Dataset from the project entitled HimFunDiff. Related to research article: Global warming alters Himalayan alpine shrub growth dynamics and climate sensitivity.
Notice bibliographique
Résumé
We examined a total of 9 populations of Rhododendron anthopogon, which were located between 3200 m and 4200 m above sea level (asl). These populations were distributed across three geographically distant transects, with each transect consisting of three sites (along an elevation gradient). The transects are referred to as northern, intermediate, and southern, while the sites at each transect are categorized as low, mid, and high (as depicted in Thakur et al 2024). The northern transect exhibited colder temperatures and lower rainfall compared to the other two transects. On the other hand, the two remaining transects had relatively similar temperatures, but the southernmost transect received higher levels of precipitation. The mean annual temperature of these populations ranged from 2 °C to 5 °C from 2021 through 2022, while volumetric soil moisture levels varied from 0.198 to 0.377 based on onsite measurements using TMS4 dataloggers (Wild et al., 2019). We collected a total of 81 wood disc samples, with 9 samples obtained from each of the 9 sites studied (9 populations × 9 discs). The samples were collected by cutting a single piece from the thickest stem segment, approximately 5 cm in length, from 81 different mature and healthy individuals. Within each site, the 9 samples were obtained from three separate plots (three samples per plot), each covering an area of approximately 100 m2. The selection criteria for these plots included: (1) the presence of Rhododendron anthopogon as one of the dominant species; (2) minimal anthropogenic disturbance; and (3) the absence of large shrubs or trees. The sampled individuals within a plot were spaced at least 5 m apart from each other, and the plots themselves were at least 20 m apart. To prevent rapid drying, the cut stem samples were immediately placed in a wet paper towel. Within 48 hours of sampling, the stem samples underwent dehydration by being immersed in 50 % ethanol for the initial 3 days, followed by 70 % ethanol for the subsequent 7 to 10 days. After the ethanol dehydration process, the samples were air-dried for 72 hours and then stored in paper bags until further processing. Plant age and growth data for each of the sampled individuals were obtained following established protocols (Doležal et al., 2018). In the laboratory, we utilized a sledge microtome to cut cross-sections from each stem sample. These cross-sections were then stained with Astra Blue and Safranin and permanently affixed to microscope slides using Canada Balsam (Doležal et al., 2022). High-resolution images of the fixed sections were captured using an Olympus BX53 microscope equipped with an Olympus DP73 camera. The software CellSense Entry 1.9 was employed to analyse the best image obtained from each individual. We measured annual radial growth increments from pith to bark to the nearest micrometre. More details are given in the article entitled Global warming alters Himalayan alpine shrub growth dynamics and climate sensitivity. https://doi.org/10.1016/j.scitotenv.2024.170252
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 | 0,001 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,045 | 0,024 |
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 ».