BGBiogeosciencesBGBiogeosciences1726-4189Copernicus PublicationsGöttingen, Germany10.5194/bg-13-3071-2016Deep ocean mass fluxes in the coastal upwelling off Mauritania from 1988 to
2012: variability on seasonal to decadal timescalesFischerGerhardgerhard.fischer@uni-bremen.dehttps://orcid.org/0000-0001-5089-4741RomeroOscarMerkelUtehttps://orcid.org/0000-0001-9851-0575DonnerBarbaraIversenMortenhttps://orcid.org/0000-0002-5287-1110NowaldNicoRatmeyerVolkerRuhlandGötzKlannMarcoWeferGeroldGeosciences Department, University of Bremen, Klagenfurter Strasse,
28359 Bremen, GermanyMarum Center for Marine and Environmental Sciences, Leobener Strasse,
28359 Bremen, GermanyAlfred Wegener Institute for Polar and Marine Research, Am
Handelshafen,
27570 Bremerhaven, GermanyGerhard Fischer (gerhard.fischer@uni-bremen.de)27May201613103071309012October20153November201510May201612May2016This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://bg.copernicus.org/articles/13/3071/2016/bg-13-3071-2016.htmlThe full text article is available as a PDF file from https://bg.copernicus.org/articles/13/3071/2016/bg-13-3071-2016.pdf
A more than two-decadal sediment trap record from the Eastern
Boundary Upwelling Ecosystem (EBUE) off Cape Blanc, Mauritania, is analysed
with respect to deep ocean mass fluxes, flux components and their variability
on seasonal to decadal timescales. The total mass flux revealed interannual
fluctuations which were superimposed by fluctuations on decadal timescales.
High winter fluxes of biogenic silica (BSi), used as a measure of marine
production (mostly by diatoms) largely correspond to a positive North
Atlantic Oscillation (NAO) index (December–March). However, this
relationship is weak. The highest positive BSi anomaly was in winter
2004–2005 when the NAO was in a neutral state. More episodic BSi
sedimentation events occurred in several summer seasons between 2001 and
2005, when the previous winter NAO was neutral or even negative. We suggest
that distinct dust outbreaks and deposition in the surface ocean in winter
and occasionally in summer/autumn enhanced particle sedimentation and carbon
export on short timescales via the ballasting effect. Episodic perturbations
of the marine carbon cycle by dust outbreaks (e.g. in 2005) might have
weakened the relationships between fluxes and large-scale climatic
oscillations. As phytoplankton biomass is high throughout the year, any dry
(in winter) or wet (in summer) deposition of fine-grained dust particles is
assumed to enhance the efficiency of the biological pump by incorporating
dust into dense and fast settling organic-rich aggregates. A good
correspondence between BSi and dust fluxes was observed for the dusty year
2005, following a period of rather dry conditions in the Sahara/Sahel region.
Large changes of all bulk fluxes occurred during the strongest El
Niño-Southern Oscillation (ENSO) in 1997–1999 where low fluxes were
obtained for almost 1 year during the warm El Niño and high fluxes in
the following cold La Niña phase. For decadal timescales, Bakun (1990)
suggested an intensification of coastal upwelling due to increased winds
(“Bakun upwelling intensification hypothesis”; Cropper et al., 2014) and
global climate change. We did not observe an increase of any flux component
off Cape Blanc during the past 2 and a half decades which might support
this. Furthermore, fluxes of mineral dust did not show any positive or
negative trends over time which might suggest enhanced desertification or
“Saharan greening” during the last few decades.
Introduction
Eastern Boundary Upwelling Ecosystems (EBUEs; Fréon et al., 2009) cover
only about 1 % of the total ocean area but contribute with about 15 %
to total marine primary production (Carr, 2002; Behrenfeld and Falkowski,
1997). Roughly, 20 % of the marine global fish catch is provided by the
four major EBUEs (Pauly and Christensen, 1995), the Benguela, the Canary, the
Californian and the Humboldt Current Systems. Continental margins may be
responsible for more than 40 % of the carbon sequestration in the ocean
(Muller-Karger et al., 2005) and are thus highly relevant for the global
carbon cycle. In the literature, multiple factors with potential influence on
upwelling systems have been mentioned. To discuss all of them would be
beyond the scope of this paper and we therefore focus on three major factors.
In the 1990s, a discussion began whether global warming may lead to
intensified coastal upwelling in the EBUEs (e.g. Bakun, 1990: “Bakun
upwelling intensification hypothesis”; Cropper et al., 2014). Since then,
various studies showed contradicting results, depending on the timescales
regarded, the area studied and the methods applied. The longer-term time
series analysis of wind stress and sea surface temperature (SST) by Narayan
et al. (2010) from coastal upwelling areas seems to support the “Bakun
upwelling intensification hypothesis”, but correlation analysis showed
ambiguous results concerning the relationships of upwelling to the North
Atlantic Oscillation (NAO). With some modification, the “Bakun hypothesis”
is supported for the Canary Current (CC) coastal upwelling system by Cropper
et al. (2014). Using an upwelling index derived from SSTs and remote sensing
wind stress, Marcello et al. (2011) obtained increased offshore spreading of
upwelled waters off Cape Blanc from 1987 to 2006. Other authors, however,
found a warming trend of the Canary Current System (e.g. Aristegui et al.,
2009). Bode et al. (2009) observed a continuous decrease in upwelling
intensity in the northern CC around the Canary Islands during the past 40 years, associated with the warming of surface waters, a decrease in
zooplankton abundance, and, locally, in phytoplankton abundance. Studying a
sediment core off Cape Ghir, Morocco, a cooling of the northern Canary
Current in the 20th century was inferred (McGregor et al., 2007).
An influence of tropical Pacific interannual variability on EBUEs has also
been proposed earlier. A link between the cold La Niña period (1997–1999
ENSO cycle) and the Mauritanian upwelling via a strengthening of the
north-easterly (NE) trade winds in autumn and winter was described by Pradhan
et al. (2006). Helmke et al. (2005) correlated these anomalous events with
deep-ocean carbon fluxes at the mesotrophic Cape Blanc study site. Using
ocean colour data, Fischer et al. (2009b) showed a large extension of the Cape Blanc filament from autumn
1998 to spring 1999 when comparing it to the rest of the record (1997–2008).
Using remote-sensing data, Nykjaer and Van Camp (1994) found a weak northwest
upwelling south of 20∘ N during and after the strong 1982–1983 El
Niño event.
The NW African margin and the low-latitude North Atlantic are heavily
influenced by Saharan dust transport, deposition (e.g. Kaufman et al., 2005)
and sedimentation (Brust et al., 2001). Dust particles influence the earth's
radiation balance and supply micro-nutrients (e.g. iron) and macro-nutrients
to the ocean surface waters (e.g. Jickells et al., 2005; Neuer et al., 2004).
Additionally, dust acts as ballast mineral (Armstrong et al., 2002; Klaas and
Archer, 2002) for organic carbon-rich particles (e.g. Fischer et al., 2009a,
b; Bory and Newton, 2000; Iversen and Ploug, 2010; Iversen et al., 2010;
Bressac et al., 2014). Dunne et al. (2007) suggested that dust may be the
major carrier for organic carbon to the seafloor. A clear coupling between
atmospheric dust occurrence and deep-sea lithogenic particle fluxes at
2000 m water depths was observed in the subtropical north Atlantic
(33∘ N, 22∘ W; Brust et al., 2011). Fischer and
Karakas (2009) proposed that high dust supply may increase particle settling
rates by ballasting and result in relatively high organic carbon fluxes in
the Canary Current system compared to other EBUEs. Wintertime African dust
transport is suggested to be affected by the NAO (Chiapello et al., 2005; Hsu
et al., 2012). As dust plays a major role in the Cape Blanc area with respect
to deep ocean fluxes and the intensity of coastal upwelling is affected by
the NAO as well, the major focus of this long-term study will be on the
relationship between deep ocean mass fluxes and NAO forcing.
General setting of the study area: (a) Oceanographic
setting in the area of the long-term mooring site Cape Blanc
(CBmeso) within the Cape Blanc filament (green arrow), dissolving
into eddies (indicated as circles with arrows) further offshore. The Cape
Verde Frontal Zone (CVFZ) separating the subsurface water masses of the NACW
and the SACW (Zenk et al., 1991) is shown. Upwelling zones are marked
according to Cropper et al. (2014). Ocean colour map (chlorophyll, 9 km
resolution) from MODIS is shown for 2 extreme years, winter 2006–2007
(b, NAO+) and winter 2009–2010 (c, NAO-). SeaWiFS
ocean colour during two contrasting situations for the strongest ENSO cycle
1997–1999: autumn 1997 during the warm El Niño phase (d), and
autumn 1998 during the cold La Niña event (e). The study site
CBmeso is indicated by a square box in the ocean colour pictures,
green arrow indicates the Cape Blanc filament, yellow arrows the major dust
transport. MC = Mauritanian Current, CC = Canary Current,
NEC = North Equatorial Current.
From the mesotrophic Cape Blanc study site CBmeso located about 200
nautical miles off the coast (Fig. 1a), we obtained an almost continuous
sediment trap record of fluxes (mostly from about 3500 m water depth) for
the past 25 years (1988–2012, only interrupted between 1992 and 1993). Long
time series of particle fluxes are rare, in particular from coastal upwelling
sites with high productivity. Although SSTs and wind data analyses over
longer timescales (e.g. decades) for the NW African upwelling system and
other EBUEs are very important to test the “Bakun upwelling intensification
hypothesis” (Bakun, 1990; Cropper et al., 2014), any potential increase of
upwelling intensity does not necessarily result in an increase of
phytoplankton standing stock and/or productivity and/or deep ocean mass
fluxes (e.g. Ducklow et al., 2009). Hence, for studying the potential changes
of the biological pump and carbon sequestration in the deep ocean over
decades and over a larger area, sediment traps are a primary and probably the
best choice. As deep ocean sediment traps have a rather large catchment area
for particles formed in the surface and subsurface waters (e.g. Siegel and
Deuser, 1997), they integrate rather local and small-scale effects, events
and processes in the highly dynamic EBUE off Mauritania.
Study areaOceanographic and biological setting
The sediment trap mooring array CBmeso is deployed in the Canary
Current System within one of the four major EBUEs (Fréon et al., 2009)
(Fig. 1a). Coastal upwelling is driven there by alongshore trade winds,
leading to offshore advection of surface waters, which are replaced by colder
and nutrient-rich subsurface waters. Around 21∘ N off Cape Blanc, a
prominent cold filament leads to offshore streaming of cold and nutrient-rich
waters from the coast to the open ocean up to about 450 km offshore
(Fig. 1a). This cold tongue is named the “giant Cape Blanc filament” (Van
Camp et al., 1991), being one of the largest filaments within all EBUEs.
The relationship between the coastal winds, SST and the biological response
(e.g. changes in chlorophyll) off Mauritania seems to be strong and almost
immediate (Mittelstaedt, 1991; Pradhan et al., 2006). Trade winds persist
throughout the year and intensify in late winter to reach their highest
intensity in spring (Barton et al., 1998; Nykjaer and Van Camp, 1994; Meunier
et al., 2012). According to Lathuilière et al. (2008), our study area is
located within the Cape Blanc inter-gyre region (19–24∘ N) which is
characterized by a weaker seasonality (peaks in winter–spring and autumn).
Following the definition by Cropper et al. (2014), our study area is situated
on the southern rim of the strong and permanent coastal upwelling zone
(21–26∘ N) (Fig. 1a).
