Benthic Ostracods as Indicators of Nearshore Pollution: An Example from Hurghada Bay, Red Sea Coast, Egypt

Abstract

Twenty-nine sediment samples were collected from Hurghada Bay, a highly impacted coastal area along the Northern Red Sea of Egypt, to evaluate environmental quality and human-induced effects on benthic ostracods. As potential bioindicators, benthic ostracods are highly responsive to environmental disturbances, with pollution leading to reduced abundance, lower diversity, and increased opportunistic taxa. To investigate the link between ostracod assemblages and sediment contamination, we measured the concentrations of eight heavy metals (Cu, Cd, Zn, Pb, As, Cr, Ni, and Mn) using inductively coupled plasma–atomic emission spectrometry (ICP-AES). Multivariate statistical analyses identified three distinct ostracod assemblages distributed across three station groups with varying pollution levels. Group I, associated with offshore stations, exhibited low to moderate heavy metal (HM) concentrations and high ostracod abundance and was dominated by Moosella striata, Hiltermannicythere rubrimaris, Ruggieria danielopoli, Neonesidea schulzi, and Paranesidea fracticorallcola, where the water depth and sand content are the main controlling factors. In contrast, Group II, corresponding to stations with the highest HMs and total organic matter (TOM), was dominated by pollution-tolerant species Jugosocythereis borchersi, Cyprideis torosa, Alocopocythere reticulata, and, to a lesser extent, Ghardaglaia triebeli, with reduced ostracod density and diversity. Group III, characterized by stations influenced by the mud-controlling factor, had the lowest HMs and was dominated by pollution-sensitive species Xestoleberis rhomboidei, Paranesidea fortificata, and Loxocorniculum ghardaquensis. These findings highlight the ecological risks posed by HM pollution and emphasize the urgent need for pollution mitigation strategies and continued monitoring to preserve the Red Sea’s benthic biodiversity.

1. Introduction

Coastal ecosystems are highly dynamic environments that support diverse marine life and provide essential ecosystem benefits. However, rapid urbanization and tourism-related activities have intensified environmental stressors, particularly in fragile marine environments like the Red Sea [1,2,3]. Coastal cities, such as Hurghada, have experienced significant expansion in the past few decades due to the growing tourism sector, leading to increased construction, sewage discharge, and other anthropogenic influences [4,5]. These human-induced disturbances contribute to various forms of pollution, including heavy metal contamination, organic enrichment, and eutrophication, all of which seriously threaten marine biodiversity [6,7,8,9].

Heavy metals such as lead (Pb), cadmium (Cd), mercury (Hg), and zinc (Zn) accumulate in marine sediments due to industrial runoff, urban waste, and fuel combustion residues, posing a persistent threat to benthic ecosystems [10,11,12]. Once deposited, these pollutants alter sediment chemistry, disrupt benthic communities, and can enter the food chain, impacting marine organisms at multiple trophic levels [13]. Given the urgency of assessing and mitigating pollution in such vulnerable ecosystems, biological indicators offer a robust, integrative approach to environmental biomonitoring.

Several studies have highlighted the need for meiofaunal biomonitoring approaches [14] to assess pollution levels in coastal environments using [1,13,15]. While benthic foraminifera have been widely used as bioindicators, recent research has emphasized the potential of benthic ostracods as complementary tools for environmental assessments [1,2,15,16]. Benthic ostracods are small, bivalved crustaceans that inhabit marine, brackish, and freshwater environments [17]. Their calcareous shells fossilized readily, making them excellent paleoenvironmental indicators [18]. Recent (living) benthic ostracods are particularly useful for monitoring environmental changes due to their sensitivity to pollution, including heavy metal contamination [2], organic enrichment [19], and changes in salinity and oxygen levels [20,21,22]. Compared to foraminifera, ostracods offer several advantages as bioindicators: they occupy various microhabitats, allowing for a broader assessment of environmental conditions [23]. Their calcified carapaces can incorporate trace metals, reflecting water and sediment chemistry [18]. However, ostracods also have certain limitations, such as lower abundances in some polluted environments and the need for detailed taxonomic expertise. Combined with foraminifera and heavy metal analyses, they provide a more comprehensive picture of ecosystem health [24,25]. While foraminifera have been widely used in bio-monitoring studies, ostracods offer complementary insights, particularly in shallow marine environments where their responses may vary due to ecological and/or physiological differences [26]. Thus, their presence or absence and shell chemistry provide an integrated measure of environmental disturbance.

The escalating environmental pressures along the Red Sea coast, particularly in Hurghada, underscore the urgent need for fine-scale biomonitoring to capture rapid ecological shifts. Unregulated tourism expansion, untreated sewage discharge, and relentless coastal development have disrupted the delicate marine balance, leaving a legacy of heavy metal accumulation and organic pollution. Although contamination hotspots have been identified in parts of the Red Sea, biomonitoring efforts using benthic ostracods as ecological sentinels remain scarce. This study fills that critical gap, leveraging ostracod assemblages to decode pollution impacts and pave the way for informed conservation strategies and sustainable coastal stewardship. By combining ecological and geochemical analyses, this research provides a multi-proxy approach to environmental monitoring in the Red Sea, addressing global knowledge gaps in pollution assessment.

