Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 5.862
Filtrar
1.
Bull Environ Contam Toxicol ; 113(1): 2, 2024 Jul 04.
Artigo em Inglês | MEDLINE | ID: mdl-38960950

RESUMO

The COVID-19 pandemic's disruptions to human activities prompted serious environmental changes. Here, we assessed the variations in coastal water quality along the Caspian Sea, with a focus on the Iranian coastline, during the lockdown. Utilizing Chlorophyll-a data from MODIS-AQUA satellite from 2015 to 2023 and Singular Spectrum Analysis for temporal trends, we found a 22% Chlorophyll-a concentration decrease along the coast, from 3.2 to 2.5 mg/m³. Additionally, using a deep learning algorithm known as Long Short-Term Memory Networks, we found that, in the absence of lockdown, the Chlorophyll-a concentration would have been 20% higher during the 2020-2023 period. Furthermore, our spatial analysis revealed that 98% of areas experienced about 18% Chlorophyll-a decline. The identified improvement in coastal water quality presents significant opportunities for policymakers to enact regulations and make local administrative decisions aimed at curbing coastal water pollution, particularly in areas experiencing considerable anthropogenic stress.


Assuntos
COVID-19 , Clorofila A , Monitoramento Ambiental , COVID-19/epidemiologia , Monitoramento Ambiental/métodos , Clorofila A/análise , Irã (Geográfico) , Humanos , Clorofila/análise , SARS-CoV-2 , Qualidade da Água , Água do Mar/química , Pandemias , Oceanos e Mares , Poluição da Água/estatística & dados numéricos
2.
Opt Express ; 32(9): 16371-16397, 2024 Apr 22.
Artigo em Inglês | MEDLINE | ID: mdl-38859266

RESUMO

Chlorophyll a (Chl-a) in lakes serves as an effective marker for assessing algal biomass and the nutritional level of lakes, and its observation is feasible through remote sensing methods. HJ-1 (Huanjing-1) satellite, deployed in 2008, incorporates a CCD capable of a 30 m resolution and has a revisit interval of 2 days, rendering it a superb choice or supplemental sensor for monitoring trophic state of lakes. For effective long-term and regional-scale mapping, both the imagery and the evaluation of machine learning algorithms are essential. The several typical machine learning algorithms, i.e., Support Vector Regression (SVR), Gradient Boosting Decision Trees (GBDT), XGBoost (XGB), Random Forest (RF), K-Nearest Neighbor (KNN), Kernel Ridge Regression (KRR), and Multi-Layer Perception Network (MLP), were developed using our in-situ measured Chl-a. A cross-validation grid to identify the most effective hyperparameter combinations for each algorithm was used, as well as the selected optimal superparameter combinations. In Chl-a mapping of three typical lakes, the R2 of GBDT, XGB, RF, and KRR all reached 0.90, while XGB algorithm also exhibited stable performance with the smallest error (RMSE = 3.11 µg/L). Adjustments were made to align the Chl-a spatial-temporal patterns with past data, utilizing HJ1-A/B CCD images mapping through XGB algorithm, which demonstrates its stability. Our results highlight the considerable effectiveness and utility of HJ-1 A/B CCD imagery for evaluation and monitoring trophic state of lakes in a cold arid region, providing the application cases contribute to the ongoing efforts to monitor water qualities.


Assuntos
Algoritmos , Clorofila A , Monitoramento Ambiental , Lagos , Aprendizado de Máquina , Lagos/análise , Clorofila A/análise , Monitoramento Ambiental/métodos , Clorofila/análise , Imagens de Satélites/métodos , Tecnologia de Sensoriamento Remoto/métodos
3.
Cells ; 13(11)2024 May 30.
Artigo em Inglês | MEDLINE | ID: mdl-38891083

RESUMO

The differential effects of cellular and ultrastructural characteristics on the optical properties of adaxial and abaxial leaf surfaces in the genus Tradescantia highlight the intricate relationships between cellular arrangement and pigment distribution in the plant cells. We examined hyperspectral and chlorophyll a fluorescence (ChlF) kinetics using spectroradiometers and optical and electron microscopy techniques. The leaves were analysed for their spectral properties and cellular makeup. The biochemical compounds were measured and correlated with the biophysical and ultrastructural features. The main findings showed that the top and bottom leaf surfaces had different amounts and patterns of pigments, especially anthocyanins, flavonoids, total phenolics, chlorophyll-carotenoids, and cell and organelle structures, as revealed by the hyperspectral vegetation index (HVI). These differences were further elucidated by the correlation coefficients, which influence the optical signatures of the leaves. Additionally, ChlF kinetics varied between leaf surfaces, correlating with VIS-NIR-SWIR bands through distinct cellular structures and pigment concentrations in the hypodermis cells. We confirmed that the unique optical properties of each leaf surface arise not only from pigmentation but also from complex cellular arrangements and structural adaptations. Some of the factors that affect how leaves reflect light are the arrangement of chloroplasts, thylakoid membranes, vacuoles, and the relative size of the cells themselves. These findings improve our knowledge of the biophysical and biochemical reasons for leaf optical diversity, and indicate possible implications for photosynthetic efficiency and stress adaptation under different environmental conditions in the mesophyll cells of Tradescantia plants.


