Journal of

Plankton Research

plankt.oxfordjournals.org

J. Plankton Res. (2016) 38(2): 331– 347. First published online December 4, 2015 doi:10.1093/plankt/fbv098

Costa Rica Dome: Flux and Zinc Experiments

Factors affecting Fe and Zn contents of mesozooplankton from the Costa Rica Dome STEPHEN B. BAINES1*, XI CHEN2, BENJAMIN S. TWINING3, NICHOLAS S. FISHER2 AND MICHAEL R. LANDRY4 1

2 DEPARTMENT OF ECOLOGY AND EVOLUTION, STONY BROOK UNIVERSITY, STONY BROOK, NY 11789-5245, USA, SCHOOL OF MARINE AND ATMOSPHERIC 3 SCIENCES, STONY BROOK UNIVERSITY, STONY BROOK, NY 11789-5000, USA, BIGELOW LABORATORY FOR OCEAN SCIENCES, EAST BOOTHBAY, ME 04544, USA AND 4 SCRIPPS INSTITUTION OF OCEANOGRAPHY, UNIVERSITY OF CALIFORNIA AT SAN DIEGO, 9500 GILMAN DR., LA JOLLA, CA 92093-0227, USA

*CORRESPONDING AUTHOR: [email protected]

Received May 18, 2015; accepted October 22, 2015 Corresponding editor: Roger Harris

Mineral limitation of mesozooplankton production is possible in waters with low trace metal availability. As a step toward estimating mesozooplankton Fe and Zn requirements under such conditions, we measured tissue concentrations of major and trace nutrient elements within size-fractioned zooplankton samples collected in and around the Costa Rica Upwelling Dome, a region where phytoplankton growth may be co-limited by Zn and Fe. The geometric mean C, N, P contents were 27, 5.6 and 0.21 mmol gdw21, respectively. The values for Fe and Zn were 1230 and 498 nmol gdw21, respectively, which are low compared with previous measurements. Migrant zooplankton caused C and P contents of the 2 – 5 mm fraction to increase at night relative to the day while the Fe and Zn contents decreased. Fe content increased with size while Zn content decreased with size. Fe content was strongly correlated to concentrations of two lithogenic tracers, Al and Ti. We estimate minimum Fe:C ratios in large migrant and resident mixed layer zooplankton to be 15 and 60 mmol mol21, respectively. The ratio of Zn:C ranged from 11 mmol mol21 for the 0.2– 0.5 mm size fraction to 33 mmol mol21 for the 2 – 5 mm size fraction. KEYWORDS: mineral limitation; size fractions; lithogenic

I N T RO D U C T I O N While several studies have characterized metal contents of zooplankton in situ, relatively little is known about the

metal contents of zooplankton from regions of the ocean where growth of primary producers are known to be limited by low trace element concentrations. The trace

available online at www.plankt.oxfordjournals.org # The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: [email protected]

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metal content of zooplankton under such situations may determine if their growth and reproduction may be reduced by low trace metal concentrations in their food (Sterner and Elser, 2002; Chen et al., 2011, 2014). Iron, for example, is an essential element for all organisms, required in large amounts by proteins of the electron transport system, as well as in a wide variety of other proteins (Frau´sto da Silva and Williams, 2001). Zinc is also required by consumers as a structural element in finger motifs of proteins involved in gene regulation, translation and deoxyribonucleic acid (DNA) repair (Frau´sto da Silva and Williams, 2001). Because Fe and Zn contents of trace metals limited phytoplankton can be substantially lower than in natural mesozooplankton (Chen et al., 2011), obtaining sufficient amounts of these elements to produce new tissue may pose a substantial challenge for zooplankton when trace metals are limiting to primary production. The threshold Fe:C in food below which growth and reproduction may be affected is primarily, although not solely, determined by the Fe:C content in zooplankton tissues (Chen et al., 2014). Indeed, Acartia tonsa exhibits lower egg production when fed Fe-limited diatoms than when fed Fe-replete diatoms (Chen et al., 2011). It is an open question whether zooplankton trace metal concentrations can vary so as to reduce the effects of food elemental composition. While the metal concentration in tissues of many organisms is known to increase with environmental concentrations at high levels of dissolved metal (Luoma and Rainbow, 2005), it is less clear whether such flexibility is typical when concentrations of metals in the diet are low. Mesozooplankton communities in chronically trace metal-limited regions could be adapted to economize and reduce their requirement for trace elements, either through reduced allocation to pathways involving metalloenzymes or through substitution of rarer metals in those enzymes for more common ones (Frau´sto da Silva and Williams, 2001). However, tradeoffs associated with thriftier use of metals (such as reductions in respiratory potential, DNA repair or transcription rates) could also place limits on the minimum Fe and Zn requirement that an organism could possess and remain ecologically successful. Life history strategies with low physiological requirements for metals may be more common under such a restriction. For example, larger zooplankton may have a lower requirement for Fe than do smaller forms because of their lower mass-specific metabolism. Alternatively, when faced with poor quality, food mesozooplankton may also exploit those prey that are likely to have higher trace element contents. Migratory plankton could feed on deep phytoplankton communities, which are exposed to higher trace metal concentrations and subject to slower growth, and thus less growth dilution of metals (Finkel et al., 2006), or on detritus which has scavenged

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metal from deeper waters. Selective predation on Fe or Zn rich prey species could also allow mesozooplankton to access a limiting metal more efficiently than bulk measurements of plankton Fe contents would suggest is possible. Nitrogen fixers typically have high Fe quotas and some diatoms attain much higher Fe contents than typically observed for other cooccurring phytoplankton, possibly due to their ability to store Fe (Sanudo-Wilhelmy et al., 2001; Kustka et al., 2003; Marchetti et al., 2009). Diatoms also typically have high Zn concentrations relative to co-occurring phytoplankton (Twining et al., 2004, 2011), while cyanobacteria can be relatively depleted in Zn (Twining et al., 2010) depending on whether extra Zn is needed for enzymes like alkaline phosphatase (Shaked et al., 2006). The ability to exploit deeper communities or to selectively remove trace metalrich species should be highly advantageous when trace element availability is low. The Costa Rica Upwelling Dome (CRD) is a suitable place to assess zooplankton trace metal contents under trace metal-limited conditions. The CRD is an openocean cyclonic eddy upwelling system in the eastern tropical Pacific, centered at 88N, 908W from July to November and with a diameter of 100– 900 km (Wyrtki 1964; Hofmann et al., 1981; Fiedler, 2002). The thermocline is unusually shallow at 10– 20 m because cyclonic surface flows cause Ekman pumping right at the shallowest point of an east –west running thermocline ridge that lies between the north equatorial and equatorial counter currents (Fiedler, 2002). Phytoplankton productivity and biomass in the CRD is highest during the summer leading to elevated zooplankton biomass, which presumably attracts the schools of blue whales that frequent the area (Fiedler, 2002). However, even when chlorophyll is elevated, this area has relatively high concentrations of unutilized macronutrients compared with adjacent oligotrophic regions (Broenkow, 1965; Fiedler, 2002; Ahlgren et al., 2014), suggesting the presence of high nutrient-low chlorophyll conditions (Minas et al., 1986). Dissolved Fe concentrations in surface waters are low enough to limit both eukaryotes and Synechococcus (Ahlgren et al., 2014). Shipboard experiments suggest that growth of eukaryotic phytoplankton in the CRD is Zn and Fe co-limited (Franck et al., 2005). Possibly reflecting the influence of trace elements low Zn concentrations and the abundance of dissolved cobalt, the biomass in surface waters is dominated by prokaryotic picoplankton Synechococcus, which forms the foundation of local food-webs (Saito et al., 2005; Ahlgren et al., 2014). Oxygen is depleted below the photic zone, and is largely absent between 400 and 1500 m. We present trace metal contents of zooplankton from the Flux and Zn Experiment (FluZiE) study of plankton and biogeochemical processes in the Costa Rican Dome that took place on cruise MV1008 of the R/V Melville

