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Article

Population Structure of the Dog Snapper, Lutjanus jocu (Bloch & Schneider, 1801), an Important Fishery Resource in the North of Bahia, Brazil: Influence of Habitat Suitability, Larvae Retention, and Fishing Pressure

by
Glaciane Conceição Marques
1,2,
Juliana Beltramin De Biasi
1,2,
Carlos Werner Hackradt
2,* and
Fabiana Cezar Félix-Hackradt
2
1
Programa de Pós-Graduação Sistemas Aquáticos Tropicais, Universidade Estadual de Santa Cruz, Campus Soane Soane Nazaré de Andrade, Ilhéus 45662-900, BA, Brazil; Universidade Federal do Sul da Bahia, Campus Sosígenes Costa, Porto Seguro 45810-000, BA, Brazil
2
Marine Ecology and Conservation Laboratory, Universidade Federal do Sul da Bahia, Porto Seguro 45810-000, BA, Brazil
*
Author to whom correspondence should be addressed.
Coasts 2025, 5(2), 21; https://doi.org/10.3390/coasts5020021
Submission received: 1 April 2025 / Revised: 29 May 2025 / Accepted: 5 June 2025 / Published: 16 June 2025
Browse Figures
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Abstract

:
The Lutjanidae family includes multiple species highly important to the global fishing industry. In Brazil, approximately 40% of the fishing landings come from a species of this family, the dog snapper, Lutjanus jocu, among the most abundant in the northeast-region fisheries. This study aimed to analyze the genetic diversity and population structure of this species in the states of Bahia and Espírito Santo through the use of microsatellite markers. The dog snapper presented a high genetic variability in the studied populations, with the presence of a distinct population stock in northern Bahia probably driven by habitat suitability, larvae retention, and fishing pressure. The L. jocu sampling sites exhibited an excess of heterozygosity, a low allelic richness, and M-ratio values close to critical levels, probably indicating a recent population decline. Additionally, the low inbreeding indices and high genetic diversity values suggest a significant connectivity and considerably effective population sizes. Although these characteristics may reflect population stability, anthropogenic factors such as habitat loss, fragmentation, and overfishing may pose threats to the sustainability of the species, particularly along the northeastern coast of Brazil.

1. Introduction

Marine environments represent one of the largest sources of biodiversity on the planet, encompassing diverse ecosystems such as mangroves, estuaries, and coral reefs [1]. For a long time, the absence of physical barriers was used as an argument to propose that marine populations were genetically homogeneous and panmitic [2]. However, more recent evidence shows that, even in ecosystems free of physical barriers, environmental, biological, and historical factors significantly influence the genetic connectivity between marine fish populations.
Although the gene flow between marine populations is intense due to the larval dispersal during the planktonic phase, variables such as the effective population size, the duration of the pelagic larval phase, and environmental factors act as filters, restricting the gene flow and generating patterns of genetic divergence [3,4]. These factors, combined with habitat discontinuities, depth, and historical dispersal processes, play a fundamental role in the generation of genetic structures between populations [5,6]. In addition, human activities such as habitat fragmentation, pollution, overfishing, and the introduction of exotic species can exacerbate population differences and contribute to the loss of genetic diversity and increased vulnerability of marine populations [7,8].
In this scenario, Lutjanus jocu, belonging to the Lutjanidae family (Perciformes), stands out as a key species for genetic and ecological studies. The Lutjanidae family includes approximately 113 described species and is of significant global fishing importance, with catches reaching up to 125,000 tons annually [9]. In Brazil, approximately 40% of the fishing landings come from species of this family [3,6]. Lutjanus jocu has a wide distribution in the Southwest Atlantic Ocean, extending from Massachusetts to the southeast of Brazil, with a higher density in the northeast coast [10,11]. It is considered an important mesopredator for the dynamics of reef ecosystems and exhibits reproductive aggregation behavior, making it especially vulnerable to fishing [12,13].
Recent data show that Lutjanus jocu exhibits high levels of genetic diversity and a strong population connectivity along the Brazilian coast [14]. This suggests that the species forms a single genetic unit, driven by the efficient dispersal of its larvae, particularly due to equatorial currents [15]. A historical analysis also suggests that environmental and climatic changes, such as ecological barriers during the Pleistocene, influenced the species population dynamics, leading to significant expansion events and demographic changes regardless its economic importance to fisheries [15].
Despite these advances, information on the current genetic structure of L. jocu, as well as the ecological factors and anthropogenic impacts affecting its populations, is still limited, as is the use of different molecular markers in investigating these factors. Previous studies focused on understanding how past events shaped the genetic structure of L. jocu, especially variations in the population size over time by employing neutral [14], SNP [15] or mtDNA [14,16] markers. However, high mutation rate markers such as microsatellites or SNPs were preferable for detecting small-scale, as well as recent patterns of genetic diversity, such as genetic losses produced by fisheries [17]. Thus, exploring these elements is essential for supporting conservation strategies and sustainable management. In this context, we transferred microsatellites markers available in the literature in order to understand the connectivity pattern and genetic diversity of Lutjanus jocu. Our goal was to address the following questions: (i) Are the populations of Lutjanus jocu homogeneous? (ii) What is the level of genetic variability along 1200 km of coastline? (iii) Are microsatellite markers efficient for conservation genetics studies? This study provides complementary data that can assist in the effective management and conservation of L. jocu along the Brazilian coast.

