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Academic literature on the topic 'Plankton'

Author: Grafiati

Published: 4 June 2021

Last updated: 14 December 2024

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Journal articles on the topic "Plankton"

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Andriyani, Nuraina, Arif Mahdiana, Endang Hilmi, and Samuel Kristian. "The Correlation Between Plankton Abundance And Water Quality in Donan River." Omni-Akuatika 16, no. 3 (December 30, 2020): 14. http://dx.doi.org/10.20884/1.oa.2020.16.3.844.

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Planktons have ability to live in aquatic ecosystem, including rivers ecosystem, estuary ecosystem, lake ecosystem and ocean ecosystem. The plankton abundance is estimated by correlation with water quality both of salinity, pH, temperature and others. This research aimed to analysis plankton abundance and to analysis correlation between plankton abundance and water quality. This research was conducted in Donan River using random sampling in 10 stations. The plankton are collected using plankton net no 25 and Lackey Drop Mikrotranset Counting (plankton analysis) and APHA (2005) to analysis water quality. The results showed that the plankton abundance ranged between 524 – 6,406 ind L-1 and best correlation with water salinity had index 0.975. Keywords: plankton abundance, water quality, Donan river, water salinity, correlation

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Maya Evita, Isnaini Nurul, Riche Hariyati, and Jafron Wasiq Hidayat. "Kelimpahan dan Keanekaragaman Plankton Sebagai Bioindikator Kualitas Air di Perairan Pantai Sayung Kabupaten Demak Jawa Tengah." Bioma : Berkala Ilmiah Biologi 23, no. 1 (June 2, 2021): 25–32. http://dx.doi.org/10.14710/bioma.23.1.25-32.

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Sayung coast is a area with a growing residential, sea ranching, and industrial area. Those aspects produce create waste that could harm the environment, directly or indirectly. Plankton is a biologic component that is used to indicate the changes of water quality in waters that has been polluted. These goals of this research are to know the water quality in Sayung coast area from the abundance of the plankton, physical-chemical parameter of the water, and also the status of water saprobity. The samples are taken in July 2017 and April 2018, in Sayung coast waters, Demak. Plankton sampling and water from 5 sampling stasions are considered to represent the diversity of the plankton and water stability. Plankton is sampled using plankton net No.25, then preserved using 70% alcohol + 4% formaldehyde. The abiotic data measureted is nitrate content, temperature, pH, salinity, DO, and turbidity. Data analysis are done using Shannon Weiner’s diversity index (H’), diversty index (e), domination index (C), saprobic index. The result shows that there are 49 species of planktons are found, which are 38 fitoplankton, and 11 zooplankton. The highest group is Bacillariophyta which is 14,24%. The diversty index value of H’ 1,58 – 2,45; therefore the Sayung coast waters is catagorized as stable. The index value of e ranges from 0,64 – 1; index C values ranges from 0,08 – 0,22; and the saprobirity index value is in β-Meso/Polisaprobik to α-Mesosaprobik phase with a very light to very high pollution levels. The physical-chemical parameter analysis of Sayung coast waters in overall is still suitable to support plankton’s life.

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NGUYEN-QUANG, TRI, and FREDERIC GUICHARD. "THE ROLE OF BIOCONVECTION IN PLANKTON POPULATION WITH THERMAL STRATIFICATION." International Journal of Bifurcation and Chaos 20, no. 06 (June 2010): 1761–78. http://dx.doi.org/10.1142/s0218127410026812.

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This paper investigates hydrodynamic processes of suspended planktonic population within a thermal stratification to represent a thermocline, in using a model of coupled equations: Navier–Stokes' equation for the fluid dynamic motion, Fisher's equation for the planktonic population with logistic growth, energy conservation equation for thermal effects and the Boussinesq approximation for the dependence on mass density of plankton. The planktonic population is assumed to be slightly denser than the fluid and to follow logistic growth. A numerical investigation is conducted to study patterns of plankton distribution under thermal stratification, and we adopt the finite volume method for solving the system of governing equations in simulations. It is found that thermal stratification constrains the feedback between hydrodynamic and plankton dynamics. More precisely, when temperature is lower in the upper than in the lower layer, the temperature gradient is destabilizing and both convection mechanisms — plankton motility (i.e. taxis behavior that can induce bioconvection) and temperature gradient — are additive. In the case of higher temperature in the upper than the lower layer, which applies to most natural systems, thermal stratification can dampen bioconvection and induce oscillatory dynamics if plankton diffuses faster than temperature. In all cases, if hydrodynamic and demographic time scales overlap, plankton growth rate has a strong effect on hydrodynamic processes involving both thermal convection and convection created by gravitaxis mechanism. Our study thus reveals the potential feedback between hydrodynamic and local demographic processes in plankton populations.

