Statistics and the future of the Antarctic ice sheet
January 18, 2020
Presented by Presented by Murali Haran
How do scientists study climate, and how do they make projections about future climate? What is the role that statistics plays in climate science? Murali Haran provides answers to these questions, with examples from collaborative research between Penn State statisticians and climate scientists. His research focuses on the future of the Antarctic ice sheet, which has an important role to play in the future of the planet. Haran explains how statistical thinking is central to science, especially now, as we have access to an unprecedented amount of new scientific data.
Predicting the future of plant diversity: New applications for digitized herbarium data
January 25, 2020
Presented by Pamela S. Soltis
Botanists have been collecting and depositing plant specimens in herbaria for centuries, with approximately 350 million specimens currently housed in the world’s herbaria. Until recently, these records of plant life on Earth were only available to those with the resources to visit herbaria in person. Recent efforts to digitize natural history collections have produced digital data and images for millions of specimens—available on the internet and in computable form for addressing today’s many societal challenges related to biodiversity. Application of modeling software to herbarium specimen information and environmental data enables characterization of the ecological niche of a species and the geographic distribution of this niche. Using projected changes in environmental variables, we can predict where the niche of a species will be under alternative future climate scenarios. Soltis’s talk will present a summary of how herbarium data are used to characterize the ecological niches of the flora of Florida and predict changes in Florida’s plant diversity during the coming century. The use of predictive modeling is an important new component of species conservation.
Understanding wildlife connectivity and disease spread through GPS tracking
February 1, 2020
Presented by Presented by Ephraim Hanks
Movement is a fundamental process driving population connectivity as well as the spread of infectious disease and invasive species. Recent advances in technology have made it possible to track animals at extremely high resolution. Hanks will show tracking data from a wide range of systems, including insects, birds, and mammals, and illustrate approaches for analyzing tracking data using modern statistical and machine learning tools. These analyses will focus on examining how individual animal movements can be explained and predicted using remotely sensed data and how individual movements scale up and define population-level structure, connectivity, and fitness.
Characterizing potentially habitable planets
February 8, 2020
Presented by Presented by Eric Ford
The Center for Exoplanets and Habitable Worlds (CEHW) at Penn State discovers and characterizes planets beyond our solar system to understand the implications for the possibility of life beyond Earth.
NASA’s Kepler mission discovered thousands of exoplanets, including hundreds of Earth-size planets. However, the planets discovered around sun-like stars by Kepler are typically thousands of light years away, making them difficult to study in detail.
.and have developed a new generation of instruments to test these models by searching nearby stars for Earth-mass planets. Learn how Penn State research is informing plans for a new generation of observatories and space missions to characterize potentially Earth-like planets.
Disease outbreak control: Harnessing the power of multiple models to work smarter, not harder
February 15, 2020
Presented by Katriona Shea
Disease outbreaks are a source of immense human, wildlife, and agricultural concern. They threaten our health, our environment, and our food security. When new outbreaks such as Ebola occur, scientists rush to help. Even so, often relatively little may be known about a disease, even as policy makers must make critical decisions about how to best to manage it. Quantitative models that describe biological processes in terms of mathematics or statistics can be incredibly helpful in such cases. They allow us to summarize what we do know while highlighting where our important knowledge gaps lie. Shea will overview the use of mathematical modeling approaches in disease settings, drawing examples from human, wildlife, livestock, and agricultural scenarios. She will also discuss important general insights that have arisen from modeling efforts, including cautionary tales, the importance of context, and ways to streamline decision-making when time is of the essence.
Predicting mutation and disease occurrence from DNA and omics data
February 22, 2020
Presented by Kateryna Makova
With affordable DNA sequencing, information on mutations in an individual’s genome is readily available. Kateryna Makova will present how mutation frequency depends on gender, age, and DNA location. Statistical models explaining and predicting mutation occurrence and applications to pregnancy planning and genetic counseling will be discussed. Mutations can cause numerous human genetic diseases but are only one contributor to the probability of disease development for an individual. Also, we now can generate microbiomics, metabolomics, epigenomics, and viromics data. Analysis of these omics data may help us understand the patterns of disease occurrence. As an example, the analysis of various omics data sets related to childhood obesity will be covered.