IRRIGATED AND RAINFED CROPS Zea mays L. (MAIZE) AND Glycine max (SOYBEAN) ACTING AS A SOURCE OR SINK FOR ATMOSPHERIC WARMING AT MEAD, NEBRASKA

Land Use and Land Cover Change (LULCC) influence the climate at a global and local scale. Using long term microclimate data (2002-2009, 2011-2012) from the Carbon Sequestration Project (CSP), Mead, NE, this study examines how crop selection and water management can mitigate heat in the atmosphere. Mitigation of global warming is dependent on the management of crop lands, and the amount and timing of rainfall during the growing season. Rainfed crops were found to heat the passing air. The irrigated maize crop was able to mitigate 20 to 62% of the sensible heat (H) compared to the rainfed maize counterpart, the lower value for wet years and the larger value for dry years. Soybeans under irrigation, on the other hand, extracted a maximum of 37% of cumulated H in comparison to rainfed soybean. The irrigated maize field can reduce the warming by as much as 76% compared to the rainfed soybean crop. In addition to increasing yields, irrigation of maize greatly reduces the heating of air, thus moderating regional climate in east central Nebraska

Fitting measured evapotranspiration data to the FAO56 dual crop coefficient method

The FAO-56 publication of the UN Food and Agriculture Organization contains guidelines on constructing and applying a ‘dual crop coefficient’ method to characterize the behavior of evapotranspiration (ET) on a day to day basis. The dual crop coefficient (Kc) method substantially improves the ability to fit simulated with measured data, as compared to the ‘single’ Kc method, by partitioning evaporation from soil (Es) from transpiration from vegetation. This permits the separate estimation of Es when there are known wetting events from precipitation and irrigation and assists in explaining behavior of measured data. The application of the dual Kc method is relatively straight forward, especially when applied using the straight-line segment method for the basal Kc curve, Kcb. Illustrations are given on fitting the dual Kc method and Kcb curve to daily ET data for irrigated and rainfed corn crops near Mead, Nebraska measured by eddy covariance and sensitivity to various soil and root zone parameters. Assessment of transferring Kcb curve parameters to other fields and years indicates that soil and root zone parameters are relatively transferrable with little modification, whereas lengths of the four crop growth stages do vary from year to year due to differences in cultivar type and possibly differences in weather

Spatio-Temporal Dynamics of Soil Microbial Communities in a Pasture: A Case Study of <em>Bromus inermis</em> Pasture in Eastern Nebraska

Today’s intensified agricultural production is characterized by crop and pasture monocultures, which have a significant impact on soil microbial diversity and abundance. This chapter provides a case study in which the relative importance of brome grass (Bromus inermis) monoculture pasture versus intra-site microhabitat diversity is explored using fatty acid methyl ester (FAMEs) assay to delineate the presence and abundance of several classes of soil microbes instrumental in soil nutrient cycling, plant health, plant organic matter decomposition, and soil stabilization. The chapter explores spatio-temporal variability of bacteria, actinomycetes, saprophytes, mycorrhizae, and micro-eukaryotes over two durations (summer and fall) collected using two distinct sampling methods. One of the methods is commonly employed, namely, transect-based, while the other is informed by soil electroconductivity measurements conducted over the entire pasture site from a previous survey

Air temperature equation derived from sonic temperature and water vapor mixing ratio for air flow sampled through closed-path eddy-covariance flux systems