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Pradhan, Anisha, Pampa Bhattacharjee, and Diamond Rajakumar Tenali. "Temporal and Spatial Dynamics of Plankton Communities in the Lower Haora River, Tripura, India." UTTAR PRADESH JOURNAL OF ZOOLOGY 45, no. 9 (April 13, 2024): 36–45. http://dx.doi.org/10.56557/upjoz/2024/v45i94022.

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Planktons are significant bioindicator of ecosystem functioning, knowledge of the seasonal fluctuation in the plankton population in riverine waters of Indian subcontinent is rather limited. In the present study, analysis regarding spatio-temporal variations based on different multivariate statistics and indicator value analysis is done along with analysis of community structure of plankton assemblages. A total of 46 plankton taxa out of which 38 phytoplankton and 8 zooplankton taxa have been identified based on examination of samples taken from four locations over three sampling seasons. The primary phytoplankton families that involve Chlorophyceae, Bacillariophyceae, Cyanophyceae, Euglenophyceae and Composopogonophyceae. Chlorophyceae dominated the phytoplankton population, followed by Bacillariophyceae and Cyanophyceae. The plankton abundance was recorded highest in spring, followed by winter, and the least reported in monsoon season. The high average percent contribution of Aulacoseira, Oscillatoria, and Spirogyra species is well represented through SIMPER analysis. In addition, the Shannon–Wiener index (H) was calculated to determine plankton diversity, and Pielous' Evenness index (E) was calculated to determine individual distribution within a community whereas Margalef’s Richness index showed species richness of the study area. This qualitative and quantitative study will aid future research on the occurrence of plankton as well as the more trustworthy information generation on fish diet and feeding behaviors. The condition of planktons as bioindicators would indirectly provide an estimation of the ecosystem's natural state or amount of pollution.

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Kirby, Richard R., and John A. Lindley. "Molecular analysis of Continuous Plankton Recorder samples, an examination of echinoderm larvae in the North Sea." Journal of the Marine Biological Association of the United Kingdom 85, no. 3 (June 2005): 451–59. http://dx.doi.org/10.1017/s0025315405011392.

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Analysis of the biological time series of plankton samples collected by the Continuous Plankton Recorder (CPR) in the North Atlantic and North Sea has shown a regime shift in the plankton in this region. Both the distributions of planktonic organisms and their timing of occurrence in the seasonal cycle have changed and these changes appear to reflect global warming. In the North Sea the planktonic larvae of echinoderms have shown a recent dramatic increase in both relative and absolute abundance and their seasonal peak of occurrence has advanced by 47 days. The identity of the echinoderm larvae involved in this change has, however, remained equivocal. The small size of many organisms like echinoderm larvae combined with incomplete taxonomic keys hinders their visual identification and their fragility often means that useful morphological features are damaged during sampling by the CPR. Here, using new molecular methods applied to CPR samples, we show that planktonic larvae of the benthic Echinocardium cordatum dominate the North Sea plankton. We argue that since this species benefits from mild winters and warmer waters their numerical increase in the plankton is consistent with recent climatic changes that appear to be affecting the wider ecology of this region.

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Prakasa, E., A. Rachman, D. R. Noerdjito, and R. Wardoyo. "Development of segmentation algorithm for determining planktonic objects from microscopic images." IOP Conference Series: Earth and Environmental Science 944, no. 1 (December 1, 2021): 012025. http://dx.doi.org/10.1088/1755-1315/944/1/012025.

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Abstract Plankton are free-floating organisms that live, grow, and move along with the ocean currents. This free-floating organism plays important roles as primary producers, they serve as a link to energy transfer, and a factor that regulates the biogeochemical cycles. Indonesia, with almost 60% of its territory covered by the ocean, harbours a wide variety of planktonic species. However, one of the issues within usual planktonic studies is the lack of a fast and accurate method for identifying and classifying the plankton type. Thus, the computer vision methods on microscopic images were proposed to deal with the problem. The classification follows two main steps, detecting plankton location and followed by plankton differentiation. The segmentation algorithm is required to limit the determination area. The present study describes the segmentation methods on fifteen plankton types. The U-Net based architecture was implemented to segment the plankton texture from other objects. The segmentation result was also compared with the manual assessment to compute the performance parameters. The accuracy, 0.970±0.025, gives the highest value whereas the smallest value is found in the precision parameter, 0.761±0.156.