The cold and nutrient-rich southward flowing CC departs from the coastline
south of Cape Blanc, later forming the North Equatorial Current (NEC)
(Fig. 1a). South of about 20∘ N, a recirculation gyre drives a
poleward coastal current fed by the North Equatorial Counter Current (NECC)
during summer. The Mauritanian Current (MC) flows northward along the coast
to about 20∘ N (Fig. 1a; Mittelstaedt, 1991), bringing warmer
surface water masses from the equatorial realm into the study area. Where the
CC departs from the coast, a NE-SW orientated salinity front in the
subsurface waters is observed, the Cape Verde Frontal Zone (CVFZ, Zenk et
al., 1991) (Fig. 1a), which separates the salty and nutrient-poor North
Atlantic Central Water (NACW) from the nutrient-richer and cooler South
Atlantic Central Water (SACW). Both water masses may be upwelled and mixed
laterally and frontal eddies develop off Cape Blanc (Meunier et al., 2012)
(Fig. 1a). Lathuilière et al. (2008) offered a comprehensive overview of
the physical background, i.e. the ocean circulation off NW Africa.
Importance of dust supply and Sahel rain fall for the study area
Dust supply from land to the low-latitude North Atlantic Ocean is not only
dependent on the strength of the transporting wind systems (NE trade winds at
lower levels and Saharan Air Layer above) but also on the rainfall and
dryness in the multiple source regions in West Africa (Goudie and Middleton,
2001; Nicholson, 2013). During long periods of droughts (e.g. in the 1980s),
dust loadings over the Sahel experienced extraordinary increases (N'Tchayi
Mbourou et al., 1997). As mass fluxes and settling rates of larger marine
particles (i.e. marine snow) are assumed to be influenced by mineral dust
particles via the ballasting effect (Armstrong et al., 2002; Fischer et al.,
2009a, 2010; Iversen and Ploug, 2010; Bressac et al., 2014; Dunne et al.,
2007; Thunell et al., 2007), climatic conditions on land need to be
considered. The contribution of dust to the settling particles in the deep
ocean off Cape Blanc amounts to one-third on average of the total mass flux
(Fischer et al., 2010), but it may be as high as 50 % during particular
flux events (Nowald et al., 2015). As shown by Jickells et al. (2005),
modelled dust fluxes from the Saharan region and their variability may be
influenced by ENSO and NAO cycles (see also Goudie and Middleton, 2001;
Chiapello et al., 2005; Hsu et al., 2012; Diatta and Fink, 2014). During the
time period of this study (1988–2012, Fig. 2), the wintertime
(December–January–February–March = DJFM) NAO index after Hurrell
(Hurrell, 1995) is characterized by switches from extremely positive (e.g.
1989, 1990) to extremely negative values (e.g. in 1996, 2010).
The NAO Hurrell index (DJFM, station-based, Lisbon-Rejkjavik,
Hurrell, 1995) plotted from 1864–2014. Grey shading indicates the time
period covered by the long-term flux record off Cape Blanc, Mauritania. A
5-point running mean is shown by the thick line.
Climate over West Africa is also influenced by the continental Inter-Tropical
Convergence Zone (ITCZ; also named Intertropical Front, Nicholson, 2013).
This low-pressure zone separates the warm and moist SW monsoon flow from the
dry NE trade winds coming from the Sahara. The tropical rainbelt in the
Atlantic realm originates from the convergence of the NE and SE trade wind
systems and migrates roughly between ∼ 3∘ S (boreal winter)
and ∼ 15∘ N (boreal summer) in the course of the year (Lucio
et al., 2012). On longer timescales, severe Sahel drought intervals occurred
in the 1980s (Chiapello et al., 2005; Nicholson, 2013). Recent evidence shows
that Sahel rainfall may have recovered during the last 2 decades and that
the region is now “greening” (Fontaine et al., 2011; Lucio et al., 2012).
Large-scale teleconnections affecting the study area
Ocean-atmosphere dynamics at our study site is influenced by large-scale
atmospheric teleconnections and climate modes. Here, such teleconnections are
illustrated based on results from a long-term present-day climate control run
which was performed using the Comprehensive Climate System Model version 3
(CCSM3; Collins et al., 2006; Yeager et al., 2006). Atmospheric sea-level
pressure (SLP) patterns describe the near-surface air flow which affects
ocean upwelling and currents as well. We therefore correlated simulated SLP
with prominent teleconnection indices such as the NAO SLP index (Hurrell,
1995) and the Niño3 area-averaged (150–90∘ W,
5∘ S–5∘ N) SST index, both calculated from the model
results (Fig. 3). Boreal winter is the season where the NAO is strongest and
where tropical Pacific SST anomalies associated with ENSO events tend to
peak.
Teleconnections affecting the study site off Cape Blanc. Correlation
of simulated sea-level pressure (SLP) with (a) the NAO SLP index
after Hurrell (Hurrell, 1995; boreal winter season), (b) the Nino3
SST index (boreal winter season), and (c) North Atlantic SST (low
pass-filter applied considering periods above 10 years). Analysis based on
the last 100 model years of a present-day control simulation using the CCSM3
model.
Correlations during winter show that NAO and ENSO may have opposite effects
on the NW African/eastern Atlantic realm (Fig. 3a, b), for instance on wind
fields, and consequently on upwelling with potential implications for deep
ocean mass fluxes. A positive phase of the NAO is associated with anomalous
high pressure in the Azores high region (Fig. 3a) and stronger northeasterly
winds along the NW African coast. In contrast, a positive phase of ENSO (El
Niño event) goes along with a weakening of the northeasterlies in the
study area (Fig. 3b). It should be noted, however, that the magnitude of
correlation in our study area is larger for the NAO than for ENSO. This
should be taken into account when disentangling the relative importance of
these climate modes. Apart from seasonal-to-interannual timescales,
low-frequent climate variability may impact on our study area as well and is
probably linked to Atlantic SST variations on decadal-to-interdecadal
timescales, e.g. the Atlantic Multidecadal Oscillation (AMO). The correlation
of SLP with area-averaged (0–70∘ N, 60–10∘ W) SST
fluctuations over periods above 10 years highlights a centre of action in the
tropical Atlantic with SLP reductions (weaker northeasterly winds) along with
higher Atlantic basin-wide SST during a positive AMO phase (Fig. 3c). This
shows the potential importance of longer-term Atlantic basin-scale SST
variations for alongshore winds and upwelling (trends) at our trap location.
ENSO-related teleconnections in the NW African upwelling system have been
described by several authors (Behrenfeld et al., 2001; Pradhan et al, 2006;
Zeeberg et al., 2008) and can be illustrated by the negative correlation of
SLP with eastern tropical Pacific SST (Fig. 3b). Fischer et
al. (2009b) showed that the size of the Cape Blanc filament was small in
winter–spring 1997–1998 and unusually high from autumn 1998 to spring 1999
(Figs. 7b, 1e). This is documented by reduced (warm El Niño) and elevated
(cold La Niña) deep ocean mass fluxes of all components. In certain
years, the filament area was more than twice as large in spring as in
fall
(e.g. 1999 La Niña Event). Tropical Pacific variability on interannual
ENSO timescales is also an important factor in driving ecosystem variability
in the California Current System (for a summary see Checkley and Barth,
2009).
Material and methodsSediment traps and moorings
We used deep-moored (> 1000 m), large-aperture time series
sediment traps of the Kiel and Honjo type with 20 cups and 0.5 m2
openings, equipped with a honeycomb baffle (Kremling et al., 1996). Mooring
and sampling dates are given in Table 1. As the traps were moored in deep
waters (mostly below 1000 m), uncertainties with the trapping efficiency due
to strong currents (e.g. undersampling, Yu et al., 2001; Buesseler et al.,
2007) and/or due to the migration and activity of zooplankon migrators
(“swimmer problem”) are assumed to be minimal. Prior to the deployments,
the sampling cups were poisoned with HgCl2 (1 mL of conc. HgCL2
per 100 mL of filtered seawater) and pure NaCl was used to increase the
salinity and density in the sampling cups (salinity = 40 ‰).
Upon recovery, samples were stored at 4 ∘C and wet-splitted in the
home laboratory using a rotating McLane wet splitter system. Larger swimmers
such as crustaceans were picked by hand with forceps and were removed by
filtering carefully through a 1 mm sieve and all flux data therefore refer to the
size fraction of < 1 mm. In almost all samples, the fraction of
particles > 1 mm was negligible, only in a few samples, larger
pteropods were found.
Deployment data of the moorings and traps at the mesotrophic
sediment trap site CB, Cape Blanc, Mauritania. Associated ships' cruises and
references to earlier publications on fluxes are indicated.
TrapLATLONGwater depthtrap depthsamplingnoremark,relevant cruise recovery/nameNW m mstartendof samplesreference to fluxesGeoB no.CB-1 lower20∘45.3'19∘44.5′3646219522.03.8808.03.8913Fischer et al. (1996, 2003)Meteor 9/4/ GeoB 1121-4CB-2 lower21∘08.7′20∘41.2′4092350215.03.8924.03.9022Fischer et al. (1996, 2003)Meteor 12/1/ GeoB 1230-1CB-3 lower21∘08.3′20∘40.3′4094355729.04.9008.04.9117Fischer et al. (1996, 2003, 2010)Polarstern ANT IX/4CB-4 lower21∘08.7′20∘41.2′4108356203.03.9119.11.9113Fischer et al. (1996, 2003, 2010)Meteor 20/1/ GeoB 1602-1CB-5 lower21∘08.6′20∘40.9′4119358706.06.9427.08.9419Meteor 29/3/ GeoB 2912-1CB-6 upper21∘15.0′20∘41.8′413777102.09.9425.10.9520Fischer et al. (2010)Polarstern ANT XIII/1CB-7 lower21∘15.4′20∘41.8′4152358620.11.9529.01.9720Meteor 38/1/ GeoB 4302-7CB-8 upper21∘16.3′20∘41.5′412074530.01.9704.06.9820Fischer et al. (2010)Meteor 41/4/ GeoB 5210-2CB-9 lower21∘15.2′20∘42.4′4121358011.06.9807.11.9920Helmke et al. (2005)Metero 46/1/ GeoB 6103-3CB-10 lower21∘17.2′20∘44.1′4125358610.11.9910.10.003mostly no seasonal samplingPolarstern ANT XVIII/1CB-11 upper21∘16.8′20∘43.0′4113100311.10.0030.03.0120Poseidon 272/ GeoB 7401-1CB-12 lower21∘16.0′20∘46.54145361005.04.0122.04.0214Meteor 53/1c/ GeoB 7917-1CB-13 lower21∘16.8′20∘46.7′4131360623.04.0208.05.0320Fischer et al. (2009b)Meteor 58/2b/ GeoB 8628-1Fischer and Karakas (2009)CB-14 upper21∘17.2′20∘47.6′4162124631.05.0305.04.0420Poseidon 310/ no numberCB-15 lower21∘17.9′20∘47.8′4162362417.04.0421.07.0520Meteor 65/2/ no numberCB-16 lower21∘16.8′20∘47.8′4160363325.07.0528.09.0620Poseidon 344/1/ GeoB 11401-1CB-17 lower21∘16.4′20.48.2′4152361424.10.0625.03.0720Merian 04/b/ GeoB 11833-1CB-18 lower21∘16.9′20∘48.1′4168362925.03.0705.04.0820Poseidon 365/2/ GeoB 12907-1CB-19 lower21∘16.2′20∘48.7′4155361722.04.0822.03.0920Merian 11/2/ GeoB 13616-4CB-20 upper21∘15.6′20∘50.7′4170122403.04.0926.02.1019Poseidon 396/ GeoB 14201-3CB-21 lower21∘15.6′20∘50.9′4155361728.02.1004.04.1120Merian 18/1/ GeoB 15709-1CB-22 lower21∘16.1′20∘50.9′4160362205.05.1111.01.1215Poseidon 425/ GeoB 16101-1CB-23 lower21∘15.8′20∘52.4′4160362220.01.1222.01.1318Poseidon 445/ GeoB 17102-5Mass fluxes
Analysis of the fraction < 1 mm, using 1/4 or 1/5 wet splits,
was performed according to Fischer and Wefer (1991). Samples were
freeze-dried and the homogenized samples were analysed for bulk (total mass),
organic carbon, total nitrogen, carbonate and biogenic opal
(BSi = biogenic silica). Organic carbon, nitrogen and calcium carbonate
were measured by combustion with a CHN-Analyser (HERAEUS). Organic carbon was
measured after removal of carbonate with 2 N HCl. Overall analytical
precision based on internal lab standards was better than 0.1 %
(±1σ). Carbonate was determined by subtracting organic carbon
from total carbon, the latter being measured by combustion without
pre-treatment with 2N HCl. BSi was determined with a sequential leaching
technique with 1M NaOH at 85 ∘C (Müller and Schneider, 1993).
