The influence of environmental variables on spatial and temporal phytoplankton dissimilarity in a large shallow subtropical lake (Lake Mangueira, southern Brazil)
Abstract:Aim:The uneven distribution of organisms in aquatic ecosystems is generally attributed to environmental heterogeneity in both space and time, reflecting the occurrence of appropriate environmental conditions and the availability of resources to biological communities. The aim of this study was to understand how the dissimilarity of the phytoplankton community in a large subtropical shallow lake is related to environmental dissimilarities. Methods: Biotic and environmental data were gathered at 19 sites along t… Show more
“…The homogeneity in the phytoplankton distribution in this study could be attributed to the similarities in the nitrate concentrations in the sampling stations. This is confirmed by the statement according to Halterman and Toetz (1984), Tilman et al (1986), and Crossetti et al (2014) that dissimilarities in nitrate availability may lead to differences in phytoplankton structure, since half-saturation concentrations for nitrate uptake may vary among phytoplankton species.…”
Section: Discussionsupporting
confidence: 70%
“…Similarly, Nowrouzi and Valavi (2011) observed positive correlation of nutrient (especially nitrate) with phytoplankton abundance in Lake Kalfter. Crossetti et al (2014) reported that the combination of environmental variables that best correlates with the dissimilarities observed in phytoplankton distribution in Lake Mangueira, southern Brazil were pH, turbidity, and nitrate. Similarly, nutrients, pH, conductivity andwater temperature were the set of environmental variables that best explained variationsin phytoplankton functional groups in Lake Mangueira in a six year data set (Crossetti et al, 2013).…”
“…The homogeneity in the phytoplankton distribution in this study could be attributed to the similarities in the nitrate concentrations in the sampling stations. This is confirmed by the statement according to Halterman and Toetz (1984), Tilman et al (1986), and Crossetti et al (2014) that dissimilarities in nitrate availability may lead to differences in phytoplankton structure, since half-saturation concentrations for nitrate uptake may vary among phytoplankton species.…”
Section: Discussionsupporting
confidence: 70%
“…Similarly, Nowrouzi and Valavi (2011) observed positive correlation of nutrient (especially nitrate) with phytoplankton abundance in Lake Kalfter. Crossetti et al (2014) reported that the combination of environmental variables that best correlates with the dissimilarities observed in phytoplankton distribution in Lake Mangueira, southern Brazil were pH, turbidity, and nitrate. Similarly, nutrients, pH, conductivity andwater temperature were the set of environmental variables that best explained variationsin phytoplankton functional groups in Lake Mangueira in a six year data set (Crossetti et al, 2013).…”
“…Approaches based on species traits have shown which groups of species have distinct responses according to their biological traits (Heino et al ; Tonkin et al ; Campos et al ). Reynolds functional groups (RFGs, supported by Kruk et al ), for example, are sensitive to environmental variation, and in this sense, trait‐based approaches have been increasingly applied to explain and predict the response of phytoplankton species to environmental conditions in aquatic systems (Nabout et al ; Crossetii et al ; Rangel et al ; Bortolini et al ). These approaches can enable the detection of patterns and underlying processes, which might not be detectable when studying the structure of the entire community (Stenger‐Kovács et al ; Vilmi et al ).…”
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.
“…(light and nutrients), in spatially heterogeneous environments have been related to phytoplankton functional diversity (Caputo et al, 2008;Rychtecký & Znachor, 2011;Crossetti et al, 2014). In this sense, the present study aimed at evaluating the influence of spatial and temporal heterogeneity on the functional structure of the phytoplankton community in a large subtropical shallow lake.…”
Aim Studies on biological communities that take into account only the species composition and abundances (or biomass) and their relative contributions, most of the time, do not reflect their ecological functions, especially considering the wide spatial and temporal variation of large shallow lakes. This paper aimed at evaluating the influence of environmental spatial and temporal heterogeneity on the functional structure of phytoplankton in a subtropical large shallow lake. Methods Seasonal samplings were carried out in 2010 and 2011, in 19 sampling sites distributed along the entire length (90 km) and width (3-10 km) of Lake Mangueira, a large (820 km2 ) and shallow lake (zmean = 2.6 m), comprising the littoral and pelagic zones of the north, central and southern regions. Abiotic variables and phytoplankton functional traits (volume, maximum linear dimension, life forms) and functional groups were analyzed as measures of functional structure. Results The results showed that there was no spatial organization of phytoplankton functional traits during the study. Colonial non-flagellated organisms, organisms with cellular volume between 103 and 104 μm3 and greater than 104 μm3, and with maximum linear dimension between 21 and 50 μm prevailed in all zones and regions. Phytoplankton functional groups and traits responded to resource variation, especially increasing their variety and contribution during spring and summer periods. Conclusions The functional structure of the phytoplankton community in Lake Mangueira, here accessed by functional traits and RFGs, was more conditioned by its environmental temporal variability rather than by the spatial variation, indicating that the resources and life conditions seasonal variation strongly influence the phytoplankton in this ecosystem.
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