Secchi Depth Research Articles

Trophic Status of Lake Niesłysz (Poland) and Related Factors

In order to ensure the protection of lakes against eutrophication, an ongoing global problem, its causes should be determined on an individual basis. In this study, we investigated Lake Niesłysz in northwestern Poland in terms of (i) the impact of nitrogen and phosphorus on primary production, (ii) the Trophic State Index (TSI), and (iii) the hydromorphological characteristics and watershed features. We determined the thermal conditions, dissolved oxygen, organic matter, and selected forms of nitrogen and phosphorus. TSI was determined using Secchi depth (SD), chlorophyll a, total phosphorus (TP), and total nitrogen (TN). Hypolimnetic anoxia was observed in summer. Surface concentrations of chlorophyll a and organic carbon, total inorganic nitrogen (TIN), and total reactive phosphorus (TRP) were 5 μg L−1, 11.7 mg C L−1, 0.049 mg N L−1, and 0.018 mg P L−1, respectively. The TN:TP ratio was >30, while TIN:TRP was <10. The TSIs for chlorophyll a, SD, and TP ranged from 42 to 59, and for TN it was >145. The total trophic state index (T-TSI) exceeded 72. In conclusion, Lake Niesłysz has an average resistance to degradation and the catchment has little influence on the release and transport of biogenic matter into the lake. The limiting nutrient for primary production was phosphorus, but the influence of nitrogen or covariates of nitrogen cannot be excluded. Based on the oxygen conditions in the hypolimnion, the lake should be classified as eutrophic. Most of the TSIs were in the mesotrophic range, while the TSIs for TN and T-TSI classified the lake as hypertonic. The results show that Lake Niesłysz is currently at a critical stage of progressive degradation, and it is advisable to develop and implement protective measures immediately.

Re-evaluation of Padre Secchi’s visual method for modern oceanography

Secchi-disk is an instrument that enables investigating water transparency, being reflective of sunlight to be used to measure the depth of light penetration in the water column. In biological marine research, the device is used to determine the intensity of primary production of planktonic algae. In the present study, we re-evaluated the practicality of Secchi’s method, developed some 160 years ago, for modern oceanography by using the same locations, methods, objectives, and comparable Secchi disk that were used in his survey in 1865. We show that the Secchi-disk is still a valid scientific method in environmental marine research and therefore defends its place reliably among modern electronical research infrastructure. Observer’s subjectivity didn’t have a significant effect on measuring but environmental conditions can influence ZSD determination in general. It is therefore justified to follow, for example, the general recommendations for the use of the Secchi net issued by HELCOM. Our results also revealed that ZSD was located about twofold deeper in 1865 than presently which cannot be explained only by annual variation. We show that green(ish) sea areas have today extended to larger sea areas than they were 160 years ago, due to an increase in the turbidity of the water resulting from, e.g., general eutrophication.

Investigating the potential of remote sensing-based machine-learning algorithms to model Secchi-disk depth, total phosphorus, and chlorophyll-a in Lake Urmia

Many terminal lakes in agricultural basins are prone to eutrophication due to restricted inflows and receiving excess nutrients from their basin.The synergy of using satellite data andmachine learning models is a low-cost way to monitor the root-cause water quality variables (WQVs) of eutrophication. This study investigates the potential ofremote sensing-based machine learning algorithms to modelchlorophyll-a(Chl-a), total phosphorus (TP), Secchi disk depth (SD),and Carlson trophic state index (CTSI)in the north part of Lake Urmia (LU).The multiple linear regression (MLR) and artificial neural network (ANN) models were developed using Landsat-8 (L8) and Sentinel-2 (S2) data with nearly concurrent in-situ WQVs of the north part of LU from February 2016 to January 2017. Results showed that models based on L8 were superior to those with S2. Moreover, the ANN models based on L8 for Chl-a, SD, and TP having NSE = 0.75, 0.98, and 0.96, respectively, outperformed MLRs (with NSE = 0.74, 0.81, 0.58). Applying atmospheric correction (i.e., ACOLITE, C2RCC, and C2RCCX) enhances the models.The resultant Chl-aand SD maps indicated an inverse spatiotemporal pattern that agrees with the variation of the abiotic condition in the lake (e.g., surface temperature and total suspended sediments).According to the CTSI maps,the north part of LU was mesotrophic in February and March and eutrophic between June and October 2016. Our study indicates the promising application ofremote sensing-based machine learning algorithms to model the spatiotemporal variation of eutrophication in LU, which provides valuable insights into cost-effective lake monitoring.

