MARINE AND FISHERY SCIENCES 34 (2): 123-142 (2021)

https://doi.org/10.47193/mafis.3422021010601

ABSTRACT. Densities of eggs and larvae of Engraulis anchoita and the nutritional condition of

larvae were analyzed in the fixed sampling station (EPEA) in the period 2000-2017. These variables

were analyzed seasonally and trends over time were determined. Ichthyoplankton samples were col-

lected by oblique trawls using Bongo nets with 300 μm of pore mesh and fixed with formaldehyde

5% in seawater. Six morphometric variables were measured to estimate the nutritional condition of

larvae. The developmental stage of each specimen was also determined. The highest mean value of

egg density was detected in the October-December period, with a secondary mode in August, fol-

lowed by one in March. Larval density presented a mode in October. Autumn and spring were the

most favorable seasons for larval condition while winter proved to be the least favorable one. An

increase in food availability during autumn and spring due to primary and secondary production

peaks could explain the high nutritional condition and growth values observed in these seasons at

the EPEA. No changes in trends of variables over time were detected. The integrated study of den-

sity and nutritional condition of E. anchoita larvae allows the determination of favorable breeding

periods for the species, while the continuation of the long term study will allow evaluating possible

effects of climate change in the early life stages of this species.

Key words: Engraulis anchoita, ichthyoplankton, nutritional condition, seasonality, time series.

Etapas tempranas de la anchoíta: abundancia, variabilidad y condición larval en la estación

fija EPEA entre 2000-2017

RESUMEN. Se analizaron las densidades de huevos y larvas de Engraulis anchoita y el estado

nutricional de las larvas en la estación de muestreo fija (EPEA) en el período 2000-2017. Estas

variables se analizaron estacionalmente y se determinaron las tendencias en el tiempo. Las muestras

de ictioplancton se recolectaron mediante arrastres oblicuos utilizando redes Bongo con 300 μm de

poro de malla y se fijaron con formaldehído al 5% en agua de mar. Se midieron seis variables mor-

fométricas para estimar el estado nutricional de las larvas. También se determinó la etapa de desa-

rrollo de cada espécimen. El mayor valor medio de densidad de huevos se detectó en el período

octubre-diciembre, con una moda secundaria en agosto, seguida de otra en marzo. La densidad lar-

varia presentó una moda en octubre. El otoño y la primavera fueron las estaciones más favorables

para la condición larvaria, mientras que el invierno resultó ser la menos favorable. Un aumento en

la disponibilidad de alimentos durante el otoño y la primavera debido a los picos de producción pri-

maria y secundaria podría explicar el alto estado nutricional y los valores de crecimiento observados

en estas temporadas en la EPEA. No se detectaron cambios en las tendencias de las variables a lo

123

*Correspondence:

eleonard@inidep.edu.ar

Received: 26 September 2020

Accepted: 11 March 2021

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

Marine and

Fishery Sciences

MAFIS

ORIGINAL RESEARCH

Early stages of anchovy: abundance, variability and larval condition at the

fixed coastal station EPEA between 2000-2017

EZEQUIEL LEONARDUZZI1, *, MARINA DOSOUTO1, 2 and MARINA V. DIAZ1, 2

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-CONICET), Facultad de Ciencias Exactas y Naturales,

Universidad Nacional de Mar del Plata (UNMdP), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina.

ORCID Ezequiel Leonarduzzi https://orcid.org/0000-0002-6232-0478, Marina Do Souto https://orcid.org/0000-0002-2259-0115,

Marina V. Diaz https://orcid.org/0000-0002-2912-5232

INTRODUCTION

Ichthyoplankton is the key component that

links primary, secondary and tertiary levels of the

trophic web in the sea. Fish generally spawn in

relation to the primary and secondary production

cycles and consequently, ichthyoplankton densi-

ties fluctuate throughout the year (Govoni 2005).

Pájaro et al. (2009) estimated the adult Engraulis

anchoita biomass from 1996 to 2004 in the

Argentine sea based on the analysis of ichthy-

oplankton samples obtained in 10 surveys. These

authors demonstrated the importance of ichthy-

oplankton analyzes in the understanding of

recruitment and management research, in this

case using a daily egg production method.

Ichthyoplankton sampling can also be used for

the prospection of new resources, establishing

the timing and location of spawning areas and

their variations, or estimating the relative abun-

dance of different stocks and monitoring their

abundance trends over time (Rodríguez et al.

2017). Furthermore, the nutritional condition of

fish larvae is a reflection of environmental condi-

tions to which they were exposed and is a useful

tool to evaluate the physiological state of organ-

isms. Monitoring the larval status over time

allows the detection of areas and seasons favor-

able for the survival and growth of individuals.

This information provides tools for the sustain-

able management of a population subject to fish-

ing exploitation since it allows establishing

appropriate fishing closure periods. One

approach to studying the nutritional condition of

larvae is the use of morphometric techniques.

These methodologies are based on the fact that

larvae in a deficient condition are typically thin-

ner, have a lower weight for a given size and have

an irregular body shape with respect to healthier

individuals. Unhealthy larvae may experience

higher mortality due to predation or due to the

transportation to unfavorable areas (Theilacker

1978; Ferron and Leggett 1994; Suthers 1998).

Therefore, the study of fish eggs and larvae is of

extreme importance in any type of biological

assessment of fisheries.

The Argentine anchovy E. anchoita is the most

abundant fish species in the southwestern Atlantic

Ocean, with a broad latitudinal distribution from

23° S to 47° S (Bakun 2006). There are two

known stocks of this species in the Argentine Sea:

the northern stock (also called Bonaerensis stock

for being in the region of the Buenos Aires

province) and the southern stock (or Patagonian

stock, associated with the Patagonian region).

The first one occurs between 34° S and 41° S, and

constitutes the most important group of pelagic

fish of the region due to its biomass (Ciechomski

and Sánchez 1988) and its trophic role as the

main prey of other species of fish, mammals and

seabirds (Angelescu 1982). During its reproduc-

tive peak in spring E. anchoita adults inhabit

coastal waters, and anchovy eggs and larvae are

found in temperatures between 9 and 23 °C, with

salinities greater than 23 (Reid 1966). Conditions

of this area are suitable for the species reproduc-

tion during spring due to the water column stabil-

ity and its trophic enrichment, both in nutrients

and larval prey (Sánchez and Ciechomski 1995).

Anchovy eggs and larvae are observed in the

Buenos Aires region throughout the year, howev-

er there is a peak of abundance in spring and a

secondary peak in autumn (Ciechomski and

Sánchez 1984).

124 MARINE AND FISHERY SCIENCES 34 (2): 123-142 (2021)

largo del tiempo. El estudio integrado de densidad y condición nutricional de larvas de E. anchoita permite determinar períodos de cría

favorables para la especie, mientras que la continuación del estudio a largo plazo permitirá evaluar posibles efectos del cambio climático

en las primeras etapas de vida de esta especie.

Palabras clave: Engraulis anchoita, ictioplancton, condición nutricional, estacionalidad, series de tiempo.

