Water Transparency Research Articles

Characteristics of plankton community structure and applicability of biomanipulation in midstream of the Jialing River—the biggest tributary of the Yangtze River

Plankton, as an important part of the food chain in the river ecosystem, is sensitive to changes in the environment. To investigate the influence of plankton community structure on the aquatic ecosystem and further verify the applicability of biomanipulation, the midstream of the Jialing River was selected as the study area. A total of 149 species (varieties) from 7 phyla, 18 orders, 34 families, and 72 genera were identified for phytoplankton. A total of 48 species were found for zooplankton. The mean density of phytoplankton was 2.09 × 106 cells/L, and the mean density of zooplankton was 27.1 ind./L. Moreover, the mean values of the Shannon–Wiener diversity index (H′), Pielou homogeneity index (J′), and Margalef abundance index (D) for phytoplankton were 3.17, 0.76, and 4.47, respectively. The mean values of the Shannon–Wiener diversity index (H′), Pielou homogeneity index (J′), and Margalef abundance index (D) for zooplankton were 2.64, 0.92, and 5.07, respectively. Based on the diversity indices, the water quality was evaluated as oligo pollution to β-medium pollution level. Redundancy analysis (RDA) was used to explore the relationship between dominant plankton species and environmental factors. The RDA results show that the main environmental factors affecting the community structure of phytoplankton and zooplankton were water temperature (WT), electrical conductivity (EC), pH, total phosphorus (TP), and transparency (Secchi depth; SD). There were 17 functional groups in phytoplankton, which are X1, S1, Y, Y2, and so on. In zooplankton, there were six functional groups, which are Pmsl, Prsu, Pfif, Pmip, Lrsf and Lmic. Many articles have demonstrated the feasibility of using biological manipulation to control algae. The number of piscivorous fish in the midstream of the Jialing River had increased, and phytoplankton density in this survey was significantly decreased. The results show that traditional biomanipulation can be applied to this region, which can provide better scientific support for the future management of the aquatic environment in the Jialing River basin.

Spatiotemporal dynamics of 2-methylisoborneol produced by filamentous cyanobacteria and associated driving factors in Lake Taihu, China

The proliferation of filamentous cyanobacteria in lakes can result in the generation of odor-causing compounds, predominantly 2-methylisoborneol (2-MIB), which pose odor-related challenges. In an effort to elucidate the spatiotemporal dynamics of 2-MIB and related influencing factors in East Lake Taihu, monthly investigations were undertaken from April 2022 to March 2023. In addition to the monthly survey, a whole-lake survey was conducted during the high-temperature period from July to September. The monthly survey revealed a distinct unimodal fluctuation in the concentration of 2-MIB in East Lake Taihu, with an average concentration at 297.0 ng/L during the high-temperature period. During the high-temperature period, the filamentous cyanobacterial communities detected in East Lake Taihu consisted primarily of species belonging to genera Leptolyngbya, Oscillatoria, Planktothricoides, and Pseudanabaena. However, no significant correlations were found between their densities and 2-MIB concentration. In addition, the mic gene was predominantly detected in genera Pseudanabaena and Planktothricoides, with the latter being the primary contributor to 2-MIB production. Furthermore, a succession of cyanobacteria capable of producing 2-MIB was detected, with water temperature and radiation intensity being identified as the primary driving factors. The temporal variation of 2-MIB concentration within East Lake Taihu during the whole year was primarily modulated by factors such as water temperature, water transparency, dissolved oxygen, and chlorophyll-a. During the high-temperature period, the 2-MIB concentration in the alga-dominated zone of East Lake Taihu was approximately 1.7 times greater than that in the macrophyte-dominated zone, with nutrient and transparency being identified as the main influencing factors. Consequently, our findings are of great significance for monitoring the sources and variation of 2-MIB in shallow lakes, providing a scientific foundation and theoretical guidance for odor management.

Spatial-temporal patterns of fish trophic guilds in a freshwater river wetland ecosystem of northeastern China.

