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Record W2336922175 · doi:10.3389/fnbeh.2016.00077

The Australian Bogong Moth Agrotis infusa: A Long-Distance Nocturnal Navigator

2016· review· en· W2336922175 on OpenAlexaff
Eric J. Warrant, Barrie J. Frost, Ken Green, Henrik Mouritsen, David L. Dreyer, Andrea Adden, Kristina Brauburger, Stanley Heinze

Bibliographic record

VenueFrontiers in Behavioral Neuroscience · 2016
Typereview
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsQueen's University
FundersKungliga Fysiografiska Sällskapet i LundU.S. Air ForceVetenskapsrådetAir Force Office of Scientific ResearchSwedish Foundation for International Cooperation in Research and Higher Education
KeywordsNocturnalBiologyGeographyEcology

Abstract

fetched live from OpenAlex

The nocturnal Bogong moth (Agrotis infusa) is an iconic and well-known Australian insect that is also a remarkable nocturnal navigator. Like the Monarch butterflies of North America, Bogong moths make a yearly migration over enormous distances, from southern Queensland, western and northwestern New South Wales (NSW) and western Victoria, to the alpine regions of NSW and Victoria. After emerging from their pupae in early spring, adult Bogong moths embark on a long nocturnal journey towards the Australian Alps, a journey that can take many days or even weeks and cover over 1000 km. Once in the Alps (from the end of September), Bogong moths seek out the shelter of selected and isolated high ridge-top caves and rock crevices (typically at elevations above 1800 m). In hundreds of thousands, moths line the interior walls of these cool alpine caves where they "hibernate" over the summer months (referred to as "estivation"). Towards the end of the summer (February and March), the same individuals that arrived months earlier leave the caves and begin their long return trip to their breeding grounds. Once there, moths mate, lay eggs and die. The moths that hatch in the following spring then repeat the migratory cycle afresh. Despite having had no previous experience of the migratory route, these moths find their way to the Alps and locate their estivation caves that are dotted along the high alpine ridges of southeastern Australia. How naïve moths manage this remarkable migratory feat still remains a mystery, although there are many potential sensory cues along the migratory route that moths might rely on during their journey, including visual, olfactory, mechanical and magnetic cues. Here we review our current knowledge of the Bogong moth, including its natural history, its ecology, its cultural importance to the Australian Aborigines and what we understand about the sensory basis of its long-distance nocturnal migration. From this analysis it becomes clear that the Bogong moth represents a new and very promising model organism for understanding the sensory basis of nocturnal migration in insects.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.035
GPT teacher head0.323
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations123
Published2016
Admission routes1
Has abstractyes

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