1a. Objectives (from AD-416):
1. Determine CO2 effects on grassland plant production, plant species composition, and soil C dynamics. 1A. Determine responses of leaf gas exchange (C assimilation, stomatal conductance), plant water status, and plant production of tallgrass prairie assemblages to a subambient to elevated gradient in atmospheric CO2 concentration. 1B. Determine responses of soil respiration and soil organic matter pools (soil C dynamics) of tallgrass prairie assemblages to a subambient to elevated gradient in atmospheric CO2 concentration. 1C. Determine the response of species composition of tallgrass prairie vegetation to a subambient to elevated gradient in atmospheric CO2 concentration. 1D. Determine responses of photosynthetic C assimilation, biomass production, and bioenergy-relevant tissue constituents of the native grass species Panicum virgatum (switchgrass) to a subambient to elevated gradient in atmospheric CO2 concentration. 1E. Determine whether CO2 enrichment from subambient to elevated concentrations increases the potential for invasion of tallgrass prairie assemblages by a non-native grass species. 2. Determine effects of inter-annual variability in precipitation on productivity of switchgrass monocultures and mixed-species plantings of tallgrass prairie species. 2A. Compare responses of aboveground net primary productivity (ANPP) of switchgrass monocultures and mixtures of tallgrass prairie species to inter-annual variability in precipitation. 2B. Determine whether the frequency and magnitude of water limitation to ANPP of switchgrass and mixed-species plantings of prairie vegetation differ between a mollisol and vertisol soil. 3. Validate plant growth and biogeochemistry models to enable simulations of the impact of CO2 enrichment and precipitation variability on grassland production. 3A. Parameterize and validate the ALMANAC model with data from the CO2 gradient experiment and field-scale plots of switchgrass and prairie species. 3B. Parameterize and validate a coupled soil-plant-atmosphere-biogeochemistry model with plant and soil data from the CO2 gradient experiment. 4. Develop strategies to assess and manage the consequences for soil productivity, including carbon, of changing crop production strategies. 4A: Conduct evaluations of short-term carbon mineralization and water extractable organic C and N as a predictor of potential nitrogen mineralization in soil under conventional (inorganic) and organic fertilization. 5: Develop new strategies to improve crop fertilizer use efficiency for agronomic, economic and environmental benefits. 5A: Make final determinations of runoff water quality impacts of fertilizer recommendations based on enhanced soil testing methods. 5B: Conduct final evaluations of liquid fertilizer injection guided by GPS auto-steer technology in terms of yield and economics.
1b. Approach (from AD-416):
Expose vegetated monoliths of three soil types to a continuous gradient in atmospheric carbon dioxide ranging from low levels of the pre-industrial period to elevated concentrations predicted within the century. We will measure leaf gas exchange (carbon assimilation, stomatal conductance), plant water status, plant production, and changes in the relative abundances of tallgrass prairie vegetation growing on each soil type. Soil carbon efflux and changes in soil organic carbon content will be measured in each soil as a function of carbon dioxide treatment. We will measure the responses of photosynthetic carbon assimilation and water use efficiency, biomass production, and bioenergy-relevant tissue constituents of the native grass species switchgrass to carbon dioxide and determine whether carbon dioxide enrichment increases the potential for invasion of tallgrass prairie vegetation by a non-native grass species. We also will compare responses of aboveground net primary productivity of field-scale plantings of switchgrass monocultures and mixtures of tallgrass prairie species to inter-annual variability in precipitation on upland and lowland soils. Two simulation models, the Agricultural Land Management Alternative with Numerical Assessment Criteria model and a coupled soil-plant-atmosphere biogeochemistry model, will be validated with data from the carbon dioxide experiment and field-scale plots of switchgrass and prairie species to simulate effects of changes in both atmospheric carbon dioxide concentration and precipitation patterns on grassland ecosystems. To evaluate short-term carbon mineralization and water extractable organic C and N as a predictor of potential nitrogen mineralization, soil samples will be collected from across the country and include samples from the NAPT soil database. Each sample will be analyzed using the ARS-developed Solvita respiration method and other currently used mineralization tests. To determine runoff water quality impacts of fertilizer recommendations based on enhanced soil testing methods, water quality samples from 6 field-scale cultivated watersheds at the Riesel Watersheds will be collected and analyzed. To evaluate the impacts of liquid fertilizer injection guided by GPS auto-steer technology on crop yield and economics, four replicated treatments (0, 20, 30, and 40 gal rates of 24-8-0 liquid fertilizer) will be implemented on two 25-ac fields, and crop yield, cost, and revenue data will be collected and analyzed.
