DISSERTATION RESEARCH: Network heterogeneity and metapopulation persistence in Pseudomonas syringae
University Of California-Berkeley, Berkeley CA
Investigators
Abstract
Society is increasingly defined by networks - groups of individuals separated by small or large distances. Movement across space to connect groups determines the strength of a network, the rates at which information spreads (social networks) or individuals interact (population networks), and the extent to which events in one group affect events in another group. This project will use a new tool to determine how, when, and why connections among populations determine whether a population persists or goes extinct. Results of the project will improve conservation and management plans for populations that are increasingly isolated by changes in land use. Improved conservation plans will be particularly important for endangered species that persist within weak networks. The project will advance the training and education of a doctoral student, who has developed and will improve a new experimental tool. Investigators will make the design and use of this tool publicly accessible, contributing to a democratic scientific process in which researchers co-design and share equipment. Use of this research approach will be extended to undergraduate and middle school students through programs that provide supervised independent research. This project will use a newly-developed experimental chamber to test directly both assumptions and predictions of existing metapopulation models; metapopulations are groups of linked populations. Bacterial populations cultured in chambers will be connected by corridors in a homogeneous lattice or a strongly heterogeneous arrangement. Both colonization and extinction rates will be controlled by manipulating corridor configurations and by disturbing populations with tetracycline, causing extinction. These manipulations will compare patch occupancy and metapopulation persistence in homogenous and heterogeneous networks across a gradient of extinction-to-colonization ratios. The researchers will next design network treatments that conform to lattice, random, exponential, and power-law distributions to identify the threshold extinction-to-colonization ratio at which bacterial populations can no longer persist. A final manipulation will create 'lonely' populations that are connected to a single neighbor and compare population persistence to that of counterpart populations connected to diverse nodes in a network. These experiments will improve understanding of the effects of spatial heterogeneity on ecological and evolutionary processes and identify appropriate conservation strategies for metapopulations comprising strong versus weak networks.
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