Global artificial light masks biologically important light cycles of animals
Bibliographic record
Abstract
We document the importance of low‐light conditions in 136 animal species and then translate the new world atlas of skyglow, which reports artificial night sky brightness, into estimates of anthropogenic illuminance (that is, artificial light reaching Earth's surface). Quantifying habitat illuminance from skyglow facilitates understanding of the disruption of natural light cycles, such as new moon conditions, which are critical to animal ecology. We corroborated this transformation of sky brightness by comparing concurrent field measurements of skyglow and illuminance. We then quantified global artificial illuminance caused by skyglow, finding that skyglow artificially doubled illuminance of new moon conditions—a critical phase for biological processes, such as foraging, courtship, and mating—for 22.9% of the Earth's terrestrial surface, 51.0% of Key Biodiversity Areas, 77.1% of Global Protected Areas, and ~20% of highly diverse areas for mammals, birds, and amphibians. We provide summaries of artificial illuminance at 750‐m pixel resolution for each protected area to aid land managers and guide policy in reducing skyglow in areas that may yield the greatest benefits for conserving animal biodiversity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".