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Record W2560347166

Habitat use by two tropical species of waterfowl in central Malaysia

2016· article· en· W2560347166 on OpenAlexfundno aff
Abdollah Salari, Mohamad Pauzi Zakaria, Mark S. Boyce

Bibliographic record

VenueWildfowl (Wildfowl & Wetlands Trust) · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
FundersUniversiti Putra MalaysiaUniversity of AlbertaDirectorate for Biological SciencesInstitut Penyelidikan Air Kebangsaan Malaysia
KeywordsHabitatWaterfowlEcologyGeographyAbundance (ecology)WetlandVegetation (pathology)Biology
DOInot available

Abstract

fetched live from OpenAlex

Two tropical species of waterfowl, the Lesser Whistling-duck (LWD) Dendrocygna javanica and Cotton Pygmy-goose (CPG) Nettapus coromandelianus, are patchily distributed across Malaysia and little is known about their habitat requirements. We studied patterns of habitat use for LWD and CPG at the Paya Indah Wetlands Reserve, Malaysia (c. 3,050 ha), by counting the birds from observation points and using a zero-altered negative binomial model to describe their abundance and distribution at the site. Habitat use by LWD and CPG was highly correlated; for instance both species frequented shallow, nutrient-rich lakes in the study area. Fine-scale measures of vegetation characteristics influenced local distribution, whereas a combination of anthropogenic activities and other habitat features best predicted abundance. Overall, LWD selected the more stable but densely-vegetated marshy shoreline while CPG used vegetated areas near the central deeper portions of the lake. Our habitat-selection models give insight into the ecology of LWD and CPG in Malaysia and can provide a tool for identifying areas for possible habitat restoration and conservation in the region.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score1.000

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 studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.009
GPT teacher head0.204
Teacher spread0.195 · 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.

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

Citations0
Published2016
Admission routes1
Has abstractyes

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