Identification Of Phytoplankton Research Articles

Environmental and Climatic Drivers of Phytoplankton Communities in Central Asia.

Artificial water bodies in Central Asia offer unique environments in which to study plankton diversity influenced by topographic barriers. However, the complexity of these ecosystems and limited comprehensive studies in the region challenge our understanding. In this study, we systematically investigated the water environment parameters and phytoplankton community structure by surveying 14 artificial waters on the southern side of the Altai Mountains and the northern and southern sides of the Tianshan Mountains in the Xinjiang region. The survey covered physical and nutrient indicators, and the results showed noticeable spatial differences between waters in different regions. The temperature, dissolved oxygen, total nitrogen, and total phosphorus of artificial water in the southern Altai Mountains vary greatly. In contrast, the waters in the northern Tianshan Mountains have more consistent physical indicators. The results of phytoplankton identification showed that the phytoplankton communities in different regions are somewhat different, with diatom species being the dominant taxon. The cluster analysis and the non-metric multidimensional scaling (NMDS) results also confirmed the variability of the phytoplankton communities in the areas. The variance partitioning analysis (VPA) results showed that climatic and environmental factors can explain some of the variability of the observed data. Nevertheless, the residual values indicated the presence of other unmeasured factors or the influence of stochasticity. This study provides a scientific basis for regional water resource management and environmental protection.

Enhanced you only look once approach for automatic phytoplankton identification

<p>Conventionally, identifying phytoplankton species is challenging due to human taxonomical knowledge limitations. Advanced technology can overcome this problem. A novel model that accurately enhances phytoplankton detection and identification classification by combining asymmetric convolution and vision transformers (ACVIT) within the YOLOv8m framework is promoted with ACVIT-YOLO. The performance of this model surpasses the original YOLOv8m model, exhibiting a notable 2.4% enhancement in precision, 5.5% improvement in recall, and 1.1% gain in mAP 50 score. The enhanced effectiveness of ACVIT-YOLO compared to the YOLOv8m model, further demonstrated by the decreased giga floating-point operations (GFLOP), decreased parameter count, and compact dimensions, significantly improves the automation of phytoplankton species identification. This suggests that the ACVIT-YOLO model could produce a better prediction system for identifying phytoplankton with similar accuracy to the original YOLOv8m model but with lower computational power and resource usage.</p>

Applying feature-similarity-metrics for long-tailed problem of phytoplankton microscopic images classification

The distribution of phytoplankton in natural water bodies holds significant importance for aquatic for maintaining healthy aquatic environments. While deep learning has become a popular research field of automating phytoplankton identification, its performance is diminished by the uneven species distribution in nature world, which biases classification models towards more advantaged species. Addressing this long-tailed problem, the paper proposed a novel deep learning idea termed feature-similarity-metrics species which utilizes the principle of decreasing intra-class differences and increasing the inter-class differences. A method called feature-center-constraint is introduced to implement the idea. Initially, a center is presupposed for each category, and these centers are distributed evenly and sparsely within the feature space using a uniform distribution initialization method. During model training, the Euclidean distance is used to measure the similarity between sample features and corresponding center. This approach enhanced the model's ability to predict disadvantaged phytoplankton species without compromising the classification accuracy of advantaged ones. Using a phytoplankton dataset of 26,564 images from 68 genera, collected from Chaohu Lake, this method demonstrates superior performance compared to existing techniques. Specially, it achieves a 5.69 % increase in micro-average F1 score and an 11.85 % rise in macro-average F1 score over general method, while F1 score is widely recognized as a reliable metric for measuring classification models' performance. These enhancements not only increase the accuracy of automated phytoplankton identification but also facilitate more effective monitoring of biodiversity and ecological health in aquatic systems. This makes the research highly beneficial for practical applications in environmental science, offering rapid and accurate insights into phytoplankton community structures, for ecological assessments.