The Estación Permanente de Estudios Ambien-

tales (EPEA) is located at 38° 28′ S and 57° 41′ W,

approximately 27 nautical miles from Mar del

Plata city, Buenos Aires Province (Figure 1). The

EPEA is a fixed sampling station where plankton

and environmental variables (physical and chemi-

cal) are studied over time since 2000. Several

authors previously described in this location the

existence of a seasonal cycle in temperature, con-

centration of chlorophyll-aand abundance of zoo-

plankton (Temperoni et al. 2011; Viñas et al.

2013). There are as well previous studies of

anchovy larvae life traits and their relationship to

the seasonality in that fixed sampling station.

Leonarduzzi et al. (2010) analyzed the growths of

anchovy larvae through their otolith microstruc-

ture and observed that the highest growth rate was

recorded during spring in comparison to the

remaining seasons. Sato et al. (2011) observed

that the highest feeding incidence of anchovy lar-

vae occurred during that same season. Do Souto et

al. (2019), analyzing a shorter time period, detect-

ed lower growth rates and lower nutritional condi-

tion values through RNA/DNA indexes of

anchovy larvae during winter. The use of morpho-

metrical techniques allowed us to evaluate larval

nutritional condition throughout a longer time

series and this technique proved to be sensitive

and complementary to other biochemical method-

ologies (Diaz et al. 2010). In addition to seasonal-

ity, fixed stations such as the EPEA allow the

analysis of time series of physical and biological

factors over long periods of time. This kind of

analysis allows detecting patterns related to large

temporal phenomena, such as the consequences of

climate change.

The objective of this work was to estimate the

density of eggs and larvae of E. anchoita and

evaluate the nutritional condition of larvae using

morphometric techniques in the search for sea-

sonal patterns and trends over time within the

period 2000-2017 at the EPEA.

125

LEONARDUZZI ET AL.: EARLY ANCHOVY STAGES AT EPEA

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

42°

41°

40°

39°

38°

37°

36°

35°

EPEA

W 61° 59° 57° 55° 53°

Mar del Plata

Atlantic Ocean

Río de la Plata

50 m

100 m

200 m

Study

area

MATERIALS AND METHODS

Sample collection

Samples were collected in 87 research surveys

at the EPEA corresponding to the Marine Plank-

ton Dynamics and Climate Change (DiPlaMCC)

project of INIDEP, between February 2000 and

November 2017 aboard different research ves-

sels: BIP ‘Capitán Cánepa’, BIP ‘Capitán Oca

Balda’, BIP ‘Doctor Eduardo E. Holmberg’, ARA

‘Puerto Deseado’ and oceanographic motor sailer

‘Dr. Bernardo Houssay’. Eighty-seven plankton

samples were collected by oblique trawls with a

Bongo net, from 40 m depth (4 m above bottom)

to the surface. The net was equipped with a mesh

of 300 μm and a flowmeter to estimate the vol-

ume of filtered water during the drag. Most of the

samples were taken around noon. Immediately

after the end of each tow, plankton samples were

preserved in a 5% solution of formaldehyde in

seawater.

Sample processing and seasonal data analysis

Eggs and larvae densities

Eggs and larvae of anchovy from each sample

were identified in the laboratory according to the

description given by Ciechomski (1967a) and

counted under a binocular-dissecting microscope.

Eggs (egg m-3) and larvae (ind. m-3) densities

were estimated from the filtered volume of each

sample. A mean density value was estimated for

each month and season for the 2000 to 2017 peri-

od. Densities obtained for different seasons for

the 2000 to 2017 period were compared using a

Kruskall Wallis K nonparametric test, since data

did not adjust to a normal distribution. Subse-

quently, a post hoc comparison test was per-

formed to compare the densities of anchovy eggs

and larvae for the four seasons using the Dunn’s

nonparametric test from the package PMCMR-

plus (Pohlert 2018). Densities of egg and larvae

were graphed in relation to salinity and tempera-

ture values at 5 m depth. These physical data

were obtained from the use of a SeaBird 19 CTD

(conductivity-temperature-depth profiler) from

surface to bottom in each survey. The R software

version 3.3.2 (R Core Team 2016) was used for

all the statistical analysis.

Morphometry

According to Diaz et al. (2009) variables

recorded were: standard length (SL), head length

(HL), head depth at the cleithrum level (HD),

body depth posterior to the head (BD), body

depth at the anus (BDA) and diameter of the eye

(ED) (Figure 2). When the eye had an oval shape,

ED was considered as the average between the

maximum and minimum diameters recorded.

Morphometric variables were recorded to the

nearest micrometer with a Carl Zeiss stereoscope

glass using Axio Vision software. No shrinkage

corrections were made.

The BDA/SL ratio was determined for each

specimen. Mean values per season were com-

126 MARINE AND FISHERY SCIENCES 34 (2): 123-142 (2021)

Figure 2. Engraulis anchoita larvae of 12 mm standard length. SL: standard length, HL: head length, HD: head depth at the clei-

thrum level, BD: body depth posterior to the head, BDA: body depth at the anus, ED: diameter of the eye.

pared by ANOVA, followed by the Tukey test

when significant differences were found. In order

to determine if there were morphological differ-

ences among individuals from different seasons

and among years, a Principal Component Analy-

sis (PCA) was conducted to evaluate the relation-

ship of all morphometric variables. Multivariate

analysis represents one of the best techniques for

studying nutritional condition since it allows the

use of multiple variables registered on the same

individual simultaneously. PCA is the only

methodology that satisfies the requirements of an

index of morphometric condition: independence

of size, biological significance and orthogonality

(McGurk 1985). Another advantage of this tech-

nique is that it allows the study of larvae captured

in situ when their nutritional condition or stage of

development is unknown (Cunha et al. 2003).

Prior to PCA, variables were normalized by larval

size according to equation 1 (Lleonart et al. 2000;

Diaz 2010). This standardization method is based

on the standardization of all morphometric vari-

ables obtained to a hypothetical reference size

(SL0), taking into account allometric relationships

between these variables and the standard length

of the larvae, using a potential equation (equation

2). Thus, a particular observed data (SLi; MVi)

becomes a theoretical value (SL0; MV − N). This

new normalized variable (MV − N) is independent

of the size of the individuals, so variations

observed are due to their physical condition and

not to their size.

Equation 1: normalized morphometric variable

(MV − Ni):

where MVi: value of a certain morphometric vari-

able of the individual iwith a standard length SLi;

SL0: reference standard length (we defined 6 mm

as reference size, since this was the mean stan-

dard length of the larvae); b: allometric coeffi-

cient.

MV N MV-=

SLi

SL0(1)

Equation 2: potential equation for the relation-

ship between standard length (SL) and morpho-

metric variables of specimens (MV ):

MVi=aSLb(2)

Trends over time

The method of analysis of time-series used in

this work was developed according to the SCOR

Global Comparisons of Zooplankton Time-series

working group (WG125), the ICES Working

Group on Zooplankton Ecology (WGZE), and the

ICES Working Group on Phytoplankton and

Microbial Ecology (WGPME). To avoid prob-

lems such as a strong seasonal cycle, calculation

of a simple annual average from low frequency or

irregular sampling (e.g. once per season, once per

year) or missing months or gaps between sam-

pling years, we used the technique of Mackas et

al. (2001), in which the annual anomaly value

(e.g. densities of anchovy eggs and larvae or

BDA/SL ratio) was calculated as the average of

individual monthly anomalies within each given

year. To accomplish this, the difference between

each monthly value and the mean value for that

year was first considered for each of the parame-

ters (e.g. BDA/SLAugust2000 −mean BDA/SL2000).