The present work is part of an ongoing project to assess the environmental impacts on the Hurghada ecosystem using several proxies [5]. Integrating biological indicators, such as ostracods, with geochemical sediment analyses enhances pollution assessments. The studied stations and associated environmental parameters were previously investigated by El-Kahawy and Mabrouk [5], who analyzed benthic foraminiferal assemblages as bioindicators of heavy metal contamination in this area. In contrast, the present study utilizes the same sampling stations and environmental dataset to explore how benthic ostracod communities reflect micro-scale pollution gradients and reshape ecological niche influenced by anthropogenic pressure in a rapidly developing coastal ecosystem like Hurghada Bay. Accordingly, this study aims to provide a more refined understanding of pollution dynamics by comparing ostracod assemblages with sediment heavy metal concentrations. Therefore, the main objectives of this study are to 1—investigate the ostracod distribution pattern in the Red Sea ecosystem, particularly the Hurghada area; 2—monitor and assess the ostracod response to environmental pollution (e.g., heavy metals) stressors, and compare their bioindicator potential with that of foraminifera; 3—evaluate the effectiveness of recent benthic ostracods as a reliable bioindicator for ecological changes in the coastal ecosystems.

2. Study Area Description

The Hurghada site lies in the southern sector of the Gulf of Suez (Figure 1). The coastal plain is broad and bordered from the west by mountainous basement rocks belonging to the Eastern Desert of Egypt. The surface of the coastal plain comprises several dry valleys and is covered by Pleistocene reefal limestone, gravel, and sand deposits. The area is characterized by offshore islands and submerged coral systems that assist in dissipating the wave energy during stormy conditions. The beach sediments come from weathering and erosion of the western mountain ranges and consist of terrigenous quartz grains [27]. The reefs to the north of Hurghada City were developed along roughly parallel ridges oriented in an NNW–SSE direction [28]. The fringing and barrier reefs are the most common in the investigated site, while the patches of coral reefs are present in two forms. The first is attached either to the mainland or to the insular roots and forms a circular shape (fringing), while the second is an independent reef surrounded by water [29]. The sediments in the Hurghada area are subdivided into two zones: the northern zone is of more terrigenous origin than the southern zone [30]. This subdivision is based on the provenance of sediments from the Hurghada area according to their carbonates, chlorides, sulfates, organic carbon, sodium, potassium, magnesium, strontium, and total iron contents.

The rapid expansion of coastal tourism in Hurghada has significantly accelerated urbanization along the shoreline. Consequently, unregulated development has led to various anthropogenic disturbances, impacting the coastal and marine environments. In addition to human activities, fluvial sediment discharge from the surrounding mountains may have influenced the early morphology of reef formations.

The tide is semidiurnal, with a maximum peak every 12 h and a mean tidal range of about 0.8 m. The average water salinity near the coast is 41 PSU and 40 PSU in deeper water. The average water temperature is 24.95 °C [5]. Winds mainly blow from NW and N most of the year. As a result, winds, waves, and tides produce coastal currents to the south and southeast. The maximum speed of the longshore current inside the zone between the reef edge and shoreline ranges from 35 cm to 40 cm [31]. The intensity of littoral drift along the Hurghada coast is significant, as indicated by the formation of well-developed spits.

3. Materials and Methods

3.1. Sampling and Processing

A systematic sampling strategy was implemented to assess the distribution of benthic ostracods and their response to environmental conditions in the Hurghada area. A total of 29 (Figure 1A–C) sediment samples were collected from various nearshore and offshore stations in July 2020, covering a range of ecological settings, including sandy beaches, seagrass meadows, and coral reef-associated environments. The sampling sites were strategically selected to collect the uppermost 0–2 cm sediments in order to capture potential pollution gradients, hydrodynamic influences, and sedimentological variations. Sediment samples were obtained using a Van Veen grab sampler for subtidal stations and a hand plastic corer for intertidal and shallow coastal areas. Each sample was carefully retrieved to preserve the sediment structure and avoid contamination. A vital staining technique was employed by adding Rose Bengal (2 g/L ethanol solution) to freshly collected sediment samples. Samples were left to stain for at least 24 h to allow living ostracods to absorb the dye, highlighting cytoplasmic contents within the carapace. Only specimens with stained soft tissues were classified as living ostracods, while unstained, empty, or fragmented shells were considered dead. In situ water depth measurements, temperature, salinity, and dissolved oxygen were recorded at each station using a Hydrolab Surveyor-4 Instrument to establish correlations between ostracod assemblages and environmental parameters. The collected sediments were stored in labelled polyethylene bags and immediately transported to the laboratory for further processing. To extract ostracods, the sediment samples were washed through a 63 µm sieve and oven-dried at 50 °C. The dried residues were carefully examined under a stereomicroscope, and ostracods were picked, sorted, and identified to the species level using standard taxonomic references. The ostracod assemblages were counted (300 individuals for statistical analysis) and identified according to the treatise on invertebrate paleontology, part Q, Ostracoda Moore [32]; Hartman [33]; Martens and Horne [34]. The identified ostracoda taxa were photographed by a scanning electron microscope of the Egyptian Mineral Resources Authority (JSM 6063LA).