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Taylor, W. D., J. H. Carey, D. R. S. Lean, and D. J. McQueen. "Organochlorine Concentrations in the Plankton of Lakes in Southern Ontario and Their Relationship to Plankton Biomass." Canadian Journal of Fisheries and Aquatic Sciences 48, no. 10 (October 1, 1991): 1960–66. http://dx.doi.org/10.1139/f91-233.

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Hydrophobic organochlorine contaminants were surveyed in net plankton from 33 lakes in southern Ontario. Organochlorines were detected in all lakes. The relative concentrations of 12 common organochlorines were generally similar, suggesting that they derive from a common source, probably atmospheric transport. Variability in relative abundances of these contaminants increased with contaminant concentration, while contaminant concentration was related to plankton biomass, total phosphorus, and conductivity. Lakes with low plankton biomass had high organochlorine concentrations in that biomass, indicating that a large portion of the variation among lakes in the concentration of contaminants in plankton can be ascribed to variable planktonic biomass. This negative relationship with plankton biomass, or biomass dilution effect, was strongest for the more hydrophobic and refractory compounds.

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Sani, M. D., P. A. Wiradana, A. Y. Maharani, R. E. Mawli, and A. T. Mukti. "The dominance and proportions of plankton in Pacific white shrimp (Litopenaeus vannamei) ponds cultivated with the intensive system in Bulukumba Regency, South Sulawesi, Indonesia." IOP Conference Series: Earth and Environmental Science 1036, no. 1 (July 1, 2022): 012057. http://dx.doi.org/10.1088/1755-1315/1036/1/012057.

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Abstract This study aimed to evaluate plankton in Pacific white shrimp (Litopenaeus vannamei) cultivation in Bulukumba Regency, South Sulawesi. The study was conducted in six intensive ponds for 84 days from November 2019 to February 2020. Plankton samples were collected every 10 days for 8 weeks based on the day of culture (DOC) of Pacific white shrimp since the first rearing in the pond using plankton net (mesh size of 25 μm). Then, planktons were preserved to 5% formalin buffer in 250 mL of sterile plastic. Next, the plankton densities and compositions were analyzed quantitatively and qualitatively. The results showed that plankton dominance in Chlorophyta species and the presence was evenly distributed across all shrimp ponds in the field. The number was relatively stable in all shrimp DOCs and was the highest proportion as well; Chlorophyta (73 to 83%), Diatom group (7.75 to 15.63%), and blue-green algae (BGA) group (7.13 to 13.50%). Plankton can be used as a biomonitor of pollution and shrimp health in dominance and the percentage proportion of each species. Regular monitoring is highly recommended to minimize plankton growth, especially the BGA type that can harm shrimp health in the intensive system.

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Li, Yan, Jiahong Guo, Xiaomin Guo, Zhiqiang Hu, and Yu Tian. "Plankton Detection with Adversarial Learning and a Densely Connected Deep Learning Model for Class Imbalanced Distribution." Journal of Marine Science and Engineering 9, no. 6 (June 8, 2021): 636. http://dx.doi.org/10.3390/jmse9060636.

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Detecting and classifying the plankton in situ to analyze the population diversity and abundance is fundamental for the understanding of marine planktonic ecosystem. However, the features of plankton are subtle, and the distribution of different plankton taxa is extremely imbalanced in the real marine environment, both of which limit the detection and classification performance of them while implementing the advanced recognition models, especially for the rare taxa. In this paper, a novel plankton detection strategy is proposed combining with a cycle-consistent adversarial network and a densely connected YOLOV3 model, which not only solves the class imbalanced distribution problem of plankton by augmenting data volume for the rare taxa but also reduces the loss of the features in the plankton detection neural network. The mAP of the proposed plankton detection strategy achieved 97.21% and 97.14%, respectively, under two experimental datasets with a difference in the number of rare taxa, which demonstrated the superior performance of plankton detection comparing with other state-of-the-art models. Especially for the rare taxa, the detection accuracy for each rare taxa is improved by about 4.02% on average under the two experimental datasets. Furthermore, the proposed strategy may have the potential to be deployed into an autonomous underwater vehicle for mobile plankton ecosystem observation.

