Agriculture Reference
In-Depth Information
grasshopper populations in Saskatchewan, a cotton pest in Australia, and regional
drought in the NCR (Gage and Mukerji 1977, Hamilton and Gage 1986, Gage
2003). The CSI is relatively easy to compute at any scale—from local to global—
since it requires only daily maximum and minimum temperature and precipitation
data, which are generally available.
Patterns of Heat, Moisture, and Crop Stress
Coupling NCR databases of temperature, precipitation, and crop yield offers a pow-
erful means for examining the relationship between yield and climate. The analyses
that follow cover a 30-year period (1971-2001) for 1053 of the 1055 counties in
the NCR where data were available, and incorporate more than 11 million daily
climate records and over 35,000 rain-fed crop yield records. Figure 4.6 represents
the structural organization of datasets used to compute the Crop Stress Index (CSI)
from monthly records. The annual crop dataset shown in the lower panel of Fig.
4.6 illustrates the extraction of the rain-fed component of the crop database. The
resulting database used in the analysis is the integration of the monthly climate and
rain-fed crop datasets.
May through July degree-day accumulation, shown as means over the 30-year
period, ranged from 334 in the northern NCR to 1258 degree-days in the south,
a 3.8-fold difference (Fig. 4.7A). Precipitation (May through July) ranged from
177 mm in the western NCR to a high of 383 mm in the south central NCR, a
2.2-fold difference (Fig. 4.7B). Of interest is that the patterns of heat and precipita-
tion are not consistent across the region. Accumulated degree-days increase from
north to south, while precipitation tends to increase toward the central portion of
the NCR, with highest accumulation in Iowa and lowest accumulation in western
states. The CSI integrates these two patterns, and likewise varies across the region,
as illustrated in Fig. 4.8. Monthly growing season patterns in the CSI (Fig. 4.8)
show that sustained stress is concentrated in the southwestern part of the region in
May, June, and July, but that May stress is also high in the northwest (Fig. 4.8A).
In June, crop stress is high in the south central NCR (Fig. 4.8B), whereas in July it
shifts primarily to the western NCR (Fig. 4.8C). The 3-month sum of average CSIs
for each county shows that the western and southern parts of the NCR have the
highest probability of crop stress (Fig. 4.8D), which is why most of the corn and
soybean fields in these areas are irrigated.
A monthly distribution of the CSI illustrates the dynamics of stress over the
30-year period (Fig. 4.9). Although climate may affect crop growth and yield
throughout the entire growing season, plants are most susceptible to stress, as
measured by yield loss, during the critical months of May-July in the NCR (Fig.
4.9). The potential for crop stress differs over this period and tends to be greatest
in July, followed by June and May The most intense crop stress occurs in late
July when grain has already set and growth is beginning to slow; however, stress
early in growing season can reduce crop yield quickly because young plants are
more susceptible to moisture deficiency as they have not fully tapped into the
belowground moisture. This was the case during the 1988 drought in the Corn
Belt region (Gage 2003).
