수륙양용드론을 활용한 수질측정 및 DO, 온도에 따른 Chl-a 예측식 개발

2019 ◽  
Vol 19 (2) ◽  
pp. 111-121
Author(s):  
Soo Hyeon Kim ◽  
◽  
Sungchul Hong ◽  
Pyongin Yi ◽  
Seongho Jang ◽  
...  
Keyword(s):  
Chl A

High light fluence impairs light-harvesting Chl a/b complex apoprotein syntheses and/or membrane uptake in the CD3 mutant of wheat

1994 ◽  
Vol 91 (4) ◽  
pp. 567-574
Author(s):  
Murray Duysen ◽  
Paul Otto ◽  
Norm Williams
Keyword(s):  
Light Harvesting ◽  
High Light ◽  
Chl A ◽  
Light Fluence

A Poisson-Pareto model of Chl-a fluorescence signals in marine environments

2015 ◽  
Vol 55 ◽  
pp. 373
Author(s):  
Stephen Woodcock ◽  
Bojana Manojlovic ◽  
Mark Baird ◽  
Peter Ralph
Keyword(s):  
Marine Environments ◽  
Chl A ◽  
Chl A Fluorescence ◽  
Pareto Model

scholarly journals The Role of Environmental Factors on the Fishery Catch of the Squid Uroteuthis chinensis in the Pearl River Estuary, China

2021 ◽  
Vol 9 (2) ◽  
pp. 131
Author(s):  
Dongliang Wang ◽  
Lijun Yao ◽  
Jing Yu ◽  
Pimao Chen
Keyword(s):  
River Estuary ◽  
Pearl River Estuary ◽  
Sea Surface ◽  
Spatiotemporal Variability ◽  
Pearl River ◽  
Coastal Current ◽  
Catch Per Unit Effort ◽  
Chl A ◽  
The Pearl River Estuary ◽  
The Pearl River

The Pearl River Estuary (PRE) is one of the major fishing grounds for the squid Uroteuthis chinensis. Taking that into consideration, this study analyzes the environmental effects on the spatiotemporal variability of U. chinensis in the PRE, on the basis of the Generalized Additive Model (GAM) and Clustering Fishing Tactics (CFT), using satellite and in situ observations. Results show that 63.1% of the total variation in U. chinensis Catch Per Unit Effort (CPUE) in the PRE could be explained by looking into outside factors. The most important one was the interaction of sea surface temperature (SST) and month, with a contribution of 26.7%, followed by the interaction effect of depth and month, fishermen’s fishing tactics, sea surface salinity (SSS), chlorophyll a concentration (Chl a), and year, with contributions of 12.8%, 8.5%, 7.7%, 4.0%, and 3.1%, respectively. In summary, U. chinensis in the PRE was mainly distributed over areas with an SST of 22–29 °C, SSS of 32.5–34‰, Chl a of 0–0.3 mg × m−3, and water depth of 40–140 m. The distribution of U. chinensis in the PRE was affected by the western Guangdong coastal current, distribution of marine primary productivity, and variation of habitat conditions. Lower stock of U. chinensis in the PRE was connected with La Niña in 2008.

scholarly journals Satellite-Derived Protein Concentration of Phytoplankton in the Southwestern East/Japan Sea

2021 ◽  
Vol 9 (2) ◽  
pp. 189
Author(s):  
Hyeonji Bae ◽  
Dabin Lee ◽  
Jae Joong Kang ◽  
Jae Hyung Lee ◽  
Naeun Jo ◽  
...  
Keyword(s):  
Protein Concentration ◽  
Japan Sea ◽  
Biological Properties ◽  
Measured Data ◽  
Trophic Levels ◽  
Coefficient Of Determination ◽  
P Value ◽  
Chl A ◽  
Major Factors

The cellular macromolecular contents and energy value of phytoplankton as primary food source determine the growth of higher trophic levels, affecting the balance and sustainability of oceanic food webs. Especially, proteins are more directly linked with basic functions of phytoplankton biosynthesis and cell division and transferred through the food chains. In recent years, the East/Japan Sea (EJS) has been changed dramatically in environmental conditions, such as physical and chemical characteristics, as well as biological properties. Therefore, developing an algorithm to estimate the protein concentration of phytoplankton and monitor their spatiotemporal variations on a broad scale would be invaluable. To derive the protein concentration of phytoplankton in EJS, the new regional algorithm was developed by using multiple linear regression analyses based on field-measured data which were obtained from 2012 to 2018 in the southwestern EJS. The major factors for the protein concentration were identified as chlorophyll-a (Chl-a) and sea surface nitrate (SSN) in the southwestern EJS. The coefficient of determination (r2) between field-measured and algorithm-derived protein concentrations was 0.55, which is rather low but reliable. The satellite-derived estimation generally follows the 1:1 line with the field-measured data, with Pearson’s correlation coefficient, which was 0.40 (p-value < 0.01, n = 135). No remarkable trend in the long-term annual protein concentration of phytoplankton was found in the study area during our observation period. However, some seasonal difference was observed in winter protein concentration between the 2003–2005 and 2017–2019 periods. The algorithm is developed for the regional East/Japan Sea (EJS) and could contribute to long-term monitoring for climate-associated ecosystem changes. For a better understanding of spatiotemporal variation in the protein concentration of phytoplankton in the EJS, this algorithm should be further improved with continuous field surveys.

