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HYPOTHESIS AND THEORY published: 28 August 2019 doi: 10.3389/fmars.2019.00509

Growth Limitation of Marine Fish by Low Iron Availability in the Open Ocean

Eric D. Galbraith1,2,3*, Priscilla Le Mézo2, Gerard Solanes Hernandez2, Daniele Bianchi4 and David Kroodsma5

1 Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain, 2 Institut de Ciència i Tecnologia Ambientals (ICTA-UAB), Universitat Autònoma de Barcelona, Barcelona, Spain, 3 Earth and Planetary Sciences, McGill University, Montreal, QC, Canada, 4 Atmospheric and Oceanic Sciences, University of California, Los Angeles, Los Angeles, CA, United States, 5 Global Fishing Watch, Washington, DC, United States

It is well-established that phytoplankton growth can be limited by the vanishingly low concentrations of dissolved iron found in large areas of the open ocean. However, the availability of iron is not typically considered an important factor in the ecology of marine animals, including fish. Here, we compile observations to show that the iron contents

Edited by: of lower trophic level organisms in iron-limited regions can be an order of magnitude Carol Robinson, less than the iron contents of most fish. Although this shortfall could theoretically be University of East Anglia, United Kingdom overcome if iron assimilation rates were very high in fish, observations suggest this Reviewed by: is not the case, consistent with the high recommended iron contents for mariculture Julian Blasco, feed. In addition, we highlight two occurrences among fish living in iron-poor regions Spanish National Research Council that would conceivably be beneficial given iron scarcity: the absence of hemoglobin in (CSIC), Spain Peter Croot, Antarctic icefish, and the anadromous life history of salmon. Based on these multiple National University of Ireland Galway, lines of evidence, we suggest that the iron content of lower trophic level organisms Ireland Rod W. Wilson, can be insufficient to support many fish species throughout their life cycles in iron-poor University of Exeter, United Kingdom oceanic regions. We then use a global satellite-based estimate of fishing effort to show *Correspondence: that relatively little fishing activity occurs in high nitrate low chlorophyll (HNLC) regions, Eric D. Galbraith the most readily identified iron-poor domains of the ocean, particularly when compared [email protected] to satellite-based estimates of primary production and the observed mesozooplankton Specialty section: biomass in those waters. The low fishing effort is consistent with a low abundance of This article was submitted to epipelagic fish in iron-limited regions, though other factors are likely to contribute as well. Marine Biogeochemistry, a section of the journal Our results imply that the importance of iron nutrition extends well beyond plankton and Frontiers in Marine Science plays a role in the ecology of large marine animals. Received: 27 November 2018 Accepted: 05 August 2019 Keywords: iron limitation, fish, fishing, Global Fishing Watch, marine ecology, HNLC region, ecosystem Published: 28 August 2019 stoichiometry, trace metal Citation: Galbraith ED, Le Mézo P, Solanes INTRODUCTION Hernandez G, Bianchi D and Kroodsma D (2019) Growth Limitation of Marine Fish by Low Iron Availability Iron is an essential element for virtually all organisms, playing a central role in many components in the Open Ocean. of the photosynthetic machinery, respiratory reactions, DNA synthesis, and for the transport Front. Mar. Sci. 6:509. and storage of oxygen. Iron can be toxic at high concentrations, but in the oceans, the scarcity doi: 10.3389/fmars.2019.00509 of dissolved iron tends to be more of a problem. Low dissolved iron concentrations are widely

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FIGURE 1 | Net primary production and sea surface nitrate concentrations in the global ocean. The left panel shows the annual mean net primary production (in mmol C m–2 day–1) as estimated from satellite-observed sea surface color and temperature averaged from three algorithms (Dunne et al., 2007). The right panel shows the minimum monthly sea surface nitrate concentration (in µM) from the World Ocean Atlas (Boyer, 2013).

recognized to play a role in limiting the growth of marine experimental aquaculture, and discuss two notable fish taxa with phytoplankton (Marchetti and Maldonado, 2016), most characteristics consistent with adaptation to low iron availability. importantly in the high nitrate low chlorophyll (HNLC) regions Finally, we show that fishing eort appears to be anomalously low that constitute more than one quarter of the open ocean in iron-limited regions, which is consistent with relatively low surface (Sarmiento and Gruber, 2006)(Figure 1). In these fish biomass in these regions. Based on these lines of evidence, large regions, the dissolved nutrient nitrate persists at relatively we propose the new hypothesis that iron availability plays an high concentrations at the ocean surface throughout the year important role in the ecology of marine fish. without causing strong phytoplankton blooms (Moore et al., 2013), a striking contrast with the adjacent coastal regions in which high nitrate concentrations would lead to rapid uptake IRON LIMITATION OF PHYTOPLANKTON by chlorophyll-rich phytoplankton. Experiments have shown that deliberate iron addition to HNLC waters accelerates the Iron is derived from rocks and supplied to the ocean surface growth rates of phytoplankton and produces more biomass, primarily by rivers, continental dust and mobilization from the confirming their iron-limited status (de Baar et al., 2005; Boyd seafloor (Tagliabue et al., 2017). Dissolved iron concentrations et al., 2007). Iron scarcity has also been shown to limit the growth tend to be relatively high in most coastal waters given their 1 and abundance of marine heterotrophic bacteria that compete proximity to iron sources, and can exceed 10 nmol L (Johnson with phytoplankton for this resource (Tortell et al., 1999). et al., 1999). In contrast, dissolved iron concentrations are very 1 Despite its demonstrated importance for microbes, little low in much of the open ocean (often less than 0.1 nmol L attention has been paid to the possibility that iron availability at the surface). This scarcity can be attributed to the fact that, 3 is important for multicellular marine life. A relatively small in oxygenated seawater, iron is dominantly present as Fe + and number of studies have considered how higher trophic level has very low solubility (Liu and Millero, 2002). In fact, almost organisms might impact the iron cycle, including estimates of all of the dissolved iron pool is maintained in solution through iron extraction from the ocean by industrial fishing (Moreno complexation with organic molecules (Gledhill and Buck, 2012), and Haa, 2014), the impact of whales on iron recycling (Lavery without which it would be lost to sinking particles. et al., 2010), and the roles of animals in ecosystem iron budgets Iron has long been recognized as an essential nutrient that (Maldonado et al., 2016; Ratnarajah et al., 2018). However, can potentially limit phytoplankton growth (Gran, 1931; Harvey, these studies all focus on the role of animals in modifying 1937), but it was only three decades ago that measurement the iron limitation of phytoplankton, rather than the impact techniques became suciently sensitive to quantify the of iron availability on the animals themselves. There has been concentrations in iron-poor surface ocean waters. Measurements some suggestion that the low iron content of phytoplankton in showed extremely low concentrations in the HNLC waters of the HNLC regions may limit the growth rates of zooplankton (Chen subarctic North Pacific, and the addition of iron was shown to et al., 2011; Baines et al., 2016), but this has not been widely increase phytoplankton growth rates, supporting the idea that investigated. We are not aware of prior work that has considered HNLC regions owe their existence to iron limitation (Martin the possibility that the highly variable availability of iron in the and Fitzwater, 1988). Although the “iron hypothesis” was met ocean environment could be a factor in determining the growth, with skepticism given competing ideas about light limitation abundance and distribution of non-planktonic marine animals. and grazing (Banse, 1990), repeated experiments supported Here, we provide an overview of the state of knowledge the growth-limiting role of iron in the North Pacific (Martin regarding iron contents and requirements of marine organisms, et al., 1990). Subsequent work confirmed that the addition of first for plankton and then for fish, along with theoretical dissolved iron also accelerates phytoplankton growth in the expectations for how iron contents will change between trophic other HNLC regions (primarily the Southern Ocean and eastern levels. We then compare these observations with the conditions equatorial Pacific). These findings led to the broadly accepted under which anemia has been shown to occur in fish grown in understanding that the surface nitrate accumulation in HNLC

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regions reflects its slow uptake by phytoplankton due to iron limitation (Boyd et al., 2007; Moore et al., 2013). Iron limitation of phytoplankton has also been demonstrated outside of HNLC regions, such as the California Current (Hutchins et al., 1998), so the absence of nitrate at the surface cannot be taken as indicating an abundance of iron. Nonetheless, we make use of HNLC regions here as clearly identifiable ocean domains that are generally iron-poor. Although iron limitation slows the growth rates of phytoplankton, they do continue to grow in HNLC regions, and some taxa are able to achieve large reductions in their Fe:C by modifying their cellular machinery (Strzepek and Harrison, 2004; Marchetti and Maldonado, 2016; Strzepek et al., 2019) (Supplementary Table 4). Eukaryotic phytoplankton appear to be particularly capable of lowering their cellular Fe:C, with some 1 FIGURE 2 | Elemental transfer from food to animal. The gray shape cultured diatoms containing less than 5 µmol Fe (mol C) represents an animal that, for an element X, incorporates in biomass a (Strzepek et al., 2011; Marchetti and Maldonado, 2016). In lifetime-averaged fraction tX of the total ingested elemental flux IX. This differs contrast, the cyanobacteria that dominate oligotrophic waters from the absorbed flux AX (also termed gut assimilation) due to the excretion appear to maintain higher cellular Fe:C, more than 40 µmol flux EX. Orange and blue rectangles illustrate the approximate relative changes 1 Fe (mol C) (Twining et al., 2010; Shire and Kustka, 2015; expected for Fe and C, respectively, between food, feces and excretion for a Marchetti and Maldonado, 2016). Consequently, lower iron growing animal. Note that feces may also include dissolved compounds. contents are generally found for planktonic samples in iron- limited open ocean regions. The low iron contents of suspended particles found in these regions may be further amplified consumed. Trophic assimilation eciencies vary by organism by an absence of iron-rich non-living detritus compared to and with food characteristics, and are lower than the uptake coastal waters (Ho et al., 2007; King et al., 2012; Twining and assimilation eciency (A/I, Figure 2) for elements that are Baines, 2013). Thus, the organic particles at the base of the food subsequently excreted. The theoretical limits of tC can exceed chain in HNLC regions can have very low Fe:C, compared to 0.7 for single-celled organisms and be as high as 0.5 for multi- iron-rich coastal waters. cellular organisms, but they tend to be much lower in practice, often varying between 0.15 and 0.25 for ectotherms (Sterner and Elser, 2002). The trophic eciency for C is much less than the ELEMENTAL TRANSFER FROM FOOD assimilation eciency across the gut, A/I, because most of the TO CONSUMER C is respired to support metabolism, and subsequently excreted (E). Thus, if we assume a tC of 0.20, a tX of 0.20 would result in Heterotrophs rely on their food to provide energy, in the X:Cconsumer being equal to X:Cfood, whereas a tX of 0.40 would form of reduced carbon, but also for the other elements cause X:Cconsumer to be twice that of X:Cfood. The ability of a required to construct their tissues (Sterner and Elser, 2002; consumer to homeostatically control their X:C relative to their Karimi et al., 2010). Thus, essentially all of the elements that food therefore depends on their capacity to modify tX and/or tC compose the marine ecosystem are extracted from seawater independently of each other. by primary producers and are transferred through the web For the essential element N, the fraction assimilated across of heterotrophs via feeding. The dependence of heterotrophic the gut wall (A/I) is quite high, so that tN could potentially be organisms on the essential elements present in their food is often much higher than tC, allowing a consumer to readily construct referred to as an aspect of “food quality” (Elser et al., 2000; tissues with higher N:C than its prey. Since consumers tend to Sterner and Elser, 2002). maintain N:C that is not very dierent than their food, they often In general, for some element “X,” the relationship between the excrete most of the N they consume. As we discuss next, the X:C of a consumer (where C is carbon) and that of its food is given case appears to be very dierent for Fe, given that Fe uptake by the ratio of the two elemental trophic eciencies, assimilation eciency tends to be quite low among animals. We first consider the experimental evidence for Fe assimilation tX X Cconsumer X Cfood eciencies in zooplankton. : = : tC The elemental trophic eciency t, as defined here, is the fraction of the element consumed that is incorporated in tissue, IRON IN HETEROTOPHIC MARINE net of all loss through egestion of feces and excretion of PLANKTON dissolved compounds (Figure 2), and integrated over the full lifetime of the organism. For C, the trophic eciency is also Few experimental studies have attempted to estimate referred to as the “Gross Growth Eciency,” and approximates zooplankton tFe or Fe assimilation eciencies. the ratio of new biomass constructed to the biomass of prey Those that do exist suggest that tFe is generally low

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FIGURE 3 | Observed concentration of epipelagic mesozooplankton. Shaded dots indicate the average carbon concentration of mesozooplankton biomass collected in net tows within the upper 200 m of the water column (Moriarty and O’Brien, 2013). Blue contour lines indicate HNLC regions, identified as surface waters with minimum monthly nitrate concentrations > 3 µM(Boyer, 2013).