Assuntos
Folhas de Planta , Tradescantia , Tradescantia/metabolismo , Folhas de Planta/metabolismo , Folhas de Planta/ultraestrutura , Fluorescência , Clorofila/metabolismo , Clorofila A/metabolismo
4.
Funct Plant Biol ; 512024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38902905

RESUMO

The aim of this study was to investigate whether silicon (Si) supply was able to alleviate the harmful effects caused by salinity stress on sorghum-sudangrass (Sorghum bicolor ×Sorghum sudanense ), a species of grass raised for forage and grain. Plants were grown in the presence or absence of 150mM NaCl, supplemented or not with Si (0.5mM Si). Biomass production, water and mineral status, photosynthetic pigment contents, and gas exchange parameters were investigated. Special focus was accorded to evaluating the PSI and PSII. Salinity stress significantly reduced plant growth and tissue hydration, and led to a significant decrease in all other studied parameters. Si supply enhanced whole plant biomass production by 50%, improved water status, decreased Na+ and Cl- accumulation, and even restored chlorophyll a , chlorophyll b , and carotenoid contents. Interestingly, both photosystem activities (PSI and PSII) were enhanced with Si addition. However, a more pronounced enhancement was noted in PSI compared with PSII, with a greater oxidation state upon Si supply. Our findings confirm that Si mitigated the adverse effects of salinity on sorghum-sudangrass throughout adverse approaches. Application of Si in sorghum appears to be an efficient key solution for managing salt-damaging effects on plants.


Assuntos
Clorofila , Fotossíntese , Salinidade , Silício , Sorghum , Sorghum/crescimento & desenvolvimento , Sorghum/efeitos dos fármacos , Sorghum/metabolismo , Silício/farmacologia , Fotossíntese/efeitos dos fármacos , Clorofila/metabolismo , Biomassa , Complexo de Proteína do Fotossistema II/metabolismo , Estresse Salino/efeitos dos fármacos , Clorofila A/metabolismo
5.
J Environ Manage ; 364: 121462, 2024 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-38878578

RESUMO

The use of remote sensing for monitoring chlorophyll-a (chla) and modelling eutrophication has advanced over the last decades. Although the application of the technology has proven successful in ocean ecosystems, there is a need to monitor chla concentrations in large, nutrient-poor inland water bodies. The main objective of this study was to explore the utility of publicly available remotely sensed Sentinel-2 (S2) imagery to quantify chla concentrations in the nutrient-deficient Lake Malawi/Niassa/Nyasa (LMNN). A secondary objective was to compare the S2 derived chla with the Global Change Observation Mission-Climate (GCOM-C) chla product that provides uninterrupted data throughout the year. In situ chla data (n = 76) from upper, middle and lower sections of LMNN served as a reference to produce remote sensing-based quantification. The line-height approach method built on color index, was applied for chla concentrations below 0.25 mg/m3. Moderate Resolution Imaging Spectroradiometer 3-band Ocean Color (MODIS-OC3) - was adopted when chla concentration exceeded 0.35 mg/m3. The MODIS-OC3 algorithm had generic model coefficients that were calibrated for each in situ sample by using GCOM-C Level 3 chla product. A weighted sum of the two algorithms was applied for chla concentrations that fell between 0.25 and 0.35 mg/m3. The above methods were then applied to the S2 data to estimate chla at each pixel. S2 showed a promising accuracy in distinguishing chla levels (MSE = 0.18) although the chla range in the lake was relatively narrow, particularly using the locally calibrated coefficients of the OC3 algorithm. Chla distribution maps produced from the S2 data revealed limited spatial variation across the LMNN with higher concentrations identified in the coastal areas. S2-derived chla and GCOM-C chla comparison showed fairly good similarity between the two datasets (MSE = 0.205). Accepting this similarity, monthly chla dynamics of the lake was profiled using the temporally reliable GCOM-C data that showed oligotrophic conditions (1.7 mg/m3 to 3.2 mg/m3) in most parts of the lake throughout the year. The study's findings advance the potential for both remote sensing approaches to provide vital information at the required spatial and temporal resolution for evidence-based policymaking and proactive environmental management in an otherwise very data deficient region.


