A Global Trend towards the Loss of Evolutionarily Unique Species in Mangrove Ecosystems
Bibliographic record
Abstract
The mangrove biome stands out as a distinct forest type at the interface between terrestrial, estuarine, and near-shore marine ecosystems. However, mangrove species are increasingly threatened and experiencing range contraction across the globe that requires urgent conservation action. Here, we assess the spatial distribution of mangrove species richness and evolutionary diversity, and evaluate potential predictors of global declines and risk of extinction. We found that human pressure, measured as the number of different uses associated with mangroves, correlated strongly, but negatively, with extinction probability, whereas species ages were the best predictor of global decline, explaining 15% of variation in extinction risk. Although the majority of mangrove species are categorised by the IUCN as Least Concern, our finding that the more threatened species also tend to be those that are more evolutionarily unique is of concern because their extinction would result in a greater loss of phylogenetic diversity. Finally, we identified biogeographic regions that are relatively species-poor but rich in evolutionary history, and suggest these regions deserve greater conservation priority. Our study provides phylogenetic information that is important for developing a unified management plan for mangrove ecosystems worldwide.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".