The carbon cost of the 2019–20 Australian fires varies with fire severity and forest type
Bibliographic record
Abstract
Abstract Aim To estimate loss of above‐ground carbon (AGC) and conversion of live carbon to dead carbon following understorey and canopy fire. Location South‐eastern Australia. Time period 2019–2020. Major taxa studied Four widespread resprouting eucalypt forests. Methods Above‐ground carbon was measured in 15 plots in each of four forest types one‐year post‐fire. We also assessed topkill, that is, trees subject to canopy loss that failed to resprout epicormically. Results While canopy fire was associated with greater declines in AGC than understorey fire, this was only statistically significant for only one forest type, where AGC declined from 154 to 85 Mg C ha−1 following canopy fire. Significant post‐fire increases in dead AGC were observed in one forest type, where dead carbon increased from 22 to 60% after canopy fire. Topkill of trees following canopy fire (48–78% of stems) was higher than topkill after understorey fire (36–53% of stems) and in unburnt forest (12–55%). Topkill occurred primarily in small‐diameter stems. Consequently, there was no effect of fire on the proportion of dead AGC in trees, with the exception of the forest with lowest productivity (i.e., lowest biomass) and lowest annual rainfall, where dead tree carbon increased from 8% in unburnt forest to 13 and 53% after understorey and canopy fire, respectively. AGC in understorey vegetation and coarse woody debris was similar or lower in burnt compared with unburnt forest. Litter carbon was significantly lower and pyrogenic carbon significantly higher in burnt forest, with no difference between understorey and canopy fire. Main conclusions While increased fire severity was associated with increased changes to carbon stocks, there were differences among forest types. Specifically, the driest forest type had the highest rates of topkill following canopy fire. These results highlight the importance of spatial variability in fire severity and forest type in determining the effects of fire on carbon stocks.
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 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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".