Assuntos
Clorofila A , Monitoramento Ambiental , Lagos , Lagos/química , Monitoramento Ambiental/métodos , Clorofila A/análise , Tecnologia de Sensoriamento Remoto , Clorofila/análise , Eutrofização , Malaui
6.
J Environ Manage ; 364: 121463, 2024 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-38878579

RESUMO

Frequent coastal harmful algal blooms (HABs) threaten the ecological environment and human health. Biscayne Bay in southeastern Florida also faces algal bloom issues; however, the mechanisms driving these blooms are not fully understood, emphasizing the importance of HAB prediction for effective environmental management. The overarching goal of this study is to offer a robust HAB predictive framework and try to enhance the understanding of HAB dynamics. This study established three scenarios to predict chlorophyll-a concentrations, a recognized representative of HABs: Scenario 1 (S1) using single nonlinear machine learning (ML) algorithms, hybrid Scenario 2 (S2) combining linear models and nonlinear ML algorithms, and hybrid Scenario 3 (S3) combining temporal decomposition and ML (TD-ML) algorithms. The novel-developed S3 TD-ML hybrid models demonstrated superior predictive capabilities, achieving all R2 values above 0.9 and MAPE under 30% in tests, significantly outperforming the S1 with an average R2 of 0.16 and the S2 with an R2 of -0.06. S3 models effectively captured the algal dynamics, successfully predicting complex time series with extremes and noise. In addition, we unveiled the relationship between environmental variables and chlorophyll-a through correlation analysis and found that climate change might intensify the HABs in Biscayne Bay. This research developed a precise predictive framework for early warning and proactive management of HABs, offering potential global applicability and improved prediction accuracy to address HAB challenges.


Assuntos
Proliferação Nociva de Algas , Florida , Monitoramento Ambiental/métodos , Algoritmos , Mudança Climática , Clorofila A/análise , Aprendizado de Máquina , Clorofila/análise
7.
Chemosphere ; 361: 142486, 2024 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-38823423

RESUMO

The dynamics of hydrographic and biogeochemical properties in a Northwestern coastal area of the Adriatic Sea were investigated. The time series data from continuous observation (2007-2022) allowed the investigation of annual trends and seasonal cycles along a coastal transect influenced by local river discharge. Various statistical models were used to investigate water temperature, salinity, chlorophyll a, dissolved organic, inorganic and particulate nutrients, precipitation and river discharge. It was found that the local river discharge regime played an essential role in interannual, and seasonal biogeochemical dynamics associated with global climate change in the Mediterranean region. A significant trend towards oligotrophic conditions was detected, as evidenced by the downward trend in the river mouth and on the sea of chlorophyll a (-0.2 µg L-1 in the sea), dissolved organic and inorganic nitrogen and phosphorus (i.e., -0.43 µM yr-1 of DON in the sea and -6.67 of DIN µM yr-1 in the river mouth or -0.07 µM yr-1 of DOP and -0.02 µM yr-1 of DIP in the river mouth) and silicate (-2.47 µM yr-1 in the river mouth) concentrations. Salinity showed a long-term increase in the sea (0.08 yr-1), corresponding to a significant decrease in water discharge from the local river (-0.27 m3 s-1 yr-1) and precipitation (-0.06 mm yr-1). The dissolved organic and inorganic nutrients highlighted a different seasonal accumulation under the river runoff regime. The nutrient enrichment was predominantly driven by river contribution. Data analysis showed that the coastal biogeochemical properties dynamics were mostly influenced by river discharge and precipitation regimes, which in turn are driven by climate change variability in the North-western Adriatic Sea.


Assuntos
Mudança Climática , Monitoramento Ambiental , Rios , Salinidade , Estações do Ano , Água do Mar , Rios/química , Água do Mar/química , Fósforo/análise , Nitrogênio/análise , Clorofila A/análise , Clorofila/análise , Temperatura , Poluentes Químicos da Água/análise
8.
J Environ Manage ; 364: 121386, 2024 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-38865920

