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Article

Changes of Macrobenthic Diversity and Functional Groups in Saltmarsh Habitat under Different Seasons and Climatic Variables from a Subtropical Coast

by
Shayla Sultana Mely
1,2,†,
Mohammad Belal Hossain
1,3,*,†,
Mahabubur Rahman
1,
Mohammed Fahad Albeshr
4 and
Takaomi Arai
5
1
Department of Fisheries and Marine Science, Noakhali Science and Technology University, Noakhali 3814, Bangladesh
2
Bangladesh Fisheries Research Institute, Mymensingh 2201, Bangladesh
3
School of Engineering and Built Environment, Griffith University, Nathan, QLD 4111, Australia
4
Department of Zoology, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia
5
Environmental and Life Sciences Programme, Faculty of Science, Universiti Brunei Darussalam, Jalan Tungku Link, Gadong BE 1410, Brunei Darussalam
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Sustainability 2023, 15(9), 7075; https://doi.org/10.3390/su15097075
Submission received: 17 February 2023 / Revised: 7 April 2023 / Accepted: 13 April 2023 / Published: 23 April 2023
(This article belongs to the Special Issue Aquatic Biodiversity under the Impact of Climate Change)
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Abstract

:
Saltmarsh is one of the most productive coastal habitats in the marine environment, and the macroinvertebrate community is crucial to its ecology and productivity. These productive ecosystems are currently under threat due to climate change and anthropogenic activities. However, macroinvertebrate communities and their functionality in saltmarsh from subtropical coastal areas have previously been largely ignored. In this study, we aimed to elucidate (i) the diversity and community assemblages, (ii) trophic structure, and (iii) changes of macroinvertebrate diversity under different seasons and climatic variables from a subtropical saltmarsh habitat. A total of 29 taxa in the eight (8) major groups were recorded in both seasons, with polychaetes being dominant (64%) in monsoon and crustaceans (50%) in post-monsoon. Among the trophic groups identified, surface deposit feeders and omnivores were dominant, accounting for 78.52% of the total groups. The highest value of diversity index (2.04) was observed at station S3 in monsoon and the lowest (1.408) at station S2 in post-monsoon. Strong seasonal variability was confirmed by two-way ANOVA and PERMANOVA, and SIMPER analysis identified that shrimp larvae (Macrobrachium sp.) were the taxa that contributed the most to grouping patterns between areas and seasons. In addition, non-metric multidimensional scaling (nMDS) revealed a great dissimilarity of macrobenthic faunal assemblages among the study stations and seasons. Spearman’s rank correlation analysis and canonical correspondence analysis (CCA) results revealed that the climatic factors water temperature, salinity, and alkalinity variation influenced the benthic community diversity.

1. Introduction

Saltmarsh is an intermediate zone between marine and terrestrial habitats [1] and constitutes a unique coastal ecotone that is the most productive system globally [2]. Saltmarshes are developed in the mouth of rivers and sheltered bays, safe from the full force of tidal waves and dominated by a variety of halophytic low shrubs, herbs, and grasses [3]. These coastal formations can range from narrow periphery on steep shoreline to several kilometers in planar magnitude that dominates in the temperate region [4] and enhance the settlement of fine sediments and nutrients [5]. Saltmarshes provide shade that ultimately reduces water and sediment temperature and pore water salinity, hold water in the sediment [6], and create suitable microhabitat, which is important to the survival of benthic macroinvertebrates [7,8]. These coastal formations also provide food and shelter for a wide variety of benthic fauna, in addition to breeding and perching grounds [9].
The coastal region of Bangladesh is vulnerable to the effects of climate change, making it one of the nations most at risk. Rising sea level, increased salinity and temperature, and reduced dissolved oxygen are some of the common effects of climate changes on the ecology of coastal ecosystems. Coastal saltmarshes constantly face hydrological oscillation and high environmental variability, whereas water exchange regulates benthic structure in coastal environments [10,11]. The distribution of macrobenthos is influenced by a broad range of parameters, such as tidal cycle, depth, sediment, saltmarsh vegetation, and food [12]. Environmental variables, such as salinity, pH, DO level, and temperature, can also affect macrobenthos distribution, survival, and metabolism [13,14,15]. In addition, being a subtropical country, the Bangladesh coast enjoys unique climatic conditions due to monsoonal influence with wide seasonal variations in rainfall and high temperatures and humidity. The rainy season (June–October) receives about 2200 mm of rainfall per year on average, accounting for 70 to 85% of the annual rainfall, which varies from 70% in the eastern part of the country to about 80% in the southwest, and 85% in the northwest. This downpour greatly influences the distribution of macrobenthos in the study area. This strong seasonal variation influences almost all prevailing ecological parameters, including salinity, pH, sediment properties, and vegetation cover.
The macrobenthos is a dominant and valuable component of saltmarsh habitat, and hence it has been well studied throughout the world [16]. However, despite its importance, the macrobenthic assemblage and the taxonomy of major groups from the coastal area of Bangladesh have not received significant attention. Located on the bank of the mighty Meghna River confluence, Noakhali is one of the coastal districts at the fringe of the Bay of Bengal with vast char land of recent origin in the south. This area is very productive because it possesses a wide range of saltmarsh areas, such as Caring Char, Noler Char, and Boyer Char, which are rich in benthic fauna continuously flooded with the tide. These saltmarshes are marshy areas near the Meghna River estuary. The habitats of this region contain communities of salt-tolerant vegetation (halophytes including grasses, herbs, reeds, sedges, and shrubs), a wide range of infaunal and epifaunal invertebrates, and low-tide and high-tide visitors such as fish and water birds. The water in saltmarshes varies from completely saturated with salt to freshwater. Both saltmarsh and estuary are affected by high and low tides. It is commonly seen that some migratory birds feed in saltmarsh during their overwintering. The Hilsha (national fish; Tenualosa illisha) fishing ground in the Meghna estuary and the adjacent coast are assumed to be connected to the saltmarsh and mangrove forest of the Noakhali coast. There has been a variety of macrobenthic community research conducted globally. However, relatively little information is available about the macrobenthos of saltmarsh in Bangladesh’s coastal region. Some researchers and scientists have recently studied the diversity and distribution of benthos in the coastal region of Bangladesh [17]. Benthic organisms are the main food sources of fishes, epibenthic crustaceans and birds [18]. In addition, the macrobenthic community is often used as a critical bioindicator to assess the quality of coastal and estuarine environments [19,20], because the community structure and distribution of macrobenthos are altered by the function of different environmental parameters [21]. Saltmarsh habitat of the Noakhali coast is of particular importance as it provides nursing grounds for critical larval and juvenile stages of commercially valuable species, e.g., Lates calcarifer, Mugil cephalus, Penaeus monodon, Hilsha ilisha, and is even used by adults of some species for spawning. This area is also a known feeding ground for migratory birds. Protecting the saltmarsh in this location is also essential since it forms part of an accreted island and marsh grasses hold the sediments together and provide protection from tidal action. Even the national strategies for saltmarsh protection reflect this significance. Studying biodiversity and the seasonal change of resident fauna is vital for the better management and protection of saltmarsh environments. Therefore, this study was conducted to answer three basic questions: (i) what were the benthic communities and their association in the study area? (ii) to which functional feeding groups did they belong? and (iii) was there any variation in benthic communities under selected climatic variables and different seasons?