Grain size analysis (20 g of sediments per sample) has been implemented via the dry sieving method adopted by Folk and Ward [35]. This method relies on setting a group of standard mesh sieves (500 µm, 350 µm, 250 µm, 200 µm, 125 µm, and 63 µm) shaken for 15 min. The retained sediments on each sieve are calculated to determine the percentages of sand and mud fractions.

3.2. Data Analysis

Statistical analyses were performed on the living benthic ostracod taxa identified in the retrieved dataset, focusing on those with a relative abundance >2%. These dominant taxa represent 87% of the total assemblage. Prior to conducting ordination procedures, stations with low species counts were proportionally normalized to eliminate potential biases in their ecological relationships. Hierarchical cluster analysis (Q- and R-modes), coupled with heatmap dendrograms, is utilized to display the degree of variability among stations and their taxa via a color-coding algorithm. The dataset was standardized via Z-score and filtered using a species-reduced model to enhance computational efficiency by reducing the complexity of the dataset and improving interpretability. The resulting dendrograms were constructed using the complete linkage method and a Bray–Curtis similarity index to enhance clustering precision.

Multivariate statistical analysis was adopted to investigate the influence of environmental variables on species composition. Accordingly, detrended correspondence analysis (DCA) was utilized to determine the most suitable multivariate method for data interpretation. The gradient length of the first axis was >4 SD units; the unimodal ordination method is recommended [36]. Consequently, a constrained canonical correspondence analysis (CCA) was selected as the optimal technique for identifying environmental drivers influencing species distributions and providing a triplot visualization of the relationships. The dataset was log-transformed, standardized, and centred to tackle extreme values, enhance species abundance comparability, and ensure that all variables contribute equally. The data representation and interpretation relied only on the first two axes, while higher axes were excluded.

Furthermore, Pearson’s correlation coefficients were determined to explore the magnitude and direction of relationships among the studied variables (

Table 1. Pearson correlation coefficients for the environmental variables, heavy metals, dominant ostracod taxa, diversity indices, and living ostracod percentages.

	TOM%	Sand%	Mud%	Cu	Pb	Zn	Cd	Ni	Mn	Cr	As	C. tor.	J. bor.	A. retic.	R. dan.	L. gha.	G. trieb.	Spec. Rich.	Indiv.	% Liv.
TOM%	1
Sand%	−0.56	1
Mud%	0.54	−0.95	1
Cu	0.40	−0.23	0.22	1
Pb	0.72	−0.54	0.46	0.38	1
Zn	0.65	−0.29	0.26	0.43	0.78	1
Cd	0.69	−0.38	0.37	0.68	0.66	0.70	1
Ni	0.55	−0.49	0.48	0.54	0.56	0.44	0.55	1
Mn	0.18	−0.24	0.20	0.36	0.34	0.37	0.42	0.52	1
Cr	0.41	−0.27	0.28	0.58	0.52	0.74	0.74	0.51	0.61	1
As	0.63	−0.52	0.43	0.62	0.76	0.74	0.81	0.48	0.48	0.80	1
C. torosa	0.59	−0.03	0.14	0.46	0.49	0.52	0.65	0.33	0.43	0.41	0.30	1
J. borchersi	−0.01	0.20	−0.39	0.27	0.20	0.16	0.20	0.12	0.29	0.31	0.34	0.03	1
A. reticulata	0.62	0.14	0.46	0.56	0.53	0.58	0.36	0.43	0.28	0.66	0.42	0.28	0.48	1
R. danielopoli	−0.04	0.41	−0.27	−0.33	−0.21	−0.16	−0.15	−0.24	−0.47	−0.39	−0.45	−0.06	−0.16	−0.35	1
L. ghardaquensis	−0.23	−0.18	0.20	−0.23	−0.30	−0.41	−0.31	−0.01	−0.22	−0.44	−0.38	−0.09	−0.33	−0.39	−0.03	1
G. triebeli	−0.21	0.30	−0.43	−0.25	−0.21	−0.24	−0.28	−0.14	0.11	−0.34	−0.27	−0.42	0.15	0.17	−0.22	−0.11	1
Species richness	−0.29	0.17	−0.04	−0.55	−0.30	−0.40	−0.47	−0.37	−0.28	−0.54	−0.60	−0.24	−0.70	−0.40	0.24	0.21	0.26	1
Individuals	−0.54	0.45	−0.42	−0.68	−0.57	−0.66	−0.75	−0.52	−0.38	−0.83	−0.85	−0.20	−0.31	−0.36	0.30	0.32	0.55	0.74	1
% Living	−0.53	0.42	−0.37	−0.61	−0.64	−0.71	−0.73	−0.46	−0.40	−0.82	−0.87	−0.15	−0.38	−0.48	0.35	0.46	0.40	0.71	0.94	1

Bold values denote correlation is significant at p < 0.05 level.

). The correlation and CCA tests were implemented at the significance level p ≤ 0.05.

The nature of the recognized benthic ostracod assemblages is evaluated by calculating diversity indices, species richness, individual numbers, Shannon, and dominance.

All the above statistical analyses and diversity indices calculations were conducted using PAST software, version 4.17 [37].

