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The article deals with the removal of humic substances from surface water in the High Tatras locality and with the reduction in the intensity of water coloration. Four different types of granular activated carbon (Norit 1240, WG12, Filtrasorb TL830, and Filtrasorb 300) were compared in the experiments. The quality of the water from the water source supplied to the filter columns, and the water at the outlet, the filtration speed, and the efficiency of sorption media were monitored. The results showed more than 70% efficiency in the removal of humic substances and CODMn from water, but only about 50% efficiency from the point of view of water color, as determined with the technology used. [ABSTRACT FROM AUTHOR]

The article deals with the removal of humic substances from surface water in the High Tatras locality and with the reduction in the intensity of water coloration. Four different types of granular activated carbon (Norit 1240, WG12, Filtrasorb TL830, and Filtrasorb 300) were compared in the experiments. The quality of the water from the water source supplied to the filter columns, and the water at the outlet, the filtration speed, and the efficiency of sorption media were monitored. The results showed more than 70% efficiency in the removal of humic substances and CODMn from water, but only about 50% efficiency from the point of view of water color, as determined with the technology used.

The work consisted in functionalizing gold nanoparticles to analytically detect heavy metals in contaminated water; in Tayacaja-Huancavelica-Peru, using physical method of laser ablation. The 450 mJ/p Nd:YAG was used as a pulsed laser generator for the production of colloids from AuNPs by the top-down approach; the target was a 1 cm x 1.5 cm high purity gold metallic plate with a thickness of 1 mm, inside a 20 ml cuvette of deionized water, containing 5 ml of L-Cysteine ≥ 75% purity. Nanoparticle colloids were characterized by UV-Vis spectroscopy from 200 to 1160 nm range. Using a convex lens, the gold metal plate was ablated by the laser equipment, located 10 cm from the focus; with λ = 1064 nm and λ = 532 nm with energy equivalent to 60.28 mJ/p and 32.99 mJ/p respectively, with a ratio of 2 Hz, for 30 and 60 min. All the samples produced were subjected to the dispersion process by sonication at 40 KHz for one hour. The functionalized nanoparticles presented a resonance displacement of the maximum wavelength peak with respect to the reference at approximately 22.51 nm; consequently, the increase in diameter occurred at 52.10 nm. The sensitive capacity of the functionalized nanoparticles was verified for different concentrations of analytes in water, made up of divalent heavy metal ions Cd2+, Pb2+, and trivalent nonmetal As3+. At a concentration greater than 500 uM, the color of the functionalized nanoparticles turned bluish, due to the presence of positive ions. Therefore, it was stated that the functionalized nanoparticles enable the detection of heavy metals in water by color variation. [ABSTRACT FROM AUTHOR]

Color is an important soil property, and is frequently used to infer soil properties such as total iron (Fe). However, soil water affects the soil color and severely limits the estimation accuracy for Fe. To improve the Fe estimation accuracy, the water-absorption-peak-based color reconstructing machine (WCRM) method was proposed and investigated in this study. The rapid dewatering functions of the WCRM method were designed based on machine learning concepts and the two water absorption troughs of visible and near-infrared light (around 1400 and 1900 nm). Color and water data for the soil samples were obtained using an ASD FieldSpec 3 spectrometer under laboratory conditions. The optimal Fe model (1900 group; i = 0.5, j = 4.5, k = 2.5) for the WCRM method was obtained to determine the final WCRM model, which produced better results (R 2 = 0.603, MREv = 6.6%, RMSEv = 2.914 g/kg, RPDv = 1.483, and RPIQv = 2.492) than the adaptive neuro-fuzzy inference system model. The WCRM method represents a new way of accurately estimating Fe and other soil properties. • The water-absorption-peak-based color reconstructing machine (WCRM) method was proposed. • The two water absorption peaks around 1400 and 1900 nm was used for color reconstructing. • The WCRM model was established based on reconstructed L∗a∗b∗ values. • This method can quickly reduce the influence of soil water during Fe multicolor modeling. [ABSTRACT FROM AUTHOR]

Spectral diffuse attenuation coefficient of down-welling irradiance (K d (λ)) is a fundamental optical parameter for water color and of significance for heat budget calculation, photosynthesis modeling and carbon sequestration. Uncertainties exist in both in situ measured and satellite derived K d (λ), therefore, evaluation of its data quality is essential. In addition, optical water classification of K d (λ) is still limited. To address these issues, we proposed an optical water classification and quality control model (OC_QC model) based on a globally collected high-quality in situ K d (λ) data. The model consists of the reference K d (λ) spectra for 7 optical water types (OWT, ranging from clear open ocean water to highly turbid water) and a scoring system. An individual K d (λ) spectrum can be assigned an OWT and quality control score (QC score) with this model. The performance of the OC_QC model is tested with independent in situ K d (λ) spectra from the turbid coastal water (Bohai Sea) and clear oceanic water (Indian Ocean). Questionable or erroneous K d (λ) spectra can be identified, suggesting the model's robustness. The model was also evaluated with the Medium Resolution Imaging Spectrometer (MERIS) Level-2 and the Moderate Resolution Imaging Spectroradiometer (MODIS) Level-3 K d (λ) data in the Bohai Sea, Yellow Sea, East China Sea and South China Sea. Satellite derived maps clearly showed the spatial and temporal variations of OWTs and QC scores, and the regions of low-quality K d (λ) were reasonably extracted. Global maps of K d (λ)-based optical water types and corresponding QC scores were also obtained with OC_QC model. With the quality controlled K d (λ) data, the retrieval accuracy of Secchi disk depth was improved. The retrieval accuracies of Chlorophyll-a concentration and total seawater absorption coefficient were also improved with the K d (λ) optical water classification based algorithms. The OC_QC model would be valuable for evaluating K d (λ) data (especially the operational global K d (λ) products), investigation of water optical properties, and development and merging of bio-optical algorithms. [ABSTRACT FROM AUTHOR]

