Mangrove Habitat Health Assessment in the Sanya River: Multidimensional Analysis of Diatom Communities and Physicochemical Water Properties

Abstract

Mangrove forests are vital ecosystems along tropical coasts, playing crucial roles in water purification and biodiversity conservation. Diatoms, as sensitive ecological indicators, were employed in this study to evaluate the health of the mangrove forests along the Sanya River. The research involved analyzing the community structure of planktonic diatoms and water physicochemical properties during spring and winter, as well as carrying out a comprehensive assessment of the ecological health of the region in terms of four seasonal–spatial–environmental–biological indices. A total of 22 genera of planktonic diatoms were identified. In winter, Melosira sp. (34.94%), Skeletonema sp. (25.50%), and Chaetoceros sp. (15%) were dominant, with relative abundances of 34.94%, 25.50%, and 15.00%. In spring, Melosira sp. became the absolutely dominant species, averaging 70.16%. Diatom cell abundance shows both significant seasonal and spatial variation. In winter, it ranged from 0.53 to 17.4 × 10⁹ cells-L⁻¹, peaking in the midstream region, whereas in spring, it ranged from 2.48 to 21.0 × 10⁹ cells-L⁻¹, peaking at the mouth of the estuary. A higher abundance of diatoms in spring strengthens primary productivity and supports the subsequent functioning of the food chain. Diatom indices (Shannon–Wiener index H’, Pielou evenness index J, and Margalef richness index D) indicated an intermediate ecological health level for the Sanya River mangrove forests. Diversity was higher in winter than in spring, with the lowest values recorded in the midstream region. Redundancy analysis (RDA) indicated that T, pH, and PO₄³⁻ were the primary environmental drivers of diatom community succession. In spring, pH was positively correlated with T and PO₄³⁻, respectively. They drove the succession of diatom communities from diverse assemblages in winter to a single dominant species.

1. Introduction

Diatoms constitute a significant portion of phytoplankton communities in lakes and reservoirs, playing a crucial role in regulating ecological balance [1]. Particularly, diatoms exhibit high sensitivity as indicators in riverine water quality assessments, which is attributed to their brief reproductive cycles and swift responses to environmental changes [2]. Research indicates that various diatom species possess distinct tolerance levels to environmental variables like pH and nutrient concentration, with shifts in their community composition precisely mirroring changes in water chemistry [3,4]. Leveraging this property, scientists have formulated diverse diatom-based bioindices, which have been refined into standard tools for routine environmental surveillance [5]. Presently, the scope of diatom index applications is broadening, encompassing domains such as river eutrophication evaluation [6], establishment of a baseline for lake ecological restoration [7], and surveillance of emerging pollutants [8]. Nevertheless, the efficacy of the diatom index can differ across various geographical and ecological contexts [9].

In estuarine mangrove ecosystems, diatoms serve as critical bioindicators for assessing water quality and ecological shifts, providing essential insights for the precise monitoring and restoration of mangrove wetlands. Benthic diatoms are fundamental in sustaining wetland ecological function [10,11,12] and exhibit significant value as ecological indicators within mangrove systems [13]. Research has demonstrated strong correlations between nutrient concentrations (such as total phosphorus (TP) and total nitrogen (TN)) and diatom community dynamics in diverse aquatic environments, including the Vistula River [14], Lake Uiam in South Korea [15], and the Jiulong River estuary [16]. Furthermore, studies have elucidated the mechanism by which diatom communities in mangroves respond to water quality alterations [17]. While diatom-based indicators are well-established for water quality evaluation in temperate ecosystems, with frameworks such as the European Union’s Water Framework Directive (WFD) [18], their direct applicability to tropical mangrove systems is constrained by the unique environmental characteristics of these habitats [19]. This is mainly due to the rapid rate of decomposition of mangrove organic matter, resulting in sharp fluctuations in nutrient concentrations in the water column [20], and under significant salinity fluctuations, tidal regimes alter the tolerance range of diatoms such that established static salinity thresholds no longer apply [21]. Therefore, studying mangrove diatoms helps to improve the accuracy of using diatoms to assess the water quality of bodies of water with rapidly changing physical and chemical parameters, such as salinity. However, ongoing research continues to enhance our understanding of diatom ecology in tropical mangroves, highlighting their role as early indicators of nutrient enrichment and habitat quality, thereby paving the way for more tailored monitoring approaches.

