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Record W4395449421 · doi:10.1016/j.gecco.2024.e02962

Mapping the distribution of the Sunda pangolin (Manis javanica) within natural forest in Sabah, Malaysian Borneo

2024· article· en· W4395449421 on OpenAlexaff
Elisa Panjang, Hong Ye Lim, Robert J. Thomas, Benoît Goossens, Andrew J. Hearn, David W. Macdonald, Joanna Ross, Seth T. Wong, Roshan Guharajan, Azlan Mohamed, Penny C. Gardner, Sharon Koh, Cheryl Cheah, Marc Ancrenaz, Isabelle Lackman, Robert C. Ong, Reuben Nilus, Alex Hastie, Jedediah F. Brodie, Alys Granados, Olga E. Helmy, Olivia Magritta Lapis, Donna Simon, Glyn Davies, Siew Te Wong, Mark Rampangajouw, Hisashi Matsubayashi, Chihiro Sano, Rebecca K. Runting, Symphorosa Sipangkui, Nicola K. Abram

Bibliographic record

VenueGlobal Ecology and Conservation · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversity of British Columbia
FundersYayasan Sime Darby
KeywordsPangolinGeographyEndangered speciesHabitatDistribution (mathematics)Critically endangeredAgroforestryNatural forestForestryEcologyBiology

Abstract

fetched live from OpenAlex

Pangolins are the most trafficked mammals in the world and are severely threatened by poaching the loss, degradation, and fragmentation of habitat. In Malaysian Borneo, conservation initiatives for the Sunda pangolin ( Manis javanica ) are hindered by a paucity of data on their distribution and population size. Using MaxEnt niche modelling and consolidated species location data, we projected the distribution of Sunda pangolins in Sabah. Additionally, we assessed the accessibility of their forest habitats to humans to understand potential threats. Our model indicated that, as of 2015, approximately half of Sabah’s land area (39,530 km²) is suitable for pangolins, with 43% in protected forests, 38% in production forests, and 19% outside of these areas. Alarmingly, our data suggest that nearly all (91%) of these suitable habitats are relatively easily accessible to poachers. Our findings provide a state-level baseline understanding of Sunda pangolin distribution and assess potential threats in Sabah. These can inform short- and long-term conservation management plans for pangolin to safeguard this critically endangered species.

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 score0.024
Threshold uncertainty score0.993

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 head0.008
GPT teacher head0.207
Teacher spread0.199 · 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
Published2024
Admission routes1
Has abstractyes

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