LETTERS

Climate-driven trends in contemporaryocean productivityMichael J. Behrenfeld1, Robert T. O’Malley1, David A. Siegel3, Charles R. McClain4, Jorge L. Sarmiento5,Gene C. Feldman4, Allen J. Milligan1, Paul G. Falkowski6, Ricardo M. Letelier2 & Emmanuel S. Boss7

Contributing roughly half of the biosphere’s net primary produc-tion (NPP)1,2, photosynthesis by oceanic phytoplankton is a vitallink in the cycling of carbon between living and inorganic stocks.Each day, more than a hundred million tons of carbon in the formof CO2 are fixed into organic material by these ubiquitous, micro-scopic plants of the upper ocean, and each day a similar amount oforganic carbon is transferred into marine ecosystems by sinkingand grazing. The distribution of phytoplankton biomass and NPPis defined by the availability of light and nutrients (nitrogen, phos-phate, iron). These growth-limiting factors are in turn regulatedby physical processes of ocean circulation, mixed-layer dynamics,upwelling, atmospheric dust deposition, and the solar cycle.Satellite measurements of ocean colour provide a means of quan-tifying ocean productivity on a global scale and linking its vari-ability to environmental factors. Here we describe global oceanNPP changes detected from space over the past decade. The periodis dominated by an initial increase in NPP of 1,930 teragrams ofcarbon a year (Tg C yr21), followed by a prolonged decrease aver-aging 190 Tg C yr21. These trends are driven by changes occurringin the expansive stratified low-latitude oceans and are tightlycoupled to coincident climate variability. This link betweenthe physical environment and ocean biology functions throughchanges in upper-ocean temperature and stratification, whichinfluence the availability of nutrients for phytoplankton growth.The observed reductions in ocean productivity during the recentpost-1999 warming period provide insight on how future climatechange can alter marine food webs.

Interannual changes in phytoplankton abundance are small rela-tive to total standing stocks and require accurate, long-term mea-surements to detect. The first satellite sensor to have this capability isthe Sea-viewing Wide Field-of-View Sensor (SeaWiFS) and so far it isthe only ocean colour sensor to have lunar-viewing calibration cap-abilities3. These measurements allow SeaWiFS to achieve water-leav-ing radiance biases across the SeaWiFS visible bands (412–555 nm) ofless than 4% when compared to field open-ocean observations4. Thecentral biological variable derived from these measurements isupper-ocean chlorophyll concentration, which can be used to estim-ate phytoplankton standing stocks and productivity (Fig. 1a)throughout the photic zone5.

Global, depth-integrated chlorophyll biomass (SChl) for the 1997to 2006 SeaWiFS record varied from 4.2 to 5.0 Tg (Tg 5 1012 g).Monthly anomalies in global SChl for this period reveal two highlysignificant (P , 0.0001) trends (green line in Fig. 1b). The initial0.3 Tg rise in SChl corresponds to the 1997 to 1999 El Nino to LaNina transition2. Since 1999, global chlorophyll concentrations

dropped on average 0.01 Tg per year, with several secondary featuresthat ended in a 2005 to 2006 rise (Fig. 1b). The two primary trends inglobal SChl are driven by changes occurring in the permanentlystratified regions of the ocean (grey circles in Fig. 1b). These regionshave annual average sea surface temperatures (SSTs) over 15 uC(black lines in Fig. 1a) and represent 74% of the global ice-free ocean.Cooler, seasonal seas also experienced local variability during theSeaWiFS period, but when integrated spatially they exhibit no sig-nificant overall trend (P . 0.5) (Supplementary Fig. 1).

The entire phytoplankton biomass of the global oceans is con-sumed every two to six days6. This rapid turnover implies that vari-ability in SChl (Fig. 1b) corresponds to far more substantial changesin NPP. One of the most commonly used models for estimatingNPP from satellite chlorophyll data is the Vertically GeneralizedProduction Model (VGPM)6. The VGPM gives global NPP estimatesfor the SeaWiFS record that vary strongly with season and rangefrom 3.8 to 4.6 3 1015 g of C per month. Monthly anomalies in thisimportant carbon flux again reveal clear (P , 0.0001) temporaltrends beginning with an El Nino/La Nina-driven 262 Tg increasein NPP between 1997 and 1999, followed by a 197 Tg decrease to2004, and finally a modest increase during 2005 (green line in Fig. 1c).These prominent NPP trends are again traceable to changes in thepermanently stratified oceans (grey circles in Fig. 1c), are highlycorrelated (r2 5 0.93) with changes in SChl (Fig. 1b), and remainwhen NPP is reassessed using alternative productivity models(Supplementary Fig. 2).

Perhaps the most challenging aspect of understanding variabilityin biological processes is associating detected changes with the envir-onmental forcings responsible. Important climate variables linked toocean circulation and productivity are sea-level pressure, surfacewinds, SST, surface air temperature, and cloudiness. These physicalfactors have been combined into a Multivariate ENSO Index (MEI)for evaluating the strength of El Nino/Southern Oscillation cycles7,8.Strong El Nino/Southern Oscillation events have major impactson phytoplankton, fisheries, marine birds and mammals2,9–12 andare striking examples of climatic influences on ocean biology.Importantly, the MEI does not distinguish between natural andanthropogenic changes in climate forcing, but instead provides anintegrated index of climate conditions for comparison with observedchanges in ocean productivity.

We find a clear, strong correspondence between MEI variabilityand SeaWiFS-based anomalies in NPP (r2 5 0.77, P , 0.005) (Fig. 2a)and SChl (Supplementary Fig. 3). An increase in the MEI (that is,warmer conditions) results in a decrease in NPP and SChl, and viceversa. This relationship emphasizes the pre-eminent role of climate

1Department of Botany and Plant Pathology, 2082 Cordley Hall, and 2College of Oceanographic and Atmospheric Sciences, Oregon State University, Corvallis, Oregon 97331, USA.3Institute for Computational Earth System Science and Department of Geography, University of California, Santa Barbara, Santa Barbara, California 93106-3060, USA. 4NASAGoddard Space Flight Center, Greenbelt, Maryland 20771, USA. 5Atmospheric and Oceanic Sciences Program, Princeton University, PO Box CN710, Princeton, New Jersey 08544,USA. 6Environmental Biophysics and Molecular Ecology Program, Institute of Marine and Coastal Sciences and Department of Geological Sciences, Rutgers University 71 Dudley Rd,New Brunswick, New Jersey 08901, USA. 7School of Marine Sciences, 209 Libby Hall, University of Maine, Orono, Maine 04469-5741, USA.

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variability on ocean productivity trends. The observed physical–biological coupling between NPP and the MEI (Fig. 2a) functionsthrough an effect of climate on water column stratification. Climaticchanges that allow surface warming cause an increase in the densitycontrast between the surface layer and underlying nutrient-richwaters. For the global stratified oceans, the density differencebetween the surface and a depth of 200 m provides a useful measureof stratification. Monthly anomalies in this stratification indexexhibit similar trends as the MEI for the SeaWiFS period (Fig. 2b).Importantly, enhanced stratification suppresses nutrient exchangethrough vertical mixing. Conversely, surface cooling favours elevatedvertical exchange. Phytoplankton in the ocean’s upper layer (that is,the populations observed from space) rely on vertical nutrient trans-port to sustain productivity, so intensified stratification during arising MEI period (Fig. 2b) is accompanied closely by decreasingNPP (Fig. 2b) (r2 5 0.73, P , 0.005).

The MEI captures global-scale trends in climate forcings on surfaceocean growth conditions for phytoplankton (Fig. 2). However, whilean increasing MEI corresponds to an overall warming period, at the

regional scale both warming and cooling events are found. Theseregional changes are registered in satellite SST data and are wellillustrated by the 1999 to 2004 period of increasing MEI.Comparison of SST changes (Fig. 3a) and modelled NPP changes(Fig. 3b) for this period reveals the anticipated inverse relationship ofincreasing temperatures coupled to decreasing production (Fig. 3c).Quantitatively, over 74% of the global oceans with SST changesexceeding 60.15 uC between 1999 and 2004 exhibited an inverserelationship between temperature and NPP changes (Fig. 3c). A con-sistent relationship is likewise observed between SST and SChl(Supplementary Fig. 4).

