MARINE AND FISHERY SCIENCES 33 (2): 205-225 (2020)

https://doi.org/10.47193/mafis.3322020301105

MARINE IMPACTS IN THE ANTHROPOCENE

The color of EPEA: variability in the in situ bio-optical properties in the

period 2000-2017

M. GUILLERMINA RUIZ1, 2, *, VIVIAN A. LUTZ1, 2, VALERIA SEGURA1, CARLA F. BERGHOFF1and RUBÉN M. NEGRI1

1Instituto Nacional de Investigación y Desarrollo Pesquero (INIDEP), Paseo Victoria Ocampo Nº 1, Escollera Norte, B7602HSA -

Mar del Plata, Argentina. 2Instituto de Investigaciones Marinas y Costeras (IIMyC), Universidad Nacional de Mar del Plata (UNMdP),

Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina

ABSTRACT. The ‘Estación Permanente de Estudios Ambientales’ (EPEA, 38° 28′ S-57° 41′ W,

Argentina) is an ecological time series of in situ observations started in 2000 aiming to assess chan-

ges in the marine environment and plankton communities under a global change scenario. Bio-opti-

cal properties are studied at EPEA since the color of the ocean undergoes temporal fluctuations, both

for natural and anthropogenic causes. Here we assessed whether bio-optical properties at EPEA

have changed during 2000-2017, identifying the occurrence of special events and inter-annual

trends in these properties. An increasing trend in chlorophyll-a concentration, possibly due to an

increase in the smaller fraction of phytoplankton was observed. Although the absorption coefficient

of phytoplankton did not follow a significant trend, it represented the occurrence of special events

of high biomass suggesting that satellite information should be useful for the study site. The specific

absorption coefficient of phytoplankton and the blue to red absorption ratio showed high values in

summer and low in winter, according to the probable dominance of different size cells and their

expected acclimation to the light regime. These results emphasize the relevance of periodic bio-opti-

cal in situ observations in understanding coastal ecosystems in a context of climate change.

Key words: Chlorophyll-a, bio-optical properties, inter-annual variability, EPEA, South Atlantic.

El color de la EPEA: variabilidad en las propiedades bio-ópticas in situ en el período 2000-2017

RESUMEN. La “Estación Permanente de Estudios Ambientales” (EPEA, 38° 28′ S-57° 41′ W,

Argentina) es una serie de tiempo ecológica de observaciones in situ iniciada en 2000 con el objetivo

de evaluar los cambios en el medio marino y las comunidades de plancton en un escenario de cambio

global. Las propiedades bio-ópticas se estudian en la EPEA ya que el color del océano sufre fluctua-

ciones temporales, tanto por causas naturales como antropogénicas. Aquí evaluamos si las propieda-

des bio-ópticas de la EPEA han cambiado durante 2000-2017, identificando la ocurrencia de eventos

especiales y tendencias interanuales en estas propiedades. Se observó una tendencia creciente en la

concentración de clorofila-a, posiblemente debido a un aumento en la fracción más pequeña de fito-

plancton. Aunque el coeficiente de absorción del fitoplancton no siguió una tendencia significativa,

representó la ocurrencia de eventos especiales de alta biomasa, lo cual sugiere que la información

satelital debería ser útil para el sitio de estudio. El coeficiente de absorción específico del fitoplancton

y la relación de absorción de azul a rojo mostraron valores altos en verano y bajos en invierno, de

acuerdo con el probable dominio de las células de diferentes tamaños y su aclimatación esperada al

régimen de luz. Estos resultados enfatizan la relevancia de las observaciones bio-ópticas periódicas

in situ para comprender los ecosistemas costeros en un contexto de cambio climático.

Palabras clave: Clorofila-a, propiedades bio-ópticas, variabilidad interanual, EPEA, Atlántico Sur.

205

Marine and

Fishery Sciences

MAFIS

*Correspondence:

mgruiz@inidep.edu.ar

Received: 13 July 2020

Accepted: 18 August 2020

ISSN 2683-7595 (print)

ISSN 2683-7951 (online)

https://ojs.inidep.edu.ar

Journal of the Instituto Nacional de

Investigación y Desarrollo Pesquero

(INIDEP)

This work is licensed under a

Creative Commons Attribution-

NonCommercial-ShareAlike 4.0

International License

INTRODUCTION

The importance of evaluating the role of the

oceans in a global climate change scenario is rec-

ognized worldwide. Ecological time series pro-

vide observations that allow assessing changes

occurring in the marine environment and its biota

in the long run (Ducklow et al. 2009). The

‘Estación Permanente de Estudios Ambientales’

(EPEA, 38° 28′ S-57° 41′ W, Argentina) was ini-

tiated in 2000 with the aim of understanding the

functioning of planktonic communities and try to

distinguish the possible effects of climate change.

Besides several physical, chemical, oceanograph-

ic and biological variables, bio-optical properties

are also studied at EPEA since the color of the

waters is one of the ocean characteristics that

undergoes temporal fluctuations, both as part of

natural cycles and due to the impact of anthro-

pogenic global change. Hence, the study of the

bio-optical properties has become an invaluable

tool to monitor changes in marine ecosystems.

Bio-optical properties are crucial in marine

ecological studies because light is an essential

factor governing the heat content in the ocean

and affecting its physical conditions. Light avail-

able in the water triggers biological processes,

providing the energy required in the photosyn-

thesis and hence determining in great part the

amount of primary production fueling the marine

food web, regulating ontogeny in different

organisms (i.e., larval stages), trophic migrations

(e.g., diel vertical movements), and facilitating

or avoiding predation (by affecting the visual

field). Furthermore, given the anthropogenic

impact on the climate, with near 28% of the

anthropogenic carbon dioxide released to the

atmosphere captured by the ocean (IPCC 2019),

there is a need to understand changes in phyto-

plankton bio-optical properties since on a global

scale phytoplankton contributes with about half

of the earth primary production (Longhurst

1995). Dutkiewicz et al. (2019), using a complex

biogeochemical model estimated that by the year

2100 changes in phytoplankton community com-

position would cause a 63% change on the

reflectance in the blue region of the electromag-

netic spectrum (an essential bio-optical property

of the oceans). Therefore, long-term records of

bio-optical properties in different places of the

ocean would provide ground-truth data to ana-

lyze in detail these possible changes.