The precision of the overall method based on replicate analyses is mostly
between ±0.2 and ±0.4 %, depending on the material analysed. For
a detailed table of standard deviations for various samples we refer to
Müller and Schneider (1993). Lithogenic fluxes or the non-biogenic
material was estimated according to
lithogenic material=dust=total mass-carbonate-opal-2×Corg.
We estimated organic matter by multiplying organic carbon by a factor of two
as about 50–60 % of marine organic matter is constituted by organic
carbon (Hedges et al., 1992). Some studies have shown a clear linear
relationship between lithogenic fluxes and particulate aluminum (e.g.
Ratmeyer et al., 1999a), the latter being derived from clay minerals as part
of the lithogenic (non-biogenic) component. Grains size studies from Ratmeyer
et al. (1999a, b) and further microscopic analysis provide evidence that most
of the lithogenic material in the study area was derived from quartz grains
in the fine silt fraction (10–30 µm, see also Friese et al., 2016).
Here we attribute the lithogenic flux to dust-derived material (= mineral
dust flux) as no large rivers supply suspended material to the study area off
Cape Blanc.
Due to logistical reasons, we had very different time resolutions of the
sediment trap collections (a few days to several weeks) which limits
comparisons between specific intervals and years. Seasonal fluxes were
calculated and shown to allow comparison between the seasons mainly with
respect to interannual variability. Seasons were defined using the dates of
opening and closure of the sampling cups closest to the start of the
astronomical seasons (21 March, 21 June, 23 September, 21 December)
(Table 2). Where lower trap data (around 3500 m) were not available, the
upper trap data (around 1000 m) were used, which mostly match the lower trap
fluxes with respect to seasonality (Fischer et al., 2009b). When plotting all
available lower and upper trap total mass fluxes for winter, a close
correspondence is observed (r2= 0.84, N= 10), with slightly
higher fluxes in the deeper trap due to lateral particle advection processes
(Fischer et al., 2009b; Karakas et al., 2006, 2009). However, considering the
entire record presented here, it seems that the upper trap fluxes of the
winter seasons 1998 and 2004 may be critical due to smaller filament areas.
As a consequence, the area/filament with elevated chlorophyll and high
particle concentrations may not have reached the upper offshore trap. Because
of lateral particle advection from the east (Karakas et al., 2006) and the
larger catchment area of the deeper traps (Siegel and Deuser, 1997), particle
fluxes might have been higher in the deeper water column in winter 1998 and
2004. In general, the seasonal patterns and the composition of the particle
fluxes were rather similar between the upper and lower traps (Fischer et al.,
2009b). The long-term means and standard deviations were calculated using
only the available deeper trap flux values. The seasonal anomalies of the
bulk fluxes were calculated using the deviations from the mean values of the
respective seasons.
Seasonal flux data and percentages of major bulk components of total
flux at the mesotrophic sediment trap site CB from 1988–2012.
CB mesointervalsample no.seasonyeardurationremarkTTL massBSiorg. carbonnitrogencarbonatelithogenicBSiorg. carbonnitrogencarb.lith.startendof trapdays g m-2 g m-2 g m-2 g m-2 g m-2 g m-2 % % % % %CB-1 lower22.03.8811.06.88#1–3spring19888115.641.910.590.0694.897.6612.233.770.4431.2548.9611.06.8827.09.88#4–7summer10823.011.571.070.13510.838.476.814.660.5947.0736.8127.09.8817.12.88#8–10fall8114.120.860.510.0566.785.466.113.600.4048.0038.7017.12.8808.03.89#11–13winter19898111.500.890.450.0555.094.637.703.920.4844.2140.23CB-2 lower15.03.8925.06.89#1–6spring10212.910.520.400.0516.924.684.033.100.4053.6036.2525.06.8918.09.89#7–11summer8513.620.490.390.0467.484.873.602.860.3454.9235.7618.09.8929.12.89#12–17fall10216.290.670.480.0568.216.454.112.950.3450.4039.5929.12.8924.03.90#18–22winter19908514.060.750.460.0556.815.585.333.270.3948.4439.69CB-3 lower29.04.9003.07.90#2–4spring64.512.680.490.390.0476.784.643.873.040.3753.4936.5503.07.9027.09.90#5–8summer8613.200.400.390.0447.354.673.052.980.3355.6435.3527.09.9022.12.90#9–12fall869.760.400.440.0524.024.464.084.520.5341.2145.6622.12.9018.03.91#13–16winter19918610.890.580.730.0914.504.345.336.730.8441.3539.87CB-4 lower18.03.9122.06.91#17 + #1–5spring71.5gap4.870.240.380.0532.091.774.897.831.0943.0236.3622.06.9120.09.91#6–14summer909.060.480.830.1103.663.255.309.161.2140.4035.8720.09.9119.11.91#15–20fall602.670.130.170.0231.310.894.876.370.8649.0633.33no samplingCB-5 lower06.06.9423.06.94#1–4spring1994171.760.050.050.0071.270.352.842.840.4072.1619.8923.06.9427.08.94#5–19summer657.300.160.140.0235.970.892.191.920.3281.7812.19CB-6 upper24.09.9421.12.94#2–5fall8811.580.260.700.1046.823.102.276.020.9058.9226.7421.12.9419.03.95#6–9winter19958812.440.960.740.1135.894.127.695.910.9147.3333.1419.03.9515.06.95#10–13spring883.500.220.240.0421.591.206.296.861.2045.4334.2915.06.9511.09.95#14–17summer880.240.000.000.0010.000.000.000.000.420.000.00CB-7 lower20.11.9519.12.95#1fall292.910.180.120.0151.221.266.264.260.5242.0643.3319.12.9516.03.96#2–5winter1996888.020.370.340.0443.803.164.554.280.5547.4039.4816.03.9612.06.96#6–9spring889.550.630.610.0804.762.946.586.380.8449.8330.8212.06.9630.09.96#10–14summer1107.440.200.290.0364.721.952.663.900.4863.3926.1530.09.9627.12.96#15–18fall888.590.380.400.0493.733.694.404.640.5743.3842.91CB-7/8 lower27.12.9620.03.97#19–20 + #1–2winter19978214.240.780.770.0975.376.555.465.410.6837.7046.00CB-8 upper20.03.9720.06.97#3–6spring9817.720.621.050.1319.695.303.505.940.7454.6829.9220.06.9702.10.97#7–10summer984.250.040.200.0262.910.900.924.660.6168.5021.2002.10.9714.12.97#11–13fall73.50.490.010.040.0060.250.122.867.141.2251.8424.0814.12.9722.03.98#14–17winter1998981.680.050.150.0240.840.453.218.871.4350.1226.4922.03.9818.06.98#18–20 + #1spring81gap1.570.010.060.0081.210.200.453.700.5176.8012.62CB-9 lower18.06.9809.09.98#2–4summer82.517.670.610.580.07412.573.343.453.290.4271.1118.8709.09.9828.12.98#5–8fall11017.061.070.770.0869.315.156.254.480.5054.5930.1928.12.9820.03.99#9–11winter199982.516.331.190.620.0737.186.717.273.810.4543.9941.1120.03.9911.06.99#12–14spring82.519.551.080.650.08311.775.405.533.330.4260.1727.6111.06.9929.09.99#15–18summer11016.880.510.570.06811.803.433.023.350.4069.9220.35CB-9/10 lower29.09.9916.12.99#19–20 + #1–2fall75gap2.200.090.090.0101.110.754.263.900.4550.3634.0716.12.9921.03.00#3winter2000948.920.140.450.0767.260.931.595.040.8581.3910.4621.03.0021.06.00#3spring928.740.140.440.0757.110.911.595.050.8681.3310.4521.06.0021.09.00#3summer928.740.140.440.0757.110.911.595.050.8681.3310.45CB-11 upper11.10.0018.12.00#3 + #1–8fall878.320.410.560.0875.131.684.936.731.0561.6620.1918.12.0022.03.01#9–19winter200193.56.510.390.600.0933.571.346.019.251.4354.8420.58CB-12 lower05.04.0127.06.01#1–4spring836.500.320.250.0342.912.764.923.850.5244.7742.4627.06.0101.10.01#5–9summer96.2512.491.030.630.0916.473.758.255.040.7351.8030.0201.10.0117.12.01#10–13fall777.900.530.430.0503.722.796.715.440.6347.0935.3217.12.0121.03.02#14 sammelwinter200294.250.880.050.040.0090.750.025.684.201.0285.232.27
Continued.
CB mesointervalsample no.seasonyeardurationremarkTTL massBSiorg. carbonnitrogencarbonatelithogenicBSiorg. carbonnitrogencarb.lith.startendof trapdays g m-2 g m-2 g m-2 g m-2 g m-2 g m-2 % % % % %CB-13 lower23.04.0219.06.02#1–3spring576.030.270.230.0293.531.784.463.780.4858.4229.5519.06.0222.09.02#4–8summer9523.101.030.620.08516.853.984.442.690.3772.9417.2322.09.0226.12.02#9–13fall959.510.420.320.0425.532.924.423.360.4458.1630.6626.12.0231.03.03#14–18winter20039511.410.550.350.0506.783.394.783.070.4459.3729.7231.03.0308.05.03#19–20spring387.710.690.270.0363.682.798.923.540.4747.7336.23CB-14 upper15.06.0316.09.03#2–7summer9311.351.260.830.1045.772.6711.067.320.9250.8023.5216.09.0318.12.03#8–13fall938.280.840.450.0613.992.5610.165.480.7448.1430.8718.12.0320.03.04#14–19winter2004930.580.030.030.0050.290.165.395.220.8749.9127.48CB-15 lower17.04.0425.06.04#1–3spring6912.490.660.450.0597.583.365.303.580.4760.6426.9025.06.0425.09.04#4–7summer9215.210.430.390.05310.753.252.802.540.3570.6421.3425.09.0426.12.04#8–11fall928.340.480.360.0434.222.935.724.250.5250.6035.1426.12.0428.03.05#12–15winter20059223.561.691.120.15212.187.447.184.760.6551.6931.5928.03.0528.06.05#16–19spring927.720.240.280.0415.001.933.043.650.5364.7224.94CB-16 lower28.06.0527.09.05#20 + #1–3summer87.5gap18.231.120.630.07810.465.406.133.430.4357.3829.6227.09.0522.12.05#4–7fall8615.871.190.630.0746.986.457.513.940.4743.9740.6322.12.0518.03.06#8–11winter20068614.900.720.460.0568.714.544.823.110.3858.4630.4818.03.0612.06.06#12–15spring8615.160.920.660.0859.043.876.094.370.5659.6425.5112.06.0628.09.06#16–20summer107.56.070.450.240.0313.551.587.383.970.5158.5126.11CB-17 lower24.10.0623.12.06#1–8fall604.340.140.140.0212.811.093.283.300.4864.8725.2423.12.0623.03.07#9–20winter20079019.891.000.840.11212.424.785.034.230.5662.4724.03CB-18 lower25.03.0725.06.07#1–5spring9211.220.380.480.0617.052.833.404.240.5462.8725.2425.06.0728.09.07#6–10summer958.570.290.330.0404.792.833.433.830.4755.9432.9628.09.0713.12.07#11–14fall767.190.390.280.0334.052.205.383.870.4656.3130.5613.12.0717.03.08#15–19winter20089510.580.640.500.0615.433.516.034.690.5851.3733.22CB-19 lower17.03.0823.06.08#20 + #1–4spring81gap5.490.240.220.0294.040.764.434.030.5373.6713.9223.06.0816.09.08#5–9summer8512.590.820.630.0728.951.586.514.990.5771.1212.5816.09.0827.12.08#10–15fall1029.010.470.440.0454.643.035.174.870.5051.4533.6027.12.0822.03.09#16–20winter2009859.510.630.420.0506.561.476.604.440.5369.0415.47CB-20 upper03.04.0930.06.09#1–5spring889.740.230.440.0608.630.072.364.560.6288.590.6730.06.0928.09.09#6–10summer903.250.090.160.0212.630.212.744.950.6580.906.4328.09.0921.12.11#11–15fall840.260.010.020.0020.160.062.316.920.7761.5422.3121.12.1126.02.10#11–19winter201067.518.770.660.950.08610.785.423.545.070.4657.4528.85CB-21 lower20.03.1028.06.10#2–6spring1007.340.240.310.0474.781.333.274.260.6465.1218.1228.06.1016.09.10#7–10summer807.720.270.270.0406.010.693.503.480.5277.858.9416.09.1025.12.10#11–15fall1009.810.260.500.0416.002.552.655.130.4261.1625.9925.12.1015.03.11#16–19winter2011804.940.200.200.0293.440.894.054.130.5969.6418.02CB-21/22 lower15.03.1121.06.11#20 + #1–3spring67gap4.900.180.210.0283.930.463.614.230.5780.229.3921.06.1114.09.11#4–8summer8510.450.280.540.0487.861.232.635.160.4675.2211.7714.09.1125.12.11#9–14fall10212.520.460.560.0578.922.023.654.430.4671.2516.13CB-22/23 lower25.12.1124.03.12#15 + #1 + #3winter201281.5 (90.5)gap17.910.870.600.08610.085.744.863.350.4856.2832.0524.03.1218.06.12#4–7spring8613.540.510.560.0645.935.973.774.170.4743.8044.0918.06.1212.09.12#8–11summer8612.900.270.310.0468.673.352.092.370.3667.2125.9712.09.1229.12.12#12–16fall107.521.100.980.730.09710.967.714.623.450.4651.9436.54Carbonate producers
To determine the major carbonate producers, the trap material was carefully
wet-sieved with a 1 mm screen and split into aliquots by a rotary liquid
splitter. Generally a 1/5 split of the < 1 mm fraction was used
to pick planktonic foraminifers and pteropods from the wet solution.
