# Omega-3 Pathways in Upwelling Systems: The Link to Nitrogen Supply

Eleonora Puccinelli, Fanny Sardenne, Laure Pecquerie, Sarah Fawcett, Eric Machu, Philippe Soudant

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Eleonora Puccinelli, Fanny Sardenne, Laure Pecquerie, Sarah Fawcett, Eric Machu, et al. Omega-3 Pathways in Upwelling Systems: The Link to Nitrogen Supply. Frontiers in Marine Science, 2021, 8, 10.3389/fmars.2021.664601. hal-03324050

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# Omega-3 Pathways in Upwelling Systems: The Link to Nitrogen Supply

Eleonora Puccinelli¹*, Fany Sardenne¹, Laure Pecquerie¹, Sarah E. Fawcett²,³, Eric Machu⁴ and Philippe Soudant¹

¹ University of Brest- UMR 6539 CNRS/UBO/IRD/Ifremer, LEMAR - IUEM, Plouzané, France, ² Department of Oceanography, University of Cape Town, Cape Town, South Africa, ³ Marine and Antarctic Research Centre for Innovation and Sustainability (MARIS), University of Cape Town, Cape Town, South Africa, ⁴ IRD/Laboratoire d'Océanographie Physique et Spatiale (LOPS), IUEM, University of Brest, CNRS/UBO/IRD/Ifremer, Plouzané, France

Omega-3 long-chain polyunsaturated fatty acids (hereafter, omega-3), including eicosapentaenoic-acid (EPA) and docosahexaenoic-acid (DHA), are essential nutritional compounds for humans, providing several benefits related to cardiovascular and neural health. Human intake of omega-3 occurs mostly via seafood, particularly fish. The primary source of omega-3 in aquatic systems is represented by primary producers, from which omega-3 are transferred throughout the food web. Nitrogen is an essential nutrient for primary producers and can be supplied to surface waters as nitrate upwelled from below, or as ammonium and other regenerated nitrogen forms recycled in situ. Eastern Boundary Upwelling Systems (EBUS) are the most productive marine systems on Earth, together covering only 2% of the ocean's surface area but supporting 25% of the global fish catch, thereby providing food for humans. In EBUS, nitrate and other nutrients are advected to the surface to support the proliferation of a phytoplankton community dominated by known omega-3 producers (i.e., diatoms). Given current climate change-related projections of ocean warming, acidification, deoxygenation, and increased upwelling intensity, phytoplankton community composition in EBUS may change. Additionally, the global production of EPA + DHA is expected to decrease by up to 30%, rendering its supply for human consumption insufficient by 2050. Here we discuss the state of knowledge related to omega-3 transfer from phytoplankton to small pelagic fish in EBUS, including factors that can influence omega-3 production, links to nitrogen cycling, climate change implications for the omega-3 supply to humans, and suggestions for future research directions to improve our understanding of omega-3 in the ocean.

**Keywords:** omega-3, food web, small pelagic fish, nitrogen supply, coastal upwelling, plankton, climate change, biogeochemical model

**OPEN ACCESS**

**Edited by:**
Susana Agusti,
King Abdullah University of Science
and Technology, Saudi Arabia

**Reviewed by:**
Heidi Pethybridge,
Oceans and Atmosphere (CSIRO),
Australia
Gleyci A. O. Moser,
Rio de Janeiro State University, Brazil
Jose Juan Barrera-Alba,
Federal University of São Paulo, Brazil

*Correspondence:
Eleonora Puccinelli
eleonora.puccinelli@univ-brest.fr;
eleonorapuccinelli@gmail.com

**Specialty section:**
This article was submitted to
Global Change and the Future Ocean,
a section of the journal
Frontiers in Marine Science

**Received:** 05 February 2021

**Accepted:** 04 May 2021

**Published:** 04 June 2021

**Citation:**
Puccinelli E, Sardenne F, Pecquerie L, Fawcett SE, Machu E and Soudant P (2021) Omega-3 Pathways in Upwelling Systems: The Link to Nitrogen Supply. *Front. Mar. Sci.* 8:664601.
doi: 10.3389/fmars.2021.664601

