Invaders' control on post-disturbance succession in coastal mangroves
Bibliographic record
Abstract
In recent years, coastal mangroves have been frequently affected by large disturbances (cyclones, hurricanes, flooding and tsunamis) and post-disturbance vegetation is often dominated by small stature mangrove, mangrove-associate and non-mangrove species potentially affecting ecosystem functioning. Knowledge on the processes of mangrove vegetation development and recovery (succession) following normal and large disturbances will benefit practitioners in designing robust ecosystem management/restoration plans. Here we propose a conceptual model of disturbance-mediated succession in mangroves. Based on field observations and species’ life history traits, we develop conceptual models of mangrove succession under normal disturbance regime and recently experienced increased frequency of large disturbances. We evaluate our conceptual models by conducting a scenario testing experiment. We suggest two predominant processes affecting mangrove succession after disturbance: propagule limitation due to damage of seed producing mature trees and dispersal barrier resulting from biological invasion associated with large disturbance. We argue that large disturbances affect mature trees more than the small-stature non-tree (shrubs, herbs and climbers) species creating a larger propagule shortage for mangrove tree species than non-tree species. Secondly, large disturbances facilitate invasion of free-floating aquatics, which may interfere with the flow-facilitated propagule dispersal and seedling establishment of mangrove species. In a scenario testing experiment, we have shown that similar levels of disturbance impact vegetation development and recovery differently depending on the presence or absence of invasive species. We conclude that since biological invasion is one of the major drivers of post-disturbance mangrove succession, the dimension of biological invasion should be included in prediction, management and restoration of mangrove forests.
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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 | 0.000 |
| 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 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".