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Record W1941742959 · doi:10.1002/wcc.127

Design of conservation strategies for climate adaptation

2011· article· en· W1941742959 on OpenAlex
Jonathan R. Mawdsley

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueWiley Interdisciplinary Reviews Climate Change · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsnot available
Fundersnot available
KeywordsVulnerability (computing)Climate changeEnvironmental resource managementAdaptive managementAdaptation (eye)GeographyWildlifeEnvironmental planningEcosystemWildlife conservationEcologyEnvironmental scienceBiologyComputer science

Abstract

fetched live from OpenAlex

Abstract A growing literature emphasizes the importance of managing the adverse effects of climate change on animal and plant species, biological communities, natural areas, and ecosystems. Although replete with general ‘climate adaptation’ strategies, this literature provides relatively limited guidance on translating these strategies into actionable conservation prescriptions. This review synthesizes information from the conservation planning and climate adaptation literature, including climate adaptation plans developed in Canada, England, México, South Africa, and USA, and presents elements of a general approach for developing actionable adaptation measures for wildlife species and conservation areas. Grounded in an adaptive management framework, this approach incorporates existing conservation tools for land and water protection, land and water management, species conservation, and monitoring, and also integrates new information from climate models, sensitivity analyses, and vulnerability assessments for species and ecosystems. WIREs Clim Change 2011 2 498–515 DOI: 10.1002/wcc.127 This article is categorized under: Climate, Ecology, and Conservation > Conservation Strategies

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.447
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0160.001

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 head0.243
GPT teacher head0.336
Teacher spread0.093 · 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