## INTRODUCTION

Omega-3 long chain polyunsaturated fatty acids (hereafter, omega-3) such as eicosapentaenoic-acid (20:5n-3, EPA) and docosahexaenoic-acid (22:6n-3, DHA) are essential compounds for marine consumers and human health (Ruess and Müller-Navarra, 2019), and are acquired through dietary intake (Arts et al., 2001). The main producers of omega-3 in the ocean are phytoplankton, with the
amount of omega-3 contained in consumers being determined
by the type of phytoplankton at the base of the food chain, and
the transfer efficiency of omega-3 across trophic levels (Dalsgaard
et al., 2003). In this context, zooplankton represent a key trophic
link between the producers of omega-3 and small pelagic fish
(e.g., sardine, anchovy, and herring; Bi and Sommer, 2020), the
latter being a major source of omega-3 for human consumption
(Hicks et al., 2019), as well as a main constituent of aquaculture
feeds (Tacon and Metian, 2009). The supply of omega-3 is
expected to change in the near future as a consequence of climate
change (e.g., Hixson and Arts, 2016; Colombo et al., 2020), with
implications for meeting the omega-3 requirements of a growing
human population that is predicted to reach 11 billion by 2100
(Roser, 2013). Major climate-driven factors relevant to omega-
3 production include warming (Hixson and Arts, 2016), ocean
acidification (Dörner et al., 2020), and variability in upwelling
intensity (Puccinelli et al., 2016a).

Coastal upwelling areas are amongst the most productive
ocean regions owing to the wind-driven advection of nutrient-
rich waters to the surface that promote primary and secondary
production (Peterson et al., 1988; Vargas et al., 2007; Flynn et al.,
2018). In these regions, nitrate (NO3- ) upwelled from depth
is the major source of nitrogen (N) for primary production
(Waldron and Probyn, 1992; Messié et al., 2009; González-
Galisteo et al., 2019), often supporting >>50% of phytoplankton
growth (Chavez and Messié, 2009; Messié et al., 2009). At the
cellular level, N is required for the synthesis of nucleic acids,
amino acids, and chlorophyll (Dagenais-Bellefeuille and Morse,
2013), thus affecting omega-3 production (Yongmanitchai and
Ward, 1991; Griffiths et al., 2012). Eastern Boundary Upwelling
Systems (EBUS) occupy 2% of ocean surface but support 25%
of the global fish catch and 8% of global primary production
(Pauly and Christensen, 1995). These systems facilitate broad-
scale fertilization of the upper water column and sustain many
of the world's important fisheries (Cury and Roy, 1989; Ward
et al., 2006), including those centered around small pelagic fish,
which provide up to 50% of annual human protein intake in
some regions (e.g., West Africa; FAO, 2014). This is particularly
relevant for the EBUS located off the African and South American
continents, upon which millions of people rely for economic
and food security. For instance, the Peruvian anchovy fishery
accounts for 65% of global anchovy production and contributes
90% to the Peruvian fishery sector's Gross Domestic Product
(Aronés et al., 2019).

Here we provide an overview of the current state of
knowledge on omega-3 transfer from phytoplankton to small
pelagic fish in EBUS, including factors that can influence
omega-3 production, links to the N cycle, climate change
implications for omega-3 availability to humans, current gaps
in our understanding and suggestions for future developments
needed to increase our knowledge of omega-3 in the ocean.
As an essential compound for human health (Ruess and
Müller-Navarra, 2019), omega-3 could aid in ameliorating
malnutrition, thus playing a fundamental role in food security.
Additionally, understanding the role that upwelling plays in
omega-3 production and how this may vary with climate change,
is relevant to the following Sustainable Development Goals

(SDGs): zero hunger (SDG2), climate action (SDG13), and life
under the sea (SDG14).

