Zenil-Ferguson, Rosana

Group Research Activities

The Zenil-Ferguson lab studies the tempo and mode of the evolutionary processes that generate phenotypic diversity across the Tree of Life. Our research collects biodiversity data via fieldwork, herbaria, and museums to understand macroevolution. To that end, we build phylogenetic trees and stochastic models that connect trait change to phylogenies. Overall, our research program can be divided into two approaches. First, the development of process-based models to understand trait evolution and diversification in plant phylogenies. The development of process-based models requires the integration of mathematics, statistics, and computer science with key evolutionary processes to create meaningful models and inferences in macroevolution. Second, we estimate the robustness of inferences derived from macroevolution models which requires lengthy inferences and simulations.

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1. Complex diversification of Flowering Plants
   Most extant species, as well as their extreme phenotypic diversity, are thought to have resulted from the processes of speciation and extinction over millions of years. Underlying abiotic and biotic mechanisms have contributed to the diversification of hundreds or thousands of plants but the role and significance of these mechanisms across hundreds or thousands of plants is unclear. On the one hand, abiotic factors like the uplift of the mountains and biogeographical changes may have acted as a barrier among populations, promoting vicariant speciation. On the other hand, biotic factors, and traits inherent to species inherent to species can also be main contributors to diversification.
   As part of our recent systematics and biodiversity grant (NSF-DEB 2323170), we are currently developing new diversification models that connect both abiotic and biotic drivers to diversification studies of the Andean flora. Our goal is to have a comparative approach to understand whether biotic or abiotic factors or their interaction are key to the radiation of Andean flora and quantify how much each factor has contributed to the diversification across clades. We are working on new macroevolution models that will simultaneously consider three key evolutionary processes: 1) biogeographical changes, 2) trait changes, and 3) speciation and extinction rates. Each of these three nodes can be connected by a function that specifies the direction and interactions that these nodes have within and between to ultimately define a large graph. In this way, a very complex model becomes an exercise of “building blocks'', rather than a mathematical exercise of modifying complex equations.

2. Chromosome number evolution theory
   The lab also focuses on the study of polyploidy (a large and recurrent mutation that produces unreduced gametes with extra sets of chromosomes) across angiosperms. Macroevolutionary models for polyploidy using chromosome numbers appeared in 2010 and revolutionized our understanding of the frequency of polyploidy across land plants. We know that flowering plants have experienced 3 to 4 rounds of polyploidy per lineage. What we know less about is how frequently a polyploid occurs in plant populations and how it persists in the face of competition with diploids. Ultimately, what we are measuring in macroevolution are ecological processes that have persisted over time, so it is essential to understand polyploidy on the population scale. Scaling polyploidy knowledge requires the development of new mathematical models that can explain how polyploidy works within each scale, and then connect these scales through model parameters. We will be doing this work through the NSF BII (2320251): Polyploidy: Integration Across Scales and Biological Systems funded in July 2024.

Computational methods

We develop phylogenetic comparative methods and demographic models in R, RevBayes, JAGS, and sometimes Julia or Python, depending on the model/method. In some instances, we require specific phylogenetic or bioinformatic software to build the phylogenetic tree for example, alignment software with IQtree, or SNaQ to build phylogenies.

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RevBayes, RevBayes+tensorphylo, JAGS, R, Julia, Python, IQtree.

Collaborators

Jake Ferguson