Links between biomass and tree demography in a northern hardwood forest: a decade of stability and change in Hubbard Brook Valley, New Hampshire
Bibliographic record
Abstract
We resurveyed a network of sampling plots (n = 371) 10 years after its establishment in Hubbard Brook Experimental Forest (New Hampshire, USA) to quantify recent trends in tree biomass and demography. We found no significant change in live-tree biomass during the decade. Total biomass was 246 Mg·ha–1 (95%CI = 235–258) in 1995–1996 and 245 Mg·ha–1 (95%CI = 234–256) in 2005–2006. Annual mortality during the period for trees ≥ 10 cm diameter at breast height (1.37 m) averaged 9.7 trees·ha–1·year–1 (95% CI of annual mortality rate = 1.36%–1.84%·year–1). Tree recruitment into the census pool was 8.4 trees⋅ha–1·year–1 (95% CI = 5.8–10.6). Although overall forest biomass remained constant, there were marked shifts in the relative dominance of the canopy species. For example, the live biomass of Betula alleghaniensis Britton declined by 7%, whereas the live biomass of Picea rubens Sarg. increased by 6% and that of Acer saccharum Marshall increased by 4%. There was no instance of recruitment significantly exceeding mortality for the major species. Relative growth rates ranged from 1.03%·year–1 for Betula papyrifera Marshall to 1.99%·year–1 for Abies balsamea (L.) Mill. Our results confirmed earlier reports that the forest at Hubbard Brook is no longer aggrading. Current live-tree biomass is lower than expected. Although effects of novel disturbances documented on a regional level have not led to directional changes in tree demography at Hubbard Brook, we suggest that these novel stressors are depressing the biomass potential of the forest.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".