RESUMO

Eutrophication is a serious threat to water quality and human health, and chlorophyll-a (Chla) is a key indicator to represent eutrophication in rivers or lakes. Understanding the spatial-temporal distribution of Chla and its accurate prediction are significant for water system management. In this study, spatial-temporal analysis and correlation analysis were applied to reveal Chla concentration pattern in the Fuchun River, China. Then four exogenous variables (wind speed, water temperature, dissolved oxygen and turbidity) were used for predicting Chla concentrations by six models (3 traditional machine learning models and 3 deep learning models) and compare the performance in a river with different hydrology characteristics. Statistical analysis shown that the Chla concentration in the reservoir river segment was higher than in the natural river segment during August and September, while the dominant algae gradually changed from Cyanophyta to Cryptophyta. Moreover, air temperature, water temperature and dissolved oxygen had high correlations with Chla concentrations among environment factors. The results of the prediction models demonstrate that extreme gradient boosting (XGBoost) and long short-term memory neural network (LSTM) were the best performance model in the reservoir river segment (NSE = 0.93; RMSE = 4.67) and natural river segment (NSE = 0.94; RMSE = 1.84), respectively. This study provides a reference for further understanding eutrophication and early warning of algal blooms in different type of rivers.


Assuntos
Clorofila A , Eutrofização , Hidrologia , Aprendizado de Máquina , Rios , Rios/química , China , Clorofila A/análise , Monitoramento Ambiental/métodos , Qualidade da Água , Clorofila/análise
9.
Physiol Plant ; 176(3): e14391, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38894595

RESUMO

Monitoring changes in chlorophyll a (ChlFa) fluorescence during dehydration can provide insights into plant photosynthetic responses to climate change challenges, which are predicted to increase drought frequency. However, the limited knowledge of how ChlFa parameters respond to water deficit hinders the exploration of the photochemical mechanism of the photosynthetic process and the simulation of photosynthetic fluorescence models. Furthermore, how to track such responses of ChlFa parameters, especially at large scales, remains a challenge. In this study, we attempted to use spectral information reflected from leaves to follow the dynamic response patterns of ChlFa parameters of seven species under prolonged dehydration. The results showed that the investigated ChlFa parameters exhibited significant changes as dehydration progressed, with considerable variability among the different species as well as under different water conditions. This study also demonstrated that the integration of both spectral and water content information can provide an effective method for tracking ChlFa parameters during dehydration, explaining over 90% of the total variance in the measured ChlFa parameters. Collectively, these results should serve as a valuable reference for predicting the response of ChlFa parameters to dehydration and offer a potential method for estimating ChlFa parameters under drought conditions.


Assuntos
Clorofila A , Clorofila , Desidratação , Folhas de Planta , Água , Folhas de Planta/fisiologia , Folhas de Planta/metabolismo , Clorofila A/metabolismo , Água/metabolismo , Fluorescência , Clorofila/metabolismo , Secas , Fotossíntese/fisiologia
10.
Ecotoxicol Environ Saf ; 280: 116519, 2024 Jul 15.
Artigo em Inglês | MEDLINE | ID: mdl-38833977

RESUMO

The indiscriminate use of zinc oxide nanoparticles (ZnO NPs) in daily life can lead to their release into soil environment. These ZnO NPs can be taken up by crops and translocated to their edible part, potentially causing risks to the ecosystem and human health. In this study, we conducted pot experiments to determine phytotoxicity, bioaccumulation and translocation depending on the size (10 - 30 nm, 80 - 200 nm and 300 nm diameter) and concentration (0, 100, 500 and 1000 mg Zn/kg) of ZnO NPs and Zn ion (Zn2+) in bok choy, a leafy green vegetable crop. After 14 days of exposure, our results showed that large-sized ZnO NPs (i.e., 300 nm) at the highest concentration exhibited greater phytotoxicity, including obstruction of leaf and root weight (42.5 % and 33.8 %, respectively) and reduction of chlorophyll a and b content (50.2 % and 85.2 %, respectively), as well as changes in the activities of oxidative stress responses compared to those of small-sized ZnO NPs, although their translocation ability was relatively lower than that of smaller ones. The translocation factor (TF) values decreased as the size of ZnO NPs increased, with TF values of 0.68 for 10 - 30 nm, 0.55 for 80 - 200 nm, and 0.27 for 300 nm ZnO NPs, all at the highest exposure concentration. Both the results of micro X-ray fluorescence (µ-XRF) spectrometer and bio-transmission electron microscopy (bio-TEM) showed that the Zn elements were mainly localized at the edges of leaves exposed to small-sized ZnO NPs. However, the Zn elements upon exposure to large-sized ZnO NP were primarily observed in the primary veins of leaves in the µ-XRF data, indicating a limitation in their ability to translocate from roots to leaves. This study not only advances our comprehension of the environmental impact of nanotechnology but also holds considerable implications for the future of sustainable agriculture and food safety.