Once the incident solar radiation passes

through the ocean surface it is attenuated due to

the scattering and absorption processes as a con-

sequence of its interaction with the seawater

(SW) and the active optical components (OACs)

present in it. OACs are the phytoplankton (Phy),

the non-algal particles (NAP) and the chro-

mophoric dissolved organic matter (CDOM).

Hence, the amount of light available for the pho-

tosynthesis depends on the types and proportions

in which the different OACs are present in a cer-

tain time and place. The degree of light attenua-

tion can be measured by the inherent bio-optical

properties, mainly the absorption and the disper-

sion coefficient (a(λ) and b(λ) respectively,

m-1), which are quantities that have spectral

dependence and are governed by a strict additivi-

ty (Prieur and Sathyendaranath 1981). This

means that the total a(λ) is equivalent to the sum

of the aSW (λ), aPhy(λ), aNAP(λ) and aCDOM (λ).

In turn, theoretically, the a(λ) of each OAC can

be expressed as the product between a specific

coefficient and its concentration, that is, a vector

that represents the spectral signature of the com-

ponent and a scalar associated with the amount of

that component present.

The spectral absorption characteristics of phy-

toplankton depend on the species, their size and

specific ensemble of pigments, as well as to their

physiological status (Sathyendranath et al. 1987;

Johnsen and Sakshaug 1996; Lutz et al. 2001;

Lutz et al. 2003). It has been observed that larger

cells have a relatively flatter absorption spectrum,

measurable by a lower value of the specific

206 MARINE AND FISHERY SCIENCES 33 (2): 205-225 (2020)

absorption coefficient of phytoplankton at 443

nm (absorption per concentration unit of chloro-

phyll-a, aBPhy(443)), and a lower ratio of absorp-

tion between the blue and red bands

[aPhy(443)/aPhy(676)], than smaller cells. At the

same time, any given species can photoacclimate

to the intensity of light to which it is exposed by

adjusting the proportion of its different pigments,

increasing those with a light-harvesting (photo-

protective) function at low (high) irradiances,

which results in spectral changes of the absorp-

tion spectrum (i.e., a lower value of aBPhy(443),

and [aPhy(443)/aPhy(676)] at low irradiances, and

vice versa). These effects, which respond to the

principle of ‘packaging effect’ (Duyens 1956;

Sathyendranath et al. 1987; Bricaud et al. 1995),

have been reported for different places of the

world ocean (Ciotti et al. 2002; Babin et al. 2003;

Lutz et al. 2003) and the Argentine Sea (Ferreira

et al. 2009; Segura et al. 2013; Williams et al.

2018; Delgado et al. 2019).

Coastal waters as the case of EPEA have a

complex mixture of OACs, which vary their con-

centrations with time. The inherent optical prop-

erties (aPhy(λ), aNAP(λ), aCDOM(λ)), the concen-

tration of chlorophyll-a as a proxy of phyto-

plankton biomass (both, the total fraction, ChlT,

and that contributed by the phytoplankton frac-

tion less than 5 µm in diameter, Chl<5) and the

irradiance integrated in the range of ‘photosyn-

thetically available radiation’ (PA R , 400-700 nm)

incident on the surface, E0(PAR) and the down-

welling on the water column, Ed(PAR), have been

systematically determined as part of the meas-

urements performed at EPEA. A first analysis of

bio-optical characteristics for the 2000-2001

annual cycle at EPEA (Lutz et al. 2006) evi-

denced that CDOM was the main contributor to

absorption, and that lower values of aBPhy(443)

were found in winter (especially during a bloom

of a large diatom) and higher in summer when

small cells (especially of the Genus Synechococ-

cus) predominated. This last result was con-

firmed in a study of ultra-phytoplankton in the

summer 2001-2002 (Silva et al. 2009). More

recently, an analysis of validation of satellite

chlorophyll-a for 18 years of the time series

(Ruiz 2018) reported that CDOM was the main

OAC throughout the year, and hence affecting

the remote sensing signal of ocean-color at

EPEA, overestimating ChlTmainly in summer.

To assess whether bio-optical properties at

EPEA have experienced a change during the 2000-

2017 period, the main objectives of this work

were: a) to provide a general description of varia-

tions in these properties; b) to identify the occur-

rence of special events; c) to analyze the occur-

rence of inter-annual trends in these properties.

MATERIALS AND METHODS

Study area

EPEA is located north of the Argentine conti-

nental shelf (38° 28′ S-57° 41′ W), 13.5 nautical

miles from the coast and close to the 50 m iso-

baths (Figure 1). Its hydrographical regime has

been described as the transition between coastal

waters of high salinity and waters of the middle

shelf (Auad and Martos 2012). Occasionally the

site can receive less salty waters from the North,

leading salinity to be less than 31.0, particularly in

summer when the Río de la Plata reaches its max-

imum southern extension (Carreto et al.1995). A

marked seasonal cycle typical of temperate

regimes has been observed at the EPEA. Sea sur-

face temperature varies between 10 °C and 21 °C

and salinity values vary from 33.5 to 34.1 (Carreto

et al. 2004; Lutz et al. 2006; Silva 2009; Ruiz

2018). The phytoplankton community reaches its

maximum biomass during winter, dominated

mainly by micro planktonic diatoms (20-200 µm)

(Negri and Silva 2011), while in summer the ultra-

phytoplankton fraction (less than 5 μm in diame-

ter) makes the major contribution to total phyto-

plankton biomass (Silva et al. 2009).

