Isaac Overcast

Investigating biodiversity across spatial, temporal, and taxonomic scales.

Materials from various workshops I have organized and contributed to. Workshop materials are normally sufficiently detailed to serve as stand-alone tutorials. In general the most recent workshop will have the most up-to-date information, but each workshop is slightly different, and the older materials should still contain some useful information.

RADSeq Assembly and Analysis

RADCamp workshops are designed to introduce ipyrad, a unified and self-contained RADSeq assembly and analysis framework, which emphasizes simplicity, performance, and reproducibility. In these workshops we proceed through all the steps necessary to assemble a typical RADSeq dataset. Additionally, we introduce the ipyrad ‘analysis’ API which provides a powerful, simple, and reproducible interface to several widely used methods for inferring phylogenetic relationships, population structure, and admixture.

Model-based inference in Phylogeography from single species to communities

CompPhylo workshops are designed to introduce a myriad of tools for making statistical inference about historical processes using genetic/genomic data. After introducing statistical approaches in model-based inferences, participants are be introduced to inference frameworks that span taxonomic scales from single-species demographic inference, to multi-species comparative analysis, to inference at the scale of the whole community. Participants also get hands on experience using approximate Bayesian computation, supervised machine learning and composite likelihood methods for model comparison.

  • CompPhylo Mexico City (2023; ½ Day; SSB Standalone Meeting; UNAM, Mexico City, Mexico)
  • Phylogeographic Temporal Analysis (PTA): Model based comparative phylogeography with machine learning
  • CompPhylo Oslo (2019; 5 Day; University of Oslo)

Multidimensional Biodiversity Data Analysis & Process-Based Modelling

This is a two-part workshop aimed at rapidly bringing participants to a high level of proficiency in the management and analysis of multidimensional biodiversity data. Part I serves as an introduction to data management and visualization, and serves as a crash course in the data methods that will be necessary to participate in Part II, which focuses on analyzing biodiversity data using process-based models and machine learning.

Multidimensional biodiversity data: management and analysis
Biodiversity researchers must work with an array of data types, including community composition and abundance information, trait, phylogenetic and genetic data. Traditionally, studies in ecology and evolution have worked with only one or a few of these data types. To successfully advance the study of biodiversity across different levels of organization, biodiversity scientists are nonetheless finding the need to integrate multiple of these disparate data types into the same analytical workflow. This workshop will promote learning in the use of multidimensional data streams, gathering biodiversity scientists and students from different sub-disciplines to help facilitate integrative, cross-specialization research.

Goals of the Workshop: This two-day workshop will introduce different data types used by biodiversity scientists in an integrative framework. We will cover common approaches for working with abundance, trait, phylogenetic, and genetic data separately, and proceed to methods for working with multiple dimensions of biodiversity data simultaneously. Finally, we will explore motivations and platforms for archiving, sharing, and accessing multidimensional biodiversity datasets as part of the wider scientific community (e.g. GEOME).

Process-based modeling and statistical inference
Process-based models are a powerful framework for generating theoretical expectations and exploring hypothetical scenarios that can then be linked directly to multidimensional biodiversity data streams (e.g. joint data on genetic and species diversity) for hypothesis testing and statistical inference. While several excellent simulation modeling platforms have been developed in recent years, these models can be technically sophisticated and difficult to work with for new users. This workshop will provide an introduction to a process-modeling approach and hands-on experience working through a complete workflow, using a user-friendly process model implemented in R: the Rules of Life Engine (RoLE) model. RoLE is a process-based eco-evolutionary simulation model which incorporates all relevant biodiversity processes (drift, migration, selection, speciation) and makes joint predictions of multiple dimensions of biodiversity data.

Goals of the Workshop: This two-day workshop will provide an introduction to process based modeling using the RoLE model. We will cover the philosophy and motivation behind process modeling, the use of simulation models to explore hypotheses and develop theoretical intuition, and statistical methods for using empirical data to test the hypotheses generated through process modeling.