4. Results

4.1. Bottom Sediments Characteristics

The sediment composition in the Hurghada area is predominantly sandy, with elevated mud content in nearshore zones (Figure S1), particularly adjacent to tourist developments. The central sector exhibits the highest sand fraction, whereas the northwestern and southeastern stations contain the highest mud percentages. The carbonate content in sediments is notably higher in the northern and southern sectors. The organic matter content fluctuates across the study area, peaking in the southeastern and northwestern sectors. Similarly, heavy metal concentrations are highest in nearshore stations, with notable enrichment in the southeastern sector (Figure S2). For a comprehensive assessment of sediment characteristics and heavy metal distribution, see El-Kahawy and Mabrouk [5].

4.2. Hydrological Features

The physicochemical properties of the Red Sea waters at Hurghada exhibited spatial variability. Higher temperatures are recorded at coastal stations, and salinity levels indicate hypersaline conditions. Seawater pH varies slightly across the study area (Table S1).

4.3. Ostracod Analysis

A total of 24 benthic ostracod taxa (living and dead) were retrieved from the samples investigated in the Hurghada site (Table S2). The relative abundance (%) of the recorded benthic ostracod species across 29 sampling stations along the Red Sea coast exhibited spatial variation in their distribution, potentially reflecting environmental gradients, including pollution effects. Twelve benthic ostracod taxa were observed in living form, while the other taxa were in dead form (Figure 2). The Cyprideis torosa, Jugosocythereis borchersi, Alocopocythere reticulata, and Loxocorniculum ghardaquensis are among the most abundant taxa across all stations. Other species, such as Ruggieria danielopoli, G. triebeli, and Moosella striata, exhibit moderate abundance, while less dominant species, including H. rubrimaris, Neonesidea schulzi, Xestoleberis rhomboidea, and Paranesidea spp., occur sporadically.

The C. torosa (14.71%) exhibits a broad distribution pattern, peaking at nearshore stations, particularly St.2, followed by St.3 and St.16 (Figure 3A). In contrast, the lowest abundances were observed near touristic villages in the southern stations (polluted), such as St.21 and St.17. On the other hand, J. borchersi (14.59%) has the highest percentages at the southern stations St.15, St.16, and St.17 (Figure 3B), while the lowest abundance was observed in the offshore stations. Alocopocythere reticulata (13.97%) and Ruggieria danielopoli (10.26%) were enriched in the nearshore stations beyond St.3, St.15, and St.6 (Figure 3C,D). The G. triebeli (10.72%) was found consistently across most Hurghada stations, peaking at the nearshore stations such as St.1 (Figure 3E). L. ghardaquensis is absent from many stations, especially the nearshore stations, while the highest values were observed at the offshore stations such as St.29 (Figure 3F).

Additionally, the percentage of living ostracods within the total assemblage is included, providing insights into population vitality and environmental conditions. The % living values vary between 17.3 (St.21) and 38.5 (St.29), indicating differences in ecological conditions affecting ostracod survival (Figure 4). Higher % living (>35) was found at stations located offshore and away from pollution sources such as St.4 (35), St.9 (35), St.3 (36), St.10 (37), St.19 (37), St.25 (37), St.26 (37), and St.29 (38). A lower % living (<25) was observed closer to the anthropogenic sources of the touristic buildings, especially the southeastern and central stations such as St.2 (23), St.7 (22), St.23 (22), St.8 (19), St.16 (19), St.18 (19), St.6 (18), St.17 (18), and St.21 (17) (Figure 4).

4.4. Benthic Ostracods Diversity Indices

The benthic ostracod at the Hurghada site showed a diverse assemblage in the offshore stations, which decreased near the coastal stations. Accordingly, the number of ostracod individuals ranges from 202 (St.21) to 326 (St.25) (Figure 5A). Stations St.25, St.14, and St.19 have the highest individual counts (>300), respectively. Stations with the lowest individual counts (St.6, St.17, and St.21, respectively) have fewer than 210 individuals. Notably, the stations located in the southeastern region, followed by the northwestern stations, have the lowest number of individuals. On the other hand, the species richness varies across stations, ranging from 6 species (St.15) to 20 species (St.3 and St.13). Stations St.3, St.13, St.25, and St.26 show high species richness (≥17), indicating greater biodiversity, whereas stations with low species richness (St.15, St.1, St.4, St.17, St.18, St.21) have values between 6 and 8, suggesting lower biodiversity (Figure 5A).

The relationships between species richness and the number of individuals have been assessed to produce diversity indices (Figure 5B). The dominance index ranges from 0.069 (St.13, lowest dominance) to 0.204 (St.15, highest dominance). Low dominance (≤0.10) is observed in St.13, St.20, St.25, and St.29, suggesting a more even distribution among species, whereas high dominance (> 0.15) in St.15, St.16, St.17, St.18, and St.21 indicates that one or a few species dominate these stations. Shannon diversity index ranges from 1.653 (St.15, lowest diversity) to 2.816 (St.13, highest diversity). The St.13, St.25, and St.20 have the highest diversity (>2.6), indicating well-balanced ecosystems, while St.15, St.21, and St.17 have the lowest diversity (<1.9), suggesting dominance by a few species (Figure 5B). Notably, the stations with high dominance index (i.e., St.21, St.18, St.17) are occupied by C. torosa, J. borchersi, A. reticulata, R. danielopoli, L. ghardaquensis, and G. triebeli.

