Dissertation Research: Linking climate dynamics and historical demographic in South American forest lizards

Cuny Graduate School University Center, New York NY

Investigators

Abstract

Tens of thousands of years ago the levels of rainfall in northeastern South America were much higher than today. As a result, the Amazon and the Atlantic rainforests were much more extensive, occupying regions that are today covered by deserts and savannahs. When the climate became drier, those forests retracted and became fragmented. This change likely had dramatic effects on the animals and plants that live in tropical rainforests. This project asks how tropical forest organisms were affected by the climatic changes experienced over the past 250,000 years. The genomes of three species of lizards that occur in the Brazilian forests will be studied, and by comparing the DNA sequences of multiple individuals per species over their geographic range, the project will uncover the extent that their populations have expanded or declined in the past. This research shed light on how these organisms have responded to environmental change, in addition to the processes that led to their current distribution patterns. This project will provide training in molecular systematic methods and mentorship for undergraduate and Masters students at The City College of New York. It also will foster new USA-Brazil scientific collaborations through joint field trips to northern Brazil. This project seeks to test how populations of forest-associated lizards have been affected by a recently proposed dynamics of moisture transport in South America during the Quaternary. It will generate Single Nucleotide Polymorphism (SNP) data of three arboreal lizard species that occur in both Amazon and the Atlantic rainforests (Anolis punctatus, A. ortonii and Polychrus marmoratus) using a restriction-site associated DNA sequencing protocol. Phylogenetic relationships will be inferred using coalescent-based methods. Analyses of genetic structure will be performed to infer the number of effective populations within the different species. Scenarios of population expansion, contraction, or persistence will be evaluated based on coalescent simulations and both likelihood-based methods and Approximate Bayesian Computation. Estimates of demographic parameters such as effective population sizes, divergence times between populations, and migration rates will be estimated using best-fit models. Together these data will provide new insights on the population structure for taxa in the Brazilian Atlantic and Amazonian rainforests, and how they have responded to recent climate perturbations.