Sustaining Lakes in a Changing Environment (SLICE) Sentinel Lakes Program Ray Valley and Don Pereira

1. Sustaining Lakes in a Changing Environment (SLICE) Sentinel Lakes Program Ray Valley and Don Pereira

2. Talk Outline • The Why - History, motivations, and aims of program • The What - Program design and sentinel lake selection • The How - Data collection activities and partnerships • The So What - Lessons learned

3. Talk Outline • The Why - History, motivations, and aims of program • The What - Program design and sentinel lake selection • The How - Data collection activities and partnerships • The So What - Lessons learned

4. Why Focus on Lakes? • Minnesota is known for her lakes • Lakes don’t flush • Focal integrators of time and space

6. Why – Glacier-like changes to landscape and climate • Shoreline and nearshore transformations • Impervious surfaces • Hydrological transformations • Human accelerators of species spread • Climate change

7. Consequences on Resilience • Cumulative impacts of stressors • Stressors to watersheds • Ditching, draining, channeling, • Impervious surface • Withdrawing & damming • Alterations to lakes • Overharvest/Overstocking • Removal of structure • Disturbance from watercraft • Time Lags • Hysteresis – “can’t go back” • Positive feedbacks Cumulative impacts of stressors System “state” Scheffer and Carpenter 2003

8. Reality Bites! In a lot of systems there’s no “going back.” Our expectations and management approach for these systems should be different for systems largely “intact”

9. Enter SLICE – informing expectations and appropriate mgt responses We ask: • In highly altered systems, how can we realistically improve water quality and provide a self-sustaining recreational fishery? • In high integrity systems, what watershed and in-lake factors are contributing to their resilience, and how can we keep those resilience mechanisms intact? • Early Detection and Rapid Response indicators What indicators tell us “all is not well” and indicate whether our responses are making a difference?

10. Sustaining Lakes in a Changing Environment (SLICE) • Program aims to: • Timely detect change to habitat conditions and species population communities • Understand and project what is/will come into our lakes (watershed modeling) • Understand and project the ultimate fate of external and internal loads (limnological modeling) • Facilitate structured decision-making and adaptive management

11. Talk Outline • The Why - History, motivations, and aims of program • The What - Program design and sentinel lake selection • The How - Data collection activities and partnerships • The So What - Lessons learned

12. Phase 1 (Pilot; 2008-2011): • Pilot phase • Establish network of sentinel lakes • Partnership and infrastructure building • Independent research projects to assess specific questions • Indicator ID • Phase 2 (2012-2016) • Using lessons learned in Pilot to guide operational program Eating the elephant one bite at a time! chrisnierhaus.com

13. Adaptive Management Process Phase 1: Oct – Jan 2006/2007 Phase 2 2013 Assess problem Phase 1 Op plan 2012 Adjust Design May-Jun 2007 Evaluate Implement Monitor 2011-12 Apr. 2008 2008-2011

14. Planning and Decision Framework Oversight DNR Fisheries1 Project Coordination2 Ray Valley 1. Information base Recommendation of direction Implementation DNR Fisheries Implementation Technical Advisory Team Eco and Waters Implementation Strategic Advisory Team PCA Implementation Analysis and Evaluation MDH Implementation PCA Water Monitoring Unit Local trends Analysis Teams Syntheses of trends Local Partners DNR Area Staff Local trends Local Partners Local trends Citizen Volunteers Public Information and Outreach Ancillary Investigations

15. Experimental Design

16. Three R’s of Statistical Study Design • Realism • Randomization • Representation Population Sample Inference

17. Questions for us here to consider: • At what spatial scale do we want to draw inference? • How much of the state do we want to cover or how “representative” do we want to be? • How quickly do we want to detect change and “check in on status?” • The answers to these questions will guide the appropriate statistical design

18. Objective of SLICE:Annual inference of status and trends in lake indicators at the Landscape Scale

19. Sentinel Lake Selection

20. Sentinel Lake Selection Stratified Approach 1. Landtype x 4 2. Mixing x 2 3. P-Concentration x 3

21. Other considerations with final candidate pool • PCA “reference” lake • Other historical datasets • Paleolimnology • Rich lake survey history • Unique partnership opportunities • Active local water monitoring programs

22. The Sentinel Lakes

23. SLICE is more than Sentinel Lakes – “Split-Panel” Design

24. Panel 1: Sentinel Lakes (2008 - ) • Stratified sampling design • Figurative Approach: “6-in wide, 1 mile deep” • Monitoring system-wide changes at a fine temporal resolution in a small number of systems spread across the state • Synchronous trends - are things behaving similarly across large scales? • Cause-effect inference • Forecast modeling w/ cont. verification Year 1 2 3 4 5 6 7 8 = The network of sentinel lakes

25. Panel 2: “Random” surveys (2013 - ) • Approach: “1 Mile-wide 6” deep” • Focus is on maximizing lakes sampled, minimal time spent at each one. • Combination with Sentinel panel is powerful for robust inference of status across time and space • Will focus on utilizing datasets from other ongoing monitoring programs Year 1 2 3 4 5 6 7 8 = Group of Lakes

26. Sentinel Lake Characteristics (ranges)

27. Sentinel Lake watershed sizes are skewed Median = 9 Median = 31 km2 Are these watersheds representative of other Minnesota lake watersheds??

28. Median = 12 km2

29. Median = 12km2

30. Median = 10

31. Sentinel Lake watershed sizes are representative! Median = 9 Median = 31 km2

32. Talk Outline • The Why - History, motivations, and aims of program • The What - Program design and sentinel lake selection • The How - Data collection activities and partnerships • The So What - Lessons learned

33. Question:What data do we need and who’s going to collect it?

34. Started with a conceptual model of system behavior

36. Right partners for the right job • PCA, DNR, SNF, Citizen Volunteers, local units of govt, researchers efficiently deployed • Research staff evaluating: • Indicator “vetting” – signal:noise • Appropriate lake and watershed models • Reconstructing past conditions • Efficient sampling methodology • Reporting and data management structures in place. • Leveraging multiple funding sources

37. “If you build it, they will come” • A platform for interdisciplinary study of lakes • Independent “off-shoot” projects focused on: • Cold-water fish and habitat • Historical reconstructions of water quality and zooplankton • Zooplankton patterns • Groundwater-surface water interactions • “Free” Analysis off of our “Free” data • Projects, investigators, lakes involved, and contact info is being tracked on SLICE web page

38. Talk Outline • The Why - History, motivations, and aims of program • The What - Program design and sentinel lake selection • The How - Data collection activities and partnerships • The So What - Lessons learned

39. Lessons Learned – Successes • Eating an elephant one bite at a time • Right partners doing the right job • We built it and now they are coming • Structured-decision making and adaptive learning process

40. Lessons Learned – Mulligans Take logistics as seriously as strategy

41. Designating a project/program “Coordinator” is a no-brainer and something the state does well

42. The logistics of who they are coordinating is another matter entirely that rarely receives sufficient attention

43. Span of Control Issues: Herding Cats • Getting dozens of staff to be all doing the same thing is not easy!

44. Other Admin Issues to consider • Data QA/QC • Data management and dissemination • Appropriate staffing for the workloads • Communication plan

45. Departing thoughts… • Stressors are slowly wearing away the resilience of our water and fisheries resources • Greater urgency with lakes – they are our legacy and they don’t flush. • Most MN lake watersheds are small – good from a management standpoint. • The interdisciplinary partnerships are the backbone of SLICE • Advice for sentinel watershed planning – give logistic operations of carrying out a program its due during the planning process.

46. Funding and Partners