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Record W2016300634 · doi:10.1111/fwb.12351

Movers and shakers: nutrient subsidies and benthic disturbance predict biofilm biomass and stable isotope signatures in coastal streams

2014· article· en· W2016300634 on OpenAlexafffund
Jennifer N. Harding, John D. Reynolds

Bibliographic record

VenueFreshwater Biology · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsSimon Fraser University
FundersHakai InstitutePacific Salmon FoundationTula Foundation
KeywordsBenthic zoneOncorhynchusEnvironmental scienceNutrientBiomass (ecology)Abiotic componentEcologySTREAMSFood webFisherySpawn (biology)Isotope analysisBiologyPredationFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Summary Nutrient subsidies and physical disturbance from migrating species can have strong impacts on primary producers. In the north Pacific, adult salmon ( O ncorhynchus spp.) transport marine‐derived nutrients back to freshwater streams and can also significantly disrupt the substratum during spawning events. We tested for effects of spawning pink ( O . gorbuscha ) and chum ( O . keta ) salmon on stream biofilm. Biofilm is a mix of algae, fungi and bacteria that provides food and habitat and forms the base of these aquatic food webs. We collected rock biofilm samples to compare stable isotopes and biomass prior to and following peak salmon spawning in 16 catchments on the central coast of B ritish C olumbia, C anada. We conducted two separate analyses. The first was a within‐stream comparison, which focused on 5 catchments that had a barrier to pink and chum salmon migration. The second was an among‐stream analysis that included all 16 catchments and explicitly considered biotic and abiotic factors, in addition to salmon density, known to influence biofilm growth and isotope ratios. Salmon density proved to be the best predictor of biofilm δ 15 N. Biofilm δ 13 C was best predicted by salmon density and catchment size. While spring chlorophyll a increased with mean salmon density, it was on average lower during spawning in the autumn, probably due to physical disturbance from spawning salmon. These results show that of the several variables considered to affect biofilm isotopes and biomass, salmon density and catchment size are among the most influential in coastal streams where salmon spawn.

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 score0.050
Threshold uncertainty score0.983

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 studies0.0000.001
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 head0.005
GPT teacher head0.192
Teacher spread0.187 · 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

Citations30
Published2014
Admission routes2
Has abstractyes

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