Nitrogen deposition altered the climatic sensitivity of vegetation phenology
Bibliographic record
Abstract
Abstract Nitrogen deposition substantially alters nutrient absorption by plant root systems, which has far-reaching consequences for leaf growth and development. However, its effects on plant phenology and climatic sensitivity remain unclear. This study investigated the effects of nitrogen deposition on vegetation phenology and its sensitivity to moisture and temperature from 1982 to 2022 by combining data from field experiments, remote-sensing observations, and land surface models. The results revealed that the start of the growing season (SOS) has become more sensitive to vapor pressure deficit (VPD), whereas its sensitivity to temperature and soil moisture (SM) has decreased in recent decades. Conversely, there was no notable trend in climatic sensitivity at the end of the growing season (EOS). The model results show that SOS’s sensitivity to VPD (SVPD) and temperature (STem) increased with higher nitrogen deposition levels (SVPD, a = 1.07 d unit−1, P < 0.01; STem, a = 0.10 d unit−1, P < 0.01). The sensitivity of EOS to soil moisture (SSM) decreased significantly with increasing nitrogen deposition (a = −1.82 d unit−1, P < 0.05), whereas SVPD decreased (a = −0.38 d unit−1, P < 0.01). Attribution analysis indicated that nitrogen deposition was the primary driver of changes in the climatic sensitivity of SOS, whereas atmospheric CO2 predominantly influenced changes in the SSM of EOS. These results emphasize the critical role of nitrogen deposition in determining the climatic sensitivity of vegetation phenology and provide a novel perspective for understanding and predicting vegetation phenology dynamics under ongoing global change.
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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 | 0.000 |
| 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".