The Sanya River mangrove forest, a quintessential tropical estuarine wetland in China, holds substantial ecological service value. Its mangrove plant communities deliver critical ecosystem services, including carbon sequestration, oxygen production, water purification, and the preservation of coastal biodiversity [22,23]. However, the mangrove area on Hainan Island has diminished by over 50% since the 1950s [24], which has been exacerbated by intensive human activities that have led to heightened water pollution and the fragmentation of wetland habitats [25,26,27]. Previous studies showed that dissolved inorganic nitrogen (DIN) input from the Sanya River is the dominant factor controlling phytoplankton and bacterioplankton biomass in Sanya Bay [28]. In response to these challenges, research on mangrove ecological restoration has evolved from conventional methods—such as vegetation rehabilitation, soil enhancement, and hydrological management [29,30]—to encompass the study of synergistic interactions between phytoplankton and environmental factors [31,32]. Moreover, advancements in integrating traditional diatom analysis with environmental DNA technology, alongside the development of sophisticated instrumental detection methods like LISST-100X, are propelling mangrove ecosystem restoration towards greater precision and efficacy [33,34].

Therefore, research on the subject of algal blooms in the Sanya River mangrove wetland is lacking, particularly when it comes to diatoms. This study innovatively integrated diatom community metrics—abundance, Shannon’s diversity, Margalef’s richness, Pielou’s evenness—with critical physicochemical parameters, including temperature (T), salinity (Sal), pH, nitrite (NO₂⁻), and phosphate (PO₄³⁻). Through multivariate statistical analyses, it systematically investigated (1) the community structure of planktonic diatoms in Sanya River mangrove forests, (2) the primary environmental drivers of seasonal and spatial variations in diatom community composition, and (3) the potential of diatoms as bioindicators for assessing ecological water quality in tropical environments.

2. Materials and Methods

2.1. Description of Study Site

Situated in the southern Sanya City, Hainan Province, the Sanya River mangrove forest represents a critical coastal wetland ecosystem on Hainan Island. To ensure the conservation of its mangrove resources, the Sanya Municipal Government designated the Sanya Mangrove Reserve as a municipal nature reserve in 1989. This ecosystem provides essential ecological services, including protection against storm surges, purification of coastal waters, and conservation of endemic mangrove plants, rare migratory birds, and marine organisms, highlighting its pivotal role in ecological preservation. To investigate the ecological dynamics of the Sanya River mangrove forest, two separate cruises were conducted in the Sanya River between the winter of 2024 (December) and the spring of 2025 (March). A total of seven stations were sampled, with two samples taken at each station: a 4 L water sample for phytoplankton observations and a 550 mL water sample for nutrient analysis. Station 1 is located near the river mouth, Station 2 and Station 3 are positioned in the midstream region, and Stations 4 through 7 are situated in the upstream area. The spatial distribution of these sampling sites is depicted in Figure 1.

2.2. Phytoplankton Sample Collection and Processing

Water samples (4 L) were collected and filtered through a silk sieve with a 15 μm pore size to obtain 15 mL of concentrated samples. These were preserved by adding 1% Lugol’s solution (Phygene Biotechnology Co., Ltd., Fuzhou, China). Selecting a 15 μm filter can effectively retain large plankton and facilitate the rapid enrichment of the target diatom community in the field. However, it is important to note that this choice may exclude diatoms with diameters smaller than 15 μm, which could limit the analysis of community structure. The choice of a 15 μm filter here takes into account the difficulty of using biomicroscopy to identify diatoms morphologically when they are smaller than 15 μm. In the laboratory, samples underwent further concentration using a low-speed centrifuge (HUNAN XIANGYI LABORATORY INSTRUMENT DEVELOPMENT CO., LTD., Changsha, China) (6000 rpm for 4 min), resulting in 3.5 mL of the final concentrated sample. The concentrated samples were homogenized, and 30.0 μL aliquots were transferred onto slides. A light biomicroscope (MOTIC CHINA GROUP Co., Ltd., Xiamen, China) was employed to identify and count algal species, with a minimum of 300 diatom cells per site enumerated and identified to the genus level, ensuring reliable ecological assessments. Species identifications were made using a group cross-validation method, which was cross-calibrated by exchanging samples between groups and repeating observations to reduce individual taxonomic bias. Diatom species were identified with reference to online diatom taxonomic libraries (Chinese Academy of Sciences Diatom Atlas, http://119.3.147.35/atlas (accessed on 15 March 2025), University of California, Santa Cruz Phytoplankton Atlas, http://oceandatacenter.ucsc.edu/PhytoGallery/phytolist.html (accessed on 15 March 2025)) to ensure taxonomic accuracy.

