Climate and Species Traits Drive Changes in Holocene Forest Composition Along an Elevation Gradient in Pacific Canada
Bibliographic record
Abstract
Projected changes in climate are expected to shift the ranges of many tree species poleward and to higher elevations. Here, we examine past changes in forest composition in Pacific Canada using a paleoecological approach and investigate the role of past changes in climate and differences in species traits in changing forest compositions. We present a new pollen record from a mid-elevation fen on central Vancouver Island, British Columbia that shows (1)Pinus contorta-dominated communities starting 14,000 cal yr BP, (2) an abrupt transition toPseudotsuga menziesiiandTsuga heterophyllaforests by 10,600 cal yr BP, and (3) a gradual transition toTsuga heterophylla-dominated forests in the mid-Holocene. We combine this mid-elevation record with nearby pollen records along a 1,400-m elevation gradient to assess sorting of dominant woody plant taxa and their life history and stress tolerance traits over the last 14,000 years. Multivariate time series confirm elevational sorting of woody plant taxa through time with the modern elevational zonation of tree taxa established by 6,000 cal yr BP. Some taxa have consistently occupied low and middle elevations (P. menziesii,Alnus rubra) or high elevations (Tsuga mertensiana), whereas other taxa (P. contorta,T. heterophylla) have occurred at a wider range of elevations. Three-table statistical techniques reveal significant relationships among forest composition, independent paleoclimate records, and species traits. Tree species with similar traits tend to be most abundant at similar times and those that are functionally dissimilar are separated in time. For example, species with “fast” life history strategies (e.g.,P. contorta,Alnus viridis) are most abundant in late-glacial plant communities, while those with “slow” life history strategies (e.g.,T. heterophylla,T. mertensiana) are most abundant in mid-late Holocene forests. This research highlights that woody plant taxa and their functional traits are sorted on long timescales in association with environmental change. Turnover in forest composition is driven primarily by changes in climate, which acts as a filter on species traits to direct changes in forest dynamics.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".