Natural iron fertilisation from Southern Ocean islands results in high
primary production and phytoplankton biomass accumulations readily visible
in satellite ocean colour observations. These images reveal great spatial
complexity with highly varying concentrations of chlorophyll, presumably
reflecting both variations in iron supply and conditions favouring
phytoplankton accumulation. To examine the second aspect, in particular the
influences of variations in temperature and mixed layer depth, we deployed
four autonomous profiling floats in the Antarctic Circumpolar Current near
the Kerguelen Plateau in the Indian sector of the Southern Ocean. Each
“bio-profiler” measured more than 250 profiles of temperature (
The productivity of the Southern Ocean is important for many reasons. It supports fisheries and high-conservation-value marine mammal and bird populations (Constable et al., 2003; Nicol et al., 2000), influences the carbon dioxide content of the atmosphere (Sarmiento and Le Quéré, 1996; Sigman and Boyle, 2000; Watson et al., 2000), and affects the magnitude of nutrient supply to large portions of the global surface ocean (Sarmiento et al., 2004). This productivity is limited by the scarce availability of iron (Fe) as an essential micronutrient (Boyd and Ellwood, 2010; Boyd et al., 2007; Martin, 1990). Island sources of Fe elevate productivity and produce downstream “plumes” of elevated phytoplankton biomass that contrasts with the general HNLC (high-nutrient, low-chlorophyll) nature of the Southern Ocean (Blain et al., 2007; de Baar et al., 1995; Mongin et al., 2009; Pollard et al., 2009; Nielsdóttir et al., 2012). Ship-based studies of several of these regions, focused on the influence of Fe on carbon (C) transfer to the ocean interior (Blain et al., 2008; Salter et al., 2007), have revealed a diversity of responses in terms of intensity of enhanced productivity, biomass accumulation, and ecosystem structures. This diversity derives from interactions between the supply and bioavailability of iron with other drivers of productivity such as temperature, water column stratification and stability, light levels, and the possibility of co-limitation by other nutrients (Assmy et al., 2013; Boyd et al., 1999, 2001; Queguiner, 2013).
Assessing influences on productivity, biomass accumulation, carbon export,
and carbon dioxide (CO
These difficulties of observation become even more acute for carbon export
estimates, which require either flux measurements (e.g. from moored or
free-drifting sediment traps or radionuclide activities; Planchon et al., 2014; Savoye et al., 2008) or the
partitioning of changes in state variables across biogeochemical vs.
oceanographic causes (e.g. nitrate depletions in surface waters or oxygen
consumption at mesopelagic depth; Matear et al., 2000;
Trull et al., 2015). Obtaining estimates of carbon export and
the depth of its penetration into the ocean interior are important to
determining impacts on the climate system, because variations in these two
factors have similar influence to variations in total primary production in
terms of the sequestration of CO
This space–time complexity is abundantly demonstrated by the “mosaic of
blooms” (i.e. patchiness pattern) encountered in waters downstream from the
Kerguelen Plateau during the KEOPS2 field programme in austral spring
(October–November 2011), as detailed in many papers in a special issue of
To explore the influence of variations in these water column properties on bloom structure at larger scale, in particular further from the plateau than could be surveyed by ship, we deployed autonomous profiling drifters. The first one was successfully launched during the KEOPS2 field programme in late October 2011, and the other three during the MyctO-3D-MAP (referred to as MYCTO, from now on in this text) interdisciplinary survey between late January and early February 2014. Given the extent of the Kerguelen biomass plume (> 1000 km; Mongin et al., 2009), the remoteness from ports, and the generally rough sea states, the use of autonomous platforms is arguably the only affordable way to survey this region. As shown in Fig. 1, these deployments returned data from a large proportion of the enriched biomass plume downstream of the Kerguelen Plateau.
Maps of bio-profiler trajectories (white and grey lines) over
remotely sensed chlorophyll
In this paper, we use the bio-profiler observations to address three questions:
Do satellite images of surface chlorophyll provide an unbiased guide to
the spatial distribution of total water column chlorophyll, or are they biased
by lack of knowledge of variations in the vertical extent of chlorophyll
distributions or the presence of subsurface chlorophyll maxima? Do regions of high biomass correlate with particular oceanographic
properties, such as warmer or fresher waters, or the intensity of
stratification? If so, are these properties determined locally or by the
upstream origins of the different water parcels? Can the fate of surface enrichments in biomass be determined (and
eventually quantified) from along-trajectory temporal variations in
biogeochemical properties, for example by progressive downward movement of
fluorescence or particulate backscattering signals or decreases in oxygen in
subsurface waters?
