Search Results (963)

The Great Salt Lake (GSL) is the largest saline lake in the Western Hemisphere. It supports billion-dollar industries and recreational activities, and is a vital stopping point for migratory birds. However, little is known about the spatiotemporal variation of phytoplankton biomass in the lake that supports these resources. Spectral reflectance provided by three remote sensing products was compared relative to their relationship with field measurements of chlorophyll a (Chl a). The MODIS product MCD43A4 with a 500 m spatial resolution provided the best overall ability to map the daily distribution of Chl a. The imagery indicated significant spatial variation in Chl a, with low concentrations in littoral areas and high concentrations in a nutrient-rich plume coming out of polluted embayment. Seasonal differences in Chl a showed higher concentrations in winter but lower in summer due to heavy brine shrimp (Artemia franciscana) grazing pressure. Twenty years of imagery revealed a 68% increase in Chl a, coinciding with a period of declining lake levels and increasing local human populations, with potentially major implications for the food web and biogeochemical cycling dynamics in the lake. The MCD43A4 daily cloud-free images produced by 16-day temporal composites of MODIS imagery provide a cost-effective and temporally dense means to monitor phytoplankton in the southern (47% surface area) portion of the GSL, but its remaining bays could not be effectively monitored due to shallow depths, and/or plankton with different pigments given extreme hypersaline conditions. Full article

Aquatic ecosystems play a crucial role in sustaining life and supporting key green and blue economic sectors globally. However, the growing population and increasing anthropogenic pressures are significantly degrading terrestrial water resources, threatening their ability to provide essential socioeconomic services. To safeguard these ecosystems and their benefits, it is critical to continuously monitor changes in water quality. Remote sensing technologies, which offer high-resolution spatial and temporal data over large geographic areas, including surface water bodies, have become indispensable for these monitoring efforts. They enable the observation of various physical, chemical, and biological water quality indicators, which are essential for assessing ecosystem health. Machine learning algorithms are well suited to handle the complex and often non-linear relationships between remote sensing data and water quality parameters. By integrating remote sensing with machine learning techniques, it is possible to develop predictive models that enhance the accuracy and efficiency of water quality assessments. These models can identify and predict trends in water quality, supporting timely interventions to protect aquatic ecosystems. This paper provides a thorough review of the major remote sensing techniques for estimating water quality indicators (e.g., chlorophyll-a, turbidity, temperature, total nitrogen and total phosphorous, dissolved organic, total suspended solids, dissolved oxygen, and hydrogen power). It examines how machine learning can improve water quality assessments. Additionally, it identifies key research gaps in current methodologies and suggests future directions to address challenges in water quality monitoring, aiming to improve the precision and scope of these critical efforts. Full article

High temperatures have adverse impacts on the photosynthetic efficiency and yield of many crop plants. This study investigated how high temperatures affect the photosynthetic efficiency parameters and chloroplast ultrastructure of three edamame cultivars (AGS354, UVE17, and UVE14) at the reproductive stages (flowering and pod-filling). Heat stress (HS) treatments were performed under controlled conditions in climate chambers set at 25/18 °C (control), 30/23 °C (HS-I), and 35/28 °C (HS-II). The AGS354 cultivar exhibited the greatest susceptibility under HS-II treatment, characterised by a reduction in the photochemical reactions, decreased chlorophyll-a (chl-a) and carotenoid accumulation, the highest increase in the starch grain traits, and reduced plastoglobule and grana area traits. In UVE 14 and UVE17, the HS-II treatment enhanced chl-a and chl-b accumulation. Elevated carotenoid levels in UVE14 and UVE17 likely protected chlorophyll from degradation and mitigated photooxidative damage. The HS-II treatment also enhanced the grana traits, supporting improved light-harvesting capacity during heat stress in UVE14 and 17. However, heat stress disrupted the photochemical reactions (quantum efficiency of photosystem II, performance index absorbance, and performance index), indicating that elevated carotenoids alone do not exhibit complete tolerance to heat stress. Since plastoglobules play an essential in carotenoid biosynthesis, increased or stabilised plastoglobule traits in UVE14 and UVE17 under HS-II treatment strongly indicate improved heat stress tolerance. Overall, UVE14 and UVE17 emerged as the most heat-tolerant cultivars, with AGS354 being the most susceptible. These findings provide valuable insights into heat stress adaptation mechanisms and suggest the UVE14 and UVE17 cultivars as potential candidates for breeding heat-tolerant edamame cultivars. Full article

