ARTICLESPUBLISHED ONLINE: 2 OCTOBER 2011 | DOI: 10.1038/NGEO1273
Eddy-induced reduction of biological production ineastern boundary upwelling systemsNicolas Gruber1*, Zouhair Lachkar1, Hartmut Frenzel2, Patrick Marchesiello3, Matthias Münnich1,James C. McWilliams2,4, Takeyoshi Nagai5 and Gian-Kasper Plattner1†
Eddies and other mesoscale oceanic processes, such as fronts, can enhance biological production in the ocean, according toseveral open-ocean studies. The effect is thought to be particularly pronounced in low-nutrient environments, where mesoscaleprocesses increase the net upward flux of limiting nutrients. However, eddies have been suggested to suppress productionin the highly productive eastern boundary upwelling systems. Here, we examine the relationship between satellite-derivedestimates of net primary production, of upwelling strength, and of eddy-kinetic energy—a measure of the intensity ofmesoscale activity—in the four most productive eastern boundary upwelling systems. We show that high levels of eddyactivity tend to be associated with low levels of biological production, indicative of a suppressive effect. Simulations usingeddy-resolving models of two of these upwelling systems support the suggestion that eddies suppress production, and showthat the downward export of organic matter is also reduced. According to these simulations, the reduction in production andexport results from an eddy-induced transport of nutrients from the nearshore environment to the open ocean. Eddies mighthave a similar effect on marine productivity in other oceanic systems that are characterized by intense eddy activity, such asthe Southern Ocean.
Over most of the ocean, primary production byphytoplankton is limited by the availability of nutrients,a consequence of the high efficiency with which the
phytoplankton strip these nutrients out of the surface ocean to fueltheir growth1,2. A fraction of these organically bound nutrients isexported to depth where they are eventually remineralized back totheir inorganic forms. The combined result of these processes isthe generation of a very depleted reservoir of inorganic nutrientsin the euphotic zone near the surface, whereas this reservoir isenriched in the aphotic zone at depth. This gives the physicalprocesses that resupply these nutrients to the euphotic zone adominant role in controlling primary production in the ocean3.In fact, most of the global ocean distribution of production can beunderstood by the strength of this vertical exchange4. Places wherenutrients are efficiently transported back, such as coastal upwellingregions, are highly productive, whereas regions where this transportis restricted, such as the vast subtropical gyres, tend to have lowbiological productivity1,5.
Role of eddies for productivityIt has been suggested that eddies and other mesoscale andsubmesoscale phenomena such as fronts, play an important rolein supplying nutrients to the euphotic zone, particularly inlow-nutrient environments characterized by stably stratified anddownwelling conditions6–12. The productivity enhancing effect inthese regions is thought to be a result of the undulation of nutrientisosurfaces that is associated with the eddies: shoaling surfaces tendto expose nutrients to the euphotic zone, where they are rapidlyconsumed, whereas deepening surfaces lead to no change. Thenet result is a ‘rectified’ transport of nutrients into the euphotic
1Environmental Physics, Institute of Biogeochemistry and Pollutant Dynamics, ETH Zurich, Zurich 8092, Switzerland, 2Department of Atmospheric andOceanic Sciences, UCLA, Los Angeles, California 90095, USA, 3Institut de Recherche pour le Développement, LEGOS, 31400 Toulouse, France, 4Instituteof Geophysics and Planetary Physics, UCLA, Los Angeles, California 90095, USA, 5Tokyo University of Marine Science and Technology, Tokyo 108-8477,Japan. †Present address: Climate and Environmental Physics, University of Bern, Bern 3012, Switzerland. *e-mail: [email protected].
zone. Observations from low-nutrient environments tend tosupport this ‘eddy pumping’ hypothesis7,11,12, although the overallmagnitude and the exact mechanisms are still controversial3,13,14.This concept of eddies and other mesoscale processes generallyenhancing biological productivity has recently been challenged bythe suggestion that these processes could have a reducing effectin eastern boundary upwelling systems (EBUS; refs 15,16). EBUS,such as the California Current System (CalCS), the Canary CurrentSystem (CanCS), the Humboldt Current System, and the BenguelaCurrent System belong to the most productive systems on Earthand support up to 20% of global fish catch17,18. This finding ofa reducing effect emerged from a correlation analysis betweensurface chlorophyll, taken here as a metric for productivity, and themagnitude of lateral stirring, interpreted as a metric for the levelof eddy activity15,16. This finding is counterintuitive, as individualeddies in EBUS tend to have higher biomass and productivity thansurrounding waters19,20.
