MLU Master’s Module: Modelling Species Distribution and Biodiversity Patterns

Part II: Measuring and comparing biodiversity patterns and processes

Instructor:

Prof. Jonathan Chase ([email protected])

Co-Instructors:

Dr. Paola Barajas ([email protected]); Dr. Shane Blowes ([email protected]); Dr. Daniela Hoss ([email protected]); Dr. Emma Ladouceur ([email protected]); Dr. Alban Sagouis ([email protected]); Dr. Kimberly Thompson ([email protected]); Dr. Roel van Klink ([email protected]); Dr. Wubing Xu ([email protected])

Course plan:

Week 1: (January 10-14): Mechanisms of biodiversity: Metacommunities Theory and Practice

Monday: Lecture, Reading, Discussion, Exercise (Jon)

Tuesday: Introduction to modelling, metacommunity theory, simulations, and exercises (Shane)

Wednesday: Metacommunity analysis: variation partitioning lecture and exercises (Wubing)(morning); from GLMs to jSDM; lecture and exercises (Kim)(afternoon)

Thursday: Independent project/analysis: simulations, analyses of empirical and/or simulated data (Kim/Wubing/Shane)

Friday: Independent project/analysis (Morning): Presentation/discussion (Afternoon)

Week 2: (January 17-21): Measuring and comparing patterns of (taxonomic) diversity

Monday: Lecture, Reading, Discussion, Exercise (Jon)

Tuesday: Calculating biodiversity metrics (richness, evenness, Hill numbers); mobr lesson (Roel)

Wednesday: Effects of sampling on biodiversity measures (species accumulation curves, etc); mobsim (Alban)

Thursday: Independent project/analysis: simulations, analyses of empirical and/or simulated data (Alban, Roel)

Friday: Independent project/analysis (Morning): Presentation/discussion (Afternoon)

Week 3: (January 24-28): Functional Diversity and Biodiversity and Ecosystem Functioning (BEF)

Monday: Lecture, Reading, Discussion, Exercise (Jon)

Tuesday: Measures of Functional Diversity (Hill Numbers) (Paola)

Wednesday: Biodiversity, Metacommunity Assembly, and Ecosystem Functions (biomass, stability) (Daniela, Emma)

Thursday: Independent project/analysis: simulations, analyses of empirical and/or simulated data (Paola, Daniela, Emma)

Friday: Independent project/analysis (Morning): Presentation/discussion (Afternoon)

Course Expectations and Grading:

The learning objectives of this course will be primarily achieved by course attendence and participation in excercises and activities. Attendence/participation is mandatory. Grading will be primarily through course attendence and participation in 'in class' activities and short weeekly independent projects