Muling River, situated amidst cultivated lands in Heilongjiang Province, northeastern China, has long been subjected to sand-digging activities, resulting in severe damage to its riverbed. However, little research has been conducted on the impact of this disturbance on the status of fish community structure and trophic guilds in this river. In this study, environmental factors, fish community structure, and fish trophic guild biomass distribution patterns from the Muling River basin were investigated among seasons (spring, summer, and autumn) and sections (upper, middle, and lower stream) in 2015 and 2017. During the six sampling times periods, 46 species of five orders and 12 families of fish were classified into seven trophic guilds. Fish species number and biomass were higher upper reaches of the watershed. The insectivores (16.26%), phytoplanktivores (10.09%), benthivores (40.17%), and omnivores (11.86%) were the dominant trophic guilds. We found that fish trophic guilds biomass and environmental factors such as transparency, water depth, pH value, total phosphorus, and chemical oxygen demand were highest in the upper section compared to other sections. Variation partitioning revealed that fish trophic guilds biomass was influenced more by environmental factors (61.2%), followed by section (0.7%) and season (0.1%). Partial RDA ordination showed that fish trophic guilds were positively correlated with water depth and transparency, while negative with turbidity. This study underscores the importance of considering trophic guilds of freshwater fishes to inform management strategies in regions experiencing significant environmental change.

Seagrasses in the Eastern Tropical Pacific: species, distribution ecology, blue carbon, and threats

Eastern Tropical Pacific (ETP) seagrasses are composed of three genera and four species: Halophila baillonii, Halodule beaudettei, Halodule wrightii, and Ruppia maritima. These are colonizing seagrass species and meadows in the ETP can be ephemeral. Current seagrass distribution in this region remains unknown, with verified extant presence at a limited number of locations and mapping heavily reliant on historical reports. Suitable environmental conditions for seagrasses in the ETP consist of sheltered bays <10 m depth with fine sediment, 19-35 salinity, 26-32°C temperature, and water transparency of up to 10 m Secchi depth. In this region, seagrass organic carbon (OC) biomass pools (<0.2 Mg ha-1) have been reported from three locations, while sediment bulk density (<1.4 g mL-1) and OC (<24 Mg ha-1) have been reported from eight locations, all found on the Pacific coast of Costa Rica. Recent blue carbon reports from the ETP have not been included in global assessments to date. OC sequestration and sediment accumulation rates are currently unknown. Seagrasses provide key ecosystem services yet they are also threatened by anthropogenic and natural stressors. Seagrasses have already disappeared from two locations within the ETP, with restoration efforts currently underway on the northern Pacific coast of Costa Rica. This overview of our current understanding of seagrasses in the ETP and their services highlights the need for further research in this understudied region.

Integrating Remote Sensing Methods for Monitoring Lake Water Quality: A Comprehensive Review

Remote sensing methods have the potential to improve lake water quality monitoring and decision-making in water management. This review discusses the use of remote sensing methods for monitoring and assessing water quality in lakes. It explains the principles of remote sensing and the different methods used for retrieving water quality parameters in complex waterbodies. The review highlights the importance of considering the variability of optically active parameters and the need for comprehensive studies that encompass different seasons and time frames. The paper addresses the specific physical and biological parameters that can be effectively estimated using remote sensing, such as chlorophyll-α, turbidity, water transparency (Secchi disk depth), electrical conductivity, surface salinity, and water temperature. It further provides a comprehensive summary of the bands, band combinations, and band equations commonly used for remote sensing of these parameters per satellite sensor. It also discusses the limitations of remote sensing methods and the challenges associated with satellite systems. The review recommends integrating remote sensing methods using in situ measurements and computer modelling to improve the understanding of water quality. It suggests future research directions, including the importance of optimizing grid selection and time frame for in situ measurements by combining hydrodynamic models with remote sensing retrieval methods, considering variability in water quality parameters when analysing satellite imagery, the development of advanced technologies, and the integration of machine learning algorithms for effective water quality problem-solving. The review concludes with a proposed workflow for monitoring and assessing water quality parameters in lakes using remote sensing methods.

