ASSESSING PHYTOPLANKTON COMMUNITIES IN MESOCOSMS AND ENDORHEIC KAZAKHSTANI LAKES USING IMAGING FLOW CYTOMETRY

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dc.contributor.authorDashkova, Veronika
dc.date.accessioned2024-04-03T12:14:25Z
dc.date.available2024-04-03T12:14:25Z
dc.date.issued2023-10-12
dc.description.abstractAccelerating climate change strongly affects inland aquatic ecosystems worldwide in physical, chemical, and biological aspects. Phytoplankton communities are the main producers, the basis of aquatic trophic webs, and are widely used as proxies for the evaluation of lake ecosystem states. They quickly react to environmental changes by shifting their composition, biomass, size, and biodiversity. However, the technologies, including light microscopy traditionally used for studying phytoplankton communities, may be challenging for research in multi-lake systems and complex mesocosm experiments requiring the processing of a large number of samples. Instead, high-throughput technologies such as imaging flow cytometry (IFC), combining flow cytometry and microscopy features and allowing a collection of large datasets of images and numerical parameters of plankton cells, provide a valuable alternative. The main goal of this study was to advance an IFC-based method for application to the routine analysis of phytoplankton community parameters in experimental artificial mesocosms and natural Kazakhstani lakes. Specific objectives include: 1. Advancement of methodology for phytoplankton, analysis based on IFC. 2. Application of advanced methodology to assess phytoplankton biomass, size distribution, and diversity in shallow lake mesocosms in response to nitrogen and temperature variations. 3. Application of advanced methodology to assess phytoplankton biomass, size distribution, and diversity along a salinity gradient in endorheic lakes, including Burabay National Nature Park (BNNP) lakes and the Aral Sea remnant waterbodies. A high-throughput IFC-based analysis pipeline capable of routine evaluation of hundreds of samples was advanced and the advanced approach was applied to characterize the phytoplankton community changes both in experimental artificial mesocosms and two natural systems of Kazakhstani lakes. Moreover, biovolume calculation formulae from microscopy 3D image analysis were adapted and modified to calculate cell biovolumes based on two-dimensional images obtained by IFC. Modified biovolume calculations were applied to the water samples from the mesocosms and endorheic lakes to obtain statistically significant quantitative data and enabled to explore patterns in phytoplankton communities in relation to the multiple environmental factors such as temperature, nutrients, and salinity gradient. In mesocosms, both nitrogen (N) and temperature variations significantly affected phytoplankton community structure. The addition of N in the phosphorus (P)-rich system caused the shift of dominance from colonial cyanobacteria to the dominance of chlorophytes and cyanobacteria. Phytoplankton size at varying temperature regimes was differentially affected by N enrichment: cellular size was reduced in the tanks with the highest temperature and increased at ambient and medium temperature tanks. The least phytoplankton diversity was caused by N enrichment at high temperatures. Phytoplankton community structure had significantly shifted along the salinity gradient in both former Aral Sea remnant water bodies and BNNP lakes. The community composition significantly differed between brackish, saline, and hypersaline sites. Also, using IFC analysis, we found that larger phytoplankton cells attributed to the brackish waters rather than saline and hypersaline sites. However, no distinct trends in phytoplankton diversity were observed in relation to the salinity gradient. We conclude that IFC methodology can be successfully used as a routine approach in both – quantitative and qualitative analysis of phytoplankton in artificial and natural water ecosystems.en_US
dc.identifier.citationDashkova, V. (2024). Assessing phytoplankton communities in mesocosms and endorheic Kazakhstani lakes using imaging flow cytometry. Nazarbayev University School of Engineering and Digital Sciencesen_US
dc.identifier.urihttp://nur.nu.edu.kz/handle/123456789/7606
dc.language.isoenen_US
dc.publisherNazarbayev University School of Engineering and Digital Sciencesen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectType of access: Restricteden_US
dc.subjectclimate changeen_US
dc.titleASSESSING PHYTOPLANKTON COMMUNITIES IN MESOCOSMS AND ENDORHEIC KAZAKHSTANI LAKES USING IMAGING FLOW CYTOMETRYen_US
dc.typePhD thesisen_US
workflow.import.sourcescience

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