The Influence of Diapycnal Nutrient Fluxes on Phytoplankton Size Distribution in an Area of Intense Mesoscale and Submesoscale Activity off Concepción, Chile

Abstract

Mesoscale and submesoscale processes that contribute to localized increases in nutrients in the sunlit layer can stimulate phytoplankton growth and community changes, but the mechanisms involved remain sparsely documented with in situ data in the case of Eastern Boundary Upwelling Systems (EBUSs) and of most ocean regions. The role of diapycnal mixing in providing nutrients to the upper layer and in influencing phytoplankton size structure was analyzed in an area of intense mesoscale and submesoscale activity during the coastal upwelling season off Concepción (~36–37°S), the Humboldt Current EBUS. Diapycnal nutrient fluxes based on conductivity, temperature, and depth vertical eddy diffusivity (Kz) values (the Thorpe scale method) and on nutrient gradients were assessed in association with size‐fractionated chlorophyll‐a and microdiatom abundance derived from in situ sampling in an area including a mesoscale intrathermocline eddy (ITE) adjacent to a coastal upwelling front (CUF). The indirect estimates of Kz values spanned between 0.01 and 4 × 10⁻⁴ m² s⁻¹, and maxima in diapycnal nitrate flux per station ranged between 0.08 and 19.1 mmol m⁻² day⁻¹. Maxima in the upward fluxes were detected at the subsurface (15–40 m depth) in the CUF and ITE areas, coinciding with maxima in the micro‐ and nano‐chlorophyll‐a fractions and in microdiatom abundance. These results suggest that ITE and CUF features, as well as their interaction, can generate intense diapycnal mixing and, thereby, contribute to increasing nutrient availability below the mixed layer. In turn, these processes enhance the contribution of larger phytoplankton cells in the coastal transition zone of EBUSs.

Full text

The Influence of Diapycnal Nutrient Fluxes on
Phytoplankton Size Distribution in an Area of
Intense Mesoscale and Submesoscale Activity
off Concepción, Chile
A. Corredor‐Acosta
1,2
, C. E. Morales
2,3
, A. Rodríguez‐Santana
4
, V. Anabalón
2
,
L. P. Valencia
2,5
, and S. Hormazabal
2,5
1
Programa de Postgrado en Oceanografía, Departamento de Oceanografía, Facultad de Ciencias Naturales y
Oceanográficas, Universidad de Concepción, Concepción, Chile,
2
Instituto Milenio de Oceanografía, Universidad de
Concepción, Concepción, Chile,
3
Departamento de Oceanografía, Facultad de Ciencias Naturales y Oceanográficas,
Universidad de Concepción, Concepción, Chile,
4
Departamento de Física, Facultad de Ciencias del Mar, Universidad de
las Palmas de Gran Canaria, Las Palmas de Gran Canaria, España,
5
Escuela de Ciencias del Mar, Facultad de Ciencias del
Mar y Geografía, Pontificia Universidad Católica de Valparaíso, Valparaíso, Chile
Abstract Mesoscale and submesoscale processes that contribute to localized increases in nutrients in the
sunlit layer can stimulate phytoplankton growth and community changes, but the mechanisms involved
remain sparsely documented with in situ data in the case of Eastern Boundary Upwelling Systems (EBUSs)
and of most ocean regions. The role of diapycnal mixing in providing nutrients to the upper layer and in
influencing phytoplankton size structure was analyzed in an area of intense mesoscale and submesoscale
activity during the coastal upwelling season off Concepción (~36–37°S), the Humboldt Current EBUS.
Diapycnal nutrient fluxes based on conductivity, temperature, and depth vertical eddy diffusivity (K
z
) values
(the Thorpe scale method) and on nutrient gradients were assessed in association with size‐fractionated
chlorophyll‐a and microdiatom abundance derived from in situ sampling in an area including a mesoscale
intrathermocline eddy (ITE) adjacent to a coastal upwelling front (CUF). The indirect estimates of K
z
values
spanned between 0.01 and 4 × 10
−4
m
2
s
−1
, and maxima in diapycnal nitrate flux per station ranged
between 0.08 and 19.1 mmol m
−2
day
−1
. Maxima in the upward fluxes were detected at the subsurface
(15–40 m depth) in the CUF and ITE areas, coinciding with maxima in the micro‐and nano‐chlorophyll‐a
fractions and in microdiatom abundance. These results suggest that ITE and CUF features, as well as their
interaction, can generate intense diapycnal mixing and, thereby, contribute to increasing nutrient
availability below the mixed layer. In turn, these processes enhance the contribution of larger phytoplankton
cells in the coastal transition zone of EBUSs.
Plain Language Summary Phytoplankton in the upper ocean are the main primary producers of
organic matter based on light, inorganic carbon (CO
2
), and nutrients. These cells range from small to
large sizes in the micrometer scale (~1–100 μm diameter). In coastal upwelling regions, wind‐driven events
lead to a nutrient enrichment favoring increases of primary production in the coastal zone and to a
dominance of large phytoplankton, which require higher nutrient levels than do smaller cells. In contrast, in
the oceanic nutrient‐poor zone, smaller phytoplankton are usually dominant. However, mesoscale and
submesoscale activity (fronts, eddies, meanders, and filaments) in the zone between the coastal and oceanic
waters, the coastal transition zone (CTZ), can generate localized injections of nutrients toward the surface
and, thereby, contribute to an enhancement of productivity and to changes in the community in the
CTZ. Several mechanisms can contribute to such injections, but field observations to document them are
sparse. Based on observations in an area of intense mesoscale and submesoscale activity, we provide
evidence of the contribution of the turbulent mixing in locally increasing nutrient availability in the upper
layer and, in turn, to sustain patches of large‐size phytoplankton cells in the CTZ.
1. Introduction
Mesoscale and submesoscale physical processes in the ocean have been identified as important contributors
to the transport and mixing of tracers (e.g., nutrients, oxygen, and plankton) through diverse mechanisms,
thereby influencing directly biological communities and biogeochemical cycles. However, observational
©2020. The Authors.
This is an open access article under the
terms of the Creative Commons
Attribution License, which permits use,
distribution and reproduction in any
medium, provided the original work is
properly cited.
RESEARCH ARTICLE
10.1029/2019JC015539
Key Points:
•Maxima in upward injection of
nutrients coincide with maxima in
diapycnal mixing in an area of
upwelling front‐mesoscale eddy
interaction
•Chlorophyll‐a maxima in
microphytoplankton and
nanophytoplankton, and in
microdiatom abundance, co‐occur
with maxima in diapycnal nutrient
fluxes
•Diapycnal nutrient supply at
mesoscale and submesoscale
contributes to an enhancement of
large cells in the coastal transition
zone
Correspondence to:
C. E. Morales,
camorale@udec.cl
Citation:
Corredor‐Acosta, A., Morales, C. E.,
Rodríguez‐Santana, A., Anabalón, V.,
Valencia, L. P., & Hormazabal, S.
(2020). The influence of diapycnal
nutrient fluxes on phytoplankton size
distribution in an area of intense
mesoscale and submesoscale activity off
Concepción, Chile. Journal of
Geophysical Research: Oceans,125,
e2019JC015539. https://doi.org/
10.1029/2019JC015539
Received 5 AUG 2019
Accepted 28 MAR 2020
Accepted article online 4 APR 2020
CORREDOR‐ACOSTA ET AL. 1of20

data of such processes and of their biological and biogeochemical effects remain sparse due to their transient
nature, requiring higher spatiotemporal sampling resolution (~0.1 km to tens of kilometers) compared to
those linked with larger scales of variability. At the same time, the mesoscale and submesoscale dimensions
are strongly intermingled because of the energy transfers and transformations generated at these scales,
besides those derived from larger and smaller scales, which leads to the coexistence of geostrophic and
ageostrophic dynamics (see reviews in Klein & Lapeyre, 2009; Mahadevan, 2016; McGillicuddy, 2016;
Klein et al., 2019). Mesoscale to submesoscale dynamics can lead to changes in nutrient availability and,
thereby, in phytoplankton growth rates and community composition (see reviews in Lévy et al., 2018;
Mahadevan, 2016; McGillicuddy, 2016). In Eastern Boundary Upwelling Systems (EBUSs), characterized
by the regular occurrence of wind‐driven upwelling of nutrient‐rich waters in the coastal zone (CZ),
intense mesoscale and submesoscale activity in the coastal transition zone (CTZ) is reflected in the forma-
tion of features such as eddies, filaments, jets, meanders, and fronts (Brink & Cowles, 1991; Capet et al.,
2014; Chaigneau et al., 2009; Pegliasco et al., 2015). EBUS coastal upwelling leads to high levels of phyto-
plankton biomass and primary production; however, patches of moderate biomass levels are also detected
in the CTZ and, in association with mesoscale and submesoscale dynamics, contribute to an offshore
advection of waters nearest to the CZ and/or through local growth in the CTZ, mediated by vertical injec-
tions of nutrients to the photic layer (Callbeck et al., 2017; Chenillat et al., 2015; Correa‐Ramirez et al.,
2007; Pietri et al., 2013).
Though mesoscale and submesoscale dynamics have been recognized as an important component of the
variability in phytoplankton size structure, observational evidence is still sparse and the mechanisms
remain unclear (Lamont et al., 2018; Rodríguez et al., 2001; Sangrà et al., 2014; Waga et al., 2019).
Phytoplankton size structure is a key component in the ocean energy flow pathways and in the efficiency
of an ecosystem to export carbon into the deep ocean, given the strong relationships between cell size
and nutrient uptake, metabolic rates, light absorption, and food web structure (reviews in Finkel et al.,
2010; Marañón, 2015; Mouw et al., 2016; Richardson, 2019). On this basis, its modulation by mesoscale
and submesoscale physical‐biological processes is highly relevant to understand the dynamics of marine
ecosystems. In the case of a mesoscale cyclonic eddy in the subtropical North Pacific, submesoscale varia-
bility in phytoplankton size distribution was denoted by a dominance of large cells in the eddy center,
where an intense vertical pulse of nutrients was detected. In addition, a dominance of smaller cells
was detected in its edges, associated with an advective flux by isopycnal mixing and a continuous low
nutrient supply (Brown et al., 2008). In the case of fronts, there is evidence in the California Current
(CC) EBUS that increased diapycnal nitrate flux below the mixed layer takes place in a CTZ front.
Based on modeling, it was concluded that an enhancement in the biomass of large phytoplankton at
the front could be stimulated by this process, together with biological dynamics. This contradicts the tra-
ditional view that coastal phytoplankton accumulates at the front as a result of other physical processes
(Li et al., 2012). A shift of phytoplankton size structure toward larger cells was also documented for the
same front (Taylor et al., 2012).
In the EBUS off western South America, the Humboldt Current System (HCS), mesoscale surface and
intrathermocline eddies (ITEs) generated near the coast are regularly detected (Chaigneau et al., 2011;
Czeschel et al., 2018; Johnson & McTaggart, 2010). ITEs in the HCS transport Equatorial Subsurface
Water (ESSW) associated with the poleward Peru‐Chile Undercurrent (PCUC), which flows at the edge of
the shelf and upper slope (Hormazabal et al., 2013; Thomsen et al., 2016). The ESSW, upwelling water mass,
is characterized by higher salinity, minima in oxygen, and higher nutrient content, compared to surface
waters in the region, such as the Subantartic Water (SAAW) and the Subtropical Water (SSTW) (Llanillo
et al., 2012; Silva et al., 2009; Strub et al., 1998). The formation of these ITEs has been associated with
instabilities in the PCUC derived from its interaction with the shelf‐slope topography. This leads to anticy-
clonic vorticity and to conditions favorable for centrifugal instabilities, which in turn generate coherent sub-
mesoscale anticyclonic PCUC eddies. The latter coalesce as they travel offshore to generate mesoscale PCUC
ITEs (Contreras et al., 2019; Thomsen et al., 2016). Centrifugal instabilities (i.e., inertial instabilities that
extract energy from the mean current through horizontal shear) involve isopycnal and diapycnal mixing
processes and small‐scale turbulence in EBUSs (Contreras et al., 2019; Dewar et al., 2015). In EBUSs, besides
horizontal advection of nutrients from the CZ to the CTZ by mesoscale and submesoscale features, diapycnal
mixing has been identified as an important mechanism of vertical mixing in the CTZ. This is especially so at
10.1029/2019JC015539
Journal of Geophysical Research: Oceans
CORREDOR‐ACOSTA ET AL. 2of20