Our results clearly link SChl and NPP changes to SST, stratifica-tion and climate variations and provide an opportunity for compar-ison with simulated ocean responses to a warming climate.Atmosphere–ocean general circulation models coupled to ocean eco-system models are essential tools for understanding global carboncycle–climate feedbacks. When forced by rising atmospheric CO2

concentrations, these prognostic models consistently yield increasedSSTs and net decreases in stratified ocean NPP13–16, consistent withobserved changes in NPP during the 1999 to 2004 period of risingMEI (Fig. 2a). Also consistent with our results, model-simulated NPPchanges are largely due to intensified water-column stratification andare not uniformly distributed across the stratified oceans13–16. Awarming climate in atmosphere–ocean general circulation modelsis also generally associated with increased NPP at higher latitudes,owing to improved mixed-layer light conditions and extended grow-ing seasons14–16. For our relatively brief observational record, thisanticipated net increase in high-latitude NPP was not observed,although NPP changes were found regionally (Fig. 3b).

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Figure 1 | Distribution and trends in global ocean phytoplanktonproductivity (NPP) and chlorophyll standing stocks. a, Annual averageNPP showing high values where surface nutrients are elevated. Low-latitude,permanently stratified waters with annual average surface temperatures over15 uC are delineated by black contour lines. b, Anomalies in globallyintegrated water-column chlorophyll concentrations (green line) aredominated by changes occurring in permanently stratified ocean regions(grey circles and black line). c, Anomalies in global NPP (green line) arelikewise driven by changes in the permanently stratified oceans (grey circlesand black line). Trend lines in b and c are least-squares fits to pre-1999 andpost-1999 data.

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Figure 2 | Ocean productivity is closely coupled to climate variability.a, NPP anomalies in the permanently stratified oceans (grey symbols, leftaxis) are highly correlated (r2 5 0.77) with the MEI of climate variability (redsymbols, right axis). NPP data are from Fig. 1c. b, Changes in oceanstratification (red symbols, right axis) link climate variability to oceanbiology, and are well correlated (r2 5 0.73) with NPP anomalies (greysymbols, left axis) in ocean regions with annual average surfacetemperatures over 15 uC. Stratification strength was assessed as the densitydifferences between the surface and a depth of 200 m using SODA data (seeMethods). Publicly accessible SODA data are available only to the end of2004. Note that the MEI and stratification axes (right) increase from top tobottom.

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Establishing relationships between ocean biology and climaterelies heavily on the accuracy to which changes in ocean ecosystemscan be detected3. The unique operational characteristics of SeaWiFShave enabled detection of the global ocean trends reported here.Unfortunately, the SeaWiFS sensor is well beyond its design lifetimeand no currently scheduled ocean-colour missions will have equalcapabilities. SeaWiFS also represents an immature state of ocean-colour remote sensing. Modelling studies suggest that shifts in eco-system structure from climate variations may be as or more import-ant than the alterations in bulk integrated properties reported here13.Susceptible ecosystem characteristics include shifts in taxonomiccomposition13, physiological status17, and light absorption bycoloured dissolved organic material18. Resolving these propertiesand their changes over time will require improved accuracies andsignificant expansions in the spectral range and resolution of futureremote-sensing measurements.

Climate effects on ocean biology are documented here for nearly adecade of satellite ocean colour measurements. The compelling cor-respondence found between NPP changes and the MEI (Fig. 2a)suggests that this integrated index of climate variability, whichextends back to 1950 (refs 6, 7), may provide a first-order proxyfor variations in photosynthetic carbon fixation in the oceans forthe period predating satellite ocean-colour measurements. It is alsoclear from the current analysis that surface warming in the perma-nently stratified ocean regions is accompanied by reductions in pro-ductivity. The index used here (MEI) to relate climate variability toNPP trends does not distinguish natural from anthropogenic con-tributions, but observational and modelling efforts indicate thatrecent changes in SST are strongly influenced by anthropogenic for-

cing19–22. These observations imply that the potential transition topermanent El Nino conditions in a warmer climate state23 would leadto lower and redistributed ocean carbon fixation relative to typicalcontemporary conditions. Such changes will inevitably alter themagnitude and distribution of global ocean net air–sea CO2

exchange15,24,25, fishery yields9,12,26, and dominant basin-scale bio-logical regimes12.

METHODS

Ocean NPP was calculated with the VGPM using monthly 1,080 3 2,160 pixel

resolution (that is, 18 km spacing at the Equator) OC4-v4 chlorophyll algorithm

products from SeaWiFS reprocessed version 5.1 data (http://oceancolor.gsfc.

nasa.gov). Comparison of this data with ,1,400 in situ match-up surface chloro-

phyll data yields a median difference of 33%, which is comparable to measure-

ment uncertainties in the field.SChl was calculated from the satellite chlorophyll

data using relationships described in ref. 5, which are based on 3,806 in situ

chlorophyll profiles and account for subsurface chlorophyll features. The

VGPM describes light-dependent changes in water-column NPP using a rela-

tionship based on 1,698 field productivity measurements6 and SeaWiFS cloud-

corrected photosynthetically active radiation data (http://oceancolor.gsfc.nasa.

gov). The standard VGPM describes photosynthetic efficiencies using a poly-

nomial function that increases with temperature below 20 uC and decreases

above 20 uC.

Ocean NPP was additionally calculated using two alternative models, with

results demonstrating the robust nature of the primary temporal trends

described here (Supplementary Fig. 2). MEI data were from http://www.cdc.

noaa.gov/people/klaus.wolter/MEI. Stratification anomalies were calculated

from Simple Ocean Data Assimilation (SODA) (http://www.atmos.umd.edu/

,ocean) monthly global density data, which assimilate available field observa-

tions. AVHRR SST data were from http://podaac-www.jpl.nasa.gov/sst.

Deseasonalized chlorophyll, NPP, and stratification anomalies were calculated

by subtracting from each monthly value the corresponding monthly average for

the entire time series. Reported statistics for relationships between NPP anom-

alies and MEI and stratification anomalies account for auto-correlation effects

inherent in comparisons between time-series data sets.

Received 18 August; accepted 6 October 2006.

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Figure 3 | Climate controls on ocean productivity cause NPP to varyinversely with changes in SST. Global changes in annual average SST (a) andNPP (b) for the 1999 to 2004 warming period (Fig. 2). c, For 74% of thepermanently stratified oceans (that is, regions between black contour lines),NPP and SST changes were inversely related. Yellow, increase in SST,decrease in NPP. Light blue, decrease in SST, increase in NPP. Dark blue,decreases in SST and NPP. Dark red, increases in SST and NPP. A similarinverse relationship is observed between SST and chlorophyll changes. (SeeSupplementary Fig. 4 for additional information.)

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1979–1999 period. J. Geophys. Res. 108, 3375, doi:10.1029/2001JC000920(2003).

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22. Barnett, T. P. et al. Penetration of human-induced warming into the world’soceans. Science 309, 284–287 (2005).

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Supplementary Information is linked to the online version of the paper atwww.nature.com/nature.

Acknowledgements We thank the Ocean Biology Processing Group at theGoddard Space Flight Center, Greenbelt, Maryland for their diligence in providingthe highest quality ocean colour products possible and the NASA Ocean Biologyand Biogeochemistry Program for support.

Author Information Reprints and permissions information is available atwww.nature.com/reprints. The authors declare no competing financial interests.Correspondence and requests for materials should be addressed to M.J.B.(mjb@science.oregonstate.edu).

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chronosequences (7) or soil respiration measure-ments (31). The assumption that soils are in asteady state is also called into question, espe-cially because it is recognized that refractory OChas been building up in soils exposed since thelast glacial (1, 5). This new paradigm likely hasits main impact on carbon budget models thatcalculate sources, sinks, and fluxes within theglobal carbon cycle on longer time scales (>1000years). This could be of relevance, for example,to studies that link vegetation type to soil carboncontent in order to estimate changing carbonstorage on land through time (9). It places theterrestrial biosphere in a more prominent positionas a slow but progressively important atmospher-ic carbon sink on geologic time scales and mayeven influence current predictions about carboncycling and soil carbon storage in response toelevated atmospheric CO2 levels.

