2. Hypothesis development Environmental quality of the Poudre River Urban impact from Fort Collins Influence assessed through physical, chemical and biological characteristics

3. 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

4. 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)

5. Biotic index A score that represents the species’ tolerance to disturbance Based on observation and expert opinion, not ecological theory Baetidae Chironomidae Lepidostomatidae AbundanceToleranceTotal 30 10 20 × × × = = = 8 1 4 240 10 80 60330 5.5 =

6. 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 Small SizeLarge Size Rhithrogena Baetis Rhyacophila Pteronarcys 60%40%Hydropsyche

7. Descriptive statistics Central tendency Mean or median Variance Standard deviation or error Range Minimum and maximum Distribution Histogram of data

8. 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

9. 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

10. 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

11. Regression Tests the variances between two sets of continuous variables May explain relationship (positive or negative) Will test strength of relationship (R 2 ) Can compute P-value