NC1179: Food, Feed, Fuel, and Fiber: Security Under a Changing Climate

(Multistate Research Project)

Status: Active

Homepage

Climate change is in the forefront of the agricultural community. Current predictions on crop and animal performance are based on research literature and accepted understanding of the current biological systems. At present, published research is one the few options available to policy makers and producers alike to predict the potential impacts of climate change over the next 30 years. Many of these issues are extremely complex and cannot be evaluated in the field because of not only this complexity, but also because the changes will be gradual. In addition, the magnitude of these changes is uncertain and difficult to predict, especially at the local scale. Also masking some of the overall changes are the large variabilities that exist within the climate system with often large inter-annual changes.

In reaction to the potential impacts caused by climate change USDA has started the process of developing regional climate hubs. These hubs are being developed to help guide research and outreach for dealing with climate change issues:
USDAs regional hubs will deliver science-based knowledge and practical information to farmers, ranchers and forest landowners within each region of the US to support decision-making related to climate change. These hubs are needed to maintain and strengthen agricultural production, natural resource management, and rural economic development under increasing climate variability. The Hubs will build capacity within USDA to deliver information and guidance on technologies and risk management practices at regional and local scales. (http://www.usda.gov/oce/climate_change/regional_hubs.htm).

NOAA and USDA have recently renegotiated a Memorandum of Understanding to work together on climate and agriculture issues as a result of the 2012 drought. Members of the committee had an opportunity to engage in this discussion and comment on the MOU.

The current committee members as state climatologists and applied climate researchers are well positioned to engage in both of these activities, the USDA Climate Hubs and the NOAA-USDA interaction. Because of the cross-disciplinary efforts of this committee for many years, the members are positioned to engage well in these activities.
A range of climate scenarios exist that attempt to describe how the climate will change over the next three to four decades (Backlund et al., 2008b). These scenarios vary in basic interpretation, but all tend to predict increased temperatures in the range of 1 to 2°C for most of the Great Plains and Midwest. The current literature is replete with results regarding the impact of temperature or drought on crop performance, but seldom are the two evaluated simultaneously and few research frameworks exist that allow for climate changes to be evaluated on a large scale, both geographically and temporally. The recent release of the latest National Climate Assessment concurs with the general trend over the Corn Belt and Plains regions.

Numerous groups have sought to evaluate the impact of climate change on crop performance and the subsequent impacts that this may have on global food, fiber and fuel supplies. Hatfield et al. (2008) indicated that high night temperatures will reduce crop yields as a result of higher respiration requirements and carbon loss. Higher temperatures are also likely to cause more rapid crop development which may result in lower yields by shortening the grain filling period (Muchow, 1990). In fact, Lobell and Asner (2003) predict a 17 percent yield reduction in corn and soybean yield for each 1°C increase in air temperatures when temperature effect was confounded with rainfall limitation. However, when the effect of rainfall deficit was accounted for separately, then Lobell and Field (2007) reported a smaller 8.3% reduction in corn yield and a 1.3% decline in soybean yield per 1ºC rise in temperature. Backlund et al. (2008) also predict that precipitation variability will increase along with the increased incidence of heat waves. This rainfall pattern will likely result in longer periods of water stress followed by intense rainfall events. Wolfe et al. (2008) estimate that crops in the Northeast US will experience higher frequency of temperature stress, perennial crops will have inadequate chilling in the winter and all crops will be exposed to increase pest and weed pressure. Crop, soil, pest, and economic models that are used singularly or simultaneously exist in systems that can rapidly test the impacts of drought and temperature stress on crop species.

Corn yields are currently increasing at a rate of approximately 95 kg ha-1 year-1. Recent trends in yields over the last four years have seen below trend yields occurring in the corn belt as a whole because of combinations of droughts, extreme heat and late planting because of wet spring conditions. Predictions suggest that because of increased night temperatures and greater incidence of water stress, this trend will decline to little or no annual improvement. Such predictions assume that plant adaptation, both natural and through human interaction (breeding), will not occur as climate change is occurring. Evaluating the impact of a breeding program, which may focus on performance under high temperatures, is difficult with current field and growth chamber technology, because most controlled environment systems, like SPAR or FACE, are too small to allow for germplasm evaluation or traditional breeding techniques (Hatfield et al., 2008). Crop models exist in systems that can rapidly test the impacts of improved drought or temperature tolerance on crop productivity as climate change occurs or they can be used to provide plant breeders with areas of focus to address this challenge.

