Trophic niche overlap in two syntopic colubrid snakes (Hierophis viridiflavus and Zamenis longissimus) with contrasted lifestyles
Bibliographic record
Abstract
In many organisms, including snakes, trophic niche partitioning is an important mechanism promoting species coexistence. In ectotherms, feeding strategies are also influenced by lifestyle and thermoregulatory requirements: active foragers tend to maintain high body temperatures, expend more energy, and thus necessitate higher energy income. We studied diet composition and trophic niche overlap in two south European snakes ( Hierophis viridiflavus and Zamenis longissimus ) in the northern part of their range. The two species exhibit contrasted thermal adaptations, one being highly mobile and thermophilic ( H. viridiflavus ) and the other being elusive with low thermal needs ( Z. longissimus ). We analyzed feeding rate (proportion of snakes with indication of a recent meal) and examined more than 300 food items (fecal pellets and stomach contents) in 147 Z. longissimus and 167 H. viridiflavus . There was noticeable overlap in diet (overlap of Z. longissimus on H. viridiflavus = 0.62; overlap of H. viridiflavus on Z. longissimus = 0.80), but the similarity analyses showed some divergence in diet composition. Dietary spectrum was wider in H. viridiflavus , which fed on various mammals, birds, reptiles, and arthropods whereas Z. longissimus was more specialized on mammals and birds. The more generalist nature of H. viridiflavus was consistent with its higher energy requirements. In contrast to our expectation, feeding rate was apparently higher in Z. longissimus than in H. viridiflavus , but this could be an artifact of a longer transit time in Z. longissimus , given its lower mean body temperature. These results allow a better understanding of the ability to coexist in snakes belonging to temperate climate colubrid communities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".