Faithful pals and familiar locales: differentiating social and spatial site fidelity during reproduction
Bibliographic record
Abstract
Site fidelity-the tendency to reuse familiar spaces-is expected to improve fitness. Familiarity with the local environment is particularly crucial when resource demands or predation risk are high. Consequently, site fidelity often peaks during reproduction when energetic costs are high and offspring are vulnerable. For many species, the environment they experience is not solely a function of geography but also of the social environment. Social fidelity, the selection for familiar social environments, could constitute an independent or parallel strategy to spatial fidelity when considering behaviour at the spatial-social interface. Using global positioning system locations from caribou across Newfoundland, we tested whether females selected calving sites based on proximity to familiar conspecifics, in addition to geographical (spatial) fidelity. These strategies were synergistic, not alternative, and correlated across the population but more variable within individuals. We also tested whether either form of fidelity affected reproductive success. We failed to detect an effect of spatial or social fidelity on reproductive success in this population. Nevertheless, given the association between social and spatial fidelity and the demonstrated fitness consequences of site fidelity in other systems, familiar conspecifics and the potential benefits these social partners provide may be an underappreciated component driving site fidelity.This article is part of the theme issue 'The spatial-social interface: a theoretical and empirical integration'.
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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 | 0.004 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".