Effects of an introduced, novel prey on diet and reproduction in the diet-specialist European Starling (<i>Sturnus vulgaris</i>)
Bibliographic record
Abstract
Diet specialization has important consequences for how individuals or species deal with environmental change that causes changes in availability of prey species. We took advantage of a “natural experiment” — establishment of a commercial insect farm — that introduced a novel prey item, black soldier flies (Hermetia illucens (Linnaeus, 1758)), to the diet-specialist European Starling (Sturnus vulgaris Linnaeus, 1758). We investigated evidence for individual diet specialization (IDS) and the consequences of diet specialization and exploitation of novel prey on breeding productivity. In all 4 years of our study, tipulid larvae were the most common prey item. Soldier flies were not recorded in diets in 2013–2014; however, coincident with the establishment of the commercial insect farming operation, they comprised 22% and 30% of all prey items in the diets of European Starling females and males, respectively, in 2015. There was marked individual variation in use of soldier flies (4%–48% and 2%–70% in females and males, respectively), but we found little evidence of dichotomous IDS, i.e., where only some individuals have a specialized diet. We found no evidence for negative effects of use of soldier flies on breeding productivity: brood size at fledging and chick quality (mass, tarsus length) were independent of the number and proportion (%) of soldier flies returned to the nest.
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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 | 0.001 |
| 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".