Phosphorus dynamics in an ice-covered lake: Insights from geochemical gradients in water and sediments
Bibliographic record
Abstract
Understanding the role of seasonally ice-covered lakes in biogeochemical cycling is important for predicting the effects of changing winter conditions. However, little is known about phosphorus (P) cycling and the mechanisms of internal P release in seasonally ice-covered lakes. We investigated under-ice P cycling in a large and temperate lake composed of several basins with significantly different water depths. We used a multifaceted approach, combining analyses of P and total iron (Fe) distributions in sediments, pore water, and the water column. During the winter period, steep gradients of redox-sensitive parameters (i.e., O2 and Eh) formed at the sediment-water interface (SWI) due to minimal water movement and water column hypoxia. P diffusive fluxes during winter are substantial (0.2–4.8 mg P/m2/day). Short-term P release in shallow basins is strongly influenced by Fe reduction. In contrast, decoupling of Fe from P in deep basins suggests that hypoxia does not play a major role in short-term P mobilization. The differences in short-term P release mechanisms can be interpreted in terms of basin depth, stability of thermal stratification and time of water mixing. This ultimately influences the behavior of Fe and P, as well as their speciation and concentration in the sediment and water column. The deep basins in LOW contained higher total phosphorus (TP) and total iron (Fe) in sediments and soluble reactive phosphorus (SRP) in deep water compared to shallow basins. In surface sediments, P bound to the redox-sensitive P binding form (BD-P) is the diagenetically reactive P phase, emphasizing strong coupling with ferric Fe. In contrast, calcium carbonate-bound P in surface sediments indicates diagenetic sequestration of P with sediment burial. Overall, this study provides evidence that P cycling remains active in winter, and an understanding of its contribution to the overall ecosystem process is needed to predict how lake ecosystems will behave under climate change.
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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".