(Hutchins and Bruland, 1994) and that, when confronted have been observed migrating to the seabed, where they ingest with iron-poor phytoplankton, zooplankton do not substantially detrital particles that appear to contribute to their iron nutrition increase their Fe assimilation eciencies (Hutchins et al., 1995; (Schmidt et al., 2011, 2016), which may be an adaptation to the Schmidt et al., 1999). This is not to say that the assimilation is poor iron content of their food. constant: the fraction of total iron that is assimilated by copepods Although the paucity of data leaves many open questions as in culture has been shown to vary significantly. However, the to how iron limitation aects zooplankton, and our limited data small number of available studies appear to show that the compilation is strongly biased, it is clear that zooplankton Fe:C Fe assimilation eciency is most strongly related to the iron varies over at least an order of magnitude in the ocean, and can content within the prey cytoplasm (Chen et al., 2014), with be very low in iron-limited waters. To first order, zooplankton little assimilation of non-cytoplasmic iron, rather than adjusting Fe:C appears to follow the local phytoplankton Fe:C, consistent to compensate for the iron content of their diet. This finding with an average tFe/tC close to 1. mirrors the cytoplasm-dependent uptake of other metals by copepods (Reinfelder and Fisher, 1991), but contrasts with the strong homeostatic regulation of N:P among zooplankton. The IRON IN MARINE FISH dependence on food iron content implies that, rather than being globally constant, the Fe:C of zooplankton communities would Fish use iron for many biochemical purposes, but one important be pulled toward the Fe:C of their food (Hutchins et al., 1995; use is the storage and transport of oxygen (Bury and Grosell, Chase and Price, 1997; Schmidt et al., 1999; Chen et al., 2014). 2003). Iron is found at the center of hemoglobin and Consistent with this expectation, the Fe:C of zooplankton in myoglobin, which bind oxygen for vascular transport and storage, the ocean has been found to vary by more than an order of respectively (Beard et al., 1996). In vertebrates, as much as magnitude, in concert with changes in phytoplankton Fe:C, with 80% of the total iron content can be bound within these two 1 reported values exceeding 200 µmol Fe (mol C) in iron-rich metalloproteins (Kuhn et al., 2016). Although rainbow trout 1 coastal regions and less than 14 µmol Fe (mol C) in iron-poor have been shown to take up iron across their gills in iron- regions of the Southern Ocean (Supplementary Table 5). rich freshwaters, this pathway requires very high dissolved iron Despite the limited ability to compensate for low Fe:C concentrations (half-saturation constant of 21 nM) (Cooper and food, zooplankton are not excluded from iron-limited waters. Bury, 2007) so that it should be negligible at the concentrations On the contrary, as shown in Figure 3, mesozooplankton found in iron-poor seawater (less than 0.2 nM). Thus, the iron abundances are quite high in HNLC regions of the ocean. supply of marine fish in low-iron waters is likely to come entirely It has been suggested that low iron availability retards the from their food, unless they have evolved a much higher anity growth rates of zooplankton in these waters (Chase and Price, gill uptake system that has not yet been investigated. It is not 1997; Chen et al., 2011), as it does phytoplankton, and likely known if fish have a regulatory mechanism for increasing iron contributes to determining which species are present according excretion rates in order to prevent iron toxicity, suggesting that to their physiology and ecological strategies (Chen et al., 2014; they may rely on down-regulating uptake when consuming iron- Baines et al., 2016). For example, Antarctic krill (Euphausia rich food (Bury et al., 2012). superba), which are relatively abundant in the strongly iron- Compared to plankton, there are few available measurements limited waters of the open Southern Ocean, can have very of Fe:C in whole marine fish. Figure 4 summarizes published, low Fe:C (Supplementary Table 5). Intriguingly, Antarctic krill peer-reviewed measurements (see Supplementary Materials for

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discerned from the handful of whole fish measurements, with reported values ranging from 2 to more than 40 µmol Fe 1 (mol C) (Supplementary Table 6). Interpreting these values is complicated by the fact that the iron content of fish muscle tissue can vary widely within a given fish. For example, red muscle contains more iron-rich myoglobin than white muscle, which can lead to more than ten-fold higher iron concentrations in red muscle (Carpene et al., 1998). Unfortunately, the published studies do not always identify whether the analyzed muscle tissues were white or red. In addition, even higher concentrations of iron can occur in organs including the liver and gill. Available comparisons suggest that muscle Fe:C is 14–45% of the whole fish Fe:C value (Honda et al., 1987), which would imply a total 1 possible range from 4–12 to >90–300 µmol Fe (mol C) on the basis of the muscle measurements (Figure 4). We would emphasize that this is a highly speculative conversion, and would greatly benefit from further whole fish measurements across a broader range of taxa. Nonetheless, the muscle data suggest that the whole body data, which are dominated by cultured salmon and Southern Ocean fish, lie at the lower end of the spectrum, and that the Fe:C of many fish can be higher. When we compare the tentative range of fish Fe:C with plankton Fe:C (Figure 4), two important features are apparent. First, the Fe:C range of fish overlaps with the lower end of the Fe:C range of plankton in Fe-rich waters. Second, the Fe:C range FIGURE 4 | Measured Fe:C molar concentration ratios from published of fish does not extend to the lowest Fe:C of plankton found in sources (see Supplementary Materials). The upper portion shows the Fe:C HNLC waters, even though some of the whole fish samples were measured in plankton, differentiated by whether they were grown under collected from the broadly iron-limited Southern Ocean. Thus, iron-rich or iron-poor conditions. The very low phytoplankton values are not this fragmentary view suggests that fish Fe:C is similar to – or included within the colored-bar range as they were grown under an extreme iron limitation in culture. The lower portion shows measured adult fish Fe:C, lower than – the plankton of iron-rich waters, but is higher than using the mean of multiple measurements when available, and recommended the plankton of HNLC waters. Fe:C in feed for aquaculture of marine fish species, with vertical lines showing Following the reasoning illustrated in Figure 2, the low Fe:C the mean values estimated by Prabhu et al. (2016). For the inferred whole-fish of iron-limited plankton relative to fish would demand that a Fe:C, filled circles show upper (dark) and lower (pale) estimates assuming that planktivorous fish in an HNLC region have a high tFe or a low muscle Fe:C is 14 and 45% of the whole-fish Fe:C, respectively; the blue bar 1 indicates the most confident range, spanning from the upper estimate for the tC. For example, maintaining an Fe:C of 20 µmol Fe (mol C) smallest measured value to the lower estimate for the largest measured value. by feeding on iron-poor zooplankton with an Fe:C of 10 µmol 1 Fe (mol C) would require a tFe/tC of about 2. So, given a standard tC of 0.2, the fish would need a tFe of 0.4. This would be much higher than tFe in humans, which ranges from 0.02 to 0.23 details) made on experimentally reared Atlantic salmon, which (Beard et al., 1996). The alternative possibility that tFe/tC could 1 ranged from 16 to 43 µmol Fe (mol C) when consuming be raised by lowering tC through physiological or behavioral normal feed (Shearer, 1994; Andersen et al., 1996), and four adaptations is theoretically interesting, but would equate to a sub- groups of wild fishes in the Southern Ocean (three Nototheniidae optimal use of the available food energy, which could be expected and one myctophid), which ranged from 10 to 26 µmol Fe to reduce fitness. Following this reasoning, a high tFe would be 1 (mol C) (Honda et al., 1987). The precise locations of the the preferred means by which fish could raise their Fe:C. Southern Ocean samples are not given, but at least two were Rather than having unusually high tFe, it appears that marine coastal (“near Showa Station”). The vertical bar within the teleosts, the dominant fish group, are no better at assimilating whole fish range indicates the average value of 25 7 µmol iron than other vertebrates. They may even have a disadvantage 1 ± Fe (mol C) for whole fish according to the meta-analysis of to other groups, since their osmotic regulation strategy requires Prabhu et al. (2016). Larval fish are not included in the figure, but maintaining an alkaline intestinal environment, which results have been found to consistently contain between 9 and 17 µmol in the production of carbonate minerals (Wilson et al., 2002) 1 Fe (mol C) (Wang and Wang, 2018). and may interfere with iron uptake (Bury et al., 2012). This is Measurements on the iron content of edible fish fractions consistent with relatively low measured iron somatic assimilation (i.e., some portion of the fish muscle) are much more widely eciencies among marine fish, which are estimated by feeding available than those on whole fish, due to their relevance radio-isotope labeled food to cultured fish and measuring their for human nutrition. These measurements suggest that Fe:C retention of the radio-isotope over the following hours. Although may vary more significantly among fish than would be not directly comparable to lifetime-integrated tFe, these reported

