Jeff Stetz, M.Sc. Research Ecologist ~ Sinopah Wildlife Research Associates Ph.D. Candidate ~ Wildlife Biology ~ U

1. Bear Populations in the NCDE & The Grizzly DNA Project Jeff Stetz, M.Sc. Research Ecologist ~ Sinopah Wildlife Research Associates Ph.D. Candidate~ Wildlife Biology ~ University of Montana Post-doctoral Researcher ~ University of Tennessee

2. Why am I here today? • Why do we care about (bear) populations? • What is reliable knowledge and why is it so important? • What tools did we use and why? • How did we estimate vital rates? • - individual and population level

3. Why am I here today? • Why do we care about conserving bear populations? • What is reliable knowledge and why is it so important? • What tools did we use and why? • How did we estimate vital rates? • - individual and population level

4. For starters, legal obligations • Federally listed Threatened species since 1975 • Need to maintain viable populations

5. Also, we like bears. • Culturally important for 10,000s of years

6. Popular culture

7. College mascots • Pro sports teams

8. Well, maybe not everyone does. • Vicious killer? • How dangerous, really?

9. 1 person out of 16,000 commits murder but only 1 grizzly bear out of 50,000 ever kills someone and only 1 black bear out of one million does.  

10. Also, conserving biodiversity: • Ecosystems • Species • Genes Unique role b/n Rescue Unique potential

11. Brown – Grizzly – Kodiak Bear Range

12. Historic Grizzly Bear Range in N. America Need to increase our knowledge of population drivers for conservation Post-glacial Historic Present

13. Why am I here today? • Why do we care about bear populations? • What is reliable knowledge and why is it so important? • What tools did we use and why? • How did we estimate vital rates? • - individual and population level

14. knowledge ≠ wisdom We really suck at this…. wisdom Shooting for this… How do we get at any of this?

15. For most of us, ‘belief’ is based on: Estimates of precision and bias, which is tough to know, so we use The latest and greatest fancy-ass model

16. To get at truth…. λ The answer lies in understanding causation. π Ψ Why How, what Where, which When, who Closed-ended (yes/no) The $100,000 Question Pyramid

17. Instead, we spend our careers chasing λ π Ψ Why How, what Where, which And that’s what we did When, who Closed-ended (yes/no)

18. Case study: grizzly abundance in the NCDE

19. Why am I here today? • Why do we care about bear populations? • What is reliable knowledge and why is it so important? • What tools did we use and why? • How did we estimate vital rates? • - individual and population level

20. Research and monitoring…new ways • Use DNA “fingerprint” to identify and track bears • Non-rewarding lure • ‘non-invasive’ • Read: less bias If you have questions about the genetics: Pid, He, etc…

21. Research and monitoring…new ways • No bait • Natural behavior (read: less bias?) • Super easy

22. Snapshot of NCDE grizzly bear: • Population “size”

23. Estimated NCDE grizzly abundance - 2004 So we used the latest and greatest fancy-ass model Pr(det) < 1 Total ? ?

24. Huggins-Pledger closed population mark-recapture models - with temporal, group, and individual covariates - mixture-model for unmodeled heterogeneity in pr(det) AICcand model averaging

25. Estimated NCDE grizzly abundance - 2004 For the record, essentially the same as Lincoln-Petersen

26. Snapshot of NCDE grizzly bear: • Population “size” • Distribution

27. Abundance and “density” • Highest densities in GNP, Great Bear • “Healthy” densities in the Bob, Whitefish Range • Rough ideas of where, but no idea why

28. Geographic distribution • Continued expansion to east, west, and south • Occupied habitat 1.4x size of recovery zone (~3.1 million ha)

29. Snapshot of NCDE grizzly bear: • Population “size” • Distribution • Genetic health

30. Genetic “health” • Summary: • Bears assigned to sub-populations • Compared across time periods • Less difference now than <1998

31. Identifying barriers to geneflow

32. Identifying potential barriers to geneflow Hwy 2 West Hwy 2 East Fst = 0.04 Fst = 0.01 Log (L(North)) Log (L(South)) Log (L(South)) Population fragmentation likely with unmitigated future development. Remember, crossing a road ≠ geneflow

33. Monitoring trend • “Snapshots” are great, but not the most important question • Montana FWP: population trend will guide management decisions • Did not identify method for estimating trend

34. ‘‘The optimum monitoring system should … not require continuous capture and handling of animals… or highly trained and specialized personnel whose time is solely devoted to grizzly bear monitoring.’’

35. Research and monitoring…traditional

36. Seems cool and exciting, but LOTS of work and is dangerous!

37. GPS data • Pros/cons: • Depends on objective/questions • Lots of information about relatively few animals • More risks to humans and animals • Can be difficult to reach targets in remote areas (read: sampling bias?)

38. Lots of work, but can be very powerful • FWP trend study • Density-distributed effort • Estimated from SSD that of female population: • 31% dep. offspring • 19% subadults • 50% adults • MANY other parameters • Estimated growth rate at 3% (95% CI: 0.93–1.10) • Not very precise; lengthy • Better options?

39. Using Noninvasive Methods to Monitor Grizzly Bear Population Status • Closed population model estimates of Pr(det) • Conducted simulations to evaluate open population models for trend • Suggest <5% CV within about 4 years

40. Using Noninvasive Methods to Monitor Grizzly Bear Population Status • USFS funded • Objectives • lambda • occupancy • relative density • genetic structure

41. Bear rub surveys • >5,000 rubs set up • 10s of thousands of hair samples per year • Analysis ongoing(?)

42. MONITORING TREND • Pradel (1996) models use CMR-type data to estimate: • realized rate of population change (rea) • apparent survival (φ) Photo: Dan Carney • and abundance (N) with > 2 surveys per year rea = Nt+1 / Nt= the net change given allpopulation processes: Nt+1= Nt + (births + immigration) – (deaths + emigration)

43. Getting back to the pyramid…. λ • Typically we address “applied” questions • The answer lies in understanding causation • Unfortunately… π Ψ Why How, what Where, which When, who Closed-ended (yes/no) The $100,000 Question Pyramid

44. Which N? Which λ? λ π Ψ

45. Know your population, dammit!

46. Know your population, dammit! Catch a larger percentage of adult bears, but all bears are represented in the sample* 92 2004 grizzly bear detections 71 16 76 11 6 2 8 M F Ad SA Yrl CoY

47. Role of Research • Locally, bears are doing well, with strong research efforts on-going • We’re learning what works and what doesn’t • Things can go bad quickly for bears if we let them

48. Locally, bears are doing well, with strong research efforts on-going • We’re learning what works and what doesn’t • We still can’t get at ‘why’ quite yet Post-glacial Historic Present

49. Bottom line? • Lots of tough questions • Some are actually important to conservation, but many are not • As professionals, we need to distinguish the two and identify the best way to answer them • Generally, this means doing good science • But we have to recognize it is an iterative process, and that other values can be far more important than data, ie beliefs vs truths

50. Thank you - Questions?