One of the important living organisms in stagnant waters, surface waters, water reservoirs, pools and dams is microalgae. Various methods have been developed and studied for the removal of these microscopic organisms from drinking water, of which the sedimentation or flocculation is one of the significant methods. The method is based on using sediments substance or flocculants. This study aimed to introduce feasible, harmless and suitable biological flocculants and evaluate their ability to precipitate Cyclotella diatoms. The presence of a large number of Cyclotella diatoms in water creates an unpleasant color and odor in the water. For this purpose, autoflocculation–sedimentation and bioflocculation processes were used to harvest Cyclotella. The effect of pH, mixing speed and time on harvest efficiency for autoflocculation–sedimentation and bioflocculation processes was investigated. The autoflocculation results showed that the removal efficiency increased with increasing pH, decreasing mixing speed and increasing settling time. For bioflocculation, Scenedesmus microalgae were used to isolate Cyclotella diatoms, and by examining the parameters affecting the rate of microalgae isolation, the optimal conditions have been determined. The ratio of 1:1 combination of microalgae–diatomaceous earth and pH = 10 and residence time of 120 min can yield up to 83% isolation and sedimentation of Cyclotella microalgae, which is a very efficient and inexpensive environmentally friendly method for the separation of infected microalgae from used drinking water. [ABSTRACT FROM AUTHOR]

Water color is an important representation reflecting the characteristics of its quality in inland lakes or ponds; however, sufficient water color image samples are often difficult to obtain due to the limitation of fishery production. For few color image samples, the existing data enhancement methods based on the depth generation model have the problems of low quality of generated data, difficulty of network training, and so on; moreover, for image classification, traditional methods based on convolutional neural network (CNN) cannot effectively extract the potential manifold structure features in the image and the full connection layer in CNN cannot simulate biological neurons well, resulting in high time cost and low efficiency. In this paper, a water quality classification method has been proposed to solve the above problems, the improved semisupervised triple-generation adversarial network (triple-GAN) algorithm is used to enhance the few water color image samples, and the feature data can then be extracted from enhanced data by manifold learning method t-distributed stochastic neighborhood embedding (t-SNE). Moreover, convolutional spiking neural network (CSNN), in which spiking neural network (SNN) has replaced the original full connection layer of CNN, is used for final water quality classification. The main contribution of this paper is to build a new algorithm framework, introduce triple-GAN and CSNN into the field of classification of few water color image samples for the first time, and make an exploration of integrating artificial intelligence (AI) and water quality analysis problems. By comparing with traditional methods, the proposed method is proved to have the advantages of less time-consuming, low operation cost, and high classification accuracy. [ABSTRACT FROM AUTHOR]

Knowledge of the evolution of the littoral zone over time is paramount for coastal science and coastal zone management. However, traditional bathymetric surveys using echo-sounding techniques are unsuitable for large-scale applications due to a variety of constraints. On the other hand, remote sensing data such as satellite imagery allow for the development and application of bathymetry inversion models on a large scale. Deep learning is a growing field of artificial intelligence that allows for the automatic construction of models from data and has been successfully used for various Earth Observation and model inversion applications. In this work, we develop and apply a deep learning-based depth inversion model combining wave kinematics and water color information from Sentinel-2 satellite imagery. We present two different satellite image processing methods to augment wave kinematics and color information as inputs to the proposed deep learning-based models. We show competitive results with a state-of-the-art physical inversion method for satellite derived bathymetry, Satellite to Shores (S2Shores), demonstrating a promising direction for the use of deep learning models in Satellite Derived Bathymetry (SDB) and Earth observation in general. [ABSTRACT FROM AUTHOR]

In this study, Profoks reactor (Cold Atmospheric Plasma reactor based on Dielelectric Barrier Discharge) was used for the treatment of textile wastewater and then the usability of the recycled water in the reactive dyeing process was investigated. After processing of 30 L textile wastewater with Profoks system under laboratory conditions, 99% efficiency was obtained in chemical oxygen demand (COD) and total suspended solid (TSS) parameters. In the wastewater sample, the treated water color amount was reduced to less than 1.5 units in Pt-Co and the conductivity value was reduced to 7790 Us/cm. In dyeing of 100% cotton Ne 30/1 single jersey (190 g/m2) fabric with reactive dyes having azo chromophore group under laboratory conditions, the dyeings made with recovery water with Profoks system were similar to those dyed with osmosis water in terms of color, levelness and fastness performance. [ABSTRACT FROM AUTHOR]

In the context of global climate change, a significant increase in the active layer thickness (ALT) of permafrost is expected in the current century. This process has been observed by researchers over the past few decades. If the current climate trend continues, an increase in ALT may have a significant impact on the concentration of organic matter in Arctic river waters. The relationship between the thickness of the seasonally thawed layer of permafrost and the concentration of dissolved organic matter in river waters has been explored using clustering, one-way ANOVA, and cross-tabulation analysis. The data set for analysis included original details on the content of organic matter in the rivers of Eastern Siberia (in terms of COD, BOD5, and the color of the water), phytoplankton abundance and biomass, and data on the permafrost active layer thickness (ALT) in the catchments. It was revealed that in the areas of catchments where the ALT is deeper, the content of organic matter in the rivers is lower than in areas with a shallow, seasonally thawed permafrost. Our results are consistent with the existing conceptual model of the influence of ALT on the chemistry of river waters in the cryolithozone. This knowledge is important for predicting the chemical composition of the Arctic rivers, eutrophication, and the rate of inflow of dissolved solids into the Arctic Ocean under the current conditions of ALT deepening. [ABSTRACT FROM AUTHOR]

In Brazil, approximately 99% of malaria cases are concentrated in the Amazon region. An acute febrile infectious disease, malaria is closely related to climatic and hydrological factors. Environmental variables such as rainfall, flow, level, and color of rivers, the latter associated with the suspended sediment concentration, are important factors that can affect the dynamics of the incidence of some infectious diseases, including malaria. This study explores the possibility that malaria incidence is influenced by precipitation, fluctuations in river levels, and suspended sediment concentration. The four studied municipalities are located in two Brazilian states (Amazonas and Pará) on the banks of rivers with different hydrological characteristics. The results suggest that precipitation and river level fluctuations modulate the seasonal pattern of the disease and evidence the existence of delayed effects of river floods on malaria incidence. The seasonality of the disease has a different influence in each municipality studied. However, municipalities close to rivers with the same characteristic color of waters (as a function of the concentration of suspended sediments) have similar responses to the disease. [ABSTRACT FROM AUTHOR]