Foraminifers and pteropods were picked by hand with a pipette under a ZEISS
Stemi 2000 microscope and rinsed with fresh water for three times and dried
at 50 ∘C overnight and counted. The mass fluxes of total carbonate
producers expressed as mg m-2 d-1 are mainly constituted of
planktonic foraminifera, pteropods and nannofossils/coccolithophorids. Masses
of foraminifera and pteropods were determined with a Sartorius BP 211D
analytical balance.
Seasonal means of major bulk fluxes of the lower traps only
(a total, b organic carbon, c nitrogen, d
biogenic silica (= BSi), e carbonate, and f
lithogenic = mineral dust) and the respective standard deviations
(1 SD), which reflect interannual variability. Relative contributions
( %) of BSi, organic carbon, nitrogen, carbonate and lithogenic materials
to total mass in the respective seasons are indicated by numbers below the
bars.
Additional web-based data
To put our flux results from the deep ocean into a broader context, we used
several observational data sets available from several of the websites given
below. For ocean colour, time series from the MODIS or SeaWiFS sensors based
on a 1∘× 1∘ box from 20–21∘ N and
21–20∘ W (9 km resolution) slightly to the east of the study site
CB have been chosen due to the generally prevailing E-W directed current
system, transporting particles to the west (Helmke et al., 2005). Larger
boxes, e.g. 2∘× 2∘ or
4∘× 4∘, revealed similar results. For the aerosol
optical thickness (AOT, 869 nm, 9 km resolution), a
1∘× 1∘ box was chosen from the SeaWiFS and MODIS
data.
Results
In the long term, seasonal bulk fluxes were highest in boreal winter and
summer and slightly lower in spring and autumn (Figs. 4, 5, 6a; Table 2). Total
bulk fluxes reached 23.6 and 23.1 g m-2 in winter and summer,
respectively (Table 2). For spring and autumn, total mass fluxes were as high
as 19.6 and 21.1 g m-2, respectively (Table 2). However, the seasonal
differences in the bulk fluxes are not statistically significant. Along with
the highest mass fluxes, winter and summer seasons also exhibit the highest
standard deviations (Fig. 4), pointing to a high interannual variability. In
general, this interannual variability is clearly higher than the seasonal
differences in bulk fluxes. Only the lithogenic components, i.e. the mineral
dust particles, did not show an increase during summer and only peaked in
winter (up to 7.4 g m-2) when dust plumes were most frequent (Goudie
and Middleton, 2001). High summer fluxes of up to 16.9 g m-2 were
mostly due to high carbonate sedimentation (Fig. 4), both of primary
(coccolithophores) and secondary producers (foraminifera and pteropods).
Organic carbon and BSi showed a rather similar pattern (Figs. 4, 6a) with a
maximum in winter (up to 1.1 and 1.7 g m-2, respectively) and a
secondary maximum in summer/autumn. This is reflected in the close
correspondence between both flux components for these seasons (Table 3).
Highest mass fluxes coinciding with highest positive flux anomalies lasting
for several seasons occurred in 1988–1989, 1998–1999, and 2005–2006
(Fig. 5).
(a) Total mass fluxes of the lower traps (grey-shaded).
Gaps were filled with upper trap data (light grey bars). Deviations of the
seasonal total mass fluxes from the long-term seasonal means (anomalies),
fitted with a 9-order polynomial (b). (c) Atlantic
Multidecadal Oscillation (AMO) Index based on monthly SST fitted with a
9th-order polynomial fit (dashed blue line). The strong ENSO cycle 1997–1999
with a warm El Niño and a cold La Niña phase is indicated.
Following the strong ENSO cycle 1997–1999, total flux anomalies were low or
negative over a longer period (autumn 1999 to autumn 2004), only interrupted by
an episodic peak in summer 2002 (Fig. 5a, b). Other episodic peaks in
sedimentation were found in winter/spring 1996–1997 and in the winter
seasons 2004–2005, 2006–2007 and 2009–2010 (Fig. 5a, b). Longer intervals
(several seasons) of negative flux anomalies were obtained in 1997–1998 and
2009–2011 (Fig. 5b). Total fluxes decreased from 1988 to 1991, from spring
2007 to 2010, later increasing from 2010 to 2012 (Fig. 5).
(a) Seasonal flux of biogenic silica (BSi, green) with gaps
filled from the upper trap data (light green bars). Deviations of the
long-term seasonal means (anomalies, b). (c) The NAO
Hurrell index (DJFM). (d) Seasonal chlorophyll concentration both
from the MODIS (light green) and the SeaWiFS (dark green) sensors at 9 km
resolution. Note that high chlorophyll biomass generally occurs in
spring but sometimes in summer/autumn as well (e.g. in 1998, 2007). SeaWiFS
chlorophyll reveals a decreasing trend from 1997–2010, not mimicked in any
flux data. The strong ENSO cycle 1997–1999 with a warm El Niño and a
cold La Niña phase is indicated.
(a) The NAO Hurrell index (DJFM, Hurrell, 1995) plotted
against winter BSi fluxes from Fig. 6. Note the increase of BSi with
increasing NAO index. However, the relationship is weak due to unusual
sedimentation events in the years 1998–1999, 2002, 2004, and, in particular
in 2005. When omitting the data point from 2005, the correlation coefficient
increases, but remains low (R2= 0.14, N= 20). Upper trap
flux data from winter 1998 and 2004 may be too low as the filament with
elevated chlorophyll was small and the particles did not reach the upper trap
(see text). Omitting these two data point would slightly improve the
relationship. (b) The size of the Cape Blanc filament (Fischer et
al., 2009b) during winter months (DJFM) versus winter BSi fluxes shows higher
fluxes with larger filament size. When omitting the BSi flux from winter
2005, a statistically significant relationship between filament size and
fluxes is obtained (R2= 0.63, N= 10). Years given in the figure
denote the respective winter seasons (e.g.
1999 = December 1998–March 1999).
In general, the major bulk flux components followed the total flux and were
well inter-correlated, except that the relationship between organic carbon
and carbonate was weak in summer (Table 3). However, the regression-based
relationships (i.e. the slope) varied interannually (e.g. Fischer et al.,
2009a). The matrix in Table 3 shows the correlation coefficients between
organic carbon and nitrogen, BSi, carbonate and lithogenic fluxes for the
four seasons (lower traps only). Organic carbon and BSi (mainly diatoms) were
highly correlated during the major upwelling events in winter
(R2= 0.70) and summer/autumn, whereas the relationship between
organic carbon and total carbonate in summer was weak (R2= 0.16,
Table 3). Dust fluxes peaked together with organic carbon, preferentially in
winter and autumn (R2= 0.63 and 0.67 , respectively Table 3). The
tight coupling between organic carbon and nitrogen is not surprising as both
elements constitute organic matter formed during photosynthesis, which is
later degraded in the upper water column forming sinking phytodetritus. The
slope is almost constant (0.13–0.11) and the reciprocal value reflects the
Redfield Ratio (Redfield et al., 1963) of the sinking organic-rich particles
(Table 3). The molar C : N varied seasonally between 8.9 and 10.6, typical
for sinking detritus collected in deep sediment traps.
Correlation coefficients between organic carbon flux and major bulk
flux components for the four different seasons (lower trap data only). Number
of data points (N) and the slopes (s) for the regression lines are given
as well. Statistically significant values for R2 at a 99.9 %
confidence level are indicated in bold.
Summary of important flux changes between 1988 and 2012 which are
related to large-scale climate modes such as NAO and ENSO. The record is
divided into six major periods, including the outstanding year 2005 (see
text).
In the long term, the composition of settling particles in the deeper traps
off Cape Blanc consisted of roughly 57 % carbonate, ca. 30 %
lithogenic particles, 4 % organic carbon, 0.5 % nitrogen and 5 %
BSi (Fig. 4). BSi contained mostly a mixture of coastal and open-ocean
diatoms (Romero et al. 1999, 2002, and unpublished data). The BSi flux
pattern (Fig. 6) was influenced by switches from a positive to a negative NAO
index which were reflected in decreasing winter fluxes, e.g. from
1989 to 1991, 1995 to 1996 and 2007 to 2010. From 2001 through 2006, NAO
variability was rather low and the index was around zero or slightly negative
(Fig. 6c; Table 4). Nevertheless, BSi fluxes varied considerably and showed
episodic peaks in the summer seasons 2001, 2002 and 2003 (Fig. 6a, b). BSi
flux was high and showed positive anomalies in 2005, except for spring 2005
(Fig. 6a, b; Table 4).
The general flux pattern of BSi (Fig. 6a, b) with values from almost zero to
1.91 g m-2 did not match the SeaWiFS ocean colour time series trend
which showed an overall decrease in chlorophyll from 1997 to 2010 (Fig. 6d).
The organic carbon flux pattern (not shown, values from almost zero to
1.1 g m-2) did not follow the ocean colour data from MODIS/SeaWiFS
either. Peak chlorophyll values were observed mostly during spring, except in
1998 (autumn maximum) and 2007 (summer maximum). The MODIS ocean colour values
generally mimicked the SeaWiFS pattern, except for the discrepancy in summer
2010 (Fig. 6d).
