Identifying Wildlife Linkages and Wildlife Collision Hot Spots on Oregon Highways Oregon Department...
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Identifying Wildlife Linkages and Wildlife Collision Hot Spots on Oregon Highways Oregon Department of Transportation Mason, Bruce & Girard, Inc. Oregon Department of Fish and Wildlife Introduction Introduction Highways restrict wildlife movement across the landscape by fragmenting habitat, thereby limiting or completely severing access to resources that support important life history needs. Given the thousands of miles of state-owned roads across Oregon, ODOT and ODFW developed The Oregon Wildlife Movement Strategy to begin addressing wildlife movement issues statewide. The first step was to identify and prioritize areas that presented wildlife movement problems related to highways. The Hot Spot Analysis was conducted to map animal- vehicle collision problem areas, and the Wildlife Linkages Study was conducted to map wildlife movement priority areas. Hot Spots - Methods Hot Spots - Methods • Step 1: “Scrub” data to create a statewide GIS dataset. Scrubbing removed 44% of the records due to data quality and GIS mapping problems. • Step 2: Look for evidence of clustering with a Nearest Neighbor Analysis. • Step 3: Spatially analyze the data with a Ripley’s K- Distribution to identify the appropriate scale at which clustering of wildlife Hot Spots - Analysis Hot Spots - Analysis • ODOT Maintenance dispatch carcass records were used because these are the most abundant sources of data available for all highways in Oregon. • These records do not represent comprehensive data on animal vehicle collisions (AVCs) because the records mainly represent animal carcasses that are a highway safety problem (e.g., large mammals such as deer and elk). Hot Spots - Results and Discussion Hot Spots - Results and Discussion • The Hot Spot Analysis identified and mapped high frequency wildlife carcass incidents on all state highways in Oregon. • This was one of the first uses of the Kernel Density Method to map wildlife collision hot spots over such a large study area (7,415 linear miles of highway). • The Kernel Density Method provided a useful visual representation of wildlife hot spots (see following figure). * * * * * For more information on the Oregon Wildlife Movement Strategy: www.dfw.state.or.us/conservation strategy For GIS data on linkages and collision hot spots: Linkage dataset with current priorities in Oregon Example of a linkage areas that crosses a transportation corridor Wildlife Linkages Study Wildlife Linkages Study Through a series of workshops, stakeholders identified wildlife linkage (key movement) areas (emphasizing areas that crossed paved roads) for a suite of focal species including big game, small mammals, amphibians, and reptiles. The result of these workshops is mapped information showing wildlife linkage areas across roads in Oregon based on expert opinion. The Wildlife Movement Strategy Working Group then prioritized the linkage areas based on a number of criteria. Next Steps Next Steps • Provide data to transportation managers for project planning/scoping. • Conduct additional surveys in hot spots and linkage areas to determine appropriate actions for improving wildlife movement. • Use linkage dataset in conjunction with hot spot data set to improve wildlife crossings and wildlife movement across Oregon. Graphic Results of the Kernel Density Analysis (exaggerated for visibility) • The Nearest Neighbor Index confirmed clustering of the data (NNI = <1 and p<0.001). • The Ripley’s K-Statistic indicated that clustering was significant at all distances between 0 and 10 miles. • The Kernel Density Method depicts the widespread nature of wildlife collisions and some distinctive high density hot spots on state highways. • Dispatch records are based on personal account of a carcass observation. • These records are neither spatially accurate nor verifiable as true AVCs. • Statewide records from 1995 – 2006 were used. • The final data set included 17,825 mapped carcass records. Wildlife underpass on SR240 in Washington (source: WDOT) Proposed overpass for elk along the I-90 corridor (source: WDOT) R ipley's K -Function 10 distance bands (d = 1 m ile) 0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 1 2 3 4 5 6 7 8 9 10 Scale distance (d)in m iles K -value O bserved Low erCI UpperCI
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Transcript of Identifying Wildlife Linkages and Wildlife Collision Hot Spots on Oregon Highways Oregon Department...