2. Materials and Methods

2.1. Study Stations

The study was conducted on the Noakhali coast, in the intertidal zone of the Meghna estuary in the southeast region of Bangladesh (Figure 1). The coast is situated along the active zone of accretion. Chars, or new lands, are consequently constantly being formed. People who are homeless or climate-vulnerable are settling in this region and rely heavily on farming, fishing, and agricultural activities to make a living. The Embankment Project was recently started by the Bangladeshi government to reclaim or safeguard areas in the Noakhali coastal zone. For instance, the Sandwip-Urir Char-Noakhali Cross Dam Project was constructed in the directions of Sandwip-Urir Char-Noakhali to seal tidal creeks that were below the highest flood levels [22]. As a result, the 370 miles of coastline along the channel between Sandwip and the Noakhali mainland are progressively becoming silted up, creating new char lands. Additionally, the multidisciplinary Sandwip-Urir Char-Noakhali Cross Dam project will create 18,000 ha of new territory over the next 30 years [22]. The area is primarily covered with the saltmarsh species Porteresia sp. [23] and directly influenced by the incoming semi-diurnal tide (two tidal cycles per lunar day of 24 h 50 min) of Bay of Bengal. Therefore, the water level in the study area shows considerable variation from neap to spring tides. The tidal range is significantly higher, with an average range of over 5.0 m. The maximum depth-integrated velocity in the dry period is 1.00–2.00 m/s along the Noakhali coast. In monsoon, current speed is higher compared to the dry season as it is dominated by strong south-west monsoon wind (average 4~5 m/s and maximum 20~30 m/s). A strong anti-clockwise circulation prevails around the coast, which is mainly caused by tide. Due to high discharge from the rivers Ganges, Jamuna, and Meghna, suspended sediment concentrations are generally abundant and the particles are fine, cohesive, prone to flocculate, and organically rich. The salinity varies from 4–6 ppt and the water temperature from 26–29 °C along the Noakhali Coast [23]. During the rainy season, the area receives on about 2200 mm of rainfall on average. In this context, three sampling stations were selected along the Noakhali coast, Caring char (22°29′25.828″ N, 91°06′54.748″ E), Noler Char (22°31′03.159″ N, 91°05′35.465″ E), and Boyar Char (22°31′03.311″ N, 91°04′54.756″ E), which were named as S1, S2, and S3, respectively. Station 1 (S1) is located near to the main channel of the estuary but protected from the direct influence of tidal waves. It is almost covered with thick macrophyte species, Porteresia sp. Sandy-clay particles are dominant in this station. Station 2 and Station 3 (S2 and S3) are away from the main channel and located on the two sides of a creek. The abundance of macrophyte species is patchy in these two stations. The bottom is mostly muddy with deposited clay particles. The distance between the sites (from S1 to S2 and S3) is approximately 20 km.

2.2. Sample Collection and Analysis

Environmental variables. including water temperature, salinity, water and soil pH, hardness, dissolved oxygen (DO), and alkalinity, were also recorded while collecting the sediment samples containing macrofaunal organisms. Dissolved oxygen was measured was using Lutron series portable DO meter (AF. 01223, Taiwan). Water pH, alkalinity, and hardness were measured using a HANNA series portable pH meter (HI 96107, Romania), alkalinity test kit (HI 3811, Romania) and portable hardness meter (TIII 14375, Romania), respectively. For the soil pH measurement, we used a portable soil pH moisture meter (KS 05). Salinity and temperature of the sub-surface water were measured using BRIX series salinity meter (RHB 32ATC) and centigrade thermometer (UK), respectively.
Sediment samples for macrobenthic faunal species quantification were collected using a hand-held mud corer (10 cm × 10 cm × 10 cm), with a mouth area of 0.01 m2 and a penetration depth of 10 cm at the edge of the grab, by excavating substrate sediment in the vegetated and unvegetated areas at low tide [13]. At each site, three replicate sediment samples were collected from August to September 2017 (monsoon) and January to February 2018 (post-monsoon) for macrofaunal analysis. Then, the sediment sample was passed through a 500 µm stainless steel hand sieve with saltmarsh water, and biological materials retained in the sieve were preserved with 10% formalin solution in plastic vials with debris. A small amount (0.5 g in 20 L of 10% formalin) of “Rose Bengal” (4,5,6,7-tetrachloro-2′,4′,5′,7′-tetraiodofluorescein) was added within the formalin solution in the laboratory to increase the visibility of organisms. Colored benthic fauna was classified into families/genera by manual separation with forceps in the presence of adequate light using a stereomicroscope (Model: XSZ21-014 DN, Shanghai, China) following [24,25,26] and counted organisms were preserved and kept in small vials with 70% alcohol. Organisms with similar morphological features were recorded as ‘morphospecies’. Identification was checked in the world taxonomic database, WoRMS (https://www.marinespecies.org, accessed on 12 November 2017). Trophic groups of macrobenthos were categorized according to Gaston and Nasci [27]. Each macrobenthos was categorized by the following feeding groups: surface deposit feeder (SDF), sub-surface deposit feeder (SSDF), filter feeder (FF), omnivorous (OMN). or carnivorous (CAR) [28,29].

2.3. Data Analysis

Macrofaunal abundance was calculated as ind./m2 before further statistical analysis. The individual mean value was calculated as the total number species of each station divided by the total number of stations. The average value of environmental variables was estimated as the total value of each station divided by the total number of stations. To compare the seasonal variation and community structure of macrobenthos for each station and significant differences of diversity indices (abundance, species richness, diversity index, and evenness index) among stations, two-way ANOVA was performed. Data normality was checked before performing statistical analyses using histograms and the Shapiro-Wilk test. In the case of asymmetric data, square-root transformation was used to normalize the data [30]. Two-way ANOVA was used to compare physical variables (water temperature, salinity, water and soil pH, hardness, dissolved oxygen, and alkalinity) between stations and seasons. Similarity matrices were performed by using Bray-Curtis distance on raw data, followed by a non-metric multidimensional scaling ordination (nMDS) to observe possible patterns of macrofaunal assemblages among sites and between seasons. Post-hoc test was used to test for differences in abundance and species richness between stations. In addition, permutational multivariate analysis of variance (PERMANOVA) and similarity percentage analysis (SIMPER) were performed to determine which organisms contributed to dissimilarities between stations and seasons [30].
In addition, Spearman’s rank correlation analysis and canonical correspondence analysis (CCA) were used to determine the correlations between diversity indices (abundance, species richness, evenness index, and diversity index) and environmental variables, in order to assess which variables were most significant for benthic faunal distributions between stations. All univariate and multivariate statistical analyses were performed using PAST (Paleontological statistics, version 4.07, Tromso, Norway).

3. Results

3.1. Environmental Characteristics

The environmental parameters of sub-surface water and sediment at three sampling stations are shown in Table 1. Water temperature values fluctuated between 31.17 ± 0.29 °C during monsoon and 24 ± 0.87 °C during post-monsoon. Salinity showed a clear seasonal variation, ranging from 8.35 ± 0.15 to 0 ppt from monsoon to post-monsoon. Water and soil pH varied from 8.91 ± 0.12 to 7.06 ± 0.06 and 6.97 ± 0.06 to 5.83 ± 0.06, respectively, with a peak in post-monsoon. Dissolved oxygen fluctuated between 8.26 ± 0.23 and 5.9 ± 0.28 mg/L during post-monsoon. Alkalinity varied from 162 ± 43.27 to 73.67 ± 3.79 ppm (peaked in post-monsoon) and hardness varied from 1486.6 ± 15.28 to 153.33 ± 30.55 (peak in post-monsoon). Two-way ANOVA results showed significant differences among sites and seasons (p < 0.05 and p < 0.001, respectively), except for alkalinity in site and DO in season (p > 0.05). A highly significant difference (p < 0.001) was found between the interaction of site and season in water temperature, water pH, and soil pH. In addition, salinity, DO, and hardness showed significant differences (p < 0.05), and the interaction term was not significant for alkalinity (Table 1).

3.2. Macrobenthos Community Dynamics

Overall, a total of 29 families, including 23,743 individuals, were recorded in sediment samples from the coast and adjacent areas during the study period (Table 2). The five most common macrobenthic fauna were shrimp larvae (16.29% of the total in all sites), Nereis sp. 1 (11.51%), Mysis sp. (10.51%), Nephtys sp. (9.97%), and Lumbrineris sp. (8.43%). Polychaetes, with 11 families (49%), and crustaceans, with 9 families (41%), were the most dominant groups, whereas insecta (4%) and bivalvia (2%) composed of only 2 families each. Other less abundant families, including oligochaete, fish larvae, clitellate, and gastropods, contributed only 4% of total abundance.

