Objectives - Understand, model and predict greenhouse gases emissions from grasslands and winter wheat croplands under changing microbes, climate, livestock and manure use across the scales of field, farm and watershed - Broaden STEM education for K-12 and college students and teachers, and engage farmers, ranchers, decision makers, and citizen scientists to participate in in-situ data collection and analyses

1. Xiangming Xiao (肖向明)
Department of Microbiology and Plant Biology
Earth Observation and Modeling Facility
Center for Spatial Analysis
University 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

2. 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 Hampshire
Jia Deng, Steve Frolking,
USDA ARS Grazinglands Research Laboratory
Brekke Peterson Munks, Jean Steiner,

3. 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, OK
Ann Marshall,
All researchers in the project

4. Scientific Background
Winter 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

5. Research Questions
A. 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
Time
Space

6. Research Question A
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?
Complex
models
Specific Research Objective A
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
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

7. IGOS and ICOS Sites in
operation
Integrated grassland
observation sites
El Reno: 2 (native tallgrass
prairie, OWB pasture)
Marena, Stillwater: 1 (tallgrass
prairie)
KAEFS, Purcell: 1 (tallgrass
prairie)
Integrated cropland
observation sites
El Reno: 2 (winter wheat; till
versus no-till; graze-out,
fall/winter graze only)
Eddy flux tower measurements: Diurnal dynamics of CO2
and 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.

8. Soil and Microbe Sampling Sites at El Reno
IGOS-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)

9. 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 site
2. Old World Bluestem pasture
site
Integrated Cropland
Observation site (ICOS)
1. Winter wheat (No till)
2. Winter wheat (Till)

10. Soil and Microbe Sampling Component and Results at El Reno, OK
Sample Depth Sampling Frequency Analysis Start Date
Sample Number at each
site
Total 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 40
Texture
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 Gas
From 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 Biomass
Carbon 60 240
Microbial Biomass
Nitrogen 60 240
Polylipid Fatty Acid
Analysis (PLFA) 60 240

11. Chamber measurements of
GHG emissions from soils
CO2 emission
Black line – Tallgrass Prairie site
Gray line – Old World Bluestem pasture site
N2O emission
CH4 emission
WFPS
From Peterson Munk, in preparation;
2016 data are in processing

12. Soil microbial community analysis
Dataintegrationandmodelling
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

13. Preliminary Results from Microbe Analyses
Native tallgrass
prairie
Winter wheat
(tillage)
From Wawrik et al., in preparation

14. Sites Number of cores per
sampling point at each
site
Sampling Dates Total Number of
Samples Collected
Samples Analyzed for
Microbial Community
Structure
4
Native 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
8/3/2016
8/17/2016
8/31/2016
9/14/2016
9/28/2016
10/12/2016
10/16/2016
11/9/2016
12/7/2016
360 cores collected
(9 time points
4 sites
10 cores each)
8/3/2016
8/17/2016
8/31/2016
9/14/2016
9/28/2016
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.

15. Research Question B
Complex
models
Specific Research Objective 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?
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
Research Task B
Incorporate representation of microbes into
biogeochemical models that estimate GHG emissions
from grasslands and croplands
DNDC model

16. 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 asterisks
legend
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

17. 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 C
Model 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

18. Education Task A
K-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)

19. Summer 2017
Authentic Research Experiences for Teachers (ARET)
Education Task A
K-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

20. Education Task B
College Teachers and
Student Education
Education Task C
Stakeholder 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.

21. Simple
models
Complex
models
Chamber
Eddy flux
CO2
N2O CH4
Micr
obe
Summary
1. 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.

22. Thank You !
Any questions?
Welcome to visit the University of Oklahoma, Norman, Oklahoma
http://www.eomf.ou.edu

23. Research Questions
A. 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 Objectives
A. 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