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Record W4389977625 · doi:10.1029/2023rg000819

River Damming Impacts on Fish Habitat and Associated Conservation Measures

2023· article· en· W4389977625 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueReviews of Geophysics · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsHabitatClimate changeEnvironmental scienceFlood mythFish habitatFish <Actinopterygii>FisheryGlobal warmingHabitat destructionEnvironmental resource managementEcologyGeographyBiology

Abstract

fetched live from OpenAlex

Abstract River damming has brought great benefits to flood mitigation, energy and food production, and will continue to play a significant role in global energy supply, particularly in Asia, Africa, and South America. However, dams have extensively altered global river dynamics, including riverine connectivity, hydrological, thermal, sediment and solute regimes, and the channel morphology. These alterations have detrimental effects on the quality and quantity of fish habitat and associated impacts on aquatic life. Indeed, dams have been implicated in the decline of numerous fishes, emphasizing the need for effective conservation measures. Here, we present a global synthesis of critical issues concerning the impacts of river damming on physical fish habitats, with a particular focus on key fish species across continents. We also consider current fish conservation measures and their applicability in different contexts. Finally, we identify future research needs. The information presented herein will help support sustainable dam operation under the constraints of future climate change and human needs.

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.

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 score0.462
Threshold uncertainty score0.382

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 head0.031
GPT teacher head0.254
Teacher spread0.224 · 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