Graduate Thesis Or Dissertation
 

Using DNA metabarcoding to describe biodiversity and disease dynamics

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  • Land-use change, particularly in the form of the conversion of primary forest to forest-matrix systems, alters species communities and species interactions. Describing these often complex and nuanced species responses is one of the great challenges in ecology. Another complementary challenge is finding and using the most efficient means for collecting quality data necessary for understanding ecological relationships. For my PhD dissertation, I utilized the emerging molecular method of DNA metabarcoding to profile species communities and answer landscape level questions about the effects of forest loss on species. DNA metabarcoding is the high-throughput DNA sequencing of taxonomically informative barcode genes to profile the diversity found using environmental samples such as water, scat, soil, or pollen. Metabarcoding can also be used with direct sources of DNA such as the bloodmeals or carrion meals from insects, which is referred to as iDNA or insect-derived DNA. I utilized both eDNA (from scat samples) and iDNA (from carrion flies, sandflies, and mosquitos) to help validate and develop metabarcoding for diversity surveillance. In Chapter 2, I profiled the diet of Alexander Archipelago wolves (Canis lupus ligoni) across an island archipelago system in southeast Alaska using both DNA metabarcoding from prey DNA in scat samples and mechanical sorting of the same scat samples. Although I found similar relative abundances of the primary and secondary prey species across the methods, DNA metabarcoding revealed a greater diversity and relative abundance of alternate prey species than had been described with mechanical sorting of scats both in our study and in previous studies. Additionally, I found that disagreement in species assignment between the two methods could be attributed to false positives from mechanical sorting due to misassignment of degraded hair. Lastly, I found that both fresh and degraded scats yielded quality DNA sequence data suggesting that metabarcoding is sensitive enough to determine prey assemblages in degraded scats. I applied this same method to studying biodiversity and disease dynamics across a deforestation gradient in the southern Amazon. I collected bulk insects as a source of insect-derived DNA from across tropical forest fragments and used metabarcoding to investigate (1) the utility of different iDNA samplers (Chapter 3) and (2) host-vector-pathogen dynamics across the deforestation gradient (Chapter 4). For Chapter 3, I used carrion flies, sandflies, and mosquitos as sources of insect-derived DNA (iDNA) and metabarcoding to both test the utility of iDNA metabarcoding for biodiversity surveillance and to profile alpha and gamma diversity across this landscape. iDNA data was also compared to camera trapping data from the same sites as a control method. I found overwhelmingly evidence that carrion flies were the most efficient and effective method at profiling biodiversity compared to all other methods. While not as proficient in describing vertebrate diversity as carrion flies and requiring a larger sampling effort, sandflies also effectively described vertebrate species and had the added benefit of being informative for disease surveillance or other disease-related study. The effectiveness of sandflies as an iDNA source segued into Chapter 4, where I used metabarcoding data to answer a big question in ecology: how does land-use change and biodiversity loss affect disease risk? This question has sparked debate in the disease ecology field over whether increased biodiversity decreases disease risk (i.e. the dilution effect) or if biodiversity has a neutral or amplification effect on disease risk. I used sandflies as sources of both vertebrate diversity data and vector diversity data to describe the host and vector communities for Leishmania parasites across the deforestation gradient. I found that the relationships between land-use change and disease-important host and vector species were nuanced. Individual species showed varied responses to deforestation with some species becoming more abundant in deforested patches (Dasypus novemcinctus and Canis lupus familiaris) while other species, such as Dasypus kappleri, were detected at higher rates in intact forests. When species were grouped into host or vector categories, the relationships to the deforestation gradient lessened in statistical significance or disappeared because the opposing responses from individual species masked the significant effects. This study demonstrated the power of DNA metabarcoding for providing both breadth and detail needed for large-scale study of the effects of land-use change on biodiversity and disease.
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  • Intellectual Property (patent, etc.)
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  • 2021-04-28 to 2021-11-28

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