CROPPING SYSTEMS Effects of Western Corn Belt Cropping Systems on Agroecosystem Functions

tices on agroecosystem functions is necessary to determine the sustainability of cropping systems. Agricultural sustainability is enhanced by management practices Performance-based indices have been used to assess that optimize the performance of multiple agroecosystem functions. the effects of management practices on agroecosystem The performance of western Corn Belt cropping systems was evalufunctions (Andrews et al., 2001; Glover et al., 2000; ated based on four agroecosystem functions: food production, raw materials production, nutrient cycling, and greenhouse gas regulation. Ericksen and McSweeney, 1999; Karlen and Stott, 1994). A simple multiattribute ranking procedure was used to quantify agroeThese indices use expert opinion or principal-compocosystem performance using data from a long-term cropping systems nent analysis to select indicators representative of speexperiment near Mead, NE. Treatments included in the procedure cific functions. Once selected, the indicators are scored were continuous corn (Zea mays L.) (CC), corn–soybean [Glycine based on their relative difference from a standard or max (L.) Merr.] (C–SB), corn–oat (Avena sativa L.) clover [80% optimum value using either linear or nonlinear techsweet clover (Melilotus officinalis L.) and 20% red clover (Trifolium niques. Scores within agroecosystem functions are typipratense L.)]–sorghum [Sorghum bicolor (L.) Moench]–soybean cally summed across functions, taking into consideration (C–OCL–SG–SB), and corn–soybean–sorghum–oat clover (C–SB– the relative importance of each function within the conSG–OCL) each at three N fertilization levels (ZERO, LOW, and text of climatic, geographical, and socioeconomic condiHIGH). Based on treatment averages of soil and crop indicators from 1983 to 1998, agroecosystem performance scores ranged from 66.6 to tions (Edwards and Newman, 1982; Stillwell et al., 1981). 77.3, with a least significant difference (LSD) between treatments of A simplified multiattribute ranking procedure using 2.2 (P 0.05). Treatments with the highest scores included C–OCL– a linear scoring technique was developed by Liebig et SG–SB/LOW (77.3), C–SB/LOW (76.9), CC/LOW (76.7), CC/HIGH al. (2001) to determine agroecosystem performance for (76.6), and C–SB–SG–OCL/LOW (75.3). Among these treatments, treatments in long-term experiments. The procedure those fertilized at the LOW N rate attained high scores through was successful in discriminating between conventional moderate performance in all four agroecosystem functions. The CC/ and alternative cropping systems when agroecosystem HIGH treatment, however, attained a high score solely through its performance was based on functions of food production, superior capacity to be highly productive, as its scores for the two raw materials production, nutrient cycling, and greenenvironmental quality–related functions were the lowest among all house gas regulation. Given the demonstrated utility of treatments. Correlations between productionand environmental prothe procedure to quantify the environmental dimension tection–related functions were negative, emphasizing the importance of agricultural sustainability, a more in-depth evaluation of employing management practices that are productive yet minimize deleterious environmental impacts. of its use is warranted. In this study, we sought to use the procedure to determine agroecosystem performance of four corn-based crop sequences (CC, C–SB, C–OCL– SG–SB, and C–SB–SG–OCL) each at three N fertilizaC systems perform multiple functions in tion levels for a long-term cropping systems experiment their role as agroecosystems. In addition to food, in the western Corn Belt. feed, and fiber production, cropping systems cycle nutrients, influence water partitioning within landscapes, and regulate greenhouse gas flux, thereby influencing enviMATERIALS AND METHODS ronmental quality as well as human and animal health Site Description (Costanza et al., 1997; Daily et al., 1997). The longData for this evaluation were used from a cropping systems term viability of cropping systems—or any agricultural experiment established in 1983 on the Agronomy Farm at the production system for that matter—is largely deterUniversity of Nebraska Agricultural Research and Developmined by how well these functions are executed within ment Center, approximately 6 km south of Mead, NE, in the context of the production, economic, and resource Saunders County (41 10 N, 96 25 W). The research site is conservation goals of agricultural producers. Conseon Peoria-age loess with nearly level topography (0–3% quently, quantifying the effects of management pracslope). The predominant soil is Sharpsburg silty clay loam (fine, smectitic, mesic Typic Argiudoll). The cropping systems study consisted of seven crop seM.A. Liebig, USDA-ARS, Northern Great Plains Res. Lab., P.O. quences (three monocultures, two 2-yr rotations, and two 4-yr Box 459, Mandan, ND 58554; and G.E. Varvel, USDA-ARS, Soil rotations) and three rates of N fertilizer (Varvel, 1994). Cornand Water Conserv. Res. Unit, 119 Keim Hall, Dep. of Agron., Univ. based cropping sequences included in the study were CC, of Nebraska, Lincoln, NE 68583-0934. The USDA-ARS is an equal opportunity/affirmative action employer, and all agency services are Abbreviations: CC, continuous corn, C–OCL–SG–SB, corn–oat available without discrimination. Received 10 Oct. 2001. *Correspondclover–sorghum–soybean; C–SB, corn–soybean; C–SB–SG–OCL, ing author (liebigm@mandan.ars.usda.gov). corn–soybean–sorghum–oat clover; HIGH, high N fertilization level; LOW, low N fertilization level; ZERO, zero N fertilization. Published in Agron. J. 95:316–322 (2003).