scholarly journals Nutrient Loading, Temperature and Heat Wave Effects on Nutrients, Oxygen and Metabolism in Shallow Lake Mesocosms Pre-Adapted for 11 Years

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 127
Author(s):  
Erik Jeppesen ◽  
Joachim Audet ◽  
Thomas A. Davidson ◽  
Érika M. Neif ◽  
Yu Cao ◽  
...  
Keyword(s):  
Heat Wave ◽  
Shallow Lake ◽  
Nutrient Loading ◽  
Global Changes ◽  
Significant Positive Effect ◽  
Mixed Effect ◽  
Chl A ◽  
Nutrient Loadings ◽  
Positive Effect ◽  
Oxygen Concentrations

Global changes (e.g., warming and population growth) affect nutrient loadings and temperatures, but global warming also results in more frequent extreme events, such as heat waves. Using data from the world’s longest-running shallow lake experimental mesocosm facility, we studied the effects of different levels of nutrient loadings combined with varying temperatures, which also included a simulated 1-month summer heat wave (HW), on nutrient and oxygen concentrations, gross ecosystem primary production (GPP), ecosystem respiration (ER), net ecosystem production (NEP) and bacterioplankton production (BACPR). The mesocosms had two nutrient levels (high (HN) and low (LN)) combined with three different temperatures according to the IPCC 2007 warming scenarios (unheated, A2 and A2 + 50%) that were applied for 11 years prior to the present experiment. The simulated HW consisted of 5 °C extra temperature increases only in the A2 and A2 + 50% treatments applied from 1 July to 1 August 2014. Linear mixed effect modeling revealed a strong effect of nutrient treatment on the concentration of chlorophyll a (Chl-a), on various forms of phosphorus and nitrogen as well as on oxygen concentration and oxygen percentage (24 h means). Applying the full dataset, we also found a significant positive effect of nutrient loading on GPP, ER, NEP and BACPR, and of temperature on ER and BACPR. The HW had a significant positive effect on GPP and ER. When dividing the data into LN and HN, temperature also had a significant positive effect on Chl-a in LN and on orthophosphate in HN. Linear mixed models revealed differential effects of nutrients, Chl-a and macrophyte abundance (PVI) on the metabolism variables, with PVI being particularly important in the LN mesocosms. All metabolism variables also responded strongly to a cooling-low irradiance event in the middle of the HW, resulting in a severe drop in oxygen concentrations, not least in the HN heated mesocosms. Our results demonstrate strong effects of nutrients as well as an overall rapid response in oxygen metabolism and BACPR to changes in temperature, including HWs, making them sensitive ecosystem indicators of climate warming.

scholarly journals Transcription Profile Analysis of Chlorophyll Biosynthesis in Leaves of Wild-Type and Chlorophyll b-Deficient Rice (Oryza sativa L.)

Agriculture ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 401
Author(s):  
Minh Khiem Nguyen ◽  
Tin-Han Shih ◽  
Szu-Hsien Lin ◽  
Jun-Wei Lin ◽  
Hoang Chinh Nguyen ◽  
...  
Keyword(s):  
Oryza Sativa ◽  
Core Protein ◽  
Profile Analysis ◽  
Oryza Sativa L ◽  
Electron Flow ◽  
Chlorophyll Biosynthesis ◽  
Wild Type ◽  
Transcription Analysis ◽  
Chl A ◽  
Chl Biosynthesis