3.3. The Seasonal and Spatial Variation of Macrobenthos

The seasonal and spatial variation of macrobenthic faunal abundance in the Noakhali coast, Bangladesh, is shown in Figure 2 and Table 3. In the present study, 11,276 individuals were found in monsoon and 12,467 individuals were recorded in post-monsoon. Polychaete was the most abundant group in monsoon and crustacea in post-monsoon. In the monsoon period, 64.84% of polychaete and 31.04% of crustacea were recorded while in the post-monsoon period, 50.26% of crustacea and 35.04% of polychaete was recorded. Polychaete and crustacea contributed 90.32% of total abundance and were found in all seasons, whereas, insecta, the 3rd most abundant macrobenthic taxonomic group, contributed 4.22% was only recorded in the post-monsoon season (Table 3). It is noteworthy that few families were present only at certain stations. For example, fish larvae and clitellate contributed at station S3. Polychaetes and crustaceans were the most diverse groups at all stations; polychaetes were dominant at station S1 (46%) and S3 (69%) but crustaceans were dominant at station S3 (67%) (Figure 2).

3.4. Trophic Structure of Macrobenthos

Table 4 summarizes that 29 taxa were classified into 5 trophic groups, viz. SSDF (9 species), OMN (7 species), SDF (5 species), CAR (4 species), and FF (4 species). SSDF and OMN were the dominant trophic groups, accounting for 78.52% of the total groups. Filter feeder (FF) showed significant differences between seasons (p < 0.05) and was higher in monsoon. A similar trend was observed for carnivorous (p < 0.05), which was higher in post-monsoon.
Two-way ANOVA of biological indices showed that no significant difference was found among stations, between seasons, and the interaction of the two factors except evenness index (Table 5). In terms of spatial distribution, the abundance of intertidal macrobenthos was higher (6233.33 ind./m2) at station S3 during the monsoon, but in post-monsoon period, the highest abundance was found at stations S2 and S3. Lower values were recorded at station S1 in both seasons. On average, higher (10.67) and lower (8) values of species richness were measured in monsoon. The highest value of diversity index (2.04) was observed at station S3 in monsoon and the lowest (1.408) at station S2 in post-monsoon. A higher value of evenness index (0.789) was observed at station S1 in monsoon whereas a lower value (0.411) was observed at station S2 in post-monsoon (Figure 3). In terms of seasonal distribution, abundance was higher (4155.67 ± 840.55 inds./m2) in post-monsoon and lower in monsoon (3758.67 ± 2152.07 inds./m2). Species richness (17 ± 0) also peaked in post-monsoon. In contrast, diversity index and evenness index peaked in monsoon. Post-hoc comparisons showed differences for abundances and species richness between S1 and S3 (p = 0.05) but did not show any significant differences for S2 and S3 (p = 0.18). However, for evenness indices they showed highly significant differences between S1 and S2 (p = 0.01), S1 and S3 (p = 0.004), and S2 and S3 (p = 0.002).
Non-metric multidimensional scaling (nMDS), based on a Bray-curtis similarity matrix from square-root-transformed abundance data, provided a stress value of 0.26, representing a poor pattern, and showed a great dissimilarity among samples of macrobenthic faunal assemblages between study sites and seasons (Figure 4). PERMANOVA analyses confirmed that macrobenthic faunal communities significantly differed among study stations and seasons, with a significant interaction between the two factors (p = 0.02) (Table 6). Pairwise post-hoc comparison tests in PERMANOVA showed significant differences among stations; S1 vs. S2 (p = 0.0003), S2 vs. S3 (p = 0.001), and S1 vs. S3 (p = 0.021). SIMPER analysis indicated that the overall average dissimilarity between stations and seasons was 54.98% and 58.44%, respectively, and the difference was primarily driven by the Macrobrachium sp. in both stations (contributed 6.80%) and seasons (contributed 6.11%) (Table 7). In addition, the average dissimilarity of three saltmarsh habitats was 63.19% in S1, 59.4% in S2, and 52.71% in S3, and the difference was primarily driven by Paraprionospio sp. (contributed 9.17%), Melinna sp. (contributed 10.21%), and Calanus sp. (contributed 9.51%) respectively.

3.5. Linkage between Biotic and Abiotic Variables

The Spearman’s rank correlation analysis indicated that biotic variables were not significantly correlated (p < 0.05), with the exception of some parameters. Water temperature and salinity were significantly positively correlated with evenness index (p = 0.003) and abundance (p = 0.006). DO showed a positive significant correlation with evenness index (p = 0.024). Alkalinity showed positive and negative significant correlations with abundance (p = 0.038) and species richness (p = 0.034), respectively (Table 8).
CCA was performed to investigate and visualize the potential relationship between macrobenthos and environmental parameters (Figure 5). The first two axes explained 65.74% of total variance. The first axis, which contributed 38.21% of total variance, showed a moderately positive correlation with water temperature (r = 0.52), a weak relationship with DO (r = 0.02), and a negative correlation with alkalinity (r = −0.47), salinity (r = −0.62), hardness (r = −0.7), water pH (r = −0.47), and soil pH (r = −0.49). Genus levels such as Macrobrachium sp., Ampelisca sp. -1, Nephtys sp., Sigambra sp., Lumbrineris sp., and Nereis sp. -1 were placed on the right side, indicating that they were positively correlated with water temperature and DO. The second axis showed weak positive correlations with water pH (r = 0.16), water temperature (r = 0.01), salinity (r = 0.03), alkalinity (r = 0.17), and soil pH (r = 0.31). Mysis sp., Calanus sp., Nereis sp. -2, and Nemanereis were positively correlated with alkalinity, salinity, hardness, and water and sediment pH, while negatively corelated with DO and water temperature.

4. Discussion

4.1. Composition of Macrobenthic Communities in Saltmarsh along Noakhali Coast

From this study, 29 taxa were recorded from the saltmarsh habitat with five functional feeding groups (sub-surface deposit feeder, omnivorous, filter feeder, surface deposit feeder, carnivorous). Polychaetes and crustaceans were dominant. However, lower numbers of taxa were reported previously by other researchers [31,32] in the saltmarsh habitat of the Noakhali coast, Bangladesh. This was possibly due to different sampling designs, poor taxonomic identification, and sampling season. Compared to other tropical coastal habitats, this result was in line with the findings of Wang et al. [31]. In addition, our results are comparable with several studies on benthic faunal abundance and distribution in saltmarsh throughout the world [6,16,18,31,33]. For example, Vinagre et al. [34] recorded 22 taxa from the saltmarsh of Tagus estuary, Braga et al. [6] identified 51 taxa from Amazon coast saltmarsh and Santos et al. [18] found 35 taxa from another tropical saltmarsh. Numerous studies have shown the interrelationships between hydrodynamic factors, sediment particle sizes, and organic matter content, as well as the correlations between all variables that influence the densities and dispersion of benthic communities. The relevant causal links, however, have not yet been thoroughly demonstrated, as found by a number of investigators [18,33,34].
According to Kneib [35], polychaetes, crustaceans, insecta, oligochaetes, and mollusks are dominant taxa in saltmarsh habitats. In general, benthic faunal diversity in saltmarsh is low [36] but shows similarities between different geographical positions because of environmental equivalence [7]. Similar results were found in the present study and other studies in tropical and subtropical saltmarshes [16,32,36,37].