Comparison of imaging flow cytometry and microscopy for freshwater algal bloom detection

Gifford SR, St. Amand A, Graham JL, Foster GM, Sauve C, Clark D, Schroeder-Larkins H. 2024. Comparison of imaging flow cytometry and microscopy for freshwater algal bloom detection. Lake Reserv Manage. 40:221–235. Imaging flow cytometry (IFC) is an emerging tool that allows for rapid identification and enumeration of phytoplankton in freshwater systems. However, few studies have assessed the effects of preservation on IFC results or compared live IFC and microscopy results in freshwater systems. Understanding the effects of preservation and differences between IFC and microscopy will improve interpretation of these data and inform strategies to use IFC-based approaches in freshwater systems. Our study objectives were to compare IFC and phase contrast with epifluorescence microscopy as techniques for phytoplankton identification and enumeration, and the effects of sample preservation with an emphasis on taxa forming harmful cyanobacterial blooms (HCBs). During June through October 2020, samples were collected from 2 lakes in the Finger Lakes region of New York. Live and preserved samples were analyzed by laboratory-based IFC, and preserved samples were analyzed by microscopy. The IFC approach captured community dynamics while detecting potential cyanobacterial bloom-forming taxa earlier and at lower abundances than microscopy. Laboratory-based IFC allowed for an intermediate level of taxonomic information when compared to microscopy, gross techniques, such as extracted chlorophyll a or fluorescence sensors, and field-based operation of IFC approaches. The laboratory-based application of IFC in this study allowed receipt of results in 5 d or less, a substantial improvement over microscopy, which can be time-consuming to conduct. However, the laboratory-based IFC approach had some limitations. Imaging flow cytometry-estimated biovolume may be less accurate than microscopy for some taxa because of the algorithms used to calculate biovolume, particularly for chrysophytes and coccoid cyanobacteria. Colonial dissociation during preservation appeared to affect detection of Microcystis by IFC less than for other fragile bloom-forming taxa like chrysophytes. Our study results advance understanding of how IFC may translate to field-based approaches for early harmful algal bloom indicators in freshwater.

Limnological Characteristics, Phytoplankton Assemblage and Environmental Assessment of Hadejia River, North-Western Nigeria: A Comprehensive Survey

Study’s Excerpt/Novelty This study is the first of its kind that offers a comprehensive analysis of phytoplankton dynamics in the Hadejia River, highlighting significant spatial and temporal variations in relation to key limnological variables. It uniquely identifies the influence of environmental factors on specific phytoplankton species and provides baseline data for future ecological monitoring. The research showcases the impact of anthropogenic activities on water quality, particularly at Station B, contributing critical insights into the river's ecological health and informing conservation strategies. Full Abstract This study assesses variations in phytoplankton abundance, composition, and distribution in the Hadejia River in relation to key limnological characteristics across both spatial and temporal dimensions. Over six months in 2018, water samples were collected from the river and analyzed for environmental variables alongside the quantification and identification of phytoplankton using standard protocols. pH and temperature measurements were conducted in situ. Results indicated significant variations (P < 0.05) in pH, temperature, turbidity, nitrate, and phosphate levels across different months, although no significant differences were observed between sampling stations. The highest nitrate value (5.41 mg/L) and phosphate levels (6.55 mg/L) were recorded in August at Station B (STB). 693 Phytoplankton individuals from five divisions were identified, with peak abundance, composition, and distribution observed during the dry season. Key species such as Selenastrum bibraianum, Tetraedron regulare, Tabellaria flocculosa, Gomphosphaeria lacustris, Microcystis aeruginosa, Rhabdoderma lineare and Tabellaria fenestrate were consistently present throughout the study period. Shannon_H diversity index values for Cyanophyta, Pyrrophyta, and Euglenophyta ranged between 1.34-2.02, while Bacillariophyta and Cyanophyta exhibited reduced diversity (1-1.32) and species richness (0.55-0.68) at STB. Canonical correspondence analysis revealed that the selected environmental variables strongly influenced phytoplankton abundance and diversity, with the exception noted for Microcystis aeruginosa, Gomphosphaeria lacustris, Rhabdoderma lineare, and Chlamydomonas ehrenbergii. These results suggest deterioration in water quality, particularly at STB, possibly due to anthropogenic activities. Furthermore, this study provides valuable baseline data for future research endeavors aimed at monitoring and managing the ecological health of River Hadejia

