Use of phytoplankton functional groups as a model of spatial and temporal patterns in reservoirs: a case study in a reservoir of central Brazil

Rodrigues, Luzia Cleide; Pivato, Bianca Mathias; Vieira, Ludgero Cardoso Galli; Bovo-Scomparin, Vânia Mara; Bortolini, Jascieli Carla; Pineda, Alfonso; Train, Sueli

doi:10.1007/s10750-017-3289-x

Cited by 47 publications

(28 citation statements)

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“…Additionally, the dominance of few species, with particular concern for the dominance of potentially harmful cyanobacteria, often occurs in semi-arid regions under drought conditions (Bouvy et al, 1999;Brasil et al, 2016). The phytoplankton classification into functional groups rather than only based on taxonomic affiliations has been often used as tool for environmental characterization of reservoirs (Silva et al, 2015;Rangel et al, 2016;Rodrigues et al, 2017). In the present study we have use Reynolds's functional groups (FGs), when the species with similar sensibilities, tolerances and ecologies affinities are placed together, being each FG selected by a set of environmental variables (habitat template) (Reynolds et al, 2002 reviewed by Padisák et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Assessing temporal and spatial variability of phytoplankton composition in a large reservoir in the Brazilian northeastern region under intense drought conditions

et al. 2017

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The present study was carried out in Castanhão Reservoir, a large aquatic system in the Brazilian semi-arid region that serves multiples uses as water drinking supply and intensive fish-cage aquaculture site. In order to understand the effects of environmental conditions on the spatial and temporal variability of the phytoplankton functional groups (FG) and the main 'characterizing taxa', sub-superficial water samples were collected from March 2012 to August 2013, a period distinguished by the continuous drop in reservoir volume due to rainfall shortage. Eighteen functional groups and 102 total phytoplankton taxa were found in the Castanhão reservoir during the study. No significant differences were observed relative to spatial variation of total phytoplankton composition throughout the reservoir (PERMANOVA, P>0.05). On the other hand, according to cluster analysis results, three temporal phases have been identified (Similarity Profile, P<0.05), based on 102 phytoplankton taxa. The 'characterizing taxa' was found using the Similarity Percentage procedure (cut-off 90%), being thus defined as those taxa that contributed the most to the similarity within each temporal phase. Nineteen 'characterizing taxa' described the Castanhão reservoir, with predominance of those typical of mixing and turbidity conditions. Cyanobacteria dominated through the three temporal phases. According to the redundancy analysis, nutrient availability and water transparency were found to influence the phytoplankton temporal dynamics. The phase I (rainy season) was most represented by Planktolyngbya minor/Pl. limnetica (FG=S1), which reached best performance under strongly decreased phosphate-P concentrations and low water transparency. In phase II (dry season), Pseudanabaena sp.1 (FG=?) outcompeted other cyanobacteria probably due the increase in water transparency and decrease in ammonium-N. Finally, in phase III (rainy season) the decrease of water transparency triggered a recovery of shade-adapted cyanobacteria, but at this time mostly represented by Pseudanabaena limnetica (FG=S1). Phase III was also distinctive from the other ones by the highest Nitrate-N and phosphate-P concentrations related to thermocline disruption, which favored an increase in total phytoplankton biomass recorded by the augment of green algae density (FGs=X1, J and F). We concluded that the temporal dynamics of phytoplankton composition was associated to environmental changes in Castanhão Reservoir from 2012 to 2013, which were driven by seasonal climate variation from region (rainy/dry seasons), as well as, by the reduction in reservoir volume that resulted in the disruption of the thermocline, water mixing and an increase in inorganic P and N.

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Section: Introductionmentioning

confidence: 99%

Assessing temporal and spatial variability of phytoplankton composition in a large reservoir in the Brazilian northeastern region under intense drought conditions

et al. 2017

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“…In the rainy period, for example, the contribution of the spatial factor suggests that mass effects may doi:10.1111/aec.12852 © 2019 Ecological Society of Australia have a strong influence on the structure of the community, since in this period dispersal stochasticity may be mediated by greater connectivity among environments (Heinoet al 2015;Devercelli et al 2016;Bortolini et al 2017;Rodrigues et al 2018). On the other hand, in the dry period lakes become more isolated from the main river channel and biological and physical characteristics can act with different intensities in each floodplain creating habitats with different characteristics (Bozelli et al 2015;Devercelli et al 2016).…”