OMEGA-3 PRODUCTION AND ROLE IN
THE OCEAN

In the ocean, omega-3 are mostly synthesized by phytoplankton, and phytoplankton community composition is a major factor regulating the amount of omega-3 produced in a particular system (Galloway and Winder, 2015). High food-quality species are characterized by high levels of EPA and/or DHA [e.g., diatoms and dinoflagellates, EPA and/or DHA > 25% of total fatty acids (FA); Hixson and Arts, 2016; Jónasdóttir, 2019] and low food-quality species by lower concentrations of EPA + DHA [e.g., cyanobacteria, which produce mostly short-chain polyunsaturated FA (PUFA), i.e., ≤C18 PUFA; Parrish, 2013]. Specifically, diatoms appear to be a major producer of EPA (Dalsgaard et al., 2003), while dinophytes and haptophytes are the main sources of DHA in the ocean (Figure 1; Remize et al., 2020). FA production can be affected by abiotic factors including temperature, which plays a key role in controlling the level of FA unsaturation, influencing the fluidity of cell membranes (Rousch et al., 2003); light availability, which affects phytoplankton species composition (Harrison et al., 1990); and salinity, which influences membrane permeability (Chen et al., 2008).

Omega-3 are a limiting factor for zooplankton and higher
trophic levels production (Bi and Sommer, 2020), as these
organisms cannot synthesize these FA in sufficient quantities to
support their nutritional requirements and must thus acquire
them through their diet (Dalsgaard et al., 2003; Litzow et al.,
2006). Omega-3 are precursors to eicosanoid hormones and a
major component of cell membranes (Parrish, 2013), playing a
fundamental role in maintaining membrane functioning, which
can be modified by changing the length and the level of
unsaturation of the FA carbon chains (Sinensky, 1974; Guschina
and Harwood, 2006). The essential role of omega-3 in marine
organism fitness is widely known. For instance, zooplankton
growth, development and reproduction output are dependent on
the amount of omega-3 available in their food (Müller-Navarra
et al., 2000; Brett et al., 2006; Ravet et al., 2010). Similarly,
fish brain and optic tectum development and oocyte quality
depend on the DHA content of their prey (Bell et al., 1995;
Garrido et al., 2007), and fish larvae with a higher EPA + DHA
content present enhanced swimming ability, schooling behavior,
and higher survival rates after hatching (Ishizaki et al., 2001;
Mourente, 2003).

LINKS BETWEEN MARINE NITROGEN
CYCLING AND OMEGA-3

Phytoplankton community composition depends on several
factors including nutrient availability. In the euphotic zone,
phytoplankton growth can be supported by NO3- supplied from
below, for instance via upwelling (yielding “new production”),
or by N forms such as ammonium (NH4+) recycled in the
<figure><img src="image_3.png" /></figure>

**FIGURE 1** | Schematic representation of omega-3 pathways in an upwelling system across trophic levels, focusing on the link between nitrogen (N) sources [newly upwelled N (NO₃⁻, white) and recycled N (NH₄⁺, orange)], select primary producers (diatoms, dinoflagellates, autotrophic bacteria), primary consumers (zooplankton), and higher trophic levels (small and large pelagic fish). The thickness of the white and orange lines indicates the relative use of upwelled NO₃⁻ and recycled NH₄⁺ by the different phytoplankton groups. Pie charts show the % of eicosapentaenoic-acid (EPA), docosahexaenoic-acid (DHA), and the sum of the other fatty acids (Other) produced by the three phytoplankton groups. With climate change, upwelling is predicted to intensify, which may increase the upward supply of NO₃⁻ and drive the ecosystem towards enhanced diatom growth, higher transfer efficiency, and elevated omega-3 production (i.e., the thick white lines will become thicker). Alternately, warming may drive a net decline in upwelled NO₃⁻, resulting in enhanced NH₄⁺ recycling, a shift toward smaller phytoplankton species, less efficient trophic transfer, and a decline in omega-3 production (i.e., the thick orange arrows will become thicker, and the white arrows will become thinner). We note that these scenarios represent just two possibilities, and that there are likely other potential outcomes. Additionally, it is conceivable that the four EBUS will not respond to climate change in the same way.

