%0 Journal Article
%4 sid.inpe.br/mtc-m21d/2022/04.04.14.17
%2 sid.inpe.br/mtc-m21d/2022/04.04.14.17.56
%@doi 10.1007/s10201-021-00685-9
%@issn 1439-8621
%T Understanding the effects of environmental heterogeneity on the morphofunctional structure of the phytoplankton community during the hydrological year in an Amazon floodplain lake, Brazil
%D 2022
%8 Apr.
%9 journal article
%A Souza, Dilailson Araújo de,
%A Kraus, Cleber Nunes,
%A Burliga, Ana Luiza,
%A Melo, Sérgio de,
%A Couceiro, Sheyla,
%A Dias Silva, Karina,
%A Simőes, Nadson Ressye,
%A Braga, Tony,
%A Bonnet, Marie Paule,
%A Marques, David da Motta,
%@affiliation Universidade Federal do Pará (UFPA)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Universidade Federal do Pará (UFPA)
%@affiliation Universidade Federal do Oeste do Pará (UFOPA)
%@affiliation Universidade Federal do Oeste do Pará (UFOPA)
%@affiliation Universidade Federal do Pará (UFPA)
%@affiliation Universidade Federal do Sul da Bahia (UFSB)
%@affiliation Universidade Federal do Oeste do Pará (UFOPA)
%@affiliation Universidade de Brasília (UnB)
%@affiliation Institut de Recherche Pour Le Développement (IRD)
%@electronicmailaddress dilailson.souza@gmail.com
%@electronicmailaddress binhokraus@gmail.com
%B Limnology
%V 23
%N 2
%P 275-286
%K Aquatic system, Biovolume, Environmental factors.
%X The Amazon floodplains are complex systems influenced by the annual hydrological regime with an effect on the structuring of physical, chemical and biological processes. Thus, we evaluated the relationship of environmental factors with the composition and variation of functional groups based on morphology (MBFG) during the hydrological year in an Amazonian floodplain lake, with monthly sampling (2013 to 2014). We used analysis of variance (ANOVA) and KruskalWallis to show differences in physicochemical variables between hydroperiods. We performed permutation analysis of variance (PERMANOVA) to assess the dissimilarity of morphofunctional groups between hydroperiods and also of environmental data between the months of the study and RDA redundancy analysis to assess the relationship between MBFGs and environmental data. It was registered 101 taxa distributed in eight taxonomic categories and was grouped into 5 MBFGs (III, IV, V, VI and VII), with Chlorophyceae (31 taxa) and Cyanobacteria (27 taxas) with the higher number of taxa. Furthermore, there was a dominance of Cyanobacteria in the total biovolume, which form blooms (MBFGs III and VII) during the periods of falling and low water in lake, influenced mainly by the reduction in the availability of light and an increase in temperature. In another scenario, the dominance of MBFGs V and VI occurred during periods of rising and high water with association with carbon compounds, rainfall, SRP and NO2. Thus, our results demonstrate that the availability of light, the concentration of nutrients and temperature were the most important variables for the morphofunctional structuring of phytoplankton in aquatic system.
%@language en
%3 Souza2022_Article_UnderstandingTheEffectsOfEnvir.pdf