2. Materials and Methods

2.1. Sampling

Samples of L. jocu were collected along 1200 km of coastline, between Bahia and Espírito Santo coasts. These include Salvador (SSA), Porto Seguro (PS), Abrolhos (ABR), and Espírito Santo (ES), which represent fishing areas extending from Porto da Barra to Morro de São Paulo (SSA), between Royal Charlotte and the northern region of Abrolhos (PS), from the southern portion of the Abrolhos Bank to Linhares (ABR), and from Linhares to Piúma, including the Vitória–Trindade chain (ES) (Figure 1). Samples from 40 individuals were randomly collected from fish landings or directly from fishermen at each location according to availability, for tissue extraction. For each individual, a 5 × 5 cm fin fragment was collected, placed in labeled vials, and stored in 70% alcohol during transportation to the Marine Ecology and Conservation Laboratory (LECOMAR) at UFSB. In the laboratory, all samples were stored in a freezer at −80 °C until DNA extraction, ensuring their complete preservation.

2.2. Genetic Analyses

DNA Extraction, Amplification, and Sequencing

DNA extraction was performed using extraction kits (PureLink™ Genomic DNA Kit—Invitrogen, ThermoFisher Scientific™, Waltham, MA, USA) following the protocol provided by the manufacturer. After extraction, DNA concentration was quantified using the Qubit Fluorometric Quantitation system (ThermoFisher Scientific™). Primers originally developed for the species Lutjanus analis, Lutjanus synagris, and Ocyurus chrysurus (renamed to L. chrysurus) and described by Shulzitski et al. [18] and Renshaw et al. [19] were tested to evaluate their inter-specific transferability to the target species of this study. Those markers were used due to the phylogenetic proximity of the studied species and its congeneric. Of the 12 tested, 10 were found to be polymorphic loci and were selected for genetic diversity analysis. These loci were distributed across three different primer mixes used in multiplex PCR reactions, organized according to primer compatibility, considering annealing temperature and the expected size of the amplified fragments, in order to avoid peak overlap in the electropherograms (Table S1). Amplification reactions were performed using the Type-it Microsatellite PCR Kit™ with adjustments to the manufacturer’s protocol, containing 1.5 μL of DNA, 3.25 μL of Type-it, 0.75 μL of primer mix at 0.25 μM derived from a stock solution of 5 μM, and 2 μL of ultrapure water. Amplifications were carried out in 3 multiplex reactions (see Table S1) following the touchdown protocol: the first cycle at 95 °C for 5 min, 35 cycles at 95 °C for 1 min, 53 °C to 58 °C for 1 min, 72 °C for 1 min, and a final extension at 72 °C for 10 min. A positive (high-quality DNA) and a negative (no DNA) control were included in all amplification rounds. For genotyping, 1.5 μL of the PCR product was diluted in 0.2 μL of LIZ 600 + 8.3 μL of formamide. Genotyping was performed on the automatic sequencer SeqStudio (Thermo Fisher Scientific, Waltham, MA, USA), using GeneScan 600 LIZ Size Standard (Thermo Fisher Scientific) as the size standard.

