Phytoplankton assemblage composition as an environmental indicator in routine lentic monitoring: Taxonomic versus functional groups

Cupertino, Arthur; Gücker, Björn; Rückert, Gabriela von; Figueredo, Cleber Cunha

doi:10.1016/j.ecolind.2019.01.054

Cited by 27 publications

(15 citation statements)

References 61 publications

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“…Algofloristic studies have covered many regions of the world since the middle of the last century (Barinova et al, 2011;Omar & Makhlough, 2014;Xuehual et al, 2019). However, the data accumulated in the scientific literature are mainly related to the certain types of aquatic ecosystems (Santana et al, 2017;Rodrigues et al, 2018;Cupertino et al, 2019). The study of formation and functioning of the patterns of the main autotrophic link in typologically different water bodies under the influence of natural and anthropogenic factors using the basin principle on the example of the Ukrainian Polissia can contribute to the further development of ideas about changes in aquatic communities (Shelyuk & Shcherbak, 2018).…”

Section: Introductionmentioning

confidence: 99%

Phytoplankton succession in the anthropogenic and climate ecological transformation of freshwater ecosystems

Shelyuk

Astahova

2021

Biosys. divers.

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The study is focused on the influence of mechanisms of anthropogenic activity and climate changes of different types and levels on the autotrophic link of freshwater ecosystems. The studies of the river, lake, water reservoir and quarry phytoplankton in the territory of the Ukrainian Polissia were carried out during 2005–2019 according to the standard methods. At the same time, we determined water hydrophysical and hydrochemical characteristics. Exactly 812 algal species represented by 877 infraspecific taxa were identified, including 75 new ones for the Ukrainian Polissia, with a significant share of thermophiles and halophiles. The dominance of Chlorophyta, Bacillariophyta, Euglenozoa and Cyanobacteria was observed in all types of water bodies. With the increase in the nutrient content in the composition of dominant complexes of river ecosystems, the role of centric diatoms Cyclotella meneghiniana, C. stelligera, Stephanodiscus hantzschii increased. The vegetation intensity of Aphanizomenon flos-aquae increased in the water courses with partially regulated flow, while vegetation of Chrysococcus rufescens, Pseudokephyrion pillidium, Kephyrion ovum intensified in rivers with increased colour of water. Water reservoirs are dominated by representatives of Bacillariophyta, Cyanobacteria, Euglenozoa, Miozoa, mostly by Aphanizomenon flos-aquae and Peridinium cinctum. The lowest number of dominant species was identified in the lakes, and belonged to the genera Trachelomonas, Peridinium, Chlamydomonas, Crucigeniella, Cyclotella, Aulacoseira. The dominant species in quarries were Cyclotella meneghiniana, Chlamydomonas monadina, Ch. globosa, Coelastrum microporum, Gomphosphaeria aponina, Trachelomonas volvocina and Microcystis aeruginosa. The obtained data can be used to predict scenarios of changes in the autotrophic link under the influence of natural and anthropogenic factors, to develop methods for monitoring and managing ecosystems at different levels of anthropogenic transformation necessary to ensure an appropriate level of their functions and ecological services.

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Section: Introductionmentioning

confidence: 99%

Phytoplankton succession in the anthropogenic and climate ecological transformation of freshwater ecosystems

Shelyuk

Astahova

2021

Biosys. divers.

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“…Phytoplankton functional groups have been used to study the impact of changes in the aquatic environment on the physiological, morphological and ecological characteristics of phytoplankton in different rivers, lakes and waters around the world (Becker et al, 2009(Becker et al, , 2010Kruk et al, 2017;Rodrigues et al, 2018). The application of the methods of classifying the functional groups of phytoplankton in aquatic ecosystems provides the key data reflecting dynamics of phytoplankton communities (Santana et al, 2017;Cupertino et al, 2019;Yao et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

The role of ecological groups in the formation of cyanobacterial communities in the ecosystems of the North Azov region (Ukraine)

