Analytical Paleobiology Short Course: Diversity estimation and multivariate methods

(Led by Jessica)

• Introduction to material
  • Data types
  • Types of diversity
  • Challenges
• Estimating richness
• Estimating diversity and evenness
• SAD, RAD

(Led by Michal and Jessica)

• Intro: similarity vs dissimilarity (Michal)
• Diversity partitioning and beta diversity (Michal)
• Cluster analysis (Jessica)
• Example: Generalized dissimilarity modeling (Jessica)

(Led mostly by Michal)

• Intro to matrix algebra, PCA (Michal)
• PCO, CA/DCA, NMDS (Michal)
• Canonical Methods: CVA, RDA, CCA, CAP (Michal)
• Multivariate tests (as time allows, Michal)
• Example: Functional data (Jessica)

• Spillover
• Practicum

Major Goals

• Summarize complex patterns within and across assemblages
• Determine dominant drivers/correlates of those patterns

Main Data Types

• Assemblage information for a single site
• Species* x site matrices
  • Occurrence or abundance of species at each site
  • *Species here is a surrogate for any unit of taxonomic information

Auxiliary Data Types

• Attributes of sites: Location, habitat, climate
• Attributes of species: Functional type, phylogenetic information

Diversity is an often vague word that describes how individuals are partitioned into species within sites and across the landscape.

We recognize three types of diversity:

• gamma: the overall diversity of the landscape, which can be partitioned into:
  • alpha: the diversity of individual locations within that landscape
  • beta: how diversity changes across the landscape

Today's exercises will focus on alpha diversity, and we'll focus on beta diversity tomorrow.

Fundamental goal:

• Describe how and why assemblages change across space and time

First step:

• Estimate the following:
  • Who / how many species are present in an assemblage?
  • How do we adequately characterize the structure of assemblages?

Aspects of assemblage structure

• Number of species (ie, richness)
• Distribution of abundance across species (Evenness, dominance measures)
• Types/attributes of species

• Difficult to estimate the true number of species present in a location for many groups and habitats
  • This is even more challenging in the fossil record due to preservation and taphonomic issues that alter what information is preserved.
• Difficult to make apples-to-apples comparisons across space or through time
  • Uneven sampling effort
  • Different deposition/preservation contexts