the continental margin, contributing to vertical injections of gases, solutes, and organic matter toward the
upper layer (Callbeck et al., 2017; Li et al., 2012; Loginova et al., 2019; Steinfeldt et al., 2015). The effects
of diapycnal mixing on phytoplankton community size distribution in EBUSs based on observational data
remain to be investigated.
In the HCS region off central southern Chile (33–40°S), where wind‐driven coastal upwelling is seaso-
nal, an intensified coastal upwelling front (CUF) has been reported during the summer (Letelier
et al., 2009). Off Concepción (~36–37°S), the CUF is usually flanked by an ITE on the offshore side
(Letelier et al., 2009; Morales et al., 2012). As for the effects of these features on phytoplankton, the
stronger density gradients in the CUF off Concepción can act as a barrier to cross‐shelf exchanges of
phytoplankton, with a dominance of larger size cells on the coastal side and smaller ones in the oceanic
side (Menschel et al., 2016; Morales et al., 2012). In the proximity of this CUF, 2‐month old mesoscale
eddies have been found to be dominated by picoplankton and nanoplankton cells, in contrast to the
dominance of microplankton cells (mostly diatoms) in the CZ during the upwelling season (Morales
et al., 2012). However, a dominance of the microplankton fraction during the early stages of eddy devel-
opment closer to the coast and of smaller size fractions as eddies move offshore was found in the same
area using a satellite approach of phytoplankton size classes (Corredor‐Acosta et al., 2018). During an
event of ITE‐CUF interaction in the same area and in the early stages of ITE formation, increases of
larger phytoplankton in the CUF and ITE areas and a cross‐shelf exchange of diatom species from
the CZ and CTZ were observed, together with intense submesoscale variability in macronutrient distri-
bution (Morales et al., 2017). These results suggested that the ITE and CUF, as well as their interaction,
probably lead to localized vertical injections of nutrients toward the upper layer, in addition to lateral
advection of nutrient from coastal waters; however, the mechanisms contributing to such nutrient path-
ways have not been explored yet.
In this study, we explore the role of diapycnal mixing on locally providing nutrients to the upper layer and,
thereby, fueling increases in phytoplankton biomass and producing a shift in the size structure in the CTZ off
Concepción, based on data reported previously by Morales et al. (2017). The selection of this mechanism,
diapycnal mixing, is based on background information available for EBUS regions and detailed above, which
have identified it as an important contributor to localized vertical injection of solutes to the upper layer in
the CTZ; this does not rule out the contribution of additional mechanisms, which could not be assessed dur-
ing this study. For this purpose, the vertical eddy diffusivity (K
z
) as an indicator of diapycnal turbulent mix-
ing was estimated using indirect estimates through the Thorpe scale method. K
z
and the vertical gradients in
nutrient concentration were used to estimate diapycnal nutrient fluxes, while the distributions of
chlorophyll‐a (Chl‐a) size fractions and microdiatom abundance were compared to those of diapycnal
nutrient fluxes.
2. Materials and Methods
Satellite and in situ observational data obtained for this study in the area off Concepción (~36–37°S, 73–
74.5°W; Figure 1) have been previously analyzed in terms of the oceanographic setting at the mesoscale
and submesoscales dimensions, its relationship with the distribution of macronutrients, and phytoplankton
composition and distribution in the upper water column (Morales et al., 2017). A summary of the methods
employed is presented in sections 2.1 and 2.2, while the methods used in the present study are described in
sections 2.3 and 2.4.
2.1. Satellite Surface Temperature, Geostrophic Circulation Field, and Chl‐a
As background information for the field observations, the mean sea surface temperature (SST), mean surface
geostrophic velocity field, and total Chl‐a distributions were derived from satellite sources for the period of
the in situ observations (PHYTO‐FRONT cruise, 3‐6 February 2014). SST was obtained from the daily
Multi‐scale Ultra‐high Resolution Sea Surface Temperature (MUR‐SST; https://podaac.jpl.nasa.gov/Multi‐
scale_Ultra‐high_Resolution_MUR‐SST) product with a spatial resolution of 1 km. The mean surface geos-
trophic velocity field was obtained from the Copernicus Marine and Environment Monitoring Service
(CMEMS; http://marine.copernicus.eu/) product with a spatial resolution of 0.25° (~25 km). The mean sur-
face total Chl‐a was obtained from version 4.0 of the Ocean Colour Climate Change Initiative (OC‐CCI, a
10.1029/2019JC015539
Journal of Geophysical Research: Oceans
CORREDOR‐ACOSTA ET AL. 3of20

merged product available at http://www.oceancolour.org/), at processing level 3 and a spatial resolution
of 4 km.
2.2. In Situ Nutrients, Size‐Fractionated Chl‐a, and Microdiatom Abundance
Nutrient samples during the PHYTO‐FRONT cruise were collected with Niskin bottles in the upper layer (0,
5, 10, 15, 20, 30, 40, 60, 80, and 100 m depth) and stored frozen (−20 °C) in aseptic high‐density polyethylene
flasks (60 ml) for subsequent analysis, following standard protocols (Atlas et al., 1971). Parallely, total and
size‐fractionated Chl‐a samples in the microphytoplankton, nanophytoplankton, and picophytoplankton
range were collected in the upper layer (0, 5, 10, 15, 20, 25, 30, 40, 60, 80, and 100 m depth) and filtered
(~250 ml) using GF/F glass fiber filters (total), together with filters covering the size fractions (3 and
20 μm pore diameter). All measurements were taken in triplicate and frozen (−20 °C) until later analysis
by fluorometry (Turner Design AU‐10) following standard procedures (Anabalón et al., 2016). In addition,
plankton samples were collected from the same bottles for composition and abundance analysis of the phy-
toplankton size fractions. In the case of diatoms, only the abundance in the microplankton size range is
analyzed here.
2.3. Thorpe Scale, Vertical Eddy Diffusivity, and Diapycnal Nutrient Fluxes
Conductivity, temperature, and depth (CTD) casts (0–300 m depth) were performed during the
PHYTO‐FRONT cruise, using a Sea‐Bird SBE 911plus CTD equipment that provides a 24 Hz sampling rate.
To estimate the Thorpe scale, which is an energy‐containing vertical overturning scale, the overturns gener-
ated by turbulence in the stratified part of the water column were detected through inversions in fine‐scale
vertical downcast density profiles. To do this using CTD data, a minimization of measurement errors and
instrument noise is needed. To obtain a fine‐scale density data, the following steps were taken, following
the procedure described by Park et al. (2014). Based on the Sea‐Bird processing software, two modules were
applied. First, the “Cell Thermal Mass”module was performed to minimize the thermal lag arising from the
conductivity cell thermal mass effects, using the recommended values (α= 0.03, 1/β= 7.0) for the SBE
911plus CTD. Second, the “Loop Edit”module was performed in order to avoid pressure reversals due to
the effect of the ship while the CTD was falling down. A third one, the module “Align,”was not executed
since the CTD includes a deck unit that advances conductivity by 0.073 s regarding the temperature, remov-
ing automatically the salinity spiking caused by the misalignment between the two measurements.
Figure 1. Map of South America indicating the study area (red rectangle) and satellite mean surface conditions during the PHYTO‐FRONT cruise (3–7 February
2014). (a) Sea surface temperature (MUR‐SST) and geostrophic circulation (CMEMS), and (b) total chlorophyll‐a (Chl‐a) concentration (ESA OC‐CCI) and
geostrophic circulation. Dots represent the position of the sampling stations in the northern (36.5°S, 73.1–74.5°W) and southern (36.75°S, 73.3–74.5°W) transects;
magenta dots indicate the position of the coastal upwelling front (CUF; Stations 5–7 and 16–18). The gray lines in (a) indicate the isotherms of 16, 16.5, 17, and
17.5 °C from the coast to offshore, respectively.
10.1029/2019JC015539
Journal of Geophysical Research: Oceans
CORREDOR‐ACOSTA ET AL. 4of20

Temperature and salinity downcast data were used to calculate potential density with the TEOS‐10 subrou-
tines for Matlab of the Gibbs‐SeaWater (GSW) Oceanographic Toolbox (McDougall & Barker, 2011). The
final vertical density profiles were subsampled at regular depth intervals of 10 cm. Each interval contained
2.4 scans, consistent with a mean fall speed of ~1 m s
−1
and the 24 Hz CTD sampling rate. For all profiles, the
first 10 to 20 m depth was removed from the analyses, to avoid surface turbulence generated by the ship and
the mixed layer, since the Thorpe analysis is applicable only to the stable stratified part of the water column.
To calculate the overturns, the vertical density profile from each station was sorted to obtain a stable mono-
tonic sequence. For this, a downward (top to bottom) intermediate density profile was obtained, maintaining
a constant density until the density change was greater than a threshold value. Likewise, an upward (bottom
to top) intermediate density profile was constructed. The final intermediate density profile for each station
was represented by the average of the two (downward and upward) profiles (Gargett & Garner, 2008; Park
et al., 2014). Therefore, differences in the intermediate density profile above a threshold level were consid-
ered as real overturns. In this study, the threshold noise value was 5 × 10
−4
kg m
−3
, calculated as the median
of the density differences inside the “well‐mixed”layer in all sampling profiles. Finally, the Thorpe scale (L
T
)
was estimated as the root‐mean‐square of an ensemble of vertical displacements (in meters) necessary to
generate the stable vertical density profiles, computed at successive nonzero Thorpe displacements (Park
et al., 2014; Sangrà et al., 2014).
Vertical eddy diffusivity coefficient (K
z
) was then estimated using the Thorpe scale, following Ozmidov
(1965) and Dillon (1982), which according to the Osborn parameterization (Osborn, 1980) is obtained as
Kz¼0:128L2
TN;(1)
where Nis the Brunt‐Väisälä frequency or buoyancy frequency at which a fluid parcel oscillates when it is
displaced from the stable state; it was calculated from the relation
N2¼
−g
ρ0
∂ρ
∂z;(2)
where gis the gravitational acceleration, ρ
0
is the mean seawater density, and ∂ρ/∂zis the vertical density
gradient. Maximum frequency values in the water column are expected where the stratification is strongest.
Diapycnal nutrient (nitrate, phosphate, and silicate or silicic acid) fluxes (F
Nutrient
) were calculated through
the relation
FNutrient¼−Kz
∂Nutrient
∂z;(3)
where K
z
is the vertical eddy diffusivity obtained in each sampling station and for the same depth range over
which the vertical nutrient concentration gradient (∂Nutrient/∂z) was calculated (Girault et al., 2015). The K
z
coefficient is an important measurement in the interpretation of turbulence dissipation rates and small‐scale
mixing processes. It is known by several names in the literature, including vertical diffusivity (Park et al.,
2014), vertical turbulent diffusivity (Girault et al., 2015), diapycnal diffusivity (Ledwell et al., 2008; Li
et al., 2012; Zhang et al., 2017), eddy diffusion coefficient (Lund‐Hansen et al., 2006), eddy diffusivity
(Rippeth et al., 2009) and vertical eddy diffusivity (Arcos‐Pulido et al., 2014; Doubell et al., 2018; Henley
et al., 2018; Hsu et al., 2019; Law et al., 2001). The appropriateness of K
z
estimates based on CTD data
depends on the relationship between the Thorpe and Ozmidov length scales. That is, a good agreement
between these scales and a proper application of the Thorpe method will be obtained in flows where the tur-
bulence is shear‐driven and characterized by overturns in the order of tens of meters (Mater et al., 2015;
Scotti, 2015).
2.4. Meridional Geostrophic Velocity and Mixed Layer Depth
Temperature and absolute salinity profiles obtained earlier were used to calculate potential density anomaly
and meridional geostrophic velocity (Pond & Pickard, 2013). The geostrophic velocity (V
g
) was computed
every three stations along each transect and was obtained from the balance between planetary vorticity
and the pressure gradient force as follows:
10.1029/2019JC015539
Journal of Geophysical Research: Oceans
CORREDOR‐ACOSTA ET AL. 5of20

