Evolution and variation of atmospheric carbon dioxide concentration over terrestrial ecosystems as derived from eddy covariance measurements
Bibliographic record
Abstract
Carbon dioxide (CO 2 ) is the most important anthropogenic greenhouse gas contributing to global climate change . Understanding the temporal and spatial variations of CO 2 concentration over terrestrial ecosystems provides additional insight into global atmospheric variability of CO 2 concentration. Using 355 site-years of CO 2 concentration observations at 104 eddy-covariance flux tower sites in Northern Hemisphere, we presented a comprehensive analysis of evolution and variation of atmospheric CO 2 concentration over terrestrial ecosystem (ACTE) for the period of 1997–2006. Our results showed that ACTE exhibited a strong seasonal variations, with an average seaonsal amplitude (peak-trough difference) of 14.8 ppm, which was approximately threefold that global mean CO 2 observed in Mauna Loa in the United States (MLO). The seasonal variation of CO 2 were mostly dominant by terrestrial carbon fluxes , i.e., net ecosystem procution (NEP) and gross primary produciton (GPP), with correlation coefficient( r ) were −0.55 and −0.60 for NEP and GPP, respectively. However, the influence of carbon fluxes on CO 2 were not significant at interannual scale, which implyed that the inter-annual changing trends of atmospheric CO 2 in Northern Hemisphere were likely to depend more on anthropogenic CO 2 emissions sources than on ecosystem change. It was estimated, by fitting a harmonic model to monthly-mean ACTE, that both annual mean and seasonal amplitude of ACTE increased over the 10-year period at rates of 2.04 and 0.60 ppm yr −1 , respectively. The uptrend of annual ACTE could be attributed to the dramatic global increase of CO 2 emissions during the study period, whereas the increasing amplitude could be related to the increases in Northern Hemisphere biospheric activity. This study also found that the annual CO 2 concentration showed large variation among ecosystems, with the high value appeared in deciduous broadleaf forest, evergreen broadleaf forest and cropland. We attribute these discrepancies to both differential local anthropogenic impacts and carbon sequestration abilities across ecosystem types.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 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".