STUDY DESIGN and INTERPRETATION

• Experimental and mensurative studies
• Categorical and quantitative data
• Sample size, power, effect size analysis

DATA ANALYTICS

• Consolidate information from databases
• Geographic Information Systems (GIS) mapping and spatial statistics 
• Scripting using R programming, R markdown
• QAQC and cleaning of complex data sets
• Data summaries, frequencies of occurrence, and visualizations 
• Community metrics (diversity, size-based indicators, biomass, abundance)

ADVANCED ANALYTICS

• Mixed effects modelling
• Hierarchical linear models (HML)
• Boosted regression tree (BRT) analysis
• Size spectrum modelling (normalized abundance size spectrum (NASS), normalized biomass size spectrum (NBSS), maximum likelihood estimation (MLE))
• Loading calculations using stratified Beale ratio estimator, weighted regression on time, discharge, and season - Kalman filter (WRTDS-K), stratified event mean concentration (EMC)
• Modelling censored data
• Simulating discharge, hydrograph separation

PRESENTATIONS and REPORTS

• Presenting complex data and findings to non-technical audiences
• Communicating science to policy advisors
• Literature review of primary research, reviews, and grey literature
• Synthesize complex knowledge into guidance and plain language summaries 
• Writing technical reports and peer-reviewed journal articles