Arrieta López de Uralde, Jesús M.

Herndl, Gerhard J.

Weinbauer, Markus G.

Digital.CSIC

Limnol. Oceanogr., 52(2), 2007, 916–918E 2007, by the American Society of Limnology and Oceanography, Inc.Response to: ‘‘Interpreting the results of oceanic mesoscale enrichment experiments: Caveatsand lessons from limnology and coastal ecology’’In their comment, Hale and Rivkin (hereafter referredto as HR) criticize the general design of the open-oceanfertilization experiments carried out so far because of thelack of replication. The basic design involves fertilizinga large area of the surface ocean and then monitoring thebiological responses inside the fertilized patch and those inunfertilized out-stations allocated in the vicinity of thefertilized area. Logistic constrains such as ship time andresource availability make it unfeasible to fertilize andcontinuously monitor more than one patch at a time. Inaddition, true replication in large-scale oceanic perturba-tion experiments may not be feasible at all because itwould require finding several physically separated sitespresenting similar initial conditions and subjected tosimilar environmental forcing for the length of theexperiment. Therefore, replication efforts are likely toresult in approximate repetition rather than exact replica-tion. Several oceanic mesoscale enrichment experimentshave reported increases in phytoplankton biomass orprimary production inside the fertilized patches ascompared with unfertilized surrounding waters (Boyd2002; Boyd et al. 2004; Coale et al. 2004; De Baar et al.2005; Thingstad et al. 2005; Le Clainche et al. 2006), whichhave been attributed to the effect of enrichment. HRrightfully argue that the use of unreplicated experimentaldesigns means that it is not possible to unequivocallyattribute the measured responses to the effect of theenrichment.916 CommentBecause of this lack of replication of experimental units,HR criticize the interpretation and the validity of thestatistical analyses performed in one of our publications inthis journal (Arrieta et al. 2004), hereafter referred to asA2004 or ‘‘our paper.’’ Testing for statistically significanttreatment effects would require replicated experimental unitsand controls, but this is not what we did. As HRacknowledge in their comment, the Mann–Whitney U-testcan be used to test whether there are differences between thevalues measured inside and outside of the fertilized patch(this is what we did). Note that every time that statistics arementioned in A2004, they are also explicitly referred to ‘‘thevalues’’ of the bacterial properties found inside and outsidethe patch and not to the treatment. HR also finddiscrepancies between their calculations of the Mann–Whitney U-test and the values we reported in our paper.They conclude that the differences are due to the ‘‘un-explained and selective exclusion of data’’ in A2004. Thedecision of taking only the values after day 5 was notarbitrary, as suggested by HR, but was based on visualinspection of the data shown in figs. 1, 2, and 3 in A2004.These figures suggest that if there were any differencesbetween the fertilized patch and the surrounding waters, thedifferences were not immediately measurable in the first daysof the experiment but only became apparent after day 5.There are several instances in the results and discussionwhere the phrase ‘‘after day 5’’ is mentioned, to clarify thatour claims refer only to that period. Therefore, we used theMann–Whitney U-test only to evaluate whether the values ofthe different bacterial properties measured inside the patchafter day 5 were different from those measured in thesurrounding waters. Thus, the values reported in A2004 aremeaningful within the context mentioned in our paper anduseful to confirm the presence of increased values of somebacterial properties inside the fertilized patch as comparedwith unfertilized waters as suggested by graphical inspection.An additional limitation of this design, not included inthe criticisms formulated by HR, is the use of unlabeledout-stations. Open ocean surface waters are highly dynam-ic; the location and shape vary over time. Thus, it isnecessary to use drifting buoys and conservative tracers likeSF6 to ensure that consecutive samples come from theoriginally fertilized patch. However, out-stations arecommonly chosen on the basis of the