Phytoplankton Diversity as a Bioindicator for Water Quality of Pertamina Harbour Ampenan, Lombok

Ampenan district is an area that has a fairly high population density. There are community activities such as selling on the beach, littering, tourism activities and crossing activities at the Pertamina Harbour Ampenan which can cause a decrease in water quality. This research was conducted to determine water quality of Pertamina Harbour Ampenan based on phytoplankton community. Sea waters samplings were carried out using a 20µm plankton net. Observation and identification of phytoplankton was carried out in advances biology laboratory, FMIPA, Mataram University using a binocular microscope. Phytoplankton data were analyzed based on the abundance, diversity, dominance and saprobity index. The results of this research showed that the phytoplankton community of the Pertamina Harbour Ampenan waters consisted of 106 species from 6 classes with an abundance value of 4324,455 ind/L. Spesies diversity and dominant indexs of phytoplankton, and saprobic indexes of the Pertamina Harbour Ampenan waters were 1,767, 0,451 and 2,56 respectively. Based on the phytoplankton species diversity index, the waters of Pertamina Harbour Ampenan was categorized as moderately polluted, whereas saprobity index the waters of Pertamina Harbour was categorized as oligosaprobic.

Relationship of Physico-chemical Properties of Water with Phytoplankton Abundance in Peraru Village Tank in Vavuniya District

The village tank cascade system, predominantly found in the Vavuniya district, satisfies the water demand for agriculture and domestic needs considerably. Among them, the Peraru village tank lies in a cascade line in the Vavuniya district. The water resource of Peraru village reservoir is treated by the National Water Supply and Drainage Board, Vavuniya, and distributed to the local public. As Peraru a drinking water fountain, the study of phytoplankton and water quality is important. The study's objective was to identify the phytoplankton and estimate the abundance of phytoplankton in the Peraru village tank along with the Physico-chemical characteristics of water. A phytoplankton sampling was done by using plankton net at the selected three locations of Peraru village reservoir weekly from March to April 2021. Totally, 24 samples were analyzed during the study period. Simultaneously, water samples were also collected at each site to determine dissolved oxygen, electrical conductivity, pH, turbidity, temperature, nitrate, and phosphate concentrations. Identification of phytoplankton was made based on standard guides, and the abundances of phytoplankton were estimated using Sedgewick- rafter counting cells. The results of Physico- chemical parameters were statistically tested using ANOVA and found correlations between the abundance of phytoplankton and Physico-chemical parameters. Phylum Bacillariophyta and genus Aulacoseira were the dominant phylum and genus in the Peraru village tank. Dissolved Oxygen (DO), Electrical Conductivity (EC), nitrate, and phosphate positively influenced the abundance of phytoplankton in the Peraru village tank, while turbidity negatively affected the same. 
 Keywords: Phytoplankton abundance, Correlation, Physico-chemical parameters

Aquatic microdiversity from urban cenotes in Cancun, Quintana Roo, Mexico

The microdiversity of cenotes in the Yucatan Peninsula, Mexico has been little studied, with the phytoplankton and protists being the most representative species. However, all previous studies have been focused on cenotes associated with touristic activities, leaving a gap in the understanding of cenotes located within urban areas. The present study is dedicated to the identification of phytoplankton and protists in the cenotes of Cancun, Quintana Roo, Mexico. We conducted our research in four urban cenotes, collecting samples using a 150 µm plankton net, filtering them with a 45 µm membrane, and examining them under optical microscopy. Subsequently, we calculated the abundance, richness, and completeness of the samples. Our findings revealed a total of 6 phyla, 4 subphyla, 10 classes, 8 subclasses, 15 orders, 15 families, 18 genus, and 17 species and 4 species indeterminata in the cenotes of Cancun, Quintana Roo, Mexico. Among these, there were 8 species of phytoplankton and 1 species indeterminata, while 9 species of protists and 3 species indeterminata. These results highlight the remarkable species richness and the complex structure and composition of urban cenotes, suggesting that some species may be unique to this particular ecosystem. Currently, there is limited knowledge regarding the behavior of these aquifers (urban cenotes), and a comprehensive inventory or characterization of their microdiversity is lacking. Such information could be instrumental in the management, conservation, and sustainable use of these valuable aquifers.

