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Record W2147456467 · doi:10.3389/fgene.2014.00334

Butterflies of the high-altitude Atacama Desert: habitat use and conservation

2014· article· en· W2147456467 on OpenAlexaff
Emma Despland

Bibliographic record

VenueFrontiers in Genetics · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLepidoptera: Biology and Taxonomy
Canadian institutionsConcordia University
Fundersnot available
KeywordsEcologyHabitatButterflyVegetation (pathology)WetlandAltitude (triangle)EndemismGeographyEcotoneFaunaBiology

Abstract

fetched live from OpenAlex

The butterfly fauna of the high-altitude desert of Northern Chile, though depauperate, shows high endemism, is poorly known and is of considerable conservation concern. This study surveys butterflies along the Andean slope between 2400 and 5000 m asl (prepuna, puna and Andean steppe habitats) as well as in high and low-altitude wetlands and in the neoriparian vegetation of agricultural sites. We also include historical sightings from museum records. We compare abundances between altitudes, between natural and impacted sites, as well as between two sampling years with different precipitation regimes. The results confirm high altitudinal turnover and show greatest similarity between wetland and slope faunas at similar altitudes. Results also underscore vulnerability to weather fluctuations, particularly in the more arid low-altitude sites, where abundances were much lower in the low precipitation sampling season and several species were not observed at all. Finally, we show that some species have shifted to the neoriparian vegetation of the agricultural landscape, whereas others were only observed in less impacted habitats dominated by native plants. These results suggest that acclimation to novel habitats depends on larval host plant use. The traditional agricultural environment can provide habitat for many, but not all, native butterfly species, but an estimation of the value of these habitats requires better understanding of butterfly life history strategies and relationships with host plants.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score0.291

Codex and Gemma teacher scores by category

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.202
Teacher spread0.192 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations17
Published2014
Admission routes1
Has abstractyes

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