Ecohydrological Response of a Tropical Peatland to Rainfall Changes Driven by Intertropical Convergence Zone Variability
Bibliographic record
Abstract
ABSTRACT Aim Tropical peatlands are globally significant carbon stores, increasingly threatened by human activities and climate change. However, their ecohydrological responses to shifting water availability remain poorly understood. In this study, we investigate the connections between climate change, hydrology and vegetation dynamics in a coastal tropical peatland in Panama, aiming to understand the effects of future drying on peatland dynamics. Location Bocas del Toro, Panama (9°22′54″N, 82°21′59″W). Taxon Angiosperms. Methods High‐resolution multiproxy palaeoecological data, including pollen and plant macrofossils (vegetation), testate amoebae (water‐table depth) and physical peat properties, are used to explore the relationships between climate change, hydrology and vegetation in a coastal tropical peatland over the past 700 years. Downscaled climate simulations are integrated with this process‐based understanding to project the likely future responses of this coastal peatland to climate change. Results We identify a clear connection between precipitation variability, driven by shifts in the Intertropical Convergence Zone and water‐table dynamics, which subsequently influence changes in the peatland vegetation mosaic. Historical drier periods are marked by the expansion of shrub communities into the open peatland plain. Main Conclusions Palaeoecological studies incorporating climate and hydrological proxies are essential for understanding both recent and future ecohydrological dynamics of tropical peatlands. Our findings suggest that in response to future climate change, water tables will lower and shrub communities will expand due to rising temperatures and reduced precipitation. Additionally, future sea‐level rise, combined with declining rainfall, may result in seawater intrusion and significant vegetation shifts in coastal tropical peatlands.
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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 | 0.000 | 0.000 |
| 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".