Size and spacing of grouse leks: comparing capercaillie (Tetrao urogallus) and black grouse (Tetrao tetrix) in two contrasting Eurasian boreal forest landscapes
Bibliographic record
Abstract
Capercaillie ( Tetrao urogallus L., 1758) and black grouse ( Tetrao tetrix L., 1758 (= Lyrurus tetrix (L., 1758))) are two sympatric Eurasian lekking grouse species that differ markedly in habitat affinities and social organization. We examined how size and spacing of leks in pristine (Russia) and managed (Norway) forests were related to habitat and social behavior. Leks of both species were larger and spaced farther apart in the pristine landscape. Capercaillie leks were regularly spaced at 2–3 km distance, increasing with lek size, which in turn was positively related to the amount of middle-aged and older forests in the surrounding area. Black grouse leks were irregularly distributed at shorter distances of 1–2 km, with lek size explained by the size of the open bog arena and the amount of open habitat in the surroundings. At the landscape scale, spatial distribution of open bogs and social attraction among male black grouse caused leks to be more aggregated, whereas mutual avoidance in male capercaillie caused leks to be spaced out. In the pristine landscape, large-scale and long-term changes in forest dynamics owing to wildfires, combined with an aggregated pattern of huge bog complexes, presumably provide both grouse species with enough time and space to build up bigger lek populations than in the managed landscape.
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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 | 0.001 | 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".