207

RUIZ ET AL.: THE COLOR OF EPEA

Sampling and determinations at EPEA station

The study period considered in this work was

January 2000-December 2017 with a monthly

sampling frequency (with gaps), covering 119

visits to EPEA, performed in different scientific

research vessels from the Instituto Nacional de

Investigación y Desarrollo Pesquero (INIDEP),

the Navy and the Naval Prefecture of Argentina.

Not all variables were obtained in all cruises. For

this work we used data from samples collected at

5 m depth.

Chlorophyll-a total concentration (ChlT)

Water samples were collected at 5 m depth

using a Niskin bottle. A total of 119 water sam-

ples for ChlTdetermination were collected in dark

bottles and immediately filtered after collection

on glass microfiber filters, Grade GF/F 0.7 μm,

under dim light and low pressure (<35 kPa). Fil-

ters were kept in liquid nitrogen (-195.8 °C) and

in an ultrafreezer (-86 °C) until analysis. For the

determination Chl<5, water samples were pre-fil-

tered through a 5 µm pore Nuclepore membrane

filters and then the same procedure as for the ChlT

was applied to the filtrate. In the laboratory, ChlT

and Chl<5were determined using a spectrofluo-

rometer (Perkin Elmer LS3) following the Holm-

Hansen et al. (1965) method for samples collect-

ed between 2000-2005 and a modified version

according to Lutz et al. (2010) since 2006.

Particulate absorption

Samples for determination of absorption spec-

tra of total particulate material were collected, fil-

tered and preserved following the same procedure

described for ChlT. A total of 110 samples were

analyzed during 2000-2017 using a spectropho-

tometer (Shimadzu UV-210-A), placing filters

close to the photomultiplier for samples collected

until 2006, and on a spectrophotometer (Shi-

madzu UV-2450) with an integrating sphere from

2006 onwards, following the quantitative filter

technique (Mitchell 1990), and using the amplifi-

208 MARINE AND FISHERY SCIENCES 33 (2): 205-225 (2020)

Figure 1. ‘Estación Permanente de Estudios Ambientales’ (EPEA), 38° 28′ S-57° 41′ W.

42°

41°

40°

39°

38°

37°

36°

35°

S

EPEA

W 61° 59° 57° 55° 53°

Mar del Plata

Atlantic Ocean

Río de la Plata

50 m

100 m

200 m

Study

area

N

cation factors of Hoepffner and Sathyendranath

(1992). Then, the method of Kishino et al. (1985)

was used to determine the aNAP(λ) spectrum and

aPhy(λ) was estimated by subtracting aNAP(λ)

from ap(λ). More details can be found elsewhere

(Lutz et al. 2006; Ruiz 2018). The specific

absorption coefficient of phytoplankton in the

blue, which is aPhy(443) normalized by ChlT

(aBPhy(443), m2mg-1), and the ratio of the absorp-

tion in the blue to the red ([aPhy(443)/aPhy(676)])

were derived from aPhy(λ) spectra.

Chromophoric dissolved organic matter (CDOM)

For the determination of CDOM absorption

spectra, a total of 78 seawater samples were col-

lected directly from the Niskin bottle into acid-

washed transparent borosilicate bottles with

teflon lids, and kept in the dark at 4 °C until

scanned at the laboratory (usually within 1 to 3

days after each cruise). Samples were filtered

through pre-combusted glass microfiber filters

Grade GF/F 0.7 μm at 450 °C during 3.5 h, and

the aCDOM (λ) of the filtrate determined in a UV-

VIS spectrophotometer (Shimadzu UV-210-A)

for samples collected until 2006 using 4 cm opti-

cal path quartz cuvettes (Lutz et al. 2006), and in

a UV-VIS spectrophotometer using 10 cm optical

path quartz cuvettes since 2006 until present

(Mitchell 1990; Ruiz et al. 2017).

Vertical profiles of conductivity-temperature-

depth (CTD)

CTD profiles in the water column were record-

ed at each cruise using a Seabird SBE19 or SBE

911 CTD, according to availability of the equip-

ment. Quality controlled temperature data

(processed by the Physical Oceanography Cabi-

net of INIDEP) was used to estimate the depth of

the thermocline (ZdTdZ, m), defined as the depth at

which the maximum value of the first derivative

of the temperature respect to depth, dTdZ, was

found. Note that this parameter is indicative of

the stratification-mixing state of the water col-

umn. The depth Z =42 m was used as a fixed

limit, when the water column was completely

mixed, in order to avoid variability regarding the

deepest depth reached by the CTD.

In situ photosynthetically available radiation

(PAR)

A submersible radiometer (PUV-500/510B,

Biospherical Instrument) was deployed manually

by releasing a conductor cable to record the

downwelling irradiance integrated between 400-

700 nm (Ed(PAR), μmol quanta m-2 s-1) as a func-

tion of depth. The euphotic depth (Zeu, m) was

determined as the depth at which the closest value

to the 1% of the recorded E0(PAR) occurred.

When the water column was completely illumi-

nated and the 1% of E0(PAR) was not reached, Zeu

was assumed to be 40 m.

Satellite photosynthetically available radiation

(PAR)

Monthly averages of incident solar radiation

were estimated using the standard photo-synthet-

ically available radiation (PAR) satellite product.

PAR product was retrieved from monthly com-

posite images collected by the Aqua Moderate

Resolution Imaging Spectroradiometer (MODIS)

at spatial resolution of 4 km, at Level 3 Standard

Mapped Image (Version R2014.0, Ocean Color

Website http://oceancolor.gsfc.nasa.gov). PAR

data was provided by the Remote Sensing Cabi-

net of INIDEP.

