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Record W2579759697 · doi:10.1002/2016gl072190

Urban heat island‐induced increases in evapotranspirative demand

2017· article· en· W2579759697 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.

Bibliographic record

VenueGeophysical Research Letters · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Heat Island Mitigation
Canadian institutionsMcGill University
FundersNational Science Foundation
KeywordsImpervious surfaceEnvironmental scienceUrban heat islandEvapotranspirationUrbanizationVegetation (pathology)Land coverGrowing seasonAtmospheric sciencesHydrology (agriculture)Land useEcologyGeographyMeteorologyGeology

Abstract

fetched live from OpenAlex

Abstract Although the importance of vegetation in mitigating the urban heat island (UHI) is known, the impacts of UHI‐induced changes in micrometeorological conditions on vegetation are not well understood. Here we show that plant water requirements are significantly higher in urban areas compared to rural areas surrounding Madison, WI, driven by increased air temperature with minimal effects of decreased air moisture content. Local increases in impervious cover are strongly associated with increased evapotranspirative demand in a consistent manner across years, with most increases caused by elevated temperatures during the growing season rather than changes in changes in growing season length. Potential evapotranspiration is up to 10% higher due to the UHI, potentially mitigating changes to the water and energy balances caused by urbanization. Our results indicate that local‐scale land cover decisions (increases in impervious cover) can significantly impact evapotranspirative demand, with likely implications for water and carbon cycling in urban ecosystems.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.672
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.047
GPT teacher head0.325
Teacher spread0.278 · 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