The influence of microhabitat, moisture and diet on stable-hydrogen isotope variation in a Neotropical avian food web
Why this work is in the frame
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Bibliographic record
Abstract
Abstract: The application of stable-hydrogen isotope (δD) measurements to the study of animal movement, resource use and physiology depends on understanding factors driving variation in δD in animal tissues. The source of micro-scale variation in δD is poorly known, yet understanding micro-scale patterns of δD could shed light on important ecological processes and improve our abilities to track animal movements. Using linear and additive models, we explored the influence of micro-scale habitat use, moisture and diet on tissue δD values of Nicaraguan cloud-forest birds. Using mist nets, we captured 211 individuals of 22 resident Neotropical species at 500–1390 m asl and collected feather and claw samples. Based on three years of data from year-round sampling, our results suggest that microhabitat, seasonal shifts in moisture δD, and diet all influence bird tissue δD values. Our model results reveal a previously undescribed microgeographical effect on δD, where foraging level (understorey versus overstorey) and foraging location (forest interior versus adjacent coffee plantation) were significant predictors of δD values in bird claws and feathers. Mean claw and feather δD values among species varied from −83‰ to −19‰. Top models for claws and feathers explained 57% and 52% of variation in δD respectively. Direct comparisons of understorey (mean ± SD of −30‰ ± 15‰) versus overstorey (−50‰ ± 15‰) claw values suggest that δD may be useful in tracking vertical, micro-scale movement. Higher δD values in forest understorey birds reveal a heavy reliance upon recycled, fog moisture. Fragmentation and climate change may result in increasingly desiccated cloud forest that may exert a more negative influence on the food webs of understorey species that seem to be supported by recycled sources of moisture in the dry season.
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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) | 0.000 | 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