Assessing the Possible Risks of Including the Reserved Forests in National Reporting under the UN Convention on Climate Change
Bibliographic record
Abstract
Дана оценка рисков включения резервных лесов в состав управляемых лесных земель для составления Национального доклада Российской Федерации о кадастре антропогенных выбросов из источников и абсорбции поглотителями парниковых газов, не регулируемых Монреальским протоколом. Рассмотрены принципы и критерии выделения управляемых лесов, которые применяются при подготовке национальных кадастров парниковых газов (ПГ) в разных странах мира и России. Приведена многолетняя динамика запасов, абсорбции, потерь и баланса углерода в биомассе резервных лесов страны. Выполнена сравнительная оценка ежегодных потерь углерода в биомассе резервных лесов, вызванных гибелью от пожаров, с потерями в защитных и эксплуатационных лесах. Подтверждено расчетами, что при современном уровне пожарных эмиссий углерода и отсутствии потерь от заготовки древесины включение резервных лесов в Национальный кадастр ПГ увеличит оценку запаса углерода в биомассе лесов страны на 17%, годичную абсорбцию – на 13%, а общую национальную оценку нетто-поглощения углерода биомассой лесов – на 13%. An assessment of the risks of including the reserved forests in managed forest land for the Russian Federation National Inventory Report of anthropogenic emissions by sources and removals by sinks of greenhouse gases not controlled by the Montreal Protocol is given. The principles and criteria for identifying the managed forests that applied in the preparation of national greenhouse gas (GHG) inventories around the world and in Russia are reviewed. Long-term trends in carbon stocks, carbon absorption, carbon losses and carbon balance of reserved forest are presented. A comparative assessment of the annual carbon losses in the biomass of reserved forests caused by fire mortality with those in protective and exploitable forests named as managed forests has been made. Confirmed by calculations that, given the current level of fire emissions and the absence of losses from timber harvesting, inclusion of reserved forests in the National GHG Inventory will increase the estimate of carbon stock in forest biomass by 17%, annual absorption by 13%, and net carbon sequestration of forest biomass in total by 13%.
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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 | 0.036 | 0.095 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".