Ecological impact and community perception of Phoenix acaulis (Roxb.) management in Shorea robusta (Garten. f.) forest of Udayapur district, Nepal
Bibliographic record
Abstract
Phoenix acaulis (Roxb.) , a common understory shrub in Nepal's Chure region, has remained largely understudied until now. Therefore, this study aims to examine the ecological impact of P. acaulis on Shorea robusta (Gaertn. f.) forest properties and to explore associated community perceptions in S. robusta forest of Udayapur district, Nepal. Stratified random sampling was adopted for this study where P. acaulis density (high, low and absent) was considered as basis of stratification. Altogether, 45 rectangular plots of 10 m x 10 m area (15 each category) were established for regeneration survey and soil sample collection (up to 30 cm). Soil quality index (SQI) method was used for soil quality assessment using indicators on the basis of prior studies conducted in Nepal. Using random sampling, a total of 52 households from the community forest user group were interviewed to gather their insights on the perceived effects of P. acaulis and its management. Highest S. robusta seedling and sapling density was observed in P. acaulis absent area (1132 ± 9.65 ha⁻¹ and 60 ± 0.63 ha⁻¹) where lowest in P. acaulis dense area (548 ± 7.4 ha⁻¹ and 4 ± 0.2 ha⁻¹). Similarly, higher SQI was in areas with high P. acaulis density (0.49) followed by low (0.45) and absent area (0.39). Most respondents advocated for removing P. acaulis from the forest, highlighting significant concerns among stakeholders. Our study suggests a positive impact P. acaulis on soil quality but indicates a negative impact on S. robusta regeneration. Therefore, further research to explore management strategies that balance the positive impact on soil quality with the observed negative influence on regeneration in P. acaulis presence areas is recommended.
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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 | 0.000 |
| 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 | 0.000 |
| 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 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".