Establishing factors that affect contaminants including potentially toxic metals in a freshwater and its surrounding soil is necessary to control the transfer of toxins into the food chain. We documented the seasonality in temperature, dissolved oxygen (DO), soil organic carbon (SOC), pH, and water color on the behavior of toxic metals in water and soil of Lake Nike. Slope and seasons statistically related significantly (p < 0.05) with DO and SOC. Only Ni was not statistically related significantly to pH, water color, and temperature of the water, while mercury and cadmium statistically related significantly to the soil pH. Temperature and pH were within the WHO safety limits which are 20–32 °C and 6.5–8.5, respectively, in both water and soil samples. Potentially toxic metals levels for lead (Pb) (0.47–2.10 mg/L), mercury (Hg) (0.57–2.01 mg/L), cadmium (Cd) (0.34–1.82 mg/L), and nickel (Ni) (0.56–2.09 mg/L) exceeded the 0.01, 0.001, 0.003, and 0.02 mg/L WHO safety limits, respectively, while Zinc (Zn) level which ranged from 0.24 to 2.51 mg/L was within the WHO limit (5 mg/L) and the standard organization of Nigeria (SON) limit (3.0 mg/L) in both seasons. From our study, Lake Nike could be relatively toxic, and unsafe for aquatic habitation and human consumption. [ABSTRACT FROM AUTHOR]

In recent decades, the increase in terrestrial inputs to freshwater and coastal ecosystems, especially occurring at northern latitudes, has led to a process of water color darkening known as "brownification." To assess how brownification affects plankton community composition and functioning in northern coastal areas, an in situ mesocosm experiment using a highly colored humic substance to simulate a brownification event was performed in a North Atlantic bay (Hopavågen, Norway) in August 2019. Manual sampling for analyses of nutrient concentrations, phytoplankton pigments and zooplankton abundances was combined with high‐frequency (every 15 min) monitoring of key environmental variables to investigate the response of the plankton community in terms of oxygen metabolism and community composition. In response to brownification, the oxygen gross primary production (GPP) and community respiration (R) slowed down significantly, by almost one‐third. However, GPP and R both decreased to the same extent; thus, the oxygen metabolic balance was not affected. Moreover, the chlorophyll‐a concentration significantly decreased under brownification, by 9% on average, and the chemotaxonomic pigment composition of the phytoplankton changed, indicating their acclimation to the reduced light availability. In addition, brownification seemed to favor appendicularians, the dominant mesozooplankton group in the mesocosms, which potentially contributed to lowering the phytoplankton biomass. In conclusion, the results of this in situ mesocosm experiment suggest that brownification could induce significant changes in phytoplankton and zooplankton community composition and significantly alter the overall oxygen metabolism of plankton communities in a northern Atlantic bay. [ABSTRACT FROM AUTHOR]

Increasing iron (Fe) concentrations are found in lakes on a wide geographical scale but exact causes are still debated. The observed trends might result from increased Fe loading from the terrestrial catchment, but also from changes in how Fe distributes between the water column and the sediments. To get a better understanding of the causes we investigated whether there has been any change in the sediment formation of Fe sulfides (FeS) as an Fe sink in response to declining atmospheric sulfur (S) deposition during recent decades. For our study, we chose Lake Bolmen in southern Sweden, a lake for which we confirmed that Fe concentrations in the water column have strongly increased along with water color during 1966–2018. Our investigations showed that Fe accumulation and speciation varied independently of S accumulation patterns in the Lake Bolmen sediment record. Thus, we were not able to relate the positive trend in Fe concentrations to reduced FeS binding in the sediments. Furthermore, we found that Fe accumulation rates increased along with lake water Fe concentrations, indicating that increased catchment loading rather than a change in the distribution between the sediments and the water column has driven the increase in Fe concentrations. The increased loading may be due to land‐use change in the form of an extensive expansion of coniferous forest during the past century. Altered forest management practices and increased precipitation may have led to enhanced weathering and erosion of organic soil layers under aging coniferous forest. Plain Language Summary: Iron concentrations are increasing in freshwaters in the Northern Hemisphere. One possible explanation is a decline in sulfur deposition in recent decades, which may have led to lower iron sulfide formation in soils and sediments, and thus to increased lake water iron concentrations. We tested this hypothesis by exploring iron concentrations in water and sediments of Lake Bolmen in southern Sweden in relation to changes in sulfur deposition, climate and catchment land‐use. We also investigated if iron sulfides were more abundant in sediments deposited during peak sulfur deposition. We found higher sediment accumulation of sulfur, but not iron, during this period. Iron sulfides were present in the sediments, but other iron forms dominated, indicating that the declined sulfur deposition is not the main driver behind lake water iron increases. A more likely explanation is a higher spruce forest cover around the lake, since soils below spruce are large sources of organic matter and iron to freshwaters. Increasing iron concentrations contribute to browning, causing concern for aquatic ecosystems, and complicating water treatment processes for lakes supplying drinking water. Thus, this study contributes needed knowledge on trend drivers, which is useful if mitigations to reduce undesirable high iron concentrations are needed. Key Points: Lake water iron concentration increase not due to less sulfide binding, as iron accumulation and speciation independent of sulfur dynamicsPositive trend in lake water iron concentration along with iron accumulation increase suggest increased catchment loading as driverExpansion of coniferous forest and increased precipitation may explain higher catchment export of iron from acidic and organic soil layers [ABSTRACT FROM AUTHOR]