2.3. Water Quality Parameter Assessment

In situ measurements of temperature, salinity, and pH were conducted using calibrated instruments (METTLER TOLEDO, Shanghai, China) in the field. A portable pH meter was employed for pH determination and was calibrated with standard buffer solutions (Shanghai Yidian Scientific Instrument Co., Ltd., Shanghai, China) (pH 6.86 and 9.18) to accommodate the alkaline properties of the water samples. Salinity was measured using a refractive salinometer (ATAGO Scientific Instruments Ltd., Guangzhou, China) that was calibrated by placing 1–2 drops of pure water on the prism, closing the cover plate, and adjusting the calibration screws to align the blue-white demarcation line with the 0% scale in the field of view. The prism was dried, and the calibration was verified to ensure accuracy.

According to the requirements of Specification for Marine Investigation Part 4: Investigation of Chemical Elements in Seawater (GB/T 12763.4-2007), the steps of seawater sample collection and processing were as follows: Water samples (550 mL) were collected and filtered in the laboratory within two hours of sampling. Concentrations of NO₂⁻ and PO₄³⁻ were determined through spectrophotometric analysis. The diazo-coupled azotron method, measured at 543 nm, was used for NO₂⁻ quantification, while the ascorbic acid-reduced phosphomolybdenum blue method, measured at 882 nm, was applied for PO₄³⁻ quantification. Each sample was determined in three parallel tests, and the relative standard deviation should be less than 5%.

2.4. Data Processing and Analysis

The planktonic diatom community structure was quantitatively assessed through the application of three biodiversity indices: Shannon–Wiener’s diversity index (H′) [35], Pielou’s homogeneity index (J) [36], and Margalef’s abundance index (D) [37]. Higher values of these indices indicate greater stability within the diatom community [38], as determined by a standardized ecological formula.

$${\mathrm{H}}^{\prime }=-\sum _{\mathrm{i}=1}^{\mathrm{s}}\left[\left({\displaystyle \frac{\mathrm{N}\mathrm{i}}{\mathrm{N}}}\right)\ln \left({\displaystyle \frac{\mathrm{N}\mathrm{i}}{\mathrm{N}}}\right)\right]$$

(1)

$$\mathrm{J}={\mathrm{H}}^{\prime }/\ln \mathrm{S}$$

(2)

$$\mathrm{D}=\left(\mathrm{S}-1\right)/\ln \mathrm{N}$$

(3)

The dominant species of the planktonic diatom community were determined by the degree of dominance (Y). Species with a Y value of ≥0.02 were classified as the dominant species, as established by a standardized ecological formula [39].

$$\mathrm{Y}=\left({\displaystyle \frac{\mathrm{N}\mathrm{i}}{\mathrm{N}}}\right)\times \mathrm{f}\mathrm{i}$$

(4)

In the specified ecological equation, S is the total number of species across all samples, N denotes the total number of individuals of all the species, Ni indicates the number of individuals of the i-th species, and fi represents the frequency of occurrence of the i-th species.

Statistical analyses and data visualizations were conducted using Microsoft Excel 2022 and Origin 2022. Spatial variations in diatom distribution and cell abundance were mapped using ArcGIS 10.8. The differences in diatom abundance, species richness, diversity index, evenness index, and physicochemical factors among different seasons and sites were investigated using IBM SPSS Statistics 27 with one-way ANOVAs, based on which the least significant difference method (LSD method) was applied for multiple comparisons between groups. To quantitatively evaluate the ecological relationships between diatom community structure and environmental covariates, redundancy analysis (RDA) was carried out using Canoco 5.

3. Results

3.1. Physicochemical Water Properties

The physicochemical parameters of water bodies within the Sanya River basin are detailed in

Table 1. Physicochemical parameters of Sanya River water body in spring and winter seasons.