4.5. Ordination Analysis

4.5.1. Hierarchical Cluster Analysis (HCA)

HCA categorized the studied stations into three distinct clusters (Q1, Q2, and Q3) (Figure 6), each representing specific environmental conditions based on benthic ostracod assemblages (R1 and R2; Figure 6), sediment composition, heavy metal concentrations, and other physicochemical parameters. Cluster Q1 includes 13 stations (St.5, St.9, St.11, St.12, St.14, St.19, St.20, St.22, St.24, St.25, St.26, St.27, St.28). It is characterized by moderate species richness and moderate ostracod abundance, with J. borchersi, C. torosa, and A. reticulata as dominant taxa. The bottom sediments in these stations are primarily dominated by fine sand, with moderate levels of TOM and carbonate content. The heavy metal concentrations of this cluster vary but remain moderate compared to other clusters.

Cluster Q2 consists of 12 stations (St.1, St.2, St.6, St.7, St.8, St.10, St.15, St.16, St.17, St.18, St.21, St.23), exhibits a low-diversity ostracod community, with R. danielopoli, G. triebeli, and H. rubrimaris being notable taxa, and is dominated by C. torosa, A. reticulata, and J. borchersi in the impacted stations. Increased dominance values mark these stations, lower Shannon diversity indices, and the lowest living percentage of the ostracod assemblage. The bottom sediments are characterized by a mix of sand and mud (higher than Q1), with the highest carbonate and organic matter content compared to Q1. Additionally, this cluster shows elevated concentrations of heavy metals, particularly Pb, Zn, Cd, Cr, and As, indicating potential anthropogenic influence.

Cluster Q3 comprises five stations (St.3, St.4, St.13, St.29) and is distinguished by the highest species richness and individual counts, particularly with significant occurrences of M. striata, L. ghardaquensis, and P. fracticorallcola (Figure 6). These stations are associated with relatively fine sand, low-to-moderate TOM levels, and high carbonate content. Notably, this cluster exhibits the lowest levels of heavy metals, suggesting their offshore settings.

4.5.2. Canonical Correspondence Analysis (CCA)

The first axis (CCA1) explains 47% of the total variance, meaning that it captures the most significant gradient in the dataset, while the second axis (CCA2) explains 20.34% (Figure 7A), indicating an additional but less dominant environmental gradient. Together, these two axes account for 67.34% of the variation in the ostracod assemblages concerning the environmental variables, making them a strong basis for interpretation. The higher axes were omitted due to their low variation patterns. Three groups (I, II, III) are the outcomes of the environmental variables, ostracod abundance, and station influence along the first two axes. These three station groups identified through CCA/clustering reflect distinct ecological zones in the Hurghada coastal area. Figure 7B illustrates the spatially distributed groups, where I mostly occupy the offshore stations of the central and southern sectors and is characterized by higher water depth and sand content, with dominance of taxa like R. danielopoli, P. fracticorallcola, H. rubrimaris, M. striata, and N. schulzi, as well as high living percentage (Figure 7A). Group II encompasses the highly enriched nearshore stations in heavy metals, organic matter, and mud percentage along the shoreline, coupled with dominance of opportunistic taxa such as A. reticulata, C. torosa, and J. borchersi. Group III comprises the northern offshore stations with the lowest heavy metal content, and is dominated by P. fortificata, L. ghardaquensis, and X. rhomboidei (Figure 7A).

CCA1 represents a pollution gradient, separating stations/species influenced by heavy metal contamination from those in cleaner environments, whereas CCA2 represents a sedimentological gradient, distinguishing between sandy vs. muddy or carbonate-rich sites. Axis 1 is positively correlated with heavy metals such as Cu (0.66), Cr (0.71), and As (0.75), as well as Cd (0.61), Pb (0.53), Zn (0.53), and Mn (0.46). Additionally, CaCO₃ (0.21) and TOM% (0.25) showed a reasonably positive correlation with Axis 1, suggesting some carbonate-rich sediments and organic matter contribution. On the other hand, the water depth (−0.33) and sand% (−0.09) are negatively correlated, meaning that deeper, sandier sites tend to have lower heavy metal concentrations. The A. reticulata, C. torosa, and J. borchersi have high positive loadings along Axis 1, suggesting that they are associated with environments rich in heavy metals. Accordingly, the CCA permutation test (n = 999) results revealed that only the first canonical axis has a statistically significant eigenvalue (p = 0.002). Therefore, species–environment correlations are interpreted primarily along Axis 1. Notably, C. torosa, A. reticulata, and J. borchersi are strongly associated with TOM and heavy metals such as Cr and Zn, aligning with their vector directions and magnitudes on the first axis. In contrast, relationships along subsequent axes (Axes 2–13) were not statistically significant (p > 0.05) and were not further interpreted to avoid weak or spurious patterns. X. rhomboidea, N. schulzi, and H. rubrimaris show negative scores along Axis 1, indicating that they prefer environments with lower heavy metal concentrations. The influence of axis 1 on the ostracod distribution pattern is observed via their association with high Axis 1 values in J. borchersi (0.47), C. torosa (0.83), and A. reticulata (1.23). These species are likely pollution-tolerant, thriving in areas with high metal concentrations, carbonate sediments, and high organic matter. Furthermore, species negatively correlated with Axis 1 (less polluted, deeper or sandier sites) are H. rubrimaris (−2.25), X. rhomboidea (−1.59), L. ghardaquensis (−1.49), and P. fortificata (−1.87). These species may indicate cleaner environments, often in deeper, sandier, or mud-rich areas. Stations scoring high on Axis 1 (potentially polluted) are St.1 (0.33), St.2 (0.4), St.16 (0.56), St.21 (0.28). These stations experience higher heavy metal contamination and have species tolerant of pollution (i.e., C. torosa, A. reticulata). Additionally, stations scoring low on Axis 1 (cleaner environments) are St.9 (−0.41), St.13 (−0.42), St.27 (−0.17), and St.28 (−0.2). These sites may represent less polluted conditions with cleaner sediments and lower heavy metal influence.