Benthic gross primary production (GPP) is often the most important part of aquatic food webs in northern lakes, which are gradually warming and receiving increased terrestrial colored dissolved organic carbon loadings due to global change. Yet, measurements of benthic GPP are fairly uncommon, and methods and unit dimensions of benthic GPP are unstandardized and rarely compared. In this study, we measured benthic GPP in 27 headwater lakes from three regions in northern Sweden and analyzed potential constraining drivers of benthic GPPz rates at discrete depths and estimates of benthic GPP averages across the whole lake, as well as across the littoral zone. We also compared in situ measurements of benthic GPP averages across the whole lake with modeled values using the "autotrophic structuring model." We found that benthic GPPz rates were best explained by, and positively related to, available light (i.e., a function of depth and water color) and temperature. Benthic GPP averages across the whole lake, on the contrary, were best explained by the relative size of the littoral area, which is a measure that combines lake bathymetry and water color. The comparison between in situ measured and modeled estimates of benthic GPP averages across the whole lake revealed that (1) the autotrophic structuring model underestimates GPP at low values and overestimates GPP at high values compared with measured data, and that (2) measured values were related to temperature, which is not included as a variable in the autotrophic structuring model. Considering future predicted changes impacting northern latitude lakes, our results suggest that increased lake water temperatures can to some extent mitigate the negative impacts of reduced light availability from lake browning on benthic GPPz rates. The combined impact of these changes on benthic GPP averages across the whole lake will depend on, and be moderated by, lake bathymetry determining the relative size of the littoral area. [ABSTRACT FROM AUTHOR]

Aspicilia humida Lee is described as a new lichen-forming fungus from a wetland forest, South Korea. The new species is distinguishable from Aspicilia aquatica (Fr.) Körb., the most similar species, by the absence of prothallus, black disk without green color in water, olivebrown epihymenium, shorter hymenium, hymenium I + yellowish blue-green, wider paraphysial tips without a vivid pigment, smaller asci, smaller ascospores, and the presence of stictic acid. Molecular analyses employing internal transcribed spacer (ITS) and mitochondrial small subunit (mtSSU) sequences strongly support A. humida as a distinct species in the A. cinerea group. A surrogate key is provided to assist in the identification of all 28 aspicilioid species of Korea. [ABSTRACT FROM AUTHOR]

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In a water treatment plant, the decision to carry out a jar test, for determining the required coagulant dosage, is made based on notable changes in treated water qualities such as treated water turbidity and color, which is essentially a reactive response to changes in water qualities. In addition, until a change that the operator deems as 'significant' occurs, the plant tends to use the same dosage determined previously using the jar test for an elongated period of time. In this study, artificial neural network (ANN) models were developed to proactively decide what coagulant dosages to use based on changes in raw water parameters. Use of ANNs also prevents the regular use of costly chemicals used for jar tests and enables responding to sudden changes in water qualities. The general regression neural network (GRNN) and extreme learning machine neural networks require minimal computational effort for model development as they involve minimal model parameters and their training algorithms are not iterative. The current study determines the more convenient and efficient model of the two for aiding the coagulation process. The GRNN and ELM-RBF models predicted test data with R values of 0.9737 and 0.9783, respectively. It was noted that the GRNN was prone to overfitting and the ELM-RBF model demonstrated higher generalization ability than the GRNN. Therefore, it was concluded that the ELM-RBF model was the more suitable model for the prediction of the coagulant dosage. [ABSTRACT FROM AUTHOR]

Predators can strongly influence disease transmission and evolution, particularly when they prey selectively on infected hosts. Although selective predation has been observed in numerous systems, why predators select infected prey remains poorly understood. Here, we use a mathematical model of predator vision to test a long‐standing hypothesis about the mechanistic basis of selective predation in a Daphnia–microparasite system, which serves as a model for the ecology and evolution of infectious diseases. Bluegill sunfish feed selectively on Daphnia infected by a variety of parasites, particularly in water uncolored by dissolved organic carbon. The leading hypothesis for selective predation in this system is that infection‐induced changes in the transparency of Daphnia render them more visible to bluegill. Rigorously evaluating this hypothesis requires that we quantify the effect of infection on the visibility of prey from the predator's perspective, rather than our own. Using a model of the bluegill visual system, we show that three common parasites, Metschnikowia bicuspidata, Pasteuria ramosa, and Spirobacillus cienkowskii, decrease the transparency of Daphnia, rendering infected Daphnia darker against a background of bright downwelling light. As a result of this increased brightness contrast, bluegill can see infected Daphnia at greater distances than uninfected Daphnia—between 19% and 33% further, depending on the parasite. Pasteuria and Spirobacillus also increase the chromatic contrast of Daphnia. These findings lend support to the hypothesis that selective predation by fish on infected Daphnia could result from the effects of infection on Daphnia's visibility. However, contrary to expectations, the visibility of Daphnia was not strongly impacted by water color in our model. Our work demonstrates that models of animal visual systems can be useful in understanding ecological interactions that impact disease transmission. [ABSTRACT FROM AUTHOR]

Organisms are facing global climate change and other anthropogenic pressures, but most research on responses to such changes only considers effects of single drivers. Observational studies and physiological experiments suggest temperature increases will lead to faster growth of small fish. Whether this effect of warming holds in more natural food web settings with concurrent changes in other drivers, such as darkening water color ("browning") is, however, unknown. Here, we set up a pelagic mesocosm experiment with large bags in the Baltic Sea archipelago, inoculated with larval Eurasian perch (Perca fluviatilis) and zooplankton prey and varying in temperature and color, to answer the question how simultaneous warming and browning of coastal food webs impact body growth and survival of larval perch. We found that browning decreased body growth and survival of larval perch, whereas warming increased body growth but had no effect on survival. Based on daily fish body growth estimates based on otolith microstructure analysis, and size composition and abundance of available prey, we explain how these results may come about through a combination of physiological responses to warming and lower foraging efficiency in brown waters. We conclude that larval fish responses to climate change thus may depend on the relative rate and extent of both warming and browning, as they may even cancel each other out. [ABSTRACT FROM AUTHOR]

