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

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Presentation on theme: "Measuring Biological Diversity EEEB G6185 James A. Danoff-Burg Dept. Ecol., Evol., & Envir. Biol. Columbia University."— Presentation transcript:

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

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

3 © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu 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?

4 © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu 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?

5 © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu 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

6 © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu 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

7 © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu 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

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

9 © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu 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

10 © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu 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

11 © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu 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

12 © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu 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

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

14 © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu 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?

15 © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu 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.

16 © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu 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

17 © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu 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

18 © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu 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)?

19 © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu 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…

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

21 © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu 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

22 © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu 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

23 © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu 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

24 © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu 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!

25 © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu 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

26 © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu Pseudoreplication Example  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 Treatment ATreatment B Site 1 Site 2 Site 3 Site 4

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

28 © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu 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

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

30 © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu 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

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

32 © 2003 Dr. James A. Danoff-Burg, jd363@columbia.edu 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 weekjd363@columbia.edu


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