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United States Department of Agriculture

Agricultural Research Service

Title: Quantifying Microbial Competition on Leaves

Authors
item Kinkel, Linda - UNIVERSITY OF MINNESOTA
item Newton, Miriam - UNIVERSITY OF MINNESOTA
item Leonard, Kurt

Submitted to: International Symposium on Microbiology of Aerial Plant Surfaces
Publication Type: Proceedings
Publication Acceptance Date: October 1, 1997
Publication Date: N/A

Technical Abstract: We used two approaches to investigate relationships between competitive ability and fitness of epiphytic microbes. First, we developed models for quantifying competitive abilities of microbes on leaves independently of population density. The models permit investigation of the impacts of competition on fitness as a function of population density. They also allow direct determinations of the relationship between competitive abilit and fitness for specific microbes on leaves. Second, we used Welden and Slausson's (1986) methods to determine the influence of competition on population growth and microbial fitness. We quantified microbial population dynamics in both the presence and absence of the competitor for a fungal obligate parasite (Puccinia graminis tritici) and a bacterial epiphyte (Pseudomonas syringae/Stentrophomonas maltophilia) on wheat leaves. With data from these two systems, we used two models to investigate relationships between competitive ability and fitness. The models showed that poorer competitors may be more fit than better competitors either in the presence or in the absence of the competitor. This is consistent with predictions of r- and K-selection that organisms having high fitness individually in a particular niche may not be good competitors. Also, the relative importance of competition to microbial fitness will be small for organisms for which variability in population sizes (high variance among leaves) depends predominantly on physical factors. On the other hand, competition will have a very large impact on fitness of microorganisms that are relatively insensitive to other sources of population variance.

Last Modified: 12/29/2014
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