Parameter	Spring		Winter		p Value
	Range	Mean ± SD	Range	Mean ± SD
Temp./(°C)	26.0~29.3	28.17 ± 1.87	23.50~24.00	23.81 ± 0.20	0.000 **
Sal./(g·kg−1)	3.00~18.00	11.43 ± 4.76	7.00~16.00	10.43 ± 3.10	0.650
pH	7.60~7.95	7.69 ± 0.15	7.31~7.65	7.43 ± 0.12	0.004 **
Phosphate/(mg·L−1)	1.21~4.21	3.27 ± 0.99	0.52~1.13	0.79 ± 0.21	0.000 **
Nitrite/(mg·L−1)	2.91~9.75	6.72 ± 2.35	3.00~6.95	4.54 ± 1.47	0.06

Note: ** indicates a significant difference at the 0.01 level.

. Mean spring water temperatures (28.17 ± 1.87 °C) are significantly elevated compared to those of winter, aligning with seasonal climatic trends. Salinity demonstrates greater variability and higher mean values in spring (11.43 ± 4.76 (g·kg⁻¹)) than in winter (10.43 ± 3.10 (g·kg⁻¹)). The water maintains a weak alkaline pH in both seasons, with mean winter values (7.43 ± 0.12) significantly lower than those in spring (7.69 ± 0.15). The mean PO₄³⁻ and NO₂⁻ values in spring were 3.27 ± 0.99 (mg·L⁻¹) and 6.72 ± 2.35 (mg·L⁻¹), respectively, whereas the mean phosphate and nitrite values in winter were 0.79 ± 0.21 (mg·L⁻¹) and 4.54 ± 1.47 (mg·L⁻¹), respectively. Therefore, the mean phosphate and nitrite values in spring were significantly higher than in winter. As depicted in Figure 2, nutrient concentrations reach their highest levels at site A6 in spring and site A4 in winter. Located at the estuary mouth, site A1 exhibits reduced nutrient levels, which are mainly due to the dilution of oligonutrient seawater. Conversely, site A6, proximate to a commercial area, is subject to continuous inputs of organic matter and nutrients from sewage discharge. Site A4, positioned in a tributary with constrained hydrodynamic flow, experiences limited nutrient diffusion, resulting in the regional accumulation of nutrients. These seasonal and spatial variations in physicochemical factors reflect the complex water environment of the Sanya River, driven by both natural dynamics and anthropogenic impacts.

3.2. Diatom Community Structure in the Sanya River

3.2.1. Diatom Species Composition

Across spring and winter, a total of 22 genera of planktonic diatoms were identified in the Sanya River basin, as illustrated in Figure 3. During winter, a total of 17 diatom genera were documented, with significant spatial variation in species composition. Sites A1, A2, and A7 demonstrated elevated species diversity of 10 species, each supporting 10 species, while site A4 exhibited the lowest diversity with only 5 species. In spring, a total of 19 diatom genera were recorded, with sites A1 and A2 hosting 13 and 11 species, respectively, compared to just 5 species at sites A3 and A4. Compared with previous surveys in tropical mangrove estuaries (Sundarbans recorded 134 species of phytoplankton, of which diatoms dominated [40]; Kaduviyar estuary recorded 85 species, of which 58 were diatoms [41]; and Pichavaram recorded a wide range of species abundance [42]), the number of diatom genera and the number of highest species at the site observed in the present survey were at a moderately low level. These findings highlight pronounced seasonal and spatial differences in diatom community structure, likely influenced by local environmental conditions.

3.2.2. Cell Abundance of Phytoplankton

Planktonic diatom abundance in the Sanya River demonstrated pronounced seasonal and spatial variability. In winter, cell abundance ranged from 0.46 × 10⁹ to 17.4 × 10⁹ cells·L⁻¹, with a mean of 4.42 × 10⁹ cells·L⁻¹. In spring, abundance was elevated, ranging from 2.48 × 10⁹ to 21.0 × 10⁹ cells·L⁻¹, with a mean of 6.57 × 10⁹ cells·L⁻¹. As illustrated in Figure 4a, winter abundance exhibited a spatial trend, rising from the estuary mouth to a peak of 17.4 × 10⁹ cells·L⁻¹ at midstream site A3, before declining to 0.46 × 10⁹ cells·L⁻¹ at upstream site A7, equivalent to 2.6% of the peak. Conversely, spring abundance, shown in Figure 4b, peaked at the estuary mouth with 21.0 × 10⁹ cells·L⁻¹, decreasing progressively upstream along the mainstem, culminating in an 88% reduction to 2.48 × 10⁹ cells·L⁻¹ at site A7. Additionally, tributary sites A4 and A5 in spring formed a secondary high-abundance zone, reaching 6.61 × 10⁹ cells·L⁻¹ and 6.04 × 10⁹ cells·L⁻¹, respectively. These patterns underscore the influence of environmental gradients and hydrodynamic conditions on diatom distribution.

