North American Land Data Assimilation System: A Framework for Merging Model and Satellite Data for Improved Drought Monitoring

Drought is a pervasive natural climate hazard that has widespread impacts on human activity and the environment. In the United States, droughts are billion-dollar disasters, comparable to hurricanes and tropical storms and with greater economic impacts than extratropical storms, wildfires, blizzards, and ice storms combined (NCDC, 2009). Reduction of the impacts and increased preparedness for drought requires the use and improvement of monitoring and prediction tools. These tools are reliant on the availability of spatially extensive and accurate data for representing the occurrence and characteristics (such as duration and severity) of drought and their related forcing mechanisms. It is increasingly recognized that the utility of drought data is highly dependent on the application (e.g., agricultural monitoring versus water resource management) and time (e.g., short- versus long-term dryness) and space (e.g., local versus national) scales involved. A comprehensive set of drought indices that considers all components of the hydrological–ecological–human system is necessary. Because of the dearth of near-real-time in situ hydrologic data collected over large regions, modeled data are often useful surrogates, especially when combined with observations from remote sensing and in situ sources. This chapter provides an overview of drought-related activities associated with the North American Land Data Assimilation System (NLDAS), which purports to provide an incremental step toward improved drought monitoring and forecasting. The NLDAS was originally conceived to improve short-term weather forecasting by providing better land surface initial conditions for operational weather forecast models. This reflects increased recognition of the role of land surface water and energy states, such as surface temperature, soil moisture, and snowpack, to atmospheric processes via feedbacks through the coupling of the water and energy cycles. Phase I of the NLDAS (NLDAS-1; Mitchell et al., 2004) made tremendous progress toward developing an operational system that gave high-resolution land hydrologic products in near real time. The system consists of multiple land surface models (LSMs) that are driven by an observation-based meteorological data set both in real time and retrospectively. This work resulted in a series of scientific papers that evaluated the retrospective data (meteorology and model output) in terms of their ability to reflect observations of the water and energy cycles and the uncertainties in the simulations as measured by the spread among individual models (Pan et al., 2003; Robock et al., 2003; Sheffield et al., 2003; Lohmann et al., 2004; Mitchell et al., 2004; Schaake et al., 2004). These evaluations led to the implementation of significant improvements to the LSMs in the form of new model physics and adjustments to parameter values and to the methods and input meteorological data (Xia et al., 2012). The system has since expanded in scope to include model intercomparison studies, real-time monitoring, and hydrologic prediction and has inspired other activities such as high-resolution land surface modeling and global land data assimilation systems (e.g., the Global Land Data Assimilation System [GLDAS], Rodell et al., 2004; the Land Information System [LIS], Kumar et al., 2006)

Insect resistance of a full sib family of tetraploid switchgrass \u3ci\u3ePanicum virgatum\u3c/i\u3e L. with varying lignin levels

Little information is available on insect resistance mechanisms and inheritance in biomass grasses. Although reduction of lignin in biomass grasses in order to increase the efficiency of fermentation may result in increased susceptibility to insect feeding, other resistance mechanisms may be more important. Field grown leaves of two tetraploid parent (Kanlow N1, Summer) and 14 progeny switchgrass (Panicum virgatum L.) plant clones selected for a diversity of plant form and ranges in lignin levels were tested for leaf resistance to feeding by the fall armyworm (Spodoptera frugiperda J. E. Smith), a grass feeding insect pest. Although lignin generally appeared important as a resistance mechanism only at early season stages, replicate clones of two low lignin progeny plants generally remained resistant to fall armyworm feeding. Mechanical damaging increased resistance to fall armyworm feeding in several of these plants. Degrees of resistance were sometimes associated with leaf form of progeny. These results indicate there are likely multiple insect resistance mechanisms operating at different stages in switchgrass, and that segregation of some mechanisms appears related to growth form of the plants

North American Land Data Assimilation System: A Framework for Merging Model and Satellite Data for Improved Drought Monitoring