Secondly, its anomaly value was calculated for

each year as the mean value of all its monthly

anomalies. As this effectively removes the sea-

sonal signal from the annual calculations, this

method reduces many of the issues caused by

using low-frequency and/or irregular monthly

sampling to calculate annual means and anom-

alies (O’Brien et al. 2012). In the case of eggs and

larvae densities, the log transformation was used

to make highly skewed distributions less skewed.

The Seasonal Kendall (SK) test, a non parametric

test for seasonal data with serial dependence and

missing data, was used to analyze the potential

existence of a temporal trend in eggs and larvae

densities and the ratio BDA/SL. The SK is an

extension of the Mann-Kendall (MK) test pre-

127

LEONARDUZZI ET AL.: EARLY ANCHOVY STAGES AT EPEA

sented in Hirsch and Slack (1984). Although there

are a variety of programs and libraries, such as

trend (a library developed in R language where

the Mann-Kendall test is implemented), they do

not contemplate those cases in which there is

missing data. For this statistical analysis, we used

the csmk program developed in Fortram language

(Hernández and Mendiolar 2018).

RESULTS

Densities of eggs and larvae

Monthly analysis of density of anchovy eggs

for the considered period (2000-2017) showed

that maximum average values occurred during

the period October-December. These values var-

ied between 17 and 24 egg m-3. Lowest monthly

values were observed in January and in the April-

June period. A secondary mode stood out in

March with 9 egg m-3, in which a rarely high den-

sity of individuals was registered in a survey in

2005, causing the average density of that month

increase to 40 egg m-3 (Figure 3 A).

As for the larvae, the main peak of average den-

sity was recorded in October (6 ind. m-3), observ-

ing a secondary peak in May (4 ind. m-3). The

highest density values of larvae were detected in

October 2003 and 2006, with 23 and 16 ind. m-3,

respectively. As observed with the eggs, larvae

were detected throughout the year with the lowest

density values in January and in the two-month

period June-July (Figure 3 C).

Eggs and larvae densities from each survey

were ordered according to the day of the year

(DOY) they were sampled and (Figure 3 B and

128 MARINE AND FISHERY SCIENCES 34 (2): 123-142 (2021)

Figure 3. Average monthly densities (A and C) and densities according to the day of the year they were sampled (DOY) of

Engraulis anchoita eggs (egg m-3) and larvae (ind. m-3) (B and D) detected in the Estación Permanente de Estudios

Ambientales (EPEA). Vertical bars correspond to the standard deviation.

100

120

0 100 200 300

Summer Autumn Winter Spring

0 100 200 300

Density (ind. m )

-3

DOY

Summer Autumn Winter Spring

123456789101112

Density (egg m )

-3

123456789101112

Month

D). The greatest abundance of eggs and larvae

was recorded during spring, while there was a

second minor peak of larval abundance during

autumn. It was also observed that seasons with

highest densities of eggs and larvae were also the

seasons with greatest dispersion values. Seasonal

analysis allowed us to observe statistical differ-

ences between the density of eggs (K =23.69, df

=3, p <0.01) and larvae (K =10.71; df =3; p =

0.01) among the four seasons (Table 1). For

instance, eggs density was higher in spring than

in summer (Dunn test, p <0.015) and in autumn

(Dunn test, p <0.015) (Table 1). A higher density

of larvae was observed in spring than in winter

(Dunn test, p <0.012) (Table 1).

There was no clear trend between the density

of egg and temperature and salinity (Figure 4).

Physical parameters that determine the absence of

eggs were not detected with clarity, however, the

lowest densities of anchovy eggs were recorded

at temperatures between 10 °C and 21 °C. High-

est densities (> 50 egg m-3) were observed in

waters with salinities between 33.55 and 33.76

and 11.61 °C and 20.29 °C of temperature. Simi-

larly, larval abundance did not show a clear asso-

ciation with physical variables (Figure 5). How-

129

LEONARDUZZI ET AL.: EARLY ANCHOVY STAGES AT EPEA

Table 1. A) Mean, standard deviation (SD) and median values of Engraulis anchoita eggs and larvae densities for each season

during 2000-2017. B) Statistical comparison of pairs between the densities of E. anchoita eggs and larvae estimated at

the EPEA for four seasons using the non-parametric Dunn’s test. n.s.: non-significant differences, *: significant differ-

ences.

Eggs Larvae

Mean SD Median Mean SD Median

Summer 3.64 9.55 0.21 1.34 1.88 0.82

Autumn 1.17 2.07 0.24 2.02 2.95 0.40

Winter 6.02 9.63 1.81 1.45 2.48 0.32

Spring 19.34 18.53 14.95 4.42 7.77 2.60

Eggs Larvae

Dunn’s test p-value Dunn’s test p-value

Summer-Autumn 2.30 >0.05 n.s. 0.21 >0.05 n.s.

Summer-Winter 13.03 > 0.05 n.s. 3.58 >0.05 n.s.

Summer-Spring -30.61 <0.001* -17.80 >0.05 n.s.

Autumn-Winter -15.33 >0.05 n.s. 3.37 >0.05 n.s.

Autumn-Spring -32.92 <0.001* -18.01 >0.05 n.s.

Winter-Spring -17.58 >0.05 n.s. -21.38 <0.05*

130 MARINE AND FISHERY SCIENCES 34 (2): 123-142 (2021)

Figure 5. Engraulis anchoita larval density at the Estación Permanente de Estudios Ambientales (EPEA). Crosses represent sta-

tions with no larvae. Larger circles indicate 10-50 ind. m-3. Numbers 1 to 4 represent the type of water mass (Martos et

al. 2005). 1: coastal waters of low salinity, 2: medium shelf waters, 3: coastal waters with high salinity, 4: waters of max-

imum salinity.

Figure 4. Density of Engraulis anchoita eggs at the Estación Permanente de Estudios Ambientales (EPEA). Crosses represent

stations with no eggs. Larger circles indicate 50-100 egg m-3. Numbers 1 to 4 represent the type of water mass (Martos

et al. 2005). 1: coastal waters of low salinity, 2: medium shelf waters, 3: coastal waters with high salinity, 4: waters of

maximum salinity.

33,4 33,5 33,6 33,7 33,8 33,9 34,0 34,1 34,2

Salinity

Temperature (°C)

1234

33,4 33,5 33,6 33,7 33,8 33,9 34,0 34,1 34,2

Salinity

Temperature (°C)

1 2 3 4

ever, highest larval densities (between 8.24 and

22.8 ind. m-3) were detected between salinities of

33.56 and 33.95, a range similar to that observed

for highest eggs densities. Regarding tempera-

ture, highest densities were registered between

10.19 and 16.23 °C, presenting a narrower ther-

mal range than eggs.