The composition of planktonic diatoms in the Sanya River exhibits significant seasonal variation, as illustrated by the percentage of genus composition in Figure 5. During winter, Melosira sp., Skeletonema sp., and Achnanthes sp. predominated, while in spring, the dominant genera shifted to Melosira sp., Cyclotella sp., and Chaetoceros sp., accompanied by a substantial reduction in the relative abundance of Achnanthes sp. and Skeletonema sp. This may be due to the increase in pH, temperature, salinity, and PO₄³⁻, which promotes the proliferation of Melosira sp., while suppressing other competing species. At site A1, located at the estuary mouth, Achnanthes sp. achieved a relative abundance of 67.2%, establishing its dominance; in spring, Melosira sp. replaced it, increasing from undetectable levels in winter to 86.4%. Sites A2–A4 were consistently dominated by Melosira sp. across both seasons, with a significant increase in its relative abundance from winter to spring. Conversely, sites A5–A7, dominated by Skeletonema sp. in winter, saw Melosira sp. emerge as the dominant genus in spring.

3.2.3. Dominant Diatom Species

The seasonal dynamics of the planktonic diatom community in the Sanya River were assessed by designating species with a dominance degree (Y) ≥ 0.02 as the dominant species, revealing distinct differences in species composition and dominance between spring and winter, as presented in

Table 2. Dominant species and dominance degree of diatoms in Sanya River.

Dominant Species	Spring	Winter
Melosira sp.	0.70	0.30
Skeletonema sp.	-	0.22
Chaetoceros sp.	0.02	0.15
Cyclotella sp.	0.14	-
Achnanthes sp.	-	0.03
Fragilaria sp.	-	0.03

. In spring, Melosira sp. was the main dominant species, achieving a dominance degree of 0.70, which is significantly higher than other species and indicative of its robust adaptation to increased water temperatures and nutrient-enriched conditions. Conversely, winter supported a more diverse community structure, with Melosira sp.’s dominance reduced to 0.30. Skeletonema sp. and Chaetoceros sp. emerged as subdominant species, with dominance degrees of 0.22 and 0.15, respectively, while Achnanthes sp. and Fragilaria sp. appeared in the winter, suggesting a greater sensitivity to environmental factors, including cooler temperatures and modified nutrient availability. These findings highlight the dynamic response of diatom assemblages to seasonal environmental variations.

3.2.4. Phytoplankton Diversity Indices

The diversity of planktonic diatoms in the Sanya River exhibited distinct seasonal patterns, as depicted in Figure 6. The Shannon–Wiener diversity index (H′) of the planktonic diatoms varied from 0.49 to 1.17 (mean: 0.76) in spring, increasing significantly in winter to 0.88–1.49 (mean: 1.26), indicating reduced competitive pressure and an enhanced coexistence of diatom genera in winter. H’ was expected to decrease with the deterioration of water quality [43]. High values of H’ would be representative of more diverse communities (namely, good water quality). The range of water bodies contaminated with toxic materials based on the H’ is divided into two categories: 1.0–3.0 = “moderate status”; <1.0 = “bad status” [44]. Therefore, the ecological health status of mangrove forests in the Sanya River is at a moderate level. Pielou’s evenness index (J) ranged from 0.12 to 0.56 (mean: 0.38) in spring, rising to 0.50–0.76 (mean: 0.62) in winter, reflecting a more equitable species distribution in winter due to the absence of a singular dominant species. Melosira sp. proliferated rapidly in spring, forming an absolutely dominant species, leading to a decrease in evenness. The Margalef richness index (D) in spring varied from 0.68 to 1.90, with a mean value of 1.19. In winter, the D value decreased slightly and varied from 0.70 to 1.56 with a mean value of 1.16. At site A1 in spring, the highest D value (1.90) coincided with lower J and H’ values, driven by Melosira sp.’s dominance (86.36% relative abundance), resulting in a homogenized community structure. In contrast, site A4 in winter and site A3 in spring exhibited the lowest diversity indices within their respective seasons, which is attributed to Melosira sp.’s rapid increase, which suppressed other diatom species and reduced overall community diversity.

