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Integration of NASA technology and wildlife ecology for use by the National Park Service (Systems Integration and Visualization of Yellowstone) Fred Watson.

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Presentation on theme: "Integration of NASA technology and wildlife ecology for use by the National Park Service (Systems Integration and Visualization of Yellowstone) Fred Watson."— Presentation transcript:

1 Integration of NASA technology and wildlife ecology for use by the National Park Service (Systems Integration and Visualization of Yellowstone) Fred Watson 1*, Bob Garrott 2*, PJ White 3*, Susan Alexander 1*, Rick Wallen 3, Wendi Newman 1, Thor Anderson 1, Tom Thein 1, Jon Detka 1, Claire Gower 2, Jason Bruggeman 2+, Matt Becker 2, Sally Plumb 3, Chris Geremia 3 1 California State University Monterey Bay, 2 Montana State University Bozeman, 3 Yellowstone National Park, * Principal Investigators, + Formerly Presented at NASA Biodiversity and Ecological Forecasting Team Meeting May 2 nd 2008, University of Maryland, College Park Funding: NASA NCC2-1186 & NCC13-03009, NSF DEB 0074444 & DEB-0413570, and NPS EcoViz: Yellowstone Ecosystem Science and Visualization

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4 Crew Volunteers: PIs: Staff & postgrads: Under- grads: National Parks Service:

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6 Forest cover survey

7 EcoViz: Yellowstone Ecosystem Science and Visualization Landsat land cover mapping

8 EcoViz: Yellowstone Ecosystem Science and Visualization Meadow phenology survey

9 MODIS phenology

10 Wind data collection EcoViz: Yellowstone Ecosystem Science and Visualization

11 Wind field model

12 EcoViz: Yellowstone Ecosystem Science and Visualization Geothermal perimeter survey

13 EcoViz: Yellowstone Ecosystem Science and Visualization Geothermal heat flux map

14 EcoViz: Yellowstone Ecosystem Science and Visualization Snowpack coring

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17 National Parks Service bison monitoring & management activities EcoViz: Yellowstone Ecosystem Science and Visualization

18 Bison movement

19 EcoViz: Yellowstone Ecosystem Science and Visualization More coring

20 ...more coring

21 ...more coring

22 ...more coring

23 EcoViz: Yellowstone Ecosystem Science and Visualization

24 Key bison areas near the Park boundary

25 EcoViz: Yellowstone Ecosystem Science and Visualization Snowpack nowcasting

26 How is the nowcasting used? “The products that you sent a couple of weeks ago were fantastic and just what we needed to convey how the snowpack conditions this year compare to the 25 year range of variability. Thank you very much for those model runs!!! We used the information in the attached brief.”...

27 EcoViz: Yellowstone Ecosystem Science and Visualization Bison distribution ~ Road grooming doesn’t strongly influence bison travel (Bruggeman et al.)

28 How are the publications used? “...development of several new approaches to understand the causes, timing, and routes of migratory movements by bison (Bison bison) that, in turn, have been applied to management decisions regarding boundary control measures and the potential for brucellosis transmission to cattle (Bjornlie and Garrott 2001, Ferrari and Garrott 2002, Coughenour 2005, Gates et al. 2005, Gogan et al. 2005, Borkowski et al. 2006, Bruggeman et al. 2006, 2007; Fuller et al. 2007a, Olexa and Gogan 2007, Chapters 26-28). These studies also provide the best available scientific information from which adjudicators, park managers, and stakeholders can infer the potential effects of winter recreation and road grooming on bison and other wildlife.” White et al. (In Garrott et al., In press.)

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30 Journal papers Book chapters

31 Broad, Robust, Efficient But potentially more difficult to identify linkages between specific management environments and data products (?) More focused, decisions realized within project timeframe But difficult to scale up & generalize Therefore costly This project

32 Key points In our experience at Yellowstone: –A bottom-up approach leads to realized outcomes in terms of National Park decision making –The bottom-up approach takes a great deal of time, resources, and teamwork –It must rest on published foundations –The dissociation of time scales for funding, collaboration, publication, and decision making heightens the challenge In the case of Yellowstone bison: –Forecasting ecological response requires careful attention to spatio- temporal pattern –This requires: spatio-temporal wildlife data, spatio-temporal landscape models, and analytical methods for relating them to each other. Can this approach be scaled for better efficiency? EcoViz: Yellowstone Ecosystem Science and Visualization

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