Spatial and Temporal Scales of Variability of Mollusks in a Strongly Threatened Mediterranean Coastal Lagoon (Mar Menor, Murcia, Spain)

Abstract

Coastal lagoons are dynamic and highly productive systems that offer a remarkable number of ecological services and benefits for humans. However, our understanding of them is still far from adequate. The Mar Menor lagoon is an ecosystem subject to anthropogenic pressures that have worsened in recent years. These pressures include coastal works, such as dredging and sand dumping, as well as changes in agricultural regimes that have induced a process of eutrophication that set off alarms after the eutrophic crisis that occurred in 2016. Benthic organisms, and in particular mollusks, are very sensitive to environmental variations, often serving as indicators of these changes. This work analyzes the malacofauna of the Mar Menor from 1981 to 2019 in the context of the environmental changes that have occurred in it during these years. Eighty-six species have been recorded throughout our study period, and species richness, abundances, local assemblage structures, along with changes in the main environmental parameters of the water column (salinity, temperature, and chlorophyll a concentration) have been used to explain the composition of the communities of the main lagoon habitats and to detect their spatial and temporal variations. With the information provided, the complete inventory of mollusks reported in the lagoon has been updated to 126 species. The results indicate that, during these almost 40 years, the total number of species has remained relatively constant, but with a high percentage of occasional and very rare species, along with a high rate of change from one species to another over time, accompanied by variations in the abundance and dominance of some species compared to others depending on the environmental conditions and pressures that the lagoon has undergone. The high spatial and temporal heterogeneity detected is determined by the restricted connectivity with the open sea, the diversity of environments and habitats, and the changes in environmental conditions due to human actions.

1. Introduction

Coastal lagoons are transitional ecosystems between land and sea, relatively isolated from the latter by a barrier or similar land features, sometimes with one or more channels through which a more or less restricted exchange of water and organisms takes place [1]. Some remarkable characteristics of these are their significant variability and heterogeneity in a reduced space, with strong physical, chemical, and biological gradients that are driven by external forces and biological activity [2,3]. These characteristics are responsible for coastal lagoons being among the most productive and valuable ecosystems in the world [4,5,6,7]. The properties mentioned also mean that coastal lagoons harbor high biodiversity [1,8,9] that conforms a reservoir of singular populations adapted to a wide, though specific to each lagoon, range of environmental conditions. However, these systems are highly pressured by human activities, and we are still far from understanding their integrated functioning and from accurately reflecting it in their management [1].

Benthic macrofauna plays an important role in coastal ecosystems and, in particular, in coastal lagoon processes, such as nutrient cycling, organic matter decomposition, sediment oxygenation, or oxygen balances in general [10]. This important role is related to the spatiotemporal patterns of the fauna, which are influenced by the degree of connectivity with the open sea that gives rise to randomness in the colonization processes of the different species and a high spatiotemporal variability [1]. Some studies carried out in the Venice lagoon indicate that approximately 40% of the macrobenthic fauna changes from one year to the next [11], and a similar percentage has been observed in the ichthyofauna of the Mar Menor [1,12]. Furthermore, information on the spatial and temporal patterns of this benthic fauna community is crucial to detect and refine predictions about potential environmental changes due to natural, anthropogenic forces, or even global climate change, and to seek appropriate management measures [13].

Mollusks are one of the major components and one of the most used groups in marine benthic fauna studies, as they are associated with different types of habitats such as seagrass meadows, soft bottoms, or rocky bottoms [14]. They are sensitive to changes in environmental conditions, providing a large amount of information on the properties of sediments, oxygen levels, salinity, and energy of the water, among other ecological factors. Their abundance and diversity over time can be used to monitor disturbances, acting as relevant indicators of environmental impacts [15]. In addition, they have great paleoecological value, and mollusk shells are useful for determining ancient coastal positions, paleoenvironments, and paleoclimates linked to atmospheric and oceanographic changes [16,17].

Previous studies carried out in different Mediterranean coastal lagoons showed how the knowledge of mollusks can help us in detecting and understanding ecosystem changes associated with the historical variation of environmental parameters [18,19,20,21,22,23,24,25,26,27,28,29] and even those effects derived from the own anthropic actions [30,31,32,33,34,35,36]. On the other hand, some of these Mediterranean lagoons support intensive exploitations of mollusks, such as Ruditapes philippinarum (A. Adams & Reeve, 1850) in Venice [37] or oysters in Thau in France [38] or attempts to do it in the Mar Menor in Spain [39]. Some of these practices have also facilitated the introduction of non-indigenous species that typically compete with the autochthonous ones [40,41,42,43]. In the Mar Menor lagoon, aquaculture experiences using Ostrea edulis Linnaeus, 1758, coincided with a massive proliferation of this species during the 1980s [39].

However, despite this number of publications, along with the important role that mollusks play in marine ecosystems as detritivores, filter feeders and predators, and the economic interest of these species, not enough information is available about them in coastal lagoons and about the sense of their spatiotemporal variability in these ecosystems. Moreover, most of the studies carried out in these environments focus on the most conspicuous species, such as mussels or oysters, and few of them address the entire mollusk community or its role in the lagoon functioning. Furthermore, it is important to note that the knowledge of the patterns and scales of variability in biological assemblages is essential when designing sampling strategies in environmental impact assessments, in which we must differentiate the changes caused by human activities and sources of natural variability. Therefore, this knowledge is crucial when implementing policies or management actions to coastal lagoons and for defining reference conditions to compare the evolution of their ecological statuses over time [44,45,46].

In the present work we have compiled the existing information, and we have provided our own data on the species of mollusks present in the coastal lagoon of the Mar Menor and their evolution in the 1981–2019 period, relating their presence and abundances to the spatiotemporal variability and the main environmental changes that the lagoon has experienced and is currently undergoing.

2. Materials and Methods

2.1. The Mar Menor Lagoon

The Mar Menor, with a surface area of 136.1 km² and an average depth of 4.4 m, is one of the largest hypersaline lagoons in the Mediterranean (Figure 1) [47,48]. The lagoon is isolated from the Mediterranean Sea by a sandbar (La Manga), which is crossed by three channels or channel complexes. Following the enlargement of El Estacio channel in the 1970s, the salinity of its water dropped from values ranging between 48.5 and 53.4 [49] to values for the study period between 31.13 and 54.59, with an average value of 43.38. Temperatures also became milder and, for the study period ranged, at local scale, from a minimum of 9.1 °C in winter to a maximum of 35.5 °C in summer, with an average value for the entire lagoon of 20.67 °C [50].

Lagoon substrates are predominantly muddy and sandy, with some areas of natural rocky bottoms around the five volcanic islands and islets that are within it. Muddy bottoms, which are mainly in the entire central area of the lagoon, are covered by a dense mixed meadow of the phanerogam Cymodocea nodosa (Ucria) Asch. and the algae Caulerpa prolifera (Forsskål) J.V. Lamouroux, dominated by the latter. Sandy bottoms (with sand contents of up to 89%), in which scattered patches of C. nodosa grow, are located on the margins of the basin and in the small bays that surround the islands [51,52,53]. Natural rocky bottoms and rock blocks of artificial hard substrata (harbor jetties and dykes designed to retain the sediment in artificial beaches) are covered by photophilous algal assemblages that exhibit vertical zonation patterns [54] (Figure 1).

The coastal lagoon of the Mar Menor has undergone significant changes as a result of various anthropic actions. For centuries, since the Phoenician and Roman times, it had been receiving massive inflows of heavy metals from mining activity in the nearby mountains, and, although these discharges ceased at the end of the 1950s, their accumulations are still detected in the lagoon sediments [55]. More recently, with the massive influx of tourism in the 1960s, coastal actions began to occur that involved an increase in urbanization, the dredging of communication channels with the Mediterranean Sea, coastal works in general, or the creation of artificial beaches. The consequent sand dredging and dumping of this last action also involved the rapid expansion of the C. prolifera meadows to shallow areas, which increased the concentration of organic matter, the retention of silts and clays in the sediments, and the generation of hypoxia in the surface layer [53,56]. More recently, changes in agricultural activity in the lagoon’s drainage basin have led to a massive influx of nutrients and irrigation water, resulting in a process of eutrophication in the lagoon [57]. This process, together with the occurrence of torrential rains and a rise in the water table, has led to a reduction in salinity and an increase in water turbidity, as well as the occurrence of an episode of stratification in the water column and hypoxia in the deep layers near the bottom following a DANA (isolated high-level depression) event.

2.2. Data Sets and Sampling Methods

This work has compiled data from various campaigns and projects carried out in different localities of the Mar Menor from 1981 to 2019 (Figure 1). In total, five data sets corresponding to the periods 1981–1988 (grouped in the analyses as the 1980s), 2002, 2006, 2007 (grouped in the analyses as 2002–2007), 2017, 2018, and 2019 are included. The last three years have been grouped into a single period solely for comparison of the main descriptors, such as species richness and species shared with the other periods. However, they have been kept separate in most analyses to assess the differences among them, as they correspond to the three different phases during the eutrophic crisis process suffered by the Mar Menor (rupture, recovery and the effects of a DANA), thereby enabling differentiation of the recent dynamics of rapid changes in the system during this process. All data sets include seasonal or monthly data for environmental and biological variables.

A total of 611 samples have been processed throughout the entire study period, 548 of which correspond to the communities common to all periods studied and used for temporal comparisons. The design of the sampling in each period has depended on the projects and objectives in which they were framed, but sampling methods have remained uniform throughout the study periods. Soft substrates in deep areas (2–6 m deep) were sampled with a stainless steel Van Veen grab [58,59] which has a surface area of 20 × 20 cm² and a volume of approximately 2400 cm³, operated from a boat. Shallow sandy or sandy-muddy bottoms (<2 m deep) were sampled by snorkeling with a shovel covering the same surface and approximately volume (20 × 20 × 6 cm³), while hard bottoms by surface scraping in a quadrat of 20 × 20 cm². The samples were introduced into nytal bags with a mesh size of 500 µm, sieved, and taken to the laboratory where, after an in vivo pre-threshing of the large taxonomic groups and the most conspicuous individuals, they were conserved in 70% ethanol for the subsequent analysis in greater detail, the identification of species, and the counting of individuals. Thanatocenosis, isolated bivalve valves, or highly fragmented shells were not considered. In all periods, the team included the same main researchers and a minimum of three researchers involved in sampling and sample processing. Thus, the investigator effect would be within the random variability factors (in the error term). The sampling locations and replication levels varied depending on the objectives of the projects considered, although there are numerous locations corresponding to the dominant communities that coincide in all periods. Likewise, all periods have been sampled in all seasons of the year, although with varying regularity. For all this, in the analyses, seasonality has not been considered as a factor, and the seasonal or monthly samples have been considered random temporal replications of the “period” factor. Similarly, the spatial factor has been referred to as a zone scale (approximately 26 km²), so that it includes a relatively high number of sampling stations and samples, which are thus considered random spatial replicas of the zone and period in question. In this way, their spatial and temporal variability has been incorporated into the levels of each factor, avoiding pseudoreplication sensu Hulbert [60]. Despite the lack of balance in the sampling design, which is to be expected when dealing with diverse projects, the total number of samples analyzed is substantial. Analysis of variance is resilient to deviations from the underlying assumptions, particularly when the design encompasses a substantial number of samples or treatments [61], which is also achieved by using permutational analysis (PERMANOVA) instead of ANOVA. As permutations are used, the test requires no specific assumption concerning the number of variables or the nature of their individual distributions or correlations [62,63].

Since 1981, the different projects considered included the monitoring of the main hydrographic and trophic parameters of the water column (salinity, temperature, and concentration of chlorophyll a). To characterize the environmental conditions of the Mar Menor in the different periods of the study, a matrix has been constructed with the mean values and standard deviations of these parameters in each month and in each of the five zones into which we have subdivided the lagoon (Figure 1). The methodologies for taking samples and analyzing environmental parameters can be found in Pérez-Ruzafa et al. [57,64]. In the 1980s, according to the nomenclature of Pérès and Picard, Augier, and Meinesz et al. [65,66,67], based on the type of substrate, vertical zonation, and exposure to waves and sunlight, thirteen biocenoses were differentiated: supralittoral rock, emerged sands, upper and lower mid-littoral rock, photophilous community of the upper infralittoral rock in calm mode with dominance of Cystoseira, photophilous community of the infralittoral rock in calm mode without dominance of fucal algae, nitrophilic community on rock, infralittoral sciaphilous biocenoses with biological concretization, communities of sandy bottoms, Cymodocea nodosa meadows, Caulerpa prolifera and mixed Cymodocea nodosa-Caulerpa prolifera meadows, Ruppia cirrhosa (Petagna) Grande meadows, compacted red clays of terrigenous origin, and Chaetomorpha linum (O.F.Müller) Kützing floating mats (Figure 1). On subsequent sampling campaigns, the sampled biocenoses have varied depending on the objectives of the projects developed and according to their relative importance in each case. For this work, we have homogenized and updated the nomenclature of these biocenoses (Table 1) and have included two of them: muddy bottoms with Caulerpa prolifera meadows or without macrophyte vegetation, which acquired special importance after the loss of vegetation caused by the decrease in the compensation depth in the lagoon during the eutrophic crisis of 2016.

The localities (El Ciervo island: IC, El Estacio channel: ES, La Ribera: LR, Los Urrutias: LU, and lagoon basin: LB) and representative habitats (WI-IR, DOCKS, CY, CACY, SAND, and CA) with data available for all periods (except MUD and CA in the 1980s, CACY in 2017 and 2018, and DOCKS in the 2002–2007 period) were selected for statistical analyses and comparisons of mollusk assemblages and their spatial and temporal variability (Table 1). For spatial analyses, samples from the same habitat have been grouped into five zones that constitute the main lagoonal functional areas according to the combination of confinement and marine or watershed influence [64] (Figure 1).

The taxonomic determinations have been performed and/or reviewed in this work and carried out at the species level by means of a binocular magnifying glass, Olympus SZX7 following Nordsieck [68], Templado [69], Murillo and Talavera [70], Ponder [71], Riedl [72], Marín and Ros [73], Bellido [74], Pérez-Ruzafa [51], Murillo [75], Rueda et al. [14], and Gofas et al. [76]. For the update of the taxonomic nomenclature and classification and for the ecological traits, we have followed the World Register of Marine Species website (WoRMS Editorial Board [77] and the Marine Species Traits editorial board [78].

2.3. Data Analysis

To characterize the spatial variability and the temporal evolution of the environmental conditions in the Mar Menor in the study period, a two-way PERMANOVA (permutational multivariate analysis of variance) [79,80] was conducted on the matrix of Euclidean distances, considering two factors, period, with five levels (1980s, 2002–2007, 2017, 2018, and 2019), and zone with five levels (1 to 5), and its corresponding pairwise comparison. The variables responsible for these differences have been identified using SIMPER [80]. The graphical representation of the groupings of the different periods according to their environmental conditions has been carried out by means of a cluster analysis using the group average technique and by the representation of the spatiotemporal variability of the different study areas, using a principal component analysis (PCA) performed on the matrix of monthly means and standard deviations of each zone in each analyzed period. All the analyses have been performed using PRIMER software version 7.0 [80], transforming the data by square root and standardizing the variables beforehand.

Mollusk assemblage composition and structure of the main habitats were specified according to their species composition and abundance (standardized to individuals/m²), species richness, Shannon diversity index expressed in bits/individual, and Pielou evenness [81]. For each species, we have also estimated its relative dominance (% D) and the frequency of occurrence (F) in each habitat and period (Supplementary Material Table S1).

To assess the differences in the assemblages between the different habitats, a first analysis of the 10 habitats sampled in the 1980s period was carried out, using both presence-absence data (using the Jaccard index) to assess the differences due to characteristic species and abundance data (using the Bray-Curtis index) to assess differences due to relative dominance of species. Cluster analyses on both resemblance matrices were performed using the flexible beta method (with beta values between −1 and 1 and 200 increments) to optimize the correlation between the resulting cophenetic matrix and the resemblance matrix [80]. To test whether the observed differences are significant, a permutational multivariate analysis of variance (PERMANOVA) [79] was carried out on the Bray-Curtis distance matrix calculated on log (x + 1) transformed abundance data.

Site ordination was carried out by detrended correspondence analysis (DCA) on the log-transformed (log (x + 1)) abundance data of each species using CANOCO 5 [82,83].

Spatial and temporal variations in the structure of mollusk assemblages throughout the different periods studied were assessed based on the seven most representative communities of the different habitats of the lagoon identified in the previous analysis (CACY, CY, CA, WI-IR, DOCKS, MUD, and SAND). For this purpose, several analyses were carried out considering three factors, period (with five levels: 1980s, 2002–2007, 2017, 2018, and 2019), habitat (with 7 levels: CA, CACY, CY, MUD, WI-IR, DOCKS, and SAND) and zone (with five levels: 1 to 5). To represent the distribution of samples of the different habitats and periods according to their species composition and abundance, a non-metric multidimensional scaling (NMDS) was used. The species responsible for the observed differences were identified using SIMPER [80]. To test for significant differences between the factors studied (habitat, zone, and period) a PERMANOVA analysis and a paired t-test were performed.

In the same manner, to determine the significant structural differences between mollusk assemblages in abundance, species richness, and Shannon diversity, a permutational multivariate analysis of variance (PERMANOVA) was carried out considering the same three factors, period (with five levels: 1980s, 2002–2007, 2017, 2018, and 2019), habitat (with 7 levels: CA, CACY, CY, MUD, WI-IR, DOCKS, and SAND) and zone (with five levels: 1 to 5), along with its corresponding pairwise comparison to identify the levels responsible for the observed differences. By using permutations, this non-parametric test requires no specific assumption concerning the nature of the distributions or correlations of the variables and accommodates unbalanced and/or asymmetrical designs [79]. All analyses were performed using the statistical software PRIMER version 7.0 [80] and R v.4.3.3 [84], using “Vegan” and “BiodiversityR” packages. Similarity matrices were based on the Bray-Curtis similarity coefficient, using a random subset of 9999 permutations and the Monte Carlo tests. Significant terms were investigated using a posteriori pairwise comparisons with the PERMANOVA t-statistic and 9999 permutations. Values were log (x + 1) transformed before the analyses.

In all PERMANOVA analyses, the percentage of variance explained by various sources of variation was estimated according to Anderson et al. [85] from the ‘Components of variation’ (ECV), considering that these can be interpreted geometrically as measures of variability of a partition based on the similarity or dissimilarity measured with the index used and can be used for comparing the relative importance of different terms in the model towards explaining overall variation [86].

