation, then MPB biomass should
correlate positively with day 1 levels and negatively with day 8 levels, i.e. flux
should have been into the sediment rather than out of it, which is the exact opposite
of what happened. The first point was made clear by Ryther and Dunstan (1971)
who demonstrated that coastal phytoplankton are far more likely to be limited by
DIN because while Redfield’s 15:1 N:P ratio may be true over oceanic spatial and
geological time scales, it certainly is not true in coastal and eutrophic waters where
the ratios of 0:0.25 prevail but the atomic content in photosynthetic cells is, on aver‐
age, 10:1. Phosphorus regenerates more rapidly in seawater than nitrogen and nitro‐
In document
Microphytobenthic diversity and function in estuarine soft sediment
(Page 132-146)