Human-driven fire and vegetation dynamics on the Caribbean island of Barbuda from early indigenous to modern times
Bibliographic record
Abstract
We present a multiproxy analysis of a sediment core from Freshwater Pond, Barbuda, one of just a few inland paleoenvironmental records from the Lesser Antilles. Our results shed light on the relative contributions of climate variability and Pre- and Post-Columbian human activities to vegetation and fire dynamics on Barbuda. The presence of macroscopic charcoal and pollen of ethnobotanically-useful and disturbance-indicator plant taxa in the sediment record suggests that Pre-Columbian subsistence activities occurred within a few kilometers of the pond between ~150 BCE and ~1250 CE. Our record extends anthropogenic fires back into the early Ceramic (500 BCE–1500 CE) and possibly late Archaic Ages (3000–500 BCE) adding evidence to the timing of arrival of the island’s earliest inhabitants. The history of island-wide biomass burning inferred from microscopic charcoal fragments showed heightened fire activity between ~540 and ~1610 CE followed by a period of quiescence that reflected the transition from Pre- to Post-Columbian land-use practices associated with European colonization of the region. The British established a permanent settlement on Barbuda in the 1660s, but given Barbuda’s unsuitability for large-scale agriculture, timber harvesting, small-scale farming, and livestock rearing, activities that left no detectable charcoal footprints likely dominated post-colonial land use. The lack of any clear correspondence between the reconstructed histories of fire and effective moisture at Freshwater Pond supports the idea that Late-Holocene fire activity on Barbuda was driven primarily by human activity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".