Influences of Movement Behavior on Animal Distributions at Edges of Homogeneous Patches
Bibliographic record
Abstract
We propose that changes in movement behavior may be a proximate mechanism that influences the accumulation of animals at habitat edges. We tested this idea with a combination of empirical and simulation experiments in a resource-free landscape. The movements of individual flour beetles,Tribolium confusum, were tracked across a paper arena edged with invisible tape until beetles crossed the edge. Movement behavior (step lengths and turn angles) and cumulative occupancy were analyzed according to distance from the edge. We found that beetles took smaller steps with larger turn angles near edges than in the center of the arena and that beetle distribution was highly biased towards the edge of the arena. We then tested two agent-based simulation models for each beetle: an edge-independent model and an edge-dependent model. Both models predicted less time spent at the edge than was observed. The proportion of time spent at edges depended on the propensity to cross the edge, which could not be explained by beetle body size or energetic condition. The distribution of animals with respect to habitat edges depends on many factors, but we suggest that proximate mechanisms such as movement behavior should be explicitly considered when interpreting animal distributions.
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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 | 0.001 |
| 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".