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1 May 2006; accepted 10 October 200610.1126/science.1129376

Recent Greenland Ice Mass Loss byDrainage System from SatelliteGravity ObservationsS. B. Luthcke,1* H. J. Zwally,2 W. Abdalati,2 D. D. Rowlands,1 R. D. Ray,1R. S. Nerem,3 F. G. Lemoine,1 J. J. McCarthy,4 D. S. Chinn4

Mass changes of the Greenland Ice Sheet resolved by drainage system regions were derived from alocal mass concentration analysis of NASA–Deutsches Zentrum für Luft- und Raumfahrt GravityRecovery and Climate Experiment (GRACE mission) observations. From 2003 to 2005, the ice sheetlost 101 ± 16 gigaton/year, with a gain of 54 gigaton/year above 2000 meters and a loss of 155gigaton/year at lower elevations. The lower elevations show a large seasonal cycle, with mass lossesduring summer melting followed by gains from fall through spring. The overall rate of loss reflectsa considerable change in trend (–113 ± 17 gigaton/year) from a near balance during the 1990sbut is smaller than some other recent estimates.

Mass changes in the Greenland Ice Sheetare of considerable interest because ofits sensitivity to climate change and

the potential for an increasing contribution ofGreenland ice loss to rising sea level. Observa-tions and models have shown that in recent yearsGreenland has experienced increased melt (1),thinning at the margins (2–4), and increaseddischarge from many outlet glaciers (5). At thesame time, the ice sheet has been growing in itsinterior (3, 4, 6).

These recent changes in the Greenland IceSheet and the wide range of mass-balance es-timates (7) highlight the importance of methodsfor directly observing variations in ice sheet

mass. Moreover, the fact that some regions areshedding mass dramatically, whereas others arenot (2–5), indicates a clear need for measure-ments with a spatial resolution that allows as-sessment of the behavior of individual drainagesystems (DSs). The local mass concentrationanalysis presented here provides an assessmentof mass balance of individual Greenland DSregions, subdivided by elevation, as well as theoverall ice sheet mass balance.

Direct measurements of mass change havebeen enabled by the NASA–Deutsches Zentrumfür Luft- und Raumfahrt Gravity Recovery andClimate Experiment (GRACE) mission (8).Since its launch in March 2002, GRACE has

been acquiring ultra-precise (0.1 mm/s) intersat-ellite K-band range and range rate (KBRR)measurements taken between two satellites inpolar orbit about 200 km apart. The changes inrange rate sensed between these satellites providea direct mapping of static and time-variablegravity.

Recent GRACE-based mass balance esti-mates of Antarctica (9) and Greenland (10, 11)have been derived from the monthly spherical-harmonic gravity fields produced by theGRACE project. Although these solutions rep-resent an important advance in the use of gravitymeasurements to assess ice sheet mass balance,they are limited in their temporal and spatialresolution. For example, the recent results pre-sented in (11) showed sizable mass loss spreadover the entire Greenland continent, in contrastwith recent studies that indicated loss concen-trated on the margins (2–5) and growth in theinterior (3, 4, 6). In addition, the fundamentalmeasurements being made by GRACE containfar more information than is currently being ex-ploited by techniques that rely on these monthly

1Planetary Geodynamics Laboratory, Code 698, NASAGoddard Space Flight Center, Greenbelt, MD 20771,USA. 2Cryospheric Sciences Branch, Code 614.1, NASAGoddard Space Flight Center, Greenbelt, MD 20771, USA.3Colorado Center for Astrodynamics Research, CooperativeInstitute for Research in Environmental Sciences, Departmentof Aerospace Engineering Sciences, University of Colorado,Boulder, CO 80309, USA. 4Science Division, SGT Incorporated,Greenbelt, MD 20770, USA.

*To whom correspondence should be addressed. E-mail:Scott.B.Luthcke@nasa.gov

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spherical-harmonic fields. Close examination ofthe KBRR measurements reveals coherent massvariation signals at better-than-400-km fullwavelength spatial and 10-day temporal resolu-tion at the mid-latitudes (12) and still betterresolution at high latitudes.

Our approach to estimating ice sheet masschanges followed a strategy of preserving thegravity information containedwithin the GRACEKBRR observations. This was accomplishedthrough an innovative processing of the GRACEintersatellite range-rate measurements (13) andthe parameterization of local mass variations asmass concentrations (mascons). Mascons wereestimated from short arc solutions of GRACEKBRR data exclusively within a local area ofinterest (12). The regional solution exploits thefact that the signal from a mass concentrationobserved in the GRACE KBRR data is centeredover the mass concentration and is spatiallylimited in extent. The mathematical formulationof mascon parameters, the details of the localmascon approach, and the results of a simulationthat validate the method are provided in (14).The results of the simulations show that the mas-con approach is capable of recovering the spatialdistribution and magnitude of realistic andcomplex ice mass change signal to better than90% (14).

For our ice sheet analysis, a mascon param-eter corresponds to a surplus or deficit of mass inan irregularly shaped DS region (Fig. 1) definedby surface slopes and climatology (15) and sub-divided into surface elevation above and below2000m. Exterior regions (as outlined in Fig. 1) aswell as daily baseline state parameters were es-timated to account for mass variations occurringoutside our Greenland DS regions of interest(14). Themascon estimates are relative to modelsof both static and time varying gravity effects(e.g., tides and atmospheric mass redistribu-tion) in order to isolate ice mass change (14).

We derived mascon solutions from GRACEKBRR data for each DS region (Fig. 1) every 10days from July 2003 through July 2005 (Table1). The individual elevation-dependent masconsolution time series can be summed over each10-day interval to produce time series for the sixoverall DSs (Fig. 2) and time series for regionsabove and below 2000 m elevation (Fig. 3).The results (Table 1 and Figs. 2 and 3) representthe total observed mass variation, including thetrends from glacial isostatic adjustment (GIA).Included separately in Table 1 is the computedGIA trend from ICE-5G using a 90-kmlithosphere and VM2 viscosity model (16).

The northern DSs 1 and 2 and the southwestDS 5 are nearly in mass balance (Fig. 2), con-sidering the associated error bars and the GIAnoted in Table 1. DSs 3, 4, and 6 all exhibitsignificant mass loss, with DS 4, the southeast,dominating the overall mass loss. Figure 3 pres-ents our mascon time series for the regionsabove and below 2000-m elevation. For the 2years (July 2003 to July 2005), our solutions

(Fig. 3) show a moderate growth of 54 ± 12Gton/year for the high-elevation Greenlandinterior, with a significant loss of 155 ± 26Gton/year occurring in the low-elevation coastalregions. Therefore, we obtain a total Greenlandtrend of –101 ± 16 Gton/year. These trends havebeen corrected for GIA and scaled by 1.1 toaccount for potential signal loss as determined inthe simulation analysis (14). Treatment of theassociated errors is discussed in (14). The massloss is dominated by loss in the eastern low-elevation coastal regions and the southeast DS 4.Our overall Greenland mass trend of –101 ± 16Gton/year is consistent with the GRACE-basedanalysis by (17), which determined a trend of–118 ± 14 Gton/year for the time period of July2002 to March 2005. However, these overalltrends are nearly a factor of 2 smaller than therecent GRACE-based trend determined in (11).The results presented in (11) show significant

mass loss over the entire continent and thereforeare difficult to reconcile with known mass lossconcentrated in the low-elevation coastal regionsand gain in the interior.

The high-elevation interior region solutionsshow little annual cycle, with an overall am-plitude of 13 ± 9 Gton, whereas in contrast thelow-elevation coastal region solutions resolve asignificant annual cycle with an amplitude of150 ± 27 Gton (Table 1 and Fig. 3). The annualcycle of the low-elevation coastal region ex-hibits significant mass shedding beginning inMay-June and ending in October, correspondingto summer melt (Fig. 3). The largest annualcycle is found in the southwest DS 5. A nearlysemiannual signal most noticeable in DS 2 is anartifact caused by mismodeled ocean tides (14).

The temporal and spatial resolution of theGRACE mascon solutions provides importantinsights into the ice sheet behavior and the

Fig. 1. Greenland DS mascon regions: regions above 2000 m elevation are labeled “a,” and thosebelow are labeled “b.” Exterior region mascons outside of Greenland are also shown outlined in red.

