If you’ve seen one worm, have you seen them all? Spatial, community, and genetic variability of tubificid communities in Montana
Freshwater science, , , 2015
Abstract: Genetic studies are recognized increasingly as important for understanding naturally occurring disease dynamics and are used to predict host genetic diversity and coevolutionary processes and to identify species composition in ecological communities. Tubifex tubifex, the definitive host of the whirling disease parasite Myxobolus cerebralis, comprises 6 known lineages that vary widely in parasite susceptibility. We used 16S ribosomal DNA (16S rDNA) to identify relationships among genetic variability of 3 oligochaete genera (T. tubifex, Rhyacodrilus spp., and Ilyodrilus spp.; Oligochaeta:Tubificidae), oligochaete assemblage composition, and the presence of whirling disease in 9 locations across 4 watersheds in Montana, USA. We assessed genetic variability among 183 tubificid worms from locations classified as positive or negative for whirling disease based on 5 to 8 y of monitoring by the Montana Department of Fish, Wildlife, and Parks. Within genera, we found 2 groups of T. tubifex (lineages I and III), 2 groups of Rhyacodrilus spp., and 4 groups of Ilyodrilus spp., possibly suggesting cryptic species. The maximum genetic variability within taxa was relatively high (∼10% sequence divergence) for all 3 genera, but haplotype diversity within groups with >5% sequence divergence was greater for Ilyodrilus spp. (0.719) than for Tubifex spp. (0.246) and Rhyacodrilus spp. (0.143). The variation was nonrandomly distributed over the landscape. Oligochaete genetic composition was more similar among locations in the same watershed than among locations with or without whirling disease. Thus, oligochaete assemblage composition did not appear to be related to the presence of the disease at this watershed spatial scale. br>
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Bongard's work focuses on understanding the general nature of cognition, regardless of whether it is found in humans, animals or robots. This unique approach focuses on the role that morphology and evolution plays in cognition. Addressing these questions has taken him into the fields of biology, psychology, engineering and computer science.
Danforth is an applied mathematician interested in modeling a variety of physical, biological, and social phenomenon. He has applied principles of chaos theory to improve weather forecasts as a member of the Mathematics and Climate Research Network, and developed a real-time remote sensor of global happiness using messages from Twitter: the Hedonometer. Danforth co-runs the Computational Story Lab with Peter Dodds, and helps run UVM's reading group on complexity.
Laurent studies the interaction of structure and dynamics. His research involves network theory, statistical physics and nonlinear dynamics along with their applications in epidemiology, ecology, biology, and sociology. Recent projects include comparing complex networks of different nature, the coevolution of human behavior and infectious diseases, understanding the role of forest shape in determining stability of tropical forests, as well as the impact of echo chambers in political discussions.
Hines' work broadly focuses on finding ways to make electric energy more reliable, more affordable, with less environmental impact. Particular topics of interest include understanding the mechanisms by which small problems in the power grid become large blackouts, identifying and mitigating the stresses caused by large amounts of electric vehicle charging, and quantifying the impact of high penetrations of wind/solar on electricity systems.
Bagrow's interests include: Complex Networks (community detection, social modeling and human dynamics, statistical phenomena, graph similarity and isomorphism), Statistical Physics (non-equilibrium methods, phase transitions, percolation, interacting particle systems, spin glasses), and Optimization(glassy techniques such as simulated/quantum annealing, (non-gradient) minimization of noisy objective functions).