Connectivity of the sea urchin Diadema mexicanum A. Agassiz, 1863 (Echinoidea, Diadematidae) in the Pacific coast of Costa Rica

Abstract

Diadema mexicanum is essential for controlling algae and maintaining coral dominance on coral reefs. Despite its importance as a key grazing species, little is known about the genetic structure and connectivity of its populations. Molecular markers are particularly sensitive to genetic differences between disjunct populations, providing insight into their resilience to environmental changes. This study seeks to genetically characterize D. mexicanum populations on coral reefs along the Pacific coast of Costa Rica. Sampling took place between May and October 2019. DNA was extracted from each sample, and microsatellite markers were subsequently amplified using primers designed for D. antillarum and Strongylocentrotus nudus. Data analysis was performed using GeneMarker, R Studio, and Structure. The analysis revealed lower genetic diversity than previously reported for these microsatellites, resulting in high inbreeding coefficient values. This could be attributed to several factors, such as high reproductive success variation and null alleles. A weak genetic structure was found among sampling sites, but this structure was independent of the region where samples were collected. No isolation by distance was detected, suggesting genetic connectivity and gene flow within populations. Future studies would benefit from analyzing a wider range of molecular markers and ensuring more equitable sampling across sites.

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91
Recepción 30 septiembre 2024 • Corregido 13 marzo 2025 • Aceptado 13 marzo 2025
DOI: http://dx.doi.org/10.15359/revmar.17-1.5
Rev. Mar. Cost. Vol. 17 (1): 91-115, enero-junio 2025
ISSN: 1659-455X • e-ISSN: 1659-407X
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Connectivity of the sea urchin Diadema mexicanum A.
Agassiz, 1863 (Echinoidea, Diadematidae) in the Pacic
coast of Costa Rica
Conectividad de la población del erizo de mar
Diadema mexicanum A. Agassiz, 1863 (Echinoidea,
Diadematidae) en el Pacíco de Costa Rica
Sofía Carvajal-Rojas1, Laura Brenes-Guillén1,2,3, Kaylen González-Sánchez1,3,
María Isabel Cordón-Krumme3, María Paula Montiel-Barrantes3 & Juan José Alvarado2,3,4*
ABSTRACT
Diadema mexicanum is essential for controlling algae and maintaining coral
dominance on coral reefs. Despite its importance as a key grazing species,
little is known about the genetic structure and connectivity of its populations.
Molecular markers are particularly sensitive to genetic differences between
disjunct populations, providing insight into their resilience to environmental
changes. This study seeks to genetically characterize D. mexicanum populations
on coral reefs along the Pacic coast of Costa Rica. Sampling took place
between May and October 2019. DNA was extracted from each sample, and
microsatellite markers were subsequently amplied using primers designed
for D. antillarum and Strongylocentrotus nudus. Data analysis was performed
using GeneMarker, R Studio, and Structure. The analysis revealed lower genetic
diversity than previously reported for these microsatellites, resulting in high
inbreeding coefcient values. This could be attributed to several factors, such
as high reproductive success variation and null alleles. A weak genetic structure
was found among sampling sites, but this structure was independent of the region
where samples were collected. No isolation by distance was detected, suggesting
1 Centro de Investigación en Biología Celular y Molecular (CIBCM), Universidad de Costa Rica, San José, Costa
Rica, 11501-2060, San José, Costa Rica; laura.brenesguillen@ucr.ac.cr ORCID: https://orcid.org/0000-0002-7185-
4084 ; soa.carvajalrojas@ucr.ac.cr ORCID: https://orcid.org/0009-0000-5121-0591
2 Escuela de Biología, Universidad de Costa Rica, San José, Costa Rica, 11501-2060, San José, Costa Rica; maria.
montielbarrantes@ucr.ac.cr ORCID: https://orcid.org/0000-0002-5945-8396
3 Centro de Investigación en Ciencias del Mar y Limnología (CIMAR), Universidad de Costa Rica, San José, Costa
Rica, 11501-2060, San José, Costa Rica; kaygs95@gmail.com ORCID: https://orcid.org/0000-0002-7208-9302 ;
isa9826@gmail.com ORCID: https://orcid.org/0000-0001-5974-5865; juan.alvarado@ucr.ac.cr ORCID: https://or-
cid.org/0000-0002-2620-9115
4 Centro de Investigación en Biodiversidad y Ecología Tropical (CIBET), Universidad de Costa Rica, San José, Costa
Rica, 11501-2060, San José, Costa Rica.

92 Rev. Mar. Cost. Vol. 17 (1): 91-115, enero-junio 2025
ISSN: 1659-455X • e-ISSN: 1659-407X
DOI: http://dx.doi.org/10.15359/revmar.17-1.5
Sofía Carvajal-Rojas; Laura Brenes-Guillén;
Kaylen González-Sánchez; María Isabel Cordón-Krumme;
María Paula Montiel-Barrantes y Juan José Alvarado
INTRODUCTION
The sea urchin Diadema mex-
icanum A. Agassiz, 1863 (Echino-
dermata: Diadematidae) has a wide
distribution in the Eastern Tropical
Pacic (ETP) (Alvarado et al. 2015a;
Paz-García et al. 2018), inhabiting a
wide variety of environments such as
coral reefs, rocky bottoms, mangrove
roots, seagrass, and sandy bottoms
(Birkeland, 1989). Diadema mexica-
num is predominant in the coral reefs
of the Pacic of Costa Rica (Alvarado
et al. 2015b; Alvarado et al. 2016a;
Alvarado et al. 2018), where they
strongly inuence algal biomass, di-
versity, and community structure, and
genetic connectivity and gene ow within populations. Future studies would
benet from analyzing a wider range of molecular markers and ensuring more
equitable sampling across sites.
Keywords: echinoid, gene ow, genetic markers, microsatellites, population
genetics
RESUMEN
Diadema mexicanum es esencial para el control de algas y el mantenimiento del
dominio coralino en los arrecifes de coral. A pesar de su importancia como especie
clave de pastoreo, se conoce poco sobre la estructura genética y la conectividad
de sus poblaciones. Los marcadores moleculares son particularmente sensibles
a las diferencias genéticas entre poblaciones disjuntas, lo que proporciona
información sobre su resiliencia frente a los cambios ambientales. Este estudio
busca caracterizar genéticamente las poblaciones de D. mexicanum en arrecifes
de coral a lo largo del Pacíco de Costa Rica. El muestreo se realizó entre
mayo y octubre de 2019. Se extrajo ADN de cada muestra y, posteriormente, se
amplicaron los marcadores microsatélites utilizando cebadores diseñados para
D. antillarum y Strongylocentrotus nudus. El análisis de datos se realizó con
GeneMarker, R Studio y Structure. El estudio reveló una diversidad genética
menor que la reportada previamente para estos microsatélites, lo que resulta en
altos valores de coeciente de endogamia. Esto podría atribuirse a varios factores,
incluyendo la alta variación en el éxito reproductivo y la presencia de alelos nulos.
Se encontró una estructura genética débil entre los sitios de muestreo, pero esta
estructura era independiente de la región donde se recolectaron las muestras. No se
detectó aislamiento por distancia, lo que sugiere conectividad genética y un ujo
génico dentro de las poblaciones. Estudios futuros se beneciarían del análisis de
una gama más amplia de marcadores moleculares y de asegurar un muestreo más
equitativo entre los sitios.
Palabras clave: echinoidea, ujo génico, genética de poblaciones, marcadores
genéticos, microsatélites

93
Rev. Mar. Cost. Vol. 17 (1): 91-115, enero-junio 2025
ISSN: 1659-455X • e-ISSN: 1659-407X
DOI: http://dx.doi.org/10.15359/revmar.17-1.5
Connectivity of the sea urchin Diadema mexicanum A. Agassiz, 1863
(Echinoidea, Diadematidae) in the Pacic coast of Costa Rica
Connectivity is essential for the
persistence and resilience of marine
populations, as it facilitates the natu-
ral processes that sustain the health of
marine ecosystems. In the absence of
connectivity, these ecosystems may
become more vulnerable to distur-
bances, experience a loss of genetic di-
versity, and face greater challenges in
terms of recovery and long-term sus-
tainability (Cowen et al. 2007; Cowen
& Sponaugle, 2009). The connectivity
between D. mexicanum populations
could occur through the dispersal of
its pelagic larvae, which can survive
up to 42 days under laboratory condi-
tions (Emlet, 1995).
Molecular markers such as mi-
crosatellites constitute very useful
tools for studying the connectivity be-
tween populations (Amiteye, 2021).
Microsatellites or simple sequence
repeats (SSR) are known for their nu-
merous advantages, including high
polymorphism, evolutionary neutrali-
ty, a high mutation rate, codominance,
multiallelic nature, reproducibility,
and transferability between related
species. These attributes make micro-
satellites a valuable tool for genetic
mapping, population structure analy-
sis, and evolutionary investigations.
They enable the precise discrimination
of genotypes within a population and
offer insights into connectivity among
nearby populations (Vieira et al. 2016).
Microsatellites have been used
to describe different populations of
are key determinants of the carbonate
balance (Alvarado et al. 2015a; Alva-
rado et al. 2016b).
The population density of D.
mexicanum is regulated by factors re-
lated to habitat complexity, the avail-
ability of algae, and the presence of
predators (Alvarado et al. 2016c). In
Costa Rica, the population density of
D. mexicanum has increased follow-
ing El Niño events due to the loss of
coral cover and the subsequent in-
crease in algae, which implies great-
er food availability due to its role as
herbivores. A decrease in the popula-
tion density of D. mexicanum has also
been observed in Marine Protected
Areas (MPAs), likely due to increases
in the abundance of predatory sh that
feed on urchins, keeping their abun-
dance under control (Alvarado & Chi-
riboga, 2008; Alvarado et al. 2012).
Therefore, the population density of
D. mexicanum is closely related to the
environmental conditions of its habi-
tat and the abundance of its predators
(Alvarado & Chiriboga, 2008; Alvara-
do et al. 2012; Alvarado et al. 2015a).
Moreover, to better understand the
communities of this species, it is also
important to study the connectivity
between subpopulations. Given D.
mexicanum’s importance as a key her-
bivore and ongoing alterations to the
ecological and environmental process-
es that determine their abundance, it
is important to study the connectivity
between subpopulations.