upper ocean ("regenerated production"; Dugdale and Goering, 1967). When available, NH₄⁺ is often the preferred N form consumed by phytoplankton because its low oxidation state (-3, the same as organic N) renders its assimilation energetically favorable (Dortch, 1990). However, surface NH₄⁺ concentrations are typically << 1 µM (Paulot et al., 2015), although its flux through the food web can be large (Gruber, 2008; Altieri et al., 2021). High NO₃⁻ availability typically leads to growth of large phytoplankton including diatoms (Kudela and Dugdale, 2000; Fawcett and Ward, 2011), while smaller phytoplankton such as cyanobacteria tend toward NH₄⁺ dependence (Probyn and Painting, 1985; Fawcett et al., 2011).

Upwelling events are among the main supply mechanisms of nutrients essential for phytoplankton production (e.g., NO₃⁻, silicate, iron; Dugdale and Wilkerson, 1998; Chavez and Messié, 2009). In upwelling systems, the ratio between new and total (i.e.,

new + regenerated) production is significantly higher than in the open ocean (0.5–0.8 versus ~0.1; Eppley and Peterson, 1979; Laws, 2004) due to the near-constant supply of NO₃⁻, which underpins the elevated productivity of these regions (Messié and Chavez, 2015). Similarly, higher-than-average surface-water iron concentrations favor phytoplankton consumption of upwelled NO₃⁻ over recycled N (Dugdale and Goering, 1967; Bruland et al., 2001), leading to a phytoplankton community dominated by omega-3-rich diatoms. A change in community from diatoms to dinophytes is commonly observed during an upwelling cycle, especially when silicate, essential for the synthesis of diatom frustules, becomes depleted (Martin-Jézéquel et al., 2000; Tilstone et al., 2000).

Since different phytoplankton contain different amounts of omega-3, changes in community composition can cause variations in omega-3 transfer to consumers, ultimately affecting
the omega-3 supply throughout the food web (Bermúdez et al., 2016; Garzke et al., 2016). For instance, it was shown that an increase in pCO₂ caused a shift from nanophytoplankton to picoeukaryotes along with a decline in PUFA in both phytoplankton size fractions, which was mirrored by a PUFA reduction in the copepod species feeding on them (Bermúdez et al., 2016). Similarly, interannual FA variations in small pelagic fish in the California Current was attributed to a shift from a dinoflagellate- to a diatom-dominated food source (Litz et al., 2010). Upwelling food webs are made more complex by the presence of mixotrophic nanoflagellates, organisms that are able to directly consume bacteria and picoplankton (Frias-Lopez et al., 2009), but that can also contribute significantly to primary production, especially during periods of upwelling relaxation (Figueiras et al., 2020). Disentangling omega-3 produced by autotrophic versus mixotrophic organisms in the ocean is challenging, and may lead to an over/underestimation of the omega-3 supply from primary producers.

## THE EASTERN BOUNDARY UPWELLING SYSTEMS

The world's four major EBUS are associated with the Benguela, California, Canary, and Humboldt Currents. Rates of primary production are comparable among these regions (>900 gCm⁻²y⁻¹, **Table 1**), with the exception of the California system where they are two-fold lower (480 gCm⁻²y⁻¹), probably due to the lower NO₃⁻ supply to the euphotic zone (Chavez and Messié, 2009). The availability of regenerated N and the mechanisms of its production (i.e., herbivores, heterotrophic bacteria, higher trophic-level organisms) vary among the systems (Dugdale, 1972). For instance, anchovies are responsible for most N regeneration in the Humboldt system (Kämpf and Chapman, 2016), while in the southern Benguela, up to 48% of the subsurface nutrients are regenerated on-shelf by heterotrophic bacteria (Flynn et al., 2020). EBUS fertilization by dust deposition also influences productivity, especially in the Canary and Benguela systems where the Sahara and Namib Deserts supply nutrients that regularly limit phytoplankton growth, including iron and phosphate (Jickells et al., 2005; Pabortsava et al., 2017).