4.2. Seasonal and Spatial Dynamics of Macrobenthic Community

Polychaetes were the most dominant group in all stations and peaked in monsoon, whereas crustaceans peaked in post-monsoon. This dominance was primarily related to the abundance of Nephtys sp. in monsoon and shrimp larvae in post-monsoon. On the other hand, large dominance was found within stations by decapod larvae. Ullah et al. [32] and Smee et al. [16] found decapods were less abundant in saltmarshes, which was opposite to the present study and other published articles [6]. Chakma et al. [38] found that oligochaete was the dominant group in freshwater earthen ponds of Noakhali district, Bangladesh, and arid and temperate saltmarshes worldwide [31,39,40,41]. Wang et al. [31] recorded high dominance of gastropods in saltmarsh along the Yangtze Estuary and British coastal saltmarsh, but less abundant gastropods were recorded in the present study. It is hypothesized that the variation of predatory interactions in saltmarsh can change food webs [42] and/or affect physio-chemical factors and sediment composition to make habitats less suitable for some species [43,44,45], which might be the cause of availability or unavailability of some species.
Our results revealed that abundance was higher in post-monsoon than monsoon. This trend was primarily related to the high abundance of the crustacean: Macrobrachium sp. and the Polychaetes: Nephtys sp., Lumbrinereis sp. and Nereis sp. -1. This condition might have occurred due to the breeding of macrobenthos and recruitment of new organisms into the faunal community in early summer. Similar seasonality of macrobenthos distribution was found in tropical saltmarshes [6,36]. As compared with saltmarsh vegetation, abundance showed significant variation between seasons, which is in agreement with Sarda et al. [46], Xie and Gao [47], and Braga et al. [6]. On the other hand, the species richness of epibenthos in China’s coastal saltmarsh did not show significant variation, which agrees with the result of this study [47].
Rahman et al. [29] and Minuz and Pires [48] found that sub-surface deposit feeder (SSDF) was the dominant trophic group in freshwater-dominated tropical estuary and in the northern region of the Sao Sebastiao Channel, which are similar to the present study area [31,47]. Omnivore (OMN) is the second most dominant trophic group in the study. Ysebaert et al. [49] reported that omnivore (OMS) was dominant in the brackish water of Schelde estuary, which supports the findings of the present study. This dominance psuggsts that macrobenthic assemblages depend on energy sources which come from the presence of detritus, altering the distribution of the deposit feeder group [50,51,52]. Omnivorous and filter feeder were higher in monsoon but Noman et al. [28] highlighted that omnivorous was higher in monsoon and filter feeder higher in pre-monsoon [32]. The cause of these dissimilarities might be attributed to the characteristics and organic content of sediment, vegetation condition, rainfall, etc. Saltmarshes are halophytes that can withstand fluctuations in salinity [53], and saltmarshes along the Noakhali coast appear to be no exception. According to Adam [54] and Bortolus et al. [55], taller and denser saltmarsh vegetation has been linked to a more plentiful and varied macroinfaunal assemblage. Precipitation variation is another factor that can affect salinity and temperature [56,57,58], which may be the main contributors to the presence of a high number of taxa and low species abundances due to broad temporal variation [59,60,61].
Based on the present study, a higher diversity index was accounted for in monsoon, and the elevation of evenness index showed significant variation among the sampling stations, between seasons and the interaction of these two factors, which was congruous with the result of Xie and Gao [47]. Salgado et al. [39] indicated a similar effect in saltmarshes of Tejo estuary (Portugal). However, lower diversity and evenness index were recorded by Ullah et al. [32] in the saltmarsh of the Noakhali coast. The differences of findings may be related to the methodology (poor sampling) used and/or largely due to changes in the number of species and hydrography of saltmarsh.

4.3. Relationship between Biotic and Abiotic Variables

Saltmarshes are flooded with water only at the highest tides, which increases the salinity exposure further down the intertidal region, resulting in less variable salinity exposure. The present study revealed that saltmarsh has definite benthic communities along the salinity gradient. The abundance and the number of taxa recorded showed a decline with decreasing salinity. This agrees with a study of the intertidal macrobenthic community in the Schelde estuary [6,40].
A clear affinity between environmental parameters and macrobenthos is found in estuaries [62,63,64] and saltmarshes [6,40]. Results from Ullah et al. [32] revealed that salinity and temperature were positively correlated with abundance and richness. Similar results were found by Beasley et al. [65] and Braga et al. [6]. In the present study, Spearman’s rank correlation analysis stated that salinity was significantly positively correlated with abundance, but no significant correlation was found between temperature and the number of taxa. This dissimilarity was contrary to the finding of Beasley et al. [65], First and Hollibaugh [66], and Braga et al. [6]. Sarker et al. [23] demonstrated that alkalinity was significantly negatively correlated with abundance, which agrees with the present findings. Diversity index showed a positive significant correlation with salinity, not only in saltmarshes in the Schelde [49] but also in other estuaries [67], which is opposite to our findings.
Macroinvertebrate communities in the study region may have varied as a result of anthropogenic actions such as land reclamation, human settlement, fishing, agriculture, and transportation, or they may have done so indirectly. In the Char lands of Noakhali, agriculture, fishing, and cattle raising are the main industries. Several reclamation projects/dams have been set up in the area. For example, the rate of siltation in the area has significantly risen as a result of the Sandwip-Urir Char-Noakhali Cross Dam Project. These human actions have a variety of effects on the diversity of environments. It is reported that changing natural flow patterns and the accumulation of fine sediments that result can decrease standing macroinvertebrate crops. Moreover, farming alters water and sediment quality, which, in turn, negatively affects aquatic organisms. Increased turbidity from sedimentation, in turn, reduces the diversity of benthic macroinvertebrates in the saltmarsh habitat due to human settlement, agricultural activity in the watershed, and lessened hydrological connectivity. Agriculture, transportation, and farming-related soil erosion may increase nutrient intake, which, in turn, causes eutrophication and algal blooms, and thus represents a potential secondary source of turbidity and changes in benthic communities.
In the present study, we found that the first two axes of CCA explained 49.54% of the total variance, which is comparable with the findings from Tagus estuarine saltmarsh as they recorded that the first two axes of the CCA encompassed 59.6% of the total variance [34]. Furthermore, our CCA revealed that Mysis sp. was positively correlated with water temperature, which is supported by the findings of David et al. [68] and Selleslagh et al. [69] at Gironde estuary in France. In addition, the CCA depicted that Nereis sp. had a positive affinity with salinity, but the opposite pattern was recorded in some estuaries [13,62,70]. However, we hypothesize that this dissimilarity might occur due to the composition of sediment particles; hence, a further in-depth study including the sediment properties is recommended.

5. Conclusions

In this study, the macroinvertebrate community structure and its functional feeding groups in a subtropical saltmarsh habitat under different seasons and climatic variables were investigated. A total of 29 taxa were recorded, and the community was dominated by polychaetes in monsoon and crustaceans in post-monsoon. Five trophic groups were identified, where surface deposit feeders and omnivores were dominant. Both univariate and multivariate analyses (two-way ANOVA and PERMANOVA, and SIMPER) demonstrated strong seasonal variability, and shrimp larvae (Macrobrachium sp.) were the most contributing taxa for grouping patterns between areas and seasons. Climatic variables, salinity, water temperature, and alkalinity were crucial factors influencing macrobenthic distribution and biodiversity, as revealed by Spearman’s rank correlation analysis and canonical correspondence analysis (CCA) results. Understanding a wetland ecosystem and its processes requires knowledge of its diversity, composition, and functional groups. As a result, our study offers crucial insights for a more comprehensive management strategy for safeguarding this type of wetland. However, due to the shorter study duration (6 months), it was not possible to draw any firm conclusions or identify distribution patterns and ecosystem functioning. Future research findings may, therefore, vary slightly from those of the current findings and opinions. However, more detailed studies, especially considering marsh vegetation, above and below ground biomass, sediment composition and organic enrichment, will help us to better understand seasonal and spatial patterns in assemblage structure associated with environmental parameters. In addition, in future studies of climate change in subtropical coastline, the indirect impact of topographic control should be assessed.

Author Contributions

Conceptualization, M.B.H.; methodology, S.S.M. and M.B.H.; formal analysis, S.S.M. and M.B.H.; investigation, S.S.M. and M.B.H.; resources, M.B.H.; data curation, S.S.M. and M.B.H.; writing—original draft preparation, S.S.M.; writing—review and editing, M.B.H., M.F.A. and T.A.; visualization, S.S.M. and M.B.H.; supervision, M.B.H. and M.R.; project administration, M.B.H.; funding acquisition, M.B.H., M.F.A. and T.A. All authors have read and agreed to the published version of the manuscript.

Funding

This study was partially funded by Universiti Brunei Darussalam under the Faculty/Institute/Center Research Grant (No. UBD/RSCH/1.4/FICBF(b)/2020/029) and (No. UBD/RSCH/1.4/FICBF(b)/2021/037) to Takaomi Arai. This research was also funded by the Researchers Supporting Project Number (RSP2023R436), King Saud University, Riyadh, Saudi Arabia.

Institutional Review Board Statement

Ethical review or approval is not required to work on macrobenthic species at Noakhali Science and Technology University.

Informed Consent Statement

Not applicable.

Data Availability Statement

All the relevant data are included in the manuscript. Raw data can be collected from corresponding author.

Acknowledgments

The authors would like to extend their sincere appreciation to the Researchers Supporting Project number (RSP-2023R436), King Saud University, Riyadh, Saudi Arabia. Thanks are also due to Salma Sultana, FIMS, Noakhali Science and Technology for creating the study map.

