Chlorophyll A
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2021 ◽  
Vol 8 ◽  
Jun Pan ◽  
Fangping Cheng ◽  
Fei Yu ◽  
Yongqiang Shi ◽  
Fan Sun ◽  

Calanus sinicus, a temperate copepod with a lethal temperature >27°C, is one of the key species in Chinese coastal marine ecosystems. The C. sinicus population increases in spring and declines in early summer annually due to increasing water temperature. Numerous C. sinicus individuals then congregate in the Yellow Sea Cold Water Mass (YSCWM) and remain under the thermocline from early summer to early autumn. Development and reproduction is halted in this cold and foodless bottom water and they avoid ascending to the hot surface water, which is regarded as an over-summering strategy. Based on discrete water sampling approaches, previous studies demonstrated that higher chlorophyll a (Chl a) levels appeared in the mixed hot surface water layer; however, the subsurface chlorophyll a maximum layer (SCML) has seldom been described. In the present study, various probes and a visual plankton recorder (VPR) were used to determine the fine vertical distributions of environmental factors and C. sinicus. VPR observations showed the ecological responses in fine scale and indicated that few C. sinicus individuals ascend at night, the main population preferred to remain below the SCML all day long. The results demonstrated that a constant thin SCML existed in the YSCWM area, and that the SCML location coincided with or was beneath the thermocline and halocline layers, where the temperature was suitable for C. sinicus. The relationship between abundance and Chl a, showed the diel vertical migration trend of C. sinicus to feed at night in the YSCWM area. In addition to temperature as a main influencing factor, dissolved oxygen concentrations and column depth were also influencing factors. Therefore, in addition to avoiding high surface temperature, energy supplement may be an important driving force confining the diel vertical migration of C. sinicus in the Yellow Sea in summer.

2021 ◽  
Vol 266 ◽  
pp. 112685
Bridget N. Seegers ◽  
P. Jeremy Werdell ◽  
Ryan A. Vandermeulen ◽  
Wilson Salls ◽  
Richard P. Stumpf ◽  

Qianming Dou ◽  
Xue Du ◽  
Yanfeng Cong ◽  
Le Wang ◽  
Chen Zhao ◽  

The characteristics of macroinvertebrate community structure can effectively reflect the health status of lake ecosystem and the quality of the lake ecological environment. It is of great significance to identify the limiting factors of macroinvertebrate community structure for the maintenance of lake ecosystem health. In this study, the community composition of macroinvertebrate assemblages and their relationships with environmental variables in 13 small lakes within Linhuan Lake was investigated. Self-organizing map, K-means clustering analysis, principal component analysis, pearson correlation analysis, and redundancy analysis were used to analyze the correlation and variability between macroinvertebrates community index and environmental factors. The results showed that the environmental variables (pH, total phosphorus, nitrate, water temperature, dissolved oxygen, conductivity, chemical oxygen demand, and ammonium) had a significant effect on the classification of macroinvertebrate community. Molluscs were significantly negatively correlated with pH and chlorophyll a, while annelids and aquatic insects were significantly positively correlated with chlorophyll a and dissolved oxygen. Species richness and Shannon’s diversity of macroinvertebrates were significantly negatively correlated with total phosphorus while biomass of macroinvertebrates was significantly negatively correlated with pH. High alkalinity characteristics and eutrophication of the lake have a serious impact on the macroinvertebrate community. Human interference and unreasonable industrial and surface runoff from agricultural farms destroy the ecological environment and affect the community structure of macroinvertebrate. Thus, the improvement of the macroinvertebrate’s community structure should be carried out by improving the Lianhuan Lake watershed ecological environment and controlling watershed environmental pollution.

Plants ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1975
Anna Sobczak ◽  
Marzena Sujkowska-Rybkowska ◽  
Janina Gajc-Wolska ◽  
Waldemar Kowalczyk ◽  
Wojciech Borucki ◽  

The aim of this study was to evaluate the effects of various supplemental greenhouse lighting systems, i.e., high-pressure sodium lamps and mixtures of red and blue light-emitting diodes, on the photochemical efficiency, anatomical leaf structure, and growth of the two pepper cultivars. The intensity levels of the photosynthetically active radiation were the same for both light treatments. In this study, the relative chlorophyll content was measured. Additionally, certain parameters of chlorophyll a fluorescence were measured under ambient light or after dark adaptation. The obtained results showed that the application of light-emitting diodes (LEDs) as supplemental lighting positively affected the anatomical leaf characteristics and plant growth. The leaves of both pepper cultivars were thicker and had larger palisade parenchyma cells under LED supplemental lighting compared to leaves grown under high-pressure sodium (HPS) lamps. Moreover, the mesophyll cells of seedlings grown under LEDs contained more chloroplasts than those growing under HPS lighting. The chlorophyll a fluorescence measurements of pepper seedlings grown under LEDs showed significant increases in photosynthetic apparatus performance index (PI) values compared to plants grown under HPS lamps; however, the values for this index were higher in cv. ‘Aifos’ as compared to cv. ‘Palermo’. We recommend that supplemental lighting systems are applied with caution, as their performance appears to depend not only on the light spectrum but also on the cultivar.