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from 22 June to 25 July 2010. Conditions in the CRD during the July 2010 were unusual in that phytoplankton biomass remained depressed relative to other years, possibly due to cloudy conditions (Landry et al., 2016). While Synechococcus cells were more abundant in the CRD than typical of other tropical waters (Taylor et al., 2016), they were not as abundant as previous observed in the region (Saito et al., 2005). Still, dissolved Zn was depleted relative to phosphate in surface waters at some stations, indicating that trace metal limitation was possible, if less extreme than typical for the region in other years (Chappell et al., 2016). Nutrient addition experiment suggested limitation of diatoms by Si, possibly because the shallow mixed layers allowed efficient export of Si to depth (Krause et al., 2016). However, at some stations, there was also an indication of co-limitation of primary producers by Zn and Fe (Chappell et al., 2016). If evidence of trace element limitation exists in the CRD during such conditions, then it is likely to be more prevalent in years when phytoplankton biomass builds up more and depletes limiting nutrients more effectively. We have three basic goals. First, we want to determine if zooplankton in the CRD region display systematically lower Fe and Zn contents than exhibited in metal replete regions of the ocean that have already been sampled. Second, we want to assess whether trace metal contents of mesozooplankton communities differ depending on whether they are collected during the day and night, or among mesozooplankton of different size classes. Such differences could suggest ways that that trace elemental requirements vary among migrant and resident zooplankton communities. Finally, we will look for correlations of Fe and Zn contents to those of other metals. Concentrations of other metals (such as Ni and Mn) differ among functional types of single-cell protozoan prey (Twining et al., 2004, 2011) and with the depth at which those prey live (Twining et al., 2010). Consequently, such correlations may indicate whether zooplankton get their Fe or Zn by feeding on certain parts of the protozoan community or at certain depths. To address this question, we measured a large number of trace metals in zooplankton size classes in association with four semi-Lagrangian process studies, as well along a transect through the region.

METHOD Study sites and sampling Mesozooplankton samples were collected at the CRD on a cruise between 22 June and 26 July 2010. Sampling was conducted within 6.6– 10.08N and 87.5 – 92.98W (Fig. 1). The entire cruise included one large transect

through the region consisting of 13 stations and 5 semi-Lagrangian drift cycles that followed the evolution of the plankton within a body of water over 4 days using a satellite-tracked drifter drogued at 15 m (Landry et al., 2016). During the transect through the CRD region, mesozooplankton samples were collected every 5 – 8 h, regardless of time of day. During the experimental cycles, samples were collected at the onset and end of each cycle at each station (day and night). The first drift cycle was not sampled for zooplankton trace metal content. Zooplankton samples were conducted with oblique tows using a standard 1-m2 ring net with 202-mm Nitex mesh. Tows extended from 130 –190 m to the surface. Samples were fractionated into 4 size ranges: 0.2– 0.5, 0.5 – 1, 1 – 2 and 2– 5 mm by sieves. Subsamples for elemental analysis were transferred to a trace metal clean hood, rinsed with 10 mL of oxalate reagent for 10 min (Tovar-Sanchez et al., 2003) and then 30 mL of trace metal free seawater for 10 min before being transferred into trace metal clean centrifuge tubes and stored in a 2808C freezer. Trace metal free seawater was produced by filtering seawater from a trace metal clean rosette through acid cleaned 0.2-mm pore size filters, and then passing the filtrate through a Chelex-100 resin. Samples were freeze-dried in the laboratory before further processing for metal concentrations.

Elemental analysis Subsamples of freeze-dried zooplankton were homogenized by crushing and weighed before being analyzed for C and N masses using a Flash EA1112 CN Analyzer (CE Elantech). Atropine was used as a standard; analytical precision was ,1%. Another portion of each freeze-dried zooplankton sample was analyzed for P. The sample was crushed and weighed before being transferred into glass scintillation vials. The remaining approach followed (Solorzano and Sharp, 1980). Specifically, vials with samples were then combusted at 4508C for 5 h to release orthophosphate from zooplankton tissues. After cooling, 10 mL of 0.5 mol L21 hydrochloric acid was added to each vial to allow P extraction at 908C for 2 h. After cooling, 2.5 mL of the extracted solution was pipetted from each vial, and 0.5 mL of a mixed reagent of ammonium molybdate, sulfuric acid, ascorbic acid and potassium antimonyl tartrate was added. After 2 h in the dark, absorbance of each sample was read at 885-nm wavelength with a Varian Cary 50 Bio Ultra-Violet - Visible light spectrophotometer (Varian, Inc., NC, USA). Absorbance of samples was compared with a standard curve and to obtain P content. A third portion of freeze-dried zooplankton samples was digested and analyzed for elemental concentrations

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Fig. 1. Locations of stations for which trace metal contents of mesozooplankton size fractions were taken. The closed circles represent stations during the transect through the Costa Rica upwelling Dome (Stations 1– 12). The open circles are stations associated with semi-Lagrangian drift studies (Cycles 2– 5).

of P, Cd, Al, Mo, Fe, Co, Cu, Zn, Ni and Ti using a Thermo-Finnigan Element2 high-resolution inductively coupled plasma mass spectrometer with an elemental scientific instruments Apex desolvating nebulizer and a CETAC ASX-100 autosampler (Twining et al., 2011). Approximately 0.5 g of each sample was digested in 2 mL of a solution containing 15.2 M Optima HNO3 and 1.45 M Optima HF at 1108C for 4 h in sealed Teflon digestion vials. Following digestion, samples were diluted 10-fold with 0.32 M Optima HNO3 containing In-115 (5 ppb) as an internal standard. Elemental concentrations were initially normalized to dry weight and then divided by P, C and N content per dry weight to determine elemental ratios.

