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Record W3207195456 · doi:10.3389/fmars.2021.742209

Kelp in the Eastern Canadian Arctic: Current and Future Predictions of Habitat Suitability and Cover

2021· article· en· W3207195456 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueFrontiers in Marine Science · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsArcticNetUniversity of ManitobaUniversité LavalDalhousie UniversityCanadian Museum of NatureFisheries and Oceans Canada
FundersAustralian Research CouncilNatural Resources CanadaFisheries and Oceans CanadaNunavut Wildlife Management BoardMarine Environmental Observation Prediction and Response NetworkOcean Frontier InstituteNatural Sciences and Engineering Research Council of CanadaBelmont ForumCanada First Research Excellence FundArcticNetBiodiversa+
KeywordsKelp forestKelpHabitatArcticEcologyClimate changeBiodiversityEnvironmental scienceOceanographyMarine ecosystemFisheryMarine protected areaLaminariaEcosystemBiologyAlgaeGeology

Abstract

fetched live from OpenAlex

Climate change is transforming marine ecosystems through the expansion and contraction of species’ ranges. Sea ice loss and warming temperatures are expected to expand habitat availability for macroalgae along long stretches of Arctic coastlines. To better understand the current distribution of kelp forests in the Eastern Canadian Arctic, kelps were sampled along the coasts for species identifications and percent cover. The sampling effort was supplemented with occurrence records from global biodiversity databases, searches in the literature, and museum records. Environmental information and occurrence records were used to develop ensemble models for predicting habitat suitability and a Random Forest model to predict kelp cover for the dominant kelp species in the region – Agarum clathratum , Alaria esculenta , and Laminariaceae species ( Laminaria solidungula and Saccharina latissima ). Ice thickness, sea temperature and salinity explained the highest percentage of kelp distribution. Both modeling approaches showed that the current extent of arctic kelps is potentially much greater than the available records suggest. These modeling approaches were projected into the future using predicted environmental data for 2050 and 2100 based on the most extreme emission scenario (RCP 8.5). The models agreed that predicted distribution of kelp in the Eastern Canadian Arctic is likely to expand to more northern locations under future emissions scenarios, with the exception of the endemic arctic kelp L. solidungula , which is more likely to lose a significant proportion of suitable habitat. However, there were differences among species regarding predicted cover for both current and future projections. Notwithstanding model-specific variation, it is evident that kelps are widespread throughout the area and likely contribute significantly to the functioning of current Arctic ecosystems. Our results emphasize the importance of kelp in Arctic ecosystems and the underestimation of their potential distribution there.

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)0.001
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 score0.590
Threshold uncertainty score0.883

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.007
GPT teacher head0.198
Teacher spread0.191 · 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