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Xiangming Xiao (肖向明)
Department of Microbiology and Plant BiologyEarth Observation and Modeling Facility
Center for Spatial AnalysisUniversity of Oklahoma
Norman, Oklahoma, 73019, USA
Multi-scale Analysis of Microbe-Climate Interactions in Greenhouse Gases Emissions from Grasslands and Croplands
http://www.eomf.ou.edu
USDA NIFA Agro-climatology Project Directors Meeting, December 17-18, 2016, San Francisco, California
Multi-scale analysis of microbe-climate interactions in greenhouse gases emissions from grasslands and croplands
USDA NIFA Award # 2016-68002-24967; Project period: 3/1/2016 - 2/28/2020 (48 months)
Project Partners – Research Component
University of Oklahoma Jeffray Basara, Zhili He, Boris Wawrik, Xiangming Xiao, Jizhong Zhou,Rajen Bajgain, Carolyn Cornell, Lauren Hale, Weiling Shi, Yuting Zhou
University of New HampshireJia Deng, Steve Frolking,
USDA ARS Grazinglands Research LaboratoryBrekke Peterson Munks, Jean Steiner,
Multi-scale analysis of microbe-climate interactions in greenhouse gases emissions from grasslands and croplands
USDA NIFA Award # 2016-68002-24967; Project period: 3/1/2016 - 2/28/2020 (48 months)
Project Partners – Education Component
University of Oklahoma (OU) The K20 Center Linda Atkinson, Heather M. Shaffery,
The BlueSTEM AgriLearning Center, El Reno, OKAnn Marshall,
All researchers in the project
Scientific BackgroundWinter wheat, rangelands and pasture are major agro-ecosystems in Southern Great Plains (Kansas, Oklahoma and Texas).
• CO2, CH4 and N2O emissions from grasslands and croplands are products of microbial activities.
• Microbes are very sensitive to changes in environment, and also highly adaptable to environmental change.
CO2
N2O CH4
Microbe
Research QuestionsA. How do microbial community structure, genetic
diversity, and functional potential affect diurnal to seasonal dynamics of GHG (CO2, N2O and CH4) emissions from grasslands and croplands at different spatial scales?
B. What are the major or minimum phylogenetic or functional molecular signatures of microbial activities to be included in biogeochemical models (e.g., DNDC) for accurately modeling diurnal and seasonal dynamics of GHG emissions from grasslands and croplands?
C. To what degree will the improved biogeochemical models better predict the spatial-temporal dynamics of GHG emissions from diverse grasslands and croplands in watersheds under changing climate and management practices (e.g., livestock grazing, manure, and irrigation)?
Simple models
Complex models
Chamber
Eddy flux
TimeSp
ace
Research Question AHow do microbial community structure, genetic diversity, and functional potential affect diurnal to seasonal dynamics of GHG (CO2, N2O and CH4) emissions from grasslands and croplands at different spatial scales?
Complex models
Specific Research Objective AMeasure and quantify the dynamics of microbial community structure, diversity, and function to better understand their role in determining GHG emissions under changing environment and management practices
Research Task A. Multi-scale measurements of microbe and GHG fluxes of grasslands and croplands
To incorporate microbe measurements as part of IGOS and ICOS
IGOS and ICOS Sites in operationIntegrated grassland observation sitesEl Reno: 2 (native tallgrass prairie, OWB pasture)
Marena, Stillwater: 1 (tallgrass prairie)
KAEFS, Purcell: 1 (tallgrass prairie)
Integrated cropland observation sitesEl Reno: 2 (winter wheat; till versus no-till; graze-out, fall/winter graze only)
Eddy flux tower measurements: Diurnal dynamics of CO2and ET from winter wheat (WW) and native tallgrass prairie (TGP) sites in 2015 at El Reno, Oklahoma
From Bajgain et al., 2016, in preparation; 2016 data are under processing.
Soil and Microbe Sampling Sites at El RenoIGOS-E (Field 13): Native tallgrass prairie. Limited management with cattle grazing. Has been in tallgrass prairie for 100+ years. Sampling occurs within EC tower fetch.
IGOS-W (Field 11): Assumed pure stand of Old World Bluestem. Cattle grazing and fertilizer addition yearly. Field has been established as Old World Bluestem for 10+ years. Sampling occurs within EC tower fetch.
ICOS-E (Winter Wheat, No-Till): Highly managed winter wheat production with cattle grazing. Fertilizer, herbicide and pesticide additions as needed and chisel plowed yearly. Established as winter wheat over 10 years ago, in 2015 transition to No-till management occurred. Sampling occurs with in the EC tower fetch.