One year of monthly sampling in some lagoons of the Po Delta and a pond in the Comacchio Valleys helped fill a gap in the knowledge of the primary producers of these degraded environments, focusing on the competition between macrophytes and phytoplankton. Key water column and surface sediment parameters showed a strong association with the different primary producers, explaining the main factors influencing the dominance of one group over the other. Phytoplankton, recorded as Chlorophyll-a and Phaeophytin-a, and Chlorophyceae among the macrophytes, dominated in conditions of high water turbidity and elevated nutrient concentrations. In contrast, macrophytes, particularly Rhodophyceae, their abundance, total biomass, and number of taxa. prevailed in clear, oxygenated waters. Under optimal conditions, sensitive macroalgae and aquatic angiosperms were also present. Additionally, the current list of macroalgal taxa has been updated, highlighting the dominance of some nonindigenous species (NIS) that had not been recorded before the 2000s. Specifically, Gracilaria vermiculophylla and Ulva australis, native to the North West Pacific (Japan, Korea, China, and Vietnam) and to South Australia, as well as the Indo-West Pacific (India, South Africa, Japan, and Korea), respectively, are now the most frequent and abundant taxa in these lagoons. Full article

The hourly L2-level chlorophyll-a (CHL-a) concentration spatial energy spectra of GOCI-II from 2021 to 2023 are employed to investigate the characteristics of the CHL-a spatial energy spectrum slopes in three regions of the East China Sea, namely nearshore, offshore, and open ocean. The seasonal trends of the spatial energy spectrum slopes are also examined for the nearshore and offshore regions. It is observed that the slopes of the CHL-a spatial energy spectrum are −2 at scales larger than 5 km, whereas at smaller scales, they are −5/3, −1, and −0.3 from the nearshore region to the open sea, respectively. On the larger scales, the spatial energy spectrum slopes are consistent with surface quasi-geostrophic (sQG) theory, but this is not the case on smaller scales. An insufficient regional CHL-a concentration leads to a flattening of the slope at the smaller scales. On the submesoscale, the slope of the nearshore CHL-a concentration spatial energy spectrum is steeper in summer and flatter in winter, a pattern that contrasts with changes observed offshore. This seasonal variation is attributed to the southward flow of ZheMin Coastal Current (ZMCC) during winter, which carries freshwater and enhances the horizontal buoyancy gradient in the nearshore region. Full article

This study examines the potential distribution of Mackerel scad (Decapterus macarellus) in the South China Sea under future climate scenarios (SSP 1.26, SSP 2.45, SSP 5.85) using an ensemble species distribution model (SDM). Key environmental variables included sea surface salinity (SSS), sea surface height (SSH), sea surface temperature (SST), mixed-layer depth (MLD), chlorophyll-a concentration (CHL), and sea-bottom temperature (SBT). Results show that SST and MLD are the primary drivers of habitat suitability, with current suitable habitats concentrated in the northern offshore areas. Projections for the 2050s and 2090s indicate a reduction in suitable habitats, particularly under high-emission scenarios, with more gradual reductions under low-emission scenarios. Habitat loss is most pronounced in the northern South China Sea, while the central region is projected to see an expansion of suitable habitats. These findings highlight the climate impact on D. macarellus distribution and inform sustainable management strategies for the species in the region. Full article

