Invasive alien species in protected areas: the dynamics of <i>Pinus taeda</i> at Rio Canoas State Park – Brazil
Bibliographic record
Abstract
Biological invasion is a growing problem, and species of the genus Pinus are known to be a problem in the forests of southern Brazil, including in conservation units. Here, we studied the ecology of Pinus taeda L. invasion in Rio Canoas State Park (PAERC) in regards to forest inventory, soil seed bank analysis, and seed rain assessment, in three distinct successional stages inside the park referred to as “Pinus invasion”, “Old Growth Vegetation”, and “Initial Vegetation”. The forest inventory of 33 (20 m × 20 m) plots found Pinus in two of the three evaluated environments. Seed rain was collected bimonthly using 33 (1 m × 1 m) seed traps for a period of 1 year. The major seed distribution periods were in April and June, confirming data found in the literature. The seed bank was analyzed in February (summer) and June (winter) of 2018. Samples were kept in a greenhouse for a period of 120 days each. Summer evaluation showed no emergence of Pinus taeda seedlings, but the winter evaluation (June) did show the emergence of seedlings. The results showed that the soil seed bank is not persistent. Accordingly, the Pinus invasion reported at PAERC requires a restoration program, as well as one that controls reinfestation.
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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 | 0.000 |
| Scholarly communication | 0.001 | 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".