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Record W4416466464 · doi:10.5194/bg-22-7079-2025

Evidence for highly variable land use but a stable climate in the southwest Maya lowlands

2025· article· en· W4416466464 on OpenAlexaff
Benjamin Keenan, Kevin J. Johnston, Andy Breckenridge, Peter Douglas

Bibliographic record

VenueBiogeosciences · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsUniversité de MontréalMcGill University
Fundersnot available
KeywordsMesoamericaLand usePopulationClimate changeMayaBefore PresentLand coverLand use, land-use change and forestry

Abstract

fetched live from OpenAlex

Abstract. The lowland Maya of Mesoamerica were affected by multiple environmental stresses throughout their history, and many experienced a major demographic and political decline, or collapse, during a period of inferred intense multidecadal drought, approximately 1200- and 1000-years BP. Given regional variation in the timing and character of the collapse (Demarest, 2004; Hodell et al., 2007; Webster et al., 2007; Kennett and Beach, 2014; Douglas et al., 2015), much remains to be discovered about the complex interactions between climate and society in the Maya lowlands. To this end, we combine carbon and hydrogen isotopic analyses of leaf wax n-alkanes with quantification of faecal stanols and polycyclic aromatic hydrocarbons from a lake sediment core from the southwest lowlands to assess whether (1) palaeoecological evidence of land use is related to population change; and (2) whether population and land use are linked to changing precipitation. Our data reveal a transition from generally more intense fire use and C4 plant agriculture during the Preclassic (3500–2000 BP) to dense populations and reduced fire use during the Classic (1600–1000 BP). This is consistent with other evidence for a more urbanised and specialised society in the Classic. We do not find evidence of drought in the hydrogen isotope leaf wax record (δDlw), implying that local drought was not a primary driver of observed variability in land use or population change in the Classic-period southwestern lowlands.

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 score0.012
Threshold uncertainty score0.998

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 studies0.0010.001
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 head0.042
GPT teacher head0.246
Teacher spread0.204 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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