2014
DOI: 10.1007/s10750-014-1950-1
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Morpho-functional classifications of phytoplankton assemblages of two deep karstic lakes

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Cited by 36 publications
(12 citation statements)
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“…A previous study from southern China (Hu et al, 2013) and other studies from different environments (Abonyi et al, 2014;Petar et al, 2014) consistently showed that MFG were able to provide an ecological classification of phytoplankton fully comparable with that obtained with FGs (Reynolds et al, 2002). The present study showed a strong concordance between the MFG and genera-based ordinations, and an increasing discordance between the genera-based configurations and those based on higher taxonomical units (i.e.…”
Section: Discussionsupporting
confidence: 88%
“…A previous study from southern China (Hu et al, 2013) and other studies from different environments (Abonyi et al, 2014;Petar et al, 2014) consistently showed that MFG were able to provide an ecological classification of phytoplankton fully comparable with that obtained with FGs (Reynolds et al, 2002). The present study showed a strong concordance between the MFG and genera-based ordinations, and an increasing discordance between the genera-based configurations and those based on higher taxonomical units (i.e.…”
Section: Discussionsupporting
confidence: 88%
“…Due to the underlying carbonate bedrock, Plitvice Lakes are hard-water lakes with a large population of calcifying cyanobacteria (Plenković-Moraj et al 2002;Žutinić et al 2014), and are characterized by conditions favourable for calcite precipitation (SIcalc values range from 3 -10 and pH values range from 8.0 -8.7) (Barešić et al 2011;Srdoč et al 1985). Calcite precipitation is highest between spring and autumn, and is lower in wintertime (Srdoč et al 1985).…”
Section: Site Descriptionmentioning
confidence: 99%
“…Izaguirre et al (2012) also found greater explanatory power with the MBFG structure and concluded that this classification compared to FG, is more sensitive to certain aspects of the phytoplankton community that are important for ecosystem dynamics. Other authors also found better statistical results with the morphological structure when compared to other classifications (Petar et al 2014;Abonyi et al 2017;Lobo et al 2018). The advantages of morphological classification are the objectivity, the relative simplicity, and the independence from the taxonomic classification.…”
Section: Discussionmentioning
confidence: 88%