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assimilation eciencies are <0.20 when fed artificial feed (Wang 1997). Nonetheless, a recent experimental study using live rotifer and Wang, 2016) and <0.08 for live feed (Wang et al., 2019). feed provided a minimum dietary recommendation of 30 µmol 1 Fish do show an ability to regulate their assimilation, with lower Fe (mol C) (Wang and Wang, 2018), which falls within the assimilation eciencies occurring in response to iron-rich feed range of recommended artificial feeds. Overall, these experiments (Wang and Wang, 2016), however, we were unable to find provide direct evidence that iron-poor food can negatively impact evidence of assimilation eciencies above 0.20, consistent with the growth of marine fish, and suggest that the Fe:C levels for a limit to the capacity for up-regulation, as found in mammals optimal fish growth can be well above those of the plankton (Beard et al., 1996). The persistently low assimilation eciencies in HNLC regions. may be attributable, in part, to the diculty of accessing iron within tightly bound components of their food, as illustrated by the egestion of exoskeleton-bound trace metals by juvenile fish POSSIBLE ADAPTATIONS TO LOW IRON (Reinfelder and Fisher, 1994). A large fraction of inaccessible iron AVAILABILITY is also consistent with high measured Fe:C in fish feces, which exceed the Fe:C in fish stomachs by a factor of 10 or more (Geesey If iron availability can indeed place a constraint on fish growth, et al., 1984). Together, these observations imply a tFe/tC . 1, as it does for plankton, one would expect to find evolutionary suggesting that it is very dicult for fish to elevate their Fe:C adaptions to iron scarcity among fish, just as they are found above the Fe:C of their food. among phytoplankton. One conceivable type of adaptation would be for fish to reduce their requirements for iron-rich proteins such as hemoglobin. Alternatively, fish could adapt their behavior ANEMIA AMONG FISH IN to take advantage of iron-rich forage at places or times that it is AQUACULTURE available, as might be achieved through migrations between iron- rich and iron-poor environments. We identify two examples of The apparent inability for fish to enrich their Fe:C significantly fish groups that are consistent with each one of these feasible above that of their prey suggests that the survival of a given fish adaptation strategies. would require the average Fe:C of all prey items to be similar to, or First, fish of the suborder Notothenioidei, found only in greater than, the minimum whole fish Fe:C requirement for that the Southern Ocean, exhibit unique physiological adaptations species. This then raises the question of what the minimum Fe:C that greatly reduce their iron requirements. The Notothenioidei might be, and how fish welfare might deteriorate as their Fe:C diversified rapidly after the separation of Antarctica and South approaches this minimum. Hypothetically, fish could experience America by tectonic forces opened the Drake Passage in the a significant welfare decrease for any reduction below their late Eocene, and this single group now dominates the Antarctic optimal Fe:C or, alternatively, they may be able to cope very well shelves to an astonishing degree, comprising >90% of the over a broad range of Fe:C and then experience a sharp mortality fish biomass (Eastman, 2005). Notothenioids generally have threshold at the minimum Fe:C. reduced erythrocyte number, hemoglobin concentrations and Studies on fish grown in mariculture, i.e., marine hemoglobin diversity compared to temperate and tropical species aquaculture, provide an experimental vantage on this question. (Verde et al., 2007), and the family Channichthyidae (“white- Mariculturalists have long recognized the occurrence of anemia blooded icefish”) have gone to the extreme measure of eliminating in fish, and have studied the problem for decades (Sakamoto the use of hemoglobin altogether, a unique occurrence among and Yone, 1978; Watanabe et al., 1997). Some experiments vertebrates (Ruud, 1954; Kock, 2005). Several species of icefish in which fish were fed low-iron diets have shown changes in have even eliminated the use of myoglobin in their hearts blood chemistry (Andersen et al., 1996) and growth retardation (Sidell and O’Brien, 2006). These extremely unusual features (Cooper et al., 2006) without causing mortality, suggesting have been most often associated with the low temperatures that fish welfare does respond to Fe:C above the minimum and high dissolved oxygen concentrations of Antarctic waters, threshold for immediate survival. As a result, aquaculture feed which could reduce the requirement for oxygen transportation recommendations for marine fish give minimum Fe:C ratios that and storage (Kock, 2005). However, the loss of hemoglobin vary by species (Supplementary Table 9), with an average of is accompanied by dramatic adaptations to maintain sucient 54 15 µmol Fe (mol C) 1 according to Prabhu et al. (2016). oxygen supply to their tissues, including up to a five-fold ± As shown in Figure 4, the recommended fish feed Fe:C values increase in ventricle size and four-fold increase in total blood lie well within the range provided by coastal zooplankton prey, volume compared to red-blooded fish of similar size (Kuhn and tend to be equal to or higher than whole fish, as would et al., 2016). Even the increased blood volumes cannot overcome be expected from the low tFe/tC for fish discussed above. The what appear to be many profound disadvantages, and explaining feed recommendations exceed the measured Fe:C of iron-limited why the absence of hemoglobin persists has been recognized oceanic zooplankton by a factor of 5–30. Some caution must be as an evolutionary conundrum (Sidell and O’Brien, 2006), even applied in comparing these Fe:C ratios directly, as the fish feeds cited as an example of a deleterious adaptation or “disaptation” are often supplemented with inorganic iron salts among which (Garofalo et al., 2009). 2 3 the iron can occur in varying proportions of Fe + and Fe +, and We propose that, rather than being an example of disaptation, which would be expected to be assimilated dierently than the the absence of hemoglobin in the Channichthyidae is a successful forms in which iron occurs in wild fish prey (Andersen et al., adaptation to the low iron availability in most parts of the

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Southern Ocean. The iron content of the white blood in icefish suggests that the dietary Fe:C requirements of fish can exceed is on the order of one-twentieth that of standard red fish what would be provided by zooplankton in iron-limited waters. blood (Ruud, 1954), reflecting a vastly reduced requirement Second, studies of anemia among fish raised in experimental for iron. This adaptation may only be feasible given the high mariculture confirm the importance of sucient dietary iron oxygen content of cold, well-ventilated Antarctic waters, but supply for fish growth. Third, some evolutionary features of fish we propose that this is a secondary factor. In contrast to living in iron-limited waters – most dramatically, the Antarctic the cold-water explanation, the iron hypothesis can explain ice fish – are consistent with adaptation to low iron availability. why no white-blooded fish occur in the arctic, where O2 is Based on these three lines of evidence, we hypothesize that the equally high but iron is more readily available. Indeed, although highly variable availability of iron in the ocean plays a role in the Arctic cod and Antarctic notothenioids both produce antifreeze ecology of marine fish that has, thus far, gone unrecognized. glycoproteins, recognized as an example of convergent evolution On the one hand, this proposed role for iron could simply to their similarly frigid environments (Chen et al., 1997), influence the relative abundances of species, and might be Arctic cod have multiple forms of hemoglobin that followed significant only under strong iron scarcity. For example, it a very dierent evolutionary history (Verde et al., 2003). The may do no more than exclude fish with the highest iron unique characteristics of the icefish are therefore consistent with requirements from the most iron-poor waters, where they would adaptation to low iron concentrations, facilitated by the cold, be outcompeted by fish with lower iron requirements. However, oxygen-rich environment. it is also conceivable that the total abundance of marine fish could Second, we suggest that the anadromous lifestyle of salmon be low in iron-poor regions relative to iron-rich regions. Testing provides an advantage for the exploitation of iron-poor forage, this latter hypothesis requires data that includes a broad spectrum most importantly in the subarctic Pacific where they are an of fish species and can be directly compared between dierent abundant epipelagic predator (Brodeur et al., 1999). As discussed regions of the global ocean. As a first attempt, we provide a test above, larval fish have no iron reserves, so that they need to using global industrial fishing eort. match their food content with the iron required to grow on a daily basis (Wang and Wang, 2016). However, as they age their relative growth rates decrease and they store increasing amounts FISHING EFFORT AS A PROXY FOR FISH of iron in their livers (Andersen et al., 1996), building up a ABUNDANCE reserve of iron. It therefore seems likely that rapidly growing larval and juvenile fish would be more immediately dependent Despite their importance, both ecologically and as a food source on an iron-rich food supply, whereas more slowly growing for humans, the distribution of fish in the global ocean has been mature individuals are able to store surplus iron in their livers dicult to assess. Scientific surveys are frequently undertaken in that can then be drawn on to survive for longer periods on national coastal waters, but fish are highly mobile and dicult relatively iron-poor forage. If correct, this would suggest that to sample, so that the global distribution of fish biomass has iron availability could be a particularly important concern for an order-of-magnitude uncertainty (Irigoien et al., 2014). One determining the location of spawning, and the habitats of larval approach to overcome the scarcity of direct observations is to and juvenile fish. use the exploitation of harvestable biomass by modern industrial The anadromous strategy of salmon, whereby spawning, fishing fleets as a proxy for fish abundance (Myers and Worm, larval and juvenile phases occur in iron-rich streams, estuaries 2003). Until recently, many fishing records were only available as and coastal waters, while adults gain a greater proportion aggregates provided by national agencies, often for specific taxa, of their diets from the relatively iron-limited oshore waters and disaggregating these to the actual catch locations is fraught (Hansen and Quinn, 1998), would therefore appear to be a good with uncertainty (Watson, 2017). However, a direct spatially strategy for exploiting the abundant iron-poor forage available resolved view on vessels ranging the global ocean is now provided in the open subarctic Pacific (Brodeur et al., 1999). The degree by satellites that intercept radio transmissions from Automatic to which salmon follow this strategy is sure to vary among Identification System transponders, as part of the Global Fishing species, given that dierent varieties spend diering portions Watch (GFW) project (Kroodsma et al., 2018). of their lives in coastal vs. oshore environments (Quinn, We use the GFW data for 2014–2016, inclusive, to provide 2018). Despite the likelihood for variations among species, we a quantitative spatial estimate of fishing eort. Identification of suggest that the overwhelming success of salmon in the North fishing vessels and their activities are made using convolutional Pacific reflects, at least in part, the ability of the anadromous neural networks, as described by Kroodsma et al. (2018). Given life cycle to overcome key bottlenecks of iron nutrition at that industrial fishing activity approximates a rational response to critical life stages. profit motives (Branch et al., 2006) and that most of the harvested fish are traded in a global market, the local fishing eort at any point on the high seas is expected to be roughly proportional to THE CASE FOR IRON the catch. The catch, in turn, depends on the eort, the ability of fishermen to catch the available fish, and biomass density. We We have identified three convergent lines of evidence that appear therefore interpret the distribution of industrial fishing eort on to support a role for iron in the ecology of marine fish. First, the high seas as a first-order proxy for the biomass density of our compilation of published organismal Fe:C contents and tFe catchable, commercially marketable fish.

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FIGURE 5 | Global fishing effort, observed and modeled. Panel (A) shows the total satellite-observed fishing effort of 2014 through 2016 as estimated by Global Fishing Watch (h km–2 year–1). The blue contours indicate HNLC regions, identified as waters with minimum monthly nitrate concentrations >3 µmol kg–1 (Boyer, 2013). In general, high surface nitrate concentrations occur where strong iron limitation occurs. Panel (B) shows a bio-economic model expectation of fishing effort (W m–2), based on the satellite-observed primary production and the climatological water temperature, and panel (C) shows the same model prediction including the iron-limitation of carbon trophic transfer efficiency described in the text. Efforts are plotted as natural logarithms. Exclusive Economic Zones are excluded.