Statistical analysis

Descriptive statistics was performed on the

bio-optical properties and thermal stratification

parameters. Spearman correlations were used to

explore the relationship between the different

variables under study. Then, monthly averages

were plotted against the months to evidence sea-

sonal cycles. Values deviating >2 standard devi-

ations (SD) from the mean were considered

‘extreme values’ or extreme events (Davies and

Gather 1993). Long term variability was assessed

209

RUIZ ET AL.: THE COLOR OF EPEA

by the Seasonal Mann Kendall Trend Test (SMK

test, Hirsch and Slack 1984), a non-parametric

test for seasonal data. For that, a FORTRAN rou-

tine implemented by Hernández and Mendiolar

(2018) was used. Values higher than mean >2 SD

were excluded of the trend calculation for each

variable.

RESULTS

Bio-optical properties and thermal stratifica-

tion parameters

The thermal classification criterion proposed

by Baldoni (2010) was applied to identify season-

al differences in each bio-optical property. It can

be observed that all properties showed a broad

range in their values, mainly attributed to season-

al variations, but also to the occurrence of special

events (Table 1). Phytoplankton absorption coef-

ficient presented a high standard deviation rela-

tive to the mean value. On average, the contribu-

tion of the small fraction of phytoplankton (quan-

tified as %Chl<5) to the total concentration of

chlorophyll was not negligible.

Annual cycle of bio-optical properties and

thermal stratification parameters

Incident PAR (estimated by the satellite prod-

uct) at EPEA reaches a maximum average value

in December and a minimum in June (Figure 2),

denoting a sinusoidal cycle expected for a middle

latitude site in the Southern hemisphere. Variabil-

ity during winter months was notoriously smaller

than during the rest of the year. Correspondingly,

light penetration is maximum in the warm period

(Zeu =31.70 ±8.02), reaching depths close to the

bottom of the water column in January, and is

minimum in the cold period (Zeu =24.78 ±5.01;

Figure 2). Since light penetration is attenuated by

OACs present in the water column, Zeu shows an

opposite sinusoidal pattern distorted respect to

the observed in incident PAR cycle. On the other

hand, the water column is homogeneous in win-

ter, and a thermocline starts to develop in spring

reaching its shallowest depths in summer (aver-

age for December ZdTdZ =27 ±8 m; Figure 3).

Variability of ZdTdZ is notoriously higher during

the cold to warm and warm periods than during

the warm to cold and cold periods.

EPEA is characterized by optically complex

waters during the whole annual cycle, with

CDOM as the main OAC contributing to total

absorption (Figure 4). Phytoplankton biomass at

EPEA, here estimated by ChlT, had an annual

mean of 1.162 ±1.019 mg m-3, with higher values

during the cold period (ChlT=1.49 ±1.14), and

lower during the warm period (ChlT=0.89 ±

0.89), although dispersion is high (Figure 5).

Chl<5contributed on average 45% to ChlTand

mean monthly values were relatively similar

throughout the annual cycle (Table 1; Figure 6).

Specific absorption coefficient of phytoplankton

(aBPhy(443)) and the ratio of absorption in the

blue over the red [aPhy(443)/aPhy(676)] carry

information regarding the packaging effect.

Although both parameters followed the same pat-

terns, the latter showed a clearest feature of

increase towards summer (Figure 7), when small

cells are predominant and they are photo-accli-

mated to high incident light (Silva et al. 2009).

Relationships between bio-optical and physi-

cal properties

Spearman rank correlations (rho) were com-

puted in order to explore the relationship between

bio-optical and physical properties at EPEA

(Table 2). Temperature was positively correlated

with Zeu and negatively correlated with ZdTdZ.

These relationships showed that as the spring pro-

gresses, the increasing incident irradiance and

hence the increase in air temperature, induced the

warming of the upper sea layer and, consequent-

ly, the thermal stratification (also denoted by the

210 MARINE AND FISHERY SCIENCES 33 (2): 205-225 (2020)

211

RUIZ ET AL.: THE COLOR OF EPEA

Table 1. Descriptive statistics of bio-optical properties and thermal stratification parameters estimated at EPEA during 2000-2017. For ZdTdZ and Zeu threshold

maximum depths were set at 42 and 40 m respectively. Temperature corresponds to sampling depth Z =5 m. Numbers between brackets indicate the

months included in each thermal period according to Baldoni (2010). Temp.: temperature, RBR: [aPhy(443)/aPhy(676)].

Warm period (12-1-2-3) Warm-cold transition (4-5) Cold period (6-7-8) Cold-warm transition (9-10-11)

Mean ±SD Range N Mean ±SD Range N Mean ±SD Range N Mean ±SD Range N

Temp. 19.48 ±1.81 14.29-23.07 45 16.99 ±1.25 15.11-18.79 14 12.09 ±1.46 10-16 26 11.95 ±1.65 9.68-15.71 33

ChlT 0.89 ±0.89 0.11-5.38 45 1.18 ±0.61 0.21-2.42 15 1.49 ±1.14 0.58-6.42 26 1.27 ±1.17 0.32-6.13 33

Chl<5 0.41 ±0.52 0.03-2.63 35 0.51 ±0.49 0.08-1.94 15 0.50 ±0.29 0.08-1.18 21 0.57 ±0.48 0.06-1.93 28