Intensification of brown color in surface waters has been observed over several decades in many areas. We examined a 64‐yr daily record (1947–2010) of visual water color, a measure of chromophoric dissolved organic matter (CDOM), in the Mississippi River at Minneapolis, Minnesota. Although no monotonic trends in daily or mean annual color were evident, our analyses revealed trends in seasonal metrics, for example, mean winter color, on decadal scales related to changes in flow (hence climatic conditions). A pattern of high color (CDOM) in late spring and summer, corresponding with higher flow, was found across the period. Daily flow accounted for ~ 50% of the variance in color, and a lag of four days was found between peak responses of flow and color, supporting a CDOM source from wetlands in northern parts of the basin. The slope of the color‐flow relationship increased over the 64 yr, driven by increased CDOM flushing in late summer‐early fall. Based on trends in seasonally aggregated color and discharge, minimum and mean color and flow increased during winter over the 64 yr, potentially due to higher temperatures. Summer months did not show increases, but color became less variable. As a result, the color difference between summer and winter became smaller over the study period. During high flow events (ice‐out or high precipitation), some hysteretic color patterns were observed consistent with observations on other large rivers. Our results indicate that long‐term color (CDOM) trends in the Mississippi Headwaters reach are related to seasonally dominant changes in climatic conditions. [ABSTRACT FROM AUTHOR]

Several floodplain lakes of the Orinoco River have been impacted by alkaline alumina-refining waste including red mud, a by-product from the Bayer process. Some of these impacted lakes have undergone algal overgrowth, which has been detected due to the unusual green color of water and the dissolved oxygen oversaturation. Thus, we conducted sampling campaigns in impacted and non-impacted lakes to measure the concentration of nitrogen (N) and phosphorous (P) in water to detect any change in the nutrient levels. Despite the content of N and P in red mud is low, our findings suggest that N is released from red mud accumulated in bed sediments to the water column in the impacted lakes, increasing the content of total N. However, the total P concentrations in impacted lakes were not affected from their background values probably due to the strong adsorptive behavior of P onto red mud minerals. [ABSTRACT FROM AUTHOR]

The bloom‐forming freshwater alga Gonyostomum semen is associated with acidic, mesotrophic brown water lakes in boreal regions. However, researchers have been unable to conclusively link G. semen abundance and bloom formation to typical brown water lake traits, that is, high water color and DOC (dissolved organic carbon) concentrations. Iron is a main driver of water color in boreal lakes, and a recent study of lake monitoring data indicated a connection between lakes with high G. semen abundance and iron concentrations >200 µg · L−1. Thus, iron may be the missing link in explaining G. semen abundance and growth dynamics. We experimentally assessed the effects of different iron concentrations above or below 200 µg · L−1 on the growth of G. semen batch monocultures. Iron concentrations <200 µg · L−1 limited G. semen growth, while iron concentrations >200 µg · L−1 did not. Moreover, the iron concentration of the medium required for growth was higher than for other common phytoplankton (Microcystis botrys and Chlamydomonas sp.) included in the experiment. These results indicate that G. semen requires high levels of iron in the lake environment. Consequently, this and previous findings using lake monitoring data support the hypothesis that high concentrations of iron favor the formation of high‐density G. semen blooms in boreal brown water lakes. As lakes get browner in a changing climate, monitoring iron levels could be a potential tool to identify lakes at risk for G. semen blooms, especially among lakes that provide ecosystem services to society. [ABSTRACT FROM AUTHOR]

Manteca yellow dry beans (Phaseolus vulgaris L.) have many quality traits that appeal to consumers, including fast cooking times, creamy texture, and sweet, buttery flavor. They are native to Chile and consumed in regions of South America and Africa but are largely unfamiliar to United States consumers. While cooking time, flavor, and texture have not been prioritized in United States dry bean breeding programs, genetic variability exists such that these traits could be addressed through breeding. In this study, a recombinant inbred line (RIL) population was developed from a cross between Ervilha (Manteca) and PI527538 (Njano), yellow dry beans with contrasting cooking time and sensory attributes. The population and parents were grown for 2 years in Michigan and evaluated for cooking time and sensory attribute intensities, including total flavor, beany, vegetative, earthy, starchy, sweet, bitter, seed-coat perception, and cotyledon texture. Cooking time ranged 19–34 min and exhibited high broad-sense heritability (0.68). Sensory attribute intensities also exhibited variation among RILs, although broad-sense heritability was low, with beany and total flavor exhibiting the highest (0.33 and 0.27). A linkage map of 870 single nucleotide polymorphisms markers across 11 chromosomes was developed for quantitative trait loci (QTL) mapping, which revealed QTL for water uptake (3), cooking time (6), sensory attribute intensities (28), color (13), seed-coat postharvest non-darkening (1), seed weight (5), and seed yield (2) identified from data across 2 years. Co-localization was identified for starchy, sweet, and seed-coat perception on Pv01; for total flavor, beany, earthy, starchy, sweet, bitter, seed-coat perception, cotyledon texture, and color on Pv03; water uptake and color on Pv04; total flavor, vegetative, sweet, and cotyledon texture on Pv07; cooking time, starchy, sweet, and color on Pv08; and water uptake, cooking time, total flavor, beany, starchy, bitter, seed-coat perception, cotyledon texture, color, and seed-coat postharvest non-darkening on Pv10. The QTL identified in this work, in particular CT8.2 and CT10.2, can be used to develop molecular markers to improve seed quality traits in future dry bean varieties. Considering yellow dry beans already excel in quality and convenience, they might be an ideal market class to signal a new focus on consumer-valued traits in the United States. [ABSTRACT FROM AUTHOR]

The matamatas (Chelus fimbriata and the recently described Chelus orinocensis) are the largest species in the family Chelidae, easily identified by their distinct morphological characteristics. The matamatas have a wide distribution in South America, occurring in Bolivia, Brazil, Colombia, Ecuador, Guyana, French Guiana, Peru, and Venezuela, as well as Trinidad and Tobago. However, there are many gaps in the knowledge of its distribution. The objective of this study was to present new records of occurrence for the C. fimbriata species complex and describe the area of distribution. We compiled data from published papers, databases in museums and other scientific collections, and research institutes and conservation organizations. From these data we mapped the species distribution, considering 3 types of river drainages based on water color in the Amazon Basin. We added 182 new records in Brazil, Venezuela, Colombia, Bolivia, and Peru, demonstrating that the C. fimbriata species complex has a wide distribution, totaling 6,907,551 km2 across all 3 river types. Most records were concentrated in areas lower than 200 m above sea level. [ABSTRACT FROM AUTHOR]