4. Discussion

4.1. Relationships Between Diatom Communities and Environmental Factors

A detrended correspondence analysis was initially performed, revealing a gradient length of 1.45 for the first axis, which is below the threshold of 4. This result indicates a linear relationship within the environmental gradient, justifying the subsequent application of RDA. An ordination analysis was conducted to investigate the relationship between the cell abundance of dominant diatom genera (Y > 0.1) and environmental factors in Sanya River during spring and winter. As shown in Figure 7, redundancy analysis (RDA) demonstrated that the first two axes explained 51.36% of the cumulative variance. Monte Carlo permutation tests demonstrated no significant differences for either the first axis (F = 8.0, p = 0.202) or all axes combined (F = 1.7, p = 0.214). Among the environmental factors, pH exhibited the highest explanatory power (34.7%) and contribution rate (66.6%), with statistically significant effects (p < 0.05). PO₄³⁻ emerged as the secondary influencing factor (explains 11.3%; contributes 21.6%). Melosira sp. exhibited a significant positive correlation with pH and Sal, while Skeletonema sp. and Chaetoceros sp. displayed strong negative correlations with pH and T. Cyclotella sp. showed positive correlations with T and PO₄³⁻ concentration, highlighting species-specific responses to environmental gradients.

The composition of dominant diatom genera varied markedly between seasons. In winter, the community was characterized by Melosira sp. (Y = 0.30), Skeletonema sp. (Y = 0.22), and Chaetoceros sp. (Y = 0.15). In spring, the community structure shifted, with Melosira sp. (Y = 0.70) and Cyclotella sp. (Y = 0.14) becoming predominant. Chaetoceros sp. and Skeletonema sp. exhibited negative correlations with T, pH, and PO₄³⁻ concentration, and their significant decline in spring coincided with elevated levels of these physicochemical factors. In contrast, Melosira sp.’s strong positive correlation with pH, further intensified by an increased pH in spring, solidified its absolute dominance. A statistically significant negative correlation was observed between the abundance of Skeletonema sp. and pH. This negative relationship was directly reflected in spring under relatively high pH conditions, manifesting as a marked inhibition and reduction in its abundance. Thus, Melosira sp. is more tolerant of high alkalinity than Skeletonema sp. Elevated PO₄³⁻ concentrations in spring, positively correlated with Cyclotella sp., further supported its prominence. These findings underscore the critical role of seasonal environmental changes in shaping diatom community dynamics.

In the mangrove tidal system of the Sanya River, the absolute dominance of Melosira sp. in spring is the result of the synergistic effect of natural seasonal drive and anthropogenic pressure. The natural drive is reflected in the tidal nutrient pulses brought by the increase in water temperature and light in spring. The anthropogenic pressure is reflected in the increase in PO₄³⁻ due to the input of domestic sewage in the midstream, which strengthens its competitive advantage. It is worth noting that their dominance is not equivalent to simple eutrophication: the coexistence of multiple dominant species in winter reflects the mesotrophic state, whereas the formation of a single dominance in spring is driven by a synergistic combination of temperature, pH (explanatory power of 34.7%), and nutrients, with the role of pH being particularly critical.

4.2. Effects of Seasonal Changes and Human Activities on the Structure of Diatom Communities

The planktonic diatom community in the Sanya River mangrove ecosystem displayed significant seasonal variation in structure and composition. In spring, Melosira sp. dominated (Y = 0.70), while winter supported a more diverse community with Melosira sp. (Y = 0.30), Skeletonema sp. (Y = 0.22), and Chaetoceros sp. (Y = 0.15) as co-dominant genera. Cell abundance ranged from 2.48 to 21.0 × 10⁹ cells·L⁻¹) in spring compared to 0.46 to 17.4 × 10⁹ cells·L⁻¹ in winter, driven by the explosive proliferation of Melosira sp. RDA analyses, depicted in Figure 7, identified a significant positive correlation between Melosira sp. and pH, with an elevated pH in spring reinforcing its predominance and homogenizing community structure. In addition, higher NO₂⁻ and PO₄³⁻ concentrations in spring, positively correlated with Cyclotella sp., bolstered its role as a dominant genus. In contrast, Chaetoceros sp. and Skeletonema sp., negatively correlated with T, pH, and PO₄³⁻ concentration, declined significantly in spring’s elevated conditions. In terms of community stability, diatom community diversity (H’ mean 1.26) and evenness (J mean 0.62) were significantly higher in winter than in spring (H’ mean 0.76, J mean 0.38), suggesting that the outbreak of a single dominant species in spring led to the homogenization of the diatom community in spring. This homogenization is a symptom of the loss of taxonomic diversity and is more likely to reduce ecosystem stability and resilience by undermining functional redundancy mechanisms [45].