Identifying Wildlife Linkages and Wildlife Collision Hot Spots on Oregon Highways
Oregon Department of Transportation Mason, Bruce & Girard, Inc. Oregon Department of Fish and Wildlife
IntroductionIntroduction
Highways restrict wildlife movement across the landscape by fragmenting habitat, thereby limiting or completely severing access to resources that support important life history needs.
Given the thousands of miles of state-owned roads across Oregon, ODOT and ODFW developed The Oregon Wildlife Movement Strategy to begin addressing wildlife movement issues statewide. The first step was to identify and prioritize areas that presented wildlife movement problems related to highways. The Hot Spot Analysis was conducted to map animal-vehicle collision problem areas, and the Wildlife Linkages Study was conducted to map wildlife movement priority areas.
Hot Spots - MethodsHot Spots - Methods• Step 1: “Scrub” data to create a statewide GIS dataset. Scrubbing removed 44% of the records due to data quality and GIS mapping problems. • Step 2: Look for evidence of clustering with a Nearest Neighbor Analysis. • Step 3: Spatially analyze the data with a Ripley’s K-Distribution to identify the appropriate scale at which clustering of wildlife carcass occurs. • Step 4: Map data using the Kernel Density Method to depict clustering.
Hot Spots - AnalysisHot Spots - Analysis• ODOT Maintenance dispatch carcass records were used because these are the most abundant sources of data available for all highways in Oregon. • These records do not represent comprehensive data on animal vehicle collisions (AVCs) because the records mainly represent animal carcasses that are a highway safety problem (e.g., large mammals such as deer and elk).
Hot Spots - Results and DiscussionHot Spots - Results and Discussion• The Hot Spot Analysis identified and mapped high frequency wildlife carcass incidents on all state highways in Oregon. • This was one of the first uses of the Kernel Density Method to map wildlife collision hot spots over such a large study area (7,415 linear miles of highway). • The Kernel Density Method provided a useful visual representation of wildlife hot spots (see following figure).
* * * * *For more information on the Oregon Wildlife
Movement Strategy: www.dfw.state.or.us/conservation strategy
For GIS data on linkages and collision hot spots:
http://nrimp.dfw.state.or.us/nrimp/default.aspx
Linkage dataset with current priorities in Oregon
Example of a linkage areas that crosses a transportation corridor
Wildlife Linkages StudyWildlife Linkages Study
Through a series of workshops, stakeholders identified wildlife linkage (key movement) areas (emphasizing areas that crossed paved roads) for a suite of focal species including big game, small mammals, amphibians, and reptiles. The result of these workshops is mapped information showing wildlife linkage areas across roads in Oregon based on expert opinion. The Wildlife Movement Strategy Working Group then prioritized the linkage areas based on a number of criteria.
Next StepsNext Steps• Provide data to transportation managers for project planning/scoping. • Conduct additional surveys in hot spots and linkage areas to determine appropriate actions for improving wildlife movement. • Use linkage dataset in conjunction with hot spot data set to improve wildlife crossings and wildlife movement across Oregon.
Graphic Results of the Kernel Density Analysis (exaggerated for visibility)
• The Nearest Neighbor Index confirmed clustering of the data (NNI = <1 and p<0.001). • The Ripley’s K-Statistic indicated that clustering was significant at all distances between 0 and 10 miles. • The Kernel Density Method depicts the widespread nature of wildlife collisions and some distinctive high density hot spots on state highways.
• Dispatch records are based on personal account of a carcass observation. • These records are neither spatiallyaccurate nor verifiable as true AVCs. • Statewide records from 1995 – 2006 were used. • The final data set included 17,825 mapped carcass records.
Wildlife underpass on SR240 in Washington (source: WDOT)
Proposed overpass for elk along the I-90 corridor (source: WDOT)
Ripley's K-Function10 distance bands (d = 1 mile)
0500
100015002000250030003500400045005000
1 2 3 4 5 6 7 8 9 10
Scale distance (d) in miles
K-v
alu
e Observed
Low er CI
Upper CI
