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Record W2044215707 · doi:10.1515/mammalia-2012-0110

Predicted distributions and conservation status of two threatened Southeast Asian small carnivores: the banded civet and Hose’s civet

2013· article· en· W2044215707 on OpenAlexaff
Andrew P. Jennings, John Mathai, Jedediah F. Brodie, Anthony J. Giordano, Géraldine Veron

Bibliographic record

VenueMammalia · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsThreatened speciesEvergreen forestGeographyEcologyHabitat destructionHabitatConservation statusNicheCarnivoreNear-threatened speciesFragmentation (computing)FrugivoreEvergreenBiologyPredation

Abstract

fetched live from OpenAlex

Abstract Knowledge of the distribution and habitat preferences of a species is of paramount importance when assessing its conservation status. We used accurately recorded occurrence records and ecological niche modelling to predict the distribution of two threatened and poorly known small carnivore species that occur in Southeast Asia, the banded civet ( Hemigalus derbyanus ) and Hose’s civet ( Diplogale hosei ), and analysed their spatial niche differentiation for habitat and elevation. We then identified possible anthropogenic threats, and used our modelling predictions to recommend surveying priorities. The predicted distribution of the banded civet was principally in lowland evergreen forest in southern Myanmar/Thailand, Peninsular Malaysia, Sumatra, Borneo and three Mentawai Islands (Siberut, Sipora and South Pagai), and for Hose’s civet in evergreen forest across the higher elevation regions of Borneo. Our niche analyses suggested that there is a tendency for these two species to separate spatially along an elevation gradient: the banded civet is mainly found in lowland areas, whereas Hose’s civet primarily occurs at higher elevations. Our study strongly indicated that these two viverrids are forest-dependent species that may be threatened by forest loss, degradation and fragmentation. Field surveys should be prioritised in areas where each species is predicted to occur and no records currently exist.

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 score0.006
Threshold uncertainty score0.853

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)0.0010.000

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 head0.011
GPT teacher head0.206
Teacher spread0.196 · 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

Citations19
Published2013
Admission routes1
Has abstractyes

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