Vg¼
1
fρ0
∂P
∂x;(4)
where fis the Coriolis parameter, ρ
0
is the mean seawater density, and ∂P/∂xis the pressure horizontal gra-
dient from the geopotential anomaly relative to the sea surface. Additionally, the mixed layer depth was eval-
uated for each sampling station using a threshold value in density (Δρ= 0.03 kg m
−3
) from a near‐surface
depth of 10 m, following the procedure of de Boyer Montégut et al. (2004).
3. Results
3.1. General Oceanographic Setting
In situ sampling took place during a period of relaxation of upwelling‐favorable winds, according to the
description in Morales et al. (2017). Satellite data indicated that the sampling took place in a region of colder
waters (<15 °C) in the CZ and warmer waters (>17 °C) in the CTZ, separated by a strong SST gradient
denoted by the 16–17 °C isotherms (Stations 6–7 and 16–18, ~70–100 km from the coast) (Figure 1a). The
geostrophic field indicated that adjacent to this thermal frontal, an anticyclonic mesoscale eddy (diameter
of ~150 km) was located in the CTZ, such that offshore stations in the northern transect were distributed
close to the eddy center and in its eastern edge, whereas in the southern transect, they were distributed
on its southeastern edge (Figure 1a). Satellite surface total Chl‐a values were highest (>3 mg m
−3
) near
the coast, and both moderate (~1–2mgm
−3
) and low values (<1 mg m
−3
) were found in the CTZ
(Figure 1b). An abrupt change from moderate to low surface Chl‐a concentrations was observed westward
from the front (Stations 7–8 and 18–19), together with an offshore plume of moderate values along a cold
filament in the northern section of the eddy. Further, an onshore intrusion of low values associated with
warm waters in the southern section of the same eddy was also observed (Figures 1a and 1b).
In upper water column (0–100 m depth), a strong uplift of isotherms and isohalines toward the coast was
detected in both transects (Figures 2a, 2b, 2d, and 2e), with colder (<16°C) and higher‐salinity (>34) waters
reaching a shallower depth in the CZ than in CTZ waters, creating a CUF area (Stations 5–7 and 16–18). The
CUF was characterized by a strong horizontal gradient in potential density (0.5–1kgm
−3
in 10 km) and also
in the vertical dimension (Figures 2c and 2f). In the offshore area (Stations 10–11 and 21–24), a dome‐shaped
subsurface uplifting of the 25.7–26.2 isopycnals, together with an intrusion of high‐salinity waters (>34.4;
Figures 2b, 2c, 2e, and 2f), signaled the presence of an ITE. Between the CUF and the ITE, a pocket of waters
with the lowest density and salinity was detected in both transects, more markedly in the southern transect
(Figures 2b, 2c, 2e, and 2f). The strong steepness of the isopycnals in this area suggests that there was an
interaction between the two features. Overall, both satellite and in situ data indicated that the sampling sta-
tions included the coastal upwelling area and an ITE adjacent to the CUF (Figures 2a–2f), as detailed in
Morales et al. (2017). Water mass distribution in the upper layer (0–100 m depth) for the CUF
stations (Stations 5–7 and 16–18) and those nearest to it in the coastal (Stations 4 and 15) and oceanic
(Stations 8 and 19) directions are represented in Figure 3. Both the ESSW and SAAW masses were detected
(Figure 3). On the coastal side, the ESSW was dominant below 30 m depth, and the SAAW was dominant
above it. In the CUF area, the contribution of the SAAW was slightly higher and reached deeper (40 m
depth), and the ESSW was dominant below it. On the oceanic side, the contribution of the SAAW was
extended down to 80 m depth, whereas that of the ESSW was minimal.
The vertical structure (0–300 m depth) of the meridional geostrophic circulation during the cruise is shown
in Figure 4. In the area immediately beyond the shelf‐break zone (~100 km from the coast), a southward flow
was dominant, with values of 0.2 m s
−1
in the CUF area of the northern transect (Station 17) and maximum
values (~0.4 m s
−1
) on the oceanic side of the CUF in the southern transect (Stations 7–8) (Figures 4a and
4b). Offshore of this flow, in the area of ITE‐CUF interaction, a change to a northward flow was detected
in both transects (Stations 9–10 and 19–21), with velocities reaching up to 0.1 m s
−1
in the stations closer
to the ITE center in the northern transect (Stations 21–23) and a higher intensity (0.1–0.2 m s
−1
) in the sta-
tions located in the southeastern edge of the eddy in the southern transect (Stations 9–10) (Figures 4a and
4b). This coastal flow configuration is consistent with the PCUC current observed and modeled in summer,
reaching values close to ~0–0.5 m s
−1
in the study region (Aguirre et al., 2012; Chaigneau et al., 2013;
Vergara et al., 2016) and off Peru (Thomsen et al., 2016). In the case of ITEs in the HCS, values reported
10.1029/2019JC015539
Journal of Geophysical Research: Oceans
CORREDOR‐ACOSTA ET AL. 6of20

previously (Thomsen et al., 2016) are not only similar to those in this study but also 1 order of magnitude
higher than estimates for two eddies in the same region (0.02 m s
−1
; Hormazabal et al., 2013). This is prob-
ably a result of eddy dynamics since Thomsen et al. (2016) also reported a time decrease (0.08 m s
−1
) as they
moved offshore.
3.2. Vertical Nutrient Gradients, Vertical Eddy Diffusivity, and Diapycnal Nutrient Fluxes
Vertical sections of macronutrient gradients in the layer immediately below the mixed layer (>10 m depth)
during the cruise are shown in Figure 5, together with isopycnal distribution. These data are based on nutri-
ent distribution in the upper layer (0–100 m depth) previously described in Morales et al. (2017). Phosphate
and nitrate vertical gradients presented a similar pattern in both transects. Higher gradient values for phos-
phate (>0.03 μMm
−1
) and nitrate (>0.5 μMm
−1
) (Figures 5a, 5b, 5d and 5e) were detected in the 10–40 m
layer of the CUF area (Stations 5–7 and 16–18) and deeper (30–40 m depth) in the ITE area (Stations 10–11
and 22–24). Gradient differences between the two transects were observed. In the northern transect, coastal
stations (Stations 12, 25, and 26) displayed maxima for phosphate (>0.06 μMm
−1
) and nitrate
(>0.5 μMm
−1
) (Figures 5a and 5b) in the 15–30 m layer. However, similar maxima for phosphate in the
southern transect (Stations 1–4) were located at a shallower depth (10–15 m) and in stations closest to the
CUF (Stations 3–4) and were accompanied by lower nitrate gradients (<0.5 μMm
−1
) (Figures 5d an 5e).
In the ITE‐CUF interaction zone (Stations 9 and 20), low values for both phosphate and nitrate gradients
were found in the whole water column, except for a localized maximum in nitrate at ~30 m depth in the
northern transect (Figures 5a, 5b, 5d, and 5e). The silicate vertical gradients were relatively similar in the
CZ and CUF areas of both transects and ranged between 0.1 and 1.0 μMm
−1
in the 15–40 m layer; localized
gradient maxima (>0.5 μMm
−1
) were found in the 15–30 m layer in the CZ and CUF areas in the northern
(Stations 12 and 16) and southern (Stations 3 and 5–6) transects. The lowest values were detected in the area
Figure 2. Vertical distribution of the oceanographic properties in the upper 100 m depth during the PHYTO‐FRONT cruise. Temperature (°C), salinity, and
potential density (kg m
−3
) in the (a–c) northern and (d–f) southern transects. The colormap of each variable was done using the cmocean colormaps package
(Thyng et al., 2016). Dots representation as in Figure 1.
10.1029/2019JC015539
Journal of Geophysical Research: Oceans
CORREDOR‐ACOSTA ET AL. 7of20

beyond the CUF toward the ITE, whereas moderate increases in the subsurface layer (30–40 m depth) of the
ITE area were observed in both transects (Stations 11 and 22–24) (Figures 5c and 5f). In general, maxima in
nutrient gradients were found shallower (~10–30 m) in the CZ and CUF areas and deeper (~30–40 m) toward
the ITE area (Figure 5), with most of them being located in the layer corresponding to the 25.5 and 26 kg m
−3
isopycnals. These isopycnals have been identified as those separating the dominant water masses in the
upper layer of this region, SAAW and ESSW (Llanillo et al., 2012).
Estimates of diapycnal nutrient fluxes for phosphate, nitrate, and silicate, together with the depth of maxi-
mum K
z
in each station, are shown in Figure 6. The maximum flux values, their location in depth, the indir-
ect estimates of the vertical eddy diffusivity (K
z
), and the respective nutrient gradient values are detailed in
Table 1. In both transects, the highest K
z
values were found in the CUF and ITE areas (~0.3–
Figure 3. T‐Sdiagrams of the upper 100 m depth for the stations located in the CUF area (Stations 5–7 and 16–18) and
for those nearest to it in the coastal (Stations 4 and 15) and oceanic (Stations 8 and 19) directions, in the (a) northern and
(b) southern transects of the PHYTO‐FRONT cruise. The colors represent depth. The blue and red rectangles indicate the
typical temperature‐salinity features of the Equatorial Subsurface Water (ESSW) and Subantartic Water (SAAW) masses,
respectively. The rectangles displayed in situ and modeled values reported by Silva et al. (2009), Llanillo et al. (2012), and
Vergara et al. (2016). ESSW: 8.5–12.5 °C, 34.4–34.9; SAAW: 11.5–14.5 °C, 33.8–34.8.
Figure 4. Meridional geostrophic velocity derived from conductivity, temperature, and depth from CTD casts in the upper 300 m depth water column for the (a)
northern and (b) southern transects of the PHYTO‐FRONT cruise. Positive (negative) velocity values represent a northward (southward) flow. The geostrophic
velocity was computed from the geopotential anomaly relative to the sea surface. The thick black line represents the zero velocity contour, and the gray lines
correspond to isopycnals; dots as in Figure 1.
10.1029/2019JC015539
Journal of Geophysical Research: Oceans
CORREDOR‐ACOSTA ET AL. 8of20

1.0 × 10
−4
m
2
s
−1
in the northern and ~1.2–4.1 × 10
−4
m
2
s
−1
in the southern). Additionally, K
z
was high in
the CZ in the southern transect (Station 1; ~2.8 × 10
−4
m
2
s
−1
) and in the coastal station nearest to the CUF
in the northern transect (Station 14; ~0.7 × 10
−4
m
2
s
−1
). Regarding nutrient fluxes, those of phosphate and
nitrate were similar, and maximum values were observed in the southern transect, compared to the northern
one. The highest values for phosphate (>0.1 mmol m
−2
day
−1
) and nitrate (>1 mmol m
−2
day
−1
) in the
northern transect (Figures 6a and 6b) were found at a shallow depth (15–20 m) in both the CUF (Station
16) and ITE (Station 22) areas and also deeper (40 m) in the ITE area (maximum in nitrate flux:
>4.0 mmol m
‐2
day
−1
). In contrast, the silicate flux (Figure 6c) displayed a single maximum (>1 mmol
m
−2
day
−1
) at depth (40 m) in the ITE area, with the rest displaying lower values (<0.5 mmol m
−2
day
−1
).
In the southern transect, maxima in phosphate (>1.0 mmol m
−2
day
−1
) and nitrate (>10 mmol m
−2
day
−1
)
fluxes (Figures 6d and 6e) were found at a shallow depth (15 m) in the CUF area (Station 5), and high values
(>0.5 and >4.0 mmol m
−2
day
−1
, respectively) were also located deeper (>30 m) in the CZ and ITE areas
(Stations 1 and 10–11). Silicate fluxes (Figure 6f) were also highest (>10 mmol m
–2
day
–1
) in the CUF area
(15 and 40 m, Stations 5–6) and moderate (1.0 to <10 mmol m
‐2
day
‐1
) at 30 m depth in the CZ and ITE areas
(Stations 1 and 11).
Since diapycnal nutrient flux depends on both nutrient gradients and K
z
, their relative contribution to flux
estimates in the CTZ is analyzed (Figure 7). It is to be noted that the K
z
values are presented in a log
10
scale,
and two extreme flux estimates in the higher range were removed from these analyses. In all the cases, nutri-
ent fluxes displayed a relationship with K
z
(Figures 7a–7c), expressed here as linear correlation coefficients
(0.42 < r< 0.54, pvalues < 0.01). In contrast, such a relationship was not found between phosphate and
nitrate fluxes and their gradients (r< 0.20; p> 0.2), though this was the case for silicate (r= 0.63;
p< 0.001) (Figures 7d–7f). Overall, these data suggest that diapycnal mixing was an important process in
the water column immediately below the mixed layer in the CTZ off Concepción.
Figure 5. Vertical distribution of nutrient gradients (μMm
−1
) in the upper 50 m depth for the (a–c) northern and (d–f) southern transects of the PHYTO‐FRONT
cruise. Gradients for (a, d) phosphate, (b, e) nitrate, and (c, f) silicate. The gray and black lines correspond to isopycnals, with potential density values less (greater)
than 26.0 kg m
−3
indicating the presence of the SAAW (ESSW) mass; triangles as in Figure 1.
10.1029/2019JC015539
Journal of Geophysical Research: Oceans
CORREDOR‐ACOSTA ET AL. 9of20