3. Results

3.1. Environmental Conditions That Characterize the Study Period

Throughout the study period (1981–2019), the temperature has oscillated locally between 9.1 °C and 35.5 °C, with an average value for the lagoon of 20.67 ± 6.1 °C. In general, the temporal pattern is very regular with minima in December to February and maxima in August. For its part, salinity, although it also tends to follow a seasonal regime, nevertheless shows a much more irregular pattern, both spatially (depending on the location of freshwater runoffs, watercourses, and the influence of Mediterranean water inputs through the inlets) and temporally (depending mainly on the time of year and magnitude of freshwater and Mediterranean water inputs as well as rainy events). The average salinity value of the lagoon in the study period was 43.38 ± 0.03, the minimum values (22.86) being found locally in 2008 at the mouths of the watercourses in the torrential rainy season, while the maximum values of 54.59 occurred in the Spring of 2011 in the southeastern area of the lagoon. It is noteworthy that there was a significant decrease in the average annual salinity of the lagoon after the successive torrential rains that occurred in September 2019, lowering the average for that year to 41.59 ± 0.11 (Figure 2).

The concentration of chlorophyll a has oscillated locally between values of almost 0 and 107.35 µg/L in the peak that occurred after the torrential rains of September 2019 at zones Z2 and Z5 in front of the mouths of the Albujón and Carrasquilla wadis, respectively. The average value for the lagoon in the study period is 2.76 ± 0.08 µg/L, although there has been a very significant change in the trophic status of the ecosystem throughout the entire period. In 1981, the average value was 0.59 ± 0.07 µg/L. Since the 1990s, the change in the agricultural regime in the drainage basin, from rainfed to irrigated, meant the continuous entry of brackish waters loaded with nutrients. However, the ecosystem maintained a low chlorophyll a concentration for several years, thanks to the top-down control of the trophic network [57,87] exerted in the water column mainly by ichthyoplankton and jellyfish, which proliferated since those years [87,88,89]. These mechanisms kept the average chlorophyll a concentration below a maximum of 1.66 ± 0.10 µg/L, which was reached in 2010.

Since 2016, the ecosystem underwent a drastic change in its trophic status with a very significant increase in chlorophyll a, reaching a mean of 11.51 ± 0.40 µg/L in the mentioned year and 6.31 ± 0.23 µg/L in 2017, with the consequent loss of transparency in the water column. The decrease in nutrient discharges, due to some restrictive measures taken by the administration, allowed a recovery in 2018, reducing the mean annual concentration to 1.74 ± 0.06 µg/L. Since then, the ecosystem has undergone fluctuations depending on the balance of inputs and the functioning of the self-regulation systems of the trophic web, reaching again 6.65 ± 0.64 µg/L again in 2019.

The PERMANOVA results show significant differences in the environmental conditions between the periods in which the malacofauna has been studied (p = 0.0001) but not between zones or their interaction (Table 2). Inter-period variability explains only 36.65% of the dissimilarity between environmental conditions, while spatial factors at the area scale have no contribution. The unexplained 63.35% could be attributed to seasonal variability and to spatiotemporal variability at smaller scales. The pairwise analyses show significant differences between all pairs of periods, except 1980s vs. 2018 and 2019, and between 2017 and 2019. The SIMPER analysis shows that the main difference between the periods before the 2016 eutrophic crisis and between those and 2018 is due, in more than 89%, to temperature. In all other comparisons between periods, chlorophyll a concentration takes on special relevance, accounting for between 28 and 71.9% (Table 3). The fact that 2018 does not show significant differences with the 1980s, and that the differences with 2002–2007 are mainly due to the average temperature, suggests that trophic conditions recovered that year after the reduction in the input of brackish water and nutrients since mid-2017. However, conditions worsened slightly again in 2019, especially after the torrential rains in September of that year.

The cluster analysis, carried out from the matrix of distances between periods calculated by PERMANOVA, shows a clear separation of the years 2019 and 2017, characterized by high concentrations of chlorophyll a, and the other periods studied (Figure 3).

On the other hand, the first two axes of the PCA carried out on the matrix of environmental variables explain 66.9% of the variance of the data. The first axis, which explains 49.8%, is characterized by the opposite gradients of salinity and chlorophyll a concentration. In the positive part are the samples with higher average salinity and lower chlorophyll concentration, while in the negative part those with the highest values of chlorophyll a and low salinity. This means that the five zones of the Mar Menor in September 2019, after the worst torrential rains in recent years, are at the negative extreme. The most affected areas are precisely those located in the mouth of the main watercourses (Z2 and Z5). Meanwhile, axis 2, which explains 17.1% of the variance, is determined by temperature, establishing a seasonal gradient, from the coldest months on the positive side to the warmer months on the negative (Figure 4).

3.2. Composition and Structure of Lagoon Mollusk Assemblages

In the last 40 years, a total of 126 different mollusk species belonging to the classes Gastropoda (33 families; 76 species), Bivalvia (20 families; 45 species), Polyplacophora (2 families; 3 species), Scaphopoda (1 family; 1 species), and Cephalopoda (1 family; 1 species) have been collected or identified in the Mar Menor lagoon, including 40 species previously registered in other works [51,70,90] (Table 4). The last 40 species that have been cited in the lagoon but did not appear in the quantitative samples of the present work, were mostly observed in the inlets and had not fully colonized the lagoon. While others, such as Pinna nobilis Linnaeus, 1758, or Octopus vulgaris Cuvier, 1797, because of their size, mobility, or because they are very scarce, do not usually appear in samples of 400 cm².

In the three major periods covered, 1980s, 2002–2007, and 2017–2019, richness has remained relatively constant at around 49 species, albeit with changes in the species present at each time or in their relative abundances.

For the entire study period, gastropods dominated in number of species (54.65%), followed by bivalves representing 43.02% of the species and, with a much lower value, by polyplacophores (2.33% of species). Additionally, for the entire period, families Trochidae (11 species), Nassaridae (8 species) and Rissoidae (7 species) from Gastropoda, as well as Veneridae (7 species) and Mytilidae (5 species) from Bivalvia, were the most abundant in terms of number of species.

Characterization of Habitats and Assemblages

The results of the cluster analysis performed on the 10 habitats sampled in the 1980s period, using both presence-absence data (Jaccard index) and abundance data (Bray-Curtis index), so as the samples ordination carried out by detrended correspondence analysis (DCA) show a complex pattern with some assemblages more differentiated than others (Figure 5 and Figure 6). The results evidenced variations in species composition and relative abundances.

The PERMANOVA analysis performed on abundance data (using the Bray-Curtis index) shows significant differences between most habitats (p < 0.05) but the pairwise comparisons showed that the most differentiated biocenoses is the mixed Cymodocea-Caulerpa meadow, which shows significant differences with the rest of the habitats. Infralittoral rocky habitats, both well illuminated (except for nitrophilic assemblages) and poorly illuminated, do not show significant differences between them, but both differentiate from midlittoral rocky assemblages (p = 0.0095 and p = 0.0367, respectively). Cymodocea nodosa meadows on sand and Ruppia cirrhosa do not differentiate significantly from rocky bottoms or just marginally from PI-IR (p = 0.077) and from WI-IR (p = 0.059), respectively. Overall, habitat explains only 43.7% of the faunal similarity, while the unexplained 56.30% could be attributed to small-scale spatial and temporal variability (Table 5).

The DCA analysis (Figure 6) shows a gradient of physical habitat conditions (from rocky to soft bottom) along Axis 1. However, the variance explained by the first two axes is low (19.7%), and axis one accounts for only 13.5%. This indicates a high degree of heterogeneity in the distribution of species and that, in addition to habitat, there may be other overlapping factors of variability, such as confinement or the influence of human activities, and that many species may inhabit different habitats. On the far right of axis 1 are samples from the mid-littoral rock, characterized by the dominant species Echinolittorina punctata (Gmelin, 1791) and Mytilaster minimus (Poli, 1795), and the species Melarhaphe neritoides (Linnaeus, 1758), which, although it has a relatively low abundance, occurs exclusively in this community. To the left of these are the infralittoral rocky assemblages, both photophilous and sciaphilous, and between them are the assemblages installed on the floating masses of Chetomormpha linum. To the left are the mixed Caulerpa—Cymodocea meadows and the nitrophilous communities. In the middle, more or less intermingled, are the meadows of Cymodocea nodosa, Ruppia cirrhosa, and sand and gravel bottoms.

In the 1980s, the well illuminated infralittoral rock was characterized mainly by Bittium reticulatum (da Costa, 1778), which reach a mean density of 6646.5 ± 4261.7 ind./m²; Parvicardium exiguum (Gmelin, 1791) and Mytilaster minimus, while the poorly illuminated infralittoral rocks were dominated by B. reticulatum and, in the pillars under the docks, by M. minimus.

The Caulerpa–Cymodocea mixed meadow was characterized mainly by the species Rissoa membranacea (J. Adams, 1800) which showed the highest dominance and frequency, Polititapes aureus (Gmelin, 1791), and Abra alba (W. Wood, 1802). The Cymodocea nodosa meadow was characterized by Bittium reticulatum and Pusillina lineolata (Michaud, 1830), Chaetomorpha linum floating mats by B. reticulatum. Nitrophilic communities on rocks by Cerastoderma edule (Linnaeus, 1758), Ruppia cirrhosa meadows by Hydrobia acuta (Draparnaud, 1805), producing a very marked peak in the total dominance of the period, and sandy bottoms by P. aureus and B. reticulatum (Figure 6 and Supplementary Material Table S1).

Beyond the differences in species composition or dominance of some species, the different habitats do not show major differences in their community structure indicators (total abundance, species richness, diversity, and equitability). Although the PERMANOVA analysis is significant (p = 0.016), the explained variability due to the habitat regarding other variability factors is similar to that of species composition and abundance. The pairwise analyses show that the differences are only due to the high abundance of individuals in the RU regarding CY (p = 0.0403), PI-IR (p = 0.0003), and SAND (p = 0.0422) (Table 6 and Table 7).

In general, in the 1980s period, the highest average species richness tends to be found in the infralittoral rocky communities, both sciaphilous (7.33 ± 1.12) and photophilous (7 ± 0.65), and in the Cymodocea nodosa meadows (7 ± 2.08). However, diversity tends to be somewhat lower than in the Chaetormorpha linum floating mats or the mixed CACY meadows due to the high dominance of some species (Table 5). The highest mean abundances are found in the photophilic communities of the infralittoral rock (8797.22 ± 5264.06 ind./m²) and in the only sample analyzed from the Ruppia cirrhosa stand (37,300 ind./m²), where they are reached, with a 99% dominance of Hydrobia acuta.

3.3. Temporal Changes in the Molluskan Assemblages’ Composition and Structure

Throughout the periods studied, species richness has remained relatively constant, ranging from 47 species in the 1980s to 49 in 2002–2007 and 2017–2019. However, the mean species richness, mean abundance, and mean diversity of the different communities, and the species composition itself have changed over the different periods analyzed. In the Supplementary Material it can be found the values of dominance of the different species in the different periods (Supplementary Material Table S2), habitats (Supplementary Material Table S3), and in the entire Mar Menor lagoon over time (Supplementary Material Table S4).

3.3.1. Temporal Changes in Molluskan Assemblages’ Composition

PERMANOVA analysis shows significant differences (p < 0.05) between all factors (period, habitat, and zone) and their interactions, except period × habitat × zone, indicating a high spatiotemporal heterogeneity, even within the same habitat (Table 8 and Supplementary Material Table S6). The representation of the MDS analysis performed on the abundance matrix of the different species in the most characteristic habitats studied in all the periods considered shows results consistent with the community analyses performed for the 1980s (Figure 7). Infralittoral rocky bottom habitats, both well illuminated WI-IR and DOCKS, are represented at the negative part of the first and second axes, while soft bottom habitats CA, CACY, CY, MUD, and SAND show a higher variability depending on the period and the sample zone, probably due to the different environmental conditions and changes in vegetation cover linked to the human impacts. Only the zones Z2 vs. Z3, in the central basin under the influence of the El Albujón watercourse, and Z1 vs. Z4, in the proximity of the main inlets, did not show significant differences.

Differences between habitats are more due to changes in the dominance of different species than to the existence of exclusive species. Seventeen species are present in all habitats, and the main differences are between rocky habitats, with 15 exclusive species, and soft substrate habitats that share most of their species with each other (Figure 8).

In fact, although 29 taxa occurred in a single habitat (Table 4), most of them appeared in a single period and with very low dominances (<0.09%), indicating that they are occasional species. On the other hand, some species, such as Bittium reticulatum, show a wide distribution, occurring in virtually all habitats. Indeed, most of the among-habitat dissimilarities revealed by the SIMPER analysis are due to differences in abundances of the shared species.

Despite the high degree of overlap and the high number of shared species, the dominant species or their relative dominance in each habitat often differed. In the infralittoral well-lit rocky bottoms (WI-IR), the dominant species were Mytilaster minimus, reaching 56.8% of total abundance, B. reticulatum, and Petricola lithophaga (Retzius, 1788), the same species as in the infralittoral sciaphilic assemblages on hard substrates (DOCKS), but in which M. minimus reached 94.5% dominance (Supplementary Material Table S3).

Sandy bottoms (SAND) were characterized by Hydrobia acuta contributing 37% of the dominance, Polititapes aureus, B. reticulatum, Cerastoderma glaucum (Bruguière, 1789) and Parvicardium exiguum while muddy bottoms (MUD) were characterized by C. glaucum 31% of dominance, Loripes orbiculatus (Poli, 1795) and Abra alba.

Cymodocea nodosa (CY), Caulerpa prolifera (CA), or the mixed meadows (CACY) shared the same characteristic species but with different relative abundances and dominances. In Cymodocea nodosa meadows (CY), B. reticulatum represents 31.8% of the total assemblage’s abundance, followed by L. orbiculatus (18.4%), Gastrana fragilis (Linnaeus, 1758) (7.7%), P. aureus (6.8%), and Rissoa membranacea (4.9%). C. prolifera meadows (CA) were characterized mainly by the species B. reticulatum (11.8%), L. orbiculatus (9.2%), and R. membranacea (6.6%). By its part, in the mixed meadow of C. prolifera and C. nodosa (CACY), B. reticulatum reached 66.8% of dominance, while R. membranacea accounted for 15.3% (Supplementary Material Table S3).

The highest dissimilarity was found between CACY and DOCKS (99.40%). DOCKS also differed from all other habitats, with high percentages of dissimilarity (95.36% with SAND and 99.33% with MUD). WI-IR also showed high dissimilarities with other habitats (88.74% with CACY, 87.32% with CA). The lowest dissimilarity was between CACY and CA (74.93%), mainly conditioned by changes in the effects of the dominance of C. prolifera (Supplementary Material Table S5).

The species that contributed most to the differences between habitats were M. minimus (17.38%) and B. reticulatum (13.39%) in CACY vs. DOCKS, and L. orbiculatus (12.8%) and C. glaucum (12.71%) in SAND vs. MUD.

Spatially, the differences between areas can be attributed to the confluence of various factors such as confinement, understood as the rate of colonization of species from the Mediterranean, the influence of human activities (agriculture, urban areas, and actions on beaches), or the diversity of habitats present or sampled in this study. Z1 and Z3 showed high dissimilarity (84.99%), with significant contributions from L. orbiculatus (14.26%) and C. glaucum (11.83%). Z2 and Z5 showed relatively lower dissimilarity (77.32%), dominated by contributions from L. orbiculatus (10.56%) and B. reticulatum (9.73%), while Z3 and Z4 showed substantial differences (79.29%), mainly influenced by L. orbiculatus (12.5%) and C. glaucum (11.8%) (Supplementary Material Table S5).

The rate of species substitution is high. Only 16 of the 86 species collected in the samples (19%) are present in all the periods considered. The percentage of species not shared between consecutive periods ranges from 45 to 57%. This percentage is even maintained at smaller temporal scale between consecutive years, ranging from 48.6% (2017 vs. 2018) to 50% (2019 vs. 2018). Of the 22 species present in all the periods studied, 8 are also the ones that showed the greatest dominance (>1%) and the highest average densities in the lagoon, considering all the habitats. Among them are the bivalves M. minimus, L. orbiculatus, P. aureus, C. glaucum, and A. alba. In the class Gastropoda, B. reticulatum was the most abundant species, followed by R. membranacea and Petricola lithophaga. The species Haminoea hydatis (Linnaeus, 1758), Tritia corrugata (Brocchi, 1814), and Tritia neritea (Linnaeus, 1758) were highly frequent but had low dominance in the total assemblage. Other overall dominant species, present only in two of the three main periods studied, were H. acuta, G. fragilis, and P. exiguum (Supplementary Material Table S4).

Furthermore, SIMPER analyses showed that the differences between pairs of periods were also determined by differences in the density of dominant species (Supplementary Material Table S5). The highest dissimilarity values occurred between the period 2002–2007 and the rest of the periods, oscillating between 77.61% (vs. 1980s) and 88.79% (vs. 2019).

The main species contributing to the dissimilarity between the different periods, with percentages of from 6.4–16.4%, were B. reticulatum, M. minimus, and R. membranacea, which, although always present, showed significant changes in abundance and dominance. Other species with significant changes between particular periods were A. alba, C. glaucum, L. orbiculatus, P. aureus, and G. fragilis which increased in density during 2017–2019 compared to the 1980s and 2002–2007.

The temporal dynamics of the assemblages in the different habitats is the result of variations in the abundance and relative dominance of the species that make them up, as well as the appearance of occasional species that colonize the Mar Menor more or less ephemerally during different periods. Figure 9 shows the changes in the dominance of the most abundant species in the Mar Menor in the different habitats where they occur during the periods studied. The observed changes are often abrupt and different in the different habitats where the species occurs in each period, and it is difficult to find a definite pattern.

The SIMPER analysis revealed that the soft bottom habitats MUD, CY, CA, CACY, and SAND underwent the most significant changes between the specified periods (Supplementary Material Table S7).

Specifically, the MUD habitat exhibited in the 2002–2007 period dissimilarities of 93.1% and 93.9% with 2017 and 2018, respectively. The species contributing most to this dissimilarity were B. reticulatum, which exhibited a marked decline in abundance in recent years (51.3% and 43.2% contribution respectively), and C. glaucum (8.57% and 10.8% contributions) and Tritia neritea (7.3% and 5.8% contributions, respectively), which increased in abundance. The change of the assemblages after the eutrophic crises of 2016 is particularly evident in this habitat, which changed from high densities of C. prolifera in 2006–2007 to a drastic reduction in its cover in 2017. In 2018, despite having begun its recovery, the low density of the C. prolifera patches allowed the reoxygenation of the surface layer of the sediments and, to a certain extent, repopulation by the fauna. In 2019, there was a progressive increase in the coverage of said algae, and in September of that same year, a DANA and a sharp stratification of the water column led to a hypoxic event in the deeper areas of the lagoon. From 2002–2007 to 2017, there was a strong increase of the populations of C. glaucum and L. orbiculatus and a decrease in T. neritea and B. reticulatum. The dissimilarity in 2018 with the 2002–2007 period reached 93.9% and of 79.6% with 2017, determined by a higher increase in the C. glaucum, A. alba, G. fragilis, and P. aureus populations and a reduction of the L. orbiculatus populations. These trends changed again in 2019 with a decrease of C. glaucum, G. fragilis, and A. alba and an increase of L. orbiculatus and P. aureus (Supplementary Material Table S7).