Morphometry

Larvae with larger size range were found in

autumn (ANOVA: F =72.27; n =1,367; p <

0.001) (Figure 6). The SL of larvae collected dur-

ing autumn varied between 2.56 and 23.55 mm,

with a mean value of 7.55 ±3.19 mm (n =438).

Sizes recorded during spring varied between 2.75

and 14.01 mm SL, with an average of 5.30 ±2.10

mm SL (n =441). In winter, SL of larvae ranged

between 2.59 and 15.67 mm and averaged 5.65 ±

2.36 mm (n =276). Finally, in summer larvae had

a range of sizes between 2.56 and 12.36 mm and

an average of 5.27 ±2.03 mm (n =212).

Main values of BDA/SL ratio presented signif-

icant differences among seasons (ANOVA: F =

73.67; n =1,367; p <0.001; Table 2 A). The aver-

age value obtained for larvae captured during

autumn was significantly higher than those corre-

sponding to other seasons. On the other hand, this

mean value ratio was the lowest in the larvae cap-

tured in winter (Tukey test p <0.05, Table 2 A).

An upward trend in the BSA/SL ratio was

observed in autumn and spring and a downward

trend in winter with respect to the advance of the

seasons (Figure 7).

The body condition of anchovy larvae was ana-

lyzed through a PCA along the period studied

(Figure 8). Morphometric variables were stan-

dardized to a reference size of 6 mm before PCA.

The first two main components of the analysis

explained 90% of the variability observed (Table

2 B). Variables that positively characterized PC1

were body widths (BD and BDA), head length

and diameter of the eye. Body widths are the vari-

ables most related to the condition and those that

explained most of the variability observed for

the first principal component. The PC2 was

explained positively by the height of the body at

the anus level, head depth and the diameter of the

131

LEONARDUZZI ET AL.: EARLY ANCHOVY STAGES AT EPEA

Figure 6. Distribution of larval sizes of Engraulis anchoita per day of the year (DOY) during 2003-2017 at the Estación

Permanente de Estudios Ambientales (EPEA). Seasons are indicated.

1 17 33 48 64 80 96 112 128 143 159 175 191 207 223 238 254 270 286 302 318 333 349 365

DOY

SL (mm)

Summer Autumn Winter Spring

eye, and negatively by body widths and head

length. The PCA revealed that the larvae collect-

ed in autumn and summer were characterized by

larger body widths.

On the other hand, PC3 explained 10% of the

variability observed (Figure 9). In all biplot

graphs larvae collected in winter were character-

ized by the lowest magnitudes in all variables. In

this way, it could be considered that in this season

they would be in a poorer nutritional condition

compared to larvae collected in other seasons of

the year.

Trends over time

Anchovy eggs and larvae did not show a sig-

nificant temporal trend in their anomalies of

abundance within the studied period (Figure 10 A

and B, SK test p =0.26 and p =0.35 to eggs and

larvae, respectively). Finally, anomalies of the

BDA/SL ratio obtained for anchovy larvae did

not show a significant temporal trend within the

studied period (Figure 10 C, SK test p =0.56).

132 MARINE AND FISHERY SCIENCES 34 (2): 123-142 (2021)

Table 2. A) Analysis of variance to compare seasonal mean values of the BDA/SL ratio for Engraulis anchoita larvae and Tukey

post hoc test. B) Eigenvalues and eigenvectors obtained in the Principal Component Analysis using normalized morpho-

metric variables recorded in E. anchoita larvae. Mean BDA/SL per season ±standard error, and number of samples

between brackets; capital letters indicate significant differences in the Tukey test. Data corresponded to 2003-2017 at the

Estación Permanente de Estudios Ambientales (EPEA). HL: head length, HD: head depth at the cleithrum level, BD:

body depth posterior to the head, BDA: body depth at the anus, ED: diameter of the eye. -N: indicates that morphometric

variables were normalized.

SS df MS F p-value Mean BDA/SL per season

Model 0.01 3 3.6E-03 60.66 < 0.0001 Winter 0.0511 ± 4.9E-04 (246)A

Season 0.01 3 3.6E-03 60.66 < 0.0001 Spring 0.0536 ± 3.8E-04 (412)B

Error 0.07 1,203 5.9E-05 Summer 0.0562 ± 5.3E-04 (212)B

Autumn 0.0585 ± 4.2E-04 (337)C

Total 0.08 1,206

Eigenvalues Eigenvectors

Lambda Value Proportion Cumulative proportion Variables PC1 PC2 PC3

1 3.46 0.69 0.69 HD-N -0.38 0.58 0.56

2 1.02 0.20 0.90 BD-N 0.48 -0.28 0.49

3 0.52 0.10 1.00 BDA-N 0.47 0.37 0.41

4 0.00 0.00 1.00 HL-N 0.53 -0.09 -0.07

5 0.00 0.00 1.00 ED-N 0.35 0.66 -0.52

DISCUSSION

Densities of eggs and larvae

In the present study, characteristics of the

early life history of E. anchoita were evaluated

during almost two decades of data, considering

possible variations related to seasonality and the

existence of a trend over time. Eggs and larvae

density values of this species recorded in the

present study were consistent with those report-

ed in previous works (Ciechomski 1969;

Ciechomski et al. 1981; Ciechomski and

Booman 1983; Sánchez 1995). Sánchez (1995)

carried out a detailed monthly analysis of the

spawning activity of this species and detected an

extraordinary expansion of the reproductive

activity in October covering the entire shelf of

Buenos Aires Province, and reaching the maxi-

mum peak of eggs and larvae densities in the

period October-November. A maximum spawn-

ing activity was detected during spring (October-

133

LEONARDUZZI ET AL.: EARLY ANCHOVY STAGES AT EPEA

Figure 7. Variation of BDA/SL ratio per day of the year (DOY) of Engraulis anchoita larvae. A) Data is shown per individual.

B) Mean value per day of the year with corresponding standard deviations. Data obtained during 2003-2017 at the

Estación Permanente de Estudios Ambientales (EPEA). Seasons are indicated.

1 18 34 51 67 84 100 117 133 150166 183 200216 233 249 266282 299 315 332348 365

0.03

0.04

0.05

0.06

0.07

0.08

0.09

BDA/SL (µm)

Summer Autumn Winter Spring

1 18 34 51 67 84 100 117 133 150166 183 200 216233249 266 282299315 332 348365

DOY

0.04

0.05

0.06

0.07

BDA/SL (µm)

134 MARINE AND FISHERY SCIENCES 34 (2): 123-142 (2021)

Figure 9. Biplot graph of principal components (PC) 1 and 3 obtained from the Principal Component Analysis of morphometric

variables of Engraulis anchoita larvae. Vectors indicate the direction and rate of change of each variable. Data were

grouped by season (blue circles). Data were obtained during 2003-2017 at the Estación Permanente de Estudios

Ambientales (EPEA). HL: head length, HD: head depth at the cleithrum level, BD: body depth posterior to the head,

BDA: body depth at the anus, ED: diameter of the eye, -N: indicates that the morphometric variables were normalized.