Air temperar (T) plays a fundamental role in many aspects of the flux exchanges between the atmosphere and ecosystems. Additionally, it is critical to know where (in relation to other essential measurements) and at what frequency T must be measured to accurately describe such exchanges. In closed-path eddy-covariance (CPEC) flux systems, T can be computed from the sonic temperature (Ts) and water vapor mixing ratio that are measured by the fast-response senosrs of three-dimensional sonic anemometer and infrared gas analyzer, respectively. T then is computed by use of either T = Ts( 1+0.51 q), where q is specific humidity, or T = Ts( 1 + 0.32e∕ P) − 1 , where e is water vapor pressure and P is atmospheric pressure. Converting q and e/P into the same water vapor mixing ratio analytically reveals the difference between these two equations. This difference in a CPEC system could reach ±0.18 K, bringing an uncertainty into the accuracy of T from both equations and raises the question of which equation is better. To clarify the uncertainty and to answer this question, the derivation of T equations in terms of Ts and H2O-related variables is thoroughly studied. The two equations above were developed with approximations. Therefore, neither of their accuracies were evaluated, nor was the question answered. Based on the first principles, this study derives the T equation in terms of Ts and water vapor molar mixing ratio (c H2O) without any assumption and approximation. Thus, this equation itself does not have any error and the accuracy in T from this equation (equation-computed T) depends solely on the measurement accuracies of Ts and c H2O . Based on current specifications for Ts and c H2O in the CPEC300 series and given their maximized measurement uncertainties, the accuracy in equation-computed T is specified within ±1.01 K. This accuracy uncertainty is propagated mainly (±1.00K) from the uncertainty in Ts measurements and little (±0.03K) from the uncertainty in c H2O measurements. Apparently, the improvement on measurement technologies particularly for Ts would be a key to narrow this accuracy range. Under normal sensor and weather conditions, the specified accuracy is overestimated and actual accuracy is better. Equation-computed T has frequency response equivalent to high-frequency Ts and is insensitive to solar contamination during measurements. As synchronized at a temporal scale of measurement frequency and matched at a spatial scale of measurement volume with all aerodynamic and thermodynamic variables, this T has its advanced merits in boundary-layer meteorology and applied meteorology

Assessing Responses of \u3ci\u3eBetula papyrifera\u3c/i\u3e to Climate Variability in a Remnant Population along the Niobrara River Valley in Nebraska U.S. through Dendroecological and Remote Sensing Techniques

Remnant populations of Betula papyrifera have persisted in the Great Plains after the Wisconsin Glaciation along the Niobrara River Valley, Nebraska. Population health has declined in recent years, and has been hypothesized to be due to climate change. We used dendrochronological techniques to assess the response of B. papyrifera to microclimate (1950-2014), and satellite imagery [Landsat 5 TM (1985-2011) and MODIS (2000-2014)] derived NDVI as a proxy for population health. Growing-season streamflow and precipitation were positively correlated with raw and standardized tree-ring widths and basal area increment increase. Increasing winter and spring temperatures were unfavorable for tree growth while increasing summer temperatures were favorable in the absence of drought. The strongest predictor for standardized tree-rings was the Palmer Drought Severity Index, suggesting that B. papyrifera is highly responsive to a combination of temperature and water availability. The NDVI from vegetation community was positively correlated with standardized tree-ring growth, indicating the potential of these techniques to be used as a proxy for ex-situ monitoring of B. papyrifera. These results aid in forecasting the dynamics of the species in the face of climate variability and change in both remnant populations and across its current distribution in northern latitudes of North America

Decision Support Tools to Address Climate Change: Climate Model - Land Surface Models, \u3ci\u3eZea mays\u3c/i\u3e L. (Corn) Phenology and Evapotranspiration-Yield Sensitivity Models For Nebraska, USA.