Identification of Phytoplankton at Ephemeral Pond with Acidic pH in Bangka Regency

AbstractEphemeral waters, the temporary aquatic environment become an interesting habitat to explore extremophile organism, include phytoplankton. Furthermore, the waters have an acidic condition or low pH that impact to metabolisms, community structure, and diversity of phytoplankton. This study was conducted on June until August 2022 in Bangka Regency, Bangka Belitung Archipelago Province, Indonesia. We analyzed the phytoplankton presence at acidic ephemeral waters to indicated their potential as primary producer in food web, bioindicator, and ecological succession agent. This study was conducted by exploration method of phytoplankton diversity. The research observed and found five class and twelve genera that consist of class Chlorophyceae (genera Enteromorpha, Ankistrodesmus, Prasiola, Pleurococcus, and Coleochaete), class Rhodophyceae (genera Lemanea), class Diatoms (genera Diatoma, Synedra, and Navicula), class Xanthophyceae (genera Ophiocytium), and class Cyanobacteria (genera Oscillatoria and Anabaena). The class Chlorophyceae, genera Enteromorpha were the highest community at the both of acidic waters and they could survive at pH 3.52 + 0.5 to 3.71 + 0.8.AbstrakPerairan ephemeral, lingkungan perairan musiman menjadi suatu habitat yang menarik untuk mengeksplorasi organisme ekstremofil, termasuk fitoplankton. Lebih jauh lagi, perairan tersebut memiliki kondisi asam atau pH rendah yang berdampak pada metabolisme, struktur komunitas, dan diversitas fitoplankton. Penelitian ini dilaksanakan pada Juni hingga Agustus 2022 di Kabupaten Bangka, Provinsi Kepulauan Bangka Belitung, Indonesia. Kami menganalisis keberadaan fitoplankton di perairan ephemeral asam untuk mengindikasikan potensi fitoplankton sebagai produsen utama, bioindikator dan agen suksesi lingkungan. Penelitian ini dilaksanakan dengan metode eksplorasi diversitas fitoplankton. Penelitian ini mengobservasi dan menemukan lima kelas dan dua belas genus yang terdiri atas kelas Chlorophyceae (genus Enteromorpha, Ankistrodesmus, Prasiola, Pleurococcus, dan Coleochaete), kelas Rhodophyceae (genus Lemanea), kelas Diatoms (genus Diatoma, Synedra, dan Navicula), kelas Xanthophyceae (genus Ophiocytium), dan kelas Cyanobacteria (genus Oscillatoria dan Anabaena). Kelas Chlorophyceae, genus Enteromorpha adalah komunitas tertinggi pada kedua perairan asam dan mampu bertahan pada pH 3.52 + 0.5 to 3.71 + 0.8.

Phytoplankton as Bioindikator of Water Quality in The Batu Dendeng River West Lombok

This exploratory descriptive study with a qualitative approach was aims to analyze the water quality of the Batu Dendeng River in West Lombok through a study of the phytoplankton community structure. Sampling was carried out using purposive sampling method. Water sampling was carried out using plankton net of 20µ mesh sized. Observation and identification of phytoplankton was carried out at the Biology Laboratory of FKIP University of Mataram using a binocular microscope. Phytoplankton data was analyzed based on abundance, species diversity, species uniformity and species dominance indexs. The results showed that the community structure of identified phytoplankton in the Batu Dendeng River consisted of 5 classes and 52 species with abundance value of 714.074 (ind/L). Phytoplankton species diversity, uniformity, and dominance indexs of Batu Dendeng River were 2.591, 0.66, and 0.13 respectively. The water pollution criteria based on the diversity index of phytoplankton species, indicates the water quality of the Batu Dendeng River West Lombok was in the slightly polluted category.