Community coalescence under variable hydrochemical conditions of the Chesapeake Bay shaped bacterial diversity and functional traits

Community coalescence related to bacterial mixing events regulates community characteristics and affects the health of estuary ecosystems. At present, bacterial coalescence and its driving factors are still unclear. The present study used a dataset from the Chesapeake Bay (2017) to address how bacterial community coalescence in response to variable hydrochemistry in estuarine ecosystems. We determined that variable hydrochemistry promoted the deterioration of water quality. Temperature, orthophosphate, dissolved oxygen, chlorophyll a, Secchi disk depth, and dissolved organic phosphorus were the key environmental factors driving community coalescence. Bacteria with high tolerance to environmental change were the primary taxa accumulated in community coalescence, and the significance of deterministic processes to communities was revealed. Community coalescence was significantly correlated with the pathways of metabolism and organismal systems, and promoted the co-occurrence of antibiotic resistance and virulence factor genes. Briefly, community coalescence under variable hydrochemical conditions shaped bacterial diversity and functional traits, to optimise strategies for energy acquisition and lay the foundation for alleviating environmental pressures. However, potential pathogenic bacteria in community coalescence may be harmful to human health and environmental safety. The present study provides a scientific reference for ecological management of estuaries.

Environmental indicators of lake ecosystem health in Aotearoa New Zealand: current state and trends

Assessments of lake ecosystem health, based on indicators of physical–chemical water quality, ecological conditions, and human health risks, are needed to apprise the public and facilitate lake management. While unrefereed lake water quality reports exist, this is the first peer-reviewed study to report data processing and analysis methods and results for current state and recent trends in multiple environmental indicators in monitored lakes across Aotearoa New Zealand. Lake grading based on national criteria indicated that many lakes are failing to achieve statutory bottom lines for phytoplankton chlorophyll a, total nitrogen, and total phosphorus concentrations. In contrast, most monitored lakes had high grades for two human health risk indicators, E. coli and cyanobacteria concentrations, and for potential toxicity of ammonia for biological communities. We included 166 lakes and considered indicator state and trends for two lake classifications based on geomorphology and land cover. Elevated scores for an indicator of trophic state (the trophic level index; TLI) in most shoreline, riverine, peat, landslide, dam, and aeolian lakes indicated eutrophic conditions or worse. Lower TLI scores were indicative of oligotrophic conditions in most glacial lakes. Nutrient, E. coli and suspended sediment concentrations and TLI scores were positively correlated, and Secchi depths negatively correlated, with high-intensity agricultural land cover. Ten-year trend analyses indicated that lakes with increasing Secchi disk depth, chlorophyll a, dissolved reactive phosphorus, E. coli, ammoniacal nitrogen, TLI, total nitrogen, and total suspended solids trends outnumbered those with decreasing trends. Twenty-year trend analyses indicated that the numbers of lakes with increasing and decreasing trends in most of the indicators we assessed were comparable, but lakes with increasing 20-year trends in total nitrogen outnumbered those with decreasing trends, and lakes with decreasing 20-year trends in ammoniacal nitrogen, dissolved reactive phosphorus, total phosphorus, and nitrate nitrogen outnumbered those with increasing trends. This study presents clear data processing steps and trend analysis methods as applied to a nationwide dataset for Aotearoa New Zealand, while acknowledging data limitations. For example, the choice of trend periods is challenging and can greatly affect conclusions. The results of this empirical study and the collective results of preceding studies of lake ecosystem health indicate that eutrophication poses a threat to the ecological health of many if not most lakes in Aotearoa New Zealand. Recommendations include monitoring network expansion especially for the indicators bottom dissolved oxygen and cyanobacteria (toxic and total cyanobacteria biovolumes) and judicious selection of trend periods in lake-specific trend analyses to determine causes for increasing or decreasing trends in environmental indicators.

