Human and Avicennia marina Mangrove Populations: with Special Reference to Qatar
Bibliographic record
Abstract
This study's aim is to find out the reasons and the ways to ensure the survival of Qatari mangroves along with the current development of the country. Mangroves are halophyte trees, able to survive in intertidal areas, between land and sea. In Qatar, the only species able to survive the extreme levels of salinity and other climatic conditions is Avicennia marina. Global distributions and unique features of A. marina have been thoroughly reviewed. Being in arid land regions, mangrove creates a space of green that highly contrasts with the surrounding barren landscapes and brings several ecosystem services for the human wellbeing and the environment. Qatari mangroves contain an exceptional biodiversity and create an important ecosystem linked to the surrounding ones. Distribution, characteristics and ecosystem goods and services of Qatari mangrove have been reviewed and discussed. Yet Qatar has recently witnessed a significant development and a dramatic increase in human population. Anthropic and demographic pressures and urban explosion are universal threats deteriorating mangrove all along the Qatari coast. All direct and indirect threats have been reviewed, assessed and thoroughly discussed. Qatar is committing itself more and more to environmental issues and many protective and conservation measures have been taken, especially in the last few years. However, there are still many gaps and agreement measures do not always seem effective in the field. Details about public awareness, successful stories and obstacles and challenges of management and conservation of Qatari mangroves in respect to local, regional and international efforts are discussed.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".