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Record W4408402676 · doi:10.3389/fmars.2025.1537498

Canopy-forming kelp forests persist in the dynamic subregion of the Broughton Archipelago, British Columbia, Canada

2025· article· en· W4408402676 on OpenAlexaffabout
Man Li, Raquel Barbosa, Luba Y. Reshitnyk, Lianna Gendall, Alena Wachmann, N. Dedeluk, U. Kim, Christopher J. Neufeld, Maycira Costa

Bibliographic record

VenueFrontiers in Marine Science · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsOkanagan University CollegeAssembly of First NationsUniversity of British Columbia, Okanagan CampusASL Environmental Sciences (Canada)University of British ColumbiaBamfield Marine Sciences CentreUniversity of Victoria
Fundersnot available
KeywordsArchipelagoKelpGeographyKelp forestCanopyOceanographyEnvironmental scienceEcologyGeologyBiologyArchaeology

Abstract

fetched live from OpenAlex

Canopy-forming kelp forests act as foundation species that provide a wide range of ecosystem services along temperate coastlines. With climate change, these ecosystems are experiencing changing environmental and biotic conditions; however, the kelp distribution and drivers of change in British Columbia remain largely unexplored. This research aimed to use satellite imagery and environmental data to investigate the spatiotemporal persistence and resilience of kelp forests in a dynamic subregion of cool ocean temperatures and high kelp abundance in the Broughton Archipelago, British Columbia. The specific objectives were to identify: 1) long-term (1984 to 2023) and short-term (2016 to 2023) kelp responses to environmental changes; and 2) spatial patterns of kelp persistence. The long-term time series was divided into three climate periods: 1984 to 1998, 1999 to 2014, and 2014 to 2023. The first transition between these periods represented a shift into cooler regional sea-surface temperatures and a negative Pacific Decadal Oscillation in 1999. The second transition represented a change into warmer temperatures (with more marine heatwaves and El Niño conditions) after 2014. In the long-term time series (1984 to 2023), which covered a site with Macrocystis pyrifera beds, kelp area increased slightly after the start of the second climate period in 1999. For the short-term time series (2016 to 2023), which focused on eight sites with Nereocystis luetkeana beds, most sites either did not change significantly or expanded in kelp area. This suggests that kelp areas remained persistent across these periods despite showing interannual variability. Thus, the dynamic subregion of the Broughton Archipelago may be a climate refuge for kelps, likely due to cool water temperatures that remain below both species’ upper thermal limits. Spatially, on a bed level, both species were more persistent in the center of the kelp beds, but across the subregion, Macrocystis had more persistent areas than Nereocystis, suggesting life history and/or other factors may be impacting these kelp beds differently. These findings demonstrate the spatiotemporal persistence of kelp forests in the dynamic subregion of the Broughton Archipelago, informing the management of kelp forest ecosystems by First Nations and local communities.

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 score0.016
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.003
GPT teacher head0.173
Teacher spread0.170 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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