The C. prolifera (CA)-dominated meadows that survived the 2016 crisis did not show major differences between 2017 and the period of their maximum extent and density in the 2000s. However, 96.8% dissimilarities appeared between the 2000s period and 2018, where C. prolifera density was drastically reduced and the surface sediments they occupied were reoxygenated. These differences are mainly marked by the decrease in the populations of M. minimus, B. reticulatum, and R. membranacea; the colonization by G. fragilis; and the increase in the populations of A. alba, C. glaucum and L. orbiculatus. For their part, P. auratus and Peringia ulvae (Pennant, 1777) which in 2017, after the crisis, reached important populations, decreased sensibly in 2018. In this biocenoses, with the recovery of the density of C. prolifera in 2019, the populations of L. orbiculatus increased and decreased again those of A. alba, G. fragilis, and C. glaucum.

In the Cymodocea nodosa meadows (CY), between the 1980s and 2002–2007, the main changes contributing to the dissimilarity consisted of a marked decrease in the populations of B. reticulatum and P. lineolata and a slight decrease in M. minimus. Between the 2000s and 2017, the dissimilarities reached 93.7% and were mainly due to the increase of L. orbiculatus, C. glaucum and Dosinia lupinus (Linnaeus, 1758), the appearance of G. fragilis, and the decrease of M. minimus and R. membranacea populations (Supplementary Material Table S7). These trends were accentuated in 2018, after the improvement of the trophic conditions of the lagoon, and the populations of A. alba also increased; however, in 2019, with the return of nutrient discharges, the regression of P. aureus, G. fragilis, D. lupinus, and A. alba was observed.

In the sandy bottoms without meadows (SAND), the dynamics between 1980 and 2000 were different than in the C. nodosa meadows, with an increase in the populations of B. reticulatum and M. minimus and a marked decrease in those of P. aureus. This situation was reversed in 2017, when B. reticulatum and M. minimus populations decreased drastically, while C. glaucum and P. exiguum populations increased. In 2018, those of P. aureus also recovered, and those of P. exiguum and C. glaucum decreased.

In the case of DOCKS, the dissimilarities between periods were low, oscillating between 51.1% and 63.8%. This dissimilarity was mainly due to changes in the densities of the species B. reticulatum, which decreased after the 1980s, and M. minimus and Petricola lithophaga, which showed slight oscillations over time.

Infralittoral well-lit rocky bottom habitats (WI-IR) showed increasing dissimilarity between the 1980s and throughout the eutrophication process, from 87% in 2002–2007, when it started, to 91% in 2017, just after the eutrophication crises. The changes responsible for such differences corresponded to the same species as in the DOCKS with a decline in M. minimus and B. reticulatum populations between the 1980s and the 2000s, which was maintained after the eutrophic crisis of 2016, alongside an increase in P. lithophaga populations, particularly high in 2018, a year in which it reached average densities of 481 ind./m².

3.3.2. Changes in the Molluskan Assemblages’ Structure Descriptors

As commented above, over the three major periods considered (1980s, 2002–2007, and 2017–2019), species richness has remained relatively constant, with an average of 49 species present in total. However, species composition has shown variations in each period, with changes in the species present and their respective relative abundances. This reflects a dynamic in the community, where some species have increased or decreased their presence, resulting in a variable species diversity in terms of their dominance and distribution (Figure 10).

Mean species richness ranged from 1.4 ± 0.2 in the DOCKS settlement in 2019 to 7 ± 2.1 and 7 ± 0.6 in the CY and WI-IR settlements in the 1980s. The highest mean densities of individuals were recorded in the well-lit rocky infralittoral bottoms in the 1980s with 8797.2 ± 5264.1 ind./m² and in the 2000s with 9280.3 ± 3307.8 ind./m², while the lowest in the DOCKS sciaphilic communities of the rocky infralittoral, especially in 2019 with only 228.6 ± 80.4 ind./m². On the other hand, the lowest diversity values in the mollusk assemblages are found in DOCKS, ranging from 0.3 ± 0.1 bits/ind. in 2018 to 1.3 bits/ind. in the 1980s, and the highest in the Cymodocea nodosa meadow, ranging from 0.8 ± 0.1 bits/ind. in 2002–2007, at the period of greatest intensity of beach regenerations in the lagoon, to 2.0 ± 0.1 bits/ind. in 2017. Assemblages of well-lit infralittoral rocky bottoms ranged from 0.5 ± 0.1 in the 2000s and in 2017 to 1.4 ± 0.1 in 2018 and 1.6 ± 0.3 bits/ind. in 2019, after the recovery from the eutrophic crisis of 2016. CA meadows ranged from 0.8 ± 0.1 in the 2000s, when they reached their maximum extent, to 1.8 ± 0.1 bits/ind. in 2018, when their density was low, following regression due to the 2016 crisis and reoxygenation of surface sediments (Table 9).

PERMANOVA analysis shows that all structural parameters, total abundance, species richness, and diversity show significant differences (p < 0.05) between habitats, periods, and in the interaction between them, indicating that the different environmental factors and human activities affected each assemblage differently in each period (Table 10). In general, the abundance decreased over time with values that ranged on average from 5270.3 ± 1138.8 ind./m² in the 1980s to 631.9 ± 64.3 ind./m² in 2019, while the species richness decreased from 6.3 ± 0.3 species/400 cm² to 2.9 ± 0.1 in 2017 but then recovered to 4.8 ± 0.2 in 2018. The same pattern was observed for diversity, which decreased from 1.3 ± 0.1 bits/ind. in the 1980s to 0.7 ± 0.1 in the 2000s and 0.9 ± 0.1 in 2017, reaching a maximum of 1.5 ± 0.1 bits/ind. in 2018.

The fact that the habitat × period interaction is significant in all cases, both for abundance, species richness, and diversity, indicates that each habitat has followed a different trajectory in the different periods. Some communities have hardly undergone any structural change. For instance, in the sandy bottom assemblage (SAND) there are only significant differences in species richness between 2017 and 2018, and the DOCKS sciaphilous assemblage only shows significant differences in abundance between 2017 compared to 2018 and 2019. The C. prolifera meadow (CA) exhibited significant variations in richness, abundance and diversity between 2018 and all other periods, except for the 1980s. In the well-lit infralittoral rocky bottom, 2018 also showed significant differences in species richness with all other periods, while 2017 exhibited significant differences with 2018 and 2019. The responses are so heterogeneous that it is difficult to differentiate what may be natural variability, both interannual and spatial, from what may be responses to the different environmental impacts suffered by the lagoon, affecting each type of habitat differently.

4. Discussion

The mollusk fauna of the Mar Menor is an enormously heterogeneous and dynamic assemblage. Far from being a single euryhaline and eurythermal biocenoses as described by Pérès and Picard [65] or Augier [66], it is, in fact, a mosaic of assemblages in which a relatively high percentage of common species, but with different dominances, are combined with species showing preferences for different types of habitats. The few species that occur in a single habitat are, in fact, occasional species that also occur only in a particular period and with low dominance. This work confirmed the high taxonomic diversity of mollusks in the lagoon assemblages, showing that the different habitats of the coastal lagoon can also maintain a high spatial heterogeneity, depending on small-scale variations in the different habitats, and suffer an important temporal variability at the interannual level both in their taxonomic composition and in their structure. This great spatio-temporal variability is, in turn, marked by a multitude of factors such as habitat type (substrate, vertical zonation, lighting, vegetation cover) overlaid by the influence of the open sea or human activities in each location and period. In the case of mollusk assemblages, salinity and habitat diversity, as well as the structural complexity of habitats, are usually among the factors that control their spatial variability in tropical and temperate coastal lagoons and estuaries [15,91].

The configuration of the biological communities and the functioning of coastal lagoons are largely governed by the degree of isolation [92] and confinement [93,94], understood as the restrictions imposed by the lagoon barriers to colonization rates, as well as the mentioned spatiotemporal variability present in them [95]. Species of mollusks such as Hydrobia acuta, Pirenella conica (Blainville, 1829), Cerastoderma glaucum, or Abra ovata (=A. segmentum (Récluz, 1843)) are considered typically paralic species or indicators of lagoon environments in the zonation defined by confinement [96]. Lagoon’s zonation and the structure of their communities can be considered as the result of the probabilities of species colonization and of their establishment ability in terms of the balance and energy costs resulting from adaptations, reproduction, population growth rates, and competition with other species, conditioned by the ecological context provided by a lagoon [1,95].

The low colonization rates due to the restrictions imposed by the communication inlets, the barriers that the differences in salinity and temperature represent, and the very randomness of the processes prevent the system from becoming homogenized and from the dominant species excluding the rare. This opens a wide range of possibilities for diversity, adaptation to changes (including global climate change), and leads to significant differences in the species composition between lagoons, while also promoting ecosystem structure and complexity [1,97].

Colonization from the open sea, in the context of the fact that the Mar Menor is a restricted lagoon with residence times of almost a year, means that population changes between periods are high (between 45% and 57%) with a high random component. The percentage of unique species in each period was also high, representing 23.4% during the 1980s, 36.7% during the period 2002–2007, and 9.6% in 2017–2019. This seems to be an inherent characteristic of coastal lagoon assemblages that show a high variability with a high renewal rate of species in a given lagoon. Around 40% of ichthyoplankton species in the Mar Menor [12] and of the macrofauna of benthic invertebrates in the Venice lagoon [11] change from one year to the next.

To date, a total of 126 different mollusks have been collected or identified in the Mar Menor lagoon, also considering the species previously registered in other works [51,70,90]. However, of these, only between 40% and 50% are present at any given time with no clear pattern in the dynamics they follow. For the period of the 1980s, a total of 47 mollusk species were cited in the lagoon (21 gastropods, 24 bivalves, and 2 polyplacophoran). In the 2002–2007 period, a total of 49 different species of mollusks were identified (27 gastropods, 21 bivalves, and 1 polyplacophoran), while in the most recent samples, corresponding to 2017–2019, we have identified 47 different species in the lagoon (26 gastropods, 20 bivalves, and 1 polyplacophoran). This proportion between the main taxonomic groups, which shows a certain regularity between periods, is also similar to that found in other Mediterranean lagoons [98].

Mollusks are sensitive to environmental changes [98] and in lagoons such as Marinello in Sicily, they have been used as indicators of long-term changes in salinity, organic matter content of sediments, and dystrophic episodes [27]. Over the last 40 years, the progressive environmental variations in the Mar Menor coastal lagoon in terms of environmental conditions in the water column, in the sediment, and in the distribution and dynamics of seagrass and macrophyte meadows [53,56,57], have produced changes in the different habitats available for mollusks and, with this, effects on their assemblages. According to the analyses, the main environmental variables determining the differences between the time periods considered are the average temperature and the chlorophyll a concentration. Both factors alternate, depending on the periods compared, in their relative contribution to the variance of the data. Although, beyond their statistical importance, from a biological point of view, in the first instance, the range of variation in average temperature (0.4–2 °C) could be considered negligible and too small to cause fast changes in community composition compared to the possible effect of changes in trophic status, in practice both factors can have real effects on lagoon assemblages. Changes in trophic status, related to chlorophyll a concentration, can be determinants of changes in species and populations, especially depending on their trophic strategies. However, the role of seemingly small changes in other environmental variables, such as temperature, either on its own or in synergy with trophic status, should not be underestimated.

Temperature can be an important factor, as it often determines the geographic ranges of species distribution, hence the effects of climate change, which in many cases are within the ranges of variation detected in the Mar Menor between periods of variability. Minimum or maximum temperatures often make the difference between species being within the limits of their niche or energy balances that allow them to reproduce within the lagoon. The colonization and rapid expansion of C. prolifera in the Mar Menor, which led to important changes in the lagoon ecology, was probably linked to a slight softening of minimum temperatures from 8 to 11 °C after the dredging and expansion of El Estacio inlet, as C. prolifera poorly tolerates temperatures below 10 °C [99]. On the other hand, slight differences in maximum temperatures, acting synergistically with eutrophication factors and balances between oxygen solubility and respiratory demand, can increase the risks of dystrophic crisis, hypoxia, and mortality events.

In general, the abundance of the different species has decreased, and both the composition and the structure of the faunal community have shown significant differences over the periods and between the different types of assemblages studied. Mainly there have been changes in the densities of the dominant species of the assemblages, such as increases and decreases in certain periods, probably related to the variation in the structural complexity of some habitats over time, as in the case of soft bottoms depending on the density and dominance relationships in the C. prolifera and C. prolifera-C. nodosa mixed meadows or the structure of the vegetation in hard substrates. This is the case of species such as Bittium reticulatum and Rissoa membranacea, which during the 1980s had very high densities and whose presence has been decreasing over time. The species B. reticulatum feeds on microalgae and is associated with seagrass meadows, and the species R. membranacea feeds on diatoms that cover macroalgae [14,100], and probably the dynamism of these vegetation covers over time is related to the decrease in their density. However, the species Mytilaster minimus maintained a high dominance in all periods, but during 2002–2007 and 2017 there was a density peak that led to a very high dominance of this species. Other species such as Abra alba, Cerastoderma glaucum, Gastrana fragilis, and Loripes orbiculatus have increased in density over time. In particular, the species L. orbiculatus is associated with eurythermal and euryhaline lagoons, anoxic environments with high sulfide levels, and fine-grained sediments with high organic carbon content from decomposing macrophyte beds [100]. High densities have been found since 2017 when the Mar Menor was in a eutrophic crisis, resulting in the loss of 85% of the lagoon’s vegetation cover, causing trophic imbalances and an increased in the demand for oxygen for the decomposition of organic matter on the bottom [57].

In addition, significant differences in assemblage composition have been observed over time. However, these differences are mainly due to changes in dominant species, as mentioned above, and to pulses of species that appeared occasionally. A considerable number of species do not dominate the assemblage but appear at low densities at specific times. Some even only occur in a single period. Species such as Dosinia lupinus, Hydrobia acuta, Haminoea hydatis, Hexaples trunculus (Linnaeus, 1758), Tritia corniculum (Olivi, 1792), Tritia neritea, and Pusillina lineolata show significant differences between the different periods and communities studied, being non-dominant species. Although these species are relatively frequent in the coastal lagoon, they do not reach a dominant role in the assemblage. Other species that have been studied in this work have been neither frequent nor dominant in the assemblage and have shown an irregular pattern, appearing completely discontinuously or even registering their presence only once. All this suggests that their frequencies in certain periods may be subject to the variation of environmental conditions. However, as mentioned above, lagoon ecosystems are characterized by high heterogeneity where probably the main sources of variability are connectivity, the high rate of species renewal [101], and the relationship with dystrophic events, increasing the probability of colonization by different species [27]. This in addition to the reproductive characteristics of the different species of mollusks, which may also show intrinsic temporal variability [14].

Changes in habitat composition over time reflected specific trends: Habitats such as WI-IR and CY showed the greatest changes over the periods, so they are probably the most susceptible to environmental pressures or disturbances, mainly due to the turbidity and sedimentation rates produced by the dredging and dumping of sand for the creation and maintenance of artificial beaches along the entire inner shore of the lagoon, which were common in the Mar Menor from the 1990s to 2014. CACY and SAND had more gradual transitions, suggesting some relative stability. In general, temporal changes were not uniform between habitats, highlighting the importance of interactions between the environmental characteristics of habitats and temporal pressures (natural or anthropogenic).

The restrictions imposed on the connectivity by the lagoon inlets make the lagoon colonization probabilities low, and this introduces a high random component in the assemblages that manifests in the natural heterogeneity of the ecosystem structure and the resilience and homeostatic capacity that coastal lagoon ecosystems have [1,102]. Another important sources of spatial variability directly affecting the biological assemblages and lagoon functioning are the hydromorphology and the substrate characteristics. The first conditions the water movements and the residence time of water within the lagoon [103]. It also conditions sediments, particles, and pollution movement and diffusion, and the physical dispersion of eggs and larvae that restraints the successful recruitment and the temporal and spatial structure of lagoon populations [47,102]. Regarding the substrate, although many coastal lagoons are dominated by muddy bottoms, many others have a mosaic of natural habitats, sandy, muddy, gravelly, or rocky outcrops, and stones. In addition, many also have man-made structures, rock, concrete, or wood used in the construction of poles, docks, and jetties, and human transformations can directly or indirectly affect other important environmental conditions [1].

An important factor affecting the composition and structure of biological populations is the impact of different human activities. In the Mar Menor, in addition to the actions in the inlets, which affect its hydrographic conditions and the connectivity with the Mediterranean and the colonization of species, the dredging and dumping of sand for the creation and maintenance of beaches, and the process of eutrophication, discussed above, other sources of pollution are heavy metals of mining origin and the entry of pesticides of agricultural origin and other emerging pollutants, including microplastics. One of the most important sources of pollution in the Mar Menor is due to heavy metals of mining origin [104,105,106], with very high levels of Pb, Cd, or Zn in the sediments [107]. The incidence of heavy metals in the waters, sediments and organisms of the Mar Menor has been studied in several works [108,109,110,111,112,113,114,115,116,117,118,119], some of them with reference to concentration levels in mollusk species [120,121,122,123,124,125,126]. The increasing level of heavy metals in marine coastal sediments is considered one of the most relevant problems due to their toxicity and persistence [127]. In the Mar Menor, mining operations and dumping date back to the Argaric period, and they ceased two decades before the period considered in this study, so the influence in the three periods analyzed can be considered temporarily homogeneous. However, there is no doubt that it can condition the spatial heterogeneity [55]. The main source of pesticides comes from agricultural activity, and their risks have already been warned by García Dory and Maldonado in 1980 [105]. Previous studies on the incidence of pesticides showed a very local influence close to the mouth of the main streams in the period of the 2000s [128], but in recent years the detection of synthetic organic pollutants, including pharmaceuticals and plastics, among others, in both sediments and some species has increased [129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145]. Most show concentrations below the maximum permitted reference levels, although there is a large spatiotemporal variability, with a close link to the mouth of the main watercourses with a seasonal pattern or linked to torrential rains. There are no specific studies on the influence of these pollutants on the composition and structure of the communities or the mollusk assemblages, but, in any case, it could be assumed that it does not significantly affect the vast majority of the sampled areas, although it could undoubtedly influence the spatial variability observed between localities. Analyzing the impact of each of these pollutants would require specific designs.

