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Record W2742739320 · doi:10.2527/asasann.2017.294

294 Productivity and carbon sequestration potential of reestablished native grassland in Canadian prairie following grazing

2017· article· en· W2742739320 on OpenAlexaffabout
Aklilu W. Alemu, A. D. Iwaasa, Roland Kröbel, B.G. McConkey

Bibliographic record

VenueJournal of Animal Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsGrazingPastureForageAgronomyGrasslandProductivityEnvironmental scienceBiomass (ecology)StockingLivestockAnimal scienceBiologyEcology

Abstract

fetched live from OpenAlex

Canadian native grasslands are recognized for providing high-quality forage for grazing livestock and wildlife. The objective of the study was to determine changes in pasture productivity and soil organic carbon (SOC) level as affected by type of forage pasture mix and grazing management. In 2001, pasture was established on 32 ha of land (16 paddocks of 2.1 ha) that was cropped since the 1920s. Treatments consisted of a completely randomized experimental design with 2 replicates: 2 pasture mixes (simple and diverse, with 7 and 12 species, respectively) and 2 grazing systems (continuous and deferred rotational grazing). Between 2005 and 2014, pasture was stocked with commercial yearling Angus steers (Bos taurus; 354 ± 13 kg) to an average stocking rate of 0.8 and 1.9 animal unit/ha for continuous and deferred rotational grazing, respectively. All pastures were grazed to an average utilization rate of 50 to 60%. Body weight was measured at the beginning and end of the grazing season. Available pasture yield was estimated by taking 10 representative 0.25-m2 quadrat samples. Soil samples (at 2 depths: 0–15 and 15–30 cm) were collected in the fall of 2000, 2004, 2008, 2011, and 2014. Data were analyzed using the mixed procedure of SAS and differences are discussed at P ≤ 0.05. Aboveground biomass and available pasture yield between simple and diverse pastures showed no difference but varied among the experimental years (P < 0.001). Available pasture was greater (P < 0.01) for rotational grazing (1,328 kg/ha) relative to continuous grazing (855 kg/ha), which increased the number of grazing days per hectare by 9% over the continuous grazing system (57 d/ha; P = 0.04). Conversely, ADG was 18% higher (P = 0.02) for continuous grazing than for rotational grazing (0.88 kg/d), which was likely related to higher OM digestibility and DE of pasture under continuous grazing. Total live weight production per hectare was slightly higher for the diverse pasture mix. Over the 10 yr of production, average SOC level was 5 (0–30 cm) and 9% (0–15 cm) higher for complex pasture on continuous grazing than on deferred rotational grazing (P < 0.01). Furthermore, SOC level was affected by year (P < 0.0001), which was expected, with the different environmental conditions experienced among the different soil sampling years. Overall, our study indicated that pasture diversity with grazing management affected productivity and SOC level of grazing lands.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.267
Teacher spread0.246 · 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 designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2017
Admission routes2
Has abstractyes

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