Older eastern white pine trees and stands sequester carbon for many decades and maximize cumulative carbon
Bibliographic record
Abstract
Abstract Pre-settlement New England was heavily forested, with some trees exceeding 2 m in diameter. New England’s forests have regrown since farm abandonment and represent what is arguably the most successful regional reforestation on record; the region has recently been identified as part of the “Global Safety Net.” Remnants and groves of primary “old-growth” forest demonstrate that native tree species can live for hundreds of years and continue to add to the biomass and structural and ecological complexity of forests. Forests are an essential natural climate solution for accumulating and storing atmospheric CO 2 , and some studies emphasize young, fast-growing trees and forests whereas others highlight high carbon storage and accumulation rates in old trees and intact forests. To address this question directly within New England we leveraged long-term, accurate field measurements along with volume modeling of individual trees and intact stands of eastern white pines ( Pinus strobus ) and compared our results to models developed by the U.S. Forest Service. Our major findings complement, extend, and clarify previous findings and are three-fold: 1) intact eastern white pine forests continue to sequester carbon and store high cumulative carbon above ground; 2) large trees dominate above-ground carbon storage and can sequester significant amounts of carbon for hundreds of years; 3) productive pine stands can continue to sequester high amounts of carbon for well over 150 years. Because the next decades are critical in addressing the climate crisis, and the vast majority of New England forests are less than 100 years old, and can at least double their cumulative carbon, a major implication of this work is that maintaining and accumulating maximal carbon in existing forests – proforestation - is a powerful near-term regional climate solution. Furthermore, old and old-growth forests are rare, complex and highly dynamic and biodiverse, and dedication of some forests to proforestation will also protect natural selection, ecosystem integrity and full native biodiversity long-term. In sum, strategic policies that grow and protect existing forests in New England will optimize a proven, low cost, natural climate solution for meeting climate and biodiversity goals now and in the critical coming decades.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| 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 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".