Assessing habitat risk from human activities to inform coastal and marine spatial planning: a demonstration in Belize
Bibliographic record
Abstract
Integrated coastal and ocean management requires transparent and accessible approaches for understanding the influence of human activities on marine environments. Here we introduce a model for assessing the combined risk to habitats from multiple ocean uses. We apply the model to coral reefs, mangrove forests and seagrass beds in Belize to inform the design of the country’s first Integrated Coastal Zone Management (ICZM) Plan. Based on extensive stakeholder engagement, review of existing legislation and data collected from diverse sources, we map the current distribution of coastal and ocean activities and develop three scenarios for zoning these activities in the future. We then estimate ecosystem risk under the current and three future scenarios. Current levels of risk vary spatially among the nine coastal planning regions in Belize. Empirical tests of the model are strong—three-quarters of the measured data for coral reef health lie within the 95% confidence interval of interpolated model data and 79% of the predicted mangrove occurrences are associated with observed responses. The future scenario that harmonizes conservation and development goals results in a 20% reduction in the area of high-risk habitat compared to the current scenario, while increasing the extent of several ocean uses. Our results are a component of the ICZM Plan for Belize that will undergo review by the national legislature in 2015. This application of our model to marine spatial planning in Belize illustrates an approach that can be used broadly by coastal and ocean planners to assess risk to habitats under current and future management scenarios.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".