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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