Using microbial community composition to predict ecosystem response to global change.

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Using microbial community composition to predict ecosystem response to global change. Kristin Matulich J. Martiny Lab November 29 th , 2011

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Using microbial community composition to predict ecosystem response to global change. Kristin Matulich J. Martiny Lab November 29 th , 2011. Overview. Inspiration Microbial BEF in the context of global change. Current ecosystem models don’t include information about microbial community. - PowerPoint PPT Presentation

Transcript of Using microbial community composition to predict ecosystem response to global change.

Page 1: Using microbial community composition to predict ecosystem response to global change.

Using microbial community composition to predict ecosystem response to global change.

Kristin MatulichJ. Martiny Lab

November 29th, 2011

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Overview• Inspiration– Microbial BEF in the context of global change.– Current ecosystem models don’t include information

about microbial community.– Justify the need to incorporate microbial parameters into

global change prediction models.

• Main Question– What role does microbial community composition play in

litter decomposition, and how does that role change under environmental perturbations?

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Approach• Field and laboratory experiment that manipulate

microbial composition and environmental perturbations.

• Experimental design will test:1. Effect of microbial community composition on litter decomposition

rates.2. How the effect of microbial community composition on

decomposition rates changes in response to environmental perturbations.

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Field Experiment: Loma Ridge

• Enclose sterile leaf litter in “microbial cages” inoculated with microbial compositions.

• Cages will be collected from the the field after 180 days to determine the total leaf litter mass loss and final community composition.

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Laboratory Experiment

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Loma Ridge Bacterial Isolates

• Isolated from litter collected at different times of year and using multiple media.– LB and Litter Agar

• Current Inventory– 35 unique OTUs (97% similarity of 16s).• 18 Actinobacteria• 11 Proteobacteria• 6 Bacteriodetes

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Gammaproteobacteria

Betaproteobacteria

Alphaproteobacteria

Actinobacteria

Bacteriodetes

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