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Quantifying the potential effects of climate change and the invasion of smallmouth bass on native lake trout populations across Canadian lakes

2009· article· en· W2067534975 on OpenAlexafffundabout
Sapna Sharma, Donald A. Jackson, Charles K. Minns

Bibliographic record

VenueEcography · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversité de Montréal
FundersFisheries and Oceans CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsMicropterusTroutEcologyForage fishLake ecosystemClimate changeThreatened speciesSalvelinusFisheryIntroduced speciesElectrofishingFreshwater ecosystemInvasive speciesEnvironmental scienceBiological dispersalOverfishingEcosystemBiologyBass (fish)PopulationHabitatFishingPredationFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Climate change and invasive species are two stressors that should have large impacts on native species in aquatic and terrestrial ecosystems. We quantify and integrate the effects of climate change and the establishment of an invasive species (smallmouth bass Micropterus dolomieu ) on native lake trout Salvelinus namaycush populations. We assembled a dataset of almost 22 000 Canadian lakes that contained information on fish communities, lake morphologies, and geography. We examined the pelagic‐benthic and littoral forage fish community available to lake trout populations across three lake size classes in these aquatic ecosystems. Due to the decreased presence of alternate prey resources, lake trout populations residing in smaller lakes are more vulnerable to the effects of smallmouth bass establishment. A detailed spatially and temporally explicit approach to assess smallmouth bass invasion risk in Ontario lakes suggests that the number of Ontario lakes with vulnerable lake trout populations could increase from 118 (~1%) to 1612 (~20%) by 2050 following projected climate warming. In addition, we identified nearly 9700 lake trout populations in Canada threatened by 2100, by the potential range expansion of smallmouth bass. Our study provides an integration of two major stressors of ecosystems, namely climate change and invasive species, by considering climate‐change scenarios, dispersal rates of invasive species, and inter‐specific biotic interactions.

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 score0.574
Threshold uncertainty score0.588

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 head0.027
GPT teacher head0.249
Teacher spread0.222 · 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

Citations56
Published2009
Admission routes3
Has abstractyes

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