Bio-profiler deployments.
The float deployment locations are provided in Table 1, along with their
identification numbers which provide access to their full data sets via the
Australian Integrated Marine Observing System (
Temperature and salinity calibrations were performed by Sea-Bird Inc., with
estimated accuracy and precision of better than 0.005
The bio-optical sensors measured chlorophyll
In contrast to typical Argo programme float missions for climate studies
(
Extensive experience from the Argo programme with profiling float measurements
for temperature (
To evaluate the possibility of temporal sensor drifts in bio-optical
variables, we examined the variations in the bio-optical variables in
mesopelagic (250–300 m) and deep water (950–1000 m) values, i.e. at depths
where little signal was anticipated and most profiles reached steady
background values (Fig. 2a). The particulate backscattering and, to a
lesser extent, the Chl
Fluorescence signals were also corrected for daytime quenching. This effect,
which derives from the photo-inhibition of phytoplankton by an excess of
light (maximum at midday), decreases surface fluorescence (Falkowski and Kolber, 1995; Kiefer, 1973) and, if
uncorrected, can produce a false impression of subsurface maxima in
fluorescence derived chlorophyll profiles. We explain this correction and
its evaluation in considerable detail in the following paragraphs, but note
that none of the conclusions of the paper depend on these corrections
because the same overall results are obtained if we use only Chl
Bio-profiler #1 observations.
Same as Fig. 3 but for bio-profiler #2.
Same as Fig. 3 but for bio-profiler #3.
Same as Fig. 3 but for bio-profiler #4.
Drift assessment of the bio-profilers over their lifetime within the [250–300] m and [950–1000] m depth layers.
We defined the daytime profiles, potentially affected by quenching, as
profiles acquired between 1 h after local sunrise time and 1 h
after local sunset time in order to allow for dark acclimation, since the quenching
effect could still persist after sunset (Sackmann et al.,
2008). Daytime profiles from the four bio-profilers are shown to illustrate
this effect (continuous lines in Fig. 2b, left panel). To correct this
bias, we applied the method of Sackmann et al. (2008), which uses the particulate backscattering signal as a relative
reference. For the sake of consistency with the other studies of this issue,
we defined the mixed layer depth, MLD, as the depth where density increased
by 0.02 kg m
The greater spikiness of the
The effects of the quenching correction on our selected chlorophyll profiles
are shown in Fig. 2b (middle panels, continuous lines), and summary
statistics for all the profiles are provided in Table 3. Without the
correction, on average, more than 70 % of the daytime profiles exhibited a
subsurface maximum exceeding 60 % of the surface value – defined after
assessing the fluorometer error (coefficient of variation of Chl
Even after our quenching correction, 10 % of the corrected daytime
profiles (on average for all four bio-profilers) still exhibited significant
decrease in the Chl
Characteristics of subsurface chlorophyll maxima occurring at
depths greater than the mixed layer depth and exceeding the surface content
by more than 60 % (top) and 100 % (bottom).
Fluorescence quenching corrections and subsurface chlorophyll maxima statistics.
Finally, we emphasise that the bio-optical measures of chlorophyll and particulate backscattering are based on laboratory calibrations that are not specific to Southern Ocean phytoplankton or particle properties. This means that, while interpretation of local variations is reasonably straightforward, quantitative comparisons to other observations are much more uncertain (except perhaps in the future for other serial numbers of these sensors, calibrated in the same limited way). For the three bio-profilers deployed in 2014, no ancillary shipboard measurements are available to evaluate this issue, but in 2011 some chlorophyll samples were collected by the KEOPS2 science team that allow for limited evaluation of the bio-profiler #1 calibration.
Bio-profiler #1 was deployed into a semi-permanent meander of the Polar
Front, which the KEOP2 programme examined as a Lagrangian time series
following surface drifters. As shown in Fig. 2c, the first and second
stations in the meander (E1 CTD-27 on 29 October 2011 at 22:46 LT
and E2 CTD-43 on 1 November 2011 at 12:00 LT) bracketed the
locations of the first 11 autonomous bio-profiler #1 profiles (Fig. 2c.i). The bio-profiler #1 temperature profiles are intermediate between
the ship results (Fig. 2c.ii), with the variations in temperature profiles
mainly driven by vertical motions associated with internal waves (Park et al., 2014b). In Fig. 2c.iii, the KEOPS2 shipboard fluorescence
results are displayed after linear calibration to high-pressure liquid
chromatography (HPLC) total chlorophyll
These variations in fluorescence
We used satellite products to provide physical and biological context for the bio-profiler trajectories, including the effectiveness of their sampling of high-biomass waters downstream of Kerguelen. The images of surface chlorophyll concentrations shown in Fig. 1 to provide context for the plume sampling achieved by the bio-profilers are the CLS SSALTO/DUACS 4 km daily product derived from NASA MODIS-Aqua observations (Fig. 1), without taking into account that this algorithm may underestimate chlorophyll in low-chlorophyll waters south of Australia (Johnson et al., 2013).
