Local and global climate signals from tree rings of<i>Parkinsonia praecox</i>in La Guajira, Colombia
Bibliographic record
Abstract
Abstract Land use change and climate change have been increasingly contributing to loss or reduction of biological and economic productivity of arid lands. The dry climate and physiographic characteristics of the Peninsula of La Guajira on the Colombian Caribbean coast are considered to be crucial drivers of the loss of vegetative cover and soil erosion; however, little knowledge exists on long‐term changes in climate in the area. This study presents a tree‐ring chronology fromParkinsonia praecox(18 trees, 45 radii) that allows the reconstruction of local and global climate drivers spanning the last 63 years. Tree‐ring width was strongly correlated with rainfall and wind data, indicating that annual tree growth was closely related to local climatic variability. The chronology also strongly correlated with an index of ENSO severity (El Niño Southern Oscillation), suggesting that large‐scale climatic phenomenon also have important influence onParkinsoniagrowth. To further investigate rainfall‐growth relationships, climate data series of annual rainfall and rainfall from September to November (SON), the rainiest months, were reconstructed using transfer functions. These data series did not exhibit a clear trend of change in rainfall over the last 63 years. The transfer functions reconstructed the total annual rainfall (R2= 0.8), and SON (R2= 0.7). This study constitutes the first attempt to reconstruct climatic patterns in Colombia with techniques of dendrochronology, and demonstrates the potential ofParkinsonia praecoxfor studying climatic patterns along the American subtropics, ranging from Mexico to Argentina. Copyright © 2011 Royal Meteorological Society
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".