The global distribution of fishing eort in the GFW database TABLE 1 | Comparison of fishing effort and mesozooplankton biomass in HNLC from 2014 through 2016 is shown in Figure 5A. The data only vs. non-HNLC regions of the open ocean. include vessels using transponders, and therefore underestimate Global Southern Tropics Northern the fishing eort that occurs within the Exclusive Economic Zones (EEZs) of countries that do not enforce transponder GFW effort 0.05 0.04 0.60.01 use, including those of the northern Indian Ocean, west Mesozooplankton biomass 1.83.82.22.4 Africa, and many Pacific islands. Nonetheless, a review of GFW effort/mesozooplankton biomass 0.04 0.02 0.30 <0.01 vessels that fish in the high seas outside of EEZs (beyond All values shown are the ratios of the indicated area-specific quantities averaged 200 nautical miles from shore) shows the GFW data includes over NO3-rich (HNLC) regions, in which phytoplankton Fe:C is generally known to 80% of the fishing eort in this area of the ocean (Sala et al., be low, vs. non-HNLC regions. The first column lists the global ratios, while the other three columns list averages in latitudinal ranges: south of 23S, from 23S 2018), and we therefore limit our analysis to the domain to 23N, and north of 23N. The first row gives the ratio for GFW fishing effort 2 1 beyond the EEZs. (h km year ). The second row gives the observed mesozooplankton biomass density (Moriarty and O’Brien, 2013) within the upper 200 m of the water column Figure 5A also shows blue contour lines corresponding to 2 (g C m ). The last row gives the ratios of the observed intensity of fishing effort a minimum monthly surface nitrate concentration of 3 µM, relative to the observed mesozooplankton biomass in HNLC vs. non-HNLC regions. which outline the HNLC regions and therefore indicate where For the last two rows, ratios are calculated including only the grid cells in which low phytoplankton Fe:C would be expected. HNLC regions are mesozooplankton biomass is available, resulting in spatial bias. Exclusive Economic not the only low-iron parts of the ocean, but they are the Zones are excluded from the calculations. largest easily identified low-iron regions (Moore et al., 2013). Comparison of the GFW data with the blue contour lines shows global scale, the average eort in HNLC waters is found to be that the fishing eort is relatively low in the HNLC waters, roughly one twentieth of that in all non-HNLC regions (Table 1). especially the subarctic Pacific and Southern Ocean. Indeed, The average HNLC eort is less dramatically reduced in the when the average area-specific fishing eort is calculated at the tropics, where it is roughly half the average non-HNLC eort,

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while it is only one hundredth the non-HNLC eort in the Thus, although regulation contributes to low fishing eort in northern oceans. the subarctic Pacific through the specific ban on salmon, it The observation of a relatively low fishing eort in HNLC does not seem to be able to explain the generally low eort regions, compared to non-HNLC regions, could have a number in HNLC regions. of possible explanations. We suggest the following possibilities, which may act independently or in concert, and which we 3. Primary production and water temperature do not support then consider in turn: (1) physical access is prohibitive for abundant fish populations fishing vessels; (2) fishery regulations prevent fishing; (3) other Primary production has been shown to limit fish catches aspects of the environment (primary production and water (Chassot et al., 2010), and temperature has strong biological temperature) are not conducive to abundant fish populations; eects, including on trophic structure. To test how these and (4) epipelagic fish have a limited ability to exploit the existing factors might influence fish growth in HNLC regions we use planktonic food resource. the expectations provided by a global bioeconomic model of commercial fish and fisheries that accounts for spatial 1. Physical access is prohibitive for fishing vessels variations in primary production and water temperature. Fishing grounds that are remote from ports may attract less The model BOATS uses observed distributions of primary eort, given that fuel costs can constitute a significant amount productivity and water temperature to estimate the growth, of the total cost of fishing (Lam et al., 2011). As a result, mortality, and reproduction rates of size-resolved fish fishing far from port tends to be more expensive than fishing populations based on empirical macroecological relationships close to port, all else being equal. This likely contributes to (Carozza et al., 2016). An economic component, directly the low fishing eort in remote parts of the Southern Ocean coupled to the fish biomass, estimates the fishing eort. and subarctic Pacific. However, as shown by Figure 5A, there The model sensitivities to NPP and water temperature are is abundant fishing in remote parts of the tropical Pacific and calibrated with historical catch records in coastal fisheries, southern Indian oceans. Conversely, there is negligible fishing among which it has good skill, explaining roughly 60% of in the subarctic Pacific HNLC waters closest to Japan, nor is the global variance in historical Large Marine Ecosystem there significant fishing in HNLC waters near South America, catches (Carozza et al., 2017). We use an ensemble of five except in the coastal waters surrounding islands where iron model configurations to span a broad range of the possible concentrations would be expected to be high (Armand et al., environmental sensitivities allowed by uncertain parameter 2008). Thus, distance can only be a contributing factor. Dicult values (Carozza et al., 2017). sea conditions, including large waves and cold temperatures, When compared with the GFW data (Figure 5B), the model could also be a factor in the subarctic Pacific and Southern ensemble captures the >5 orders-of-magnitude range of eort Ocean. However, these conditions do not prohibit fishing activity between highly productive coastal waters and the subtropical on the Bering Shelf or in the Barents Sea; fishing even occurs gyres, and reproduces some features such as focused eort during winter in these regions. And neither access nor weather along the northern subtropical fronts. However, in contrast can explain the relatively low fishing eort in the eastern to the observations, the model expects that the Subantarctic equatorial Pacific. Southern Ocean, eastern equatorial Pacific and subarctic Pacific would have a very high fishing eort. The magnitude of 2. Fishery regulations prevent fishing this discrepancy is shown by a comparison of normalized On the high seas, only Regional Fisheries Management eorts, summarized in Figure 6. Essentially, the model expects Organizations (RFMOs) provide any mechanism for regulation fishing eort to be globally similar in HNLC and non-HNLC (Cullis-Suzuki and Pauly, 2010). The North Pacific Anadromous regions of the open ocean (i.e., close to 1) and higher in the Fish Commission does prohibit the fishing of any salmonids eastern equatorial and subarctic Pacific given the relatively high outside of EEZs in the North Pacific (NPAFC, 2017), but there NPP. We would caution that BOATS is a very simple model are no prohibitions on other types of fishing in this area. Thus, and does not discriminate benthic from pelagic ecosystems, the apparent ability of the salmon fishing ban to eliminate which may lead to an overestimation of fish production in most fishing would be consistent with salmon being the most the pelagic HNLC regions (Stock et al., 2017). Perhaps even abundant catchable, marketable fish in the subarctic Pacific. more importantly, it does not include fish movement, which is For comparison, the fishing of salmonids is also prohibited particularly important for the highly migratory species targeted in the high seas of the North Atlantic by the North Atlantic in high seas fisheries (Lehodey et al., 1997; Guiet et al., 2019). Salmon Conservation Organization (NASCO, 1984), yet there Seasonal aggregation of tuna and billfish may explain many remains significant fishing eort for other taxa in the open North of the high concentrations of fishing eort which are not Atlantic. In Antarctic waters, fishing can be managed through captured by the model. The model also ignores the cost of the Commission for the Conservation of Antarctic Marine Living travel, which could decrease catches at inaccessible locations. Resources (Croxall and Nicol, 2004), but in practice this has Despite the many detailed shortcomings of the model, the first- focused only on reducing illegal, unreported and unregulated order expectation based on the coastal fishery calibration to NPP fishing in the productive coastal waters of Subantarctic islands and temperature is simply that there is no consistent dierence (Österblom and Bodin, 2012) and to our knowledge there in fish abundance between HNLC and non-HNLC regions of is no prohibition on fishing in the open Southern Ocean. the high seas.

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so that tC has the standard value tC0 when NO3 is low, and decreases smoothly as NO3 rises, with a value of 0.5 tC0 when NO3 = k. Figure 5C shows the global eort for this model version, using k =5µM. Although many biases remain, the overestimates of fishing eort in the three iron- limited regions are greatly reduced by this representation of iron limitation. This improvement is also evident in the global averages (Figure 6). To some degree, this ad hoc modification may compensate for other model biases, and should be seen only as an illustration. Nonetheless, it is consistent with a significant impact of iron limitation on the abundance of fish in iron-poor parts of the open ocean.

FIGURE 6 | Comparison of observed and modeled fishing effort in HNLC vs. OUTLOOK non-HNLC domains. A value of unity (dashed line) indicates the same average fishing intensity in the two domains. The standard model (red) does not show This paper provides multiple lines of evidence that support a significant difference in effort between HNLC and non-HNLC domains at the a hypothetical role for iron in the ecology of marine fish global scale, and actually shows relatively high effort in HNLC waters of the (summarized in section “The Case for Iron,” above). In addition, tropics and northern hemisphere. In contrast, both the Global Fishing Watch observations (blue) and the iron-limited model (orange) show lower effort in industrial fishing eort is used as indirect evidence for low fish HNLC regions relative to non-HNLC regions. Latitude ranges are given in abundance in HNLC waters which may arise, at least in part, due Table 1. EEZs are excluded from the calculation. to iron scarcity. Testing this hypothesis requires the collection of new observations, such as more extensive measurements of the iron contents of marine organisms, and dietary experiments In addition, as mentioned above, the biomass of that are relevant to wild animals rather than mariculture. The mesozooplankton is relatively large in HNLC regions hypothesis also opens a host of new questions, a few of which (Figure 3). In fact, the average epipelagic mesozooplankton we outline here. concentration is roughly twofold higher inside HNLC regions Our discussion has mostly focused on the epipelagic (surface- than outside of them (Table 1). Where mesozooplankton dwelling) fish raised in aquaculture and targeted by industrial biomass data are available, the globally averaged ratio of GFW fisheries in the high seas. The abundance of mesopelagic fish, eort:mesozooplankton is 25-fold higher outside HNLC regions which are not commercially harvested, is very poorly known, than within them, consistent with relatively little catchable, but may exceed that of all other fish (Irigoien et al., 2014). marketable fish biomass for the existing production of lower Intriguingly, mesopelagic fish appear to be relatively abundant trophic level biomass. in HNLC waters. In the Southern Ocean, myctophids such as Electrona antarctica dominate the fish community in the iron- 4. Fish have a limited ability to exploit the existing planktonic limited waters north of the shelf break (Moteki et al., 2011), food resource while the subarctic Pacific shows a similarly high abundance The last possibility we address is that epipelagic fish are not of mesopelagic fish (Beamish et al., 1999). If mesopelagic fish able to fully exploit the existing planktonic food resource in are indeed less negatively impacted by iron limitation than HNLC waters, leading to lower overall abundance. Low water commercially targeted epipelagic species, it would appear to be temperatures are likely to disadvantage ectothermic pelagic a topic worthy of further research. predators in the subarctic Pacific and Southern Ocean, and recent Meanwhile, iron limitation is likely to aect other groups work has argued that endotherms including cetaceans, pinnipeds, of marine animals to a greater or lesser degree. For example, and birds have a strong advantage in cold waters given their the high metabolic demand of endothermy requires rapid ability to maintain high levels of activity (Grady et al., 2019). This respiration, resulting in tC < 0.03 (Humphreys, 1979), and cannot be important in the eastern equatorial Pacific, but could be consequently up to an order of magnitude more enrichment of a major factor in the other two regions. However, given the case Fe:C than expected for a fish given the same tFe. This could for iron limitation outlined above, it also appears feasible that the be expected to alleviate iron limitation among endothermic limitation of fish growth due to iron scarcity contributes to the seabirds and mammals, giving them a relative advantage over anomalously low fishing eort identified in HNLC regions. ectotherms in iron-limited waters, abetting the thermal advantage To illustrate this, we modified the BOATS model to provide endotherms have over ectotherms in the cold waters of the a crude estimate of iron limitation, taking high surface nitrate subarctic Pacific and Southern Ocean (Grady et al., 2019). concentration as a proxy for low iron concentrations. We As another example, cephalopods use the copper protein modified the trophic eciency for carbon as, hemocyanin as an oxygen transporter, rather than hemoglobin (Schipp and Hevert, 1978). This use of copper could reduce the NO3 iron requirements of cephalopods, consistent with relatively low tC tC0 1 = k NO measured iron contents of edible squid tissue compared with fish ✓ + 3 ◆

