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Record W2555638114 · doi:10.2527/jam2016-0690

0690 Effects of native and tame grassland species reintroduction on carbon sequestration potential on the Canadian Prairies

2016· article· en· W2555638114 on OpenAlexaffabout
A. D. Iwaasa, B.G. McConkey, H. Wang

Bibliographic record

VenueJournal of Animal Science · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsGrasslandCarbon sequestrationAgroforestryEcologyBiologyCarbon dioxide

Abstract

fetched live from OpenAlex

Rising concentration of carbon dioxide in the atmosphere has prompted interest in implementing improved grassland management practices that could lead to a net accumulation of carbon in grassland soils. Converting cropland into native or tame perennial grasslands may result in substantial increase in soil C sequestration. Two studies were started in southern Saskatchewan where semiarid cropland was converted to perennial grasslands: Study 1 (2000–2014) seeded two different native pasture mixes (Simple, 7 species, and Diverse, 12 species) and Study 2 (2006–2011) seeded four different pasture types (meadow bromegrass + alfalfa [A], native grass mix [NG], NG + A, and NG + native legume). The objective of the studies was to determine the change in soil organic carbon (SOC) levels as affected by type of forage pasture mix and form of disturbance (grazing and nongrazing). In Study 1, the disturbance treatments were continuous, rotational, and nongrazing and the stocking rates were 0.8 and 1.9 animal unit (AU) ha−1, respectively. In Study 2, continuous grazing occurred and the stocking rate ranged from 2.0 to 4.0 AU ha−1 depending on which pasture treatment was used. All pastures were grazed to a utilization rate of 50 to 60%. Soil samples from each pasture were collected from three locations and at each location, a five radial (star pattern) sampling pattern occurred. From each of the five microsites, core samples were taken at five depths (0–7.5, 7.5–15, 15–30, 30–45, and 45–60 cm). Soil sampling for study 1 occurred in 2000, 2004, 2008, 2011, and 2014, whereas in study 2, it occurred in 2008 and 2011. In study 1, no SOC level (0–15 cm) differences were observed between disturbance and pasture mix combinations and interaction after 14 production years. Soil organic C levels were affected by year (P < 0.0001), which was expected with the different environmental conditions experienced among the different soil sampling years. In study 2, no SOC level (0–15 cm) differences were observed for interaction or main effects after three production years. Our studies did not support our hypothesis that a more diverse native mix (higher species richness) and tame grass + alfalfa would have higher SOC level than other treatments. Detecting small SOC change is difficult due to spatial heterogeneity in initial SOC, soil texture, bulk density, and plant productivity. Using our results, we develop criteria for measurement systems to detect changes design to detect SOC change.

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)0.001
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 score0.059
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.197
Teacher spread0.192 · 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
Published2016
Admission routes2
Has abstractyes

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