Figure 8. Biplot graph of the first two principal components (PC) obtained through Principal Component Analysis employing

morphometric variables of Engraulis anchoita larvae. Vectors indicate the direction and rate of change of each vari-

able. Data were grouped by season (blue circles). Data were obtained during 2003-2017 at the Estación Permanente

de Estudios Ambientales (EPEA). HL: head length, HD: head depth at the cleithrum level, BD: body depth posterior

to the head, BDA: body depth at the anus, ED: diameter of the eye. -N: indicates that morphometric variables were

normalized.

-3.00 -1.50 0.00 1.50 3.00

PC 1 (69.2%)

-3.00

-1.50

0.00

1.50

3.00

PC 3 (10.3%)

HD-N BD-N

BDA-N

HL-N

ED-N

Summer

Autumn

Winter

Spring

-4.00 -2.00 0.00 2.00 4.00

PC 1 (69.2%)

-4.00

-2.00

0.00

2.00

4.00

PC 2 (20.5%)

HD-N

BD-N

BDA-N

HL-N

ED-N

Summer

Autumn

Winter

Spring

135

LEONARDUZZI ET AL.: EARLY ANCHOVY STAGES AT EPEA

Figure 10. Anomalies of Engraulis anchoita, egg abundance (A), larvae (B), and BDA/SL ratio (C) between 2000 and 2017 at

the Estación Permanente de Estudios Ambientales (EPEA).

Eaggs density anual nomaly

Year

-1,00

-0,80

-0,60

-0,40

-0,20

0,00

0,20

0,40

0,60

0,80

2002 2004 2006 2008 2010 2012 2014 2016

-1,00

-0,80

-0,60

-0,40

-0,20

0,00

0,20

0,40

0,60

0,80

1,00

1,20

22000 2002 2004 2006 2008 2010 2012 2014 2016

-8,00

-6,00

-4,00

-2,00

0,00

2,00

4,00

6,00

2002 2004 2006 2008 2010 2012 2014 2016

Laarvae density anual nomaly

BDA/SL quotient anual nomalya

22000

December) at the EPEA, and a secondary one in

late summer-early autumn period, which seems

to be related to the secondary anchovy peak

observed in autumn-winter. Although restricted

to October, the density of anchovy larvae also

had a maximum peak during spring and a sec-

ondary mode in March-May, somewhat shifted

in time with respect to the secondary mode of

eggs density. Results obtained at the EPEA are

similar to those indicated by Sánchez (1995),

except for the great abundance of eggs and lar-

vae found during winter in this present work.

This difference could be due to the high densities

registered in August 2004 and August 2010, typ-

ical of spring time.

South of 37° S, the distribution of anchovy

eggs and larvae has been related to the position of

a surface thermal front (Pájaro et al. 2008). This

front separates homogeneous coastal waters from

stratified waters of the middle shelf regime in the

vicinity of the 40-50 m isobaths, where the EPEA

is located. During years in which the position of

the front moves towards deep waters or is absent,

lower densities of eggs and larvae have been

observed. On the contrary, in years when the

frontal system was strong, densities of anchovy

eggs and larvae were higher (Pájaro et al. 2008).

Therefore, differences in the formation and posi-

tion of the front could be the cause of changes in

the abundance of eggs and larvae at the EPEA.

The inter-annual variation of eggs was very

high in seasons with the most intense spawning.

This may be related to the fact that the distribu-

tion of anchovy eggs and larvae is highly conta-

gious (Sánchez 1986). Therefore, this variation

could be due to a methodological problem, since

in some cases the sampling could have been done

in the center of the patch of organisms, and some-

times it could have carried out in its periphery.

However, to maximize the catchability of eggs

and larvae, samples were collected from near the

bottom (40 m) to the surface, since the relatively

close-to-surface distribution observed for E.

anchoita larvae seems typical of Clupeiforms

(Matsuura et al. 1992; Matsuura and Kitahara

1995; Castro et al. 2000; Spinelli et al. 2013;

Torquato and Muelbert 2014).

The lowest abundance of anchovy eggs was

detected in autumn, with statistical differences

between that season and spring. However, when

analyzing the larvae, no differences were found

between autumn and winter-spring, and the aver-

age autumn densities were even higher than those

of summer and winter. This could indicate that

the survival of larvae born in autumn would be

higher than that of larvae hatched in other seasons

of the year. However, to understand the cause of

this phenomenon other studies will be necessary,

including the abundance of food zooplankton

throughout the year and the presence of predators.

Several studies correlated egg and larval abun-

dance to zooplankton biomass (Viñas et al. 2002;

Twatwa et al. 2005; Somarakis and Nikolioudakis

2007; Zarrad et al.2012; Malavolti et al. 2018).

For example, a significant relationship was found

between the abundance of small copepods and the

abundance of anchovy eggs during the spring in

the coastal area of Buenos Aires Province (Viñas

et al. 2002). This relationship could have trophic

implications as these small copepod species pro-

duce eggs and nauplii in the optimum size range

of prey for first-feeding anchovy larvae (Viñas

and Ramírez 1996). Future integrative analyses

have to be performed to understand whether

spawning of E. anchoita in the EPEA area, with

high zooplankton concentrations, provides better

conditions to larval survival.

In this study we observed a wide range of tem-

peratures and salinities in which anchovy eggs

and larvae occurred, as previously indicated by

Ciechomski (1967b), Brewer (1976), Matsuura

and Kitahara (1995) and Torcuato and Muelbert

(2014). We did not find a clear pattern of egg and

larvae densities in relation to temperature or salin-

ity suggesting that thermal tolerance enables lar-

vae to exploit different habitats or seasons (Mat-

suura et al. 1992; Torcuato and Muelbert 2014).

On the Buenos Aires shelf (south of 37° S), there

136 MARINE AND FISHERY SCIENCES 34 (2): 123-142 (2021)

is a middle shelf front near the 50 m isobath,

which separates vertically homogeneous coastal

waters from stratified waters of the middle shelf

(Lucas et al. 2005; Martos et al. 2005). Condi-

tions of most of the surveyed water masses corre-

sponded to coastal waters of high salinity, and to

a lesser extent to those of the medium shelf. Asso-

ciated with these two water masses, the highest

densities of anchovy eggs and larvae were detect-

ed. Auad and Martos (2012), through in situ data

analysis and numerical modeling for the period

1993-2008, determined that the intensity of the

front, the flow along the coast, and the abun-

dances of anchovy larvae would be connected and

forced by the effort of the wind along the coast.

These results are particularly interesting espe-

cially when considering inter-annual variations,

and they might explain the abrupt changes in

recruitment observed from one year to another. In

the past, biomass fluctuations from one to six mil-

lion tons have been detected to the northern stock

of the species (Hansen 2004). For this reason, it is

emphasized the importance of time series to

detect how anchovy responds to possible environ-

mental variations resulting from climate change.

In general, surface layers of the oceans have pro-

gressively increased their temperature in recent

decades, with an important effect on the distribu-

tion and reproduction of marine species (Edwards

and Richardson 2004; Richardson and Schoeman

2004). To detect these effects, it is essential to

have time series of data that reflect these changes.

