Module II: Stream Ecology

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Module II Stream Ecology

• BIOL3144 Ecology Lab

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Research goals

• To investigate the role of riparian buffers on
  water quality and biological processes in a
  stream.
• Research site Toby Creek

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Technical goals

• To learn techniques for determination of water
  quality parameters
• To design and carry out an experiment for
  comparison of decomposition rates in stream areas
  with and without riparian buffers
• To compare invertebrate communities in stream
  areas with and without riparian buffers.

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Brief Intro What is a riparian zone?

• Interface between land and a flowing body of
  surface water (e.g. river, stream, creek)

Riparian zone in Everglades
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Brief Intro Functions of riparian buffer

• Dissipation of stream energy
• Sediment trap
• Filters pollutants from surface runoff
• Provides wildlife habitat, increase biodiversity
• Wildlife corridors
• Native landscape irrigation (extends seasonal or
  perennial flows of water)
• Temperature buffer

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Brief Intro Effects of a riparian buffer on
water temperature
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Goals for brainstorming session

• Hypotheses?
• Experimental design?
• Study locations?
• Measured parameters?

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Basics of experimental design in ecology

• Data collection replication
• Statistical analysis

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Why replication is needed?

• Experimental or observational units are chosen as
  similar as possible however they are not
  identical!
• There is always unwanted variation between your
  experimental or observational units can you get
  rid of it?

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Pseudoreplication How to avoid it and what to do
if it cannot be avoided
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Statistic tidbits

• Parametric vs non-parametric tests
• Assumptions of parametric statistics
• Paired vs non-paired tests

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Steps in statistical analysis of data (1)

• Test for outliers
• Measurement error, experimental error, true
  outlier
• Determine whether the data are normally
  distributed
• If yes, proceed to parametric tests (such as
  t-test or ANOVA)
• If not, transform data so that they become
  normally distributed
• If transformation does not result in normally
  distributed data, proceed with non-parametric
  tests (e.g. Kruskall-Wallis test, Wilcoxon test)

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Steps in statistical analysis of data (2)

• If the data are normally distributed and you have
  decided to use t-test to compare means, you need
  to determine whether your comparisons are paired
  or not
• If yes, proceed with paired t-test
• If no, proceed with unpaired t-test

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Gaussian (Normal) distribution

• Measures of central tendency
• Mean
• Median
• Mode

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Grubbs test for outliers
OUTLIERS
Before testing for outliers ask yourself
Was the value entered into the computer
correctly? Were there any experimental problems
with that value?Is the outlier caused by
biological diversity?
if Z gt Ztabl, then Plt0,05 gt reject H0
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Testing for normality
GraphKolmogorov-Smirnov test (d-statistic)Shapir
o-Wilks test (W-statistic)
if d- or W-statistic is significant gt your
distribution is NOT normal

• Data transformationLogarithmic (measurement
  data) log (X) Square root (counts)
  vXReciprocal (time, duration) 1/X Arcsine
  (proportion) Arcsine(vX)

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Students t-test
df nxny-2
?
Paired t gt ta
df n-1
S?
? mean difference between X and Y