In our work, the environmental conditions in the water column show significant differences between periods but not between zones. The lack of spatial differentiation is probably a matter of scale, since, although some localities suffer more directly than others from the entry of fresh water and nutrients or the marine influence, the irregularity in the intensity of these events and their small-scale spatiotemporal variability prevents the detection of spatial differences at the zone scale.

This implies that analyzing the effects of human activities on lagoon communities must be done with sampling designs at small spatial scales. On the other hand, possible long-term effects are obscured by the high inter-annual variability inherent to lagoon communities. Both circumstances may, however, constitute an important mechanism of homeostasis of the lagoon communities, as they allow environmental impacts not to affect all areas simultaneously, leaving strongholds that favor recolonization and recovery of the most affected areas, and up to 50% of the species may be renewed annually.

On the other hand, beyond the environmental factors that determine or condition the specific composition, mollusk populations play an essential role in the trophic networks of the Mar Menor. According to the Ecopath trophic model carried out with the lagoon communities for the 1980s, this ecosystem has a highly complex food web with important regulatory mechanisms that allow it to control the effects of eutrophication [50]. Both bivalves and gastropods are among the groups with the highest biomasses, ranging from 14.35–315.18 g C/m² and 0.68–178.50 g C/m², respectively. In addition, both are among the five functional groups with the highest keystone index, with Gastropoda having the highest value and the highest relative total impact. Despite the diversity of trophic strategies displayed by the different species, the average trophic level based on the weighted abundance of all species is 2.1 for gastropods and 2.0 for bivalves. However, Dicentrarchus labrax (Linnaeus, 1758), Bivalvia and Gastropoda showed the greatest direct and indirect mixed trophic impacts on the other food web groups, with mollusks having a slightly lower negative impact than D. labrax, showing top-down control over other invertebrate populations. At the same time, the populations of both groups of mollusks are controlled top-down by predation from other higher levels of the food web. Of the 92 trophic compartments considered in the model, 31 prey, to a greater or lesser extent, on mollusks. Among those that include them in a higher percentage of their diet are some species of cnidarians (i.e., Cereus pedunculatus (Pennant, 1777)), and numerous species of fish, mainly Sparus aurata Linnaeus, 1758, Lithognathus mormyrus (Linnaeus, 1758), Symphodus roissali (Risso, 1810), Diplodus annularis (Linnaeus, 1758), or Gobius cobitis Pallas, 1814. Some of them are migratory and others reproduce in the lagoon, but all of them are stable components of the fauna of the Mar Menor and of many Mediterranean coastal lagoons.

The wide range of trophic strategies and their response to environmental variable conditions allow mollusk assemblages to be a key link in both water quality and nutrient cycling [35,146]. Deposit feeding species such as A. alba, L. orbiculatus, and C. glaucum displace sediment particles, mixing them vertically, allowing oxygen to be present, the grazer gastropods remove epiphytic algae allowing photosynthesis by the phanerogams, and filter feeders play a clear role in maintaining water quality [147]. Suspension-feeding bivalve assemblages, mainly epifaunal mussels and oysters, can also contribute to maintaining water quality by facilitating the accumulation of organic N, P, and C in sediments due to biodeposition [148], and even by removing inorganic particles, separating them from the more nutritious ones before ingestion, and depositing them as pseudofeces in mucous aggregates [149,150]. However, bivalves can also have the opposite effect, as they contribute significantly to the release of NH₄ and PO₄ from shallow sandy sediments [151,152] and may represent a greater contribution than the input from land [153]. The balances may depend on the system studied, although in some cases it has been suggested that the overall effect may be a reduction in sedimentation due to the consumption of phytoplankton and zooplankton by grazing [154].

In this way, mollusk assemblages probably played an important role in the recovery of water quality and trophic conditions after the eutrophic crisis of 2016 occurred in the Mar Menor, through the functional reorganization of the trophic strategies. Throughout the periods studied, the functional structure of mollusk assemblages has changed from a dominance of browsing species such as the gastropods B. reticulatum and Rissoa membranacea during the 1980s to an increase in the dominance of detritivores. In 2017 there was an increase in the density and dominance of deposit- and suspension-feeding species that tolerate hypoxic conditions in the sediment, such as A. alba, G. fragilis, and L. orbiculatus. Similar changes have been observed in other lagoons, such as Venice [155] where species such as L. orbiculatus and A. alba increased their populations with the organic enrichment produced by a proliferation event and subsequent decomposition of algae such as Ulva rigida C. Agardh, while species such as C. glaucum were reduced and restricted to periods with less oxygen deficit, and Parvicardium exiguum was relegated to the seagrass meadows.

This work provides an idea of the diversity and long-term variability of mollusk assemblages in the Mar Menor coastal lagoon. The results indicate that, during these almost 40 years, the total number of species has remained relatively constant, but with a high percentage of occasional and very rare species and a high rate of change and species substitution over time, reaching up to 57% independently of the temporal scale (decades or interannual) considered. Furthermore, the assemblages showed variations in the abundance and dominance of some species compared to others depending on the environmental conditions and pressures that the lagoon has undergone. This high spatial and temporal heterogeneity is determined by the restricted connectivity with the open sea, the diversity of environments and habitats, and the changes in environmental conditions due to human actions.

This translates into a high ability to adapt to changing environmental conditions and human impacts, as well as the important role they can play in self-regulation mechanisms and recovery of water quality in eutrophication processes and after eutrophic crisis events. However, the details and quantification of these mechanisms will require specific studies and experimental designs.

Author Contributions

A.P.-R.; conceptualization and original idea, research, formal analysis, data curation and analysis, supervision, writing original draft, projects management and administration, review, editing and validation; O.S.-F.; research, data curation and analysis, writing original draft; A.S.-M.; research; C.M.; supervision, projects management and administration, review, editing and validation; and P.P.; research. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

Dataset available upon request to the authors.

Acknowledgments

We also would like to thank Club Náutico de lo Pagán for the port facilities offered and all the researchers and collaborators of the research group “Ecology and management of coastal marine ecosystems” from the University of Murcia who have participated in the sampling and taxonomic work over all these years. We would like to thank L. Murillo, a pioneer in the malacological studies of the Mar Menor, for the initial training of O.S.-F. in the determination of species.

Conflicts of Interest

The authors declare no conflicts of interest.

Footnotes

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Figures and Tables

Figure 1. (A) Location of the Mar Menor and the sampling stations studied from 1981 to 2019, distributed in the 5 zones in which we have divided the lagoon for spatial analyses, and (B) main bottom biocenoses in 1980s. Locations: LR: La Ribera; Es: El Estacio inlet; IC: El Ciervo island; LU: Los Urrutias.

Figure 2. Monthly and interannual dynamics of the environmental variables measured in the water column (salinity, temperature, and chlorophyll a concentration) throughout the study period. The values represent the monthly mean in the lagoon, and the bars correspond to the standard errors. The shaded areas correspond to the periods in which the malacofauna has been sampled.

Figure 3. Cluster analysis of the periods studied according to their environmental conditions in the water column (salinity, temperature, and chlorophyll a concentration). The shaded areas frame the periods that do not show significant differences from each other in the PERMANOVA analysis performed for pairwise comparison. The blank separations indicate significant differences for p [less than] 0.05. The symbols under the periods correspond to those that characterize the samples for each period in Figure 1.

Figure 4. Results of the PCA carried out on the variables of the water column (salinity, temperature, and concentration of chlorophyll a) measured monthly in the five zones into which the sampling in the Mar Menor has been divided in the different study periods.

Figure 5. (A) Cluster analysis performed on the Jaccard index distance matrix on presence-absence data. (B) Cluster analysis performed on the Bray-Curtis distances on log (x + 1) transformed abundance data. CACY: Caulerpa—Cymodocea mixed meadows, CHAE: Chaetomorpha linum floating mats, CY: Cymodocea nodosa meadows, DOCKS: protected poorly illuminated infralittoral rocks under docks, MR; midlittoral rocks, NITR; nitrophilic communities on rocks, SAND: sandy bottoms, RU; Ruppia cirrhosa meadows, WI-IR: well illuminated infralittoral rocks and PI-IR: poorly illuminated infralittoral rocks. (Z1–Z5) Mar Menor spatial zones.

Figure 6. Graphic representation of relationships among the spatiotemporal patterns in sample ordination and species analyzed using detrended correspondence analysis (DCA) on the species abundance matrix after log (x + 1) transformation. Analyses were performed for the 1980s period. Habitat abbreviations refer to Table 1.

Figure 7. Nonmetric multidimensional scaling (nMDS) plot based on quantitative (log (x + 1) transformed abundance data) similarities (Bray-Curtis index) among the total molluskan assemblage in each analyzed habitat and period. Stress value 0.122. Abbreviations of habitats in Table 1.

Figure 8. Venn diagram showing the number of taxa shared by the distinct habitats (A) and periods (B). Abbreviations of habitats in Table 1.

Figure 9. Dynamics of the temporal evolution of the dominant species of the total mollusk assemblages in each period and habitat analyzed in the coastal lagoon of the Mar Menor. Abbreviations of habitats in Table 1.

Figure 10. Evolution of the structural descriptors of mollusk populations in the main habitats of the Mar Menor in the periods studied (N: average density of individuals per m2, S: average species richness, H’: average Shannon diversity index, and J’: evenness). Habitat’s abbreviations refer to Table 1. The colors of the habitats correspond to those used in Figure 6 and Figure 7.

Table 1

Main habitats and biocenoses in the Mar Menor lagoon, along with the locations and characteristics of the mollusk samples used in this work, which include unpublished data from Pérez-Ruzafa [51].

Habitats	Habitat Abbrev.	Location	Period of Sampling	Deep	Zone
Shallow littoral sandy bottoms with dominance of Cymodocea nodosa	CY	Los Urrutias (LU)El Ciervo island (IC)	1980s, 2002–2007, 2017, 2018, 2019	<2 m	2, 5
Muddy bottoms with a mixed meadow with different biomass values of Caulerpa prolifera and Cymodocea nodosa	CACY	Lagoon basin (LB)	1980s, 2002–2007, 2019	2–6 m	1–5
Mid-littoral rocks	MR	El Ciervo island (IC)El Estacio channel (ES)	1980s, 2002–2007	<2 m	4, 5
Well illuminated infralittoral rocks	WI-IR	La Ribera (LR)El Ciervo island (IC)El Estacio channel (ES)	1980s, 2002–2007, 2017, 2018, 2019	2–6 m	1, 4, 5
Protected shallow infralittoral rocks and poorly illuminated on pillars under docks	DOCKS	La Ribera (LR)	1980s, 2017, 2018, 2019	<2 m	1
Poorly illuminated infralittoral rocks	PI-IR	La Ribera (LR)El Ciervo island (IC)El Estacio channel (ES)	1980s	2–6 m	1, 4, 5
Nitrophilic community on rocks	NITR	La Ribera (LR)El Ciervo island (IC)	1980s	<2 m	1, 5
Chaetomorpha linum floating mats	CHAE	La Ribera (LR)Lo Pagán (LP)	1980s	2–6 m	1
Ruppia cirrhosa meadows	RU	Lo Pagán (LP)La Perdiguera island (PI)	1980s	<2 m	1, 3
Shallow littoral sandy bottoms with or without the presence of Acetabularia spp.	SAND	El Barón island (BI)Las Encañizadas (E)	1980s, 2017, 2018, 2019	<2 m	1, 4
Muddy bottoms with dominance of Caulerpa prolifera	CA	Lagoon basin (LB)El Ciervo island (IC)Los Urrutias (LU)La Perdiguera island (PI)	2002–2007, 2017, 2018, 2019	2–6 m	1–5
Muddy bottoms without macrophyte biomass	MUD	Lagoon basin (LB)	2002–2007, 2017, 2018, 2019	2–6 m	1–5
Red compacted clays	RC	Los Urrutias (LU)	1980s, 2002–2007	<2 m	2

Table 2

Results of PERMANOVA and pairwise comparisons of the environmental conditions in the periods in which the malacofauna has been studied. Bold figures indicate significant differences. ECV: Explained component of variation.

Source	df	SS	MS	F	p	ECV (%)
Period	4	164.2	41.051	19.201	0.0001	36.65
Zone	4	4.0649	1.0162	0.47534	0.9023	0
Period × Zone	12	5.0262	0.41885	0.19592	1	0
Res	273	583.65	2.1379			63.35
Total	293	756.27
Pairwise Test
Groups	t	p
1980s vs. 2002–2007	1.7766	0.0306
1980s vs. 2017	2.8894	0.0001
1980s vs. 2018	1.26	0.1828
1980s vs. 2019	1.4501	0.1366
2002–2007 vs. 2017	9.8814	0.0001
2002–2007 vs. 2018	3.7351	0.0001
2002–2007 vs. 2019	5.4861	0.0001
2017 vs. 2018	5.7227	0.0001
2017 vs. 2019	0.96323	0.3542
2018 vs. 2019	2.8444	0.0016

Table 3

Results of the SIMPER analysis of differences in environmental conditions (mean temperature (°C) and mean chlorophyll a) between the periods in which the malacofauna has been studied.

Period	Variable	Av. Value	Av. Value	Av. Sq. Dist	Sq. Dist/SD	Contrib%
1980s vs. 2002–2007	Temperature	20.8	22.3	59.8	0.86	89.37
1980s vs. 2017	Temperature	20.8	20.4	63.9	0.88	56.73
	Chlorophyll a	0.84	6.03	41.2	0.84	36.64
1980s vs. 2018	Temperature	20.8	20.2	61.2	0.9	89.57
1980s vs. 2019	Chlorophyll a	0.84	7.53	243	0.29	75.75
2002–2007 vs. 2017	Temperature	22.3	20.4	79.9	0.87	62.44
	Chlorophyll a	1.01	6.03	39.8	0.82	31.1
2002–2007 vs. 2018	Temperature	20.8	20.2	61.2	0.9	89.57
2002–2007 vs. 2019	Chlorophyll a	1.01	7.53	241	0.29	71.39
2017 vs. 2018	Temperature	20.4	20.2	79.5	0.89	67.42
	Chlorophyll a	6.03	1.86	33	0.76	27.96
2017 vs. 2019	Chlorophyll a	6.03	7.53	214	0.3	70.01
2018 vs. 2019	Chlorophyll a	1.86	7.53	231	0.29	71.91

Table 4

Taxonomic list of the species recorded in the Mar Menor between 1980 and 2019, the habitats where they were found and their overall dominance in the lagoon during the different periods of their occurrence. The abbreviations of the habitats correspond to those described in Table 1. (*) Species cited in the Mar Menor by several authors recorded in Pérez-Ruzafa [51], but not found in quantitative samplings in this work. For the species that have been found in a single habitat this has been highlighted in color.

