measuring biological diversity eeeb g6185 james a. danoff-burg dept. ecol., evol., & envir....

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Measuring Biological Measuring Biological DiversityDiversity

EEEB G6185EEEB G6185

James A. Danoff-Burg

Dept. Ecol., Evol., & Envir. Biol.

Columbia University

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

Today: Course IntroductionToday: 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

Goals of the CourseGoals 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

Course FormatCourse 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

Tools to AcquireTools 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

Course ScheduleCourse 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

Course RequirementsCourse 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

Course MaterialsCourse 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

Content IntroductionContent 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

Basics of Basics of Measuring Biological Measuring Biological

DiversityDiversity

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

CommunityCommunity

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

Implications of DefinitionImplications 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

Basics of Basics of Measuring Biological Measuring Biological

DiversityDiversity

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

Aspects of BiodiversityAspects 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

How to Summarize How to Summarize & Describe Nature?& 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

Types of Censusing DesignsTypes 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

Choosing Between Choosing Between Censusing DesignsCensusing 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

Surveying DesignSurveying 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

Surveying TechniquesSurveying 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

Basics of Basics of Measuring Biological Measuring Biological

DiversityDiversity

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

Purposes of ReplicationPurposes 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

Some DefinitionsSome 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

Pseudoreplication - DefinedPseudoreplication - 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

Prevalence of Prevalence of PseudoreplicationPseudoreplication

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

ExamplesExamples

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

Pseudoreplication ExamplePseudoreplication 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 A Treatment B

Site 1

Site 2

Site 3

Site 4

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

Controlling Pseudoreplication IControlling 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

Controlling Pseudoreplication Controlling Pseudoreplication IIII

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

Basics of Basics of Measuring Biological Measuring Biological

DiversityDiversity

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

Application of Techniques – Application of Techniques – An ExerciseAn 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

Basics of Basics of Measuring Biological Measuring Biological

DiversityDiversity

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

AssignmentAssignment

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

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