2.3. Data Analysis

Allele identification was performed using Geneious 7.1.9.9 software [20]. Loci and individuals with more than 20% missing data were excluded from the analysis, and the polymorphism index was evaluated by the polymorphic information content (PIC), calculated using the “poppr” package in R. Genetic diversity was determined using several indices: number of alleles (A), private alleles (Ap), mean allelic richness (Ar), observed heterozygosity (HO), expected heterozygosity (HE), and Hardy–Weinberg equilibrium (HWE), which was tested for each locus through 2000 Monte Carlo permutations. Significance levels were adjusted with the sequential Bonferroni correction [21]. Linkage disequilibrium between loci was investigated using the general linkage test, with significance tested based on 999 permutations. All calculations were conducted using the “diveRsity” and “poppr” [22] packages in R.
To evaluate the existence of total and locus-specific genetic structure, the Jost’s D (Dest) index [23] was calculated, and significance was determined through 10,000 bootstrap repetitions using the “hierfstat” package in R. Additionally, the inbreeding coefficient (FIS) and fixation index (FST) were calculated for each locus [24] using the “hierfstat” and “adegenet” packages in R [25,26]. A Bayesian clustering analysis was performed using STRUCTURE v2.3.4 software [27], with ten repetitions for each inferred population, each with 1,000,000 MCMC steps and 100,000 iterations. The optimal number of population clusters (K) was based on the second-order rate of change of LnP(D) and the AIC index [28] through the pophelper v2.3.1 web application [29]. Additionally, we used discriminant analysis of principal components (DAPC) and the BIC index to select the number of principal components that explain the variation in the genetic data using the “adegenet” [25,30,31], “factoextra”, and “ade4” [32] packages. Finally, a hierarchical analysis of molecular variance (AMOVA) was performed to test the significance of the clusters formed from STRUCTURE and DAPC, using 999 permutations in the ‘poppr’ package [22].
To test the isolation-by-distance (IBD) hypothesis, we used the Mantel test with 9999 permutations through the “ade4” package [32]. The extent and direction of gene flow were estimated using calculations of the relative migration rate and direction, assuming that gene flows are bidirectional and asymmetric, based on Nei’s GST and 1000 bootstrap repetitions using the “DEMEtics” package [21].

3. Results

3.1. Genetic Variability

Twelve loci were analyzed, of which ten were successfully transferred and found to be highly polymorphic, making them crucial for the evaluation of genetic variability. These loci, originally developed for species within the same genus as Lutjanus analis, Lutjanus ocyurus, and Lutjanus synagris, proved effective in amplifying the microsatellite DNA region of L. jocu species. All loci were included in the analysis based on their PIC values (Table S2). The number of samples analyzed (n) varied across the locations, with values ranging from 15 (ES) to 41 (ABR).
About 50% of the loci were in Hardy–Weinberg equilibrium (HWE), particularly those associated with primers from L. annalis LA25 and LA39, L. synagris LSY13, and L. chrysurus OCH13 (Table S2). However, when considering the localities, it was observed that all the populations were at equilibrium (HWE = 0). None of the loci showed evidence of linkage disequilibrium after applying the Bonferroni correction (Figure S1 and Table S3).
The number of alleles (A) per locus and locality (Table 1) varied slightly, ranging from 2 to 7 per locus, and between 36 (ES) and 41 (PS and ABR) per locality, following the same pattern as allele richness, which was lower in ES (3.42) and higher in PS (3.83). The heterozygosity indices, on the other hand, were higher in SSA (HE = 0.65, HO = 0.64) and lower in ES (HE = 0.58) and PS (HO = 0.59), but PS was the only locality where HO < HE. Similarly, the FIS value at PS was positive, while the other localities had negative values (an excess of heterozygotes); however, all values were close to zero (−0.03 to 0.06), indicating a low level of inbreeding. All localities showed M-ratio values above critical (Mc = 0.68), not indicating a recent population reduction, according to Garza and Williamson [33], although values were very close to critical. It is worth noting that, regardless of the locality, OCH9 was the locus with the lowest genetic diversity indices and the highest inbreeding values, while LA25 showed the lowest M-ratio values (Table S3).

