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Record W4392589316 · doi:10.5194/egusphere-egu24-965

Resilience and adaptation of First Nations communities in Canada to disappearing winter road infrastructure in a changing climate

2024· preprint· en· W4392589316 on OpenAlexaboutno aff
Annette Salles, Donal Mullan, Matteo Spagnolo, Gemma Catney

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsnot available
Fundersnot available
KeywordsResilience (materials science)Adaptation (eye)Climate change adaptationClimate changeGeographyPsychological resilienceClimate resiliencePolitical scienceEnvironmental resource managementEnvironmental planningEconomic geographyRegional scienceEnvironmental sciencePsychologyOceanography

Abstract

fetched live from OpenAlex

In Canada’s North, winter roads serve as vital lifelines for remote First Nations communities, connecting them to essential resources and services. Constructed over seasonally frozen lakes, rivers, and land, these temporary roads are the only means to transport food, fuel and building materials in large volumes. Winter temperature increases of > 3° C in several provinces have already led to shorter operating seasons and less lake ice thickness, compromising safety, supply, and well-being.Limited meteorological data, a lack of economic or political relevance and the provincial jurisdiction over winter roads have so far discouraged broader research. The few localised studies leave a large knowledge gap with respect to the historical correlation of climate data with winter road seasons and the ability to predict their future. In addition, scientific studies rarely include the existing traditional environmental knowledge without which the adaptive capacity and resilience potential of Indigenous communities cannot be fully understood and realised.Using GIS tools to create a map of all Canadian winter road systems, ERA5 data to analyse location-specific temperature trends, and observations of lake ice thickness to validate a one-dimensional lake model as proxy for freezing trends all aim to explore the natural science base. Surveys and extended interviews in a Manitoba First Nations community complement the study in a decolonising approach, following the concept of Two-Eyed Seeing.Comprehensive mapping shows that most winter road tracks have recently been rerouted to avoid lake surfaces despite the difficult terrestrial underground. Temperature trends are highest in January and vary from +0.4° C in Ontario to +1° C per decade in the Northwest Territories, while modelled ice thickness has decreased between 9% and 14% from 1950 until 2022. Shorter winter road seasons have resulted in food insecurity, educational deprivation, and a housing crisis in many remote First Nations communities, worsened by the intergenerational trauma of residential schools and legislative hurdles to self-determination as defined by the UN Declaration on the Rights of Indigenous Peoples.For Indigenous communities in Canada, cryosphere services are not limited to winter road infrastructure, they include traditional food harvesting, cultural connectivity and identity. Without a profound connection to the land, change observations remain inconsequential, adaptive measures and resilience unobtainable.

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 score0.065
Threshold uncertainty score0.503

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 science0.0000.002
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 head0.009
GPT teacher head0.213
Teacher spread0.204 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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