94 Rev. Mar. Cost. Vol. 17 (1): 91-115, enero-junio 2025
ISSN: 1659-455X • e-ISSN: 1659-407X
DOI: http://dx.doi.org/10.15359/revmar.17-1.5
Sofía Carvajal-Rojas; Laura Brenes-Guillén;
Kaylen González-Sánchez; María Isabel Cordón-Krumme;
María Paula Montiel-Barrantes y Juan José Alvarado
echinoderms. For example, they have
been employed in studies of sea cucum-
bers such as Holothuria leucospilota
(Yang et al. 2024) and Apostichopus
japonicus (Dong et al. 2018), sea stars
such as Coscinasterias tenuispina and
Echinaster sepositus (García-Cisneros
et al. 2013), and sea urchins such as
Paracentrotus lividus (Calderón et al.
2009), Arbacia lixula (García-Cisne-
ros et al. 2013), and Strongylocentrotus
droebachiensis. To date, microsatellites
have not been used to study sea urchin
D. mexicanum populations.
Lessios et al. (2001) indicated
that populations of D. mexicanum
in the Galápagos and Cocos Islands
are the same genetically as those in
Panama and Mexico. Lessios et al.
(2001) used mitochondrial DNA as
a molecular marker; however, it has
been demonstrated that microsatel-
lites can detect isolation by distance
when mitochondrial DNA fails to
do so (Teske et al. 2018). The oth-
er molecular marker used by Lessios
et al. (2001) was isozymes. When
compared to microsatellites, it was
observed that the SSRs can more ef-
fectively detect genetic differences
(Becerra & Paredes, 2000).
Given the ecological relevance
of D. mexicanum and the opportuni-
ty to test new molecular techniques
for this species, we genetically cha-
racterized the population of D. mexi-
canum in the coral reefs from the
Pacic coast of Costa Rica using
microsatellites. The goal is to deter-
mine if there is connectivity between
the populations, describing the gene-
tic diversity and structure of the po-
pulations and assessing the genetic
connectivity.
MATERIAL AND METHODS
Sampling sites
The sampling was conducted at
various coral reef locations along the
Pacic coast of Costa Rica between
May and October 2019. Collection
was carried out using SCUBA gear at
depths ranging from 0 to 10 m. Ad-
ditionally, three specimens from the
Museum of Zoology of the Universi-
dad de Costa Rica, collected in Punta
Ulloa, Cocos Island in 2006 and 2011,
were included. The study was divid-
ed into three regions: 1) The oceanic
Cocos Island, 2) the north mainland
Pacic, and 3) the southern mainland
Pacic (Fig. 1).
DNA extraction
DNA extraction was performed
using tissue from the ambulacral feet
stored in 90% alcohol following the
protocol of the NucleoSpin Tissue Kit
(Macherey-Nagel, 2020). The quali-
ty of the extracted DNA was veried
through electrophoresis on a 1% aga-
rose gel, and its concentration was
quantied using a NanoDrop™ 2000
(Thermo Scientic).
Microsatellites (SSR)
A total of 48 sea urchins were
analyzed. There was no report of

95
Rev. Mar. Cost. Vol. 17 (1): 91-115, enero-junio 2025
ISSN: 1659-455X • e-ISSN: 1659-407X
DOI: http://dx.doi.org/10.15359/revmar.17-1.5
Connectivity of the sea urchin Diadema mexicanum A. Agassiz, 1863
(Echinoidea, Diadematidae) in the Pacic coast of Costa Rica
Fig. 1. Sampling locations of individuals of Diadema mexicanum and number
of individuals (n) collected along the Pacic coast of Costa Rica, including two
sites at the oceanic Cocos Island (Manuelita and Punta Ulloa), ve sites in the
northernmost mainland of the Pacic, along the coast of Guanacaste (Northern
Pacic: Bahía Santa Elena, Murciélago Island (MM), Güiri, Playa Blanca,
Matapalo) and three sites along the southernmost mainland of the Pacic
(Southern Pacic: Caño Island, Mogos and Punta Adela)
Fig. 1. Localizaciones de muestreo de individuos de Diadema mexicanum y
número de individuos (n) colectados a lo largo de la costa del Pacíco de Costa
Rica incluyendo: dos sitios en la oceánica Isla del Coco (Manuelita y Punta
Ulloa), cinco sitios en la parte más norte del Pacíco, en la costa de Guanacaste
(Pacíco Norte: Bahía Santa Elena, Isla Murciélago (MM), Güiri, Playa Blanca,
Matapalo) y tres sitios en la parte más sur del Pacíco costarricense (Pacíco
Sur: Isla del Caño, Mogos y Punta Adela)
microsatellite primers specic for
D. mexicanum. Therefore, 10 mi-
crosatellite primers developed for
taxonomically close species, such
as Diadema antillarum (Chandler
et al. 2017) and Strongylocentrotus
nudus (Li & Li, 2008), were chosen
and tested on D. mexicanum. How-
ever, only four out of the ten SSRs
were amplied in D. mexicanum

96 Rev. Mar. Cost. Vol. 17 (1): 91-115, enero-junio 2025
ISSN: 1659-455X • e-ISSN: 1659-407X
DOI: http://dx.doi.org/10.15359/revmar.17-1.5
Sofía Carvajal-Rojas; Laura Brenes-Guillén;
Kaylen González-Sánchez; María Isabel Cordón-Krumme;
María Paula Montiel-Barrantes y Juan José Alvarado
using end-point Polymerase chain
reactions (PCR), and therefore, they
were used in this study. These four
markers were uorescently labeled
with either Applied Biosystems™
6-FAM or NED (Table 1). PCR were
performed following the protocols
specied in the references for each
of the primers (Chandler et al. 2017;
Li & Li, 2008). Briey, for KS03,
KS09 and KS29, the reactions took
place using 1μL DNA, 2μL 10x PCR
buffer, 1.3μL 25mM MgCl2, 1.6μL
10mM dNTPs, 1μL 10μM reverse
primer, 0.3μL 10μM forward prim-
er, 0.2μL DreamTaq DNA Poly-
merase, and 1μL 10mM uorescent
dye. PCRs included an initial dena-
turation step at 94°C for 4 min, 35
cycles at 94°C for 30 s., annealing
at 55°C for 35 s., and 72°C for 45
s., followed by a nal extension pe-
riod at 72°C for 7 min. For SN225,
the PCR contained 0.25 U Dream-
Taq DNA Polymerase 1X PCR buf-
fer (10 mM Tris–HCl, 50 mM KCl,
pH 8.3), 0.2 mM dNTP mix, 1 uM
of each primer set, 1.5 mM MgCl2
and and 1μL 10mM uorescent dye.
The PCR was performed as follows:
3 min at 94°C; 35 cycles of 1 min at
94°C, annealing for 1 min, 72°C for
1 min per cycle; followed by 5 min at
72°C. The PCR reactions were per-
formed in a Veriti™ Thermal Cycler,
96-well Fast. The PCR products were
analyzed by capillary electrophore-
sis using an Applied Biosystems®
Data analysis
Once all the samples were gen-
otyped, the Hardy-Weinberg equilib-
rium test was performed using 1,000
replicates for the Monte Carlo pro-
cedure (Guo & Thompson, 1992).
Linkage disequilibrium (LD) was
evaluated by calculating the Stan-
dardized Index of Association rbarD
for the SSR (Kamvar et al. 2015).
Statistical signicance of LD was
assessed by conducting a one-sided
permutation test, where the observed
LD values were compared against
those generated from 999 simulated
datasets. The percentage of null al-
leles was calculated using the Free-
NA software with 10000 replicates
(Chapuis & Estoup, 2007). To assess
the genetic diversity, observed (Ho)
and expected (He) heterozygosity, al-
lelic richness (AR), number of pri-
vate alleles, and number of effective
alleles (Ne) were estimated per locus,
location, and region. The reduction
in individual heterozygosity within
the locations and regions was calcu-
lated through the inbreeding coef-
cient (Fis). To investigate if there is
a genetic structure in the established
regions (i.e., if they behave as iso-
lated populations), two tests were
conducted: 1) Nei´s genetic differ-
entiation (Gst) and 2) a discriminant
analysis of principal components
ABI3130 and genotyped with the
software GeneMarker® 2.6.4 (Soft
Genetics, 2021).

