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Record W4413283051 · doi:10.1080/23308249.2025.2543806

The Sleeping Giant of Kalimantan: A Review of Fish and Fisheries of the Peatlands

2025· review· en· W4413283051 on OpenAlexaff
Kirsty L. Nash, Dwi Atminarso, Jessica Blythe, Andi Chadijah, Septiana Sri Astuti, Agus Djoko Utomo, Boby Bagja Pratama, Bayu Kreshna Adhitya Sumarto, Gunawan Muhamad, Indah Lestari Surbani, Arif Wibowo

Bibliographic record

VenueReviews in Fisheries Science & Aquaculture · 2025
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicAquatic life and conservation
Canadian institutionsBrock University
FundersAustralian Centre for International Agricultural Research
KeywordsPeatFisheryFish <Actinopterygii>GeographyEnvironmental scienceBiologyArchaeology

Abstract

fetched live from OpenAlex

The extensive peatlands of Kalimantan, recognized for the critical ecosystem services they provide, are subject to broadscale degradation through land use change, deforestation, drainage and fire. An often-overlooked component of these peatlands are the fish and fisheries, which are central to local livelihoods. Here, a comprehensive review details the state of knowledge within the English and Indonesian literature on the importance, vulnerabilities and trajectories of fish communities and fisheries across Kalimantan. There is evidence that the fish communities are diverse, exhibit high levels of endemism and vary considerably among watersheds and seasons, but characterization of fish assemblages is incomplete. Peatland degradation is impacting fish communities, however, there are considerable gaps in understanding how changes are playing out, both among locations and in relation to different pressures. Fisheries play an important role in many, particularly Dayak, communities, providing a key source of protein, income, and cultural identity. Of particular concern are the impacts of increased fishing pressure and peatland drainage on fish stocks and fisheries yields. Restoration efforts may help reverse these declines, however, for restoration to be successful, initiatives must account for local perspectives and the importance of fisheries livelihoods. Finally, eight research priorities are presented, relating to fish ecology and fisheries livelihoods, essential for developing a comprehensive understanding of the peatland fish and fisheries of Kalimantan.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.941
Threshold uncertainty score0.495

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.054
GPT teacher head0.288
Teacher spread0.234 · 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 designOther design
Domainnot available
GenreReview

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
Published2025
Admission routes1
Has abstractyes

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