3.2. Genetic Structure

The genetic structure analysis of L. jocu conducted in the STRUCTURE program identified the existence of two population stocks between the populations of the states of Bahia and Espírito Santo, with SSA individuals distinguishing from other localities. The presence of individuals with distinct genotypes from the predominant one was observed in all localities, especially in SSA, where the proportion of individuals was higher (Figure 2). Similarly, the discriminant analysis of principal components (DAPC) reinforced the genetic structure present in SSA compared to the other localities, where the two discriminant axes accounted for 88% of the genetic data variation (Figure 2).
Additionally, the analysis of molecular variance (AMOVA) revealed a significant substructure between the SSA locality and the others (PS + ABR + ES), indicating that 15.72% of the genetic variation is explained by these groupings and another 9% is within those groups. However, the vast majority of the existing genetic variability, 75.15%, occurred within the samples (Table 2).
The results of the FST fixation and the D Jost indices confirmed the existence of genetic differentiation among the subpopulations of L. jocu across the sampled locations. Significant FST and D values were observed between SSA samples and other localities, and also between PS and ES, but differences between PS and ABR were detected only for D values (Table 3).
The result obtained from the relative migration network, based on Nei’s GST (Figure 3), revealed a strong connectivity between the PS, ABR, and ES locations, and reduced the gene flow between these locations and SSA, particularly involving ES (GST = 0.17) and ABR (GST = 0.23). The Mantel test, which correlates the FST index with geographic distance (km), showed a low and non-significant correlation coefficient (r = 0.329, p = 0.708), not supporting the isolation-by-distance hypothesis for the L. jocu populations analyzed.

