Observations on the dynamics and fate of dissolved organic phosphorus in lake water and a new model of eplimnetic P cycling
Bibliographic record
Abstract
Phosphorus (P) in lake water is commonly partitioned into particulate P and dissolved P by membrane filtration, and dissolved P is then fractionated into soluble reactive P (SRP, reactive with molybdate) and dissolved unreactive or organic P (DOP). Much of what is known about DOP is derived from radiotracer studies using gel chromatography, and summarized by a kinetic model (Lean, Science 179:678–680, 1973a ; Lean, J Fish Res Board Can 30:1525–1536, 1973b ). Since this work, several relevant discoveries have been made on the role of enzymes, viruses and zooplankton in regenerating dissolved P, and the role of filtration damage in generating dissolved P in filtrates. Herein we present the results of new radiotracer experiments on the fate of DOP in lake water filtrates, consistent with the hypothesis that some of the high molecular weight organic P breaks down spontaneously to smaller molecules, which in turn break down to PO 4 3− . We use inhibitors, including competitive inhibitors of phosphatases and a commercial product (RNA-later ® ) to support the hypothesis that the larger molecules include nucleic acids, and that the smaller molecules are substrates for alkaline phosphatase. We also find that colloidal P (i.e., P > 5000 MW according to gel filtration) includes some virus-sized material that can be collected on 0.02 or 0.03 µm filters. Finally, we provide a new model of the cycling of epilimnetic P that is consistent with these and earlier observations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 |
| 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".