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Record W2797161355 · doi:10.2174/1874401x01811010001

Have Invasive Mysids (Mysis diluviana) Altered the Capacity of Osoyoos Lake, British Columbia to Produce Sockeye Salmon (Oncorhynchus nerka)?

2018· article· en· W2797161355 on OpenAlexafffundabout
Kim D. Hyatt, Donald J. McQueen, Athena D. Ogden

Bibliographic record

VenueThe Open Fish Science Journal · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsYork UniversityFisheries and Oceans Canada
FundersFisheries and Oceans CanadaWashington State University
KeywordsOncorhynchusPlanktivoreFisheryZooplanktonPredationTrophic levelBiologyForage fishBioenergeticsEcologyEnvironmental sciencePhytoplanktonNutrientFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Background: During 2005-13, at Osoyoos Lake, British Columbia, we investigated trophic relationships among fry ofOncorhynchus nerkaWalbaum (Sockeye and kokanee), a suite of limnetic planktivores includingMysis diluviana, and their zooplankton prey. Objectives: Our goal was to quantify the impacts that a recently introduced population ofMysiswould have on density, growth and survival of resident age-0 Sockeye Salmon. Methods: Evidence ofMysisimpact was based on (a) simple correlation analysis between various biophysical performance measures and (b) production and bioenergetics models used to identify the strength of bottom-up (i.e. production-driven) and top-down (i.e.consumption-driven) processes. Results: This nine-year study indicated that the Osoyoos Lake food web was strongly influenced by external events These included: large annual variations in river discharge, an earthen dam failure and effluent input from an Okanagan River tributary, and highly variable recruitment ofO. nerkafry given out-of-basin factors (harvest, marine survival) controlling adult salmon returns. Surprisingly, large annual variations inO. nerkarecruitment (0.63 - 7.0 million fry), did not induce significant “top-down” associations in growth, survival or subsequent production among the macro-planktivores (pelagic fish andMysis) and their zooplankton prey. A single significant correlation (p ≤ 0.05) betweenO. nerkafry abundance and their von BertalanffyW∞parameter emerged from a set of 14 potential top-down associations tested. By contrast, we identified several strongly positive “bottom-up” effects in which survival ofO. nerkafry was significantly associated (p ≤ 0.01) with annual variations in total zooplankton biomass,Daphniabiomass andEpischurabiomass. Our results indicate thatMysisplayed a dual role in the Osoyoos Lake pelagic food web. As predators, they accounted for an average (June-October) of 64% of the total prey biomass consumed by fish andMysis. As prey,Mysiscontributed an average of 35% of the prey biomass consumed by fish. Consumption by fish andMysistogether accounted for daily losses of only 4.5% of non-mysid zooplankton biomass and 34% of daily zooplankton production. Conclusion: We conclude that in all years, combined prey consumption byMysisand fish was never high enough, acting alone, to reduce the availability of their potential zooplankton forage base. However, we also estimate that in the absence ofMysis,O. nerkafry could experience a 43% increase in their daily food intake and that fish andMysismight control their principal prey taxa when exogenous factors (e.g.annual discharge) induced major reductions in zooplankton biomass. Finally, althoughMysishas clearly altered the energy flow pathways from plankton to fish in the Osoyoos Lake food-web, mysids have not precluded rebuildingO. nerkaabundance to levels at or exceeding historic maxima.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.693
Threshold uncertainty score0.611

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.249
Teacher spread0.225 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2018
Admission routes3
Has abstractyes

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