Along with increased variability in precipitation, it has been predicted that total rainfall amounts in the Midwest and Great Plains will be reduced approximately 10% with a shift toward more precipitation being received during the winter months and less during the summer months (Backlund et al., 2008). Increased precipitation variability will increase the risk associated with crop production through longer periods of drought and higher intensity thunderstorms. These events result in lower yields as well as greater opportunities for soil erosion and crop damage from hail and damaging winds. Increased intensity of heavy rainfall events will continue to cause excess run-off, flooding and increased soil erosion.

Soil organic matter levels affect water infiltration rates, soil water holding capacity (Hudson, 1994), crop productivity, and is a regarded as one of the primary measures of soil quality. Increases in temperatures, reduced crop productivity and increased soil water deficits (because of increased precipitation variability) could reduce soil organic matter levels if management practices such as reduced tillage and the use of cover crops are not adopted. The effects of reduced tillage and the use of cover crops [cite] are well documented as methods of increasing soil organic matter, but the effects of increased temperatures and reduced soil water content are not and will be difficult to assess with current field and growth chamber techniques and technology. Integrated or coupled crop, soil, and economic models can be deployed to address these problems. The advantage of a modeling approach is the range of treatments that can be tested is nearly unlimited and is only constrained by the model functionality.

A great deal of focus has been placed on the impacts that increased temperatures and precipitation variability may have on crop productivity. However, these climate scenarios may equally affect disease, insect and weed pests. Increased temperatures will likely alter insect, disease and weed lifecycles as well. Recent research has illustrated that some weed species require greater quantities of herbicide to control them when CO2 increases (Ziska et al., 1999). However the change for many pests can be positive, negative or neutral depending on the local environment change (Coakley et al., 1999). The impact is even more complicated since climate change not only affects the pest response, but equally affects the host response to disease and insect attack (Garrett et al., 2006). Until climate change scenarios can be down-scaled to the level where pest impact can be modeled and assessed, uncertainty will remain (Seem, 2004).
To complicate the challenges associated with climate change, the Renewable Fuel Standard Program mandate to quadruple bioenergy contributions to the U.S. fuel supply by 2010 (U.S. Dep. of Energy, 2007; http://www.epa.gov/oms/renewablefuels/). Biofuel production has many production challenges, but protecting soil and water simultaneously is also important to society as a whole. Many agricultural practices developed over the past decade (nutrient and manure management, cropping systems, reduced tillage systems) have made great strides in improving and protecting soil and water resources that benefit the general public as well as the crop producer. However, if pressure to remove residue from production fields to produce bioenergy is not properly balanced, then these soil quality gains could be lost along with soil through erosion and water quality through impairments via runoff. Developing crop management systems that provide bioenergy feedstocks while protecting soil and water resources will be difficult to study in the field because runoff studies require large watersheds, numerous locations and many years to encompass a wide range of environments. These types of studies require a large amount of financial support and will span five to ten years before tangible results will be available. Once again, integrated models can address these questions rapidly and can evaluate a larger number of treatments than field experiments. Coupled or integrated crop, soil and economic models are poised to address questions that may arise because of expected climate change.

Other questions related to bioenergy production include the most appropriate species to be produced at a given location and the evaluation of perennial, annual or mixed cropping systems to address the needs of the bioenergy industry. Perennial crops have the advantage that after establishment, annual production costs and energy requirements are lower than annual crops. Traditional perennial grass production has largely occurred in marginal areas, which means that there is not a clear understanding of their production potential if grown in higher production environments (i.e. switchgrass on deep silt loam soils or under irrigation). It would be within the framework of the existing databases and crop models to evaluate switchgrass or other perennial crops both spatially and temporally across the ten-state region.