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Gong, Luo Jun, Xiao Xiao Wang, Jun Li, Wei Han, and Qian Qian Yan. "Preliminary Observation of Plankton in the Rural Village Wetland Sewage Treatment System." Advanced Materials Research 664 (February 2013): 222–27. http://dx.doi.org/10.4028/www.scientific.net/amr.664.222.

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We determined that there are 5 door 35 species of phytoplankton, 6 Galaxy ecological agriculture co., LTD, The average biomass liveweight is 0.6006 mg/l. The reason of less species of plankton and low liveweight of biomass in the system is that the ecological environment of the system is not suitable for general plankton's survival and growth. Therefore, the rural village wetland sewage treatment system has certain inhibition on plankton. On the system engineering designing we shouldn’t consider the factor of plankton.

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Dissertations / Theses on the topic "Plankton"

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Striebel, Maren. "PLANKTON DYNAMICS." Diss., lmu, 2008. http://nbn-resolving.de/urn:nbn:de:bvb:19-92597.

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Del, Giorgio Paul A. "Heterotrophy in lake plankton." Thesis, McGill University, 1993. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=41362.

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The overall aim of this thesis was to determine the relative importance of heterotrophy and autotrophy in lake plankton. Empirical analyses using extensive surveys of literature data revealed three specific patterns in metabolism and biomass structure in freshwater plankton. First, the ratio of phytoplankton production to plankton respiration (P/R ratio) tends to be low in unproductive lakes ($<$1), and increases along gradients of enrichment. Second, the contribution of planktonic heterotrophs (bacteria and zooplankton) to community respiration is highest in oligotrophic lakes. Third, planktonic heterotrophs dominate community biomass in oligotrophic lakes, whereas phytoplankton increasingly dominate plankton biomass along gradients of enrichment. These three distinct patterns were then tested simultaneously in a set of lakes that span a wide trophic gradient. Results indicated that the plankton of oligotrophic and mesotrophic lakes were characterized by P/R ratios well below unity, and a high contribution of heterotrophs to both community respiration and biomass. These trends are completely the opposite in the most productive lakes. The plankton communities of oligotrophic temperate lakes are predominantly heterotrophic and extensively utilize external inputs of carbon, and therefore only the plankton of eutrophic lakes conformed to the classical phytoplankton-based food web. In most lakes, excess heterotrophic activity could be supported by inputs of organic matter from the drainage basin. Excess plankton respiration, fueled by allochthonous organic carbon, could represent an important source of CO$ sb2$ to lakes.

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Birch, Daniel A. "Plankton modeling at multiple scales." Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2007. http://wwwlib.umi.com/cr/ucsd/fullcit?p3274810.

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Thesis (Ph. D.)--University of California, San Diego, 2007.
Title from first page of PDF file (viewed October 9, 2007). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 132-138).

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Kotrc, Benjamin. "Evolution of Silica Biomineralizing Plankton." Thesis, Harvard University, 2013. http://dissertations.umi.com/gsas.harvard:10969.

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The post-Paleozoic history of the silica cycle involves just two groups of marine plankton, radiolarians and diatoms. I apply paleobiological methods to better understand the Cenozoic evolution of both groups. The Cenozoic rise in diatom diversity has long been related to a concurrent decline in radiolarian test silicification. I address evolutionary questions on both sides of this coevolutionary coin: Was the taxonomic diversification of diatoms accompanied by morphological diversification? Is our view of morphological diatom diversification affected by sampling biases? What evolutionary mechanisms underlie the macroevolutionary decline in radiolarian silicification? Conventionally, diatom diversification describes a steep, monotonic rise, a view recently questioned due to sampling bias. For a different perspective, I constructed a diatom morphospace based on discrete characters, populated through time using an occurrence-level database. Distances between taxa in morphospace and on a molecular phylogeny are not strongly correlated, suggesting that morphospace was explored early in their evolutionary history, followed by relative stasis. I quantified morphospace occupancy through time using several disparity metrics. Metrics describing average separation of taxa show stasis, while metrics describing occupied volume show an increase with time. Disparity metrics are also subject to sampling biases. Under subsampling, I find that disparity metrics show varied responses: metrics describing separation of taxa into morphospace are unaffected, while those describing occupied volume lose their clear increases. Disparity can have geographic components, analogous to \(\alpha\) and \(\beta\) taxonomic diversity; I find more evidence of stasis in an analysis of \(\bar{\alpha}\) disparity. Overall, these results suggest stasis in Cenozoic diatom disparity. The radiolarian decline in silicification could result from either macroevolutionary processes operating above the species level (punctuated queilibria) or anagenetic changes within lineages. I measured silicification in three phyletic lineages, Stichocorys, Didymocyrtis, and Centrobotrys, from four tropical Pacific DSDP sites. Likelihood-based model fitting finds no strong support for directional evolution, pointing toward selection among species, rather than within species. Each lineage shows a different trajectory, perhaps due to differences in the ecological role played by the test. Because Stichocorys shows close correspondence to the assemblage-level trend, abundance may be an important factor through which within-lineage changes can influence the macroevolutionary pattern.
Earth and Planetary Sciences

