1. terminology species data = the measured variables we want to explain (response or dependent variables) environmental data = the variables we use for explaining the species data (explanatory or independent variables) sites are rows columns are variables

2. data transformation Usually applied to response variables only – Make the measurement scales similar or the same – Stabilize variance (log / sqrt) – recode into binary variables

3. association measures Q mode – distances, e.g., Euclidean R mode – correlations, e.g., Pearson's correlation

4. distances Q mode, quantitative – Bray-Curtis gives the same weight to same differences in abundances irrespective of the scales 1... 2 -> 1 and 1001... 1002 -> 1 Usually at least square root transformation before distances are calculated – Hellinger abundances are divided by the site's total abundance and then square root transformed

5. distances Q mode, presence / absence – Jaccard