97
Rev. Mar. Cost. Vol. 17 (1): 91-115, enero-junio 2025
ISSN: 1659-455X • e-ISSN: 1659-407X
DOI: http://dx.doi.org/10.15359/revmar.17-1.5
Connectivity of the sea urchin Diadema mexicanum A. Agassiz, 1863
(Echinoidea, Diadematidae) in the Pacic coast of Costa Rica
Table 1. Sequence of the Forward (F) and Reverse (R) primers, uorescent dyes, species in which the primers
were designed, and reference of the article of each primer used in this investigation. ND= No data available in the
original publication
Cuadro 1. Secuencia de los cebadores Forward (F) y Reverse (R), colorantes uorescentes, especies en las que
se diseñaron los cebadores y referencia del artículo de cada cebador utilizado en esta investigación. ND= No hay
información disponible en la publicación de referencia
Locus Primer sequences (5´-3´) Ta (°C) Dyes Species Repeat motif Size range (bp) Reference
KS03 F:
TGTAAAACGACGGCCAGTCTTCCCGTTTTGTTGCATTT
57 6-Fam Diadema
antillarum
ND ND Chandler et al.
2017
R: CCGAACATGGATCCCTAAAA
KS09 F:
TGTAAAACGACGGCCAGTTTTGCCAATGAGCTGTCAAG
62 NED
R: CCACCTCAACCACATCTGAG
KS29 F:
TGTAAAACGACGGCCAGTCTTCCCGTTTTGTTGCATTT
62 6-Fam
R: AGTTGGAAGGGACGATGTTG
SN225 F: 5’TATTTTGGTTCCGATTTCA 3’ 6-Fam Strongylocentrotus
nudus
(GA)10 253-261 Li & Li 2008
R: 5’TCGTGTCAAGTCGCTGTC 3’ 49

98 Rev. Mar. Cost. Vol. 17 (1): 91-115, enero-junio 2025
ISSN: 1659-455X • e-ISSN: 1659-407X
DOI: http://dx.doi.org/10.15359/revmar.17-1.5
Sofía Carvajal-Rojas; Laura Brenes-Guillén;
Kaylen González-Sánchez; María Isabel Cordón-Krumme;
María Paula Montiel-Barrantes y Juan José Alvarado
(DAPC) (Jombart et al. 2010). Ad-
ditionally, to estimate genetic differ-
ences between Pacic regions and
sampling location, a global molec-
ular analysis of variance (AMOVA)
was performed. To determine the
presence of genetic isolation among
the sampling sites is associated
with geographical distance, a Man-
tel test was conducted, which uses
geographic distances between col-
lection sites and Nei’s genetic dif-
ferentiation (Gst) (Nei, 1973; Nei &
Chesser, 1983). The mentioned test
and statistics were conducted using
R studio software (R Core Team,
2021), using the following libraries:
poppr (Kamwar et al. 2015), hierf-
stat (Goudet, 2005), adegenet (Jom-
bart & Ahmed, 2011), ade4 (Dray et
al. 2007), mmod (Winter, 2012), and
pegas (Paradis, 2010). To conclude,
a Bayesian-based clustering meth-
od was performed with the program
STRUCTURE v2.3.4 (Pritchard
et al. 2000), to determine the most
likely number of clusters (K) sup-
ported by the data, with 10 runs for
each cluster from 1 to 10 (10 000 it-
erations with 10 000 burn-in period).
StructureSelector program (Li & Li,
2018) was used to process the data
from the previous analysis.
RESULTS
Diversity estimates per molecular
marker
A total of 48 sea urchins were
genotyped with four microsatel-
lite markers; among these, only the
SN225 marker exhibited a signi-
cant deviation from HWE (Table 2);
consequently, this marker was ex-
cluded from analyses of population
strata. Overall, the global null allele
frequency was 9.5%, while the es-
timated frequency was 15%. There
was no evidence of linkage disequi-
librium among the markers (rbarD
= 0.03, P = 0.46). Marker KS03
showed the greater number of alleles
and effective alleles Na = 47 and Ne
= 6.44, while SN225 had the lowest
number of alleles and fewer effec-
tive alleles Na = 18 and Ne = 2.91. All
the SSRs presented a lower observed
heterozygosity than expected (Table
2). The marker with more genetic di-
versity was KS03 Ho= 0.83; on the
other hand, SN225 was the least di-
verse Ho = 0.54. The marker KS29
had the highest heterozygotes decit
(Fis = 0.37), while KS09 had the low-
est (Fis = 0.18).
Diversity estimates per region
Out of the 48 genotyped samples,
32 belong to the North Pacic region,
four to Cocos Island, and 12 to the
South Pacic region. The North Pacif-
ic showed a higher number of alleles

99
Rev. Mar. Cost. Vol. 17 (1): 91-115, enero-junio 2025
ISSN: 1659-455X • e-ISSN: 1659-407X
DOI: http://dx.doi.org/10.15359/revmar.17-1.5
Connectivity of the sea urchin Diadema mexicanum A. Agassiz, 1863
(Echinoidea, Diadematidae) in the Pacic coast of Costa Rica
Table 2. Estimates of genetic diversity and allelic richness per SSR for D. mexicanum collected in three regions
of the Pacic coast of Costa Rica: Number of alleles (Na), number of effective alleles (Ne), heterozygosity
(Ho) observed, heterozygosity expected (He), inbreeding coefcient (Fis), observed (Obs) and estimated (Est)
frequency of null alleles, Hardy-Weinberg equilibrium test, and allelic richness (AR) per region (North Pacic,
South Pacic, and Cocos Island) using the sample size (N) for each region
Cuadro 2. Estimación de la diversidad genética y riqueza alélica por SSR para D. mexicanum colectado en tres
regiones de la costa Pacíca de Costa Rica: Número de alelos (Na), número de alelos efectivos (Ne), heterocigosidad
observada (Ho), heterocigosidad esperada (He), coeciente de endogamia (Fis), frecuencia observada (Obs) y
estimada (Est) de alelos nulos, prueba de equilibrio Hardy-Weinberg y riqueza alélica (RA) por región (Pacíco
Norte, Pacíco Sur e Isla del Coco) utilizando el tamaño de muestra (N) para cada región
North Pacic South Pacic Cocos Island
SSR Na Ne Ho He Fis Null Alelle
Obs
Null Alelle
Est
HWE test N AR N AR N AR
KS03 47 6.44 0.83 0.97 0.23 0.03 0.05 chi2=1102.3589, df=1081,
P >0 .05
31 5.69 12 5.63 4 4.93
KS09 40 5.61 0.73 0.96 0.18 0.05 0.1 chi2=930.9167, df=780,
P > 0.05
30 5.51 12 5.73 3 6
KS29 40 5.64 0.72 0.96 0.37 0.11 0.19 chi2=1023.4341, df=780,
P > 0.05
32 5.57 12 5.62 3 4
SN225 18 2.91 0.54 0.73 0.25 0.16 0.25 chi2=348.184, df=153,
P < 0.05
31 3.28 12 3.98 3 4
Mean 36.25 5.15 0.71 0.91 0.26 0.09 0.15 ---- 31 5 12 5.24 3.25 4.73
SD 12.61 1.54 0.12 0.12 0.08 0.06 0.09 ---- 0.82 1.18 0 0.84 0.5 0.95

100 Rev. Mar. Cost. Vol. 17 (1): 91-115, enero-junio 2025
ISSN: 1659-455X • e-ISSN: 1659-407X
DOI: http://dx.doi.org/10.15359/revmar.17-1.5
Sofía Carvajal-Rojas; Laura Brenes-Guillén;
Kaylen González-Sánchez; María Isabel Cordón-Krumme;
María Paula Montiel-Barrantes y Juan José Alvarado
Na= 64, effective alleles Ne= 22.76 (±
2.95) and private alleles (21 ± 2.86).
The region with the lowest number of
alleles Na= 5 and effective alleles Ne=
4.97 (± 1.01) and private alleles (1.67
± 0.47) was Cocos Island (Table 3).
The South Pacic region pre-
sented the highest genetic diversity
(Ho= 0.80 ± 0.09) and the Cocos Is-
land region had the lowest (Ho = 0.61
± 0.34). Regarding the inbreeding
coefcient, Cocos Island showed the
highest Fis (0.38 ± 0.35) and the South
Pacic the lowest (Fis = 0.18 ± 0.10).
It was found that the region with the
highest allelic richness is the South
Pacic (AR= 5.24 ± 0.84), while the
North Pacic showed the lowest (AR
= 5.00 ± 1.18; Table 2).
Diversity estimates per sampling
location
The sampling location that
showed the highest genetic diversity
was Güiri (Ho = 0.92 ± 0.14), while
Punta Ulloa had the lowest genetic di-
versity (Ho = 0.36 ± 0.48). It was found
that MM had many private alleles (20),
whereas Playa Blanca had the minori-
ty (2). The location with the highest in-
breeding coefcient was Santa Elena
Bay (Fis = 0.35 ± 0.06), while Mogos
presented the lowest (Fis = 0.11 ± 0.18;
Table 3).
Genetic structure
Among the regions, no evi-
dence of genetic structure was found
(GstNei = 0.0563, P ˃ 0.05), where-
as a global small but signicant
structure was detected between the
sampling locations (GstNei = 0.031,
P < 0.05, Table 4). Signicant ge-
netic structure was found among the
sampling sites within regions ac-
cording to AMOVA (Table 5). The
biggest source of variation (80.46%)
comes from differences within the
samples (P < 0.01), followed by
18.31% of variation between the
samples within the locations (P <
0.01) and 2.19% variation is coming
from between the regions (P < 0.01).
According to the DAPC results (Fig.
2), three distinct groups were identi-
ed: 1) Isla del Caño and Matapalo,
2) Mogos, Bahía Santa Elena, Playa
Blanca, and Manuelita and 3) Güiri
and MM Islas Murciélago. The sam-
pling site Punta Adela is entirely sep-
arate from these groups, while Punta
Ulloa is positioned nearby but does
not overlap with any of the groups
mentioned. In addition, the data
showed no evidence of isolation by
geographic distance (P = 0.49) (Fig.
3). Bayesian clustering analyses per-
formed revealed the presence of two
genetic groups across populations (K
= 2, ΔK = 4.63) (Fig. 4). The mean
likelihood values remained low and
showed no signicant improvement
with increasing K, suggesting that
two clusters are the most biological-
ly relevant grouping for the data.