Axis 2 positively correlates with mud percentage (0.411) and CaCO₃ (0.18). This means that sites scoring higher on axis 2 tend to be finer-grained and have more calcium carbonate content. However, sand percentage (−0.35) is negatively correlated, suggesting that sandier sediments score lower on Axis 2. The relationship with heavy metals is weaker compared to Axis 1, with Cu (0.22), Pb (0.15), and As (0.21) showing only mild correlations. Species associated with high Axis 2 values (muddy, carbonate-rich sites) are X. rhomboidea (1.29), L. ghardaquensis (1.75), and P. fortificata (1.89). L. ghardaquensis and P. fortificata have high positive scores on Axis 2, meaning that they are more associated with muddy environments. M. striata and R. danielopoli have negative scores on Axis 2, suggesting that they prefer habitats with higher carbonate content. This suggests that Axis 2 captures a transition from sandy to muddy environments, with some species preferring finer sediments with higher CaCO₃. Stations associated with high Axis 2 values (muddy, CaCO₃-rich environments) are St.4 (0.61), St.10 (0.32), and St.19 (0.01). These stations are likely associated with finer sediments and carbonate-rich conditions.

5. Discussion

The type of substrate is one of the main factors controlling the occurrence of ostracods in marine ecosystems [38]. The grain size analysis (see Figure 3; [5]) indicates a seabed type with a high content of the sand fraction (up to 81%), which is characterized by medium-to-fine sand sizes, where the sediment samples revealed significant differences between the bottom sediments of each station. In contrast, the stations near the anthropogenic sources (i.e., southeastern transects) had high percentages of the finer sediments (mud %). Accordingly, the decrease in grain size is directly proportional to water depth, where the environment’s energy reduction causes the finest fraction (mud %) to increase further away from the coast [39]. The substrate type strongly influences benthic ostracod distribution, where it has been observed that the size, shape, and sculpture of benthic ostracods broadly reflect the stability and grain size of the substrate [2,40]. The ostracod taxa with coarsely ornamented thick valves typically inhabit a sandy substrate [1,38]. However, the coarse-grained sediments support only a small ostracod population [41], whereas mud-mixed sand sediments usually have a larger and much more diversified ostracod community [14,42]. According to Sell [43], the intraspecific morphological variability of carapace shape in flourishing Heterocypris salina populations in brackish water is due to different substrates, whereas the taxa with smooth, non-ornamented valves are typical of muddy sand facies [44]. In the present study, the ostracod community, involving species richness, individual numbers, living percentage, and some dominant taxa, is positively correlated. The sand sediments showed a fairly positive correlation coefficient with R. danielopoli (r = 0.41, p < 0.05) and G. triebeli (r = 0.30, p < 0.05), whereas both A. reticulata and L. ghardaquensis displayed weak and negative correlation coefficients (r = 0.14 and r = −0.18; p < 0.05). This is compatible with the recorded results reported by Aljahdali et al. [1] and El-Kahawy et al. [2]. Benthic ostracods in the study area predominantly inhabited colonies within seagrass meadows, macroalgal beds, and reef-associated environments with three distinct zones. These ecological niches provide suitable habitats for various taxa, including L. ghardaqensis, R. danielopoli, G. triebeli, Xestolebris spp., Paransidea spp., N. schulzi, M. striata, and H. rubrimaris. These species are particularly abundant at offshore stations of the northern and southern sectors and farther from pollution sources. The high proportion of living specimens and calcified forms of ostracod taxa in these groups (I and III) suggests a relatively stable, oxygenated, and low-disturbance environment. Similar offshore assemblages with high sand content and stable salinity were observed in the Red Sea benthic studies by El-Kahawy et al. [45], where calcareous, stenohaline taxa prevailed in less impacted habitats. In contrast, the southeastern and northeastern stations (i.e., St.21, St.17, and St.2) of group II are characterized by fine-grained, higher mud percentage, and lack seagrass and reef sediments. This absence is likely attributed to effluent discharge from ships and tourism-related activities. Such conditions significantly contribute to the decline in the abundance of living ostracods in the Hurghada site. Furthermore, these stations are inhabited by opportunistic benthic ostracod taxa such as C. torosa, J. borchersi, and A. reticulata, which are more tolerant to environmental stress influences [1]. This aligns with findings from similar eutrophic and stressed coastal zones [46], where C. torosa, in particular, has been documented as a robust indicator of environmental stress due to its euryhaline and low-oxygen tolerance [47] and A. reticulata as an organic matter enrichment indicator [45]. The population bursts and/or resting stages in these taxa are often denoted as hypoxia-influenced environments [48].

