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Pollen–plant–climate relationships in sub‐Saharan Africa

2006· article· en· W2019039879 on OpenAlexaff
J Watrin, Anne‐Marie Lézine, Konrad Gajewski, Annie Vincens

Bibliographic record

VenueJournal of Biogeography · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of Ottawa
FundersAgence Nationale de la Recherche
KeywordsPollenTaxonBiomeRange (aeronautics)Biological dispersalVegetation (pathology)EcologyClimate changeBiologyGeographyEcosystemPopulation

Abstract

fetched live from OpenAlex

Abstract Aim To demonstrate that incorporating the bioclimatic range of possible contributor plants leads to improved accuracy in interpreting the palaeoclimatic record of taxonomically complex pollen types. Location North Tropical Africa. Methods The geographical ranges of selected African plants were extracted from the literature and geo‐referenced. These plant ranges were compared with the pollen percentages obtained from a network of surface sediments. Climate‐response surfaces were graphed for each pollen taxon and each corresponding plant species. Results Several patterns can be identified, including taxa for which the pollen and plant distributions coincide, and others where the range limits diverge. Some pollen types display a reduced climate range compared with that of the corresponding plant species, due to low pollen production and/or dispersal. For other taxa, corresponding to high pollen producers such as pioneer taxa, pollen types display a larger climatic envelope than that of the corresponding plants. The number of species contained in a pollen taxon is an important factor, as the botanical species included in a taxon may have different geographical and climate distributions. Main conclusions The comparison between pollen and plant distributions is an essential step towards more precise vegetation and climate reconstructions in Africa, as it identifies taxa that have a high correspondence between pollen and plant distribution patterns. Our method is a useful tool to reassess biome reconstructions in Africa and to characterize accurately the vegetation and climate conditions at a regional scale, from pollen data.

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 score0.021
Threshold uncertainty score0.383

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.217
Teacher spread0.195 · 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

Citations38
Published2006
Admission routes1
Has abstractyes

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