Multi-scale analysis of microbe-climate interactions in greenhouse gas emissions from grasslands and croplands

58 %
42 %
Information about Multi-scale analysis of microbe-climate interactions in greenhouse gas...

Published on December 23, 2016

Author: NIFA_IBCE

Source: slideshare.net

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

Add a comment