The effect of grazing and anthropogenic disturbances on floristic and physiognomic characteristics in oriental beech communities, Masal Forest, Iran
Bibliographic record
Abstract
This study aimed to investigate floristic and physiognomic characteristics of all plant species in relation to grazing and anthropogenic disturbances. So that, 100 ha beech communities were studied including 50 ha as protected and 50 ha as unprotected area of oriental beech communities in Masal forest, Guilan Province, Iran. The results indicated that the number of all species were higher in the protected area. The main family of the protected area was the Rosaceae, while in the unprotected area the Asteracea had the highest frequency. To identify and classify forest types in both areas, we used the proportion of each tree species larger than 7.5 cm in diameter to determine species dominance according to the classification method of Gorji Bahri. The applied tree classification method indicated that there were three main types and two secondary types in the protected area, whereas six main types were identified in the unprotected area. Physiognomic studies indicated that trees from both areas were in the same height classes, whereas, the total canopy cover percentage was higher in the protected area. Height classes and canopy cover percentage of deciduous broadleaf in shrub layer, were significantly higher in unprotected area than in protected one. In the latter area, the coverpercentage of herbaceous species was different. So that, forbs species had the highest coverpercentage. According to these results, destructive factors have altered the main composition in these communities. So that, avoid of livestock grazing and local people in these areas or livestock exclusion can be recommended as a management.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".