The world's oldest man‐made biological experiment
Bibliographic record
Abstract
Biological experiments are often short‐lived due to logistical or resource‐related challenges, and short‐term observations are extrapolated to make long‐term predictions. However, the effects of experimental treatments on biological communities and processes take time to develop. Consequently, the robustness of conclusions drawn from observations increases with the duration of the experiment. As a striking real‐world example, and scattered throughout central Laos, thousands of large stone jars have been left behind from ancient burial rituals. The most famous sites in the Xiengkhouang province are collectively referred to as the Plain of Jars. These jars form a massive biological experiment: for approximately 2000 years, rainwater has interacted with the geological origin of each jar to create unique yet replicated aquatic ecosystems influenced by different tree cover levels. The layout of these jars, with clusters of up to several hundred jars separated by several kilometers, allows for controlled testing of multiple questions within ecology and evolution. Here, we report, for the first time, how these ancient mesocosms can be used to test ecosystem responses to local abiotic variation and disturbance. We show that tree cover dominates every jar ecosystem's state, and that variations in tree cover density create gradients in oxygen (O 2 ) and nutrient concentrations among jar ecosystems. These initial findings show that litter contribution to aquatic ecosystems leads to higher nutrient content and lower O 2 concentration, even in systems under different long‐term selection, in the oldest man‐made ecosystems ever analyzed. This first environmental analysis provides a fundamental understanding of a unique environment and offers trajectories for future exploration.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.003 | 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 teacher head, 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".