Conflicts of Interest

The authors declare that there is no conflict of interest.

References

  1. Regteren, V.M.; Amptmeijer, D.; De Groot, A.V.; Baptist, M.J.; Elschot, K. Where does the salt marsh start? Field-based evidence for the lack of a transitional area between a gradually sloping intertidal flat and salt marsh. Estuar. Coast. Shelf Sci. 2020, 243, 106909. [Google Scholar] [CrossRef]
  2. Banerjee, K.; Sappal, S.M.; Ramachandran, P.; Ramesh, R. Salt marsh: Ecologically important, yet least studied blue carbon ecosystems in India. J. Clim. Chang. 2017, 3, 59–72. [Google Scholar] [CrossRef]
  3. Sarika, M.; Zikos, A. Coastal Salt Marshes: Structure and Function of Plant Communities. In Handbook of Halophytes: From Molecules to Ecosystems towards Biosaline Agriculture; Springer: Berlin/Heidelberg, Germany, 2021; pp. 199–237. [Google Scholar]
  4. Laegdsgaard, P. Ecology, disturbance and restoration of coastal saltmarsh in Australia: A review. Wetl. Ecol. Manag. 2006, 14, 379–399. [Google Scholar] [CrossRef]
  5. Tang, H.; Xin, P.; Ge, Z.; Gong, Z.; Yang, Y.; Zhang, Y.; Qi, W. Response of a salt marsh plant to sediment deposition disturbance. Estuar. Coast. Shelf Sci. 2020, 237, 106695. [Google Scholar] [CrossRef]
  6. Braga, C.F.; Monteiro, V.F.; Rosa-Filho, J.S.; Beasley, C.R. Benthic macroinfaunal assemblages associated with Amazonian saltmarshes. Wetl. Ecol. Manag. 2011, 19, 257–272. [Google Scholar] [CrossRef]
  7. Nybakken, J.W.; Bertness, M.D. Estuaries and salt marshes. In Marine Biology: An Ecological Approach; Nybakken, J.W., Bertness, M.D., Eds.; Pearson/Benjamin Cummings: San Francisco, CA, USA, 2005; Volume 6, p. 579. [Google Scholar]
  8. Whitcraft, C.R.; Levin, L.A. Regulation of benthic algal and animal communities by salt marsh plants: Impact of shading. Ecology 2007, 88, 904–917. [Google Scholar] [CrossRef]
  9. Bortolus, A.; Iribarne, O. Effects of the SW Atlantic burrowing crab Chasmagnathus granulata on a Spartina salt marsh. Mar. Ecol. Prog. Ser. 1999, 178, 79–88. [Google Scholar] [CrossRef]
  10. McArthur, V.E.; Koutsoubas, D.; Lampadariou, N.; Dounas, C. The meiofaunal community structure of a Mediterranean lagoon (Gialova lagoon, Ionian Sea). Helg. Mar. Res. 2000, 54, 7. [Google Scholar] [CrossRef]
  11. Koutsoubas, D.; Arvanitidis, C.; Dounas, C.; Drummond, L. Community structure and dynamics of the molluscan fauna in a Mediterranean lagoon (Gialova lagoon, SW Greece). Belg. J. Zool. 2000, 130, 131–138. [Google Scholar]
  12. Saad, S.A.; Wade, C.M. Seasonal and Spatial Variations of Saltmarsh Benthic Foraminiferal Communities from North Norfolk, England. Microb. Ecol. 2017, 73, 539–555. [Google Scholar] [CrossRef]
  13. Hossain, M.B.; Marshall, D.J. Benthic infaunal community structuring in an acidified tropical estuarine system. Aquat. Biosyst. 2014, 10, 11. [Google Scholar] [CrossRef]
  14. Shou, L.; Zeng, J.; Liao, Y.; Xu, T.; Gao, A.; Chen, Z.; Yang, J. Temporal and spatial variability of benthic macrofauna communities in the Yangtze River estuary and adjacent area. Aquat. Ecosyst. Health Manag. 2013, 16, 31–39. [Google Scholar] [CrossRef]
  15. Zhang, J.; Xiao, N.; Zhang, S.; Xu, F.; Zhang, S.A. Comparative study on the macrobenthic community over a half century in the Yellow Sea, China. J. Oceanogr. 2016, 72, 189–205. [Google Scholar] [CrossRef]
  16. Smee, D.L.; Sanchez, J.A.; Diskin, M.; Trettin, C. Mangrove expansion into salt marshes alters associated faunal communities. Estuar. Coast. Shelf Sci. 2017, 187, 306–313. [Google Scholar] [CrossRef]
  17. Islam, M.S.; Pervez, A.; Asseri, A.H.; Al-Mutair, M.; Sumon, M.A.A.; Taleb, M.A.; Molla, M.H.R. Diversity and seasonal succession of resident and migratory macrobenthic fauna of saltmarsh restoration site at Sonadia Island, Cox’s Bazar, Bangladesh. Reg. Stud. Mar. Sci. 2022, 3, 102460. [Google Scholar] [CrossRef]
  18. Herman, P.M.J.; Middelburg, J.J.; Koppel, J.V.D.; Heip, C.H.R. Ecology of estuarine macrobenthos. Adv. Ecol. Res. 1999, 29, 195–240. [Google Scholar]
  19. Li, S.Z.; Cui, B.S.; Xie, T.; Zhang, K.J. Diversity pattern of macrobenthos associated with different stages of wetland restoration in the yellow river delta. Wetlands 2016, 36, 1–11. [Google Scholar] [CrossRef]
  20. Conlan, K.; Aitken, A.; Hendrycks, E.; McClelland, C.; Melling, H. Distribution patterns of Canadian Beaufort shelf macrobenthos. J. Mar. Syst. 2008, 74, 864–886. [Google Scholar] [CrossRef]
  21. Hossain, M.B.; Rakib, M.R.J.; Jolly, Y.N.; Rahman, M. Metals uptake and translocation in salt marsh macrophytes, Porteresia sp. from Bangladesh coastal area. Sci. Total Environ. 2021, 764, 144637. [Google Scholar] [CrossRef]
  22. Hoque, M.Z.; Islam, I.; Ahmed, M.; Hasan, S.S.; Prodhan, F.A. Spatio-temporal changes of land use land cover and ecosystem service values in coastal Bangladesh. Egypt. J. Remote Sens. Space Sci. 2022, 25, 173–180. [Google Scholar]
  23. Sarker, M.J.; Patwary, M.S.A.; Uddin, A.M.M.B.; Hasan, M.M.; Tanmay, M.H.; Kanungo, I.; Parvej, M.R. Macrobenthic Community Structure-An Approach to Assess Coastal Water Pollution in Bangladesh. Fish. Aquac. J. 2016, 7, 2. [Google Scholar] [CrossRef]
  24. Fauchald, K. The polychaete worms. In Definitions and Keys to the Orders, Families and Genera; Natural History Museum of Los Angeles County, Science Series; Natural History Museum of Los Angeles County: Los Angeles, CA, USA, 1977; Volume 28, pp. 1–188. [Google Scholar]
  25. Pillai, N.G.K. On some benthic polychaetes from Cochin Estuary. J. Mar. Biol. Assoc. India 2001, 43, 120–135. [Google Scholar]
  26. Al-Yamani, F.Y.; Skryabin, V.; Boltachova, N.; Revkov, N.K.; Makarov, M.; Grintsov, V.; Kolesnikova, E. Illustrated Atlas on the Zoobenthos of Kuwait; Kuwait Institute for Scientific Research: Safat, Kuwait, 2012. [Google Scholar]
  27. Gaston, G.R.; Nasci, J.C. Trophic structure of macrobenthic communities in the Calcasieu Estuary, Louisiana. Estuaries 1988, 11, 201. [Google Scholar] [CrossRef]
  28. Noman, M.; Mamunur, R.; Islam, M.S.; Hossain, M.B. Spatial and seasonal distribution of intertidal macrobenthos with their biomass and functional feeding guilds in the Naf River estuary, Bangladesh. J. Oceanol. Limnol. 2019, 37, 1010–1023. [Google Scholar] [CrossRef]
  29. Rahman, M.K.; Hossain, M.B.; Majumdar, P.R.; Mustafa, M.G.; Noman, M.A.; Albeshr, M.F.; Arai, T. Macrobenthic Assemblages, Distribution and Functional Guilds from a Freshwater-Dominated Tropical Estuary. Diversity 2022, 14, 473. [Google Scholar] [CrossRef]