Method for extracting pigment characteristic spectra from the phytoplankton absorption spectrum.

The extraction of pigment characteristic spectra from the phytoplankton absorption spectrum has high application value in phytoplankton identification and classification and in quantitative extraction of pigment concentrations. Derivative analysis, which has been widely used in this field, is easily interfered with by noisy signals and the selection of the derivative step, resulting in the loss and distortion of the pigment characteristic spectra. In this study, a method based on the one-dimensional discrete wavelet transform (DWT) was proposed to extract the pigment characteristic spectra of phytoplankton. DWT and derivative analysis were applied simultaneously to the phytoplankton absorption spectra of 6 phyla (Dinophyta, Bacillariophyta, Haptophyta, Chlorophyta, Cyanophyta, and Prochlorophyta) to verify the effectiveness of DWT in the extraction of pigment characteristic spectra.

Conditions Of Phytoplankton Community Structure In Lake Toba Ajibata, Toba Samosir Regency

The research was conducted with the aim of knowing the condition of the phytoplankton community structure based on diversity index criteria in the waters of Lake Toba, Ajibata District, Toba Samosir Regency. This research was conducted in February -March 2021. This type of research was ex post de facto, carried out at 5 observation stations with 3 repetitions. Phytozooplankton samples were taken using Net plankton No. 25. Identification of phytoplankton was carried out in the Biology Laboratory of the Faculty of Mathematics and Natural Sciences, Medan State University. Phytoplankton found in 12 genera, namely: Achnantes, Aulacoisera, Encyonema, Claphora, Stigeoclonium, Dictyosphaerium, Staurastrum, Monoraphidium, Oscillatoria, Microcytis, Nostoc, and Chroococcus. The diversity index at Station I was 1.35, II was 1.36, III was 1.31, IV was 1.36, and V was 1.72. The condition of the phytoplankton community structure is stable in the moderate category. The temperature of the waters ranges from 22°C-25°C, the light transparency to the waters ranges from 4-4.5 m, the pH of the waters ranges from 7.36-8.85, the DO of the waters ranges from 6.84-8.25 mg/l, the BOD of the waters ranged from 1.01 to 3.42 mg/l. Lake Toba water quality based on physical and chemical parameters is within the normal range.

PMOT2023: A Large-Scale Multi-Object Tracking (MOT) Dataset with Application to Phytoplankton Observation

Phytoplankton play a critical role in marine food webs and biogeochemical cycles, and their abundance must be monitored to prevent disasters and improve the marine environment. Although existing algorithms for automatic phytoplankton identification at the image level are available, there are currently no video-level algorithms. This lack of datasets is a significant obstacle to the development of video-level automatic identification algorithms for phytoplankton observations. Deep learning-based algorithms, in particular, require high-quality datasets to achieve optimal results. To address this issue, we propose the PMOT2023 (Phytoplankton Multi-Object Tracking), a multi-video tracking dataset based on 48,000 micrographs captured by in situ observation devices. The dataset comprises 21 classes of phytoplankton and can aid in the development of advanced video-level identification methods. Multi-object tracking algorithms can detect, classify, count, and estimate phytoplankton density. As a video-level automatic identification algorithm, multi-object tracking addresses trajectory tracking, concentration estimation, and other requirements in original phytoplankton observation, helping to prevent marine ecological disasters. Additionally, the PMOT2023 dataset will serve as a benchmark to evaluate the performance of future phytoplankton identification models and provide a foundation for further research on automatic phytoplankton identification algorithms.

Distribution of heavy metal and phytoplankton in calabar river port terminals, calabar, cross river state - nigeria.

