Evidence for phosphorus, nitrogen, and iron colimitation of phytoplankton communities in Lake Erie
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Three nutrient enrichment experiments involving the addition and removal of iron (Fe) alone, as well as in combination with phosphorus (P) and/or nitrogen (N), were conducted in the offshore and nearshore waters of the eastern basin of Lake Erie. Lake Erie phytoplankton are at times colimited by P, N, and Fe. This was most clearly demonstrated in the offshore, strongly stratified waters, where the Fe concentration was below detection (DL = 2.0 nmol L −1 ), and nutrient limitation indicators (APA, P debt, C: P, N: P, N debt, and C: N) indicated strong P and moderate N limitation. Enrichment with Fe alone did not result in a significant increase in phytoplankton biomass, but the combined addition of Fe, P, and N yielded greater biomass increases than the addition of P and N alone. Phosphorus and Fe were both required to stimulate biomass increases. Nutrient limitation indicators and dissolved nutrient measurements showed that P and Fe additions facilitated the uptake of nitrate (NO 3 ‐ ), which is the most abundant source of N because of the low ammonium (NH 4 + ) concentrations in Lake Erie. Our results support a colimitation hypothesis wherein the addition of Fe reduces N limitation by allowing the phytoplankton communities to use NO 3 − , take up more P, and become more strongly P limited. Phytoplankton communities of the eastern basin of Lake Erie and numerous other lakes experience colimitation by P, N, and Fe during the summer period of thermal stratification.
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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 it