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Record W4408314295 · doi:10.3389/fmars.2025.1521526

How much time and who will do it? Organizing the toolbox of climate adaptations for small-scale fisheries

2025· article· en· W4408314295 on OpenAlexaff
Sieme Bossier, Yoshitaka Ota, Ana Lucía Pozas-Franco, Andrés M. Cisneros‐Montemayor

Bibliographic record

VenueFrontiers in Marine Science · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsToolboxFisheryScale (ratio)Climate changeEnvironmental resource managementFisheries scienceFisheries managementAdaptation (eye)GeographyEnvironmental scienceOceanographyComputer scienceFishingBiologyGeologyCartography

Abstract

fetched live from OpenAlex

Adaptation to climate impacts will be necessary for small-scale fisheries and fishers (SSFs) to safeguard their food security, livelihoods, and cultural heritage. SSFs are often vulnerable to environmental impacts due to the place-based, multi-scale and direct dependencies on local ecosystems, and generally fewer resources or abilities for relocation, diversification, and modification of their fishing practices. Strategic adaptation is therefore essential. This study emphasizes the timelines, requirements, and burdens of implementing existing and proposed adaptations, e.g., who pays, who does the work, and how long would it take? To categorize possible actions (tools) for analysis, we adapt the FAO climate adaptation framework and propose five areas of action: Institutional, Communication, Livelihood, Risk Resilience, and Science. Our results highlight two interconnected trends; first, the burdens and benefits of proposed climate adaptations are unevenly distributed, usually against fishers themselves. Second, there is a general lack of research focusing on the equity implications of current governance structures that de-emphasize fisher’s needs. This creates a lack of understanding among policy makers about the adaptation priorities of SSFs, and what resources or support they would need to implement them. We applied this framework to a case study involving octopus SSFs in Yucatán, Mexico. Interview results reinforce the finding that adaptation strategies that fishers thought would be most important for them (e.g. changes in policies/regulations to improve healthcare, reduce excess capacity, or reinforce fishing laws) were actions they could not often realize without external support; conversely, tools often proposed as “easier” by non-fishers (e.g. changing jobs, fishing gears, or going further out to sea) were not seen as particularly viable to fishers. Due to these mismatches, we argue there is a need to go beyond the classical focus on quantifying climate vulnerability towards a stronger emphasis on prioritizing adaptation strategies to meet the goals of fisherfolk themselves and aligning organizational and governance structures accordingly. The toolbox organization framework we propose can serve as an initial guidance for many fishing communities, decision makers and other stakeholders to anticipate implementation needs and find the right tools to adapt to future climatic conditions and prevent negative socioeconomic and ecological impacts.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.352
Threshold uncertainty score0.669

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.034
GPT teacher head0.270
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 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

Citations3
Published2025
Admission routes1
Has abstractyes

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