Table 1. Summary of Greenland drainage system mascon solutions above and below 2000-melevation (July 2003 to July 2005). GIA calculated from ICE-5G with use of a 90-km lithosphere andVM2 viscosity model (16).

Drainagesystem

Observed mass change(Gton/year)

GIA(Gton/year)

Annual amplitude(Gton)

>2000 m <2000 m >2000 m <2000 m >2000 m <2000 m1 13 ± 2 –4 ± 4 0 2 7 ± 2 34 ± 52 40 ± 2 –32 ± 2 –1 2 12 ± 2 11 ± 33 50 ± 3 –75 ± 2 –1 0 8 ± 4 24 ± 24 –38 ± 11 –33 ± 3 –1 0 12 ± 13 33 ± 35 3 ± 3 –3 ± 13 –4 –3 19 ± 3 62 ± 146 –27 ± 3 6 ± 5 –1 0 14 ± 3 20 ± 6Greenland 41 ± 8 –140 ± 24 –8 1 13 ± 9 150 ± 27

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quality of the mascon solutions. The moderategrowth of the high-elevation interior ice sheetwith significant mass shedding of the low-elevation coastal regions is consistent with otherrecent studies (1–6). In addition, the solutionsexhibit a relatively small annual cycle for thehigh-elevation interior ice sheet, consistent withlow temperatures, negligible melting, and smallseasonal variation in precipitation. The lowelevations show a large annual cycle, with thelargest in the southwest DS 5. These results areconsistent with warm summer temperatures ofthe coastal regions in general and, combinedwith shallow slopes for DS 5 in particular, leadto the most extensive summer melt (18). There-

fore, our mascon time series for the low eleva-tions exhibit seasonal characteristics that arevery consistent with the well-known net ab-lation during summer melt followed by growthduring winter, as shown for example by radaraltimeter data (3) and surface mass balancemodels (19).

Comparison of our 2003–2005 ice masstrends by DS in Table 2 to the 1992–2002 trendscomputed from satellite radar and airborne laseraltimetry (3) provides insights into the evolutionof the ice sheet. The changes of the trends withtime of the two most northerly DSs, 1 and 2, arenot significantly different from zero, which isconsistent with the lack of glacier acceleration

(5) or detected icequakes (20) reported for thoseareas. DS 3 in the east appears to have changedby –20 Gton/year from a slightly negativebalance (–5 Gton/year) to a significantly nega-tive overall balance of –25 Gton/year, with verylarge mass shedding in the low-elevation coastalregion and growth at high elevations (Table 1).Although DS 3 had one accelerating glacier (5)and icequakes in two glaciers (20), it has alsohad a large average annual mass input of 42Gton/year (3) and is therefore very sensitive tointerannual variations or trends in precipitationand ice accumulation. Our largest observedchange (–61 Gton/year) occurred in DS 4 inthe southeast, whereas the other significantnegative change occurred in DS 6 in the west(–32 Gton/year), consistent with glacier accel-erations (5) and increases in icequakes (20) inthat system. In particular, the acceleration ofthree glaciers in DS 4 indicated an increase inthe rate of loss in 2005, compared with that in1996, of –56Gton/year (5), which is comparableto our change of –61 Gton/year. In DSs 5 and 6,the change from glacier accelerations was –25Gton/year (5), which compares well with ourtotal change of –37 Gton/year that includeschanges in surface balance as well as changesin glacier discharge. Although the extent towhich meaningful conclusions can be drawnfrom a 2-year time series is limited because of theinfluence of interannual variations, the consist-ency of our results with all other indications ofaccelerating mass loss (1, 4, 5, 19) strongly sup-ports our interpretation that a significant changein the Greenland mass balance has occurredprimarily in DSs 3, 4, and 6.

The high temporal resolution of the masconsolutions provides unprecedented observation ofmass change events and provides the opportu-nity to apply filtering techniques to reduce thesolution noise. By reliably resolving ice masschange observations into ice sheet DS scalessubdivided by surface elevation, the masconsolutions provide the ability to separate the areasof rapid loss [e.g., the southeast DS 4 and thelow-elevation coastal regions (Figs. 2 and 3)]from areas of slower loss or even gain (e.g.,high-elevation interior regions). The masconsolutions provide a better basis for comparisonto passivemicrowave-derivedmelt data (18) andsurface mass balance models (19) and facilitatethe comparison to flux-based methods (5) andaltimetric methods (2–4, 6, 21) that examineindividual drainage basins.

Our GRACE mascon solutions provide adirect measure of mass changes on the scale ofDSs subdivided into regions above and below2000-m surface elevation. In contrast with otherrecent gravity-based mass balance estimates(10, 11, 17), our mascon solutions exhibitimproved spatial resolution, delineating high-elevation interior region growth and substantialmass loss for the low-elevation coastal regions. Inaddition, the mascon solutions show improvedtemporal resolution, delineating the large season-

Fig. 2. Greenland drainage systems 2-year (July 2003 to July 2005) mascon time series (summingregions above and below 2000-m elevation for each system) derived from GRACE KBRR data: 10-dayestimates (blue dots with error bars); Gaussian 1-day filter with 30-day window applied to 10-dayestimates (green line); and trend (red line) recovered from simultaneous estimation of bias, trend,annual and semi-annual sinusoid. Trends have not been corrected for GIA. Error bars indicate 1-scalibrated uncertainties. Gt/yr, Gton/year.

Fig. 3. Time series computed from the sum of mascon region solutions above and below 2000-melevation: 10-day estimates (blue dots with error bars); Gaussian 1-day filter with 30-day windowapplied to 10-day estimates (green line); and trend (red line) recovered from simultaneousestimation of bias, trend, annual and semi-annual sinusoid. Trends have not been corrected forGIA. Error bars indicate 1-s calibrated uncertainties.

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al cycle for the low-elevation coastal regions andobserving the summer melt and winter growthcycles. Our finding of an overall mass loss of101 ± 16 Gton/year for 2003 to 2005 isconsistent with the finding of near balanceduring the 1990s (3) and with the recent resultson increased melt rates (1), acceleration ofoutlet glaciers (5, 20), and the increasinglynegative surface balance in recent years (22).The Greenland mass loss contributes 0.28 ±0.04 mm/year to global sea level rise, which isnearly 10% of the 3 mm/year rate recently ob-served by satellite altimeters (23). The ob-served change from the 1990s of –113 ± 17Gton/year represents a change from a smallgrowth of about 2% of the annual mass input toa loss of about 20%, which is a significant changeover a period of less than 10 years (24). This resultis in very good agreement with the change in trendof –117 Gton/year from 1996 to 2005 determinedfrom radar interferometry (5). During the 1990s,the observed thinning at the margins and thegrowth inland were both expected responses toclimate warming. Our new results suggest thatthe processes of significant ice depletion at themargins, through melting and glacier accelera-tion, are beginning to dominate the interiorgrowth as climate warming has continued.

References and Notes1. An update of (18) posted at http://cires.colorado.edu/

science/groups/steffen/greenland/melt2005 shows a 31%increase in mean melt area between 1979 and 2005.

2. W. Krabill et al., Geophys. Res. Lett. 31, L24402 (2004).3. H. J. Zwally et al., J. Glaciol. 51, 509 (2005).4. R. Thomas et al., Geophys. Res. Lett. 33, L10503 (2006).5. E. Rignot, P. Kanagaratnam, Science 311, 986 (2006).6. O. M. Johannessen, K. Khvorostovsky, M. W. Miles,

L. P. Bobylev, Science 310, 1013 (2005); publishedonline 20 October 2005 (10.1126/science.1115356).

7. For mass balance within the 1992–2002 time period, thefollowing estimates have been published: +11 ±3 Gton/year for 1992–2002 (3), –46 Gton/year for 1993/4 – 1998/9 (21), –72 ± 11 Gton/year for 1997–2003 (2),and –83 ± 29 and –127 ± 29 Gton/year for 1996 and2000, respectively (5). If the correction for firncompaction used in the radar altimeter analysis (3) isapplied to the airborne altimeter estimates (2, 4, 21), thedifference between the two approaches is reduced byabout 23 Gton/year, as reflected by revised airbornevalues of –4 to –50 Gton/year for 1993 to 1999 (4).

