1. Welcome to Methods in experimental ecology PCB 6466

2. Instructor: Pedro F. Quintana- Ascencio, Office: Biology Bldg. 401 E Phone: 823-1662 pquintan@mail.ucf.edu http://biology.ucf.edu/~pascencio / pquintan@mail.ucf.edu Office hours : Mon-Wed: 8:00-10:00 Or by appointment

3. Species correlates of Florifacies mirabila in playa linda Pedro Quintana-Ascencio University of Cancun, Yucatan, Mexico

4. Florifacies mirabila Small mammal Feed on insects. It has glandules around the mouth producing a sweet secretion that attract plant pollinators. It is extremely sedentary Endemic to the Yucatan peninsula

5. Thorny plant (Opuntia sp.)

6. Objective To evaluate the association between Florifacies and Thorny plant (Opuntia sp.) Hypothesis Because both have flower like structures Florifacies and Thorny plant are positively associated

7. Methods I “subjectively” established 59 1 x 2 m plots I counted every individual of Florifacies and Thorny plant (Opuntia sp.) within the plot Data was entered in Excel and analyzed with SPSS software

8. Florifacies mirabila Thorny plant Nice Palms Pedro Quadrats Sampling design

9. Are Florifacies and Thorny associated ? FlorifaciesTotal AbsentPresent ThornyAbsent46450 Present459 Total50959 Likelihood ratio = 10.155, d.f.= 1, Asymptotic significance (2 sided)=0.001 3 cells (75.0%) have expected count less than 5. The minimum expected count is.17

10. Individual density N=59 quadrats Do Florifacies density correlates with thorny plant density? How?

11. Conclusions Florifacies and Thorny plant (Opuntia sp.) are associated (P=0.001) Their densities are are positively correlated (P<0.001) My hypothesis was correct

12. What is wrong? Do you agree with this conclusions? Is the experimental design acceptable? Is the analysis correct? Write a one page commenting your conclusions on this analysis

13. How can we access this door? Experimental design and Data Analysis

14. What we need? ?

15. We need to Be able to design experiments and sampling programs optimally Know the pitfalls and assumptions of particular statistical methods Be able to identify the type of model appropriate for the sampling design and kind of data that we plan to collect Be able to interpret the output of analysis using these models

16. We need to Frame our questions in such a way as to get a sensible answer Be aware of biological considerations that may cause statistical problems Understand the advice or analysis that we receive, and be able to translate that back into biology

17. Class objectives We will learn to: Design sampling programs that represent the best use of our resources Review and discuss case studies to recognize common research problems in ecology Avoid mistakes that make analyzing our data difficult Analyze the data Apply available statistical analysis in a critical way to address ecological research problems Compare different ecological and statistical techniques Recognize the advantages and limitations of different approaches to evaluate ecological data

18. What is this course about? Everybody is learning We will learn by example. We will have exercises in most classes Why R?

19. All statistical analysis Are variations of a common theme of statistical modeling: Constructing a model for the data and then determining whether observed data fit this particular model