Mid‐elevation ecosystems of Panama: future uncertainties in light of past global climatic variability
Bibliographic record
Abstract
ABSTRACT Modern changes in regional climates will result in high ecosystem turnover and substantial biodiversity rearrangements. Understanding these changes requires palaeoecological studies at temporal resolutions comparable to the time window at which modern climate change is occurring. Here we present a multi‐proxy, high‐resolution record of forest and lake ecosystem change that occurred during the last 1100 years at middle elevations in Panama. From ∼900 to 1400 CE, regional forest and lake ecosystems were characterized by high seasonality, probably associated with both high El Niño activity and higher global temperatures. At ∼1400 CE, an abrupt transition marked the decoupling of forest and lake responses, with forest responding mostly to local patterns of human occupation, and lake trophic status being controlled mostly by the regional precipitation–evaporation balance, possibly associated with solar irradiance. Factors that played important roles in shaping regional ecosystems during the last 1100 years will probably again play critical roles within the coming decades, i.e. higher precipitation seasonality and higher temperatures. Past responses of the system, together with pervasive human activities, suggest that future conditions will simplify mid‐elevation forests. Given the importance of these geographical locations as hotspots of biological diversity, substantial losses of global biodiversity are foreseen.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".