The European forest carbon budget under future climate conditions and current management practices
Bibliographic record
Abstract
Abstract. To become carbon neutral by 2050, the European Union (EU27) net carbon sink from forests should increase from the current level of about −360 to −450 Mt CO2eq yr−1 by 2050. Reaching this target requires additional efforts, which should be informed by the expected interactions between current age-class distributions, the effect of forest management practices and the expected impacts of future climate change. However, modelling the combined effect of these drivers is challenging, since it requires a mechanistic assessment of climate impacts on primary productivity and heterotrophic respiration and a detailed representation of the forest age structure and of the management practices across the entire EU. To achieve this goal, we combined the output provided by four land–climate models – run under two different Representative Concentration Pathway scenarios (RCP2.6 and RCP6.0) – to parameterize the input data used in an empirical forest growth model. This hybrid modelling approach aims to quantify the impact of climate change and forest management on the long-term (i.e. to 2100) evolution of the EU27 + UK forest carbon budget. This approach was tested using a business-as-usual (BAU) scenario, based on the continuation of the management practices applied by EU member states within the historical period 2000–2015. We emphasize that our study does not explore a specific policy scenario but describes a methodological framework. Our results highlight that, under our BAU case, the EU27 + UK forest C sink would decrease to about −250 Mt CO2eq yr−1 in 2050 and −80 Mt CO2eq yr−1 by 2100. The main driver of the long-term evolution of the forest C sink is the ongoing ageing process of the European forests, mostly determined by past and ongoing management. In addition, climate change may further amplify or mitigate this trend. Due to the large uncertainty in climate projections, in 2050 the net C sink may range from −100 to −400 Mt CO2eq yr−1 under RCP2.6 and from −100 to −300 Mt CO2eq yr−1 under RCP6.0. These results suggest that while a change in management practices would be needed to reverse an otherwise declining trend in the sink, climate change adds a considerable uncertainty, potentially nearly doubling or halving the sink associated with management.
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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 | 0.001 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".