% Chl<5 48.23 ±23.02 19-100 35 40.27 ±22.71 14-100 15 41.04 ±22.34 6-74 21 47.54 ±25.36 10-93 28

aPhy(443) 0.04 ±0.04 0.01-0.27 41 0.04 ± 0.01 0.02-0.06 14 0.04 ±0.01 0.02-0.06 23 0.08 ±0.17 0.01-0.81 30

aNAP(443) 0.02 ±0.02 0-0.07 41 0.03 ±0.01 0.01-0.05 14 0.03 ±0.02 0.01-0.10 23 0.02 ±0.01 0-0.07 30

aCDOM(443) 0.07 ±0.03 0.02-0.16 28 0.06 ±0.03 0.02-0.13 13 0.06 ±0.03 0.01-0.14 14 0.06 ±0.02 0.02-0.1 21

aBPhy(443) 0.07 ±0.05 0.01-0.24 41 0.04 ±0.03 0.02-0.14 14 0.03 ±0.02 0.01-0.07 23 0.04 ±0.03 0.01-0.13 30

RBR 2.78 ±0.57 1.86-5.17 41 1.97 ±0.25 1.48-2.27 14 2.08 ±0.36 1.57-3.05 23 2.35 ±0.36 1.65-3.09 30

ZdTdZ 31.42 ±7.75 9-42 45 39.93 ±3.35 33-42 15 41.5 ±1.3 36-43 26 35.88 ±10.09 5-42 33

dT/dZ -1.21 ±0.94 -3.94-0 45 -0.12 ±0.39 -1.49-0 15 0 ±0 -0.01-0.0 26 -0.17 ±0.32 -1.32-0 33

Zeu 31.70 ±8.02 11.1-40 34 25.98 ± 5.63 20.1-38.9 14 24.78 ±5.01 14.0-33.8 18 29.31 ±6.71 15.5-39.6 25

positive correlation between Zeu and dTdZ). In

turn, Zeu showed a significant negative correla-

tion with ZdTdZ, that is, the more mixed the water

column, the weaker the stratification and the shal-

lower the light penetration.

ChlThad a significant negative correlation with

temperature, dTdZ, Zeu, aBPhy(443) and [aPhy(443)/

aPhy(676)], while it was positively correlated with

ZdTdZ. These relationships indicated that phyto-

plankton biomass tended to be higher during win-

212 MARINE AND FISHERY SCIENCES 33 (2): 205-225 (2020)

Figure 2. Monthly satellite incident PAR irradiance (black squares) and monthly averages Zeu (open circles) at EPEA for 2003-

2017. Purple circles indicate extreme Zeu values (> 2 SD), not used in the calculation of the means. Bars indicate SD.

Figure 3. ZdTdZ for 2000-2017. Black circles represent monthly averages. Bars indicate SD. Purple circles indicate extreme val-

ues (>2 SD), not used in the calculation of the means.

60

50

40

30

20

10

0

10

20

30

40

Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec.

Z

eu

(m)

E

0

(PAR) (M quanta m d)

-2 -1

Month

0

5

10

15

20

25

30

35

40

45

Jan. Feb.Mar. Apr. May Jun. Jul. Aug.Sep. Oct. Nov.Dec.

Z

dTdZ

(m)

Month

ter, mainly due to the presence of larger cells with

lower light absorption efficiency and greater pack-

aging effect coupled with a mixed water column

and less light penetration. This interpretation is

consistent with the negative correlations found

between aBPhy(443) and [aPhy(443)/aPhy(676)]

with ZdTdZ, and positive correlation with dTdZ and

Zeu. Regarding the relationships with the OACs,

ChlTwas more positively correlated with

aPhy(443) than with aNAP(443) and non-correlated

213

RUIZ ET AL.: THE COLOR OF EPEA

Figure 4. Contribution to total absorption coefficient at 443 nm of optically active components (phytoplankton, NAP and

CDOM) expressed as percentage in a ternary plot.

Figure 5. In situ ChlTfor 2000-2017. Black circles represent monthly averages. Bars indicate SD. Purple circles indicate extreme

values (> 2 SD), excluded from the calculation of the means.

20

40

60

80

100

20

40

60

80

100

20

40

60

80

100

PHY

CDOM NAP

7

6

5

4

3

2

1

0Jan. Feb.Mar. Apr. May Jun. Jul. Aug.Sep. Oct. Nov.Dec.

Chl

T

(m )g m

-3

Month

with aCDOM(443), which was expected in part

since aNAP(443) increased with mixing also due to

resuspension of bottom material. In turn,

aCDOM(443) was not correlated with stratification

parameters, suggesting an independent behavior of

the mixing-stratification cycle at EPEA station.

%Chl<5showed only a weak positive signifi-

cant correlation with Zeu, dTdZ and [aPhy(443)-

/aPhy(676)], suggesting that when light penetra-

tion is deeper and stratification stronger at

EPEA, the percentage of smaller cells tended to

increase.

214 MARINE AND FISHERY SCIENCES 33 (2): 205-225 (2020)

Figure 6. Percentage of Chl<5over ChlTfor 2000-2017. Black circles represent monthly averages. Bars indicate SD. Purple cir-

cles indicate extreme values (>2 SD), excluded from the calculation of the means.

Figure 7. Values of [aPhy(443)/aPhy(676)] for 2000-2017. Black circles represent monthly averages. Bars indicate SD. Purple cir-

cles indicate extreme values (> 2 SD), excluded from the calculation of the means.

%Chl

<5

100

80

60

40

20

0Jan. Feb. Mar. Apr. May Jun. Jul. Aug.Sep. Oct. Nov.Dec.

Month

5

4

3

2

1Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov.Dec.

a (443)/a (676)

Phy Phy

Month

Inter-annual variations in bio-optical proper-

ties and extreme events

Time series of bio-optical observations

throughout the study period (2000-2017) reflect-

ed the repetition of seasonal cycles as well as the

occurrence of extreme events (Figures 8, 9 and

10) which were associated to specific events

involving an exceptional increase in phytoplank-

ton abundance. An extremely high ChlTvalue of

6.420 mg m-3 (the highest for the entire time

series) was recorded in June 2001, but unfortu-

215

RUIZ ET AL.: THE COLOR OF EPEA

Table 2. Spearman correlation coefficients between bio-optical and physical properties at EPEA. Spearman coefficient of corre-

lation (rho), probability (p) and data number (n) used are written from top to bottom. Temp.: temperature, RBR:

[aPhy(443)/aPhy(676)]. Bold values are significant at a α=0.05 confidence level.

