September 1, 2007-August 31, 2011
Level of Access
Spatial effects, such as habitat fragmentation and the location and size of disturbance events, play a key role in the dynamics of populations. This is true in natural populations (such as herbs living under a forest canopy) as well as human-dominated systems (for example, crop pests in agricultural landscapes). Focusing on the development of spatial population models, the project seeks to better understand how and why spatially autocorrelated disturbances affect the dynamics of populations with mixtures of short- and long-distance dispersal. A variety of disturbances are considered, including (1) static disturbance, representing habitat heterogeneity across a landscape; (2) short-term disturbance whereby populations are removed from sites which may then be recolonized, e.g. representing short-term control of agricultural crop pests, and (3) landscapes with specified spatial and temporal autocorrelation, whereby blocks of sites become unsuitable and cannot be recolonized until some time has elapsed. The primary objectives of the computational side of the project are to improve the simulation methodology used for these types of spatial models, to enable more rapid/complete exploration of the parameter space and the use of simulation models in Monte Carlo parameter estimation techniques.
Spatial disturbances and heterogeneities play a fundamental role in any ecological system. This project develops mathematical models and computational tools to be used in the study of various types of disturbances. Possible applications include the modeling of understory plant species in a forest where gap formation renders a group of sites unsuitable until the canopy regenerates, or the application of pesticides over a region which leaves those sites unsuitable for recolonization by pests for some time. The project will include collaboration with entomologists and other biologists to study the effects of different strategies for controlling pests across agricultural landscapes, such as maggot flies in commercial blueberry fields. The effects of changing habitat distributions on populations, due to factors such as changing land-use patterns and global climate change, will also be considered. Significant undergraduate research training will be included in the project, including participation in a summer research program primarily aimed at underrepresented minority groups.
Rights and Access Note
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Hiebeler, David, "Spatial Population Models in Spatiotemporally Structured Environments" (2011). University of Maine Office of Research Administration: Grant Reports. 295.
Other Collaborators or Contacts
Young S. Lee, Dept. of Mathematics and Computer Science, Manchester College, N. Manchester, IN
Tae S. Do, Department of Mathematics Education, Kwandong University, Kangneung, South Korea
Frank Drummond, School of Biology and Ecology, University of Maine
Tod Shockey, Dept of Mathematics and Statistics, University of Maine