Assuntos
Bioacumulação , Brassica , Nanopartículas Metálicas , Tamanho da Partícula , Folhas de Planta , Poluentes do Solo , Óxido de Zinco , Óxido de Zinco/toxicidade , Óxido de Zinco/química , Poluentes do Solo/toxicidade , Brassica/efeitos dos fármacos , Brassica/metabolismo , Brassica/crescimento & desenvolvimento , Folhas de Planta/efeitos dos fármacos , Folhas de Planta/metabolismo , Nanopartículas Metálicas/toxicidade , Solo/química , Clorofila/metabolismo , Estresse Oxidativo/efeitos dos fármacos , Raízes de Plantas/efeitos dos fármacos , Raízes de Plantas/metabolismo , Clorofila A/metabolismo , Nanopartículas/toxicidade
11.
J Hazard Mater ; 474: 134644, 2024 Aug 05.
Artigo em Inglês | MEDLINE | ID: mdl-38838520

RESUMO

Nanoplastics, as emerging pollutants, have harmful effects on living organisms and the environment, the mechanisms and extent of which remain unclear. Microalgae, as one of the most important biological groups in the food chain and sensitive environmental indicators to various pollutants, are considered a suitable option for investigating the effects of nanoplastics. In this study, the effects of polystyrene nanoplastics on the growth rate, dry weight, chlorophyll a and carotenoid levels, proline, and lipid peroxidation in the Spirulina platensis were examined. Three concentrations of 0.1, 1, and 10 mg L-1 of PSNPs were used alongside a control sample with zero concentration, with four repetitions in one-liter containers for 20 days under optimal temperature and light conditions. Various analyses, including growth rate, dry weight, proline, chlorophyll a and carotenoid levels, and lipid peroxidation, were performed. The results indicated that exposure to PSNP stress led to a significant decrease in growth rate, dry weight, and chlorophyll a and carotenoid levels compared to the control sample. Furthermore, this stress increased the levels of proline and lipid peroxidation in Spirulina platensis. Morphological analysis via microscopy supported these findings, indicating considerable environmental risks associated with PSNPs.


Assuntos
Carotenoides , Clorofila , Peroxidação de Lipídeos , Microalgas , Poliestirenos , Prolina , Spirulina , Spirulina/efeitos dos fármacos , Spirulina/crescimento & desenvolvimento , Spirulina/metabolismo , Poliestirenos/toxicidade , Carotenoides/metabolismo , Peroxidação de Lipídeos/efeitos dos fármacos , Prolina/metabolismo , Clorofila/metabolismo , Microalgas/efeitos dos fármacos , Microalgas/crescimento & desenvolvimento , Clorofila A/metabolismo , Nanopartículas/toxicidade
12.
Sci Total Environ ; 945: 174119, 2024 Oct 01.
Artigo em Inglês | MEDLINE | ID: mdl-38906304

RESUMO

With the death and decomposition of widely distributed photosynthetic organisms, free natural pigments are often detected in surface water, sediment and soil. Whether free pigments can act as photosensitizers to drive biophotoelectrochemical metabolism in nonphotosynthetic microorganisms has not been reported. In this work, we provide direct evidence for the photoelectrophic relationship between extracellular chlorophyll a (Chl a) and nonphotosynthetic microorganisms. The results show that 10 µg of Chl a can produce significant photoelectrons (∼0.34 A/cm2) upon irradiation to drive nitrate reduction in Shewanella oneidensis. Chl a undergoes structural changes during the photoelectric process, thus the ability of Chl a to generate a photocurrent decreases gradually with increasing illumination time. These changes are greater in the presence of microorganisms than in the absence of microorganisms. Photoelectron transport from Chl a to S. oneidensis occurs through a direct pathway involving the cytochromes MtrA, MtrB, MtrC and CymA but not through an indirect pathway involving riboflavin. These findings reveal a novel photoelectrotrophic linkage between natural photosynthetic pigments and nonphototrophic microorganisms, which has important implications for the biogeochemical cycle of nitrogen in various natural environments where Chl a is distributed.


