Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e2025-676, enero-diciembre 2025 (Publicado Set. 23, 2025)

Combining environmental DNA metabarcoding and specimen collections to

describe fish biodiversity in the Tukakas Bay, Colombian Caribbean

Vanessa Yepes-Narváez1*; https://orcid.org/0000–0001–7174–5382

Alice Valentini2; https://orcid.org/0000–0001–5829–5479

Coline Gaboriaud2; https://orcid.org/0009–0009–4510–7251

Alejandro Rodríguez-Sánchez1; https://orcid.org//0009–0005–9181–293X

Mayra Atencia-Galindo1; https://orcid.org/0000-0003-2557-5380

1. Programa de Biodiversidad y Ecosistemas Marinos, Instituto de Investigaciones Marinas y Costeras “José Benito Vives

de Andréis”, Santa Marta, Magdalena, Colombia; vanessa.yepes@invemar.org.co (*Correspondence), alejandro.rodri-

guez@invemar.org.co, mayra.atencia@invemar.org.co

2. SPYGEN, 17 rue du Lac Saint-André Savoie Technolac BP 274, Le Bourget-du-Lac, 73375, France; alice.valentini@

spygen.com, coline.gaboriaud@spygen.com

Received 28-VI-2024. Corrected 07-IV-2025. Accepted 02-IX-2025.

ABSTRACT

Introduction: Tukakas Bay, located on the border between Colombia and Venezuela, is practically unknown in

terms of its marine biodiversity. This lack of knowledge generated the need to carry out an expedition to evaluate

the current state of its associated biodiversity.

Objective: To describe for the first time fish biodiversity in Tukakas Bay through integrated sampling

methodologies.

Methods: We combined environmental DNA (eDNA) from seawater with observations and morphological

methods, and subsequent mitochondrial DNA barcoding (COI, 16S) to describe fish biodiversity. Water samples

for eDNA analysis were concentrated in four transects along the bay and processed in laboratory. Visual censuses

were carried out through scuba diving and snorkelling, and fish were collected in 17 stations. Tissue samples were

subtracted and preserved for DNA barcoding. Voucher specimens were fixed and preserved for taxonomy. Both

specimens and tissue samples are part of reference collections at MHNMC, and their metadata are available in

the public domain.

Results: We identified 481 ASVs belonging to 95 species, 68 genera, and 52 families from eDNA, visual censuses,

and morphology (including DNA barcoding). Detections made with eDNA included solitary species and rep-

resented 65 % of all identified fish taxa in Tukakas Bay, from which 15 species were also observed or collected.

Specimen collections were effective for the creation of 45 DNA barcodes and 164 DNA sequences, and the con-

firmation of taxonomic assignations obtained by the other two methods. We improved taxonomic resolution for

20 % of the taxa by combining these three survey methods.

Conclusion: Integrating eDNA metabarcoding approaches to traditional fish surveys significantly improves

biodiversity assessments specially on remote areas.

Keywords: Bio Expedition “Lamuuna Neimalu’u”; Wayuu indigenous communities; La Guajira desert;

Colombian Caribbean; molecular taxonomy.

https://doi.org/10.15517/4z83mm52

AQUATIC ECOLOGY

2Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e2025-676, enero-diciembre 2025 (Publicado Set. 23, 2025)

INTRODUCTION

La Guajira is the northernmost depart-

ment of Colombia, with the largest continental

shelf and highest rates of seasonal upwelling

events due to strong winds and the indirect

effects of the Darien counter current (Gómez-

Gaspar & Acero, 2020; Murcia-Riaño et al.,

2017). Since it does not present important

rivers to contribute with organic matter, these

events control most fisheries production, as

they modify the availability of nutrients (Par-

amo et al., 2003). In addition, this area hosts a

great diversity of costal and marine ecosystems

and an abundant biodiversity, especially ich-

thyofauna (Acero et al., 2023).

Fish diversity in La Guajira is comprised

of around 667 species from which 40 % have

some commercial value for local and national

users (Corpoguajira & Instituto de Investiga-

ciones Marinas y Costeras “José Benito Vives

de Andréis” [Invemar], 2012). Subsistence

fisheries are the main economic support to

coastal communities of the Wayuu indigenous

culture. Artisanal fishermen in the upper half

of the department have mastered the cap-

tures of marine fish resources under changing

environmental conditions for centuries, which

lately have forced them to navigate further away

offshore to obtain this resource (Guerra et al.,

2015). Unsustainable fishing activities could

negatively impact natural populations through

habitat destruction, and indiscriminate cap-

tures (Carneiro & Martins, 2021). Therefore,

fisheries need legislation and accurate manage-

ment to reduce impacts on fish stocks.

Currently, strategies to understand and

quantify fish composition involve observational

identification and abundance calculations using

traditional techniques such as, captures (with

several methodologies) and underwater visual

census (Stat et al., 2018). These, have their own

RESUMEN

Combinando el metabarcoding de ADN ambiental y la recolección de especímenes

para describir la biodiversidad de peces en la Bahía de Tukakas, Caribe colombiano

Introducción: La Bahía de Tukakas, ubicada en la zona fronteriza entre Colombia y Venezuela, es prácticamente

desconocida en términos de su biodiversidad marina. Este desconocimiento generó la necesidad de realizar una

expedición para evaluar el estado actual de su biodiversidad asociada.

Objetivo: Describir por primera vez la biodiversidad de peces en la Bahía de Tukakas a través de metodologías

de muestreo integradas.

Métodos: Combinamos el ADN ambiental (eDNA) en agua marina con métodos de observación y morfología y la

creación de códigos de barras de ADN a partir de genes mitocondriales (COI, 16S) para describir la biodiversidad

de peces en la Bahía de Tukakas. Las muestras de agua para el análisis de eDNA se concentraron en cuatro transec-

tos a lo largo de la bahía y se procesaron en el laboratorio. Se realizaron censos visuales a través de buceo y snorkel.