DiscussionParticle transport processes in the water column
Mass fluxes and particle transport processes off Cape Blanc (Mauritania) have
been described by summarising articles of Fischer et al. (2009b) and Karakas
et al. (2006). Common flux patterns were the increase of fluxes in late
winter–spring and late summer of all components at both trap levels. This
matched the seasonal intensification of coastal upwelling (e.g. Meunier et
al., 2012) due to wind forcing and a stronger offshore streaming of the Cape
Blanc filament (e.g. Fischer et al., 2009b). The increase of fluxes in late
summer to autumn was mostly due to enhanced biogenic carbonate sedimentation
(Fig. 4e), associated with the northward flowing warm MC, coming from
tropical regions (Mittelstaedt, 1991). In the Canary Current upwelling
system, which is dominated by carbonate producers, particle settling rates
are rather high (around 300 m d-1), compared to EBUEs dominated by BSi
sedimentation (Fischer and Karakas, 2009; Fischer et al., 2009a). As
suggested by Fischer et al. (2009a), the relatively high organic carbon flux
in the deep ocean off NW Africa may be due to the high availability of
mineral ballast, i.e. from coccolithophorids and fine-grained mineral dust
(Iversen et al., 2010; Iversen and Ploug, 2010; Ploug et al., 2008). Direct
evidence for the influence of the deposition of dust particles on the
settling rates of larger particles and the flux attenuation in the epi- and
mesopelagic has been found on short timescales, i.e. days. This was observed
during a severe dust outbreak in January 2012 (Iversen, unpublished
observations) by deploying drifting traps before and after the dust outbreak
(Fig. 8a, insert image).
(a) Seasonal flux of lithogenic (= mineral dust)
particles (orange) with gaps filled from the upper trap data (light orange
bars). Deviations from the long-term seasonal means (anomalies, b).
Note the large positive anomalies with longer duration in 1988–1989,
1997–2000 and 2005–2006. From about 2000 to 2004–2005, lithogenic fluxes
remain rather low. In 2005, dust sedimentation and BSi flux (Fig. 6b) were
high throughout the year. (c) The AOT from the SeaWiFS (brown) and
MODIS (light brown) sensors shows repeatedly high values in summer, but
not in winter when dust sedimentation is highest in the study area. A typical
short-term (2-day) dust storm in January 2012 is shown as insert in the upper
right. The strong ENSO cycle 1997–1999 with a warm El Niño and a cold La
Niña phase is indicated.
Influence of the NAO on biogenic silica sedimentation
The NAO both affects coastal upwelling and productivity off Mauritania
through wind forcing (upwelling) and dust/nutrient supply (Chiapello et al.,
2005), mainly during winter (DJFM) (Goudie and Middleton, 2001; Cropper et
al., 2014). Indeed, we observed an increase of both the winter NAO index and
associated winter BSi fluxes (Figs. 6, 7a), the latter known to be indicative
of coastal upwelling strength and productivity. When plotting winter BSi
fluxes versus the Azores pressure alone (DJFM Ponta Delgada SLP, 1989–2002),
the relationship improves slightly (R2= 0.19 N= 11, not shown)
but remains statistically insignificant. Since upwelling is wind-driven and
large-scale wind patterns in the study area are positively correlated to NAO
variability (Fig. 3a), a close linkage between a positive (negative) NAO and
higher (lower) BSi fluxes can be expected. Organic carbon flux showed less
correspondence to the winter NAO index (not shown). No clear relationship can
be seen between the winter (DJFM) NAO index and BSi and organic carbon fluxes
later in spring, if we consider a time delay of a few weeks between wind
forcing of coastal upwelling, high chlorophyll standing stock, particle
formation and sedimentation and, finally, the documentation of increasing
fluxes in the deep traps in spring.
Relationships between BSi and lithogenic (= mineral dust) fluxes
for the winter (a) and summer (b) seasons. Note the high
correspondence in winter (R2= 0.78, N= 21); a lower coefficient
is found for the summer season. During the outstanding year of 2005 (see
Fig. 7), both points for winter and summer are close to the linear regression
line.
From 2001 to 2006 when the winter NAO index became close to zero (Fig. 6c),
the BSi flux showed rather unusual (episodic) peaks either in summer, autumn or
in winter 2004–2005 (Fig. 6a, b). This suggests increasing coastal upwelling
in summer and autumn (e.g. Cropper et al., 2014) and/or a strengthening of the
northward flowing and warmer MC, combined with an enhanced supply of a
nutrient- and Si-richer source water (SACW instead of NACW). We favour the
latter scenario as there is evidence of unusual warm surface water conditions
(SST anomalies of +3 ∘C) related to weak trade wind intensity
between 2002 and 2004 (Zeeberg et al., 2008; Alheit et al., 2014). These
conditions might have led to a stronger influence of the northward flowing MC
and the silicate-richer SACW which mixes into the Cape Blanc upwelling
filament and, thus, contributed to higher BSi productivity and sedimentation.
Such a scenario was proposed by Romero et al. (2008) to explain the
extraordinary high content of BSi in Late Quaternary sediments deposited off
Cape Blanc during Heinrich Event 1 and Younger Dryas following the Last
Glacial Maximum.
The 2004–2005 winter BSi flux clearly falls off the regression line of
winter BSi flux versus the winter NAO index (Fig. 7a). Exceptional conditions
in 2005 are also indicated when plotting the area with high chlorophyll
(> 1 mg Chl a m-3) covered by the Cape Blanc filament
(Fischer et al., 2009b) versus the BSi fluxes (Fig. 7b). In general, a larger
(smaller) Cape Blanc filament area has been associated with higher (lower)
BSi fluxes (Fig. 7b) and also with higher total mass fluxes (not shown).
However, in winter of 2004–2005 (a relatively cold season with negative SST
anomalies), the filament area was smaller and chlorophyll standing stock was
lower (Figs. 6d, 7b). Nevertheless, BSi fluxes were the highest of the entire
record. The seasonal variability of chlorophyll from the entire SeaWiFS
record (1997–2010, Fig. 6d) indicates no relationship between the
chlorophyll standing stock and deep ocean BSi flux (or organic carbon flux,
not shown). These observations point to additional regulators for organic
carbon and BSi export to the deep sea. Ocean colour imagery even revealed a
decreasing trend from 1997 to 2010 (Fig. 6d), which suggests a decrease in
upwelling. This is not consistent with the “Bakun upwelling intensification
hypothesis” (Bakun, 1990) nor with studies from Kahru and Mitchell (2008).
Throughout 2005, however, the positive BSi flux anomalies corresponded well
with positive dust flux anomalies (Figs. 6b, 8b). As seen from Aerosol
Optical Thickness (AOT, Fig. 8c), dust availability was rather high in 2005
and corresponded to high dust sedimentation in summer and autumn 2005 (Fig. 8;
see Sect. 5.3). We suggest, therefore, that the linear relationship between
the NAO index and BSi fluxes may be biased in years of anomalous dust input
into the surface ocean.
(a) Seasonal flux of total carbonate (blue) with gaps
filled from the upper trap data (light blue bars). Deviations from the
long-term seasonal means (anomalies, b). (c) Seasonal flux
of pteropods. During the strongest ENSO cycle 1997–2000, longer periods of
low and high carbonate fluxes occurred. Note the episodic sedimentation
pattern of pteropods with maxima e.g. in summer 1998, 2002 and 2004. The
strong ENSO cycle 1997–1999 with a warm El Niño and a cold La Niña
phase is indicated.
Interaction between mineral dust and the biological pump
Fischer and Karakas (2009) stated that particle settling rates and organic
carbon fluxes in the Canary Current system were unusually high compared to
other EBUEs. This was mainly attributed to particle loading by dust particles
(see also Fischer et al., 2009a, b; Iversen et al., 2010). BSi and lithogenic
(mineral dust) fluxes point to a close linear relationship
(R2= 0.78, N= 21, Fig. 9a) mainly in winter where dust
availability and deposition is high (Goudie and Middleton, 2001), but not in
summer (R2= 0.56, N= 23, Fig. 9b). High supply of dust into the
surface ocean is often associated with dry conditions in the Sahel/Sahara in
the previous year (Engelstaedter et al., 2006; Prospero and Lamb, 2003;
Moulin and Chiapello, 2004). Indeed, the interval 2002–2004 in particular is
known to have been much warmer and drier during summer/autumn on land and in
the ocean (Zeeberg et al., 2008; Alheit et al., 2014). These conditions might
have allowed the later wind-induced mobilization of larger amounts of dust
particles into the atmosphere and led to a dust-enriched atmosphere during
the entire year 2005, combined with elevated deep ocean mass fluxes.
Typically, highest dust flux off Cape Blanc occurs in winter (Fig. 8) whereas part of the summer dust load is transported further westward and deposited
in the Caribbean Sea (Goudie and Middleton, 2001; Prospero and Lamb, 2003).
However, the rainfall pattern exhibits elevated precipitation in summer and
autumn 2005 when the tropical rainbelt was far north; this might have led to
unusual wet deposition of dust in summer over our study site (Friese et al.,
2016). As shown earlier, BSi fluxes show positive anomalies in summer and
autumn 2005 (Fig. 6b), pointing to a stronger dust-influenced biological pump.
In contrast to BSi, winter sedimentation of mineral dust did not show any
common trend with the winter NAO index (not shown). Using satellite-derived
AOT, Chiapello et al. (2005) suggested a close relationship of atmospheric
dust content and the NAO index. High AOT, however, does not necessarily
correspond with high dust deposition into the ocean. Moreover, dust
deposition into the ocean surface does not unavoidably and directly result in
particle export and transfer to the deep ocean. Dust deposition is not only
controlled by wind strength and direction in the trap area but also by source
region conditions and precipitation over the trap site. Consequently,
considering the NAO as the only controlling factor for dust deposition and
sedimentation even if the correlation between SLP (and thus winds) and NAO is
strong in the study area (Fig. 3a), would be an oversimplification.
Another explanation for the missing relationship could be that fine-grained
dust accumulates in surface waters until the biological pump produces
sufficient organic particles to allow the formation of larger particles which
then settle into the deep ocean (Bory et al., 2002; Ternon et al., 2010;
Nowald et al., 2015). Cape Blanc dust particles have predominant grain sizes
between 10 and 20 µm (Ratmeyer et al., 1999a, b; Friese et al.,
2016) and, thus, would sink too slowly to build a deep ocean flux signal. We
propose that only the close coupling between the organic carbon pump, dust
particles and the formation of dense and larger particles led to elevated
export and sedimentation (Bory et al., 2002; Fischer et al., 2009a; Fischer
and Karakas, 2009). Thunell et al. (2007) found that organic carbon fluxes
strongly correlated with mineral fluxes in other upwelling-dominated
continental margin time series such as the Santa Barbara Basin located within
the California Current System. However, the detailed processes and
interaction between different groups of phytoplankton and types of ballast
minerals (e.g. quartz versus clay minerals etc.) are largely unknown and need
clarification. Laboratory experiments with different ballast minerals (e.g.
Iversen and Roberts, 2015) and measurements of organic carbon respiration and
particle settling rates suggest a significant influence of ballast minerals
on particle settling rates, carbon respiration and flux (Ploug et al., 2008;
Iversen and Ploug, 2010). In a time series study with optical measurements,
addressing particle characteristics (e.g. sizes) and using fluxes at the
nearby eutrophic sediment trap off Cape Blanc (CBeu), Nowald et
al. (2015) suggested an influence of dust outbreaks on particle sedimentation
down to 1200 m. Interestingly, settling organic-rich particles off Cape
Blanc were only around 1 mm in size during the two-year deployment from 2008
to 2010 (Nowald et al., 2015). Higher fluxes were mostly attributed to higher
numbers of small particles rather than to larger particle sizes during blooms
in the Cape Blanc area (Nowald et al., 2015).
