Beetle diversity in a matrix of old‐growth boreal forest: influence of habitat heterogeneity at multiple scales
Bibliographic record
Abstract
The relative contribution of compositional and structural heterogeneity on biodiversity is currently ambiguous because field studies generally integrate these two sources of habitat heterogeneity into a single index. We established the relationship between species richness of ground‐dwelling and flying beetles and compositional and structural attributes of forest heterogeneity. The relationship was evaluated at two spatial scales: the scale of forest stand, corresponding to an 11.3 m radius, and the scale of landscape, corresponding to either a 400 or 800 m radius. Seventy stands were sampled in the matrix of old‐growth boreal forest of the North Shore region of Québec, Canada, during the summers of 2004 and 2005. A total of 133 ground‐dwelling beetle species (range: 4–42 species per site) were captured in the pitfall traps and 251 flying species (range 16–58 species per site) in flight‐interception traps. We found that the most relevant type of heterogeneity to explain variations in species richness and the significance of landscape scale information varied between groups of beetles. Compositional heterogeneity (i.e. the number of species of forest trees and shrubs) at the stand scale best predicted species richness in ground‐dwelling beetles. On the other hand, it was the combined influence of structural and compositional habitat heterogeneity at stand and landscape scales that best explained richness patterns in flying beetles. Our study outlines the significance of considering multiple types and spatial scales of habitat heterogeneity when describing patterns of species richness.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".