Spatial and temporal variability of water transparency, its primary drivers, and other optical properties in the Hudson River Estuary

Water transparency, measured as the diffuse attenuation coefficient of photosynthetically-active (400–700 nm) radiation, KdPAR, was measured monthly from May–Oct 2020 at 73 locations along 250 km of the Hudson River estuary (HRE) between New York City, NY and Waterford, NY. Three primary optical drivers of KdPAR variability: chlorophyll concentration (CHL), turbidity, and light absorption by colored dissolved organic matter (aCDOM), were measured concurrently to assess their relative importance to spatial and temporal KdPAR patterns. KdPAR was higher and more variable in the brackish HRE relative to limnetic regions further north. KdPAR was also significantly higher nearshore and near sewage treatment plant outfalls relative to midchannel sites. Temporal variability at individual stations was generally lower than cross-channel or cross-region spatial variability. Turbidity was the most important factor in KdPAR variability in all regions of the HRE, followed by CHL, with aCDOM playing a lesser role. Although many water quality variables have changed in the HRE over recent decades, KdPAR measurements in the brackish regions overlapped with published observations from the 1970s–1990s. KdPAR in the limnetic regions was lower in 2020 than measurements made prior to the Zebra mussel invasion in the early 1990s, but similar to measurements in the limnetic regions made since the invasion. Results of this study can be used to optimize satellite-based remote sensing algorithms for synoptic water quality observations of the HRE. Proposed future alterations in the HRE, including dredging and the construction of storm-surge barriers, would likely change existing KdPAR patterns. This study therefore provides an updated baseline for optical parameters in the HRE and highlights the importance of understanding the impacts of any proposed alterations to upper-water-column turbidity in this system. Results also demonstrate that KdPAR, euphotic depths, and Secchi depth measurements were positively correlated throughout the HRE. Secchi depth measurements may therefore be useful for additional retrospective studies, and future monitoring (including by satellite-derived KdPAR) of water transparency in the HRE.

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.

Spatiotemporal Assessment of Water Pollution for Beira Lake, Sri Lanka

Beira Lake, located in Colombo, Sri Lanka, has suffered severe anthropogenic impacts, with previous restoration attempts failing due to a limited understanding of pollutant dynamics. Aiming to fill this gap, a comprehensive study was conducted during dry and wet seasons to assess the spatiotemporal water pollution of Beira Lake, employing key physicochemical parameters, numerical indices, and remote sensing analysis. The water pollution index (WPI) results categorize Beira Lake as highly polluted, with WPI values ranging from 2.38 ± 0.92 in the wet season to 2.53 ± 1.32 in the dry season. Comparatively higher COD levels recorded in the Beira Lake network, especially for Gangarama Lake show significant pollution levels during both the dry and wet seasons, e.g., the highest COD levels, at 306.40 mg/L, were observed during the wet season. The Trophic State Index (TSI) results indicate eutrophic and hypereutrophic conditions in Beira Lake, which are particularly pronounced during the wet season. The heavy metal pollution index (HPI) results suggest elevated heavy metal concentrations in Beira Lake, especially in the wet season. Combined with field investigation results, a remote sensing data analysis between 2016 and 2023 reveals significant improvements in water transparency, suggesting positive effects of recent management interventions. Parameters demanding attention include COD, nitrate, and total phosphate levels due to their consistent exceedance of permissible limits. The PCA results of indices correlations between wet and dry seasons offer valuable insights into the complex dynamics of Beira Lake’s water quality. The study makes recommendations for restoring Beira Lake, including stringent pollution controls, regular dredging, green infrastructure implementation, implementing new rules and regulations, and community engagement.

Does water transparency control the banding in shallow water iron formations?