Taxon	Abbrev.	Habitat	1980s	2002–2007	2017	2018	2019
			Dominance (%)
Bivalvia
Family Anomiidae
Anomia ephippium (Linnaeus, 1758)	Anoeph	WI_IR, PI_IR	0.03			0.02
Family Arcidae
Arca noae Linnaeus, 1758	Arcnoa	DOCKS, PI_IR	0.01		0.02
Family Cardiidae
Cerastoderma edule (Linnaeus, 1758)	Ceredu	CY, NITR	0.02	0.01
Cerastoderma glaucum (Bruguière, 1789)	Cergla	CA, CY, CACY, MUD, SAND, RC, WI_IR	0.3	0.3	15.3	13.1	1.1
Parvicardium exiguum (Gmelin, 1791)	Parexi	CA, CY, CACY, CHAE, MUD, SAND, WI_IR, DOCKS, PI_IR	1.18		4.64	1.89	0.97
Parvicardium scriptum (Bucquoy, Dautzenberg and Dollfus, 1892)	Parscr	CA, CY, RC, WI_IR		0.16
Family Chamidae
Chama gryphoides Linnaeus, 1758	Chagry	PI_IR	0.01
Pseudochama gryphina (Lamarck, 1819)	Psegry	WI_IR	0.01
Family Corbulidae
Varicorbula gibba (Olivi, 1792)	Vargib	CA, MUD			0.22	0.14	0.03
Family Donacidae
Donax semistriatus Poli, 1795	Dosem	*(SAND)	*
Family Gastrochaenidae
Rocellaria dubia (Pennant, 1777)	Rocdub	WI_IR, DOCKS			0.11	0.76
Family Lasaeidae
Tellimya ferruginosa (Montagu, 1808)	Telfer	CY		0.03
Family Limidae
Limaria hians (Gmelin, 1791)	Limhia	WI_IR		0.01
Limaria loscombi (G. B. Sowerby I, 1823)	Limlos	*(MUD)
Limaria tuberculata (Olivi, 1792)	Limtub	WI_IR	0.01
Family Lucinidae
Ctena decussata (O. G. Costa, 1829)	Ctedec	CA		0.01
Loripes orbiculatus (Poli, 1795)	Lororb	CA, CY, CACY, MUD, SAND, RC, WI_IR	1.62	0.22	11.76	8.91	35.17
Lucinoma borealis (Linnaeus, 1767)	Lucbor	*(SAND)	*
Family Mactridae
Mactra corallina (Linnaeus, 1758)	Maccor	*(SAND)	*
Mactra stultorum (Linnaeus, 1758)	Macstu	MUD		0.01
Family Mytilidae
Modiolus adriaticus (Lamarck, 1819)	Modadr	CA, CY, CACY, MUD, SAND, PI_IR, RC	0.04	0.27	0.6	0.03
Modiolus barbatus (Linnaeus, 1758)	Modbar	CACY, WI_IR, SAND	0.06
Mytilaster minimus (Poli, 1795)	Mytmin	CA, CY, RU, MUD, SAND, CHAE, PI_IR, RC, WI_IR, DOCKS	6.18	83.97	44.3	17.02	6.06
Mytilus edulis (Linnaeus, 1758)	Mytedu	MR		0.04
Mytilus galloprovincialis (Lamarck, 1819)	Mytgal	WI-IR	0.02
Family Ostreidae
Ostrea edulis (Linnaeus, 1758)	Ostedu	CACY, MUD, WI_IR, PI_IR, DOCKS	0.06	0.01	0.33	0.09
Ostrea stentina (Payraudeau, 1826)	Ostste	WI_IR	0.01
Ostrea sp. Linnaeus, 1758	Ostsp	WI_IR, DOCKS			0.04
Family Pectinidae
Mimachlamys varia (Linnaeus, 1758)	Mimvar	CY		0.01
Family Pinnidae
Pinna nobilis Linnaeus, 1758	Pinnob	*(SAND)	*
Family Pholalidae
Pholas dactylus Linnaeus, 1758	Phodac	*(RC)	*
Family Semelidae
Abra alba (W. Wood, 1802)	Abralb	CA, CY, CACY, MUD, SAND, WI_IR, RC	1.02	0.02	1.54	9.28	13.16
Abra segmentum (Récluz, 1843)	Abrseg	CACY, DOCKS	0.26
Family Thraciidae
Thracia phaseolina (Lamarck, 1818)	Thrpha	WI_IR				0.09
Family Tellinidae
Gastrana fragilis (Linnaeus, 1758)	Gasfra	CA, CY, CAM, MUD, SAND, WI_IR, PI_IR	0.09		2.25	13.2	10.15
Macomangulus tenuis (da Costa, 1778)	Macten	*(SAND)	*
Moerella distorta (Poli, 1791)	Moedis	MUD			0.02
Peronaea planata (Linnaeus, 1758)	Perpla	*(PI_IR)	*
Family Veneridae
Chamelea gallina (Linnaeus, 1758)	Chagal	CA, CY, CHAE, MUD	0.01	0.01	0.07	0.03
Dosinia lupinus (Linnaeus, 1758)	Doslup	CA, CY, CACY, MUD	0.01	0.01	1.03	1.25	3.33
Irus irus (Linnaeus, 1758)	Iruiru	WI_IR, MR, PI_IR	0.07	0.01
Petricola lithophaga (Retzius, 1788)	Petlit	SAND, RC, WI_IR, DOCKS, MR, PI_IR	0.36	0.06	2.94	8.58	2.94
Polititapes aureus (Gmelin, 1791)	Polaur	CA, CY, CACY, CHAE, NITR, MUD, SAND, RC, WI_IR, MR, PI_IR	4.15	0.81	2.63	7.87	16.14
Ruditapes decussatus (Linnaeus, 1758)	Ruddec	CY, CA, CACY	0.02	0.01	0.04
Venerupis corrugata (Gmelin, 1791)	Vencor	CA, CY, CACY, MUD		0.05
Gastropoda
Family Aeolidiidae
Aeolidiella alderi (Cocks, 1852)	Aald	*(RU, CA)	*
Aeolidiidae sp. (Gray, 1827)	Aelsp	CA, WI_IR, MR, DOCKS		0.01		0.05
Berghia verrucicornis (A. Costa, 1867)	Berver	*(PI_IR inlets)	*
Spurilla neapolitana (Delle Chiaje, 1841)	Spunea	*(CA inlets)	*
Family Aplysiidae
Aplysia fasciata Poiret, 1789	Aplfas	*(inlets)	*
Family Bullidae
Bulla striata Bruguière, 1792	Bulstr	CA, CACY, MR, RC		0.05
Family Cerithiidae
Bittium latreillii (Payraudeau, 1826)	Bitlat	CA				0.02
Bittium reticulatum (da Costa, 1778)	Bitret	CA, CY, CACY, RU, CHAE, MUD, SAND, RC, WI_IR, PI_IR, DOCKS, MR	59.27	8.47	6.83	3.29	3.39
Cerithium lividulum (Risso, 1826)	Cerliv	RC		0.01
Cerithium vulgatum (Bruguière, 1792)	Cervul	CA, CY, CACY, MUD, SAND, RC, WI_IR, MR	0.06	0.88		0.1	0.14
Cerithium sp. (Bruguière, 1792)	Cersp	SAND					0.03
Family Cochliopidae
Eupaludestrina stagnorum (Gmelin, 1791)	Eupsta	CACY	0.02
Family Columbellidae
Columbella rustica (Linnaeus, 1758)	Colrus	CA, CACY		0.01
Family Conidae
Conus ventricosus Gmelin, 1791	Conven	CA, SAND, DOCKS		0.02		0.02	0.03
Family Doridiae
Doris verrucosa Linnaeus, 1758	Dorver	PI_IR	0.04
Family Dotidae
Doto coronata (Gmelin, 1791)	Dotcor	*(RU)	*
Family Ellobiidae
Myosotella myosotis (Draparnaud, 1801)	Mmyo	*(MR)	*
Ovatella firminii (Payraudeau, 1827)	Ovafir	*(PI_IR)	*
Family Haminoeidae
Haminoea hydatis (Linnaeus, 1758)	Hamhyd	CA, CACY, MUD, SAND, WI_IR, MR, RC	0.74	0.02	0.11	0.61	0.7
Haminoea navicula (da Costa, 1778)	Hamnav	MR, RC		0.01
Haminoea orbignyana (A. Férussac, 1822)	Hamorb	*(CA)	*
Haminoea orteai (Talavera, Murillo and Templado, 1987)	Hamort	MR		0.02
Family Hydrobiidae
Hydrobia acuta (Draparnaud, 1805)	Hydacu	CA, CY, CACY, RU, MUD, SAND, CHAE, WI_IR, MR	11.93		0.3	5.3	0.35
Peringia ulvae (Pennant, 1777)	Perulv	CA, CY, CACY, RU, MUD, SAND, WI_IR	0.14	0.01	2.5	2.5	0.1
Family Limapontiidae
Calliopaea bellula d’Orbigny, 1837	Calbel	CY, WI_IR, MR	0.09
Ercolania viridis (A. Costa, 1866)	Ercvir	*(CHAE)	*
Family Littorinidae
Echinolittorina punctata (Gmelin, 1791)	Echpun	CA, MR	0.35	0.01
Melarhaphe neritoides (Linnaeus, 1758)	Melner	MR	0.06
Family Mangeliidae
Mangelia sp. Risso, 1826	Mansp	WI_IR				0.12
Family Murchisonellidae
Ebala pointeli (de Folin, 1868)	Ebapoi	CA, CY, MUD			0.07		0.1
Family Muricidae
Bolinus brandaris (Linnaeus, 1758)	Bolbra	*(SAND)
Hexaplex trunculus (Linnaeus, 1758)	Hextru	CA, CY, MUD, SAND, RC, WI_IR	0.01	0.01	0.09	0.41	0.24
Stramonita haemastoma (Linnaeus, 1767)	Strhae	*(WI_IR)	*
Family Nassariidae
Tritia corniculum (Olivi, 1792)	Tricor	CA, CY, CACY, MUD, SAND, RC, WI_IR, DOCKS, MR		0.16	0.,38	1.16	0.3
Tritia corrugata (Brocchi, 1814)	Tricorr	CA, CY, CACY, MUD, SAND, WI_IR, MR	0.21	0.2	0.27	0.9	0.21
Tritia incrassata (Strøm, 1768)	Triinc	*(SAND inlets)	*
Tritia neritea (Linnaeus, 1758)	Triner	CA, CY, CACY, MUD, SAND	0.43	0.09	0.31	0.52	1.35
Tritia pellucida (Risso, 1826)	Tripel	CA, CY, CACY, MUD		0.01		0.02	0.03
Tritia reticulata (Linnaeus, 1758)	Triret	*(MUD, SAND)	*
Tritia unifasciata (Kiener, 1834)	Triuni	CA, MUD			0.04		0.07
Tritia sp. Risso, 1826	Trisp	CA					0.07
Family Oxynoidae
Oxynoe olivacea Rafinesque, 1814	Oxyoli	CA		0.02
Family Patellidae
Patella aspera Röding, 1798	Pasp	*(MR)	*
Patella caerulea Linnaeus, 1758	Pcae	*(MR)	*
Family Phasianellidae
Tricolia tenuis (Michaud, 1829)	Triten	CA		0.01
Family Philinidae
Philine quadripartita Ascanius, 1772	Phiqua	CA, CY, CACY, MUD	0.02	0.01		0.02	0.55
Family Plakobranchidae
Elysia timida (Risso, 1818)	Elytim	WI_IR	0.01
Elysia viridis (Montagu, 1804)	Elyvir	*(inlets)	*
Family Pyramidellidae
Parthenina terebellum (R. A. Philippi, 1844)	Parter	CA, MUD			0.02	0.03
Pyrgiscus rufus (Philippi, 1836)	Pyruf	*(CHAE)	*
Family Retusidae
Retusa truncatula (Bruguière, 1792)	Rettru	CA, MUD			0.02	0.11
Family Rissoidae
Alvania cimex (Linnaeus, 1758)	Alvcim	WI_IR					0.03
Pusillina lineolata (Michaud, 1830)	Puslin	CA, CY, CACY, CHAE, MUD, SAND, RC, WI_IR, MR, PI_IR	1.69	0.11	0.2	0.35	1.18
Rissoa auriscalpium (Linnaeus, 1758)	Risaur	*(CY)	*
Rissoa membranacea (J. Adams, 1800)	Rismem	CA, CY, CACY, CHAE, MUD, SAND, RC, WI_IR, MR, PI_IR	8.9	3.75	0.45	1.96	1.8
Rissoa similis Scacchi, 1836	Rissim	CA, MUD				0.26
Rissoa ventricosa Desmarest, 1814	Risven	MUD			0.02
Rissoa sp. (Desmarest, 1814)	Rissp	CA, CHAE, MUD	0.03				0.24
Family Runcinidae
Runcina capreensis Mazzarelli, 1894	Runcap	*(CY)	*
Family Siphonariidae
Siphonaria pectinata (Linnaeus, 1758)	Sipec	*(WI_IR)	*
Family Tergipedidae
Tergipes tergipes (Forsskål, 1775)	Tter	*(CY)	*
Family Trinchesiidae
Catriona maua Ev. Marcus and Er. Marcus, 1960	Catmau	*(RU)	*
Tenellia adspersa (von Nordmann, 1845)	Tads	*(RU, CY)	*
Family Trochidae
Gibbula ardens (Salis Marschlins, 1793)	Gibard	CA, CY, WI_IR, MR		0.07
Jujubinus gravinae (Dautzenberg, 1881)	Jujgra	CACY, CY, MR	0.06
Jujubinus striatus (Linnaeus, 1758)	Jujstr	CA, CY, CACY, MUD, RC, WI_IR, MR	0.02	0.08
Phorcus articulatus (Lamarck, 1822)	Phoart	MR		0.01
Phorcus richardi (Payraudeau, 1826)	Phoric	*(MR)	*
Phorcus turbinatus (Born, 1778)	Photur	*(MR, inlets)	*
Steromphala adriatica (Philippi, 1844)	Steadr	*	*
Steromphala divaricata (Linnaeus, 1758)	Stediv	*(MR, WI_IR)	*
Steromphala rarilineata (Michaud, 1829)	Sterar	*(MR, WI_IR)	*
Steromphala umbilicaris (Linnaeus, 1758)	Steumb	CA, CY, CACY, WI_IR		0.02
Steromphala varia (Linnaeus, 1758)	Stevar	CA, WI_IR		0.01
Family Truncatellidae
Truncatella subcylindrica (Linnaeus, 1767)	Trusub	CA, RU, MUD, PI_IR	0.01		0.13	0.03
Family Vitrinellidae
Circulus striatus (Philippi, 1836)	Cirstr	*(PI_IR)	*
Polyplacophora
Family Chitonidae
Chiton sp. Linnaeus, 1758	Chisp	WI_IR	0.02
Rhyssoplax olivacea (Spengler, 1797)	Rhyoli	CY, CACY, MUD, SAND, RC, WI_IR, PI_IR	0.38	0.02	0.4	0.05	0.03
Family Tonicellidae
Lepidochiton cinerea (Linnaeus, 1767)	Lepcin	*(WI_IR)	*
Scaphopoda
Family Dentaliidae
Antalis inaequicostata (Dautzenberg, 1891)	Antina	*(SAND, MUD)	*
Cephalopoda
Family Octopodidae
Octopus vulgaris Cuvier, 1797	Octvul	*(WI_IR)	*

Table 5

Results of the PERMANOVA analyses performed for the habitats sampled in 1980s period on the Bray-Curtis distance matrix calculated on log (x + 1) transformed abundance data. Only significant comparisons (<0.05) in bold and marginally significant (*) in the pairwise tests are represented. Habitat abbreviations referred to Table 1. ECV: Explained component of variation expressed in % of dissimilarity.

Source	df	SS	MS	F	p	ECV (%)
Habitat	9	57,959	6439.9	3.757	0.0001	43.70
Res	49	83,991	1714.1			56.30
Total	58	141,950
Pairwise test	t				p
Groups
CACY vs. CHAE	1.6724				0.0293
CACY vs. CY	1.986				0.0038
CACY vs. WI-IR	3.1051				0.0001
CACY vs. DOCKS	1.8606				0.0104
CACY vs. PI-IR	2.9462				0.0001
CACY vs. MR	2.8173				0.0001
CACY vs. NITR	1.8822				0.0117
CACY vs. RU	1.945				0.0061
CACY vs. SAND	1.9946				0.0028
WI-IR vs. MR	1.9547				0.0095
WI-IR vs. NITR	2.0473				0.0079
WI-IR vs. RU	1.5793				0.0591 *
PI-IR vs. MR	1.8032				0.0367
PI-IR vs. NITR	2.0368				0.0261
CY vs. PI-IR	1.4798				0.0767 *

Table 6

Average values (mean ± se) of the main descriptors of mollusk assemblage structure for the different habitats in the 1980s period in the Mar Menor lagoon. S: species richness; N: density (ind./m²); H’: Shannon diversity (bits/ind.); J’: Pielou evenness. Habitat abbreviations refer to Table 1.

Habitats	S	N	H’ (log2)	J’
CACY	6.57 ± 0.50	5413.30 ± 1070.75	1.43 ± 0.08	0.59 ± 0.03
CHAE	6 ± 2	1375 ± 300	1.46 ± 0.27	0.59 ± 0.01
CY	7 ± 2.08	2922.92 ± 1093.40	1.10 ± 0.44	0.38 ± 0.10
DOCKS	4	250	1.34	0.67
MR	3.67 ± 1.20	3197.92 ± 2038.68	0.80 ± 0.44	0.46 ± 0.18
NITR	2	75	0.92	0.92
PI-IR	7.33 ± 1.12	1088.54 ± 269.75	1.34 ± 0.22	0.49 ± 0.07
RU	5	37,300	0.1	0.04
SAND	4.33 ± 1.45	1368.75 ± 1253.59	1.24 ± 0.39	0.64 ± 0.14
WI-IR	7 ± 0.65	8797.22 ± 5264.06	1.12 ± 0.19	0.39 ± 0.07
Total	6.31 ± 0.35	5270.32 ± 1138.75	1.29 ± 0.07	0.53 ± 0.03

Table 7

Results of PERMANOVA analyses performed on Bray-Curtis distances estimated for the community structural descriptors matrix (total abundance, species richness, and Shannon diversity) in habitats sampled in the 1980s period. Only significant (<0.05) comparisons (in bold) and marginally significant (*), in pairwise tests, are represented. Habitat abbreviations refer to Table 1. ECV: Explained component of variation expressed in % of dissimilarity.

Source	df	SS	MS	F	p	ECV (%)
Habitat	9	15	2	2	0.0162	42.04
Res	49	38	0.76785			57.96
Total	58	53
Pairwise test	t				p
CACY, RU	3				0.0013
CY, RU	3.5192				0.0403
PI-IR, RU	6.0824				0.0003
RU, SAND	3.6247				0.0422
CHAE, RU	6.9479				0.0573 *

Table 8

Results of PERMANOVA analyses for testing differences in the species abundance matrix of mollusk assemblages considering the factor habitat (with 7 levels: CA, CACY, CY, WI-IR, DOCKS, SAND, and MUD), the spatial factor zone (with 5 levels: Z1–Z5), and the temporal factor period (with 5 levels: 1980s, 2002–2007, 2017, 2018, and 2019). The results of the pairwise analysis are shown in the Supplementary Material Table S6.

PERMANOVA	Df	SS	MS	F	p	ECV (%)
Period	4	20,777	67,506	34.146	0.001	15.71
Habitat	6	49,200	71,482	36.157	0.001	21.31
Zone	4	27,870	6828.5	3.454	0.001	4.74
Period × Habitat	19	11,245	5806.4	2.937	0.001	10.95
Period × Zone	15	42,298	2769.1	1.4057	0.007	4.46
Habitat × Zone	13	53,493	4132.5	2.0978	0.001	8.76
Period × Habitat × Zone	14	34,420	2458.5	1.2436	0.062	5.92
Total	548

Table 9

Average values (mean ± se) of the main descriptors of mollusk assemblage structure for the different habitats and periods studied in the Mar Menor lagoon. N: abundance (ind./m²); S: species richness; H’: Shannon diversity (bits/ind.); and J’: Pielou evenness. Habitat abbreviations are in Table 1.

