Monitoring natural phytoplankton communities: a comparison between traditional methods and pulse-shape recording flow cytometry

Aquatic Microbial Ecology

L. Haraguchi¹ 

关键词: Phytoplankton;    Pulse-shape recording flow cytometry;    Microscopy;    Monitoring;    Biomass;    Timescale;   

DOI  :  10.3354/ame01842

学科分类：生物科学（综合）

来源: Inter-Research

【 摘 要 】

The phytoplankton community can vary within hours (physiology) to years (climatic and anthropogenic responses), and monitoring at different timescales is relevant for understanding community functioning and assessing changes. However, standard techniques used in monitoring programmes are time-consuming and/or expensive, limiting sampling frequency. The use of faster methods, such as flow cytometry, has become more frequent in phytoplankton studies, although comparisons between this technique and traditional ones are still scarce. This study aimed to assess if natural phytoplankton communities analysed with pulse-shape recording flow cytometry (PFCM) and classical techniques (chl a extracts and microscopy) provide comparable results. Monthly samples (March to September 2015) from 4 stations in Roskilde Fjord (Denmark) were analysed with PFCM and classical techniques. Results showed a highly significant correlation between total red fluorescence and chl a, and comparable cell counts from PFCM and microscopy for cell sizes >5 µm, but not for sizes <5 µm. We propose an empirical algorithm to obtain cell volumes from the integrated forward scatter signal from PFCM, making it possible to estimate carbon biomass with PFCM, applying the same conversion factors as for microscopy. Biomasses obtained with PFCM, estimated from live cells, were higher than microscopy for natural samples. We conclude that PFCM results are comparable to classical techniques, yet the data from PFCM had poor taxonomic resolution without support of other techniques. With the faster analysis capacity of PFCM, post-processing of data and analysis of high-resolution time series may be made easier.

【 授权许可】

Unknown