Data for "Effects of urbanization on local adaptation and eco-evolutionary feedbacks in white clover"
Notice bibliographique
Résumé
Data required for all analyses described in the paper “Effects of urbanization on selection, local adaptation, and eco-evolutionary feedbacks” (2025), testing how urban and rural environments affect the fitness and ecological interactions of white clover (Trifolium repens, L.; Fabaceae). Data is from a reciprocal transplant common garden experiment conducted in 2023 in the Greater Toronto Area, Canada using white clover from urban and rural populations and that either did or did not produce hydrogen cyanide (HCN). All analyses were conducted in R version 4.4.2 DATA FILES: 1. biomass_2023.csv contains dry end-of-season aboveground biomass data. Data Explanation: Source_Hab: Source population habitat of the white clover plant. U = urban (plant comes from an urban population), R = rural (plant comes from a rural population). Population_Num: Source population of the white clover plant, from Santangelo et al. 2020. Populations 1-5 are urban, populations 22-27 are rural. Plant_Num: Parent plant within each population. ID_Num: Individual number for plants from the same parent. Stolon: A or B, two stolon cuttings were taken from each plant to produce the final sample size. Tag_ID: Unique identifier for each plant, in the format Population Number - Plant Number - ID Number - Stolon HCN_Status: 0 or 1, 0 = does not produce HCN, 1 = does produce HCN. Site_Hab: Urban or Rural. Habitat of the common garden site where the plant was located. Site_ID: Common garden site name Dry_Biomass_g: biomass data in grams 2. leafarea.csv contains output from Easy Leaf Area analysis of leaf area data from May and July 2023, and May 2024, used to calculate growth rate. Data Explanation: filename: Unique identifier for each plant May_green: Number of green pixels identified by Easy Leaf Area in the May 2023 area photos May_red: Number of red pixels (coin for scale) identified by Easy Leaf Area in the May 2023 area photos May_leafarea: Leaf area (cm) calculated by Easy Leaf Area in the May 2023 area photos May_photodate: Date the area photo was taken in May 2023 Jul_green: Number of green pixels identified by Easy Leaf Area in the July 2023 area photos Jul_red: Number of red pixels (coin for scale) identified by Easy Leaf Area in the July 2023 area photos Jul_leafarea: Leaf area (cm) calculated by Easy Leaf Area in the July 2023 area photos Jul_photodate: Date the area photo was taken in July 2023 May24_green: Number of green pixels identified by Easy Leaf Area in the May 2024 area photos May24_red: Number of red pixels (coin for scale) identified by Easy Leaf Area in the May 2024 area photos May24_leafarea: Leaf area (cm) calculated by Easy Leaf Area in the May 2024 area photos May24_photodate: Date the area photo was taken in May 2024 3. survival_2023.csv contains overwinter survival data. Data Explanation: Source_Hab: Source population habitat of the white clover plant. U = urban (plant comes from an urban population), R = rural (plant comes from a rural population). Population_Num: Source population of the white clover plant, from Santangelo et al. 2020. Populations 1-5 are urban, populations 22-27 are rural. Plant_Num: Parent plant within each population. ID_Num: Individual number for plants from the same parent. Stolon: A or B, two stolon cuttings were taken from each plant to produce the final sample size. Tag_ID: Unique identifier for each plant, in the format Population Number - Plant Number - ID Number - Stolon HCN_Status: 0 or 1, 0 = does not produce HCN, 1 = does produce HCN. Site_Hab: Urban or Rural. Habitat of the common garden site where the plant was located. Site_ID: Common garden site name Survival_Sept2023: 0 or 1, 0 = not alive in September 2023 (end of field season), 1 = alive in September 2023. Survival_May2024: 0 or 1, 0 = not alive in May 2024, 1 = alive in May 2024 4. Flowers_2023.csv contains data on inflorescence production. Data Explanation: Source_Hab: Source population habitat of the white clover plant. U = urban (plant comes from an urban population), R = rural (plant comes from a rural population). Population_Num: Source population of the white clover plant, from Santangelo et al. 2020. Populations 1-5 are urban, populations 22-27 are rural. Plant_Num: Parent plant within each population. ID_Num: Individual number for plants from the same parent. Stolon: A or B, two stolon cuttings were taken from each plant to produce the final sample size. Tag_ID: Unique identifier for each plant, in the format Population Number - Plant Number - ID Number - Stolon HCN_Status: 0 or 1, 0 = does not produce HCN, 1 = does produce HCN. Site_Hab: Urban or Rural. Habitat of the common garden site where the plant was located. Site_ID: Common garden site name N_flowers_collected: Number of flower heads collected during seed collections N_Flowers_notcollected: Number of flower heads not collected (unripe at time of final harvest) Total_flowers: Total number of flower heads (sum of previous two columns) 5. seedmass_2023.csv