Los peces se recolectaron en 17 estaciones. Se extrajeron muestras de tejido y se conservaron para realizar códigos

de barras de ADN. Se fijaron y preservaron especímenes de referencia para taxonomía. Tanto los especímenes

como las muestras de tejido forman parte de colecciones del MHNMC y sus metadatos son de dominio público.

Resultados: Identificamos 481 ASVs pertenecientes a 95 especies, 68 géneros y 52 familias a partir de eDNA,

censos visuales y morfología (incluyendo códigos de barras de ADN). Las detecciones realizadas con eDNA inclu-

yeron especies solitarias y representaron el 65 % de todos los taxa de peces identificados en la Bahía de Tukakas, de

los cuales también se observaron y/o recolectaron 15 especies. Las recolecciones fueron efectivas para la creación

de 45 códigos de barras de ADN y 164 secuencias de ADN, y la confirmación de asignaciones taxonómicas obte-

nidas por los otros dos métodos. Mejoramos la resolución taxonómica para el 20 % de los taxones combinando

estos tres métodos de muestreo.

Conclusión: La integración del metabarcoding de eDNA en los estudios tradicionales de peces mejoran signifi-

cativamente las evaluaciones de biodiversidad, especialmente en áreas remotas.

Palabras clave: Expedición Bio “Lamuuna Neimalu’u”; comunidades indígenas Wayuu; desierto de La Guajira;

Caribe colombiano; taxonomía molecular.

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e2025-676, enero-diciembre 2025 (Publicado Set. 23, 2025)

limitations with regards to the geographical

coverage and are biased by some biological

aspects such as life stage, sexual maturity or

sizes that could affect representativeness esti-

mates, and in addition, they all require spe-

cialist equipment and taxonomists to confirm

species (Logan et al., 2017). In addition, poorly

surveyed areas with difficult access such as

border and offshore regions have limitations

with regards to the implementation of extenu-

ating sampling efforts and sampling designs.

For this, recent molecular techniques such as

eDNA metabarcoding are complementing fish

inventories at a lower cost and reduced process-

ing times (Jeunen et al., 2019; Stat et al., 2017).

The estimation of species diversity using

environmental DNA allows us to detect the pres-

ence of a wide range of taxonomic groups from

environmental samples (water, soil, air) without

observing or catching them, causing the least

impact on its natural systems. This represents a

snapshot of ecosystem dynamics at times close

to its collection. These samples contain frag-

ments of genomic DNA that have been expelled

by the present organisms at low concentra-

tions through their biological activities (excre-

tion, reproduction, shedding, etc.) (Thomsen

& Willerslev, 2015). Therefore, it has many

advantages with respect to traditional methods,

in terms of the cost efficiency of the detections

of taxa that frequent sampling sites, especially

in difficult–to–access areas such as Tukakas Bay

in La Guajira, where the physical isolation of

complete organisms is impractical, expensive or

challenging (Guardiola et al., 2015; Kelly et al.,

2014; Polanco-Fernández et al., 2020).

Tukakas Bay, is an isolated and desertic

zone in the border with Venezuela, composed

of poorly characterized seagrass meadows,

mangroves, coral formations, beaches and sedi-

mentary bottoms it is an area of interest for

conservation due to the biophysical features

of its location and protected by the indig-

enous Wayuu authorities of the Uribia district

(Shopoiki, Icheput, Warruttamana, Warpana

and Jichipaa). It is also therefore an important

location for the development of conservation,

management, and restoration efforts for key

species, such as mangroves, sea turtles and

migratory birds. However, most of these eco-

systems are yet to be characterized and are

home to ecological important species of fauna

and flora which represent the main food source

to local Wayuu populations. Here, we combined

eDNA metabarcoding with visual censuses and

morphology along with DNA barcoding to

maximise the detection of fish biodiversity and

provide the first inventory of species.

This research contributed to the country’s

marine–coastal biodiversity surveys and sets a

precedent in terms of the integration of tradi-

tional knowledge from indigenous communi-

ties in the construction of applied science.

MATERIALS AND METHODS

Visual censuses: Sampling was conducted

in April 2023 in the Tukakas Bay, an area of

approximately 1 000 ha located in the district of

Puerto Lopez, in the La Guajira desert, on the

Caribbean border with Venezuela (Fig. 1), dur-

ing dry season. Specimen observation required

five band transects (60 m2) through SCUBA

diving and snorkelling; occurrences were input

in logbooks and annotations on life stage and

behaviour were registered as well as notes from

traditional knowledge about their distribution

seasonality and their historical availability in

the area.

Fish DNA barcoding (ITF): One repre-

sentative of each fish species was collected from

17 stations using either manual captures, hand

nets, cast nets or clove oil for cryptobenthic

species (SMT 1). An additional sampling was

conducted in a station 10 km offshore from the

bay through artisanal fisheries to compare fish

diversity between contrasting zones. All speci-

mens were measured, photographed, and three

2 mm tissue replicates were subtracted from

each individual and preserved in molecular

grade ethanol for Integrative taxonomy (mor-

phology and DNA barcoding) (from now will

be mentioned as ITF). Voucher specimens were

then fixated and preserved in ethanol 70 % for

morphological taxonomy.

4Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e2025-676, enero-diciembre 2025 (Publicado Set. 23, 2025)

DNA extraction was performed for each

fish tissue preserved, using either a commercial

extraction kit (Qiagen® DNeasy Blood & Tis-

sue) following the manufacturer’s instructions

or the CTAB method (Doyle & Doyle, 1987)

with some modifications, using ammonium

acetate as a protein precipitator, the incubation

time was 1-3 h and the DNA elution was per-

formed with 40 µl of AguaMQ.

