Seasonal changes in digestive enzymes in five bird species
Bibliographic record
Abstract
Most animals must cope with seasonal fluctuations in environmental conditions, including variations in food availability and composition. Accordingly, it is expected that most species should exhibit reversible seasonal phenotypic adjustments in their physiology. Here, we assessed seasonal variation in the activity of three digestive enzymes (sucrase, maltase, and aminopeptidase-N) in one omniviorous bird species (Rufous-collared Sparrow (Zonotrichia capensis (P. L. Statius Müller, 1776))), three granivorous bird species (Black-chinned Siskin (Carduelis barbata (Molina, 1782)), Common Diuca Finch (Diuca diuca (Molina, 1782)), and Mourning Sierra Finch (Phrygilus fruticeti (Kittlitz, 1833))), and one insectivorous bird species (Plain-mantled Tit-Spinetail (Leptasthenura aegithaloides (Kittlitz, 1830))). Based on the adaptive modulation hypothesis, we predicted that the omnivorous species should exhibit the largest seasonal variation in the activity of its digestive enzymes in relation to granivorous and insectivorous species. We found that Z. capensis adjusts total activities of disaccharidases, total sucrase activity varied between seasons in C. barbata, and total activity of aminopeptidase-N only changed seasonally in L. aegithaloides. Moreover, this last species modified the tissue-specific activity of both disaccharidases as well as the wet mass of its intestine. Taken together, our results suggest that seasonal dietary changes occur in most of the species, regardless of the trophic categories in which they belong. Consequently, a better knowledge of the diet and its seasonal variation is necessary to better account for the results recorded in this study.
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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 | 0.001 | 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 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".