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A case study at Rancho Largo Cattle Company (RLCC) illustrates how complexity generally makes "scientific management systems" fail. At RLCC goal-driven adaptive management based on scientific studies of specific ecological processes lead to improved economic returns. Improved returns derived from improved ecological conditions. The RLCC case study shows the importance of "kinked" graphical relationships in complex systems for producers and scientists. These V-shaped or S-shaped graphs serve as road maps for producers since at inflection points a small change of a management variable can give significant changes of production variables. The kinked variable relationships in economic and ecological systems require producers to adapt scientific data to their specific operations. Specific goals are essential to drive effective adaptive management since they focus producers on ecological processes rather than management methods. Adaptive management knowledge is not rigorous at the micro-scale. Producers rely on inductive reasoning without variable controls; hence, conclusions about causality are suspect for individual management trials. However, every management decision is a "trial" and managers are forced to make hundreds of decisions a month. Hence, producers are positioned to find the kinks in variable relationships. Macro-scale management knowledge, where multiple producers over multiple years find consistent results is invaluable in understanding complex systems.