Changes in beta diversity and species functional traits differ between saplings and mature trees in an old‐growth forest
Bibliographic record
Abstract
Abstract Invasion by generalist tree species can cause biotic homogenization, and such community impoverishment is likely more important in rare forest types. We quantified changes in tree diversity within Carolinian (range in Central Hardwood Forest), central (range in Central Hardwood Forest and Northern Hardwood‐Conifer Forest), and northern species [range reached Northern‐Conifer‐Hardwood/closed Boreal (spruce‐Fir) Forest] in an old forest tract in southern Canada at points surveyed 24 years apart. We asked: How did mature tree and sapling composition and abundance change for the three species’ groups? Did those changes lead to biotic homogenization? Can species’ changes be explained by community traits? We tested for differences in temporal and spatial tree β‐diversity, as well as forest composition and structure, using univariate/multivariate analyses and a community trait‐based approach to identify drivers of change. Major increases occurred in abundance for matureAcer rubrum(northern), while other species decreased (Fraxinus americana,Populus grandidentata); declines were found inA. saccharinum(central) andCornus florida(Carolinian). Species composition of saplings, but not mature trees, changed due to replacement; no evidence for biotic homogenization existed in either cohort. As a group, northern mature tree species increased significantly, while central species decreased; saplings of pooled Carolinian species also declined. Shade tolerance in mature trees increased, reflecting successional changes, while drought tolerance decreased, perhaps due to changing temperatures, altered precipitation or ground water levels. Saplings showed declines in all traits, probably because of compositional change. Our results demonstrated that saplings can more closely reflect change in forest dynamics than mature trees, especially over short time periods. Based on sapling trends, this remnant could ultimately transition to a mesophytic hardwood stand dominated byA. rubrumand other shade‐tolerant species, creating a more homogeneous forest. While encouraging regeneration for Carolinian and central tree species could ensure high levels of diversity are conserved in the future, it is important to balance this with the primary management goal of maintaining the forest's old‐growth characteristics.
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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 | 0.000 | 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".