Nitrogen deposition reveals global patterns in plant and animal stoichiometry
Bibliographic record
Abstract
The elemental content of organisms links cellular biochemistry to ecological processes, from physiology to nutrient dynamics. While plant stoichiometry is thought to vary with climate and nutrient availability across latitudes, the consistency of these patterns across trophic groups and realms remains unclear. Using the StoichLife database, which includes nitrogen and phosphorus content data for 5443 species across 1390 sites, we examine how solar energy (temperature, radiation) and nutrients (nitrogen and phosphorus) influence stoichiometric variation. We find that plant stoichiometry in terrestrial and freshwater ecosystems is more strongly associated with environmental gradients, particularly nitrogen deposition, than animal stoichiometry. Contrary to expectations, temperature, radiation, and labile P show limited global effects. Latitudinal patterns in stoichiometry are more closely associated with species turnover rather than intraspecific variation. Given the strong links between stoichiometry and organismal performance, these findings underscore the need to predict the ecological consequences of anthropogenic disruption to global biogeochemical cycles.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".