The use of living Arthrospira platensis (A. platensis) cultures emerges as a promising green solution for the bioremediation of water contaminated by toxic metal waste. The scope of the present study is to evaluate the microalga’s potential in heavy metal remediation, in the case of multi-metal-treated (multi-MT) systems. For this reason, A. platensis cultures were exposed to mono- and multi-metal solutions of Cu, Cd, Ni, Pb, and Zn, and their metal adsorption ability was investigated. The heavy metal removal efficiency of A. platensis cultures was evaluated using atomic absorption spectroscopy (AAS). Additionally, the cultures were examined using Fourier transform infrared (FTIR) spectroscopy, Near-Infrared (NIR) Spectroscopy, UV-Vis spectrophotometry, and optical microscopy, together with pH and electrical conductivity (EC) measurements to evaluate the quality of the cultures and the changes induced by heavy metal stress. The results showed that metal removal is still efficient in multi-MT cultures. In particular, Cu, Cd, Pb, and Zn removal of multi-MT cultures is elevated or relative to the respective removal of the mono-metal-treated (mono-MT) cultures, showing a synergistic or cooperative interaction between the metals, while the removal of Ni of multi-MT cultures decreased compared to Ni of mono-MT cultures, showing an antagonistic interaction to the other metals. The study shows that A. platensis is considered an effective microalga toward the bioremediation of multi-metal polluted cultures. Full article

The Global Change Observation Mission-Climate (GCOM-C) satellite, launched in December 2017, is equipped with the Second-generation Global Imager (SGLI) sensor, featuring a moderate spatial resolution of 250 m and 19 spectral bands, including the unique 380 nm band. After six years in orbit, a comprehensive evaluation of SGLI products and their temporal consistency is needed. Remote sensing reflectance ($R_{rs}$) is the primary product for monitoring water quality, forming the basis for deriving key oceanic constituents such as chlorophyll-a (Chla) and total suspended matter (TSM). The Japan Aerospace Exploration Agency (JAXA) provides $R_{rs}$ products through two platforms, G-Portal and JASMES, each employing different atmospheric correction methodologies and assumptions. This study aims to evaluate the SGLI full-resolution $R_{rs}$ products from G-Portal and JASMES at regional scales (Japan and East Asia) and assess G-Portal $R_{rs}$ products globally between January 2018 and December 2023. The evaluation employs in situ matchups from NASA’s Aerosol Robotic Network-Ocean Color (AERONET-OC) and cruise measurements. We also assess the retrieval accuracy of two water quality indices, Chla and TSM. The AERONET-OC data analysis reveals that JASMES systematically underestimates $R_{rs}$ values at shorter wavelengths, particularly at 412 nm. While the $R_{rs}$ accuracy at 412 nm is relatively low, G-Portal’s $R_{rs}$ products perform better than JASMES at shorter wavelengths, showing lower errors and stronger correlations with AERONET-OC data. Both G-Portal and JASMES show lower agreement with AERONET-OC and cruise datasets at shorter wavelengths but demonstrate improved agreement at longer wavelengths (530 nm, 565 nm, and 670 nm). JASMES generates approximately 12% more matchup data points than G-Portal, likely due to G-Portal’s stricter atmospheric correction thresholds that exclude pixels with high reflectance. In situ measurements indicate that G-Portal provides better overall agreement, particularly at lower $R_{rs}$ magnitudes and Chla concentrations below 5 mg/m³. This evaluation underscores the complexities and challenges of atmospheric correction, particularly in optically complex coastal waters (Case 2 waters), which may require tailored atmospheric correction methods different from the standard approach. The assessment of temporal consistency and seasonal variations in $R_{rs}$ data shows that both platforms effectively capture interannual trends and maintain temporal stability, particularly from the 490 nm band onward, underscoring the potential of SGLI data for long-term monitoring of coastal and oceanic environments. Full article

The coastal waters of Zhejiang feature a complex aquatic environment and abundant biological resources, creating an ideal habitat for various fish species. However, the systematic monitoring of fish larvae in these offshore waters is limited. This study collected 24,232 fish larvae using large plankton nets during April and November 2022, as well as February and July 2023, and identified 93 species, primarily warm-temperate and warm-water species, with a peak occurrence in summer. The dominant species include Larimichthys croceus, Sebastiscus marmoratus, Lateolabrax japonicus, and Odontamblyopus lacepedii, among others, and these species exhibit frequent seasonal changes. Fish larvae are typically found to be aggregated along estuaries and bays in spring, autumn, and summer, while in winter, they tend to shift towards areas near the boundaries of motor trawler fisheries areas. Our cluster analysis revealed spatial heterogeneity in the community structure, driven by an abundance of dominant and important species. Our Mantel tests and canonical correspondence analysis (CCA) identified seawater temperature and salinity as core drivers of the aggregation and distribution of fish larvae, interacting with factors such as the chlorophyll-a concentration, water turbidity, water depth, and dissolved oxygen. This research provides a scientific basis for the dynamic monitoring of spawning grounds and effective management of fishery resources in Zhejiang’s coastal waters. Full article

