Historic low‐level phosphorus enrichment in the Great Lakes inferred from biogenic silica accumulation in sediments
Bibliographic record
Abstract
Sedimentary biogenic silica (BSi) accumulation was used in conjunction with a hypothetical model of BSi accumulation to show that BSi is a sensitive proxy for low‐level phosphorus enrichment in the Great Lakes. We hypothesize that historic nutrient‐driven changes in diatom production altered silica biogeochemistry and induced biologically mediated silica depletion (BMSD) and that a record of the underlying mechanism, enhanced diatom production and BSi sedimentation stimulated by anthropogenic phosphorus enrichment, is preserved in the sediment record. Paleolimnological results support three hypotheses based on this model. First, BSi accumulation increased in Lake Superior and Lake Huron at total phosphorus (TP) concentrations (4 and 5 µg TP L −1 or 0.13 and 0.16 µmol L −1 , respectively) too small to induce BMSD and with changes in TP concentration too small to be detected by routine water‐column sampling. Second, a peak in BSi accumulation in Lake Michigan resulted from epilimnetic silica depletion that developed rapidly in the 1950s and 1960s when TP averaged 8 mg L −1 (0.26 µmol L −1 ). In addition, epilimnetic silica depletion in the late 1800s was inferred from BSi accumulation in Lake Erie and Lake Ontario when the TP concentration was <10 µg L −1 (0.32 µmol L −1 ). Third, a secondary peak in BSi accumulation in the 1950s and 1960s signaled water‐column silica depletion in Lake Ontario and the eastern basin of Lake Erie that developed as TP concentration increased to 27 µg L −1 (0.87 µmol L −1 ). Ratios of NAIP :TP, BSi :TP, and BSi : NAIP also provide sensitive proxies for phosphorus enrichment. BSi accumulation is a sensitive proxy for phosphorus enrichment because BSi production by diatoms integrates silica utilization over an annual cycle, silica is recycled slowly (on annual time scales) compared with phosphorus, and sedimented BSi is focused into depositional zones.
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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".