Ecological thresholds under atmospheric nitrogen deposition for 1200 herbaceous species and 24 communities across the United States
Bibliographic record
Abstract
Abstract Nitrogen (N) emissions and atmospheric deposition have increased significantly during the last century and become a stressor for many N‐sensitive plant species. Understanding individual and community herbaceous plant species thresholds to atmospheric N deposition can inform emissions reduction policy. Here, we present results using Threshold Indicator Taxa Analysis (TITAN) applied to more than 1200 unique plant species and 24 vegetation communities (i.e., alliances) across the United States (US) to assess vulnerability to N deposition. Alliance‐level thresholds (change points) for species decreasing in abundance along the gradient ranged from 1.8 to 14.3 kg N ha─1 year─1 and tended to be lower in the west than the east, which suggests that eastern communities, where N deposition has been historically higher, may have already lost many sensitive species. For the species that were present in more than one alliance, over half had a variable response to the N deposition gradient, suggesting that local factors affect vulnerability. Significant progress has been made during the past 30 years to reduce N emissions, which has reduced the percentage of plots at risk to N deposition from 72% to 35%. Nevertheless, over a third of plots remain at risk, and an average reduction of N deposition of 20% would protect half of the plots where N deposition exceeds community thresholds. Furthermore, the alliance‐ and species‐level change points determined in this study may be used to inform N critical loads.
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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 | 0.001 | 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".