Here, we first revisit the relationship between eddies andbiological production across all four major EBUS to show thathigh eddy activity indeed tends to be associated with unusuallylow biological production, that is, that eddies and other mesoscaleprocesses have a suppressing effect. We then employ an eddy-resolving model of the CalCS to confirm this finding and toinvestigate the processes underlying it. We will demonstrate thatthis suppressing effect is a consequence of mesoscale processesinducing a net lateral transport of the limiting nutrients from thenearshore region to the offshore. This leakage strongly reducesthe inventory of these nutrients in the waters that later upwell,leading to a lower supply of the primary factor limiting biologicalproduction. Further model simulations using an analogous set-up
Figure 1 | Relationship of observationally based estimates of NPP to upwelling strength and EKE in the four major EBUS. a, Relationship ofEKE-normalized NPP to upwelling strength. b, Relationship of upwelling strength normalized NPP to EKE. NPP was normalized by first fitting it to a multiplelinear regression model with upwelling strength and EKE as independent variables, and then using the respective coefficients (shown in the plots as well forthe case where data from all EBUS were used) to remove the effect of the other independent variable from the data. The lines represent the projection ofthe multiple linear regression model to the normalized data.
of the CanCS support these key findings and suggest a broaderapplicability (see Supplementary Information).
Satellite analyses across all EBUSTo uncover the impact of eddies and other mesoscale processeson primary production across all four major EBUS, we usesatellite-inferred net primary production (NPP) and investigateits relationship with the magnitude of Ekman-driven upwellingand the level of eddy-kinetic energy (EKE), a direct measureof the number and intensity of mesoscale phenomena (seeMethods and Supplementary Information for details). A multiplelinear regression analysis of annual mean NPP as a functionof upwelling strength and EKE, averaged over 4◦ meridionalintervals and between the shore and 500 km (except for EKE, seeMethods) reveals that upwelling strength is clearly the dominantfactor, explaining nearly 50% of the total variance in NPP. Thissupports the canonical perspective of productivity in EBUS beingprimarily controlled by the magnitude of the upwelling favourablewinds21–24. The regression analysis also shows that variationsin EKE can explain an additional significant fraction of NPP(∼15%; Fig. 1)—a fraction that is higher than that explained byseveral other potential explanatory variables, such as sea surfacetemperature (SST; not shown).
The relationship between NPP and EKE is not really linear,however, particularly as the residuals of the fit vary strongly withEKE. Although regions of elevated EKE are clearly associated withlow NPP (Fig. 1b), the relationship is weak at low EKE. Thus, itmight be more appropriate to consider EKE as a limiting factor,which progressively prevents high levels of NPP as EKE increases.This perspective may also help to explain the lack of a significantnegative relationship in most EBUS if they are analysed separately,as such a relationship appears only when a sufficiently large set ofobservations are analysed. A further potential reason for the lack of atrend within each EBUS is their low range of EKE, which makes thestatistical detection of a trend challenging. Thus, and particularlywhen taking into account that each 4◦ bin can be considered as anindependent sample, the absence of a relationship in a particularregional subset cannot be regarded as a falsification of an overallnegative relationship between NPP and EKE across all EBUS. Thisinterpretation is supported by the data from the CalCS, whichshow a clear trend congruent with the overall slope defined by thedata from all EBUS. Thus, although it has a substantial amount ofscatter, we regard the negative relationship between NPP and EKEas statistically robust. Nevertheless, unless we can clearly explain theprocesses underlying this relationship, it remains inconclusive.
