Wheat May Fare Better Under Climate Change than Normally Assumed

Issue: The long-term sustainability of wheat-based dryland cropping systems in the inland Pacific Northwest (PNW) depends on how these systems adapt to climate change. Climate models project warming in the region, with drier summers and slight increases in winter precipitation. These conditions are likely to decrease yields, particularly of spring crops, although adaptations such as earlier planting will help delay negative effects. However, the rising levels of atmospheric carbon dioxide (CO₂) that are driving global warming also have direct beneficial effects on crops, promoting crop growth and improving wateruse efficiency. This effect, sometimes referred to as “CO₂ fertilization,” might mean that the future of dryland agriculture is better than it is assumed to be when considering climate warming alone.

Action taken: To understand the interaction between climate change and increasing atmospheric CO₂ in the inland PNW and its impact on regional wheat-based systems, we used computer simulations that combined cropping systems models with weather  generated from projections by 12 global circulation models. The models considered two levels (low and high) of increasing atmospheric CO₂ and associated warming (higher warming associated with higher atmospheric CO₂). We developed projections of future crop yields for this century and compared them with baseline yields for the period 1979 to 2010.

Results: Despite the common assumption of negative climate change impacts on agricultural production, computer simulations indicated that wheat productivity will actually increase in the inland PNW for most of the century. Higher winter and spring temperatures should benefit the growth of winter crops and allow for earlier planting of spring crops. Earlier maturity of both types of crops would help  avoid the more extreme and  damaging summer heat.

Considering only climate change (temperature increase and some change in precipitation but no CO₂ fertilization effect), yields were projected to remain constant throughout the century at the lower level of warming but to first increase and then decline below baseline values at the higher level of warming. When CO₂ fertilization effects were included, wheat yields for the lower levels of atmospheric CO₂ and warming were projected to have a small and steady increase until the end of the century, but at higher levels of atmospheric CO₂ and warming, wheat yields were projected to increase up to midcentury and then decline by the end of the century to levels generally similar to baseline. 

Above: Daily time-step comparison of METRIC and EC ET_a at four REACCH sites (MSMN, LIND, CFNT, and CFCT) and three growing seasons. Abbreviations: SB=Spring Barley, SP=Spring Pea, WW=Winter Wheat, SG=Spring Garbanzo, SC=Spring Canola. Below: Comparison of remote sensing–simple crop growth algorithms and measurements of seasonal progression of aboveground biomass (AGB) accumulation for three crops at the CFCT site.

Regional estimation of water use and yields based on remote sensing and simple crop growth algorithms

Issue: From the perspective of global food security under population increase and climate change, regional monitoring of cropping systems, water use, and crop yields are of significant interest for land management, food pricing, and trading policies. Monitoring data are difficult to obtain on a real-time or nearreal-time basis at large scales, however, since crop models, statistical models, and other similar approaches are either difficult to implement and parameterize or include sizeable uncertainty. Remote sensing data offer significant promise for regional assessment and crop yield forecasting if image processing can be enhanced by software development and linked with simple cropmodeling algorithms.

Action taken: We have adapted and evaluated METRIC for use in the dryland area of the inland Pacific Northwest. This remote sensing-based method uses an energy balance approach to estimate actual crop evapotranspiration (ETa = sum of crop water use and soil water evaporation) without having to specifically account for hydrological, soil water, and crop processes. We compared estimations of ETa with eddy covariance measurements at four REACCH study sites, across three seasons and five different crops, and with annual precipitation ranging from 247 to 680 millimeters. After METRIC evaluation, we linked simple crop-growth algorithms and topsoil water balance to 30 x 30 meter resolution estimates of ETa to calculate crop water use, seasonal biomass production, and grain yields.

Results: Remote sensing-based METRIC estimates of ETa compared well with on-the-ground measurements obtained with eddy covariance instrumentation, with standard errors ranging from 0.3 to 0.5 millimeters per day for satellite overpass days and 0.4 to 0.8 millimeters per day for other days, with the higher bias generally associated with fallow periods. The daily progression of METRIC ETa at all sites and among all crops reasonably matched eddy covariance measurements without any calibration for specific crops or sites (top).

Our evaluation found that METRIC can estimate ETa in dryland areas, where crops are often limited by water, with similar accuracy to that reported for irrigated crops. Combining METRIC ETa with simple crop-growth and topsoil water balance algorithms resulted in seasonal aboveground estimates that compared well with direct measurements at all sites, as shown (bottom) for one of the sites evaluated. These are very encouraging preliminary results that may lead to the development of reasonably accurate regional assessments of evapotranspiration and crop yields forecasting.

Stable and dynamic agroecological classes (AECs) for the REACCH region based on 2007 through 2013 cropland data layers.

Defining agroecological classes for assessing land use dynamics

Issue: Defining agroecological classes (AECs), which classify land use, cover, and changes through time, enables researchers, stakeholders, students, the public, and policy makers to acquire a more holistic understanding of agriculture and climate change. AECs are intended to be part of a prescription for land management that, given climate change, will support and enhance the use of information from climate models; socio-economic models; crop models; pest, disease, and weed vulnerabilities; and many other data sources.

Action taken: We originated the concept of Dynamic AECs, developed methodology for quantifying AECs, and produced regional maps of Dynamic AECs that show the major dryland cropping systems of the inland Pacific Northwest. The Dynamic AECs use the annual NASS Cropland Datalayer and quantify annual and long-term changes in major cropping systems, crops, and overall land use.

Results: Many REACCH investigators have used the AEC concept to frame their research and to give it agricultural context. They have documented changes in cropping systems and in specific crops on an annual basis. Regions where AECs were stable or dynamic have been identified, enabling hypothesis development to further understand land-use change.