How Can I Effectively Integrate Species Distribution Modeling With Remotely Sensed Data To Assess The Impact Of Increasing Tourist Activity On The Habitat Fragmentation And Population Dynamics Of The Endangered Iberian Lynx In The Mediterranean Coastal Scrublands Of Southern Spain?

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To effectively integrate species distribution modeling (SDM) with remotely sensed data (RSD) and assess the impact of increasing tourism on the Iberian lynx, follow this structured approach:

1. Data Collection and Preparation

  • Remotely Sensed Data (RSD):

    • Land Cover Mapping: Use satellite imagery (e.g., Landsat, Sentinel) to map land use changes over time, focusing on natural habitats and tourist infrastructure.
    • Vegetation Health: Apply indices like NDVI to assess habitat degradation.
    • Environmental Variables: Extract temperature, precipitation, and topography data.

  • Species Data:

    • Collect presence-only or presence-absence data for the Iberian lynx from existing studies or databases.

  • Tourism Data:

    • Gather data on tourist infrastructure (hotels, roads) and visitation patterns.

2. Species Distribution Modeling (SDM)

  • Model Development:

    • Use machine learning techniques (MaxEnt, Random Forests) to build an SDM incorporating environmental and tourism-related variables.
    • Include variables like distance to tourist areas and infrastructure density.

  • Variable Importance:

    • Assess the impact of tourism factors relative to other environmental variables.

3. Habitat Fragmentation Analysis

  • Landscape Metrics:
    • Use tools like FRAGSTATS to compute metrics (patch density, edge density) from land cover maps.
    • Link these metrics to SDM to understand fragmentation impacts on lynx habitat.

4. Population Dynamics and Scenario Analysis

  • Population Modeling:

    • Predict changes in population size and distribution under different tourism growth scenarios.
    • Consider prey distribution and climate variables in the model.

  • Scenario Analysis:

    • Test scenarios with varying levels of tourism to evaluate potential impacts on lynx populations.

5. Validation and Accuracy Assessment

  • Model Validation:
    • Validate SDM using field data or existing surveys.
    • Ensure model robustness by testing under different scenarios.

6. Conservation Recommendations

  • Critical Habitat Identification:
    • Highlight areas needing protection from tourism development.
    • Suggest sustainable tourism practices to minimize habitat fragmentation.

7. Collaboration and Ground Truthing

  • Expert Collaboration:
    • Engage with local experts for insights on tourism patterns and lynx behavior.
    • Conduct ground truthing to validate RSD and SDM results.

8. Data Resolution and Study Scale

  • Data Management:
    • Balance spatial and temporal resolutions for RSD, possibly using multiple satellites.
    • Focus on high-impact coastal regions in southern Spain.

9. Presentation of Results

  • Visual Outputs:
    • Create maps of habitat suitability and fragmentation metrics.
    • Present population projections under different tourism scenarios.

10. Conclusion

This approach integrates RSD and SDM to provide a comprehensive analysis of tourism impacts on the Iberian lynx, offering actionable insights for conservation and sustainable tourism.