4. Discussion

Despite recent studies indicating that L. jocu consists of a single highly connected population, we found that, along 1200 km of coastline, this species of highly economic importance for traditional populations in northeastern Brazil showed two genetic clusters, with the Salvador population being distinct from other southern localities (Porto Seguro, Abrolhos, and Espirito Santo). Despite the intense fishing activity, it maintains a high genetic diversity and did not show signs of recent population decline, although the M-ratio values are very close to critical and a low allelic richness was observed. In this sense, precautions should be taken in the fishery management of this species, even though its population does not appear to be experiencing genetic effects from exploitation or other anthropogenic impacts.
The populations of Lutjanus jocu between Bahia and Espírito Santo showed characteristics suggesting they are in Hardy–Weinberg equilibrium, which may be related to the observed excess of heterozygosity. The excess of heterozygotes is commonly related to (i) the Whalund effect, when admixed populations combine together, improving heterozigosity levels [34], or (ii) bottleneck effects, where the reduction in population size leads to the loss in alleles more quickly than the loss in heterozygosity; or, also, (iii) by a high gene flow and large population sizes, which reduce the impact from inbreeding depression and drift by retaining genetic diversity [35].
Due to the fact that our results did not indicate population admixture (see below), it remains to be assumed that the heterozygosity excess was produced by bottleneck events and/or by a large population with a high gene flow.
During bottlenecks, many alleles can be lost without an immediate reduction in heterozygosity, which may lead to a temporary “excess of heterozygotes”, as discussed by Luikart and Cornuet [36]. Previous studies on Lutjanus jocu have identified a historical bottleneck event, followed by population expansion, attributed to fluctuations in habitat availability driven by sea-level changes during the last glacial–interglacial cycles [15,16]. During glacial periods, the reduction in coastal habitat accessibility led to population contraction. Subsequent ice melt and rising sea levels provided new habitat opportunities, facilitating demographic recovery in L. jocu. Although our results did not indicate bottleneck effects, the low allelic richness found (mean 3.6), along with the negative values of Fis in most localities, and the M-ratio values close to critical (Mc = 0.68) for all populations, especially at PS, are consistent with the recent population reduction effects.
Other congeneric species widely used for commercial purposes also show high heterozygosity indices, as observed in Lutjanus analis (h = 0.9926, π = 3.7%) [37], Lutjanus alexandrei (h = 0.999, π = 3.9%) [6], Lutjanus chrysurus (h = 0.963, π = 1.7%) [38], and, also, in Lutjanus jocu (h = 0.9984, π = 2.6%) [14]. The high genetic connectivity, possibly attributed to a combination of historical and ecological factors, including sea level fluctuations during the Pleistocene and habitat continuity, for example, may have facilitated the expansion of coastal populations, contributing to the maintenance of genetic diversity [3,6,15,38]. Additionally, coastal currents, such as the Brazil Current, favor larval dispersal, which can last in the planktonic phase for about 25 days [39], homogenizing populations and sustaining genetic diversity in species widely distributed in the South Atlantic [40,41]. Consequently, the heterozygosity excess can be attributed to either the population reduction effects or high connectivity; but see below.
However, using microsatellite molecular markers, our study reveals an important population structure distinguishing the northernmost L. jocu population (SSA) from others, in disagreement with recent studies that considered L. jocu as a panmitic population across the Brazilian coast [14,15,16]. Those studies employed mtDNA markers [14,16] which have a lower power to detect population differences than microsatellites. Furthermore, the spatial scale of their work was broader, covering more sectors of the Brazilian coast, which may mask small-scale differences. However, Verba et al. [15], using SNP markers, and highly polymorphic markers such as microsatellites, find support in the STRUCTURE results for both k = 1 and k = 2 studying L. jocu along the Brazilian coast. However, due to the large variance found at k = 2, they concluded that the most parsimonious result was a panmitic distribution.
Nevertheless, our analysis of molecular variance (AMOVA) revealed a statistically significant difference between the Salvador locality and the others, accounting for 21.62% of the variation observed. The genetic differentiation is sustained by a high and significant FST and D Jost indices. However, the observed genetic structure is not explained by the isolation-by-distance (IBD) hypothesis, indicating that other factors may be influencing this variation.