Abstract Iron formations (IFs) are marine chemical sediments that are conined to the Precambrian rock record and provide unique insights into the co-evolution of the atmosphere-hydrosphere and biosphere through almost three billion years of Earth’s history. IFs commonly appear throughout the Archaean until the Palaeoproterozoic ca. 1.8 billion years ago and re-appear during the “Snowball Earth” epoch in the Neoproterozoic. The formation and deposition mechanism(s) of IFs are, however, still incompletely understood, hindering unique interpretations of palaeoenvironments. Many IFs are banded iron formations (BIFs) with layer thickness of alternating Fe- and Si-rich layers ranging over several orders of magnitude from the nanometre to the metre scale. A second textural type, so called granular iron formations (GIFs) that form above storm wave base become widespread in the Palaeoproterozoic. Understanding the fundamental mechanisms that are responsible for the textural types and the periodicity of banding in BIFs is crucial to link these features to the environmental and geochemical evolution of the Earth. We here provide a conceptual model that highlights the role of changing light conditions and water transparency for Iron Formation (IF) precipitation. We show that the model is particularly feasible for IFs deposited in shallow waters but may also be applicable for some IFs deposited in deeper water settings. The model builds on other primary Banded Iron Formation (BIF) precipitation models postulating that Fe(III)-(oxyhydr)oxide production can be dominated by anoxygenic photoautotrophic Fe2+-oxidising bacteria. These so called photoferrotrophs are adapted to very low light levels corresponding to about 1% of the light level required by oxygen-producing phototrophs allowing them to thrive deep down in the water column. The depth of Fe(III)-(oxyhydr)oxide production is mainly controlled by water turbidity which controls how deep photosynthetically available radiation (PAR) penetrates the water column. Eutrophic conditions result in relatively shallow Fe(III)-(oxyhydr)oxide production depth due to turbidity either induced by the biomass itself and/or by particles that are actively or passively produced by microorganisms (e.g., Fe(III) and Mn(IV)-(oxyhydr)oxides, sulphides), triggering the formation of Fe-rich bands. During oligotrophic stages, Fe(III)-(oxyhydr)oxides are only produced relatively deep down in the water column, so that only silica-rich bands form in the Fe(III)-(oxyhydr)oxide free upper water column. Reactive transport modelling adopted from Ozaki et al., (2019) shows that besides upwelling and nutrient supply, alternating Fe(III) production depth is mainly associated with changing light conditions as a result of water transparency. Periodicities reflected by alternating Fe- and Si-rich bands in IFs in our model can thus be associated with: (1) nutrient supply patterns; (2) additional sources of turbidity in the water column such as Fe(III) and Mn(IV) oxide particles, sulphides, and wind-blown silicate particles; or (3) formation and clearing of organic haze in the atmosphere. One or all of these reasons for low light conditions seem to become more important in the Palaeoproterozoic (<2.4 Ga) and could be partly responsible for the more widespread occurrences of shallow marine granular IFs relative to former epochs, which is often assigned to the gradual oxidation of the ocean. Our model shows that variable water transparency should be considered as additional factor for IF deposition especially for shallow marine settings. This model also reasonably explains the prominent layering in BIFs as syn-depositional feature.

High temperature and solar radiation in the Red Sea enhance the dissolution of crude oil from surface films

The Red Sea is a hotspot of biodiversity susceptible to oil pollution. Besides, it is one of the warmest seas on the Earth with highly transparent waters. In this study, we estimated the oil dissolution rates under natural sunlight spectra and temperature conditions using coastal oil slicks collected after the 2019 Sabiti oil spill in the Red Sea. Optical analyses revealed the significant interactive effect of sunlight and temperature in enhancing the dissolution of oil into dissolved organic matter (DOM). The highest oil dissolution rate (38.68 g C m−3 d−1) was observed in full-spectrum sunlight. Oil dissolution significantly enhanced total organic carbon (TOC) and polycyclic aromatic hydrocarbons (PAHs) in seawater. High nucleic acid (HNA) bacteria, likely the oil degraders, proliferated from 30 to 70 – 90% after 4 days. The heavier stable carbon isotopic composition of methane (δ13C-CH4) and lighter stable carbon isotopic composition of carbon dioxide (δ13C-CO2) indicate the putative role of bacterial processes in the natural degradation of crude oil. The results indicated that the combined effect of temperature and solar radiation enhanced the biological and photochemical dissolution of oil on the Red Sea surface.