A DNA fragment of approximately 600

bp for the cytochrome c oxidase I (COI) gene

was amplified using three primer combinations

(Table 1) and a c.a. 550 bp fragment was ampli-

fied for 16S rDNA gene (Table 1). DNA ampli-

fications were performed in a final volume of

30 μl of amplification mixture, using 1-3 μl of

DNA extract as the template. The amplification

mixture contained 1x Taq Buffer, 2 mM MgCl2,

0.2-0.4 mM dNTPs mix, 0.1 µM of each primer,

0.1 U of BIOLINE Taq polymerase and 3 µl of

genomic DNA. The temperature cycle condi-

tions for all primers were, denaturation at 94°C

for 2 min, followed by 35 cycles of 94 °C for 30

sec, 52-55 °C for 40 sec and 72°C for 1 min, and

a final extension at 72°C for 5-10 min. Positive

PCR products were sequenced with Sanger

technology at Macrogen inc. in Korea, for

which it was necessary to obtain two exporta-

tion permits for NON–CITES material granted

by the National Environmental License Author-

ity of Colombia–ANLA (Permits No.3347 and

No. 3579).

Chromatograms were edited using

Geneious Prime v2023.1.1 software to obtain

high quality sequences for taxonomic assign-

ments using reliable BOLD Systems databases.

When not identity was found with this data-

base, we used the GenBank alignment tool

(nBLAST) and sought taxonomic validation

with experts in the field. Sequences with a

Fig. 1. Fish sampling stations for DNA–based and visual censuses methods in the Tukakas Bay, La Guajira, Colombia. eDNA

transects are indicated by yellow dots and specimen collections and observation stations are marked with red dots.

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e2025-676, enero-diciembre 2025 (Publicado Set. 23, 2025)

similarity greater than 99 % were considered for

delimitation at the species level and 90-99 % to

the genus level and 85-90 % to the family level.

Environmental DNA sampling: for the

eDNA sampling the water was collected along-

side four transects located in pristine zones,

Reef formations (Outside the bay (5 km linear

transect)); Canal (Sandy bottoms (3 km lin-

ear transect); Seagrass meadows (Inside the

bay (3 km circular transect) and Muddy bot-

toms (inside the bay (6 km circular transect)

(Fig. 1; SMT 1).

Seawater samples were collected in the

morning during high tide from the bow of a 3m

long speed boat to avoid contamination. Water

filtration design was planned to maximise spa-

tial coverage and to guarantee the collection

of rare DNA fragments. It consisted of two

replicates of 30l of seawater for 30 minutes (1 l/

min) at 1.0 m depth along horizontal or circular

transects at 2 knots of speed. For this, two Athe-

na® peristaltic pumps (Proactive Environmental

Products LLC) were used in parallel, as well as

sterilized single–use tubing kits), disposable

gloves and 0.2µm single–use filtration capsules

per each replicate (VigiDNA; SPYGEN). At the

end of each filtration, the water in the filter was

emptied and 80 ml of CL1 buffer (SPYGEN)

were added to preserve the eDNA concentrated

in the filtration capsules. The capsules were

stored in the dark at room temperature.

eDNA Metabarcoding and bioinformat-

ics analysis: The eDNA metabarcoding process,

involving extraction, amplification of 12 repli-

cates per samples using Vert01 primers (Table

1; Riaz et al., 2011; Taberlet et al., 2018) was

performed following the procedure described

in Polanco-Fernández et al. (2020). Purified

PCR products were pooled in equal volumes

to achieve a theoretical sequencing depth of 1

000 000 reads per sample. Three libraries were

prepared using the TruSeq protocol (Illumina)

and paired end sequenced (2 × 150 bp) with an

Illumina NextSeq 1 000 sequencer using a P1

Flow Cell (Illumina) for two libraries and a P2

Flow Cell (Illumina) for the last one, following

the manufacturer’s instructions. Three nega-

tive extraction controls and two negative PCR

controls (12 replicates) were also amplified with

12 replicates and sequenced in parallel to the

samples to monitor for possible contaminants.

For bioinformatics analysis, the readings

were processed to eliminate errors using pro-

grams implemented in the OBITools package

(Boyer et al., 2016) based on the protocol

proposed by Valentini et al. (2016). Reads for

Forward and Reverse were assembled with the

Illumina paired end program, using a mini-

mum score of 40 and recovering only aligned

sequences. Readings were then assigned to each

sample using NGSFILTER software. A separate

data set was created for each sample by splitting

the original data set into multiple files using

Table 1

DNA markers used for DNA Barcoding and eDNA metabarcoding.

Target Marker Primer Sequence (5´– 3´) Reference

Fish COI FishF1 TCAACCAACCACAAAGACATTGGCAC Ward et al. (2005)

FishR1 TAGACTTCTGGGTGGCCAAAGAATCA

FishF2 TCGACTAATCATAAAGATATCGGCAC

FishR2 ACTTCAGGGTGACCGAAGAATCAGAA

FF2D TTCTCCACCAACCACAARGAYATYGG Ivanova et al. (2007)

FR1D CACCTCAGGGTGTCCGAARAAYCARAA

16S 16Sbr CTCCGGTTTGAACTCAGATCA Palumbi et al. (1996)

16SA CGCCTGTTTATCAAAAACAT

Vertebrates 12S Vert01F

Vert01R

TAGAACAGGCTCCTCTAG

TTAGATACCCCACTATGC

Riaz et al. (2011); Taberlet et al.

(2018);

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OBISPLIT. Each sample was then analyzed

individually before being coupled to the list of

taxa for the final ecological analysis. Identical

sequences were clustered using OBIUNIQ and

sequences with less than 20 bp or with less than

10 occurrences were excluded using the OBIG-

REP program.

Taxonomic assignment of the remaining

sequences was performed using the ECOTAG

program with the sequences retrieved from

the release 247 of GenBank®. The taxonomic

assignments were corrected to avoid overesti-

mations so that only identification with identity

matches of 100-98 % (for the species level),

96-98 % (for the genus level) or between 90 %

and 96 % of similarity (for family level).

