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Enregistrement W6970059048 · doi:10.5683/sp3/m0sunj

Plant Composition and Biomass Data

2023· dataset· en· W6970059048 sur OpenAlexaff

Notice bibliographique

RevueBorealis · 2023
Typedataset
Langueen
Domaine
Thématique
Établissements canadiensUniversity of Alberta
Organismes subventionnairesnon disponible
Mots-clésQuadratBiomass (ecology)Plant communitySampling (signal processing)Abundance (ecology)Context (archaeology)Vascular plant

Résumé

récupéré en direct d'OpenAlex

Summary: Vascular plant composition and biomass data collected for the AGGP AMP project. Detailed description of methods available within https://doi.org/10.1111/1365-2664.14181 and below. Composition data collected during 2017-2018, biomass data collected during 2018. To capture plant community responses to AMP grazing relative to regionally typical management, we established 0.5 × 0.5 meter quadrats in which we identified plant community abundances and biomass estimates. As outlined in Grenke et al. (2022), due to our prioritization of sampling many pairs of ranches rather than conducting intensive sampling within each ranch, rarefaction curves for each of our study sites did not saturate. Therefore, plant community measures should be considered on a relative rather than an absolute basis. To determine the potential for specific components of the plant community to influence biomass production we assessed community composition. Composition was sampled by randomly placing five quadrats within each of three landscape positions, for a total of 15 quadrats per study site. Sampling was stratified by topographic landscape position in order to capture potential topographically sourced heterogeneity, with landscape designations representative of relative positioning within the context of each ranch pair. Areas were designated as “low” if they occurred within the bottom third of a local relief, “high” if they occurred within the top third of the local relief, and “medium” if they occurred within the middle third of the landscape relief. To assess how vascular plant species composition may have influenced biomass production we recorded vascular plant species abundance (percent cover) at every site using a 0.5 meter × 0.5 meter quadrat. All non-senesced vascular plants within the quadrat were identified to species (USDA, NRCS 2021). Vascular plant species abundances were collected over two years, during the peak growing seasons of both 2017 and 2018, typically between June 15 and July 15. To reduce variance in our diversity estimates, we pooled data across the two years of sampling. Further details can be found in Grenke et al. (2022). 2.3.2. Plant community biomass estimates We measured plant biomass (aboveground biomass, litter mass, and roots from soil cores) using three randomly selected quadrats from each of the three landscape positions within the ranch (9 quadrats per ranch). Biomass data were taken from a randomly determined half of the plant composition quadrat (0.25 meter × 0.5 meter total). Plant biomass measures were collected during the peak growing season of 2018 at the same time as vascular plant species abundance sampling (June 15-July 15). Litter mass was removed using hand raking, followed by clipping all standing plants to ground level (aboveground biomass). Two soil cores (6 cm diameter, 15 cm deep) were then taken within the same area and pooled within a quadrat, with roots later sieved out and washed. All biomass and litter mass was dried to constant weight at 70°C, weighed, and standardized to g/m². The resulting root biomass measures were lower than would be reasonably expected from these systems (e.g., see Bork et al., 2019). This was likely due to extensive fine-root degradation in transport as well as breakage during the washing process. As such, root biomass measures represent the within-study relative treatment effects, not absolute indicators of total root biomass present. To measure aboveground biomass and biomass removal by livestock, we required approximate measures of plant growth with and without current-year grazing. The adaptive nature of ranch operations at our sites, as well as the geographic breadth of the sampling area, precluded us from systematically placing exclusion cages prior to grazing. Thus, at each plot, we installed an exclosure cage (1 × 1 meter) located 2 meters away from the non-exclosed plot a minimum of 2 weeks before plant community sampling. Biomass (aboveground, litter mass, and soil cores) and vascular plant species composition were sampled at the excluded and non-excluded sites within each pair. Subsequent analysis and discussion of biomass refer to those data collected from exclosure cages to mitigate the confounding influence of short-term grazing.

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)0,003
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: Jeu de données · Signal consensuel: Jeu de données
Score de désaccord entre enseignants0,094
Score d'incertitude au seuil0,315

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0070,008
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0020,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0940,064

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 Opus0,064
Tête enseignante GPT0,311
Écart entre enseignants0,247 · 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
GenreJeu de données

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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