Long-term prediction of algal chlorophyll based on empirical models and the machine learning approach in relation to trophic variation in Juam Reservoir, Korea

This study analyzed spatiotemporal variation and long-term trends in water quality indicators and trophic state conditions in an Asian temperate reservoir, Juam Reservoir (JR), and developed models that forecast algal chlorophyll (CHL-a) over a period of 30 years, 1993–2022. The analysis revealed that there were longitudinal gradients in water quality indicators along the reservoir, with notable influences from tributaries and seasonal variations in nutrient regimes and suspended solids. The empirical model showed phosphorus was found to be the key determinant of algal biomass, while suspended solids played a significant role in regulating water transparency. The trophic state indices indicated varying levels of trophic status, ranging from mesotrophic to eutrophic. Eutrophic states were particularly observed in zones after the summer monsoons, indicating a heightened risk of algal blooms, which were more prevalent in flood years. The analysis of trophic state index deviation suggested that phosphorus availability strongly influences the reservoir trophic status, with several episodes of non-algal turbidity at each site during Mon. Increases in non-algal turbidity were more prevalent during the monsoon in flood years. This study also highlighted overall long-term trends in certain water quality parameters, albeit with indications of shifting pollution sources towards non-biodegradable organic matter. According to the machine learning tests, a random forest (RF) model strongly predicted CHL-a (R2 = 0.72, p < 0.01), except for algal biomass peaks (>60 μg/L), compared to all other models. Overall, our research suggests that CHL-a and trophic variation are primarily regulated by the monsoon intensity and predicted well by the machine learning RF model.

Smart Water Pollution Management: IoT for Automatic Detection and Prevention

Water quality monitoring is vital for public health and environmental sustainability, but traditional methods face challenges such as high costs, lack of portability, and limited real-time data access. This paper presents a solution using Arduino-based sensors integrated with IoT technology to enhance water quality monitoring. The system employs various sensors to measure parameters like Total Dissolved Solids (TDS), turbidity, water transparency, methane gas, and alcohol gas. Data from these sensors is transmitted to a NodeMCU microcontroller and uploaded to the Blynk cloud platform, allowing real-time monitoring and remote access via customizable dashboards. The proposed system is cost-effective, portable, and provides immediate data access, addressing the limitations of traditional methods. It enables timely detection of water quality issues, facilitating prompt responses to health and environmental threats. This innovative approach significantly advances water quality monitoring by leveraging IoT technologies to improve environmental management practices

Hydrophobic micro-crosslinked sulfonated polystyrene flame retardant for simultaneous fire safety, transparency and high performance of polycarbonate

Sulfonate is considered to be the best flame retardant, which can endow polycarbonate (PC) excellent flame retardancy with low addition. Unfortunately, the water absorption and solubility of sulfonate will increase the cost of transportation and storage. In addition, sulfonate flame retardant is easy to migrate and precipitate from PC composites resulting in a negative impact on the sustainable use of PC materials. To ameliorate this issue, a sulfonate flame retardant (CSPS) with unparalleled hydrophobicity and thermal stability was synthesized through the incorporation of sodium p-styrene sulfonate as the main chain of crosslinked polystyrene. The PC/CSPS composites could pass UL 94 test V-0 rating with 0.3 wt.% CSPS addition, and the LOI is increased from 24.5 % to 31.4 %. Simultaneously, the PC/CSPS composites preserve their initial transparency. Moreover, the combustion test results indicated that the peak of heat release rate (PHRR) and the peak of smoke production rate (PSPR) of PC/CSPS-0.3 composites decreased by 40 % and 41 % respectively, and the time to reach PHRR and PSPR increased by 35.8 % and 56.5 % respectively. These results were attributed to the catalytic char formation and gas phase limitation of CSPS, which made PC composites with higher fire safety. Importantly, the PC/CSPS-0.3 composites can maintain tensile strength similar to that of PC. This research proposes a simplified and efficient methodology for fabricating PC composites with outstanding water resistance, flame retardancy, transparency, and mechanical fortitude, which is of considerable importance for the application of PC composites in emerging fields.