Recently, rising distress over ecological pollution owing to water contamination by coloring effluents primarily due to dyes is of growing concern. The development of semiconductor/magnetic oxide–based nanomaterials has verified to be a potent remediation means for water pollution. In the present article, the fabrication of nanocomposites was carried out by the facile hydrothermal method. The ZnO and ZnSe nanoparticles were in situ formed on the α-Fe2O3 layer, thereby forming a heterojunction. The prepared α-Fe2O3/ZnSe nanocomposite possessed a degradation of 98.9% for a Congo red aqueous solution of 100 ppm. The α-Fe2O3/ZnO nanocomposite showed only 26% degradation of 100 ppm dye solution depicting a poor photocatalytic performance. This is attributed to the formation of recombination-enhanced configuration (type-I heterostructure) in the α-Fe2O3/ZnO nanocomposite (NC). In contrast, α-Fe2O3/ZnSe NC accomplished a higher and enhanced photocatalytic response. The key rationale for elevated photocatalytic response is the establishment of a recombination-free configuration (type-II heterostructure). Thus, α-Fe2O3/ZnSe NC known as one of outstanding nanoparticle-nanocomposite photocatalysts was synthesized under mild conditions exclusive of some multifaceted post-treatment, for dye abatement process. [ABSTRACT FROM AUTHOR]

In recent years, object recognition and detection technology, which is a very important research direction in the field of computer vision, is widely used in human life. The technology has been relatively mature for the recognition of objects such as people and objects on land. However, due to some conditions, it is relatively rare in the marine field. The reasons for the analysis mainly include two points: underwater classification and localization are affected by multiple factors such as illumination uniformity, occlusion and water color, and secondly, underwater video acquisition is also relatively difficult. These issues have long been the focus of attention. Therefore, effective classification and recognition of objects in underwater video is of great significance for the intelligentization of marine equipment. This paper mainly locates and classifies the images of seacucumber, scallop, seaurchin. This paper uses two algorithms that are widely used at present to texperiment with underwater image dataset. The experimental results show that the mean Average Precision (mAP) of YOLOv3 algorithm is 6.4% higher than Faster R-CNN, and the recall rate (Recall) is 13.9% higher. Moreover, the detection speed of the YOLOv3 algorithm is 20Fps, which is 12Fps higher than the speed of Faster R-CNN. The detection speed of the YOLOv3 algorithm basically meets the real-time detection requirements in this experiment. [ABSTRACT FROM AUTHOR]

Multiple studies have reported widespread browning of Northern Hemisphere lakes. Most examples are from boreal lakes that have experienced limited human influence, and browning has alternatively been attributed to changes in atmospheric deposition, climate, and land use. To determine the extent and possible causes of browning across a more geographically diverse region, we examined watercolor and dissolved organic carbon (DOC) time series in hundreds of northeastern U.S. lakes. The majority of lakes have increased in both DOC and color, but there were neither coherent spatial patterns in trends nor relationships with previously reported drivers. Color trends were more variable than DOC trends, and DOC and color trends were not strongly correlated, indicating a cause other than or in addition to increased loading of terrestrial carbon. Browning may be pronounced in regions where climate and atmospheric deposition are dominant drivers but muted in more human‐dominated landscapes with a limited extent of organic soils where other disturbances predominate. [ABSTRACT FROM AUTHOR]

Water colour is the result of its constituents and their interactions with solar irradiance; this forms the basis for water quality monitoring using optical remote sensing data. The Forel-Ule Index (FUI) is a useful comprehensive indicator to show the water colour variability and water quality change in both inland waters and oceans. In recent decades, lakes around the world have experienced dramatic changes in water quality under pressure from both climate change and anthropogenic activities. However, acquiring consistent water colour products for global lakes has been a challenge. In this paper we present the first time series FUI dataset for large global lakes from 2000–2018 based on MODIS observations. This dataset provides significant information on spatial and temporal changes of water colour for global large lakes during the past 19 years. It will be valuable to studies in search of the drivers of global and regional lake colour change, and the interaction mechanisms between water colour, hydrological factors, climate change, and anthropogenic activities. Measurement(s) color Technology Type(s) satellite imaging Factor Type(s) temporal interval Sample Characteristic - Environment water body • lake Sample Characteristic - Location global Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.13257218 [ABSTRACT FROM AUTHOR]

Rivers are among the most imperiled ecosystems globally, yet we do not have broad‐scale understanding of their changing ecology because most are rarely sampled. Water color, as perceived by the human eye, is an integrative measure of water quality directly observed by satellites. We examined patterns in river color between 1984 and 2018 by building a remote sensing database of surface reflectance, RiverSR, extracted from 234,727 Landsat images covering 108,000 kilometers of rivers > 60 m wide in the contiguous USA. We found 1) broad regional patterns in river color, with 56% of observations dominantly yellow and 38% dominantly green; 2) river color has three distinct seasonal patterns that were synchronous with flow regimes; 3) one third of rivers had significant color shifts over the last 35 years. RiverSR provides the first map of river color and new insights into macrosystems ecology of rivers. Plain Language Summary: Rivers can appear different colors such as blues, greens, browns, and yellows. Water color is linked to water quality and can be related to the amount of sediment, algae, and dissolved organic carbon in water. Humans can therefore discern waters' suitability for use with our eyes. While we know many rivers are impaired globally, often due to poor water quality, the color of rivers has not been widely measured to investigate changes through space and time. Satellites act as "eyes in the sky" and regularly observe earth's large rivers. Using satellite remote sensing records from 1984 to 2018, we measured the color of rivers across the USA. We found that large rivers have distinct seasonal patterns in color that change with river flow, and that the dominant color in one third of rivers has significantly changed. Observations of water color can pinpoint rivers undergoing rapid environmental change and work toward continental‐scale understanding of rivers. Key Points: ∼15.9 million satellite observations over 35 years show USA rivers (>60 m wide) are dominantly yellow and green in colorRiver color has three distinct seasonal patterns that are synchronous with flow regimesRiver color significantly changed over the last three decades in one third of large US rivers [ABSTRACT FROM AUTHOR]

