March 3 2016

5:00 pm 154 BSRB

EcoEvoPub Series

Graduate Student Presentations


Monique Ambrose
Department of Ecology and Evolutionary Biology, UCLA

Inferring transmission information of a zoonotic pathogen from surveillance data

One of the primary sources of emerging infectious diseases in humans is zoonotic spillover, which makes the study of zoonotic pathogens an important public health priority. Information on zoonotic pathogens is often limited to the data collected during public health surveillance programs. As a result, many important pieces of information are often unknown, including the infectious source of cases, the exact geographic location of cases, the disease dynamics in the animal host, and even the extent of the surveillance program. These data limitations complicate efforts to characterize the dynamics of zoonotic pathogens and conduct rational risk assessments. I developed likelihood-based methods that account for many of the unknown elements common to zoonotic disease datasets and enable us to extract information on transmission patterns, such as the pathogen’s effective reproductive number and spillover rate. After testing the methods against simulated datasets, I applied them to a dataset of human monkeypox cases collected during an active surveillance program in the Democratic Republic of the Congo in the 1980s. The results shed light on epidemiological parameters underlying the system and the transmission distance kernel for human monkeypox.

Tyler McCraney
Department of Ecology and Evolutionary Biology, UCLA

Temporal genetic analysis of the endangered tidewater goby: extinction–colonization dynamics or drift in isolation?

Extinction and colonization dynamics are critical to understanding the evolution and conservation of metapopulations. However, traditional field studies of extinction–colonization are potentially fraught with detection bias and have rarely been validated. Here, we provide a comparison of molecular and field-based approaches for assessment of the extinction–colonization dynamics of tidewater goby in northern California. Our analysis of temporal genetic variation across 14 northern California tidewater goby populations failed to recover genetic change expected with extinction–colonization cycles. Similarly, analysis of site occupancy data from field studies (94 sites) indicated that extinction and colonization are very infrequent for our study populations. Comparison of the approaches indicated field data were subject to imperfect detection, and falsely implied extinction–colonization cycles in several instances. For northern California populations of tidewater goby, we interpret the strong genetic differentiation between populations and high degree of within-site temporal stability as consistent with a model of drift in the absence of migration, at least over the past 20–30 years. Our findings show that tidewater goby exhibit different population structures across their geographic range (extinction–colonization dynamics in the south vs. drift in isolation in the north). For northern populations, natural dispersal is too infrequent to be considered a viable approach for recolonizing extirpated populations, suggesting that species recovery will likely depend on artificial translocation in this region. More broadly, this work illustrates that temporal genetic analysis can be used in combination with field data to strengthen inference of extinction–colonization dynamics or as a stand-alone tool when field data are lacking.















































































































































































































































































































































































































































































































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