Raptorial birds and environmental gradients in the southern Neotropics: A test of species‐richness hypotheses
Why this work is in the frame
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Bibliographic record
Abstract
Abstract We investigated the spatial patterns of raptor species richness in the southern Neotropics and tested three hypotheses that were most likely to explain spatial variations: ambient energy, productivity and habitat heterogeneity. We used non‐linear regression analysis and eliminated alternative hypotheses by finding the best single environmental predictor of raptor species richness among potential evapotranspiration (PET), actual evapotranspiration (AET), mean annual temperature and precipitation and vegetation structure coefficient. As expected, the number of raptor species decreases monotonically as latitude increases. Raptor species richness was significantly correlated with each of the environmental factors considered in this study, reflecting covariation of climatic and habitat descriptors. Correlation coefficients showed positive associations between species richness and each single environmental variable. Mean annual temperature was the strongest environmental predictor of raptor species richness (explaining 82% of the variance), consistent with the ambient energy hypothesis. Another descriptor of ambient energy (PET) explained 75% of the spatial variation. Both the AET and the vegetation structure coefficient explained 77% of the spatial variation in richness. The spatial clusters of extreme residuals identified the subtropical rainforests and the arid heights and low plateaux of the study area as regions where local environmental conditions appear to interfere with the general trend identified by the model at the regional scale.
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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 | 0.000 | 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) | 0.020 | 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