Assuntos
Clorofila A , Nitratos , Shewanella , Nitratos/metabolismo , Shewanella/metabolismo , Clorofila A/metabolismo , Fotossíntese , Oxirredução , Fármacos Fotossensibilizantes , Clorofila/metabolismo
13.
Sci Total Environ ; 945: 174076, 2024 Oct 01.
Artigo em Inglês | MEDLINE | ID: mdl-38908583

RESUMO

Chlorophyll-a (Chl-a) is a crucial pigment in algae and macrophytes, which makes the concentration of total Chl-a in the water column (total Chl-a) an essential indicator for estimating the primary productivity and carbon cycle of the ocean. Integrating the Chl-a concentration at different depths (Chl-a profile) is an important way to obtain the total Chl-a. However, due to limited cost and technology, it is difficult to measure Chl-a profiles directly in a spatially continuous and high-resolution way. In this study, we proposed an integrated strategy model that combines three different machine learning methods (PSO-BP, random forest and gradient boosting) to predict the Chl-a profile in the Mediterranean by using several sea surface variables (photosynthetically active radiation, spectral irradiance, sea surface temperature, wind speed, euphotic depth and KD490) and subsurface variables (mixed layer depth) observed by or estimated from satellite and BGC-Argo float observations. After accuracy estimation, the integrated model was utilized to generate the time series total Chl-a in the Mediterranean from 2003 to 2021. By analysing the time series results, it was found that seasonal fluctuation contributed the most to the variation in total Chl-a. In addition, there was an overall decreasing trend in the Mediterranean phytoplankton biomass, with the total Chl- decreasing at a rate of 0.048 mg/m2 per year, which was inferred to be related to global warming and precipitation reduction based on comprehensive analysis with sea surface temperature and precipitation data.


Assuntos
Clorofila A , Monitoramento Ambiental , Fitoplâncton , Monitoramento Ambiental/métodos , Clorofila A/análise , Mar Mediterrâneo , Clorofila/análise , Imagens de Satélites , Água do Mar/química , Estações do Ano , Região do Mediterrâneo , Aprendizado de Máquina
14.
Sci Data ; 11(1): 611, 2024 Jun 12.
Artigo em Inglês | MEDLINE | ID: mdl-38866750

RESUMO

The concentration of chlorophyll a in phytoplankton and periphyton represents the amount of algal biomass. We compiled an 18-year record (2005-2022) of pigment data from water bodies across the United States (US) to support efforts to develop process-based, machine learning, and remote sensing models for prediction of harmful algal blooms (HABs). To our knowledge, this dataset of nearly 84,000 sites and over 1,374,000 pigment measurements is the largest compilation of harmonized discrete, laboratory-extracted chlorophyll data for the US. These data were compiled from the Water Quality Portal (WQP) and previously unpublished U.S. Geological Survey's National Water Quality Laboratory (NWQL) data. Data were harmonized for reporting units, pigment type, duplicate values, collection depth, site name, negative values, and some extreme values. Across the country, data show great variation by state in sampling frequency, distribution, and methods. Uses for such data include the calibration of models, calibration of field sensors, examination of relationship to nutrients and other drivers, evaluation of temporal trends, and other applications addressing local to national scale concerns.


Assuntos
Clorofila A , Lagos , Fitoplâncton , Rios , Estados Unidos , Clorofila A/análise , Rios/química , Monitoramento Ambiental , Proliferação Nociva de Algas , Clorofila/análise
15.
Nat Commun ; 15(1): 4999, 2024 Jun 12.
Artigo em Inglês | MEDLINE | ID: mdl-38866834

RESUMO

Cryptophytes are ancestral photosynthetic organisms evolved from red algae through secondary endosymbiosis. They have developed alloxanthin-chlorophyll a/c2-binding proteins (ACPs) as light-harvesting complexes (LHCs). The distinctive properties of cryptophytes contribute to efficient oxygenic photosynthesis and underscore the evolutionary relationships of red-lineage plastids. Here we present the cryo-electron microscopy structure of the Photosystem II (PSII)-ACPII supercomplex from the cryptophyte Chroomonas placoidea. The structure includes a PSII dimer and twelve ACPII monomers forming four linear trimers. These trimers structurally resemble red algae LHCs and cryptophyte ACPI trimers that associate with Photosystem I (PSI), suggesting their close evolutionary links. We also determine a Chl a-binding subunit, Psb-γ, essential for stabilizing PSII-ACPII association. Furthermore, computational calculation provides insights into the excitation energy transfer pathways. Our study lays a solid structural foundation for understanding the light-energy capture and transfer in cryptophyte PSII-ACPII, evolutionary variations in PSII-LHCII, and the origin of red-lineage LHCIIs.


