SIMMAP

One-sentence definition. SIMMAP (Stochastic Mapping) is a Bayesian method that samples complete histories of character-state transitions mapped continuously onto each branch of a phylogeny, providing a posterior distribution over the number and timing of each transition.

One-sentence analogy. SIMMAP is like asking not just “what state was an ancestor in?” but “draw me a full movie of how the trait changed across the whole tree, accounting for uncertainty” — you get thousands of such movies and summarize them statistically.

Why it matters. Stochastic mapping is central to the lab’s work because it allows co-occurrence analyses (e.g., do Y chromosome gains co-occur with reductions in autosome number?), expected state dwell times, and transition count posteriors — quantities that simple parsimony or marginal likelihood reconstruction cannot provide. In Adephaga beetles, stochastic mapping over karyotype and sex chromosome states simultaneously estimates that at least 49% of Y chromosome gains co-occur with autosome-number reductions consistent with X–autosome fusions. Summary statistics from 1,000 stochastic maps are routinely reported in the lab’s chromosome evolution papers.

Where you meet it in the wiki.

• Ancestral state reconstruction — stochastic mapping as the Bayesian complement to marginal reconstruction.
• Sex chromosome evolution — stochastic mapping used to quantify Y-gain co-occurrence with fusion events.
• Karyotype evolution overview — SIMMAP for chromosome number and state histories.

Primary citation. null

Prerequisites: Mk model, ancestral state reconstruction Next, learn about: BiSSE, ancestral state reconstruction