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New views on an old forest: assessing the longevity, resilience and future of the Amazon rainforest

2005· article· en· W2171650299 on OpenAlexaff
Mark Maslin, Yadvinder Malhi, Oliver L. Phillips, Sharon A. Cowling

Bibliographic record

VenueTransactions of the Institute of British Geographers · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRainforestAmazon rainforestEcologyAmazonianGeographyTropical rainforestCenozoicAridGeologyPaleontologyBiology

Abstract

fetched live from OpenAlex

The aim of this paper is to investigate the longevity and diversity of the Amazonian rainforest and to assess its likely future. Palaeoclimate and palaeoecological records suggest that the Amazon rainforest originated in the late Cretaceous and has been a permanent feature of South America for at least the last 55 million years. The Amazon rainforest has survived the high temperatures of the Early Eocene climate optimum, the gradual Cenozoic cooling, and the drier and lower carbon dioxide levels of the Quaternary glacial periods. Two new theories for the great diversity of the Amazon rainforest are discussed – the canopy density hypothesis and the precessional‐forced seasonality hypothesis. We suggest the Amazon rainforest should not be viewed as a geologically ephemeral feature of South America, but rather as a constant feature of the global Cenozoic biosphere. The forest is now, however, entering a set of climatic conditions with no past analogue. The predicted future hotter and more arid tropical climates may have a disastrous effect on the Amazon rainforest.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.003
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.240
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 source (direct Gemma or distilled Codex), 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

Citations69
Published2005
Admission routes1
Has abstractyes

Explore more

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