101
Rev. Mar. Cost. Vol. 17 (1): 91-115, enero-junio 2025
ISSN: 1659-455X • e-ISSN: 1659-407X
DOI: http://dx.doi.org/10.15359/revmar.17-1.5
Connectivity of the sea urchin Diadema mexicanum A. Agassiz, 1863
(Echinoidea, Diadematidae) in the Pacic coast of Costa Rica
Table 3. Genetic diversity estimates for D. mexicanum across regions (North Pacic, South Pacic, and Cocos
Island) and sampling locations: Number of individuals (n), percentage and standard deviation of number of alleles
(Na), number of effective alleles (Ne), observed heterozygosity (Ho), expected heterozygosity (He), inbreeding
coefcient (Fis), private alleles, and observed (Obs) and estimated (Est) frequencies of null alleles
Cuadro 3. Estimaciones de la diversidad genética de D. mexicanum en las distintas regiones (Pacíco Norte,
Pacíco Sur e Isla del Coco) y lugares de muestreo: Número de individuos (n), porcentaje y desviación estándar
del número de alelos (Na), número de alelos efectivos (Ne), heterocigosidad observada (Ho), heterocigosidad
esperada (He), coeciente de endogamia (Fis), alelos privados, y frecuencias observadas (Obs) y estimadas (Est)
de alelos nulos
Na Ne Ho He Fis
Private
Alleles Location n Na Ne Ho He Fis
Private
Alleles
Null
Alelle
Obs
Null
Alelle
Est
North
Pacic
64 22.76 ± 2.95 0.76 ± 0.07 0.97 ± 0.05 0.21 ± 0.06 21 ± 2.86 Santa Elena
Bay 7 31 6.34 ± 3.51 0.63 ± 0.06 0.98 ±0.01 0.35 ± 0.06 11 0 0
Islas
Murciélago
(MM) 9 45 8.66 ± 3.10 0.70 ± 0.13 1 ± 0.02 0.27 ± 0.12 20 0.04 0.14
Güiri 4 21 4.72 ± 2.01 0.92 ± 0.14 0.94 ± 0.02 0.30 ± 0.17 5 0 0.24
Playa Blanca 2 10 2.42 ± 1.26 0.83 ± 0.29 --- --- 2 0.17 0.17
Matapalo 10 48 9.19 ± 4.77 0.83 ± 0.21 1 ± 0.03 0.13 ± 0.19 18 0.56 0.61
South
Pacic
19 15.75 ± 0.84 0.80 ± 0.09 0.98 ± 0.008 0.18 ± 0.10 6 ± 2.62 Caño Island 5 27 5.80 ± 2.48 0.80 ± 0.2 0.97 ± 0.01 0.17 ± 0.21 8 0 0.05
Mogos 4 24 5.33 ± 0.00 0.83 ± 0.14 0.9 ± 0.02 0.11 ± 0.18 6 0 0
Punta Adela 3 21 4.88 ± 0.75 0.78 ± 0.19 1 ± 0 0.22 ± 0.19 8 0 0.08
Cocos
Island
5 4.97 ± 1.01 0.61 ± 0.34 1 ± 0.00 0.38 ± 0.35 1.67 ±
0.47
Manuelita
Coral Garden 2 12 2.73 ± 0.98 0.67 ± 0.29 1 ± 0 0.33 ± 0.29 3 0 0
Punta Ulloa 2 8 1.92 ± 0.69 0.50 ± 0.5 --- --- 4 0.13 0.28

102 Rev. Mar. Cost. Vol. 17 (1): 91-115, enero-junio 2025
ISSN: 1659-455X • e-ISSN: 1659-407X
DOI: http://dx.doi.org/10.15359/revmar.17-1.5
Sofía Carvajal-Rojas; Laura Brenes-Guillén;
Kaylen González-Sánchez; María Isabel Cordón-Krumme;
María Paula Montiel-Barrantes y Juan José Alvarado
Table 4. Genetic distance matrix based on Nei’s Gst among the sampling sites of the sea urchin D. mexicanum
from 10 sampling sites along the Pacic coast: North Pacic (PN), South Pacic (PS), and Cocos Island (IC)
Cuadro 4. Matriz de distancias genéticas según Gst de Nei entre los sitios de muestreo del erizo de mar D.
mexicanum provenientes de 10 sitios de muestreo a lo largo de la costa pacíca: Pacíco Norte (PN), Pacíco Sur
(PS) y la Isla del Coco (IC)
PN_PlayaBlanca
Bahía Culebra
PN_Bahía
Santa Elena
PS_Isla
del Caño
IC_Manuelita
Coral Garden
IC_Punta
Ulloa
PN_Islas
Murciélago (MM)
PS_Mogos
Golfo Dulce
PN_Matapalo
Guanacaste
PS_Punta Adela
Golfo Dulce
PN_Güiri
Bahía Culebra
PN_Playa Blanca
Bahia Culebra
0 0.023 0.024 0.033 0.104 0.028 0.018 0.025 0.011 0.031
PN_Bahía Santa
Elena
0.023 0 0.013 0.038 0.075 0.016 0.014 0.014 0.025 0.022
PS_Isla del Caño 0.024 0.013 0 0.028 0.072 0.022 0.03 0.011 0.019 0.022
IC_Manuelita Coral
Garden IC
0.033 0.038 0.028 0 0.125 0.017 0.02 0.03 0.04 0.006
IC_Punta Ulloa IC 0.104 0.075 0.072 0.125 0 0.083 0.105 0.088 0.097 0.101
PN_Islas Murciélago
(MM)
0.028 0.016 0.022 0.017 0.08 0 0.008 0.016 0.017 0.009
PS_Mogos Golfo
Dulce
0.018 0.014 0.03 0.02 0.1 0.008 0 0.022 0.027 0.015
PN_Matapalo
Guanacaste
0.025 0.014 0.011 0.03 0.09 0.016 0.022 0 0.019 0.016
PS_Punta Adela
Golfo Dulce
0.011 0.025 0.019 0.04 0.1 0.017 0.027 0.019 0 -0.002
PN_Güiri Bahia
Culebra
0.031 0.022 0.022 0.006 0.1 0.009 0.015 0.016 -0.001 0

103
Rev. Mar. Cost. Vol. 17 (1): 91-115, enero-junio 2025
ISSN: 1659-455X • e-ISSN: 1659-407X
DOI: http://dx.doi.org/10.15359/revmar.17-1.5
Connectivity of the sea urchin Diadema mexicanum A. Agassiz, 1863
(Echinoidea, Diadematidae) in the Pacic coast of Costa Rica
Table 5. Analysis of molecular variance AMOVA of 48 samples of D. mexicanum from 10 sampling sites within
3 regions of the Pacic coast of Costa Rica obtained with four SSRs
Cuadro 5. Análisis de varianza molecular AMOVA de 48 muestras de D. mexicanum provenientes de 10 sitios de
muestreo dentro de 3 regiones de la costa pacíca de Costa Rica obtenidas con cuatro SSRs
Source of variation d.f. Sum of squares Variance components Percentage of variation phi values p value
Between regions 2 6.67 -0.03 -0.96 0.2 0.96
Between locations within regions 6 24.23 0.06 2.19 0.19 0.003
Between samples within locations 34 116.22 0.53 18.31 0.02 0.0009
Within samples 43 101 2.35 80.46 -0.01 0.0009
Total 85 248.12 2.92 100 ---