To better understand the observed bio-profiler trajectories, we calculated
expected movements based on geostrophic currents estimated from satellite
altimetry using the multi-satellite global product Delayed Time Maps of
Absolute Dynamic Heights (DT-MADT) developed by the CNES/CLS Aviso project
(
The drifts of the bio-profilers provided coverage of a large portion of the
elevated biomass plume (Fig. 1), from near the Kerguelen Plateau to more
than 700 nautical miles downstream (71 to 95
Bio-profiler #1 in spring 2011 and bio-profiler #3 in 2014 were
deployed in the centre of the quasi-stationary cyclonic recirculation just
east of the northern Kerguelen Plateau (d'Ovidio et al., 2015; Park et al.,
2014a). Both bio-profilers exited this region to the north-east, tracking
towards the Gallieni Spur, before transiting strongly southward near
74
Bio-profiler #2 was deployed further south, close to the region where the strong north-to-south transport portions of the bio-profilers #1 and #3 trajectories finished. Thus bio-profiler #2 provided some overlap with the southern portion of the bio-profiler #1 trajectory, before being carried the furthest south, where it explored cold waters close to the Williams Ridge, which extends to the south-east of Heard Island and terminates near the Fawn Trough (a gap in the plateau which permits the passage of much of the deep water eastward transport; Park et al., 2008b; 2014a). Waters in this region tend to exhibit archetypical high-nutrient, low-chlorophyll characteristics and were used as a reference station for iron non-fertilised waters during the KEOPS field programme in 2005 (Blain et al., 2007, 2008).
In contrast, bio-profiler #4 was deployed at a similar latitude to
bio-profilers #1 and #3 but further east, in particular east of the
southward meander of the Polar Front which carried these others to the
south. Bio-profiler #4 remained in the northern portion of the plume
throughout its deployment, drifting to the north-east roughly parallel to the
shallow eastern Kerguelen Ridge before becoming trapped in a cyclonic eddy
in which it obtained a time series of
The bio-profilers return a large number of water column observations, making visualisation at the scale of individual profiles only possible for targeted issues. The simplest first-order assessment is most easily done by presenting the results as along-trajectory sections. These are shown for all the observed variables for each bio-profiler in Figs. 3, 4, 5, and 6, and briefly described in the following paragraphs.
Bio-profiler #1, launched in late October 2011 in the centre of the deep
water recirculation just east of the Kerguelen Islands, initially encountered
cold, well-oxygenated waters with moderate biomass (
Bio-profiler #2, launched in late January 2014 south and east of the
recirculation feature, initially encountered Polar Frontal Zone waters which
were present further south in this region than during the 2011 year sampled
by bio-profiler #1. For approximately the first 150 profiles, these
waters displayed relatively homogeneous, moderately warm temperatures (4–5
Bio-profiler #3, launched in late January 2014 in the northern portion of
the recirculation feature, followed a similar trajectory to that of
bio-profiler #1 launched in October 2011 and encountered much warmer
waters with similar mixed layer depths, between 40 and 70 m (Fig. 5).
Presumably this represents seasonal warming as salinities were similar to
those encountered in spring (
Bio-profiler #4, deployed well east of the recirculation feature in early
February, was initially in warm, quite salty, and well-oxygenated waters,
characterised by moderate biomass (first 80 profiles:
With this overview of the spatial and temporal characteristics of our observations in hand, we proceed to evaluate our research questions.
As discussed in the Introduction, it is important to determine whether the water column information provided by the bio-profilers changes perspectives on the mesoscale distributions of chlorophyll as seen in satellite images (Fig. 1). This is a larger issue than whether our in situ measurements of surface values differ from satellite values. We did not evaluate that question owing to extensive cloud cover greatly limiting match-ups between bio-profiler and satellite observations, and because we know that both our sensor calibrations and the satellite algorithms have large uncertainties (see Sects. 2.2 and 2.3). Instead, we examined the bio-profiler water column observations to determine what biases might be expected from observing only their upper portions, i.e. as a satellite would. There are two aspects of this issue that we could readily address: (1) were subsurface chlorophyll maxima commonly present below the depth of satellite observation, and did they vary spatially or temporally? (2) Were surface chlorophyll values linearly and tightly correlated with water column inventories with similar dynamic ranges, or were surface values poor guides to water column inventories? We address these issues in this order in the following paragraphs.