On the other hand, variations in the average tem-

perature of seawater can result in movements of

peaks of secondary production, resulting in a

decoupling with the peak of larval production and

therefore affecting the survival of the first stages

of development of fish.

Morphometry

Morphometric techniques represent a simple

methodology that does not require sophisticated

or expensive equipment, and has a great potential

for studying the nutritional condition of fish lar-

vae (Diaz et al. 2009). This methodology is based

on the fact that thin larvae with an irregularly

shaped body are regarded to be in poor condition

(Ferron and Leggett 1994). Moreover, body

height includes, among other structures, the

height of the digestive tract and the liver, tissues

that have been shown to be highly sensitive to the

larval condition (Theilacker 1978). One of the

main limitations of morphometric techniques is

the dependence on the size of the larvae, which

provides a source of additional variability that

overlaps with the effects of starvation on the stud-

ied variables. Removal of the size effect can be

accomplished by applying mathematical transfor-

mations or limiting the size range (Suthers 1998).

To solve this problem, morphometrical variables

were normalized in this study following Leonart

et al. (2000) and Diaz (2010). This method rela-

tivizes recorded variables of all individuals to the

same size and thus morphological differences are

due solely to the condition of the specimens

regardless of their size.

PCA results indicated that larvae obtained in

winter were characterized by lower values of

body widths (BD and BDA), variables directly

related to the nutritional condition (Diaz et al.

2009). Additionally, the average winter BDA/SL

ratio was significantly lower than those in other

seasons. Even though a great individual variabil-

ity among larvae was observed, it can be assumed

that larvae collected in winter are in a poorer

nutritional condition with respect to those

obtained in other seasons. In contrast, mean

BDA/SL obtained for larvae collected during

autumn was the highest recorded among seasons.

Furthermore, it was observed that the BDA/SL

ratio obtained for larvae collected in spring was

more variable than that corresponding to the lar-

vae collected in autumn. Studying larvae of the

same species in ‘El Rincón’ area (an estuarine

environment close to our study area), Diaz et al.

(2009) found a reduction in the nutritional condi-

tion of individuals when larval densities were

137

LEONARDUZZI ET AL.: EARLY ANCHOVY STAGES AT EPEA

extremely high. Similarly, density-dependent fac-

tors could be acting at the EPEA during spring

that would lead to a somewhat poorer nutritional

condition when a temporal coincidence of high

larval densities and moderate or low concentra-

tions of larval prey is observed. Using the

RNA/DNA condition index, Do Souto et al.

(2019) also observed that the larval condition of

E. anchoita was significantly lower during the

winter period 2009-2017. In accordance with the

results herein presented, these same authors estab-

lished that autumn and spring would be the most

favorable seasons for the growth and condition of

anchovy larvae at the EPEA. Do Souto et al.

(2019) coincidentally observed that RNA/DNA

index presented less variability during autumn in

comparison to spring. On the contrary, low larval

growth rates, as well as poor nutritional condition,

would indicate that winter represents an unfavor-

able period for the anchovy larvae.

Trends over time

We did not observe significant trends over time

in densities of early developmental stages of

anchovy or in the nutritional condition of larvae

within the studied period. This may be because

the number of samples analyzed was too small to

show long-term patterns. These results reinforce

the need to maintain this time series and analyze

a longer period of time in the future. Long-term

study of anchovy abundances and nutritional con-

dition will allow evaluating the possible effect of

climate change on the early ontogeny of this

species.

The importance of this type of studies lies in

the fact that it allows determining the existence of

favorable areas for the growth and survival of lar-

vae, providing tools for the comprehensive man-

agement of a population subjected to fishing

exploitation. Although E. anchoita represents at

present an underexploited resource, it has great

fishing potential for the future (Madureira et al.

2009). Interdisciplinary studies are needed in

order to deepen the knowledge about this pelagic

species particularly vulnerable to environmental

variations resulting from climate change. The

only way to assess the impact of climate change

on natural planktonic communities is by making

continuous long-term observations. At the

moment few observations are maintained fre-

quently enough to respond to possible changes in

these communities over time attributable to cli-

mate change. The synchrony in the growth cycle

of phytoplankton-zooplankton-larval hatching

(strongly affected by the environment) is critical

in the life of fish (Hjort 1914; Cushing 1969,

1990; Sinclair and Tremblay 1984). Therefore,

modification of plankton communities and their

interactions, strongly affected by the climate

change, could have dramatic socioeconomic

impacts through the effects on species of com-

mercial interest, exacerbating the impact of over-

fishing (Beaugrand et al. 2003).

ACKNOWLEDGEMENTS

The authors express their gratitude to the staff

belonging to the Project “Marine Plankton

Dynamics and Climate Change” for all kinds of

collaboration provided during research and mate-

rial processing, to the authorities of the INIDEP

and onboard personnel. Special thanks to the “Dr.

Bernardo Houssay” captain and crew. INIDEP

contribution no 2238.

REFERENCES

ANGELESCU V. 1982. Ecología trófica de la

anchoíta del Mar Argentino (Engraulidae,

Engraulis anchoita). Parte II. Alimentación,

comportamiento y relaciones tróficas en el

ecosistema. Contrib Inst Nac Invest Desarr

Pesq (Mar del Plata). Nº 409. 83 p.

138 MARINE AND FISHERY SCIENCES 34 (2): 123-142 (2021)

AUAD G, MARTOS P. 2012. Climate variabilityof

the Northern Argentinean Shelf Circulation:

impact on Engraulis anchoita. Int J Ocean

Climate Syst. 3 (1): 17-43. doi:10.1260/1759-

3131.3.1.17

BAKUN A. 2006. Wasp-waist populations and

marine ecosystem dynamics: navigating the

“predator pit” topographies. Prog Oceanogr.

68: 271-288.

BEAUGRAND G, BRANDER KM, LINDLEY JA,

SOUISSI S, REID PC. 2003. Plankton effect on

cod recruitment in the North Sea. Nature. 426:

661-664.

BREWER GD. 1976. Thermal tolerance and

resistence of the northern anchovy Engraulis

mordax. Fish Bull US. 74: 1- 8.

CASTRO LR, SALINAS GR, HERNÁNDEZ EH. 2000.

Environmental influences on winter spawning

of the anchoveta Engraulis ringens off Central

Chile. Mar Ecol Prog Ser. 197: 247-258.

CIECHOMSKI JD. 1967a. Present state of the inves-

tigations on the Argentine Anchovy Engraulis

anchoita (Hubbs, Marini). Cal Coop Ocean

Fish. 11: 58-66.

CIECHOMSKI JD. 1967b. Influence of some envi-

ronmental factors upon the embryonic devel-

opment of the Argentine anchovy Engraulis

anchoita. Cal Coop Ocean Fish. 11: 67-71.

CIECHOMSKI JD. 1969. Investigaciones sobre la

distribución de huevos de anchoíta frente a las

costas argentinas, uruguayas y sur del Brasil;

resultados de nueve campañas oceanográficas,

agosto 1967-julio 1968. FAO Proy Desarr

Pesq. Ser Inf Téc. 14: 1-10.