3.3. Total and Size‐Fractionated Chl‐a and Phytoplankton Cross‐Shore Distribution
In order to evaluate how the phytoplankton size distribution compares with the estimated diapycnal nutri-
ent fluxes, the depth of Chl‐a maxima in each fraction size and the spatial distribution of total and microphy-
toplankton Chl‐a concentrations are displayed in Figure 8; isopycnals and the depth of the mixed layer and
that of the maxima in nitrate flux are also included. Maximum values in microphytoplankton, nanophyto-
plankton, and picophytoplankton Chl‐a concentrations are detailed in Table 1, and their distribution has
been previously described in Morales et al. (2017). Regarding the depth of the Chl‐a maxima in each size
fraction (Figures 8a and 8d), those in the microphytoplankton and nanophytoplankton fractions displayed
a similar pattern, being located at a shallower depth (<20 m) in the CZ and deeper toward offshore. In con-
trast, those of picophytoplankton were all located at a shallow depth. The vertical distribution of Chl‐a max-
ima in the larger‐size fractions, especially those of the microphytoplankton, followed closely those of
maxima in diapycnal nitrate flux. Maxima in total Chl‐a (>3 mg m
−3
) were detected in the surface layer
(<20 m depth) of the CUF area (Stations 5 and 16), together with moderate values (~1–3mgm
−3
) in the sur-
face layer of the CZ and at the subsurface (~20–30 m depth) in the ITE area (Stations 10–11 and 20–24). The
highest values were all located at or above the depth of maximum diapycnal nitrate flux and above or below
the mixed layer (Figures 8b and 8e). In contrast, maxima in microphytoplankton Chl‐a were located only in
the CUF (Stations 5 and 16) and ITE (Stations 10 and 22) areas, above and below the mixed layer in the CUF
area and below it in the ITE area (Figures 8c and 8f) (Table 1). Overall, these results suggest that maxima in
microphytoplankton Chl‐a below the mixed layer are probably the result of vertical nutrient injections in the
ITE‐CUF zone.
Further, the spatial distribution of total microdiatom abundance and that of two numerically dominant dia-
tom species (Chaetoceros debilis and Pseudo‐nitzschia pseudo‐delicatissima) were analyzed in combination
with the depth of maxima in nitrate flux and of the mixed layer (Figure 9). It must be noted that
Figure 6. Vertical distribution of the upward diapycnal nutrient fluxes (mmol m
−2
day
−1
) in the upper 50 m depth for the (a–c) northern and (d–f) southern
transects of the PHYTO‐FRONT cruise. Fluxes for (a, d) phosphate, (b, e) nitrate, and (c, f) silicate. Thick black lines indicate the depth at which the
maximum in each nutrient flux in each sampling station was detected. Lines and triangles as in Figure 5.
10.1029/2019JC015539
Journal of Geophysical Research: Oceans
CORREDOR‐ACOSTA ET AL. 10 of 20

Table 1
Mixed Layer Depth (MLD; m), Maximum Diapycnal Nutrient Flux (mmol m
−2
day
−1
), and Vertical Nutrient Gradients (μMm
−1
) for Phosphate, Nitrate, and Silicate, Vertical Eddy Diffusivity
Coefficient (K
z
;m
2
s
−1
), and Maximum Values of Size‐Fractionated (Microphytoplankton, Nanophytoplankton, and Picophytoplankton) Chl‐a Values (mg m
−3
) at Each Sampling Station
During the PHYTO‐FRONT Cruise
Longitude (°W)
−73.1 −73.2 −73.3 −73.4 −73.5 −73.6 −73.7 −73.8 −73.9 −74.0 −74.1 −74.3 −74.5
North transect
Variable 1 Variable 2 CZ CUF ITE
Station 25 Station 26 Station 12 Station 14 Station 16 Station 18 Station 20 Station 22 Station 24
MLD 13.5 19.0 10.5 10.5 10.5 15.5 12.5 14.0 19.0
Phosphate Flux 0.02 (30) 0.01 (30) 0.01 (20) 0.08 (40) 0.21 (15) 0.04 (30) 0.04 (30) 0.26 (40) 0.01 (40)
Gradient 0.0310 0.0250 0.0290 0.0135 0.0690 0.0310 0.0550 0.0300 0.0510
K
z
0.09e−4 0.07e−4 0.02e−4 0.71e−4 0.35e−4 0.14e−4 0.09e−4 1.00e−4 0.03e−4
Nitrate Flux 0.46 (30) 0.09 (30) 0.08 (20) 1.05 (40) 1.63 (15) 0.29 (30) 0.55 (30) 5.12 (40) 0.20 (40)
Gradient 0.5940 0.1460 0.3480 0.1720 0.5330 0.2450 0.7100 0.5910 0.7200
K
z
0.09e−4 0.07e−4 0.02e−4 0.71e−4 0.35e−4 0.14e−4 0.09e−4 1.00e−4 0.03e−4
Silicate Flux 0.28 (30) 0.01 (30) 0.05 (40) 0.33 (40) 0.85 (15) 0.24 (30) 0.07 (30) 2.53 (40) 0.06 (40)
Gradient 0.3590 0.0100 0.3460 0.0535 0.2780 0.2050 0.0865 0.2920 0.2060
K
z
0.09e−4 0.07e−4 0.01e‐4 0.71e−4 0.35e−4 0.14e−4 0.09e−4 1.00e−4 0.03e−4
Chl‐a Micro 0.30 (5) 1.63 (5) 1.34 (5) 0.58 (20) 13.74 (10) 1.30 (30) 1.23 (25) 1.99 (30) 0.90 (30)
Nano 0.67 (0) 0.58 (5) 1.44 (20) 1.19 (15) 2.89 (10) 0.35 (15) 1.36 (30) 0.66 (30) 0.55 (30)
Pico 0.38 (5) 0.24 (0) 0.69 (15) 0.53 (10) 0.28 (10) 0.08 (10) 0.08 (5) 0.31 (20) 0.05 (10)
South transect
CZ CUF ITE
Station 1 Station 2 Station 3 Station 4 Station 5 Station 6 Station 7 Station 8 Station 9 Station 10 Station 11
MLD 12.5 11.5 11.5 12.5 11.0 11.5 11.0 17.5 14.5 12.0 10.5
Phosphate Flux 0.83 (30) 0.01 (20) 0.06 (40) 0.02 (30) 2.25 (15) 0.62 (40) 0.08 (40) 0.03 (40) 0.02 (40) 0.53 (30) 0.66 (30)
Gradient 0.0335 0.0480 0.0210 0.0180 0.0680 0.0180 0.0080 0.0720 0.0350 0.0150 0.0620
K
z
2.86e−4 0.03e−4 0.32e−4 0.12e−4 3.83e−4 4.02e−4 1.22e−4 0.05e−4 0.06e−4 4.12e−4 1.24e−4
Nitrate Flux 9.06 (30) 0.11 (20) 3.23 (30) 0.35 (30) 19.11 (15) 0.90 (30) 1.31 (30) 0.44 (40) 0.08 (40) 8.65 (30) 8.01 (30)
Gradient 0.3670 0.4740 0.1060 0.3440 0.5780 0.2320 0.4800 0.9050 0.1360 0.2430 0.7480
K
z
2.86e−4 0.03e−4 3.53e−4 0.12e−4 3.83e−4 0.45e−4 0.32e−4 0.05e−4 0.06e−4 4.12e−4 1.24e−4
Silicate Flux 6.22 (30) 0.09 (20) 0.74 (40) 0.19 (30) 23.07 (15) 10.12 (40) 0.77 (40) 0.06 (20) 0.06 (40) 1.00 (30) 1.63 (30)
Gradient 0.2520 0.3720 0.2710 0.1920 0.6980 0.2910 0.0730 0.0900 0.1120 0.0280 0.1520
K
z
2.86e−4 0.03e−4 0.32e−4 0.12e−4 3.83e−4 4.02e−4 1.22e−4 0.08e−4 0.06e−4 4.12e−4 1.24e−4
Chl‐a Micro 0.26 (10) 0.54 (5) 0.15 (15) 0.62 (20) 2.25 (10) 0.25 (10) 0.24 (10) 0.10 (30) 0.16 (30) 1.01 (20) 1.09 (30)
Nano 0.97 (5) 0.94 (5) 1.37 (5) 0.94 (5) 1.23 (10) 1.64 (10) 0.95 (30) 0.95 (30) 0.48 (30) 1.10 (20) 1.09 (30)
Pico 0.68 (10) 1.05 (0) 1.02 (0) 0.40 (0) 0.59 (5) 0.48 (5) 0.29 (20) 0.09 (10) 0.06 (10) 0.06 (5) 0.31 (5)
Note. The depth (m) of Chl‐a maxima is in parentheses.
10.1029/2019JC015539
Journal of Geophysical Research: Oceans
CORREDOR‐ACOSTA ET AL. 11 of 20

dominant diatoms are included in both size classes since most of them form chains (micro‐) before or after
evolving as single cells (nano‐) in the region (Morales et al., 2017). The highest values of total abundance
were detected above and below the mixed layer depth in the CUF and ITE areas of the transects
(Figures 9a and 9d), coinciding with maxima in microplankton Chl‐a (Figures 8c and 8f); in contrast,
their abundance was lower, and the maxima were found above the mixed layer depth in the CZ. Primary
maxima in the abundance of the coastal diatom Ch. debilis were observed in the CUF area and secondary
ones in the ITE area in the northern transect. In the southern transect, abundances were lower, and
secondary maxima were located in the subsurface of the ITE area (Figures 9b and 9e). Primary maxima in
the abundance of the oceanic diatom P. pseudo‐delicatissima were located in the ITE area in both
transects and a secondary one in the CUF area of the northern transect, most of them below the mixed
layer depth (Figures 9c and 9f). Overall, microplankton Chl‐a and the abundance of microdiatoms were
maxima in the areas of highest diapycnal nitrate (and phosphate) flux. Although the distribution of
maxima in silicate flux was slightly different from these other two nutrients (Figure 6), maxima in the
CUF and ITE areas were relatively similar for all of them, so that the results based on nitrate apply to the
other two nutrients.
Altogether, diapycnal nutrient fluxes in the CTZ were the highest in the southern transect compared to those
in the northern one (Figure 6), and the reverse is true for both microphytoplankton Chl‐a (Figures 8c and 8f)
and total microdiatom abundance (Figures 9a and 9d). This difference could be related to an intense silicate
deficit (N/Si ratios >3) in the water column of the southern transect, associated with an intrusion of Si‐poor
waters through the southern edge of the ITE (Morales et al., 2017). In addition, a higher abundance of the
coastal diatom species Ch. debilis in the CUF area of the northern transect, compared to the southern one,
may also be related to their initial entrainment in coastal waters advected offshore through mesoscale
and/or submesoscale processes, but which may subsist on vertical nutrient injections.
Figure 7. Relationship between nutrient (phosphate, nitrate, and silicate) flux and the two variables that define it, (top) vertical eddy diffusivities or K
z
coefficient
and (bottom) nutrient gradients in the CUF and ITE areas for both transects of the PHYTO‐FRONT cruise. Nutrient flux units in mmol m
−2
day
−1
, nutrient
gradients in μMm
−1
, and log
10
(K
z
) units in m
2
s
−1
.
10.1029/2019JC015539
Journal of Geophysical Research: Oceans
CORREDOR‐ACOSTA ET AL. 12 of 20

