Rapid adaptation of harmful cyanobacteria to rising CO2.
Ontology highlight
ABSTRACT:
SUBMITTER: Sandrini G
PROVIDER: S-EPMC4995953 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background and Aims:Studies have indicated that plant stomatal conductance (gs) decreases in response to elevated atmospheric CO2, a phenomenon of significance for the global hydrological cycle. However, gs increases across certain CO2 ranges have been predicted by optimization models. The aim of this work was to demonstrate that under certain environmental conditions, gs can increase in response to elevated CO2. Methods:Using (1) an extensive, up-to-date synthesis of gs responses in free air CO2 enrichment (FACE)experiments, (2) in situ measurements across four biomes showing dynamic gs responses to a CO2 rise of ~50 ppm (characterizing the change in this greenhouse gas over the past three decades) and (3) a photosynthesis-stomatal conductance model, it is demonstrated that gs can in some cases increase in response to increasing atmospheric CO2. Key Results:Field observations are corroborated by an extensive synthesis of gs responses in FACE experiments showing that 11.8 % of gs responses under experimentally elevated CO2 are positive. They are further supported by a strong data-model fit (r2 = 0.607) using a stomatal optimization model applied to the field gs dataset. A parameter space identified in the Farquhar-Ball-Berry photosynthesis-stomatal conductance model confirms field observations of increasing gs under elevated CO2 in hot dry conditions. Contrary to the general assumption, positive gs responses to elevated CO2, although relatively rare, are a feature of woody taxa adapted to warm, low-humidity conditions, and this response is also demonstrated in global simulations using the Community Land Model (CLM4). Conclusions:The results contradict the over-simplistic notion that global vegetation always responds with decreasing gs to elevated CO2, a finding that has important implications for predicting future vegetation feedbacks on the hydrological cycle at the regional level.
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Project description:Cyanobacteria are photosynthetic bacteria with a unique CO2 concentrating mechanism (CCM), enhancing carbon fixation. Understanding the CCM requires a systems level perspective of how molecular components work together to enhance CO2 fixation. We present a mathematical model of the cyanobacterial CCM, giving the parameter regime (expression levels, catalytic rates, permeability of carboxysome shell) for efficient carbon fixation. Efficiency requires saturating the RuBisCO reaction, staying below saturation for carbonic anhydrase, and avoiding wasteful oxygenation reactions. We find selectivity at the carboxysome shell is not necessary; there is an optimal non-specific carboxysome shell permeability. We compare the efficacy of facilitated CO2 uptake, CO2 scavenging, and HCO3- transport with varying external pH. At the optimal carboxysome permeability, contributions from CO2 scavenging at the cell membrane are small. We examine the cumulative benefits of CCM spatial organization strategies: enzyme co-localization and compartmentalization.
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Project description:Lake restoration practices based on reducing fish predation and promoting the dominance of large-bodied Daphnia grazers (i.e., biomanipulation) have been the focus of much debate due to inconsistent success in suppressing harmful cyanobacterial blooms. While most studies have explored effects of large-bodied Daphnia on cyanobacterial growth at the community level and/or on few dominant species, predictions of such restoration practices demand further understanding on taxa-specific responses in diverse cyanobacterial communities. In order to address these questions, we conducted three grazing experiments during summer in a eutrophic lake where the natural phytoplankton community was exposed to an increasing gradient in biomass of the large-bodied Daphnia magna. This allowed evaluating taxa-specific responses of cyanobacteria to Daphnia grazing throughout the growing season in a desired biomanipulation scenario with limited fish predation. Total cyanobacterial and phytoplankton biomasses responded negatively to Daphnia grazing both in early and late summer, regardless of different cyanobacterial densities. Large-bodied Daphnia were capable of suppressing the abundance of Aphanizomenon, Dolichospermum, Microcystis and Planktothrix bloom-forming cyanobacteria. However, the growth of the filamentous Dolichospermum crassum was positively affected by grazing during a period when this cyanobacterium dominated the community. The eutrophic lake was subjected to biomanipulation since 2005 and nineteen years of lake monitoring data (1996-2014) revealed that reducing fish predation increased the mean abundance (50%) and body-size (20%) of Daphnia, as well as suppressed the total amount of nutrients and the growth of the dominant cyanobacterial taxa, Microcystis and Planktothrix. Altogether our results suggest that lake restoration practices solely based on grazer control by large-bodied Daphnia can be effective, but may not be sufficient to control the overgrowth of all cyanobacterial diversity. Although controlling harmful cyanobacterial blooms should preferably include other measures, such as nutrient reductions, our experimental assessment of taxa-specific cyanobacterial responses to large-bodied Daphnia and long-term monitoring data highlights the potential of such biomanipulations to enhance the ecological and societal value of eutrophic water bodies.
