Experimental evidence for an ideal free distribution in a breeding population of a territorial songbird
Bibliographic record
Abstract
According to the ideal despotic distribution (IDD), dominant individuals gain a fitness advantage by acquiring territories that are of higher quality, thereby forcing other individuals into lower quality habitat. In contrast, the ideal free distribution (IFD) predicts that local density is a function of habitat quality, but that individuals achieve the same fitness in different habitat types as a result of density‐dependent variation in territory size. Although the IFD represents an alternative, population dynamics of territorial species are generally expected to be driven by an IDD. We tested the predictions of IFD and IDD by monitoring the demographic response of the Ovenbird (Seiurus aurocapilla) to selection harvesting (30–40% tree removal) during the first five years postharvest in five pairs of 25‐ha study plots, each comprising a control (undisturbed) and a treatment (harvested plot). In the first year following harvesting, Ovenbird territory size increased in treatment plots relative to controls, whereas density, productivity per unit area, and the abundance of litter invertebrates decreased. Treatment effects declined consistently as stands regenerated, and most effects were no longer significant by the fifth year postharvest. However, there was no treatment effect on daily nest survival rate nor on per capita productivity. These results are consistent with the IFD, whereby similar per capita productivity is achieved across habitat types through density adjustments facilitated by changes in territory size. To our knowledge, this is the first study providing evidence for an IFD in a territorial bird species.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".