8  Introduction to the MESS Model

8.1 Key questions

1. What is the MESS Model?
2. How does MESS differ from other biodiversity models?
3. What are some example applications of MESS?
4. Where can I get a cool MESS logo sticker?

8.2 Lesson objectives

After this lesson, learners should be able to…

1. Describe the (high-level) concept for MESS.
2. Situate MESS in the wider process modeling state space.
3. Formulate scientific questions and decide if/how MESS can be used to explore them.

8.3 Planned exercises

8.3.1 Process-based modeling with the Massive Eco-evolutionary Synthesis Simulations (MESS) Model

Neutral Assembly Process

8.3.2 Overview of MESS simulation and analysis workflow

The basic steps of MESS model simulation-based machine learning inference are as follows:

• Step 1 - Set model parameters based on prior knowledge of empirical system
• Step 2 - Run many, many simulations
• Step 3 - Use ML to infer community assembly process (neutral/competition/filtering)
• Setp 4 - Use ML to estimate key community assembly parameters
• Step 5 - ???
• Step 6 - Profit!!

8.4 Key points

• MESS is a process-based model in the direct lineage of Island Biogeograpy Theory and Neutral Biodiversity Theory.
• MESS models the 4 fundamental biodiversity processes: dispersal, speciation, selection, and drift.
• MESS generates joint predictions of multiple biodiversity patterns: abundances, trait values, genetic diversities, and phylogenies.