8. B. D. Tapley, S. Bettadpur, J. C. Ries, P. F. Thompson,M. M. Watkins, Science 305, 503 (2004).

9. I. Velicogna, J. Wahr, Science 311, 1754 (2006); publishedonline 1 March 2006 (10.1126/science.1123785).

10. I. Velicogna, J. Wahr, Geophys. Res. Lett. 32, L18505(2005).

11. J. L. Chen, C. R. Wilson, B. D. Tapley, Science 313, 1958(2006); published online 10 August 2006 (10.1126/science.1129007).

12. D. Rowlands et al., Geophys. Res. Lett. 32, L04310 (2005).13. S. B. Luthcke et al., Geophys. Res. Lett. 33, L02402 (2006).14. Materials and methods are available as supporting

material on Science Online.15. H. J. Zwally, M. B. Giovinetto, Ann. Glaciol. 31, 126

(2000).16. W. R. Peltier, Annu. Rev. Earth Planet. Sci. 32, 111

(2004).

17. G. Ramillien et al., J. Global Planet. Change 53, 10.1016/j.gloplacha.2006.06.003 (2006).

18. W. Abdalati, K. Steffen, J. Geophys. Res. 106, 33983(2001).

19. J. E. Box et al., J. Clim. 19, 2783 (2006).20. G. Ekstrom, M. Nettles, V. C. Tsai, Science 311, 1756

(2006).21. W. Krabill et al., Science 289, 428 (2000).22. E. Hanna et al., J. Geophys. Res. 110, D13108 (2005).23. A. Cazenave, R. S. Nerem, Rev. Geophys. 42, 10.1029/

2003RG000139 (2004). An update is posted at http://sealevel.colorado.edu.

24. For the 1990s, we used the small 11 Gton/year mass gainfrom (3) and noted that the negative balances discussedin (7) either would give significantly less negativechanges than 113 Gton/year or would give positivechanges, in contradiction to the evidence for increases inmelt and glacier accelerations. Also, our 113 ± 17 Gton/year is in good agreement with the change in mass fluxof 117 Gton/year from 1996 to 2005 from radarinterferometry (5).

25. We acknowledge NASA’s Solid Earth and Natural HazardsProgram, NASA’s Cryospheric Sciences Program, andNASA’s Ice, Cloud, and Land Elevation Satellite andGRACE missions for their support of this research and thequality of the GRACE Level 1B products produced by ourcolleagues at the Jet Propulsion Laboratory. We thankS. Klosko, T. Williams, and D. Pavilis for their manycontributions and the reviewers for their astutecommentary.

Supporting Online Materialwww.sciencemag.org/cgi/content/full/1130776/DC1Materials and MethodsFig. S1

2 June 2006; accepted 10 October 2006Published online 19 October 2006;10.1126/science.1130776Include this information when citing this paper.

Abundance Distributions ImplyElevated Complexity of Post-PaleozoicMarine EcosystemsPeter J. Wagner,1* Matthew A. Kosnik,2 Scott Lidgard1

Likelihood analyses of 1176 fossil assemblages of marine organisms from Phanerozoic (i.e., Cambrianto Recent) assemblages indicate a shift in typical relative-abundance distributions after the Paleozoic.Ecological theory associated with these abundance distributions implies that complex ecosystems are farmore common among Meso-Cenozoic assemblages than among the Paleozoic assemblages thatpreceded them. This transition coincides not with any major change in the way fossils are preserved orcollected but with a shift from communities dominated by sessile epifaunal suspension feeders tocommunities with elevated diversities of mobile and infaunal taxa. This suggests that the end-Permianextinction permanently altered prevailing marine ecosystem structure and precipitated high levels ofecological complexity and alpha diversity in the Meso-Cenozoic.

Marine ecosystem complexity is thoughtto have increased over the past 540million years, in terms both of the

alpha [i.e., local (1)] diversity of fossilized as-semblages and of the numbers of basic ecologicaltypes (i.e., “guilds”) (2–5). Ecological theory pre-dicts that ecosystem complexity affects relative-abundance distributions (RADs) (6). Therefore,if fossiliferous assemblages adequately reflectoriginal communities, then RADs implying inter-actions and/or a multiplicity of basic ecologiesshould become more common over time, and

RADs implying simple partitioning and/or limitedinteraction should become less common. Tapho-nomic studies show that death assemblages canaccurately reflect one aspect of RADs of skeleton-ized taxa within living communities, namely, rank-order abundance (7). Moreover, paleoecological

1Department of Geology, Field Museum of Natural History,1400 South Lake Shore Drive, Chicago, IL 60605, USA.2School of Marine and Tropical Biology, James CookUniversity, Townsville, QLD 4811, Australia.

*To whom correspondence should be addressed. E-mail:pwagner@fmnh.org

Table 2. Comparison of mascon-derived trends with previous values determined from satelliteand airborne altimetry (3). The mascon-derived trends were corrected for GIA and potential signalloss (~9%) as determined from simulation analysis (14). Errors computed as in (14) along withassuming 100% error in GIA.

Drainagesystem

2003–2005mascon-derivedice mass trend(Gton/year)

1992–2002altimeter-derivedice mass trend (3)

(Gton/year)

Delta(2003–2005) –(1992–2002)(Gton/year)

1 8 ± 5 1.6 ± 0.3 6 ± 52 8 ± 4 8.8 ± 0.2 –1 ± 43 –25 ± 4 –4.9 ± 2.0 –20 ± 44 –77 ± 11 –15.7 ± 1.2 –61 ± 115 7 ± 13 11.4 ± 0.8 –5 ± 136 –22 ± 7 10.5 ± 0.5 –32 ± 7Greenland –101 ± 16 11.7 ± 2.5 –113 ± 17

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DOI: 10.1126/science.1129116 , 449 (2006); 314Science

et al.R. Eugene Turner,RitaWetland Sedimentation from Hurricanes Katrina and

www.sciencemag.org (this information is current as of January 24, 2007 ):The following resources related to this article are available online at

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including high-resolution figures, can be found in the onlineUpdated information and services,

http://www.sciencemag.org/cgi/content/full/1129116/DC1 can be found at: Supporting Online Material

found at: can berelated to this articleA list of selected additional articles on the Science Web sites

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sors represents an additional dimension of

sensitivity and specificity for molecular imag-

ing. The depletion process generating the image

contrast depends on several parameters, includ-

ing saturation power and time, sensor concen-

tration, and ambient temperature. The latter

parameter provides another promising approach

to increase sensitivity even further, because the

exchange rate increases considerably when ap-

proaching 37-C (10). Characterization of the

saturation dynamics is currently under way and

will reveal optimized parameters for future

applications.

The technique is also quite promising for

biomedical imaging in vivo. A typical surface

coil of 20 cm diameter detects a volume of ca.

2.1 liters, thus decreasing S/N for a (2.8 mm)3

voxel by a factor of 27.2 compared with our

setup. This loss is less than 50% of the gain for

an optimized system using 945% polarized

isotopically enriched 129Xe. An isotropic reso-

lution of 2 to 3 mm is feasible without signal

averaging for a concentration of pure polarized129Xe that is È2 mM in tissue. This minimum

value is below those observed for direct

injection of Xe-carrying lipid solutions into rat

muscle (70 mM) or for inhalation delivery for

brain tissue (8 mM) used in previous studies

that demonstrated Xe tissue imaging in vivo

(17). Sensitive molecular imaging of the bio-

sensor is therefore possible as long as the

distribution of dissolved xenon can be imaged

with sufficient S/N and the biosensor target is

not too dilute, because HYPER-CEST is based

on the detection of the free Xe resonance, not

direct detection of the biosensor resonance.

The HYPER-CEST technique is amenable to

any type of MRI image acquisition methodology.

We demonstrated CSI here, but faster acquisition

techniques that incorporate a frequency encoding

domain such as FLASH (fast low angle shot)

have been successfully used to acquire in vivo Xe

tissue images (17).

The modular setup of the biosensor (i.e., the

nuclei that are detected are not covalently bound

to the targeting molecule) allows accumulation

of the biosensor in the tissue for minutes to hours

before delivery of the hyperpolarized xenon

nuclei, which have much higher diffusivity. In

combination with the long spin-lattice relaxation

time of Xe, this two-step process optimally pre-

serves the hyperpolarization before signal acqui-

sition. Biosensor cages that yield distinct xenon

frequencies allow for multiplexing to detect

simultaneously several different targets (18).