Data analysis: Both voucher and tissue

samples are available in reference collections

at the Marine Natural History Museum of

Colombia (MHNMC) and their metadata and

molecular information is publicly available

on the Marine Biodiversity information sys-

tem database (SIBM) of INVEMAR, BOLD

Systems databases and GBIF DNA–derived

data test tool.

Species lists from visual censuses, Fish

DNA Barcoding and eDNA metabarcoding

identified to the species level were used to build

a composition and richness matrix. Therefore,

statistical analyses were performed at the spe-

cies level to facilitate comparisons between the

different surveys’ approaches. All the statistical

analyses were performed in R version 4.3.2.

Univariate analyses were performed to compare

sampling methods resolution. To calculate sam-

pling effort on the overall fish richness, taxon

accumulation curves were created for each col-

lection method using the “specaccum” function

in the R vegan package (Oksanen et al., 2016).

Euler Diagram was made using “eulerr” pack-

age and the function “euler_plot”.

RESULTS

During the visual census surveys, 28 fish

observations were recorded in logbooks. In

addition, 196 sequences (COI and 16S) were

obtained from 84 specimen samples collected

in 17 stations (Table 2), for which 98 % of the

sequence could be resolved at the species level

(58 species identified with observations and

DNA barcoding).

For the eDNA metabarcoding approach,

we obtained 5 905 329 raw paired end reads

for the eight eDNA samples and after all the

bioinformatics steps 4 118 413 reads (mean = 9

698 reads/sample, SD = 217.65) were retrieved

for the subsequent analysis. Although a 12S

vertebrate primer was used for this study, all

sequences retrieved belonged to fish taxa; how-

ever, the proportion of sequences were not

equally distributed across the ASVs detected.

Table 2

Summary of the numbers of sequencing reads, total ASVs identified and assigned to fish taxa, as well as the mean number

of the previously known record of species and genus in La Guajira.

Method

N° of seqs

after

Bioinformatics

filters

Total ASVs/species

identified

No. of assigned ASVs Unassigned

ASVs

Known record

for La Guajira

species

level

genus

level

family

level Species Genera

eDNA

(12S)

4 118 413 427 79 90 231 27 267

(OBIS–SIBM)

182

(OBIS–SIBM)

DNA barcoding

(COI–5p)

88 51 38 2 9 2

DNA barcoding

(16S)

108 55 41 1 13 0

Morphology only – 32 28 3 1 –

Visual census – 28 28 0 0 –

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A total of 426 unique ASVs (Amplicon

sequence variant) resulted from this method

after the taxonomic assignment. Around 19.7 %

of the fish taxa detected with eDNA could be

resolved to the species level and 22.5 and

57.7 % were detected at the genera and family

level respectively (SMT 2). Using integrative

taxonomy (morphology and DNA barcoding)

(ITF), the specimen collections included 85 fish

samples from which 45 unique DNA barcodes

and 164 DNA sequences were created and

uploaded in the BOLD systems database and

allowed the confirmation of taxonomic assigna-

tions obtained by the other two methods (Table

3) and After taxonomic validation the merged

dataset, made from the combination of visual

censuses, ITF and eDNA, was composed by 95

Actinopteri species across all samples belong-

ing to 68 genera and 52 families (Table 3).

Fish taxa identified by visual censuses

were significantly less diverse than the other

two methods, however it contributed 28 species

Table 3

Species–level detections using eDNA, visual censuses and integrative taxonomy –morphology and DNA barcoding (ITF)

methods.

Fish taxa Habitat MHNMC code Barcode (BOLD)

Detection method

Visual

census ITF eDNA

Acanthurus tractus CR x

Acanthostracion quadricornis CR x

Abudefduf sp. CR x

Abudefduf saxatilis CR x

Abudefduf taurus CR x

Anchoa sp. SB–MB–SG x

Anchovia clupeoides CR x

Anisotremus surinamensis CR x

Anchoa lyolepis CR x

Anisotremus virginicus CR x x

Archosargus probatocephalus CR x

Archosargus rhomboidalis SG INV TEJ3789 | INV TEJ3807 CBINP016–24 |

CBINP031–24

Atherinella brasiliensis SG INV TEJ3830 | INV TEJ3909 |

INV TEJ3911 | INV PEC13286

CBINP041–24 |

CBINP065–24 |

CBINP066–24

Bagre bagre CR–MB–SG x

Bagre filamentosus CR x

Bairdiella ronchus SB INV TEJ3887 | INV PEC13281 CBINP058–24 x

Bathygobius soporator SB x

Batrachoides manglae MR INV TEJ3811 | INV PEC13288 CBINP033–24 x

Caranx hippos CR x

Cathorops wayuu SB INV TEJ3866 | INV PEC13277 CBINP051–24 x

Centropomus ensiferus SB INV TEJ3863 | INV TEJ3881 |

INV TEJ3905 | INV PEC13298

CBINP050–24 |

CBINP056–24 |

CBINP064–24

Centropomus parallelus SB INV TEJ3878 | INV PEC13299 x

Centropomus undecimalis SB INV TEJ3848 | INV TEJ3878 |

INV TEJ3902

CBINP046–24 |

CBINP055–24 |

CBINP063–24

Chaetodipterus faber SB–MB–SG–CR INV TEJ3857 | INV PEC13280 CBINP048–24 x x

Chilomycterus sp. CR x

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Fish taxa Habitat MHNMC code Barcode (BOLD)

