Trophic niche differentiation mirrors intra-island population structure of Galápagos marine iguanas (Amblyrhynchus cristatus)
Bibliographic record
Abstract
Abstract Background: Differences in the trophic niche often underlie ecological specialization of individuals and can promote ecological speciation of populations, but studies showing a link between differences in the trophic niche and genetic differentiation of populations are rare. On the island of San Cristóbal (Galapágos archipelago), a strong genetic differentiation between two relatively proximate populations (subspecies; Amblyrhynchus cristatus mertensi and A. c. godzilla) of marine iguanas along the coastline has been observed. Here, we explore whether this genetic differentiation is mirrored in the iguanas’ trophic niche. Results: Although, no significant difference in the number of consumed algal taxa between subspecies were detected, the Schoener index exhibited low diet overlap between A. c. mertensi and A. c. godzilla. The latter was also demonstrated by the PERMANOVA analysis with significantly different diet OTU composition from the fecal samples between subspecies. Stable isotope analysis revealed that subspecies identity was overall more important than site for the iguanas’ resource use. Conclusions: By applying a metabarcoding approach on feces samples in combination with stable isotope analysis of skin sheds, we found that A. c. mertensi and A. c. godzilla differ in their ecological niches. Moreover, stable isotope analysis indicated that marine iguana populations have low spatial foraging distances, which, together with the diet partitioning patterns, might explain, at least partially, the lack of gene flow between these geographically proximate marine iguana populations. Key words: diet analysis, trophic niche, metabarcoding, stable isotopes, marine iguanas, Amblyrhynchus cristatus
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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) | 0.001 | 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".