4. Discussion
4.1. Thorpe Scale Method to Estimate Vertical Eddy Diffusivity
The use of density overturns in the water column to estimate the dissipation rate of turbulent kinetic energy
assumes a linear relationship between the Thorpe length scale and the Ozmidov length scale, with the latter
interpreted as the vertical size of the largest eddies that can overturn (Ozmidov, 1965). Mater et al. (2015),
through a detailed analysis of in situ data from different regions (Luzon Strait and Atlantic Ocean), found
that the Thorpe scale method in comparison with microstructure profiler data overestimates the dissipation
rates when the vertical size of the overturns is too large, that is, when the Thorpe scale is larger than the
Ozmidov scale. In agreement with this, Scotti (2015) concluded that in cases of convective‐driven mixing
(i.e., when the mixing is driven by the available potential energy of the mean flow), the Thorpe scale is larger
than the Ozmidov scale and the Thorpe method tends to overestimate the dissipation rate and turbulent mix-
ing. In contrast, the Thorpe scale is equivalent to the Ozmidov scale in cases of shear‐driven flows, which
means that the method is appropriate to estimate vertical eddy diffusivities when the energy for mixing
comes from the kinetic energy associated with the mean flow. In summary, the performance of the
Thorpe scale method based on CTD data, compared to direct estimates obtained from direct microstructure
measurements, will depend on the environmental conditions and the energetics for mixing (Mater et al.,
2015; Park et al., 2014; Scotti, 2015). In regions of high stable stratification and diapycnal turbulent mixing
in deep waters (>200 m), both direct and indirect methods have been reported to have a good agreement
(Ferron et al., 1998; Klymak et al., 2008). In contrast, in regions under extreme environmental conditions
and low stratification (e.g., Southern Ocean and the Drake Passage), as well as under conditions of
double‐diffusive convection events (diffusive‐layering events) produced by fresh, cold waters overlying salty,
warm waters (e.g., fjord regions), dissipation rates of turbulent kinetic energy have been reported to be over-
estimated by 1 to 2 orders of magnitude when using the CTD‐based Thorpe scale method (Frants et al., 2013;
Pérez‐Santos et al., 2014).
In our study, no direct measurements of turbulence dissipation rates through a microstructure profiler were
available. Instead, the Thorpe length scale to estimate K
z
was applied to CTD data, assuming a conceptual
Figure 8. Spatial distribution of phytoplankton size‐fractionated biomass (Chl‐a) in the upper 50 m depth for the (a–c) northern and (d–f) southern transects of
the PHYTO‐FRONT cruise. (a, d) Depth of maximum Chl‐a size fraction at each station and distribution of (b, e) total and (c, f) microphytoplankton Chl‐a values.
The brown line indicates the mixed layer depth obtained by using Δρ= 0.03 kg m
−3
following the procedure of de Boyer Montégut et al. (2004). The gray lines
correspond to isopycnals, and the thick black line indicates the depth of nitrate flux maxima. Triangles as in Figure 1.
10.1029/2019JC015539
Journal of Geophysical Research: Oceans
CORREDOR‐ACOSTA ET AL. 13 of 20

model where a combination of two prominent mechanisms, frontogenesis and symmetric instability, was
taking place. Under this assumption, the following processes could have been occurring: (i) the mesoscale
velocity field of the ITE might have contributed to enhance the cross‐frontal density gradient,
compressing and steepening the isopycnals in the offshore side of the CUF and, thereby, increasing the
vertical shear and the turbulence in the area; and (ii) an intensification of the surface currents produced
by the ITE‐CUF interaction might lead to submesoscale shear instabilities, allowing the extraction of
kinetic energy from the geostrophic flow and turning it into turbulence and mixing. In both cases, the
energetics for mixing would come from the kinetic energy associated with the mean flow, cases in which
the Thorpe scale is equivalent to the turbulent component of the Thorpe displacements, so that indirect
estimates with the Thorpe method become adequate in the assessment of turbulent diapycnal mixing
(Scotti, 2015). The two mechanisms described above have been previously shown to be interacting in the
upper layer (<200 m depth) of the northern region in the HCS (upwelling system off southern Peru), where
intense mesoscale and submesoscale activity was registered with in situ glider monitoring (Pietri et al., 2013).
In addition, inertial or symmetric instability in the upper layer (<100 m) has been detected through model-
ing the ITE formation process in the southern region of the HCS (upwelling system off central southern
Chile) (Contreras et al., 2019). However, the specific contributions of each of these or other mechanisms
to turbulence and/or diapycnal mixing in the HCS remain to be investigated.
Studies focused on the comparison and validation of indirect estimates of vertical diffusivities from the
Thorpe method with those directly obtained from microstructure profiler have not been reported for the
HCS EBUS. However, during an oceanographic campaign (Humboldt‐2009 Bio‐Hesperides) conducted off
Chile (24–42°S), both types of measurements (CTD density overturns and microstructure profiles) were per-
formed at four sampling stations closest to the CZ (<100 km offshore). In all the cases and in the upper 450 m
Figure 9. Spatial distribution of diatom abundance (cells × 10
6
m
−3
) in the upper 50 m depth for the (a–c) northern and (d–f) southern transects of the
PHYTO‐FRONT cruise. (a, d) Total diatom abundance, (b, e) coastal species Chaetoceros debilis, and (c, f) oceanic species Pseudo‐nitzschia
pseudo‐delicatissima. Lines and triangles as in Figure 8.
10.1029/2019JC015539
Journal of Geophysical Research: Oceans
CORREDOR‐ACOSTA ET AL. 14 of 20

depth, the data available indicate that both methods matched in the areas of maximum and minimum K
z
,
with values oscillating between ~10
−6
and 10
−4
m
2
s
−1
(Hormazabal, unpublished data). Our K
z
estimates
are within the upper range of these data (~10
−4
m
2
s
−1
; Table 1). Further, they agree with direct measure-
ments in the CC EBUS (e.g., Hales et al., 2005; Li et al., 2012). In summary, the Thorpe scale method using
CTD data is still a useful method for the assessment of turbulent mixing (e.g., Correa‐Ramirez et al., 2019),
whenever the underlying processes that generate mixing are considered (Mater et al., 2015; Scotti, 2015).
Since mixing processes are a key factor controlling nutrient fluxes in the sunlit layer and hence have an
important role in the submesoscale variability of phytoplankton communities (D'Asaro et al., 2011; de
Verneil et al., 2019), future studies in the HCS region would benefit from using multidisciplinary approaches
and multiple sampling techniques, to obtain high‐spatiotemporal‐resolution physical, biogeochemical, and
biological data.
4.2. Diapycnal Nutrient Fluxes in Areas of Intense Mesoscale and Submesoscale Activity in EBUSs
Most studies on vertical nutrient fluxes in EBUS regions refer only to nitrate flux. In the case of frontal zones,
elevated mixing has been registered with a microstructure profiler in a front located in the CC, with esti-
mates of turbulent nitrate fluxes in the order of 0.1 to 0.3 × 10
−5
mmol m
−2
s
−1
(0.08 to 0.26 mmol m
−2
day
−1
)
(Johnston et al., 2011). This range is in the lower limit of the nitrate flux maxima per station in our study
(0.08–19.1 mmol m
−2
day
‐1
; Table 1). However, the latter were derived from in situ nutrient distribution,
whereas in the former, they were estimated from nutrient‐density correlations, implying a greater degree
of uncertainty in the comparison. In addition, the above CC estimates are between 1 and 2 orders of magni-
tude lower, compared to direct microstructure measurements in a shelf‐break front off New England (wes-
tern North Atlantic), which reached 6 × 10
−5
mmol m
−2
s
−1
(5.2 mmol m
−2
day
−1
) (Hales et al., 2009), and
in CC fronts, with reported values of 0.0001 mmol m
−2
s
−1
(8.64 mmol m
−2
day
−1
) (Hales et al., 2005) and up
to 6.9 mmol m
−2
day
−1
(Li et al., 2012). In summary, estimates available for the CC are in the middle range of
our maximum estimates of diapycnal nitrate flux per station.
Differences in the nitrate fluxes detailed above could be associated with differences in the energy sources for
turbulence and with the impact of front interaction with other mesoscale or submesoscale features. Without
a certainty on the specific contribution of different mechanisms in generating higher or lower nitrate flux
values, we speculate that changes in the mechanisms will also imply changes between the reported nitrate
fluxes in the CC front and with our estimates. In the CC front, Johnston et al. (2011) proposed that turbulent
mixing was due to the increased shear by the reflected near‐inertial internal waves on the dense side of the
front and the frontogenesis produced by near‐surface currents along the front. However, the mean shear was
not as high as the authors expected from frontogenesis or straining, resulting in lower diapycnal nitrate flux.
Hales et al. (2005) and Li et al. (2012) found the nitrate flux estimates are similar but the physical dynamics
appear to have been different. In the first case, high nitrate content at the front was due to upwelling trans-
port along isopycnal surfaces, and the role of turbulent mixing across isopycnals was to maintain the upward
injection of nitrate, implying that nutrient gradient was of greater importance in the diapycnal nitrate flux.
In the second case, an intense cross‐isopycnals vertical mixing due to density instabilities by the Ekman flow
was reported, accompanied by an ageostrophic cross‐frontal circulation and symmetric instabilities. The
three latter mechanisms can simultaneously promote intense turbulent mixing (D'Asaro et al., 2011;
Franks & Walstad, 1997; Thomas & Taylor, 2010). In our case, we suggest that symmetric instabilities as a
source of cross‐isopycnals mixing and the ageostrophic circulation as a consequence of frontogenesis were
taking place, with the latter as the intensification of the CUF due to the acceleration of the geostrophic flow
by the ITE. Our maximum diapycnal nitrate flux estimate is almost double that reported by Li et al. (2012),
despite the similarity in the mechanisms that may have been involved. On this basis, we suggest that the
ITE‐CUF interaction in our study acts as a potential amplifier of diapycnal mixing through an acceleration
of the geostrophic flow by the ITE, also enhancing the nitrate flux toward the upper layer.
In the case of eddies in EBUSs, no records on diapycnal nutrient fluxes have been reported yet, to the best of
our knowledge. As a reference on an oceanic mesoscale eddy in the North Atlantic, diapycnal nitrate and
phosphate fluxes (1.8 and 1.25 mmol m
−2
day
−1
) at the base of the mixed layer are in the lower range of
our maximum estimates per station (20 and 2.25 mmol m
−2
day
−1
, respectively). The study concludes that
the contribution of vertical turbulence to nutrient delivery was lower, compared to that of advective pro-
cesses (Law et al., 2001). Likewise, Zhang et al. (2018) used a long‐term high‐resolution simulation for the
10.1029/2019JC015539
Journal of Geophysical Research: Oceans
CORREDOR‐ACOSTA ET AL. 15 of 20