Detection method

Visual

census ITF eDNA

Citharichthys spilopterus SG INV TEJ3841 | INV PEC13284 CBINP043–24 x

Ctenogobius boleosoma SG INV TEJ3793 CBINP026–24 x

Cynoscion sp. SB–CR–SG x

Cynoscion acoupa SB INV TEJ3854 |

INV TEJ3860 | INV TEJ3875 |

INV TEJ3893 | INV PEC13282

CBINP047–24 |

CBINP049–24 |

CBINP053–24 |

CBINP060–24

Diapterus sp. SG x

Diapterus auratus SG x

Diapterus rhombeus SB–MB–SG–CR x

Diodon hystrix CR x

Diplectrum formosum CR x

Echeneis naucrates CR x x

Elops smithi SB–MB–SG–CR x

Epinephelus itajara SB–CR–SG–MB INV TEJ3896 CBINP061–24 x x

Erotelis smaragdus SG INV TEJ3792 CBINP025–24 x x

Eucinostomus argenteus SG–CR x

Eucinostomus gula SG INV TEJ3795 |

INV TEJ3844 | INV PEC13289

CBINP027–24 |

CBINP044–24

x x

Eucinostomus jonesii SG INV TEJ3846 | INV PEC13293 CBINP045–24 x x

Eugerres plumieri SG x

Evorthodus lyricus SG INV TEJ3809 CBINP032–24 x

Gerres cinereus SB INV TEJ3838 x x

Gymnothorax funebris CR x x

Haemulon sp. CR x

Haemulon aurolineatum CR x

Haemulon bonariense SG x

Haemulon plumierii SG x

Haemulon flavolineatum CR x

Haemulon parra CR x

Halichoeres sp. CR x

Harengula clupeola CR–MB–SG x

Harengula jaguana CR–MB–SG–SB x

Hemiramphus sp. CR x

Hippocampus reidi SG x

Hyporhamphus unifasciatus CR–SG–SB–MB x

Lachnolaimus sp. CR x

Lachnolaimus maximus CR x x

Larimus sp. MB x

Lobotes surinamensis SG x

Lophogobius cyprinoides SG INV TEJ3813 | INV PEC13296 CBINP034–24 x

Lutjanus sp. SB–CR–SG x

Lutjanus analis SG x

Lutjanus apodus SG x

Lutjanus cyanopterus SB INV TEJ3818 CBINP037–24 x

Lutjanus jocu CR x x

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Fish taxa Habitat MHNMC code Barcode (BOLD)

Detection method

Visual

census ITF eDNA

Lutjanus griseus SB–CR–SG x x

Lutjanus mahogoni CR x

Lutjanus synagris CR x

Lycengraulis limnichthys SB–MB–SG x

Lycengraulis grossidens SB–MB–SG x

Macrodon ancylodon CR x

Malacoctenus delalandii CR INV TEJ3696 | INV TEJ3698 |

INV TEJ3777 | INV PEC13287

CBINP001–24 |

CBINP002–24 |

CBINP020–24

Membras sp. MB–SG x

Megalops atlanticus SB–MB–SG–CR x

Micropogonias furnieri CR–SG INV TEJ3827 | INV TEJ3877 |

INV PEC13285

CBINP040–24 |

CBINP054–24

x x

Mugil curema SG–CR–SB–MB INV TEJ3824 | INV TEJ3872 |

INV TEJ3884 | INV PEC13278

CBINP039–24 |

CBINP052–24 |

CBINP057–24

x x

Mugil incilis SB–CR–SG x

Mugil liza SG–CR–SB–MB x

Mugil rubrioculus SG–CR–SB– x

Mugil trichodon SG–CR–SB–MB x

Nicholsina usta SB x

Odontoscion dentex CR x

Opisthonema oglinum CR x

Orthopristis scapularis CR x

Paraclinus fasciatus SG INV TEJ3797 x

Rypticus saponaceus SB–SG x

Scartella cristata CR x

Scarus iseri CR x

Scarus taeniopterus CR x

Sciades herzbergii SG INV TEJ3836 | INV TEJ3890 |

INV PEC13295

CBINP042–24 |

CBINP059–24

Sciades proops MB INV TEJ3899 CBINP062–24 x

Scomberomorus brasiliensis CR x

Scorpaena plumieri CR x

Sparisoma chrysopterum CR–SG x

Sparisoma rubripinne CR x

Sphoeroides sp. SG INV TEJ3791 | INV TEJ3816 CBINP024–24 |

CBINP036–24

Sphoeroides greeleyi SG INV TEJ3800 | INV PEC13290 CBINP029–24 x

Sphoeroides spengleri CR x

Sphoeroides testudineus CR–SB–MB–SG INV TEJ3803 | INV PEC13290 CBINP030–24 x x

Sphyraena barracuda CR x

Stegastes adustus CR x x

Stephanolepis hispida CR x

Strongylura timucu CR– SB–MB– SG INV TEJ3821 CBINP038–24 x x x

Syngnathus sp. SB x

Syngnathus caribbaeus SG x

10 Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e2025-676, enero-diciembre 2025 (Publicado Set. 23, 2025)

from which 20 were not detected by the other

two methods. In addition, 73 % of the reports

were obtained associated with coral reefs and

seagrasses, with only two observations associ-

ated with muddy and sandy bottoms. Seven

species were also detected with eDNA in the

same environments. Haemulidae (n = 5 spp.)

and Lutjanidae (n = 4 spp.) where the most

registered families and Haemulon aurolinea-

tum, Haemulon plumierii, Lutjanus griseus and

Lutjanus jocu were the most observed species.

ITF methods allowed a better taxonomic

resolution which resulted in 48 species belong-

ing to 38 genera, 26 families and 17 orders

(Fig. 2). Acanthuriformes grouped most of the

records (n = 14 spp.), followed by Carangi-

formes (n = 8 spp.), Siluriformes (n = 4 spp.)

and Gobiiformes (n = 4 spp.). Families contain-

ing most of the species included Sciaenidae (n

= 6 spp.), Ariidae (n = 4 spp.), Carangidae (n =

4 spp.) and Gerreidae (n = 4 spp.). From the 38

genera identified, Cynoscion was the most con-

spicuous (n = 4 spp.) followed by Centropomus

and Sphoeroides (n = 3 spp. each) (SMT 2).

