Restoring and rehabilitating watercourses in the Ria Formosa Nature Park (Algarve): intervention principles, processes and techniques
Bibliographic record
Abstract
The core objective of this article is to contribute towards defining a project methodology for rehabilitating fluvial ecosystems in strongly humanized Mediterranean landscapes. To achieve this objective, interrelated with the management and maintenance of these landscapes, we took into consideration the theory and the praxis that frame interventions in watercourses experiencing situations of risk. This article spans these two core, interwoven facets, approaching both the theoretical research and the applied research undertaken within the scope of proposals for rehabilitating five watercourses in Eastern Algarve. The project approach to the restoration of the ecological corridors associated with the downstream sections of the Cacela, Canada, Tronco, Bela-Mandil streams, and the Seco River thus accounted for the shortage and irregularity in the distribution of precipitation and the torrential regime characterizing the region in conjunction with the high level of artificialism displayed by these fluvial systems. Under the auspices of the project process, the aforementioned watercourses were perceived as dynamic, complex, open, and multi-functional socio-ecological systems with a role and importance in ensuring the biological balance and physical stability of the coastal plain and the Ria Formosa lagoon system. The project concept was rooted in a strategy based on intervention flexibility, taking into account a balance between the rehabilitation of natural values and resources and the presence of human activities. Hence, in the rehabilitation proposals developed, the materials applied were entirely natural (plants, wood, and stone), with recourse to technical-scientific concepts and procedures drawn from the fields of Landscape Architecture and Biophysical Engineering.
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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 | 0.002 | 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 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".