104 Rev. Mar. Cost. Vol. 17 (1): 91-115, enero-junio 2025
ISSN: 1659-455X • e-ISSN: 1659-407X
DOI: http://dx.doi.org/10.15359/revmar.17-1.5
Sofía Carvajal-Rojas; Laura Brenes-Guillén;
Kaylen González-Sánchez; María Isabel Cordón-Krumme;
María Paula Montiel-Barrantes y Juan José Alvarado
Fig. 2. DAPC analysis using sampling locations for D. mexicanum in the Pacic
of Costa Rica as prior populations. Three distinct groups were identied based
on overlap: 1) Isla del Caño and Matapalo, 2) Mogos, Bahía Santa Elena, Playa
Blanca, and Manuelita, and 3) Güiri and MM Islas Murciélago. Punta Adela is
entirely separate from these groups, while Punta Ulloa is positioned nearby but
does not overlap with any of them
Fig. 2. Análisis DAPC utilizando los sitios de muestreo de D. mexicanum en el
Pacíco de Costa Rica como poblaciones previas. Se identicaron tres grupos
distintos basados en el traslape: 1) Isla del Caño y Matapalo, 2) Mogos, Bahía
Santa Elena, Playa Blanca y Manuelita, y 3) Güiri y MM Islas Murciélago.
Punta Adela está completamente separada de estos grupos, mientras que Punta
Ulloa se encuentra cerca, pero no se traslapa con ninguno de ellos

105
Rev. Mar. Cost. Vol. 17 (1): 91-115, enero-junio 2025
ISSN: 1659-455X • e-ISSN: 1659-407X
DOI: http://dx.doi.org/10.15359/revmar.17-1.5
Connectivity of the sea urchin Diadema mexicanum A. Agassiz, 1863
(Echinoidea, Diadematidae) in the Pacic coast of Costa Rica
Fig. 3. Isolation by distance plot. Pairwise relationship between estimated genetic
distance and geographic distance between the different sampling locations (km) of
D. mexicanum. The color represents different correlation densities of genetic and
geographic distances (red = high density, blue = low density). No pattern of data
dispersion shows that the longer the distance, the greater the genetic difference.
Also, the Mantel test does not show a signicant relationship between the genetic
distance and the geographical distance for these samples (P > 0.05)
Fig. 3. Gráca de aislamiento por distancia. Relación por pares entre la distancia
genética estimada y la distancia geográca entre las diferentes ubicaciones de
muestreo (km) de D. mexicanum. El color representa diferentes densidades
de correlación de las distancias genéticas y geográcas (rojo = alta densidad,
azul = baja densidad). No existe un patrón de dispersión de datos que muestre
que cuanto mayor sea la distancia, mayor será la diferencia genética. Además,
la prueba de Mantel no muestra una relación signicativa entre la distancia
genética y la distancia geográca para estas muestras (P > 0.05)

106 Rev. Mar. Cost. Vol. 17 (1): 91-115, enero-junio 2025
ISSN: 1659-455X • e-ISSN: 1659-407X
DOI: http://dx.doi.org/10.15359/revmar.17-1.5
Sofía Carvajal-Rojas; Laura Brenes-Guillén;
Kaylen González-Sánchez; María Isabel Cordón-Krumme;
María Paula Montiel-Barrantes y Juan José Alvarado
Fig. 4. Inferences of the number of
genetic groups (K) based on Bayesian
analysis in STRUCTURE with 10 runs
for each cluster from 1 to 10 (10,000
iterations with 10,000 burn-in periods)
Fig. 4. Inferencias del número grupos
genéticos (K) según análisis Bayesiano
en STRUCTURE con 10 runs para
cada cluster 1 to 10 (10 000 iteraciones
con períodos de 10 000 burn-in)
DISCUSSION
Genetic diversity
Among the SSR markers ana-
lyzed, KS03, KS09, and KS29 exhib-
ited lower heterozygosity, with KS03
showing the highest value. Both re-
sults are contrary to Chandler’s nd-
ings (2017). For marker SN225, this
study reports higher heterozygosity
compared to Li & Li (2008); howev-
er, it was the only SSR that did not
meet Hardy-Weinberg equilibrium.
Correspondingly, SN225, as in Li &
Li (2008), also exhibited the highest
estimated null allele frequency, fol-
lowed by KS29. The success of SSR
cross-amplication from markers de-
veloped for other species is related to
the evolutionary closeness between
the species (Steinkellner et al. 1997).
Marker SN225 was originally devel-
oped for the sea urchin Strongylocen-
trotus nudus, which is less related to
D. mexicanum than D. antillarum, the
species for which the KS markers were
designed. The presence of null alleles
can underestimate population diversi-
ty and bias genetic structure analyses
(Chapuis & Estoup, 2007). As such,
developing species-specic markers
for the study organism is crucial. No
evidence of linkage disequilibrium
(LD) was found using the standardized
index of association (rbarD) for the
SSR markers. This supports the null
hypothesis of recombination occurring
across all loci and between popula-
tions (Kamvar et al. 2015), suggesting
that alleles from these markers are not
associated and should not inuence
the data analysis. The average allelic
richness values show a general trend
where the South Pacic population
presents the highest genetic diversity,
followed by North Pacic and Co-
cos Island. Allelic richness is a more
sensitive measure than heterozygosi-
ty for detecting reductions in genetic
diversity, as it is directly affected by
genetic drift events and bottlenecks

107
Rev. Mar. Cost. Vol. 17 (1): 91-115, enero-junio 2025
ISSN: 1659-455X • e-ISSN: 1659-407X
DOI: http://dx.doi.org/10.15359/revmar.17-1.5
Connectivity of the sea urchin Diadema mexicanum A. Agassiz, 1863
(Echinoidea, Diadematidae) in the Pacic coast of Costa Rica
(Greenbaum et al. 2014). In marine
populations, connectivity and gene
ow can inuence the distribution of
genetic diversity. The lower allelic
richness observed for D. mexicanum
in Cocos Island could be related to its
geographic isolation and reduced gene
ow with continental populations.
Across all regions and loca-
tions, observed heterozygosity was
consistently lower than expected het-
erozygosity, which is consistent with
the high inbreeding coefcient (Fis)
values obtained. While it is common
to nd higher levels of local retention
than dispersal, such a decit in het-
erozygotes typically should not result
in high inbreeding if populations are
genetically homogeneous. This sug-
gests that the populations might be
experiencing a degree of isolation or
could be very small in size. Addison
and Hart (2005) suggest that such a
decit in heterozygotes can occur in
planktonic larvae due to factors such
as the Wahlund effect, the presence of
null alleles (commonly observed in
free-spawning echinoderms), and high
variance in reproductive success. Sim-
ilarly, Hedgecock (1994) hypothesized
that elevated inbreeding coefcients in
marine free spawners could result from
their inherently high variance in repro-
ductive success. In this study, the low
levels of genetic structure observed
across regions and locations suggest
that the Wahlund effect may be at
play, and geographic distance or small
population sizes could also inuence
these results. Furthermore, null alleles
detected across all sampling sites and
the potential combined effects of high
reproductive variance could also ex-
plain these patterns.
As demonstrated by Alvarado
et al. (2016c), D. mexicanum occurs
at intermediate densities in the ETP, a
critical factor for reproduction in this
species. The Allee effect is particularly
relevant in free-spawning organisms
like D. mexicanum, where changes in
population density can signicantly
impact reproductive success. At low
densities, mate or sperm limitation can
occur, while at high densities, poly-
spermy and increased competition
for mates and resources may reduce
tness (Levitan, 2012). Additionally,
reproduction in this species is closely
linked to spatial and temporal oceano-
graphic processes that inuence gonad
maturation, spawning, fertilization,
larval survival, and recruitment (He-
dgecock, 1994). It is known that D.
mexicanum aligns its spawning period
with environmental conditions, typ-
ically between April and November
(Lessios, 1981; Olivares-González,
1986). This period is further shaped by
oceanic dynamics and currents, which
play a crucial role in larval survival
(Ruiz-Bravo, 2013). Also, in Cocos Is-
land, no synchrony has been observed
hence organisms in all gametogenic
stages can be found (Pearse, 1968).

108 Rev. Mar. Cost. Vol. 17 (1): 91-115, enero-junio 2025
ISSN: 1659-455X • e-ISSN: 1659-407X
DOI: http://dx.doi.org/10.15359/revmar.17-1.5
Sofía Carvajal-Rojas; Laura Brenes-Guillén;
Kaylen González-Sánchez; María Isabel Cordón-Krumme;
María Paula Montiel-Barrantes y Juan José Alvarado
Genetic structure
The results indicate a small but
signicant genetic structure, with the
main sources of variation arising from
within samples and within and be-
tween locations. However, no isolation
by distance was detected, despite the
geographical separation between loca-
tions along the Pacic coast and those
on Cocos Island. The DAPC analysis
further revealed that some locations
form groups, but these are independent
of the Pacic region to which they be-
long. Additionally, the results of the
Bayesian analysis suggest that all sam-
ples can be grouped into two clusters.
This implies a high level of connectiv-
ity, likely driven by gene ow and the
presence of structure, which could in-
dicate that the existing ow is not uni-
form. These ndings align with those
of Lessios et al. (2001), who, using
allozymes and mitochondrial DNA,
determined that D. mexicanum popu-
lations in the Galapagos Islands and
Cocos Island are genetically indistin-
guishable from Panama and Mexico.
The AMOVA reveals that most
genetic variation (80.46%) occurs
within individual samples, with only a
small amount attributed to differences
between regions and locations. This
suggests a high level of genetic homo-
geneity between broader regions, but
more variation exists within specif-
ic sampling sites. The DAPC further
supports this nding by showing no
differences between regions but clear
differences between sampling sites,
with Punta Adela (Golfo Dulce) ap-
pearing the most distinct. Golfo Dulce,
with its four major rivers owing into
the sea, presents a challenging envi-
ronment for coral reef development
(Cortés, 1990). These unique condi-
tions may reduce genetic connectivity,
as variations in habitat conditions can
impact the tness of dispersing indi-
viduals (Hendry, 2004).
Sampling sites from the south-
ern region, such as Mogos, and the
North Pacic region, including Santa
Elena Bay, Playa Blanca, and Cocos
Island, are grouped together, indicat-
ing high connectivity among these lo-
cations. Finally, we observe that Isla
del Caño, located in the South Pacic,
is grouped with Matapalo, which are
not particularly close sites. In contrast,
the sites of Güiri and MM, which are
closer to each other, also group togeth-
er, suggesting the presence of genetic
ow and high connectivity between
these populations. However, to obtain
more robust conclusions and explain
the presence of group populations that
are difcult to explain biologically, it
is essential to increase the sampling
size to enhance the statistical power
and accuracy (Puechamaille, 2016).
The circulation of the Golfo
Dulce is very slow, primarily due to
its basin’s shape and geographic posi-
tion (Quesada-Alpízar & Morales-Ra-
mírez, 2004; Svendsen et al. 2006).
During the dry season (January-May),