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Mantilla, Jose G. (Jose Gabriel) 1972. "Models of plankton biomass spectra." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/80212.

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Martin, Mark A. "The influence of seasonal and climatic environmental changes on plankton in the marine mixed layer /." Thesis, Connect to this title online; UW restricted, 2000. http://hdl.handle.net/1773/6788.

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Kramer, Kurt A. "Identifying plankton from grayscale silhouette images." [Tampa, Fla.] : University of South Florida, 2005. http://purl.fcla.edu/fcla/etd/SFE0001402.

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Pitchford, Jonathan William. "Dynamics of multi-species plankton populations." Thesis, University of Leeds, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.397772.

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Pascual-Dunlap, Maria Mercedes. "Some nonlinear problems in plankton ecology." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/38049.

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Matuszewski, Damian Janusz. "Computer vision for continuous plankton monitoring." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/45/45134/tde-24042014-150825/.

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Plankton microorganisms constitute the base of the marine food web and play a great role in global atmospheric carbon dioxide drawdown. Moreover, being very sensitive to any environmental changes they allow noticing (and potentially counteracting) them faster than with any other means. As such they not only influence the fishery industry but are also frequently used to analyze changes in exploited coastal areas and the influence of these interferences on local environment and climate. As a consequence, there is a strong need for highly efficient systems allowing long time and large volume observation of plankton communities. This would provide us with better understanding of plankton role on global climate as well as help maintain the fragile environmental equilibrium. The adopted sensors typically provide huge amounts of data that must be processed efficiently without the need for intensive manual work of specialists. A new system for general purpose particle analysis in large volumes is presented. It has been designed and optimized for the continuous plankton monitoring problem; however, it can be easily applied as a versatile moving fluids analysis tool or in any other application in which targets to be detected and identified move in a unidirectional flux. The proposed system is composed of three stages: data acquisition, targets detection and their identification. Dedicated optical hardware is used to record images of small particles immersed in the water flux. Targets detection is performed using a Visual Rhythm-based method which greatly accelerates the processing time and allows higher volume throughput. The proposed method detects, counts and measures organisms present in water flux passing in front of the camera. Moreover, the developed software allows saving cropped plankton images which not only greatly reduces required storage space but also constitutes the input for their automatic identification. In order to assure maximal performance (up to 720 MB/s) the algorithm was implemented using CUDA for GPGPU. The method was tested on a large dataset and compared with alternative frame-by-frame approach. The obtained plankton images were used to build a classifier that is applied to automatically identify organisms in plankton analysis experiments. For this purpose a dedicated feature extracting software was developed. Various subsets of the 55 shape characteristics were tested with different off-the-shelf learning models. The best accuracy of approximately 92% was obtained with Support Vector Machines. This result is comparable to the average expert manual identification performance. This work was developed under joint supervision with Professor Rubens Lopes (IO-USP).
Microorganismos planctônicos constituem a base da cadeia alimentar marinha e desempenham um grande papel na redução do dióxido de carbono na atmosfera. Além disso, são muito sensíveis a alterações ambientais e permitem perceber (e potencialmente neutralizar) as mesmas mais rapidamente do que em qualquer outro meio. Como tal, não só influenciam a indústria da pesca, mas também são frequentemente utilizados para analisar as mudanças nas zonas costeiras exploradas e a influência destas interferências no ambiente e clima locais. Como consequência, existe uma forte necessidade de desenvolver sistemas altamente eficientes, que permitam observar comunidades planctônicas em grandes escalas de tempo e volume. Isso nos fornece uma melhor compreensão do papel do plâncton no clima global, bem como ajuda a manter o equilíbrio do frágil meio ambiente. Os sensores utilizados normalmente fornecem grandes quantidades de dados que devem ser processados de forma eficiente sem a necessidade do trabalho manual intensivo de especialistas. Um novo sistema de monitoramento de plâncton em grandes volumes é apresentado. Foi desenvolvido e otimizado para o monitoramento contínuo de plâncton; no entanto, pode ser aplicado como uma ferramenta versátil para a análise de fluídos em movimento ou em qualquer aplicação que visa detectar e identificar movimento em fluxo unidirecional. O sistema proposto é composto de três estágios: aquisição de dados, detecção de alvos e suas identificações. O equipamento óptico é utilizado para gravar imagens de pequenas particulas imersas no fluxo de água. A detecção de alvos é realizada pelo método baseado no Ritmo Visual, que acelera significativamente o tempo de processamento e permite um maior fluxo de volume. O método proposto detecta, conta e mede organismos presentes na passagem do fluxo de água em frente ao sensor da câmera. Além disso, o software desenvolvido permite salvar imagens segmentadas de plâncton, que não só reduz consideravelmente o espaço de armazenamento necessário, mas também constitui a entrada para a sua identificação automática. Para garantir o desempenho máximo de até 720 MB/s, o algoritmo foi implementado utilizando CUDA para GPGPU. O método foi testado em um grande conjunto de dados e comparado com a abordagem alternativa de quadro-a-quadro. As imagens obtidas foram utilizadas para construir um classificador que é aplicado na identificação automática de organismos em experimentos de análise de plâncton. Por este motivo desenvolveu-se um software para extração de características. Diversos subconjuntos das 55 características foram testados através de modelos de aprendizagem disponíveis. A melhor exatidão de aproximadamente 92% foi obtida através da máquina de vetores de suporte. Este resultado é comparável à identificação manual média realizada por especialistas. Este trabalho foi desenvolvido sob a co-orientacao do Professor Rubens Lopes (IO-USP).

