The Conservation of Biodiverse and Threatened Dry Rainforest Plant Communities Is Vital in a Changing Climate
Bibliographic record
Abstract
Dry rainforest communities are globally threatened by anthropogenic pressures and climatic change but are less well researched and more poorly conserved than mesic rainforests. In response to the increasing loss of biodiversity, the Australian Government joined other international signatory parties to adopt the Kunming-Montreal Global Biodiversity Framework (GBF). The GBF emphasises the maintenance of connectivity and genetic diversity of whole ecosystems via landscape-scale conservation initiatives. Rainforest plant diversity, distinctiveness, and the current level of conservation of seasonal rainforest regional ecosystems of the Central Queensland Coast region in Australia were evaluated. Our three-marker DNA barcode dated phylogeny of rainforest plant taxa together with community species lists were used to calculate phylogenetic diversity (PD) estimates and species composition. Levels of rainforest ecosystem protection were assessed using Queensland government data. This study found selection pressures for moisture and geology significantly influence rainforest distribution and species diversity and evidence of a high degree of variability in terms of conservation. While some phylogenetically distinctive rainforest community types were well conserved, restricted or endangered communities were very poorly protected. Additionally, we found smaller dry rainforests in the Central Queensland Coast represent regional plant migration but are inadequately protected, highlighting the need for a revision of conservation objectives within the region.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".