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ODOT Wildlife Hotspot Study. Prepared by: Melinda Trask Oregon Department of Transportation, Geo-Environmental Section, Salem OR John Lloyd, Francesca Cafferata Coe, Jessica Burton, and Ellen Voth Mason, Bruce & Girard, Inc., Portland OR. Pilot Study: ODOT District 10.

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ODOT Wildlife Hotspot Study


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    Presentation Transcript
    1. ODOT Wildlife Hotspot Study Prepared by: Melinda Trask Oregon Department of Transportation, Geo-Environmental Section, Salem OR John Lloyd, Francesca Cafferata Coe, Jessica Burton, and Ellen Voth Mason, Bruce & Girard, Inc., Portland OR Pilot Study: ODOT District 10

    2. Wildlife Collision Data in Oregon • Types of Data: • Crash Records • Dispatch Carcass Records • Road Kill Observations • Expert Opinion

    3. ODOT's Wildlife Collision Prevention Plan • ODOT’s Mission and Addressing wildlife passage • Lack of information • Priorities • Non-regulated but supported by FHWA, ODFW, USFWS, CETAS, nationwide attention

    4. US Hwy ODOT Wildlife Collision Hot Spot Study • Statewide, analytical approach • Purpose: identify high frequency animal-vehicle collision zones • Uses existing carcass pick-up records • Pilot study to determine the feasibility of extending this analysis statewide Density: 1-2 animals 2-5 animals 6-10 animals

    5. ODOT District 10 Study Area

    6. Data Preparation • Original # Records in D10 = 6,546 (100%) • Step 1: Data Processing • Tabular Information Problems (28% reduction) • Narrowing Acceptable parameters (additional 21% reduction) • Step 2: Linkage to GIS (additional 17% reduction) • GIS Mapping • Route ≠ ODOT Highway Number • Final Data set totals 2,184 records (33% of total)

    7. Tabular Examples

    8. Tabular Examples

    9. Tabular Examples

    10. Analysis Study Area

    11. Results: Nearest Neighbor Analysis • Wildlife-vehicle collisions occur significantly closer together than would be expected by chance • Nearest Neighbor Index = 0.69 • Nearest Neighbor Index < 1 • Nearest Neighbor distance not included in confidence interval • Does not identify where the clusters occur

    12. Results: Ripley’s K Distribution

    13. Results: Nearest Neighbor Hierarchical Clustering

    14. Results: Kernal Density Evaluation

    15. Lessons Learned Data Processing • Long term: ODOT improving methods for tying field data to ODOT highway referencing system Data Analysis • The four methods of analysis offer complimentary information. • The Kernal Density Analysis provides the most informative results for ODOT management decisions.

    16. Recommendations • This study did not address explanatory factors contributing to wildlife vehicle collision hotspots • ODOT Management Decisions • Coordination with Maintenance

    17. Future Work • Apply what has been learned to other parts of the state highway network • Prioritize with ODOT staff • Identify explanatory factors contributing to wildlife vehicle collision hotspots (not currently funded) • Wildlife Linkage Areas • Workshops led by ODFW • GIS maps • Combine w/hot spots • Evaluate barriers

    18. RoadKill ≠ (always) Linkage Area X

    19. The End