ABSTRACT We explored systematic patterns in predictability of phytoplankton species from 83 lakes... more ABSTRACT We explored systematic patterns in predictability of phytoplankton species from 83 lakes over a gradient ranging from subpolar to tropical regions in South America. We estimated the explained variance (proxy of predictability) of the presence and biomass (estimated as biovolume) of species using multiple regressions from commonly measured environmental variables such as nutrient levels, light, mixing depth, temperature, and zooplankton biomass. Both the presence and biomass of species occurring at least in 10 lakes were quite well predicted from the environmental variables, with average values of 35% and 58%, respectively. Predictability was not systematically related to phylogenetic affiliation or particular functional groups as defined by morphology. However, biomass predictability decreased with increasing occurrence, and improved with larger species size (maximum linear dimension). Species that were predictable in terms of biomass (R2 $ 0.5, p # 0.05) had, on average, a larger volume, and were relatively more frequent in lakes from warmer regions, with high water temperature, low chlorophyll a, low nutrient concentrations, and low total zooplankton biomass. Although we cannot diagnose the mechanisms involved, our finding that the number of predictable species increases towards warmer regions resembles situations where competition for nutrients and grazing are likely to be less severe, and may imply that in a future warmer world phytoplankton will be easier to predict.
The application of trait-based approaches has become a widely applied tool to analyse community a... more The application of trait-based approaches has become a widely applied tool to analyse community assembly processes and dynamics in phytoplankton communities. Its advantages include summarizing information of many species without losing essentials of the main driving processes. Here, we used trait-based approaches to study phytoplankton temporal succession in a subtropical reservoir. We applied a combined approach including morphological traits (i.e. volume, surface) and functional clustering of species (morphology-based functional groups (MBFG) and Reynolds' groups) and related the clustering of species with the environment. We found that this reservoir is characterized by a low richness and a bimodal distribution of phytoplankton biomass. Taxonomic and functional classifications were coincident, and the dominant species and groups biomasses were explained by the same group of variables. For instance, group X 2, MBFG V and Carteria sp. biomasses were explained by: pH, Secchi dis...
Proceedings of the Royal Society B: Biological Sciences, 2011
The mechanisms that drive species coexistence and community dynamics have long puzzled ecologists... more The mechanisms that drive species coexistence and community dynamics have long puzzled ecologists. Here, we explain species coexistence, size structure and diversity patterns in a phytoplankton community using a combination of four fundamental factors: organism traits, size-based constraints, hydrology and species competition. Using a 'microscopic' Lotka-Volterra competition (MLVC) model (i.e. with explicit recipes to compute its parameters), we provide a mechanistic explanation of species coexistence along a niche axis (i.e. organismic volume). We based our model on empirically measured quantities, minimal ecological assumptions and stochastic processes. In nature, we found aggregated patterns of species biovolume (i.e. clumps) along the volume axis and a peak in species richness. Both patterns were reproduced by the MLVC model. Observed clumps corresponded to niche zones (volumes) where species fitness was highest, or where fitness was equal among competing species. The latter implies the action of equalizing processes, which would suggest emergent neutrality as a plausible mechanism to explain community patterns.
ABSTRACT We explored systematic patterns in predictability of phytoplankton species from 83 lakes... more ABSTRACT We explored systematic patterns in predictability of phytoplankton species from 83 lakes over a gradient ranging from subpolar to tropical regions in South America. We estimated the explained variance (proxy of predictability) of the presence and biomass (estimated as biovolume) of species using multiple regressions from commonly measured environmental variables such as nutrient levels, light, mixing depth, temperature, and zooplankton biomass. Both the presence and biomass of species occurring at least in 10 lakes were quite well predicted from the environmental variables, with average values of 35% and 58%, respectively. Predictability was not systematically related to phylogenetic affiliation or particular functional groups as defined by morphology. However, biomass predictability decreased with increasing occurrence, and improved with larger species size (maximum linear dimension). Species that were predictable in terms of biomass (R2 $ 0.5, p # 0.05) had, on average, a larger volume, and were relatively more frequent in lakes from warmer regions, with high water temperature, low chlorophyll a, low nutrient concentrations, and low total zooplankton biomass. Although we cannot diagnose the mechanisms involved, our finding that the number of predictable species increases towards warmer regions resembles situations where competition for nutrients and grazing are likely to be less severe, and may imply that in a future warmer world phytoplankton will be easier to predict.
The application of trait-based approaches has become a widely applied tool to analyse community a... more The application of trait-based approaches has become a widely applied tool to analyse community assembly processes and dynamics in phytoplankton communities. Its advantages include summarizing information of many species without losing essentials of the main driving processes. Here, we used trait-based approaches to study phytoplankton temporal succession in a subtropical reservoir. We applied a combined approach including morphological traits (i.e. volume, surface) and functional clustering of species (morphology-based functional groups (MBFG) and Reynolds' groups) and related the clustering of species with the environment. We found that this reservoir is characterized by a low richness and a bimodal distribution of phytoplankton biomass. Taxonomic and functional classifications were coincident, and the dominant species and groups biomasses were explained by the same group of variables. For instance, group X 2, MBFG V and Carteria sp. biomasses were explained by: pH, Secchi dis...
Proceedings of the Royal Society B: Biological Sciences, 2011
The mechanisms that drive species coexistence and community dynamics have long puzzled ecologists... more The mechanisms that drive species coexistence and community dynamics have long puzzled ecologists. Here, we explain species coexistence, size structure and diversity patterns in a phytoplankton community using a combination of four fundamental factors: organism traits, size-based constraints, hydrology and species competition. Using a 'microscopic' Lotka-Volterra competition (MLVC) model (i.e. with explicit recipes to compute its parameters), we provide a mechanistic explanation of species coexistence along a niche axis (i.e. organismic volume). We based our model on empirically measured quantities, minimal ecological assumptions and stochastic processes. In nature, we found aggregated patterns of species biovolume (i.e. clumps) along the volume axis and a peak in species richness. Both patterns were reproduced by the MLVC model. Observed clumps corresponded to niche zones (volumes) where species fitness was highest, or where fitness was equal among competing species. The latter implies the action of equalizing processes, which would suggest emergent neutrality as a plausible mechanism to explain community patterns.
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