109
Rev. Mar. Cost. Vol. 17 (1): 91-115, enero-junio 2025
ISSN: 1659-455X • e-ISSN: 1659-407X
DOI: http://dx.doi.org/10.15359/revmar.17-1.5
Connectivity of the sea urchin Diadema mexicanum A. Agassiz, 1863
(Echinoidea, Diadematidae) in the Pacic coast of Costa Rica
the lack of rainfall results in the Gulf
lacking an internal engine to drive
water movement, which causes the
waters to remain stagnant for longer
periods. Additionally, at this time of
year, the Intertropical Convergence
Zone (ITCZ) shifts southward, weak-
ening the Costa Rican Coastal Current
(CRCC), which ows from south to
north (Wyrtki, 1965; Brenes & Leon,
1988). By May, the trade winds begin
to weaken, allowing the ITCZ to move
northward, thus favoring the intensi-
cation of the CRCC. The dynamics
of these currents and related oceano-
graphic and atmospheric factors help
explain the connectivity between pop-
ulations along the coast, as the CRCC
facilitates the potential movement of
larvae from south to north, connecting
Golfo Dulce with the North Pacic of
Costa Rica. Furthermore, during the
dry season, coastal upwelling intensi-
es, driving water from north to south
(Amador et al. 2016; Fallas & Ovie-
do, 2003), which maintains high con-
nectivity between areas as close as the
Murcielago Islands and Culebra Bay.
Although Cocos Island is located 500
km off the coast, it is inuenced by
the North Equatorial Countercurrent
(NECC), which moves water from
west to east, from the island toward
the continent. During the dry season,
this current weakens, and the ow
from east to west becomes more prom-
inent (Wyrtki, 1965; Lizano, 2006;
Lizano, 2007; Amador et al. 2016).
These ocean currents enhance the con-
nection between Cocos Island and the
mainland. The isolation of Punta Ad-
ela in the analysis may be attributed
to its location in the inner eastern part
of Golfo Dulce, where larval retention
may be higher and movement to other
regions is limited. In contrast, Mogos,
located in the northern inner part of the
Gulf near several rivers, may experi-
ence greater water movement during
the rainy season.
Furthermore, species with resis-
tant larvae such as those of D. mexi-
canum that can survive up to 42 days
(under laboratory conditions) (Emlet,
1995) are expected to maintain this
relatively panmictic population across
large geographical scales (Binks et al.
2011). This can result in a widespread
dispersion potential. As mentioned be-
fore, oceanographic currents may be
an important contributor in facilitat-
ing the transport of larvae (Díaz et al.
2018). Cocos Island exhibits different
oceanic dynamics throughout the year.
During the rst quarter, an anticyclon-
ic circulation is identied, centered
slightly south of the island. The inten-
sity of this current is evident along the
northern edge of the current, reaching
the coast of Costa Rica. In the second
quarter, the circulation pattern remains
the same, but the current intensies in
a northeast direction due to the arrival
of the NECC. By the third quarter, the
NECC is well established around Co-
cos Island, owing eastward. Finally,

110 Rev. Mar. Cost. Vol. 17 (1): 91-115, enero-junio 2025
ISSN: 1659-455X • e-ISSN: 1659-407X
DOI: http://dx.doi.org/10.15359/revmar.17-1.5
Sofía Carvajal-Rojas; Laura Brenes-Guillén;
Kaylen González-Sánchez; María Isabel Cordón-Krumme;
María Paula Montiel-Barrantes y Juan José Alvarado
in the fourth quarter, the current behav-
ior remains like the previous quarter,
but the NECC reaches its maximum
intensity further east, reaching the
Costa Rican coast (Lizano, 2008).
The upwelling phenomenon that
reaches the North Pacic of Costa Rica
between December and April causes
a marked difference in biological pro-
ductivity (Alfaro et al. 2012; Fernán-
dez-García et al. 2012). As observed
in the DAPC, some sampling locations
that experience upwelling are grouped,
suggesting possible connectivity due
the inuence of the winds and currents
characteristic of upwelling seasons.
Additionally, it has been established
that D. mexicanum reproduces between
April and November, with reproduc-
tion inuenced by winds currents and
temperature. In upwelling areas, es-
pecially in the north Pacic it spawns
just before the event to ensure that the
currents do not disrupt larval settlement
and movement (Alvarado et al. 2015a;
Benítez-Villalobos et al. 2015).
CONCLUSION
The species D. mexicanum has
been ecologically well-studied in Costa
Rica; however, there is a gap in gene-
tic studies related to this keystone sea
urchin. Through this research, we have
studied the genetic diversity and connec-
tivity of the D. mexicanum population
in the Pacic of Costa Rica, generating
novel results. We found that cross-am-
plifying microsatellite primers created
for species related to D. mexicanum
was advantageous in terms of cost and
time. Our results suggest that, although
there is a slight genetic structure along
the Pacic coast of Costa Rica, eviden-
ce of connectivity and gene ow is also
present. We consider that these ndings
are due to the characteristics of this spe-
cies’ larvae combined with the different
currents that maintain our sampling lo-
cations connected. For future studies,
we recommend increasing the number
of SSR markers and ensuring a more
uniform sample size across locations to
enhance the robustness of genetic analy-
ses. Additionally, incorporating samples
from the Central Pacic region would
provide a more comprehensive unders-
tanding of this species population dyna-
mics. A more balanced sampling effort
could lead to more representative and re-
liable conclusions about D. mexicanum
connectivity and genetic diversity.
ACKNOWLEDGMENTS
We thank the Centro de Investi-
gaciones en Ciencias del Mar y Lim-
nología (CIMAR), the Laboratorio
de Genética y Biología Molecular de
Organismos Acuáticos; the Escuela de
Biología and the Laboratorio de Ge-
nética Humana Molecular, especially
Adriana Rojas and Andrea Ramírez.
We also want to thank all the people

