MétaCan
Menu
Back to cohort
Record W2794969033 · doi:10.1002/ecs2.2170

Transitional climate mortality: slower warming may result in increased climate‐induced mortality in some systems

2018· article· en· W2794969033 on OpenAlexaboutno aff
Brian Buma

Bibliographic record

VenueEcosphere · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsnot available
FundersU.S. Forest ServiceCalifornia Department of Fish and Wildlife
KeywordsClimate changeEnvironmental scienceTemperate climateLatitudeGlobal warmingClimatologyMortality rateClimate modelEcologyAtmospheric sciencesPhysical geographyGeographyBiologyDemographyGeology

Abstract

fetched live from OpenAlex

Abstract The potential for climate change to cause mass tree mortality in forested systems by pushing environmental conditions past physiological tolerance thresholds is well documented. Less well studied is damage and mortality associated with climatic transitions, where mortality is less on either side of the transition; the shift from freezing winter conditions to thawed winter conditions in temperate and high latitudes is a clear example. “Transitional climate mortality” is sporadic, but widespread, associated with exposure to mortality during these climatic transitions, and triggered by proximal weather events like a hard freeze after a period of above freezing temperatures. Interestingly, this suggests that slower warming could result in more intensive mortality because of extended exposure to potential mortality events. The concept is tested using a well‐studied species ( Callitropsis nootkatensis ) on the US /Canadian Pacific coast. To identify the transitional mortality zone, statistical modeling combined with a current mortality map and bioclimatic variables was used. This process identified the −5° to 0°C zone (mean temperature of the coldest month) as particularly associated with transitional mortality. Weather station data from multiple locations were used to validate observations. Four GCM s (General Circulation Model) and two future warming scenarios (representative concentration pathway 2.6 and 8.5) were used to estimate time and spatial extent of exposure at broad scales; slower warming results in more intensive cumulative exposure than faster warming. Finally, by combining the observed mortality zone with weather station data a generalizable binomial model was tested as a means to estimate potential future mortality. This model is applicable to any system where the transitional mortality zone (e.g., temperature range) and the frequency of proximal mortality triggers are known. This type of mortality phenomena has been understudied but may be a large driver of future forest change, given the frequency of mortality events and the ubiquity of the freeze–thaw transition across temperate systems globally.

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 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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.017
GPT teacher head0.249
Teacher spread0.232 · 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 teacher head, not a consensus.

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

Explore more

Same venueEcosphereSame topicPlant Water Relations and Carbon DynamicsFrench-language works237,207