Statistical analysis All continuous variables including zooplankton elemental contents were log-transformed prior to analysis to insure normality and homoscedasticity. Outliers reflecting unique sampling, contamination, analysis or transcription errors were removed before analyses. To do so, we calculated jack-knife multivariate Mahalanobis

distance for each observation using the contents (mol g-dry wt21) for every element (Twining et al., 2004; Twining and Fisher, 2004). If the distance of any observation exceeded the threshold of 5, it was excluded and the distances were recalculated using the new data. The process was repeated until no observations exceeded the threshold. Three observations out of 108 were excluded using this process. Differences among size fractions and locations were analyzed by analysis of variance (ANOVA). Tukey’s honestly significant difference (HSD) test was used to test for post hoc differences among groups. While samples were only collected around noon and midnight for the Lagrangian studies, samples were collected at a range of times over course of a day during the transect across the CRD. Therefore, when testing for diel differences for data that included the transect samples, we fitted a quadratic relationship between time of day and elemental content or elemental ratios. A step-wise regression approach was used to explore possible factors influencing Zn and Fe contents and ratios in mesozooplankton. Transect and cycle data were modeled separately to determine if the patterns were

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consistent across the two independent datasets. Linear models predicting Fe or Zn normalized to dry weight, P, C and N were built using all other measured elemental concentrations normalized in the same way as the response variables. Categorical predictors for the cycle data included size fraction, location and night/day. For the transect data, sampling times could not be categorically separated into day and night, so a quadratic function was used to relate time of day to Zn and Fe contents. First-order interaction terms for categorical predictors were included as potential predictors except for the interaction between location and size fraction in the cycle data, which consumed too many degrees of freedom. The dataset was too sparse and predictors too correlated to include all predictors at once and establish an interpretable model. So we adopted a model selection procedure using a standard forward-backward step-wise model selection process (Draper and Smith, 1981). Predictor variables were added to the model based on which had the lowest P-value after entry, as long as that P-value was ,0.25. After each addition, P-values of all included predictors were determined and any variable with P . 0.25 was excluded. This alternate addition/ subtraction was continued until no more predictors met the threshold for entry or removal. Variables were evaluated and entered as whole effects. The high threshold P-value used here allows more variables to be considered and increases the possibility of finding the best combination of variables. However, the result can be a model with many parameters that do not meet statistical significance. We were primarily interested in which variables were included as predictors, not on the performance of the model per se. Consequently, the model was pruned by sequentially removing variables with the highest

P-values until no more variables with P . 0.05 were left as predictors. We also explored alternative model structures to determine if covariates could equally explain the patterns. All analyses were performed by JMP 7.01 (SAS).

R E S U LT S The average C, N and P contents for all zooplankton were 27, 5.6, 0.21 mmol gdw21, respectively (Table I). Carbon and N contents were tightly correlated (r ¼ 0.93, P , 0.0001, Table II), whereas P content was less well correlated to both C and N contents. Because patterns of carbon- and nitrogen-normalized metal concentrations were so similar, we only deal with carbon-normalized contents below. The average contents of Fe and Zn were 1230 and 498 nmol gdw21, respectively. Ratios of C:N, C:P and N:P were 4.8, 145 and 30.3, respectively. Ratios of Fe:C and Fe:P were 46 and 5875 mmol mol21, respectively, whereas Zn:C and Zn:P ratios were 2.5  lower, averaging 18 and 2377 mmol mol21. Concentrations of all measured elements differed among size fractions, although patterns differed among elements. Both C and N contents were lower in the larger size fractions (P , 0.0001 for C; P ¼ 0.012 for N, Tables I and III). In contrast, P content was subtly greater in the larger size fractions (P ¼ 0.045). As might be expected from these patterns C:N (P ¼ 0.012), C:P (P ¼ 0.0004) and N:P (P ¼ 0.01) were all significantly higher in the smaller size fractions. The contents of Fe and Zn exhibited opposite patterns to each other, with Fe content declining with size in the 0.2 – 2 mm size range (P ¼ 0.003, Fig. 1, Tables I and III), whereas the Zn content increased with size (P , 0.0001, Fig. 1, Tables I

Table I: Statistics and geometric means of elemental contents and elemental ratios from a one-way ANOVA with size fraction as a predictor r2

P 21

0.2 – 0.5 mm

0.5 –1 mm

1 –2 mm

2–5 mm

All size fractions

28.2 + 3% 5.8 + 3% 0.20 + 6% 4.8 + 1% 153.9 + 4% 31.9 + 4%

26.1 + 3% 5.4 + 3% 0.22 + 6% 4.8 + 1% 137.9 + 4% 28.5 + 4%

24.1 + 3% 5.2 + 3% 0.24 + 6% 4.6 + 1% 130.3 + 4% 28.2 + 4%

27 + 2% 5.6 + 2% 0.21 + 3% 4.8 + 1% 146 + 2% 30 + 2%

1400 + 18% 402 + 8% 50 + 19% 6997 + 19% 14 + 9% 2009 + 9%

1231 + 17% 572 + 8% 47 + 18% 5720 + 18% 22 + 8% 2657 + 9%

728 + 18% 791 + 8% 30 + 20% 3078 + 20% 32 + 9% 3343 + 10%

1230 + 9% 498 + 5% 46 + 9% 5875 + 10% 18 + 6% 2377 + 5%

21

Macro-elements (mmol g dw ) and ratios (mol mol ) C 0.22 ,0.0001 29.1 + 3% N 0.10 0.012 5.9 + 3% P 0.08 0.045 0.19 + 6% C:N 0.10 0.012 4.9 + 1% C:P 0.16 0.0004 161.1 + 4% N:P 0.11 0.01 32.9 + 4% Trace metals (nmol gdw21) and ratios (mmol mol21) Fe 0.13 0.003 1728 + 17% Zn 0.41 ,0.0001 351 + 8% Fe:C 0.07 0.05 59 + 19% Fe:P 0.16 0.0004 9069 + 19% Zn:C 0.45 ,0.0001 12 + 9% Zn:P 0.21 ,0.0001 1841 + 9%

Standard errors are de-transformed standard errors of the ANOVA group means and are expressed as a percentage of the geometric mean. The P-values are for F-tests for the predictor variable size fraction. Data include samples from both the transect stations and the stations from the last four Lagrangian process studies (n ¼ 105).