111
Rev. Mar. Cost. Vol. 17 (1): 91-115, enero-junio 2025
ISSN: 1659-455X • e-ISSN: 1659-407X
DOI: http://dx.doi.org/10.15359/revmar.17-1.5
Connectivity of the sea urchin Diadema mexicanum A. Agassiz, 1863
(Echinoidea, Diadematidae) in the Pacic coast of Costa Rica
involved in the collection of the orga-
nisms. This project was registered and
funded by the Vice-Rectorate of Re-
search of the University of Costa Rica
under the code B9084. We are grateful
to the reviewers of the paper who im-
proved it and to Andrew Sellers for his
language corrections and comments.
REFERENCES
Addison, J. A. & Hart, M.W. (2005). Spawn-
ing, copulation and inbreeding co-
efcients in marine invertebrates.
Biol. Lett., 1(4), 450-453. https://doi.
org/10.1098/rsbl.2005.0353
Alfaro, E. J., Cortés, J., Alvarado, J. J.,
Jiménez, C., León, A., Sánchez-Nogu-
era, C., Nivia-Ruiz, J. & Ruiz, E.
(2012). Clima y temperatura sub-su-
percial del mar en Bahía Culebra,
Golfo de Papagayo, Costa Rica. Rev.
Biol. Trop., 60(S2), 159-171. https://
doi.org/10.15517/rbt.v60i2.20000
Alvarado, J. J. & Chiriboga, A. (2008). Distri-
bución y abundancia de los equinoder-
mos de las aguas someras en la Isla del
Coco, Costa Rica (Pacico Oriental).
Rev. Biol. Trop., 56 (S2), 99-111.
Alvarado J. J., Cortés, J. & Reyes-Bonilla, H.
(2012). Reconstruction of Diadema
mexicanum A. Agassiz, 1863 bioero-
sion impact on three Costa Rican Pacif-
ic coral reefs. Rev. Biol. Trop., 60(S2),
121-132. https://doi.org/10.15517/rbt.
v60i2.19975
Alvarado, J. J., Reyes-Bonilla, H. & Bení-
tez-Villalobos, F. (2015a). Diadema
mexicanum, erizo de mar clave en los
arrecifes coralinos del Pacíco Tropical
Oriental: lo que sabemos y perspectiv-
as futuras (Diadematoida: Diademati-
dae). Rev. Biol. Trop., 63(S2), 135-157.
Alvarado, J. J., Beita, A., Mena, S., Fernán-
dez-García, C. & Guzmán, A. G.
(2015b). Ecosistemas coralinos del
Área de Conservación Osa, Costa Rica:
análisis estructural y necesidades de
conservación. Rev. Biol. Trop., 63(S1),
219-259. https://doi.org/10.15517/rbt.
v63i1.23105
Alvarado, J. J., Beita, A., Mena, S., Fernán-
dez-García, C., Guzmán, A. G. & Cortés,
J. (2016a). Ecosistemas coralinos del
Parque Nacional Isla del Coco, Costa
Rica: análisis estructural y temporal. Rev.
Biol. Trop., 64(S1), 153-175. https://doi.
org/10.15517/rbt.v64i1.23423
Alvarado, J. J., Cortés, J., Guzman, H. &
Reyes-Bonilla, H. (2016b). Bioerosion
by the sea urchin Diadema mexicanum
along Eastern Tropical Pacic coral
reefs. Mar. Ecol., 37(5), 1088-1102.
https://doi.org/10.1111/maec.12372
Alvarado, J. J., Cortés, J., Guzman, H. &
Reyes-Bonilla, H. (2016c). Density,
size, and biomass of Diadema mexica-
num (Echinoidea) in Eastern Tropical
Pacic coral reefs. Aqua. Biol., 24(3),
151-161. https://doi.org/10.3354/
ab00645
Alvarado, J. J., Beita-Jiménez, A., Mena, S.,
Fernández-García, C., Cortés, J., Sán-
chez-Noguera, C., … & Guzmán-Mora,
A. G. (2018). Cuando la conservación
no puede seguir el ritmo del desarrol-
lo: Estado de salud de los ecosiste-
mas coralinos del Pacíco Norte de
Costa Rica. Rev. Biol. Trop., 66(S1),
S280-S308. https://doi.org/10.15517/
rbt.v66i1.33300
Amador, J. A., Rivera, E. R., Durán-Quesada,
A. M., Mora, G., Sáenz, F., Calderón,
B. & Mora, N. (2016). The eastern-
most tropical Pacic. Part I: A cli-
mate review. Rev. Biol. Trop., 64(S1),
1-22. https://doi.org/10.15517/rbt.
v64i1.23407

112 Rev. Mar. Cost. Vol. 17 (1): 91-115, enero-junio 2025
ISSN: 1659-455X • e-ISSN: 1659-407X
DOI: http://dx.doi.org/10.15359/revmar.17-1.5
Sofía Carvajal-Rojas; Laura Brenes-Guillén;
Kaylen González-Sánchez; María Isabel Cordón-Krumme;
María Paula Montiel-Barrantes y Juan José Alvarado
Amiteye, S. (2021). Basic concepts and
methodologies of DNA marker sys-
tems in plant molecular breeding.
Heliyon, 7(10), e08093. https://doi.
org/10.1016/j.heliyon.2021.e08093
Becerra, V. & Paredes, M. (2000). Uso
de marcadores bioquímicos y mo-
leculares en estudios de diversi-
dad genética. Agricul. Téc., 60(3),
270-281. http://dx.doi.org/10.4067/
S0365-28072000000300007
Benitez Villalobos, F., Avila-Poveda, O. H.,
Díaz-Martínez, J. P. & Bravo-Ruiz, A.
(2015). Gonad development stages and
reproductive traits of Diadema mexi-
canum (Echinodermata: Echinoidea)
from Oaxaca, Mexico. Invert. Reprod.
Develop., 59, 237-249. https://doi.org/
10.1080/07924259.2015.1108935
Binks, R. M., Evans, J. P., Prince, J. & Kenning-
ton, W. J. (2011). Fine-scale patterns of
genetic divergence within and between
morphologically variable subspecies
of the sea urchin Heliocidaris eryth-
rogramma (Echinometridae). Biol. J.
Linn. Soc., 103(3), 578-592. https://doi.
org/10.1111/j.1095-8312.2011.01663.x
Birkeland, C. (1989). The inuence of echi-
noderms on coral-reef communities. In
M. Jangoux & J. M. Lawrence (Eds.),
Echinoderm Studies 3 (pp. 1-79). Neth-
erlands: A. A. Balkema.
Brenes, C. L. & León, S. (1988). Algunos
aspectos físico-químicos del Golfo
Dulce. Ingen. Cien.Quím., 12(1-2),
12-16.
Calderón, I., Turon, X., & Pascual, M.
(2009). Isolation of nine nucle-
ar microsatellites in the common
Mediterranean sea urchin, Paracen-
trotus lividus (Lamarck). Mol. Ecol.
Res., 9(4), 1145-1147. https://doi.
org/10.1111/j.1755-0998.2009.02585.x
Chandler, L. M., Walters, L. J., Sharp, W.
C. & Hoffman, E. A. (2017). Genetic
structure of natural & broodstock pop-
ulations of the long-spined sea urchin
Diadema antillarum. throughout the
Florida Keys. Bull. Mar. Sci., 93(3),
881-889. https://doi.org/10.5343/
bms.216.1101
Chapuis, M. P. & Estoup. A. (2007). Micro-
satellite null alleles and estimation of
population differentiation. Mol. Biol.
Evol., 24(3), 621-631. https://doi.
org/10.1093/molbev/msl191
Cortés, J. (1990). The coral reefs of Golfo
Dulce, Costa Rica: distribution and
community structure. Atoll Res. Bull.,
344, 1-37. https://doi.org/10.5479/
si.00775630.344.1
Cowen, R. K., Gawarkiewicz, G., Pineda,
J., Thorrold, S. R. & Werner, F. E.
(2007). Population connectivity in ma-
rine systems an overview. Oceanogr.,
20(3), 14-21. https://doi.org/10.5670/
oceanog.2007.26
Cowen, R. K. & Sponaugle, S. (2009). Larval
dispersal and marine population con-
nectivity. An. Rev. Mar. Sci., 1, 443-
466. https://doi.org/10.1146/annurev.
marine.010908.163757
Díaz, A., Gerard, K., González-Wevar, C.,
Maturana, C., Féral, J. P., David,
B., Saucède, T. & Poulin, E. (2018).
Genetic structure and demograph-
ic inference of the regular sea urchin
Sterechinus neumayeri (Meissner,
1900) in the Southern Ocean: The role
of the last glaciation. PloS One, 13(6),
e0197611. https://doi.org/10.1371/
journal.pone.0197611
Dong, Z., Chen, Y., Xu, G., Kang, C., Fu, G.,
Chen, B. & Li, J. (2018). Twenty-one
microsatellite loci from sea cucum-
ber Apostichopus japonicus (Selenka,
1867), an endangered species on the
IUCN Red List. 3 Biotech., 8, 1-4.

113
Rev. Mar. Cost. Vol. 17 (1): 91-115, enero-junio 2025
ISSN: 1659-455X • e-ISSN: 1659-407X
DOI: http://dx.doi.org/10.15359/revmar.17-1.5
Connectivity of the sea urchin Diadema mexicanum A. Agassiz, 1863
(Echinoidea, Diadematidae) in the Pacic coast of Costa Rica
Dray, S., Dufour, A. & Chessel, D. (2007). The
ade4 Package - II: Two-Table and K-Ta-
ble Methods. R. News, 7(2), 47-52.
Emlet, R. B. (1995). Developmental mode and
species geographic range in regular sea
urchins (Echinodermata: Echinoidea).
Evol., 49(3), 476-489. https://doi.
org/10.1111/j.1558-5646.1995.tb02280.x
Fallas, J. C. & Oviedo, R. (2003). El clima
en Centroamérica. En J. C. Fallas &
R. Oviedo (Eds.), Fenómenos atmos-
féricos y cambio climático, visión
centroamericana (pp. 70). Costa Rica,
Instituto Meteorológico Nacional.
Fernández-García, C., Cortés, J., Alvarado, J. J.
& Nivia-Ruiz, J. (2012). Physical factors
contributing to the benthic dominance of
the alga Caulerpa sertularioides (Caul-
erpaceae, Chlorophyta) in the upwelling
Bahía Culebra, north Pacic of Costa
Rica. Rev. Biol. Trop., 60(S2), 93-107.
https://doi.org/10.15517/rbt.v60i2.19970
García-Cisneros, A., Valero-Jiménez, C.,
Palacín, C. & Pérez-Portela, R. (2013).
Characterization of thirty-two micro-
satellite loci for three Atlanto-Mediter-
ranean echinoderm species. Conserv.
Gen. Res., 5, 749-753.
Guo, S. W. & Thompson, E. A. (1992). Mon-
te Carlo method for combined segre-
gation and linkage analysis. J. Hum.
Gen., 51, 1111-1126. https://doi.
org/10.1007/978-1-4612-0751-1_2
Goudet, J. (2005). Hierfstat. a pack-
age for R to compute and test hi-
erarchical F-statistics. Mol. Ecol.
Not., 5(1), 184-186. https://doi.
org/10.1111/j.1471-8286.2004.00828.x
Greenbaum, G., Templeton, A. R., Zarmi, Y. &
Bar-David, S. (2014). Allelic richness
following population founding events–a
stochastic modeling framework incor-
porating gene ow and genetic drift.
PloS one, 9(12), e115203. https://doi.
org/10.1371/journal.pone.0115203
Hedgecock, D. (1994). Does variance in
reproductive success limit effective
population sizes of marine organ-
isms. In A. Beaumont (Ed.), Genetics
and evolution of aquatic organisms
(pp. 122-134). United Kingdom:
Chapman and Hall.
Hendry, A. P. (2004). Selection against migrants
contributes to the rapid evolution of eco-
logically dependent reproductive isola-
tion. Evol. Ecol. Res., 6(8), 1219-1236.
Jombart, T. & Ahmed, I. (2011). adegen-
et 1.3-1: new tools for the anal-
ysis of genome-wide SNP data.
Bioinform., 27(21), 3070-307. https://
doi.org/10.1093/bioinformatics/btr521
Jombart, T., Devillard, S. & Balloux, F. (2010).
Discriminant analysis of principal
components: a new method for the
analysis of genetically structured popu-
lations. BMC Genet, 11, 94. https://doi.
org/10.1186/1471-2156-11-94
Kamvar, Z. N., Brooks, J. C. & Grünwald, N.
J. (2015). Novel R tools for analysis
of genome-wide population genetic
data with emphasis on clonality. Front.
Genet. 6, 208. https://doi.org/10.3389/
fgene.2015.00208
Lessios, H. A. (1981). Reproductive pe-
riodicity of the echinoids Diade-
ma and Echinometra on the two
coasts of Panama. J. Exp. Mar. Biol.
Ecol., 50(1), 47-61. https://doi.
org/10.1016/0022-0981(81)90062-9
Lessios, H. A., Kessing, B. D. & Pearse, J. S.
(2001). Population structure and spe-
ciation in tropical seas: global phylo-
geography of the sea urchin Diadema.
Evol., 55(5), 955-975. https://doi.org
/10.1554/0014-3820(2001)055[0955
:PSASIT]2.0.CO;2
Levitan, D. R. (2012). Contemporary evolu-
tion of sea urchin gamete-recognition
proteins: experimental evidence of
density-dependent gamete performance