Modeling attenuation of photosynthetically active radiation across the optical gradient in the Laurentian Great Lakes with application to Lake Erie

Representation of subsurface photosynthetically active radiation (PAR) in biophysical models of the Laurentian Great Lakes (LGL) is imperative to their utility as tools for research and management. Here we consolidated measured vertical profiles of subsurface PAR with concurrent water quality (WQ) data from four LGL. We estimated the diffuse attenuation coefficient of PAR (Kd(PAR)) by fitting an exponential function to measured PAR over depth, and evaluated 68 regressions predicting Kd(PAR) as a function of water quality variables (Kd-WQ regressions). We compare four of the top cross-lake calibrated regressions against two published regressions trained on western Lake Erie (WLE) data. Then, as a case study, we demonstrate the utility of our cross-lake calibrated Kd-WQ regressions with a simplified biophysical model of Lake Erie consisting of the Finite Volume Community Ocean Model with submodules for simulating suspended sediment and dissolved organic carbon (FVCOM-SS-DOC). Twenty-five Kd-WQ regressions were identified as candidates for use in biophysical models based on their skill determined via cross-validation. WLE-trained Kd-WQ regressions were less able to simulate Kd(PAR) and PAR in more transparent waters compared to cross-lake calibrated Kd-WQ regressions, which translated to considerable differences in primary production estimates for the central and eastern basins when using WQ data simulated by FVCOM-SS-DOC. A cross-lake calibrated Kd-WQ regression was installed into FVCOM-SS-DOC, which then simulated spatial patterns of suspended sediments and Kd(PAR). These calibrated Kd-WQ regressions can be used in a variety of biophysical models across optically-distinct waters of the LGL to support adaptive management of nutrient inputs and fisheries.

Replenishment of landscape water with reclaimed water: threshold of hydraulic retention time employing transparency as a control indicator

ABSTRACT There exists a significant risk of water blooms during the utilization of recycled water in landscape environments. The nitrogen and phosphorus discharge standards of sewage treatment plants are very low. Controlling hydraulic retention time (HRT) is currently the most effective means to control water bloom. This article proposes a new method for determining the HRT threshold based on water transparency as a control indicator. The following results were obtained: (1) with the nitrogen and phosphorus concentrations of 15 and 0.5 mg/L, respectively, the threshold for HRT under high temperature and strong light is 4.6 days, while the threshold under low temperature and low light is 11.5 days. (2) With the nitrogen and phosphorus concentrations of 10 and 0.3 mg/L, respectively, the threshold for HRT under high temperature and strong light is 5 days, while the threshold under low temperature and low light conditions is 12.3 days. (3) The HRT threshold obtained under high temperature and strong light is lower than that obtained under low temperature and low light conditions. (4) The higher the concentrations of nitrogen and phosphorus, the smaller the HRT threshold obtained. (5) Blue algae have stronger adaptability than green algae and diatoms.

WATER QUALITY OF BATANG MERAO WATERSHED AND IMPLEMENTATION OF LANDSAT 8 OLI FOR THE TRANSPARENCY OF LAKE KERINCI WATERS

This research aims to analyse the water quality of the Batang Merao watershed and the implementation of the algorithm model from Landsat 8 Operational Land Imager (OLI) for the transparency of Lake Kerinci waters. The method used is descriptive quantitative, which is used to obtain measured data on water quality using the Pollution Index (PI) method based on the Decree of the State Minister for the Environment (KEPMENLH) No. 115/2003, PP No. 82/2001, and PP No. 22/2021, as well as the kriging method from an algorithm of the Landsat 8 OLI for total suspended solid (TSS) concentrations with the transparency of the waters of Lake Kerinci. Based on the test results of water samples in the Batang Merao DAS showed that several water quality parameters exceeded the Class II water quality standard PP No. 82/2001, which covers Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), and oil and fats parameters. The relationship between TSS concentration and water transparency of Kerinci Lake has a high coefficient of determination, reaching 0.8344; this indicates the transparency of Kerinci Lake is around 2 m or less. This means that the waters of Lake Kerinci have lower transparency.