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(Kongkachuichai et al., 2002) and with the low measured iron Although the latter possibility remains a hypothesis to be tested, 1 content (4 µmol Fe mol C ) of whole Loligo opalescens from it suggests that marine fish growth may be enhanced by iron the Californian coast (Falandysz, 1991). The low iron content of fertilization, in addition to any impact the iron may have on squid may therefore give them an advantage over hemoglobin- primary production. dependent fish when faced with severe iron limitation. The fact that squid are found as a direct predator on mesopelagic myctophid fish in the Antarctic Polar Frontal Zone, in the AUTHOR CONTRIBUTIONS absence of any similar vertebrate fish predators (Rodhouse and White, 1995), would appear to be consistent with this possibility. PLM compiled and interpreted the literature data. DK provided In general, we suggest that the taxon-dependent susceptibility of and interpreted the fishing eort data. GH conducted the iron- animals to iron limitation will determine the degree to which they limited model simulations. EG wrote the manuscript. All authors are constrained by iron availability, with consequences for the contributed to the revisions of the manuscript. structure and diversity of marine ecosystems. Finally, we have focused on iron because of its prominence as a limiting factor for phytoplankton. However, other micronutrients FUNDING can also be limiting to phytoplankton (Moore et al., 2013) as well as larval fish (Wang and Wang, 2018). It is therefore This study was supported by the European Research Council conceivable that other micronutrients could also be limiting to (ERC) under the European Union’s Horizon 2020 Research fish in the marine environment. For example, Zn additions have and Innovation Program (Grant Agreement No 682602) and been found to increase phytoplankton growth in HNLC regions the Spanish Ministry of Science, Innovation and Universities, (Crawford et al., 2003), suggesting the ambient concentrations through the “María de Maeztu” Program for Units of Excellence are low, and Zn has also been found to be a critical element for (MDM-2015-0552). the nutrition of larval fish (Wang and Wang, 2018). ACKNOWLEDGMENTS CONCLUSION We thank Jérôme Guiet, Ian Hatton, Maite Maldonado, and The idea that dietary iron supply can constrain fish growth is Adrian Marchetti for helpful discussions. not new: it has been recognized in mariculture for decades. The new hypothesis advanced here proposes that iron supply also plays a role in the wild. At the very least, the data summarized SUPPLEMENTARY MATERIAL in Figure 4 imply that some fish have iron requirements that exclude them from iron-limited waters. The more consequential The Supplementary Material for this article can be found possibility is that the epipelagic fish biomass is significantly lower online at: https://www.frontiersin.org/articles/10.3389/fmars. in iron-limited waters than it would be were iron more abundant. 2019.00509/full#supplementary-material

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Frontiers in Marine Science | www.frontiersin.org 13 August 2019 | Volume 6 | Article 509 Supplementary Material for “Growth limitation of marine fish by low iron availability in the open ocean”

Galbraith, Eric D., Priscilla Le M´ezo, Gerard Solanes Hernandez, Daniele Bianchi and David Kroodsma

1 Conversion factors for previously-reported Fe mea- surements

The diversity of units in which Fe concentrations have been reported in the literature presents a challenge for comparison of Fe among organisms. Many studies on plankton report Fe:C ratios, but this is very rarely the case for higher trophic levels. Instead, most report the Fe concentration relative to biomass, either fresh (wet) or dessicated (dry). In order to compare the concentrations directly, we converted the biomass-specific Fe ratios to C-specific ratios (Table S1), assuming that 12.5% of fish wet weight is carbon (50% of organism dry weight is carbon and dry weight is 25% of wet weight) and assuming 6.2% of zooplankton wet weight is carbon (39% of organism dry weight is carbon and dry weight is 16% of wet weight) (Table S1). These conversions were chosen as representative averages based on the reported conversions given in tables S2 and S3, but it should be borne in mind that they have significant uncertainties, and could be greatly improved by further work. In the tables that follow, we indicate the units in which the iron contents were originally reported, as well as the converted Fe:C molar ratio.

Supplementary Table 1: Conversion factors used in this study, based on the mean values from tables S2 and S3.

dry weight : wet C mass : dry From ppm wet weight From ppm dry weight Organism weight weight to μmolFe/molC to μmolFe/molC

Zooplankton 0.16 0.39 ~3.44 ~0.55 Fish 0.25 0.50 ~1.74 ~0.43

1

1 Supplementary Table 2: Conversion factors between dry and wet weight for marine plankton and marine fish from the literature. Table S2 : Conversion factors between dry and wet weight

Organism Dry matter content in wet matter Ratio dry/wet Reference

Plankton

Euphausids wet:dry = 8.45 0.12 Martin and Knauer, 1973 Copepods wet:dry = 10.78 0.09 Martin and Knauer, 1973 Radiolarians wet:dry = 13.05 0.08 Martin and Knauer, 1973 Euphausiids 4.7 wet-dry ratio 0.21 Fowler, 1977 Krill dw=23%wm 0.23 Nicol et al., 1992 Krill 14.4-26.2 %dm 0.14-0.26 Bernard and Allen, 2002 Krill, pacifica 18.9 %dm 0.19 Bernard and Allen, 2002 Krill, superba 19.2 %dm 0.19 Bernard and Allen, 2002 Zooplankton dm=12%wm 0.12 Griffiths et al., 2006 Zoobenthos dm=20%wm 0.20 Griffiths et al., 2006 Gelatinous group 4-5 %wm 0.04-0.05 Ctenophores 4.0 +/- 0.4 0.04 Tunicates 5.4 +/- 1.9 0.05 Cnidarians 4.1 +/- 0.3 0.04 Non-gelatinous group 18.3 +/- 1.9 %wm 0.18 +/- 0.02 Chaetognaths 9.3 +/- 1.6 0.09 Kiorboe et al., 2013 Polychaetes 13.4 +/- 1.7 0.13 Pteropods 23.0 +/- 19.4 0.23 Copepods 16.2 +/- 2.4 0.16 Euphausids 22.8 +/- 1.4 0.23 Amphipods 23.9 +/- 9.0 0.24 Squid 17.2 % 0.17 Mazzaro et al., 2016 Fish

Atlantic Salmon 18-40 % dry matter in ww 0.18-0.4 Shearer, 1994 Yellow perch dw = 22-27.5 % ww 0.22-0.28 Hartman & Brandt, 1995 Rainbow trout dw = 28-38 % ww 0.28-0.38 Hartman & Brandt, 1995 Bay anchovy dw = 11-23 % ww 0.11-0.23 Hartman & Brandt, 1995 Anchovies 25.8-36.9 %dm 0.26-0.37 Butterfish 31 % dm 0.31 Capelin 14.6-22.8 %dm 0.15-0.23 Goldfish 19.4 %dm 0.19 Herring 23.9-32.1 %dm 0.24-0.32 Herring, Atlantic 20.6-28.6 %dm 0.21-0.29 Mackerel, Atlantic 31.2-36.9 %dm 0.31-0.37 Mackerel, Pacific 23.7-33.4 %dm 0.24-0.33 Bernard and Allen, 2002 Mackerel, Spanish 33.8 %dm 0.34 Minnows 18.6 %dm 0.19 Salmon 22.3 %dm 0.22 Shrimp, whole 18.8-23.3 %dm 0.19-0.23 Silversides 26.7-29.3 %dm 0.27-0.29 Smelt, ocean 20.4-25.4 %dm 0.20-0.25 Squid 15.4-18.8 %dm 0.15-0.19 Whitebait 20.4 %dm 0.20 Fish dm=22%wm 0.22 Griffiths et al., 2006 Atlantic herring dm=25 % wm 0.25 Mazzaro et al., 2016 Atlantic mackerel dm=31.3 +/- 1.6 % wm 0.31 Mazzaro et al., 2016 Capelin dm=21.3 +/- 0.3 % wm 0.21 Mazzaro et al., 2016

1

2 Supplementary Table 3: Conversion factors between carbon content and dry weight for marine plankton and fish from the literature.Table S3 : Conversion factors between dry weight and carbon content

Organism C content (% dry mass) Reference

Plankton

Zooplankton 32 Baines et al., 2016

Gelatinous group 9.5 Ctenophores 5.1 +/- 2.2 Tunicates 10.3 +/- 3.9 Cnidarians 13.2 +/- 2.1 Non-gelatinous group 43.5 +/- 1.3 Chaetognaths 36.7 +/- 3.1 Kiorboe et al., 2013 Polychaetes 37.0 +/- 3.6 Pteropods 28.9 +/- 4.8 Copepods 48 +/- 1.4 Euphausids 41.9 +/- 4.1 Amphipods 34.5 +/- 3.2 Amphipod (Parathemisto japonica) 37 Euphausiids (Thysanoessa longipes) 43.9 Copepod (Calanus plumchrus) 39.1 Masuzawa et al., 1988 Chaetognath (Sagitta elegans) 45.2 Mixed zooplankton 37.1

Fish

Fish (muscles and organs) 44.3-56 Vinogradov, 1953 Various fishes (n=242) 46 Sterner and George, 2000 Wild caught marine fish (whole body) 38.8-47.5 (mean=41) Czamanski et al., 2011 Aquacultured fish (whole body) 43.7-58.7 (mean=52.1) E. japonicus (whole fish tissue) 45 Huang et al., 2012

1

3 2 Iron content of phytoplankton

The Fe:C molar ratios of phytoplankton were calculated from studies in the literature. We di- vided the measurements between organisms that were living in “Very likely Fe-poor conditions” and “Very likely Fe-rich conditions”. For the former, we took only measurements that had been made on organisms isolated from iron-poor waters. We did not include organisms isolated from iron-rich coastal waters and grown under iron-limited conditions, given that they were not adapted to low-iron conditions and therefore may not be representative of iron-limited commu- nities. Similarly, for the “Very likely Fe-rich conditions” category, we took only measurements that had been made on organisms isolated from coastal, presumably iron-rich waters and grown in culture under iron-replete conditions.