Most fish specimens collected correspond-

ed to either juvenile or small reef–associated

adults (Fig. 3). Traditional taxonomy allowed

the description of all specimens and DNA

barcoding improved resolution to species level.

Environmental DNA results included soli-

tary species and represented 65 % of all identi-

fied fish species in Tukakas Bay, from which 15

species were also observed or collected (SMT

3). The taxonomic resolution of eDNA results

per sample (mean = 31.75 [12.17]) was sig-

nificantly higher than through visual censuses

(mean = 7 [4.24]; Mann–Whitney–Wilcoxon

Test, W = 83.2, p < 0.05) and ITF (morphol-

ogy/DNA barcoding) (mean = 8 [7, 4]; Mann–

Whitney–Wilcoxon Test, W = 127.5, p < 0.05).

The number of fish species detected with eDNA

in seagrasses (n = 34), sandy bottoms (n = 24),

muddy bottoms (n = 21) and coral reefs (n =

48) was greater than with DNA barcoding and

morphology (n = 18, n = 9, n = 3 and n = 2,

respectively) as well as with visual censuses (n

= 11, n = 5, n = 2, n = 10, respectively).

Fish taxa Habitat MHNMC code Barcode (BOLD)

Detection method

Visual

census ITF eDNA

Syngnathus pelagicus SG INV TEJ3799 | INV TEJ3814 |

INV PEC13294

CBINP028–24 |

CBINP035–24

Trachinotus falcatus CR x

Tylosurus acus CR x

Tylosurus crocodilus CR x

Habitat: Coral reefs (CR), Seagrasses (SG), Mud bottoms (MB), Mangroves (MR) and Sandy bottoms (SB). MHNMC: Marine

Natural History Museum of Colombia deposit ID (INV TEJ: Tissue reference collection code; INV PEC: Fish reference

collection code) for collected fish samples.

Fig. 2. Relative abundance of fish families detected with

Integrative taxonomy (ITF), eDNA and visual censuses in

the Tukakas Bay.

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e2025-676, enero-diciembre 2025 (Publicado Set. 23, 2025)

The species accumulation curves for the

number of fish species detected for each meth-

od appeared close to saturation except for visual

censuses (Fig. 4). Taxa identified with eDNA

surpassed by 32.3 and 29.2 % the detections

made by visual censuses and ITF respectively

Fig. 3. Fish collected on Tukakas Bay and identified both with morphology and DNA barcoding. 1. Archosargus rhomboidalis.

2. Sphoeroides testudineus. 3. Atherinella brasiliensis. 4. Sphoeroides greeleyi. 5. Chaetodipterus faber. 6. Batrachoides manglae.

7. Ctenogobius boleosoma. 8. Bairdiella ronchus. 9. Cathorops wayuu. 10. Citharichthys spilopterus. 11. Centropomus ensiferus.

12. Erotelis smaragdus. 13. Cynoscion acoupa. 14. Epinephelus itajara. 15. Sciades proops. 16. Centropomus undecimalis. 17.

Eucinostomus gula. 18. Eucinostomus jonesii. 19. Gerres cinereus. 20. Paraclinus fasciatus. 21. Malacoctenus delalandii. 22.

Strongylura timucu. 23. Sphoeroides sp. 24. Evorthodus lyricus. 25. Syngnathus pelagicus. 26. Lophogobius cyprinoides. 27.

Sciades herzbergii. 28. Mugil curema. 29. Lutjanus cyanopterus. 30. Micropogonias furnieri.

12 Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e2025-676, enero-diciembre 2025 (Publicado Set. 23, 2025)

and added further 31 genera to the overall spe-

cies biodiversity assessment.

Fish species composition was different bet-

ween eDNA, visual censuses and specimen

collection (ITF) samples (p < 0.005) and for

the interaction between sampling methods and

ecosystems surveyed (p < 0.005). eDNA con-

tributed with 79 species which corresponds to

53.8 % of the total species record for Tukakas

Bay. These belong to 48 genera and 42 families,

Mugilidae had the largest detections within the

Bay (n = 89 ASVs), followed by Engraulidae

(n = 78 ASVs) and Sciaenidae (n = 35 ASVs).

From the detected genera Mugil was the most

detected (n = 45 ASVs), followed by Lycen-

graulis (n = 11 ASVs), Harengula (n = 9 ASVs)

and Anchoa (n = 8 ASVs). Mugil incilis (n =

6 ASVs), Mugil trichodon (n = 5 ASVS) and,

Mugil liza (n = 4 ASVs) were the most repre-

sented species from eDNA assessment (SMT 2).

Samples collected in the outgroup located

10 Km offshore (E8), contained 20 species

from which six were also detected in the bay

using eDNA (n = 3) and collected associated

with coral reefs and seagrasses (n = 3). In addi-

tion, E8 contained 14 different genera that

were not recorded by any of the three methods

used (SMT 4); therefore, this station was dif-

ferent from the rest of stations in Tukakas bay

(Mann–Whitney–Wilcoxon Test, W = 184.5, p

< 0.05).

DISCUSSION

In this study, we combined eDNA metaba-

rcoding, visual censuses and specimen col-

lections to describe for the first–time fish

biodiversity in the Tukakas Bay at the border

between Colombia and Venezuela. As expected,

we detected more species with eDNA metabar-

coding than with the other two methods, even

when less sampling effort, which is confirmed

by other studies that performed similar com-

parisons (Hallam et al., 2021; Mathon et al.,

2022; McElroy et al., 2020; Oka et al., 2020;

Polanco-Fernández et al., 2020; Stat et al., 2018;

Valdivia-Carrillo et al., 2021; West et al., 2020).