Gulf Stream region and found a nitrate flux of ~3 mmol m
−2
day
−1
within anticyclonic mesoscale eddies. The
authors argued that such flux was mainly related to eddy‐wind interactions inducing Ekman pumping and
enhanced vertical advective fluxes at the base of the photic zone. Besides the potential for an upward advec-
tive flux of nutrients, downward vertical velocities have also been found along isopycnals in upwelling fronts
and in the periphery of mesoscale eddies, as well as in eddy flow fields through convergence and/or fronto-
genesis. This generates subsurface intrusions of surface water properties and a downward transport of Chl‐a
and particulate organic carbon (Callbeck et al., 2017; Mahadevan & Tandon, 2006; Omand et al., 2015).
Recently, de Verneil et al. (2019) suggested that mixing along isopycnals would tend to erase localized phy-
toplankton patches, instead of creating them or producing high phytoplankton biomass across different iso-
pycnals. This pattern would imply that a distinction between the two vertical mixing mechanisms (along
isopycnals and across isopycnals) could be made.
Advective flux of nutrients was not quantified in our study due to the poor resolution in the velocity field in
all directions (zonal, meridional, and vertical), but it could have been involved as well. At the same time, the
suggested mechanisms as energy sources for vertical mixing are not exclusive to turbulent diapycnal mixing.
We can only interpret that the estimated density overturns in the water column using K
z
are associated with
cross‐isopycnal (diapycnal) mixing. Nevertheless, K
z
does not fully represent the 3‐D submesoscale and
mesoscale dynamics. In our study, nutrient fluxes toward the upper layer were found to be highly associated
with the turbulent diapycnal mixing (Figure 7), leading us to argue that this mechanism is contributing to
nutrient injections toward the upper layer in the central southern HCS, as it happens in the CC (Li et al.,
2012). No doubt, future studies are needed to assess the specific or relative contribution of different physical
mechanisms to understand their impacts on mesoscale and submesoscale variability in nutrients and phyto-
plankton communities in EBUSs.
4.3. Diapycnal Mixing as a Mechanism Contributing to Phytoplankton Increases and Community
Size Structure in the CTZ of EBUSs
The mechanisms leading to changes in phytoplankton biomass/production and community structure in
mesoscale and submesoscale features is a complex subject of analysis due to the transient nature of such fea-
tures, the continuous cascading of energy to and from these scales, the simultaneous occurrence of different
physical processes within these features (e.g., downwelling, upwelling, stirring, and trapping), regional dif-
ferences in water mass composition, and nutrient content associated with them. The biological and ecologi-
cal dynamics (e.g., growth, grazing, and symbiosis) taking place at these scales (Lévy et al., 2018;
Mahadevan, 2016; McGillicuddy, 2016) also contribute in this regard. An understanding of the mechanisms
involved becomes more complex in the case of mesoscale and submesoscale features adjacent to wind‐driven
coastal upwelling zones in EBUSs (Chenillat et al., 2015; Nagai et al., 2015; Stramma et al., 2013). This is
more so in the case of adjacent interacting features, such as eddy‐eddy and eddy‐front interactions
(Harrison & Siegel, 2014; Krause et al., 2015). In the case of EBUSs, observational studies on the physical
mechanisms that have an impact on the mesoscale and submesoscale variability of phytoplankton commu-
nities are still very limited and those available refer to a single type of feature and only to total Chl‐a varia-
bility (de Verneil et al., 2019; Johnston et al., 2011; Li et al., 2012; Pietri et al., 2013) or productivity
(Brzezinski & Washburn, 2011). In this context, the present study explored only one of the physical mechan-
isms leading to submesoscale and microscale vertical injection of nutrients toward the upper sunlit layer, the
influence of diapycnal mixing on nutrient fluxes, and, thereby, on phytoplankton biomass and size structure
distributions in the southern HCS. We recognize that diapycnal mixing might take place in combination
with other processes, simultaneously or in sequence, to modulate nutrient distribution and phytoplankton
communities in the HCS, so that further investigations on the contribution of diverse processes will be
required to complete the picture presented here.
To put our results in perspective, we summarize below the current knowledge of the mechanisms driving
phytoplankton biomass and/or size variability in EBUSs. In the case of frontal areas in coastal and CTZ
regions (i.e., upwelling fronts, shelf‐break fronts, and CTZ deep fronts), several mechanisms can contribute
to increases observed in phytoplankton, including physical and biological processes. Among the physical
mechanisms, turbulent mixing and water mass convergence have been identified as promotors of local phy-
toplankton growth and/or phytoplankton biomass accumulation in the CC EBUS (de Verneil et al., 2019;
Hales et al., 2005; Johnston et al., 2011; Krause et al., 2015; Li et al., 2012; Taylor et al., 2012). As for the
10.1029/2019JC015539
Journal of Geophysical Research: Oceans
CORREDOR‐ACOSTA ET AL. 16 of 20

phytoplankton community structure in EBUS frontal areas, our results are similar to those obtained in the
CC CTZ, where an enhancement of phytoplankton biomass and a size shift toward larger cells were found at
the front (Taylor et al., 2012). In the case of EBUS eddies, enhanced phytoplankton biomass and/or primary
productivity in them have been shown to be influenced by enhanced vertical nutrient supply associated with
an uplift of isopycnal surfaces (eddy pumping or other), convergence, and/or by occasional entrainment of
phytoplankton and nutrients from the advection of water upwelled (eddy trapping) in the CZ (Brzezinski &
Washburn, 2011; Chenillat et al., 2015). As for the effects of eddy dynamics on phytoplankton size structure,
to the best of our knowledge, in situ variability has not been reported for EBUSs yet, but only on
satellite‐derived size structure (Corredor‐Acosta et al., 2018). The latter results suggest that microphyto-
plankton was an important fraction of total Chl‐a in the early stages of the eddy lifetime, when they are clo-
ser to the CZ, but no mechanisms to explain this pattern were assessed.
Based on the results in Morales et al. (2017), front‐eddy interactions in EBUSs could contribute to sustain
phytoplankton growth in the CTZ through localized upward injections of nutrients, combined with
ITE‐induced horizontal advection of coastal waters and vertical nutrient inputs to the surface layer.
Results in the present study suggest that maxima in microphytoplankton Chl‐a below the mixed layer are
most probably the result of localized vertical nutrient injections in the ITE‐CUF zone (Figures 8 and 9), espe-
cially considering that nutrients were nearly depleted at a shallow depth (<20 m) in this zone. The mechan-
isms leading to similar maxima in the mixed layer in the CUF area are less clear (e.g., biomass accumulation
by advection from the CZ and subsequent subduction versus in situ growth stimulated by vertical nutrient
injections). However, the fact that dominant coastal and oceanic diatoms (Ch. debilis and P. pseudo‐
delicatissima, respectively) were most abundant in the ITE and CUF areas than in the CZ (Figure 9) suggests
that there was a cross‐shore mixing of coastal and oceanic species at the sampling time (see also Morales
et al., 2017), in contrast to an accumulation of coastal phytoplankton biomass at the CUF. Nevertheless,
the latter process can occur under conditions different from the ones here, as suggested by the distribution
of size‐fractionated Chl‐a in the CZ and CTZ in the same area of study (Morales et al., 2012). At the same
time, fronts and eddies include both upwelling and subduction submesoscale processes, so that a combina-
tion of diverse mechanisms can be in place to influence phytoplankton distribution and production. The
mechanisms involved cannot be disentangled if measurements of primary production rates, as well as of
other planktonic metabolic rates in the region, are included and regularly monitored in both the upwelling
CZ and the CTZ in EBUSs. Future time series studies using fine‐scale sampling methods combined with tra-
ditional approaches would be most important in resolving the mechanisms that contribute to the high pro-
ductivity of the HCS, other than wind‐driven coastal upwelling, and how they might be affected by regional‐
and large‐scale oceanographic variability and vice versa.
5. Conclusions
EBUSs are regions of intense mesoscale and submesoscale activity, such as CUFs, filaments, surface eddies
and ITEs, and all these features have an important impact on phytoplankton distribution, community struc-
ture, and ecosystem dynamics. This study focuses on the role of small‐scale turbulent diapycnal mixing in
modulating phytoplankton size distribution in a zone of ITE‐CUF interaction in the HCS off central south-
ern Chile. Our results suggest that maximum values in vertical nutrient fluxes took place in the CUF and ITE
areas in association with maxima diapycnal mixing, favoring the competitive advantage that larger phyto-
plankton cells (diatoms) have compared to that of small sizes. In the CUF area, maximum abundance of
coastal diatom taxa was found in association with higher diapycnal nutrient fluxes below the mixed layer
depth. These findings suggest that turbulent diapycnal mixing in zones of intense mesoscale and submesos-
cale activity, including ITE‐CUF interactions, can promote the presence of large phytoplankton cells and
could be an important mechanism to support primary productivity in EBUSs.
Conflict of Interest:
The authors declare that the research was conducted in the absence of any commercial or financial relation-
ships that could be considered as a potential conflict of interest.
10.1029/2019JC015539
Journal of Geophysical Research: Oceans
CORREDOR‐ACOSTA ET AL. 17 of 20

