Factors Affecting the Use of Reforested Sites by Reptiles in Cleared Rainforest Landscapes in Tropical and Subtropical Australia
Bibliographic record
Abstract
Abstract Despite recent efforts to reforest cleared rainforest landscapes, in Australia and elsewhere, the value of reforested sites for rainforest‐dependent reptiles is unknown. We surveyed the occurrence of reptiles in a range of reforestation types (monoculture and mixed‐species timber plantations, diverse “ecological restoration” plantings and regrowth), as well as reference sites in pasture and rainforest, in tropical and subtropical Australia. We recorded 29 species of reptiles from 104 sites, including 15 rainforest‐dependent species. Most rainforest reptiles were strongly associated with complex microhabitats (tree trunks, logs, rocks). The richness and abundance of rainforest‐dependent reptiles varied between the different types of reforestation and between regions. In the tropics, rainforest reptiles were recorded in old timber plantations and ecological restoration plantings but not in young timber plantations or regrowth. Rainforest reptiles were recorded in few reforested sites in the subtropics. The occurrence of rainforest‐dependent reptiles in reforested sites appears to be influenced by (1) habitat structure; (2) proximity to source populations in rainforest; and (3) biogeography and historical differences in the extent of rainforest. Restoration of cleared land for rainforest‐dependent reptiles may require the development, or deliberate creation, of complex structural attributes and microhabitats in reforested sites. Where reforested sites are located away from rainforest, recolonization by rainforest reptiles may require the construction of corridors of suitable habitat between reforested sites and rainforest or the translocation of reptiles to reforested sites.
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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 | 0.000 |
| Science and technology studies | 0.000 | 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".