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Record W2971327900 · doi:10.1098/rsbl.2019.0284

Palaeo-trajectories of forest savannization in the southern Congo

2019· article· en· W2971327900 on OpenAlexafffund
Julie C. Aleman, Olivier Blarquez, Hilaire Elenga, Jordan Paillard, Victor Kimpuni, Gaubin Itoua, Gauthier Issele, A. Carla Staver

Bibliographic record

VenueBiology Letters · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversité de MontréalQuébec Science (Canada)
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaSigma Delta Epsilon-Graduate Women in Science
KeywordsBiomeEcologyContext (archaeology)EcosystemDisturbance (geology)Fire regimeVegetation (pathology)Climate changeBiologyPaleontology

Abstract

fetched live from OpenAlex

Tropical savannah and forest are thought to represent alternative stable states in ecosystem structure in some climates. The implication is that biomes are maintained by positive feedbacks, e.g. with fire, and that historical distributions could play a role in determining modern ones. In this context, climate alone does not govern transitions between biomes, and understanding the causes and pathways of such transitions becomes crucial. Here, we use a multi-proxy analysis of a 2000-year core to evaluate modes of transition in vegetation structure and fire regimes. We demonstrate a first transition ca 1540 BP, when a cyclic fire regime entered a forested landscape, eventually resulting, by ca 1060 BP, in a transition to a more open savannah-like or mosaicked structure. This pattern may parallel currently accelerating fire regimes in tropical forests suggesting that fires can savannize forests, but perhaps more slowly than feared. Finally, ca 540 BP, a drought combined with anthropogenic influences resulted in a conclusive transition to savannah, probably resembling the modern landscape in the region. We show here that fire interacted with drought to transition forest to savannah, suggesting that disturbance by fire can be a major driver of biome change.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.250

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 head0.006
GPT teacher head0.207
Teacher spread0.201 · 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

Citations14
Published2019
Admission routes2
Has abstractyes

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