contains seed mass data. Data Explanation: Source_Hab: Source population habitat of the white clover plant. U = urban (plant comes from an urban population), R = rural (plant comes from a rural population). Population_Num: Source population of the white clover plant, from Santangelo et al. 2020. Populations 1-5 are urban, populations 22-27 are rural. Plant_Num: Parent plant within each population. ID_Num: Individual number for plants from the same parent. Stolon: A or B, two stolon cuttings were taken from each plant to produce the final sample size. Tag_ID: Unique identifier for each plant, in the format Population Number - Plant Number - ID Number - Stolon HCN_Status: 0 or 1, 0 = does not produce HCN, 1 = does produce HCN. Site_Hab: Urban or Rural. Habitat of the common garden site where the plant was located. Site_ID: Common garden site name Seed_mass_g: mass of seeds produced in grams 6. herbivory.csv contains herbivory data. Herbivory was evaluated as the percentage of leaf area missing from each leaflet on three leaves per plant at two time points: July and August. Source_Hab: Source population habitat of the white clover plant. U = urban (plant comes from an urban population), R = rural (plant comes from a rural population). Population_Num: Source population of the white clover plant, from Santangelo et al. 2020. Populations 1-5 are urban, populations 22-27 are rural. Plant_Num: Parent plant within each population. ID_Num: Individual number for plants from the same parent. Stolon: A or B, two stolon cuttings were taken from each plant to produce the final sample size. Tag_ID: Unique identifier for each plant, in the format Population Number - Plant Number - ID Number - Stolon HCN_Status: 0 or 1, 0 = does not produce HCN, 1 = does produce HCN. Site_Hab: Urban or Rural. Habitat of the common garden site where the plant was located. Site_ID: Common garden site name Jul_Leaf1_leaflet1: Leaf area missing in July on Leaf 1, leaflet 1 Jul_Leaf1_leaflet2: Leaf area missing in July on Leaf 1, leaflet 2 Jul_Leaf1_leaflet3: Leaf area missing in July on Leaf 1, leaflet 3 Jul_Leaf2_leaflet1: Leaf area missing in July on Leaf 2, leaflet 1 Jul_Leaf2_leaflet2: Leaf area missing in July on Leaf 2, leaflet 2 Jul_Leaf2_leaflet3: Leaf area missing in July on Leaf 2, leaflet 3 Jul_Leaf3_leaflet1: Leaf area missing in July on Leaf 3, leaflet 1 Jul_Leaf3_leaflet2: Leaf area missing in July on Leaf 3, leaflet 2 Jul_Leaf3_leaflet3: Leaf area missing in July on Leaf 3, leaflet 3 Aug_Leaf1_leaflet1: Leaf area missing in August on Leaf 1, leaflet 1 Aug_Leaf1_leaflet2: Leaf area missing in August on Leaf 1, leaflet 2 Aug_Leaf1_leaflet3: Leaf area missing in August on Leaf 1, leaflet 3 Aug_Leaf2_leaflet1: Leaf area missing in August on Leaf 2, leaflet 1 Aug_Leaf2_leaflet2: Leaf area missing in August on Leaf 2, leaflet 2 Aug_Leaf2_leaflet3: Leaf area missing in August on Leaf 2, leaflet 3 Aug_Leaf3_leaflet1: Leaf area missing in August on Leaf 3, leaflet 1 Aug_Leaf3_leaflet2: Leaf area missing in August on Leaf 3, leaflet 2 Aug_Leaf3_leaflet3: Leaf area missing in August on Leaf 3, leaflet 3 Jul_Leaf1_Total: Mean leaf area missing in July on Leaf 1 Jul_Leaf2_Total: Mean leaf area missing in July on Leaf 2 Jul_Leaf3_Total: Mean leaf area missing in July on Leaf 3 Aug_Leaf1_Total: Mean leaf area missing in August on Leaf 1 Aug_Leaf2_Total: Mean leaf area missing in August on Leaf 2 Aug_Leaf3_Total: Mean leaf area missing in August on Leaf 3 Jul_Average: Mean percent leaf area missing across all leaves in July Aug_Average: Mean percent leaf area missing across all leaves in August Jul_VertHerb: Binary vertebrate herbivory in July (0 = no vertebrate herbivory; 1 = vertebrate herbivory). Vertebrate herbivory was assigned when at least 1 leaf was completely missing. Aug_VertHerb: Binary vertebrate herbivory in August (0 = no vertebrate herbivory; 1 = vertebrate herbivory). Vertebrate herbivory was assigned when at least 1 leaf was completely missing. Jul_InvertHerb: Binary invertebrate herbivory in July (0 = no invertebrate herbivory; 1 = invertebrate herbivory). Invertebrate herbivory was assigned when there was >1 and < 100% leaf area missing on at least 1 leaf. Aug_InvertHerb: Binary invertebrate herbivory in August (0 = no invertebrate herbivory; 1 = invertebrate herbivory). Invertebrate herbivory was assigned when there was >1 and < 100% leaf area missing on at least 1 leaf. Jul_Leaf1_Vert: Binary vertebrate herbivory in July (0 = no vertebrate herbivory; 1 = vertebrate herbivory) on leaf 1. Vertebrate herbivory was assigned when the leaf was completely missing. Jul_Leaf2_Vert: Binary vertebrate herbivory in July (0 = no vertebrate herbivory; 1 = vertebrate herbivory) on leaf 2. Vertebrate herbivory was assigned when the leaf was completely missing. Jul_Leaf3_Vert: Binary vertebrate herbivory in July (0 = no vertebrate herbivory; 1 = vertebrate herbivory)
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 | 0,000 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,021 | 0,001 |
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 ».