CIECHOMSKI JD, BOOMAN CI. 1983. Distribución

cuantitativa de huevos y larvas de anchoíta

(Engraulis anchoita) en la plataforma conti-

nental, frente a las costas de la Argentina y

Uruguay en el ciclo anual 1981/1982. Contrib

Inst Nac Invest Desarr Pesq (Mar del Plata).

Nº 431. 14 p.

CIECHOMSKI JD, EHRLICH MD, LASTA CA,

SÁNCHEZ RP. 1981. Distribución de huevos y

larvas de peces en el Mar Argentino y evalu-

ación de los efectivos de desovantes de

anchoíta y de merluza. Contrib Inst Nac Invest

Desarr Pesq (Mar del Plata). Nº 383. 20 p.

CIECHOMSKI JD, SÁNCHEZ RP. 1984. Field esti-

mates of embryonic mortality of Southwest

Atlantic anchovy (Engraulis anchoita).

Meeresforschung. 30: 172-187.

CIECHOMSKI JD, SÁNCHEZ RP. 1988. Análisis

comparativo de las estimaciones de biomasa

de la anchoíta (Engraulis anchoita) en el

Atlántico Sudoccidental en diferentes años y

con distintas metodologías. Publ Com Téc

Mix Fr Mar. 4. 14 p.

CUNHA I, SABORIDO-REY F, PLANAS M. 2003. Use

of multivariate analysis to assess the nutrition-

al condition of fish larvae from nucleic acids

and protein content. The Biol Bull. 204: 339-

349.

CUSHING DH. 1969.The regularity of the spawn-

ing season of some fishes. J Cons Int Explor

Mer. 33: 81-92.

CUSHING DH. 1990. Plankton production and

year-class strength in fish populations: an

update of the match/mismatch hypothesis. In:

BLAXTER JHS, SOUTHWARD AJ, editors.

Advances in marine biology. San Diego:

Academic Press Limited. p. 250-313.

DIAZ MV. 2010. Análisis espacio-temporal del

estado nutricional de larvas de anchoíta

Engraulis anchoita. Relación con las caracte-

rísticas hidrográficas y la disponibilidad de

alimento [PhD thesis]. Buenos Aires: Facultad

de Ciencias Exactas y Naturales, Universidad

de Buenos Aires. 282 p.

DIAZ MV, PÁJARO M, SÁNCHEZ RP. 2009.

Employment of morphometric variables to

assess nutritional condition of Argentine

anchovy larvae Engraulis anchoita Hubbs &

Marini, 1935. Rev Biol Mar Oceanog. 44:

539-549.

DOSOUTO M, BROWN DR, LEONARDUZZI E,

CAPITANIO F, DIAZ MV. 2019. Nutritional con-

dition and otolith growth of Engraulis anchoi-

ta larvae: the comparison of two life traits

139

LEONARDUZZI ET AL.: EARLY ANCHOVY STAGES AT EPEA

indexes. J Marine Syst. 193: 94-102.

EDWARDS M, RICHARDSON AJ. 2004. Impact of

climatic change on marine pelagic phenology

and trophic mismatch. Nature. 430: 881-884.

FERRON A, LEGGETT WC. 1994. An appraisal of

condition measures for marine fish larvae.

Adv Mar Biol. 30: 217-303.

GOVONI JJ. 2005. Fisheries oceanography and the

ecology of early life histories of fishes: a per-

spective over fifty years. Sci Mar. 69: 125-

137.

HANSEN JE. 2004. Anchoíta (Engraulis anchoita).

In: SÁNCHEZ RP, BEZZI SI, editors. El Mar

Argentino y sus recursos pesqueros. Tomo 4.

Los peces marinos de interés pesqueros.

Caracterización biológica y evaluación del

estado de explotación. Mar del Plata: Instituto

Nacional de Investigación y Desarrollo Pes-

quero (INIDEP). p. 101-115.

HERNÁNDEZ RD, MENDIOLAR M. 2018. Programa

csmk, implementación de un test no

paramétrico para datos estacionales con

dependencia serial y datos faltantes. Inf Ases

Transf INIDEP Nº 143/2018: 1-13.

HIRSCH RM, SLACK JR. 1984. A nonparametric

trend test for seasonal data with serial depend-

ence. Water Resour. Res. 20: 727-732.

HJORT J. 1914. Fluctuations in the great fisheries

of northern Europe viewed in the light of bio-

logical research. Rapp P-V Reun Cons int

Explor Mer. 20: 1-228.

LEONARDUZZI E, BROWN DR, SÁNCHEZ R. 2010.

Seasonal variations in the growth of anchovy

larvae (Engraulis anchoita) on the Argentine

coastal shelf. Sci Mar. 74: 267-274.

LLEONART J, SALAT J, TORRES GJ. 2000.

Removing allometric effects of body size in

morphological analysis. J Theor Biol. 205: 85-

93.

LUCAS AJ, GUERRERO RA, MIANZAN HW, ACHA

EM, LASTA CA. 2005. Coastal oceanographic

regimes of the Northern Argentine Continental

Shelf (34-43°S). Estuar Coast Shelf Sci. 65:

405-420.

MACKAS DL, THOMSON RE, GALBRAITH M. 2001.

Changes in the zooplankton community of the

British Columbia continental margin, 1985-

1999, and their covariation with oceanograph-

ic conditions. Can J Fish Aquat Sci. 58: 685-

702.

MADUREIRA LASP, CASTELLO JP, HERNANDEZ CP,

QUEIROZ MI, ESPÍRITO SANTO MLP, RUIZ WA,

ABDALLAH PR, HANSEN JE, BERTOLOTTI MI,

MANCA EA, et al. 2009. Current and potential

alternative food uses of the Argentine anchoita

(Engraulis anchoita) in Argentina, Uruguay

and Brazil. In: HASAN MR, HALWART M, edi-

tors. Fish as feed inputs for aquaculture: prac-

tices, sustainability and implications. Rome:

FAO. p. 269-287.

MALAVOLTI S, DEFELICE A, COSTANTINI I,

BIAGIOTTI I, CANDUCI G, GRILLI F, MARINI M,

TIRELLI V, B ORME D, CAPUTO BARUCCHI V,

LEONORI I. 2018. Distribution of Engraulis

encrasicolus eggs and larvae in relation to

coastal oceanographic conditions (a south-

western Adriatic Sea case study). Medit Mar

Sci. 19: 180-192.

MARTOS P, HANSEN JE, NEGRI RM, MADIROLAS

A. 2005. Factores oceanográficos relaciona-

dos con la abundancia relativa de anchoíta

sobre la plataforma bonaerense (34° S-41° S)

durante la primavera. Rev Invest Desarr Pesq.

17: 5-33.

MATSUURA Y, K ITAHARA EM. 1995. Horizontal

and vertical distribution of anchovy Engraulis

anchoita eggs and larvae off Cape Santa

Marta Grande in southern Brazil. Arch Fish

Mar Res. 42: 239-250.

MATSUURA Y, S PACH HL, KATSURAGAWA M. 1992.

