Communities with diverse subsistence needs require a variety of functional tree traits
Bibliographic record
Abstract
Abstract Tree species preference is an understudied yet crucial component of sustainable forest management, as unsustainable harvesting can lead to non‐random loss of functional traits. We examine wood resource preference across five regions of Madagascar's biodiverse eastern humid forests. We asked forest users in 19 men's and 19 women's focus groups to list their preferred tree species for common short‐ (charcoal, firewood) and long‐term (house construction, furniture, tools) uses. We then measured functional traits of 260 preferred and common tree species: height, DBH, bark thickness, specific leaf area, wood specific gravity, and seed dispersal syndrome in the surrounding landscape. Using household interviews, we determined the average distance households would need to travel to access each species. Forest users preferred shorter travel distances for short‐term uses, whereas species preferences for long‐term uses were associated with specific functional traits. Women focused mainly on firewood and tool provisioning and were more likely to prefer species at a shorter walking distance than men. We found no clear relationships between tree species preference and dispersal syndromes, suggesting that a diverse community of seed‐dispersing animal species may be necessary to maintain traits preferred for tree harvest in Malagasy humid forests. We suggest strategies to support reducing deforestation, promoting traditional ecological knowledge, and increasing accessibility of wood resources to women.
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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 | 0.001 | 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) | 0.004 | 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".