Bibliographic record
Abstract
If you were to take a stroll along the beaches of Newfoundland in late summer, it would not be uncommon to stumble upon a lost Atlantic puffin fledgling, Fratercula arctica, known as pufflings. For these avian adventurers, it is a rite of passage to venture out alone into the night to find their way over the open ocean. But for many, these maiden flights are cut short as they are drawn towards the glow of human settlements, leaving them stranded on land. Given the increasing coastal development near puffin breeding colonies and the Eastern Atlantic puffin population's continual decline, Taylor Brown from Trent University, Canada, and colleagues decided to find out how artificial light at night impacts puffin fledglings as they embark on their maiden voyage.Brown and colleagues tested how the youngsters reacted when they encountered a brightly lit area. Over the course of 11 nights in August 2022, the team flooded a 50 m stretch of beach opposite the Gull Island puffin colony with bright white LED light. Then they monitored pufflings with night vision binoculars, tracking the progress of 136 youngsters as they flew across the illuminated beach. Many of the pufflings flew either along the shoreline or headed back inland, with the researchers rescuing youngsters that became stranded. In contrast, when the team monitored a nearby dark beach during the same time, only two pufflings passed by. The irresistible pull of the ever-growing glow of coastal developments could have dire consequences for the already dwindling Eastern Atlantic puffin population.Conversion to energy-efficient LED streetlights is changing the colour of the Newfoundland nightscape, so the team investigated which light colours stranded pufflings were most attracted to. First, they built an arena from metal and plastic boxes, with a dark foyer leading to a choice of two corridors illumined with various forms of light (including warm white light produced by sodium lamps, cool white LEDs, warm white LEDs, warm white LEDs with an orange filter and cool white LEDs with a blue filter) or darkness. Then, working alongside the local ‘Puffin Patrol’ – a team of volunteers that rescue pufflings throughout stranding season – Brown visited puffling stranding ‘hotspots’, collecting waylaid youngsters before placing individuals in the foyer of the arena and giving them 13 min to decide which of the two corridors they wished to occupy. The pufflings were always drawn to the light, but, contrary to the team's expectations, had no preference between blue, orange or white light.However, when the pufflings were placed in a larger light-filled arena, the type of lighting drastically changed their behaviour. The team could see and hear the puffling's clawed feet tapping as they walked about and flew under the sodium lights, but the birds stopped traversing the arena under LED light and froze most under cool white LEDs. Brown acknowledges that the blue-tinged white light of LEDs might scare the youngsters, causing them to halt, but the team observed the pufflings preening during these quiet moments, suggesting that they might, instead, find the bluer light calming.It seems that these seabirds cannot resist the lure of artificial lights of any kind, so there might not be any alternative light source in the Newfoundland nightscape that can reduce puffling strandings. However, the puffling's love for light may help them in the end, with Brown suggesting that light beacons could lure wayward puffins toward ‘Puffin Patrol’ beaches where they can be safely seen back out to sea.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".