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Enregistrement W4210623669 · doi:10.1017/9781009157964.005

Polar Regions

2022· book-chapter· en· W4210623669 sur OpenAlexaboutno aff

Notice bibliographique

RevueCambridge University Press eBooks · 2022
Typebook-chapter
Langueen
DomaineEnvironmental Science
ThématiquePolar Research and Ecology
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPolarComputer scienceAction (physics)Content (measure theory)PhysicsMathematicsAstronomy

Résumé

récupéré en direct d'OpenAlex

This chapter assesses the state of physical, biological and social knowledge concerning the Arctic and Antarctic ocean and cryosphere, how they are affected by climate change, and how they will evolve in future.Concurrently, it assesses the local, regional and global consequences and impacts of individual and interacting polar system changes, and it assesses response options to reduce risk and build resilience in the polar regions.Key findings are:The polar regions are losing ice, and their oceans are changing rapidly.The consequences of this polar transition extend to the whole planet, and are affecting people in multiple ways.Arctic surface air temperature has likely 1 increased by more than double the global average over the last two decades, with feedbacks from loss of sea ice and snow cover contributing to the amplified warming.For each of the five years since the IPCC 5th Asesssment Report (AR5) (2014)(2015)(2016)(2017)(2018), Arctic annual surface air temperature exceeded that of any year since 1900.During the winters (January to March) of 2016 and 2018, surface temperatures in the central Arctic were 6ºC above the 1981-2010 average, contributing to unprecedented regional sea ice absence.These trends and extremes provide medium evidence 2 with high agreement of the contemporary coupled atmosphere-cryosphere system moving well outside the 20th century envelope.{Box 3.1; 3.2.1.1} The Arctic and Southern Oceans are continuing to remove carbon dioxide from the atmosphere and to acidify (high confidence).There is medium confidence that the amount of CO 2 drawn into the Southern Ocean from the atmosphere has experienced significant decadal variations since the 1980s.Rates of calcification (by which marine organisms form hard skeletons and shells) declined in the Southern Ocean by 3.9 ± 1.3% between 1998 and 2014.In the Arctic Ocean, the area corrosive to organisms that form shells and skeletons using the mineral aragonite expanded between the 1990s and 2010, with instances of extreme aragonite undersaturation.{3.2.1.2.4}Both polar oceans have continued to warm in recent years, with the Southern Ocean being disproportionately and increasingly important in global ocean heat increase (high confidence).Over large sectors of the seasonally ice-free Arctic, summer upper mixed layer temperatures increased at around 0.5ºC per decade during 1982-2017, primarily associated with increased absorbed solar radiation accompanying sea ice loss, and the inflow of ocean heat from lower latitude increased since the 2000s (high confidence).During 1970-2017, the Southern Ocean south of 30ºS accounted for 35-43% of the global ocean heat gain in the upper 1 In 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, e.g., 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. 2In 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, e.g., 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).the mass of glaciers.Important differences in the trajectories of loss emerge from 2050 onwards, depending on mitigation measures taken (high confidence).For stabilised global warming of 1.5ºC, an approximately 1% chance of a given September being sea ice free at the end of century is projected; for stabilised warming at a 2ºC increase, this rises to 10-35% (high confidence).The potential for reduced (further 5-10%) but stabilised Arctic autumn and spring snow extent by mid-century for Representative Concentration Pathway (RCP)2.6 contrasts with continued loss under RCP8.5 (a further 15-25% reduction to end of century) (high confidence).Projected mass reductions for polar glaciers between 2015 and 2100 range from 16 ± 7% for RCP2.6 to 33 ± 11% for RCP8.5 (medium confidence).{3.2.2; 3.3.2;3.4.2,Cross-Chapter Box 6 in Chapter 2}Both polar oceans will be increasingly affected by CO2 uptake, causing conditions corrosive for calcium carbonate shell-producing organisms (high confidence), with associated impacts on marine organisms and ecosystems (medium confidence).It is very likely that both the Southern Ocean and the Arctic Ocean will experience year-round conditions of surface water undersaturation for mineral forms of calcium carbonate by 2100 under RCP8.5;under RCP2.6 the extent of undersaturated waters are reduced markedly.Imperfect representation of local processes and sea ice interaction in global climate models limit the ability to project the response of specific polar areas and the precise timing of undersaturation at seasonal scales.Differences in sensitivity and the scope for adaptation to projected levels of ocean acidification exist across a broad range of marine species groups.{3.2.1; 3.2.2.3; 3.2.3}Future climate-induced changes in the polar oceans, sea ice, snow and permafrost will drive habitat and biome shifts, with associated changes in the ranges and abundance of ecologically important species (medium confidence).Projected shifts will include further habitat contraction and changes in abundance for polar species, including marine mammals, birds, fish, and Antarctic krill (medium confidence).Projected range expansion of subarctic marine species will increase pressure for high-Arctic species (medium confidence), with regionally variable impacts.Continued loss of Arctic multi-year sea ice will affect ice-related and pelagic primary production (high confidence), with impacts for whole ice-associated, seafloor and open ocean ecosystems.On Arctic land, projections indicate a loss of globally unique biodiversity as some high Arctic species will be outcompeted by more temperate species and very limited refugia exist (medium confidence).Woody shrubs and trees are projected to expand, covering 24-52% of the current tundra region by 2050.{3.2.2.1; 3.2.3;3.2.3.1;Box 3.4; 3.4.2;3.4.3}The projected effects of climate-induced stressors on polar marine ecosystems present risks for commercial and subsistence fisheries with implications for regional economies, cultures and the global supply of fish, shellfish, and Antarctic krill (high confidence).Future impacts for linked human systems depend on the level of mitigation and especially the responsiveness of precautionary management approaches (medium confidence).Polar regions support several of the world's largest commercial fisheries.Specific impacts on the stocks and economic value in both regions will depend on future climate change and on the strategies employed to manage the effects on stocks and ecosystems (medium confidence).Under high emission scenarios current management strategies of some high-value stocks may not sustain current catch levels in the future (low confidence); this exemplifies the limits to the ability of existing natural resource management frameworks to address ecosystem change.Adaptive management that combines annual measures and within-season provisions informed by assessments of future ecosystem trends reduces the risks of negative climate change impacts on polar fisheries (medium confidence).{3.2.4; 3.5.2;3.5.4}Responding to climate change in polar regions will be more effective if attention to reducing immediate risks (short-term adaptation) is concurrent with long-term planning that builds resilience to address expected and unexpected impacts (high confidence).Emphasis on short-term adaptation to specific problems will ultimately not succeed in reducing the risks and vulnerabilities to

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)0,001
score de la tête « metaresearch » (Gemma)0,002
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 enseignants0,283
Score d'incertitude au seuil0,948

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,002
Études des sciences et des technologies0,0020,001
Communication savante0,0040,003
Science ouverte0,0010,003
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,2830,190

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 Opus0,022
Tête enseignante GPT0,198
Écart entre enseignants0,176 · 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

Citations330
Publié2022
Routes d'admission1
Résumé présentoui

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