Carbonate fluxes and potential ENSO teleconnections
Deep ocean total mass and carbonate fluxes (Figs. 5, 10) showed elevated
values over more than a year from summer 1998 to autumn 1999 during a La
Niña event, whereas BSi and dust fluxes showed positive anomalies of
shorter duration (autumn 1998 to spring 1999) (Fig. 6b). Investigating
SeaWiFS-derived ocean colour in the Mauritanian upwelling region, Pradhan et
al. (2006) obtained a link between the multivariate ENSO index, the strength
of upwelling and the chlorophyll standing stock (250 % increase) during
the 1998–1999 La Niña. They also observed that during the mature La
Niña phase in the Pacific Ocean, NW African trade winds increased in
winter–spring. Coincidentally, Helmke et al. (2005) obtained a more than
doubling of the deep ocean organic carbon fluxes in autumn 1998 to summer 1999
during the major La Niña phase.
We obtained positive carbonate flux anomalies with a longer duration in
summer 1998 to autumn 1999 and summer 2005 to spring 2006 (Fig. 10b). During
autumn 1998 (La Niña phase), the area of the Cape Blanc filament was
unusually large compared with autumn 1997 (El Niño phase) (Fig. 1d, e). The
contribution of major carbonate producers to total carbonate flux varied both
on seasonal and interannual timescales (Fischer et al., 2009a). These authors
observed that nannofossils contributed almost 95 % to carbonate
sedimentation in 1991 (a relatively cold year) but only 64 % in 1989 (a
relatively warm year). In the long term, nannofossils showed a rather low
seasonality. Among the calcareous microorganisms, pteropods had the strongest
seasonal signal which did not quite match the pattern of carbonate flux
(Fig. 10a, c). As previously observed by Kalberer et al. (1993), a possible
explanation is the high pteropod flux (mostly Limacina inflata) in
summer 1989 due to unusual high SSTs. In our record, we found distinct pulses
of pteropods in the summer seasons of 1998, 2002 and 2004 (Fig. 10c). In
particular, the peaks in 2002 and 2004 can be attributed to anomalously warm
conditions in the study area (Zeeberg et al., 2008; Alheit et al., 2014).
Here, a period of near-neutral NAO together with an almost permanent El
Niño phase during 2002–2004 might have acted in concert towards
weakening trade winds which allows a stronger influence of the warm and
northward flowing MC, supplying high amounts of pteropods from tropical
waters. In summary, ENSO may impact differently on different flux components.
Whereas an increase in pteropod fluxes is found during the El Niño phase,
La Niña induces an increase in total carbonate flux.
Decadal variability and potential trends in mass fluxes
Our records allow a first estimate of deep-ocean mass flux variations beyond
seasonal-to-interannual timescales. The “Bakun upwelling intensification
hypothesis” (Bakun, 1990) has been supported by other studies using
long-term SSTs, wind stress records or upwelling indices (e.g. Cropper et
al., 2014; Narayan et al., 2010). Kahru and Mitchell (2008) applied satellite
derived chlorophyll time series from SeaWiFS to conclude that chlorophyll
standing stock in major upwelling regions of the world oceans had increased
since September 1997. However, these records are rather short (1997–2006)
and started in an unusual period with the strongest ENSO ever reported
(1997–1998). In our record, no long-term trend in any mass flux component
from 1988 through 2012 is seen, which would indicate a long term increase or
decrease in the strength of coastal upwelling off Cape Blanc. The 1997–2010
chlorophyll time series from SeaWiFS (Fig. 6d) shows a decreasing standing
stock, which might indicate a decrease in the strength of coastal upwelling
in the Cape Blanc area. The upwelling indices used by Cropper et al. (2014)
showed a decreasing trend from 1980–2013 for the Mauritanian-Senegalese
upwelling zone (12–19∘ N), while observing some interdecadal
variability. All these observations together point to regional differences
within the upwelling system along the NW African coast (Cropper et al., 2014)
with respect to long-term trends in upwelling and chlorophyll standing stock.
According to these findings, only the southernmost weak permanent upwelling
zone (21–26∘ N) would be in concert with the “Bakun upwelling
intensification hypothesis”. Another implication is that trends detected
from near-surface data/indices are not necessarily reflected in changes of
deep-ocean mass fluxes and organic carbon sequestration. No evidence of
decreasing dust fluxes from the Sahara/Sahel is seen in our lithogenic (dust)
flux record (Fig. 8a), which might indicate “Saharan greening” and reduced
dust plumes during the past 2 decades (Zhao et al., 2010; Fontaine et al.
2011). Thus, mass flux patterns might be partly independent from chlorophyll
standing stock or the size of the Cape Blanc filament.
Long-term model simulations under present-climate boundary conditions allow
to study the linkages within the climate system on decadal timescales and
beyond. Climate modes such as the AMO are operating in this frequency band,
and a correlation between large-scale patterns of SLP and North Atlantic SST
(AMO) index (both lowpass-filtered for periods above 10 years, Fig. 3c)
suggests that even on these long timescales, climate modes such as the AMO
might impact on climate variables such as SLP, SST and wind patterns,
specifically through a weakening of the trade winds over the eastern Atlantic
during the AMO warm phase (Fig. 3c). This response of the winds to
low-frequency SST variations is consistent with earlier findings on
interdecadal Atlantic SST variability (Kushnir, 1994; Alexander et al.,
2014), and could influence the main characteristics of particle fluxes at our
study site (Fig. 5). However, as current particle flux records from sediment
traps only cover a few decades and cannot resolve AMO cycles with statistical
robustness, continuation of trap experiments are essential to capture all
relevant timescale variations. They will help to understand modern particle
settling rates and the interpretation of marine sediment records used in
paleoclimate reconstructions.
Summary and conclusions
In our study, we presented a sediment trap record from the Eastern Boundary
Upwelling Ecosystem area off Cape Blanc (Mauritania) for the period
1988–2012. Our major findings can be summarized as follows (also see
Table 4):
Winter BSi fluxes showed a trend of increasing values with an increasing
NAO Hurrell Index and the increasing Azores SLP as well. However, both
relationships are statistically insignificant.
Episodic BSi flux peaks occurred between 2000 and 2005 when the NAO was
neutral or negative. Dust outbreaks, followed by dry (winter) and wet
(summer) deposition (e.g. in 2005) into the ocean, might have modified the
efficiency of the biological pump and resulted in increased downward fluxes
(e.g. of BSi or organic carbon) which were not related to any large-scale
forcings.
Only the extreme 1997–1999 ENSO was documented clearly in the record,
with low fluxes for almost a year during the warm El Niño phase,
followed by high fluxes of almost a year during the following cold La
Niña phase.
In addition to episodic BSi fluxes, episodic peaks of pteropods occurred
in the summers 2002 and 2004 (Fig. 10c, Table 4). This occurred during a
neutral NAO phase and weakening trade winds, allowing a stronger influence
from tropical surface waters from the south via the Mauritanian Current (MC)
and an entrainment of Si-richer subsurface waters.
Teleconnections from ENSO and the NAO may have opposite effects on the NW
African upwelling (Fig. 3) with potential implications for deep ocean mass
fluxes. In particular, ENSO might confound the relationship between the NAO
and BSi fluxes.
Fluxes from 1988–2012 point to a long-term decadal variability,
probably related to the Atlantic Multidecadal Oscillation. However, the time
series record is too short to reproduce AMO cycles with statistical
robustness.
No long-term trend of any flux component was observed in the Mauritanian
upwelling off Cape Blanc and therefore does not support the “Bakun upwelling
intensification hypothesis” (Bakun, 1990; Cropper et al., 2014).
We found no evidence of an increasing/decreasing supply of dust and its
deposition off Mauritania between 1988 and 2012.
The long-term flux record allows insights into the influences of major
climatic oscillations such as the NAO and on particle export and transfer of
particles to the deep ocean and might help to evaluate how the ecosystem off
Mauritania could develop in the future. We have some indications that the
relationships between major Northern Hemisphere climate oscillations (e.g.
the NAO) and deep ocean mass fluxes are weakened by short-term ecosystem
perturbations, e.g. due to dust outbreaks, the latter probably leading to
episodic sedimentation pulses into the deep ocean. The complex processes of
the interaction of non-biogenic particles (e.g. different minerals within
dust, e.g. Iversen and Roberts, 2015) with organic materials produced by
photosynthesis, aggregate formation and disintegration in the epi- and
mesopelagic, particle characteristics (e.g. Nowald et al., 2015), settling
rates and remineralization require further process studies, combined with
laboratory experiments and different modelling approaches (e.g. particle
(dis-) aggregation, Karakas et al., 2009).
Additionally, our record provides information on potential long-term changes
or trends of mass fluxes which point to ecosystem changes or an
intensification/weakening of the NW African upwelling system in the study
area. Considering the present record of bulk fluxes of more than 2 decades, we have no indication of any long-term trend which might suggest a
fundamental ecosystem change or a regime shift (step-wise change) in this
important coastal upwelling ecosystem.
Data availability
Text data availalbility
The flux data shown in the tables of the manuscript and the sediment trap metadata will be made available under: www.pangaea.de.
Gerhard Fischer prepared the ms with contributions from the co-authors.
Oscar Romero investigated the diatom producers and contributed to the
discussion, Ute Merkel contributed the model simulations and the analysis,
Barbara Donner studied the carbonate producers, Morten Iversen and his group
did the dust experiments and provided unpublished results/observations,
Nico Nowald and Volker Ratmeyer
performed the optical observations and analysis of particles,
Götz Ruhland and Marco Klann designed the sediment trap experiments and
analysed the sediment trap samples, Gerold Wefer planned the entire program
and contributed to the discussion.
Acknowledgements
We are greatly indebted to the masters and crews of many expeditions
(Table 1). Many thanks also go to the chief scientists of the expeditions for
their support during the cruises and for the planning activities and
cooperations. We also would like to thank the Mauritanian, Moroccan and
German authorities for their help during the planning phases of the
expeditions. This work was only possible because of the long-term funding by
the Deutsche Forschungsgemeinschaft through the SFB 261 (The South Atlantic
in the Late Quaternary: Reconstruction of Mass Budget and Current Systems,
1989–2001) and the Research Center Ocean Margins. During about the last
decade, the study is supported by the Marum Excellence Cluster, “The Ocean
in the Earth System”. The model simulation done by Ute Merkel has been
performed at the supercomputer of the Norddeutscher Verbund für Hoch- und
Höchstleistungsrechnen (HLRN), Hannover, Germany. We thank the two
anonymous reviewers for helpful, fair and constructive comments and the
associate editor for handling the manuscript.
The article processing charges for this open-access
publication were covered by the University of Bremen. Edited by: J. Middelburg
References
Alexander, M. A., Kilbourne, K. H., and Nye, J. A.: Climate variability
during warm and cold phases of the Atlantic Multidecadal Oscillation (AMO)
1871–2008, J. Marine Syst., 133, 14–26, 2014.
Alheit, J., Licandro, P., Coombs, S., Garcia, A., Giráldez, A.,
Santamaría, M. T. G., Slotte, A., and Tsikliras, A. C.: Atlantic
Multidecadal Oscillation (AMO) modulates dynamics of small pelagic fishes and
ecosystem regime shifts in the eastern North and Central Atlantic, J. Mar.
Syst., 133, 88–102, 2014.
Arístegui, J., Barton, E. C., Álvarez-Salgado, X. A., Santos, A. M.
P., Figueiras, F. G., Kifani, S., Hernández-León, S., Mason, E.,
Machú,E., and Demarcq, H.: Sub-regional ecosystem variability in the
Canary Current upwelling, Prog. Oceanogr., 83, 33–48, 2009.
Armstrong, R. A., Lee, C., Hedges, J. I., Honjo, S., and Wakeham, S. G.: A
new mechanistic model of organic carbon fluxes in the ocean based on the
quantitative association of POC with ballast minerals, Deep-Sea Res. Pt. II,
49, 219–236, 2002.
