Comparative effects of ammonium, nitrate and urea on growth and photosynthetic efficiency of three bloom‐forming cyanobacteria
Bibliographic record
Abstract
Abstract Urea‐based fertilisers have grown in popularity over the past half‐century and are now the dominant nitrogen (N) form applied to agricultural landscapes. The widespread use of urea fertilisers has favoured its export to local waterways, and urea pollution may be contributing to the propagation and maintenance of cyanobacteria harmful algal blooms in fresh waters. The relative success of cyanobacteria in response to urea and inorganic N additions was studied to understand whether the recent changes in the magnitude and composition of N loading have created a scenario that now favours the dominance of cyanobacteria in fresh waters. Growth and photosynthetic efficiency of three bloom‐forming freshwater cyanobacteria ( Microcystis , Dolichospermum and Synechococcus ) grown on nitrate ( ), ammonium ( ) and urea (CO(NH 2 ) 2 ) as the sole N form were monitored. We hypothesised that N substrates that require the lowest energetic investment or offer the highest energetic return would favour optimal growth and photosynthetic performance. We predicted that urea would result in higher cellular growth and pigment production relative to or , as urea provides twice the amount N and an additional carbon (C) source making it more energetically efficient. Cyanobacteria biomass was not significantly enhanced on urea relative to inorganic N forms. Growth on urea was matched by for all species, whereas growth on was halved compared urea or . However, cyanobacteria cells had higher pigment concentrations when grown on urea relative to inorganic N sources. These findings suggest that the additional nutrient building blocks supplied from the hydrolysis of urea were not directed towards active growth, but rather accumulated in secondary pools to increase production of N‐rich compounds, such as pigments. Although urea did not influence cyanobacteria quantity “(i.e. biomass)” compared to inorganic N sources, it produced higher “quality” cells by enhancing pigment synthesis and potentially giving cyanobacteria a competitive advantage in light‐limiting conditions. Furthermore, when supplied in excess, cyanobacteria rapidly consumed urea in excess of their biosynthetic requirements suggesting a form of urea “gluttony.” These results demonstrate the importance of N speciation on cyanobacteria physiological responses and reinforce the emerging links between urea and cyanobacteria harmful algal blooms in inland waters.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".