2021 ◽  
Sayaka Yasunaka ◽  
Tsuneo Ono ◽  
Kosei Sasaoka ◽  
Kanako Sato

Abstract. Chlorophyll a (Chl-a) often retains its maximum concentration not at the surface but in the subsurface layer. The depth of the Chl-a maximum primarily depends on the balance between light penetration from the surface and nutrient supply from the deep ocean. However, a global map of subsurface Chl-a concentrations based on observations has not been presented yet. In this study, we integrate Chl-a concentration data not only from recent biogeochemical floats but also from historical ship-based and other observations, and present global maps of subsurface Chl-a concentration with related variables. The subsurface Chl-a maximum deeper than the mixed layer depth was stably observed in the subtropics and tropics (30° S to 30° N), only in summer in midlatitudes (30–40° N/S), and rarely at 45–60° S of the Southern Ocean and in the northern North Atlantic (north of 45° N). The depths of the subsurface Chl-a maxima are deeper than those of the euphotic layer in the subtropics and shallower in the tropics and midlatitudes. In the subtropics, seasonal oxygen increases below the mixed layer implied substantial biological new production, which corresponds to 10 % of the net primary production there. During El Niño, the subsurface Chl-a concentration in the equatorial Pacific is higher in the middle to the east and lower in the west than that during La Niña, which is opposite that on the surface. The spatiotemporal variability of the Chl-a concentration described here would be suggestive results not only for the biogeochemical cycle in the ocean but also for the thermal structure and the dynamics of the ocean via the absorption of shortwave radiation.

Foods ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 2226
Ernesta Tolpeznikaite ◽  
Vadims Bartkevics ◽  
Modestas Ruzauskas ◽  
Renata Pilkaityte ◽  
Pranas Viskelis ◽  

The aim of this study was to evaluate the characteristics of macroalgae (Cladophora rupestris, Furcellaria lumbricalis, Ulva intestinalis) and microalgae (Arthrospira platensis (Sp1, Sp2), Chlorella vulgaris) extracts, including micro- and macroelement transition to extract, antioxidant, antimicrobial properties, the concentrations of chlorophyll (-a, -b), and the total carotenoid concentration (TCC). In macroalgae, the highest TCC and chlorophyll content were found in C. rupestris. In microalgae, the TCC was 10.1-times higher in C. vulgaris than in Sp1, Sp2; however, the chlorophyll contents in C. vulgaris samples were lower. A moderate negative correlation was found between the chlorophyll-a and TCC contents (r = −0.4644). In macroalgae extract samples, C. rupestris and F. lumbricalis showed the highest total phenolic compound content (TPCC). DPPH antioxidant activity and TPCC in microalgae was related to the TCC (r = 0.6191, r = 0.6439, respectively). Sp2 extracts inhibited Staphylococcus haemolyticus; C. rupestris, F. lumbricalis, U. intestinalis, and Sp2 extracts inhibited Bacillus subtilis; and U. intestinalis extracts inhibited Streptococcus mutans strains. This study showed that extraction is a suitable technology for toxic metal decontamination in algae; however, some of the desirable microelements are reduced during the extraction, and only the final products, could be applied in food, feed, and others.

2021 ◽  
Vol 13 (18) ◽  
pp. 3717
Haibin Ye ◽  
Shilin Tang ◽  
Chaoyu Yang

The abundance of phytoplankton is generally estimated by measuring the chlorophyll-a concentration (Cchla), which is an important factor in photosynthesis and can be used to analyze the density and biomass of phytoplankton in the ecosystem. The band-ratio-based empirical or semi-analytical algorithms are operationally applied to retrieve Cchla in global oceans, which generally experience difficulties from the diversity of optical properties and the complexity of the radiative transfer equations in analytical analyses, respectively. With an attempt to develop an accurate Cchla retrieval model for the optically complex coastal and estuarine waters, this study aimed to explore the deep learning (DL) methods in satellite retrieval of Cchla. A two-stage convolutional neural network (CNN), named Cchla-Net, was proposed, which utilized the spectral information of remote sensing reflectances at MODIS/Aqua’s visible bands. In the first-stage phase, the Cchla-Net was pretrained by a set of remote sensing patches, in which the Cchla was generated from an existing model (OC3M). The pretrained results were than used as the initial values to refine the network with the synthetic oversampled in-situ dataset in the second-stage training phase. Using in-situ samples for training with the new initial values has a higher probability to reach the global optimum. The quantitative analyses showed that the two-stage training was more likely to achieve a global optimum in the optimization than the one-stage training. Matchups of the in-situ Cchla measurements were used to evaluate the retrieval models. Results showed that the proposed Cchla-Net produced obvious better performance than the empirical and semi-analytical algorithms, implying the DL method was more effective for optically complex waters with extremely high Cchla. This study provided an applicable method for remote sensing retrieval of Cchla, which should be helpful for studying the spatial distribution and temporal variability in the productive Pearl River estuary (PRE) waters.

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