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Record W2905265363 · doi:10.1186/s13021-018-0114-4

Pasture enclosures increase soil carbon dioxide flux rate in Semiarid Rangeland, Kenya

2018· article· en· W2905265363 on OpenAlexaff
Collins Oduor, Nancy Karanja, Richard N. Onwonga, Stephen Mureithi, David E. Pelster, Gert Nyberg

Bibliographic record

VenueCarbon Balance and Management · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland Management and Livestock Ecology
Canadian institutionsAgriculture and Agri-Food Canada
FundersConsortium of International Agricultural Research CentersInternational Livestock Research InstituteImperial College LondonHarvard University
KeywordsPastureEnvironmental scienceRangelandGrazingGreenhouse gasVegetation (pathology)Soil carbonBiomass (ecology)Carbon sequestrationEnclosureSoil waterCarbon dioxideAgronomyHydrology (agriculture)AgroforestrySoil scienceEcologyBiology

Abstract

fetched live from OpenAlex

Pasture enclosures play an important role in rehabilitating the degraded soils and vegetation, and may also influence the emission of key greenhouse gasses (GHGs) from the soil. However, no study in East Africa and in Kenya has conducted direct measurements of GHG fluxes following the restoration of degraded communal grazing lands through the establishment of pasture enclosures. A field experiment was conducted in northwestern Kenya to measure the emission of CO 2 , CH 4 and N 2 O from soil under two pasture restoration systems; grazing dominated enclosure (GDE) and contractual grazing enclosure (CGE), and in the adjacent open grazing rangeland (OGR) as control. Herbaceous vegetation cover, biomass production, and surface (0–10 cm) soil organic carbon (SOC) were also assessed to determine their relationship with the GHG flux rate. Vegetation cover was higher enclosure systems and ranged from 20.7% in OGR to 40.2% in GDE while aboveground biomass increased from 72.0 kg DM ha −1 in OGR to 483.1 and 560.4 kg DM ha −1 in CGE and GDE respectively. The SOC concentration in GDE and CGE increased by an average of 27% relative to OGR and ranged between 4.4 g kg −1 and 6.6 g kg −1 . The mean emission rates across the grazing systems were 18.6 μg N m −2 h −1 , 50.1 μg C m −2 h −1 and 199.7 mg C m −2 h −1 for N 2 O, CH 4 , and CO 2 , respectively. Soil CO 2 emission was considerably higher in GDE and CGE systems than in OGR ( P < 0.001). However, non-significantly higher CH 4 and N 2 O emissions were observed in GDE and CGE compared to OGR ( P = 0.33 and 0.53 for CH 4 and N 2 O, respectively). Soil moisture exhibited a significant positive relationship with CO 2 , CH 4 , and N 2 O, implying that it is the key factor influencing the flux rate of GHGs in the area. The results demonstrated that the establishment of enclosures in tropical rangelands is a valuable intervention for improving pasture production and restoration of surface soil properties. However, a long-term study is required to evaluate the patterns in annual CO 2 , N 2 O, CH 4 fluxes from soils and determine the ecosystem carbon balance across the pastoral landscape.

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)0.000
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 score0.029
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.004
GPT teacher head0.195
Teacher spread0.191 · 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

Citations11
Published2018
Admission routes1
Has abstractyes

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