ChlT aNAP(443) aPhy(443) aBPhy(443) RBR aCDOM(443) ZdTdZ dTdZ Zeu %Chl<5

Temp. -0.307 -0.117 0.016 0.391 0.500 0.031 -0.505 0.588 0.311 0.104

0.000 0.224 0.869 0.000 0.000 0.785 0.000 0.000 0.003 0.295

118 109 109 109 109 77 118 118 91 102

ChlT 0.238 0.584 -0.639 -0.365 0.229 0.340 -0.454 -0.647 -0.061

0.012 0.000 0.000 0.000 0.044 0.000 0.000 0.000 0.542

110 110 110 110 78 119 119 92 103

aNAP(443) 0.336 0.007 -0.233 0.137 0.193 -0.361 -0.638 -0.404

0.000 0.945 0.014 0.232 0.043 0.000 0.000 0.000

110 110 110 78 110 110 90 99

aPhy(443) 0.136 -0.093 0.230 0.150 -0.178 -0.607 -0.031

0.157 0.335 0.043 0.117 0.062 0.000 0.762

110 110 78 110 110 90 99

aBPhy(443) 0.449 -0.075 -0.386 0.475 0.268 -0.061

0.000 0.513 0.000 0.000 0.011 0.551

110 78 110 110 90 99

RBR 0.022 -0.610 0.661 0.468 0.206

0.848 0.000 0.000 0.000 0.040

78 110 110 90 99

aCDOM(443) -0.045 0.004 -0.209 0.002

0.693 0.972 0.072 0.987

78 78 75 77

ZdTdZ -0.704 -0.392 -0.095

0.000 0.000 0.341

119 92 103

dTdZ 0.536 0.200

0.000 0.043

92 103

Zeu 0.316

0.002

91

nately no bio-optical data is available for that

sampling. In November 2005 an event character-

ized by values of ChlT=6.130 mg m-3, aPhy(443)

=0.811 m-1 and aNAP(443) =0.0128 m-1 was

observed. In December 2008 another maximum

of phytoplankton occurred, characterized by high

values of chlorophyll concentration and OACs

absorption (ChlT=5.377 mg m-3, aPhy(443) =

0.266 m-1 and aNAP(443) =0.063 m-1). The high

absorption by OACs attenuated the light produc-

ing the shallowest Zeu registered at EPEA (Zeu =

11.1 m). Interestingly, in the following month

(January 2009) stratification intensified reaching

an extreme value of dTdZ =-2.9 and ZdTdZ =24.0

m, while ChlTdecreased up to 0.353 mg m-3 and

the ratio [aPhy(443)/aPhy(676)] increased to 3.66,

a rather high value denoting a change in the phy-

toplankton composition. In turn, aNAP(443) and

aCDOM(443) continued to be high (0.06 m-1 and

0.096 m-1, respectively), probably as a conse-

quence of the bloom decay. Finally, in November

2016 another extreme increase in phytoplankton

occurred, evidenced by both the high values

of ChlTand aPhy(443) of 4.163 mg m-3 and

0.527 m-1 respectively. Possibly other extreme

events have occurred at EPEA in between our on-

site sampling.

Trends in bio-optical and physical properties

for the period 2000-2017

ChlTand Chl<5 showed significant increasing

216 MARINE AND FISHERY SCIENCES 33 (2): 205-225 (2020)

Figure 8. Inter-annual distribution of coefficients of light absorption at 443 nm by phytoplankton [aPhy(443)], non-algal particles

[aNAP(443)], and CDOM [aCDOM(443)] estimated for 5 m samples at EPEA for the period 2000-2017. Purple circles indi-

cate extreme values (>2 standard deviations).

0.16

0.14

0.12

0.10

0.08

0.06

0.04

0.02

0.00

0.10

0.08

0.06

0.04

0.02

0.00

0.80

0.60

0.40

0.20

0.09

0.06

0.03

0.00

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

Serial years

a (443)

Phy

[m ]

-1

a (443)

NAP

[m ]

-1

a (443)

CDOM

[m ]

-1

trends (Table 3; Figures 11 and 12). Percentage of

Chl<5also showed a significant positive trend

(Figure 13), in agreement with the significant

positive trend in the pico-phytoplankton fraction

observed at EPEA (Silva, pers. comm.). On the

other hand, the Seasonal Mann-Kendal test

(SMK) revealed that the specific absorption coef-

ficient of phytoplankton, aBPhy(443), decreased

significantly during the same period (Figure 14).

This trend appears to be simply governed by the

increasing trend in chlorophyll, since an increase

in pico-phytoplankton is expected to be reflected

in an increase in the efficiency of light absorption

per unit chlorophyll. The rest of properties stud-

ied didn’t show any significant trend of change

during the period analysed (Table 3).

DISCUSSION

Changes in the incident irradiance at EPEA

seem to be the main driver of the seasonal forma-

tion of a warmer less dense upper layer separated

by a thermocline from deep colder waters (Ruiz,

2018; Luz Clara, pers. comm.). Basic description

of phytoplankton growth cycle in temperate seas

explains that blooms occur in spring as the water

column stratifies, allowing cells to remain in the

lit zone at the same time that they have plenty of

nutrients, which were replenished by mixing dur-

ing the previous winter (Riley 1946). Neverthe-

less, at EPEA, except for special events, phyto-

217

RUIZ ET AL.: THE COLOR OF EPEA

Figure 9. Inter-annual distribution of concentration of chlorophyll-a ChlT, percentage of Chl<5from ChlT, and ratio

[aPhy(443)/aPhy(676)] estimated for 5 m samples at EPEA for the period 2000-2017. Purple circles indicate extreme val-

ues (>2 standard deviations).