  30. Clarke, K.R.; Warwick, R.M. Change in Marine Communities: An Approach to Statistical Analysis and Interpretation, 1st ed.; Plymouth Marine Laboratory: Plymouth, UK, 1994. [Google Scholar]
  31. Wang, R.; Yuan, L.; Zhang, L. Impacts of Spartina alterniflora invasion on the benthic communities of salt marshes in the Yangtze Estuary, China. Ecol. Eng. 2010, 36, 799–806. [Google Scholar] [CrossRef]
  32. Ullah, M.; Hossain, M.; Hossain, M.B.; Rahman, M. Intertidal variation of macrobenthos in a saltmarsh habitat, Noakhali coast, Bangladesh. Egypt. J. Aquat. Biol. Fish. 2020, 24, 377–390. [Google Scholar] [CrossRef]
  33. Reis, A.; Krull, M.; Carvalho, L.R.; Barros, F. Effects of tropical saltmarsh patches on the structure of benthic macrofaunal assemblages. Wetlands 2019, 39, 945–954. [Google Scholar] [CrossRef]
  34. Vinagre, C.; Cabral, H.N.; Caçador, I. Influence of halophytes and metal contamination on salt marsh macro-benthic communities. Estuar. Coast. Shelf Sci. 2008, 76, 715–722. [Google Scholar] [CrossRef]
  35. Kneib, R.T. Patterns of invertebrate distribution and abundance in the intertidal salt marsh: Causes and questions. Estuaries 1984, 7, 392–412. [Google Scholar] [CrossRef]
  36. Tang, M.; Kristensen, E. Associations between macrobenthos and invasive cordgrass, Spartina anglica, in the Danish Wadden Sea. Helgol. Mar. Res. 2010, 64, 321. [Google Scholar] [CrossRef]
  37. Scheffel, W.A.; Heck, K.L.; Johnson, M.W. Tropicalization of the northern Gulf of Mexico: Impacts of salt marsh transition to black mangrove dominance on faunal communities. Estuar. Coasts 2018, 41, 1193–1205. [Google Scholar] [CrossRef]
  38. Chakma, S.; Rahman, M.M.; Akter, M. Composition and Abundance of Benthic Macro-invertebrates in Freshwater Earthen Ponds of Noakhali District, Bangladesh. Am. J. Biosci. Bioeng. 2015, 5, 50–56. [Google Scholar] [CrossRef]
  39. Salgado, J.P.; Cabral, H.N.; Costa, M.J. Spatial and temporal distribution patterns of the macrozoobenthos assemblage in the salt marshes of Tejo estuary (Portugal). Hydrobiologia 2007, 587, 225–239. [Google Scholar] [CrossRef]
  40. Hampel, H.; Elliott, M.; Cattrijsse, A. Macrofaunal communities in the habitats of intertidal marshes along the salinity gradient of the Schelde estuary. Estuar. Coast. Shelf Sci. 2009, 84, 45–53. [Google Scholar] [CrossRef]
  41. Craft, C.; Sacco, J. Long-term succession of benthic infauna communities on constructed Spartina alterniflora marshes. Mar. Ecol. sProg. Ser. 2003, 257, 45–58. [Google Scholar] [CrossRef]
  42. Hammerschlag, N.; Morgan, A.B.; Serafy, J.E. Relative predation risk for fishes along a subtropical mangrove–seagrass ecotone. Mar. Ecol. Prog. Ser. 2010, 401, 259–267. [Google Scholar] [CrossRef]
  43. Alongi, D.M.; Sasekumar, A.; Chong, V.C.; Pfitzner, J.; Trott, L.A.; Tirendi, F.; Dixon, P.; Brunskill, G.J. Sediment accumulation and organic material flux in a managed mangrove ecosystem: Estimates of land–ocean-atmosphere exchange in peninsular Malaysia. Mar. Geol. 2004, 208, 383–402. [Google Scholar] [CrossRef]
  44. Castañeda-Moya, E.; Twilley, R.R.; Rivera-Monroy, V.H. Allocation of biomass and net primary productivity of mangrove forests along environmental gradients in the Florida Coastal Everglades, USA. For. Ecol. Manag. 2013, 307, 226–241. [Google Scholar] [CrossRef]
  45. Comeaux, R.S.; Allison, M.A.; Bianchi, T.S. Mangrove expansion in the Gulf of Mexico with climate change: Implications for wetland health and resistance to rising sea levels. Estuar. Coast. Shelf Sci. 2012, 96, 81–95. [Google Scholar] [CrossRef]
  46. Sarda, R.; Foreman, K.; Valiela, I. Macroinfauna of a southern New England salt marsh: Seasonal dynamics and production. Mar. Biol. 1995, 121, 431–445. [Google Scholar] [CrossRef]
  47. Xie, W.; Gao, S. Invasive Spartina alterniflora-induced factors affecting epibenthos distribution in coastal salt marsh, China. Acta Oceanol. Sin. 2013, 32, 81–88. [Google Scholar] [CrossRef]
  48. Muniz, P.; Pires, A.M.S. Trophic structure of polychaetes in the São Sebastião Channel (southeastern Brazil). Mar. Biol. 1999, 134, 517–528. [Google Scholar] [CrossRef]
  49. Ysebaert, T.; Meire, P.; Maes, D.; Buijs, J. The benthic macrofauna along the estuarine gradient of the Schelde estuary. Neth. J. Aquat. Ecol. 1993, 27, 327–341. [Google Scholar] [CrossRef]
  50. Hossain, M.B. Trophic functioning of macrobenthic fauna in a tropical acidified Bornean estuary (Southeast Asia). Int. J. Sed. Res. 2019, 34, 48–57. [Google Scholar] [CrossRef]
  51. Whitlatch, R.B. Animal-sediment relationships in intertidal marine benthic habitats: Some determinants of deposit-feeding species diversity. J. Exp. Mar. Biol. Ecol. 1981, 53, 31–45. [Google Scholar] [CrossRef]
  52. Rossi, F. Short-term response of deposit-feeders to an increase of the nutritive value of the sediment through seasons in an intertidal mudflat (Western Mediterranean, Italy). J. Exp. Mar. Biol. Ecol. 2003, 290, 1–17. [Google Scholar] [CrossRef]
  53. Pennings, S.C.; Bertness, M.D. Salt marsh communities. In Marine Community Ecology; Bertness, M.D., Gaines, S.D., Hay, M.E., Eds.; Sinauer Associates: Sunderland, MA, USA, 2001; pp. 313–351. 550p. [Google Scholar]
  54. Adam, P. Saltmarsh Ecology; Cambridge University Press: Cambridge, UK, 1990; 461p. [Google Scholar]
  55. Bortolus, A.; Schwindt, E.; Iribarne, O. Positive plant–animal interactions in the high marsh of an Argentinean coastal lagoon. Ecology 2002, 83, 733–742. [Google Scholar]
  56. Longley, W.L. Freshwater Inflows to Texas Bays and Estuaries: Ecological Relationships and Methods for Determination of Needs; Texas Parks and Wildlife Department: Austin, TX, USA; Texas Water Development Board: Austin, TX, USA, 1994; 386p.
  57. Russell, M.J.; Montagna, P.A.; Kalke, R.D. The effect of freshwater inflow on net ecosystem metabolism in Lavaca Bay, Texas. Estuar. Coast. Shelf Sci. 2006, 68, 231–244. [Google Scholar] [CrossRef]
  58. Xu, Y.J.; Wu, K. Seasonality and interannual variability of freshwater inflow to a large oligohaline estuary in the Northern Gulf of Mexico. Estuar. Coast. Shelf Sci. 2006, 68, 619–626. [Google Scholar] [CrossRef]
  59. Alongi, D.M. Ecology of tropical soft-bottom benthos: A review with emphasis on emerging concepts. Rev. Biol. Trop. 1989, 37, 85–100. [Google Scholar]
  60. Dittmann, S. Benthic fauna in tropical tidal flats–A comparative perspective. Wetl. Ecol. Manag. 2002, 10, 189–195. [Google Scholar] [CrossRef]
  61. Guzmán-Alvis, A.I.; Lattig, P.; Ruiz, J.A. Spatial and temporal characterization of soft bottom polychaetes in a shallow tropical bay (Colombian Caribbean). Bol. Investig. Mar. Costeras 2006, 35, 19–36. [Google Scholar] [CrossRef]
