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Record W3198050490 · doi:10.1080/17565529.2021.1971059

Adaptation to climate change induced water stress in major glacierized mountain regions

2021· article· en· W3198050490 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClimate and Development · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsClimate changeEnvironmental resource managementAdaptation (eye)Environmental planningTourismHydropowerBusinessStakeholderEnvironmental scienceNatural resource economicsGeographyPolitical scienceEconomics

Abstract

fetched live from OpenAlex

Mountains are a critical source of water. Cryospheric and hydrological changes in combination with socio-economic development are threatening downstream water security triggering the need for effective adaptation responses. Here, we present a global systematic review (83 peer-reviewed articles) that assesses different water-related stressors and the adaptation responses to manage water stress in major glaciated mountain regions. Globally, agriculture (42%), tourism (12%), hydropower (8%) and health and safety (4%) are among the main sectors affected by hydrological and cryospheric changes . A broad set of adaptation measures has already been implemented in the world’s mountain regions. We find that globally the most commonly used adaptation practices correspond to the improvement of water storage infrastructure (13%), green infrastructure (9.5%), agricultural practices (17%), water governance and policies (21%), disaster risk reduction (9.5%) and economic diversification (10%). Successful implementation of adaptation measures is limited by reduced stakeholder capacities, collaboration and financial resources, and policies and development. To overcome these limitations, funding for climate change adaptation and development programmes in mountains and trust-building measures such as shared stakeholder activities need to be strengthened. Local awareness raising of both, the adverse effects of climate change and potentially positive implications of specific adaptation measures can help to support successful adaptation.

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)0.000
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 score0.099
Threshold uncertainty score1.000

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 science0.0000.000
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 head0.066
GPT teacher head0.249
Teacher spread0.183 · 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