The high primary productivity of EBUS propagates throughout their ecosystems, with a given concentration of phytoplankton supporting approximately 25- and 50-times as much zooplankton biomass and fish production (Chavez and Messié, 2009; Kämpf, and Chapman, 2016). In the Humboldt system, fish production and zooplankton biomass are an order of magnitude higher than in the other three systems (**Table 1**), which has been attributed to a high transfer efficiency among trophic levels, resulting in optimal conditions for the proliferation and retention of zooplankton and fish (Chavez and Messié, 2009). The same pattern is not evident in omega-3 content, which varies considerably within and among systems. For instance, Benguela phytoplankton contain the lowest amount of omega-3, while omega-3 in zooplankton and small pelagic fish is higher compared to the other EBUS. We note, however, that

limited information is available on omega-3 in EBUS, especially for the Canary system, precluding our ability to generalize while also highlighting the need for further investigations.

## CLIMATE CHANGE EFFECTS ON UPWELLING SYSTEMS AND N SUPPLY

As a result of climate change, upwelling frequency appears to be increasing in several EBUS (Sydeman et al., 2014) due to increasing wind stress (Narayan et al., 2010). This may increase the nutrient supply to phytoplankton, favoring large diatoms and higher transfer efficiency, yielding enhanced production of omega-3. However, changes to upwelling are likely to be complex (Rykaczewski et al., 2015), and along with warming and/or acidification of surface waters, will modify phytoplankton metabolism and community composition, potentially favoring smaller phytoplankton (e.g., picoeukaryotes) at the expense of the nano- and microphytoplankton (e.g., diatoms, chlorophytes, haptophytes; Pérez et al., 2010; Armbrecht et al., 2014). A decrease in phytoplankton cell size will likely lead to longer food webs and a reduction in trophic transfer efficiency, with a consequent decline in omega-3 transfer to higher trophic levels (Berglund et al., 2007; Bermúdez et al., 2016).

Global warming is predicted to enhance seawater stratification while decreasing ocean mixing, reducing the upward NO₃⁻ supply (Falkowski et al., 1998; Sarmiento et al., 1998; Capotondi et al., 2012) and favoring the growth of species such as cyanobacteria and mixotrophic nanoflagellates (Peter and Sommer, 2012; Leles et al., 2018). In general, smaller phytoplankton preferentially consume NH₄⁺ (Fawcett et al., 2011; Glibert et al., 2016), such that their growth should be favored under lower-nutrient conditions, in comparison to that of diatoms, which mainly utilize NO₃⁻ (Kudela and Dugdale, 2000; Fawcett and Ward, 2011). In contrast, by increasing the bioavailability of micronutrients such as iron, ocean acidification may promote the growth of phytoplankton reliant on NO₃⁻, the assimilation of which has a high iron requirement (Price et al., 1991; Schoffman et al., 2016). That said, increased iron availability is also predicted to favor the growth of N₂ fixers (Wannicke et al., 2018), a group of cyanobacteria (Monteiro et al., 2010) that produce predominantly short-chain PUFA (Parrish, 2013).