  62. Ysebaert, T.; Herman, P.M.J.; Meire, P.; Craeymeersch, J.; Verbeek, H.; Heip, C.H.R. Large-scale spatial patterns in estuaries: Estuarine macrobenthic communities in the Schelde estuary, NW Europe. Estuar. Coast. Shelf Sci. 2003, 57, 335–355. [Google Scholar] [CrossRef]
  63. Zhang, J.; Xu, F.; Liu, R. Community structure changes of macrobenthos in the South Yellow Sea. Chin. J. Oceanol. Limnol. 2012, 30, 248–255. [Google Scholar] [CrossRef]
  64. Xie, Z.; Zhang, J.; Cai, K.; Wu, D.; Wang, B. Temporal and spatial distribution of macrobenthos communities and their responses to environmental factors in Lake Taihu. Acta Ecol. Sin. 2016, 36, 16–22. [Google Scholar] [CrossRef]
  65. Beasley, C.R.; Fernandes, C.M.; Gomes, C.P.; Brito, B.A.; Santos, S.M.L.; Tagliaro, C.H. Molluscan diversity and abundance among coastal habitats of northern Brazil. Ecotropica 2005, 11, 9–20. [Google Scholar]
  66. First, M.R.; Hollibaugh, J.T. Environmental factors shaping microbial community structure in salt marsh sediments. Mar. Ecol. Prog. Ser. 2010, 399, 15–26. [Google Scholar] [CrossRef]
  67. Mannino, A.; Montagna, P.A. Small-scale spatial variation of macrobenthic community structure. Estuaries 1997, 20, 159–173. [Google Scholar] [CrossRef]
  68. David, V.; Sautour, B.; Chardy, P.; Leconte, M. Long-term changes of the zooplankton variability in a turbid environment: The Gironde estuary (France). Estuar. Coast. Shelf Sci. 2005, 64, 171–184. [Google Scholar] [CrossRef]
  69. Selleslagh, J.; Lobry, J.; N’Zigou, A.R.; Bachelet, G.; Blanchet, H.; Chaalali, A.; Boët, P. Seasonal succession of estuarine fish, decapods, macrozoobenthos and plankton: Physico-chemical and trophic influence. The Gironde estuary as a case study. Estuar. Coast. Shelf Sci. 2012, 112, 243–254. [Google Scholar] [CrossRef]
  70. Ysebaert, T.; Herman, P.M. Spatial and temporal variation in benthic macrofauna and relationships with environmental variables in an estuarine, intertidal soft-sediment environment. Mar. Ecol. Prog. Ser. 2002, 244, 105–124. [Google Scholar] [CrossRef]
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Figure 1. Location of the 3 stations (S1 = Caring Char, S2 = Noler Char, and S3 = Boyar Char) surveyed for saltmarsh along the Noakhali coast. The boundary lines between sub-areas are also shown.
Figure 1. Location of the 3 stations (S1 = Caring Char, S2 = Noler Char, and S3 = Boyar Char) surveyed for saltmarsh along the Noakhali coast. The boundary lines between sub-areas are also shown.
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Figure 2. Changes in percentage (%) composition of macrobenthos groups at different stations in study area.
Figure 2. Changes in percentage (%) composition of macrobenthos groups at different stations in study area.
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Figure 3. Seasonal and spatial variation of diversity indices at different stations during study period in Noakhali coast, Bangladesh. M = monsoon, Pm = post-monsoon, S = station.
Figure 3. Seasonal and spatial variation of diversity indices at different stations during study period in Noakhali coast, Bangladesh. M = monsoon, Pm = post-monsoon, S = station.
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Figure 4. nMDS ordination of macrofaunal samples (2D stress = 0.26), using paired-group linking of Bray-Curtis similarities based on square-root-transformed data.
Figure 4. nMDS ordination of macrofaunal samples (2D stress = 0.26), using paired-group linking of Bray-Curtis similarities based on square-root-transformed data.
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Figure 5. CCA ordination of abundance data of macrobenthos and environmental parameters in Noakhali coast, Bangladesh. Code of taxa: Ne-1 = Nereis sp. -1, Ne-2 = Nereis sp. -2, Nem = Nemanereis sp., Cal = Calanus sp., Lbn = Lumbrineris sp, Nep = Nephtys sp., Sig = Sigambra sp., Amp-1 = Ampelica sp. -1, Mc =Macrobrachium sp., Mys = Mysis sp.
Figure 5. CCA ordination of abundance data of macrobenthos and environmental parameters in Noakhali coast, Bangladesh. Code of taxa: Ne-1 = Nereis sp. -1, Ne-2 = Nereis sp. -2, Nem = Nemanereis sp., Cal = Calanus sp., Lbn = Lumbrineris sp, Nep = Nephtys sp., Sig = Sigambra sp., Amp-1 = Ampelica sp. -1, Mc =Macrobrachium sp., Mys = Mysis sp.
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Table
Table 1. Mean ± SD and ANOVA results for environmental variables in study stations along Noakhali coast. M = monsoon, Pm = post-monsoon, S = station.
Table 1. Mean ± SD and ANOVA results for environmental variables in study stations along Noakhali coast. M = monsoon, Pm = post-monsoon, S = station.
StationMS1MS2MS3PmS1PmS2PmS3SourcedfFp
Water temp (°C)31.17 ± 0.2930.13 ± 0.1530.03 ± 0.0628.25 ± 0.0924 ± 0.8725 ± 0.53Station262.720.004 *
Season1518.10.00005 **
Station: season2210.0001 **
Salinity (ppt)0 ± 00 ± 00 ± 08.09 ± 0.098.35 ± 0.157.13 ± 0.12Station284.750.003 *
Season1207.20.00001 **
Station: season284.750.003 *
Water pH8.1 ± 0.18.13 ± 0.127.06 ± 0.068.91 ± 0.128.33 ± 0.28.36 ± 0.32Station234.640.007 *
Season194.250.004 *
Station: season216.290.0004 **
Soil pH6.6 ± 0.16.73 ± 0.155.83 ± 0.066.93 ± 0.066.97 ± 0.066.77 ± 0.15Station247.450.005 *
Season1101.30.003 *
Station: season219.350.0001 **
DO (mg/L)7.33 ± 0.157.23 ± 0.127.67 ± 0.155.9 ± 0.288.26 ± 0.238.1 ± 0.1Station285.430.003 *
Season10.020.89
Station: season272.780.002 *
Alkalinity (ppm)73.67 ± 3.7973.67 ± 8.3376.67 ± 11.68162 ± 43.27113 ± 13.53126 ± 26.15Station21.90.19
Season131.760.0001 **
Station: season22.040.17
Hardness (µS)153.3 ± 30.55310 ± 26.46231 ± 46.181473.3 ± 25.171470 ± 17.321486.6 ± 15.28Station210.850.002 *
Season184870.00001 **
Station: season211.830.001 *
Significant differences are indicated with the asterisk (*). * indicates significant at 5% level; ** indicates significant at 1% level.
Table
Table 2. Abundance of macrobenthic fauna in study stations along the Noakhali coast. SD = standard deviation; taxonomic group: SSDF: sub-surface deposit feeder; OMN: omnivorous; FF: filter feeder; SDF: surface deposit feeder; CAR: carnivorous.
Table 2. Abundance of macrobenthic fauna in study stations along the Noakhali coast. SD = standard deviation; taxonomic group: SSDF: sub-surface deposit feeder; OMN: omnivorous; FF: filter feeder; SDF: surface deposit feeder; CAR: carnivorous.
Benthic GenusTrophic GroupMean ± SDTotal%
Macrobrachium sp.OMN644.5 ± 917.43386716.29
Nereis sp. 1SSDF455.67 ± 223.69273411.51
