Quantifying the biodiversity value of tropical primary, secondary, and plantation forests
Bibliographic record
Abstract
Biodiversity loss from deforestation may be partly offset by the expansion of secondary forests and plantation forestry in the tropics. However, our current knowledge of the value of these habitats for biodiversity conservation is limited to very few taxa, and many studies are severely confounded by methodological shortcomings. We examined the conservation value of tropical primary, secondary, and plantation forests for 15 taxonomic groups using a robust and replicated sample design that minimized edge effects. Different taxa varied markedly in their response to patterns of land use in terms of species richness and the percentage of species restricted to primary forest (varying from 5% to 57%), yet almost all between-forest comparisons showed marked differences in community structure and composition. Cross-taxon congruence in response patterns was very weak when evaluated using abundance or species richness data, but much stronger when using metrics based upon community similarity. Our results show that, whereas the biodiversity indicator group concept may hold some validity for several taxa that are frequently sampled (such as birds and fruit-feeding butterflies), it fails for those exhibiting highly idiosyncratic responses to tropical land-use change (including highly vagile species groups such as bats and orchid bees), highlighting the problems associated with quantifying the biodiversity value of anthropogenic habitats. Finally, although we show that areas of native regeneration and exotic tree plantations can provide complementary conservation services, we also provide clear empirical evidence demonstrating the irreplaceable value of primary forests.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".