Spatial modelling of biodiversity conservation priorities in Portugal’s <i>Montado</i> ecosystem using Marxan with Zones
Why this work is in the frame
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Bibliographic record
Abstract
Summary Spatial models are increasingly being used to target the most suitable areas for biodiversity conservation. This study investigates how the spatial tool Marxan with Zones (MARZONE) can be used to support the design of cost-effective biodiversity conservation policy. New in this study is the spatial analysis of the costs and effectiveness of different agro-environmental measures (AEMs) for habitat and biodiversity conservation in the Montado ecosystem in Portugal. A distinction is made between the financial costs paid to participating landowners and farmers for adopting AEMs and the broader economic opportunity costs of the corresponding land-use changes. Habitat and species conservation targets are furthermore defined interactively with the local government agency responsible for the management of protected areas, while the costs of agro-forestry activities and alternative land uses are estimated in direct consultation with local landowners. MARZONE identifies the spatial distribution of priority areas for conservation and the associated costs, some of which overlap with existing protected areas. These results provide useful insights into the trade-offs between nature conservation and the opportunity costs of protecting ecologically vulnerable areas, helping to improve current and future conservation policy design.
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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 | 0.000 |
| 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 it