114 Rev. Mar. Cost. Vol. 17 (1): 91-115, enero-junio 2025
ISSN: 1659-455X • e-ISSN: 1659-407X
DOI: http://dx.doi.org/10.15359/revmar.17-1.5
Sofía Carvajal-Rojas; Laura Brenes-Guillén;
Kaylen González-Sánchez; María Isabel Cordón-Krumme;
María Paula Montiel-Barrantes y Juan José Alvarado
predicts shifts in allele frequencies over
time. Evol., 66(6), 1722-1736. https://doi.
org/10.1111/j.1558-5646.2012.01608.x
Li, J. & Li, Q. (2008). A set of microsatellite
markers for use in the endangered sea
urchin Strongylocentrotus nudus devel-
oped from S. purpuratus ESTs. Cons-
er. Gen., 9(3), 743-745. https://doi.
org/10.1007/s10592-007-9382-3
Li, Y-L. & Liu, J-X. (2018). StructureSelec-
tor: A web based software to select
and visualize the optimal number of
clusters using multiple methods. Mol.
Ecol. Res., 18,176-177. https://doi.
org/10.1111/1755-0998.12719
Lizano, O. G. (2006). Algunas características
de las mareas en la costa Pacíca y Ca-
ribe de Centroamérica. Rev. Cien. Tec-
nol., 24, 51-64.
Lizano, O. G. (2007). Climatología del viento
y el oleaje frente a las costas de Costa
Rica. Rev. Cien. Tecnol., 25(1-2), 43-56.
Lizano, O. G. (2008). Dinámica de aguas alre-
dedor de la Isla del Coco, Costa Rica.
Rev. Biol. Trop., 56(S2), 31-48.
Macherey-Nagel. (2020). NucleoSpin Tis-
sue Kit. https://www.mn-net.com/
nucleomag-tissue-kit-for-dna-purica-
tion-from-cells-and-tissue-744300.4
Nei, M. (1973). Analysis of gene diversity
in subdivided populations. Proc. Nat.
Acad. Sci., 70(12), 3321-3323. https://
doi.org/10.1073/pnas.70.12.3321
Nei, M. & Chesser, R. K. (1983). Estimation of
xation indices and gene diversities. An.
Hum. Genet., 47(3), 253-259. https://
doi.org/10.1111/j.1469-1809.1983.
tb00993.x
Olivares-González, E. (1986). Algunos aspec-
tos sobre la biología del erizo de espina
larga Diadema mexicanum (Echinoidea:
Echinodermata). I. Periodos reproducti-
vos y II. Parasitismo. (Tesis de doctorado
no publicado), Universidad Autónoma
de Baja California Sur, La Paz, México.
Paradis, E. (2010). pegas: an R package
for population genetics with an in-
tegrated-modular approach. Bioin-
form., 26(3), 419-420. https://doi.
org/10.1093/bioinformatics/btp696
Paz-García, D. A., Valencia-Méndez, O.,
Domínguez-Domínguez, O. & Balart,
E. F. (2018). Living on the edge: Di-
adema mexicanum in the upper Gulf
of California. Mar. Biodiv., 48(2),
1261-1264. https://doi.org/10.1007/
s12526-016-0539-5
Pearse, J. S. (1968). Gametogenesis and re-
production in several abyssal and shal-
low water echinoderms of the Eastern
Tropical Pacic. Stanford Oceanogr.
Exp. Cruise, 20, 225-234.
Pritchard, J. K., Stephens, M. & Donnelly, P.
(2000). Inference of population struc-
ture using multilocus genotype data.
Genetics, 155(2), 945-959. https://doi.
org/10.1093/genetics/155.2.945
Puechmaille, S. J. (2016). The program struc-
ture does not reliably recover the
correct population structure when sam-
pling is uneven: subsampling and new
estimators alleviate the problem. Mol.
Ecol. Res., 16(3), 608-627. https://doi.
org/10.1111/1755-0998.12512
Quesada-Alpízar, M. A. & Morales-Ramírez,
A. (2004). Comportamiento de las ma-
sas de agua en el Golfo Dulce, Costa
Rica durante El Niño (1997-1998).
Rev. Biol. Trop., 52(Suppl.2), 95-103.
R Core Team. (2021). R: A language and en-
vironment for statistical computing. R
Foundation for Statistical Computing.
https://www.R-project.org/
Ruiz-Bravo, A. (2013). Patrones reproducti-
vos de Diadema mexicanum A. Agassiz,
1863 (Echinodermata: Echinoidea) en
Bahía La Entrega, Huatulco, Oaxa-
ca. (Tesis de doctorado no publicada).
Universidad del Mar, Oaxaca, México.

115
Rev. Mar. Cost. Vol. 17 (1): 91-115, enero-junio 2025
ISSN: 1659-455X • e-ISSN: 1659-407X
DOI: http://dx.doi.org/10.15359/revmar.17-1.5
Connectivity of the sea urchin Diadema mexicanum A. Agassiz, 1863
(Echinoidea, Diadematidae) in the Pacic coast of Costa Rica
Soft Genetics. (2021). GeneMarker 2.24.2
[Software de análisis de datos genéti-
cos]. Soft Genetics. https://genemark-
er.software.informer.com/2.2/
Steinkellner, H., Lexer, C., Turetschek, E.
& Glössl, J. (1997). Conservation of
(GA) n microsatellite loci between
Quercus species. Mol. Ecol., 6(12),
1189-1194. https://doi.org/10.1046/
j.1365-294X.1997.00288.x
Svendsen, H., Rosseland, R., Myking, S.,
Vargas, J. A., Lizano, O. G. & Alfaro,
E. (2006). A physical-oceanographic
study of Golfo Dulce. Rev. Biol. Trop.,
54(S1), 147-170.
Teske, P. R., Golla, T. R., Sandoval-Castillo, J.,
Emami-Khoyi, A., van der Lingen, C.
D., von der Heyden, S., … & Beherega-
ray, L. B. (2018). Mitochondrial DNA
is unsuitable to test for isolation by dis-
tance. Scient. Rep., 8, 8448. https://doi.
org/10.1038/s41598-018-25138-9
Vieira, M. L. C., Santini, L., Diniz, A. L. &
Munhoz, C. de F. (2016). Microsatellite
markers: What they mean and why they
are so useful. Gen. Mol. Biol., 39(3),
312-328. https://doi.org/10.1590/1678-
4685-GMB-2016-0027
Winter, D. J. (2012). MMOD: an R library
for the calculation of population dif-
ferentiation statistics. Mol. Ecol.
Res., 12(6), 1158-1160. https://doi.
org/10.1111/j.1755-0998.2012.03174.x
Wyrtki, K. (1965). Surface Currents of the
Eastern Tropical Pacic Ocean. Bull.
Inter-Amer. Trop. Tuna Comm., 9,
269-304.
Yang, Y., Ren, C., Luo, P., Jiang, X., Lin, T.,
Li, X., Li, X., … & Chen, T. (2024).
Pipeline for identication of ge-
nome-wide microsatellite markers and
its application in assessing the genetic
diversity and structure of the tropical
sea cucumber Holothuria leucospilota.
Aquacul. Rep., 37, 102207. https://doi.
org/10.1016/j.aqrep.2024.102207