The role of the climate niche in repeated abrupt tree declines and ecotone dynamics in the Appalachian Mountains during the Holocene
Bibliographic record
Abstract
Forests in eastern North American did not achieve a stable composition during the Holocene. Both prolonged and abrupt shifts in the distributions of tree species were common. Studying the dynamics involved can help anticipate the responsiveness of forest biogeography to climate change today. Here, we evaluate changes in two >12,000-year fossil pollen stratigraphies from the Appalachian Plateaus Province, Pennsylvania. They show repeated episodes of forest turnover following the widespread collapse of hemlock ( Tsuga canadensis ) populations at ca. 5000 years before present (YBP). The changes from 5000-2500 YBP include abrupt declines in taxa such as birch ( Betula spp.) and beech ( Fagus grandifolia ), which produced unique forest phases each lasting 300-500 years. Emergent communities included the resurgence of oak ( Quercus spp.) and white pine ( Pinus strobus ), which had been important several thousand years earlier. Two oak maxima at 4800-4250 and 3800-3200 YBP mark northward shifts in the regional oak-hardwood ecotone known as the “Tension Zone” and involve centennial-scale droughts during a millennial-scale period of warming. The changes, like those elsewhere along the ecotone from Ontario to Massachusetts, differ from successional dynamics that might have been expected after the hemlock decline. Instead, the forest histories included abrupt changes, short-lived communities, and asynchronous changes across sites consistent with the interaction of a) individualistic species’ climate niches and b) multiple scales of climate variation. Comparison of the pollen records with heuristic forest history simulations demonstrates that landscape-scale forest changes, integrated across mosaics of many stands, match patterns expected from deterministic, equilibrium responses to climate change.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".