Bakun, A.: Global climate change and intensification of coastal ocean
upwelling, Science, 247, 198–201, 1990.
Barton, E. D., Arístegui, J., Tett, P., Cantón, M.,
García-Braun, J., Hernández-León, S., Nykjaer, L., Almeida, C.,
Almunia, J., Ballesteros, S., Basterretxea, G., Escánez, J.,
García-Weill, L., Hernández-Guerra, A., López-Laatzen, F.,
Molina, P., Montero, M. F ., Navarro-Pérez, E., Rodriguez, J. M., van
Lenning, K., Vélez, H., and Wild, K.: Eastern Boundary of the North
Atlantic: northwest Africa and Iberia, in: The Global Coastal Ocean, Vol. 11,
edited by: Robinson, A. R. and Brink, K., John Wiley and Sons, New York,
Chichester, Weinheim, Brisbane, Singapore, Toronto, 29–67, 1998.
Behrenfeld, M. J. and Falkowski, P. G.: Photosynthetic rates derived from
satellite based chlorophyll concentration, Limnol. Oceanogr., 42, 1–20,
1997.
Behrenfeld, M. J., Randerson, J. T., McClain, C. R., Feldman, G. C., Los, S.
O., Tucker, C. J., Falkowski, P., Field, C. B., Frouin, R., Esaias, W. E.,
Kolber, D. D., and Pollack, N. H.: Biospheric primary production during an
ENSO transition, Science, 291, 2594–2597, 2001.
Bode, A., Alvarez-Ossorio, M. T., Cabanas, J. M., Miranda, A., and Varela,
M.: Recent trends in plankton and upwelling intensity off Galicia (NW Spain),
Prog. Oceanogr., 83, 342–350, 2009.
Bory, A. J. M. and Newton, P. P.: Transport of airborne lithogenic material
down through the water column in two contrasting regions of the eastern
subtropical North Atlantic Ocean, Global Biogeochem. Cy., 14, 297–315, 2000.
Bory, A., Dulac, F., Moulin, C., Chiapello, I., Newton, P. P., Guelle, W.,
Lambert, C. E., and Bergametti, G.: Atmospheric and oceanic dust fluxes in
the northeastern tropical Atlantic ocean: how close a coupling?, Ann.
Geophys., 20, 2067–2076, 2002.Bressac, M., Guieu, C., Doxaran, D., Bourrin, F., Desboeufs, K., Leblond, N.,
and Ridame, C.: Quantification of the lithogenic carbon pump following a
simulated dust-deposition event in large mesocosms, Biogeosciences, 11,
1007–1020, 10.5194/bg-11-1007-2014, 2014.Brust, J., Schulz-Bull, D. E., Leipe, T., Chavagnac, V., and Waniek, J. J.:
Descending particles: from the atmosphere to the deep ocean: A time series
study in the subtropical NE Atlantic, Geophys. Res. Lett., 38, L06603.
10.1029/2010GL045399, 2011.
Buesseler, K. O., Antia, A. A., Chen, M., Fowler, S. W., Gardner, W. D.,
Gustafsson, O., Harada, K., Michaels, A. F., Rutgers van der Loeff, M.,
Sarin, M., Steinberg, D. K., and Trull, T.: An assessment of the use of
sediment traps for estimating upper ocean particle fluxes, J. Mar. Res., 65,
345–416, 2007.
Carr, M.-E.: Estimation of potential productivity in Eastern Boundary
Currents using remote sensing, Deep-Sea Res. Pt. I, 49, 59–80, 2002.
Checkley Jr., D. M. and Barth, J. A.: Patterns and processes in the
California Current Systems, Prog. Oceanogr., 83, 49–64, 2009.Chiapello, I., Moulin, C., and Prospero, J. M.: Understanding the long-term
variability of African dust transport across the Atlantic as recorded in both
Barbados surface concentrations and large-scale Total Ozone Mapping
Spectrometer (TOMS) optical thickness, J. Geophys. Res., 110, D18S10,
10.1029/2004JD005132, 2005.
Collins, W. D., Bitz, C. M., Blackmon, M. L. Bonan, G. B., Bretherton, C. S.,
Carton, J. A., Chang, P., Doney, S. C., Hack, J. J., Henderson, T. B., Kiehl,
J. T., Large, W. G., McKenna, D. S., Santer, B. D., and Smith, R. D.: The
Community Climate System Model Version (CCSM3), J. Climate, 19, 2122–2143,
2006.
Cropper, T. E., Hanna, E., and Bigg, G. R.: Spatial and temporal seasonal
trends in coastal upwelling off Northwest Africa, 1981–2012, Deep-Sea Res.
Pt. II, 86, 94–111, 2014.
Diatta, S. and Fink, A. H.: Statistical relationship between remote climate
indices and West African monsoon variability, Int. J. Climatol., 34,
3348–3367, 2014.
Ducklow, H. W., Doney, S. C., and Steinberg, D. K.: Contributions of
long-term research and teim-sereis observations to marine ecology and
biogeochemistry, Annu. Rev. Mar. Sci., 1, 279–302, 2009.Dunne, J. P., Sarmiento, J. L., and Gnanadesikan, A.: A synthesis of global
particle export from the surface ocean and cycling through the ocean interior
and on the seafloor, Global Biogeochem. Cy., 21, GB4006,
10.1029/2006GB002907, 2007.
Engelstaedter, S., Tegen I., and Washington, R.: North African dust emissions
and transport, Earth Sci. Rev., 79, 73–100, 2006.Feldman, G.: NASA/Goddard Flight Space Center, Ocean Color Web,
http://oceancolor.gsfc.nasa.gov/cgi/l3?ctg=Standard&sen=A&prd=CHL_chlor_a&per=SN&date=21Jun2002&res=9km&num=24,
2015.Feldman, G.: NASA/Goddard Flight Space Center, Ocean Color Web,
http://oceancolor.gsfc.nasa.gov/cgi/l3/S19972641997354.L3m_SNAU_CHL_chlor_a_9km.png?,
2015.Fischer, G. and Karakas, G.: Sinking rates and ballast composition of
particles in the Atlantic Ocean: implications for the organic carbon fluxes
to the deep ocean, Biogeosciences, 6, 85–102, 10.5194/bg-6-85-2009,
2009.
Fischer, G. and Wefer, G.: Sampling, preparation and analysis of marine
particulate matter, in: The Analysis and Characterization of Marine
Particles, edited by: Hurd, D. C. and Spencer, D. W., Geophys. Monogr.
Serie., 63, 391–397, 1991.Fischer, G., Donner, B., Ratmeyer, V., Davenport, R., and Wefer, G.: Distinct
year-to-year particle flux variations off Cape Blanc during 1988–1991:
Relation to delta δ18O-deduced sea-surface temperatures and trade
winds, J. Mar. Res., 54, 73–98, 1996.
Fischer, G., Wefer, G., Romero, O., Dittert, N., Ratmeyer, V., and Donner,
B.: Transfer of particles into the deep Atlantic and the global Ocean:
control of nutrient supply and ballast production, in: The South Atlantic in
the Late Quaternary: Reconstruction of material budget and current systems,
edited by: Wefer, G., Mulitza, S., and Ratmeyer, V., Springer, Berlin,
Heidelberg, New York, 21–46, 2003.
Fischer, G., Karakas, G., Blaas, M., Ratmeyer, V., Nowald, N., Schlitzer, R.,
Helmke, P., Davenport, R., Donner, B., Neuer, S., and Wefer, G.: Mineral
ballast and particle settling rates in the coastal upwelling system off NW
Africa and the South Atlantic, 98, 281–298, 2009a.
Fischer, G., Reuter, C., Karakas, G., Nowald, N., and Wefer, G.: Offshore
advection of particles within the Cape Blanc filament, Mauritania: Results
from observational and modelling studies, Prog. Oceanogr., 83, 322–330,
2009b.
Fischer, G., Neuer, S., Davenport, R., Romero, O., Ratmeyer, V., Donner, B.,
Freudenthal, T., Meggers, H., and Wefer, G.: The Northwest African Margin, in:
Carbon and Nutrient Fluxes in Continental Margins: A Global Synthesis, edited
by: Liu, K. K., Atkinson, L., Quinones, R., and Talaue-McManaus, L., IGBP
Book Series, Springer, Berlin, 77–103, 2010.
Fontaine, B., Roucou, P., Gaetani, M., and Marteau, R.: Recent changes in
precipitation, ITCZ convection and northern tropical circulation over North
Africa (1979–2007), Int. J. Climatol., 31, 633–648, 2011.
Fréon, P., Barange, M., and Aristegui, J.: Eastern Boundary Upwelling
Ecosystems: integrative and comparative approaches, Prog. Oceanogr., 83,
1–14, 2009.
Friese, C., van der Does, M., Merkel, U., Iversen, M., Fischer, G., and
Stuut, J.-B.: Environmental factors controlling the seasonal variation in
particle size of modern Saharan dust deposited offshore Cape, Blanc, Aeolian
Res., in press, 2016.
Goudie, A. S. and Middleton, N. J.: Saharan dust storms: nature and
consequences, Earth Sci. Rev., 56, 179–204, 2001.
Hedges, J. I., Baldock, J. A., Gelinas, Y., Lee, C., Peterson, M. L., and
Wakeham, S. G.: The biochemical and elemental compositions of marine
plankton: a NMR perspective, Mar. Chem., 78, 47–63, 2002.Helmke, P., Romero, O., and Fischer, G.: Northwest African upwelling and its
effect on off-shore organic carbon export to the deep sea, Global
Biogeochem. Cy., 19, GB4015, 10.1029/2004GB002265, 2005.Hsu, N. C., Gautam, R., Sayer, A. M., Bettenhausen, C., Li, C., Jeong, M. J.,
Tsay, S.-C., and Holben, B. N.: Global and regional trends of aerosol optical
depth over land and ocean using SeaWiFS measurements from 1997 to 2010,
Atmos. Chem. Phys., 12, 8037–8053, 10.5194/acp-12-8037-2012, 2012.Hurrell, J. W.: NAO Index Data provided by the Climate Analysis Section,
NCAR, Boulder, USA, Updated regularly,
http://climatedataguide.ucar.edu/guidance/hurrell-north-atlantic-oscillation-nao-index-station-based
(last access: 01 January 2012), 1995.Hurrell, J.: National Center for Atmospheric Research, NCAR/UCAR Climate Data Guide,
https://climatedataguide.ucar.edu/climate-data/hurrell-north-atlantic-oscillation-nao-index-station-based,
2015.Ichoku, C.: NASA/Goddard Flight Space Center, NASA Earth Observatory, Global Maps,
http://earthobservatory.nasa.gov/GlobalMaps/?eocn=topnav&eoci=globalmaps,
2015.Iversen, M. H., and Ploug, H.: Ballast minerals and the sinking carbon flux
in the ocean: carbon-specific respiration rates and sinking velocities of
marine snow aggregates, Biogeosciences 7, 2613–2624,
10.5194/bg-7-2613-2010, 2010.
Iversen, M. H. and Robert, M. L.: Ballasting effects of smectite on aggregate
formation and export from a natural plankton community, Mar. Chem., 175,
18–27, 2015.
Iversen, M. H., Nowald, N., Ploug, H., Jackson, G. A., and Fischer, G.: High
resolution profiles of vertical particulate organic matter export off Cape
Blanc, Mauritania: degradation processes and ballasting effects, Deep-Sea
Res. Pt. I, 57, 771–784, 2010.
Jickells, T. D., An, Z. S., Andersen, K. K., Baker, A. R., Bergametti, G.,
Brooks, N., Cao, J. J., Boyd, P. W., Duce, R. A., Hunter, K. A., Kawahata,
H., Kubilay, N., laRoche, J., Liss, P. S., Mahowald, N., Prospero, J. M.,
Ridgwell, A. J., Tegen, I., and Torres, R.: Global iron connections between
desert dust, ocean biogeochemistry, and climate, Science, 308, 67–71, 2005.