ICOS-W (Winter Wheat, Conventional Till): Highly managed winter wheat production with cattle grazing. Fertilizer, herbicide and pesticide additions as needed and chisel plowed yearly. Established as winter wheat over 10 years ago and has been in conventional tillage since. Sampling occurs with in the EC tower fetch.
Old World Bluestem pastureNative tallgrass
prairie
Winter wheat (till) Winter wheat (no-till)
Field sites at the USDA ARS Grazinglands Research Laboratory, El Reno, OK
ICOS-E
IGOS-W
IGOS-E
IGOS-E: Native Tallgrass Prairie site ; IGOS-W: Old World Bluestem (OWB) Pasture site
ICOS-E: Winter Wheat (No Till) site
Integrated Grassland Observation site (IGOS)
1. Native tallgrass prairie site2. Old World Bluestem pasture
site
Integrated Cropland Observation site (ICOS)
1. Winter wheat (No till)2. Winter wheat (Till)
Soil and Microbe Sampling Component and Results at El Reno, OKSample Depth Sampling Frequency Analysis Start Date Sample Number at each
siteTotal Number of
Samples from all 4 sites
Soil 0-15 cm
Pre/Post season
Total Carbon
February 2016, Results Pending
10 40
Total Nitrogen 10 40
pH 10 40Texture 10 40
Bulk Density 10 40
Inorganic Carbonates 10 40
Total Organic Carbon 10 40
Bi-weekly
Dissolved Organic Carbon 120 480
Dissolved Organic Nitrogen 120 480
Nitrate 120 480
Ammonium 120 480
Greenhouse GasFrom Stationary
Chamber at 0, 15, 30 and 45 minutes
Bi-Weekly
Carbon Dioxide 120 480
Methane 120 480
Nitrous Oxide 120 480
Microbial Analysis 0-15 cm Monthly
Microbial BiomassCarbon 60 240
Microbial Biomass Nitrogen 60 240
Polylipid Fatty Acid Analysis (PLFA) 60 240
Chamber measurements of GHG emissions from soils
CO2 emission
Black line – Tallgrass Prairie siteGray line – Old World Bluestem pasture site
N2O emission
CH4 emission
WFPS
From Peterson Munk, in preparation; 2016 data are in processing
Soil microbial community analysis
Data integration and m
odelling Linkages with
environment
Distance
Unexplained
water
Community
• Soil environmental properties• Ecosystem properties and
processes
• 16S rRNA gene amplicon sequencing for bacteria
• ITS amplicon sequencing for fungi• Key functional gene (e.g., nifH,
nosZ, mcrA) amplicon sequencing
• Functional genes involved in nutrient cycling, stress responses, plant beneficial processes, disease repression, and greenhouse gas emissions
Microbial diversity
Correlation
Network analysis
Preliminary Results from Microbe Analyses
Native tallgrass prairie
Winter wheat (tillage)
From Wawrik et al., in preparation
Sites Number of cores per sampling point at each site
Sampling Dates Total Number of Samples Collected
Samples Analyzed for Microbial Community Structure
4Native tallgrass prairie
Old world bluestem pasture
Winter wheat (No-till)
Winter wheat (conventionally Tilled)
10 cores
Cores from each site are sifted and homogenized; then sub-sampled in quadruplicate
8/3/20168/17/20168/31/20169/14/20169/28/201610/12/201610/16/201611/9/201612/7/2016
360 cores collected
(9 time points4 sites10 cores each)
8/3/20168/17/20168/31/20169/14/20169/28/2016
Main Conclusions to date –• Native grassland soils contain greater microbial biomass than managed soils (DNA proxy).
• Microbial biomass varies by as much as one order of magnitude in response to rainfall events.• Native grassland soils harbor more diverse microbial communities than managed soils.• Microbial community structure in El Reno soils occurs along a continuum in which native grasslands and
agricultural soils that are managed by tilling and manure application form end members.
Research Question B
Complex models
Specific Research Objective B
What are the major or minimum phylogenetic orfunctional molecular signatures of microbial activitiesto be included in biogeochemical models (e.g., DNDC)for accurately modeling diurnal and seasonal dynamicsof GHG emissions from grasslands and croplands?