In order to improve the spatiotemporal coverage of satellite Chlorophyll-a (Chl-a) concentration products in marginal seas, a physically constrained deep learning model was established in this work to reconstruct sea surface Chl-a concentration in the Bohai and Yellow Seas using a Long Short-Term Memory (LSTM) neural network. Adopting the permutation feature importance method, time sequences of several geographical and physical variables, including longitude, latitude, time, sea surface temperature, salinity, sea level anomaly, wind field, etc., were selected and integrated to the reconstruction model as input parameters. Performance inter-comparisons between LSTM and other machine learning or deep learning models was conducted based on OC-CCI (Ocean Color Climate Change Initiative) Chl-a product. Compared with Gated Recurrent Unit, Random Forest, XGBoost, and Extra Trees models, the LSTM model exhibits the highest accuracy. The average unbiased percentage difference (UPD) of reconstructed Chl-a concentration is 11.7%, which is 2.9%, 7.6%, 10.6%, and 10.5% smaller than that of the other four models, respectively. Over the majority of the study area, the root mean square error is less than 0.05 mg/m³ and the UPD is below 10%, indicating that the LSTM model has considerable potential in accurately reconstructing sea surface Chl-a concentrations in shallow waters. Full article

Rivers play a crucial role in nutrient cycling, yet are increasingly affected by eutrophication due to anthropogenic activities. This study focuses on the Barato River in Hokkaido, Japan, employing an integrated approach of field measurements and Sentinel-2 satellite remote sensing to monitor eutrophication as the river experiencing huge sewage effluents. Key parameters such as chlorophyll-a (Chla), dissolved inorganic nitrogen (DIN), dissolved inorganic phosphorus (DIP), and Secchi Disk Depth (SDD) were analyzed. The developed empirical models showed a strong predictive capability for water quality, particularly for Chla (R² = 0.87), DIP (R² = 0.61), and SDD (R² = 0.82). Seasonal analysis indicated peak Chla concentrations in October, reaching up to 92.4 μg/L, alongside significant decreases in DIN and DIP, suggesting high phytoplankton activity. Advanced machine learning models, specifically back propagation neural networks, improved the prediction accuracy with R² values up to 0.90 for Chla and 0.83 for DIN. Temporal analyses from 2018 to 2022 consistently revealed the Barato River’s eutrophic state, with severe eutrophication occurring for 33% of the year and moderate for over 50%, emphasizing the ongoing nutrient imbalance. The strong correlation between DIP and Chla highlights phosphorus as the main driver of eutrophication. These findings demonstrate the efficacy of integrating remote sensing and machine learning for dynamic monitoring of river eutrophication, providing critical insights for nutrient management and water quality improvement. Full article

The objective of this study is to better identify the state of eutrophication of coastal waters along the southern coast of the city of Jeddah in the Red Sea. Thirty-six samples from surface seawater were collected during the spring and autumn of 2021. Water temperature, pH, salinity, dissolved oxygen (DO), nutrients, and chlorophyll-a (Chl-a) content were examined as a guide of water quality indicators. The present data revealed low levels of Chl-a content (in the range of 0.11–0.24 µg L⁻¹). The average concentrations of DIN (dissolved inorganic nitrogen) forms follow the order NO₃-N > NH₄-N ~ NO₂-N (representing about 11.4–29.4% of the total nitrogen). To investigate the trophic status and water quality, numerical indicators were applied to the results of the analysis of chemical variables (NH₄-N, NO₃-N, and PO₄-P) and the biological analysis (Chl-a) in the aqueous environment within the study area. These indicators are simplified based on the specialist, the non-specialist, the decision-maker, and the one responsible for managing the coastal areas. We also obtain through this method a single numerical value that expresses the state of the coastal waters. According to the analysis of phosphorus and nitrogen data and a trophic index (TRIX), the study area’s trophic status was determined as oligotrophic, due to low nutrient concentrations in the seawater. The current study identified a total of 58 species of phytoplankton comprised four classes in the investigated areas; Bacillariophyceae was the dominant algal class (Diatoms 30 species), followed by Chlorophyceae (9 species), Dinophyceae (11 species), and Cyanophyceae (8 species). Seasonally, spring recorded the highest value of total phytoplankton, recording a value of 251 × 10³ cells/L with a percentage of 61%, while autumn recorded the lowest value of 186 × 10³ cells/L with a percentage of 39%. Phytoplankton classes can be arranged in order of prevalence as follows: Bacillariophyceae >> Dinophyceae > Chlorophyceae > Cyanophyceae. Full article