Nebraska\u27s climate is highly variable and is expected to change in the future with anthropogenic global warming (AGW), resulting in warmer spring and summer temperatures coupled with more erratic rainfall events. This has strong implications for agriculture in the region, yet it is not clear that current modeling and decision-support tools are adequate to address these looming changes and provide planning, mitigation and adaptation strategies. To address climate change and its implications to agriculture in Nebraska, a set of robust decision support tools are very crucial. This study herein are divided into three chapters, with each chapter addressing a specific tool/s and its usefulness as a support decision tool. The first chapter, examines climate models and land surface models that provide weather forecasts. The usefulness of climate models and land surface models (LSM) hinges on their accuracy. Two candidate LSMs were evaluated: the Noah and the Community Land Surface Model (Version 3.5). The findings are helpful in selecting useful models that can be applied to make weather predictions in the near future for yield predictions and decision making. The second chapter examines the current modeling of phenological sensitivity and development of corn to temperature using thermal units also known as, Growing Degree Days (GDDs) based on an upper and lower temperature threshold of 30°C and 10°C respectively. Additionally, the accuracy of closest weather station data in modelling corn phenology for rainfed and irrigated sites was evaluated. In the third chapter the sensitivity of corn to water stress during different growth periods/stages is examined with the intention of supporting irrigation scheduling decisions with limited water resources. Since crops are not equally sensitive to growth in all stages of their development, multiplicative empirical models are developed using two approaches. The new sensitivity coefficients are also compared to those derived for the USA cornbelt by Meyer et al. (1993). The models developed will facilitate analysis of deficit irrigation strategies and their impacts on crop yields thereby offering a means of sustaining high corn yields in the future in lieu of imminent climate changes. Co-Advisers: Kenneth Hubbard and Ayse Kili

Decision support tools to address climate change: Climate model - land surface models, Zea mays l. (corn) phenology and Evapotranspiration-yield sensitivity models for Nebraska, USA

Nebraska\u27s climate is highly variable and is expected to change in the future with anthropogenic global warming (AGW), resulting in warmer spring and summer temperatures coupled with more erratic rainfall events. This has strong implications for agriculture in the region, yet it is not clear that current modeling and decision-support tools are adequate to address these looming changes and provide planning, mitigation and adaptation strategies. To address climate change and its implications to agriculture in Nebraska, a set of robust decision support tools are very crucial. This study herein are divided into three chapters, with each chapter addressing a specific tool/s and its usefulness as a support decision tool. The first chapter, examines climate models and land surface models that provide weather forecasts. The usefulness of climate models and land surface models (LSM) hinges on their accuracy. Two candidate LSMs were evaluated: the Noah and the Community Land Surface Model (Version 3.5). The findings are helpful in selecting useful models that can be applied to make weather predictions in the near future for yield predictions and decision making. The second chapter examines the current modeling of phenological sensitivity and development of corn to temperature using thermal units also known as, Growing Degree Days (GDDs) based on an upper and lower temperature threshold of 30°C and 10°C respectively. Additionally, the accuracy of closest weather station data in modelling corn phenology for rainfed and irrigated sites was evaluated. In the third chapter the sensitivity of corn to water stress during different growth periods/stages is examined with the intention of supporting irrigation scheduling decisions with limited water resources. Since crops are not equally sensitive to growth in all stages of their development, multiplicative empirical models are developed using two approaches. The new sensitivity coefficients are also compared to those derived for the USA cornbelt by Meyer et al. (1993). The models developed will facilitate analysis of deficit irrigation strategies and their impacts on crop yields thereby offering a means of sustaining high corn yields in the future in lieu of imminent climate changes

Biological Suppression of Velvetleaf (\u3ci\u3eAbutilon theophrasti\u3c/i\u3e ) in an Eastern Nebraska Soil