Periods/Habitats	N	S	H’	J’
1982–1988	5270.3 ± 1138.8	6.3 ± 0.3	1.3 ± 0.1	0.5 ± 0.0
CY	2922.9 ± 1093.4	7 ± 2.1	1.1 ± 0.4	0.4 ± 0.1
CACY	5413.3 ± 1070.8	6.6 ± 0.5	1.4 ± 0.1	0.6 ± 0.0
SAND	1368.8 ± 1253.6	4.3 ± 1.5	1.2 ± 0.4	0.6 ± 0.1
WI-IR	8797.2 ± 5264.1	7 ± 0.6	1.1 ± 0.2	0.4 ± 0.1
DOCKS	250	4	1.3	0.7
2002–2007	6341.7 ± 1955.1	3.8 ± 0.4	0.7 ± 0.1	0.5 ± 0.0
CA	3056.6 ± 1302.2	3.6 ± 0.6	0.8 ± 0.1	0.6 ± 0.0
CY	1104.9 ± 327.0	3.0 ± 0.5	0.8 ± 0.1	0.7 ± 0.0
CACY	2612.8 ± 1073.7	9.5 ± 3.1	1.5 ± 0.7	0.5 ± 0.1
MUD	1183.3	12	2	0.6
SAND	841.7 ± 313.7	2.7 ± 0.3	0.6 ± 0.4	0.4 ± 0.2
WI-IR	9280.3 ± 3307.8	4.2 ± 1.7	0.5 ± 0.2	0.4 ± 0.0
2017	779.0 ± 169.4	2.9 ± 0.1	0.9 ± 0.1	0.7 ± 0.0
CA	619.4 ± 248.8	3.4 ± 0.6	1.1 ± 0.2	0.7 ± 0.1
CY	1843.2 ± 703.9	5.6 ± 0.8	2.0 ± 0.1	0.8 ± 0.0
MUD	453.9 ± 61.6	3.2 ± 0.2	1.1 ± 0.1	0.7 ± 0.0
SAND	554.2 ± 347.9	1.8 ± 0.4	0.5 ± 0.2	0.8 ± 0.1
WI-IR	1492.2 ± 780.2	2.3 ± 0.2	0.5 ± 0.1	0.5 ± 0.0
DOCKS	671.9 ± 166.5	1.6 ± 0.2	0.2 ± 0.1	0.5 ± 0.1
2018	1099.3 ± 116.5	4.8 ± 0.2	1.5 ± 0.1	0.7 ± 0.0
CA	901.3 ± 123.5	5.7 ± 0.3	1.8 ± 0.1	0.8 ± 0.0
CY	2746.0 ± 961.7	5.2 ± 1.3	1.6 ± 0.3	0.7 ± 0.0
MUD	802.6 ± 102.6	4.8 ± 0.3	1.6 ± 0.1	0.8 ± 0.0
SAND	1830.0 ± 1506.5	4.4 ± 0.7	1.3 ± 0.4	0.6 ± 0.2
WI-IR	1887.9 ± 379.8	5.2 ± 0.6	1.4 ± 0.1	0.7 ± 0.0
DOCKS	244.6 ± 49.5	1.5 ± 0.1	0.3 ± 0.1	0.6 ± 0.1
2019	631.9 ± 64.3	3.7 ± 0.2	1.2 ± 0.1	0.8 ± 0.0
CA	644.7 ± 94.8	3.9 ± 0.3	1.3 ± 0.1	0.8 ± 0.0
CY	1253.9 ± 231.5	3.4 ± 0.6	1.1 ± 0.2	0.7 ± 0.1
CACY	312.5 ± 182.7	2.5 ± 1.2	0.8 ± 0.5	0.9 ± 0.1
MUD	507.3 ± 125.2	3.8 ± 0.4	1.3 ± 0.2	0.8 ± 0.0
SAND	540.0 ± 268.9	3.4 ± 0.5	1.1 ± 0.1	0.7 ± 0.1
WI-IR	862.5 ± 280.9	4.4 ± 0.8	1.6 ± 0.3	0.9 ± 0.0
DOCKS	228.6 ± 80.4	1.4 ± 0.2	0.3 ± 0.2	0.7 ± 0.1

Table 10

PERMANOVA analyses (F-values and associated significance) and pairwise tests performed on assemblage structural parameters: richness (S), density (D) (ind./m²), and diversity (H’) (bits/ind.), considering the factors period (with four levels, 1980s, 2002–2007, 2017, 2018, and 2019) and habitat (with 7 levels, CACY, CA, CY, MUD, SAND, WI-IR, and DOCKS). Significant values (p < 0.05) are in bold. In pairwise tests, only significant differences are represented. Abbreviations of habitats are in Table 1. ECV: Explained component of variation expressed in % of dissimilarity.

Source		Df	SS	MS	F	p	ECV (%)
Density (ind./m2)
Habitat		6	3190.3	531.71	3.94	0.0005	17.06
Period		4	1505.2	376.31	2.78	0.0244	11.55
Period × Habitat		19	5001.2	263.22	1.95	0.0076	15.23
Res		518	69,896	134.93			56.14
Species richness (S)		Df	SS	MS	F	p
Habitat		6	7832.5	10,305.4	5.11	0.0001	17.42
Period		4	8138.6	2034.7	7.97	0.0001	19.7
Period × Habitat		19	10,438	549.36	2.15	0.0016	14.45
Res			132,120	255.05			48.40
Shannon Index (H’)		Df	SS	MS	F	p
Habitat		6	8354.2	1392.4	4.97	0.0005	19.59
Period		4	3019.9	754.98	2.42	0.0428	11.46
Period × Habitat			10,954	576.55	1.85	0.0197	15.48
Res		19	130,570	310.89			53.63
Pairwise Test	Density (ind./m2)		Species richness (S)		Shannon Index (H’)
Habitat × Period	t	p	t	p	t	p
CA
2002–2007 vs. 2018	1.92	0.0521	5.64	0.0001	3.77	0.0001
2002–2007 vs. 2019			2.16	0.028	2.56	0.0099
2017 vs. 2018			3.44	0.001	3.38	0.0015
2018 vs. 2019	2.79	0.0049	3.83	0.0001	2.05	0.0371
CACY
2002–2007 vs. 2019			1.46	0.014
2019 vs. 1980s	3.27	0.003	4.06	0.0003
CY
2002–2007 vs. 2017	2.13	0.035	3.01	0.0037	3.08	0.0033
2002–2007 vs. 2018	2.24	0.029
2002–2007 vs. 1980s			2.18	0.034
2017 vs. 2019			2.13	0.048	3.10	0.0078
2017 vs. 1980s					2.94	0.0138
MUD
2002–2007 vs. 2017			2.14	0.012
2002–2007 vs. 2018			1.66	0.053
2017 vs. 2018	3.04	0.0028	4.38	0.0001	3.44	0.0001
2018 vs. 2019	2.08	0.003	2.20	0.024
SAND
2017 vs. 2018			3.04	0.012
2017 vs. 2019			2.33	0.043
WI-IR
2002–2007 vs. 2017	2.67	0.008
2002–2007 vs. 2018			2.26	0.0238
2002–2007 vs. 2019					2.53	0.021
2002–2007 vs. 1980s			2.92	0.009
2017 vs. 2018			4.17	0.0001	3.68	0.0002
2017 vs. 2019			2 en	0.024	4.53	0.0001
2017 vs. 1980s	3.14	0.002	5.08	0.0001	1.79	0.0571
2018 vs. 1980s	1.75	0.048	1.89	0.057
2019 vs. 1980s	2.51	0.02	2.08	0.046
DOCKS
2017 vs. 2018	2.09	0.048
2017 vs. 2019	2.14	0.037
2018 vs. 1980s			2.38	0.038

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/w17050657/s1, Supplementary Material Table S1: Species recorded in the Mar Menor in the period 1980s–2019. Mean SE: density of individuals (ind./m²) and standard error; D%: dominance; F%: frequency, of each species in each habitat and period; Supplementary Material Table S2: Percentage of dominance of the species recorded in the Mar Menor in the study periods; Supplementary Material Table S3: Percentage of dominance of the mollusk species collected in the different habitats studied in the Mar Menor; Supplementary Material Table S4: Percentage of total dominance of the mollusk species collected in the Mar Menor in the study period; Supplementary Material Table S5: Results of the SIMPER analysis, showing species that mostly contributed to dissimilarity of the samples for each period, habitat and zone in the composition of mollusk assemblages; Supplementary Material Table S6: PERMANOVA and Pair-wise analyses for testing differences in mollusk assemblages performed for Habitat (CA, CACY, CY, WI-IR, DOCKS, SAND, MUD), Zone (Z1–Z5) and Period (1980s, 2002–2007, 2017, 2018, 2019) factors; Supplementary Material Table S7: Results of the SIMPER analysis, showing species that mostly contributed to dissimilarity between periods for each habitat in the mollusk assemblages.

References

1. Pérez-Ruzafa, A.; Pérez-Ruzafa, I.M.; Newton, A.; Marcos, C. Coastal lagoons: Environmental variability, ecosystem complexity, and goods and services uniformity. Coasts and Estuaries, the Future; Wolanski, E.; Day, J.; Elliott, M.; Ramesh, R. Elsevier: Amsterdam, The Netherlands, 2019; pp. 253-276.

2. UNESCO. Coastal Lagoons Research, Present and Future; UNESCO Technical Papers in Marine Science, 33 UNESCO: Paris, France, 1981.

3. Tagliapietra, D.; Sigovini, M.; Volpi-Ghirardini, A. A review of terms and definitions to categorise estuaries, lagoons and associated environments. Mar. Freshw. Res.; 2009; 60, pp. 497-509. [DOI: https://dx.doi.org/10.1071/MF08088]

4. Anthony, A.; Atwood, J.; August, P.; Byron, C.; Cobb, S.; Foster, C.; Fry, A.; Gold, A.; Hagos, K.; Heffner, L. et al. Coastal lagoons and climate change: Ecological and social ramifications in U.S. Atlantic and Gulf coast ecosystems. Ecol. Soc.; 2009; 14, 8.Available online: http://www.ecologyandsociety.org/vol14/iss1/art8/ (accessed on 20 January 2021). [DOI: https://dx.doi.org/10.5751/ES-02719-140108]

5. Russi, D.; ten Brink, P.; Farmer, A.; Badura, T.; Coastes, D.; Förster, J.; Kumar, R.; Davidson, N. The Economics of Ecosystems and Biodiversity for Water and Wetlands; IEEP: London, UK, Brussels, Belgium, Ramsar Secretariat: Gland, Switzerland, 2013.

6. Pérez-Ruzafa, A.; Pérez-Marcos, M.; Marcos, C. Coastal lagoons in focus: Their environmental and socioeconomic importance. J. Nat. Conserv.; 2020; 57, 125886. [DOI: https://dx.doi.org/10.1016/j.jnc.2020.125886]

7. Pérez-Ruzafa, A.; Molina-Cuberos, G.J.; García-Oliva, M.; Umgiesser, G.; Marcos, C. Why coastal lagoons are so productive? Physical bases of fishing productivity in coastal lagoons. Sci. Total Environ.; 2024; 922, 171264. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2024.171264]

8. European Environment Agency. Ecosystem accounting and the cost of biodiversity losses. The Case of Coastal Mediterranean Wetlands; EEA Technical Report 3/2010 EEA: Copenhagen, Denmark, 2010.

9. De Wit, R. Biodiversity of coastal lagoon ecosystems and their vulnerability to global change. Ecosystems Biodiversity; BoD—Books on Demand: Norderstedt, Germany, 2011; pp. 29-40.

10. Janas, U.; Burska, D.; Kendzierska, H.; Pryputniewicz-Flis, D.; Łukawska-Matuszewska, K. Importance of benthic macrofauna and coastal biotopes for ecosystem functioning. Oxygen and nutrient fluxes in the coastal zone. Estuar. Coast. Shelf Sci.; 2019; 225, 106238. [DOI: https://dx.doi.org/10.1016/j.ecss.2019.05.020]

11. Sigovini, M. Multiscale Dynamics of Zoobenthic Communities and Relationships with Environmental Factors in the Lagoon of Venice. Ph.D. Thesis; Università Ca’Foscari di Venezia: Venice, Italy, 2011.

12. Quispe, J.I. Dinámica Espacio-Temporal del Ictioplancton del Mar Menor (SE España). Ph.D. Thesis; University of Murcia: Murcia, Spain, 2014.

13. Paraskevopoulou, S.; Monokrousos, N.; Kappas, I.; Abatzopoulos, T.J. Spatio-temporal variability of benthic macrofauna in a coastal lagoon assessed by ecological interaction networks. Community Ecol.; 2015; 16, pp. 10-22. [DOI: https://dx.doi.org/10.1556/168.2015.16.1.2]

14. Rueda, J.L.; Gofas, S.; Urra, J.; Salas, C. A highly diverse molluscan assemblage associated with eelgrass beds (Zostera marina L.) in the Alboran Sea: Micro-habitat preference, feeding guilds and biogeographical distribution. Sci. Mar.; 2009; 73, (Suppl. S4), pp. 679-700. [DOI: https://dx.doi.org/10.3989/scimar.2009.73n4679]

15. De Jesús-Carrillo, R.M.; Ocaña, F.A.; Hernández-Ávila, I.; Mendoza-Carranza, M.; Sánchez, A.J.; Barba-Macías, E. Mollusk distribution in four habitats along a salinity gradient in a coastal lagoon from the Gulf of Mexico. J. Nat. Hist.; 2020; 54, pp. 1257-1270. [DOI: https://dx.doi.org/10.1080/00222933.2020.1785030]

16. Avramidis, P.; Iliopoulos, G.; Kontopoulos, N.; Panagiotaras, D.; Barouchas, P.; Nikolaou, K.; Papadopoulou, P. Depositional environments, sediment characteristics, palaeoecological analysis and environmental assessment of an internationally protected shallow Mediterranean lagoon, Gialova Lagoon—Navarino Bay, Greece. Earth Environ. Sci. Trans. R. Soc. Edinb.; 2014; 105, pp. 189-206. [DOI: https://dx.doi.org/10.1017/S1755691015000031]

17. Currás, A.; Ghilardi, M.; Peche-Quilichini, K.; Fagel, N.; Vacchi, M.; Delanghe, D.; Ottaviani, J.C. Reconstructing past landscapes of the eastern plain of Corsica (NW Mediterranean) during the last 6000 years based on molluscan, sedimentological and palynological analyses. J. Archaeol. Sci. Rep.; 2017; 12, pp. 755-769. [DOI: https://dx.doi.org/10.1016/j.jasrep.2016.09.016]

18. Mars, P. Recherches sur quelques étangs du litoral méditerranéen francais et sur leurs faunes malacologiques. Vie Milieu; 1966; 20, pp. 1-359.

19. Nicolaidou, A.; Bourgoutzani, F.; Zenetos, A.; Guelorget, O.; Perthuisot, J.P. Distribution of molluscs and polychaetes in coastal lagoons in Greece. Estuar. Coast. Shelf Sci.; 1988; 26, pp. 337-350. [DOI: https://dx.doi.org/10.1016/0272-7714(88)90016-9]

20. Millet, B.; Guelorget, O. Relationships between benthic communities and physical environment in a lagoon ecosystem. J. Coast. Res.; 1993; 9, pp. 378-389.

21. Bernasconi, M.P.; Stanley, D.J. Molluscan biofacies and their environmental implications, Nile delta lagoons, Egypt. J. Coast. Res.; 1994; 10, pp. 440-465.

22. Koutsoubas, D.; Dounas, C.; Arvanitidis, C.; Kornilios, S.; Petihakis, G.; Triantafyllou, G.; Eleftheriou, A. Macrobenthic community structure and disturbance assessment in Gialova Lagoon, Ionian Sea. ICES J. Mar. Sci.; 2000; 57, pp. 1472-1480. [DOI: https://dx.doi.org/10.1006/jmsc.2000.0905]

23. Tlig-Zouari, S.; Maamouri-Mokhtar, F. Macrozoobenthic species composition and distribution in the Northern lagoon of Tunis. Trans. Waters Bull.; 2008; 2, pp. 1-15.

24. Evagelopoulos, A.; Koutsoubas, D.; Gerovasileiou, V.; Katsiaras, N. Macrobenthic molluscs from a marine-lagoonal environmental transition in Lesvos Island (Greece). Biodivers. Data J.; 2016; 4, e9541. [DOI: https://dx.doi.org/10.3897/BDJ.4.e9541]

25. Orabi, O.H.; El-Badry, A.E.M.A.; Alhejoj, I. Response of mollusk assemblages to environmental conditions: A case study from the Burullus Lagoon, Egypt. J. Geol. Soc. India; 2018; 91, pp. 583-588. [DOI: https://dx.doi.org/10.1007/s12594-018-0908-8]

26. Bellino, A.; Mangano, M.C.; Baldantoni, D.; Russell, B.D.; Mannino, A.M.; Mazzola, A.; Vizzini, S.; Sarà, G. Seasonal patterns of biodiversity in Mediterranean coastal lagoons. Divers. Distrib.; 2019; 25, pp. 1512-1526. [DOI: https://dx.doi.org/10.1111/ddi.12942]

27. Leonardi, M.; Bergamasco, A.; Giacobbe, S.; Azzaro, F.; Cosentino, A.; Crupi, A.; Lanza, A.; Randazzo, G.; Crisafi, E. A four decades multiparametric investigation in a Mediterranean dynamic ecosystem: Mollusc assemblages answer to the environmental changes. Estuar. Coast. Shelf Sci.; 2020; 234, 106625. [DOI: https://dx.doi.org/10.1016/j.ecss.2020.106625]

28. El Asri, F.; Martin, D.; Errhif, A.; Tamsouri, M.N.; Maanan, M.; Zidane, H. Community structure and spatial patterns of soft-bottom macrozoobenthos in Oualidia Lagoon, Moroccan Atlantic. Thalass. Int. J. Mar. Sci.; 2021; 37, pp. 119-129. [DOI: https://dx.doi.org/10.1007/s41208-020-00263-3]

29. El Kamcha, R.; Boutoumit, S.; Bououarour, O.; Pouzet, P.; Maanan, M.; Benhoussa, A.; Bazairi, H. New insights into the benthic composition and structure in a southern-west Mediterranean coastal lagoon after restoration actions: Spatial and seasonal patterns. Reg. Stud. Mar. Sci.; 2023; 60, 102820. [DOI: https://dx.doi.org/10.1016/j.rsma.2023.102820]

30. Bachelet, G.; De Montaudouin, X.; Auby, I.; Labourg, P.J. Seasonal changes in macrophyte and macrozoobenthos assemblages in three coastal lagoons under varying degrees of eutrophication. ICES J. Mar. Sci.; 2000; 57, pp. 1495-1506. [DOI: https://dx.doi.org/10.1006/jmsc.2000.0902]

31. Macali, A.; Conde, A.; Smriglio, C.; Mariottini, P.; Crocetta, F. The evolution of the molluscan biota of Sabaudia Lake: A matter of human history. Sci. Mar.; 2013; 77, pp. 649-662. [DOI: https://dx.doi.org/10.3989/scimar.03858.05M]

32. Elgharsalli, R.; Rabaoui, L.; Aloui-Bejaoui, N. Community structure of a molluscan assemblage in an anthropized environment, Hammamet Marina, North-Eastern Tunisia. Turk. J. Fish. Aquat. Sci.; 2015; 15, pp. 757-766. [DOI: https://dx.doi.org/10.4194/1303-2712-v15_3_20]

33. Fortunato, H. Mollusks: Tools in environmental and climate research. Am. Malacol. Bull.; 2015; 33, pp. 310-324. [DOI: https://dx.doi.org/10.4003/006.033.0208]

34. Wakkaf, T.; El Zrelli, R.; Kedzierski, M.; Balti, R.; Shaiek, M.; Mansour, L.; Tlig-Zouari, S.; Bruzaud, S.; Rabaoui, L. Microplastics in edible mussels from a southern Mediterranean lagoon: Preliminary results of seawater-mussel transfer and implications for environmental protection and seafood safety. Mar. Pollut. Bull.; 2020; 158, 111355. [DOI: https://dx.doi.org/10.1016/j.marpolbul.2020.111355]

35. Abdelhady, A.A. Anthropogenic-induced environmental changes in the Nile-delta and their consequences on molluscan biodiversity and community structure. Ecol. Indic.; 2021; 126, 107654. [DOI: https://dx.doi.org/10.1016/j.ecolind.2021.107654]

36. Sandonnini, J.; Del Pilar-Ruso, Y.; Valverde-Urrea, M.; Giménez-Casalduero, F. Infauna evolution of the invertebrate community after a severe eutrophic crisis in the coastal lagoon of the Mar Menor (W Mediterranean). Reg. Stud. Mar. Sci.; 2024; 79, 103824. [DOI: https://dx.doi.org/10.1016/j.rsma.2024.103824]

37. Boscolo Brusà, R.; Cacciatore, F.; Ponis, E.; Molin, E.; Delaney, E. Clam culture in the Venice lagoon: Stock assessment of Manila clam (Venerupis philippinarum) populations at a nursery site and management proposals to increase clam farming sustainability. Aquat. Living Resour.; 2013; 26, pp. 1-10. [DOI: https://dx.doi.org/10.1051/alr/2013042]

38. Gangnery, A.; Chabirand, J.M.; Lagarde, F.; Le Gall, P.; Oheix, J.; Bacher, C.; Buestel, D. Growth model of the Pacific oyster, Crassostrea gigas, cultured in Thau Lagoon (Méditerranée, France). Aquaculture; 2003; 215, pp. 267-290. [DOI: https://dx.doi.org/10.1016/S0044-8486(02)00351-4]

39. Rosique, M.J.; Cano, J.; Rocamora, J. Variación estacional de la composición bioquímica y del índice de condición de la ostra plana Ostrea edulis L., del Mar Menor (Murcia, SE España). Iberus; 1995; 13, pp. 9-22.