5

4

3

2

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

Serial years

100

80

60

40

20

0

7.0

6.0

5.0

4.0

2.7

1.8

0.9

0.0

Chl

T

[]mg m

-3

%Chl

<5

a (443)/a (676)

Phy Phy

218 MARINE AND FISHERY SCIENCES 33 (2): 205-225 (2020)

Figure 10. Inter-annual distribution of euphotic depth, Zeu, the depth at which the maximum value of the derivate of temperature

with respect to depth (dT/dZ) occurred, ZdTdZ, and the strength of the dT/dZ at EPEA for the period 2000-2017. Purple

circles indicate extreme values (>2 standard deviations).

0

10

20

30

40

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

Serial years

0

10

20

30

40

0

-1

-2

-3

-4

Z

eu

(m)

Z (m)

dTdT

dT/dT

Table 3. Values of pobtained from the Seasonal Mann-Kendal test (SMK) trend analysis for bio-optical properties and thermal

stratification parameters at EPEA for the period 2000-2017. Values marked in bold are significant at a α=0.05 confi-

dence level.

Property Trend sign p SMK

ChlT Positive 0.00013

Chl<5 Positive < 0.00001

%Chl<5 Positive < 0.00002

aPhy(443) 0.5945

aNAP(443) 0.1878

aCDOM(443) 0.2167

aBPhy(443) Negative < 0.00003

aPhy(443)/aPhy(676) 0.5272

ZdTdZ 0.2659

Zeu 0.7282

plankton biomass as indicated by ChlTdoes not

follow this dynamic, since ChlTtends to be higher

at the end of winter. This could be due to the fact

that bottom depth (~ 48 m) is shallow enough to

allow phytoplankton cells to be brought up by

mixing to the lit layer with a frequency that per-

mits them to grow, even during the darkest

months at EPEA. Incident irradiance starts

increasing in August, being the trigger for a rela-

tive increment in phytoplankton growth, whose

biomass starts to decrease as the stratification

progresses and nutrients are consumed (Negri et

219

RUIZ ET AL.: THE COLOR OF EPEA

Figure 11. Annual mean ChlTanomalies for the period 2000-2017.

Figure 12. Annual mean Chl<5 anomalies for the period 2000-2017.

-0.5

-0.4

-0.3

-0.2

-0.1

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

Annual mean anomaly

Year

p 1e-05<

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2013 2014 2015 2016 2017

Annual mean anomaly

Year

2012

0.60

0.55

0.50

0.45

0.40

0.35

0.30

0.25

0.20

0.15

0.10

0.05

0.00

-0.05

-0.10

-0.15

-0.20

-0.25

-0.30

2000

p 1e-05<

al. 2003; Carreto et al. 2004). Relationships

among properties studied add evidence to this

explanation since ChlTwas significantly and pos-

itively correlated with ZdTdZ and significantly and

negatively correlated with Zeu.

It is known that small cells are more efficient

to assimilate nutrients when these are scarce, due

to their higher surface to volume ratio (Richard-

son et al. 1983; Chisholm 1992), and at the same

time of being better suited to cope with high irra-

diances, which may cause photo-inhibition due to

the higher proportion of photo-protective pig-

220 MARINE AND FISHERY SCIENCES 33 (2): 205-225 (2020)

Figure 13. Annual mean %Chl<5 anomalies for the period 2000-2017.

Figure 14. Annual mean aBPhy(443) anomalies for the period 2000-2017.

-0.020

-0.015

-0.010

-0.005

0.000

0.005

0.010

0.015

0.020

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

Annual mean anomaly

Year

p 3e-05<

-20

-15

-10

-5

0

5

10

15

20

25

2000 2002 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

Annual mean anomaly

Year

p 5e-05<

20032001

ments, such as zeaxanthin in Synechococcus.

Higher blue to red ratios have been attributed to

the dominance of phytoplankton populations with

small cell sizes and photoacclimated to high light

(Sosik and Mitchell 1995; Millán-Núñez et al.

2004). At EPEA station, this photoacclimation

strategy is evidenced in higher values of blue to

red absorption ratio [aPhy(443)/aPhy(676)] during

summer and also in the correlation with the shal-

lower and stronger stratification and deeper

euphotic depth. A similar but not as conspicuous

pattern was observed for aBPhy(443), a bio-optical

property indicative of absorption efficiency

which is usually negatively correlated with cell

size. Thus, it is possible to discern the link of bio-

optical properties following main seasonal varia-

tions in phytoplankton types and how they pho-

toacclimate, even at this optically complex

coastal site.

Variations in the annual cycle of absorption

coefficients of OACs at EPEA station for the peri-

od 2000-2017 have been previously analyzed

(Lutz et al. 2006; Ruiz 2018). From those studies

it became clear that aCDOM(443) is the OAC with

largest values of absorption at all months (with

peaks in fall and summer), followed by aPhy(443)

(with almost no variation throughout the year),

and finally aNAP(443) which is maximum in win-

ter. The fact that at EPEA aPhy(443) did not show

seasonal variability as it was in the case for ChlT

could be due to the fact that the spectral absorp-

tion coefficient of phytoplankton is a complex

bio-optical property that represents the sum of the

absorption by different pigment-protein complex-

es present in different phytoplankton species that

make up a given sample. However, aPhy(443) still

was correlated to ChlT, and it showed extreme

values in events when phytoplankton biomass

was high. As mentioned, the blue to red absorp-

tion ratio [aPhy(443)/aPhy(676)] is a property that

changes both with the phytoplankton community

and with how the cells were photoacclimated,

with the advantage that as being dimensionless it

emphasizes these variations in the absorption

spectral shape rather than in its magnitude (Sosik

and Mitchell 1995). At EPEA, the annual cycle of

[aPhy(443)/aPhy(676)] showed higher values dur-

ing the warm period; whether this suggests that

phytoplankton populations are mainly composed

of small cells (Negri and Silva 2003) or different

size cells which were photoacclimated to high

irradiances remains to be addressed.

