Scale‐dependent changes in tree diversity over more than a century in eastern Canada: Landscape diversification and regional homogenization
Bibliographic record
Abstract
Abstract A better understanding of how disturbance impacts tree diversity at different scales is essential for our ability to conserve and manage forest ecosystems in the context of global changes. Here we test the impacts of land use‐related disturbances on tree diversity since the 19th century across a broad region (>150,000 km 2 ) of northern temperate forests in eastern Canada. We used a large and unique dataset of early land surveys conducted during the 19th century (>130,000 species lists), along with modern forest inventories (>80,000 plots), to analyse long‐term changes in taxonomic and functional tree diversity at several scales (grid cell resolutions ranging from 12.5 to 1,600 km 2 ; we refer to one grid cell as a ‘landscape’). Our results show that land use‐related disturbances have led simultaneously to (a) increased diversity within landscapes and a (b) homogenization at the regional scale (i.e. decreased composition dissimilarity among landscapes). These trends were found for both taxonomic diversity and functional diversity, with temporal changes more pronounced for taxonomic than functional diversity. We also found an increase over time in the strength of correlations between environmental variables and diversity both within and among landscapes. Synthesis . Our results support the idea that human‐induced impacts on biodiversity are strongly scale‐dependent and not necessarily associated with biodiversity loss. This highlights possible ways that human‐driven changes in tree diversity might impact forest resistance and resilience to future global changes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".