Lab on a Secchi disk: A prototype open‐source profiling package for low‐cost monitoring in aquatic environments

AbstractOwing to the high cost of commercial optical sensors, there is a need to develop low‐cost optical sensing packages to expand monitoring of aquatic environments, particularly in under‐resourced regions. Visual methods to monitor the optical properties of water, like the Secchi disk and Forel‐Ule color scale, remain in use in the modern era owing to their simplicity, low‐cost and long history of use. Yet, recent years have seen advances in low‐cost, electronic‐based optical sensing. Here, the designs of a miniaturized hand‐held device (mini‐Secchi disk) that measures the Secchi depth and Forel‐Ule color are updated. We then extend the device by integrating a small electronic sensing package (Arduino‐based) into the Secchi disk, for vertical profiling, combining historic and modern methods for monitoring the optical properties of water into a single, low‐cost sensing device, that measures positioning (GPS), light spectra, temperature, and pressure. It is charged and transfers data wirelessly, is encased in epoxy resin, and can be used to derive vertical profiles of spectral light attenuation and temperature, in addition to Secchi depth and Forel‐Ule color. We present data from a series of deployments of the package, compare its performance with commercially available instruments, and demonstrate its use for validation of satellite remotely sensed data. Our designs are made openly available to promote community‐based development and have potential in communicating and teaching science, participatory science, and low‐cost monitoring of aquatic environments.

Estimating beluga whale abundance from space: using drones to ground‐validate VHR satellite imagery

AbstractRoutine monitoring of cetaceans is imperative for understanding their population trends and making informed management decisions. However, the inherent nature of cetaceans and the marine ecosystems they inhabit make annual population surveys logistically and economically challenging with current survey methods. One emerging solution is utilizing very high‐resolution (VHR) satellite imagery, which is a logistically efficient method for providing an instantaneous view of areas spanning hundreds of square kilometers. The objective of this study was to determine two factors required to reliably conduct beluga whale population abundance estimates with VHR satellite imagery: (1) depths that beluga whales are visible in VHR satellite images, which are used to define availability bias correction factors, and (2) a comparison of abundance estimates in VHR satellite imagery to current aerial methods. We submerged beluga whale models to different depths in two different water clarities and determined that beluga whales are distinguished only at the surface in turbid water (Secchi depth: 2.56 m) and at depths of 0–2 m in clear water (Secchi depth: 4.04 m). Based on the proportion of time beluga whales spend at these depths, an availability bias correction factor for Western Hudson Bay beluga whales was defined as 2.40 ± 0.16 for turbid water and 1.89 ± 0.05 for clear water. Synchronous ground‐validation surveys determined availability corrected beluga whale abundance estimates in 0.31 m VHR satellite imagery (n = 173 beluga whales) and imagery that was HD sharpened using a proprietary algorithm to approximate 0.15 m resolution (n = 170) to be comparable to drone imagery (n = 164). VHR satellite imagery has the potential to increase the frequency of beluga whale population surveys, which has become increasingly important as beluga whales face rapid ecosystem changes and increased anthropogenic disturbances.

Breeding waterbird species as ecological indicators of shifts from turbid to clear water conditions in northwest European shallow eutrophic lakes

AbstractWe used biological and physical responses at 71 shallow waterbodies with contrasting nutrient levels undergoing recovery from eutrophication to predict potential changes in waterbird species abundance, an important component of lake ecosystems. These general predictions were tested using 28 years of breeding waterbird data from three Danish shallow eutrophic lakes, comparing species-specific responses to improved nutrient and water transparency in two lakes with a third where conditions remained constantly suitable for breeding waterbirds. We predicted positive responses to improved water quality from pursuit diving predators (three grebe species), a specialist zooplankton feeder (northern shoveler Anas clypeata) and waterbirds feeding on (common pochard Aythya ferina) or within (tufted duck A. fuligula) submerged macrophyte underwater canopies. These species were characterised by positive waterbird community composition changes (using Principal Components Analysis) associated with decreasing nutrient loading and increasing water transparency at two lakes, with no change in breeding waterbird community at the third. Secchi depth explained 73–95% of variance in both PC axes at both restored lakes, but not at the third, suggesting water transparency was the major factor driving waterbird community composition. These examples show predicting waterbird species-specific responses to management can usefully direct the use of breeding waterbirds as indicator species.

