Reconciling apparent inconsistencies in estimates of terrestrial CO2 sources and sinks
Bibliographic record
Abstract
The magnitude and location of terrestrial carbon sources and sinks remains subject to large uncertainties. Estimates of terrestrial CO2 fluxes from ground-based inventory measurements typically find less carbon uptake than inverse model calculations based on atmospheric CO2 measurements, while a wide range of results have been obtained using models of different types. However, when full account is taken of the processes, pools, time scales and geographic areas being measured, the different approaches can be understood as complementary rather than inconsistent, and can provide insight as to the contribution of various processes to the terrestrial carbon budget. For example, quantitative differences between atmospheric inversion model estimates and forest inventory estimates in northern extratropical regions suggest that carbon fluxes to soils (often not accounted for in inventories), and into non-forest vegetation, may account for about half of the terrestrial uptake. A consensus of inventory and inverse methods indicates that, in the 1980s, northern extratropical land regions were a large net sink of carbon, and the tropics were approximately neutral (albeit with high uncertainty around the central estimate of zero net flux). The terrestrial flux in southern extratropical regions was small. Book-keeping model studies of the impacts of land-use change indicated a large source in the tropics and almost zero net flux for most northern extratropical regions; similar land use change impacts were also recently obtained using process-based models. The difference between book-keeping land-use change model studies and inversions or inventories was previously interpreted as a "missing" terrestrial carbon uptake. Land-use change studies do not account for environmental or many management effects (which are implicitly included in inventory and inversion methods). Process-based model studies have quantified the impacts of CO2 fertilisation and climate change in addition to land use change, and found that these environmental effects are in the right order of magnitude to account for the "missing" terrestrial carbon uptake. Despite recent carbon losses due to fire and insect attack in Canada and Russia, the northern extratropical regions generally have been a net carbon sink, only partially due to land-use changes such as abandonment of agricultural land. In the tropics, inventory data and flux measurements in extant forests support the existence of an environmental or management sink that counterbalances the effect of deforestation. Woody encroachment in savannas may also be a significant (but as yet poorly quantified) cause of tropical carbon uptake.
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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 | 0.037 | 0.079 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".