Implying that eDNA metabarcoding provide a

larger detection power and has the capacity to

identify rare and solitary species more efficient-

ly than visual census or specimen collections.

We found that when combining all three

sampling methods a larger species record was

obtained. Although most detections belonged

to small reef–associated or seagrass–associated

species, eDNA allowed to identify other pelagic

species that seem to migrate horizontally from

the open sea and did not detect the presence of

elasmobranchs inside the bay. This study evi-

denced the potential of eDNA metabarcoding

in fish biodiversity assessments in remote areas.

Below, we discuss the main results regarding

the strengths and limitations of each survey

method and how they all complemented the

species record.

Complementarity of specimen collec-

tions, visual census and eDNA survey meth-

ods: All three sampling methods provide

fundamentally different information and mea-

suring units; therefore, their outcomes cannot

be fairly compared (Ruppert et al., 2019). The

species detected from eDNA samples highly

depend on the oceanographic conditions of

the bay since DNA fragments are transported

at different rates depending on the ecosys-

tem dynamics and taxonomic assignations are

Fig. 4. Species accumulation curve for the number of fish

species detected in Tukakas Bay with eDNA, integrative

taxonomy (ITF) and visual censuses (numbers in

parenthesis indicate total number of species detected).

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e2025-676, enero-diciembre 2025 (Publicado Set. 23, 2025)

obtained from the specificity of the primers

used (Barnes & Turner, 2016; Hajibabaei et

al., 2019; Stat et al., 2017; Thomsen & Willer-

slev, 2015). In contrast, traditional sampling

methods such as visual census and specimen

collection can be affected by observer bias

and specificity of the net pore sizes that limit

catch species and life stages (Juhel et al., 2020;

Polanco-Fernández et al., 2020). Another limi-

tation is that their detection success relies on

good environmental conditions and sampling

design which determines the efficiency of the

approach (Emslie et al., 2018; Juárez-Hernán-

dez & Sánchez-Vega, 2022). Therefore, in this

study we focused on their complementarity

rather than on their individual efficiency at

detecting fish species in Tukakas Bay.

Tukakas Bay in addition to being unknown,

in our opinion is very poor in terms of biodi-

versity based on our assessment. We employed

a generic primer for vertebrates to detect as

many ASVs/species from all the vertebrate

community within the bay, including birds

and mammals; however, their occurrence was

rare even in the visual censuses performed and

therefore our ability to catch an eDNA trace

was also limited, resulted in only fish DNA

being detected. It is important to address that

while eDNA metabarcoding is very robust,

it can only provide an understanding of the

presence of biodiversity as a picture of the

moment of collection, but only constant moni-

toring could inform about species absence. This

research opened new questionings about the

state of biodiversity, and it is a good example of

how useful could eDNA tools be for ecosystems

monitoring and assessment

In respect to the number of fish families

detected (n = 52), 42 were identified using

eDNA, 26 with ITF and 15 through visual

censuses from which seven were detected by

all three methods (Fig. 2). In addition, 11 of

families detected with eDNA were validated by

the identifications made with ITF, and another

five families detected with eDNA were also

observed during visual censuses, confirming

those identifications. On the other hand, the

detections made with eDNA also included rare

species and represented 35 % of the total species

recorded, of which 14 species were observed and

collected during the expedition. Specimen col-

lection was effective for creating DNA barcodes

and 305 sequences and confirming taxonomic

assignments obtained with the other two meth-

ods. In this study we created a genetic reference

dataset for Tukakas Bay using DNA barcoding

(16S and COI) in BOLDSystems however, due

to the project funds and time limitations was

not possible to also include a database for 12S

which was the target gene for our eDNA meth-

ods. This could also explain the lower detection

of fish species that were observed and collected.

Future work in the area should address this gap

and further eDNA monitoring is recommended

to assess biodiversity.

Table 3 lists all fish species-level detec-

tion using the integrative taxonomy, observa-

tions and eDNA metabarcoding; however, it

is important to clarify that in the case of the

species/ASVs detected at the genus level such

as Abudefduf sp., Diapterus sp., Lachnolaimus

sp., and Syngnathus sp. that do not have other

known species in the Caribbean other than the

listed (Acero et al., 2023) could not necessarily

represent a different species but that their DNA

sequence did not match over 99 % the registered

in genetic databases (eg. BOLD, NCBI). This

situation could be a result of poor sequencing

performance, poor DNA quality of the case of

species differentiation, and was provided here

with the obtained resolution for future revision.

Each sampling effort is considered important

due to its own limitations with respect to bay

conditions, such as low visibility and high tur-

bidity that made visual fish surveys difficult,

very shallow areas due to high sedimentation,

and increasing temperatures. Environment that

could affect eDNA degradation rates and visible

habitat deterioration.

Fish biodiversity in Tukakas Bay: Fish

biodiversity in Tukakas Bay represents 35.5 %

of the total species recorded for La Guajira. The

combination of eDNA, visual censuses and ITF

in the Tukakas Bay allowed the identification of

95 fish species belonging to 68 genera and 52

14 Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e2025-676, enero-diciembre 2025 (Publicado Set. 23, 2025)

families. Environmental DNA alone detected

58 of these species which 65 % corresponded

to reef–associated species from 43 genera, from

which Mugil (n = 5 spp.) and Lutjanus (n = 4

spp.) had the most species detected (SMT 2).

These results coincide with the literature for

La Guajira (Acero et al., 2023; Aguirre-Pabón

et al., 2022; Escobar et al., 2019), since these

genera include migratory species that com-

monly form large schools around the produc-

tive shallow ecosystems of the department and

in the case of Mugil species, due to their high

abundance are part of the main food source in

the region (Mendoza-Ureche et al., 2019).

