Project Number: 2090-11000-006-00-D
Project Type: Appropriated
Start Date: Mar 26, 2010
End Date: Mar 5, 2015
Objective 1. Characterize key environmental and management drivers of agricultural wind-blown dust and PM10/PM2.5 emissions that will improve process-oriented models and decision aids. Sub-obj. 1.a. Determine the relationship between soil wetness/crusting and emission of windblown dust and PM10/PM2.5. Sub-obj. 1.b. Determine the biotic factors driving aggregate formation and stability in dryland soils and their influence on windblown dust and PM10/PM2.5 emissions. Sub-obj. 1.c. Determine the effect of wind erosion and management practices on soil organic matter (SOM), soil biological communities and other soil characteristics. Objective 2. Develop techniques for identifying sources of PM10/PM2.5 to better associate management practices with PM10/PM2.5 emissions and to corroborate models. Sub-obj. 2.a. Determine the efficacy of FAME and tracer methods in discerning soils contained in various mixtures. Sub-obj. 2.b. Determine point source soil movement and FAME efficacy using known microbial tracers. Sub-obj. 2.c. Determine the effectiveness of using FAME fingerprinting to corroborate the Columbia Plateau regional dust transport model. Objective 3. Characterize roles of environmental and management drivers on soil C and N cycling as factors regulating GHG (N2O, CO2) emissions from agricultural soils. Sub-obj. 3.a. Determine soil C sequestration rates and CO2 flux as influenced by agroecosystem drivers (e.g. soil, topography, micro-climate, organisms, management). Sub-obj. 3.b. Determine biogeochemical dynamics of soil C and N including N2O flux as influenced by agroecosystem drivers (e.g. soil, topography, micro-climate, organisms, management). Objective 4. Develop agricultural PM10/PM2.5 and GHG mitigation strategies and management decision aids for Pacific Northwest cropping systems. Sub-obj. 4.a. Determine the effectiveness of alternative tillage and cropping practices in reducing the emission of windblown dust and PM10/PM2.5 from agricultural soils. Sub-obj. 4.b. Develop precision N management practices that increase N use efficiency and decrease N2O emissions. Objective 5: As part of the LTAR network, and in concert with similar long-term, land-based research infrastructure in Inland Pacific Northwest, use the R.J. Cook Agronomy Farm LTAR (CAF) to improve the observational capabilities and data accessibility of the LTAR network, to support research to sustain or enhance agricultural production and environmental quality in agroecosystems characteristic of the Inland Pacific Northwest, as per the LTAR site responsibilities and other information outlined in the 2012 USDA Long- LTAR Network Request for Information (RFI) to which the location successfully responded, and the LTAR Shared Research Strategy, a living document that serves as a roadmap for LTAR implementation. Participation in the LTAR network includes research and data management in support of the ARS GRACEnet and/or Livestock GRACEnet projects.
1a. Sediment and PM10/PM2.5 flux, will be evaluated as a function of soil water content/matric potential & crust type/cover/thickness for five major soil types using a portable wind tunnel. Crust type & morphology will be ascertained by microscopy & PLFA & FAME analyses. 1b. Soil aggregate properties will be assessed under a range of crop & tillage systems being examined to control wind-blown dust. Soil aggregate size classes from different crop & tillage systems will be analyzed to identify microbial community composition (PLFA & FAME analyses), active SOM, C source & crushing strength. 1c. Long-term cropping system studies at Lind, Pullman, & Ritzville will be used to assess impacts on soil quality over time including bulk density, soil pH, electrical conductivity, organic C & N, aggregate size distribution, N movement & soil microbial constituents. 2a. Ongoing research will fingerprint soils & PM10 material from across the PNW using FAME. 2b. Bacteria & fungi containing natural markers will also be evaluated as tracers that can be retrieved from soils due to their unique traits of antibiotic resistance or strain-specific molecular markers to determine point source soil movement. 2c. The FAME & bacterial tracer studies will be used to aid corroboration of the Columbia Plateau regional dust transport model by: (1) determining if modeled emissions are from given fields or grid areas; & (2) characterizing the mode of transport from given regions. 3a. Studies are part of GRACEnet (Greenhouse Gas Reduction through C sequestration & Carbon Enhancement Network) & REAP (Renewable Energy Assessment Project), established to assess management impacts on greenhouse gas emissions & soil C status. We will assess tillage & crop rotation affects on soil C storage across variable soil & terrain attributes of the WSU Cook Agronomy Farm (CAF). 3b. Two studies will assess management & environmental effects on soil C and N cycling & GHG emissions. The first study (CAF) was previously described in sub-objective 3a. The second study was established in 2001 at the USDA Palouse Conservation Field Station & consists of five different farming systems including no-till, perennial biofuels, organic, & native perennials. These two field studies will be used to assess soil gas (CO2, N2O) flux, N mineralization-immobilization-turnover & soil C accumulation. 4a. A portable wind tunnel will be used to assess differences in windblown sediment & PM10/PM2.5 emissions among tillage & cropping systems established at various locations across the Columbia Plateau. Wind speed profiles will be measured using pitot tubes, sediment catch obtained using an isokinetic vertical slot sampler, & PM10 concentration profiles obtained using DustTrak aerosol samplers. 4b. Field studies at the CAF will evaluate two N management treatments for winter & spring wheat: (1) site-specific N management based on the spatial pattern of input variables; & (2) uniform N management. N use efficiency will be evaluated to monitor cropping system N use, assess N management strategies & identify key areas for improvements.