Section: Discussionmentioning

confidence: 99%

“…Biological communities are shaped by various drivers, and understanding the processes that determine their distribution represents a major interest to ecologists (Datry et al 2016). Considering that organisms may present different responses to the environment (Litchman et al 2012), the use of deconstructive approaches, such as functional classification models (Reynolds et al 2002;Padis ak et al 2009;Kruk et al 2010;Chen et al 2015), can be an important tool for understanding the effects of environmental heterogeneity on phytoplankton structure, in addition to providing important information for monitoring aquatic systems (Abonyi et al 2012;Bortolini et al 2014;Rodrigues et al 2018).…”

Section: Introductionmentioning

confidence: 99%

A functional deconstructive approach to mixotrophic phytoplankton responds better to local, regional and biogeographic predictors than species

et al. 2019

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The use of deconstructive approaches, such as functional classification models, can be an important tool for understanding aquatic systems. This study aimed to evaluate the distribution and community structure of mixotrophic flagellates in lakes of four large Brazilian floodplain systems, those of Amazon River, Araguaia River, Pantanal and upper Paraná River, in contrasting hydrological periods. A partial redundancy analysis (pRDA) was used to estimate the relative roles of environmental, spatial and biogeographic factors on both the entire community and a deconstructive approach using Reynolds' mixotrophic flagellate functional groups (RFGs). High environmental variability was found between the rainy and dry periods, mostly for the Amazon floodplain system. We identified 135 taxa and seven RFGs of mixotrophic flagellates: E, Lo, Q, W1, W2, Ws and Y. A permanova evidenced that biomass of mixotrophic flagellate RFGs reflected differences among floodplains and between hydrological periods. Our results showed that the use of RFGs better summarises the mixotrophic phytoplankton metacommunity structure when compared to the use of the entire community. The pRDA showed that explanatory matrices explained up to 37% of variation in the community. Environmental, spatial and biogeographic factors were important to explain the structure of the mixotrophic flagellates; however, the importance of the different components seemed to depend on the hydrological period and the traits of each RFG.

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“…5). The hydrological regime mainly contributed to the low biomass and high similarity of the phytoplankton composition during the high flow period, due to the high connectivity and extensive dispersal stochasticity (Rodrigues et al, 2018). On the contrary, there was a relative high level of total biomass during the dry season (Fig.…”

Section: Response Of Phytoplankton Community To Multiple Stressorsmentioning

confidence: 99%

Riverine phytoplankton functional groups response to multiple stressors variously depending on hydrological periods

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Makarevičiūtė

et al. 2019

Ecological Indicators

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Rivers and related freshwater ecosystems are facing increasing natural disturbance and anthropogenic stressors. Understanding the key ecological processes that govern the riverine biota in aquatic ecosystems under multiple pressures has crucial importance. However, there is still insufficient knowledge in quantifying of stressors interactions. Moreover, the understanding of the responses of riverine phytoplankton to multiple stressors is still scarce from catchment aspect. As an interdisciplinary study, the catchment hydrological processes were linked to ecological responses in this study, and we chose phytoplankton functional groups (PFGs) instead of taxonomic classifications of algae to examine their responses to land-use pattern (L), hydrological regime (H), and physicochemical condition (P) across two contrasting hydrological periods (dry, wet). The traits-based phytoplankton functional groups are highly suggested as robust bio-indicators for better understanding the current ecological status. The hydrological regime was described by a matrix indices of hydrological alteration based on the outputs of a well-established ecohydrological model (SWAT). The results from variation partitioning analysis showed that P and H dominate during the dry period and P in high flows. Structural equation models (SEM) showed that the skewness of 7 days discharge emerged as a key driver of H, and had always an indirect effect on functional group TB (benthic diatoms) during both hydrological periods. The functional group M (mainly composed by Microcystis) has directly related to phosphorous in both periods, while indirectly to L of urban area in high flow period, and water bodies in low flow period. This study emphasized that climate change and anthropogenic activities such as altering flow regime and land-use pattern affect directly or indirectly riverine phytoplankton via physicochemical conditions. In addition, our findings

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Use of phytoplankton functional groups as a model of spatial and temporal patterns in reservoirs: a case study in a reservoir of central Brazil

Cited by 47 publications

References 33 publications

Assessing temporal and spatial variability of phytoplankton composition in a large reservoir in the Brazilian northeastern region under intense drought conditions

Assessing temporal and spatial variability of phytoplankton composition in a large reservoir in the Brazilian northeastern region under intense drought conditions

A functional deconstructive approach to mixotrophic phytoplankton responds better to local, regional and biogeographic predictors than species

Riverine phytoplankton functional groups response to multiple stressors variously depending on hydrological periods

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