THE IMPACT ON LANDSCAPE FRAGMENTATION INDUCED BY THE ESTABLISHMENT OF NATURA 2000 NETWORK IN ROMANIA
Bibliographic record
Abstract
Habitat fragmentation is a significant threat to biodiversity conservation and the establishment of protected areas has been proposed as one of the main strategies for mitigating its impacts. Romania has established numerous Natura 2000 sites to protect habitats and species of European importance, but their effectiveness remains unclear. In Romania, the Natura 2000 network was established in 2007. This study aims to evaluate the effectiveness of Sites of Community Importance (SCI), part of Natura 2000 network in Romania, in reducing habitat fragmentation. Using the Corine Land Cover database (CLC2006 and CLC2018), we analyzed changes in landscape fragmentation from SCIs between 2006 and 2018 (before and after the establishment of Natura 2000 sites in Romania). We calculated a set of landscape metrics using Patch Analyst version 5.2.0.16, in order to assess habitat fragmentation and configuration in this period. Our results indicate that, at landscape level, habitat fragmentation has decreased in protected areas for the analyzed period. At class level, the most significant changes for land use and land cover were registered for arable land and semi natural areas (increases in surfaces) and permanent crops, pastures and heterogeneous agricultural areas (decreases in surfaces). Our findings suggest that the establishment of Natura 2000 sites has been effective in reducing habitat fragmentation in protected areas of Romania. This study provides a baseline for monitoring the effectiveness of Natura 2000 sites in Romania, only terrestrial SCI, and highlights the need for better management and conservation practices to mitigate habitat fragmentation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".