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Record W4312727825 · doi:10.1071/wr22079

Abundance, demography, and harvesting of water snakes from agricultural landscapes in West Java, Indonesia

2022· article· en· W4312727825 on OpenAlexaff
Mirza Dikari Kusrini, Ramdani Manurung, Fata Habiburrahman Faz, Aristyo Dwiputro, Arief Tajalli, Huda Nur Prasetyo, Pramitama Bayu Saputra, Umar Fhadli Kennedi, Ditro Wibisono Parikesit, Richard Shine, Daniel J. D. Natusch

Bibliographic record

VenueWildlife Research · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsEcologyHabitatAbundance (ecology)GeographyContext (archaeology)PopulationFisheryBiologyWildlifeRange (aeronautics)

Abstract

fetched live from OpenAlex

Context Across much of its geographic range, the masked water snake, Homalopsis buccata, is harvested each year in large numbers, questioning the sustainability of that offtake. Aims To quantify abundance and demography of water snakes in anthropogenically disturbed habitats in an area of West Java, where these snakes are subject to intensive harvest. Methods We accompanied professional snake-collectors, and conducted our own surveys of ponds and irrigation canals, to record the numbers and attributes (species, sex, size, etc.) of snakes that were captured using a variety of methods. Key results Snakes of several species were abundant, with mean capture rates of 32 666 snakes km-1 of irrigation canals, and 57 501 snakes km-2 of fishponds (9500 and 43 788 for H. buccata alone). Sex ratios of H. buccata were female-biased in ponds but not irrigation channels. Ponds underlain by deeper mud contained more snakes. Collecting methods varied among habitat types, in a way that reduced collateral risk to commercially farmed fish in ponds. Conclusions These water snakes are extremely abundant in Java, despite high levels of historical and continuing harvest. The inference of low population sizes for H. buccata in Indonesia, as presented in the IUCN Red List, is erroneous. Implications An ability to utilise anthropogenic resource subsidies (in this case, fish farmed in village ponds) allows some native predator species to attain remarkably high abundances, and to withstand intense efforts at harvesting.

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 categoriesInsufficient 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 score0.028
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.022
GPT teacher head0.264
Teacher spread0.243 · 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

Citations8
Published2022
Admission routes1
Has abstractyes

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