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Record W4414788419 · doi:10.1139/facets-2025-0060

Using climate change metrics to inform conservation of Canada's Priority Places for Species at Risk

2025· article· en· W4414788419 on OpenAlexaffvenueabout
Hsien‐Yung Lin, Max Ryan, Alaine F. Camfield, Matt Carlson, Matthieu Carrière, Calla Raymond, Ilona Naujokaitis‐Lewis

Bibliographic record

VenueFACETS · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsUniversity of British ColumbiaEnvironment and Climate Change Canada
Fundersnot available
KeywordsClimate changeFunction (biology)PrecipitationGlobal warmingEffects of global warming

Abstract

fetched live from OpenAlex

The Canadian federal government, in collaboration with the provinces and territories, agreed to implement the Pan-Canadian Approach to Transforming Species at Risk Conservation in Canada in 2018. Under this approach, 11 priority places were selected based on their biodiversity, concentrations of species at risk, and opportunities to advance conservation. Understanding the potential exposure of priority places to climate change is critical to inform effective conservation action. However, climate change makes threat assessments challenging because species respond in diverse and sometimes unpredictable ways to factors like rising temperatures and extreme weather events. We quantified potential changes across Canada's priority places using metrics representing multidimensional aspects of climate change. All priority places are projected to experience substantial change across multiple bioclimatic variables, but the nature of change differs. Annually, priority places in the west and east may experience higher precipitation, while central prairie priority places may become hotter and drier. Seasonally, western priority places may have hot and dry summers, while in the east, summer precipitation might increase and the highest temperature increase will occur during winter. Priority places with more complex topography may have capacity to function as climate refugia. These results will inform existing decision-making processes, threat assessments, and implementation of climate-informed conservation.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.474
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.074
GPT teacher head0.295
Teacher spread0.221 · 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.

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
Published2025
Admission routes3
Has abstractyes

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