Disentangling determinants of nearshore fish and crayfish assemblages in a canyon-shaped Mediterranean reservoir

The distinct origin and hydrological characteristics of reservoirs, shaped by fluctuating water levels and seasonal variations, play a crucial role in determining aquatic species assemblages across diverse limnological zones. This study aimed to analyze fish and crayfish assemblages in the nearshore area of a canyon-shaped Mediterranean reservoir, seeking to identify seasonal and spatial convergent patterns and infer the factors influencing them. Samplings were conducted at five stations along the longitudinal profile of the reservoir at depths around 7 m using gillnets and hoops nets. A seasonal pattern emerged regarding species abundance and biomass, with higher values recorded during the warmer period. Additionally, a spatial trend was observed, indicating higher species abundance in the middle part of the reservoir and lower abundance near the dam, particularly during the colder period. Water transparency, temperature, and the distance from the dam were identified as the most significant factors affecting species assemblages in terms of abundance and biomass. This research provides valuable insights into the intricate interplay between environmental factors, seasonal changes, and the assemblages of aquatic species in a Mediterranean reservoir, contributing to our understanding of its ecological dynamics.

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.

Fabrication, structure, characterization and emulsion application of citrate agar

In this study, citric acid successfully reacted with agar through the dry heat method, and citrate agar (CA) gel was used to stabilize O/W emulsions. The mechanisms of the CA structure and emulsion pH that affected emulsion stabilization were analyzed, and the application of CA gel emulsion (CAGE) was explored. Compared with native agar (NA), CA showed lower gel strength, higher transparency, and higher water contact angle. These changes indicate that a cross-linking reaction occurred, and it was demonstrated via FTIR and NMR. The emulsion properties were evaluated using particle size, ζ-potential, and the emulsification activity index. Results showed that CAGEs had a smaller particle size and lower ζ-potential than the native agar gel emulsion (NAGE). Meanwhile, confocal laser scanning microscopy confirmed that the CA gels stabilized the emulsions by forming a protective film around the oil droplets. Stability experiments revealed that CAGE (prepared with CA gel [DS = 0.145]) exhibited better stability than NAGE in the pH range of 3–11, and the rheological results further confirmed that the stability of the emulsions was influenced by the network structure and oil droplet interaction forces. Afterward, the application prospect of CAGE was evaluated by encapsulating vitamin D3 and curcumin.

Quantifying minimum survey effort to reliably detect Amazonian manatees using an unoccupied aerial vehicle (UAV) at an ex situ soft-release site

Detection of many threatened aquatic mammals, such as manatees (Trichechus spp.), using traditional visual observation methods is associated with high uncertainty due to their low surfacing times, cryptic behaviors, and the environmental heterogeneity of their habitats. Rapid advancements in technology provide an opportunity to address these challenges. In this study, we aimed to quantify survey effort of unoccupied aerial vehicles (UAVs) for detecting the Vulnerable Amazonian manatee (T. inunguis). Using a closed population of manatees that is being rehabilitated within a lake at the Rainforest Awareness, Rescue, and Education Center in Iquitos, Peru, we calculated the number of repeat surveys needed to detect at least one individual with 95% (n = 3.10) and 99% (n = 4.76) confidence. We used both generalized linear mixed-effect models and Bayesian single-species and single-season detection models to determine the effects of the environment (water depth, water transparency, cloud cover, wind speed), time of day, and behavior (breathing, foraging, milling) on the time-to-detection and detection probability, respectively. Both models indicated a significant interaction between water depth and water transparency, causing an increase in the time-to-detection (β = 0.032; 95% CI = 0.028, 0.037) and a decrease in the probability of detecting manatees (α = -0.65; 95% CI = -1.3, -0.007), which was calculated to be 0.62 (95% CI = 0.23, 0.94). Due to the similarities between the lake and in situ habitats, the results of this study could be used to design in situ UAV survey protocols for Amazonian manatees or other difficult-to-detect freshwater aquatic mammals and to monitor ex situ animals pre-and post-release, which should ultimately contribute to a better understanding of their spatial ecology and facilitate data-driven conservation efforts.