Photosynthesis is an essential biological process and a key approach for raising crop yield. However, photosynthesis in rice is not fully investigated. This study reported the photosynthetic properties and transcriptomic profiles of chlorophyll (Chl) b-deficient mutant (ch11) and wild-type rice (Oryza sativa L.). Chl b-deficient rice revealed irregular chloroplast development (indistinct membranes, loss of starch granules, thinner grana, and numerous plastoglobuli). Next-generation sequencing approach application revealed that the differential expressed genes were related to photosynthesis machinery, Chl-biosynthesis, and degradation pathway in ch11. Two genes encoding PsbR (PSII core protein), FtsZ1, and PetH genes, were found to be down-regulated. The expression of the FtsZ1 and PetH genes resulted in disrupted chloroplast cell division and electron flow, respectively, consequently reducing Chl accumulation and the photosynthetic capacity of Chl b-deficient rice. Furthermore, this study found the up-regulated expression of the GluRS gene, whereas the POR gene was down-regulated in the Chl biosynthesis and degradation pathways. The results obtained from RT-qPCR analyses were generally consistent with those of transcription analysis, with the exception of the finding that MgCH genes were up-regulated which enhance the important intermediate products in the Mg branch of Chl biosynthesis. These results indicate a reduction in the accumulation of both Chl a and Chl b. This study suggested that a decline in Chl accumulation is caused by irregular chloroplast formation and down-regulation of POR genes; and Chl b might be degraded via the pheophorbide b pathway, which requires further elucidation.

scholarly journals Spatiotemporal Variability of Surface Phytoplankton Carbon and Carbon-to-Chlorophyll a Ratio in the South China Sea Based on Satellite Data

2020 ◽  
Vol 13 (1) ◽  
pp. 30
Author(s):  
Wenlong Xu ◽  
Guifen Wang ◽  
Long Jiang ◽  
Xuhua Cheng ◽  
Wen Zhou ◽  
...  
Keyword(s):  
South China Sea ◽  
Chlorophyll A ◽  
South China ◽  
Satellite Data ◽  
Phytoplankton Biomass ◽  
The South China Sea ◽  
Spatiotemporal Variability ◽  
The South ◽  
Chl A ◽  
China Sea

The spatiotemporal variability of phytoplankton biomass has been widely studied because of its importance in biogeochemical cycles. Chlorophyll a (Chl-a)—an essential pigment present in photoautotrophic organisms—is widely used as an indicator for oceanic phytoplankton biomass because it could be easily measured with calibrated optical sensors. However, the intracellular Chl-a content varies with light, nutrient levels, and temperature and could misrepresent phytoplankton biomass. In this study, we estimated the concentration of phytoplankton carbon—a more suitable indicator for phytoplankton biomass—using a regionally adjusted bio-optical algorithm with satellite data in the South China Sea (SCS). Phytoplankton carbon and the carbon-to-Chl-a ratio (θ) exhibited considerable variability spatially and seasonally. Generally, phytoplankton carbon in the northern SCS was higher than that in the western and central parts. The regional monthly mean phytoplankton carbon in the northern SCS showed a prominent peak during December and January. A similar pattern was shown in the central part of SCS, but its peak was weaker. Besides the winter peak, the western part of SCS had a secondary maximum of phytoplankton carbon during summer. θ exhibited significant seasonal variability in the northern SCS, but a relatively weak seasonal change in the western and central parts. θ had a peak in September and a trough in January in the northern and central parts of SCS, whereas in the western SCS the minimum and maximum θ was found in August and during October–April of the following year, respectively. Overall, θ ranged from 26.06 to 123.99 in the SCS, which implies that the carbon content could vary up to four times given a specific Chl-a value. The variations in θ were found to be related to changing phytoplankton community composition, as well as dynamic phytoplankton physiological activities in response to environmental influences; which also exhibit much spatial differences in the SCS. Our results imply that the spatiotemporal variability of θ should be considered, rather than simply used a single value when converting Chl-a to phytoplankton carbon biomass in the SCS, especially, when verifying the simulation results of biogeochemical models.

Particulate light absorption and the prediction of phytoplankton biomass and planktonic metabolism in northeastern Spanish aquatic ecosystems

2000 ◽  
Vol 57 (1) ◽  
pp. 25-33 ◽  
Author(s):  
C M Duarte ◽  
S Agustí ◽  
J Kalff
Keyword(s):  
Absorption Coefficient ◽  
Light Absorption ◽  
Aquatic Ecosystems ◽  
Coastal Lagoons ◽  
Strong Relationship ◽  
Community Respiration ◽  
Chl A ◽  
Light Absorption Coefficient ◽  
Alpine Rivers ◽  
Detrital Particles

Examination of particulate light absorption and microplankton metabolism in 36 northeastern Spanish aquatic ecosystems, ranging from alpine rivers to inland saline lakes and the open Mediterranean Sea, revealed the existence of general relationships between particulate light absorption and the biomass of phytoplankton and microplankton metabolism. The particulate absorption spectra reflected a dominance of nonphotosynthetic, likely detrital, particles in rivers and a dominance of phytoplankton in coastal lagoons. There was a strong relationship between the light absorbed by phytoplankton and the chlorophyll a (Chl a) concentration of the systems, which indicated an average (±SE) Chl a specific absorption coefficient of 0.0233 ± 0.0020 m2·mg Chl a-1 for these widely diverse systems. Chl a concentration was a weaker predictor of the total particulate light absorption coefficient, pointing to an important role of nonphytoplanktonic particles in light absorption. Gross production was very closely related to the light absorption coefficient of phytoplankton, whereas community respiration was strongly correlated with the total particulate light absorption coefficient, indicating the optical signatures of sestonic particles to be reliable predictors of planktonic biomass and metabolism in aquatic ecosystems.

