Is atmospheric phosphorus pollution altering global alpine Lake stoichiometry?
Bibliographic record
Abstract
Abstract Anthropogenic activities have significantly altered atmospheric chemistry and changed the global mobility of key macronutrients. Here we show that contemporary global patterns in nitrogen (N) and phosphorus (P) emissions drive large hemispheric variation in precipitation chemistry. These global patterns of nutrient emission and deposition (N:P) are in turn closely reflected in the water chemistry of naturally oligotrophic lakes (r2 = 0.81, p < 0.0001). Observed increases in anthropogenic N deposition play a role in nutrient concentrations (r2 = 0.20, p < 0.05); however, atmospheric deposition of P appears to be major contributor to this pattern (r2 = 0.65, p < 0.0001). Atmospheric simulations indicate a global increase in P deposition by 1.4 times the preindustrial rate largely due to increased dust and biomass burning emissions. Although changes in the mass flux of global P deposition are smaller than for N, the impacts on primary productivity may be greater because, on average, one unit of increased P deposition has 16 times the influence of one unit of N deposition. These stoichiometric considerations, combined with the evidence presented here, suggest that increases in P deposition may be a major driver of alpine Lake trophic status, particularly in the Southern Hemisphere. These results underscore the need for the broader scientific community to consider the impact of atmospheric phosphorus deposition on the water quality of naturally oligotrophic lakes.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".