Supplementary Table 4: Iron to carbon ratios in phytoplankton Table S4 : Iron content of phytoplankton

Content in original units (µmolFe/molC) Reference Common name Latin name Locality min mean max std

Phytoplankton Whole ocean 2.13 60.5 258 Moore et al., 2013

Very likely Fe-poor conditions - 6 Twining et al., 2004 Diatoms Southern Ocean - Equatorial Pacific 12.3 Twining et al., 2011 Pseudo-Nitzschia Subarctic Pacific 2.8 3.7 Marchetti et al., 2006 Autotrophic - Southern Ocean 8.7 Twining et al., 2004 flagellates - Equatorial Pacific 14.2 Twining et al., 2011 F. kerguelensis 0.8 4.2 Diatoms E. antarctica Southern Ocean 0.9 1.0 Strzepek et al., 2011 P. inermes 0.4 2.6

Very likely Fe-rich conditions Diatoms T. oceanica 31.5 3.6 Stony Brook Cryptophyte R. salina 23.5 3.5 Chen et al., 2011 Harbor Prymnesiophyte I. galbana 36.7 5.1

- Southern Ocean 22.8 Twining et al., 2004 T. weissflogii - 35 6 Schmidt et al., 1999

Pseudo-Nitzschia Northeast Pacific 222 26 Diatoms Pseudo-Nitzschia Denmark 176 20 Marchetti et al., 2006 T. oceanica Sargasso Sea 115 4 Estuaries on Long Sunda and Huntsman, T. weissflogii 30.8 Island 1995 Autotrophic - Southern Ocean 36.1 Twining et al., 2004 flagellates Estuaries on Long Sunda and Huntsman, Dinoflagellate P. minimum 36.5 Island 1995 Sunda and Huntsman, Cyanobacteria S. bacillaris - 250 1995

Table 6 from King et al., 2012 ? (biogenic Fe:C by 3size fractions Iron not content of zooplankton taxa) The Fe:C molar ratios were calculated from studies in the literature, including both field samples and laboratory cultures. Because it is not clear to what degree zooplankton of a given species can alter their cellular Fe:C under iron limitation, we did not include zooplankton isolated from coastal waters and fed low-iron food in the “Very likely Fe-poor conditions” section, but only included zooplankton that had been collected from waters identified by the authors as iron-poor. Nor did we classify samples from coastal Antarctic waters as Fe-poor conditions. This leaves three observations as being very likely from iron-poor conditions, one of which is krill muscle only (rather than whole body). For the latter, we used the observed mean ratio between the

4

1 muscle iron content and the whole body iron content given by Ratnarajah et al., 2016 to compute a whole body iron to carbon ratio for this observation. We also include “Uncertain/mixed status” measurements in order to provide a broader context, though we do not include these values in Figure 2. Notably, the reported iron contents of krill are highly variable, spanning more than an order of magnitude, as previously explored by Ratnarajah et al., 2016. It seems likely that at least some of the high concentrations are due to the inclusion of lithogenic iron in krill stomachs, as reported by Schmidt et al. (2011); we did not include whole krill or salps (e.g. Krishnamurthy et al., 1985) that had been explicitly identified as containing lithogenic iron in our table. The variability among krill is also likely to include spatial or seasonal variations (Ratnarajah et al., 2016).

5 Table S5 : Iron content of heterotrophs. SI units are calculated by assuming 16% dry matter in wet matter and 39% carbon in dry matter (mean values for Supplementary Table 5: Ironzooplankton to carbon (excluding ratios gelatinous in zooplankton. zooplankton) from See Tables section S2 and S3) 3 above for conversion factors.

Content in original units Content in SI units (µmolFe/ Common name Latin name Locality Comment Original units molC) Reference min mean max std min mean max std

Very likely Fe-poor conditions

Heterotrophic Southern Ocean 14.1 14.1 Twining et al., 2004 µmolFe/molC flagellates Equatorial Pacific 9.4 9.4 Twining et al., 2011 muscle only 2400 µgFe/kg dry matter 1.3 Schmidt et al., 2011 whole krill using Krill Euphausia superba Scotia sea Ratnarajah et Schmidt et al., 2011 7440 µgFe/kg dry matter 4.1 al., 2016 Ratnarajah et al., 2016 mean whole/ muscle ratio

Very likely Fe-rich conditions Stony Brook A. tonsa Fe-rich food 47.8 7.9 µmolFe/molC 47.8 7.9 Chen et al., 2011 Copepods Harbor Calanus plumchus Japan Sea 33 µgFe/g dry weight 18 Masuzawa et al., 1988

P. imperforata Vineyard Sound 98 3 98 3 Chase and Price, Microflagellates Fe-rich food µmolFe/molC P. butcheri Sargasso Sea 101 12 101 12 1997

Thysanoessa Japan Sea 110 µgFe/g dry weight 60.5 Masuzawa et al., 1988 Euphausiids longipes - NW Med Sea 64 µgFe/g dry matter 35.2 Fowler, 1977

Parathemisto Amphipods Japan Sea 240 µgFe/g dry weight 132 Masuzawa et al., 1988 japonica

Chaetognaths Sagitta elegans Japan Sea 190 µgFe/g dry weight 104.5 Masuzawa et al., 1988

Mixed zooplankton Japan Sea 450 µgFe/g dry weight 247.5 Masuzawa et al., 1988

Amonalocera 191 µgFe/g dry weight 105.05 Copepod patersoni 306 µgFe/g dry weight 168.3 Off Monaco coast, Krishnaswami et al., Crab larvae - Mediterranean Sea 85 µgFe/g dry weight 46.75 1985 - 248 µgFe/g dry weight 136.4 Mixed copepods - 278 µgFe/g dry weight 152.9

Uncertain/Mixed status - Coastal Antarctic Whole 208 µgFe/g dry matter 114.4 Honda et al., 1987 Stony Brook Fe-poor food A. tonsa 54.8 8.7 µmolFe/molC 54.8 8.7 Chen et al., 2011 Harbour

Copepods - - Fe-poor food 5 3 5 3 µmolFe/molC Schmidt et al., 1999 - - Fe-rich food 12 10 12 10 Martin and Knauer, - Monterray Bay 197 µgFe/g dry weight 108 1973 Martin and Knauer, Euphausiids Monterray Bay 92 µgFe/g dry weight 51 1973 Martin and Knauer, Radiolarians Monterray Bay 315 µgFe/g dry weight 173 1973 Heterotrophic Southern Ocean 21.9 µmolFe/molC 21.9 Twining et al., 2004 flagellates Euphausia superba Coastal Antarctic Whole 5.55 14.4 27.1 µgFe/g dry matter 3.1 7.9 14.8 Honda et al., 1987 Euphausia superba Scotia sea Whole 27.5 32.5 41.1 µgFe/g dry matter 15.0 17.7 22.4 Yamamoto et al., 1990

Western Antarctic Whole 4.7 15.4 59.5 Locarnini and Presley, Euphausia superba 8.50 28.0 108.0 µgFe/g dry matter Peninsula 1995

Euphausia superba Ross Sea 7.59 0.02 µgFe/g wet mass 26.1 0.1 Caroli et al., 1998 Euphausia superba Marguerite Bay 5.71 0.07 µgFe/g wet mass 19.6 0.2 Caroli et al., 1998

Euphausia superba Livingston island 5.68 0.02 µgFe/g wet mass 19.5 0.1 Caroli et al., 1998

Euphausia superba Southern Ocean 56.2 10 µgFe/g dry weight 30.9 5.5 Barbante et al., 2000

Euphausia superba Southern Ocean 174.3 mgFe/kg dry matter 95.9 Nicol et al., 2010 Pseudeuphausia Southern Ocean 151.1 mgFe/kg dry matter 83.1 Nicol et al., 2010 latifrons Nyctiphanes Southern Ocean 91.4 mgFe/kg dry matter 50.3 Nicol et al., 2010 australis Krill Euphausia pacifica Southern Ocean 62.1 mgFe/kg dry matter 34.2 Nicol et al., 2010 Euphausia similis Southern Ocean 36.5 mgFe/kg dry matter 20.1 Nicol et al., 2010 Euphausia krohnii Southern Ocean 34.2 mgFe/kg dry matter 18.8 Nicol et al., 2010 Maganyctiphanes Southern Ocean 12 3.3 mgFe/kg dry matter 6.6 1.8 Nicol et al., 2010 norvegica digestive 13.7 1.6 13.7 1.6 gland stomach 7.1 0.6 7.1 0.6 krill body (no stomach and µmolFe/molC 4.3 0.6 4.3 0.6 Prydz Bay, digestive Euphausia superba Ratnarajah et al., 2016 Antarctica gland) whole krill 10.3 4.3 10.3 4.3 19 7 10.5 3.9 whole krill 10 3 5.5 1.7 mgFe/kg dry weight 18 12 9.9 6.6

1

6 Content in original units Content in SI units (µmolFe/ Common name Latin name Locality Comment Original units molC) Reference min mean max std min mean max std muscle 5 1 2.8 0.6

P. imperforata Vineyard Sound 8.2 0.1 µmolFe/molC 8.2 0.1 Chase and Price, Microflagellates Fe-poor food P. butcheri Sargasso Sea 12.5 0.2 µmolFe/molC 12.5 0.2 1997

Mesozooplankton 1230 nmolFe/g dry weight 38.1 Large migrant Coasta Rica 15 µmolFe/molC 15 Baines et al., 2016 zooplankton Upwelling Dome Resident mixed 60 µmolFe/molC 60 layer zooplankton

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7 4 Iron content of fish

The iron content of edible fish tissues has been widely measured for nutritional purposes. All fish-tissue iron content measurements we identified in the peer-reviewed literature since 1977 are given in Table S6. In addition, we include three peer-reviewed sources that unambiguously reported the Fe content of the whole body for marine fish (Shearer et al., 1994; Andersen et al., 1996 and Honda et al., 1987), which is the quantity of most relevance here. These values are highlighted with a grey background in the table. A number of whole body Fe contents are provided by Bernard and Allen (1997), cited in Moreno and Ha↵a (2014), but these are not peer-reviewed and are therefore given in a separate table (Table S7). We would emphasize the limitations of the existing data constraints, which would greatly benefit from further work. A large number of fish muscle Fe content has also been compiled in Vinogradov (1953), these values are listed in Table S8 but are not included in the figures as the measurements were likely biased due to practical limitations.

8 Table S6 : Iron content of marine fish. SI units are calculated by assuming 25% dry matter in wet matter and 50% carbon in dry matter (mean values for marine fish from Tables S2 and S3). Supplementary Table 6: Iron toGrams carbon of edible ratios matter inare associated marine to fish. grams See of wet section matter. 3 above for conversion factors.

