Impact of <i>Ligustrum lucidum</i> invasion on the structure and functioning of coastal dry forests: a case study from Argentina
Bibliographic record
Abstract
The Ligustrum lucidum invasion of Argentinian forests has significantly altered their structure and functioning. This study assesses and compares structural variables (tree density, sapling density, basal area, and understory cover) and functional variables over time (leaf area index (LAI), fraction of photosynthetically active radiation (fPAR), relative growth rate (RGR), and net primary productivity (NPP)) through field measurements in preserved, partially invaded and invaded dry forests in natural reserve “El Destino”, Buenos Aires province. Results show that the high L. lucidum RGR enhanced light-use capacity of invaded forests, evidenced by an increase in tree density, a 50% higher LAI and consistently elevated fPAR compared to preserved forests. However, the expected NPP increase was not observed. Invaded forests intercepted over 95% of solar radiation year-round, suppressing understory development and produced a dense leaf litter layer. The linear relationship between LAI and canopy height highlighted vertical structure’s role in light interception. Furthermore, the high density of L. lucidum saplings in preserved forests and the presence of dead native trees in invaded forests suggest competitive displacement toward monospecific stands of L. lucidum. These findings enhance our understanding of how L. lucidum reshapes ecosystem structure and function in these native forests, providing insights for forest management.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".