presence ofbackground levels of SF6 in areas close to the fertilizedpatch, but there is no indication of whether or not the out-of-the-patch samples belong to a coherent experimentalunit. Therefore, in the absence of a mechanism allowingconsecutive sampling of a defined water mass, out-of-thepatch measurements can only be used as an indication ofthe variability of ‘‘background’’ levels of the parameterstudied in the area. Although we dedicated the first lines ofthe discussion to stress this point in A2004, HR do notmention this issue, which should be added to their list ofconcerns. This limitation affects directly the alternativeanalyses of our data proposed by HR. These authorssuggest the use of an analysis of covariance (ANCOVA)including time as a covariate in order to assess whether thetemporal trends in the Fe-fertilized patch did differ fromthose observed in the surrounding waters. However,because the out-of-the-patch stations are not necessarilylinked to a coherent water mass, repeated sampling of thesame experimental unit over consecutive days cannot betaken for granted. Therefore, it is impossible to determinewhether any development observed in the variablesmeasured outside the patch is the result of an ongoingprocess or that of randomly sampling different sites. Thisreasoning would preclude the use of ANCOVA for the out-of-the-patch data.Although we are not confident about the usability ofANCOVA in this situation, we tried to repeat the analysesreported by HR. As stated by HR, we calculated the meanvalues of each parameter over the upper 40 m of the watercolumn inside the patch and in the surrounding waters,excluding only those measurements of the edge stations, asin the original paper. ANCOVA analyses are based ona linear model. If this model fails, inferences of ANCOVAwill be in error (Sokal and Rohlf 1997). Because most of theobserved responses were not linear with time, we triedtransforming the data (log or square root) as stated by HRto obtain a significant linear regression (p , 0.05) withtime. The significance of different regression lines obtainedby the use of untransformed values, log-transformedvalues, or square root–transformed values versus time islisted in Table 1. Most of the regression coefficients werenot significant when either untransformed values or any ofthe proposed transformations were used, and no single casewas observed where the regression coefficients weresignificant for both in- and out-of-the-patch values by thesame transformation. Moreover, visual examination ofresiduals versus fitted data plots shows clear evidence ofnonlinearity and/or high leverage for most of the regressionlines by using either transformed or untransformed data.Although HR claim to have tested the linearity require-ments of the ANCOVA analysis, we did not find any usablesignificant linear relationship in the data. Therefore, wemust conclude that the results of their ANCOVA analysisare meaningless and should be disregarded. All analyseswere conducted using R 2.2.0 (R Development Core Team2005).The most important valid criticism formulated by HR intheir comment is that we concluded that the observedinduction of bacterial activity was caused directly orindirectly by iron fertilization. We admit that it is notpossible to completely rule out alternative explanationswith an unreplicated experiment. This is an important factthat has been ignored in previous reports where theobserved biological responses have been attributed to theeffect of iron enrichment (Boyd 2002; De Baar et al. 2005;Le Clainche et al. 2006), including those signed by HR(Boyd et al. 2004; Le Clainche et al. 2006). Although eachof these unreplicated experiments alone may provide weakevidence in favor of the claimed effect of iron fertilization,the fact that different teams have found an enhancement ofprimary production in different regions of the oceancannot be ignored. The repetition of these unreplicatedexperiments by different teams that used sometimesdifferent methodologies adds weight to our inference(Hawkins 1986) and may be more informative than merereplication (Carpenter 1990). Thus, we would like to stressComment 917that despite the design limitations outlined by HR, theopen-ocean mesoscale enrichment experiments performedso far have made very important contributions to ourunderstanding of biological