An aquatic ecological evaluation of Calabar River Port terminals was carried out from February 2020 to January, 2021 with the aim of assessing seasonal variation of heavy metals and the distribution of phytoplankton. Atomic absorption spectroscopy (AAS) was employed to analyze heavy metal concentration and standard procedure was use in identification of phytoplankton from three sampling stations namely Eco marine terminal, INTELS terminal and Shoreline terminals in Calabar River port. Results showed elevated levels of lead, Chromium, Mercury, Zink, Nickel and copper in all the stations beyond the NESREA recommended limits. The study also showed significant negative relationship between plankton and heavy metals. It recommends a yearly monitoring by regulatory agencies to ensure that shipping activities do not interfere with water quality at the terminals.

Using cyanobacteria and other phytoplankton to assess trophic conditions: A qPCR-based, multi-year study in twelve large rivers across the United States

Phytoplankton is the essential primary producer in fresh surface water ecosystems. However, excessive phytoplankton growth due to eutrophication significantly threatens ecologic, economic, and public health. Therefore, phytoplankton identification and quantification are essential to understanding the productivity and health of freshwater ecosystems as well as the impacts of phytoplankton overgrowth (such as Cyanobacterial blooms) on public health. Microscopy is the gold standard for phytoplankton assessment but is time-consuming, has low throughput, and requires rich experience in phytoplankton morphology. Quantitative polymerase chain reaction (qPCR) is accurate and straightforward with high throughput. In addition, qPCR does not require expertise in phytoplankton morphology. Therefore, qPCR can be a useful alternative for molecular identification and enumeration of phytoplankton. Nonetheless, a comprehensive study is missing which evaluates and compares the feasibility of using qPCR and microscopy to assess phytoplankton in fresh water. This study 1) compared the performance of qPCR and microscopy in identifying and quantifying phytoplankton and 2) evaluated qPCR as a molecular tool to assess phytoplankton and indicate eutrophication. We assessed phytoplankton using both qPCR and microscopy in twelve large freshwater rivers across the United States from early summer to late fall in 2017, 2018, and 2019. qPCR- and microscope-based phytoplankton abundance had a significant positive linear correlation (adjusted R2 = 0.836, p-value < 0.001). Phytoplankton abundance had limited temporal variation within each sampling season and over the three years studied. The sampling sites in the midcontinent rivers had higher phytoplankton abundance than those in the eastern and western rivers. For instance, the concentration (geometric mean) of Bacillariophyta, Cyanobacteria, Chlorophyta, and Dinoflagellates at the sampling sites in the midcontinent rivers was approximately three times that at the sampling sites in the western rivers and approximately 18 times that at the sampling sites in the eastern rivers. Welch's analysis of variance indicates that phytoplankton abundance at the sampling sites in the midcontinent rivers was significantly higher than that at the sampling sites in the eastern rivers (p-value = 0.013) but was comparable to that at the sampling sites in the western rivers (p-value = 0.095). The higher phytoplankton abundance at the sampling sites in the midcontinent rivers was presumably because these rivers were more eutrophic. Indeed, low phytoplankton abundance occurred in oligotrophic or low trophic sites, whereas eutrophic sites had greater phytoplankton abundance. This study demonstrates that qPCR-based phytoplankton abundance can be a useful numerical indicator of the trophic conditions and water quality in freshwater rivers.

High-throughput sequencing and marker pigment analysis of freshwater phytoplankton: A direct comparison with microscopic count data in the tropical crater lakes of Western Uganda

