1. Predictive Modeling of Northern Spotted Owl Home Ranges Presented by Elizabeth Willy USFWS File Photo

2. Presentation Overview Northern Spotted Owl (NSO) Northern Spotted Owl (NSO) Models Models Study Area Study Area Data Data Methods and Analysis Methods and Analysis Research Relevance Research Relevance Potential Challenges Potential Challenges

3. Northern Spotted Owl Listed as Threatened in 1990 Listed as Threatened in 1990 Habitat Habitat Surveys Surveys Conservation Conservation Christy Cheyne, Klamath National Forest NSO Project Objectives Models Study Area Data Methods and Analysis Research Relevance Potential Challenges

4. Current Method to Assess Effects of Human Activities to NSO NSO territories are centered on an ‘activity center’ NSO territories are centered on an ‘activity center’ 0.5-mile core area 0.5-mile core area 1.3-mile radius home range 1.3-mile radius home range Radio telemetry studies Radio telemetry studies NSO Project Objectives Models Study Area Data Methods and Analysis Research Relevance Potential Challenges

5. Research Question: Is there a way to describe home ranges for Northern Spotted Owls that does not use circles? NSO Project Objectives Models Study Area Data Methods and Analysis Research Relevance Potential Challenges

6. Project Objectives Refine the current circle-based analysis method Refine the current circle-based analysis method Telemetry data Telemetry data Abiotic attributes: Abiotic attributes: NSO Project Objectives Models Study Area Data Methods and Analysis Research Relevance Potential Challenges  Modeling scenarios  Abiotic-only  Habitat-only  Abiotic + Habitat  Validation  Testing with reserved telemetry points  Aspect  Curvature  Distance to stream  Solar radiation  Elevation  Slope percent  Slope position

7. Models NSO Project Objectives Models Study Area Data Methods and Analysis Research Relevance Potential Challenges Maximum Entropy (Maxent) Model (Maxent) Model Adapted from Phillips et al. 2006 Species Distributions Occurrence Localities Predicted Potential Distribution Environmental Variables … + HexSim Model Population Simulator Adapted from Schumaker 2009

8. Study Areas NSO Project Objectives Models Study Area Data Methods and Analysis Research Relevance Potential Challenges

9. Topography and Telemetry Points: Hilt and Goosenest Study Areas NSO Project Objectives Models Study Area Data Methods and Analysis Research Relevance Potential Challenges

10. Data Vector Data Telemetry points Telemetry points Activity center points Activity center points Streams Streams Vegetation/Habitat Vegetation/Habitat Raster Data Raster Data 10-meter Digital Elevation Models (DEMs) NSO Project Objectives Models Study Area Data Methods and Analysis Research Relevance Potential Challenges

11. Data Pre-processing NSO Project Objectives Models Study Area Data Methods and Analysis Research Relevance Potential Challenges Obtain Data Vector: Activity Center Pts Streams Telemetry Pts Vegetation/Habitat Raster: 10-m DEMs Project all data to NAD83 Mosaic DEM Tiles Telemetry data exploration Generate abiotic surfaces Slope Position  Extract raster values to points  Review frequency distributions of extracted data  Explore correlations between abiotic features and vegetation/habitat Convert and input data into models Stream cost weighted distance AspectSlopeCurvatureSolar Radiation

12. Maxent Modeling: Abiotic-only Input occurrence data Input occurrence data Telemetry points Telemetry points Input abiotic variables Input abiotic variables Aspect Aspect Curvature Curvature Distance to stream Distance to stream Elevation Elevation Slope percent Slope percent Slope position Slope position Solar radiation Solar radiation NSO Project Objectives Models Study Area Data Methods and Analysis Research Relevance Potential Challenges

13. Maxent Modeling: Habitat-only Input occurrence data Input occurrence data Telemetry points Telemetry points Input habitat variables Input habitat variables Habitat Habitat NSO Project Objectives Models Study Area Data Methods and Analysis Research Relevance Potential Challenges Nesting/ roosting Foraging Non- habitat

14. Maxent Modeling: Abiotic + Habitat Input occurrence data Input occurrence data Telemetry points Telemetry points Input abiotic variables Input abiotic variables Aspect Aspect Curvature Curvature Distance to stream Distance to stream Elevation Elevation Slope percent Slope percent Slope position Slope position Solar radiation Solar radiation Input habitat variables Input habitat variables Habitat Habitat NSO Project Objectives Models Study Area Data Methods and Analysis Research Relevance Potential Challenges Nesting/ roosting Foraging Non- habitat

15. Maxent Model Outputs Probability surface Analysis of variable contribution Raw data Species responses for individual variables NSO Project Objectives Models Study Area Data Methods and Analysis Research Relevance Potential Challenges

16. HexSim Model Input data Nest points Nest points HexMap of spatial data from Maxent HexMap of spatial data from Maxent NSO Project Objectives Models Study Area Data Methods and Analysis Research Relevance Potential Challenges

17. HexSim Model: Range Parameters Maximum search radius Maximum search radius Maximum area searched Maximum area searched NSO Project Objectives Models Study Area Data Methods and Analysis Research Relevance Potential Challenges

18. HexSim Model: Search Parameters Uniform NSO Project Objectives Models Study Area Data Methods and Analysis Research Relevance Potential Challenges OptimalGreedy

19. HexSim Model Outputs Maps Maps Spatial data Spatial data Simulation data Simulation data NSO Project Objectives Models Study Area Data Methods and Analysis Research Relevance Potential Challenges

20. Analysis Evaluate Maxent probability distributions Evaluate Maxent probability distributions Testing with reserved telemetry data Testing with reserved telemetry data Compare HexSim home ranges to circles Compare HexSim home ranges to circles Assess research question Assess research question NSO Project Objectives Models Study Area Data Methods and Analysis Research Relevance Potential Challenges

21. Research Relevance Refine current circle-based analysis method Refine current circle-based analysis method Likelihood of use Likelihood of use Extent of use Extent of use Degree of effects Degree of effects Repeatable methods Repeatable methods Future applications Future applications Landscape level assessments of potential for NSO occupancy Landscape level assessments of potential for NSO occupancy Habitat restoration activities Habitat restoration activities Prescribed fire and fuels management Prescribed fire and fuels management NSO Project Objectives Models Study Area Data Methods and Analysis Research Relevance Potential Challenges

22. Potential Challenges Maxent and HexSim models Maxent and HexSim models Permission for some data can be revoked Permission for some data can be revoked Too much data Too much data Addition of abiotic variables Addition of abiotic variables Abiotic variables may not be important to NSO Abiotic variables may not be important to NSO Time!! Time!! NSO Project Objectives Models Study Area Data Methods and Analysis Research Relevance Potential Challenges

23. Acknowledgements Brian Woodbridge, U.S. Fish and Wildlife Service Brian Woodbridge, U.S. Fish and Wildlife Service Jeff Dunk, Humboldt State University Jeff Dunk, Humboldt State University Nathan Schumaker, U.S. Environmental Protection Agency Nathan Schumaker, U.S. Environmental Protection Agency Dave LaPlante, Natural Resource Geospatial Dave LaPlante, Natural Resource Geospatial National Council for Air and Stream Improvement National Council for Air and Stream Improvement Fruit Growers Supply Company Fruit Growers Supply Company Timber Products Company Timber Products Company Klamath National Forest Klamath National Forest

24. Questions?