1. Modeling bat activity across the fire- managed landscape of Mammoth Cave Nat’l Park using remotely-sensed forest canopy data Dodd, L.E. 1, M.J. Lacki 1, N.S. Skowronski 2, M.B. Dickinson 2, & L.K. Rieske 3 1 Forestry Department, University of Kentucky 2 Northern Research Station, US Forest Service 3 Entomology Department, University of Kentucky

2. Remote Sensing & Wildlife Large-scale patterns 1 Large-scale patterns 1 Feasibility Feasibility Necessity Necessity 1 Vierling et al. 2008. Frontiers in Ecology & the Environment 6: 90-98. Hudak et al. 2009. Remote Sensing 1: 934-951..

3. Bats at Mammoth Cave Variable foraging & habitat use across species 1 Variable foraging & habitat use across species 1 Prey availability & forest canopy structure Prey availability & forest canopy structure White-nose syndrome White-nose syndrome Now at Mammoth Cave; changing predator-prey dynamics? Now at Mammoth Cave; changing predator-prey dynamics? 1 Swartz et al. 2003. Pp. 257-300 in: Bat Ecology. Lacki et al. 2007. Pp. 83–128 in: Bats in Forests: Conservation and Management

7. Core Hibernacula - 2004 - 2005 - 2007 - 2009 - 2008 - 2010 Burn Areas Mammoth Cave Nat’l Park

8. Core Hibernacula - 2004 - 2005 - 2007 - 2009 - 2008 - 2010 Burn Areas Survey Transects, Aug 2010 onward Mammoth Cave Nat’l Park

9. Core Hibernacula - 2004 - 2005 - 2007 - 2009 - 2008 - 2010 Burn Areas Survey Transects, Aug 2010 onward Mammoth Cave Nat’l Park

10. Methods

11. Methods

12. Methods Bat Activity Zero-crossing acoustic surveys Zero-crossing acoustic surveys Spanning 2010-2012 (still ongoing) Spanning 2010-2012 (still ongoing) 170 nights (1,086 detector / nights) 170 nights (1,086 detector / nights) Emphasis on April-May, Aug-Oct Emphasis on April-May, Aug-Oct

13. Methods Bat Variables Echoclass v.1.1 1 Echoclass v.1.1 1 High freq (> 34 kHz) High freq (> 34 kHz) Low freq (≤ 34 kHz) Low freq (≤ 34 kHz) Feeding buzzes Feeding buzzes 1 USFWS. Indiana Bat Survey Guidance. http://www.fws.gov/midwest/Endangered/mammals/inba/inbasummersurveyguidance.html

14. Methods Bat Variables Echoclass v.1.1 1 Echoclass v.1.1 1 High freq (> 34 kHz) High freq (> 34 kHz) Low freq (≤ 34 kHz) Low freq (≤ 34 kHz) Feeding buzzes Feeding buzzes Total Activity 1 USFWS. Indiana Bat Survey Guidance. http://www.fws.gov/midwest/Endangered/mammals/inba/inbasummersurveyguidance.html

15. Methods LiDAR Survey Figure by Renslow LiDAR = Light Detection and Ranging LiDAR = Light Detection and Ranging Discrete-return scanning LiDAR 1 Discrete-return scanning LiDAR 1 900-1,600 nm wavelength 900-1,600 nm wavelength > 4 pulses / m² > 4 pulses / m² 1 Skowronski et al. 2007. Remote Sensing of Environment 108: 123-129.

16. Methods LiDAR Survey Figure by Renslow LiDAR = Light Detection and Ranging LiDAR = Light Detection and Ranging Data collected Fall 2010 (leaf-off) via fixed-wing aircraft Data collected Fall 2010 (leaf-off) via fixed-wing aircraft

17. Methods LiDAR Variables What scale is meaningful? What scale is meaningful?

18. Methods LiDAR Variables 1 Lesak et al. 2011. Remote Sensing of Environment 115: 2823-2835 Laser returns across over-, mid-, & understory strata 1 Laser returns across over-, mid-, & understory strata 1 Under Mid Over

19. Methods LiDAR Variables 15 m Laser returns across over-, mid-, & understory strata 1 Laser returns across over-, mid-, & understory strata 1 15 m radii around survey points 1 15 m radii around survey points 1 1 Lesak et al. 2011. Remote Sensing of Environment 115: 2823-2835 Under Mid Over

20. Methods LiDAR Variables Strata (absolute & relative) Strata (absolute & relative) Over-, mid-, & understory Over-, mid-, & understory Determining canopy shape Determining canopy shape Mid:Over, Under:Mid, & Under:Over Mid:Over, Under:Mid, & Under:Over