Also the serum- and tissue-specific Xe NMR

signals (19, 20) arising after injection of the

carrier medium can be used for perfusion studies

(Fig. 3B) in living tissue, making Xe-CSI a

multimodal imaging technique.

References and Notes1. J. M. Tyszka, S. E. Fraser, R. E. Jacobs, Curr. Opin.

Biotechnol. 16, 93 (2005).

2. A. Y. Louie et al., Nat. Biotechnol. 18, 321 (2000).

3. S. Aime, C. Carrera, D. Delli Castelli, S. Geninatti,E. Terreno, Angew. Chem. Int. Ed. 44, 1813 (2005).

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10654 (2001).6. T. J. Lowery et al., Magn. Reson. Imaging 21, 1235

(2003).7. K. Bartik, M. Luhmer, J. P. Dutasta, A. Collet, J. Reisse,

J. Am. Chem. Soc. 120, 784 (1998).

8. C. Hilty, T. J. Lowery, D. E. Wemmer, A. Pines, Angew.Chem. Int. Ed. 45, 70 (2006).

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10. M. M. Spence et al., J. Am. Chem. Soc. 126, 15287 (2004).11. A. Bifone et al., Proc. Natl. Acad. Sci. U.S.A. 93, 12932

(1996).

12. K. M. Ward, A. H. Aletras, R. S. Balaban, J. Magn. Res.143, 79 (2000).

13. A. A. Maudsley, S. K. Hilal, W. H. Perman, H. E. Simon,J. Magn. Res. 51, 147 (1983).

14. N. Goffeney, J. W. M. Bulte, J. Duyn, L. H. Bryant, P. C. M.van Zijl, J. Am. Chem. Soc. 123, 8628 (2001).

15. K. Knagge, J. Prange, D. Raftery, Chem. Phys. Lett. 397,11 (2004).

16. J. L. Mynar, T. J. Lowery, D. E. Wemmer, A. Pines,J. M. Frechet, J. Am. Chem. Soc. 128, 6334 (2006).

17. B. M. Goodson et al., Proc. Natl. Acad. Sci. U.S.A. 94,14725 (1997).

18. G. Huber et al., J. Am. Chem. Soc. 128, 6239 (2006).19. J. P. Mugler et al., Magn. Res. Med. 37, 809 (1997).20. S. D. Swanson, M. S. Rosen, K. P. Coulter, R. C. Welsh,

T. E. Chupp, Magn. Res. Med. 42, 1137 (1999).21. This work was supported by the Director, Office of

Science, Office of Basic Energy Sciences, MaterialsSciences and Engineering Division, of the U.S.Department of Energy under contract no. DE-AC03-76SF00098. L.S. acknowledges support from theDeutsche Forschungsgemeinschaft (SCHR 995/1-1)through an Emmy Noether Fellowship. T.J.L.acknowledges the Graduate Research and Education inAdaptive bio-Technology (GREAT) Training Program of theUC Systemwide Biotechnology Research and EducationProgram (no. 2005-264), and C.H. acknowledges supportfrom the Schweizerischer Nationalfonds through apostdoctoral fellowship.

Supporting Online Materialwww.sciencemag.org/cgi/content/full/314/5798/446/DC1Materials and MethodsFig. S1References

28 June 2006; accepted 29 August 200610.1126/science.1131847

Wetland Sedimentation fromHurricanes Katrina and RitaR. Eugene Turner,1,2* Joseph J. Baustian,1,2 Erick M. Swenson,1,2 Jennifer S. Spicer2

More than 131 � 106 metric tons (MT) of inorganic sediments accumulated in coastal wetlandswhen Hurricanes Katrina and Rita crossed the Louisiana coast in 2005, plus another 281 � 106 MTwhen accumulation was prorated for open water area. The annualized combined amount ofinorganic sediments per hurricane equals (i) 12% of the Mississippi River’s suspended load, (ii)5.5 times the inorganic load delivered by overbank flooding before flood protection levees wereconstructed, and (iii) 227 times the amount introduced by a river diversion built for wetlandrestoration. The accumulation from hurricanes is sufficient to account for all the inorganicsediments in healthy saltmarsh wetlands.

Inorganic sediments accumulating in coastal

wetlands may be delivered from inland

sources via (i) unconstrained overbank flood-

ing, (ii) explosive releases through unintentional

breaks in constructed levees, and (iii) river diver-

sions. They may also arrive from offshore during

tidal inundation or storm events. It is important to

know the quantities delivered by each pathway to

understand how inorganic sediments contribute

to wetland stability and to spend wetland res-

toration funds effectively. Here we estimate the

amount of inorganic sediments deposited on

wetlands of the microtidal Louisiana coast

during Hurricanes Katrina and Rita.

Hurricanes Katrina and Rita passed through

the Louisiana (LA) coast on 29 August and 24

September, 2005, respectively, leaving behind a

devastated urban and rural landscape. Massive

amounts of water, salt, and sediments were re-

distributed across the coastal zone within a few

hours as a storm surge of up to 5 m propagated in

a northerly direction at the coastline south of New

Orleans, LA (Katrina), and near Sabine Pass,

Texas (TX) (Rita), inundating coastal wetlands in

the region. A thick deposit of mud remained in

these coastal wetlands after the storm waters re-

ceded (Fig. 1). We used this post-storm remnant

to learn about how coastal systems work.

The loss of LA_s coastal wetlands peaked be-

tween 1955 and 1978 at 11,114 ha year–1 (1)

and declined to 2591 ha year–1 from 1990 to

2000 (2). Coastal wetlands, barrier islands, and

shallow waters are thought to provide some pro-

tection from hurricanes, by increasing resistance

to storm surge propagation and by lowering hur-

ricane storm surge height (3). Restoring LA_swetlands has become a political priority, in part

because of this perceived wetland/storm surge

connection. A major part of LA_s restoration

effort is to divert part of the Mississippi River

into wetlands, and at considerable cost Eref.(S1) in supporting online material (SOM)^.Widely adopted assumptions supporting this

1Coastal Ecology Institute, 2Department of Oceanographyand Coastal Sciences, Louisiana State University, BatonRouge, LA 70803, USA.

*To whom correspondence should be addressed. E-mail:euturne@lsu.edu

REPORTS

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diversion are that flood protection levees have

eliminated overbank flooding, which has caused

diminished sediment accumulation and eventual

wetland loss, and introducing sediments into

estuaries via river diversions will enhance wet-

land restoration.

If increasing inorganic sediment loading to

coastal wetlands is important for their restora-

tion, then it is important to quantify the major

sediment pathways. Hurricanes Katrina and

Rita obviously brought some inorganic sedi-

ment into the coastal wetlands, but how much,

and where was it distributed? A few measure-

ments of the inorganic sediments accumulating

from a hurricane have been made at specific

sites along the coast (4–8) Eref. (S7) in SOM^,but until this study there were no coastwide

data on the inorganic sediments accumulating

from hurricanes. Here we show that the dom-

inant pathway of inorganic sediments into the

microtidal LA coastal wetlands is from offshore

to inshore during hurricanes, and not from over-

bank flooding along the main channel of the

Mississippi River, from smaller storm events, or

from tidal inundations.

We sampled from the shoreline to the on-

shore limit of storm sediment deposition in

wetlands (9) (Fig. 1A). We collected samples

from all coastal watersheds in LA and at seven

sites in eastern TX, using a helicopter and air-

boat (145 samples) or by walking out 920 m

into the wetland from access points reached by

boat or car (53 samples). Freshly deposited mud

was easily identifiable from the layers beneath

on the basis of color, texture, and density, and

by the absence of plant debris (Fig. 1E). At least

one preliminary sampling was done at each

location (often three or four) before the final

sample was taken. Samples for sediment depth

(in centimeters) and density (in grams per

cm3) were taken only over the vegetation zone

and not in rivulets between clumps of wetland

plants.