Hyperspectral resolution image products of a synthetic sensor featuring the high spatial resolution of the space-borne sensor can offer cost-effective means for enhancing our current capabilities in terms of providing an array of images in lieu of designing an expensive system for image acquisition, which can serve the expanding needs of the scientific and user communities for various critical water color applications. Despite several studies on enhancing the capability of land remote sensing sensors, full spectrum reconstruction of water color images with varying spectral bands is hampered by the lack of methods and accurate atmospheric correction procedures. In the present work, a novel method is developed for reconstruction of hyperspectral resolution images from high spatial-resolution Sentinel 2 Multispectral Instrument (MSI) data representative of many complex waters in coastal and inland zones. This method uses a deep neural network (DNN) with multiple blocks of deconvolution and dense layers. The spectral reconstruction of hyperspectral resolution images from multispectral data was based on rigorous training data from the atmospherically-corrected and validated HICO normalized water-leaving radiance products (with spectral resolution 438-868 nm sampled at 5.7 nm) of diverse water types. The generalizability and versatility of the DNN method was tested and evaluated systematically by means of various qualitative and quantitative analyses using concurrent space-borne (MSI and HICO) and in-situ measurements from different regional waters. Reconstructed hyperspectral resolution radiances obtained from the MSI images closely matched with independent HICO and MSI measurements within the desired accuracy. Successful reconstruction and validation of the hyperspectral radiances indicate that the proposed state-of-the-art method provides possible future directions for enhancing our current capabilities of space-borne sensors for various research purposes and societal applications at local, regional and global scales. [ABSTRACT FROM AUTHOR]

Copyright of Biotechnologie, Agronomie, Societe et Environnement is the property of Les Presses Agronomiques de Gembloux and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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Copyright of Journal of Central China Normal University is the property of Huazhong Normal University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Knowledge of water clarity is an essential component of coral reef ecology. While qualitative trends are well known, there are currently few published records of spectral—varying as a (relatively) continuous function of wavelength—water optical properties for these systems. The purpose of this study is to quantify trends in the range and variability of the spectral diffuse attenuation coefficient (Kd) in coral reef and adjacent waters. Using a Biospherical PRR-800, 199 vertical profiles of downwelling spectral irradiance were collected across the reefs and nearby optically deepwaters of Bermuda and Hawaii. A single spectral Kd was calculated for each profile. Results reveal water types ranging from clear oceanic to turbid coastal, with Bermuda and Hawaii showing similar patterns. Kd roughly correlates with reef geomorphic zonation, consistent with well-known reef water characteristics: (a) Suspended sediments are ubiquitous on coral reef flats and in lagoons, chiefly comprising calcium carbonate, which is effectively spectrally flat and has the effect of increasing the overall magnitude of Kd; (b) reefs generate large amounts of dissolved organic matter, which becomes apparent in some lagoonal Kd; and (c) the Kd data exhibit little indication of chlorophyll, which is typically very low in the water column above reefs. These patterns appear reproducible when compared with prior data from French Polynesia. The depth of the 1% light level varies accordingly, approximately 30 m, 45 m, 75 m, and 105 m for lagoon, reef flat, fore reef, and offshore, respectively. The data presented here provide some insight into trends in the spatial context of reef geomorphology and lay the foundation for a more quantitative understanding of reef water clarity and color and their importance to reef ecology. [ABSTRACT FROM AUTHOR]

This study evaluates the feasibility of sucrose replacement by erythritol, xylitol, sorbitol and maltitol to double the shelf stability of cookies with insight into the molecular weight impact. These sucrose-rich products have difficulty to retain softness beyond a week if they are not protected in the package and are devoid of flour in their formula (eg; coconut macaroon in this study). Sucrose was substituted completely or partially with polyols to examine the impact of molecular weight on physicochemical properties of samples within 6 days. D-optimal mixture design was applied to determine optimum formula and synergistic effect of the mixed polyols. Fitted model for responses on day 6 indicated the highest coefficient factor of lower molecular weight polyols (LMWP), mainly xylitol, on moisture content, water activity and color lightness with negative synergistic effect when it was combined with other polyols. Comparatively, LMWP exhibited higher enthalpy on day 1, which induced higher moisture content on day 6 and resulted in a softer product. Statistical design with the lowest hardness and water activity and highest moisture response after 6 days contained xylitol and scored highest acceptancy by sensory panelists, and presented low glycemic index. [ABSTRACT FROM AUTHOR]

Copyright of Revista Ambiente e Água is the property of Revista Ambiente e Agua and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Dissolved organic carbon (DOC) and iron (Fe) have been observed to be the important contributors to surface water brownification. Additionally, the DOC quality influences water color by forming Fe-DOC complexes that provide additive effects and is influenced by dominant land use type within watersheds. However, the influence of quantity and quality of DOC on Fe and water color is poorly understood in headwater streams. The aim of this study was to investigate the effects of DOC and Fe on water color in forest (FC) and pasture (GFC) fine-scale watersheds to remove the confounding effects of climate and soil parent material. Significant differences of DOC, Fe, and water absorbance at 420 nm (a420) between FC and GFC were found (p < 0.05). A dominant contribution to water color was from DOC (95.5 − 63.7%) with a decreasing trend when Fe increased from 0.011 to 0.258 mg L−1. There were no significant interactions between FC and GFC and Fe on either a420/DOC (p = 0.06) or specific ultraviolet absorbance at 254 nm (SUVA254) (p = 0.30). Increasing values of a420/DOC and SUVA254 were significantly associated with increasing Fe concentration (p < 0.01). Significant interactions were found between FC and GFC and Fe on spectral slope ratio (S ratio) (p < 0.01). The response rate of S ratio with increasing Fe per unit was 0.235 for GFC while it was − 11.043 for FC. These differences indicate that land use may change the quality of DOC, influence Fe-DOC interactions, and thus affect water color. Linking the effects of soil Fe and DOC and headwater Fe and DOC may help identify optimal management practice to mitigate surface water brownification. [ABSTRACT FROM AUTHOR]

