Effect of anthropogenic light on bird movement, habitat selection, and distribution: a systematic map protocol
Bibliographic record
Abstract
Abstract Background Anthropogenic light is known or suspected to exert profound effects on many taxa, including birds. Documentation of bird aggregation around artificial light at night, as well as observations of bird reactions to strobe lights and lasers, suggests that light may both attract and repel birds, although this assumption has yet to be tested. These effects may cause immediate changes to bird movement, habitat selection and settlement, and ultimately alter bird distribution at large spatial scales. Global increases in the extent of anthropogenic light contribute to interest by wildlife managers and the public in managing light to reduce harm to birds, but there are no evidence syntheses of the multiple ways light affects birds to guide this effort. Existing reviews usually emphasize either bird aggregation or deterrence and do so for a specific context, such as aggregation at communication towers and deterrence from airports. We outline a protocol for a systematic map that collects and organizes evidence from the many contexts in which anthropogenic light is reported to affect bird movement, habitat selection, or distribution. Our map will provide an objective synthesis of the evidence that identifies subtopics that may support systematic review and knowledge gaps that could direct future research questions. These products will substantially advance an understanding of both patterns and processes associated with the responses of birds to anthropogenic light. Methods The protocol describes the steps taken to ensure the search for evidence is comprehensive, transparent and replicable. We will find relevant studies in the grey and peer-reviewed literature using publication databases, Google Scholar, stakeholder suggestions, and organizational websites. We will select studies for inclusion in the map by identification of relevant: (i) population including any species of bird; (ii) intervention or exposure to anthropogenic light; and (iii) outcomes including changes in bird movement, habitat occupancy, population density, or distribution. We will extract and organize metadata into a systematic map that can support subsequent search by interested individuals. The quantity of evidence on particular topics will be characterized through heat maps and narrative syntheses, but subsequent work will be needed to evaluate evidence validity.
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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 | 0.059 | 0.128 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.028 | 0.018 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.125 | 0.019 |
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".