Weed-suppressive soils contain naturally occurring microorganisms that suppress a weed by inhibiting its growth, development, and reproductive potential. Increased knowledge of microbe–weed interactions in such soils could lead to the identification of management practices that create or enhance soil suppressiveness to weeds. Velvetleaf death and growth suppression was observed in a research field (fieldA) that was planted with high populations of velvetleaf, which may have developed via microbial mediated plant–soil feedback. Greenhouse studies were conducted with soil collected from fieldA (soilA) to determine if it was biologically suppressive to velvetleaf. In one study, mortality of velvetleaf grown for 8 wk in soilA was greatest (86%) and biomass was smallest (0.3 g plant-1) in comparison to soils collected from surrounding fields with similar structure and nutrient content, indicating that suppressiveness of soilA was not likely caused by physical or chemical factors. When soilA was autoclaved in another study, mortality of velvetleaf plants in the heat-treated soil was reduced to 4% compared to 55% for the untreated soil, thus suggesting that suppressiveness of soilA is biological in nature. A third set of experiments showed that suppressiveness to velvetleaf could be transferred to an autoclaved soil by amending the autoclaved soil with untreated soilA; this provided additional evidence for a biological basis for the effects of soilA. The suppressive condition in these greenhouse experiments was associated with high soil populations of fusaria. Fusarium lateritium was the most frequently isolated fungus from roots of diseased velvetleaf plants collected from fieldA, and also was the most virulent when inoculated onto velvetleaf seedlings. Results of this research indicate that velvetleaf suppression can occur naturally in the field and that F. lateritium is an important cause of velvetleaf mortality in fieldA

Photosynthetic performance of invasive \u3ci\u3ePinus ponderosa\u3c/i\u3e and \u3ci\u3eJuniperus virginiana\u3c/i\u3e seedlings under gradual soil water depletion

Changes in climate, land management and fire regime have contributed to woody species expansion into grasslands and savannas worldwide. In the USA, Pinus ponderosa P. & C. Lawson and Juniperus virginiana L. are expanding into semiarid grasslands of Nebraska and other regions of the Great Plains. We examined P. ponderosa and J. virginiana seedling response to soil water content, one of the most important limiting factors in semiarid grasslands, to provide insight into their success in the region. Photosynthesis, stomatal conductance, maximum photochemical efficiency of PSII, maximum carboxylation velocity, maximum rate of electron transport, stomatal limitation to photosynthesis, water potential, root-to-shoot ratio, and needle nitrogen content were followed under gradual soil water depletion for 40 days. J. virginiana maintained lower Ls, higher A, gs, and initial Fv/Fm, and displayed a more gradual decline in Vcmax and Jmax with increasing water deficit compared to P. ponderosa. J. virginiana also invested more in roots relative to shoots compared to P. ponderosa. Fv/Fm showed high PSII resistance to dehydration in both species. Photoinhibition was observed at ~30% of field capacity. Soil water content was a better predictor of A and gs than Ψ, indicating that there are other growth factors controlling physiological processes under increased water stress. The two species followed different strategies to succeed in semiarid grasslands. P. ponderosa seedlings behaved like a drought-avoidant species with strong stomatal control, while J. virginiana was more of a drought-tolerant species, maintaining physiological activity at lower soil water content. Differences between the studied species and the ecological implications are discussed

Assessing Responses of \u3ci\u3eBetula papyrifera\u3c/i\u3e to Climate Variability in a Remnant Population along the Niobrara River Valley in Nebraska U.S. through Dendroecological and Remote Sensing Techniques

Remnant populations of Betula papyrifera have persisted in the Great Plains after the Wisconsin Glaciation along the Niobrara River Valley, Nebraska. Population health has declined in recent years, and has been hypothesized to be due to climate change. We used dendrochronological techniques to assess the response of B. papyrifera to microclimate (1950-2014), and satellite imagery [Landsat 5 TM (1985-2011) and MODIS (2000-2014)] derived NDVI as a proxy for population health. Growing-season streamflow and precipitation were positively correlated with raw and standardized tree-ring widths and basal area increment increase. Increasing winter and spring temperatures were unfavorable for tree growth while increasing summer temperatures were favorable in the absence of drought. The strongest predictor for standardized tree-rings was the Palmer Drought Severity Index, suggesting that B. papyrifera is highly responsive to a combination of temperature and water availability. The NDVI from vegetation community was positively correlated with standardized tree-ring growth, indicating the potential of these techniques to be used as a proxy for ex-situ monitoring of B. papyrifera. These results aid in forecasting the dynamics of the species in the face of climate variability and change in both remnant populations and across its current distribution in northern latitudes of North America