Measuring Biological Diversity EEEB G6185

1. Measuring Biological DiversityEEEB G6185 James A. Danoff-Burg Dept. Ecol., Evol., & Envir. Biol. Columbia University

2. Today: Course Introduction • Introduction to the course • Tools to acquire • Course format • Course requirements • Required materials • Content: Basics of measuring biological diversity © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

3. Goals of the Course • Provide skills in censusing & measuring biological diversity • Choosing appropriate indices for your question • Comparing biodiversity between samples • Design your thesis / dissertation? • Publish a paper or two together? © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

4. Course Format • Weekly meetings, W 4:10 - 6:00 • 252 Engineering Terrace computer center • Preparatory readings • Southwood & Henderson 2000 • Magurran 1988 • Primary literature & Web resources • Lecture introduction • In-class exploration of techniques • Write-ups of the techniques • Produce a publishable paper? © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

5. Tools to Acquire • Survey techniques • How to design your survey • Specific to question, taxon, location • Diversity indices – understanding & use • Point: diversity at a single point or microenvironment • Alpha: within habitat diversity • Beta: species diversity along transects & gradients • High Beta indicates number of spp increases rapidly with additional sampling sites along the gradient • Gamma: diversity of a larger geographical unit (island) • Epsilon: regional diversity (if time) • Applying biodiversity to conservation decisions © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

6. Course Schedule • Week 1; 22 Jan - Intro to community diversity & biotic inventories, • Week 2; 29 Jan - Richness, abundance, & generation of biodiversity • Week 3; 5 Feb - Evenness & broken stick diagrams • Week 4; 12 Feb - Simple community diversity indices I • Week 5; 19 Feb - Simple community diversity indices II • Week 6; 26 Feb - Simple community diversity indices II • Week 7; 5 Mar - Choosing between & improving indices (JDB away?) • Week 8; 12 Mar - Beta diversity indices • Week 9; 19 Mar - Spring Break • Week 10; 26 Mar - Community ordination techniques • Week 11; 2 Apr - Gamma diversity indices I • Week 12; 9 Apr - Gamma diversity indices II • Week 13; 16 Apr - Prioritizing areas for conservation • Week 14; 23 Apr - Implementing conservation decisions • Week 15; 30 Apr - Deadline for submission of term paper © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

7. Course Requirements • Several short write-ups through term – 20% • Approximately 4-8 • Ex: describe an appropriate sampling protocol for your research question • In-Class participation – 30% • Final paper – 50% • Due at end of term • Written collaboratively © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

8. Course Materials • Required: • Magurran 1988 (Labyrinth) • EstimateS • (from Rob Colwell at http://viceroy.eeb.uconn.edu/EstimateS) • Excel and SPSS software programs • Others • Recommended: • Southwood & Henderson 2000 (Labyrinth) © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

9. Content Introduction • Will begin biodiversity & indices next week • Today – Basics of Measuring Biological Diversity • Introduce some terms • Talk about experimental design to collect biodiversity data • Discuss how to implement designs © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

10. Basics of Measuring Biological Diversity • What is a community? • What is biodiversity & how to survey it? • Censusing • Pseudoreplication • Applying these techniques • Assignment for next time © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

11. Community • Define community? • Some possibilities • Group of populations in a single place (Krebs 85) • Assemblage of species populations which occur together in space & time (Begon et al. 86) • Distillation & modification: • Group of interacting populations, single time, single defined place © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

12. Implications of Definition • Species in a community interact with each other • Can include all species • Can be limited to a single guild • More common, more tractable • Defined by a consistent spatial boundary How we design our studies (sampling & indices) depends on our question © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

13. Basics of Measuring Biological Diversity • What is a community? • What is biodiversity & how to survey it? • Pseudoreplication • Applying these techniques • Assignment for next time © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

14. Aspects of Biodiversity • What can we measure? • Possibilities • Species (richness) • Abundance • Diversity • relationship between richness & abundance • Guild • Trophic structure • Evolutionary diversity • Within species diversity (genetic, morphological) • Others? © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

15. How to Summarize & Describe Nature? • Near-infinite number of things to record • How to simplify? • Dictated by: experimental question, location, taxon • Sample (really subsample) from nature • Choose an aspect of biodiversity • Location • Life stage • Etc. © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

16. Types of Censusing Designs • Grid • Using regular intervals along a 2-dimensional design • Transect • Sampling with reference to a straight line • Random • Can be used to site point-quarters, quadrats, other sampling methods © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

