Data associated with "Spatially explicit modelling and prediction of shrub cover increase near Umiujaq, Nunavik"
Notice bibliographique
Résumé
These data are associated with the article "Spatially explicit modelling and prediction of shrub cover increase near Umiujaq, Nunavik", published in Ecological Monographs. They include field data, GPS locations, as well as land cover maps. A README file has been provided to explain the contents of each file. Abstract of the article : A circumpolar increase in shrub growth and cover has been underway in Arctic and subarctic ecosystems for the last few decades, but there is considerable spatial heterogeneity in this shrubification process. Although topography, hydrology and edaphic factors are known to influence shrubification patterns, a better understanding of the landscape-scale factors driving this phenomenon is needed to accurately predict its impacts on ecosystem function. In this study, we generated land cover change models in order to identify variables driving shrub cover increase near Umiujaq (Québec, Canada). Using land cover maps from 1990/1994 and 2010, we modelled observed changes using two contrasting conceptual approaches: binomial modelling of transitions to shrub dominance and multinomial modelling of all land cover transitions. Models were used to generate spatially explicit predictions of transition to shrub dominance in the near future as well as long-term predictions of the abundance of different land cover types. Model predictions were validated using both field data and current Landsat-derived trends of NDVI increase in the region in order to assess their consistency with observed patterns of change. We found that both variables related to topography and to vegetation were useful in modelling land cover changes occurring near Umiujaq. Shrubs tended to preferentially colonize low-elevation areas and moderate slopes, while their cover was more likely to increase in the vicinity of existing shrub patches. Deterministic realizations of the spatially explicit models of land cover change had a good predictive capability, although they performed better at predicting the proportion of different cover types than at predicting the precise location of the changes. Binomial models performed as well as multinomial models, indicating that neglecting land cover changes other than shrubification does not result in decreased prediction accuracy. The predicted probabilities of shrub increase in the region were consistent with patterns of change inferred from field data, but only partly supported by recent local increases in NDVI. Our findings increase the current understanding of the factors driving shrubification, while warranting further research on its impacts on ecosystem function and on the link between land cover changes and shifts in remotely sensed vegetation indices.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,059 | 0,011 |
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; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».