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Record W3125158233 · doi:10.1139/facets-2020-0027

Thermal sensitivity and flow-mediated migratory delays drive climate risk for coastal sockeye salmon

2021· article· en· W3125158233 on OpenAlexafffundvenue
William I. Atlas, Karl M. Seitz, Jeremy W.N. Jorgenson, Ben Millard‐Martin, William Housty, Daniel Ramos‐Espinoza, Nicholas J. Burnett, Mike Reid, Jonathan W. Moore

Bibliographic record

VenueFACETS · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsMcGill UniversityTula FoundationInStream Fisheries Research (Canada)Simon Fraser University
FundersHakai Institute
KeywordsOncorhynchusFish migrationWatershedFisheryEnvironmental scienceClimate changeStreamflowFish <Actinopterygii>GeographyOceanographyDrainage basinBiologyGeology

Abstract

fetched live from OpenAlex

Climate change is subjecting aquatic species to increasing temperatures and shifting hydrologic conditions. Understanding how these changes affect individual survival can help guide conservation and management actions. Anadromous Pacific salmon ( Oncorhynchus spp.) in some large river systems are acutely impacted by the river temperatures and flows encountered during their spawning migrations. However, comparatively little is known about drivers of en route mortality for salmon in smaller coastal watersheds, and climate impacts may differ across watersheds and locally adapted salmon populations. To understand the effects of climate on the survival of coastal sockeye salmon ( Oncorhynchus nerka; hísn in Haíɫzaqv), we tagged 1785 individual fish with passive integrated transponders across four migration seasons in the Koeye River—a low-elevation watershed in coastal British Columbia—and tracked them during their relatively short migration (∼13 km) from river entry to spawning grounds. Overall, 64.7% of sockeye survived to enter the spawning grounds, and survival decreased rapidly when water temperatures exceeded 15 °C. The best-fitting model included an interaction between river flow and temperature, such that temperature effects were worse when flows were low, and river entry ceased at the lowest flows. Results revealed temperature-mediated mortality and migration delays from low water that may synergistically reduce survival among sockeye salmon returning to coastal watersheds.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.595

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 head0.006
GPT teacher head0.202
Teacher spread0.196 · 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 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

Citations17
Published2021
Admission routes3
Has abstractyes

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