17. Choosing Between Censusing Designs • How to choose between sampling layouts? • Depends on experimental question • Gradients • Probably best to use a transect • Ensures comparability • Relatively uniform sampling area • Random probably best – if done frequently enough, get equal representation of areas included • Grid may be useful when need to uniformly sample area © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

18. Surveying Design • Need to equally capture / census entire community (or subset) to be studied • Be consistent • Have equal sampling effort in different areas • Time, area, quantity sampled • Appropriately represent area studied • Equally sample disparate constituent areas • Random vs. orderly (grid, transect)? © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

19. Surveying Techniques • In short: Any viable form of collecting or sampling • Need to be sited at a level appropriate to the question • Examples: • Point-Quarter • Proximity to a central point within a cross • Quadrat • Sampling within a small area • Pitfall traps • Beating Sheets • Mist netting • Seining • Etc… © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

20. Basics of Measuring Biological Diversity • What is a community? • What is biodiversity & how to survey it? • Pseudoreplication • Applying these techniques • Assignment for next time © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

21. Purposes of Replication • Why replicate? • Controls for random or stochastic error • E.g., untested independent factors may otherwise determine the outcome of the experiment • Increases the precision of the test • Increases the generalizability of the test • If you test across many sites – you can safely generalize to many others © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

22. Some Definitions • Replicate = Sample • Maximize these in your experimental design • Greatest number possible, given logistical limitations • If you are a professional, use a power analysis • Subsample = Pseudoreplicate • Only true if the subsamples are incorrectly treated as true replicates for statistical analysis • Subsamples: useful to increase the accuracy of the data estimate for that replicate • A special type of statistical analysis are therefore possible © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

23. Pseudoreplication - Defined • Incorrect “replication” • Replicating samples, not treatments • Replicates are not independent • Problem is that it violates a key assumption of statistical analysis: • Independence of replicates • Increasing precision of studies if independent • Approximates “truth” better if independent • Accounts for normal random error • Allows us to set α and keep it constant • All of these are violated if pseudoreplicated © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

24. Prevalence of Pseudoreplication • 48% of all studies had pseudoreplication (Hurlbert, S.H., 1984. Pseudoreplication and the design of ecological field experiments. Ecological Monographs 54:187-211) • 71% of studies using ANOVA (a common statistical test) had design errors (Underwood. 1981. Techniques of analysis of variance in experimental marine biology and ecology. Ann. Rev. Oceanogr. Mar. Biol.19: 513-605) • Particularly acute in studies with logistical problems • Rare animals • Transportation or financial limitations • Many that are in print! © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

25. Examples • Many samples from a single site • These are actually subsamples • Only a single sample for each treatment condition • These are actually replicates, but cannot do statistics on a sample size of one • Single samples from a single site, but replicated in time • Would be true samples if the experimental question is time-dependent • If not, it is pseudoreplication © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

26. Pseudoreplication Example Treatment A Treatment B • Question – What is the affect of treatments A & B? • Pseudoreplication = treating stars of the same color as replicates • Replication = include only a single star of each color, or their average Site 3 Site 1 Site 2 Site 4 © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

27. Controlling Pseudoreplication I • Know your question • Question determines whether design includes pseudoreplication • Taxonomic level • Ecological hierarchy level • Clearly define your independent and dependent variables © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

28. Controlling Pseudoreplication II • What constitutes a unit of data? • Plant branch? Individual? Population? Etc.? • Identify what is the unit of replication • Individual? Population? Community? Site? • Replicate accordingly – sites are often the level of replication for our projects • Randomize your sampling design • Helps to decrease sampling errors • Increases accuracy of estimation © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

29. Basics of Measuring Biological Diversity • What is a community? • What is biodiversity & how to survey it? • Pseudoreplication • Applying these techniques • Assignment for next time © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

30. Application of Techniques – An Exercise • Group up • Design a study, avoiding pseudoreplication • Include visual representations of sampling method • Include: • Experimental question • Manipulations • Hypotheses (null, alternatives) • Target organisms • Censusing design • Censusing method © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

31. Basics of Measuring Biological Diversity • What is a community? • What is biodiversity & how to survey it? • Pseudoreplication • Applying these techniques • Assignment for next time © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu

32. Assignment • Project of your own design • Write up a short (2-3 paragraphs) description of your proposed study in normal scientific prose • Include question and hypotheses (including null and all alternative hypotheses) • Include sampling design, sampling method • Be specific and thorough • Email to jd363@columbia.edu before the start of class next week © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu