Littoral Research Articles

Sensitivity Assessment on Satellite Remote Sensing Estimates of Primary Productivity in Shelf Seas

The vertically generalized production model (VGPM) is one of the most important methods for estimating marine net primary productivity (PP) using remote sensing. However, different data sources and parameterization schemes of the input variables for the VGPM can introduce uncertainties to the model results. This study compared the PP results from different data sources and parameterization schemes of three major input variables (i.e., chlorophyll-a concentration (Copt), euphotic depth (Zeu), and maximum photosynthetic rate (PoptB)) and evaluated the sensitivity of VGPM in the Yellow and Bohai Seas on the inputs. The results showed that the sensitivity in the annual mean PP was approximately 40%. Seasonally, the sensitivity was lowest in the spring (35%), highest in the winter (70%), and approximately 60% in the summer and autumn. Spatially, the sensitivity in nearshore water (water depth < 40 m) was more than 60% and around two times higher than that in deep water areas. Nevertheless, all VGPM results showed a decline trend in the PP from 2003 to 2020 in the Yellow and Bohai Seas. The influence of PoptB and Copt was important for the magnitude of annual mean PP. The PP seasonal variation pattern was highly related to the parameterization scheme of PoptB, whereas the spatial distribution was mostly sensitive to the data sources of Copt.

Composition and distribution of the near-shore waters bordering the coral reefs of Aruba, Bonaire, and Curaçao in the Southern Caribbean

This study aimed to identify ocean- and land-based sources of nutrients to the coral reef communities surrounding the Southern Caribbean islands Aruba, Bonaire, and Curaçao (ABC islands). The composition of water masses around these islands were assessed to depths up to 300 m and three distinct overlying water masses were identified, separated by mixing zones. A fluctuating pycnocline separating surface from deeper (>∼50 m) water indicated the presence of internal waves. Nutrient profiles were typical of tropical waters with oligotrophic waters occurring above the pycnocline and a deep chlorophyll-a maximum (DCM) just below it (∼65 m). Concentrations of dissolved nutrients differed among islands. Inorganic nitrogen (DIN) and phosphate concentrations were respectively lowest around Bonaire and Curaçao. The spatial distribution of chlorophyll-a (indicative of phytoplankton biomass), rather than nutrient concentrations, suggested the presence of higher-than-average nutrient concentrations in islands with higher population densities and near urbanized/industrial areas.

Multi-parameter correlation analysis and multi-step prediction of seawater quality based on graph spatio-temporal analysis network

Abstract In recent years, with the increasing pollution of near-shore waters, the water quality pollution incidents have been aggravated, which seriously threatens many aspects of coastal economic development, ecological environment and living health. Therefore, there is an urgent need for an effective method to predict the water quality of near-shore waters. However, due to seasonal changes, ocean currents, biological activities and other factors, the marine environment has strong complexity and uncertainty, which leads to the monitoring data of seawater quality parameters are unstable, non-linear and other characteristics. At the same time, there are interactions between different parameters, so it is not easy to dig deeper into the information in the data, and the accuracy of the existing prediction methods for multi-parameter multi-step prediction of seawater quality is generally low. To solve the above problems, a new graph neural network model is proposed in this paper. The model can effectively extract the local time correlation, global time correlation and spatial correlation in non-Euclidean space of seawater quality parameter data from multiple dimensions. Finally, this paper evaluates the model performance using the seawater parameter data from the near-shore waters of Beibu Gulf, and compared with the five baseline models, the model proposed in this paper shows the best performance in all the defined evaluation indexes.

Generative Simplex Mapping: Non-Linear Endmember Extraction and Spectral Unmixing for Hyperspectral Imagery

We introduce a new model for non-linear endmember extraction and spectral unmixing of hyperspectral imagery called Generative Simplex Mapping (GSM). The model represents endmember mixing using a latent space of points sampled within a (n−1)-simplex corresponding to n unique sources. Barycentric coordinates within this simplex are naturally interpreted as relative endmember abundances satisfying both the abundance sum-to-one and abundance non-negativity constraints. Points in this latent space are mapped to reflectance spectra via a flexible function combining linear and non-linear mixing. Due to the probabilistic formulation of the GSM, spectral variability is also estimated by a precision parameter describing the distribution of observed spectra. Model parameters are determined using a generalized expectation-maximization algorithm, which guarantees non-negativity for extracted endmembers. We first compare the GSM against three varieties of non-negative matrix factorization (NMF) on a synthetic data set of linearly mixed spectra from the USGS spectral database. Here, the GSM performed favorably for both endmember accuracy and abundance estimation with all non-linear contributions driven to zero by the fitting procedure. In a second experiment, we apply the GTM to model non-linear mixing in real hyperspectral imagery captured over a pond in North Texas. The model accurately identified spectral signatures corresponding to near-shore algae, water, and rhodamine tracer dye introduced into the pond to simulate water contamination by a localized source. Abundance maps generated using the GSM accurately track the evolution of the dye plume as it mixes into the surrounding water.

Lake Shore Restoration with Vallisneria spiralis in Lake Como (Northern Italy) to Improve Sustainability

In the Anthropocene era, lake ecosystems are increasingly subjected to significant human-induced pressures, leading to declines in both biodiversity and habitat quality. However, restoration initiatives offer promising avenues for enhancing the resilience of freshwater environments. This research investigated a range of established and novel methods aimed at promoting the growth of the macrophyte Vallisneria spiralis in the littoral zone of Lake Como, a southern alpine lake in Italy. To conduct this study, samples of Vallisneria spiralis were collected and placed in tanks containing four different types of 3D-printed biodegradable substrates. The optimal conditions for the growth of this species were identified as follows: a temperature range of 25 to 27 °C, the continuous operation of a circulation pump equipped with a filter, the presence of a fertile substrate, and light cycles comprising 6 h of peak illumination followed by 6 h of darkness. Remarkably, the plants exhibited a growth rate of 4 mm per day, increasing from an initial count of 12 specimens to 400 within four months, with a total of over 700 plants by the end of the study. Among the substrates tested, the patch substrate was found to be the most effective. After their introduction into the natural environment, the survival rate of plants established on stable substrates in contact with the lakebed reached an impressive 85.7%. This research represents a pioneering step in demonstrating that Vallisneria spiralis may serve as a viable option for restoration projects in coastal lake habitats, particularly when employing biodegradable substrates.

Art and algae: an ocean intimacy. A story in four parts

ABSTRACT I am a photographer, author and designer of many books, with my last few focusing on the world of seaweed and kelp. My most recent book, The Curious World of Seaweed, is the basis for a travelling exhibition of prints by the same name. I am the co-director of Above/Below, a campaign working to bring the recognition afforded the forests on land to the kelp forests below the ocean’s surface. Above/Below’s signature effort is a web-based book titled The Mysterious World of Bull Kelp. Released in November 2023, it has been accessed by over 10,000 kelp-curious learners with ocean educators, kelp researchers, and graduate students interested in the convergence of art and science using the website frequently. For over 20 years I have used my flatbed scanner and computer exclusively for generating imagery. Synthesizing the scientific stories of the Pacific and Atlantic rocky coasts, beaches, and nearshore waters is my overriding passion, bringing thoughtfulness and stewardship to these extraordinary places of discovery. This essay, Art & Algae: An Ocean Intimacy, concludes that artmaking is essential for our human relationships with seaweed and kelp so that understanding of these organisms can flourish. It is told as a diaristic account of four instances of place-based, algal artmaking.

The First Information on the Low Molecular Metabolom Lobelia dortmanna (Campanulaceae, Magnoliophyta) Growing in the Northwest of the Russian Federation

The low molecular weight metabolome (LMWM) of Lobelia dortmanna L. (Campanulaceae, Magnoliophyta), a relic aquatic macrophyte listed in the Red Data Books of the Russian Federation and Republic of Belarus, was studied for the first time using the GC/MS technique. It is a macrophyte that grows in oligotrophic lakes in the northwest of the Vologda Region, Russia. Thirteen major chemicals were among the 127 volatile low molecular weight organic compounds (VOCs) discovered, which accounted for 77.23% of the overall VOC content (198.75 µg/g dry plant weight). The main components of LMWM were carboxylic acids and hydrocarbons. The presence of a large number of biologically active metabolites with a high concentration in L. dortmanna LMWM may indicate a significant effect of this plant on the hydrobiocenoses of the littoral zone of oligotrophic lakes. Further research into the LMWM of aquatic macrophytes in oligotrophic lakes, a valuable renewable resource, is needed to assess the background characteristics of the natural environment for more effective monitoring of the ecological state of water bodies in the Russian Federation's North-West and the rational use of their biological resources.

Composition of the Low Molecular Weight Metabolome of Potamogeton perfoliatus (Potamogetonaceae) as an Indicator of the Transformation of the Ecological State of the Littoral Zone

The composition and nature of changes in the low-molecular-weight metabolome (NM) of Potamogeton perfoliatus L., growing in 6 biotopes of Lake Ladoga with different types of the anthropogenic load has been analyzed. According to the research results, it was found that the total number of low molecular weight organic compounds (LMWOCs) in the P. perfoliatus NM composition is directly dependent on anthropogenic load, which is well marked by the development of cyanobacteria. The greater the intensity of pollution or eutrophication of waters, or the higher the number of cyanobacteria, the lower the total number of LMWOCs and their concentration. A strongly pronounced dependence of the total concentrations of groups of NM compounds on the anthropogenic disturbance of the biotope and the concentration of cyanobacteria was revealed. A decrease in the number, relative amount, total concentration of carboxylic acids, number and content of unsaturated fatty acids, and, at the same time, an increase in the composition and content of phenols and the total content of aldehydes and ketones depends on an increase in anthropogenic pressure. The specific composition of NM of pierced pondweed depends on its response to biotic and abiotic factors of the aquatic environment, including anthropogenic ones. The revealed features of the change in the composition of P. perfoliatus NM make it possible to use it as an integral indicator of the anthropogenic impact on the littoral biotopes of water bodies and the deterioration of their ecological state.

Counting fish at night using artificial light: transect survey of common bream Abramis brama and northern pike Esox lucius abundance as an example.

Visual transect counting of large-bodied fish using artificial light at night in a shallow littoral zone (<1 m water depth) is introduced as a complementary survey method for fishes such as common bream Abramis brama and northern pike Esox lucius that are under-represented in standard gillnet surveys. The results suggest that transect counting at night and applying necessary corrections for environmental variables could provide a simple and repeatable method to assess the presence and abundance of large-bodied fishes in lakes with satisfactory water clarity.

Primary Production in the Littoral Zone of Lake Onego and Its Contribution to the Productivity of the Reservoir

Primary Production in the Littoral Zone of Lake Onego and Its Contribution to the Productivity of the Reservoir

Evaluation of SDGSAT-1 MII data in total suspended matter estimation in clear to extremely turbid rivers

ABSTRACT The Multispectral Imager (MII) onboard the newly launched SDGSAT-1 holds significant promise for monitoring and understanding variations in water quality within nearshore water systems, with an impressive spatial resolution of 10 m, seven spectral bands in the visible and near-infrared domain and a wide swath of 300 km. This paper evaluates the MII data in estimating the concentration of total suspended matter (TSM) in rivers and estuaries from clear to extremely turbid conditions. For atmospheric correction, the ACOLITE model showed superior performance compared to the FLAASH and 6SV, with average unbiased relative error (AURE) ranging from 11.8% to 26.4% in the four visible bands of MII. Through comparison, a TSM model based on the visible band ratio (i.e., Rrs (660)/Rrs (560)) was proposed to ensure the application of MII data in both clear and turbid waters, with an overall AURE of 40.9%. The model was then applied to map the TSM variations in the Hai and Liao Rivers in northern China using the MII data, where reliable spatial and temporal patterns were observed. The study concludes by discussing the applicability of MII data in water quality mapping in nearshore waters, along with key considerations such as model applicability, atmospheric correction, and land adjacency.

Exploring Spatial Dynamics of Water Quality in a Tropical Lake Affected by Aquaculture

Lake Maninjau, like many surface water bodies worldwide, faces significant water pollution challenges due to extensive aquaculture activities, making it an ideal site to study the impact of fish farming on water quality, which has contributed to eutrophication and declining water quality. This study investigates the physicochemical parameters and pollution levels in the lake, aiming to provide insights into its environmental health. In August 2022, a comprehensive sampling campaign was undertaken at nine stations within the upper layers of open water and littoral zones of Lake Maninjau. In situ measurements, including temperature, dissolved oxygen, and pH, were conducted, accompanied by water sample collection for laboratory analysis of trace elements and heavy metals. Our study revealed notable variability in water parameters across different sites, with surface water layers exhibiting the greatest differences. While certain parameters such as temperature and conductivity remain relatively stable, pH levels show a decreasing trend with increasing water depth. Dissolved oxygen levels vary widely, while oxidation–reduction potential indicates water pollution, particularly in littoral zones. Potassium dominance within cations likely suggests anthropogenic influences, notably from aquaculture activities, that may also contribute to nutrient enrichment and heavy metal pollution. Elevated levels of total nitrogen and ammonia underscore the lake’s moderate pollution levels, with heavy metals such as mercury exceeding permissible limits, posing risks to aquatic life and human health.

The Driving Factors and Path Selection for the Development Level of China’s Mariculture—A Dynamic Analysis Based on the TOE Framework

Mariculture is a key practice to promote the supply-side reform of fishery, and it is of strategic significance to explore the causes and paths of its high-level development. Based on the TOE (Technology-Organization-Environment) theoretical framework and the configuration methodology, this paper adopts the dynamic qualitative comparative analysis (QCA) method and panel data from 10 coastal provinces and cities in China from 2013 to 2021 to explore the configuration effects of six antecedents, namely, the intensity of technology promotion, investment in scientific research, personnel specialization, industry intensification, nearshore water quality, and offshore pollution discharge, along temporal and spatial dimensions, on the level of mariculture development. The results show that (1) individual driving factors do not constitute the necessary conditions for a high level of mariculture industry development, but the necessity of the three conditions—research funding, industry intensification and nearshore seawater quality—shows a general increasing trend; and (2) the results of the path analysis show that a total of seven configuration paths for a high level of development are generated, which can be further classified into “organization-led and technology synergistic”, “technology-organization-environment multiple-driven type”, and “technology-environment dual-driven type”. Based on the panel data, this study explores the impact of spatial and temporal changes in factor combinations on the development level of mariculture and provides a theoretical basis and practical insights for the development of locally adapted execution pathways.

Salinity impacts on n-alkanes in lake sediments of the Badain Jaran Desert, Northwestern China: Implications for paleoclimate reconstruction

n-Alkanes in lake sediments are essential biomarkers for paleoclimate research, yet the influence of lake salinity on their distribution remains unclear. This study investigates this relationship by analyzing sediments from eight lakes in the Badain Jaran Desert, all subject to similar climatic conditions but varying in salinity. Soil samples from the shoreline vegetation belt and suspended particle matter (SPM) were collected to identify the origin of plant input in the lake sediments. Additionally, sediment samples from the littoral zone to the lake center were all gathered to evaluate the salinity effects at different water depths. Key indexes such as content, the proportion of aquatic macrophyte (Paq), average chain length (ACL), and carbon preference index (CPI) of n-alkanes were examined to elucidate salinity effects. The result showed that the surrounding vegetation belt is the primary source of n-alkanes in lake sediments, with minimal contributions from SPM. Increased salinity was found to decrease CPI in the littoral zone, while also reducing Paq and increasing ACL in the lake bottom sediments. Changes of Paq, ACL and CPI in sediments are not attribute to variations in vegetation belt input but rather suggest that high salinity enhances n-alkane degradation, particularly favoring the degradation of mid-chain compounds in lake bottom sediments. Consequently, the reliability of n-alkane indexes as indicators of aquatic macrophyte in deep lake cores may be compromised by salinity. This study underscores the importance of accounting for salinity effects when using n-alkanes in reconstructing paleoclimate and suggests that their potential as indicators of lake salinization merits further attention.

Evaluation of Urbanization Influences on Beach Sediment Contamination with Heavy Metals Along the Littoral Zone of Alexandria City, Egypt

The western coastal area of Alexandria City, Egypt, faces significant environmental challenges due to heavy metal (HM) contamination in beach sediments, driven by intensive urbanization, tourism, commercial harbors, and industrial activities. Therefore, this study focuses on geochemically assessing HM levels in sediment samples from 28 sites and employed various descriptive and multivariate statistical approaches, pollution indices, and sediment quality guidelines (SQGs) to identify pollution hotspots, define contamination grades, and assess the quality of beach sediments. The average concentrations of Cd, Co, Cr, Cu, Pb, and Zn were 25.7, 30, 2.2, 7.5, 2.9, and 8.0 times, respectively, compared to the geochemical background (carbonate sedimentary rocks). et al.-Hanuvil Beach, relatively elevated contents of these metals were recorded. In addition, samples showed Zn levels higher than the corresponding probable effect concentration (PEC) and effect range medium (ERM) values, suggesting adverse impacts on biota. The principal component (PC) analysis revealed the anthropogenic origin of Cd, Co, and Pb in PC1, the mixed origin of Cr, Cu, Mn, and Zn in PC2, and the natural source of Fe in PC3. According to the applied single pollution indices, HM contamination grades were ranked in ascending order of Mn < Fe < Cr < Cd < Cu < Pb < Zn < Co. In conclusion, the HMs (Cu, Zn, Cd, Co, Pb, and Cr) in the study area are anthropogenic, attributed mainly to untreated discharge of municipal and industrial wastewater and solid wastes, atmospheric deposition of air pollutants, and tourism activities.

Dynamic Coastal Mapping Using Sentinel-1 and Sentinel-2 Data Through Digital Earth Africa

Abstract. Coastal erosion poses a continuous threat to ecosystems, infrastructure, and property. To address these challenges and mitigate the effects of coastal changes, effective and current monitoring is essential. It is particularly important to monitor coastlines and coastal changes in Africa, where a significant portion of the population resides in coastal regions. While optical satellite imagery has been used for large-scale annual coastlines and change monitoring for Africa, its availability and quality are largely limited by the presence of cloud and cloud shadow. In comparison, using radar satellite observations such as Sentinel-1 data can provide consistent coastal mapping and change detection regardless of cloud presence. This paper outlines a fully automated supervised machine learning workflow using Sentinel-1 data and training samples extracted from Sentinel-2 data. It also explores the performance of the workflow for different coastal morphology types across the African coast. The workflow has proved to perform better and produced results that were visually more consistent with Sentinel-2 data compared to thresholding methods. While challenges exist to distinguish between land and water over smooth sandy beaches and rough near-shore water surfaces, our workflow provides an alternative method for coastal change mapping where optical satellites provide insufficient observations free from clouds. Python code of the proposed methodology has been made publicly available.

Pulsed wind-driven control of phytoplankton biomass at a groundwater-enriched nearshore environment

Along some Mediterranean coastal areas and other world regions, nutrient and chlorophyll concentrations often show gradient increases of up to one order of magnitude perpendicular to the coast. This nearshore stripe, extending a few hundred meters from the coast, is enriched by submarine groundwater discharges (SGD) containing elevated nutrient concentrations that may eventually sustain high biomass phytoplankton blooms. During a survey carried out in the summer of 2018, we examined the short-term (hours) variability of the phytoplankton biomass (measured as chlorophyll; Chl) in response to environmental changes associated with SGD and wind forcing in the nearshore waters of Palma Beach (Mediterranean Sea). Continuous CTD records revealed a general salinity decline indicative of SGD along the shoreline. Large and pulsed salinity fluctuations (i.e. 2–3 psu variations, 1–4 h) were observed each day that were consistent with offshore advection episodes of the lower salinity water retained in the nearshore (peak crosshore velocity 5–6 cm s−1). Chl near the shoreline was markedly higher than offshore (3.55 ± 1.29 and 0.68 ± 0.27 mg m−3 respectively) but recurrently fluctuated in the afternoon to up to >7 mg m−3. Primary production estimations showed that despite the higher production in the nearshore (50.29 ± 10.98 μmol O2 L−1 d−1, 4-fold offshore values) productivity per unit chlorophyll did not significantly vary (p > 0.01) therefore suggesting that, at this time scales, high biomass episodes in the nearshore are driven by an accumulation mechanism. Statistical analysis (CCA) demonstrates that Chl variability is largely explained (93 %) by variations in wind and current velocity. Our results provide evidence that the dynamics of this nearshore environment are modulated by the interplay between the shoreward wind-induced flow and the offshore directed density flow. This mechanism could explain the occurrence and episodic nature of high biomass blooms in the nearshore, as well as be an important factor influencing the microbial community structure at the coastal zone.

Distribution, community structure and metabolic potential of bacterioplankton in a small boreal lake: Microscopy-based survey and 16S rRNA-based DNA metabarcoding

Bacteria are numerous and diverse organisms that have a significant impact on the functioning of aquatic ecosystems. On the vast territory of the West Siberian Lowland (Russia) there are many rivers, lakes and bogs, the microbial communities of which are almost unexplored. Here, we report the study results on the distribution, diversity, community structure and functions of bacterioplankton in the pelagic and littoral zones of one of the lakes, located in this region (Lake Kuchak) obtained using microscopic techniques and 16S rRNA gene metabarcoding. The high total bacterial abundance and biomass, the diversity indices, and the high number of Actinobacteria amplicon sequence variants (ASVs), along with the relatively low number of Betaproteobacteria ASVs, indicate the eutrophication of the lake, especially in its overgrown littoral zone. Similar bacterial communities developed in the pelagic and littoral zones due to similar environmental conditions in these habitats of this small and shallow lake. Nevertheless, there were some differences between the pelagic and littoral zones, causing differences in the bacterial communities of these zones more in size and morphological structure than in taxonomic composition. Comparative analysis of the bacterial metabolic ways showed the higher functional potential in the pelagic zone compared to the littoral one. Signs of methylotrophic and methanotrophic activities, as well as pollutant biodegradation potential of the bacterioplankton were identified. The bacterial distribution and community composition indicates the input of organic substances into the lake from the watershed, but also shows the community resistance to allochthonous microorganisms. Alpha diversity indices, distribution of taxonomic groups and some other results indicate deterioration of water quality in the overgrown littoral zone.

Design considerations for a continuous mussel farm in New England Offshore waters. Part I: Development of environmental conditions for engineering design

Sustainable aquaculture in nearshore waters faces challenges such as stakeholder conflicts, environmental pollution, and spatial constraints. Offshore aquaculture offers a promising solution but requires robust engineering design to withstand extreme weather conditions. This study develops the environmental conditions essential for engineering the design of a continuous mussel dropper system in New England offshore waters. A potential farm location was identified using criteria including water depth, federal boundaries, seafloor suitability, farm size, and proximity to ports, based on bathymetric and sedimentary maps. Historical data from five wave monitoring stations and two current velocity stations were analyzed to model extreme environmental conditions, as waves and currents pose primary threats. The extreme wave and current conditions are modeled using the Weibull distribution, on the annual maximum hourly significant wave height data and the largest 0.3 % of current speeds. A newly proposed method combining Spalding’s wall function with a fourth-order polynomial is used to enhance the current profile analysis. Additionally, a joint probability density function was developed for wave height and current velocity at a specific depth, providing insights into wave height, period, and wavelength for various return periods such as 10, 25, 50, and 100 years. The results suggest a 10-yr wave of 8 m significant wave height and a current speed of 1.68 m/s, while a 50-yr values are 9.4 m and 1.96 m/s respectively. These findings offer critical data on extreme wave and current conditions in New England’s offshore waters, providing practical guidance for the engineering design of offshore mussel farms. This research advances offshore mussel farming and benefits the development of all types of offshore aquaculture systems.

Multi-omics analysis of sea urchin (Strongylocentrotus intermedius) adaptation to salt stress reveals epigenetic regulatory mechanisms

Increased precipitation and surface runoff due to global warming has reduced surface seawater and nearshore water salinity, affecting marine organism survival. Nevertheless, the epigenetic mechanisms underlying the adaptation of sea urchins (Strongylocentrotus intermedius) to low-salinity stress remains unknown. This study utilized response surface methodology to formulate growth models for S. intermedius at different salinity levels and shell diameters. Whole genome bisulphite sequencing, RNA-sequencing, and metabolome analysis were performed on low-salinity stressed sea urchins, and a total of 3006 differential methylated regions, 945 differential methylated genes, 886 differentially expressed genes, and 271 differential metabolites were identified. Multi-omics analysis revealed significant alterations in the gene expression and DNA methylation of key genes (e.g., SPHK2, Arpc1a, and SLC23A1) in S. intermedius under low-salinity stress conditions. These changes subsequently influenced the metabolism of substances, including sphingosine-1-phosphate, ethanolamine phosphate, vitamin C, taurine, and choline. These alterations impacted functions related to immunity, osmoregulation, and energy metabolism in the organism. This study was to comprehensively elucidate the epigenetic mechanisms of S. intermedius under low-salinity stress from the perspective of DNA-RNA-metabolites, providing new insights into salinity adaptation of marine invertebrates.