processes in high nutrient–lowchlorophyll (HNLC) regions of the ocean. The repetitionof unreplicated experiments has resulted in compellingevidence in favor of the hypothesized effects of ironfertilization on phytoplankton in HNLC regions of theocean. We are confident that similar contributions fromrecent unreplicated experiments will be extremely useful inelucidating the dynamics of other compartments of thefood web, which have received comparatively less atten-tion. Future reports on the outcome of unreplicatedperturbation experiments in the open ocean should discussthe limitations of the experimental design. However, theselimitations should not be an excuse to disregard these dataand those not yet published, because accumulatingevidence will be an invaluable source of information forfuture meta-analyses.Finally, we agree with HR in that the design of futureopen-ocean fertilization experiments should be improved.Although the logistic constraints of open ocean researchare very different from those in limnology and coastalecology, we may be able to adapt some of the designs thathave been successfully applied by our colleagues.Jesu´s M. ArrietaInstituto Mediterra´neo de Estudios Avanzados (CSIC-UIB)Miquel Marque´s 2107190 Esporles, Mallorca, SpainMarkus G. WeinbauerLaboratoire d’Oce´anographie de Villefranche (LOV)B.P. 2806234 Villefranche-sur-mer, Cedex-FranceG. J. HerndlDepartment of Biological OceanographyRoyal Netherlands Institute for Sea Research (NIOZ)P.O. Box 591790 ABDen Burg, The NetherlandsReferencesARRIETA, J. M., M. G. WEINBAUER, C. LUTE, AND G. J. HERNDL.2004. Response of bacterioplankton to iron fertilization in theSouthern Ocean. Limnol. Oceanogr. 49: 799–808.BOYD, P. W. 2002. The role of iron in the biogeochemistry of theSouthern Ocean and equatorial Pacific: A comparison of insitu iron enrichments. Deep Sea Res. II 49: 1803–1821.———, AND oTHERS. 2004. The decline and fate of an iron-inducedsubarctic phytoplankton bloom. Nature 428: 549–553.CARPENTER, S. R. 1990. Large-scale perturbations—opportunitiesfor innovation. Ecology 71: 2038–2043.COALE, K. H., AND oTHERS. 2004. Southern Ocean iron enrichmentexperiment: Carbon cycling in high- and low-Si waters.Science 304: 408–414.DE BAAR, H. J. W., AND oTHERS. 2005. Synthesis of ironfertilization experiments: From the Iron Age in the Age ofEnlightenment. J. Geophys. Res. 110: C09S16.HAWKINS, C. P. 1986. Pseudo-understanding of pseudoreplication:A cautionary note. Bull. Ecol. Soc. Am. 67: 184–185.LE CLAINCHE, Y., AND oTHERS. 2006. Modeling analysis of the effectof iron enrichment on dimethyl sulfide dynamics in the NEPacific (SERIES experiment). J. Geophys. Res. 111: C01011.R DEVELOPMENT CORE TEAM. 2005. R: A language and environ-ment for statistical computing [Internet]. Vienna, Austria: RFoundation for Statistical Computing [accessed July 2006].Available from http://www.R-project.orgSOKAL, R. R., AND F. J. ROHLF. 1997. Biometry, 3rd ed. W. H.Freeman.THINGSTAD, T. F., AND oTHERS. 2005. Nature of phosphoruslimitation in the ultraoligotrophic eastern Mediterranean.Science 309: 1068–1071.Received: 7 April 2006Amended: 2 August 2006Accepted: 8 August 2006Table 1. Significance (p values) of the regression lines of untransformed and transformedbacterial properties versus time. Values in bold indicate a significant (p , 0.05) slope of theregression line.UntransformedSquare-roottransformedLogtransformedOut In Out In Out InBacterial abundance 0.64 0.02 0.67 0.02 0.70 0.02Leucine incorporation 0.28 0.16 0.27 0.18 0.27 0.20Thymidine incorporation 0.24 0.36 0.22 0.40 0.21 0.44a-glucosidase 0.82 0.90 0.77 0.81 * 0.52b-glucosidase 0.96 0.49 0.95 0.42 0.94 0.40Aminopeptidase 0.82 0.11 0.81 0.12 0.81 0.12Cell-specific leucine incorporation 0.67 0.19 0.65 0.22 0.63 0.24Cell-specific thymidine incorporation 0.54 0.39 0.50 0.37 0.46 0.35Cell-specific a-glucosidase 0.95 0.58 0.85 0.72 * 0.99Cell-specific b-glucosidase 0.85 0.80 0.90 0.96 0.94 0.85Cell-specific aminopeptidase 0.71 0.17 0.71 0.17 0.71 0.17*a-glucosidase and cell-specific a-glucosidase contained ‘‘zero’’ values, and therefore the logarithmictransformation was not used.918 Comment

Response to Interpreting the results of oceanic mesoscale enrichment experiments: Caveats and lessons from limnology and coastal ecology

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