High-throughput DNA sequencing (HTS) and photosynthetic marker-pigment analysis can provide cost-and time-efficient alternatives for morphology-based microscopic identification and counting of lacustrine phytoplankton. However, application of particularly HTS in tropical lakes is still uncommon. We analyzed the community composition of cyanobacterial and eukaryotic phytoplankton in relation to trophic status and other environmental factors in 15 tropical crater lakes in western Uganda, using both high-performance liquid chromatography (HPLC) of photosynthetic marker pigments and HTS of 16 S and 18 S small subunit rRNA genes. We then compared the results with phytoplankton composition data based on microscopic identification and cell counting to evaluate whether the two former methods can be alternative or complementary approaches to analyze these lakes’ phytoplankton communities. HTS recorded 105 operational taxonomic units (OTUs) of cyanobacteria, and 197 OTUs of autotrophic eukaryotes mainly from dinoflagellates, cryptophytes and green algae. Ochrophyta (chrysophytes and diatoms) were present in low abundances only, and the few remaining sequences belonged to Streptophyta and Haptophyta. Marker pigment distribution among samples reflected the widespread and often dominant presence of cyanobacteria (primarily zeaxanthin, myxoxanthophyll and echinenone), followed by green algae (chlorophyll b, lutein, antheraxanthin, neoxanthin) and diatoms (fucoxanthin, diato-diadinoxanthin), and with cryptophyta (alloxanthin) important in some of the lakes. Direct and indirect ordinations of the OTUs and marker pigments revealed that, similar to patterns observed in cell counts, phytoplankton community composition differed between deep oligotrophic lakes and shallower more productive lakes, even though the distribution of cyanobacterial OTUs was more related to lake water conductivity and season than to trophic status. Procrustes analyses of the composition of green algae and Ochrophyta, the two dominant eukaryotic groups, based on HTS data showed patterns significantly similar to composition data based on cell counts, but no significant correlations were found between the complete eukaryotic or cyanobacterial HTS data and cell count data. While the latter discrepancies can be attributed to method-related biases in both HTS and microscopy, in contrast to the microscopic approach HTS failed to identify trophic indicator species and did not assign all lakes to the correct trophic category. Composition data based on marker pigments clustered the 15 lakes according to their trophic level only when pigment abundances were expressed as absolute concentrations, not when expressed as fractional abundances. We attribute this lower discriminating power partly to the wide distribution of cyanobacteria in these tropical crater lakes, besides the pigments’ low taxonomic resolution. Nevertheless, as the compositional patterns in relation to environmental variation observed in marker pigments and OTUs of the dominant eukaryotic phytoplankton groups are similar to those in cell count data, both methods hold potential for ecosystem-level monitoring of tropical crater lakes. However, the high-resolution HTS approach is handicapped by non-uniform amplification of gene sequences, while the low-resolution marker-pigment approach is handicapped by the widespread dominance of cyanobacteria in these systems irrespective of their trophic status.

Hydro-biological assessment of sustainable desert Rain-Fed ponds of Western Rajasthan using Physico-chemical characteristics and Phyto-planktonic indices

The present study reports the water quality of small rain-fed water reservoirs of Nagaur district, Rajasthan, India. These surface water bodies are called Talab and Nadis in the local language and play a significant role in fulfilling rural domestic water demands throughout the year from July2020-June 2021. The microfloral investigations of these ponds were neglected in the past. So, investigation is needed for water quality checks to improve the use of storage water strategy. The water samples were collected from July 2020 to June 2021 from selected four sampling ponds located in and around Nagaur city in nearby villages for Physico-chemical and phytoplankton analysis once in a month. Physical and chemical parameter were determined such as odour, pH, Total Dissolved Solid (TDS), Total Hardness, carbonate and bi-carbonate hardness and Total Alkalinity with organic parameter BOD, COD and organic matter by following the standard method of A.P.H.A., The Bureau of Indian Standards' IS:10500 drinking water standard was used to compare the outcomes (B.I.S. 2012). Palmer Pollution Index for genera was also employed by using algal and phytoplankton identification. It was concluded from the physicochemical and phytoplanktonic analysis results that among all sampling sites one of the urban sampling Talab (Jada Talab) located in Nagaur city showed deteriorated water quality but, all village ponds satisfactory water quality was recorded in rainy and winter but in summer phytoplankton analysis indicated poor water quality. The present study will be helpful in the future framework for the improved understanding of hydro-biological research and improvement in sustainable water management strategies in old water conservation rain-fed ponds of Western Rajasthan.