Author Contributions:
Data collection during the PHYTO‐FRONT cruise was carried out by C. E. M., V. A., L. P. V., S. H., and
A. C. A. In situ size‐fractionated Chl‐a and diatom abundance analysis was done by V. A., C. E. M., and
A. C. A. Thorpe scale method and diapycnal nutrient fluxes analysis was performed by L.P.V., A.R.S., C.E.
M., and A.C.A. Manuscript writing was the responsibility of A. C. A. and C. E. M., with input from
all coauthors.
References
Aguirre, C., Pizarro, O., Strub, P. T., Garreaud, R., & Barth, J. A. (2012). Seasonal dynamics of the near‐surface alongshore flow off central
Chile. Journal of Geophysical Research,117, C01006. https://doi.org/10.1029/2011JC007379
Anabalón, V., Morales, C. E., González, H. E., Menschel, E., Schneider, W., Hormazabal, S., & Escribano, R. (2016). Micro‐phytoplankton
community structure in the coastal upwelling zone off Concepción (central Chile): Annual and inter‐annual fluctuations in a highly
dynamic environment. Progress in Oceanography,149, 174–188. https://doi.org/10.1016/j.pocean.2016.10.011
Arcos‐Pulido, M., Rodríguez‐Santana, A., Emelianov, M., Paka, V., Arístegui, J., Benavides, M., et al. (2014). Diapycnal nutrient fluxes on
the northern boundary of Cape Ghir upwelling region. Deep Sea Research Part I: Oceanographic Research Papers,84, 100–109. https://
doi.org/10.1016/j.dsr.2013.10.010
Atlas, E., Hager, S., Gordon, L., & Park, P. (1971). A practical manual for use of the Technicon Autoanalyzer in sea water nutrient analyses
(Tech. Rep. 215). Corvallis, OR: Department of Oceanography, Oregon State University.
Brink, K. H., & Cowles, T. J. (1991). The coastal transition zone program. Eos, Transactions of the American Geophysical Union,69(27),
698–707. https://doi.org/10.1029/88EO01006
Brown, S. L., Landry, M. R., Selph, K. E., Yang, E. J., Rii, Y. M., & Bidigare, R. R. (2008). Diatoms in the desert: Plankton community
response to a mesoscale eddy in the subtropical North Pacific. Deep Sea Research Part II: Topical Studies in Oceanography,55(10‐13),
1321–1333. https://doi.org/10.1016/j.dsr2.2008.02.012
Brzezinski, M. A., & Washburn, L. (2011). Phytoplankton primary productivity in the Santa Barbara Channel: Effects of wind‐driven
upwelling and mesoscale eddies. Journal of Geophysical Research,116, C12013. https://doi.org/10.1029/2011JC007397
Callbeck, C. M., Lavik, G., Stramma, L., Kuypers, M. M., & Bristow, L. A. (2017). Enhanced nitrogen loss by eddy‐induced vertical
transport in the offshore Peruvian oxygen minimum zone. PLoS ONE,12(1), e0170059. https://doi.org/10.1371/journal.pone.
0170059
Capet, A., Mason, E., Rossi, V., Troupin, C., Faugère, Y., Pujol, I., & Pascual, A. (2014). Implications of refined altimetry on estimates of
mesoscale activity and eddy‐driven offshore transport in the Eastern Boundary Upwelling Systems. Geophysical Research Letters,41,
7602–7610. https://doi.org/10.1002/2014GL061770
Chaigneau, A., Dominguez, N., Eldin, G., Vasquez, L., Flores, R., Grados, C., & Echevin, V. (2013). Near‐coastal circulation in the Northern
Humboldt Current System from shipboard ADCP data. Journal of Geophysical Research: Oceans,118, 5251–5266. https://doi.org/
10.1002/jgrc.20328
Chaigneau, A., Eldin, G., & Dewitte, B. (2009). Eddy activity in the four major upwelling systems from satellite altimetry (1992–2007).
Progress in Oceanography,83(1‐4), 117–123. https://doi.org/10.1016/j.pocean.2009.07.012
Chaigneau, A., Le Texier, M., Eldin, G., Grados, C., & Pizarro, O. (2011). Vertical structure of mesoscale eddies in the eastern South Pacific
Ocean: A composite analysis from altimetry and Argo profiling floats. Journal of Geophysi cal Research: Oceans,116, C11025. https://doi.
org/10.1029/2011JC007134
Chenillat, F., Franks, P. J. S., Rivière, P., Capet, X., Grima, N., & Blanke, B. (2015). Mesoscale activity in the Southern California Current
System. Biological dynamics of a coastal eddy. Journal of Geophysical Research: Oceans,120, 5566–5588. https://doi.org/10.1002/
2015JC010826
Contreras, M., Pizarro, O., Dewitte, B., Sepulveda, H. H., & Renault, L. (2019). Subsurface mesoscale eddy generation in the ocean off
central Chile. Journal of Geophysical Research,124,5700–5722. https://doi.org/10.1029/2018JC014723
Correa‐Ramirez, M. A., Hormazabal, S., & Yuras, G. (2007). Mesoscale eddies and high chlorophyll concentrations off central Chile (29°–
39°S). Geophysical Research Letters,34, L12604. https://doi.org/10.1029/2007GL029541
Correa‐Ramirez, M. A., Rodriguez‐Santana, A., Ricaurte‐Villota, C., & Paramo, J. (2019). The Southern Caribbean upwelling system off
Colombia: Water masses and mixing processes. Deep Sea Research Part I: Oceanographic Research Papers,155, 103145. https://doi.org/
10.1016/j.dsr.2019.103145
Corredor‐Acosta, A., Morales, C. E., Brewin, R. J. W., Auger, P. A., Pizarro, O., Hormazabal, S., & Anabalón, V. (2018). Phytoplankton size
structure in association with mesoscale eddies off central‐southern Chile: The satellite application of a phytoplankton size‐class model.
Remote Sensing,10(6), 834. https://doi.org/10.3390/rs10060834
Czeschel, R., Schütte, F., Weller, R. A., & Stramma, L. (2018). Transport, properties and life cycles of mesoscale eddies in the eastern tro-
pical South Pacific. Ocean Science,14(4), 731–750. https://doi.org/10.5194/os‐14‐731‐2018
D'Asaro, E., Lee, C., Rainville, L., Harcourt, R., & Thomas, L. (2011). Enhanced turbulence and energy dissipation at ocean fronts. Science,
332(6027), 318–322. https://doi.org/10.1126/science.1201515
de Boyer Montégut, C., Madec, G., Fischer, A. S., Lazar, A., & Iudicone, D. (2004). Mixed layer depth over the global ocean: An
examination of profile data and a profile‐based climatology. Journal of Geophysical Research,109, C12003. https://doi.org/10.1029/
2004JC002378
de Verneil, A., Franks, P. J. S., & Ohman, M. D. (2019). Frontogenesis and the creation of fine‐scale vertical phytoplankton structure.
Journal of Geophysical Research: Oceans,124, 1509–1523. https://doi.org/10.1029/2018JC014645
Dewar, W. K., McWilliams, J. C., & Molemaker, M. J. (2015). Centrifugal instability and mixing in the California undercurrent. Journal of
Physical Oceanography,45(5), 1224–1241. https://doi.org/10.1175/JPO‐D‐13‐0269.1
Dillon, T. M. (1982). Vertical overturns: A comparison of Thorpe and Ozmidov length scales. Journal of Geophysical Research,87(C12),
9601–9613. https://doi.org/10.1029/JC087iC12p09601
Doubell, M. J., Spencer, D., van Ruth, P. D., Lemckert, C., & Middleton, J. F. (2018). Observations of vertical turbulent nitrate flux during
summer in the Great Australian Bight. Deep Sea Research Part II: Topical Studies in Oceanography,157‐158,27–35. https://doi.org/
10.1016/j.dsr2.2018.08.007
10.1029/2019JC015539
Journal of Geophysical Research: Oceans
CORREDOR‐ACOSTA ET AL. 18 of 20
Acknowledgments
The authors thank the European Space
Agency for the production and
distribution of the Ocean Colour
Climate Change Initiative data set,
Version 4.0, available online (at http://
www.oceancolour.org/). The
Multi‐scale Ultra‐high Resolution Sea
Surface Temperature (MUR‐SST) data
were distributed by NASA (https://
podaac.jpl.nasa.gov/Multi‐scale_Ultra‐
high_Resolution_MUR‐SST). Mean
surface geostrophic velocity field and
sea level anomaly data were distributed
by the Copernicus Marine and
Environment Monitoring Service
(CMEMS; http://marine.copernicus.
eu/). Nutrient sampling and analyses
were undertaken by Dr. M. Cornejo and
M.Sc. N. Silva (PUCV), for which we are
grateful. The PHYTO‐FRONT cruise
was successful thanks to the support
from the crew in the R/V A. Molina
(IFOP) and from the students
participating in it. We are grateful to Dr.
O. Pizarro for his useful clarifications
on physical dynamics. The in situ
observational data are freely available
at the PANGAEA repository (https://
doi.pangaea.de/10.1594/
PANGAEA.913733; doi:101594.
PANGAEA.913733). This research was
funded by FONDECYT Projects
1120504, 1151299, and 1171895
(CONICYT‐Chile). Additional support
during the writing phase was provided
by the Instituto Milenio de
Oceanografía (IMO‐Chile), funded by
the Iniciativa Científica Milenio (ICM‐
Chile). A. C. A. was supported by a
CONICYT‐Chile Scholarship (2013–
2017).

Ferron, B., Mercier, H., Speer, K., Gargett, A., & Polzin, K. (1998). Mixing in the Romanche Fracture Zone. Journal of Physical
Oceanography,28(10), 1929–1945. https://doi.org/10.1175/1520‐0485(1998)028<1929:MITRFZ>2.0.CO;2
Finkel, Z. V., Beardall, J., Flynn, K. J., Quigg, A., Rees, T. A. V., & Raven, J. A. (2010). Phytoplankton in a changing world: Cell size and
elemental stoichiometry. Journal of Plankton Research,32(1), 119–137. https://doi.org/10.1093/plankt/fbp098
Franks, P. J. S., & Walstad, L. (1997). Phytoplankton patches at fronts: A model of formation and response to wind events. Journal of Marine
Research,55(1), 1–29. https://doi.org/10.1357/0022240973224472
Frants, M., Damerell, G. M., Gille, S. T., Heywood, K. J., MacKinnon, J., & Sprintall, J. (2013). An assessment of density‐based finescale
methods for estimating diapycnal diffusivity in the Southern Ocean. Journal of Atmospheric and Oceanic Technology,30(11), 2647–2661.
https://doi.org/10.1175/JTECH‐D‐12‐00241.1
Gargett, A., & Garner, T. (2008). Determining Thorpe scales from ship‐lowered CTD density profiles. Journal of Atmospheric and Oceanic
Technology,25(9), 1657–1670. https://doi.org/10.1175/2008JTECHO541.1
Girault, M., Arakawa, H., Barani, A., Ceccaldi, H. J., Hashihama, F., & Gregori, G. (2015). Heterotrophic prokaryote distribution along a
2300 km transect in the North Pacific subtropical gyre during a strong La Niña conditions: Relationship between distribution and
hydrological conditions. Biogeosciences,12(11), 3607–3621. https://doi.org/10.5194/bg‐12‐3607‐2015
Hales, B., Hebert, D., & Marra, J. (2009). Turbulent supply of nutrients to phytoplankton at the New England shelf break front. Journal of
Geophysical Research,114, C05010. https://doi.org/10.1029/2008JC005011
Hales, B., Moum, J. N., Covert, P., & Perlin, A. (2005). Irreversible nitrate fluxes due to turbulent mixing in a coastal upwelling system.
Journal of Geophysical Research,110, C10S11. https://doi.org/10.1029/2004JC002685
Harrison, C. S., & Siegel, D. A. (2014). The tattered curtain hypothesis revised: Coastal jets limit cross‐shelf larval transport. Limnology and
Oceanography: Fluids and Environments.,4(1), 50–66. https://doi.org/10.1215/21573689‐2689820
Henley, S. F., Jones, E. M., Venables, H. J., Meredith, M. P., Firing, Y. L., Dittrich, R., et al. (2018). Macronutrient and carbon supply, uptake
and cycling across the Antarctic Peninsula shelf during summer. Philosophical Transactions of the Royal Society A ‐Mathematical
Physical and Engineering Sciences,376(2122), 20170168. https://doi.org/10.1098/rsta.2017.0168
Hormazabal, S., Combes, V., Morales, C. E., Correa‐Ramirez, M. A., Di Lorenzo, E., & Nuñez, S. (2013). Intrathermocline eddies in the
coastal transition zone off central Chile (31–41°S). Journal of Geophysical Research,118, 4811–4821. https://doi.org/10.1002/jgrc.20337
Hsu, P. C., Cheng, K. H., Jan, S., Lee, H. J., & Ho, C. R. (2019). Vertical structure and surface patterns of Green Island wakes induced by the
Kuroshio. Deep Sea Research Part I: Oceanographic Research Papers,143,1–16. https://doi.org/10.1016/j.dsr.2018.11.002
Johnson, G. C., & McTaggart, K. E. (2010). Equatorial Pacific 13°C water eddies in the eastern subtropical South Pacific Ocean. Journal of
Physical Oceanography,40(1), 226–236. https://doi.org/10.1175/2009JPO4287.1
Johnston, T. M. S., Rudnick, D. L., & Pallàs‐Sanz, E. (2011). Elevated mixing at a front. Journal of Geophysical Research,116, C11033.
https://doi.org/10.1029/2011JC007192
Klein, P., & Lapeyre, G. (2009). The oceanic vertical pump induced by mesoscale and submesoscale turbulence. Annual Review of Marine
Science,1(1), 351–375. https://doi.org/10.1146/annurev.marine.010908.163704
Klein, P., Lapeyre, G., Siegelman, L., Qiu, B., Fu, L.‐L., Torres, H., et al. (2019). Ocean‐scale interactions from space. Earth and Space
Science.,6, 795–817. https://doi.org/10.1029/2018ea000492 2018EA000492
Klymak, J. M., Pinkel, R., & Rainville, L. (2008). Direct breaking of the internal tide near topography: Kaena Ridge, Hawaii. Journal of
Physical Oceanography,38(2), 380–399. https://doi.org/10.1175/2007JPO3728.1
Krause, J. W., Brzezinski, M. A., Goericke, R., Landry, M. R., Ohman, M. D., Stukel, M. R., & Taylor, A. G. (2015). Variability in diatom
contributions to biomass, organic matter production and export across a frontal gradi ent in the California Current Ecosystem. Journal of
Geophysical Research: Oceans,120, 1032–1047. https://doi.org/10.1002/2014JC010472
Lamont, T., Barlow, R. G., & Brewin, R. J. W. (2018). Variations in remotely‐sensed phytoplankton size structure of a cyclonic eddy in the
Southwest Indian Ocean. Remote Sensing,10(7), 1143. https://doi.org/10.3390/rs10071143
Law, C. S., Martin, A. P., Liddicoat, M. I., Watson, A. J., Richards, K. J., & Woodward, E. M. S. (2001). A Lagrangian SF6 tracer study of an
anticyclonic eddy in the North Atlantic: Patch evolution, vertical mixing and nutrient supply to the mixed layer. Deep Sea Research Part
II: Topical Studies in Oceanography.,48(4‐5), 705–724. https://doi.org/10.1016/S0967‐0645(00)00112‐0
Ledwell, J. R., McGillicuddy, D. J. Jr., & Anderson, L. A. (2008). Nutrient flux into an intense deep chlorophyll layer in a mode ‐water eddy.
Deep Sea Research Part II: Topical Studies in Oceanography.,55(10‐13), 1139–1160. https://doi.org/10.1016/j.dsr2.2008.02.005
Letelier, J., Pizarro, O., & Nuñez, S. (2009). Seasonal variability of coastal upwelling and the upwelling front off central Chile. Journal of
Geophysical Research,114, C12009. https://doi.org/10.1029/2008JC005171
Lévy, M., Franks, P. J., & Smith, K. S. (2018). The role of submesoscale currents in structuring marine ecosystems. Nature Communications,
9(1), 4758. https://doi.org/10.1038/s41467‐018‐07059‐3
Li, Q. P., Franks, P. J., Ohman, M. D., & Landry, M. R. (2012). Enhanced nitrate fluxes and biological processes at a frontal zone in the
Southern California Current System. Journal of Plankton Research,34(9), 790–801. https://doi.org/10.1093/plankt/fbs006
Llanillo, P. J., Pelegrí, J. L., Duarte, C. M., Emelianov, M., Gasser, M., Gourrion, J., & Rodríguez‐Santana, A. (2012). Meridional and zonal
changes in water properties along the continental slope off central and northern Chile. Ciencias Marinas,38(1B), 307–332. https://doi.
org/10.7773/cm.v38i1B.1814
Loginova, A. N., Thomsen, S., Dengler, M., Lüdke, J., & Engel, A. (2019). Diapycnal dissolved organic matter supply into the upper
Peruvian oxycline. Biogeosciences,16(9), 2033–2047. https://doi.org/10.5194/bg‐16‐2033‐2019
Lund‐Hansen, L. C., Ayala, P. C. D. A., & Reglero, A. F. (2006). Bio‐optical properties and development of a sub‐surface chlorophyll
maxima (SCM) in southwest Kattegat, Baltic Sea. Estuarine, Coastal and Shelf Science,68(1‐2), 372–378. https://doi.org/10.1016/j.
ecss.2006.02.019
Mahadevan, A. (2016). The impact of submesoscale physics on primary productivity of plankton. Annual Review of Marine Science,8(1),
161–184. https://doi.org/10.1146/annurev‐marine‐010814‐015912
Mahadevan, A., & Tandon, A. (2006). An analysis of mechanisms for submesoscale vertical motion at ocean fronts. Ocean Modelling,
14(3‐4), 241–256. https://doi.org/10.1016/j.ocemod.2006.05.006
Marañón, E. (2015). Cell size as a key determinant of phytoplankton metabolism and community structure. Annual Review of Marine
Science,7(1), 241–264. https://doi.org/10.1146/annurev‐marine‐010814‐015955
Mater, B. D., Venayagamoorthy, S. K., St. Laurent, L., & Moum, J. N. (2015). Biases in Thorpe‐scale estimates of turbulence dissipation. Part
I: Assessments from large‐scale overturns in oceanographic data. Journal of Physical Oceanography,45(10), 2497–2521. https://doi.org/
10.1175/JPO‐D‐14‐0128.1
McDougall, T. J., & P. M. Barker. (2011). Getting started with TEOS‐10 and the Gibbs Seawater (GSW) Oceanographic Toolbox, 28pp.
SCOR/IAPSO WG127, ISBN 978‐0‐646‐55621‐5.
10.1029/2019JC015539
Journal of Geophysical Research: Oceans
CORREDOR‐ACOSTA ET AL. 19 of 20