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Table II: Correlation coefficients among logtransformed elemental concentrations (n ¼ 105) log N log P log Fe log Zn

log C

log N

log P

log Fe

0.93 0.41 20.16 20.40

0.50 20.27 20.31

20.16 0.24

0.06

Table III: Evidence for diel variability of elemental content and elemental ratios with time of day Diel variation

log C log N log P log C:N log C:P log N:P log Fe log Zn log Fe:C log Fe:P log Zn:C log Zn:P

0.2 – 0.5 mm (n ¼ 27)

0.5 –1 mm (n ¼ 26)

1 – 2 mm (n ¼ 27)

2–5 mm (n ¼ 24)

r2

P

r2

P

r2

P

r2

P

0.02 0.03 0.07 0.03 0.01 0.02 0.15 0.08 0.16 0.16 0.1 0.12

0.77 0.69 0.42 0.71 0.85 0.80 0.14 0.39 0.13 0.12 0.30 0.21

0.01 0.01 0.08 0.04 0.11 0.08 0.00 0.04 0.00 0.01 0.05 0.10

0.93 0.92 0.40 0.65 0.28 0.39 0.99 0.63 1.00 0.86 0.59 0.30

0.24 0.39 0.22 0.23 0.10 0.03 0.12 0.13 0.13 0.15 0.25 0.38

0.038 0.003 0.052 0.042 0.30 0.71 0.22 0.19 0.18 0.15 0.030 0.004

0.65 0.64 0.56 0.28 0.35 0.50 0.24 0.33 0.33 0.42 0.56 0.67

< 0.0001 < 0.0001 0.0001 0.025 0.004 0.0005 0.054 0.015 0.012 0.002 0.0001 < 0.0001

Statistics refer to a quadratic model that relates elemental content and ratios to local time of day. The P-value is the significance of the squared parameter in the quadratic model. Values in bold are significant at the 95% level.

and III). Zn:C and Zn:P ratios increased significantly with size (P , 0.0001, Tables I and III). The ratios Fe:C (P ¼ 0.05) and Fe:P (P ¼ 0.0004) both decreased with increasing size of fractions (Tables I and III). Zooplankton elemental concentrations varied with time of day for the two larger size groups (Fig. 2 and Table III), indicating a clear difference in elemental composition of vertical migrants and surface resident communities. Both the Fe and Zn contents in the 2 – 5 mm size group had the highest values at mid-day and the lowest at midnight, displaying a parabolic distribution (P ¼ 0.054 for Fe, P ¼ 0.015 for Zn, Fig. 4 and Table III). In contrast, macro-elements C, N and P displayed the opposite trend, with the lowest concentrations at mid-day and higher concentrations at night (P , 0.0001 for all three elements in the 2 –5 mm group, Fig. 4 and Table III). This pattern also held for C and N contents in the 1-2 mm size fraction, although to a lesser degree. Because trace metals and macro-nutrient elements had different patterns of variation in the elemental contents

Fig. 2. Fe:C and Zn:C in different size classes of zooplankton measured in this study and published in the literature (see Tables VI and VII for references). Open circles in the left-hand panels represent individual field observations. The dark circles are the median values for each size fraction. Ratios have been directly measured for this study. For the literature data the ratio was determined from Fe and Zn contents reported in Tables VI and VII assuming a C:dw ratio of 0.325 (as measured here). Mixed zooplankton refers to net samples that aggregate different species. Each dot for the copepod, euphausiid and amphipod data is a geometric mean for all individuals of a species. Dots represent the geometric mean and bars ¼ 1 standard error.

with the sampling time of a day, zooplankton Fe:C, Fe:P, Zn:C and Zn:P ratios showed even more pronounced parabolic distributions in both of the 1 – 2 and 2 – 5 mm size groups (Table III). Differences in patterns of elemental content between night and day indicate that the vertically migrating fraction of the mesozooplankton community was on average markedly richer in P and C, and poorer in Zn, than the community of large zooplankton that was resident in the upper 150 m throughout the day (Fig. 4). P contents of the 2 –5 mm size class were 60% greater at night than the average for all size classes during day. During the day, carbon content tended to decline with size. This decline in carbon content with size disappeared at night because the carbon content of the largest size fraction during that period was 47% higher than during the day time. This pattern implies that the carbon poor community of larger zooplankton resident in the upper 150 m during the day was augmented at night by a vertically migrating community that was more carbon rich. These large migrants

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had to be more carbon-rich even than the zooplankton in the smaller size classes. The difference in Zn contents between the largest and smallest size fractions was more pronounced during day (3-fold) than during the night (2-fold), indicating that migrants were Zn poor (Fig. 4). However, the day – night difference in the Zn content of the 2 – 5 mm fraction was not statistically significant. The increase in Zn:C with zooplankton size was even more pronounced, amounting to a 4-fold difference between day and night samples of the largest size class (Fig. 3). This difference was statistically significant (Fig. 4). For Fe, the only statistically significant difference between night and day was for the largest size fraction, for which Fe content was 3.5 times lower at night than during the day, and Fe:C was more than 5 times lower (Fig. 4). This implies an Fe-poor migrant community in the 2–5 mm fraction.

Step-wise regression revealed that Fe contents were strongly related to other elemental variables, and that these associations explained most of the differences among size classes (Table IV). Regardless of whether they were constructed using data from the transect stations or the cycles, the step-wise modeling procedure always selected the lithogenic tracers Al or Ti as main predictor variables. These two variables were closely correlated (Fig. 4) and were largely interchangeable in the models— i.e. when one was forcibly removed the other would replace it. When predicting Fe, the step-wise procedure also always selected Mn as a predictor. Other elemental variables were less regularly included in the models. Ni was a highly significant predictor in three of the four models for the transect data, but was never included in the models of the cycle data. Molybdenum was included

Fig. 3. The diel pattern of elemental concentrations measured for samples collected during the cycles. From left to right, the panels in each row relate to the 0.2–0.5, 0.5–1, 1 –2 and 2– 5 mm size fractions, respectively. Data in each panel were fitted by a quadratic model with time of day as a predictor. Solid lines ¼ significant regressions (P , 0.05); dotted lines ¼ non-significant regressions. See Table III in text for summary statistics.

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Fig. 4. Elemental ratios of Fe:C, Fe:P, Zn:C, Zn:P, C:N and C:P of different size groups in zooplankton samples collected at night and during the day. Empty bars represent samples collected at daytime; filled bars represent samples collected at night. Error bars represent the standard errors of the corresponding groups as determined with a two-way ANOVA.

in four models, but never accounted for a large fraction of the variability. The macro-nutrient elements only entered rarely. The categorical variables for time of day, station and size class were by comparison less important than the elemental variables. Station was included in seven of eight models, but was always the predictor with the least explanatory power. Time of day could only be explored in the cycle data because transect stations were only sampled once; it entered three of four models as one of the predictors of secondary importance. Size entered only three of the eight models, all for the transect data. In contrast, Zn content of mesozooplankton was best predicted by size when considering the cycle data (Table V). It also entered three of the four models in the transect data as the second most important variable, with copper concentrations being the most important predictor for the response variable Zn:P. Manganese also entered as a predictor in all four models based on the cycle data, but did not enter any of the transect models. Nickel, Ti and Cd and P were only intermittently included as predictors.