Ecosystem changes in eight Danish lakes after zebra mussel invasion

AbstractInvasion of zebra mussels (Dreissena polymorpha) can have profound effects on lake ecosystems. We investigated the overall ecological effects after invasion and fast expansion of zebra mussels in eight lakes in Denmark belonging to the same watercourse systems but with different morphological and eutrophication characteristics. A few years after the invasion, most of the lakes had experienced profound changes in lake water quality, e.g. chlorophyll a had been reduced by 18–62% and Secchi depth had increased by 38–171%. Nutrient concentrations also decreased, total phosphorus to 37–64% and total nitrogen to 49–77% of pre-invasion concentrations. Seasonally, differences between both summer and winter phosphorus and nitrogen concentrations diminished, suggesting a change in internal nutrient cycling after the invasion. In most lakes, the abundance of submerged macrophytes rose substantially, and often coverage increased by a factor 10 or more, and the maximum colonisation depth increased by up to 5.4 m. Plant species numbers increased markedly in four of the six lakes with macrophyte data. The fish community changed towards higher dominance of potential piscivorous perch and an increase in their body size. The profound effects of zebra mussel invasion may affect lake management and how ecological quality should be interpreted.

Advancing reservoirs water quality parameters estimation using Sentinel-2 and Landsat-8 satellite data with machine learning approaches

Reservoir eutrophication, caused by human activities and climate change, has emerged as a critical environmental concern that has attracted both governmental and public attention. However, accurate measurement of water quality parameters, such as chlorophyll a (CHL-a), water clarity (Secchi depth; SD), and total suspended solids (TSS), in inland waters is challenging due to the optical complexity of individual water bodies, which impedes the optimization of conventional bio-optical algorithms. The aim of this study was to demonstrate the viability of harmonizing Sentinel-2 Multi-Spectral Imager (MSI) and Landsat-8 Operational Land Imager (OLI) satellite imagery surface reflectance (SR) products to facilitate the monitoring of inland reservoir CHL-a, SD, and TSS using the Google Earth Engine (GEE) platform and machine learning algorithms. Machine learning models were trained using Landsat-8 OLI and Sentinel-2 MSI surface reflectance products to identify bands and combinations predicting CHL-a, SD, and TSS. Among the machine learning algorithms tested, random forest (RF) (S-2 MSI: R2 = 0.61, mean absolute error [MAE] = 6.56%, root-mean-square error [RMSE] = 12.51 μg/L, L-8 OLI: R2 = 0.56, MAE = 8.44%, RMSE = 16.01 μg/L) yielded the best results in the test set for CHL-a prediction from the Sentinel-2 MSI and Landsat-8 OLI, outperforming the k-nearest neighbor (KNN), AdaBoost, and artificial neural network (ANN) models. It also showed superior performance for SD and TSS prediction. The feature importance analysis revealed that specific band ratios, such as (red/red edge1)*red edge2 for Sentinel-2 MSI and red/blue for Landsat-8 OLI, were significant predictors of CHL-a and TSS. The red/blue band ratio and the green band were highly predictive for SD in Sentinel-2 MSI and Landsat-8 OLI, respectively. The results of fall CHL-a predictions revealed varying trophic levels in the reservoirs. Landsat-8 OLI indicated that 2% of the reservoirs were oligotrophic, while 46%, 43%, and 9% were mesotrophic, eutrophic, and hypertrophic, respectively. Meanwhile, the Sentinel-2 MSI results showed that 51% of the reservoirs were mesotrophic, while 6%, 35%, and 8% were oligotrophic, eutrophic, and hypertrophic, respectively. Overall, this study demonstrates the effectiveness of Landsat-8 OLI and Sentinel-2 MSI surface reflectance products in estimating and monitoring reservoir water quality parameters using machine learning algorithms. This approach has the potential to yield valuable insights aiding the assessment and management of water quality at the regional, national, and global levels.