The advantage of annual crop systems for bioenergy production is they allow producers flexibility to respond to the food, fiber and fuel needs of society rapidly. It is conceivable that future bioenergy systems that adequately balance food and fuel needs while simultaneously protecting soil and water resources will include both food and fuel crops with the use of cover crops during fallow periods to reduce the negative impacts of annual crop production. Developing such a system can be easily evaluated with integrated models across a wide range of environments and soils types (Hoogenboom et al., 2004).

Earlier iterations of this committee, (North Central Regional Committee 1018) have not only developed a spatial-temporal database of soils, weather, and crop information for the ten north central states, it has developed a research model that can easily be replicated in other regions of the U.S. or the world. The methodologies used to aggregate these data to a county resolution could be applied to other regions to develop similar databases. The system also has the ability to create input files for use in integrated crop-soil-environment suites such as the Decision Support System for Agrotechnology Transfer (DSSAT; Hoogenboom et al., 2004), but also has lower level soil and crop simulation models programmed within the Modeling Applications Integrated Framework (MASIF) database at the Computational Ecology and Visualization Laboratory at Michigan State University. The future plans are to use the existing measured weather data to develop climate change scenarios which will add a new suite of capabilities to this system that can aid in answering production, economic and policy oriented questions.

In addition several current NC-1179 members run state networks through then own auspices ranging from the Pacific Northwest, to the Plains and Corn Belt. These networks have been developed to enhance monitoring and forecasting for disease, insect and irrigation applications. The networks also provide a unique ability for cooperation on monitoring lesser-noted atmospheric data such as humidity, wind, soil temperature and soil moisture. In some cases these stations provide the only data available in regions. Collaboration among the members will allow for better development and monitoring of changes and variability in these additional types of data. Long term data sets for temperature and precipitation at higher spatial density (roughly county level), but are not available for the other data sets. The continuing monitoring of these types of data in their states will continue to show the trends and variability existing in these data. The existence of these state networks was the basis for a soil moisture and snow monitoring proposal for the Upper Missouri Basin which is currently part of a WRDA (Water Resources Development Act S.R 601) which passed out of the Senate in the spring of 2013. The committee also has a long history of developing new and innovative measurement standards, data manipulation and quality control methods.

Most climate change scenario predictions are at very large scales (several 1000 km2); however, the NC-94/1018 database has a county level spatial resolution. It has an existing temporal resolution of 30 year with the tools and templates in place to expand temporally as more data is measured. The importance of these data is they first can serve as baseline for measured data comparisons over the next 30 to 40 years AND can serve as a baseline from which to develop climatologies from the climate change model predictions. An integrated modeling approach is needed in order to develop effective policies, management programs that secure our food, fuel, and fiber supply as well as protect our natural resources. Often these systems need to be evaluated simultaneously for the biological, agronomic, ecologic and economic impacts. Since all of these variables are intertwined, one model type (crop model, soil model, etc) will seldom accomplish -the objectives set forth here. The scientists who participate in NC-1018 encompass a wide range of disciplines and include crop modelers, soil scientists, climatologists, and agricultural economists. This integrated team has the capabilities to address all of the issues described above and objectives stated below through large scale, integrated modeling efforts.

The committee is also well positioned in working with currently-funded USDA and NOAA grants to develop tools for producers. These projects include the AFRI-funded (U2U) Useful to Usable Project developing tools for producers in the Corn Belt, the Corn CAP, working on climate change issues and tools in the Corn Belt and the NOAA Regional Integrated Sciences Assessment -The Southeast Climate Consortium. Six state climatologists are also involved. All are using climate information to help develop decision-making in agriculture in some form to help users make decisions. These tool applications are excellent methods of connected current research to tools and applications for producers.
Log Out ?

Are you sure you want to log out?

Press No if you want to continue work. Press Yes to logout current user.

Report a Bug
Report a Bug

Describe your bug clearly, including the steps you used to create it.