40. Chiesa, S.; Marzano, F.N.; Minervini, G.; De Lucrezia, D.; Baccarani, G.; Bordignon, G.; Argese, E. The invasive Manila clam Ruditapes philippinarum (Adams and Reeve, 1850) in Northern Adriatic Sea: Population genetics assessed by an integrated molecular approach. Fish. Res.; 2011; 110, pp. 259-267. [DOI: https://dx.doi.org/10.1016/j.fishres.2011.04.013]

41. Crocetta, F.; Turolla, E. Mya arenaria Linné, 1758 (Mollusca: Bivalvia) in the Mediterranean Sea: Its distribution revisited. J. Biol. Res.; 2011; 16, pp. 188-193.

42. Wolf, M.A.; Buosi, A.; Juhmani, A.S.F.; Sfriso, A. Shellfish import and hull fouling as vectors for new red algal introductions in the Venice Lagoon. Estuar. Coast. Shelf Sci.; 2018; 215, pp. 30-38. [DOI: https://dx.doi.org/10.1016/j.ecss.2018.09.028]

43. Boudouresque, C.F.; Blanfuné, A.; Pergent, G.; Pergent-Martini, C.; Perret-Boudouresque, M.; Thibaut, T. Impacts of marine and lagoon aquaculture on macrophytes in Mediterranean benthic ecosystems. Front. Mar. Sci.; 2020; 7, 218. [DOI: https://dx.doi.org/10.3389/fmars.2020.00218]

44. Arvanitidis, C.; Atzigeorgiou, G.; Koutsoubas, D.; Dounas, C.; Eleftheriou, A.; Koulouri, P. Mediterranean lagoons revisited: Weakness and efficiency of the rapid biodiversity assessment techniques in a severely fluctuating environment. Biodivers. Conserv.; 2005; 14, pp. 2347-2359. [DOI: https://dx.doi.org/10.1007/s10531-004-1668-x]

45. Pérez-Ruzafa, A.; Marcos, C.; Pérez-Ruzafa, I.M.; Barcala, E.; Hegazi, M.I.; Quispe, J. Detecting changes resulting from human pressure in a naturally quick-changing and heterogeneous environment: Spatial and temporal scales of variability in coastal lagoons. Estuar. Coast. Shelf Sci.; 2007; 75, pp. 175-188. [DOI: https://dx.doi.org/10.1016/j.ecss.2007.04.030]

46. Pérez-Ruzafa, A.; Marcos, C. Coastal lagoons in the context of water management in Spain and Europe. Sustainable Use and Development of Watersheds; Gönenc, I.E.; Vadineanu, A.; Wolflin, J.P.; Russo, R.C. NATO Science for Peace and Security Series; Springer: Dordrecht, The Netherlands, 2008; pp. 299-321.

47. Ghezzo, M.; De Pascalis, F.; Umgiesser, G.; Zemlys, P.; Sigovini, M.; Marcos, C.; Pérez-Ruzafa, A. Connectivity in three European coastal lagoons. Estuaries Coasts; 2015; 38, pp. 1764-1781. [DOI: https://dx.doi.org/10.1007/s12237-014-9908-0]

48. García-Oliva, M.; Pérez-Ruzafa, Á.; Umgiesser, G.; McKiver, W.; Ghezzo, M.; De Pascalis, F.; Marcos, C. Assessing the hydrodynamic response of the Mar Menor lagoon to dredging inlets interventions through numerical modelling. Water; 2018; 10, 959. [DOI: https://dx.doi.org/10.3390/w10070959]

49. Aravio-Torre, J.; Arévalo, A. La salinidad del Mar Menor, sus variaciones. Algunas consideraciones sobre el intercambio de aguas con el Mar Mediterráneo. Boletín. Inst. Español Oceanogr.; 1971; 146, pp. 1-19.

50. Pérez-Ruzafa, A.; Morkune, R.; Marcos, C.; Perez-Ruzafa, I.M.; Razinkovas-Baziukas, A. Can an oligotrophic coastal lagoon support high biological productivity? Sources and pathways of primary production. Mar. Environ. Res.; 2020; 153, 104824. [DOI: https://dx.doi.org/10.1016/j.marenvres.2019.104824] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/31735509]

51. Pérez-Ruzafa, A. Estudio Ecológico y Bionómico de los Poblamientos Bentónicos del Mar Menor (Murcia, SE de España). Ph.D. Thesis; University of Murcia: Murcia, Spain, 1989.

52. Pérez-Ruzafa, A.; Ros, J.; Marcos, C.; Ballester, R.; Pérez-Ruzafa, I.M. Distribution and biomass of the macrophyte beds in a hypersaline coastal lagoon (the Mar Menor, SE Spain), and its recent evolution following major environmental changes. International Workshop on Posidonia Beds; Bouderesque, C.F.; Meinesz, A.; Fresi, E.; Gravez, V. GIS Posidonie: Marseille, France, 1989; Volume 2, pp. 49-62.

53. Pérez-Ruzafa, A.; Marcos, C.; Bernal, C.M.; Quintino, V.; Freitas, R.; Rodrigues, A.M.; García-Sánchez, M.; Pérez-Ruzafa, A. Cymodocea nodosa vs. Caulerpa prolifera: Causes and consequences of a long-term history of interaction in macrophyte meadows in the Mar Menor coastal lagoon (Spain, southwestern Mediterranean). Estuar. Coast. Shelf Sci.; 2012; 110, pp. 101-115. [DOI: https://dx.doi.org/10.1016/j.ecss.2012.04.004]

54. Pérez-Ruzafa, A.; Hegazi, M.I.; Pérez-Ruzafa, I.M.; Marcos, C. Differences in spatial and seasonal patterns of macrophyte assemblages between a coastal lagoon and the open sea. Mar. Environ. Res.; 2008; 65, pp. 291-314. [DOI: https://dx.doi.org/10.1016/j.marenvres.2007.11.008] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/18187188]

55. Pérez-Ruzafa, A.; Dezileau, L.; Martínez-Sánchez, M.J.; Pérez-Sirvent, C.; Pérez-Marcos, M.; von Grafenstein, U.; Marcos, C. Long-term sediment records reveal over three thousand years of heavy metal inputs in the Mar Menor coastal lagoon (SE Spain). Sci. Total Environ.; 2023; 902, 166417. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2023.166417]

56. Pérez-Ruzafa, A.; García-Charton, J.A.; Barcala, E.; Marcos, C. Changes in benthic assemblages as a consequence of coastal works in a coastal lagoon: The Mar Menor (Spain, Western Mediterranean). Mar. Pollut. Bull.; 2006; 53, pp. 107-120. [DOI: https://dx.doi.org/10.1016/j.marpolbul.2005.09.014]

57. Pérez-Ruzafa, A.; Campillo, S.; Fernández-Palacios, J.M.; García-Lacunza, A.; García-Oliva, M.; Ibañez, H.; Marcos, C. Long-term dynamic in nutrients, chlorophyll a, and water quality parameters in a coastal lagoon during a process of eutrophication for decades, a sudden break and a relatively rapid recovery. Front. Mar. Sci.; 2019; 6, 26. [DOI: https://dx.doi.org/10.3389/fmars.2019.00026]

58. Schlieper, C. Research Methods in Marine Biology; University of Washington Press: Seattle, WA, USA, 1972; Volume XIII, 356p.

59. Holme, N.A.; Mcintyre, A.D. Methods for the Study of Marine Benthos; 2nd ed. Blackwell: Oxford, UK, 1984; Volume XII, 387p.

60. Hulbert, S.J. Pseudoreplication and the design of ecological field experiments. Ecol. Monogr.; 1984; 54, pp. 187-211. [DOI: https://dx.doi.org/10.2307/1942661]

61. Underwood, A.J. Experiments in Ecology; Cambridge University Press: Cambridge, MA, USA, 1997; 522p.

62. Anderson, M.J. A new method for non-parametric multivariate analysis of variance. Austral Ecol.; 2001; 26, pp. 32-46.

63. Anderson, M.J.; Diebel, C.E.; Blom, W.M.; Landers, T.J. Consistency and variation in kelp holdfast assemblages: Spatial patterns of biodiversity for the major phyla at different taxonomic resolutions. J. Exp. Mar. Biol. Ecol.; 2005; 320, pp. 35-56. [DOI: https://dx.doi.org/10.1016/j.jembe.2004.12.023]

64. Pérez-Ruzafa, A.; Fernández, A.I.; Marcos, C.; Gilabert, J.; Quispe, J.I.; García-Charton, J.A. Spatial and temporal variations of hydrological conditions, nutrients, and chlorophyll a in a Mediterranean coastal lagoon (Mar Menor, Spain). Hydrobiologia; 2005; 550, pp. 11-27. [DOI: https://dx.doi.org/10.1007/s10750-005-4356-2]

65. Pérès, J.M.; Picard, J. Nouveau Manuel de Bionomie Benthique de la Mer Méditerranée; Station Marine d’Endoume: Marseille, France, 1964.

66. Augier, H. Inventory and Classification of Marine Benthic Biocenoses of the Mediterranean; Council of Europe: Strasbourg, France, 1982; pp. 18-50.

67. Meinesz, A.; Boudouresque, C.F.; Falconetti, C.; Astier, J.M.; Bay, D.; Blanc, J.J.; Bourcier, M.; Cinelli, F.; Cirik, S.; Cristiani, G. et al. Normalisation des symboles pour la réprésentation et la cartographie des biocénoses benthiques littorales de Méditerranée. Ann. Inst. Océanogr.; 1983; 59, pp. 155-172.

68. Nordsieck, F. Die Europäischen Meeres-Gehäuseschnecken (Prosobranchia): Vom Eismeer bis Kapverden, Mittelmeer und Schwarzes Meer; 2nd ed. Gustav Fischer Verlag: Stuttgart, Germany, 1982.

69. Templado, J. Moluscos de las Formaciones de Fanerógamas Marinas en las Costas del Cabo de Palos (Murcia). Ph.D. Thesis; Complutense University of Madrid: Madrid, Spain, 1982.

70. Murillo, L.; Talavera, P. Aportación a la malacología de una laguna litoral: El Mar Menor (Murcia). Iberus; 1983; 3, pp. 15-28.

71. Ponder, W.F. A review of the genera of the Rissoidae (Mollusca: Mesogastropoda: Rissoacea). Rec. Aust. Mus.; 1985; 4, pp. 1-221. [DOI: https://dx.doi.org/10.3853/j.0812-7387.4.1985.100]

72. Riedl, R. Fauna y Flora del mar Mediterráneo: Una Guía Sistemática para Biólogos y Naturalistas; Omega: Barcelona, Spain, 1986.

73. Marín, A.; Ros, J. Catálogo preliminar de los gasterópodos marinos del sudeste español. Iberus; 1987; 7, pp. 137-145.

74. Bellido, M. Fauna Ibérica: Invertebrados y Vertebrados: Claves Dicotómicas; Rueda: Madrid, Spain, 1989.

75. Murillo, L. Adiciones a la malacofauna del Mar Menor (Murcia). Not. Soc. Española Malacol.; 1995; 23, pp. 35-39.

76. Gofas, S.; Salas, C.; Moreno, D. Moluscos Marinos de Andalucía; Servicio de Publicaciones e Intercambio Científico de la Universidad de Málaga: Málaga, Spain, 2011; Volume 2.

77. WoRMS Editorial Board. World Register of Marine Species. Available online: https://www.marinespecies.org (accessed on 19 December 2024).

78. Marine Species Traits Editorial Board. Marine Species Traits. Available online: http://www.marinespecies.org/traits (accessed on 2 August 2022).

79. Anderson, M.J. Permutational Multivariate Analysis of Variance (PERMANOVA); Wiley StatsRef: Statistics Reference Online: Hoboken, NJ, USA, 2017; pp. 1-15. [DOI: https://dx.doi.org/10.1002/9781118445112.stat07841]

80. Clarke, K.; Gorley, R. PRIMER v7: User Manual/Tutorial; PRIMER-E: Plymouth, UK, 2015.

81. Magurran, A. Measuring Biological Diversity; John Wiley & Sons: New York, NY, USA, 2004.

82. ter Braak, C.J.F. Update Notes: Canoco v. 3.15; Agricultural Mathematics Group DLO: Wageningen, The Netherlands, 1997.

83. ter Braak, C.J.F.; Prentice, I.C. A theory of gradient analysis. Adv. Ecol. Res.; 1988; 18, pp. 271-317.

84. R Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2018.

85. Anderson, M.J.; Gorley, R.N.; Clarke, K.R. PERMANOVA+ for PRIMER: Guide to Software and Statistical Methods; PRIMER-E: Plymouth, UK, 2008.

86. Underwood, A.J.; Petraitis, P.S. Structure of intertidal assemblages in different locations: How can local processes be compared?. Species Diversity in Ecological Communities: Historical and Geographical Perspectives; Ricklefs, R.E.; Schluter, D. University of Chicago Press: Chicago, IL, USA, 1993; pp. 38-51.

87. Pérez-Ruzafa, A.; Gilabert, J.; Gutiérrez, J.M.; Fernández, A.I.; Marcos, C.; Sabah, S. Evidence of a planktonic food web response to changes in nutrient input dynamics in the Mar Menor coastal lagoon, Spain. Hydrobiologia; 2002; 475, pp. 359-369. [DOI: https://dx.doi.org/10.1023/A:1020343510060]

88. Fernández-Alías, A.; Marcos, C.; Quispe, J.I.; Sabah, S.; Pérez-Ruzafa, A. Population dynamics and growth in three scyphozoan jellyfishes, and their relationship with environmental conditions in a coastal lagoon. Estuar. Coast. Shelf Sci.; 2020; 243, 106901. [DOI: https://dx.doi.org/10.1016/j.ecss.2020.106901]

89. Fernández-Alías, A.; Montaño-Barroso, T.; Conde-Caño, M.R.; Manchado-Pérez, S.; López-Galindo, C.; Quispe-Becerra, J.I.; Marcos, C.; Pérez-Ruzafa, A. Nutrient overload promotes the transition from top-down to bottom-up control and triggers dystrophic crises in a Mediterranean coastal lagoon. Sci. Total Environ.; 2022; 846, 157388. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2022.157388]

90. Olmo, R.; Ros, J.D. La malacocenosis del Mar Menor. Estudio y comparación con comunidades de medios lagunares semejantes. Actas IV Simpósio Ibérico Estud. Benthos Mar.; 1984; 1, pp. 253-260.

91. Davis, T.R.; Harasti, D.; Kelaher, B.; Smith, S.D.A. Spatial and temporal variation in subtidal molluscan diversity amongst temperate estuarine habitats. Mar. Ecol.; 2017; 38, e12428. [DOI: https://dx.doi.org/10.1111/maec.12428]

92. Kjerfve, B. Coastal lagoons. Elsevier Oceanography Series; Elsevier: Amsterdam, The Netherlands, 1994; pp. 1-8.

93. Guelorget, O.; Perthuisot, J.P. Le domaine paralique. Expressions géologiques, biologiques et économiques du confinement. Trav. Lab. Géologie; 1983; 16, pp. 1-136.

94. Guelorget, O.; Frisoni, G.F.; Perthuisot, J.P. Zonation biologique des milieux lagunaires: Definition d’une échelle de confinement dans le domaine paralique méditerranéen. J. Rech. Océanographique; 1983; 8, pp. 15-35.

95. Pérez-Ruzafa, A.; Marcos, C. La teoría del confinamiento como modelo para explicar la estructura y zonación horizontal de las comunidades bentónicas en las lagunas costeras. Publicaciones Espec. Inst. Español Oceanogr.; 1993; 11, pp. 347-358.

96. Guelorget, O.; Perthuisot, J.P. Paralic Ecosystems Biological Organization and Functionning. Vie Milieu; 1992; 42, pp. 215-251.

97. Basset, A.; Galuppo, N.; Sabetta, L. Environmental heterogeneity and benthic macroinvertebrate guilds in Italian lagoons. Transitional Waters Bull.; 2006; 1, pp. 48-63.

98. Ateş, A.S.; Doğan, A.; Acar, S.; Büyükateş, Y.; Dağlı, E.; Bakır, A.K.; Mülayim, A. Seasonal Effects of Environmental Variables on Molluscan Communities in Çardak Lagoon (Turkish Straits). Russ. J. Mar. Biol.; 2023; 49, pp. 215-228. [DOI: https://dx.doi.org/10.1134/S1063074023030021]

99. Meinesz, A. Contribution a l’Etude des Caulerpales (Chlorophytes). Ph.D. Thesis; Universite de Nice: Nice, France, 1979; 262p.

100. Weber, K.; Zuschin, M. Delta-associated molluscan life and death assemblages in the northern Adriatic Sea: Implications for paleoecology, regional diversity and conservation. Palaeogeogr. Palaeoclimatol. Palaeoecol.; 2013; 370, pp. 77-91. [DOI: https://dx.doi.org/10.1016/j.palaeo.2012.11.021]

101. Pérez-Ruzafa, A. El papel de la conectividad restringida en la construcción de los ecosistemas marinos semiaislados: El ejemplo de las lagunas costeras y los archipiélagos. Rev. Acad. Canar. Cienc.; 2015; 27, pp. 411-456.

102. Pérez-Ruzafa, A.; De Pascalis, F.; Ghezzo, M.; Quispe-Becerra, J.I.; Hernández-García, R.; Muñoz, I.; Marcos, C. Connectivity between coastal lagoons and sea: Asymmetrical effects on assemblages’ and populations’ structure. Estuar. Coast. Shelf Sci.; 2018; 216, pp. 171-186. [DOI: https://dx.doi.org/10.1016/j.ecss.2018.02.031]

103. Elliott, M.; Whitfield, A.K. Challenging paradigms in estuarine ecology and management. Estuar. Coast. Shelf Sci.; 2011; 94, pp. 306-314. [DOI: https://dx.doi.org/10.1016/j.ecss.2011.06.016]

104. Manteca, J.I.; Pérez de Perceval Verde, M.A.; López Morell, M.A. La Industria Minera en Murcia durante la época contemporánea. Bocamina. Patrimonio Minero de la Región de Murcia; Agua, M.d.l.C.y.e. Ayuntamiento de Murcia: Murcia, Spain, 2005; pp. 123-136.

