Climate Variability Induced Shifts in Nitrogen Loading fromTerrestrial to Aquatic Ecosystems
Bibliographic record
Abstract
Nitrogen is one of the critical nutrients regulating terrestrial and aquatic productivity, and is linked to degradation of water quality of freshwater and marine ecosystems worldwide. The landscape patterns of stream nitrogen components, concentrations and loadings and their relationships with climate variability and landuse, were analyzed and quantified in this study. We used stream nitrogen concentration data collected at 2,125 sites and climate data at 301 weather stations during 1976 to 2005 in 30 eco-regions across British Columbia, Canada. While the patterns of stream nitrogen component, concentration, and loading distributions were found to be related to landscape patterns of climate variability, human activities, landuse, natural vegetation, and relief across British Columbia, the climate variability on both temporal a d spatial scales were found to be the dominant driver of variability in loading and concentrations of nitrogen. Elevated air temperature gradient across the landscape of British Columbia resulted in a significant increase in stream nitrogen loading from terrestrial into aquatic ecosystems. Precipitation, nitrogen deposition, population density and urban area also significantly affected the stream nitrogen components, concentrations and loadings. We suggest that climate change, especially shifts in temperature and precipitation, along with increased human activities tend to have important implications for loading of nitrogen from terrestrial to aquatic ecosystems and associated water quality in aquatic ecosystems.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".