21. Methods LiDAR Variables Strata (absolute & relative) Strata (absolute & relative) Over-, mid-, & understory Over-, mid-, & understory Determining canopy shape Determining canopy shape Mid:Over, Under:Mid, & Under:Over Mid:Over, Under:Mid, & Under:Over Gap Index Gap Index Percentage of pixels with no laser returns >3 m height Percentage of pixels with no laser returns >3 m height

22. ANOVAs for site, temporal, & fire effects ANOVAs for site, temporal, & fire effects Analysis & Results

23. ANOVAs for site, temporal, & fire effects ANOVAs for site, temporal, & fire effects Multiple linear regressions relating activity to forest veg Multiple linear regressions relating activity to forest veg Response variables: Response variables: - high freq pulses - low freq pulses - feeding buzzes - high freq pulses - low freq pulses - feeding buzzes Predictive models: Predictive models: - understory - midstory - overstory - “total” clutter - understory - midstory - overstory - “total” clutter Model selection using Akaike’s Information Criterion Model selection using Akaike’s Information Criterion Models in SAS 9.0, then protocol of Burnham & Anderson 1 Models in SAS 9.0, then protocol of Burnham & Anderson 1 1 Model Selection & Multimodal Inference, 2 nd Edition Analysis & Results

24. Site, Season, & Annual Effects

25. Unsurprisingly, lots of variation across sites! Unsurprisingly, lots of variation across sites!

26. Site, Season, & Annual Effects Far fewer replicates (n = 6)

27. Site, Season, & Annual Effects

29. High Freq: F 2,1083 = 3.6, P = 0.02 Low Freq: F 2,1083 = 29.2, P < 0.01 AAB ab c

30. Site, Season, & Annual Effects

31. A B B a bab No apparent WNS impacts in 2012… No apparent WNS impacts in 2012… High Freq: F 2,1083 = 4.1, P = 0.02 Low Freq: F 2,1083 = 3.0, P = 0.05

32. Site, Season, & Annual Effects

33. Sites surveyed in Fall 2010 Sites surveyed in Fall 2010

34. Effect of Fire Core Hibernacula - 2004 - 2005 - 2007 - 2009 - 2008 - 2010 Burn Areas Survey Transects, Aug 2010 onward Repeated visits have Repeated visits have created a time-series… created a time-series…

35. As with sites, lots of variation across years since burn! As with sites, lots of variation across years since burn! Effect of Fire

36. Far fewer replicates (n ~ 5)

37. Effect of Fire Far more replicates (n > 200 each)

38. Effect of Fire

39. High Freq: F 2,1083 = 11.1, P < 0.01 Low Freq: F 2,1083 = 1.0, P = 0.37 A BB Effect of Fire

40. A BB Feeding Buzzes F 2,1083 = 11.1, P < 0.01 Effect of Fire

41. Core Hibernacula - 2004 - 2005 - 2007 - 2009 - 2008 - 2010 Burn Areas Survey Transects, Aug 2010 onward

42. Effect of Fire Analyses pending

43. Effect of Fire Analyses pending

44. Effect of Fire Analyses pending

45. Effect of Fire Relation to Canopy Clutter Data within first year of burning (2010-2011) Data within first year of burning (2010-2011)

54. High frequency echolocators negatively High frequency echolocators negatively associated a cluttered understory associated a cluttered understory

57. Low frequency echolocators negatively Low frequency echolocators negatively associated with a cluttered understory & overstory associated with a cluttered understory & overstory

58. Feeding buzzes negatively associated with a cluttered Feeding buzzes negatively associated with a cluttered understory & overstory; positively associated with canopy gaps understory & overstory; positively associated with canopy gaps

59. Low Frequency Bat Activity Predictive Map – Total Clutter

60. Discussion & Implications Activity lower at burned sites, but models suggest activity is also Activity lower at burned sites, but models suggest activity is also positively related to less-cluttered canopy conditions… positively related to less-cluttered canopy conditions… High frequency & low frequency echolocators both respond to High frequency & low frequency echolocators both respond to differences in clutter… And are relatable to management! differences in clutter… And are relatable to management! How does this relate to longer-term fire management plans? How does this relate to longer-term fire management plans?

61. Funding Funding – Joint Fire Science Program NPS Personnel NPS Personnel – Dr. Rick Toomey – Steve Thomas – Shannon Trimboli Tech Support! Tech Support! – Tracy Culbertson – Stella James – Klint Rose – Jennifer Winters Thanks!