Building Resilience through Territorial Planning: Water Management Infrastructure and Settlement Design in the Coastal Wetlands of Northern Apulia (Salpia vetus-Salapia) from the Hellenistic Period to Late Antiquity
Bibliographic record
Abstract
This Gulf of Manfredonia has, for millennia, been the primary water feature of the coastal wetland of Northern Apulia, Italy, although modern reclamation works make writing its long-term history challenging. Our recent paleoenvironmental research has reconstructed the evolution of the southern half of this lagoon since the Neolithic period. Here, we write a history of water management and environmental change in this landscape from the perspective of two key urban sites: pre-Roman Salpia vetus and Roman Salapia. The Roman architectural historian Vitruvius recounts the abandonment of Salpia vetus and the refoundation of Salapia. We employ his narrative as a frame for a more complex environmental history, starting from a historiography of this landscape’s study and a summary of our interdisciplinary research agenda, which unifies environmental, topographical, remote sensing, and archaeological approaches. Resilience in this changeable wetland environment was only possible through an integrated and intentional management of water among rivers, the lagoon, and the Adriatic Sea. While Salpia vetus exploited this wetland and thrived for centuries, the settlement eventually collapsed due to human and environmentally impelled factors. Roman Salapia subsequently emerged with a different approach, new infrastructure, and a new location. This blueprint would sustain urban life in this wetland for six centuries and lay the groundwork for the Medieval town.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".