Fine-scale movement decisions of tropical forest birds in a fragmented landscape
Bibliographic record
Abstract
The persistence of forest-dependent species in fragmented landscapes is fundamentally linked to the movement of individuals among subpopulations. The paths taken by dispersing individuals can be considered a series of steps built from individual route choices. Despite the importance of these fine-scale movement decisions, it has proved difficult to collect such data that reveal how forest birds move in novel landscapes. We collected unprecedented route information about the movement of translocated forest birds from two species in the highly fragmented tropical dry forest of Costa Rica. In this pasture-dominated landscape, forest remains in patches or riparian corridors, with lesser amounts of living fencerows and individual trees or "stepping stones." We used step selection functions to quantify how route choice was influenced by these habitat elements. We found that the amount of risk these birds were willing to take by crossing open habitat was context dependent. The forest-specialist Barred Antshrike (Thamnophilus doliatus) exhibited stronger selection for forested routes when moving in novel landscapes distant from its territory relative to locations closer to its territory. It also selected forested routes when its step originated in forest habitat. It preferred steps ending in stepping stones when the available routes had little forest cover, but avoided them when routes had greater forest cover. The forest-generalist Rufous-naped Wren (Campylorhynchus rufinucha) preferred steps that contained more pasture, but only when starting from non-forest habitats. Our results showed that forested corridors (i.e., riparian corridors) best facilitated the movement of a sensitive forest specialist through this fragmented landscape. They also suggested that stepping stones can be important in highly fragmented forests with little remaining forest cover. We expect that naturally dispersing birds and species with greater forest dependence would exhibit even stronger selection for forested routes than did the birds in our experiments.
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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 | 0.000 |
| 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) | 0.000 | 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".