Time of day was included in all four models for which it was allowed, and was the second most important variable for the Zn content and Zn:P models. It was less important in the Zn:C and Zn:N models. Other categorical variables, including interaction terms, were of secondary importance as predictors. Station entered as the last variable and was significant in six of eight models. Mesozooplankton Fe:C and Zn:C varied by less than two-fold among cycle stations and differences among cycles or among stations were rarely significant, after accounting for the effects of other variables. The only significant difference among the cycles was between Cycle 3 with at 34 mmol mol21 and Cycle 5 at 56 mmol mol21 (P , 0.05, Tukey’s HSD). Stations 2 and 4 were intermediate with averages of 45 and 50 mmol mol21, respectively. Nighttime Fe:C ratios were 14% lower and daytime averages were 20% higher than these values based on the model. Zn:C ratios did not differ among cycle stations (Table V), ranging between 8 and 14 mmol mol21 in the smallest size fraction and from 24 to 30 mmol mol21 in the largest.

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DISCUSSION In this study, we documented variability in measurements of C, P, N, Fe and Zn in zooplankton samples collected from the CRD to determine their response to these conditions. In the following sections, we place those results in context, discuss the factors affecting contents of these

Table IV: Results of step-wise regression procedure to predict Fe in mesozooplankton Rank of predictor in final model

F-value in final model

Fe

Fe:P

Transect stations (n ¼ 50) Ti 1 1 Mn 3 2 Ni 2 Mo 4 P C 3 Size 4 Station 5 5 Cycle stations (n ¼ 55) Mn 1 2 Al 2 1 N 3 Mo 4 Time 3 Station 5

Fe:C

Fe:N

Fe

Fe:P

Fe:C

Fe:N

1 2 3

1 3 2

28.4 15.1 23.1

46.4 16.1

34.3 19.1 9.9

25.3 15.5 20.8

6.5 5

5.2 7.0

3 6

4 5

6.3 2.7

1 2

1 2

4 3 5

3 4 5

25.9 11.8 10.8 5.0

2.1

10.1 3.1

7.1 2.7

26.1 41.1

31.0 11.2

30.7 11.3

4.1

6.9 7.7 3.3

5.9 5.6 3.3

3.2

Data from the transect stations and the cycle stations separately. The rank is based on the relative size of the F-values which are also presented to the right. Empty spaces mean the variable was not included in the final model. Elemental predictors were normalized in the same way as the response variables in a model, and both were always logarithmically transformed.

elements and try to establish reasonable bounds for trace metal composition. We then address variability in elemental content among the different cycle stations.

Major elements and community dynamics The average C content in zooplankton (32% of dry weight calculated from 27.15 mmol gdw21) is a little lower than what has previously been measured for crustacean zooplankton (e.g. 33– 60% dry weight, Beers, 1966; Kiørboe et al., 1985; Andersen and Hessen, 1991; Walve and Larsson, 1999). The average N (7.95% of dry weight calculated from 5.68 mmol gdw21) and P (0.67% of dry weight calculated from 0.22 mmol gdw21) contents were also on the lower end of the ranges reported in those studies (5.3– 12.7% of dry weight for N, 0.43– 2.02% of dry weight for P). The decrease in C and N content with size may be related to the composition of zooplankton in each size group. For example, the most common organisms in the largest size group within the CRD (2 –5 mm) were euphausiids and eucalanoids (De´cima et al., 2016; Jackson and Smith, 2016). The latter are generally resident in surface waters shallower than 100 m and have particularly low C, P, protein and lipid contents and high body-water content compared with other copepods (Flint et al., 1991; Ohman, 1997; Cass and Daly, 2015; Jackson and Smith, 2016). This so-called gelatinous body type is considered an adaptation to low food conditions and involves a low-activity cryptic ecological strategy (Flint et al., 1991). In contrast, the smaller size groups (0.2 – 0.5 mm, 0.5 – 1 mm)

Table V: Results of step-wise regression procedure to predict Zn in mesozooplankton Rank of predictor in final model

Transect stations (n ¼ 50) Cu Size Ni Ti Cd Station Cycle stations (n ¼ 55) Size Time Mn Ni P Time  size Station  size Station

F-value in final model

Zn

Zn:P

Zn:C

Zn:N

Zn

Zn:P

Zn:C

Zn:N

1 2

1

1 2

1 2

37.6 13.4

30.0

35.6 16.1

36.3 15.6

3.0

3.0

45.1 6.0 24.1 10.6

44.9 6.3 24.7 11.0

2 3 4 3

21.6 11.7 11.3 3

3

3.2 37.8 31.3 15.9

41.5 37.7 16.2

13.2 6.2 5.8 3.6

6.7 6.2 3.8

1 2 3

1 2 3

1 4 2 3

1 4 2 3

4 5 6 7

4 5 6

4 5 6

4 5 6

6.0 3.4 2.5*

6.3 3.6 2.3*

Data from the transect stations and the cycle stations separately. The rank represents the relative size of the F-values which are also presented to the right. Empty space mean the variable was not included in the model. Elemental predictors were normalized in the same way as the response variables in a model, and both were always logarithmically transformed. All variables are significant at the 0.05 level, unless marked by an asterisk. *Included because of significance of interaction.

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usually comprise fast growing zooplankton juveniles and fast feeding adults. Euphausiids contribute to the largest size fraction and migrate in the CRD from the oxygen minimum zone on a daily basis and are entirely absent from the mixed layer during the day (De´cima et al., 2016). The central dome cycles (2, 3 and 4) all exhibited high migrant biomass (De´cima et al., 2016). Appendicularians and salps were only common during cycles outside or along the fringes of the dome. Ostracods and doliolids were abundant during Cycle 3 (De´cima et al., 2016). The differences in elemental contents among size classes at different times of the day can be used to infer roughly the relative compositions for three fractions of the mesozooplankton community: resident small zooplankton, large resident eucalanoids and large migrating euphausiids. The composition of the resident eucalanoids is reflected in that of the large size fractions during the day. These samples are poor in C and N relative to the other two fractions, as expected for species with a gelatinous body type, but also rich in Zn. By comparison, the large migrant community that is mostly composed of euphausiids stands out as being poor in both Zn and Fe, but rich in P. Interestingly, the euphausiids from the CRD appear to contain less Fe and Zn than would be expected from previous measurements in the literature (Table VI). No measurements for eucalanoids could be found in the literature.