Content in original units Content in SI units (µmolFe/molC) Common name Latin name Locality Comment Original units Reference min mean max std min mean max std Bristol Bay, Sockeye salmon Oncorhynchus nerd 23.9 4.6 10.3 2.0 Alaska Gadus Pacific cod 13.7 1.6 5.9 0.7 macrocephalus Microstomus Dover sole 14.7 1.2 6.3 0.5 pacificus Sebastodes Rockfish, black 15.1 1 6.5 0.4 melanops Gordon and Roberts, North Pacific muscle µgFe/g dry weight Sebastodes 1977 Rockfish, orange coast (Astoria, 21.3 2.6 9.2 1.1 pinniger Newport) Ling cod Ophidon elongatus 15.7 2.2 6.8 0.9 Petrale sole Eopsetta jordani 9.1 1 3.9 0.4 English sole Parophys vetulus 16.6 2.1 7.1 0.9 Merluccius Pacific hake 24.3 3 10.4 1.3 productus muscle 0.95 2.1 8.25 1.6 3.6 14.2 Trematomus Emerald rockcod liver 14.9 44.9 102 25.6 77.2 175.4 bernacchii whole 6.93 14.9 46.5 11.9 25.6 80.0 muscle 1.42 2.84 5.95 2.4 4.9 10.2 Pagotenia Bald notothen Antarctic liver 10 43.2 114 µgFe/g wet weight 17.2 74.3 196.1 Honda et al., 1987 bochgrevinki whole 4.04 6.51 9.25 6.9 11.2 15.9 Notothenioidei whole 3.71 5.81 7 6.4 10.0 12.0 Myctophid whole 10.8 12.3 13.8 18.6 21.2 23.7 Scomberomorus Seer 1.1 18.9 guttatus Hilsa Hilsa hilsa 1.2 20.6 Anchovy Thryssa purava 1.5 25.8 Pomfret (black) - 0.8 13.8 Pseudosciaena Jew fish 0.9 15.5 diacanthus Mullet Mugil cephalus 0.8 13.8 Rastrelliger Chandrashekar and Mackerel India 1.3 mgFe/100g muscle 22.3 kanagurta Deosthale, 1993 Muraenesox Conger eel 0.8 13.8 talabon Pomfret Pampus argenteus 0.5 8.6 Trevally Caranx sansun 1.8 30.9 Nemipterus Pink Perch 1.7 29.2 japonicus Lesser Sardine Sardinella fimbriata 1.1 18.9 Thread fins Polynemus indicus 0.8 13.8 Whole body 15 20 26 34 - juveniles Atlantic salmon Salmo salar ppm, wet weight Shearer et al., 1994 Whole body 15 25 26 43 - mature fish Fe limited Whole body 6.3 9.5 11 16 Fe limited Liver 18 56 31 96 Atlantic salmon Salmo salar L. mg/kg wet weight Andersen 1996 Fe replete Whole body 9.5 15 16 26 Fe replete Liver 56 124 96 213 different Fe Atlantic salmon whole body 7.0 10.1 18.7 mg/kg wet weight 12.0 17.4 32.1 Andersen et al., 1997 supplementation Engraulis Anchovy 1.13 0.02 19.4 0.3 encrosicholus Sprattus sprattus Sprat 0.47 0.04 8.1 0.7 sprattus Trachurus Scad 0.45 0.03 7.7 0.5 mediterraneus Merlangius Black sea mgFe/100g edible Güner et al., 1998 Whiting 0.25 0.01 4.3 0.2 merlangus euxinus Red Mullet Mullus barbatus 0.45 0.04 7.7 0.7 Garfish Belone belone 0.59 0.04 10.1 0.7 Shad Alosa alosa 1.58 0.09 27.2 1.5 Sea bream Smaris alcedo 0.35 0.04 6.0 0.7 Bonito Sarda sarda 1.56 0.11 26.8 1.9 Dicentrarchus Cultured Sea bass 51.22 2.83 22.0 1.2 labrax Dicentrarchus Greece µgFe/g dry weight Alasalvar et al., 2002 Wild Sea bass 63.1 5.86 27.1 2.5 labrax muscle 19.6 7.84 8.4 3.4 Gilthead Sparus auratus liver 256.5 108.8 110.2 46.8 gill 152.91 62.33 65.7 26.8 muscle 78.4 36.84 33.7 15.8 Smelt Atherina hepsetus liver 393.22 171.4 169.0 73.7 gill 793.73 411.1 341.1 176.7 muscle 38.71 18.28 16.6 7.9 Grey mullet Mugil cephalus liver 370.43 252.7 159.2 108.6 gill 275.67 71.28 118.5 30.6 NE Med Sea µgFe/g dry weight Canli and Atli, 2003 muscle 30.68 10.2 13.2 4.4 Red gurnard Trigla cuculus liver 582.37 208.9 250.3 89.8 gill 499.05 339.9 214.5 146.1 muscle 39.6 8.62 17.0 3.7 Sardine Sardina pilchardus liver 225.47 51.49 96.9 22.1 gill 227.42 32.46 97.7 14.0 muscle 29.82 16.24 12.8 7.0 Scomberesox Saury Pike liver 407.08 144.9 174.9 62.3 saurus gill 885.49 514.3 380.5 221.0 Brushtooth Saurida 0.82 4.175 11.28 0.4 1.8 4.8 lizardfish undosquamis Iskenderun Bay muscle mgFe/kg dry weight Türkmen et al., 2005 Red mullet Mullus barbatus 2.45 9.682 17.92 1.1 4.2 7.7 Gilthead sea bream Sparus aurata 4.59 13.166 27.35 2.0 5.7 11.8 Engraulis European anchovy 95.6 8.1 41.1 3.5 encrasicholus Gilthead seabream Sparus aurata 69.7 5.6 30.0 2.4 Merlangius Whiting 104 9.8 44.7 4.2 merlangus Black scorpionfish Scorpaena porcus Black and 81.5 7.1 35.0 3.1 µgFe/g dry matter Uluozlu et al., 2007 Red mullet Mullus barbatus Aegean Seas 163 12 70.1 5.2 Bluefish Pomatus saltor 68.6 5.3 29.5 2.3 Atlantic horse Trachurus 74.3 6.1 31.9 2.6 mackerel trachurus Flathead mullet Mugil cephalus 82.7 5.6 35.5 2.4 Atlantic bonito Sarda sarda 73.5 6.3 31.6 2.7 Gizzard shad Nematolosa nasus 39.6 45.2 71.5 17.0 19.4 30.7 Scad Alepes para Parangipettai 3.5 24.11 46.8 1.5 10.4 20.1 edible Cleftbelly trevally Atropus atropos coast, south- 42.6 50.3 78.5 µgFe/g dry weight 18.3 21.6 33.7 Raja et al., 2009 muscle east India

1 9 Content in original units Content in SI units (µmolFe/molC) Common name Latin name Locality Comment Original units Reference coast, south- min mean max std µgFe/g dry weight min mean max std Raja et al., 2009 Parastromateus muscle Black pomfret east India 16.7 28.4 50.4 7.2 12.2 21.7 niger Coastal waters 604.75 259.9 off Kochi Sea bass Lates calcifier Coastal waters 500.75 215.2 off Mangalore Coastal waters 438.30 188.4 Nemipterus off Kochi Pink Perch japonicus Coastal waters 333.30 143.2 off Mangalore Coastal waters 649.60 279.2 Caranx off Kochi Bluefin trevally Coastal waters muscle ppm, dry weight Rejomon et al., 2010 melampygus 541.60 232.8 off Mangalore Coastal waters 604.75 259.9 Rastrelliger off Kochi Indian mackerel kanagurta Coastal waters 500.75 215.2 off Mangalore Coastal waters 602.75 259.0 Malabar tongue Cyanoglossus off Kochi sole macrostomus Coastal waters 500.75 215.2 off Mangalore Zebrafish 39.7 mgFe/kg dry matter 17 Kaushik et al., 2011 Coastal waters Nine commercial of Kalpakkam, muscle 17.67 75.83 117 32.32 µgFe/g dry weight 7.6 32.6 50.3 13.9 Biswas et al., 2012 species east of India Atlantic herring Clupea harengs 71 30.5 Scomber 1 month frozen Atlantic mackerel Whole body 70 4 ppm, dry weight 30.1 1.7 Mazzaro et al., 2016 scombrus post-harvest Capelin Mallotus villosus 71 7 30.5 3.0 Common sole Solea solea 3.86 13.52 25.76 1.61 6.6 23.3 44.3 2.8 Red mullet Mullus barbatus Mersin, Turkey muscle 0.93 10.40 19.58 1.36 mgFe/kg wet weight 1.6 17.9 33.7 2.3 Korkmaz et al., 2017 Sardine Sardina pilchardus 1.66 10.3 21.2 1.24 2.9 17.7 36.5 2.1 Larval marine Oryzias melastigma 36 81 15.5 34.8 medaka whole Larval golden Trachinotus ovatus (smallest 25 80 10.7 34.4 pompano value at Wang and Wang, Larval Gilthead sea mgFe/kg dry matter Sparus aurata hatching) 20 110 8.6 47.3 2018 bream Newly hatched the 3 above whole 20 40 8.6 17.2 larvae

Supplementary Table 7: Iron to carbon ratios in zooplankton and marine fish from Bernard and Allen (2002) (non peer- reviewedTable S7 paper).: Iron content See section of zooplankton 3 above and for marine conversion fish from factors. Bernard and Allen (2002). Not peer-reviewed. Conversions are made using 16% dry matter in zooplankton and 25% dry matter in fish (Table S2)

Content in SI units (µmolFe/ Number of Content in original units Common name Latin name Original units molC) samples min mean max min mean max Anchovies Engraulis mordax 10 98 2060 42 886 Butterfish Peprilus sp. 1 147 63 Capelin Mallatus villosus 16 36 140 15 60 Goldfish Cyprinus carpio 1 307 132 Herring Not indicated 6 64 274 28 118 Herring, Atlantic Clupea harengus 5 64 132 28 57 Krill Euphasia sp. 3 96 138 53 76 Krill, pacifica Euphasia pacifica 1 19 10 Krill, superba Euphasia superba 1 432 238 Scomberomorus Mackerel, Atlantic 3 63 100 27 43 scrombus Scomberomorus ppm of dry matter Mackerel, Pacific 3 153 184 66 79 japonicus Mackerel, Scomberomorus 1 83 36 Spanish maculatus Minnows Cyprinidae 1 225 97 Shrimp, whole Penaeus sp. 2 18 180 8 77 Silversides Menidia andens 4 32 54 14 23 Smelt, ocean Osmerus sp. 2 29 36 12 15 Squid Ilex and Loligo sp. 2 12 29 5 12 Clupea harengus Whitebait 1 112 48 or sprattus

2 10 SupplementaryTable S8 : Iron Table content 8: of Ironfish. SI to units carbon are calculated ratios by in assuming fish from 25% Vinogradov dry matter in wet (1953)’s matter and compilation. 50% carbon in Seedry matter section (mean 3 values above for for fish conversion from factors. Tables S2 and S3). Living matter is associated to wet matter.

Content in SI units (µmolFe/ Content in original units Common name Latin name Comment Original units molC) Reference min mean max min mean max Sardinia white muscle 0.001 % living matter 17.2 melanostica Fujikawa and Sardinia Naganuma, 1936 red muscle 0.0015 25.8 melanostica soft parts and Common torpedo 0.0025 % living matter 43.0 Weyl, 1881 Torpedo ocellata muscle European Clupea 0.0012 20.6 pilchard (sardina) pilchardus Merluccius European hake 0.0056 % living matter 96.3 vulgaris soft parts and Carteni and Aloj, Polyprion muscle 1934 Wreckfish 0.0032 55.0 americanus European Engraulis 0.0049 84.2 anchovy encrasicholus soft parts and Tench muscle. whole 0.00145 24.9 Tinca tinca Skanavi-Griigorieva, organism % living matter 1939 soft parts and Common carp 0.00136 23.4 Cyprinus carpio muscle. 5month soft parts and Common carp Cyprinus carpio muscle. whole 0.0013 % living matter 22.3 Bezold, 1857 organism Northern pike Esox lucius 0.0042 72.2 soft parts and Katz, 1896 European eel Anguilla anguilla muscle 0.0056 % living matter 96.3 Haddock Gadus aeglefinus 0.0056 96.3 soft parts and 0.024 % living matter 412.6 Yamamura, 1934 Gadus sp. muscle. dry Six-lined Pelates trumpeter sexlineatus Sillago sp. Pomatomus Bluefish pedica Leptocephalus sp. Caranx White trevally georgianus Regificola grandis Arripis Australian herring georgianus Australian salmon Arripis trutta Australian salmon Arripis trutta Sciaena antarctica Cynoscion atelodus Chrysophrys guttulatus Roughleyia australis Girella Parore tricuspidata Scatophagus Spotted scat argus Cheilodactylus Tarakihi macropterus Snoek Thyrsites atun Scomber Blue mackerel australasicus Neoplatycephalu % living matter soft parts and Clements and s macrodon 0.001 17.2 Maccullochella muscle Hutchinson, 1939 Trout cod macquariensis Pleuronectes arsius Synaptura nigra Fan-bellied Monacanthus leatherjacket chinensis Pseudomonacant hus ayraudi Reporhamphus australis Mustelus Gummy shark antarcticus Raja sp. Potamalosa novaehollandiae Trachichthodes affinis Zeus australis Australilan Sphyraena barracuda novaehollandiae Flathead grey mullet Mugil cephalus Australian threadfin Polynemus sp.

