Karstic spring wetlands of the Persepolis Basin, southwest Iran: unique sediment archives of Holocene environmental change and human impacts
Bibliographic record
Abstract
Palustrine carbonates are frequently found with active and dried karstic springs in the foothills of the mountains bordering the Persepolis Basin, southwest Iran. A combination of geological conditions favours their formation, including (i) the presence of karstic limestone aquifers in the limbs of anticlines cut through by fault systems; (ii) very gentle slopes from the spring resurgence point towards the centre of the alluvial plain, creating a flat waterlogged area; and (iii) a semiarid climate with marked precipitation seasonality or significant fluctuations in water discharge and wetland water table. We suggest the term “anastomosing wetlands” or “anastomosing palustrine environments” to denote the studied karstic spring–fed carbonate wetlands, because of similarities with anastomosing river systems in aerial view. The common presence of extended anastomosing wetland carbonates in the Persepolis Basin and adjacent basins in the central and southern Zagros suggests that they can play an important role in the geological records of collision-related basin-and-range settings dominated by karstic limestones. Karstic spring wetlands are a main source of fresh water hosting a rich biodiversity, which attracts human communities, whose impact is visible in the archaeological material imbedded in the wetland stratigraphy. Fresh water availability, through these spring wetlands, partly explains why the semiarid Persepolis region was selected by successive civilizations, from Elamites to Persians until early Islamic entities, to establish regional centres throughout the period from the third millennium B.C. to the first millennium A.D. Only a few of these ecosystems have survived the intensive human activities of recent decades.
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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 | 0.002 |
| 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".