Drought is a pervasive natural climate hazard that has widespread impacts on human activity and the environment. In the United States, droughts are billion-dollar disasters, comparable to hurricanes and tropical storms and with greater economic impacts than extratropical storms, wildfires, blizzards, and ice storms combined (NCDC, 2009). Reduction of the impacts and increased preparedness for drought requires the use and improvement of monitoring and prediction tools. These tools are reliant on the availability of spatially extensive and accurate data for representing the occurrence and characteristics (such as duration and severity) of drought and their related forcing mechanisms. It is increasingly recognized that the utility of drought data is highly dependent on the application (e.g., agricultural monitoring versus water resource management) and time (e.g., short- versus long-term dryness) and space (e.g., local versus national) scales involved. A comprehensive set of drought indices that considers all components of the hydrological–ecological–human system is necessary. Because of the dearth of near-real-time in situ hydrologic data collected over large regions, modeled data are often useful surrogates, especially when combined with observations from remote sensing and in situ sources. This chapter provides an overview of drought-related activities associated with the North American Land Data Assimilation System (NLDAS), which purports to provide an incremental step toward improved drought monitoring and forecasting. The NLDAS was originally conceived to improve short-term weather forecasting by providing better land surface initial conditions for operational weather forecast models. This reflects increased recognition of the role of land surface water and energy states, such as surface temperature, soil moisture, and snowpack, to atmospheric processes via feedbacks through the coupling of the water and energy cycles. Phase I of the NLDAS (NLDAS-1; Mitchell et al., 2004) made tremendous progress toward developing an operational system that gave high-resolution land hydrologic products in near real time. The system consists of multiple land surface models (LSMs) that are driven by an observation-based meteorological data set both in real time and retrospectively. This work resulted in a series of scientific papers that evaluated the retrospective data (meteorology and model output) in terms of their ability to reflect observations of the water and energy cycles and the uncertainties in the simulations as measured by the spread among individual models (Pan et al., 2003; Robock et al., 2003; Sheffield et al., 2003; Lohmann et al., 2004; Mitchell et al., 2004; Schaake et al., 2004). These evaluations led to the implementation of significant improvements to the LSMs in the form of new model physics and adjustments to parameter values and to the methods and input meteorological data (Xia et al., 2012). The system has since expanded in scope to include model intercomparison studies, real-time monitoring, and hydrologic prediction and has inspired other activities such as high-resolution land surface modeling and global land data assimilation systems (e.g., the Global Land Data Assimilation System [GLDAS], Rodell et al., 2004; the Land Information System [LIS], Kumar et al., 2006)

Interferometry

The following recommended programs are reviewed: (1) infrared and optical interferometry (a ground-based and space programs); (2) compensation for the atmosphere with adaptive optics (a program for development and implementation of adaptive optics); and (3) gravitational waves (high frequency gravitational wave sources (LIGO), low frequency gravitational wave sources (LAGOS), a gravitational wave observatory program, laser gravitational wave observatory in space, and technology development during the 1990's). Prospects for international collaboration and related issues are also discussed

Age-Induced Diminution of Free Radical Scavenging Capacity in Bee Pollens and the Contribution of Constituent Flavonoids

Bee-collected pollen (“bee pollen”) is promoted as a health food with a wide range of nutritional and therapeutic properties. The objective of the current study is to evaluate the contribution made through the free radical scavenging capability of bee-collected floval pollens by their flavonoid/phenolics constituents, and to determine whether this capability is affected by aging. The free radical scavenging effectiveness of a bee pollen (EC50) as measured by the DPPH method is shown to be determined by the nature and levels of the constituent floral pollens, which can be assayed via their phenolics profiles by HPLC. Each pure floral pollen has been found to possess a consistent EC50 value, irrespective of its geographic origin or date of collection, and the EC50 value is determined to a large extent (ca. 50%) by the nature and the levels of the pollen's flavonoids and phenolic acids. Non-phenolic antioxidants, possibly proteins, account for the balance of the activity. Pollen aging over 3 years is demonstrated to reduce the free radical scavenging activity by up to 50% in the most active floral pollens, which tend to contain the highest levels of flavonoids/phenolic acids. It is suggested that the freshness of a bee pollen may be determined from its free radical scavenging capacity relative to that of fresh bee pollen containing the same floral pollen mix

N fertilizer and harvest impacts on bioenergy crop contributions to SOC

Below ground root biomass is infrequently measured and simply represented in models that predict landscape level changes to soil carbon stocks and greenhouse gas balances. Yet, crop-specific responses to N fertilizer and harvest treatments are known to impact both plant allocation and tissue chemistry, potentially altering decomposition rates and the direction and magnitude of soil C stock changes and greenhouse gas fluxes. We examined switchgrass (Panicum virgatum L.) and corn (Zea mays L.,) yields, below ground root biomass, C, N and soil particulate organic matter-C (POM-C) in a 9-year rain fed study of N fertilizer rate (0, 60, 120 and 180 kg N ha-1) and harvest management near Mead, NE, USA. Switchgrass was harvested with one pass in either August or postfrost, and for no-till (NT) corn, either 50% or no stover was removed. Switchgrass had greater below ground root biomass C and N (6.39, 0.10 Mg ha-1) throughout the soil profile compared to NT-corn (1.30, 0.06 Mg ha-1) and a higher below ground root biomass C:N ratio, indicating greater recalcitrant below ground root biomass C input beneath switchgrass. There was little difference between the two crops in soil POM-C indicating substantially slower decomposition and incorporation into SOC under switchgrass, despite much greater root C. The highest N rate decreased POM-C under both NT-corn and switchgrass, indicating faster decomposition rates with added fertilizer. Residue removal reduced corn below ground root biomass C by 37% and N by 48% and subsequently reduced POM-C by 22% compared to no-residue removal. Developing productive bioenergy systems that also conserve the soil resource will require balancing fertilization that maximizes above ground productivity but potentially reduces SOC sequestration by reducing below ground root biomass and increasing root and soil C decomposition