Mysis sp.OMN427.67 ± 413.85256610.81
Nephtys sp.SSDF394.67 ± 400.5423689.97
Lumbrineris sp.SSDF333.5 ± 357.9220018.43
Nereis sp. 2SSDF246 ± 284.4814766.22
Sigambra sp.OMN183.5 ± 341.1811014.64
Nemanereis sp.SSDF183.33 ± 136.3011004.63
Ampelisca sp. -1FF144.5 ± 132.968673.65
Calanus sp.CAR138.83 ± 227.558333.51
Chironomus sp.SDF100 ± 183.946002.53
Ampelisca sp. -2FF94.5 ± 121.915672.39
Apanthura sp.CAR83.33 ± 93.715002.11
Tellina sp.FF83.16 ± 124.214992.10
Capitella sp.SSDF77.83 ± 27.274671.97
Ephemera sp.SDF66.83 ± 81.814011.69
Melinna sp.SDF55.5 ± 120.513331.40
Apseudes sp.SDF44.5 ± 72.122671.12
Macrochlamys sp.OMN38.83 ± 53.332330.98
Otolithoides sp.OMN38.83 ± 61.062330.98
Monhysterida sp.SSDF22.17 ± 40.351330.56
Paraclepsis sp.CAR22.17 ± 40.351330.56
Paraprionospio sp.SSDF5.5 ± 13.47330.14
Gammarus sp.OMN5.5 ± 13.47330.14
Bellamya sp.SDF5.5 ± 13.47330.14
Polymesda sp.FF5.5 ± 13.47330.14
Glycera sp.SSDF5.5 ± 13.47330.14
Eteone sp.CAR5.5 ± 13.47330.14
Table
Table 3. Seasonal variation of macrobenthic taxonomic groups (inds./m2) for each season in Noakhali coast.
Table 3. Seasonal variation of macrobenthic taxonomic groups (inds./m2) for each season in Noakhali coast.
Macrobenthos GroupMonsoonPost-MonsoonTotalMean ± SDContrib. (%)
inds./m2%inds./m2%
Polychaeta731164.84436835.0411,6795839.5 ± 2081.0249.19
Crustacea350031.04626650.2697664883 ± 1955.8641.13
Insecta0010018.031001500.5 ± 707.814.22
Bivalvia4323.831000.8532266 ± 234.762.24
Gastropoda330.292331.87266133 ± 111.421.12
Fish larvae002331.87233116.5 ± 104.760.98
Oligochaeta001331.0713366.5 ± 34.050.56
Clitellata001331.0713366.5 ± 34.050.56
Total11,276 12,467 23,743 100
inds. = individual, SD = standard deviation, Contrib. = contribution.
Table
Table 4. Seasonal abundance of trophic group of macrobenthos in study stations.
Table 4. Seasonal abundance of trophic group of macrobenthos in study stations.
Trophic GroupNumber of SpeciesSeason% Contri.p
MonsoonPost-Monsoon
SSDF91033.33 ± 291.271733 ± 1018.4243.570.39
OMN71959 ± 893.871489.33 ± 370.9234.950.46
FF4555.33 ± 77.88100 ± 50.958.280.02 *
SDF50 ± 0499.67 ± 164.246.880.54
CAR4211 ± 128.38333.67 ± 150.476.310.02 *
SSDF: sub-surface deposit feeder; OMN: omnivorous; FF: filter feeder; SDF: surface deposit feeder; CAR: carnivorous; Contri.: contribution. Significant differences are marked with the asterisk (*). * indicates significant at 5% level.
Table
Table 5. Average biological indices and two-way ANOVA for macrobenthos between seasons and stations in Noakhali coast.
Table 5. Average biological indices and two-way ANOVA for macrobenthos between seasons and stations in Noakhali coast.
Biological IndicesMonsoonPost-MonsoonSourcedfFp
Abundance3758.67 ± 2152.074155.67 ± 840.55Station23.160.08
Season11.7860.21
Station: season22.3780.13
Species richness13.33 ± 0.5817 ± 0Station21.9830.18
Season11.0850.32
Station: season20.62710.55
Diversity index2.31 ± 0.052.20 ± 0.36Station23.4270.07
Season12.1680.17
Station: season21.7920.21
Evenness index0.75 ± 0.0050.553 ± 0.175Station24.7510.03 *
Season115.710.002 **
Station: season25.6470.02 *
Significant relations are shown in bold and indicated with the asterisk (*). * p < 0.05; ** p < 0.01.
Table
Table 6. PERMANOVA (permutational ANOVA) result for macrobenthic fauna between stations and seasons in Noakhali coast.
Table 6. PERMANOVA (permutational ANOVA) result for macrobenthic fauna between stations and seasons in Noakhali coast.
SourceSSdfMSFp
Station0.43347820.216742.04790.01 *
Season0.53610.5365.06460.0001 **
Interaction0.40782220.203911.92670.02 *
Residual1.26999120.10583
Total2.647317
SS = sum of square, MS = mean square, df = degree of freedom. * p < 0.05; ** p < 0.01.
Table
Table 7. SIMPER analysis for macrobenthos between stations and seasons in Noakhali coast.
Table 7. SIMPER analysis for macrobenthos between stations and seasons in Noakhali coast.
StationSeason
SpeciesS1S2S3Av. Dissim.Contrib. %SpeciesMPMAv. Dissim.Contrib. %
Mean abun.Mean abun.
Macrobrachium sp.4.335.542.153.746.80Macrobrachium sp.4.143.873.576.11
Nereis sp. 22.233.606.393.586.51Melinna sp.3.770.003.526.02
Mysis sp.0.884.993.313.386.15Nereis sp. -23.944.213.155.39
Lumbrineris sp.2.492.695.383.285.97Calanus sp.0.003.343.125.33
Capitella sp.2.121.544.193.185.78Capitella sp.2.982.253.085.27
Melinna sp.1.072.941.652.654.81Lumbrineris sp.3.893.153.075.25
Nemaneris sp.4.582.695.852.564.66Mysis sp.2.793.322.995.12
Calanus sp.1.980.003.032.564.65Minuspio sp.2.590.002.694.61
Ampelisca sp. -11.720.772.692.344.26Chironomus sp.0.002.582.594.44
Minuspio sp.2.721.170.002.344.26Apseudes sp.2.740.002.544.35
abun. = abundance, Av. Dissim. = average dissimilarity, Contrib. = contributed, S1 = Caring Char, S2 = Noler Char, S3 = Boyar Char, M = monsoon, Pm = post-monsoon.
Table
Table 8. Spearman’s rank correlations between macrobenthic community and environmental variables at the study stations. S = species richness; A = abundance; H′ = diversity index; e = evenness index.
Table 8. Spearman’s rank correlations between macrobenthic community and environmental variables at the study stations. S = species richness; A = abundance; H′ = diversity index; e = evenness index.
Environmental VariablesAH′ES
Water temperature (°C)−0.6380.0290.943 **−0.58
Salinity (ppt)0.277 **−0.334−0.6980.216
Water pH−0.058−0.086−0.314−0.058
Soil pH−0.029−0.486−0.543−0.058
DO (mg/L)0.579−0.143−0.7710.579 *
Alkalinity (ppm)0.441 *0.289−0.579−0.471 *
Hardness (µS)0.3190.2−0.60.319
Significant relations are shown in bold and indicated with the asterisk (*, **). * p < 0.05, ** p < 0.001.
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Mely, S.S.; Hossain, M.B.; Rahman, M.; Albeshr, M.F.; Arai, T. Changes of Macrobenthic Diversity and Functional Groups in Saltmarsh Habitat under Different Seasons and Climatic Variables from a Subtropical Coast. Sustainability 2023, 15, 7075. https://doi.org/10.3390/su15097075

AMA Style

Mely SS, Hossain MB, Rahman M, Albeshr MF, Arai T. Changes of Macrobenthic Diversity and Functional Groups in Saltmarsh Habitat under Different Seasons and Climatic Variables from a Subtropical Coast. Sustainability. 2023; 15(9):7075. https://doi.org/10.3390/su15097075

Chicago/Turabian Style

Mely, Shayla Sultana, Mohammad Belal Hossain, Mahabubur Rahman, Mohammed Fahad Albeshr, and Takaomi Arai. 2023. "Changes of Macrobenthic Diversity and Functional Groups in Saltmarsh Habitat under Different Seasons and Climatic Variables from a Subtropical Coast" Sustainability 15, no. 9: 7075. https://doi.org/10.3390/su15097075

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