The average bulk density of the newly

deposited material was 0.37 g cm–3 (T1 SD 0T 0.35; range, 0 to 1.78 g cm–3; n 0 170

samples); it was highest near the coastline and

decreased inland (Fig. 2B). The bulk density of

material in these wetlands was determined by

the amount of inorganic materials, not the

organic content, and so bulk density multiplied

by deposition height is an estimate of inorganic

sediment deposition (9, 10). Sediment with a

bulk density 91 was largely composed of sand

(Fig. 1A) (9). There was sparse plant debris

(stems, leaves, and roots) in the newly

deposited sediments within a few kilometers

from the shoreline. The unconfirmed hypoth-

esis is that the source materials from offshore

came from where the bottom resistance to the

hurricane winds before landfall was the

greatest: in the shallow water zone immedi-

ately offshore of the deposition site.

The average dry weight accumulation of the

deposition layer at all sampled locations was

2.23 g cm–2 (T1 SD 0 T 3.4; range, 0 to 28.6 g

cm–2; n 0 169) and 2.25 g cm–2 in the deltaic

plain. The thickness of the newly deposited

mud was 5.18 cm (T1 SD 0 T 7.7; range, 0 to

68 g cm; n 0 186). The thickest newly de-

posited sediments were observed inland of the

area of maximum bulk density in eastern LA

but were coincidental with the sediments of

highest bulk density in western LA (Fig. 2C).

The annualized average sediment accumulation

from one hurricane was 89% of the average

accumulation in healthy saltmarsh wetlands in

the deltaic plain E0.166 g cm–2 year–1 (10)^.Sediment deposition (in grams per cm2) was

greatest near the center of the storm track (Fig.

2D). The highest values in the Chenier Plain

were on the east side of the hurricane path,

where counterclockwise winds brought a storm

surge inland, and were least on the western side,

where water was withdrawn in a southerly

direction out of the wetlands (Fig. 2, D to F).

The greatest deposition in the Deltatic Plain was

in the Breton Sound estuary, on the east side of

the Mississippi River. The marshes within the

4- longitude distance between the two hurri-

canes (approximately 300 km) had intermediate

rates of deposition. The peak water level, but

not sediment accumulation, was higher in west-

ern Lake Pontchartrain during Hurricane Rita

than during Hurricane Katrina because of these

differences in wind fields (11). The peak in bulk

density was highest on the eastern side of the

center of the storm track.

There were peaks in sediment deposition

where navigation channels confined the incom-

ing storm surge to a narrow area at Sabine Pass,

TX, and in the industrial canal by Paris Road,

New Orleans, where the Intracoastal Waterway

Fig. 1. Examples of sediments deposited by Hurricanes Katrina and Rita. (A) Sand overwash on theformer location of the coastal community of Holly Beach, LA (photo taken 18 November 2005 byR.E.T.). (B) Mud on the lawn of a St. Bernard Parish subdivision home (photo taken 27 September2005 by M. Collins). (C) Mud on the marsh surface brought by Hurricanes Katrina and Rita (phototaken 16 November 2005 by J.B.). (D) Recent mud deposit (10.5 cm) accumulated over a root massin the St. Bernard estuary (photo taken 16 November 2005 by J.B.). (E) Dried mud on the lawn of aChalmette, LA, subdivision home, September 2005 (photo taken by R. Richards).

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meets the Mississippi River Gulf Outlet. These

observations are consistent with results from

modeled storm surge velocities (12).

The total amount of recently deposited wet-

land sediments on the LA coast was calculated

using information on the average sediment

accretion and wetland area for each of four to

six subunits of four coastal regions. The min-

imum amount of inorganic sediment brought

in by these two hurricanes was estimated to be

131 � 106 metric tons (MT) (9) (Table 1). The

average occurrence of a Category 3 or larger

hurricane on this coast was every 7.88 years

from 1879 to 2005 (9) (table S1). The

annualized deposition from one hurricane

would be 8.3 � 106 MT year–1 if all hurricanes

brought an equal amount of sediments to these

wetlands. If sediments from these hurricanes are

deposited in open-water areas at the same rate as

in wetlands (9), then the pro rata deposition for

open-water areas is proportional to the open

water/wetland area (1) and is equal to 17.8 �106 MT year–1, for a combined sediment

deposition of 26.1 � 106 MT year–1.

The sediment accumulations in wetlands and

open water were 4.0 and 8.5%, respectively, of

the average annual suspended sediment load of

the Mississippi River (210 � 106 MT year–1)

(Table 1) (13). The more frequent smaller storms

not included in this analysis may also trans-

port substantial amounts of inorganic material

(14, 15).

The amount of sediments delivered to coast-

al wetlands by Hurricanes Katrina and Rita was

greater than the estimated amounts once flow-

ing through or over Mississippi River banks.

The suspended sediments overflowing uncon-

fined (natural) levees of the Mississippi River

in the past century were 4.8 � 106 MT year–1,

and 1.7 � 106 MT year–1 in a confined levee

system with occasional crevasses (Table 1).

The Caernarvon Diversion, a restoration project

located downstream from New Orleans, LA,

delivered a 2-year average sediment load of

0.115 � 106 MT year–1 (16). One conclusion

to be drawn from these numbers is that the

amount of sediment deposited on these wet-

lands from an average Category 3 or larger

hurricane is 1.7 times the amount potentially

available through unconfined overbank flood-

ing, 4.6 times more than through crevasses in

the unconfined channel, and 72 times more than

from this river diversion. The combined sedi-

ment accumulation in wetlands and open water

resulting from an average Category 3 or larger

hurricane is 5.5 times larger than the material

delivered by unconfined flow in the Mississippi

River and 227 times larger than that delivered

by the Caernarvon Diversion.

However, these comparisons are conserva-

tive estimates. Not all of the inorganic sediment

flowing from rivers and over or through levees

is deposited onto a wetland. Levees are higher

than the surrounding land because inorganics

settle out onto the levees or within the nearby

marshes. Also, the peak in river heights, and

hence in discharge, occurs in the spring when

water levels in the estuary are at their seasonal

low and wetlands are infrequently flooded (17).

Sediments that do accumulate are deposited

close to the diversion. For example, the

Caernarvon Diversion distributes about 50%

of its sediments into the wetlands for a

maximum distance of about 6 km, covering

about 15% of a direct path to the coastline

(Table 1) (18). Hurricanes, in contrast, are

much more democratic in that they flood the

entire coastal landscape with new sediments.

A coastwide perspective on sediment load-

ing to these wetlands, and perhaps to other mi-

crotidal coastal wetlands, is that most of the

inorganics accumulating in them went down

the Mississippi_s birdfoot delta before they

were deposited during large storms. The es-

timates indicate that the amount of storm-

transported material is much greater than that

introduced to wetlands from the historical over-

bank flow, from crevasses, or from river diver-

sions. In particular, hurricanes appear to be the

overwhelming pathway for depositing new in-

organic sediments in coastal wetlands in west-

ern LA, because the few riverine sources bring

relatively trivial amounts of inorganic sedi-

Table 1. Estimates of the sediment source pathways for the Mississippi River deltaic plain inLouisiana.

Sediment source pathways Amount (106 MT year–1 )

Mississippi River discharge into ocean (13) 210One hurricane every 7.88 years (table S1)

Onto wetland only 8.3Onto wetland and into open water (9) 25.9

Overbank flooding (before flood protection levees) and into open water (22) 4.79Crevasses through levees and into open water (22) 1.81Caernarvon Diversion

Into the estuary (16) 0.115Onto wetland (18) 0.06

Fig. 2. Location of re-cent sediment samplesand data arranged bylongitude. (A) Sample lo-cations (red dots) andthe distribution of coast-al wetlands in southernLA (black background).The vertical gray arrowis the crossing locationof Hurricanes Rita (west-ern LA) and Katrina (east-ern LA). (B) All samples(open circles) and sam-ples with a bulk densityvalue 91.0 g cm–3 (reddots). (C) All samples(open circles) and sam-ples with a vertical ac-cretion 93 cm (red dots).(D) Accumulation rela-tive to the longitude ofsample collection (blackcircles). (E) Bulk densityrelative to the longitudeof sample collection. (F)Vertical accretion relativeto the longitude of sam-ple collection.

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ments into the marsh. Because hurricanes are so

important to the inorganic sediment budget, other

factors must be considered to understand how to

reduce wetland losses and further their restora-

tion. Changes in the in situ accumulation of

organics, rather than the reduction of inorganic

sediments arriving via overbank flooding, are

implicated as a causal agent of wetland losses on

this coast. This is illustrated by the fact that the

soil volume occupied by organic sediments plus

water in healthy saltmarsh wetlands is 990%(10) and is certainly the same or higher in

wetlands of lower salinity. This organic portion

plays a major role in wetland soil stability and

hence in wetland ecosystem health (19).