Assuntos
Microscopia Crioeletrônica , Criptófitas , Complexos de Proteínas Captadores de Luz , Complexo de Proteína do Fotossistema II , Complexo de Proteína do Fotossistema II/metabolismo , Complexo de Proteína do Fotossistema II/química , Complexos de Proteínas Captadores de Luz/metabolismo , Complexos de Proteínas Captadores de Luz/química , Criptófitas/metabolismo , Fotossíntese , Modelos Moleculares , Transferência de Energia , Complexo de Proteína do Fotossistema I/metabolismo , Complexo de Proteína do Fotossistema I/química , Clorofila A/metabolismo , Clorofila A/química
16.
J Environ Manage ; 362: 121259, 2024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38830281

RESUMO

Machine learning methodology has recently been considered a smart and reliable way to monitor water quality parameters in aquatic environments like reservoirs and lakes. This study employs both individual and hybrid-based techniques to boost the accuracy of dissolved oxygen (DO) and chlorophyll-a (Chl-a) predictions in the Wadi Dayqah Dam located in Oman. At first, an AAQ-RINKO device (CTD+ sensor) was used to collect water quality parameters from different locations and varying depths in the reservoir. Second, the dataset is segmented into homogeneous clusters based on DO and Chl-a parameters by leveraging an optimized K-means algorithm, facilitating precise estimations. Third, ten sophisticated variational-individual data-driven models, namely generalized regression neural network (GRNN), random forest (RF), gaussian process regression (GPR), decision tree (DT), least-squares boosting (LSB), bayesian ridge (BR), support vector regression (SVR), K-nearest neighbors (KNN), multilayer perceptron (MLP), and group method of data handling (GMDH) are employed to estimate DO and Chl-a concentrations. Fourth, to improve prediction accuracy, bayesian model averaging (BMA), entropy weighted (EW), and a new enhanced clustering-based hybrid technique called Entropy-ORNESS are employed to combine model outputs. The Entropy-ORNESS method incorporates a Genetic Algorithm (GA) to determine optimal weights and then combine them with EW weights. Finally, the inclusion of bootstrapping techniques introduces a stochastic assessment of model uncertainty, resulting in a robust estimator model. In the validation phase, the Entropy-ORNESS technique outperforms the independent models among the three fusion-based methods, yielding R2 values of 0.92 and 0.89 for DO and Chl-a clusters, respectively. The proposed hybrid-based methodology demonstrates reduced uncertainty compared to single data-driven models and two combination frameworks, with uncertainty levels of 0.24% and 1.16% for cluster 1 of DO and cluster 2 of Chl-a parameters. As a highlight point, the spatial analysis of DO and Chl-a concentrations exhibit similar pattern variations across varying depths of the dam according to the comparison of field measurements with the best hybrid technique, in which DO concentration values notably decrease during warmer seasons. These findings collectively underscore the potential of the upgraded weighted-based hybrid approach to provide more accurate estimations of DO and Chl-a concentrations in dynamic aquatic environments.


Assuntos
Qualidade da Água , Incerteza , Algoritmos , Análise Espacial , Teorema de Bayes , Análise por Conglomerados , Monitoramento Ambiental/métodos , Redes Neurais de Computação , Aprendizado de Máquina , Clorofila A/análise
17.
Water Sci Technol ; 89(10): 2703-2715, 2024 May.
Artigo em Inglês | MEDLINE | ID: mdl-38822609

RESUMO

The aim of the present study was to evaluate the spatio-temporal variability of various physical and chemical parameters of water quality and to determine the trophic state of Lake Ardibo. Water samples were collected from October 2020 to September 2021 at three sampling stations in four different seasons. A total of 14 physico-chemical parameters, such as water temperature, pH, dissolved oxygen (DO), electrical conductivity, turbidity, alkalinity, Secchi-depth, nitrate, ammonia, silicon dioxide, soluble reactive phosphorus, total phosphorus, chloride, and fluoride were measured using standard methods. The results demonstrated that temporal variation existed throughout the study period. Except for turbidity, the water quality of the lake varied significantly within the four seasons (ANOVA, p < 0.05). DO levels decreased significantly during the dry season following water mixing events. Chlorophyll-a measurements showed significant seasonal differences ranging from 0.58 µg L-1 in the main-rainy season to 8.44 µg L-1 in the post-rainy period, indicating moderate algal biomass production. The overall category of Lake Ardibo was found to be under a mesotrophic state with medium biological productivity. A holistic lake basin approach management is suggested to maintain water quality and ecological processes and to improve the lake ecosystem services.