While much remains unknown of how different phytoplankton species will respond to climate change, particularly given the number of overlapping drivers and their potentially complex interactions, any change in community composition will have consequences for omega-3 production. These effects will be reflected in the amount of omega-3 transferred to consumers, as well as on their performance and survival strategies. For instance, a decrease in the amount of essential FA available to consumers has been shown to reduce the abundances, growth, and reproduction of zooplankton (Rossoll et al., 2012). At lower pH (i.e., high pCO₂), fish larvae tend to stock omega-3 to increase their chances of survival (Díaz-Gil et al., 2015), in contrast to Antarctic krill that appear unaffected by increasing pCO₂ (Ericson et al., 2019). Additionally, different
<table><caption>**TABLE 1** | Comparison of selected abiotic and biotic parameters in the four Eastern Boundary Upwelling Systems (Benguela, California, Canary, Humboldt) based on published literature.</caption><thead><tr><th></th><th>Benguela</th><th>California</th><th>Canary</th><th>Humboldt</th><th>References</th></tr><tr><th></th><th>28°S-18°S</th><th>34°N-44°N</th><th>12°N-22°N</th><th>16°S-6°S</th><th></th></tr></thead><tbody><tr><td>Temperature (°C)</td><td>9-18</td><td>7-15</td><td>12-24</td><td>11-22</td><td>Chavez and Messié, 2009; Messié et al., 2009</td></tr><tr><td>Average wind speed (m s<sup>-1</sup>)</td><td>7.2</td><td>7.8</td><td>6.8</td><td>5.7</td><td>Chavez and Messié, 2009; Messié et al., 2009</td></tr><tr><td>Upwelled volume (Sv)</td><td>1.5</td><td>1</td><td>1.4</td><td>1.6</td><td>Chavez and Messié, 2009; Messié et al., 2009</td></tr><tr><td>Nitrate supply (mmol m<sup>-1</sup> mm<sup>-1</sup>)</td><td>30.9</td><td>19.3</td><td>32.2</td><td>33.8</td><td>Chavez and Messié, 2009; Messié et al., 2009</td></tr><tr><td>Potential new production (g C m<sup>-2</sup> yr<sup>-1</sup>)</td><td>517</td><td>323</td><td>539</td><td>566</td><td>Chavez and Messié, 2009; Messié et al., 2009</td></tr><tr><td>Satellite primary production (g C m<sup>-2</sup> yr<sup>-1</sup>)</td><td>976</td><td>479</td><td>1213</td><td>855</td><td>Chavez and Messié, 2009; Messié et al., 2009</td></tr><tr><td>Satellite chlorophyll (mg m<sup>-3</sup>)</td><td>3.1</td><td>1.5</td><td>4.3</td><td>2.4</td><td>Chavez and Messié, 2009; Messié et al., 2009</td></tr><tr><td>Mix layer depth (m)</td><td>44.8</td><td>43.3</td><td>28.9</td><td>30.7</td><td>Chavez and Messié, 2009; Messié et al., 2009</td></tr><tr><td>Dust deposition (g m<sup>-2</sup>)</td><td>11.7</td><td>0.3</td><td>33.1</td><td>0.3</td><td>Chavez and Messié, 2009; Messié et al., 2009</td></tr><tr><td><strong>Phytoplankton abundance</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Diatoms (cell L<sup>-1</sup>)</td><td>8-5240</td><td>7-2328×10<sup>3</sup></td><td>37-490×10<sup>4</sup></td><td>25-16802</td><td>Painting et al., 1993; Anabalón et al., 2014; Du et al., 2015; Riquelme-Bugueño et al., 2020</td></tr><tr><td>Dinoflagellates (cell L<sup>-1</sup>)</td><td>1-10×10<sup>4</sup></td><td>2-425×10<sup>3</sup></td><td>20-60×10<sup>6</sup></td><td>99-340×10<sup>3</sup></td><td>Böttjer and Morales, 2007; Anabalón et al., 2014; Du et al., 2015; van der Lingen et al., 2016; Riquelme-Bugueño et al., 2020</td></tr><tr><td>Bacteria (cell mL<sup>-1</sup>)</td><td>1-14</td><td>3-51×10<sup>5</sup></td><td>100-600</td><td>100-300×10<sup>3</sup></td><td>Brown et al., 1991; Hauss et al., 2012; Anabalón et al., 2014; Schulien et al., 2017</td></tr><tr><td>Total lipids (SPM, µg L<sup>-1</sup>)</td><td>NA</td><td>50-70</td><td>NA</td><td>2-70</td><td>Gutiérrez et al., 2012; Fischer et al., 2014; Puccinelli et al., 2016a</td></tr><tr><td>Omega-3 (SPM, µg L<sup>-1</sup>)</td><td>1-5</td><td>8-11</td><td>NA</td><td>1-18</td><td>Gutiérrez et al., 2012; Fischer et al., 2014; Puccinelli et al., 2016a</td></tr><tr><td><strong>Zooplankton</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Abundance (individual m<sup>-3</sup>)</td><td>1-3500</td><td>10-2237</td><td>1-5250</td><td>1-512</td><td>Peterson et al., 1979; Verheye et al., 2005; Fontana et al., 2016; Ndour et al., 2018; Berrahe et al., 2019; Schukat et al., 2021</td></tr><tr><td>Biomass (g C m<sup>-2</sup>)</td><td>0-12</td><td>0-20</td><td>1-7</td><td>0-101</td><td>Mackas et al., 2006; Huggett et al., 2009; Aronés et al., 2019; Medellín-Mora et al., 2020</td></tr><tr><td>Annual production (g C m<sup>-2</sup> yr<sup>-1</sup>)</td><td>11-160</td><td>6-67</td><td>11-20</td><td>6-23</td><td>Huggett et al., 2009; Medellín-Mora et al., 2020</td></tr><tr><td>Total lipids (µg individual<sup>-1</sup>)</td><td>7-250</td><td>20-99</td><td>NA</td><td>18-84</td><td>Lavaniegos and López-Cortés, 1997; Verheye et al., 2005; Schukat et al., 2014, 2021</td></tr><tr><td>Omega-3 (% TFA)</td><td>19-52</td><td>10-31</td><td>NA</td><td>NA</td><td>Lavaniegos and López-Cortés, 1997; Verheye et al., 2005; Schukat et al., 2014; Riquelme-Bugueño et al., 2020</td></tr><tr><td><strong>Small pelagic fish</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Fish production (landing, KT)</td><td>12-36<br>(anchovy)</td><td>3-1096<br>(sardine)</td><td>0-424<br>(anchovy)</td><td>59-13060<br>(anchovy)</td><td>Lluch-Belda et al., 1989; Rykaczewski and Checkley, 2008; Lanz et al., 2009; FAO, 2014; Diankha et al., 2015; Shabangu et al., 2019</td></tr><tr><td>Omega-3 (% TFA)</td><td>38-68</td><td>38-43</td><td>16-24</td><td>36-39</td><td>Njinkoué et al., 2002; Okada and Morrissey, 2008; Castro et al., 2010; Standal et al., 2012; Connan et al., 2017</td></tr></tbody></table>