References and Notes1. R. H. Baumann, R. E. Turner, Environ. Geol. Water Res.

15, 189 (1990).

2. T. A. Morton, J. C. Bernier, J. A. Barras, N. F. Ferina, USGSOpen-File Rep. 2005-1215 (2005).

3. G. W. Stone, X. Zhang, A. Sheremet, J. Coastal Res. 44,40 (2005).

4. J. M. Rybczyk, D. R. Cahoon, Estuaries 25, 985 (2002).5. M. L. Parsons, J. Coastal Res. 14, 939 (1998).6. D. R. Cahoon et al., J. Coastal Res. 21 (special issue), 280

(1995).7. J. P. Morgan, L. G. Nichols, M. Wright, Morphological

Effect of Hurricane Audrey on the Louisiana Coast

(contribution no. 58-3, Coastal Studies Institute, LouisianaState Univ., Baton Rouge, LA, 1958).

8. J. A. Nyman, R. D. DeLaune, H. H. Roberts, W. H. PatrickJr., Mar. Ecol. Prog. Ser. 96, 269 (1992).

9. Materials and methods are available as supportingmaterial on Science Online.

10. R. E. Turner, E. M. Swenson, C. S. Milan, in Concepts andControversies in Tidal Marsh Ecology, M. Weinstein,D. A. Kreeger, Eds. (Kluwer, Dordrecht, Netherlands,2001), pp. 583–595.

11. The peak water measured by U.S. Geological Surveywater-level gage 30174809020900, at Pass ManchacTurtle Cove near Ponchatoula, LA, in the western LakePontchartrain watershed, was about 6 cm higher duringHurricane Rita than during Hurricane Katrina, eventhough the hurricane path was over 300 km further away.

12. Storm surge model results for Hurricanes Katrina and Ritaare available at the Louisiana State University HurricaneCenter Web sites (http://hurricane.lsu.edu/floodprediction/katrina/deadly_funnel1.jpg and http://hurricane.lsu.edu/floodprediction/rita24/images/adv24_SurgeTX_LA.jpg).

13. G. J. Chakrapani, Curr. Sci. 88, 569 (2005).14. R. H. Baumann, thesis, Louisiana State Univ., Baton

Rouge, LA (1980).15. D. J. Reed, N. De Luca, A. L. Foote, Estuaries 20, 301

(1997).16. G. A. Snedden, J. E. Cable, C. Swarzenski, E. Swenson,

Estuar. Coastal Shelf Sci., in press.17. R. E. Turner, Estuaries 14, 139 (1991).18. K. W. Wheelock, thesis, Louisiana State Univ., Baton

Rouge, LA (2003).19. R. E. Turner, E. M. Swenson, C. S. Milan, J. M. Lee,

T. A. Oswald, Ecol. Res. 19, 29 (2004).

20. R. H. Kesel, Environ. Geol. Water Res. 11, 271 (1988).21. C. M. Belt Jr., Science 189, 681 (1975).22. Kesel (20) estimated the sediment load in the spring

floods using water records from 1950 to 1983 anddetermined the amount of sediment that would beavailable from unconfined overbank flooding if the leveeswere not there. The estimate is actually an overestimateof the amount available, because the artificial constric-tion of the river channel throughout the basin raised theflood stage for the same-sized discharge event (21).

23. Supported by the NSF Division of Geomorphology andLand-Use Dynamics (award EAR-061250), the NationalOceanic and Atmospheric Administration Coastal OceanProgram MULTISTRESS (award no. NA16OP2670), and aLouisiana Board of Regents Fellowship (J.S.S.). We thankJ. Gore for assistance in sampling from an airboat; E. Babinfor assistance in finding photographs; H. Hampp, our deft,safe, and considerate helicopter pilot; and B. Sen Gupta,N. N. Rabalais, and three anonymous reviewers forconstructive reviews of the manuscript.

Supporting Online Materialwww.sciencemag.org/cgi/content/full/1129116/DC1Materials and MethodsSOM TextFig. S1Table S1References and Notes

24 April 2006; accepted 1 September 2006Published online 21 September 2006;10.1126/science.1129116Include this information when citing this paper.

ACombinedMitigation/GeoengineeringApproach to Climate StabilizationT. M. L. Wigley

Projected anthropogenic warming and increases in CO2 concentration present a twofold threat, bothfrom climate changes and from CO2 directly through increasing the acidity of the oceans. Future climatechange may be reduced through mitigation (reductions in greenhouse gas emissions) or throughgeoengineering. Most geoengineering approaches, however, do not address the problem of increasingocean acidity. A combined mitigation/geoengineering strategy could remove this deficiency. Here weconsider the deliberate injection of sulfate aerosol precursors into the stratosphere. This action couldsubstantially offset future warming and provide additional time to reduce human dependence on fossilfuels and stabilize CO2 concentrations cost-effectively at an acceptable level.

In the absence of policies to reduce the mag-

nitude of future climate change, the globe is

expected to warm by È1- to 6-C over the

21st century (1, 2). Estimated CO2concentra-

tions in 2100 lie in the range from 540 to 970

parts per million, which is sufficient to cause

substantial increases in ocean acidity (3–6).

Mitigation directed toward stabilizing CO2

concentrations (7) addresses both problems but

presents considerable economic and technologi-

cal challenges (8, 9). Geoengineering (10–17)

could help reduce the future extent of climate

change due to warming but does not address the

problem of ocean acidity. Mitigation is therefore

necessary, but geoengineering could provide

additional time to address the economic and

technological challenges faced by a mitigation-

only approach.

The geoengineering strategy examined here is

the injection of aerosol or aerosol precursors Esuchas sulfur dioxide (SO

2)^ into the stratosphere to

provide a negative forcing of the climate system

and consequently offset part of the positive

forcing due to increasing greenhouse gas con-

centrations (18). Volcanic eruptions provide ideal

experiments that can be used to assess the effects

of large anthropogenic emissions of SO2on

stratospheric aerosols and climate. We know, for

example, that the Mount Pinatubo eruption EJune1991 (19, 20)^ caused detectable short-term cool-

ing (19–21) but did not seriously disrupt the

climate system. Deliberately adding aerosols or

aerosol precursors to the stratosphere, so that the

loading is similar to the maximum loading from

the Mount Pinatubo eruption, should therefore

present minimal climate risks.

Increased sulfate aerosol loading of the strato-

sphere may present other risks, such as through its

influence on stratospheric ozone. This particular

risk, however, is likely to be small. The effect of

sulfate aerosols depends on the chlorine loading

(22–24). With current elevated chlorine loadings,

ozone loss would be enhanced. This result would

delay the recovery of stratospheric ozone slightly

but only until anthropogenic chlorine loadings

returned to levels of the 1980s (which are ex-

pected to be reached by the late 2040s).

Figure 1 shows the projected effect of mul-

tiple sequential eruptions of Mount Pinatubo

every year, every 2 years, and every 4 years.

The Pinatubo eruption–associated forcing that

was used had a peak annual mean value of

–2.97 W/m2 (20, 21). The climate simulations

were carried out using an upwelling-diffusion

energy balance model EModel for the Assessment

of Greenhouse gas–Induced Climate Change

(MAGICC) (2, 25, 26)^ with a chosen climate

sensitivity of 3-C equilibrium warming for a CO2

doubling (2 � CO2). Figure 1 suggests that a

sustained stratospheric forcing of È–3 W/m2 (the

average asymptotic forcing for the biennial

eruption case) would be sufficient to offset much

of the anthropogenic warming expected over the

next century. Figure 1 also shows how rapidly the

aerosol-induced cooling disappears once the in-

jection of material into the stratosphere stops, as

might become necessary should unexpected envi-

ronmental damages arise.

Three cases are considered to illustrate pos-

sible options for the timing and duration of aerosol

injections. In each case, the loading of the strato-

sphere begins in 2010 and increases linearly to

National Center for Atmospheric Research, Post Office Box3000, Boulder, CO 80307–3000, USA. E-mail: wigley@ucar.edu

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