Spatially, the diatom community structure varied, as it was influenced by nutrient dynamics and human activities. In terms of cell abundance, the peak of diatom abundance in winter appeared at site A3 (17.4 × 10⁹ cells·L⁻¹) in the midstream residential area, while the highest value in spring shifted to the estuary area (21.0 × 10⁹ cells·L⁻¹). PO₄³⁻ concentrations were significantly higher in the spring than in the winter, and the concentrations of PO₄³⁻ near the river estuary showed the lowest values in both spring and winter, mainly due to dilution by oligotrophic seawater. Nutrient concentrations were significantly higher in the commercial area in spring and in the tributary area in winter due to domestic sewage discharge and restricted water exchange, highlighting the anthropogenic impacts. Eutrophication, which particularly increased PO₄³⁻ in spring, enhanced Melosira sp.’s dominance by suppressing Chaetoceros sp. and Skeletonema sp., shaping community dynamics. In addition, the positive correlation between PO₄³⁻ and Cyclotella sp. contributed to its emergence as a dominant genus in the spring, which is in line with the results of the American River-based study by Potapova & Charles based on the American River: Cyclotella meneghiniana was identified as a typical indicator species of high total phosphorus (TP), and its relative abundance was significantly and positively correlated with nutrient enrichment [6], whereas changes in the concentration of PO₄³⁻, as an important component of total phosphorus, may directly affect the response pattern of diatom communities. These findings emphasize the interplay of environmental and human-induced factors in driving diatom community structure.

The seasonal succession of planktonic diatom communities in the mangrove forests of the Sanya River (multi-species coexistence in winter and the outbreak of a single dominant species, Melosira sp., in spring) is closely related to environmental factors (pH, temperature, and PO₄³⁻) and human activities. The ecological significance of this study is as follows: in spring, Melosira sp. forms a dominant species by virtue of its high tolerance to high pH and PO₄³⁻, which can increase primary productivity but may lead to a decrease in the stability of the food chain, an imbalance in material cycling, and a weakening of ecosystem resistance to disturbance; in winter, the coexistence of multiple dominant species can efficiently utilize the ecological resources, with a high degree of redundancy in function and a stronger resistance to disturbance. Therefore, when there is a switch in the dominant species, the risk of possible imbalance of the ecological structure and local eutrophication in the area needs to be guarded against.

5. Conclusions

In this study, we combined the structure of planktonic diatom communities (abundance and diversity index) with key physicochemical parameters such as water temperature, pH, and PO₄³⁻, and systematically revealed the seasonal–spatial dynamics of diatom communities in tropical estuarine mangrove forests and their responses to environmental factors by using multivariate statistical methods such as RDA in the Sanya River. This method is suitable for the unique tropical climate of the Sanya River and provides a new biomonitoring method for this region and similar tropical estuarine wetlands. The analysis of diatom indicators and physicochemical factors led to the following conclusion: the water quality of the mangrove wetland of the Sanya River still maintains its basic ecological function, but we need to be vigilant about two major risks: first, the risk of ecological imbalance caused by the outbreak of a single dominant species, such as Melosira sp., in spring, and the risk of localized eutrophication in the middle reaches of the river and tributary areas due to human activities (input of domestic wastewater and restricted water exchange). The study provided a bioindicator system for water quality monitoring in tropical estuarine wetlands through the dynamic correlation of key drivers such as pH, temperature, PO₄³⁻, and diatom abundance and diversity indices. Future studies can further improve the sensitivity of monitoring micro-sized diatoms and low-abundance species and provide a more refined scientific basis for mangrove ecological restoration and management.