Barriers to forest regeneration of deforested and abandoned land in Panama
Bibliographic record
Abstract
Summary In Panama, abandoned agricultural lands that supported tropical rain forest are invaded by the exotic invasive grass Saccharum spontaneum, which precludes native forest regeneration. This study aimed to evaluate the importance of several barriers to forest regeneration and highlight mitigation opportunities. We examined four barriers to natural regeneration: Saccharum competition, seed dispersal limitation, fire and soil nutrient deficiency. Tree and shrub regeneration was measured in a factorial experiment combining Saccharum cutting treatments, distances from adjacent forest and a prescribed burn to assess the first three barriers, respectively. We compared soil nutrients in Saccharum plots with those from adjacent forest. Additionally, we determined the importance of distance to remnant vegetation (large‐leaved monocots, shrubs and isolated trees) on forest regeneration. Fire significantly decreased plant species richness of forest regeneration. Fire inhibited the germination of most species; the effect was exacerbated by cutting the Saccharum. Grass competition significantly decreased seedling growth, while soil nutrient deficiency did not affect forest regeneration. Seed dispersal limitation affected density and species richness. Significantly more species (3×) regenerated at 10 m compared with 35 m from the forest. Mean seedling densities were, respectively, four, three and two times higher under large‐leaved monocots, isolated trees and shrubs than in open Saccharum. When seed input was experimentally equalized, large‐seeded species had the highest establishment rate, suggesting that if their propagules were dispersed to the site they would regenerate in high proportions. However, under natural conditions they regenerated poorly and represented the most dispersal‐limited species group. Synthesis and applications. Our results suggest that facilitation of natural regeneration may be a feasible, low‐cost management option for restoring native forest cover to large areas. Firebreaks must be established to promote biodiversity of forest regeneration. We do not recommend Saccharum cutting or fertilization as site treatments. Shading effectively eliminates Saccharum. Planting a variety of tree species in clumps throughout the Saccharum may overcome dispersal limitations and catalyse natural regeneration. Trees that attract different frugivores are recommended, especially large‐seeded forest species.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".