Which Factors Drive Macroevolutionary Rates of Speciation and Extinction

Introduction

Biodiversity is modeled by the process of speciation and extinction. There is clear evidence both from living and extinct species that biodiversity is extremely variable through time and among species. However, we still do not know what factors, e.g., environmental or species intrinsic, drive speciation and extinction rates on a macroevolutionary level.

Challenges in Biodiversity Modeling

To complicate matters, species diversification models are not identifiable. That is, there are infinitely many combinations of continuous speciation and extinction rate functions that are statistically indistinguishable.

Research Objectives

1. Extend Diversification Models
   First, I will extend previous diversification models to jointly infer time-varying and lineage-specific diversification rates using phylogenies of extinct and extant taxa.

2. Address Non-Identifiability
   Second, I will tackle the non-identifiability problem and explore which patterns, e.g., rapid increases in diversification rates and mass extinctions, can be inferred.

3. Combined Paleo-Phylogenetic Approach
   Third, I will use a combined paleo-phylogenetic approach and estimate diversification rates from phylogenies with extinct and extant taxa.

Methodology

Thus, I will combine statistical, computational, neontological, and paleobiological approaches to study macroevolutionary dynamics.

Data Collection

I will produce species-level phylogenies for each of the following groups:

• Carnivora
• Cetartiodactyla
• Crocodyliformes
• Squaliformes

This will be done using novel morphological datasets and models.

Hypothesis Testing

I will test if diversification rates are correlated with:

• Environmental factors (e.g., CO2 or temperature)
• Species-specific traits (e.g., body size and life history traits)

Ultimately, we will test if specific traits are correlated with mass extinction survival probabilities, as for example, the Lilliput Effect predicts smaller species to have higher survival probabilities.