3. Progress Report:
Scientific effort and fiscal resources from a project terminated in September 2012 were consolidated with the previous version of this project. Objectives 4 and 5 were added. We made substantial progress in addressing each of the five current objectives and related sub-objectives of this project, all of which relate to Objectives identified in National Programs 212 and 215. Objective 1 - We analyzed 7 years of data from an experiment in which assemblages of grassland plants on intact monoliths of each of three soil types have been exposed to a CO2 gradient spanning pre-Industrial to elevated concentrations. One goal is to determine CO2 effects on litter decomposition, soil organic matter pools, and soil C dynamics as mediated by abiotic variables, including soil type and water content, and biotic variables, such as litter quality and the soil microbial community. Litter decomposition rates were increased by increasing soil water content and the frequency of soil drying and re-wetting. Decomposition was greater in clay than sandy soils. Soil type also influenced the response of soil microbial communities to CO2. The number of fungal species and relative abundance of a group of fungi (chytrids) increased linearly with CO2 in a clay soil, whereas the relative abundance of arbuscular mycorrhizal fungi that facilitate plant uptake of soil phosphorus increased linearly with CO2 in a sandy soil. With ARS collaborators at Lincoln, NE, we are evaluating CO2 effects on productivity and bioenergy-relevant tissue constituents in switchgrass (Panicum virgatum). Objective 2 - Using data from 4 long-term experiments, we and university collaborators found that variability in grassland production is reduced by increasing the number of plant species per unit of land area. Production varied less in species-rich than species-poor communities because increasing species richness increased the amount by which assemblages over-yielded relative to yields expected based on production of monocultures of component species. Objective 3 - With university collaborators, we began to develop and test the ALMANAC model for describing CO2 effects on grasslands. ALMANAC was parameterized and validated for a native prairie community of six plant species growing on three soil types at ambient CO2. Daily weather input was created for each monolith along the experimental subambient to elevated CO2 gradient. We are evaluating the capacity of ALMANAC to simulate CO2-caused changes in aboveground production. Objective 4A - Data collection was continued at the USDA-ARS Riesel Watersheds to evaluate runoff water quality impacts of fertilizer recommendations based on enhanced soil testing methods. Objective 4B - Data collection was completed for evaluation of liquid fertilizer injection guided by GPS auto-steer technology. Objective 5 - The enhanced method to rapidly determine soil microbial activity based on CO2 evolution after drying/rewetting soil was completed. This will empower commercial and research labs to produce cost-effective and more accurate quantitative estimates of N mineralization potential and biological soil quality.
1. Innovative soil nitrogen test reduces farm fertilizer expenses and agriculture's environmental impact. Current soil test methods do not determine all sources of plant available nitrogen in the soil. Thus, fertilizer recommendations based on soil test results commonly overestimate the nitrogen required, which results in over application of fertilizer and adverse on-farm economic and offsite environmental impacts. Research at Temple, Texas, through a CRADA with private industry led to the development and commercialization of laboratory soil test methods to rapidly and inexpensively determine the total plant available nitrogen in soils. The test methods, introduced in September 2010, have been adopted by more than 40 soil testing laboratories, including both university and private labs in the US (e.g., Rutgers University, South Carolina University, Auburn University, Colorado State University, Warbs Labs, Brookside Labs, Agvise Labs, and A&L labs), and Ward Labs is now offering the complete "Haney Soil Health Test". The impact of this research has been tremendous. The estimated N fertilizer savings in 2012 from 3000 soil samples was $2.5 million, and this accomplishment has potential to contribute to substantial reduction in agriculture's nitrogen contribution to water quality problems such as Gulf of Mexico Hypoxia.
2. Growth and physiology of the widely dispersed bioenergy plant switchgrass are strongly adapted to environmental conditions at the site of origin. Growth and leaf functional trait variation among genotypes of a geographically widespread dominant species could provide insight into mechanisms of local adaptation and may be important for predicting species and ecosystem responses to environmental change. Together with university collaborators, ARS scientists at Temple, Texas, grew nine genotypes of the dominant C4-tallgrass prairie species Panicum virgatum L. (switchgrass) representing latitudes from Nebraska to south Texas to determine whether there was evidence of local adaptation as demonstrated by an aligning of genotype productivity, morphology, and leaf functional traits with latitude of origin. Genotypes from warmer latitudes began growth earlier, flowered later, produced more aboveground biomass, and had thicker leaves with greater physiological activity compared to genotypes from cooler latitudes. Moreover, genotype leaf thickness showed high broad-sense heritability (0.60) and was genetically correlated with leaf nitrogen and chlorophyll content and leaf water and carbon exchange rates with the atmosphere. Overall, productivity and leaf functional trait variation among P. virgatum genotypes was largely determined by growing season length, strong evidence for local adaptation in P. virgatum. Results will inform scientists about variation among switchgrass genotypes in potential bioenergy production under present and future climates, and guide biomass producers in choosing genotypes well adapted to the Southern Central Plains.
3. Plant traits predict grassland responses to inter-annual variation in precipitation. Plant production varies among years in grassland or pastures as in other ecosystems in response to inter-annual variation in precipitation. Economic returns from grasslands could be improved by adjusting the number or kinds of plant species so as to reduce inter-annual variability in production, but guidance for doing so is lacking. Annual precipitation varied by greater than a factor of three over an 11-year period in central Texas,leading to large inter-annual variation in aboveground production of species mixtures or assemblages planted with different numbers and species of grassland plants. ARS scientists at Temple, Texas, together with university collaborators, found that inter-annual variation in production was least and temporal stability was greatest for plant assemblages with many rather than few species and in which dominant species either rooted shallowly or had dense leaves with little water content relative to dry weight. Managers may use rather easily-measured plant traits to guide their choice of grassland species, which when grown together exhibit relatively stable total yields in the face of inter-annual variability in precipitation. Our results also are directly relevant to scientists and land management agencies responsible for guiding grassland management and improving the economic viability of agricultural producers.
Daneshgar, P.P., Wilsey, B.J., Polley, H.W. 2013. Simple plant traits explain functional group diversity decline in novel grassland communities of Texas. Plant Ecology. 214:231-241.