The restriction of gene flow between the individuals from Salvador (SSA) and the other localities was also evidenced by the connectivity network analysis, which revealed a complex gene flow pattern. Abrolhos and Espirito Santo were the most connected localities, and a gradual restriction of gene flow were observed while moving north, with Porto Seguro more connected to ABR than ES and SSA, and SSA more connected to ABR and ES than PS. This pattern may be associated with the step-in-stone model, where the gene flow occurs indirectly through intermediate populations, rather than direct connections [42], normally as a result of adult movement, but also through coastal currents which facilitate long-distance larval connectivity southward [41,43].
Furthermore, habitat plays a crucial role in reef fish genetic patterns [44]. The coast of Salvador has the narrowest shelf (8 km wide) in the entire Brazilian continental margin [45]. In their work, Verba et al. [15] observed that the northern region of Bahia state (~SSA) along with CE appears to have less suitable habitats for the dog snapper, displaying high levels of pairwise FST between these localities and others evaluated. The habitat restriction might be the one possible explanation of SSA isolation from other localities in our work. Moreover, the Abrolhos bank encompasses an extensive shallow continental area with 47.000 km2 [46] extending from Prado (Bahia) until Linhares (ES) [47], in which the most important coral reef formations of South Atlantic lies [48,49]. Although L. jocu is considered an estuarine-dependent species, it can live in marine environments through its entire life cycle [11], using shelf reefs as their main living area. The great habitat availability in the Abrolhos bank may have contributed to the higher connectivity of ABR-ES samples, and in a lower proportion with PS. Although Royal Charlotte is the northern extension of the Abrolhos bank, and very close to Porto Seguro, it has a much smaller area, 7000 km2, proportionate with the lower reef cover [50], and, thus, contributing to the lower habitat availability.
Although this study did not aim to assess the impact of fishing on the genetic diversity of L. jocu, we cannot disregard its potential influence. The L. jocu, like other snappers, are important carnivorous species which play a fundamental role in equilibrating other prey populations in coral reef systems [51]. They engage in spawning aggregation events (SA) which are important mechanisms to maximize the reproductive output and contribute to genetic homogenization. Many SAs were already identified through the whole study range. França et al. [52] have observed some evidence of dog snapper aggregations just in the south of Salvador region and also in the Abrolhos bank [13,51], an important fishing ground for this species. SAs are highly spatially predictable due to individuals’ fidelity to reproductive sites [53]. Therefore, fishing pressure over those SA sites might produce negative effects on population species sustainability, especially for long-lived species such as L. jocu [54].
Similarly to global reef fisheries, the snapper–grouper complex is the most important species target in the Brazilian Northeast region [55]. In fact, L. jocu was the second most abundant species observed in spearfishing monitoring through the Bahia state, with the greatest captures occurring in the Salvador region [56]. The high fishing pressure of the dog snapper in SSA and its surroundings, together with habitat limitation, may have strengthened the population structure observed in this study. SA events usually occur at shelf-edges, continental slopes, or other deep reef environment [13], which, at the SSA locality, is situated very close to shore. The intense fishing activity, facilitated by the greater proximity of fishing grounds, might have reduced the number of fish participating in SA events, contributing to the SSA distinct genetic pattern through the loss of genetic diversity [57].
Finally, according to the biophysical modeling of Cuban snappers’ larval connectivity from spawning aggregations, the majority of larvae produced in those reproductive events settle within the same region where they were spawned, with the mean local retention varying from 18 to 50% [58]. Salvador is located at the second-largest estuarine embayment of the Brazilian coast, the “Todos os Santos Bay”, at 1100 km2 [59]. This large estuarine system in the northernmost region evaluated in this study must have contributed to the retention of most fish larvae produced at the dog snapper spawning sites, which are closest to the shore, thus supporting the isolation of the SSA region.
Due to its biological traits—including a long lifespan, late maturity, and aggregation spawning—Lutjanus jocu exhibits a high vulnerability to overfishing [60]. A recent review indicates a temporal decline in Lutjanus spp. landings since 1990, alongside reductions in mean body size, suggesting an overfishing effect [61]. Bigger snapper and grouper species have been substituted by larger low-trophic species such as parrotfishes or smaller invertivores, in a clear “fishing down the marine food web” pattern. However, the impacts of fishing on the genetic diversity of L. jocu remain poorly understood. Large-scale genetic comparisons between populations inside Marine Protected Areas (MPAs) and adjacent fished zones could elucidate fishery-induced genetic changes. Additionally, integrating genetic larval assignment with biophysical dispersal models would help quantify local retention rates from spawning aggregations, clarifying their role in population sustainability and their importance for local fisheries.

