Darwin's finches and their diet niches: the sympatric coexistence of imperfect generalists
Bibliographic record
Abstract
Adaptive radiation can be strongly influenced by interspecific competition for resources, which can lead to diverse outcomes ranging from competitive exclusion to character displacement. In each case, sympatric species are expected to evolve into distinct ecological niches, such as different food types, yet this expectation is not always met when such species are examined in nature. The most common hypotheses to account for the coexistence of species with substantial diet overlap rest on temporal variation in niches (often diets). Yet spatial variation in niche overlap might also be important, pointing to the need for spatiotemporal analyses of diet and diet overlap between closely related species persisting in sympatry. We here perform such an analysis by characterizing the diets of, and diet overlap among, four sympatric Darwin's ground finch species at three sites and over 5 years on a single Galápagos island (Santa Cruz). We find that the different species have broadly similar and overlapping diets - they are to some extent generalists and opportunists - yet we also find that each species retains some 'private' resources for which their morphologies are best suited. Importantly, use of these private resources increased considerably, and diet overlap decreased accordingly, when the availability of preferred shared foods, such as arthropods, was reduced during drought conditions. Spatial variation in food resources was also important. These results together suggest that the ground finches are 'imperfect generalists' that use overlapping resources under benign conditions (in space or time), but then retreat to resources for which they are best adapted during periods of food limitation. These conditions likely promote local and regional coexistence.
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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 | 0.001 |
| 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".