Kahru, M. and Mitchell, B. G.: Ocean colour reveals increased blooms in
various parts of the world ocean, EOS, 89, p. 170, 2008.
Kalberer, M., Fischer, G., Pätzold, J., Donner, B., Segl, M., and Wefer,
G.: Seasonal sedimentation and stable isotope records of pteropods off Cape
Blanc, Mar. Geol., 113, 305–320, 1993.Karakas, G., Nowald, N., Blaas, M., Marchesiello, P., Frickenhaus, S., and
Schlitzer, R.: High-resolution modeling of sediment erosion and particle
transport across the northwest African shelf, J. Geophys. Res., 111. C06025,
10.1029/2005JC003296, 2006.
Karakas, G., Nowald, N., Schäfer-Neth, C., Iversen, M. H., Barkmann, W.,
Fischer, G., Marchesiello, P., and Schlitzer, R.: Impact of particle
aggregation on vertical fluxes of organic matter, Prog. Oceanogr., 83,
331–341, 2009.Kempler, S. J.: NASA/Goddard Flight Space Center, GIOVANNI,
http://giovanni.sci.gsfc.nasa.gov/giovanni/?instance_id=ocean_month,
2015.Kaufman, Y. J., Koren, I., Remer, L. A., Tanré, D., Ginoux, P., and Fan,
S.: Dust transport and deposition from the Terra-Moderate Resolution Imaging
Spectroradiometer (MODIS) spacecraft over the Atlantic Ocean, J. Geophys.
Res., 110, D10S12, 10.1029/2003JD004436, 2005.Klaas, C. and Archer, D. E.: Association of sinking organic matter with
various types of ballast in the deep sea: Implications for the rain ratio,
Global Biogeochem. Cy., 16, 1116, 10.1029/2001GB001765, 2002.
Kremling, K., Lentz, U., Zeitzschell, B., Schulz-Bull, D. E., and Duinker, J.
C.: New type of time-series sediment trap for the reliable collection of
inorganic and organic trace chemical substances, Rev. Scient. Instr., 67,
4360–4363, 1996.
Kushnir, Y.: Interdecadal variations in North Atlantic sea surface
temperature and associated atmospheric conditions, J. Climate, 7, 141–157,
1994.Lathuilière, C., Echevin, V., and Levy, M.: Seasonal and intraseasonal
surface chlorophyll-a variability along the northwest African coast, J.
Geophys. Res.-Ocean., 13, C05007, 10.1029/2007JC004433, 2008.
Lucio, P. S., Baldicero Molion, L. C., de Avial-Valadão, C. E., Conde, F.
C., Malheiro Ramos, A., and Dias de Melo, M. L.: Dynamical outlines of the
rainfall variability and the ITCZ role over the West Sahel, Atmos. Clim.
Sci., 2, 337–350, 2012.
Marcello, J., Hernandez-Guerra, A., Eugenio, F., and Fonte, A.,: Seasonal and
temporal study of the northwest African upwelling system, Int. J. Remote
Sens., 32, 1843–1859, 2011.
McGregor, H. V., Dima, M., Fischer, H. W., and Mulitza, S.: Rapid 20th
century increase in coastal upwelling off Northwest Africa, Science, 315,
637–639, 2007.Meunier, T., Barton, E. D., Barreiro, B., and Torres, R.: Upwelling filaments
off Cape Blanc: interaction of the NW African upwelling current and the Cape
Verde frontal zone eddy field?, J. Geophys. Res.-Ocean., 117, C08031,
10.1029/2012JC007905, 2012.
Mittelstaedt, E.: The ocean boundary along the northwest African coast:
Circulation and oceanographic properties at the sea surface, Prog. Oceanogr.,
26, 307–355, 1991.Moulin, C. and Chiapello, I.: Evidence of the control of summer atmospheric
tansport of African dust over the Atlantic by Sahel sources from TOMS
satellites (1979–2000), Geophys. Res. Lett., 31, L02107,
10.1029/2003GL019031, 2004.
Müller, P. J. and Schneider, R.: An automated leaching method for the
determination of opal in sediments and particulate matter, Deep-Sea Res. Pt.
I, 40, 425–444, 1993.Muller-Karger, F. E., Varela, R., Thunell, R., Luerssen, R., Hu, C., and
Walsh, J. J.: The importance of continental margins in the global carbon
cycle, Geophys. Res. Lett., 32, L01602, 10.1029/2004GL021346, 2005.Narayan, N., Paul, A., Mulitza, S., and Schulz, M.: Trends in coastal
upwelling intensity during the late 20th century, Ocean Sci., 6, 815–823,
10.5194/os-6-815-2010, 2010.Neuer, S., Torres-Padron, M.E., Gelado-Caballeo, M.D., Rueda, M.J.,
Hernandez-Brito, J., Davenport, R., and Wefer, G.: Dust deposition to the
eastern subtropical North Atlantic gyre: Does ocean's biogeochemistry
respond?, Global Biogeochem. Cy., 18, GB4020, 10.1029/2004GB002228, 2004.Nicholson, S. E.: The West African Sahel: A review of recent studies on the
rainfall regime and its interannual variability, ISRN Meteorology, 2013,
453521, 10.1155/2013/453521, 2013.
Nowald, N., Iversen, M. H., Fischer, G., Ratmeyer, V., and Wefer, G.: Time
series of in-situ particle properties and sediment trap fluxes in the coastal
upwelling filament off Cape Blanc, Mauritania, Prog. Oceanogr. Pt. A, 137,
1–11, 2015.
N'Tchayi Mbourou, G., Berrand, J. J., and Nicholson, S. E.: The diurnal and
seasonal cycles of wind-borne dust over Africa north of the equator, J. Appl.
Meteorol., 36, 868–882, 1997.
Nykjaer, L. and Van Camp, L.: Seasonal and interannual variability of coastal
upwelling along northwest Africa and Portugal from, 1981 to 1991, J. Geophys.
Res., 99, 197–207, 1994.
Pauly, D. and Christensen, V.: Primary production required to sustain global
fisheries, Nature, 374, 255–257, 1995.
Ploug, H., Iversen, M. H., and Fischer, G.: Ballast, sinking velocity, and
apparent diffusivity within marine snow and zooplankton fecal pellets:
implications for substrate turnover by attached bacteria, Limnol. Oceanogr.,
53, 1878–1886, 2008.
Pradhan, Y., Lavender, S. J., Hardman-Mountford, N. J., and Aiken, J.:
Seasonal and inter-annual variability of chlorophyll-a concentration in the
Mauritanian upwelling: observation of an anomalous event during 1998–1999,
Deep-Sea Res. Pt. II, 53, 1548–1559, 2006.
Prospero, J. M.: Mineral-aerosol transport to the North Atlantic and North
Pacific: The impact of African and Asian sources, in: The long range
atmospheric transport of natural and contaminant substances, edited by: Knap,
A. H., Dordrecht, Mathematical and Physical Sciences, Kluwer Academic
Publishers, 19–52, 1990.
Prospero, J. M. and Lamb, P. J.: African droughts and dust transport to the
Caribbean: climate change implications, Science, 302, 1024–1027, 2003.
Ratmeyer, V., Fischer, G., and Wefer, G.: Lithogenic particle fluxes and
grain size distributions in the deep ocean off northwest Africa: Implications
for seasonal changes of aeolian dust input and downward transport, Deep-Sea
Res. Pt. II, 46, 1289–1337, 1999a.
Ratmeyer, V., Balzer, W., Bergametti, G., Chiapello, I., Fischer, G., and
Wyputta, U.: Seasonal impact of mineral dust on deep-ocean particle flux in
the eastern subtropical Atlantic Ocean, Mar. Geol., 159, 241–252, 1999b.
Redfield, A. C., Ketchum, B. H., and Richards, F. A.: The influence of
organisms on the composition of seawater, in: The Sea, edited by: Hill, M.
N., Wiley and Sons, Chichester, 2, 26–77, 1963.
Romero, O. E., Lange, C. B., Swap, R. J., and Wefer, G.: Eolian-transported
freshwater diatoms and phytoliths across the equatorial Atlantic record
temporal changes in Saharan dust transport patterns, J. Geophys. Res., 104,
3211–3222, 1999.
Romero, O. E., Lange, C. B., and Wefer, G.: Interannual variability
(1988–1991) of siliceous phytoplankton fluxes off northwest Africa, J.
Plank. Res., 24, 1035–1046, 2002.Romero, O. E., Kim, J.-H., and Donner, B.: Submillennial-to-millennial
variability of diatom production off Mauritania, NW Africa, during the last
glacial cycle, Paleoceanography, 23, PA3218, 10.1029/2008PA001601, 2008.
Shanahan, T. M., Overpeck, J. T., and Anchukaitis, K. J., Beck, J. W., Cole,
J. E., Dettman, D. L., Peck, J. A., Scholz, C. A., and King, J. W.: Atlantic
Forcing of persistent drought in West Africa, Science, 324, 377–380, 2009.
Siegel, D. A. and Deuser, W. G.: Trajectories of sinking particles in the
Sargasso Sea: modeling of statistical funnels above deep-ocean sediment
traps, Deep-Sea Res. Pt. I, 44, 1519–1541, 1997.Stokes, D. C.: NOAA, IRI/LDEO Climate Data Library,
http://iridl.ldeo.columbia.edu/filters/.NINO/SOURCES/.NOAA/.NCEP/.EMC/.CMB/.GLOBAL/.Reyn_SmithOIv2/.monthly/.ssta/,
2015.Ternon, E., Guieu, C., Loÿe-Pilot, M.-D., Leblond, N., Bosc, E., Gasser,
B., Miquel, J.-C., and Martín, J.: The impact of Saharan dust on the
particulate export in the water column of the North Western Mediterranean
Sea, Biogeosciences, 7, 809–826, 10.5194/bg-7-809-2010, 2010.Thunell, R., Benitez-Nelson, C., Varela, R., Astor, Y., and Muller-Karger,
F.: Particulate organic carbon fluxes along upwelling-dominated continental
margins: rates and mechanisms, Global Biogeochem. Cy., 21, GB1022,
10.1029/2006GB002793, 2007.
US Department of Commerce: NOAA Earth System Research Laboratory,
http://www.esrl.noaa.gov/psd/data/timeseries/AMO/, 2015.
Van Camp, L., Nykjær, L., Mittelstaedt, E., and Schlittenhardt, P.:
Upwelling and boundary circulation off Northwest Africa as depicted by
infrared and visible satellite observations, Prog. Oceanogr., 26, 357–402,
1991.
Yeager, S. G., Shields, C. A., Large, W. G., and Hack, J. J. : The
Low-Resolution CCSM3, J. Climate, 19, 2545–2566, 2006.Yu, E. F., Francois, R., Honjo, S., Fleer, A. P., Manganini, S. J., Rutgers
van der Loeff, M. M., and Ittekkot, V.: Trapping efficiency of
bottom-tethered sediment traps estimated from the intercepted fluxes of
230Th and 231Pa, Deep-Sea Res. Pt. I, 48, 865–889, 2001.Zeeberg, J., Corten, A., Tjoe-Awie, P., Coca, J., and Hamady, B.: Climate
modulates the effects of Sardinella aurita fisheries of Northwest
Africa, Fish. Res., 89, 65–75, 2008.
Zenk, W., Klein, B., and Schroder, M.: Cape Verde Frontal Zone, Deep-Sea Res.
Pt. I, 38, 505–530, 1991.Zhao, T. X.-P., Laszlo, I., Guo, W., Heidinger, A., Cao, C., Jelenak, A.,
Tarpley, D., and Sullivan, J.: Study of long-term trend in aerosol optical
thickness observed from operational AVHRR satellite instrument, J. Geophys.
Res., 113, D07201, 10.1029/2007JD009061, 2008.