From all species identified, six (6.2 %)

were detected both by eDNA and visual census

associated with coral reefs including remora

Echeneis naucrates and green moray Gymno-

thorax funebris and eight (8.4 %) were vali-

dated both by ITF and eDNA including two

mojarra species (Eucinostomus gula and E.

jonesii) and grouper Epinephelus itajara. Only

needlefish Strongylura timucu was detected by

all three methods. Elasmobranchs and a larger

fish biodiversity were recorded only in the

outgroup station (n = 20 spp.) in comparison

to the smaller, juvenile and of low commercial

interest species associated with seagrass, soft

bottoms, and mangroves found inside Tukakas

Bay (SMT 4). This could be related to the bio-

physical conditions of the bay, that might be

restricting the horizontal migration of larger

individuals and therefore these species could

only be found at deeper zones away from the

shallow turbid ecosystems of the bay. However,

environmental parameters were not included

within this study due to unforeseen complica-

tions related to the hard accessibility to the area

and the limitations regarding environmental

sampling preservation and processing, there-

fore, further studies should explore other ways

to obtain these important measurements that

allow understanding the biodiversity dynamics

and patterns.

Although specimen collections and visual

census were not as effective as eDNA in detect-

ing fish species, all three methods evidenced

differences between species richness depending

on the habitat sampled. The number of spe-

cies detected associated with coral reef was

greater than the ones associated with muddy

bottoms. Low transparency of the water and

the very shallow areas played an important

role in limiting the performance of visual cen-

sus and specimen collections using artisanal

nets. According to Corpoguajira and Invemar

(2007), in the central part of Tukakas Bay there

is a channel approximately 4 to 5 meters deep

and on both sides of the channel there are ter-

races of consolidated terrain (medium to fine

sands) with Thalassia testudinum patches, at

just 20 cm. from the surface. Despite the envi-

ronmental demands that predominate in the

Alta Guajira sector, these seagrass meadows

continue to develop with a predominance of

the T. testudinum and Syringodium spp. inside

Tukakas Bay on the submerged margin in front

of most of the mangrove stands (Gómez-López

et al., 2014). Outside the bay, on the coral reef

zone, several macroalgae species have colonised

most decaying coral heads (some colonies of

Porites astreoides) up to approximately 4 m

deep, which have could have an impact on the

fish species distribution in the area.

Regarding to trophic levels among fish

detections, 67 % of all species are carnivorous,

feeding mostly on small invertebrates such

as crustaceans and molluscs and 14 % corre-

sponded to herbivores mostly reef–associated

species (SMT 3). No top predator was either

observed or detected inside the bay, which

could lead to ecosystem imbalance and serious

affectations to overall ecological health, further

studies should investigate the species dynam-

ics in the bay to determine possible ecological

patterns and the development of conservation

strategies in Tukakas Bay.

In this study, we demonstrated that the

combination of visual censuses, specimen col-

lections and eDNA metabarcoding is a power-

ful approach to describe a pristine and nearly

unknow area. We also demonstrated that the

integrating eDNA metabarcoding approaches

to traditional fish surveys significantly improves

biodiversity assessments specially in water with

low transparency and the very shallow areas

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e2025-676, enero-diciembre 2025 (Publicado Set. 23, 2025)

that limits the performance of visual census

and specimen collections using artisanal nets.

We were able to successfully describe fish bio-

diversity in the Tukakas Bay for the first time,

showing the absence of Elasmobranchs, larger

fish and thus top predators. These results high-

lighted the urgent need for the development of

conservation strategies in Tukakas Bay.

Data availability: All raw Illumina

sequencing data are available, and the pro-

cessed ASVs visualization matrix is public-

ly available at the GBIF DNA–derived data

publication test tool https://doi.org/10.21373/

wsuzwh. All biodiversity metadata including

morphological fish data from the Expedition

BIO Tukakas-Lamuuna Neimalu’u”, is published

at https://obis.org/dataset/e3c48dc5–ab62–

4652–a60e–1d05298ef385. Fish barcodes are

publicly available on BOLDSystems database

inside CCBIO container, under Project CBINP

(Colombia-BIO-INVEMAR-Peces-Tukakas).

Ethical statement: The authors declare

that they all agree with this publication and

made significant contributions; that there is no

conflict of interest of any kind; and that we fol-

lowed all pertinent ethical and legal procedures

and requirements. All financial sources are fully

and clearly stated in the acknowledgments sec-

tion. A signed document has been filed in the

journal archives.

See supplementary material

a55v73n1-suppl. 1

a55v73n1-suppl. 2

ACKNOWLEDGMENTS

Special thanks to the traditional indigenous

authorities of the district of Puerto López Mrs.

Sofía Romero-Icheput Community; Mr. José

Antonio González-Shopoiki Community; Mrs.

Adriana Gonzáles-Warruttamana Community;

Mr. Rufino González-Jichipaa Community;

Mrs. Iris Isabel Cambar-Warpana Community,

for allowing us to sample in their territory and

opening the doors of their homes and families.

To the Ministry of Science and Technology

through the National Financing Fund for Sci-

ence, Technology and Innovation, Francisco

José De Caldas Fund for financing the BIO

Expedition under Contract No. 092–2022; to

the Marine and Coastal Research Institute “José

Benito Vives de Andreis”- INVEMAR for co–

financing the Project and their administrative

and logistical support specially to the project

coordinators David Alonso Carvajal, Cristina

Cedeño Posso and Martha Vides Casado. We

thank Natalia Rivas for supporting the speci-

men collections and visual censuses. To the

Information Services Laboratory (LABSIS,

GEZ) for preparing the map and the staff of the

Marine Natural History Museum of Colombia-

MAKURIWA for their collaboration during the

expedition especially to Erika Montoya Cada-

vid for her support with specimen metadata

visualization and publication. Contribution No.

1406 from the Marine and Coastal Research

Institute (INVEMAR). We thank SPYGEN staff

for their help in the eDNA laboratory analysis.

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