5. Conclusions

We conclude that the populations of Lutjanus jocu in Bahia and Espírito Santo exhibit a high genetic variability, with the presence of a distinguishing population stock in northern Bahia, probably mediated by habitat suitability, larvae retention, and fishing pressure. The studied species showed an excess of heterozygosity, a low allelic richness, and close-to-critical M-ratio values in the studied localities, evidencing a recent population reduction. Moreover, a low inbreeding rate and high genetic diversity values indicate a high connectivity and large population effective sizes. These characteristics might reflect population stability, but anthropogenic factors such as habitat loss and fragmentation, as well as overfishing, can impose difficulties on L. jocu sustainability, especially along the northeast Brazilian coast. Due to its importance to local artisanal fisheries and high vulnerability, management actions such as protecting spawning aggregation sites, establishing minimum and maximum sizes of capture, and implementing MPAs, which integrates essential habitats for L. jocu, should be carried out in order to prevent it from over-exploitation. Additionally, the genetic uniqueness of SSA samples should be considered in the development of more effective management and conservation strategies for the dog snapper, which plays a critical role in the population dynamics of Brazilian reefs.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/coasts5020021/s1; Table S1: Descriptions of the primers used for amplification of microsatellite DNA fragments in Lutjanus jocu; Table S2: Values of polymorphic information content (PIC) for each locus; Table S3: Genetic diversity descriptors of Lutjanus jocu from 10 microsatellite loci, collected in Salvador, Porto Seguro, Abrolhos, and Espírito Santo; Table S4: Values of linkage disequilibrium for the loci after Bonferroni correction; Figure S1: Graph with values of linkage disequilibrium for the loci.

