There’s no smoke without fire!
Notice bibliographique
Résumé
Amazon deforestation data are used as a gauge, at the national and international levels, to indicate the current situation of the political management of the control of and combat against this process, which is usually widely disseminated in the media.Due to the weakening of environmental policies in recent years, there was a forecast that deforestation for the year 2020 1 would be the highest of the decade, above that of 2019, which exceeded 10,800km 2 1 , the highest rate since 2008.Although 2020 had a slightly lower rate than 2019, deforestation in 2021 and 2022 exceeded 12,000km 2 2 , which again featured prominently in global media.Recently, the Yanomami crisis revealed another growing threat to Amazonian life: the push of mining activities in the region.Estimates point to increased mining rates mainly after 2010, and 2020 data showed that the total mining area exceeded the industrial mining area 3 .The negative impacts -beyond social and cultural ruptures caused to indigenous peoplesinclude increased disease rates, environmental contamination, and food insecurity 4 .The advance of deforestation reveals a small part of the socio-environmental problem related to the Amazonian forests.A recent study 5 quantified that fire, forest fragmentation and logging between 2001 and 2018 have already impacted more than 5.5% of the forests in the entire Amazon basin, and this extension corresponds to 112% of the total area deforested in that period.If we add to this list of forest degradation vectors the occurrence of extreme droughts, the area increases to 38% of the remaining Amazonian forests.It is widely known that fire is the main instrument for disposing of biomass after clear-cutting the forest, and that it causes a series of negative socioeconomic and environmental impacts.For example, on the global scale, greenhouse gas emissions from slash-and-burn practices and wildfires directly affect the rainfall and temperature regime and, on the regional scale, directly generate air pollution, thus affecting air quality 6,7 .Locally, the negative impacts of fires include the degradation of soils and forests, the imposition of restrictions and losses on those who depend on them, affecting their properties, public infrastructure or even services 8 .However, it is much less known that areas with forest fragmentation 9 , logging 10 , and forest areas that have already been affected by fire are more susceptible to new fires 11 .Moreover, extreme droughts, which have intensified and become more recurrent due to climate change 12 , amplify the extent and magnitude of fires 7 .This means that even if deforestation rates are controlled, there are still all the other forcings that lead to the occurrence of fires present in human practices and Amazonian landscapes 13 , and these have increased over this century 14 .
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,126 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».