Multifactor controls on terrestrial N <sub>2</sub> O flux over North America from 1979 through 2010
Bibliographic record
Abstract
Abstract. Nitrous oxide (N2O) is a potent greenhouse gas which also contributes to the depletion of stratospheric ozone (O3). However, the magnitude and underlying mechanisms for the spatiotemporal variations in the terrestrial sources of N2O are still far from certain. Using a process-based ecosystem model (DLEM – the Dynamic Land Ecosystem Model) driven by multiple global change factors, including climate variability, nitrogen (N) deposition, rising atmospheric carbon dioxide (CO2), tropospheric O3 pollution, N fertilizer application, and land conversion, this study examined the spatial and temporal variations in terrestrial N2O flux over North America and further attributed these variations to various driving factors. From 1979 to 2010, the North America cumulatively emitted 53.9 ± 0.9 Tg N2O-N (1 Tg = 1012 g), of which global change factors contributed 2.4 ± 0.9 Tg N2O-N, and baseline emission contributed 51.5 ± 0.6 Tg N2O-N. Climate variability, N deposition, O3 pollution, N fertilizer application, and land conversion increased N2O emission while the elevated atmospheric CO2 posed opposite effect at continental level; the interactive effect among multiple factors enhanced N2O emission over the past 32 yr. N input, including N fertilizer application in cropland and N deposition, and multi-factor interaction dominated the increases in N2O emission at continental level. At country level, N fertilizer application and multi-factor interaction made large contribution to N2O emission increase in the United States of America (USA). The climate variability dominated the increase in N2O emission from Canada. N inputs and multiple factors interaction made large contribution to the increases in N2O emission from Mexico. Central and southeastern parts of the North America – including central Canada, central USA, southeastern USA, and all of Mexico – experienced increases in N2O emission from 1979 to 2010. The fact that climate variability and multi-factor interaction largely controlled the inter-annual variations in terrestrial N2O emission at both continental and country levels indicate that projected changes in the global climate system may substantially alter the regime of N2O emission from terrestrial ecosystems during the 21st century. Our study also showed that the interactive effect among global change factors may significantly affect N2O flux, and more field experiments involving multiple factors are urgently needed.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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; both teacher heads agree on what is shown here.
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".