1

11 Content in SI units (µmolFe/ Content in original units Common name Latin name Comment Original units molC) Reference min mean max min mean max Barramundi Lates calcarifer Epinephelus sp. (?) Sevenbar Epinephelus grouper ergastularius Plectroplites ambiguus Ruboralga jacksoniensis starspotted Oya and Shimada, 3 0.24 4.1 smooth-hound Mustelus manazo 1933 Shackleton and 0.33 5.7 Raja latis McCance, 1936 Acipenser Sterlet sturgeon 1.6 27.5 Kostychev, 1883 ruthenus Acipenser sp. 1.5 25.8 Kostychev, 1883 soft parts and 3.3 56.7 Kostychev, 1883 Acipenser sp. muscle. ROE Alosa Parks and Rose, American shad 0.48 8.3 sapidissima 1933 Alosa Peterson and American shad 0.53 9.1 sapidissima Elvehjem, 1928 Parks and Rose, Atlantic herring 0.57 9.8 Clupea harengus 1933 Peterson and Atlantic herring 0.59 10.1 Clupea harengus Elvehjem, 1928 Shackleton and Atlantic herring 1.02 17.5 Clupea harengus McCance, 1936 Shackleton and Atlantic herring 0.63 10.8 Clupea harengus McCance, 1936 European Clupea Carteni and Aloj, 1.2 20.6 pilchard pilchardus 1934 South American Nilson and Coulson, 2.483 42.7 pilchard Sardina caerulea 1939 Sardinia Fujikawa and white muscle 0.7 12.0 melanostica Naganuma, 1936 Sardinia Fujikawa and red muscle 1 17.2 melanostica Naganuma, 1936 Sardinia Oya and Shimada, 2 1.28 22.0 melanostica 1933 Sardinia sp. 0.028 0.5 Lepierre, 1938 European Engraulis Carteni and Aloj, 4.9 84.2 anchovy encrasicholus 1934 Peterson and Whitefish 0.42 7.2 Coregonus sp. Elvehjem, 1928 Whitefish Coregonus sp. 2.1 36.1 Kostychev, 1883 Salmon Roe 2.5 mgFe/100g living 43.0 Greig, 1898 matter Peterson and Salmon Muscles 0.83 14.3 Elvehjem, 1928 Toscani and Salmon 3 0.87 15.0 Reznikoff, 1934 Parks and Rose, Salmon 0.86 14.8 1933 Salmon 1.2 20.6 Rose, 1933 Salmon 2.45 42.1 Kostychev, 1883 Salmo fario 2.8 48.1 Kostychev, 1883 Peterson and 0.78 13.4 Salmo fario Elvehjem, 1928 Parks and Rose, 0.72 12.4 Salmo fario 1933 Osmerus Parks and Rose, European smelt 0.41 7.0 eperlanus 1933 Liver 4.9 5.3 84 91 Spleen 9.5 10.9 163 187 Bones 4.8 5 83 86 Heart 6.4 7.7 110 132 Common carp Kidneys 8.2 8.8 141 151 Kojima, 1930 (freshwater) Cyprinus carpio White muscle 1.3 1.5 22 26 Red muscle 5 5.6 86 96 Stomach 6.5 7.3 112 125 Intestines 5.6 9 96 154 Ovaries 4.1 4.4 70 75 Brain 2.6 3 45 51 Common carp Oya and Shimada, 3 0.78 13.4 (freshwater) Cyprinus carpio 1933 Parks and Rose, 0.94 16.1 Silurus sp. 1933 Esox sp. 2.4 41.1 Kostychev, 1883 Peterson and Young 0.8 13.7 Esox sp. Elvehjem, 1928 Peterson and Young 0.3 5.1 Esox sp. Elvehjem, 1928 Parks and Rose, Young 0.58 9.9 Esox sp. 1933 Parks and Rose, European eel 0.51 8.7 Anguilla anguilla 1933 Henriques and European eel Muscle 2.2 mg Fe/100g dm 9.5 Anguilla anguilla Roche, 1933 Silver eel Liver 105 1805 McCance, 1944 Peterson and Haddock 0.42 7.2 Gadus aeglefinus Elvehjem, 1928 Flesh 1.5 25.8 Whiting Gadus merlangus Whole 82 1409.6 Boussingault, 1872 Bone 10 171.9

2

12 Content in SI units (µmolFe/ Content in original units Common name Latin name Comment Original units molC) Reference min mean max min mean max Nilson and Coulson, Atlantic cod 0.518 8.9 Gadus morrhua 1939 mgFe/100g living Peterson and Atlantic cod 0.36 6.2 Gadus morrhua matter Elvehjem, 1928 Peterson and Atlantic cod 0.34 5.8 Gadus morrhua Elvehjem, 1928 Parks and Rose, Atlantic cod 0.34 5.8 Gadus morrhua 1933 Atlantic cod Gadus morrhua 1.26 21.7 Kostychev, 1883 Atlantic cod Gadus morrhua 4 68.8 Yamamura, 1934 Atlantic cod Gadus morrhua 4.2 72.2 Boussingault, 1872 Henriques and Atlantic cod 6 2.35 10.1 Gadus morrhua mg Fe/100g dm Roche, 1933 Atlantic cod Gadus morrhua Liver 17.3 74.4 McHargue, 1925 Shackleton and Atlantic cod 0.34 5.8 Gadus morrhua McCance, 1936 Parks and Rose, 2.8 48.1 Gadus navaga (?) 1933 Parks and Rose, Burbot 0.96 16.5 Lota vulgaris (?) 1933 Melanogrammus Nilson and Coulson, Haddock 0.516 8.9 aeglefinus 1939 Merluccius Carteni and Aloj, European hake 5.6 96.3 vulgaris 1934 Parks and Rose, Moon fish 0.34 5.8 Molva sp. (?) 1933 Parks and Rose, Wachna cod 0.48 8.3 1933 Flathead grey Nilson and Coulson, 1.1779 20.2 mullet Mugil cephalus 1939 Liver 8 14.1 137.5 242.4 Spleen 38 48 653.2 825.1 Bones 5 6.3 86.0 108.3 Heart 3.5 3.9 60.2 67.0 Flathead grey Kidneys 4.7 5.1 80.8 87.7 Mugil cephalus Kojima, 1930 mullet White muscle 1.6 1.7 27.5 29.2 Red muscle 3.4 4.3 58.4 73.9 Stomach 3.5 4.2 mgFe/100g living 60.2 72.2 Intestines 3.5 3.6 matter 60.2 61.9 Brain 2.7 3 46.4 51.6 Eurpoean Peterson and 0.26 4.5 seabass Labrax lupus Elvehjem, 1928 Japanese Lateolabrax Oya and Shimada, 0.57 9.8 seabass japonicus 1933 Polyprion Carteni and Aloj, Wreckfish 3.2 55.0 americanus 1934 Lucioperca Pike-perch 1.6 27.5 Kostychev, 1883 sandra Peterson and Eurpopean perch 0.48 8.3 Perca fluviatilis Elvehjem, 1928 Parks and Rose, Eurpopean perch 0.42 7.2 Perca fluviatilis 1933 Peterson and Bluefish 0.6 10.3 Pomatomus sp. Elvehjem, 1928 Peterson and Red snapper 0.4 6.9 Lutjanus sp. Elvehjem, 1928 Northern red Lutjanus Nilson and Coulson, 1.158 19.9 snapper blackfordii 1939 Oya and Shimada, 0.24 4.1 Sparus batus 1933 Anarchichas Shackleton and 0.36 6.2 lupus McCance, 1936 Dragonet Callionymus lyra Postlarvae 31 mg Fe/100g dm 133.3 Cooper, 1939 Scomber Nilson and Coulson, Atlantic mackerel 1.224 21.0 scombrus 1939 Scomber Peterson and Atlantic mackerel 0.75 12.9 scombrus Elvehjem, 1928 Scomber Parks and Rose, Atlantic mackerel 0.87 15.0 scombrus 1933 Toscani and Tuna 1.8 30.9 Thunnus sp. Reznikoff, 1934 Tuna Thunnus sp. 1.2 20.6 Rose, 1933 Pacific bluefin Thunnus Oya and Shimada, 3 1.29 mgFe/100g living 22.2 tuna orientalis matter 1933 Oya and Shimada, 1.69 29.1 Limanda sp. 1933 Parks and Rose, 2 0.52 8.9 Pleuronectes sp. 1933 Peterson and 0.73 12.5 Pleuronectes sp. Elvehjem, 1928 Hippoglossus Peterson and Atlantic halibut 0.93 16.0 hipoglossus Elvehjem, 1928 Hippoglossus Shackleton and Halibut 0.44 7.6 vulgaris McCance, 1936

3

13 5 Aquaculture feed recommendations

In Table S8 we compile recommended minimum iron concentrations for fish feed in aquaculture. Aquaculture studies have shown that the availability of iron can vary with the feed composition (e.g. Sugiuraa et al., 1998). In nature, iron bioavailability can be linked to the amount of cytoplasm within the prey and whether iron is bound externally to the prey or is internal (e.g. Reinfelder and Fisher, 1994). It is therefore possible that aquaculture feeds, because of their lack of refractory material such as the exoskeleton of zooplankton, may have more bioavailable iron than some natural prey.

Supplementary Table 9: Iron to carbon ratios recommended in fish food from aquaculture studies. See section 3 above for conversion factors. Table S9 :Aquaculture feed recommendations. SI units calculated using 50% C in dry matter.

Concentration in food in original units Common name Concentration in SI units (µmolFe/molC) Reference (mgFe/kg dry mattter) Larval fish 70 30.1 Wang and Wang, 2018 Larval medaka 83.9 36 Wang and Wang, 2016 Red drum 330 141.8 Zhou et al., 2009 Orange grouper 245 105.3 Ye et al., 2007 Tilapia 85-160 36.5-68.8 Shiau and Su, 2003 Hybrid striped bass 66 28.4 Webster and Lim, 2002 Puffer fish 90-140 38.7-60.2 Zibdeh et al., 2001 Atlantic salmon 60 25.8 Naser 2000 Teleost fish 30-170 12.9-73.1 Watanabe et al., 1997 Atlantic salmon 60-100 25.8-43 Andersen et al., 1996 Yellow tail 101 43.4 Ukawa et al., 1994 Atlantic Salmon 148-156 63.6-67 Tacon & De Silva, 1983 Red sea bream 150 64.5 Sakamoto and Yone, 1978 Japanese eel 170 73.1 Nose and Arai, 1976

14

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