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Record W2281343810 · doi:10.2134/agronj2015.0484

Predicted Yield and Nutritive Value of an Alfalfa–Timothy Mixture under Climate Change and Elevated Atmospheric Carbon Dioxide

2016· article· en· W2281343810 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAgronomy Journal · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPasture and Agricultural Systems
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsForageYield (engineering)Climate changeAgronomyDry matterEnvironmental scienceGreenhouse gasPrecipitationCarbon dioxide in Earth's atmosphereCarbon dioxidePhleumLegumeGrowing degree-dayAnimal scienceBiologyEcologyGeographyPhenologyMeteorology

Abstract

fetched live from OpenAlex

Climate change studies have often focused on individual forage species although legume‐grass mixtures are predominant on dairy farms in northern areas of North America. We assessed the effect of (i) future climate conditions (temperature and precipitation) and elevated atmospheric CO 2 concentration ([CO 2 ]), separately and together, on yield of alfalfa ( Medicago sativa L.) and timothy ( Phleum pratense L.), grown alone or in mixture, and (ii) an adaptation strategy (timing and number of harvests) on future yield and nutritive value of an alfalfa–timothy mixture. Forage dry matter (DM) yield and nutritive value for two contrasting climate areas in eastern Canada were simulated with the Integrated Farm System Model over two future periods (2020–2049 and 2050–2079) using three climate models and two representative concentration pathways (RCP 4.5 and 8.5) of greenhouse gas emissions. Under projected future climate and without adaptation, annual forage yield of both species and the mixture increased in the colder area and decreased in the warmer area. In both areas, first‐cut yield increased due to faster growing degree‐day accumulation, while regrowth yield decreased due to greater water and temperature stresses. Under elevated [CO 2 ], annual yield and the alfalfa percentage in the mixture increased. When combining climate change and elevated [CO 2 ], yield increased, except with the more drastic scenario (RCP 8.5, 2050–2079) in the warmer area, and forage nutritive value was reduced. With adaptation, the mixture yield was increased from 5 to 35%, while nutritive value was generally maintained under all future scenarios, mostly because of additional cuts. Core Ideas In eastern Canada, colder areas will benefit the most from climate change. In future climate, water and temperature stresses will reduce forage summer regrowth. Elevated CO 2 will result in a higher yield increase in alfalfa than in timothy. When adapting harvest timing and number, annual forage mixture yield will increase. When adapting harvest timing and number, forage nutritive value will be maintained.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.887
Threshold uncertainty score0.206

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.016
GPT teacher head0.197
Teacher spread0.180 · 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