N fertilizer and harvest impacts on bioenergy crop contributions to SOC

Below ground root biomass is infrequently measured and simply represented in models that predict landscape level changes to soil carbon stocks and greenhouse gas balances. Yet, crop-specific responses to N fertilizer and harvest treatments are known to impact both plant allocation and tissue chemistry, potentially altering decomposition rates and the direction and magnitude of soil C stock changes and greenhouse gas fluxes. We examined switchgrass (Panicum virgatum L.) and corn (Zea mays L.,) yields, below ground root biomass, C, N and soil particulate organic matter-C (POM-C) in a 9-year rain fed study of N fertilizer rate (0, 60, 120 and 180 kg N ha-1) and harvest management near Mead, NE, USA. Switchgrass was harvested with one pass in either August or postfrost, and for no-till (NT) corn, either 50% or no stover was removed. Switchgrass had greater below ground root biomass C and N (6.39, 0.10 Mg ha-1) throughout the soil profile compared to NT-corn (1.30, 0.06 Mg ha-1) and a higher below ground root biomass C:N ratio, indicating greater recalcitrant below ground root biomass C input beneath switchgrass. There was little difference between the two crops in soil POM-C indicating substantially slower decomposition and incorporation into SOC under switchgrass, despite much greater root C. The highest N rate decreased POM-C under both NT-corn and switchgrass, indicating faster decomposition rates with added fertilizer. Residue removal reduced corn below ground root biomass C by 37% and N by 48% and subsequently reduced POM-C by 22% compared to no-residue removal. Developing productive bioenergy systems that also conserve the soil resource will require balancing fertilization that maximizes above ground productivity but potentially reduces SOC sequestration by reducing below ground root biomass and increasing root and soil C decomposition

A crucial role for HVEM and BTLA in preventing intestinal inflammation

The interaction between the tumor necrosis factor (TNF) family member LIGHT and the TNF family receptor herpes virus entry mediator (HVEM) co-stimulates T cells and promotes inflammation. However, HVEM also triggers inhibitory signals by acting as a ligand that binds to B and T lymphocyte attenuator (BTLA), an immunoglobulin super family member. The contribution of HVEM interacting with these two binding partners in inflammatory processes remains unknown. In this study, we investigated the role of HVEM in the development of colitis induced by the transfer of CD4(+)CD45RB(high) T cells into recombination activating gene (Rag)(-/-) mice. Although the absence of HVEM on the donor T cells led to a slight decrease in pathogenesis, surprisingly, the absence of HVEM in the Rag(-/-) recipients led to the opposite effect, a dramatic acceleration of intestinal inflammation. Furthermore, the critical role of HVEM in preventing colitis acceleration mainly involved HVEM expression by radioresistant cells in the Rag(-/-) recipients interacting with BTLA. Our experiments emphasize the antiinflammatory role of HVEM and the importance of HVEM expression by innate immune cells in preventing runaway inflammation in the intestine

Twelve Years of Stover Removal Increases Soil Erosion Potential without Impacting Yield

Corn (Zea mays L.) stover (non-grain aboveground biomass) in the US Corn Belt is used increasingly for livestock grazing and co-feed and for cellulosic bioenergy production. Continuous stover removal, however, could alter long-term agricultural productivity by affecting soil organic C (SOC) and soil physical properties, indicators of soil fertility and erosion potential. In this study, we showed that 12 consecutive yr of 55% stover removal did not affect mean grain yields at any N fertilizer rate (4.5, 6.3, and 6.0 Mg ha−1 for 60, 120, and 180 kg N ha−1 yr−1, respectively) in a marginally productive, rainfed continuous corn system under no-till (NT). Although SOC increased in the top 30 cm of all soils since 1998 (0.54–0.79 Mg C ha−1 yr−1), stover removal tended to limit SOC gains compared with no removal. Near-surface soils (0–5-cm depth) were more sensitive to stover removal and showed a 41% decrease in particulate organic matter stocks, smaller mean weight diameter of dry soil aggregates, and lower abundance of water-stable soil aggregates compared with soils with no stover removal. Increasing N fertilizer rate mitigated losses in total water-stable aggregates in near-surface soils related to stover removal. Collectively, however, our results indicated soil structure losses in surface soils due to lower C inputs. Despite no effect on crop yields and overall SOC gains with time using NT management, annually removing stover for 12 yr resulted in a higher risk of wind and water erosion at this NT continuous corn site in the western Corn Belt