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Analysis of macroinvertebrates as indicators of biotic integrity . Hypothesis development. Environmental quality of the Poudre River Urban impact from Fort Collins Influence assessed through physical, chemical and biological characteristics. Data sampling. Environmental data

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Presentation Transcript
hypothesis development
Hypothesis development
  • Environmental quality of the Poudre River
  • Urban impact from Fort Collins
  • Influence assessed through physical, chemical and biological characteristics
data sampling
Data sampling
  • Environmental data
    • Physical data
      • Watershed-scale
        • Urbanization, road density, etc.
      • Reach-scale
        • Stream width, slope, etc.
    • Chemistry data
      • Nitrate, conductivity, etc.
  • Biological data
    • Invertebrate metrics
      • Taxonomic, biotic index, species traits
    • Epilithon
      • AFDM, Chl a
    • Benthic organic matter
      • AFDM
taxonomic community structure
Taxonomic community structure
  • Richness (how many taxa)
  • Abundance (how many individuals per taxa)
  • Specific taxonomic groups
    • Based on knowledge of group tolerance levels
      • % Chironomids
      • % Ephemeroptera, Plecoptera and Trichoptera (EPT)
biotic index
Biotic index
  • A score that represents the species’ tolerance to disturbance
  • Based on observation and expert opinion, not ecological theory

Abundance

Tolerance

Total

Chironomidae

30

×

8

=

240

5.5

Lepidostomatidae

10

×

1

=

10

=

20

×

4

=

80

Baetidae

60

330

species traits
Species traits
  • Traits are morphological, behavioral, ecological, or physiological characteristics of species
  • Traits link the environment to species distribution
  • Convert community metric (e.g., richness, abundance, biomass) into proportion of taxa with each trait state

Rhithrogena

60%

40%

Hydropsyche

Baetis

Rhyacophila

Pteronarcys

descriptive statistics
Descriptive statistics
  • Central tendency
    • Mean or median
  • Variance
    • Standard deviation or error
  • Range
    • Minimum and maximum
  • Distribution
    • Histogram of data
hypothesis testing
Hypothesis testing
  • For every hypothesis, there is a null
  • For example
    • You observe that shredders eat leaf material, which is a significant portion of benthic organic matter (BOM)
    • Hypothesis: Shredder distribution is dependent on the quantity of BOM
      • Null: Shredder distribution is NOT dependent on BOM quantity
    • Alternative hypothesis: Small streams have more leaf litter per unit area, so shredder abundance is related to the width of streams
      • Null: Shredder abundance is NOT related to stream width
null hypothesis testing
Null hypothesis testing
  • Statistics test the null hypothesis
  • P-value is the probability that the null hypothesis is true
  • Or, if the data were randomly generated, P-value is the probability that you would find the same result
anova
ANOVA
  • Tests the means and variances of categorical data
    • Two or more samples per category required to calculate variance
    • T-test equivalent to ANOVA with only two categories
regression
Regression
  • Tests the variances between two sets of continuous variables
    • May explain relationship (positive or negative)
    • Will test strength of relationship (R2)
    • Can compute P-value