et al. 2020

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The role of Cyanoprokaryota ecological groups in the ecosystems of the North Azov region was revealed in this work. On the territory of Pryazovskyi National Nature Park, 9 experimental polygons were studied, which covered steppe areas or slopes, salt marshes, coastal sandy soils and water bodies (rivers, lakes, estuaries, sea bays, lagoons). As a result of research on the territory of Pryazovskyi National Nature Park, 124 species of cyanoprokaryotes were identified, which include 127 intraspecific taxa. It was proved that the procedure of canonical correspondence analysis is the most suitable for the analysis of the species matrix. The axes identified as a result of the ordination procedure, which indicate the coordinated dynamics of the species, correlated with both synecological characteristics, such as diversity indicators, and with autoecological characteristics, such as ecotypes of cyanoprokaryotes in relation to habitat types or types of adaptation to salinity conditions. The first four canonical axes together explain 47.5% of species matrix variability. Canonical axis 1 explains 18.0% of the variability of the species matrix and is mostly marked by aqual subaerophytes and eurybionts. This axis indicates the presence of a gradient of salinity conditions where the most saline conditions correspond to the positive values of the axis, and the negative values correspond to less saline. Canonical axis 2 describes 12.1% of species matrix variability. This axis differentiates aquatic ecosystems from others. Canonical axis 3 explains 10.0% of the communities’ variability. This axis distinguishes freshwater ecosystems from saline ecosystems. Markers of freshwater communities are stenotopic halotolerants, which are narrow-range, common mainly in the temperate zone of Europe. The canonical axis 4 explains 7.3% of variability of the matrix of species and is able to differentiate sand ecosystems. The ecotopic structure and geographic range width of community species have the greatest independent value among the considered sources of variation. The independent role of adaptation to the salinity conditions of the ecotope and the role of the type of ecosystems is somewhat smaller. The interaction between the sources of variation is important in the variation of the structure of communities. The interaction between the ecotopic structure and the geographic range width of species and the triple interaction between the ecotopic structure of a community, the width of the geographic range of species and the ecosystem type plays the greatest role in the variation of community structure. Ecotopic groups, which indicate the preference of a particular habitat, correlate with the species composition of the communities. It is shown that the ratio of ecototopic groups in a community is a characteristic that reveals the features of the community as a whole.

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“…Studies have shown that phytoplankton functional groups H, X1, LO, and S1 are the most representative during the rainy and dry seasons in semi-arid reservoirs in Brazil [17], while phytoplankton functional groups LM, P, T, and Y exhibit strong seasonal variation in Erhai Lake, Yunnan, China [18]. The application of phytoplankton functional group classification methods in aquatic ecosystems provides key data that reflect the dynamics of phytoplankton communities [19,20].…”

Section: Introductionmentioning

confidence: 99%

Seasonal Succession of Phytoplankton Functional Groups and Driving Factors of Cyanobacterial Blooms in a Subtropical Reservoir in South China

Yao

Zhao

Zhou

et al. 2020

Water

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Freshwater phytoplankton communities can be classified into a variety of functional groups that are based on physiological, morphological, and ecological characteristics. This classification method was used to study the temporal and spatial changes in the phytoplankton communities of Gaozhou Reservoir, which is a large municipal water source in South China. Between January 2015 and December 2017, a total of 155 taxa of phytoplankton that belong to seven phyla were identified. The phytoplankton communities were classified into 28 functional groups, nine of which were considered to be representative functional groups (relative biomass > 10%). Phytoplankton species richness was greater in the summer and autumn than in the winter and spring; cyanobacterial blooms occurred in the spring. The seasonal succession of phytoplankton functional groups was characterized by the occurrence of functional groups P (Staurastrum sp. and Closterium acerosum) and Y (Cryptomonas ovata and Cryptomonas erosa) in the winter and spring, and functional groups NA (Cosmarium sp. and Staurodesmus sp.) and P (Staurastrum sp. and Closterium acerosum) in the summer and autumn. The temperature, nitrogen, and phosphorus levels were the main factors driving seasonal changes in the phytoplankton communities of Gaozhou Reservoir. The functional group M (Microcystis aeruginosa) dominated the community during the cyanobacterial blooms in spring 2016, with the maximum algal cell density of 3.12 × 108 cells L−1. Relatively low temperature (20.8 °C), high concentrations of phosphorus (0.080–0.110 mg L−1), suitable hydrological and hydrodynamic conditions (e.g., relatively long retention time), and relatively closed geographic location in the reservoir were the key factors that stimulated the cyanobacterial blooms during the early stages.

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Phytoplankton assemblage composition as an environmental indicator in routine lentic monitoring: Taxonomic versus functional groups

Cited by 27 publications

References 61 publications

Phytoplankton succession in the anthropogenic and climate ecological transformation of freshwater ecosystems

Phytoplankton succession in the anthropogenic and climate ecological transformation of freshwater ecosystems

The role of ecological groups in the formation of cyanobacterial communities in the ecosystems of the North Azov region (Ukraine)

Seasonal Succession of Phytoplankton Functional Groups and Driving Factors of Cyanobacterial Blooms in a Subtropical Reservoir in South China

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