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Record W2157583132 · doi:10.1071/zo12068

The lizard fauna of litter mats in the stony desert of the southern Northern Territory

2012· article· en· W2157583132 on OpenAlexaff
Peter J. McDonald, Chris R. Pavey, Greg Fyfe

Bibliographic record

VenueAustralian Journal of Zoology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsDepartment of Environment and Conservation
Fundersnot available
KeywordsEcologyHerbivoreFaunaTramplingBiologyLitterHabitatThreatened speciesGrazing

Abstract

fetched live from OpenAlex

The formation of Australia’s stony deserts 2–4 million years ago will have reduced the availability of suitable habitat for lizards extant at that time, particularly for fossorial species. For such taxa, mats of litter, which form underneath woody vegetation, may offer the only suitable refuge sites in a greater matrix of unsuitable stony and compacted clay habitat. The integrity of litter mats in Australia’s stony deserts is potentially threatened by trampling by large introduced herbivores and by surface flows during flood events. Here we assess the importance of litter mats as habitat for lizards in these stony deserts and determine the suitability of the mats in relation to disturbance regimes. We surveyed 85 sites in the stony desert in the extreme south of the Northern Territory, using hand-raking as the sampling technique. We located 85 individuals of eight lizard species from three families, including 18 individuals of the nationally vulnerable monotypic pygopodid Ophidiocephalus taeniatus, establishing the significance of this limited microhabitat. Lizards were located underneath mats produced from the litterfall of four species of Acacia shrubs, though were not evenly distributed across these four mat types. Our results also provide the first evidence of the impact of large introduced herbivores on the suitability of litter mats. Although this was not statistically significant, lizards were more likely to be located at sites without disturbance from large herbivores, and were located only under individual mats that exhibited no sign of disturbance.

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)0.001
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 score0.008
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.017
GPT teacher head0.240
Teacher spread0.223 · 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

Citations9
Published2012
Admission routes1
Has abstractyes

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