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Record W6967125300 · doi:10.5061/dryad.59zw3r26r

Data from: Indigenous knowledge of key ecological processes confers resilience to a small-scale kelp fishery

2021· dataset· en· W6967125300 on OpenAlexaffabout

Bibliographic record

VenueOpen MIND · 2021
Typedataset
Languageen
Field
Topic
Canadian institutionsFisheries and Oceans CanadaBell (Canada)Simon Fraser University
Fundersnot available
KeywordsIndigenousStewardship (theology)Ecological resilienceTraditional knowledgeKelpPsychological resilienceEnvironmental stewardshipKelp forest

Abstract

fetched live from OpenAlex

1. Feedbacks between social and ecological processes can lead to sustainable stewardship practices that support ecological resilience among harvested populations. This is evident along the world’s coast lines, where Indigenous knowledge systems have facilitated millennia of human nature coexistence. However, social-ecological conditions globally are quickly shifting, posing challenges for coastal Indigenous communities where customary harvest of ocean resources, such as kelps, need to adapt to growing markets, novel climates and changing governance regimes. Consequently, a pressing need exists to determine how specific ecological and social variables drive key dynamics within coupled human-ocean systems. 2. Motivated by the information needs of an Indigenous community on Canada’s Pacific Coast, we co-designed a traditional harvest experiment, field surveys, and semi-directed interviews with Indigenous resource users and managers to measure the ecological resilience of the feather boa kelp (Egregia menziesii) to harvest and determine what environmental variables most affected its recovery. We wove these results with information on current stewardship practices to inform future management of this slow growing perennial kelp based on Indigenous knowledge and western science. 3. We found that Egregia recovered from traditional harvest levels faster than expected with minimal impact on its productivity because plants sprouted new fronds. In fact, traditional harvest levels of Egregia mimicked natural frond loss. Indigenous knowledge and empirical ecological evidence revealed the importance of individual plant size, site-specific seawater temperature and wave exposure in driving Egregia recovery. Indigenous stewardship practices reflected these ecological relationships in the practice of selecting large plants from sites with healthy patches of Egregia. While we documented key social controls of harvest, current self-reported harvest levels of kelp fronds were 2 times greater than the stated social norm, but only 1.2 times greater in terms of kelp biomass. 4. Consequently, traditional harvest protocols facilitate Egregia recovery and promote its sustained use. However, its ecological resilience is susceptible to the erosion of customary practices and warming ocean temperatures. 5. Co-produced research that mobilizes multiple bodies of knowledge can enhance our understanding of social-ecological resilience, empower local decision makers, and democratize the science and practice of natural resource management.

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)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.064
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0290.006

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 head0.129
GPT teacher head0.366
Teacher spread0.237 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2021
Admission routes2
Has abstractyes

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