A comparison with the findings of El-Kahawy and Mabrouk [5], who studied benthic foraminifera at the same stations, reveals both similarities and differences in faunal responses to heavy metal enrichment. Both ostracod and foraminiferal assemblages showed reduced diversity and shifts in community composition at sites with elevated concentrations of trace metals and organic matter, indicating a general sensitivity of benthic microfauna to pollution. However, the ostracod assemblages in this study exhibited relatively higher tolerance at certain stations (St.17 and St. 21) where foraminiferal abundances were markedly diminished, suggesting possible differences in physiological resilience, microhabitat utilization, or feeding strategies between the two groups. The feeding, microhabitat, and reproduction strategies are critical approaches in assessing the response of benthic foraminifera and ostracod groups to environmental degradation. Benthic foraminifera are sessile or limited in mobility, feeding via reticulopodia and relying heavily on particulate organic matter within their surroundings, potentially show strong sensitivity to changes in oxygen and food availability [49] and to organic enrichment or hypoxic conditions [50]. On the other hand, some ostracod taxa can tolerate low-oxygen sediments due to reduced metabolic demands or specific respiratory adaptations [51]. Ostracods are motile crustaceans that predominantly deposit or filter feeders with diverse diets, including bacteria, algae, detritus, and small invertebrates, which allows them to exploit a broader range of microhabitats and to actively avoid degraded zones [46,52]. Benthic foraminifera often show a stronger vertical microhabitat zonation in the sediment columns, while ostracods are more associated with horizontal gradients across sediment types and pollution levels [53]. Benthic ostracods frequently form resting instars (offsprings) representing growth stages, enabling survival under adverse conditions [54], whereas foraminiferal taxa lack such dormancy strategies and often show increased test deformities under environmental stress [3,46,55]. These ecological and physiological distinctions, such as mobility, feeding adaptation, reproductive strategies, and microhabitat, help explain why ostracods and foraminifera respond differently to pollution gradients in benthic environments. These discrepancies underscore the importance of employing multiple bioindicator taxa to comprehensively assess environmental health in polluted marine systems.

The quantity of organic matter measured in sediments influences meiofauna abundance and species richness, particularly benthic ostracods [15,56,57,58]. Additionally, Mirto et al. [58] showed that ostracod abundance decreased following the installation of fish and mussel farms because of bio-deposition from the farming complexes, whereas Noguera and Hendrickx [59] reported a positive relationship between organic matter content and ostracod density. Fauzielly et al. [56] considered species-specific responses where they reported a positive correlation between some ostracod taxa and total organic matter content, such as Loxoconcha viva and Callistocythere alate. In the Hurghada site, a positive correlation coefficient is observed among organic matter content and mud-type of sediments (r = 0.54, p < 0.05), particularly around St.21 and St.17. Noteworthy to mention that the ostracods response significantly influenced by the TOM enrichments, where negative correlation is observed with the dominated ostracods taxa J. borchersi, R. danielopoli, L. ghardaquensis, and G. triebeli. On the other hand, positive correlation coefficients between TOM and A. reticulata (r = 0.62, p < 0.05) and C. torosa (r = 0.59, p < 0.05) are illustrated in Table 1, which is compatible with El-Kahawy et al. [2]. Furthermore, the low species richness, individual numbers, and living percentage of the benthic ostracods in the polluted stations, such as St.16, St.17, St.18, and St.21, are most probably attributed to the influence of tourist village activities, ships, and sewage discharges.

