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Record W2788615691 · doi:10.1088/1748-9326/aaac0c

Underestimation of the Tambora effects in North American taiga ecosystems

2018· article· en· W2788615691 on OpenAlexaffabout
Fabio Gennaretti, Étienne Boucher, Antoine Nicault, Guillermo Gea‐Izquierdo, Dominique Arseneault, Frank Berninger, Martine M. Savard, Christian Bégin, Joël Guiot

Bibliographic record

VenueEnvironmental Research Letters · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsGeological Survey of CanadaNatural Resources CanadaUniversité du Québec à RimouskiUniversité du Québec à Montréal
FundersH2020 Marie Skłodowska-Curie ActionsEuropean Commission
KeywordsTaigaBiosphereClimate changeEcosystemProxy (statistics)Physical geographyClimatologyForest ecologyEnvironmental scienceVolcanoGeographyEcologyForestryGeologyBiology

Abstract

fetched live from OpenAlex

The Tambora eruption (1815 AD) was one of the major eruptions of the last two millennia and has no equivalents over the last two centuries. Here, we collected an extensive network of early meteorological time series, climate simulation data and numerous, well-replicated proxy records from Eastern Canada to analyze the strength and the persistence of the Tambora impact on the regional climate and forest processes. Our results show that the Tambora impacts on the terrestrial biosphere were stronger than previously thought, and not only affected tree growth and carbon uptake for a longer period than registered in the regional climate, but also determined forest demography and structure. Increased tree mortality, four times higher than the background level, indicates that the Tambora climatic impact propagated to influence the structure of the North American taiga for several decades. We also show that the Tambora signal is more persistent in observed data (temperature, river ice dynamics, forest growth, tree mortality) than in simulated ones (climate and forest-growth simulations), indicating that our understanding of the mechanisms amplifying volcanic perturbations on climates and ecosystems is still limited, notably in the North American taiga.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.987

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 studies0.0000.001
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 head0.021
GPT teacher head0.268
Teacher spread0.247 · 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.

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

Citations15
Published2018
Admission routes2
Has abstractyes

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