Modelling the California and Canary current systemsWe investigate the processes underlying this result usingsimulations and analyses of a coupled physical–biogeochemical–ecological model of the CalCS (ref. 25; see Methods) and supportit with results from the CanCS (ref. 26). The physical model, basedon the Regional Oceanic Modelling System27, was configured forboth systems at a fully eddy-resolving horizontal resolution of5 km. The biogeochemical/ecological model consists of a nutrient–phytoplankton–zooplankton–detritus (NPZD) model that wasadapted for the upwelling conditions of the two systems25,26. Theannual and seasonal mean distributions of the model-simulatedproperties compare favourably with several observational con-straints (see Supplementary Information), suggesting that thedegree of realism of the model is sufficient for the purposeof our experiments.
We use two independent approaches to determine the roleof eddies and other mesoscale processes in this model, that is,(1) we compare simulations with varying resolution, benefitingfrom the fact that the level of eddy activity increases stronglywith increasing resolution28, and (2) we compare our standardsimulation with one where we modified the model’s physicsin such a way that the generation of mesoscale variations issuppressed (see Methods and Supplementary Information fordetails). The latter is accomplished by setting the nonlinearterms in the momentum equation to zero. The former approachhas been used successfully in the past (for example ref. 29),but has the downside that the resolution not only alters thelevel of eddy activity, but potentially also the structure of thelarge-scale circulation and upwelling. The latter novel methodavoids many of these problems, as it maintains the large-scalegeostrophic transport and the offshore Ekman transport fromthe full physics model. A potential downside is that the sink formomentum normally supplied by the eddy-generated dissipationis compensated by grid-level ‘noise’.
The simulations for the CalCS show a very substantialsuppressing effect of eddies on primary production and exportproduction (Table 1). The non-eddy and 60 km resolutionsimulations exhibit throughout the CalCS similar overallreductions, of the order 50–70% for NPP and 35–50% for organiccarbon export. The largest reductions occur in the region between100 and 500 km (Fig. 2), where eddies seem to suppress NPPby 70 to 80% and export production by 45 to 60% (Table 1).Further offshore the trend changes sign, with the simulationsthat include eddies exhibiting higher production and export(Fig. 2). Further simulations with a resolution of 15 km, and with
Table 1 | Primary production and organic carbon export for different offshore regions of the CalCS (34◦ N–42◦ N).*
Simulation 0–100 km 100–500 km 500–1,000 km 0–1,000 km
Net primary production (mol C m−2 yr−1)
5 km eddy (standard) 23.0 8.1 1.7 6.05 km non-eddy 31.7 14.6 1.0 8.9Difference (eddy—non-eddy) −8.7 (−38%) −6.6 (−81%) 0.6 (38%) −2.9 (−49%)60 km 27.4 14.0 4.5 10.0Difference (eddy—60 km) −4.5 (−19%) −5.9 (−73%) −2.9 (−173%) −4.0 (−68%)
Organic carbon export (mol C m−2 yr−1)
5 km eddy (standard) 6.1 2.9 0.8 2.15 km non-eddy 8.4 4.7 0.4 2.8Difference (eddy—non-eddy) −2.3 (−38%) −1.8 (−60%) 0.3 (43%) −0.7 (−34%)60 km 6.1 4.2 1.8 3.1Difference (eddy—60 km) 0.0 (0%) −1.3 (−45%) −1.0 (−134%) −1.0 (−48%)
*See Fig. 2 for boundaries. The areas are as follows: 0–100 km: 96,656 km2 ; 100–500 km: 420,602 km2 ; 500–1,000 km: 588,201 km2 .
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Figure 2 |Modelled impact of eddies on the distribution of primary and export production in the CalCS. Maps of model-simulated depth integratedprimary production (a–c) and of organic carbon export (across 100 m) (d–f), in units of mol C m−2 yr−1. a,d, Results from the non-eddy simulation (seetext for details) colour scales as for b and e, respectively. b,e, Results from the eddy simulation. c,f, Difference between the eddy and the non-eddy cases.Also shown in c and f are the 100 km, 500 km, and 1,000 km offshore regions over which budgets were analysed.
a resolution of 5 and 15 km, but with the topography of the60 km set-up, have NPP and exports in between the eddy andnon-eddy cases, consistent with their EKE also lying in betweenthe two endmembers (Supplementary Information). In fact, NPPand export production scale nearly linearly with EKE across allof our CalCS simulations (Supplementary Fig. S.8), giving usconfidence that we are capturing the net effect of eddies with ourtwo modelling approaches in a similar fashion. Simulation resultsfrom an analogous set of set-ups of the CanCS (ref. 26) demonstratethat the same negative trend with EKE occurs in that EBUS as well(Supplementary Fig. S.8), despite it having substantially lower EKE,on average (Fig. 1).