5.1. Heavy Metal Influence on Benthic Ostracods

The distribution and diversity of benthic ostracods are significantly influenced by heavy metals in marine sediments, which act as environmental stressors, leading to shifts in community structure and species richness. Numerous studies have shown that heavy metal pollution, often associated with anthropogenic activities, alters the environment by impacting the availability of microhabitats and modifying the chemical conditions required for ostracod survival [53,60]. Heavy metals such as Pb, Cd, Cu, and Zn tend to bioaccumulate in marine ecosystems, often binding to fine-grained sediments such as mud, which serve as major repositories due to their high surface area and adsorption capacity [61,62]. The affinity of heavy metals to fine sediments has been well documented, particularly in coastal zones where urban and industrial discharges contribute to their enrichment [63]. Since ostracods are benthic organisms with varying tolerance to heavy metal contamination, areas with high mud content often show reduced species diversity and lower abundance, particularly in species sensitive to metal toxicity [64,65]. Mud-dominated sediments enhance heavy metal maintenance and influence oxygen availability and organic matter content, which are crucial in determining ostracod assemblages. Fine sediments often lead to hypoxic conditions due to organic matter degradation, further exacerbating the stress imposed by heavy metals. In a study conducted in the Adriatic Sea, Baldrighi et al. [66] demonstrated that ostracod species richness declined significantly in muddy environments with high metal concentrations, and only a few tolerant species persisted in such conditions. Tan et al. [19] confirmed that increasing concentrations of heavy metals in muddy coastal sediments led to lowering ostracod diversity, with evidence of improper calcification and reduced reproductive attainment. The interaction between heavy metals and sediment characteristics suggests that pollution assessments are necessary to consider both metal concentrations and sedimentological parameters. In our study area, similar patterns were observed, where sites characterized by finer sediments with elevated metal content exhibited a noticeable reduction in total ostracod abundance, which is consistent with findings from previous works [1,2,53,65]. This behavior demonstrated that benthic ostracods are excellent indicators of metal pollution due to their sensitivity to sediment-bound contaminants. Moreover, certain opportunistic taxa, such as Xestoleberis and Loxoconcha, showed relative resilience in polluted, muddy environments, reinforcing the notion that community composition shifts toward more tolerant species under stress conditions [60]. Notably, the investigated sites displayed mean heavy metal concentrations (Cd, Pb, and As) that exceeded the standard average shale reported by Wedepohl [67]. Similarly, the comparison with the background values measured on the Red Sea coastal sediments by Hanna [68] revealed enriched heavy metal concentrations for all the measured sites of the present study.

5.2. Data Limitations and Future Directions

This study highlights the potential of ostracods as bioindicators for environmental reconstruction and water quality assessment; however, several data limitations should be acknowledged. The analysis mostly relied on species-level identifications based on morphological characters, which may not fully capture cryptic diversity or subtle ecological preferences. Additionally, the spatial and temporal coverage of the collected samples was limited, potentially affecting the representativeness of the results, especially in heterogeneous environments. Moreover, environmental parameters such as salinity, temperature, and nutrient levels were inferred rather than directly measured in all cases, introducing uncertainties in the interpretations. Another limitation lies in the underrepresentation of specific ecological settings, such as hypersaline lakes, deep marine anoxic basins, or highly dynamic estuarine systems, where ostracod communities may respond differently to environmental stressors. The dataset may also be biased toward more accessible or better-studied regions, limiting global-scale generalizations. For future studies, integrating molecular techniques (e.g., DNA metabarcoding) with traditional taxonomy could enhance species resolution and ecological interpretations. Expanding sampling efforts to include broader spatial gradients, seasonal variations, and extreme environments (e.g., hypersaline or anoxic settings) will improve the robustness of ostracods as bioindicators. Furthermore, combining ostracod-based data with complementary proxies, such as diatoms and foraminifera, could strengthen multi-proxy reconstructions of past environments. Long-term monitoring studies are also recommended to better understand ostracod community dynamics under ongoing environmental change and anthropogenic pressures.

Future research should prioritize expanding sampling efforts across diverse environments and time intervals, integrating molecular approaches to improve species-level resolution and incorporating multi-proxy analyses with geochemical and sedimentological data. Establishing standardized ostracod sampling and analysis protocols will also enhance data comparability across studies and regions.

6. Conclusions and Recommendations

This study aimed to evaluate the potential of ostracods as bioindicators for inspecting the environmental conditions and assessing the present-day aquatic ecosystem health in 29 stations on the Red Sea coast of the Hurghada area, Egypt. Our findings demonstrate that ostracod assemblages provide valuable insights into variations in salinity, water depth, and oxygenation levels across the studied sites. The identified species and their ecological preferences allowed for pollution status to be tracked. Accordingly, the C. torosa and A. reticulata proved their abilities to thrive in the enriched heavy metal ecosystem, whereas X. rhomboidea, L. ghardaqensis, and Paranesidea fortificata could be used as sensitive taxa. Additionally, this study underscores the utility of integrating ostracod data with sedimentological and geochemical proxies to build a more comprehensive understanding of present-day ecosystems. Consequently, the southeastern, along with the northeastern, Hurghada stations exhibited the highest pollution levels, particularly St.21, St.17, and St.16. These stations were enriched by organic matters, which clarified a positive correlation with C. torosa and A. reticulata. By addressing current limitations and adopting integrative, interdisciplinary approaches, future research can unlock the full potential of ostracods in reconstructing ecosystem dynamics across spatial and temporal scales. We recommend several suggestions to enhance the robustness and applicability of ostracod-based bioindicators in environmental studies. First, integrating molecular approaches, such as DNA barcoding and metabarcoding, alongside traditional morphological taxonomy, will help overcome challenges related to cryptic diversity, refine species-level identification, clarify phylogenetic relationships, and improve ecological interpretations. Secondly, expanding the spatial and temporal coverage of ostracod studies is critical via broader sampling across diverse geographic regions, ecological settings (such as freshwater, hypersaline lakes, and wide ranges of marine ecosystems), and a wider range of water depths, which strengthens temporal frameworks and enables precise correlations between ostracod assemblages and environmental change. Thirdly, long-term monitoring of ostracod communities in disturbed and undisturbed ecosystems will provide valuable insights to inform conservation and management strategies from anthropogenic influences. Finally, further experimental and observational studies addressing taphonomic processes, including dissolution, transport, and bioturbation, are essential for understanding how mortality factors influence ostracod assemblages.