Assessing the ecological suitability of land-use change. Lessons learned from a rural marginal area in southeast Portugal
Bibliographic record
Abstract
Land-use planning practice and policy are still lacking a landscape perspective that takes into account landscape history integrated with land suitability. This article presents a method that allows assessing the ecological suitability of land-use change. This method was applied to Baixo Guadiana, a rural marginal area in southeast Portugal. The first step of the land-use change ecological assessment is the study area delimitation. Baixo Guadiana limits were obtained through land morphology and slopes cartography, based on the "morphological landscape unit” concept. The second step - land suitability analysis - includes a characterization of the landscape ecological suitability. The third step - land-use change analysis - combines landscape history, with land-use change analysis and historical literature review. The final step – land-use change ecological assessment – is the evaluation of the land-use changes regarding land suitability. This paper highlights how the integration of two widely used methods, land-use change and land suitability analysis, supports land use policy analysis. Firstly, this research shows how past policies did not consider Baixo Guadiana Landscape Suitability. The current lack of natural regeneration of holm and cork oaks, the death of these adult trees and the low production of stone pine plantations, represent the main challenges to the planning and recovery of this landscape. Secondly, besides highlighting how these problems resulted from past inadequate land uses, promoted by national and European agricultural policies, this study indicates the areas where landscape recovery actions should be financed.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".