The subsurface chlorophyll maximum depth (SCMD) is an indicator of the spatial activity of marine organisms and changes in the ecological environment. Ubiquitous mesoscale eddies are among the important factors regulating the Kuroshio–Oyashio confluence region. In this study, we use satellite altimeter observations and high-resolution reanalysis data to explore seasonal variations in the SCMD and its responses to different types of eddies based on methods of composite averaging and normalization. The results show that variations in the SCMD induced by the evolution of the eddies were prominent in the summer and autumn. The monopoles of the SCMD exhibited internally shallow and externally deep features in the cyclonic eddies (CEs), while the contrary trend was observed in the anticyclonic eddies (ACEs). The SCMD was positively correlated with the intensity of the eddies and sea surface temperature, and was negatively correlated with the depth of the mixed layer. These correlations were more pronounced in the CEs (summer) and ACEs (autumn). Both the CEs and ACEs prompted the westward transport of chlorophyll-a (Chl-A), where ACEs transported it over a longer distance than the CEs. Full article

Chelidonichthys spinosus is a common fish distributed in the Northwest Pacific. To ensure sustainable utilization, it is crucial to understand the potential impacts of environmental changes on habitat suitability. A habitat suitability index (HSI) model was developed for C. spinosus based on seasonal bottom trawling survey data and remote-sensing oceanographic data collected in the East China Sea and southern Yellow Sea from 2015 to 2017. The model examined the relationships between the spatio-temporal distribution of fish and environmental variables. The suitable ranges of sea bottom temperature, sea bottom salinity, depth and chlorophyll-a for C. spinosus in four seasons were identified. Each variable was then combined into the HSI model with weights defined by the Gradient Boosting Regression Tree. The spatial distribution and the centroid of the HSI revealed that C. spinosus exhibits a seasonal southward and southwestward migratory pattern throughout the year. This migration pattern indicates the suitable habitats for reproductive, feeding, and overwintering activities. The conservation of C. spinosus resources is a matter of great urgency, and some of the feasible proposals have been put forth in this purpose. Full article

The East Sea is a jointly managed maritime area of Korea, Russia, and Japan, where the frequency of strong typhoons is anticipated to increase with climate change, affecting its marine ecosystem and regional climate regulation. This study investigated the environmental and ecological impacts of summer typhoons entering the East Sea by analyzing satellite-derived chlorophyll-a (Chl-a) data, Argo float measurements, and ERA5 wind data. Our findings revealed that summer typhoons generally increased surface Chl-a concentrations by 65.4%, with typhoon intensity substantially influencing this process. Weak typhoons caused marginal Chl-a increases attributed to redistribution rather than nutrient supply, whereas normal and strong typhoons increased Chl-a through enhanced vertical mixing and nutrient upwelling in the East Sea. Stronger typhoons notably impacted the mixed layer depth and isothermal layer depth, leading to greater Chl-a concentrations within the strong wind radius. However, the increased Chl-a magnitude was lower than that of other strong typhoons in other regions. The East Sea uniquely responds to typhoons with fewer upper environment changes, possibly due to a stable barrier layer limiting vertical mixing. These findings underscore the importance of continuous monitoring and integrated observational methods in order to better understand the ecological effects of typhoons, particularly as their intensity increases with climate change. Full article