Zinc contents and quotas Since Zn may limiting to some phytoplankton in the CRD (Franck et al., 2005; Saito et al., 2005), zooplankton in this region should exhibit relatively low Zn contents relative to those observed in other regions. Indeed, the geometric means for zooplankton Zn content and Zn:C that we report here are on the low end of average values for individual species and mixed plankton in the literature (Table VI and Fig. 2). The same values for the smallest size fraction were among the lowest regional average values yet observed and lower than any average reported for a species, while the values for the largest size fraction skirted the lower range of previous estimates. Strict comparisons are problematic, however, as Zn contents often vary by 1– 2 orders of magnitude across coastal-openocean gradients (Martin and Knauer, 1973; Hamanaka and Tsujita, 1981; Rejomon et al., 2010; Hsiao et al., 2011). One possible reason for the lower zooplankton Zn concentration in our study may have been that surface-adsorbed Zn in our samples were rinsed off by the oxalate reagent, which was not done in other studies. However, Kahle and Zauke (2003) have argued that Zn adsorption onto zooplankton exoskeleton was generally negligible. Indeed, Zn

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in the open ocean is highly soluble and mostly bound to ligands which do not allow it to readily adsorb to surfaces (Bruland, 1989). Alternatively, the low zooplankton Zn contents could reflect low concentrations of food. Phytoplankton show substantial stoichiometric flexibility in response to gradients in Zn availability, although there is evidence for regulation of Zn contents within the natural range of ambient dissolved Zn (Sunda and Huntsman, 1992, 1995). Moreover, phytoplankton biomass in CRD surface waters can often be dominated by Synechococcus (Li et al., 1983; Saito et al., 2005), which typically has a lower cellular Zn concentration than eukaryotes, possibly making these organisms better adapted to low Zn environments (Saito et al., 2005; Twining et al., 2010, 2011). While copepods and other crustacean zooplankton do not feed on these organisms directly, they feed on protozoa and mixotrophic algae that do. Flagellate consumers have also been shown to be flexible in their contents of major nutrient elements and Fe (Chase and Price, 1997; Hantzsche and Boersma, 2010). Thus, low Zn contents in Synechococcus could propagate up through the food web to affect food quality of larger zooplankton. The increase in Zn content with increasing size fraction may be explained in one of two ways, each of which has different implications for limitation of zooplankton by Zn. First, the pattern of increasing Zn content with increasing size could indicate that larger, more complex animals have higher Zn demand. Animals use Zn heavily in finger proteins, which act as structuring agents for DNA and ribonucleic acid as well as regulatory factors in DNA expression and DNA repair (Frau´sto da Silva and Williams, 2001). Thus, more complex metazoans may have a greater need for gene and translational regulation and, therefore, a greater need for Zn. Such a viewpoint could imply less flexibility in the Zn content of zooplankton than typically is assumed for metals. However, much previous work has concerned responses of tissue concentrations to high levels of ambient metal, which are far from limiting (Reinfelder et al., 1998; Luoma and Rainbow, 2005). Over space, zooplankton tend to vary less in their Zn contents than do the particles that comprise their food (Zauke et al., 1998), suggesting some level of stoichiometric homeostasis (Sterner and Elser, 2002). A fixed Zn tissue concentration would make larger mesozooplankton more prone to mineral limitation by Zn in the diet than smaller size classes. The increase in Zn with size could also result from biomagnification of Zn as it is passes up the food chain (Wang, 2002). Copepods assimilate metals, including Zn, much more efficiently when fed organisms which themselves have obtained those metals primarily from food (Twining and Fisher, 2004). In fact, assimilation efficiencies for Zn in such instances can approach those for

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Table VI: Published Zn concentrations (nmol gdw21) in mesozooplankton Taxon

Species

Region

Conc.

Reference

Amphipods

Eusirus propeperdentatus Hyperia sp. Paraceradocus gibber Parathemisto japonica Phrosina semilunata Phronima sedentaria Themisto abyssorum Themisto compressa Themisto gaudichaudii Themisto libellula Acartia clausi Acartia pacifica Calanoides acutus Calanus cristatus Calanus finmarchi./helgol Calanus finmarchicus Calanus glacialis Calanus hyperboreus Calanus plumchrus Calanus propinquus Canthocalanus pauper Cosmocalanus darwini Euchaeta barbata Euchaeta glacialis Euchaeta norvegica Metridia curicauda Metridia gerlachei Metridia longa Oncaea venusta Rhincalanus gigas Temora discaudata Temora turbinata Undinula vulgaris Eukrohnia hamata Sagitta elegans Chorismus antarcticus Notocrangon antarcticus Systellaspis debilis Euphausia pacifica Euphausia superba Hymenodora glacialis Meganyctiphanes norvegica Thysanoessa inermis Thysanoessa longipes Conchoecia borealis

Antarctic Peninsula Northern North Sea Antarctic Peninsula Sea of Japan Mediterranean NW Mediterranean Fram Strait and Greenland Sea NE Atlantic Antarctic Fram Strait and Greenland Sea Mediterranean East China Sea Weddell Sea Bering Sea North Sea Fram Strait and Greenland Sea Fram Strait and Greenland Sea Fram Strait and Greenland Sea N Pacific, Sea of Japan Weddell Sea East China Sea East China Sea Fram Strait and Greenland Sea Fram Strait and Greenland Sea Fram Strait and Greenland Sea Weddell Sea Weddell Sea Fram Strait and Greenland Sea East China Sea Weddell Sea East China Sea East China Sea East China Sea Fram Strait and Greenland Sea Sea of Japan Weddel Sea Weddel Sea Atlantic (African coast) N Pacific Antarctic Fram Strait and Greenland Sea Firth of Clyde, NE Atlantic, Greenland Sea, Mediterranean Fram Strait and Greenland Sea Bering Sea, Sea of Japan Fram Strait and Greenland Sea Monterey Bay, California Monterey Bay, California Monterey Bay, California Sea of Japan Gulf of California Bay of Bengal

749 1101 964 1239 2294 1652 –3013 1422 –2401 1162 902 –1009 1055 –1315 2570 7 –2192 2799 1851 1071 –1973 1346 –2692 795 902 –5369 719 –2019 2921 125 –5202 100 –3432 5154 2631 3441 4252 7923 642 –933 104 –5674 6608 57 – 2480 27 – 4100 327 –2382 1193 2875 673 704 642 –1422 195 –2983 505 –1040 566 –1208 658 –1591 1315 902 –2677 5476 –5950 1354 1081 1773 2554 306 –8410 5456 –12 008

14 16 14 9 3 13 17 10 10 17 18 20 19 6 16 12, 17 17 12, 17 6, 9 19 20 20 17 17 17 19 19 17 20 19 20 20 20 17 9 14 14 7 6 5, 8, 10, 14, 15 17 1, 4, 10, 11, 13, 17 17 6, 9 17 2 2 2 9 21 22

Copepods

Chaetognaths Decapods

Euphausiids

Ostracod Mixed Zooplankton

Mostly euphausiids Mostly copepods

Values are geometric means for a species. Ranges are reported if several stations or regions are reported for a species or sample type. 1. Leatherland et al. (1973), 2. Martin and Knauer (1973), 3. Fowler and Benayoun (1974), 4. Fowler (1977), 5. Stoeppler and Brandt (1979), 6. Hamanaka and Tsujita (1981), 7. Ridout et al., (1985), 8. Yamamoto et al. (1987), 9. Masuzawa et al. (1988), 10. Rainbow (1989), 11. Ridout et al. (1989), 12. Pohl (1992), 13. Romeo et al. (1992), 14. Petri and Zauke (1993), 15. Locarnini and Presley (1995), 16. Zauke et al. (1998), 17. Ritterhoff and Zauke (1997), 18. Fisher et al. (2000), 19. Kahle and Zauke (2003), 20. Hsiao et al. (2011), 21. Renteria-Cano et al. (2011), 22. Rejomon et al. (2010).

carbon. When these assimilation efficiencies are larger than excretion rates for Zn, and when specific losses of carbon due to respiration and excretion are high, biomagnification of Zn can occur (Reinfelder et al., 1998). Such a process could explain the increase in Zn contents with size only if larger size classes feed further up the food chain.