Monitoring 36-year water clarity dynamics in turbid waters of the Pearl River Estuary, China, using Landsat data

Water clarity, commonly determined by Secchi disk depth (SDD), is a critical water quality parameter for assessing estuarine ecosystems heath. Since the 1980s, significant changes in SDD have been observed in the Pearl River Estuary (PRE), a robust, economical, and densely populated estuary in southern China. However, its long-term patterns and associated drivers have not yet been systematically investigated. In this study, three novel semi-analytical algorithms suitable for Landsat 5, 7, and 8 images were applied to 36-year (1987–2022) Landsat series data to explored the spatiotemporal heterogeneity of SDD in the PRE. The results indicated that the proposed SDD estimation algorithms yielded well-accepted performances and few errors, with mean absolute percentage errors <27% and root mean square errors <0.105 m. Spatially, the SDDs in the Western regions of the PRE (0.25 ± 0.1 m) were significantly lower than that in the Open areas (0.55 ± 0.15 m). In addition, the SDD showed an overall increasing trend from 1987 to 2022 with a rate of 0.032 m/y over the entire area, indicating gradually improved water quality in the PRE, owing to the less anthropogenic perturbations and landscape change. This research not only produces a 36-year historical SDD dataset for estuarine areas, but also imparts new insights into the complex mechanisms involved in watershed management.

Ecological condition of marine waters in the area of dredging operations of the kashagan field, Kazakhstan

To determine the hydrophysical and hydrochemical parameters of sea water and their changes during dredging works in the north‐eastern part of the Caspian Sea along the Western Approach Route and near/inside block D, islands EPC‐2, EPC‐3, EPC‐4 and island A of the Kashagan field.Measurement of hydrophysical parameters: salinity, temperature, turbidity, dissolved oxygen concentration, electrical conductivity, pH of seawater was carried out using a portable multi‐parameter analyser "Horiba‐U53" directly in the water column. Water transparency was determined using a Secchi disc. The depth of the water layer was determined using a sounder. Hydrochemical investigations were carried out for seven parameters, with all components sampled in the near‐surface and benthic horizons. Water samples were taken using probes or bathometers: BM‐48, GR‐18 or their analogues.Hydrochemical analyses of seawater samples for: biogens (NO2, NO3, NH4, Ntotal, and Ptotal), synthetic surfactants, phenols, hydrocarbons including polyaromatic hydrocarbons (PAHS), heavy metals, chemical oxygen demand (COD) and biochemical oxygen demand (BOD5). These were carried out in laboratory conditions using analytical equipment according to scientifically accepted methods.The data obtained as a result of the research allow us to draw the following conclusion: changes in the amount of suspended sediment in sea water lead to changes in physical and chemical properties of water (increase in turbidity, disturbance of sediment composition and properties), changes in biotopes, deterioration of oxygen regime, optical properties of water and temperature regime.

Hydrobiological assessment of two lakes of Jahangirnagar University campus, savar, Bangladesh

The physicochemical and biological parameters of the water in two different lakes on the Jahangirnagar University campus were evaluated between December 2018 and August 2019. The chosen metrics were air and water temperature, Secchi depth, alkalinity, conductivity, pH, total dissolved solids (TDS), dissolved oxygen (DO), soluble reactive phosphate (SRP), soluble reactive silicate (SRS), nitrate-nitrogen (NO3-N) and phytoplankton density (PD). The correlation between all the matrics was done. 37 orders of phytoplankton from lake-1 and 35 orders of phytoplankton from lake-2 were found under 8 classes (Cyanophyceae, Chlorophyceae, Bacillariophyceae, Synurophyceae, Euglenophyceae, Cryptophyceae, Dinophyceae, and Xanthophyceae). According to the principal component Analysis (PCA), 53.8% variation was found among the classes. In addition, Monoraphidium, Oscillatoria, Cosmarium, Actinastrum, Trachlelomonas, Euglena, Pediastrum, Pinnularia, and Synedra were found to be dominant species. It examined the relationships between various environmental factors and dominant phytoplankton species in two lakes and found that the effects of the physicochemical parameters differ depending on the lake and dominant phytoplankton type. The study found negative correlations between various water quality parameters and phytoplankton taxa, suggesting an influence of environmental conditions on phytoplankton communities. Bangladesh J. Bot. 53(1): 159-171, 2024 (March)