105. García Dory, M.A.; Maldonado, J.L. La degradación ambiental del Mar Menor. Prog. Water Technol.; 1980; 12, pp. 481-499.

106. Navarro, M.C.; Pérez-Sirvent, C.; Martínez-Sánchez, M.J.; Vidal, J.; Tovar, P.J.; Bech, J. Abandoned mine sites as a source of contamination by heavy metals: A case study in a semi-arid zone. J. Geochem. Explor.; 2008; 96, pp. 183-193. [DOI: https://dx.doi.org/10.1016/j.gexplo.2007.04.011]

107. Simonneau, J. Mar Menor: Évolution Sédimentologique et Géochimique Récent en Remplissage. Ph.D. Thesis; University of Toulouse: Toulouse, France, 1973.

108. Sanchiz, C.; García-Carrascosa, A.M.; Pastor, A. Heavy Metal Contents in Soft-Bottom Marine Macrophytes and Sediments Along the Mediterranean Coast of Spain. Mar. Ecol.; 2000; 21, pp. 1-16. [DOI: https://dx.doi.org/10.1046/j.1439-0485.2000.00642.x]

109. Marín-Guirao, L.; Cesar, A.; Marín, A.; Vita, R. Valoración de la contaminación por metales en los sedimentos de la laguna costera del Mar Menor (SE de España): Distribución de metales, toxicidad, bioacumulación y estructura de las comunidades bentónicas. Cienc. Mar.; 2005; 31, pp. 413-428. [DOI: https://dx.doi.org/10.7773/cm.v31i2.53]

110. Marín-Guirao, L.; Marín, A.; Lloret, J.; López, E.M.; García Fernández, A.J. Effects of mining wastes on a seagrass ecosystem: Metal accumulation and bioavailability, seagrass dynamics and associated community structure. Mar. Environ. Res.; 2005; 60, pp. 317-337. [DOI: https://dx.doi.org/10.1016/j.marenvres.2004.11.002]

111. Conesa, H.M.; Jiménez-Cárceles, F. The Mar Menor lagoon (SE Spain): A singular natural ecosystem threatened by human activities. Mar. Pollut. Bull.; 2007; 54, pp. 839-849. [DOI: https://dx.doi.org/10.1016/j.marpolbul.2007.05.007]

112. Conesa, H.M.; Jiménez-Cárceles, F.; María-Cervantes, A.; González-Alcaraz, M.N.; Egea-Nicolas, C.; Alvarez-Rogel, J. Heavy metal contamination caused by mining activities in the Mar Menor lagoon (SE Spain). Biogeochemistry and Pedogenetic Process in Saltmarsh and Mangrove Systems; Pérez, X.L.O.; Vázquez, F.M. Nova Science Publishers: New York, NY, USA, 2010; pp. 253-269.

113. Dassenakis, M.; Garcia, G.; Diamantopoulou, E.; Girona, J.D.; García-Marín, E.M.; Filippi, G.; Fioraki, V. The impact of mining activities on the hypersaline Mar Menor lagoon. Desalination Water Treat.; 2010; 13, pp. 282-289. [DOI: https://dx.doi.org/10.5004/dwt.2010.1036]

114. Muñoz-Vera, A.; García, G.; García-Sánchez, A. Metal bioaccumulation pattern by Cotylorhiza tuberculata (Cnidaria, Scyphozoa) in the Mar Menor coastal lagoon (SE Spain). Environ. Sci. Pollut. Res.; 2015; 22, pp. 19157-19169. [DOI: https://dx.doi.org/10.1007/s11356-015-5119-x]

115. Muñoz-Vera, A.; Penas-Castejon, J.M.; García, G. Patterns of trace element bioaccumulation in jellyfish Rhizostoma pulmo (Cnidaria, Scyphozoa) in a Mediterranean coastal lagoon from SE Spain. Mar. Pollut. Bull.; 2016; 110, pp. 143-154. [DOI: https://dx.doi.org/10.1016/j.marpolbul.2016.06.069] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/27376999]

116. García-Fernández, G.; Muñoz-Vera, A. Characterization and evolution of the sediments of a Mediterranean coastal lagoon located next to a former mining area. Mar. Pollut. Bull.; 2015; 100, pp. 249-263. [DOI: https://dx.doi.org/10.1016/j.marpolbul.2015.08.042] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/26371846]

117. Navarro, G.; Jerez, S.; Farinós, P.; Robledano, F.; Motas, M. Evaluación de la exposición a elementos inorgánicos (Cr, Mn, Ni, Cu, Zn, As, Se, Cd y Pb) en cormoranes grandes (Phalacrocorax carbo sinensis) de la laguna costera del Mar Menor de Murcia. An. Vet.; 2010; 26, pp. 97-110.

118. Tsakovski, S.; Kudłak, B.; Simeonov, V.; Wolska, L.; García, G.; Namieśnik, J. Relationship between heavy metal distribution in sediment samples and their ecotoxicity by the use of the Hasse diagram technique. Anal. Chim. Acta; 2012; 719, pp. 16-23. [DOI: https://dx.doi.org/10.1016/j.aca.2011.12.052] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/22340526]

119. Martínez-López, S.; Martínez-Sánchez, M.J.; Gómez-Martínez, M.C.; Perez-Sirvent, C. Assessment of the risk associated with mining-derived arsenic input in a lagoon system. Environ. Geochem. Health; 2019; 42, pp. 2439-2450. [DOI: https://dx.doi.org/10.1007/s10653-019-00385-5]

120. De León, A.R.; Guerrero, J.; Faraco, F. Evolution of the pollution of the coastal lagoon of Mar Menor. Journées Études Pollut. Mar. Méditerranée C.I.E.S.M.; 1983; 6, pp. 355-358.

121. Auernheimer, C.; Llavador, F.; Piña, J.A. Chemical minority elements in bivalve shells—A natural model (Mar Menor, Spain). Arch. Sci.; 1984; 37, pp. 317-331.

122. Auernheimer, C.; Chinchon, S.; Piña, J.A. Lead pollution in bivalve shells. Mar Menor, Spain. Arch. Sci.; 1996; 49, pp. 87-98.

123. Marín-Guirao, L.; Lloret, J.; Marín, A. Carbon and nitrogen stable isotopes and metal concentration in food webs from a mining-impacted coastal lagoon. Sci. Total Environ.; 2008; 393, pp. 118-130. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2007.12.023]

124. Benedicto, J.; Marín-Guirao, L.; Guerrero, J. Contaminación por metales y compuestos organoestannicos en el Mar Menor. El Mar Menor. Estado Actual del Conocimiento Científico; Fundación Instituto Euromediterráneo del Agua/Fundación Cluster: Murcia, Spain, 2009; pp. 203-237.

125. María-Cervantes, A.; Jiménez-Cárceles, F.J.; Álvarez-Rogel, J. As, Cd, Cu, Mn, Pb, and Zn contents in sediments and mollusks (Hexaplex trunculus and Tapes decussatus) from coastal zones of a Mediterranean Lagoon (Mar Menor, SE Spain) affected by mining wastes. Water Air Soil Pollut.; 2009; 200, pp. 289-304. [DOI: https://dx.doi.org/10.1007/s11270-008-9913-7]

126. León, V.M.; Moreno-González, R.; Besada, V.; Martínez, F.; Ceruso, C.; García, V.; Schultze, F.; Campillo, J.A. Sea snail (Hexaplex trunculus) and sea cucumber (Holothuria polii) as potential sentinel species for organic pollutants and trace metals in coastal ecosystems. Mar. Pollut. Bull.; 2021; 168, 112407. [DOI: https://dx.doi.org/10.1016/j.marpolbul.2021.112407]

127. Varol, M.; Şen, B. Assessment of nutrient and heavy metal contamination in surface water and sediments of the upper Tigris River, Turkey. CATENA; 2012; 92, pp. 1-10. [DOI: https://dx.doi.org/10.1016/j.catena.2011.11.011]

128. Pérez-Ruzafa, A.; Navarro, S.; Barba, A.; Marcos, C.; Cámara, M.A.; Salas, F.; Gutiérrez, J.M. Presence of Pesticides Throughout Trophic Compartments of the Food Web in the Mar Menor Lagoon (SE Spain). Mar. Pollut. Bull.; 2000; 40, pp. 140-151. [DOI: https://dx.doi.org/10.1016/S0025-326X(99)00193-9]

129. Bayo, J.; Rojo, D.; Olmos, S. Abundance, morphology and chemical composition of microplastics in sand and sediments from a protected coastal area: The Mar Menor lagoon (SE Spain). Environ. Pollut.; 2019; 252, pp. 1357-1366. [DOI: https://dx.doi.org/10.1016/j.envpol.2019.06.024] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/31254893]

130. Campillo, J.A.; Albentosa, M.; Valdés, N.J.; Moreno-González, R.; León, V.M. Impact assessment of agricultural inputs into a Mediterranean coastal lagoon (Mar Menor, SE Spain) on transplanted clams (Ruditapes decussatus) by biochemical and physiological responses. Aquat. Toxicol.; 2013; 142, pp. 365-379. [DOI: https://dx.doi.org/10.1016/j.aquatox.2013.09.012]

131. Campillo, J.A.; Sevilla, A.; Albentosa, M.; Bernal, C.; Lozano, A.B.; Cánovas, M.; León, V.M. Metabolomic responses in caged clams, Ruditapes decussatus, exposed to agricultural and urban inputs in a Mediterranean coastal lagoon (Mar Menor, SE Spain). Sci. Total Environ.; 2015; 524, pp. 136-147. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2015.03.136]

132. Desbiolles, F.; Malleret, L.; Tilizacos, C.; Wong-Wah-Chung, P.; Laffont-Schwob, I. Occurrence and ecotoxicological assessment of pharmaceuticals: Is there a risk for the Mediterranean Aquatic environment?. Sci. Total Environ.; 2018; 639, pp. 1334-1348. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2018.04.351]

133. León, V.M.; Moreno-González, R.; González, E.; Martínez, F.; García, V.; Campillo, J.A. Interspecific comparison of polycyclic aromatic hydrocarbons and persistent organochlorines bioaccumulation in bivalves from a Mediterranean coastal lagoon. Sci. Total Environ.; 2013; 436, pp. 975-987. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2013.06.075]

134. León, V.M.; Moreno-González, R.; García, V.; Campillo, J.A. Impact of flash flood events on the distribution of organic pollutants in surface sediments from a Mediterranean coastal lagoon (Mar Menor, SE Spain). Environ. Sci. Pollut. Res.; 2017; 24, pp. 4284-4300. [DOI: https://dx.doi.org/10.1007/s11356-015-4628-y]

135. Martínez-Gómez, C.; Lamoree, M.; Hamers, T.; Van Velzen, M.; Kamstra, J.H.; Fernández, B.; Benedicto, J.; León, V.M.; Vethaak, A.D. Integrated chemical and biological analysis to explain estrogenic potency in bile extracts of red mullet (Mullus barbatus). Aquat. Toxicol.; 2013; 134, pp. 1-10. [DOI: https://dx.doi.org/10.1016/j.aquatox.2013.02.015]

136. Martínez-Gómez, C.; Valdehita, A.; Vethaak, A.D.; Navas, J.M.; Leon, V.M. Toxicity characterization of surface sediments from a Mediterranean coastal lagoon. Chemosphere; 2020; 253, 126710. [DOI: https://dx.doi.org/10.1016/j.chemosphere.2020.126710]

137. Moreno-González, R.; León, V.M. Presence and distribution of current-use pesticides in surface marine sediments from a Mediterranean coastal lagoon (SE Spain). Environ. Sci. Pollut. Res.; 2017; 24, pp. 8033-8048. [DOI: https://dx.doi.org/10.1007/s11356-017-8456-0]

138. Moreno-González, R.; Campillo, J.A.; García, V.; León, V.M. Seasonal input of regulated and emerging organic pollutants through surface watercourses to a Mediterranean coastal lagoon. Chemosphere; 2013; 92, pp. 247-257. [DOI: https://dx.doi.org/10.1016/j.chemosphere.2012.12.022] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/23399306]

139. Moreno-González, R.; Campillo, J.A.; León, V.M. Influence of an intensive agricultural drainage basin on the seasonal distribution of organic pollutants in seawater from a Mediterranean coastal lagoon (Mar Menor, SE Spain). Mar. Pollut. Bull.; 2013; 77, pp. 400-411. [DOI: https://dx.doi.org/10.1016/j.marpolbul.2013.09.040] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/24139646]

140. Moreno-González, R.; Rodríguez-Mozaz, S.; Gros, M.; Pérez-Canóvas, E.; Barceló, D.; León, V.M. Input of pharmaceuticals through coastal Surface watercourses into a Mediterranean lagoon (Mar Menor, SE Spain): Sources and seasonal variations. Sci. Total Environ.; 2014; 490, pp. 59-72. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2014.04.097] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/24840281]

141. Moreno-González, R.; Rodríguez-Mozaz, S.; Gros, M.; Barceló, D.; León, V.M. Seasonal distribution of pharmaceuticals in marine wáter and sediment from a mediterranean coastal lagoon (SE Spain). Environ. Res.; 2015; 138, pp. 326-344. [DOI: https://dx.doi.org/10.1016/j.envres.2015.02.016]

142. Moreno-González, R.; Rodríguez-Mozaz, S.; Huerta, B.; Barceló, D.; León, V.M. Do pharmaceuticals bioaccumulate in marine molluscs and fish from a coastal lagoon?. Environ. Res.; 2016; 146, pp. 282-298. [DOI: https://dx.doi.org/10.1016/j.envres.2016.01.001]

143. Salgueiro-González, N.; Campillo, J.A.; Viñas, L.; Beiras, R.; López-Mahía, P.; Muniategui-Lorenzo, S. Occurrence of selected endocrine-disrupting compounds in Iberian coastal areas and assessment of the environmental risk. Environ. Pollut.; 2019; 249, pp. 767-775. [DOI: https://dx.doi.org/10.1016/j.envpol.2019.03.107]

144. Traverso-Soto, J.M.; Lara-Martín, P.A.; León, V.M.; González-Mazo, E. Analysis of alcohol polyethoxylates and polyethylene glycols on marine sediments. Talanta; 2013; 110, pp. 171-179. [DOI: https://dx.doi.org/10.1016/j.talanta.2013.02.027]

145. Traverso-Soto, J.M.; Lara-Martin, P.A.; Gonzalez-Mazo, E.; León, V.M. Distribution of anionic and nonionic surfactants in a sewage-impacted Mediterranean coastal lagoon: Inputs and seasonal variations. Sci. Total Environ.; 2015; 503, pp. 87-96. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2014.06.107]

146. Ehrnsten, E.; Sun, X.; Humborg, C.; Norkko, A.; Savchuk, O.P.; Slomp, C.P.; Timmermann, K.; Gustafsson, B.G. Understanding Environmental Changes in Temperate Coastal Seas: Linking Models of Benthic Fauna to Carbon and Nutrient Fluxes. Front. Mar. Sci.; 2020; 7, 450. [DOI: https://dx.doi.org/10.3389/fmars.2020.00450]

147. Rodrigues-Filho, J.L.; Macêdo, R.L.; Sarmento, H.; Pimenta, V.R.A.; Alonso, C.; Teixeira, C.R.; Pagliosa, P.R.; Netto, S.A.; Santos, N.C.L.; Daura-Jorge, F.G. et al. From ecological functions to ecosystem services: Linking coastal lagoons biodiversity with human well-being. Hydrobiologia; 2023; 850, pp. 2611-2653. [DOI: https://dx.doi.org/10.1007/s10750-023-05171-0] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/37323646]

148. Rasmussen, E.K.; Petersen, O.S.; Thompson, J.R.; Flower, R.J.; Ayache, F.; Kraiem, M.; Chouba, L. Model analyses of the future water quality of the eutrophicated Ghar El Melh lagoon (Northern Tunisia). Hydrobiologia; 2009; 622, pp. 173-193. [DOI: https://dx.doi.org/10.1007/s10750-008-9681-9]

149. Hawkins, A.J.S.; Bayne, B.L.; Bougrier, S.; Héral, M.; Iglesias, J.I.P.; Navarro, E.; Smith, R.F.M.; Urrutia, M.B. Some general relationships in comparing the feeding physiology of suspension-feeding bivalve molluscs. J. Exp. Mar. Bio. Ecol.; 1998; 219, pp. 87-103. [DOI: https://dx.doi.org/10.1016/S0022-0981(97)00176-7]

150. Gallardi, D. Effects of Bivalve aquaculture on the environment and their possible mitigation: A review. Fish. Aquac. J.; 2014; 5, 105. [DOI: https://dx.doi.org/10.4172/2150-3508.1000105]

151. Magni, P.; Montani, S.; Takada, C.; Tsutsumi, H. Temporal scaling and relevance of bivalve nutrient excretion on a tidal flat of the Seto Inland Sea. Jpn. Mar. Ecol. Prog. Ser.; 2000; 198, pp. 139-155. [DOI: https://dx.doi.org/10.3354/meps198139]

152. Norkko, A.; Villnäs, A.; Norkko, J.; Valanko, S.; Pilditch, C. Size matters: Implications of the loss of large individuals for ecosystem function. Sci. Rep.; 2013; 3, 2646. [DOI: https://dx.doi.org/10.1038/srep02646]

153. Saraiva, S.; Fernandes, L.; van der Meer, J.; Neves, R.; Kooijman, S.A.L.M. The role of bivalves in the Balgzand: First steps on an integrated modelling approach. Ecol. Modell.; 2017; 359, pp. 34-48. [DOI: https://dx.doi.org/10.1016/j.ecolmodel.2017.04.018]

154. Maar, M.; Bolding, K.; Petersen, J.K.; Hansen, J.L.S.; Timmermann, K. Local effects of blue mussels around turbine foundations in an ecosystem model of Nysted off-shore wind farm. Denmark. J. Sea Res.; 2009; 62, pp. 159-174. [DOI: https://dx.doi.org/10.1016/j.seares.2009.01.008]

155. Sfriso, A.; Birkemeyer, T.; Ghetti, P.F. Benthic macrofauna changes in areas of Venice lagoon populated by seagrasses or seaweeds. Mar. Environ. Res.; 2001; 52, pp. 323-349. [DOI: https://dx.doi.org/10.1016/S0141-1136(01)00089-7]