Mechanisms of eddy-induced reduction in productionThe mechanisms responsible for the reduction in production andexport can be deduced by inspecting vertical sections extendingfrom the US west coast in the offshore direction (Fig. 3). It becomesevident that this reduction is a direct consequence of a strongeddy-induced decrease in the nitrate content of the entire nearshore∼500 km of the CalCS, extending deep into the pycnocline (Fig. 3f).In contrast, the eddies increase the nitrate content of the upperpycnocline beyond about ∼500 km. Consistent with the decreasein nearshore productivity, the organic carbon concentration is alsolower in response to the eddies, whereas the offshore concentrationsare elevated (Fig. 3i).
Figure 3 |Vertical distribution of modelled density, nitrate, and total organic matter along offshore sections. Sections of a–c potential density (kg m−3),d–f, nitrate (mmol m−3), g–i, total organic carbon (mmol m−3) with the left column showing the non-eddy case, the middle column the eddy case, and theright column the difference between the eddy and non-eddy cases. The sections represent average conditions over a 100 km swath starting in MontereyBay (37◦ N, 121.8◦W) and extending to about 33.7◦ N, 132◦W, nearly 1,000 km into the open ocean. Colour scales for a,d and g are as for b,eand h, respectively.
These changes can be understood best by the lateral circulationand mixing that eddies cause in upwelling systems28,30,31. In suchsystems, eddies tend to induce a shoreward advective and diffusiveheat transport in the near-surface layer, bringing heat and buoyancytowards the shore, leading to a flattening of the isopycnal surfaces(Fig. 3a–c), similar to what occurs on the flanks of subtropicalgyres32. A second consequence of the eddies is the sharpening ofthe upwelling front, which we find at about 100–300 km from theshore in ourmodel, causing convergence and associated subductionthere33,34 (T. Nagai et al. manuscript in preparation). The impactof these eddy-induced physical changes on the nitrogen transportcan be revealed by a Reynolds decomposition, where the transportis decomposed into one part that is driven by the mean flowand another part that is driven by the time-varying, eddy-inducedtransport (see Supplementary Information).
An offshore section of the eddy-induced horizontal flux of totalfixed nitrogen reveals the expected high level of eddy-inducedtransport in the near-surface ocean within the nearshore 100 kmassociated with ephemeral mesoscale processes such as filaments(Fig. 4). Between about 100 and 300 km from shore, the near-surface offshore transport by eddies weakens, but a substantialamount of subduction occurs, removing total fixed nitrogen fromthe near-surface ocean (Fig. 4a). The subducted total nitrogen istransported further offshore by eddies, (T. Nagai et al. manuscriptin preparation), with the maximum eddy-induced offshore fluxoccurring at a distance between 150 and 400 km from the shoreand at depths of around 100m (Fig. 4b). Most of this offshoreflux occurs in the form of nitrate, although all fixed nitrogencomponents contribute to it. The joint effect of the eddy-inducedsubduction and the subsequent eddy-induced offshore transportis to remove inorganic and organic nutrients from the nearshoreand to enrich the offshore region of the CalCS (Fig. 3f,i), enhancingproductivity there35,36. This loss results in less nutrients beingupwelled, which then supports less primary production, leading
to less export of organic nutrients. The diminished export leadsto a smaller amount of organic nutrients being remineralized inthe water column and sediments and consequently less inorganicnutrients being added to the waters that are the source ofthe upwelling, generating a further drop in production andexport (Fig. 4c). Support of this interpretation comes from theobservation that the CalCS has, on average, substantially lowernitrate concentrations in the upper thermocline in the nearshoreenvironment comparedwith the other EBUS (refs 24,37), consistentwith the CalCS having the highest EKE.