Long-term study of phytoplankton dynamics in a supply reservoir reveals signs of trophic state shift linked to changes in hydrodynamics associated with flow management and extreme events

This study analyses over a decade (2009–2022) of monitoring data to understand the impact of hydrological characteristics on water quality and phytoplankton dynamics in Prospect Reservoir, a critical water supply for Greater Sydney, Australia, known for its excellent water quality. Water quality and phytoplankton dynamics were related to hydrodynamics, linked to flow management and the water quality of inflows. Phytoplankton biovolume increased after a prolonged drawdown and subsequent refill event, mainly driven by dinoflagellates, and corresponded to increases in total phosphorus and water temperature. The hydrological period following the 2019/2020 summer bushfires (post-bushfire) that impacted connected reservoirs, was marked by increased flow activity and nutrient loading, leading to significant shifts in the phytoplankton community. Functional group classification and ordination analysis indicated a transition from taxa typically dominant in oligotrophic conditions to meso‑eutrophic. This transition correlated with elevated nutrient levels and chlorophyll-a (Chl-a), and reduced Secchi depth and dissolved oxygen, providing evidence of eutrophication. Q index indicated good water quality post-bushfire, contrasting with a eutrophic status assessment using Chl-a. Our findings highlight the importance of analysing long-term datasets encompassing varied hydroclimatological conditions for a deeper understanding of reservoir behaviour. A comprehensive approach to water quality assessment is recommended, combining functional group classification, Q index and Chl-a measurements for effective reservoir health assessment. This research provides novel insights into the effects of disturbances such as bushfires, on water quality and phytoplankton dynamics in an underrepresented geographic region, offering valuable knowledge for managing water resources amidst growing climate variability.

Patterns of the relationship between the Secchi disk depth and the optical characteristics of water in the Neva Estuary (Baltic Sea): the influence of environmental variables

The Secchi disc depth (Dsd) measurement is widely used to monitor eutrophication and the quality of the aquatic environment. This study aimed to investigate the relationship between Dsd and various factors, including the coefficient of attenuation of photosynthetically active radiation [Kd (PAR)], the depth of the euphotic zone (Deu), PAR at the Secchi disk depth (Esd) and the absorption coefficient of PAR (F) in the Neva Estuary, one of largest estuaries of the Baltic Sea. Environmental variables impacting these indices were identified using data collected from midsummer 2012 to 2020. The Dsd values in the estuary ranged from 0.3 to 4.0 m, with an average value of 1.8 m, while the Deu/Dsd ratio ranged from 1.5 to 6.0 with an average value of 2.8. These values were significantly lower than those observed in the open waters of the Baltic Sea. The highest Deu/Dsd ratio was observed in turbid waters characterized by high Kd(PAR) and low Dsd. Contrary to expectations, Dsd did not exhibit a significant relationship with the concentration of chlorophyll a, raising doubts about the utility of historical Dsd data for reconstructing phytoplankton development in the estuary. Principal component analysis did not identify the primary environmental variables strongly affecting the optical characteristics of water. However, recursive partitioning of the dataset using analysis of variance (CART approach) revealed that the concentration of suspended mineral matter (SMM) was the primary predictor of Deu/Dsd, Kd(PAR), and F. This SMM was associated with the frequent resuspension of bottom sediments during windy weather and construction activities in the estuary. Concentrations of suspended organic matter and the depth of the water area were found to be less significant as environmental variables. Furthermore, the CART approach demonstrated that different combinations of environmental variables in estuarine waters could result in similar optical indicator values. To reliably interpret the data and determine the optical characteristics of water in estuaries from Dsd, more complex models incorporating machine learning and neural connections are required. Additionally, reference determinations of Esd in various regions with specific sets of environmental variables would be valuable for comparative analyses and better understanding of estuarine systems.