The visual capacity of aquatic organisms is, in general, related to light penetration in the water. Therefore, aquatic environments that differ in color can potentially contribute to species polymorphism, especially in fish. In this study, we explore the relationship between light quality and intensity in water bodies and the eye and mouth size in Galaxias maculatus, one of the most widespread fish. Fish morphology was studied photographically, and the vertical attenuation coefficient of light (Kd) was measured in five aquatic systems: two humic lakes, two estuaries, and one river. Water color was also estimated as absorbance at 440 nm. In those environments with less light penetration and darker water color, we observed bigger eyes and, additionally, larger mouths. The darkness of water bodies was mainly related to water color associated with humic substances. As G. maculatus is known to be a visual predator, our results suggest that bigger eyes increase visual capacity in darker environments, which would result in improved feeding rates, also supported by larger mouth length. [ABSTRACT FROM AUTHOR]

Both in culture and cartography, colors are assigned to specific features, concepts, and ideas that are frequently accepted and followed as norms. In this paper, I argue that these color codes create a sensation of ontological security that, at the same time, excludes alternative ideas or discourses from daily-life and scientific practices. Through a discussion of the use of the color blue in cartography, culture, and art, I seek to point out the relativity and subjectivity of color selection and argue that scientific rules and cultural definitions, especially artistic expressions, are not opposites but complementary key elements of a dialog between sciences and the humanities, in which conventions should be conceived as mechanisms that are embedded in the broader context of visual culture. A deeper analysis of cartographic principles in a cultural context could help to establish a stronger relation between mapping practices and the map idea in society. [ABSTRACT FROM AUTHOR]

Among tropical fruits, guava (Psidium guajava L.), is one of the most consumed thanks to its excellent organoleptic and functional properties, rich in bioactive compounds. Its agroindustrial use generates a large number of by-products, including the epicarp, which represents approximately 25 to 30% of the fruit's weight. The objective of the present investigation was to determine, in the epicarp of guava, the physicochemical properties, the color coordinates and characterize it in is content of carotenoid and phenolic compounds, as well as to determine its antioxidant activity. Guava epicarp flour (GEF) was made and based on approved methods, yield in weight, pH, titratable acidity, soluble solids, moisture content, water activity and color parameters was determined, as well as the bioactive compounds noted. The results for the physicochemical parameters were high and the content of carotenoid compounds for the different fractions fluctuated between 9,414 for the a-carotene fraction and 10,894 for the ß-cryptoxanthin fraction. The antioxidant activity showed a value of 62,281% and the content of phenolic compounds was 24,948 mg EAG/g. It is concluded that GEF can be used as a source of natural bioactive compounds in the food industry. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Central China Normal University is the property of Huazhong Normal University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A system has been developed for diagnosing the biological production of lake ecosystems with input parameters: geographic latitude, specific watershed, normal annual air temperature, annual precipitation, mean and maximal depth of the water body, water residence time in it, and the values of water color index and daily assimilation number of phytoplankton chlorophyll a, averaged over vegetation season. Several lakes and reservoirs situated in different geographic zones of RF (from Northwest to the Far East) have been used to forecast the annual production of terrestrial vegetation in the drainage basin and the key groups of aquatic organisms: primary producers, bacterioplankton, and consumers, including fishes. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Hydrogeology Journal is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Ecotones mark zones of rapid change in ecological structure at various spatial scales. They are believed to be particularly susceptible to shifts caused by environmental transformation, making them key regions for studying the effects of global change. Here, we explored the variation in assemblage structure of aquatic primary producer and consumer communities across latitudinal transects in northeastern North America (Québec‐Labrador) to identify spatial patterns in biodiversity that indicated the location of transition zones across the landscape. We analyzed species richness and the cumulative rate of compositional change (expressed as beta‐diversity) of diatoms and chironomids to detect any abrupt shifts in the rate of spatial taxonomic turnover. We used principal coordinates analysis to estimate community turnover with latitude, then applied piecewise linear regression to assess the position of ecotones. Statistically significant changes in assemblage composition occurred at 52 and 55°N, corresponding to the transition between closed‐ and open‐crown forest, and to the southern onset of the forest tundra (i.e., the forest limit), respectively. The spatial distribution of ecotones was most strongly related to air temperature for chironomids and to vegetation‐ and soil‐related chemical attributes of lake water for diatoms, including dissolved organic carbon content and water color. Lakes at mid‐ to high‐latitudes currently face pressures from rapidly rising temperatures, accompanied by large increases in organic carbon inputs from their catchments, often leading to browning and its associated effects. The biota at the base of food webs in lakes located in transition zones are disproportionately affected by the cascading effects of these multi‐factorial changes, concurrent with pronounced terrestrial greening observed in these regions. Similar patterns of biotic shifts have been observed along alpine aquatic transects, indicating the potential for widespread restructuring of cold, high‐altitude and high‐latitude freshwater communities due to global change. [ABSTRACT FROM AUTHOR]

Increase in surface water color (browning), caused by rising dissolved organic carbon (DOC) and iron concentrations, has been widely reported and studied in the last couple of decades. This phenomenon has implications to aquatic ecosystem function and biogeochemical carbon cycling. While recovery from acidification and changes in climate‐related variables, such as precipitation and length of growing season, are recognized as drivers behind browning, land‐use change has received less attention. In this study, we include all of the above factors and aim to discern their individual and combined contribution to water color variation in an unprecedentedly long (1940–2016) and highly resolved dataset (~20 times per month), from a river in southern Sweden. Water color showed high seasonal variability and a marked long‐term increase, particularly in the latter half of the dataset (~1980). Short‐term and seasonal variations were best explained by precipitation, with temperature playing a secondary role. All explanatory variables (precipitation, temperature, S deposition, and land‐use change) contributed significantly and together predicted 75% of the long‐term variation in water color. Long‐term change was best explained by a pronounced increase in Norway spruce (Picea abies Karst) volume—a measure of land‐use change and a proxy for buildup of organic soil layers—and by change in atmospheric S deposition. When modeling water color with a combination of explanatory variables, Norway spruce showed the highest contribution to explaining long‐term variability. This study highlights the importance of considering land‐use change as a factor behind browning and combining multiple factors when making predictions in water color and DOC. [ABSTRACT FROM AUTHOR]