Long term trends of change were observed both

for ChlT,Chl<5 and %Chl<5. This fact could have

been exacerbated by the change in the extraction

method of the chlorophyll concentration determi-

nation that took place in 2006 at EPEA station

(from acetone 90% to methanol 100%), which is

more efficient in the case of smaller cells (Lutz et

al. 2010). Nevertheless, independent sources of

ChlTestimation (satellite) in the region also ren-

dered an increasing trend (Marrari et al. 2017).

However, despite the positive and significant cor-

relation observed between ChlTand aPhy(443),

long-term changes were not reflected in a signifi-

cant trend of aPhy(443). This could have been pos-

sibly related to the wide seasonal variability of

this coefficient and the fact that absorption coeffi-

cients are complex properties encompassing many

factors. In agreement with the positive significant

trend in Chl<5, the picoplankton and nanoplankton

size fractions showed significant positive trends

(Silva, pers. Comm.). Contrary to what could be

expected from these observations, we have

observed a significant decreasing trend in the total

aBPhy(443) (which is a lineal combination of ChlT,

aBPhy(443) =aPhy(443)/ChlT) and no trend in

[aPhy(443)/aPhy(676)].

A few special bloom events were observed at

EPEA, some of them associated with different

extraordinary physical conditions. In 2001, an

almost exclusively blooming of diatoms from the

nano and micro planktonic size fraction was

observed. In November 2005 a bloom of the

Genus Prymnesium sp. was identified, character-

ized by the absence of micro planktonic diatoms.

In December 2008, another maximum of phyto-

plankton occurred, which was associated with an

221

RUIZ ET AL.: THE COLOR OF EPEA

event of cold temperature and characterized by

the presence of atypical phytoplankton species for

the study site and the absence of micro planktonic

diatoms, which could be the reason why a relative

high aPhy(443) was observed for the recorded

ChlT(Negri et al. 2015). The bloom observed in

November 2016 was particular due to its high

concentration of nano planktonic dinoflagellates.

Whether the frequency of such events has been

increasing at EPEA is a question that we cannot

still assess upon our in situ database, mainly

given the unfortunate gaps in the sampling. Nev-

ertheless, in this work it has been shown that IOPs

did capture these special events, indicating that

satellite information should also be useful to

detect them, even considering the possible inac-

curacies of this data source for the study site

(Ruiz 2018; IOCCG 2020). Long term time series

of observations, either in situ or satellite, are not

exempt from changes in the methodologies or

from gaps in the sampling frequency. These two

factors, together with the autocorrelation and

decadal natural variability of oceanic ecosystems

challenge the unambiguous detection of a trend,

possibly driven by climate change, above the nat-

ural variability. It has been stated that time series

of about 40 years long would be necessary to dis-

tinguish a trend from natural variability, assuming

no gaps on the observational record (Henson et al.

2010). This is a condition that only very few eco-

logical time series are able to meet so far, which

points out the necessity of maintaining time series

to assess changes occurring in the marine envi-

ronment (O’Brien et al. 2017). Long-term in situ

bio-optical data is particularly scarce in the global

ocean. From the beginning of this time series to

the present, the technological capacity imple-

mented (ships, equipment, human resources) has

been improved, and despite the irregular sam-

pling frequency, this work based on the observa-

tions at EPEA emphasize the relevance of in situ

ecological time series to contribute to the under-

standing of coastal ecosystems dynamics in a

context of climate change.

CONCLUSIONS

Our results derived from almost two decades

of in situ observations at this coastal site in the

South Atlantic indicate an increasing trend in

chlorophyll-a concentration, possibly due to an

increase in the smaller fraction of phytoplankton.

Although the absorption coefficient of phyto-

plankton did not follow a significant trend, it did

represent the occurrence of special events of high

biomass, which is an encouraging result for the

use of satellite information at the study site. Two

main parameters of phytoplankton absorption, the

specific absorption coefficient of phytoplankton

aBPhy(443) and the blue to red ratio

[aPhy(443)/aPhy(676)], follow an annual cycle

with high values in summer and low in winter,

according to the probable dominance of different

size cells and their expected acclimation to the

light regime. Though, aBPhy(443) showed a trend

to decrease throughout the years, which is consis-

tent with the increase in ChlT, but how this is con-

nected to the increase in small cells should be fur-

ther investigated. An in depth study of the vari-

ability in the phytoplankton absorption spectral

shapes and its direct link to phytoplankton

species and their photoacclimation status would

be a next step at EPEA. Possible sources of

CDOM should also be explored, since it is a

major component absorbing light and was not

correlated to any of the variables studied.

ACKNOWLEDGEMENTS

This work was supported by INIDEP and

CONICET. The authors thank Daniel Cucchi

Colleoni for his collaboration on board and labo-

ratory analysis since the beginning of the time

series. Special thanks to Daniel Hernández and

Manuela Mendiolar who provided statistical

222 MARINE AND FISHERY SCIENCES 33 (2): 205-225 (2020)

advice, and to Ezequiel Cozzolino who provided

satellite data. The authors are also thankful to the

crew and captains of all the vessels used to

achieve the sampling at EPEA time series and to

the anonymous reviewers. INIDEP contribution

no 2224.

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