Ecological degradation of a fragile semi-arid wetland and the implications in its microbial community: The case study of Las Tablas de Daimiel National Park (Spain)

Las Tablas de Daimiel National Park (TDNP, Iberian Peninsula) is a semi-arid wetland of international significance for waterfowl and serves as a migratory route for various bird species. However, TDNP presents strong anthropization and fluctuating water levels, making it a highly fragile ecosystem. Water physico-chemical parameters and microbial diversity of the three domains (Bacteria-Archaea- Eukarya) were analysed in Zone A and Zone B of the wetland (a total of eight stations) during spring and summer, aiming to determine how seasonal changes influence the water quality, trophic status and ultimately, the microbial community composition. Additionally, Photosynthetically Active Radiation (PAR) was used to determine the trophic status instead of transparency using Secchi disk, setting the threshold to 20–40 μmol/sm2 for benthic vegetation growth. In spring, both zones of the wetland were considered eutrophic, and physico-chemical parameters as well as microbial diversity were similar to other wetlands, with most abundant bacteria affiliated to Actinobacteriota, Cyanobacteria, Bacteroidota, Gammaproteobacteria and Verrumicrobiota. Methane-related taxa like Methanosarcinales and photosynthetic Chlorophyta were respectively the most representative archaeal and eukaryotic groups. In summer, phytoplankton bloom led by an unclassified Cyanobacteria and mainly alga Hydrodictyon was observed in Zone A, resulting in an increase of turbidity, pH, phosphorus, nitrogen, chlorophyll-a and phycocyanin indicating the change to hypertrophic state. Microbial community composition was geographical and seasonal shaped within the wetland as response to changes in trophic status. Archaeal diversity decreases and methane-related species increase due to sediment disturbance driven by fish activity, wind, and substantial water depth reduction. Zone B in summer suffers less seasonal changes, maintaining the eutrophic state and still detecting macrophyte growth in some stations.This study provides a new understanding of the interdomain microbial adaptation following the ecological evolution of the wetland, which is crucial to knowing these systems that are ecological niches with high environmental value.

A variational optimization algorithm for Secchi disk depth based on Multi-satellite data

A Secchi depth is a basic parameter to describe the optical properties of water, which is related to the composition and content of chlorophyll, suspended solids and yellow substances in water, and is also closely related to solar radiation on the surface of water, physical and chemical properties of water and meteorological conditions. The most direct way to obtain the spatiotemporal distribution of water Secchi depth is to use ships to regularly measure the Secchi depth of the base-stations, but this method can only obtain the Secchi depth of the measurement station state, and it is impossible to obtain the Secchi depth characteristics of seawater with large spatiotemporal distribution. As a brand-new observation method, remote sensing technology can obtain the distribution characteristics of ocean parameters in large time and space. In recent years, with the rapid development of remote sensing technology, especially the development of water-colored remote sensors and the improvement of the accuracy of inversion algorithms, many remote sensing products for water Secchi depth have been provided. However, due to the difference in orbit operation and observation parameters of different remote sensing loads, water Secchi depth products are affected by clouds and meteorological climate environment, and there is no same standard for verification and evaluation, which limit the promotion and application of water Secchi depth products. At the same time, data integrated technology has been widely recognized by many disciplines and has been greatly developed in recent years, and pixel-level, feature-level, decision-level integrated technology and development are also popular research directions in the world. Therefore, based on an improved variational optimization algorithm, this article integrates SDD retrieval products on multiple satellite data t such as SNPP, MODIS, and MERIS, and verifies them with ship survey data. The correlation is better than 0.9, proving that this method can improve the accuracy of SDD inversion products.

Contribution of combined stressors on density and gene expression dynamics of the copepod Temora longicornis in the North Sea.

The impact of multiple environmental and anthropogenic stressors on the marine environment remains poorly understood. Therefore, we studied the contribution of environmental variables to the densities and gene expression of the dominant zooplankton species in the Belgian part of the North Sea, the calanoid copepod Temora longicornis. We observed a reduced density of copepods, which were also smaller in size, in samples taken from nearshore locations when compared to those obtained from offshore stations. To assess the factors influencing the population dynamics of this species, we applied generalised additive models. These models allowed us to quantify the relative contribution of temperature, nutrient levels, salinity, turbidity, concentrations of photosynthetic pigments, as well as chemical pollutants such as polychlorinated biphenyls and polycyclic aromatic hydrocarbons (PAHs), on copepod density. Temperature and Secchi depth, a proxy for turbidity, were the most important environmental variables predicting the densities of T. longicornis, followed by summed PAH and chlorophyll concentrations. Analysing gene expression in field-collected adults, we observed significant variation in metabolic and stress-response genes. Temperature correlated significantly with genes involved in proteolytic activities, and encoding heat shock proteins. Yet, concentrations of anthropogenic chemicals did not induce significant differences in the gene expression of genes involved in the copepod's fatty acid metabolism or well-known stress-related genes, such as glutathione transferases or cytochrome P450. Our study highlights the potential of gene expression biomonitoring and underscores the significance of a changing environment in future studies.