Comparsion of spawning patterns of the

Brazilian sardine (Sardinella brasiliensis) and

anchoita (Engraulis anchoita) in Ubatuba

region, southern Brazil during 1985 through

1988. Bolm Inst Oceanogr USP. 40: 101-115.

MCGURK MD. 1985. Multivariate analysis of

morphometry and dry weight of Pacific her-

ring larvae. Mar Biol. 86: 1-11.

140 MARINE AND FISHERY SCIENCES 34 (2): 123-142 (2021)

O’BRIEN TD, LIWKW, MORÁN XAG. 2012.

ICES phytoplankton and microbial plankton

status report 2009/2010. ICES Coop Res Rep.

313. 196 p.

PÁJARO M, HANSEN JE, LEONARDUZZI E,

GARCIARENA D. 2009. Biomasa de los repro-

ductores de la población boanerense de

anchoíta (Engraulis anchoita) en el año 2008:

estimación mediante el método de producción

diaria de huevos. INIDEP Inf Téc. 29. 19 p.

PÁJARO M, MARTOS P, LEONARDUZZI E, MACCHI

GJ, DÍAZ MV, BROWN D. 2008. Estrategia de

puesta de la anchoita (Engraulis anchoita) en

el Mar Argentino y Zona Común de Pesca

Argentino-Uruguaya. Inf Téc INIDEP Nº

11/2008. 14 p.

POHLERT T. 2018. PMCMRplus. Calculate pair-

wise multiple comparisons of mean rank sums

extended, R package version 1.3.0. https://

cran.r-project.org/web/packages/PMCMR/

PMCMR.pdf.

R CORE TEAM. 2016. R: A language and environ-

ment for statistical computing. R Foundation

for Statistical Computing, Vienna, Austria.

https://www.R-project.org/.

REID JL. 1966. Oceanic environments of the

genus Engraulis around the world. Cal Coop

Ocean Fish. 11: 29-33.

RICHARDSON AJ, SCHOEMAN DS. 2004. Climate

impact on plankton ecosystems in the

Northeast Atlantic. Science. 305: 1609-1612.

RODRÍGUEZ JM, ALEMANY F, GARCIA A. 2017. A

guide to the eggs and larvae of 100 common

Western Mediterranean Sea bony fish species.

Rome: FAO. 256 p.

SÁNCHEZ RP. 1986. Estudios sobre las variaciones

espacio-temporales en los patrones de dis-

tribución de embriones y larvas de la anchoíta

(Engraulis anchoita), en relación con la esti-

mación de su intensidad reproductiva. Rev

Invest Desarr Pesq. 5: 92-142.

SÁNCHEZ RP. 1995. Patrones de distribución espa-

cio-temporal de los estadios embrionarios y

larvales de la anchoíta (Engraulis anchoita

Hubbs y Marini) a micro y macroescala, su

relación con la supervivencia y el reclutamien-

to [PhD thesis]. Buenos Aires: Facultad de

Ciencias Exactas y Naturales, Universidad de

Buenos Aires. 672 p.

SÁNCHEZ RP, CIECHOMSKI JD. 1995. Spawning

and nursery grounds of pelagic fish species in

the sea-shelf off Argentina and adjacent areas.

Sci Mar. 59: 455-478.

SATO N, HERNÁNDEZ D, VIÑAS MD. 2011.

Hábitos alimentarios de las larvas de

Engraulis anchoita (Hubbs & Marini, 1935)

en las aguas costeras de la Provincia de

Buenos Aires, Argentina. Lat Am J Aquat Res.

39: 16-24.

SINCLAIR M, TREMBLAY MJ. 1984. Timing of

spawning of Atlantic herring (Clupea haren-

gus harengus) populations and the match-mis-

match theory. Can J Fish Aquat Sci. 41 (7):

1055-1065.

SOMARAKIS S, NIKOLIOUDAKIS N. 2007.

Oceanographic habitat, growth and mortality

of larval anchovy (Engraulis encrasicolus) in

the northern Aegean Sea (eastern

Mediterranean). Mar Biol. 152: 1143-1158.

SPINELLI ML, GUERRERO R, PÁJARO M,

CAPITANIO FL. 2013. Distribution of

Oikopleura dioica (Tunicata, Appendicularia)

associated with a coastal frontal system (39°-

41°S) of the SW Atlantic Ocean in the spawn-

ing area of Engraulis anchoita anchovy. Braz

J Oceanogr. 61: 141-148.

SUTHERS IM. 1998. Biger? Fatter? Or is fast

growth better? Considerations on condition in

larval and juvenile coral-reef fish. Austral

Ecol. 23: 265-273.

TEMPERONI B, VIÑAS MD, DIOVISALVI N, NEGRI

RM. 2011. Seasonal production of Oithona

nana Giesbrecht, 1893 (Copepoda:

Cyclopoida) in temperate coastal waters off

Argentina. J Plankton Res. 33: 729-740.

THEILACKER G. 1978. Effect of starvation on the

histological and morphological characteristics

of jack mackerel, Trachurus symmetricus, lar-

141

LEONARDUZZI ET AL.: EARLY ANCHOVY STAGES AT EPEA

vae. Fish Bull US. 76: 403-414.

TORQUATO FO, MUELBERT JH. 2014. Horizontal

and vertical distribution of larvae of Engraulis

anchoita (Hubbs & Marini 1935) off

Albardão, Southern Brazil. Pan Am J Aquat

Sci. 9: 154-166.

TWATWA NM, VAN DER LINGEN CD, DRAPEAU L,

MOLONEY CL, FIELD JG. 2005. Characterising

and comparing the spawning habitats of

anchovy Engraulis encrasicolus and sardine

Sardinops sagax in the southern Benguela

upwelling ecosystem. Afr J Mar Sci. 27: 487-

499.

VIÑAS MD, RAMÍREZ FC. 1996. Gut analysis of

first-feeding anchovy larvae from Patagonian

spawning area in relation to food availability.

Arch Fish Mar Res. 43: 231-256.

VIÑAS MD, NEGRI RM, CEPEDA GD, HERNÁNDEZ

D, SILVA RI, DAPONTE MC, CAPITANIO FL.

2013. Seasonal succession of zooplankton in

coastal waters of the Argentine Sea

(Southwest Atlantic Ocean): prevalence of

classical or microbial food webs. Mar Biol

Res. 9: 371-382.

VIÑAS MD, NEGRI, RM, RAMÍREZ FC,

HERNÁNDEZ D. 2002. Zooplankton assem-

blages and hydrography in the spawning area

of anchovy (Engraulis anchoita) off Rio de la

Plata estuary (Argentina-Uruguay). Mar

Freshwater Res. 53: 1031-1043.

ZARRAD R, ALEMANY F, JARBOUI O, GARCIA A,

AKROUT F. 2012. Comparative characteriza-

tion of the spawning environments of

European anchovy, Engraulis encrasicolus,

and round sardinella, Sardinella aurita

(Actinopterygii: Clupeiformes) in the eastern

coast of Tunisia. Acta Ichthyol Piscat. 42: 9-

19.

142 MARINE AND FISHERY SCIENCES 34 (2): 123-142 (2021)