1. Factors Influencing Pika Foraging Behavior in North Cascades National Park, Washington Rachel Richardson 1,2 and Jason Bruggeman 1 1--Beartooth Wildlife Research, LLC; 2--University of Montana

2. Rising temperatures Changing precipitation patterns Increased frequency of extreme weather events Shifting species distributions Upslope range contractions in alpine species Global Climate Change

3. Alpine species are vulnerable! American pika (Ochotona princeps)

4. Pika Ecology Small herbivorous lagomorphs Restricted to talus slopes (i.e., rock piles) Well adapted to moist, cool climates Behaviorally thermoregulate Resting body temperature near lethal maximum Sensitive to higher temperatures Retreat under rocks to avoid stressful daytime temps (Smith 1974)

5. Climate Change Indicator Species

6. Pika Foraging Behavior Grazing behavior - immediately consume plants Haying behavior - collect, transport, and store plants for winter use - cache vegetation in hay piles

7. Why are these hay piles important? Provide adequate forage for overwinter survival (Dearing 1997) Seasonal fluctuation in food availability Enable pikas to manage resources during winter Preferred plants contain beneficial compounds (Dearing 1997) Hay piles may insulate nesting sites from extreme temps (Krear 1965) Provide predator protection (Ivins 1984)

8. However … Short summer growing season (early July – August) Time available to build hay piles restricted (Huntly et al. 1986) Increased foraging during peak vegetation biomass (Morrison et al. 2009) Thermal stress may constrain time available for foraging

9. North Cascades National Park Encompasses 275,684 ha in north central Washington Elevations ranging between 300 and 2,800 m

11. Study Area

12. High Priority Species

13. Primary Research Question: How will a changing climate affect pika foraging behavior?

14. Research Plan Collect data on pika behavioral time budgets Calculate proportion of time spent grazing and haying Evaluate relationships between foraging behaviors and temperature, elevation, date, climate and vegetation covariates

15. Data Collection Methods Pika Surveys - Direct observations - Audible vocalizations - Active hay piles with fresh vegetation Focal Animal Sampling - 5 minute individual observations on up to 5 pikas in a patch

16. Data Collection Methods Habitat Attributes - 25 m vegetation transects (classification, % cover) - Recorded surface temperature - GIS elevation layer Covariate Estimation - Data from 8 NRCS SNOTEL sites (estimate SWE, melt date)

17. 2009 Surveys 30 1-km 2 areas surveyed in 2009 27 areas with pikas Behavioral observations in 15 of the selected sites

18. 2010 Surveys 13 1-km 2 areas resurveyed in 2010 13 areas with pikas Behavioral observations in 8 of the selected sites

19. Analysis Methods 8 predictor variables: TEMP, ELEV, DATE, MELT, SWEMAX, VEGCOVER, FORAGECOVER, YEAR Logistic regression modeling Evaluated 71 models with additive combinations of covariates R 2.6.2 to fit models and estimate parameter coefficients AIC c and w i for each model ΔAIC c to rank and select top models

20. Hypotheses CovariatesProportion of time grazing Proportion of time haying Temperature -- Elevation ++ Date -+ Date of spring snowmelt + - Maximum snowpack snow water equivalent (SWEMAX) +- Proportion of vegetation cover ++ Proportion of forage cover ++

21. Results 95 foraging observations 15 unique 1-km 2 survey areas and 37 unique patches ELEV: 889 – 2,173m (mean = 1,552; SE = 34) TEMP: 42.9°F – 83.5°F (mean = 61.5; SE = 1.0) DATE: June 25 - September 27 (mean = August 14; SE = 2) SWEMAX: 0.5 - 1.1 m (mean = 0.72; SE = 0.02 ) MELT: May 12 - August 9 (mean = June 14; SE = 2) VEGCOVER: 0.07 - 0.66 (mean = 0.29; SE = 0.01) FORAGECOVER: 0.0 - 0.3 (mean = 0.09; SE = 0.01)

22. Results -- Grazing Models ModelΔAIC c w i 47 0.000.808 46 2.930.187

23. ModelΔAIC c w i 47 0.000.808 46 2.930.187 Model #47 Coefficient Sign TEMP- ELEV- DATE- MELT + VEGCOVER- YEAR (2010)+ Results -- Grazing Models All significant at P = 0.05

24. Results -- Haying Models ModelΔAIC c w i 46 0.000.999 47 13.960.001

25. Results -- Haying Models ModelΔAIC c w i 46 0.000.999 47 13.960.001 Model #46 Coefficient Sign TEMP+ ELEV+ DATE+ SWEMAX - VEGCOVER+ YEAR (2010) - All significant at P = 0.05

26. Some answers … CovariatesProportion of time grazing TEMP- DATE- MELTDATE+ CovariatesProportion of time haying DATE+ ELEV+ VEGCOVER+ SWEMAX- TEMP : Behavioral thermoregulation DATE : Time/energetic considerations MELTDATE : Time constraint ELEV : Availability of higher quality forage, lower temperatures VEGCOVER : Increased availability of vegetation in a talus patch SWEMAX : Greater snowpack accumulation may delay melt and influence new vegetative growth

27. More questions … CovariatesProportion of time grazing ELEV- VEGCOVER- CovariatesProportion of time haying TEMP+ ELEV : Differences in plant abundance/quality among elevations? VEGCOVER : Influence of preferred forage types? TEMP : Data limitation? Not enough observations at higher temps?

28. Conclusions -- Pikas and Climate Change Multiple interacting factors influencing pika foraging behavior Increasing temps, shifting precip patterns may negatively impact forage availability - Less forage = smaller hay piles - Smaller hay piles = lower winter survival (reduction in food and nest insulation)

29. Conclusions -- Pikas and Climate Change Increasing temps may also limit time available for foraging - Less daytime activity = shift to night activity? Low elevation populations may experience effects of climate warming first - Unsuitable habitat = low elevation extirpations = upslope range contractions

30. Management Recommendations Compare environmental variables across elevations Observations throughout the day to better understand temp variability Evaluate changes in plant communities across elevations Annual surveys!

31. North Cascades NPS Complex Seattle City Lights Wildlife Research Program Field crews during 2009 and 2010 Acknowledgements

32. Questions?