Mercedes PascualPascual Lab website
- Howard Hughes Medical Institute Investigator
- Rosemary Grant Collegiate Professor of Ecology and Evolutionary Biology
- University of Michigan
2045 Kraus Natural Science Building
830 North University
Ann Arbor, MI 48109-1048
- Phone: (734) 615-9808
- Lab: (734) 615-9805
- Fax: (734) 763-0544
- Email: firstname.lastname@example.org
I am a theoretical ecologist interested in population and community dynamics.
Research in my lab is primarily on infectious diseases--such as cholera and malaria--whose dynamics are environmentally driven, for example on the role of climate variability and climate change. We are also interested in the the interplay of ecological and evolutionary dynamics in infectious diseases, and the related questions of the origin and consequences of pathogen diversity.
A second main theme in the lab is on ecological networks of species interactions, known as food webs. In food webs, the nodes are the species and the links represent interactions between species. We are exploring patterns in the structure of these large networks, as well as models that can generate these structures and help us understand their biological basis. We are interested in the relationship between structure and dynamics in food webs, with the goal of better understanding what underlies the 'stability' of ecological communities.
Both infectious diseases and food webs are examples of complex ecological systems. They are both systems of consumer-resource interactions, between predator and prey, host and pathogens, pathogens and the immune system. They both involve nonlinear interactions (whose per-capita rates depend on the state of the system itself) and many components. They can respond to perturbations in ways that defy simple correlative analyses, and they raise many interesting challenges to the understanding of their temporal and spatial patterns, especially on the level of detail that one should incorporate in mathematical or computational models for the purposes of both understanding and prediction.
A third general theme is the relationship between ecological dynamics at different spatial or organizational scales. We are interested in approaches to scale-up systems for consumer-resource interactions from small, individual, levels to more aggregated, population, levels, and to develop simple models for the aggregated dynamics of complex ecological systems. We have been working on spatio-temporal systems for the propagation of disease (predation or disturbance) that exhibit critical transitions and generate spatial (fractal) patterns over a broad range of scales.
Our work relies on a variety of extensive data sets, from long time series on disease levels that span decades, to large empirical food webs, to pathogens' sequence data in time and space. The disease work involves international collaborations with public health and research partners. On the theoretical front, we use mathematical models, but also computational and statistical approaches that bridge between data and models.
(1) The population dynamics of endemic cholera in Bangladesh: retrospective understanding of interannual variability and prospective prediction based on climate variability (including Sea Surface Temperatures - for the El Niño Southern Oscillation or ENSO - and regional variables that mediate the local effect of this remote ocean forcing).
(2) The population dynamics of epidemic cholera currently in Africa and historically in former British India. Commonalities with forest fire dynamics.
(3) The population dynamics of epidemic malaria in desert fringes of NW India: the role of climate variability and its interplay with land-use and socio-economic factors, with the goal of developing an early-warning system for this region.
(4) Epidemic malaria and climate change: retrospective studies in E. African highlands in recent decades with dynamical models of disease transmission.
(5) Pathogen (antigenic) diversity in malaria: origin and influence as related to within-host and between-host population dynamics.
(6) Interpandemic influenza: evolutionary and ecological dynamics.
(7) Food webs: models of structure and relationship between structure and 'stability.'