The effects of <i>Daphnia</i> on nutrient stoichiometry and filamentous cyanobacteria: a mesocosm experiment in a eutrophic lake
Bibliographic record
Abstract
1. Stoichiometric theory predicts that the nitrogen : phosphorus (N : P) ratio of recycled nutrients should increase when P‐rich zooplankton such as Daphnia become dominant. We used an enclosure study to test the hypothesis that an increased biomass of Daphnia will increase the relative availability of N versus P sufficiently to decrease the abundance of filamentous cyanobacteria. The experiment was conducted in artificially enriched Lake 227 (L227) in the Experimental Lakes Area (ELA), north‐western Ontario, Canada. Previous studies in L227 have shown that the dominance of filamentous, N‐fixing cyanobacteria is strongly affected by changes in the relative loading rates of N and P. 2. We used a 2 × 2 factorial design with the addition or absence of D. pulicaria and high or low relative loading rates of N and P (+NH 4 , –NH 4 ) in small enclosures as treatment variables. If Daphnia can strongly affect filamentous cyanobacteria by altering N and P availability, these impacts should be greatest with low external N : P loading rates. The phytoplankton community of L227 was predominantly composed of filamentous Aphanizomenon spp. at the start of the experiment. 3. Daphnia strongly reduced filamentous cyanobacterial density in all enclosures to which they were added. The addition of NH 4 had only a small impact on algal community composition. Hence, we conclude that Daphnia did not cause reductions in cyanobacteria by altering the N : P ratio of available nutrients. 4. Despite the lack of evidence that Daphnia affected filamentous cyanobacteria by altering the relative availability of N and P, we found changes in nutrient cycling consistent with other aspects of stoichiometric theory. In the presence of Daphnia , total P in the water column decreased because of an increase in P sedimentation. In contrast to P, a decrease in suspended particulate N was offset by an increase in dissolved N (especially NH 4 ). Hence, dissolved and total N : P ratios in the water column increased with Daphnia as a result of differences in the fate of suspended particulate N versus P. There was minimal accumulation and storage of P in Daphnia biomass in the enclosures. 5. Our experiment demonstrated that Daphnia can strongly limit filamentous cyanobacterial abundance and affect the biogeochemical cycling of nutrients. In our study, changes in nutrient cycling were apparently insufficient to cause the changes in phytoplankton community composition that we observed. Daphnia therefore limited filamentous cyanobacteria by other mechanisms.
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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 | 0.000 |
| 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".