Iron contents and ratios As with Zn, the median Fe:C of bulk zooplankton size fractions fell within the lower half of the wide range observed in previous studies and were generally lower than average literature values for bulk community biomass (Fig. 2). The value for the largest size fraction

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was among the lowest that has been reported to date. Again such comparisons are ambiguous; studies of Fe content are rarer than for Zn content. Also, there are 1 –2 orders of magnitude variation among studies and among the species and sites within studies that overlap with the CRD measurements. The mean value for Calanus plumchrus from the Sea of Japan (21 mmol mol21 Fe:C) was below the average of 30 mmol mol21 Fe:C for the largest size class in the CRD (Masuzawa et al., 1988). Individual station measurements of Canthocalanus pauper, Temora turbinata and Undinula vulgaris in the East China Sea reached as low as 10– 20 mmol mol21 Fe:C (Hsiao et al., 2011). While these values are lower than the means reported here, measurements for size classes in our data were ,20 mmol mol21 Fe:C on 17 of 109 occasions, and as low as 6.3 mmol mol21 Fe:C. The tendency for Fe and Zn contents of mesozooplankton to vary with size in opposite ways clearly indicates that these two variables are regulated by different factors. A size-dependent decrease in Fe requirement makes some biological sense because mass-specific respiration rates tend to decrease with size (Moloney and Field, 1989), which should mean less Fe is required for respiratory proteins. Fe content of a copepod size fraction measured by Martin and Knauer (Martin and Knauer, 1973) was larger than observed in the amphipod fraction. The rest of the literature data is nonetheless quite equivocal. The large range of values resulting from sensitivity of Fe content to ambient availability causes Fe contents for various copepod species to vary over a range that includes values reported for larger amphipods (Hsiao et al., 2011, Table VII). Lithogenic contributions may account for the decline in Fe content with size in the CRD. Unlike Zn, Fe in

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zooplankton is strongly associated with Al (r 2 ¼ 0.60) and Ti (r 2 ¼ 0.52; Fig. 5 and Table IV). The differences in Fe content among size fractions are statistically insignificant when either Al or Ti is included as a covariate in analysis of covariance (P . 0.1). This suggests that the association of Fe with Al and Ti is largely responsible for the observed differences in metal content of different size fractions. Al and Ti are often considered tracers for terrestrial and sediment sources of metal as neither is known to have a biological role and both are abundant in clays (Martin and Knauer, 1973). The origins of lithogenic metals associated with the zooplankton, and especially the small size fraction, are unclear. No immediate source of sedimentary metal is obvious, and the relatively wet, well-vegetated regions along the coast are not an obvious source of dust to surface waters. Possibly, the lithogenic metal is a remnant of the CRD’s formation nearer to the coast in spring (Fiedler, 2002; Landry et al., 2016). Metal associated with food in the gut would not have been affected by the oxalate rinse method. Consequently, the Al and Ti and lithogenic Fe in zooplankton samples may have been contained within clays in zooplankton guts as there was no attempt to evacuate zooplankton guts during collection, and egestion of gut contents was prevented by anesthetizing the zooplankton samples with carbonated water. However, correcting the Fe for lithogenic contributions by assuming a Fe:Al ratio typical of Saharan dust (Rauschenberg and Twining, 2015) did not alter the relationship between Al and Fe in zooplankton biomass. This result is not surprising considering that the Fe:Al ratio in zooplankton averages 3.3 mol mol21, almost an order of magnitude larger than the ratio of 0.375:1 in Saharan dust. It is therefore tempting to hypothesize that the lithogenic metal was not ingested as

Table VII: Fe concentration (nmol gdw21) in zooplankton from other regions Taxon

Species

Region

Conc.

Reference

Amphipods Chaetognaths Copepods

Parathemisto japonica Sagitta elegans Acartia pacifica Calanus plumchrus Canthocalanus pauper Cosmocalanus darwini Oncaea venusta Temora discaudata Temora turbinate Undinula vulgaris Meganyctiphanes norvegica Thysanoessa longipes

Sea of Japan Sea of Japan East China Sea Sea of Japan East China Sea East China Sea East China Sea East China Sea East China Sea East China Sea Mediterranean Sea of Japan Monterey Bay, California Sea of Japan Monterey Bay, California Monterey Bay, California

4298 3402 314 – 6092 591 94 –5231 340 – 5722 215 – 11 784 197 – 10 847 76 –9717 106 – 11 002 1146 1970 6169 8058 1934 3370

3 3 4 3 4 4 4 4 4 4 2 3 1 3 1 1

Euphausiids Mixed zooplankton

Mostly euphausiids Mostly copepods

Values are geometric means for a species. Ranges are reported if several stations or regions are reported for a species or sample type. 1. Martin and Knauer (1973), 2. Fowler (1977), 3. Masuzawa et al. (1988), 4. Hsiao et al. (2011).

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Fig. 5. Relationships among Fe, Al and Ti in zooplankton biomass.

clay particles, but as colloids or adsorbed metal that had formed after previously being dissolved. Smaller zooplankton may feed on somewhat smaller food items, which could have more adsorbed metal because of their higher surface to volume ratios. However, single-cell analyses did not indicate statistically significant trends in Fe quotas with cell size in diatoms or flagellates (Baines et al., 2016). Use of ingested colloidal material or metals