scholarly journals Research on Inversion Mechanism of Chlorophyll—A Concentration in Water Bodies Using a Convolutional Neural Network Model

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 664
Author(s):  
Yun Xue ◽  
Lei Zhu ◽  
Bin Zou ◽  
Yi-min Wen ◽  
Yue-hong Long ◽  
...  
Keyword(s):  
Neural Network ◽  
Regression Model ◽  
Convolutional Neural Network ◽  
Chlorophyll A ◽  
Language Processing ◽  
Water Bodies ◽  
Inversion Effect ◽  
Least Squares Regression ◽  
Chlorophyll A Concentration ◽  
Chl A

For Case-II water bodies with relatively complex water qualities, it is challenging to establish a chlorophyll-a concentration (Chl-a concentration) inversion model with strong applicability and high accuracy. Convolutional Neural Network (CNN) shows excellent performance in image target recognition and natural language processing. However, there little research exists on the inversion of Chl-a concentration in water using convolutional neural networks. Taking China’s Dongting Lake as an example, 90 water samples and their spectra were collected in this study. Using eight combinations as independent variables and Chl-a concentration as the dependent variable, a CNN model was constructed to invert Chl-a concentration. The results showed that: (1) The CNN model of the original spectrum has a worse inversion effect than the CNN model of the preprocessed spectrum. The determination coefficient (RP2) of the predicted sample is increased from 0.79 to 0.88, and the root mean square error (RMSEP) of the predicted sample is reduced from 0.61 to 0.49, indicating that preprocessing can significantly improve the inversion effect of the model.; (2) among the combined models, the CNN model with Baseline1_SC (strong correlation factor of 500–750 nm baseline) has the best effect, with RP2 reaching 0.90 and RMSEP only 0.45. The average inversion effect of the eight CNN models is better. The average RP2 reaches 0.86 and the RMSEP is only 0.52, indicating the feasibility of applying CNN to Chl-a concentration inversion modeling; (3) the performance of the CNN model (Baseline1_SC (RP2 = 0.90, RMSEP = 0.45)) was far better than the traditional model of the same combination, i.e., the linear regression model (RP2 = 0.61, RMSEP = 0.72) and partial least squares regression model (Baseline1_SC (RP2 = 0.58. RMSEP = 0.95)), indicating the superiority of the convolutional neural network inversion modeling of water body Chl-a concentration.

scholarly journals Response of Total Suspended Sediment and Chlorophyll-a Concentration to Late Autumn Typhoon Events in the Northwestern South China Sea

2021 ◽  
Vol 13 (15) ◽  
pp. 2863
Author(s):  
Junyi Li ◽  
Huiyuan Zheng ◽  
Lingling Xie ◽  
Quanan Zheng ◽  
Zheng Ling ◽  
...  
Keyword(s):  
South China Sea ◽  
Continental Shelf ◽  
Suspended Sediment ◽  
Chlorophyll A ◽  
South China ◽  
Total Suspended Sediment ◽  
Offshore Area ◽  
Chl A ◽  
Late Autumn ◽  
China Sea

Strong typhoon winds enhance turbulent mixing, which induces sediment to resuspend and to promote chlorophyll-a (Chl-a) blooms in the continental shelf areas. In this study, we find limited Chl-a responses to three late autumn typhoons (typhoon Nesat, Mujigae and Khanun) in the northwestern South China Sea (NWSCS) using satellite observations. In climatology, the Chl-a and total suspended sediment (TSS) concentrations are high all year round with higher value in autumn in the offshore area of the NWSCS. After the typhoon passage, the Chl-a concentration increases slightly (23%), while even TSS enhances by 280% on the wide continental shelf of the NWSCS. However, in the southern area, located approximately 100 km from the typhoon tracks, both TSS and Chl-a concentrations increase 160% and 150% after typhoon passage, respectively. In the deeper area, the increased TSS concentration is responsible for the considerable increase of the Chl-a. An empirical analysis is applied to the data, which reveals the TSS and Chl-a processes during typhoon events. The results of this study suggest a different mechanism for Chl-a concentration increase and thus contribute toward further evaluation of typhoon-induced biological responses.

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