The reduction of the nutrient inventory in the nearshoreregions is overall well co-localized with the regions of high EKE(Supplementary Fig. S.10), but the reduction extends beyond theregions ofmost intense eddy activity, leading to lower than expectedprimary production also in neighbouring regions with low EKE.This could flatten the relationship between primary production andEKE in our statistical analyses, because it would smooth meridionalgradients in NPP, whilst leaving EKE unaffected. However, themagnitude of this effect would be highly dependent on the regionalcharacteristics. Nevertheless, this may explain, in part, why theslope of the relationship between primary production and EKE isflatter within most of the EBUS when compared with the trendlinecomputed from the data from all EBUS (Fig. 1b).
Overall, the satellite data analyses and the modelling studiestogether provide strong evidence for a reducing effect of eddieson primary and export production in EBUS. We also identifiedan eddy-driven lateral nutrient leakage from the nearshoreenvironment as the main mechanism, which is supported bytheoretical arguments and limited observations. However, it isclear from the substantial amount of still unexplained variance inNPP in EBUS that several further factors could be important aswell, possibly including shelf width26,38, mixed-layer depth, ironlimitation39 and other possible factors associated with the transientand variable nature of mesocale and submesoscale processes and
Figure 4 |Offshore sections illustrating the role of eddies in inducing alateral loss of total nitrogen (TN) from the CalCS. a, Eddy-induced verticalfluxes (w′ ·TN′ in nmol m−2 s−1 with w′ and TN′ being the time-varyingcomponents of the vertical velocity and total nitrogen, respectively).b, Eddy-induced horizontal fluxes (v′ ·TN′ in µmol m−2 s−1, with v′ being thetime-varying component of the zonal velocity). White lines in a and b showpotential density; black dashed lines indicate negative fluxes. c, Conceptualdiagram of the impact of mesoscale eddies on coastal circulation, nitrogentransport, and organic matter production and export. The thick linesindicate total nitrogen transports and the thin lines depict circulationpattern. Shown in blue are the Ekman-driven transports and circulations.The red arrows show the eddy-driven transports and (bolus) velocities.Contour lines denote potential density and green arrows the vertical exportof organic matter. The eddy-induced fluxes in a and b were determined by aReynolds decomposition (see Supplementary Information).
the nonlinear interactions between the physical environment andocean ecosystems14,40.
Eddies and other mesoscale phenomena are ubiquitous in theocean and tend to dominate the variance spectrum. Yet, theirimpact and role for ocean circulation, oceanic primary production,and ocean biogeochemistry is still being uncovered41. We haveadded here another impact of eddies on ocean biogeochemistry,primarily active in EBUS. Our findings also raise the questionof whether mesoscale eddies have a similarly reducing effect onproduction in the Southern Ocean, the ocean’s largest upwellingsystem and also a region of intense eddy activity42. Our findingsmay also help to better predict how productivity in EBUS andother upwelling systems will react to future climate change,particularly in response to a potential increase in upwelling dueto strengthened alongshore winds43 (Z. Lachkar and N. Gruber,manuscript in preparation).
MethodsData analyses. We used satellite-derived observations of: (1) daily windspeed and direction from QuikSCAT from 1999–2004, (2) 8-day averagedchlorophyll-a concentration from SeaWiFS from 1997–2004, (3) 8-day averagedphotosynthetically available radiation (PAR), also from SeaWiFS, (4) SST fromAVHRR from 1985 to 2003, and (5) EKE from 1995 to 2003 estimated from thegeostrophic velocity anomalies calculated using the mapped sea level anomaly(SLA) data obtained from merged Topex/Poseidon/ERS/Jason-1/ENVISAT maps.Net primary production was computed from chlorophyll-a, SST, and PAR usingthe Vertically Generalized Production Model (VGPM; ref. 44). For each satelliteproduct, first a monthly climatology at the original resolution of the product wasproduced, from which an annual climatology was then computed. Ekman-drivenupwelling along the coasts (a mass flux per metre of coastline) was calculatedfrom the QuikSCAT winds, that is, we computed the offshore transport in aperpendicular direction to the coast, Mx , from Mx = τy/f , where τy is the windstress parallel to the local coastline, and f is the Coriolis parameter45. For the windstress, we assumed a dependence of the drag coefficient on wind speed followingthe formulation of Yelland and Taylor46.
