Data from: Small montane cloud forest fragments are important for conserving tree diversity in the Ecuadorian Andes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AbstractMontane tropical cloud forests, with their complex topography, biodiversity, high numbers of endemic species, and rapid rates of clearing are a top global conservation priority. However, species distributions at local and landscape scales in cloud forests are still poorly understood, in part because few regions have been surveyed. Empirical work has focused on species distributions along elevation gradients, but spatial variation among forests at the same elevation is less commonly investigated. In this study, the first to compare tree communities across multiple Andean cloud forests at similar elevations, we surveyed trees in five ridge-top forest reserves at the upper end of the ‘mid-elevation diversity bulge’ (1900-2250 masl) in the Intag Valley, a heavily deforested region in the Ecuadorian Andes. We found that tree communities were distinct in reserves located as close as 10 to 35 km apart, and that spatially closer forests were not more similar to one another. Although larger (1500 to 6880 ha), more intact forests contained significantly more tree species (108-120 species/0.1ha) than smaller (30 to 780ha) ones (56-87 species/0.1ha), each reserve had unique combinations of more common species, and contained high proportions of species not found in the others. Results thus suggest that protecting multiple cloud forest patches within this narrow elevational band is essential to conserve landscape-level tree diversity, and that even small forest reserves contribute significantly to biodiversity conservation. These findings can be applied to create management plans to conserve and restore cloud forests in the Andes and tropical montane cloud forests elsewhere.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.012 | 0.008 |
| 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 it