Multivariate Analyses of Phytoplankton Pigment Fluorescence from a Freshwater River Network
| Autor: | Ruchi Bhattacharya, Christopher L. Osburn |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Chlorophyll
Multivariate analysis 010504 meteorology & atmospheric sciences Nitrogen Fresh Water STREAMS 010501 environmental sciences 01 natural sciences Freshwater ecosystem Rivers Phytoplankton Environmental Chemistry Organic matter 0105 earth and related environmental sciences chemistry.chemical_classification Hydrology Herbivore General Chemistry Fluorescence chemistry Environmental chemistry Multivariate Analysis River network Environmental science Seasons Environmental Monitoring |
| Zdroj: | Environmental Science & Technology. 51:6683-6690 |
| ISSN: | 1520-5851 0013-936X |
| Popis: | Monitoring phytoplankton classes in river networks is critical to understanding phytoplankton dynamics and to predicting the ecosystem response to changing land-use and seasons. Applicability of phytoplankton fluorescence as a quick and effective ecological monitoring approach is relatively unexplored in freshwater ecosystems. We used multivariate analyses of fluorescence from pigment extracted in 90% acetone to assess the variability in phytoplankton classes, herbivory, and organic matter quality in a freshwater river network. A total of four models developed by the parallel factor analysis (PARAFAC) of fluorescence excitation and emission matrices identified six components: Model 1 (pheophytin-A and chlorophyll-A), Model 2 (chlorophyll-B and chlorophyll-C), Model 3 (pheophytin-B), and Model 4 (pheophytin-C). Redundancy analyses revealed that in the summer, urban and agricultural streams were abundant in chlorophylls, fresh organic matter, and organic nitrogen, whereas in winter, streams were high in phaeopigments. A slow-moving, light-limited wetland stream was an exception as high phaeopigment abundance was observed in both seasons. The PARAFAC components were used to develop a partial least-squares regression-based model (r |
| Databáze: | OpenAIRE |
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