Student NameNatalie Patten
Faculty Mentor NamePamela Soltis, PhD; Douglas Soltis, PhD
CollegeFlorida Museum of Natural History
Research Interestsdifferential equations, bioinformatics, scientific computing, mathematical logic, complex analysis
Academic AwardsMartin County Bar Association Scholarship (2019), Alvin and Sunny Domroe Scholarship (2019), Florida Bright Futures Academic Scholars Award and Academic Top Scholars Award (2019), University Honors Program (2019), University Research Scholars Program (2019), Dean's List (2019-present), Emerging Scholars Program (2021)
OrganizationsPresident and founder of Women in Mathematics and Statistics, Retreat Chair of Theta Alpha Sorority, University Honors Program, peer mentor for University Research Scholars Program, Delta Alpha Pi Honor Society
VolunteeringUF Dance Marathon/UF Health Shands Children's Hospital
Hobbies and Interestscomputer science, reading, cooking and baking, rock music

Research Project

Reproducible Workflow For Projecting Climatic Impacts On Florida Plants

 Digitized biodiversity data have increased access to museum specimens and facilitated novel research (Soltis, 2017). The Global Biodiversity Information Facility (GBIF) and Integrated Digitized Biocollections (iDigBio) each hold over 100 million records (Nelson & Ellis, 2018). Data aggregators like GBIF, iDigBio, and Biodiversity Information Serving Our Nation (BISON) have enabled numerous publications utilizing herbarium data to investigate a variety of questions (Heberling et al. 2019). Applications in research have included species delimitation, understanding ecological niche, global patterns of biodiversity, and investigating the impact of climate change on species distribution. Despite the broad applications of digitized herbarium specimens in research, there is debate with respect to obtaining and processing biodiversity data for research applications. Which repositories to use, how to identify duplicate specimens, and additional processing steps remain unclear. Furthermore, publications often report simplified methods for accessing and processing the data, when in reality the process is quite complex. Thus, I will create an R package to aid researchers through this critical data processing. Additionally, I will create a step-by-step workflow with graphics. This workflow will include functions that streamline downloading records from GBIF, iDigBio, and BISON. In addition, we will develop functions to identify flagged records or those that need to be georeferenced. Functions related to cleaning specimen records will also be developed, including functions that will remove duplicate data points, check precision, and retain only one point per pixel. To demonstrate the application of this workflow, I will obtain and process data for 25 endangered plant species of Florida. Specifically, I will use herbarium records and environmental data to generate ecological niche models for these species. I will then project these models onto climatic conditions for 2050 and 2070 in order to predict the distributions of these species in response to climate change. I expect that our models will show that these species will decrease in range and niche breadth. The multiple socioeconomic scenarios projected for each species reflect either hindrance or aid in mitigation and adaptation to climate change. Overall, my research will enable the scientific community to better explain the processing of biodiversity data, thus contributing to our overall knowledge of climate change and its impacts on Florida plant species. My study will also be helpful in determining needs for conservation efforts for endangered and threatened plant species in Florida.