2. Ecological Principles of Diversity 1. Principle of Limiting Similarity - There is a limit to the similarity of coexisting competitors; they cannot occupy the exact same niche. 2. Niche Separation / Differentiation - Competitors use different resources to coexist. 3. Environmental heterogeneity - Creates more niche possibilities; therefore, higher environmental diversity leads to higher species diversity.

3. Purpose, Hypotheses, and Prediction PURPOSE: Test the idea that increased environmental/physical diversity leads to increased species diversity. PURPOSE: Test the idea that increased environmental/physical diversity leads to increased species diversity. Hypotheses and predictions Hypotheses and predictions H 1 : Fish diversity increases with habitat diversity in the physical environment, due to competition for niche space and the principle of limiting similarity. H 1 : Fish diversity increases with habitat diversity in the physical environment, due to competition for niche space and the principle of limiting similarity. Prediction: There will be a significant positive correlation between fish diversity and habitat diversity. Prediction: There will be a significant positive correlation between fish diversity and habitat diversity.

4. Other Possible Hypotheses The fish assemblage is structured by: Predation or number of trophic levels Predation or number of trophic levels Flooding Flooding Glacial and geographic history (age of the stream, and its history of isolation) Glacial and geographic history (age of the stream, and its history of isolation) (more are possible…use your knowledge of ecology to think of a few more) (more are possible…use your knowledge of ecology to think of a few more)

5. Habitat Parameters that Could Influence Species Composition 1. Physical (our focus) Water depth Water depth Current velocity Current velocity Substrate type Substrate type 1. Physical (extra) Temperature Temperature 2. Chemical Dissolved O 2 Ions pH 3. Biological Other organisms present Nutrient input Nutrient cycling Note: We are not measuring all factors, so this is not a complete test of the hypothesis (we can support but not falsify).

6. Background for Calculations Diversity addresses 1) how many categories exist, and 2) how evenly the categories are represented. Diversity addresses 1) how many categories exist, and 2) how evenly the categories are represented. For example, we may have 2 communities with 7 species (species richness = 7) and 21 total individuals, but each species may not be represented evenly. For example, we may have 2 communities with 7 species (species richness = 7) and 21 total individuals, but each species may not be represented evenly. More Diverse  Less Diverse 

7. Evenness addresses how evenly the categories are represented. Numbers of species do not matter. Note that unless you add evenness values together, they cannot be higher than 1.00. Evenness addresses how evenly the categories are represented. Numbers of species do not matter. Note that unless you add evenness values together, they cannot be higher than 1.00. Evenness = 0.63 Evenness = 0.98Evenness = 1.00

8. A. E. H. G. C. F. B. D.

9. A. E. H. G. C. F. B. D. H’= 1.38 H’= 0.41 H’= 0.69 H’= 1.39 H’ = 1.10 H’= 1.39 H’= 1.24 H’ = 1.61

10. Diversity Calculations For the fish assemblages and habitat parameters we calculate diversity using the following equation: For the fish assemblages and habitat parameters we calculate diversity using the following equation: H’=-∑ p i lnp i Where p i = # of individuals in a category/total # of individuals

11. Diversity and Evenness Calculations We calculate evenness using the following equation: J=H’ln(S) Where S = # of categories of habitat type that you measured in your data.

12. Is There a Correlation Between Habitat Diversity and Species Diversity? Today, we will compile fish diversity and habitat evenness results from all groups in our lab. Today, we will compile fish diversity and habitat evenness results from all groups in our lab. This correlation will only involve two or three data points, so it will probably not be significant. Therefore, we also will examine some data from a previous year to increase sample size (n). This correlation will only involve two or three data points, so it will probably not be significant. Therefore, we also will examine some data from a previous year to increase sample size (n).