Aquatic biodiversity patterns along gradients of multiple stressors and disturbance histories: Integration of paleocology and molecular techniques

Modern geological time is commonly referred to as the Anthropocene; a designation recognizing the extent to which humans dominate processes and life on Earth. Within this context, a major theme of biodiversity research is to model and predict species losses due to land exploitation and use. However, in order to more completely understand the effect of human stressors on biodiversity, species losses and gains along with biodiversity change over varied temporal and spatial scales need to be considered in concert. My research seeks to fulfill two main objectives related to both biodiversity trends throughout the Anthropocene and the expansion of paleolimnological techniques for biodiversity science. Firstly, by paying closer attention to the way in which beta diversity can uncover trends previously missed when examining alpha or gamma diversity alone, my work helped improve our understanding of freshwater biodiversity responses to the anthropogenic stressors that have accelerated over the last ~ 150 years. Secondly, by integrating paleolimnological data with data collected from contemporary timescales, and with the application of DNA-based approaches to paleolimnology, I answered questions novel to both paleolimnology and biodiversity science. In my first chapter, I used diatom assemblage data from the U.S. Environmental Protection Agency's National Lakes Assessment (NLA) program to compare the variation in diatom assemblages across environmental and spatial gradients, using both water-column and surface sediment data. Here I showed that diatom assemblages from both types of sampling were characterized by environmental and spatial gradients in similar ways. In my second chapter, I extended this work with the NLA data, examining modern and historical (pre-1850 CE) timeframes, and showed that beta diversity responded strongly to national-scale land use gradients, with turnover hotspots in regions with low forest cover. My third chapter focused on a specific stressor for aquatic biodiversity, metal contamination in an iron-ore mining region of northern Québec, and showed that the beta diversity of zooplankton communities responded strongly to heavy metal loading. Finally, in my fourth chapter I used metabarcoding approaches to more fully characterize microbial eukaryote communities from sediment cores in this same mining region and showed substantial temporal beta diversity in both diatoms and green algae. This final chapter was the capstone for this work, continuing the integration of paleolimnological data with DNA-based approaches, capturing a more complete representation of aquatic biodiversity than possible with individual proxies. I also demonstrated how beta diversity is an important way to characterize diversity in systems experiencing multiple stressors. In general, this research provides insight into the importance of multi-scale and multi-metric methods in the study of aquatic biodiversity, while illuminating key drivers of aquatic assemblages through time.

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