Distribution and environmental drivers of multi-functional community traits in the Sundarbans mangrove forest
Bibliographic record
Abstract
ABSTRACT Mangrove forests are vital blue-carbon ecosystems, playing a crucial role in global carbon storage, climate regulation, and biodiversity conservation. However, escalating environmental threats, particularly salinity intrusion, necessitate a deeper understanding of their functional dynamics to inform effective conservation and restoration strategies. This study examines the distribution of multi-functional community traits (MFCT) and their environmental drivers across mangrove functional groups (pioneer, mid-successional, climax) along salinity gradients in the Sundarbans, the world’s largest mangrove forest. Using data from 62 plots, nine functional traits from 17 mangrove species were analysed to evaluate MFCT diversity and its environmental determinants. Results revealed distinct variations in MFCT diversity, with mid-successional species exhibiting the highest trait diversity (64.0 ± 1.58), followed by climax (51.3 ± 2.09) and pioneer groups (50.2 ± 2.26). Climax species demonstrated resilience to salinity increases (R² = 0.29, p < 0.001), whereas mid-successional and pioneer groups were negatively affected (R² = 0.22, p < 0.001 and R² = 0.17, p < 0.001). Annual precipitation exerted contrasting effects, reducing diversity in climax species (R² = 0.25, p < 0.001) but enhancing it in mid-successional (R² = 0.22, p < 0.001) and pioneer groups (R² = 0.06, p = 0.05). Notably, MFCT values remained stable across salinity gradients, underscoring the ecosystem’s functional resilience. These findings highlight mid-successional species as keystones in sustaining mangrove multifunctionality and resilience under environmental stressors. Prioritizing these species in conservation and restoration efforts can mitigate the impacts of salinity intrusion and climate variability. By integrating the MFCT framework, resource managers can develop targeted restoration strategies to enhance ecosystem functionality and long-term stability. These insights provide a critical foundation for policymakers to align global mangrove conservation with adaptive management strategies, reinforcing coastal resilience, biodiversity conservation, and climate change mitigation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".