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Publication Date

2023-3

First Advisor

Laura A. Katz

Document Type

Honors Project

Degree Name

Bachelor of Arts

Department

Biological Sciences

Keywords

machine learning, biology, ecology, niche, modeling, Arcellinida

Abstract

Arcellinida are an ancient clade of single-celled eukaryotes distinguished by their tests (shells). They occupy a variety of habitats, including freshwater and other moist environments like leaf litter and soil. The question of how microbes like Arcellinida are dispersed has long troubled microbiologists. Arcellinida are seen as cosmopolitan morphospecies, but studies have shown the distribution of cryptic species within these lineages may be limited by environmental factors or geographical regions. Understanding Arcellinida distribution patterns is important to interpret their evolutionary history and possible ecological shifts that influenced speciation events. Previous studies often focused on a few sites over a small geographic range, making it difficult to assess broad environmental drivers that govern restricted habitat distributions. Here, we use MaxEnt, a machine learning software that uses presence-absence data to assess Arcellinda through time, space, and geography, to predict preferred ecological niches across North America. We train this model by introducing location data collected from a literature review of sites where Arcellinida have been recorded and environmental layers collected from the global climate data site Worldclim. Based on the abiotic characteristics of the literature observation sites, MaxEnt predicts other habitats across North America where Arcellinida are likely to be found. We then use sets of future data taken from the Coupled Model Intercomparison Project, which predict what environmental conditions will be in the years 2050 and 2070, to predict how Arcellinida habitats will shift as a result of climate change. Preliminary results suggest that current habitats for Arcellinida are concentrated in Northern Mexico, along the West Coast of Canada, and the south of the United States. These niches are predicted to shift increasingly Northwest over time, with a narrowing latitudinal range. This work will help us better understand the most influential environmental conditions for Arcellinida distribution and lays the groundwork for future assessments of paleoclimate. By increasing our understanding of the geographic and evolutionary history of the Arcellinida clade, this project will contribute to our understanding of a major microbial community, and allow us to understand how the environment has and will shape diversity in the future.

Rights

©2023 Emma Schumacher. Access limited to the Smith College community and other researchers while on campus. Smith College community members also may access from off-campus using a Smith College log-in. Other off-campus researchers may request a copy through Interlibrary Loan for personal use.

Language

English

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