Our statistics on the occurrence of subsurface chlorophyll maxima (Table 3)
show that these features were present in a significant fraction of the
profiles (up to 14 % of the night profiles and up to 21 % of the
quenching-corrected day profiles). They mostly occurred at depths greater
than the MLD (Table 3) and were thus too deep to be taken into account in the
satellite observations. Without radiation sensors on the bio-profilers, the
first penetration depth (
These SubMax
Subsurface chlorophyll maxima beyond the reach of satellite imagery can be
thought of as a specific class of the wide range of possible chlorophyll
distributions (such as varying thicknesses of relatively constant
near-surface biomass layers, or changes in the rate of decrease in biomass
with depth) that could introduce bias between surface concentration and
water column inventory perspectives. To gain perspective on the overall
importance of these possibilities, we compared surface chlorophyll
concentrations measured by the profilers (using the shallowest
Concerning the particulate backscattering signal, the linear correlations between surface values
and inventories were generally not as strong as for
Chl
Because our qualitative assessment indicated that surface Chl
To further explore this issue, we calculated expected water column
inventories for chlorophyll layers confined to the physical mixed layer
depths at the time of observation (by multiplying each surface concentration
by its associated mixed layer depth, MLD). This is akin to trying to improve
satellite assessments using mixed layer depth information from, for example,
standard ARGO floats that measure only temperature and salinity. These
comparisons are shown in Fig. 9a and reveal that this approach badly
underestimates water column inventories (at least with our MLD definition)
and that this underestimation is very common. Most of the “0–200 m
integrated Chl
The most probable explanation for these observations is that the mixed layer
at the time of observation was shallower than at the time of generation of
the biomass. This is of course expected as a result of seasonal shallowing
of the mixed layer, but the magnitude of the effect is important to
recognise (as we have shown above), as it is well above what could be corrected
using some other mixed layer depth criterion. Interestingly, there appears
to be a relatively simple hyperbolic relationship between the ratio “0–200 m integrated Chl
Overall, these results emphasise the major challenges that are present for connecting surface chlorophyll distributions to total water column biomass and primary productivity, since they reveal that physical mixed layer depths are often not a reliable guide to biomass distributions. These physical and biological responses seem to be modulated differently on diel, weather, and seasonal timescales, and are also affected by the mesoscale and sub-mesoscale interleaving of water parcels. The quantification of near-surface mixing (i.e. going beyond the limited mixed layer depth concept) is currently under very active exploration and debate in the context of seasonal drivers of production (Behrenfeld, 2010; Taylor and Ferrari, 2011), and these data reveal the need to extend those perspectives to shorter time and space scales. The presence of significant amounts of chlorophyll below the mixed layer is also important to its ultimate fate – if this biomass is not re-entrained then it may well contribute preferentially to export and to mesopelagic oxygen consumption (issues which we revisit in Sect. 4.3 below).
Relationship between 0–200 m integrated chlorophyll
Lagrangian diagnostics computed from altimetry. Maps of age and
origins of the water parcels shown in plots
To evaluate this issue, we examined bivariate regressions of Chl
Eddy entrapment of bio-profiler #4.
