Nitrogen fixation may not balance the nitrogen pool in lakes over timescales relevant to eutrophication management
Bibliographic record
Abstract
We explored multiyear linear trends in nutrient concentrations, nitrogen (N) : phosphorus (P) ratio, and phytoplankton biomass within the 37‐yr, whole‐ecosystem nutrient enrichment experiment in Lake 227 of the Experimental Lakes Area, Canada. Based on experimental conditions, data were divided into subsets, which included (1) the period from 1969 to 1989 when the lake was fertilized with both N and P; (2) the period from 1990 to 2005 when the lake was fertilized with P alone; and (3) the period from 1997 to 2005 when the lake was fertilized with P alone and which also postdated a food web manipulation experiment, which left the lake without fish. After N fertilization was halted in 1990, total N concentrations decreased, which resulted in a decrease in the ratio of total N to total P and suggested increasing N deficiency. Chlorophyll ά concentration decreased over this same period. Phytoplankton biomass (mg m −3 ) was highly variable during the food web manipulation experiment but exhibited a clear decrease from 1997 to 2005, which was the longest period of monotonic change in phytoplankton biomass over the entire 37‐yr study. Collectively, these results suggest that Lake 227 has become increasingly N‐limited since N fertilization was halted and indicate that N fixation by cyanobacteria was not sufficient to offset the decrease in external N inputs to Lake 227. Furthermore, phytoplankton biomass decreased in response to decreased N availability, suggesting that the degree of eutrophication can be controlled by managing N inputs concurrently with P.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 source (direct Gemma or distilled Codex), 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".