McGillicuddy, D. J. Jr. (2016). Mechanisms of physical‐biological‐biogeochemical interaction at the oceanic mesoscale. Annual Review of
Marine Science,8(1), 125–159. https://doi.org/10.1146/annurev‐marine‐010814‐015606
Menschel, E., Gonzalez, H. E., & Giesecke, R. (2016). Coastal‐oceanic distribution gradient of coccolithophores and their role in the car-
bonate flux of the upwelling system off Concepción, Chile (36°S). Journal of Plankton Research,38(4), 798–817. https://doi.org/10.1093/
plankt/fbw037
Morales, C. E., Anabalón, V., Bento, J. P., Hormazabal, S., Cornejo, M., Correa‐Ramírez, M. A., & Silva, N. (2017). Front‐eddy influence on
water column properties, phytoplankton community structure, and cross‐shelf exchange of diatom taxa in the shelf‐slope area off
Concepción (∼36–37°S). Journal of Geophysical Research: Oceans,122, 8944–8965. https://doi.org/10.1002/2017JC013111
Morales, C. E., Hormazabal, S., Correa‐Ramírez, M., Pizarro, O., Silva, N., Fernandez, C., et al. (2012). Mesoscale variability and
nutrient‐phytoplankton distributions off central‐southern Chile during the upwelling season: The influence of mesoscale eddies.
Progress in Oceanography,104,17–29. https://doi.org/10.1016/j.pocean.2012.04.015
Mouw, C. B., Barnett, A., McKinley, G. A., Gloege, L., & Pilcher, D. (2016). Phytoplankton size impact on export flux in the global ocean.
Global Biogeochemical Cycles,30(10), 1542–1562. https://doi.org/10.1002/2015GB005355
Nagai, T., Gruber, N., Frenzel, H., Lachkar, Z., McWilliams, J. C., & Plattner, G.‐K. (2015). Dominant role of eddies and filaments in the
offshore transport of carbon and nutrients in the California Current System. Journal of Geophysical Research: Oceans,120, 5318–5341.
https://doi.org/10.1002/2015JC010889
Omand, M. M., D'Asaro, E. A., Lee, C. M., Perry, M. J., Briggs, N., Cetinić, I., & Mahadevan, A. (2015). Eddy‐driven subduction exports
particulate organic carbon from the spring bloom. Science,348(6231), 222–225. https://doi.org/10.1126/science.1260062
Osborn, T. R. (1980). Estimates of the local rate of vertical diffusion from dissipation measurements. Journal of Physical Oceanography,
10(1), 83–89. https://doi.org/10.1175/1520‐0485(1980)010<0083:EOTLRO>2.0.CO;2
Ozmidov, R. V. (1965). On the turbulent exchange in a stably stratified ocean. Izv. Acad. Sci. USSR. Atmos. Oceanic Phys.,1, 861–871.
Park, Y. H., Lee, J. H., Durand, I., & Hong, C. S. (2014). Validation of Thorpe‐scale‐derived vertical diffusivities against microstructure
measurements in the Kerguelen region. Biogeosciences,11(23), 6927–6937. https://hal.sorbonne‐universite.fr/hal‐01308076. https://doi.
org/10.5194/bg‐11‐6927‐2014
Pegliasco, C., Chaigneau, A., & Morrow, R. (2015). Main eddy vertical structures observed in the four major Eastern Boundary Upwelling
Systems. Journal of Geophysical Research: Oceans,120, 6008–6033. https://doi.org/10.1002/2015JC010950
Pérez‐Santos, I., Garcés‐Vargas, J., Schneider, W., Ross, L., Parra, S., & Valle‐Levinson, A. (2014). Double‐diffusive layering and mixing in
Patagonian fjords. Progress in Oceanography,129,35–49. https://doi.org/10.1016/j.pocean.2014.03.012
Pietri, A., Testor, P., Echevin, V., Chaigneau, A., Mortier, L., Eldin, G., & Grados, C. (2013). Finescale vertical structure of the upwelling
system off southern Peru as observed from glider data. Journal of Physical Oceanography,43(3), 631–646. https://doi.org/10.1175/JPO‐D‐
12‐035.1
Pond, S., & Pickard, G. L. (2013). Introductory dynamical oceanography (2nd ed.). Oxford: Elsevier.
Richardson, T. L. (2019). Mechanisms and pathways of small‐phytoplankton export from the surface ocean. Annual Reviews in Marine
Science.,11(1), 57–74. https://doi.org/10.1146/annurev‐marine‐121916‐063627
Rippeth, T. P., Wiles, P., Palmer, M. R., Sharples, J., & Tweddle, J. (2009). The diapcynal nutrient flux and shear‐induced diapcynal mixing
in the seasonally stratified western Irish Sea. Continental Shelf Research,29(13), 1580–1587. https://doi.org/10.1016/j.csr.2009.04.009
Rodríguez, J., Tintoré, J., Allen, J. T., Blanco, J. M., Gom is, D., Reul, A., & Jiménez‐Gómez, F. (2001). Mesoscale vertical motion and the size
structure of phytoplankton in the ocean. Nature,410(6826), 360–363. https://doi.org/10.1038/35066560
Sangrà, P., García‐Muñoz, C., García, C. M., Marrero‐Díaz, A., Sobrino, C., & Mouriño‐Carballido, B. (2014). Coupling between upper
ocean layer variability and size‐fractionated phytoplankton in a non‐nutrient‐limited environment. Marine Ecology Progress Series,499,
35–46. https://doi.org/10.3354/meps10668
Scotti, A. (2015). Biases in Thorpe‐scale estimates of turbulence dissipation. Part II: energetics arguments and turbulence simulations.
Journal of Physical Oceanography,45(10), 2522–2543. https://doi.org/10.1175/JPO‐D‐14‐0092.1
Silva, N., Rojas, N., & Fedele, A. (2009). Water masses in the Humboldt Current System: Properties, distribution, and the nitrate deficit as a
chemical water mass tracer for Equatorial Subsurface Water off Chile. Deep Sea Research Part II: Topical Studies in Oceanography.,
56(16), 1004–1020. https://doi.org/10.1016/j.dsr2.2008.12.013
Steinfeldt, R., Sültenfuß, J., Dengler, M., Fischer, T., & Rhein, M. (2015). Coastal upwelling off Peru and Mauritania inferred from helium
isotope disequilibrium. Biogeosciences,12(24), 7519–7533. https://doi.org/10.5194/bg‐12‐7519‐2015
Stramma, L., Bange, H. W., Czeschel, R., Lorenzo, A., & Frank, M. (2013). On the role of mesoscale eddies for the biological productivity
and biogeochemistry in the eastern tropical Pacific Ocean off Peru. Biogeosciences,10(11), 7293–7306. https://doi.org/10.5194/bg‐10‐
7293‐2013
Strub, P. T., Mesias, J. M., Montecino, V., Rutllant, J., & Salinas, S. (1998). Coastal ocean circulation off western South America. In A.
Robinson, & K. Brink (Eds.), The sea (Vol. 11, pp. 273–313). New York, NY: John Wiley.
Taylor, A. G., Goericke, R., Landry, M. R., Selph, K. E., Wick, D. A., & Roadman, M. J. (2012). Sharp gradients in phytoplankton community
structure across a frontal zone in the California Current Ecosystem. Journal of Plankton Research,34(9), 778–789. https://doi.org/
10.1093/plankt/fbs036
Thomas, L. N., & Taylor, J. R. (2010). Reduction of the usable wind‐work on the general circulation by forced symmetric instability.
Geophysical Research Letters,37, L18606. https://doi.org/10.1029/2010GL044680
Thomsen, S., Kanzow, T., Krahmann, G., Greatbatch, R. J., Dengler, M., & Lavik, G. (2016). The formation of a subsurface anticyclonic
eddy in the Peru‐Chile Undercurrent and its impact on the near‐coastal salinity, oxygen, and nutrient distributions. Journal of
Geophysical Research: Oceans,121, 476–501. https://doi.org/10.1002/2015JC010878
Thyng, K. M., Greene, C. A., Hetland, R. D., Zimmerle, H. M., & DiMarco, S. F. (2016). True colors of oceanography: Guidelines for effective
and accurate colormap selection. Oceanography https://doi.org/10.5670/, 29(3), 9–13.
Vergara, O. A., Echevin, V., Sepulveda, H. H., Colas, F., & Quiñones, R. A. (2016). Modelling the seasonal dynamics of the Peru‐Chile
Undercurrent off central Chile (30–40°S). Continental Shelf Research,123,61–79. https://doi.org/10.1016/j.csr.2016.04.001
Waga, H., Hirawake, T., & Ueno, H. (2019). Impacts of mesoscale eddies on phytoplankton size structure. Geophysical Research Letters,46,
13,191–13,198. https://doi.org/10.1029/2019GL085150
Zhang, J. Z., Baringer, M. O., & Fischer, C. J. (2017). An estimate of diapycnal nutrient fluxes to the euphotic zone in the Florida Straits.
Scientific Reports,7(1), 16098. https://doi.org/10.1038/s41598‐017‐15853‐0
Zhang, S., Curchitser, E. N., Kang, D., Stock, C. A., & Dussin, R. (2018). Impacts of mesoscale eddies on the vertical nitrate flux in the Gulf
Stream region. Journal of Geophysical Research: Oceans,123, 497–513. https://doi.org/10.1002/2017JC013402
10.1029/2019JC015539
Journal of Geophysical Research: Oceans
CORREDOR‐ACOSTA ET AL. 20 of 20