Data on temperature, phytoplankton, zooplankton and small pelagic fish are reported as ranges. Fish production is listed only for the main small pelagic fish species in each system. SPM, suspended particulate matter; NA, not available; TFA, total fatty acids. Omega-3 refers to long chain polyunsaturated fatty acids (≥C20 PUFA).

consumers have different omega-3 requirements (Litzow et al., 2006), such that their responses to climate change are likely to be variable and difficult to predict.

## KNOWLEDGE GAPS AND FUTURE DIRECTIONS

There is broad consensus that upwelling shapes the diets of primary and secondary consumers, from coastal (Puccinelli et al., 2016a,b; Docmac et al., 2017) to open-ocean environments (Hauss et al., 2012; Schukat et al., 2021). Globally, the omega-3

supply from fish is projected to soon become insufficient for the growing human population, although the sign and magnitude of future changes in EBUS omega-3 production are unknown. Global estimates indicate that phytoplankton and zooplankton EPA + DHA supplies amount to 80 Mt, yet approximately 90% of EPA + DHA is lost between primary producers and higher predators (Hamilton et al., 2020). Humans require 1.4 Mt of EPA + DHA annually to meet the 500 mg daily recommended intake, yet only 0.8 Mt are available, largely from aquaculture and fisheries (Tocher, 2015; Hamilton et al., 2020). Despite the general understanding that the omega-3 supply to humans is limited, information on omega-3 production and transfer
in productive upwelling systems is scarce, and almost absent at the level of primary consumers such as zooplankton and small pelagic fish (Table 1). The available studies are largely laboratory- or mesocosm-based investigations that constrain selected environmental parameters in order to investigate a specific metabolic or physiological pathway (De Troch et al., 2012; Mayor et al., 2015). Meta-analyses have been used as an alternative tool to formulate predictions related to omega-3 supply (e.g., Galloway and Winder, 2015; Hixson and Arts, 2016), but they are usually conducted at a large scale (regional, global) and focused on primary producers. Recently, an algorithm that links satellite chlorophyll-a data and EPA production was developed for the northwestern Atlantic and used for global EPA estimates (Budge et al., 2014). Applying this algorithm to EBUS that collectively support 8% of global primary production yields an EBUS EPA production rate of 19.2 Mt year⁻¹. Assuming a transfer efficiency of 10% among trophic levels and a three-level food chain, we estimate that 0.19 Mt year⁻¹ of EPA is available in the small pelagic fish of EBUS. While this approach is useful for illustrating the role of EBUS in omega-3 production, it has several limitations, such as assuming that diatoms are the only EPA producers, neglecting DHA production, and assuming a 10% transfer efficiency. Additionally, while the studies cited above have advanced our knowledge of omega-3 in the ocean, they do not provide reliable estimates of EPA + DHA or consider future changes in omega-3 production.