Author Contributions

Conceptualization, G.C.M. and F.C.F.-H.; methodology, G.C.M., F.C.F.-H. and J.B.D.B.; software genetic analysis, G.C.M.; formal analysis, G.C.M. and J.B.D.B.; resources, and writing—original draft preparation, G.C.M. and F.C.F.-H.; writing—review and editing, G.C.M., F.C.F.-H. and C.W.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All relevant data are contained in this document and Supplementary Materials.

Acknowledgments

We acknowledge the Fishermen’s Association of Itapuã for their collaboration in collecting the samples from Salvador. The first author received a scholarship from FAPESB (Foundation for Research Support of the State of Bahia) BOL0280/2023.

Conflicts of Interest

The authors declare that there are no conflicts of interest.

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Figure 1. Sampling areas of Lutjanus jocu specimens. A1—Salvador (n = 32), A2—Porto Seguro (n = 37), A3—Abrolhos (n = 41), and A4—Espírito Santo (n = 15).
Figure 1. Sampling areas of Lutjanus jocu specimens. A1—Salvador (n = 32), A2—Porto Seguro (n = 37), A3—Abrolhos (n = 41), and A4—Espírito Santo (n = 15).
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Figure 2. Bayesian population structure analysis of Lutjanus jocu showing (A) the STRUCTURE result, indicating the existence of two gene pools, (B) the Evanno Method result with K = 2 as the most likely number of genetic clusters, and (C) the DAPC result showing the separation of the SSA samples based on genetic variation. Legend: Salvador (SSA), Porto Seguro (PS), Abrolhos (ABR), and Espírito Santo (ES).
Figure 2. Bayesian population structure analysis of Lutjanus jocu showing (A) the STRUCTURE result, indicating the existence of two gene pools, (B) the Evanno Method result with K = 2 as the most likely number of genetic clusters, and (C) the DAPC result showing the separation of the SSA samples based on genetic variation. Legend: Salvador (SSA), Porto Seguro (PS), Abrolhos (ABR), and Espírito Santo (ES).
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Figure 3. Data from the directional relative migration network between the sampled locations based on Nei’s GST. The arrows indicate the direction, and the thickness and colors of the lines represent the intensity of gene flow between the studied subpopulations. Legend: Salvador (SSA), Porto Seguro (PS), Abrolhos (ABR), and Espírito Santo (ES).
Figure 3. Data from the directional relative migration network between the sampled locations based on Nei’s GST. The arrows indicate the direction, and the thickness and colors of the lines represent the intensity of gene flow between the studied subpopulations. Legend: Salvador (SSA), Porto Seguro (PS), Abrolhos (ABR), and Espírito Santo (ES).
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Table 1. Genetic diversity descriptors of L. jocu based on 10 microsatellite loci, collected in Salvador (SSA), Porto Seguro (PS), Abrolhos (ABR), and Espírito Santo (ES). Legend: n = number of samples, A = number of alleles, Ar = allelic richness, Ap = number of private alleles, HO = observed heterozygosity, HE = expected heterozygosity, Fis = inbreeding coefficient, M-ratio = bottleneck effect.
Table 1. Genetic diversity descriptors of L. jocu based on 10 microsatellite loci, collected in Salvador (SSA), Porto Seguro (PS), Abrolhos (ABR), and Espírito Santo (ES). Legend: n = number of samples, A = number of alleles, Ar = allelic richness, Ap = number of private alleles, HO = observed heterozygosity, HE = expected heterozygosity, Fis = inbreeding coefficient, M-ratio = bottleneck effect.
LocalitiesSSAPSABRES
n30.335.14014.6
A38414136
Ar3.663.833.733.42
Ap0111
HO0.650.590.620.60
He0.640.630.610.58
FIS−0.010.06−0.02−0.03
M-ratio0.800.690.810.82
Table 2. Analysis of Molecular Variance (AMOVA), indicating the partitioning of variance according to the analyzed localities. All sigma values were significant (p < 0.05). Legend: Df—degrees of freedom, Sum Sq—sum of squares, Mean Sq—mean squares, sigma—standard deviation, % of total—proportion of total variance. Statistical significance: p < 0.001 (*).
Table 2. Analysis of Molecular Variance (AMOVA), indicating the partitioning of variance according to the analyzed localities. All sigma values were significant (p < 0.05). Legend: Df—degrees of freedom, Sum Sq—sum of squares, Mean Sq—mean squares, sigma—standard deviation, % of total—proportion of total variance. Statistical significance: p < 0.001 (*).
Source of VariationDfSum SqMean SqSigma% of Total
Between groups143.30343.300.6015.72
Within groups226.11613.050.359.12
Within populations123350.6172.892.89 *75.15
Total126420.03759.243.85100
Table 3. Values of the pairwise FST (lower diagonal) and D Jost (upper diagonal) indices, indicating genetic differences between the sampled locations. Statistical significance: p > 0.05 (ns), p < 0.05 (*), p < 0.01 (**).
Table 3. Values of the pairwise FST (lower diagonal) and D Jost (upper diagonal) indices, indicating genetic differences between the sampled locations. Statistical significance: p > 0.05 (ns), p < 0.05 (*), p < 0.01 (**).
AbrolhosEspírito SantoPorto SeguroSalvador
Abrolhos 0.0290.0590.111 **
Espírito Santo0.012 0.092 **0.103 **
Porto Seguro0.0240.043 * 0.112 **
Salvador0.075 *0.077 *0.074 *
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Marques, G.C.; De Biasi, J.B.; Hackradt, C.W.; Félix-Hackradt, F.C. Population Structure of the Dog Snapper, Lutjanus jocu (Bloch & Schneider, 1801), an Important Fishery Resource in the North of Bahia, Brazil: Influence of Habitat Suitability, Larvae Retention, and Fishing Pressure. Coasts 2025, 5, 21. https://doi.org/10.3390/coasts5020021

AMA Style

Marques GC, De Biasi JB, Hackradt CW, Félix-Hackradt FC. Population Structure of the Dog Snapper, Lutjanus jocu (Bloch & Schneider, 1801), an Important Fishery Resource in the North of Bahia, Brazil: Influence of Habitat Suitability, Larvae Retention, and Fishing Pressure. Coasts. 2025; 5(2):21. https://doi.org/10.3390/coasts5020021

Chicago/Turabian Style

Marques, Glaciane Conceição, Juliana Beltramin De Biasi, Carlos Werner Hackradt, and Fabiana Cezar Félix-Hackradt. 2025. "Population Structure of the Dog Snapper, Lutjanus jocu (Bloch & Schneider, 1801), an Important Fishery Resource in the North of Bahia, Brazil: Influence of Habitat Suitability, Larvae Retention, and Fishing Pressure" Coasts 5, no. 2: 21. https://doi.org/10.3390/coasts5020021

APA Style

Marques, G. C., De Biasi, J. B., Hackradt, C. W., & Félix-Hackradt, F. C. (2025). Population Structure of the Dog Snapper, Lutjanus jocu (Bloch & Schneider, 1801), an Important Fishery Resource in the North of Bahia, Brazil: Influence of Habitat Suitability, Larvae Retention, and Fishing Pressure. Coasts, 5(2), 21. https://doi.org/10.3390/coasts5020021

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