Effects of flood suppression on natricine snake diet and prey overlap
Bibliographic record
Abstract
Organisms may become adapted to disturbances when these disturbances occur periodically and at intermediate intensity. To investigate the effects of flood suppression, this study compared diet and competition of semi-aquatic snakes during flood (2000–2001) and no flood (2003–2005) years. Three natricine species, Nerodia erythrogaster (Forster in Bossu, 1771), Nerodia fasciata (L., 1766), and Thamnophis proximus (Say in James, 1823), were palpated for prey items in an east Texas floodplain under both conditions. Prey items were classified as crayfish, salamanders, anurans, or fish. Simpson’s diversity index of prey, frequency of consumed prey type, and prey importance values were compared between flood and no flood years. Pianka’s index of niche overlap was used to compare changes in diet overlap between species in the years with floods and those without. In the absence of floods, the number of prey types consumed by N. erythrogaster and T. proximus decreased. The frequency of prey types consumed during flood years was significantly different from the period of flood suppression for all three species. The order of prey importance also changed in the absence of floods for all three snake species. Without floods, diet overlap decreased between N. erythrogaster and the other two species; however, overlap between N. fasciata and T. proximus doubled.
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 | 0.000 | 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) | 0.001 | 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".