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Project description:Harmful cyanobacterial blooms in freshwater ecosystems are closely associated with changes in the composition of symbiotic microbiomes, water quality, and environmental factors. In this work, the relationship between two representative harmful cyanobacterial species (Anabaena sp. and Microcystis sp.) and their associated bacterial assemblages were investigated using a 16S rRNA-based meta-amplicon sequencing analysis during a large-scale cultivation of cyanobacteria under different light conditions with limited wavelength ranges (natural light, blue-filtered light, green-filtered light, and dark conditions). During the cultivation periods, the growth pattern of cyanobacteria and bacterial composition of the phycosphere considerably varied in relation to light restrictions. Unlike other conditions, the cyanobacterial species exhibited significant growth during the cultivation period under both the natural and the blue light conditions. Analyses of the nitrogenous substances revealed that nitrogen assimilation by nitrate reductase for the growth of cyanobacteria occurred primarily under natural light conditions, whereas nitrogenase in symbiotic bacteria could also be activated under blue light conditions. Sphingobium sp., associated with nitrogen assimilation via nitrogenase, was particularly dominant when the cell density of Microcystis sp. increased under the blue light conditions. Thus, cyanobacteria could have symbiotic relationships with ammonium-assimilating bacteria under light-limited conditions, which aids the growth of cyanobacteria.
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Project description:Harmful algal blooms threaten the water quality of many eutrophic and hypertrophic lakes and cause severe ecological and economic damage worldwide. Dense blooms often deplete the dissolved CO2 concentration and raise pH. Yet, quantitative prediction of the feedbacks between phytoplankton growth, CO2 drawdown and the inorganic carbon chemistry of aquatic ecosystems has received surprisingly little attention. Here, we develop a mathematical model to predict dynamic changes in dissolved inorganic carbon (DIC), pH and alkalinity during phytoplankton bloom development. We tested the model in chemostat experiments with the freshwater cyanobacterium Microcystis aeruginosa at different CO2 levels. The experiments showed that dense blooms sequestered large amounts of atmospheric CO2, not only by their own biomass production but also by inducing a high pH and alkalinity that enhanced the capacity for DIC storage in the system. We used the model to explore how phytoplankton blooms of eutrophic waters will respond to rising CO2 levels. The model predicts that (1) dense phytoplankton blooms in low- and moderately alkaline waters can deplete the dissolved CO2 concentration to limiting levels and raise the pH over a relatively wide range of atmospheric CO2 conditions, (2) rising atmospheric CO2 levels will enhance phytoplankton blooms in low- and moderately alkaline waters with high nutrient loads, and (3) above some threshold, rising atmospheric CO2 will alleviate phytoplankton blooms from carbon limitation, resulting in less intense CO2 depletion and a lesser increase in pH. Sensitivity analysis indicated that the model predictions were qualitatively robust. Quantitatively, the predictions were sensitive to variation in lake depth, DIC input and CO2 gas transfer across the air-water interface, but relatively robust to variation in the carbon uptake mechanisms of phytoplankton. In total, these findings warn that rising CO2 levels may result in a marked intensification of phytoplankton blooms in eutrophic and hypertrophic waters.
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