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Books on the topic "Plankton"

1

Voskuil, J. J. Plankton. Amsterdam: G.A. van Oorschot, 1997.

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Kierc, Bogusław. Plankton. Wrocław, Poland: Biuro Literackie, 2006.

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1952-, Sommer Ulrich, ed. Plankton ecology: Succession in plankton communities. Berlin ; New York: Springer-Verlag, 1989.

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1952-, Sommer Ulrich, ed. Plankton ecology: Succession in plankton communities. Berlin: Springer-Verlag, 1989.

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Nontji, Anugerah. Plankton laut. Jakarta: Lembaga Ilmu Pengetahuan Indonesia, LIPI Press, 2008.

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Sommer, Ulrich, ed. Plankton Ecology. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-74890-5.

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Lockett, Fred. Plankton & PSP. Bellingham, WA: Huxley College of Environmental Studies, 2000.

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U, Haq Bilal, ed. Plankton biochronology. Oxford: Elsevier, 1989.

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M, Bolli Hans, Saunders John B, and Perch-Nielsen Katharina, eds. Plankton stratigraphy. Cambridge [Cambridgeshire]: Cambridge University Press, 1985.

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Walz, Norbert, ed. Plankton Regulation Dynamics. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-77804-9.

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Book chapters on the topic "Plankton"

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Gomez, Felipe. "Plankton." In Encyclopedia of Astrobiology, 1285. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-11274-4_1232.

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Gomez, Felipe. "Plankton." In Encyclopedia of Astrobiology, 1944–45. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-44185-5_1232.

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Denne, Richard A. "Plankton." In Selective Neck Dissection for Oral Cancer, 1–11. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-02330-4_55-1.

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Gomez, Felipe. "Plankton." In Encyclopedia of Astrobiology, 1. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-27833-4_1232-2.

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Gomez, Felipe. "Plankton." In Encyclopedia of Astrobiology, 2385–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 2023. http://dx.doi.org/10.1007/978-3-662-65093-6_1232.

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Paerl, Hans W. "Marine Plankton." In Ecology of Cyanobacteria II, 127–53. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-3855-3_5.

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Bährle-Rapp, Marina. "Plankton Extract." In Springer Lexikon Kosmetik und Körperpflege, 432. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-71095-0_8033.

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Beyers, Robert J., and Howard T. Odum. "Plankton Columns." In Springer Advanced Texts in Life Sciences, 322–40. New York, NY: Springer New York, 1993. http://dx.doi.org/10.1007/978-1-4613-9344-3_15.

