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Biometeorological feedbacks on peatlands: Raising the water table to reduce meteorologically-related stress on cattle

2024· article· en· W4404165711 on OpenAlexaff
Wanda Gherca, Inke Forbrich, Adrien Jacotot, Sara Knox, Paul Leahy, Ross Morrison, Torsten Sachs, Elke Eichelmann

Bibliographic record

VenueAgricultural and Forest Meteorology · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEffects of Environmental Stressors on Livestock
Canadian institutionsOkanagan University CollegeMcGill UniversityUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersBiological and Environmental ResearchSight Research UKOffice of ScienceUniversity of WaikatoNatural Environment Research CouncilU.S. Department of EnergyNational Science Foundation
KeywordsPeatEnvironmental scienceRaising (metalworking)Hydrology (agriculture)Water stressBiometeorologyMeteorologyGeographyEcologyAgronomyBiologyGeologyEngineeringGeotechnical engineering

Abstract

fetched live from OpenAlex

Peatland restoration is an important mitigation action in the fight against climate change. Researchers encourage farmers to rewet deep-drained lands on organic soil to a shallow water table depth (WTD) to reduce carbon emissions. Raising WTD under grasslands will likely affect local air temperature (TA) and increase relative humidity (RH), with uncertain consequences during heat waves on cattle welfare. We used WTD, TA and RH data (both measured between 1.25 and 2 m above ground) from 22 peatland sites globally to evaluate peatlands’ overall Temperature Humidity Index (THI), an indicator correlated to cattle welfare used in dairy farms (THI>68 increases heart rate, breathing rate and reduces milk yield). We compared them with THI at state weather stations located on neighbouring lands with short grass on non-organic soil, and assessed the impact of WTD. At most sites, peatlands with shallow WTD had lower TA, higher RH, and an overall lower THI than surrounding lands, compared to those with deep WTD. In most cases, THI decreased with increasing WTD, especially at night in the temperate region, except for coastal peatlands. Shallow and submerged sites had 20 % less hours with stressful meteorologic conditions (high THI) than surrounding areas. In contrast, the number of hours with high THI did not change significantly on peatlands with WTD under 20 cm below ground level compared to control sites. Our results confirm the influence of WTD on local temperature and THI, and suggest that raising WTD on drained peatlands will slightly improve cattle welfare with reduced THI during heat waves, but also acknowledge that local geographic characteristics add complexity to this relationship. Our research indicates that raising WTD to ground level in sections of grasslands could provide “heat wave shelters” and increase cattle resilience to climate change while contributing to the global reduction of carbon emissions.

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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.013
GPT teacher head0.223
Teacher spread0.210 · 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".

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Citations1
Published2024
Admission routes1
Has abstractyes

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