Assessing climatic change impacts on mangrove structural dynamics on the northern coasts of the Persian Gulf
Bibliographic record
Abstract
Abstract. Monitoring long-term trends in structural changes within mangrove ecosystems is essential for understanding their response to climate change and devising effective adaptation strategies in coastal regions. This study examines changes in mangrove patchiness within the Hara Biosphere Reserve (HBR) along the northern coasts of the Persian Gulf (PG) over a 31-year period (1986-2017), focusing on variations in rainfall patterns and drought occurrences. Employing a 35-year time series of monthly Standardized Precipitation Index (SPI) values alongside satellite imagery analysis, trends in both the number of patches (NP) and the Largest Patch Index (LPI) were assessed at the mangrove stand level. The analysis reveals a significant correlation between structural changes in mangroves and drought events. Pre-1998, characterized by wetter conditions, witnessed a decrease in both NP and LPI, indicating patch expansion and habitat extension. Conversely, post-1998, during drought periods, both indices increased, indicating habitat degradation due to heightened drought intensity. Pre-1998 structural changes in the HBR signify habitat expansion, with increased patch extent and core areas reflecting enhanced structural integrity. However, post-1998, a concerning trend of habitat degradation emerged, with increased NP and LPI attributed to intensified droughts. These findings highlight a transitional period marked by favourable conditions for mangrove growth followed by habitat degradation linked to increased drought intensity. This underscores the vulnerability of mangrove ecosystems to climate change impacts, particularly exacerbated droughts, necessitating urgent efforts for conservation and management to preserve biodiversity and ecosystem services in coastal regions.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".