Temporal evolution of physical and biological properties during
the eddy entrapment of bio-profiler #4 for three density layers, with
sigma ranges of surface to 26.6, 26.6–26.8, and 26.8–26.9. Left column plots
Linking local water parcel properties to past water trajectories with respect
to the Kerguelen Plateau, as a known natural source of iron fertilisation,
provides an additional view of the role of water mass properties in the
control of chlorophyll inventories. For the waters richest in Chl
These results suggest that the northern Kerguelen Plateau is an important
target region for future studies of iron delivery mechanisms into the plume
downstream. In terms of the secondary influences of mixed layer depth and
stratification, the bio-profiler #1 profiles with integrated Chl
Evaluating this question requires the extraction of a temporal perspective
from the bio-profiler records, and is thus only possible for portions of
their trajectories which appear to be essentially Lagrangian. The best
record for this approach is for bio-profiler #4 during the period when it
carried out several clockwise loops in late autumn, i.e. for profiles
150–240 (Fig. 6a). During this time, its trajectory was very similar to
that expected based on surface currents estimated from satellite altimetry,
the density stratification of the water column was relatively steady, and
the
At the start of this period (blue lines subset in Fig. 12e), chlorophyll
profiles showed moderate to high surface and subsurface layer levels, well
above HNLC background values, with some profiles exhibiting subsurface
maxima reaching up to 1.5
During the Lagrangian eddy entrapment period, the surface mixed layer
chlorophyll levels declined further from 1.5 to
To evaluate these possibilities we examined changes in three layers: the surface layer (labelled layer 1 and defined as the surface down to the 26.6 isopycnal surface) and two density layers immediately below it (layers 2 and 3, respectively, for density ranges 26.6–26.8 and 26.8–26.9). In order to characterise the existence of vertical or horizontal mixing during the eddy entrapment, mean temperature, salinity, and depth of the density layers, as well as their thickness and stratification state, are shown in Fig. 13a, b, and c). The thickness and mean depth of the surface density layer were relatively constant in the first half of the eddy entrapment, then slightly increased as some warmer and fresher – thus lighter – water entered into the eddy structure (profiles 200–220). Contrastingly, the physical properties of the two deeper underlying density layers showed insignificant temporal trends and smaller variability over the period of interest, and thus changes in their biogeochemical properties can be attributed to local processes rather than exchanges.
The evolution of chlorophyll, particulate backscattering, and dissolved
oxygen inventories also exhibited different trends and variability for each
layer (as shown in Fig. 13d, e, and f). In the surface layer (layer 1), mean
chlorophyll and
To verify that these changes were oceanographic, we again evaluated
fluorometer and oxygen sensor drifts, but this time only over the range of
profiles considered for the eddy entrapment investigation (following the
approach used in Table 2 of examining the evolution of the mean values
within the depth layer 950–1000 m). Chl
In combination, these results suggest that not all of the accumulated
biomass was respired in the surface layer, with the CO
The bio-profilers revealed several interesting aspects of the enriched
biomass plume downstream from the Kerguelen Plateau by providing
observations of its vertical dimension. First of all, the observations show
that surface and total water column chlorophyll inventories are generally
well correlated, which suggests that satellite perspectives on bloom spatial
dynamics (e.g. Mongin et al., 2008, 2009) are
unlikely to be strongly biased. This result holds true despite the presence
of moderate (60 % above surface values) subsurface chlorophyll maxima in
up to
The occurrence of moderate subsurface chlorophyll maxima in our data
(17 %) was higher than for results obtained with fluorescence sensors
deployed on elephant seals around the Kerguelen Plateau (
Our initial research goals included looking for oxygen supersaturations in
deep chlorophyll maxima to estimate net community production (Spitzer and Jenkins, 1989), but this could not be achieved owing to
confounding effects on supersaturations from strong mixing with higher
productivity overlying waters, and on aliasing of daily cycles by internal
waves (Park et al., 2008a). Thus our results cannot address the
issues of whether productivity in subsurface layers may partly explain
offsets between satellite and in situ estimates of the Southern Ocean
biological pump (Schlitzer, 2002) or whether the phytoplankton
that grow in deep chlorophyll maxima are preferential contributors to carbon
export (Kemp et al., 2000; Queguiner, 2013). We
were able to make a first simple assessment of subsurface autumn oxygen
consumption during the portion of the bio-profiler #4 trajectory that
delivered a quasi-Lagrangian time series, and this provided the very useful
result that approximately 35 % of the biomass respiration in that period
occurred beneath the mixed layer, and thus at depths favouring CO
Our simple correlative evaluation of the bio-profiler observations of biomass
variations revealed that the highest chlorophyll levels were observed in
surface waters with a narrow range of densities and moderate temperatures
(
This work was supported by the Australian Commonwealth Cooperative Research
Program via the ACE CRC. M. Grenier was supported by a conjoint LEGOS and
ACE CRC postdoctoral appointment and a CAMPUS FRANCE grant (FASIC award #30418QG; campusfrance.org). A. Della Penna was supported by a conjoint
Frontières du Vivant (Paris 7) and CSIRO-UTAS Quantitative Marine
Science PhD scholarship. We thank Ann Thresher (CSIRO) for the harvesting
and processing of the data from the bio-profilers, as supported by the
Australian Integrated Marine Observing Argo and Southern Ocean Time Series
facilities. We thank Cedric Cotté and Francesco d'Ovidio (LOCEAN,
Universite de Paris VI) and the crew of the RV