globalchange  > 影响、适应和脆弱性
项目编号: 1451356
项目名称:
Application of thermodynamic theory for predicting microbial biogeochemistry
作者: Joseph Vallino
承担单位: Marine Biological Laboratory
批准年: 2014
开始日期: 2015-04-15
结束日期: 2016-03-31
资助金额: USD203658
资助来源: US-NSF
项目类别: Standard Grant
国家: US
语种: 英语
特色学科分类: Geosciences - Earth Sciences
英文关键词: mep ; model ; microbial biogeochemistry ; mep biogeochemistry modeling approach
英文摘要: Most of the elements critical for life on Earth, such as nitrogen, carbon, phosphorous, sulfur and many trace metals, are cycled between land, water and the atmosphere by the actions of microscopic bacteria and archaea that both extract and recycle these elements on a continuous basis. Understanding how microbes control these so called biogeochemical cycles is critical for understanding how the environment will change in the face of natural and anthropogenic alterations. To predict how ecosystems will respond to increases in nutrient inputs, changes in temperatures, increases in atmospheric carbon dioxide and similar drivers, computer models are constructed based on how bacteria grow and interact. However, because a single gram of soil or liter of water contains billions of bacteria consisting of thousands of difference species, it can be challenging to accurately predict their collective geochemistry by modeling all of their growth characteristics and interactions. An alternative approach assumes that complex systems, whether composed of living organisms or not, naturally organize to maximize the extraction and use of available energy. Known as the maximum entropy production (MEP) principle, this theory can be used to describe the collective actions of a community of microorganisms without needing to know exactly which microbes are present and exactly how they interact. If true, the MEP-based approach should produce models with better predictive capabilities than models based on conventional approaches. This project seeks to demonstrate the usefulness of MEP by comparing model predictions to biogeochemical observations collected in an aquatic environment. The investigators will disseminate the modeling approach and research results via journal publications and presentations. The research project will support one postdoctoral scholar in a multidisciplinary research area, independent undergraduate research projects via Marine Biological Laboratory's Semester in Environmental Science Program, and summer internships as part of the Woods Hole Partnership Education Program, which is a consortium of institutions committed to increasing diversity in Woods Hole.

A mathematical framework to predict microbial biogeochemistry based on the maximum entropy production (MEP) principle applied to a distributed metabolic network has been developed. The model accurately predicts microbial dynamics and associated chemistry in experimental methanotrophic microcosms and is also adept in predicting metabolic switching between the known nitrate reduction pathways (denitrification, dissimilatory nitrate reduction to ammonium, and anammox) in well-mixed systems as a function of environmental conditions. The MEP approach describes both geochemistry and biogeochemistry, where the latter differs from the former in that living organisms maximizing energy dispersal over time and space as opposed to instantaneously. The objectives of this project are to: 1) advance the MEP biogeochemistry modeling approach by incorporating metabolic reactions for aerobic and anaerobic-based phototrophy; 2) extend the approach from 0D to 1D to examine hypotheses for integrating MEP over space; 3) collect diel biogeochemical measurements over vertical profiles in a meromictic pond (Siders Pond on Cape Cod, MA) for model development and testing; 4) measure allocation of molecular machinery associated with key biogeochemical pathways over depth in Siders Pond using metagenomics and metatranscriptomics and compare these observations to model predictions.
资源类型: 项目
标识符: http://119.78.100.158/handle/2HF3EXSE/94812
Appears in Collections:影响、适应和脆弱性
气候减缓与适应

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Joseph Vallino. Application of thermodynamic theory for predicting microbial biogeochemistry. 2014-01-01.
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