Improve DNDC biogeochemical model by incorporatingthe measured microbial dynamics into the modelframework to simulate the interactions among soilclimate, nutrients, microbial activity, and GHGemissions in grasslands and croplands
Research Task BIncorporate representation of microbes into biogeochemical models that estimate GHG emissions from grasslands and croplands
DNDC model
Complex models
NH4+/NH3 NO2- NO N2O N2
NO3-
NO2- NO N2
NO/N2O
Aerobic microsites
Anaerobic microsites
N2O
Nitrification Denitrification Nitrifier denitrification
Emission Transfer of N pools
N gas fluxes
***
****
* *
* new transfers and pool are labeled with asteriskslegend
The improvements will enable DNDC to simulate N2O and NO production from a new pathway – nitrifier-denitrification (dark blue arrows).
Current developments of N-gas flux processes in DNDC
N2O
GPP
DNDC simulations
From Bajgain et al., in preparation
To what degree will the improved biogeochemical models better predict the spatial-temporal dynamics of GHG emissions from diverse grasslands and croplands in watersheds under changing climate and management practices (e.g., livestock grazing, manure, and irrigation)?
Apply the improved plant-soil-microbe modeling system to model and predict potential of alternative management practices on mitigating GHG emissions from grasslands and croplands across ecosystems to watershed scales
Research Question C
Specific Research Objective C
Research Task CModel and predict GHG emissions in watersheds under varying climate, livestock and manure applications
The Northern Canadian River Watershed in northwest Oklahoma
Annual GPP and daily maximum GPP in 2010 in North America
Education Task AK-12 Teachers and Student Education
The BlueSTEM AgriLearning Center
1. Three students from local schools did primary research under the mentorship of a GRL scientist, and gave poster presentation at the end of school year (2015/2016)
2. Five students from local schools are now working with three GRL scientists for primary research and will give poster presentation at the 15th Annual Kansas, Nebraska and Oklahoma Junior Science and Humanities Symposium, and submit their research paper to National High School Journal of Science (2016/2017 school year)
Summer 2017 Authentic Research Experiences for Teachers (ARET)
Education Task AK-12 Teachers and Student Education
4-day summer workshop for 12+ middle and high school teachers from around the Oklahoma state
Work with researchers at GRL for soil science and relevant field technique
Work with researchers at OU for geospatial technologies and application
Engage in professional development to bring the experience into their STEM classroom
Close collaboration and integration among education groups from K20 and BlueSTEM and research groups in GRL and OU
Education Task BCollege Teachers and Student Education
Education Task CStakeholder and Citizen Education
2016 Geospatial Information Science Day (GISday) The University of Oklahoma, November 17, 2016
Participants: 269 students, faculty, researchers, staff, researchers, exhibitors, and visitors
Exhibitors: 32 booths College Students Poster
Contest and Exhibit: 16 graduate and 2 undergraduate student posters.
K-12 Participation and Activities: 11 AP Geography Southeast High School in Oklahoma City
Financial sponsorship: 12 partners
It is the 5th annual event since 2012.
Simple models
Complex models
Chamber
Eddy flux
CO2
N2O CH4
Microbe
Summary1. We are into the 10th month of the project. 2. Continue to expand the advanced
measurement systems, improve DNDC models, and prepare for watershed study
3. Continue to integrate research and education components.
Thank You !
Any questions?
Welcome to visit the University of Oklahoma, Norman, Oklahoma
http://www.eomf.ou.edu
Research QuestionsA. How do microbial community structure, genetic
diversity, and functional potential affect diurnal to seasonal dynamics of GHG (CO2, N2O and CH4) emissions from grasslands and croplands at different spatial scales?
B. What are the major or minimum phylogenetic or functional molecular signatures of microbial activities to be included in biogeochemical models (e.g., DNDC) for accurately modeling diurnal and seasonal dynamics of GHG emissions from grasslands and croplands?
C. To what degree will the improved biogeochemical models better predict the spatial-temporal dynamics of GHG emissions from diverse grasslands and croplands in watersheds under changing climate and management practices (e.g., livestock grazing, manure, and irrigation)?
Complex models
Specific Research ObjectivesA. Measure and quantify the dynamics of microbial
community structure, diversity, and function to better understand their role in determining GHG emissions under changing environment and management practices
B. Improve DNDC biogeochemical model by incorporating the measured microbial dynamics into the model framework to simulate the interactions among soil climate, nutrients, microbial activity, and GHG emissions in grasslands and croplands
C. Apply the improved plant-soil-microbe modeling system to model and predict potential of alternative management practices on mitigating GHG emissions from grasslands and croplands across ecosystems to watershed scales