Weather and Management Impact on Crop Yield Variability in Rotations

Crop rotation offers several advantages to improve farmers' systems worldwide. The positive attributes of rotations are usually dependent upon crop choices, cropping sequence, soil fertility management, and weather factors. Of these, weather is most uncontrollable, but its effects can be partially manipulated through management. This study presents information on how weather affected cropping systems in a 12‐yr span. The study also illustrates the use of indices of weather (composite) variables to predict yields. The composite variables are three biological windows (BW) and a standardized precipitation index (SPI). Biological windows based on soil temperature and soil moisture indicate the number of days favorable for or detrimental to crop growth. Biological window 2 (temperature > 41°F+moist soil) in combination with May temperature explained more than 80% of the variability in corn ( Zeu mays ) and soybean ( Glycine max ) yields. August temperature negatively affected corn and soybean yields, especially in continuous monocrops. Preseason 9‐mo SPI (September–May) explained up to 50% of the subsequent season's corn yields, and this information could influence crop choice. Overall, yields in rotations were higher than in continuous monocropping systems. Nitrogen fertilization increased cereal yields more in continuous monocropping than in rotations with legumes. Corn and soybean appeared more sensitive to soil moisture and temperature variability ( P < 0.0001) than sorghum ( Sorghum bicolor [L] Moench) ( P > 0.05). Risk as measured by standard deviation in yields or incomes did not differ significantly among systems. Research Question Crop rotations are designed to increase productivity and reduce costs. These advantages are contingent upon favorable weather and require appropriate management. Unpredictable weather poses risks to dryland crop production. Information on how weather affects yields in different cropping systems and how farmers could respond with management would help minimize risk and stabilize yield and income. We evaluated the effects of preseason and growing season weather variability on continuous and sequential cropping of corn, sorghum, and soybean in a 12‐yr span, and suggest how management decisions could influence cropping system performance. Literature Summary Models of different levels of sophistication have been developed to link yields of individual crops with weather factors. But there is a paucity of information on how weather and management affect yields in whole cropping systems. Furthermore, many models demand a large amount of input data, which is a major limitation to routine application by potential users. This study developed simple empirical models to relate yield and management with a combined index of composite weather variables in whole cropping systems. Study Description The study was conducted from 1984 to 1995 at the Agricultural Research and Development Center near Mead, NE. Correlation and regression analyses were used to relate system performance to weather. Yield was the dependent variable and several combined indices of weather factors were predictor variables. The combined indices of weather or composite weather variables were biological windows (BW) and standardized precipitation index (SPI). Biological windows represent the time during the entire year during which rainfall and air temperature favor biological activities. The biological windows are derived from the mean monthly precipitation and temperature data. The SPI is the difference of precipitation from the long‐term average (>30 yr) divided by the standard deviation, a measure used to determine how wet or dry a period of time is compared with average weather patterns, up to a certain date. Both BW and SPI are calculated with simple computer programs. Standard deviation was used as a measure of yield/income variability. Weather effects on yield and income fluctuations of the cropping systems are discussed, along with potentials for the farmer to influence this variability through management. Applied Questions Which weather factors greatly influence year‐to‐year variability of crop yields? Are certain crops and cropping systems more resilient to these variable climatic conditions? Temperature and soil moisture are the two most critical factors for crop yields. Three BW are defined that influence crop growth and development. Biological window 1 is the number of days in the entire year when the soil moisture is dry and temperature > 41°F. Biological window 2 is the number of days the soil is moist (between permanent wilting point and field capacity) and temperature > 41°F, and BW 3 represents number of days that soil is moist with a temperature > 47°F. These three BW correlated strongly and consistently with yields of corn and soybean but not with grain sorghum yields. Yields decreased as number of dry days increased, while elevated temperature during August also reduced yields. Corn in the 4‐yr rotation of oat/clover‐sorghum‐soybean‐corn, and soybean in both 4‐yr rotations, were least affected by high August temperature. Corn in the 4‐yr rotation of soybean‐sorghum‐oat/clover‐corn and continuous soybean benefitted more than other systems from increased days in BW2. In general, yields of corn and soybean were reduced by drought (BW1) and increased in years with favorable rainfall and temperatures (BW2, BW3). Preseason temperature in April correlated positively with sorghum yield. Also, SPI for the 7 to 9 mo preceding planting influenced yield of the following season's corn crop, especially in the rotational systems. In general, yields of all crops in rotations were consistently higher than in continuous cropping systems, especially at lower N rates. Risk as measured by income variation generally was higher for corn, similar for soybean, and lower for sorghum in rotations compared to continuous cropping. Management decisions based on BW include the type of system (continuous vs. rotations) best suited to a given location and the most profitable levels of N fertilizer based on long‐term experience. Specific precipitation index for the months before planting could be used to decide the appropriate N rate, or more importantly whether to break the rotation cycle and plant corn if the rainfall is highly favorable or grain sorghum if there is low rainfall and below average stored soil moisture. Although these weather variables are useful as management guides, the farmer must also consider relative crop prices, machinery requirements, needs on the farm for specific commodities, and other factors in deciding which crop, systems, and N rates will be most profitable in a given year, as well as contribute to long‐term stability.