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Emschermann, Peter, Odwin Hoffrichter, Helge Körner, and Dieter Zissler. "Das Plankton." In Meeresbiologische Exkursion, 171–211. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-39396-9_2.

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Adolf, Jason E. "Mixotrophic Plankton." In Encyclopedia of Estuaries, 447–48. Dordrecht: Springer Netherlands, 2015. http://dx.doi.org/10.1007/978-94-017-8801-4_408.

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Conference papers on the topic "Plankton"

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Mengüç, M. P., S. Alstedt, and S. Manickavasagam. "On the Optical and Radiative Properties of Phytoplankton." In Optical Remote Sensing of the Atmosphere. Washington, D.C.: Optica Publishing Group, 1997. http://dx.doi.org/10.1364/orsa.1997.omd.4.

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More than 70 percent of the surface of the earth is covered with water, which serves as habitat for a vast number of living creatures. The suspended particulate matter in the sea is divided into living organisms, known as plankton, and dead (decaying) matter called detrius. Plankton includes all passive creatures drifting in the sea; actually, the Greek term plankton means migratory, wandering. Plankton are varying greatly in size and growth rate, and is divided in subgroups, most importantly the nutritionally dependent zooplankton and phytoplankton, which represent a large group of planktonic plants residing in the surface waters. The phytoplankton group encompasses hundreds, maybe thousands of species, ranging in size from less than 2 μm to more than 2 mm, with most falling within 5 – 50 μm.

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Ishibashi, Shojiro, Hiroshi Yoshida, Dhugal J. Lindsay, Hiroyuki Yamamoto, Tadahiro Hyakudome, Takao Sawa, Hikaru Okuno, and Takayuki Uemura. "An Underwater Vehicle for the Tracking Marine Organism “PICASSO”." In ASME 2009 28th International Conference on Ocean, Offshore and Arctic Engineering. ASMEDC, 2009. http://dx.doi.org/10.1115/omae2009-80072.

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So far, a special net is used to sample marine organism such as planktons in the marine biology. It is called as a plankton-net. However it often breaks the tissue of the marine organism. So scientists of the marine biology demand a good tool to observe the marine organism instead of the plankton-net sampling. On the other hand, an underwater vehicle has been a focus of constant attention in order to observe the marine organism. The vehicle should be equipped with devices to observe the marine organism and measure the sea characteristic. So Japan Agency for Marine-Earth Science and Technology (JAMSTEC) has developed a new underwater vehicle “PICASSO”. It is small size vehicle, but it can be equipped with various observation and measurement devices. And also it can be applied to a small ship as its own support ship owing to its size. In this paper, the outline of PICASSO and its key technologies are described, and results of sea trials carried out until now are shown.

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Yigiterhan, Oguz, Jassem Abdulaziz Al-Thani, Samah Dib, Hamood Abdulla Alsaadi, and Ebrahim Mohd Al-Ansari. "The Influence of Qatari Dust on the Element Composition of Marine Plankton." In Qatar University Annual Research Forum & Exhibition. Qatar University Press, 2021. http://dx.doi.org/10.29117/quarfe.2021.0019.

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The Exclusive Economic Zone (EEZ) of Qatar is affected by extreme dust and extensive industrialization, making it an ideal location to examine influences of coastal processes on biological activity, which greatly affects marine biogeochemical cycling. In this study, the influence of dust on the trace element composition of plankton and how distance from shore effects elemental concentrations in marine plankton was investigated. Samples were collected using net tows with mesh sizes of 50 (bulkplankton) and 200 (zooplankton) mm size-fractions in 2012 and 2014 to examine temporal and spatial variabilities. The samples were strong acid digested and analyzed using ICP-OES. Trace metal clean techniques were used. The biogenic concentrations of trace metals were determined by correcting the bulk analyses for the lithogenic contribution using aluminum content of Qatari dust as a lithogenic tracer. The relative trace metal composition of plankton from EEZ of Qatar is Fe > Zn ≈ Cu > V ≈ Ni ≈ Cr ≈ As ≈ Mo > Cd ≈ Co. Small and large size planktonic compositions were similar, except for Ba, Mn, Pb, Mo which were higher in zooplankton than bulkplankton. It was not clear if the variability was due to differences in biology, proximity to the coast or interannual effects. The geochemical and statistical analysis suggested that the concentrations of Al, Fe, Cr, Co, Mn, Ni, Pb, Li in net-tow plankton samples were mostly of lithogenic (dust) and Cd, Cu, Mo, Zn, Ca are most likely of biogenic/anthropogenic origin. The excess concentrations relative to average dust from Qatar for most elements (except Cd) decreased with distance from shore. This may be due to contamination or uncertainties with the lithogenic correction or due to our sampling locations in a marginal sea, dominated by dust input. This is an aspect of this study that warrants more research.