Data were analysed for each of the four EBUS, extending from the coastlineto 500 km offshore and from 24◦ N to 48◦ N for the CalCS, from 12◦ N to 34◦ Nfor the CanCS, from 10◦ S to 34◦ S for the Humboldt Current System, and from10◦ S to 30◦ S for the Benguela Current System. These boundaries were chosen toinclude as much of these current systems as possible, but to exclude other majoroceanographically important features that are unrelated to coastal upwelling, suchas the Agulhas retroflection area in the Benguela Current System. For EKE thevalues in the nearshore 150 km were not included, as their errors are consideredtoo large47. Data were then averaged over 2◦ and then 4◦ bins in the meridionaldirection and over the 500 km coastal strip.
A step-wise multiple linear regression analysis was then performed onbin-averaged NPP, upwelling strength, and EKE.
Model simulations. The employed model is based on the Regional OceanicModelling System (ROMS; ref. 27) and configured for the CalCS as described byGruber et al.25, with the exception that the resolution is a uniform 5 km and thevertical resolution was increased to 32 layers. On average, about 12 levels are withinthe euphotic zone, defined here as the 1% light level. At the surface, the model isforced with monthly mean climatologies of wind stress (QuikSCAT) and fluxes ofheat and freshwater (COADS).
The ecological-biogeochemical model is a nitrogen-based nutrient–phytoplankton–zooplankton–detritus (NPZD)model. The parameters of themodelhave been chosen to represent typical upwelling conditions, resulting in a goodagreement of modelled properties in the highly productive nearshore region, but asystematic underestimation in the unproductive offshore regions25. Two parametersof the model, the initial slope of the light-response curve for phytoplankton growth(αP ) and the mortality rate of phytoplankton (ηmort
P ), were doubled relative to theprevious study25 to enhance themodel’s simulated NPP and improve the agreementwith observationally based estimates ofNPP (see Supplementary Information).
The non-eddy simulation was constructed by manipulating the momentumequations in the code of the model, that is, by setting all nonlinear momentumterms to zero. No explicit viscosity was added to compensate for the lack of eddies,resulting in some enhanced numerical grid-level noise for the velocities. However,the tracers are not affected.
Two further resolutions of the standard model were considered, one at 60 km,with a level of EKE that is more than four times lower than the standard 5 km set-up(see Supplementary Table S.1), and one at 15 km, with a level of EKE that is about40% lower. We also consider cases for the 5 km and 15 km set-ups that employ thebathymetry and coastline of the 60 km model. However, these latter modificationslead to only minor changes in EKE. A summary of the model set-ups considered isgiven in Supplementary Table S.2.
All models were run for 12 years from the same initial conditions, with theaverage of years 10 through 12 being used for all our analyses.
Received 18 April 2011; accepted 25 August 2011; published online2 October 2011
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AcknowledgementsThis work was supported financially by ETH Zürich, by the FP7 project CarboChange(Project reference 264879), by the National Aeronautics and Space Agency(NASA-NNG04GJ89G), and by the US National Science Foundation (NSF-ITRand NSF-ICRR). We also thank the Center for Climate Systems Modelling (C2SM)for support. We are grateful to N. Lovenduski for providing us with high-resolutionsatellite-based climatologies of surface winds and primary production. The EKEproduct was produced by SSALTO/DUACS as part of the Environment and ClimateEuropean Enact project (EVK2-CT2001-00117) and distributed by AVISO, withsupport from CNES.
Author contributionsN.G. designed the study, co-analysed the data, and wrote the paper. Z.L. assisted inthe design of the study, performed most of the experiments, and led the data analyses.H.F. and T.N. ran earlier experiments and assisted in the analyses. P.M., J.C.M.,G.K.P. and M.M. provided conceptual and theoretical advice with regard to designand analyses. All authors discussed the results and implications and commented onthe manuscript at all stages.
Additional informationThe authors declare no competing financial interests. Supplementary informationaccompanies this paper on www.nature.com/naturegeoscience. Reprints and permissionsinformation is available online at http://www.nature.com/reprints. Correspondence andrequests for materials should be addressed to N.G.