adsorbed to food could potentially provide a means for zooplankton to access Fe despite its relatively low ambient availability. However, such a mechanism would require that Fe be assimilated in this form, and assimilation of adsorbed or mineral metal by zooplankton is often quite poor (Reinfelder and Fisher, 1991; Hutchins and Bruland, 1994). Alternatively, the lithogenic Fe may reflect inorganic particles or colloids may have adsorbed on mucilage from aggregates or from gelatinous zooplankton that were then caught in the sample. While larger identifiable gelatinous zooplankters were removed from samples where possible, fragments of mucilage could easily have been captured on the small mesh. To the extent that either mechanism was contributing to measured Fe contents, those measurements would be less indicative of metal requirements of the mesozooplankton community. The effect of this contaminating Fe is likely to be greatest when using the smallest size mesh, which is more likely to retain mucilage. Fe contents are also more likely to reflect biological need when crustacean zooplankton biomass is large enough to swamp these other sources of Fe, as in night samples with large numbers of migrants. The inclusion of Mn as a predictor of Fe contents in every model across two independent datasets suggests that this element was a tracer for some source of Fe to the food web. In all cases, Mn in mesozooplankton was positively related to Fe. One possible source of elevated Fe and Mn are autotrophs, since both elements are heavily required as cofactors in the enzymatic photosynthetic machinery for photosynthesis (Raven et al., 1999, 2012). Single-cell measurements have shown photoautotrophs to have higher Mn contents than co-occurring heterotrophs (Twining et al., 2004, 2011). Diatoms in particular tend to be enriched in trace metals relative to other cooccurring phytoplankton functional groups (Twining and Baines, 2013), and pennates of the eastern Equatorial Pacific exhibit 2- to 4-fold higher Fe quotas than flagellates or picocyanobacteria (Twining et al., 2011), possibly owing to use of ferritin to store Fe released by photoreduction during the day (Marchetti et al., 2009). Single-cell elemental analysis indicated that diatoms in the CRD were elevated in Fe, but we found no evidence for Mn enrichment of diatoms relative to other protists in this region (Baines et al., 2016). Our results allow us to estimate a possible minimum Fe:C ratio in zooplankton biomass in a number of ways. First, we can take Fe contents of the largest size fractions or those samples with small contributions of Al and Ti as the most conservative indicator of Fe requirement of mesozooplankton. In that case, the average Fe:C for the nighttime large migrant community is 15 mmol mol21, while the average Fe:C for the large daytime resident

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community was about 60 mmol mol21 (Fig. 4). By comparison, water column average Fe:C for flagellates (estimated from cellular Fe:S) was 11.5– 20.4 mmol mol21 during Cycles 2 – 5 (Baines et al. 2016). This pattern would suggest that the larger migrant community may be less susceptible to mineral limitation by dietary Fe:C than the large resident zooplankton community. This pattern may explain the high relative importance of vertically migrating euphausiids in the region (Sameoto et al., 1987; De´cima et al., 2016). However, it could also be argued that this pattern results from a lagged response of copepods in surface waters to upwelling in the center of the CRD (De´cima et al., 2016). Interestingly, the minimum Fe:C for the large resident mesozooplankton community is actually similar to the cell-specific measurements of Fe:C for diatoms during the cycles (43 – 65 mmol mol21). Such elevated Fe:C contents have been reported in from other regions of the Equatorial Pacific (Twining et al., 2011). Although diatom biomass was ,2% of autotrophic biomass during this study (Taylor et al., 2016), a greater abundance of diatoms at other times could allow the large surface resident community to achieve a higher Fe:C diet more in line with likely requirements. A number of studies have shown that rapid production of dissolved Fe from zooplankton can help support some primary production under Fe-limited conditions (Strzepek et al., 2005; Sarthou et al., 2008; Boyd et al., 2012; Giering et al., 2012). There are a number possible ways to resolve the apparent conflict between such observations and the observation that Fe:C in zooplankton tissues is low compared with food. First, while the Fe:C of zooplankton tissues is one of the main factors influencing the minimum requirements for Fe:C in food, it is not the only variable. Ingestion rates, assimilation efficiency, respiration rates, growth efficiency all help to determine Fe:C requirement (Chen et al., 2014). In fact, when growth is very low, mass balance suggests that the Fe:C requirement becomes decoupled from the Fe:C in zooplankton tissues, and becomes solely a function of processes related to the assimilation and retention of Fe and C. Second, excretion of Fe would only be related to Fe content of the food only if organisms were exhibiting stoichiometric homeostasis, as has been shown for P and N. However, Acartia tonsa in the laboratory and wild calanoid populations show little evidence of such regulation (Schmidt et al., 1999; Chen et al., 2014). This suggests that zooplankton may be physiologically “committed” to excreting Fe at some rate based on factors not related to Fe:C content of food, a viewpoint commonly held by those studying bioaccumulation of metals in invertebrates (Rainbow and Luoma, 2007). For species which experience Fe-limited conditions only sporadically or

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seasonally, it may be easier to evolve life histories that simply avoid or tolerate low Fe food conditions when they occur than to maintain complex homeostatic mechanisms for a range of metals. Finally, in some cases, the production of dissolved Fe by feeding may not be strictly due to excretion, as it does not have to occur after the Fe has been assimilated. Breakage of cells during feeding (sloppy feeding) or loss via defecation of unassimilated Fe is just as likely to result in production of dissolved Fe from the particulate phase (Møller et al., 2003).

CONCLUSIONS Several aspects of the trace element composition of zooplankton in the CRD suggest that trace metal limitation is significant for these organisms. First, Zn:C concentrations are among the lowest yet observed for zooplankton, suggesting that elemental composition is responding to reduced Zn availability in the CRD. While zooplankton Zn:C ratios for all size fractions are low by comparison with previously published measurements, they are still higher than measured for open ocean phytoplankton from the Eastern Equatorial Pacific (Twining et al., 2011) and in some locations within the CRD (Baines et al., 2016). The challenge to obtain enough Zn from the diet will be greatest for largest zooplankton which may have a higher minimum Zn:C content than do the smaller fractions. Fe:C ratios were also at the low end of previously reported values, although not without precedent. Except for the night time migrant zooplankton community, these ratios are generally higher than measured in flagellates collected simultaneously, especially for the small zooplankton size fractions (Baines et al., 2016). However, they were similar to values measured for diatoms in the CRD (Baines et al., 2016), raising the possibility that selective predation and diet mixing by zooplankton could allow these fractions to obtain enough Fe to maintain growth. Low Fe conditions may favor the large migrant community and the relative abundance of diatoms may play a key role in determining whether other zooplankton fractions can avoid mineral limitation by Fe.

DATA A RC H I V I N G All data on trace metal contents of zooplankton size fraction have been deposited at the Biological and Chemical Oceanography Data Management Office under the project title “Costa Rica Dome FLUx and Zinc Experiments” (http://www.bco-dmo.org/project/515387).

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Costa Rica Dome: amplifying variability through the plankton food web. J. Plankton Res., 38, 317 –330.

AC K N OW L E D G E M E N T S Thanks to the crew of the RV Melville and to Moira De´cima for aid with net tows.

Draper, N. and Smith, H. (1981) Applied Regression Analysis, 2d edn. Wiley, New York. Fiedler, P. C. (2002) The annual cycle and biological effects of the Costa Rica Dome. Deep-Sea Res. I, 49, 321– 338.

FUNDING U. S. National Science Foundation grants OCE- 0962201 to S.B.B., OCE-0928289 to BST, and OCE-0826626 to M.R.L.

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Factors affecting Fe and Zn contents of mesozooplankton from the Costa Rica Dome.

Mineral limitation of mesozooplankton production is possible in waters with low trace metal availability. As a step toward estimating mesozooplankton ...
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