IDENTIFIKASI FITOPLANKTON PADA PERUT IKAN SELINCAH (Belontia hasselti) DARI RAWA MENTUKUL DI KABUPATEN BANGKA SELATAN

The Selincah fish (Belontia hasselti) is a local Indonesian fish that is widely consumed and has the potential to become ornamental fish. This fish must be domesticated to suppress its exploitation from natural catches. The domestication process requires biological information including eating habits. For this reason, in this study, the identification of phytoplankton contained in the stomach contents of the agile fish was carried out. Fish samples were obtained from Rawa Metukul, South Bangka Regency. The types of phytoplankton in the stomach and intestines of lively fish are the classes Bacillariophyceae, Chlorophyceae, Cyanophyceae, Chlorophyceae, Chrysophyceae, Chrysophyceae. The most dominant species were found in the Chlorophyceae class with an Index of preponderance value of 42.42%, while the Chrystophyceae class was found at least 2.99%.

Methodology for Phytoplankton Taxonomic Group Identification towards the Development of a Lab-on-a-Chip

This paper presents the absorbance and fluorescence optical properties of various phytoplankton species, looking to achieve an accurate method to detect and identify a number of phytoplankton taxonomic groups. The methodology to select the excitation and detection wavelengths that results in superior identification of phytoplankton is reported. The macroscopic analyses and the implemented methodology are the base for designing a lab-on-a-chip device for a phytoplankton group identification, based on cell analysis with multi-wavelength lighting excitation, aiming for a cheap and portable platform. With such methodology in a lab-on-a-chip device, the analysis of the phytoplankton cells’ optical properties, e.g., fluorescence, diffraction, absorption and reflection, will be possible. This device will offer, in the future, a platform for continuous, autonomous and in situ underwater measurements, in opposition to the conventional methodology. A proof-of-concept device with LED light excitation at 450 nm and a detection photodiode at 680 nm was fabricated. This device was able to quantify the concentration of the phytoplankton chlorophyll a. A lock-in amplifier electronic circuit was developed and integrated in a portable and low-cost sensor, featuring continuous, autonomous and in situ underwater measurements. This device has a detection limit of 0.01 µ/L of chlorophyll a, in a range up to 300 µg/L, with a linear voltage output with chlorophyll concentration.

Imaging Technologies Build Capacity and Accessibility in Phytoplankton Species Identification Expertise for Research and Monitoring: Lessons Learned During the COVID-19 Pandemic.

As primary producers, phytoplankton play an integral role in global biogeochemical cycles through their production of oxygen and fixation of carbon. They also provide significant ecosystem services, by supporting secondary production and fisheries. Phytoplankton biomass and diversity have been identified by the Global Ocean Observing System (GOOS) as Essential Ocean Variables (EOVs), properties that need to be monitored to better understand and predict the ocean system. Phytoplankton identification and enumeration relies on the skills and expertise of highly trained taxonomic analysts. The training of new taxonomic analysts is intensive and requires months to years of supervised training before an analyst is able to independently and consistently apply identification skills to a sample. During the COVID-19 pandemic, access to laboratories was greatly restricted and social distancing requirements prevented supervised training. However, access to phytoplankton imaging technologies such as the Imaging FlowCytobot (IFCB), FlowCam, and PlanktoScope, combined with open online taxonomic identification platforms such as EcoTaxa, provided a means to continue monitoring, research, and training activities remotely when in-person activities were restricted. Although such technologies can not entirely replace microscopy, they have a great potential for supporting an expansion in taxonomic training, monitoring, surveillance, and research capacity. In this paper we highlight a set of imaging and collaboration tools and describe how they were leveraged during laboratory lockdowns to advance research and monitoring goals. Anecdotally, we found that the use of imaging tools accelerated the training of new taxonomic analysts in our phytoplankton analysis laboratory. Based on these experiences, we outline how these technologies can be used to increase capacity in taxonomic training and expertise, as well as how they can be used more broadly to expand research opportunities and capacity.