Coupled physical-biogeochemical models are powerful tools for understanding ocean dynamics and their role in biogeochemical cycles at various spatial (from global to regional) and temporal (event to climate) scales (Brasseur et al., 2009; Bachlery et al., 2016). Biogeochemical models are often used to represent the cycles of carbon and selected nutrients (e.g., N), but they can also simulate energy flow to higher trophic levels (Koné et al., 2005; Chust et al., 2014). These models encompass a variety of complexities and applications, ranging from Nitrate-Phytoplankton-Zooplankton-Detritus to more complex planktonic food webs (Rose et al., 2007; Aumont et al., 2015; Butenschön et al., 2016). They depend, however, on field observations and experimental data to define parameters and constrain assumptions. 3D-physical-biogeochemical models have been developed for the four EBUS to simulate marine productivity and carbon cycling at low trophic levels (i.e., phytoplankton and zooplankton) (Lachkar and Gruber, 2012; Gutknecht et al., 2013; Auger et al., 2016; Espinoza-Morriberón et al., 2017; Glock et al., 2018; Cheresh and Fiechter, 2020). While the models account for the N source(s) available to phytoplankton and the main nutrients ratios (cell-quota

formulation), none of them track omega-3 in either the primary or secondary consumers. The only mathematical model to investigate omega-3 transfer between phytoplankton and zooplankton is the mechanistic approach developed by Perhar et al. (2012, 2013), which accounts for omega-3 availability in its calculation of grazing efficiency. This model has been used to investigate the role of N, phosphorus and omega-3 in zooplankton growth and abundances. A combined physical-biogeochemical model that includes the approach of Perhar et al. (2012, 2013) could be implemented for EBUS to (i) elucidate the mechanisms governing the fate of omega-3 production based on the N source(s) available to phytoplankton, and (ii) quantify the amount of omega-3 available to small pelagic fish, at present and in the future, considering EBUS-specific parameters.

## SUMMARY

Omega-3 are essential compounds for all living organisms and their supply is tightly connected to phytoplankton growth and community composition in the ocean, as well as to the efficiency of their transfer through the food web. Human population growth and the likely decline in omega-3 availability linked to global warming underscore the urgency of prioritizing long-term predictions of omega-3 supply in EBUS. In particular, there is a clear need for a predictive model to explore climate-induced changes in omega-3 supply throughout the food web; such a model would be valuable to multiple sectors, including fisheries management and food production.

## AUTHOR CONTRIBUTIONS

EP, LP, SF, EM, and PS conceptualization. EP wrote the first manuscript draft with major contribution from FS, SF, and PS. All authors contributed to the article and approved the submitted version.

## FUNDING

This work is supported by the ISblue project, Interdisciplinary graduate School for the blue planet (ANR-17-EURE-0015) and co-funded by a grant from the French government under the program "Investissements d'Avenir." This work is a contribution to the SOLAB project (ANR-18-CE32-0009). SF acknowledges the support of a Royal Society/African Academy of Sciences FLAIR fellowship.

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**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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