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Enregistrement W4210731414 · doi:10.1017/9781009157964.004

High Mountain Areas

2022· book-chapter· en· W4210731414 sur OpenAlexaboutno aff

Notice bibliographique

RevueCambridge University Press eBooks · 2022
Typebook-chapter
Langueen
DomaineEnvironmental Science
ThématiqueEnvironmental and Cultural Studies in Latin America and Beyond
Établissements canadiensnon disponible
Organismes subventionnairesUniversität InnsbruckUniversidad de Buenos AiresConsejo Nacional de Investigaciones Científicas y Técnicas
Mots-clésComputer science

Résumé

récupéré en direct d'OpenAlex

The cryosphere (including, snow, glaciers, permafrost, lake and river ice) is an integral element of high mountain regions, which are home to roughly 10% of the global population.Widespread cryosphere changes affect physical, biological and human systems in the mountains and surrounding lowlands, with impacts evident even in the ocean.Building on the IPCC's 5th Assessment Report (AR5), this chapter assesses new evidence on observed recent and projected changes in the mountain cryosphere as well as associated impacts, risks and adaptation measures related to natural and human systems.Impacts in response to climate changes independently of changes in the cryosphere are not assessed in this chapter.Polar mountains are included in Chapter 3, except those in Alaska and adjacent Yukon, Iceland and Scandinavia, which are included in this chapter. Observations of cryospheric changes, impacts, and adaptation in high mountain areasObservations show general decline in low-elevation snow cover (high confidence 1 ), glaciers (very high confidence) and permafrost (high confidence) due to climate change in recent decades.Snow cover duration has declined in nearly all regions, especially at lower elevations, on average by 5 days per decade, with a likely 2 range from 0-10 days per decade.Low elevation snow depth and extent have declined, although year-to-year variation is high.Mass change of glaciers in all mountain regions (excluding the Canadian and Russian Arctic, Svalbard, Greenland and Antarctica) was very likely -490 ± 100 kg m -2 yr -1 (-123 ± 24 Gt yr -1 ) in 2006-2015.Regionally averaged mass budgets were likely most negative (less than -850 kg m -2 yr -1 ) in the southern Andes, Caucasus and the European Alps/Pyrenees, and least negative in High Mountain Asia (-150 ± 110 kg m -2 yr -1 ) but variations within regions are strong.Between 3.6-5.2 million km 2 are underlain by permafrost in the eleven high mountain regions covered in this chapter corresponding to 27-29% of the global permafrost area (medium confidence).Sparse and unevenly distributed measurements show an increase in permafrost temperature (high confidence), for example, by 0.19ºC ± 0.05ºC on average for about 28 locations in the European Alps, Scandinavia, Canada and Asia during the past decade.Other observations reveal decreasing permafrost thickness and loss of ice in the ground.{2.2.2, 2.2.3, 2.2.4}Glacier, snow and permafrost decline has altered the frequency, magnitude and location of most related natural hazards (high confidence).Exposure of people and infrastructure to natural hazards has increased due to growing population, tourism and 1 In this report, the following summary terms are used to describe the available evidence: limited, medium, or robust; and for the degree of agreement: low, medium or high.A level of confidence is expressed using five qualifiers: very low, low, medium, high and very high, and typeset in italics, for example, medium confidence.For a given evidence and agreement statement, different confidence levels can be assigned, but increasing levels of evidence and degrees of agreement are correlated with increasing confidence (see Section 1.9.2 and Figure 1.4 for more details).2In this report, the following terms have been used to indicate the assessed likelihood of an outcome or a result: Virtually certain 99-100% probability, Very likely 90-100%, Likely 66-100%, About as likely as not 33-66%, Unlikely 0-33%, Very unlikely 0-10% and Exceptionally unlikely 0-1%.Additional terms (Extremely likely: 95-100%, More likely than not >50-100% and Extremely unlikely 0-5%) may also be used when appropriate.Assessed likelihood is typeset in italics, for example, very likely (see Section 1.9.2 and Figure 1.4 for more details).This Report also uses the term 'likely range' to indicate that the assessed likelihood of an outcome lies within the 17-83% probability range. High Mountain Areas Chapter 2 2Enablers and response options to promote adaptation and sustainable development in high mountain areasThe already committed and unavoidable climate change affecting all cryosphere elements, irrespective of the emission scenario, points to integrated adaptation planning to support and enhance water availability, access, and management (medium confidence).Integrated management approaches for water across all scales, in particular for energy, agriculture, ecosystems and drinking water supply, can be effective at dealing with impacts from changes in the cryosphere.These approaches also offer opportunities to support social-ecological systems, through the development and optimisation of storage and the release of water from reservoirs (medium confidence), while being cognisant of potential negative implications for some ecosystems.Success in implementing such management options depends on the participation of relevant stakeholders, including affected communities, diverse knowledge and adequate tools for monitoring and projecting future conditions, and financial and institutional resources to support planning and implementation (medium confidence).{2.3.1, 2.3.3,2.4} Effective governance is a key enabler for reducing disaster risk, considering relevant exposure factors such as planning, zoning, and urbanisation pressures, as well as vulnerability factors such as poverty, which can challenge efforts towards resilience and sustainable development for communities (medium confidence).Reducing losses to disasters depend on integrated and coordinated approaches to account for the hazards concerned, the degree of exposure, and existing vulnerabilities.Diverse knowledge that includes community and multi-stakeholder experience with past impacts complements scientific knowledge to anticipate future risks.{CCB-1, 2.3.2,2.4}International cooperation, treaties and conventions exist for some mountain regions and transboundary river basins with potential to support adaptation action.However, there is limited evidence on the extent to which impacts and losses arising from changes in the cryosphere are specifically monitored and addressed in these frameworks.A wide range of institutional arrangements and practices have emerged over the past three decades that respond to a shared global mountain agenda and specific regional priorities.There is potential to strengthen them to also respond to climate-related cryosphere risks and open opportunities for development through adaptation (limited evidence, high agreement).The Sustainable Development Goals (SDGs), Sendai Framework and Paris Agreement have directed some attention in mountain-specific research and practice towards the monitoring and reporting on targets and indicators specified therein.{2.3.1, 2.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,216
Score d'incertitude au seuil0,721

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,002
Études des sciences et des technologies0,0010,000
Communication savante0,0020,001
Science ouverte0,0010,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,2160,044

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,010
Tête enseignante GPT0,169
Écart entre enseignants0,159 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations216
Publié2022
Routes d'admission1
Résumé présentoui

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