Assuntos
Lagos , Estações do Ano , Qualidade da Água , Lagos/química , Etiópia , Monitoramento Ambiental , Fósforo/análise , Clorofila A/análise
18.
Chirality ; 36(6): e23681, 2024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38839280

RESUMO

An N-centered epimeric mixture of chlorophyll-a derivatives methylated at the inner nitrogen atom was separated by reverse-phase high-performance liquid chromatography. Circular dichroism (CD) spectroscopic analyses of the epimerically pure N22-methyl-chlorins revealed that the minor first-eluted and major second-eluted stereoisomers were (22S)- and (22R)-configurations, respectively. Their visible absorption and CD spectra in solution were dependent on the N22-stereochemistry. The epimer-dependent spectral changes were independent of the substituents at the peripheral 3-position of the core chlorin chromophore.


Assuntos
Clorofila A , Clorofila , Dicroísmo Circular , Estereoisomerismo , Clorofila/química , Metilação , Clorofila A/química , Cromatografia Líquida de Alta Pressão/métodos , Nitrogênio/química
19.
PLoS One ; 19(6): e0304831, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38923971

RESUMO

This study investigated the mitigating effects of spermidine on salinity-stressed yarrow plants (Achillea millefolium L.), an economically important medicinal crop. Plants were treated with four salinity levels (0, 30, 60, 90 mM NaCl) and three spermidine concentrations (0, 1.5, 3 µM). Salinity induced electrolyte leakage in a dose-dependent manner, increasing from 22% at 30 mM to 56% at 90 mM NaCl without spermidine. However, 1.5 µM spermidine significantly reduced leakage across salinities by 1.35-11.2% relative to untreated stressed plants. Photosynthetic pigments (chlorophyll a, b, carotenoids) also exhibited salinity- and spermidine-modulated responses. While salinity decreased chlorophyll a, both spermidine concentrations increased chlorophyll b and carotenoids under most saline conditions. Salinity and spermidine synergistically elevated osmoprotectants proline and total carbohydrates, with 3 µM spermidine augmenting proline and carbohydrates up to 14.4% and 13.1% at 90 mM NaCl, respectively. Antioxidant enzymes CAT, POD and APX displayed complex regulation influenced by treatment factors. Moreover, salinity stress and spermidine also influenced the expression of linalool and pinene synthetase genes, with the highest expression levels observed under 90 mM salt stress and the application of 3 µM spermidine. The findings provide valuable insights into the responses of yarrow plants to salinity stress and highlight the potential of spermidine in mitigating the adverse effects of salinity stress.


Assuntos
Achillea , Clorofila , Estresse Salino , Espermidina , Espermidina/farmacologia , Espermidina/metabolismo , Achillea/metabolismo , Achillea/efeitos dos fármacos , Estresse Salino/efeitos dos fármacos , Clorofila/metabolismo , Fotossíntese/efeitos dos fármacos , Carotenoides/metabolismo , Prolina/metabolismo , Regulação da Expressão Gênica de Plantas/efeitos dos fármacos , Salinidade , Antioxidantes/metabolismo , Cloreto de Sódio/farmacologia , Clorofila A/metabolismo
20.
Sci Total Environ ; 944: 173915, 2024 Sep 20.
Artigo em Inglês | MEDLINE | ID: mdl-38871328

RESUMO

The 2021 Tajogaite eruption in La Palma (Canary Islands, Spain) emitted vast volumes of lava during 85 days, which reached the ocean in several occasions at the western flank of the island. Most of these flows merged to create a primary lava delta, covering an area of 48 ha, with an additional 30 ha underwater. Here we characterize the effects of the lava-seawater interaction on the surrounding marine environment. The area was sampled during two multidisciplinary oceanographic cruises: the first one comprised the days before the lava reached the ocean and after the first contact; and the second took place a month later, when the lava delta was already formed but still receiving lava inputs. Physical-chemical anomalies were found in the whole water column at different depths up to 300 m in all measured parameters, such as turbidity (+9 NTU), dissolved oxygen concentration (-17.17 µmol kg-1), pHT25 (-0.1), and chlorophyll-a concentration (-0.33 mg m-3). Surface temperature increased up to +2.3 °C (28.5 °C) and surface salinity showed increases and decreases of -1.01 and +0.70, respectively, in a radius of 4 km around the lava delta. In the water column, the heated waters experimented a lava-induced upwelling, bringing deeper, nutrient-rich waters to shallower depths; however, this feature did not trigger any phytoplankton bloom. In fact, integrated chlorophyll-a showed an abrupt decrease of -41 % in just two days and -69 % a month later, compared to prior conditions. The chlorophyll-a depletion reached a distance larger than 2.5 km (not delimited).


Assuntos
Clorofila , Água do Mar , Água do Mar/química , Espanha , Clorofila/análise , Monitoramento Ambiental , Erupções Vulcânicas , Clorofila A , Salinidade , Fitoplâncton
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA
...