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Record W6970059048 · doi:10.5683/sp3/m0sunj

Plant Composition and Biomass Data

2023· dataset· en· W6970059048 on OpenAlexaff

Bibliographic record

VenueBorealis · 2023
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsQuadratBiomass (ecology)Plant communitySampling (signal processing)Abundance (ecology)Context (archaeology)Vascular plant

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.094
Threshold uncertainty score0.315

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.008
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0940.064

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.064
GPT teacher head0.311
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2023
Admission routes1
Has abstractyes

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