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Record W4362587479 · doi:10.3390/w15071352

Hydropower Dam Development and Fish Biodiversity in the Mekong River Basin: A Review

2023· review· en· W4362587479 on OpenAlexfundno aff
Ian G. Baird, Zeb Hogan

Bibliographic record

VenueWater · 2023
Typereview
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersUniversity of AlbertaUnited States Agency for International Development
KeywordsBiodiversityHydropowerMekong riverThreatened speciesStructural basinFisheryPopulationGeographyEnvironmental scienceDrainage basinWater resource managementEcologyBiologyHabitat

Abstract

fetched live from OpenAlex

Over the last few decades, considerable concern has been expressed about the threat of Mekong River Basin hydropower dams to a range of important freshwater riverine fisheries, particularly for fish that seasonally migrate long distances. However, much less attention has been given to the threat of hydropower dams to fish biodiversity in the high-diversity Mekong River Basin, the focus of this paper. Through reviewing the existing state of knowledge regarding Mekong River Basin fish biodiversity, and threats to it, we argue that even though no species are definitively known to have been extirpated from the Mekong River Basin to date, hydropower dam development and various other developments nevertheless pose a serious threat to fish biodiversity. Indeed, dams typically significantly block fish migrations and fish larvae distribution, cause river fragmentation, fundamentally alter river hydrology, and change water quality, all factors that have the potential to intersect with each other and lead to significant species extirpation and extinction, or in some cases, functional extinction, when a small population remains but the important larger population is lost permanently. The circumstances are further exacerbated by the lag time between impact and when that impact becomes evident, cumulative impacts, a lack of consistent data collection, including the collection of base-line data, and insufficient post-project research related to biodiversity. We contend that much more could and should be done to ensure that the Mekong River basin’s exceptional fish biodiversity is not variously diminished and destroyed during the coming years.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.130
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)0.0010.005

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 head0.045
GPT teacher head0.264
Teacher spread0.219 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations32
Published2023
Admission routes1
Has abstractyes

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