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Lindsay, D., H. Yoshida, S. Ishibashi, M. Umetsu, A. Yamaguchi, H. Yamamoto, J. Nishikawa, et al. "The uROV PICASSO, the Visual Plankton Recorder, and other attempts to image plankton." In 2013 IEEE International Underwater Technology Symposium (UT 2013). IEEE, 2013. http://dx.doi.org/10.1109/ut.2013.6519854.

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Chernyavskaya, E. A. "Laser diagnostics of water plankton." In 17th Congress of the International Commission for Optics: Optics for Science and New Technology. SPIE, 1996. http://dx.doi.org/10.1117/12.2316188.

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Jenkinson, Ian R., Albert Co, Gary L. Leal, Ralph H. Colby, and A. Jeffrey Giacomin. "Ocean Rheology and Plankton Biology." In THE XV INTERNATIONAL CONGRESS ON RHEOLOGY: The Society of Rheology 80th Annual Meeting. AIP, 2008. http://dx.doi.org/10.1063/1.2964791.

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Prabhu, Santhosh, Ali Kheradmand, Brighten Godfrey, and Matthew Caesar. "Predicting Network Futures with Plankton." In APNet'17: First Asia-Pacific Workshop on Networking. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3106989.3106991.

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Zhao, Feng, Feng Lin, and Hock Soon Seah. "Bagging based plankton image classification." In 2009 16th IEEE International Conference on Image Processing ICIP 2009. IEEE, 2009. http://dx.doi.org/10.1109/icip.2009.5414357.

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Davis, Cabell S. "Optical imaging of ocean plankton." In Digital Holography and Three-Dimensional Imaging. Washington, D.C.: OSA, 2008. http://dx.doi.org/10.1364/dh.2008.dmb1.

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Dyomin, Victor V., and Alexey S. Olshukov. "Digital holographic video of plankton." In Optical Engineering + Applications, edited by Andrew G. Tescher. SPIE, 2008. http://dx.doi.org/10.1117/12.794713.

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Reports on the topic "Plankton"

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Banse, Karl. Plankton Production Biology. Fort Belvoir, VA: Defense Technical Information Center, September 2010. http://dx.doi.org/10.21236/ada541815.

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Banse, Karl. Plankton Production Biology. Fort Belvoir, VA: Defense Technical Information Center, September 2012. http://dx.doi.org/10.21236/ada573308.

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Banse, Karl. Plankton Production Biology. Fort Belvoir, VA: Defense Technical Information Center, September 2013. http://dx.doi.org/10.21236/ada599066.

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Banse, Karl. Plankton Production Biology. Fort Belvoir, VA: Defense Technical Information Center, September 2007. http://dx.doi.org/10.21236/ada604620.

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Donaghay, Percy L. Plankton Patch Feasibility Experiments. Fort Belvoir, VA: Defense Technical Information Center, September 2000. http://dx.doi.org/10.21236/ada609785.

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Donaghay, Percy L. Plankton Patch Feasibility Experiments. Fort Belvoir, VA: Defense Technical Information Center, September 1997. http://dx.doi.org/10.21236/ada627832.

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Donaghay, Percy L. Plankton Patch Feasibility Experiments. Fort Belvoir, VA: Defense Technical Information Center, September 2001. http://dx.doi.org/10.21236/ada628051.

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Donaghay, Percy L. Plankton Patch Feasibility Experiments. Fort Belvoir, VA: Defense Technical Information Center, September 1999. http://dx.doi.org/10.21236/ada629834.

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Adler, Robert. Superprocesses and Plankton Dynamics. Fort Belvoir, VA: Defense Technical Information Center, November 1997. http://dx.doi.org/10.21236/ada336941.

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Provenzale, A. Plankton Sinking and Turbulence. Fort Belvoir, VA: Defense Technical Information Center, July 2010. http://dx.doi.org/10.21236/ada557215.

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