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Record W2127007647 · doi:10.1071/wr09060

Predicting the ecological impact of cane toads (Bufo marinus) on threatened camaenid land snails in north-western Australia

2009· article· en· W2127007647 on OpenAlexaff
David Pearson, Matthew Greenlees, Georgia Ward‐Fear, Richard Shine

Bibliographic record

VenueWildlife Research · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsDepartment of Environment and Conservation
FundersAustralian Research Council
KeywordsThreatened speciesEcologyHabitatBiologyWildlife conservationIntroduced species

Abstract

fetched live from OpenAlex

The spread of cane toads (Bufo marinus) through north-western Australia may threaten populations of endemic camaenid land snails because these snails exhibit restricted geographic distributions, low vagility and ‘slow’ life-histories. We conducted laboratory trials to determine whether toads would consume camaenids if they encountered them, and conducted field surveys to evaluate the likelihood of such encounters (on the basis of habitat overlap). In laboratory trials with 13 camaenid species, cane toads were more likely to consume camaenids than were two species of native frogs that we tested (Cyclorana australis, Litoria caerulea). However, field surveys suggested that many camaenids are active on vertical surfaces in limestone outcrops, and cane toads rarely venture into these habitats. Although the preferred habitats and activity patterns of camaenids thus reduce their vulnerability to cane toads, we recommend regular surveys of toad and snail numbers to monitor toad impacts. Given the restricted distributions of threatened saxicoline camaenid species in the Kimberley, localised management of grazing stock and fire is feasible to maintain vine-thicket vegetation cover and snail populations, as well as reducing open habitats favoured by toads.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0010.000

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 head0.078
GPT teacher head0.374
Teacher spread0.296 · 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 designSimulation or modeling
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

Citations19
Published2009
Admission routes1
Has abstractyes

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