1. …empowering communities through modeling and adaptive management Evaluate & Share Did We Make It?

2. Adaptive Management Framework Plan Where should we go? Implement How will we get there? Evaluate Did we make it? Discuss Where are we? Share Who should know?

3. Step 4: Evaluation 1.Prepare data for analysis 2.Analyze results 3.Compare results to desired model scenario

4. Prepare data for analysis How are you going to compare the data? Compare two groups to see if they are different? Compare more than two groups? Are two variables related to each other? There are many statistical tests designed to do different tasks. Each has strengths and weaknesses

5. Prepare data for analysis How are you going to compare the data? Compare two groups to see if they are different? Compare more than two groups? Are two variables related to each other? There are many statistical tests designed to do different tasks. Each has strengths and weaknesses

6. Analyze your results The key reason for analyzing your results is to see if the treatment had a real and measurable effect. Sometimes, small perceived differences could be due to random fluctuations Scientists use the “95% confidence interval” to be sure that the differences they see are likely due to the experimental variable, and not random chance

7. Analyze your results The key reason for analyzing your results is to see if the treatment had a real and measurable effect. Sometimes, small perceived differences could be due to random fluctuations Scientists use the “95% confidence interval” to be sure that the differences they see are likely due to the experimental variable, and not random chance

8. Comparisons Compare results to the predictions made by the model scenarios. Are our data consistent with our proposed model? How should we change our model in light of this information? Is there further data we can collect to improve our model?

9. Data Analysis Example Let’s assume that your goal was to increase habitat quality in a local stream by reducing runoff from local farms and neighborhoods.

10. Data Analysis Example After extensive research, your group decides that a good measure of stream habitat quality is the number of chironomid fly larvae in the stream.

11. Data Analysis Example The stream was sampled for fly larvae one month before the restoration and exactly one year later Meters South of Bridge102030405060708090100110120130 Chironomid population before intervention15122519185117212325131718 Chironomid population after intervention11253945492030253544 3037 In most of the sites, the number of larvae increased.

12. Data Analysis Example The stream was sampled for fly larvae one month before the restoration and exactly one year later Meters South of Bridge102030405060708090100110120130 Chironomid population before intervention15122519185117212325131718 Chironomid population after intervention11253945492030253544 3037 But in some, it decreased

13. Data Analysis Example The stream was sampled for fly larvae one month before the restoration and exactly one year later Meters South of Bridge102030405060708090100110120130 Chironomid population before intervention15122519185117212325131718 Chironomid population after intervention11253945492030253544 3037 The average number of larvae is higher after the intervention, but is this difference statistically significant? Average (mean) = 33 Average (mean) = 21

14. Data Analysis Example Degrees Of Freedom12 Test Statistics2.72139Pooled Variance111.08333 Two-tailed distribution p-level0.01856t Critical Value (5%)2.17881 By using a T-test, we can see that there is about a 1.8% chance that the data we collected were done so from two populations that were in fact NOT different. Since this is less than 5%, we can safely say that there is a real difference before and after.

15. Data Analysis Example But wait! Do we KNOW that the difference was caused by our intervention? What else could have caused the differences we noted?

16. Data Analysis Example But wait! Do we KNOW that the difference was caused by our intervention? What else could have caused the differences we noted? Reduction of a predator by over fishing? A new nutrient caused by a landowner using a new fertilizer? Climate change? Almost anything!

17. Data Analysis Example Controls!

18. Adapt Your Model and Plan Revise model and desired scenario Adjust implementation plan as needed Plan Where should we go? Implement How will we get there? Evaluate Did we make it? Discuss Where are we? Share Who should know?

19. Adaptive Management Plan Where should we go? Implement How will we get there? Evaluate Did we make it? Discuss Where are we? Share Who should know?

20. Share Sharing the results of the intervention is really a three part process: 1.Document 2.Share 3.Use

21. Document Keeping accurate records Keeping well organized records Making a final report Making an “executive summary” or press release

22. Show CollaborativeScience.org tools

23. Share Identify key stakeholders needing access to information Land owners Land managers Interested members of the community The scientific community Distribute widely Media organizations Community organizations Newsletters, listservs, websites Scientific publication

24. Use Remember that adaptive land management is similar to the scientific process: results from previous trials need to be used to inform future decisions. Hopefully, your group will continually improve how your project develops.

25. …empowering communities through modeling and adaptive management This project is funded by the National Science Foundation

26. The Virginia Master Naturalist Program is sponsored by the following agencies.