Satellite imagery as a management tool for monitoring water clarity across freshwater ponds on Cape Cod, Massachusetts

Water clarity serves as both an indicator and a regulator of biological function in aquatic systems. Large-scale, consistent water clarity monitoring is needed for informed decision-making. Inland freshwater ponds and lakes across Cape Cod, a 100-km peninsula in Massachusetts, are of particular interest for water clarity monitoring. Secchi disk depth (SDD), a common measure of water clarity, has been measured intermittently for over 200 Cape Cod ponds since 2001. Field-measured SDD data were used to estimate SDD from satellite data, leveraging the NASA/USGS Landsat Program and Copernicus Sentinel-2 mission, spanning 1984 to 2022. Random forest machine learning models were generated to estimate SDD from satellite reflectance data and maximum pond depth. Spearman rank correlations (rs) were “strong” for Landsat 5 and 7 (rs = 0.78 and 0.79), and “very strong” for Landsat 8, 9, and Sentinel-2 (rs = 0.83, 0.86, and 0.80). Mean absolute error also indicated strong predictive capacity, ranging from 0.65 to 1.05 m, while average bias ranged from −0.20 to 0.06 m. Long- and recent short-term changes in satellite-estimated SDD were assessed for 193 ponds, selected based on surface area and the availability of maximum pond depth data. Long-term changes between 1984 and 2022 established a retrospective baseline using the Mann-Kendall test for trend and Theil-Sen slope. Generally, long-term water clarity improved across the Cape; 149 ponds indicated increasing water clarity, and 8 indicated deteriorating water clarity. Recent short-term changes between 2021 and 2022 identified ponds that may benefit from targeted management efforts using the Mann-Whitney U test. Between 2021 and 2022, 96 ponds indicated deteriorations in water clarity, and no ponds improved in water clarity. While the 193 ponds analyzed here constitute only one quarter of Cape Cod ponds, they represent 85% of its freshwater surface area, providing the most spatially and temporally comprehensive assessment of Cape Cod ponds to date. Efforts are focused on Cape Cod, but can be applied to other areas given the availability of local field data. This study defines a framework for monitoring and assessing change in satellite-estimated SDD, which is important for both local and regional management and resource prioritization.

Remote monitoring of water clarity in coastal oceans of the Guangdong-Hong Kong-Macao Greater Bay Area, China based on machine learning

The development of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), one of the most developed and densely populated regions in China, has posed an increasing threat to the health of the water environment in adjacent coastal oceans. However, the spatiotemporal variations of water clarity in the coastal oceans of the GBA (COGBA) have not been well-documented. Therefore, this study aims to develop a remote sensing retrieval algorithm for assessing water clarity, represented by Secchi disk depth (ZSD), based on Landsat-8 OLI imagery for the COGBA using a machine learning method. Cross-validation demonstrated that the algorithm performed exceptionally well, with an R2 value greater than 0.8. By applying the algorithm to 263 Landsat-8 OLI images, we obtained a time series of ZSD for the period of 2013–2021 over the COGBA. Results indicate that the Pearl River Estuary (PRE) exhibited the highest turbidity, followed by the Daya Bay and the Mirs Bay. Generally, ZSD increased from the northwest to the southeast of the COGBA. Seasonal, interannual, and long-term variations in ZSD were also observed with long-term increases in the PRE and the Daya Bay. The interannual variations in ZSD during fall were primarily regulated by different factors in each region. In the PRE, the negative effects of sediment discharge and wind speed played a significant role. In Mirs Bay, wind speed and sediment discharge had a negative impact on ZSD. In Daya Bay, precipitation and wind speed were the key factors influencing ZSD. The development and findings of our algorithm contribute to the protection and management of the water environment in the COGBA, facilitating effective governance measures.