Increased density and spatial uniformity increase weed suppression by spring wheat

It has been hypothesized that increased crop density and spatial uniformity can increase weed suppression and thereby play a role in weed management. Field experiments were performed over 2 years to investigate the effects of the density and spatial arrangement of spring wheat (Triticum aestivum) on weed biomass and wheat yield in weed-infested fields. We used three crop spatial patterns (normal rows, random and uniform) and three densities (204, 449 and 721 seeds m⁻²), plus a fourth density (1000 seeds m⁻²) in the random pattern. Increased crop density reduced weed biomass in all three patterns. Weed biomass was lower and crop biomass higher in wheat sown in the random and uniform patterns than in normal rows in both years. At 449 seeds m⁻², weed biomass was 38% lower in the uniform and 27% lower in the random pattern than in rows. There was evidence of decreasing grain yield due to intraspecific competition only at 1000 seeds m⁻². The results not only confirm that increasing density and increasing crop spatial uniformity increase the suppression of weeds, but also suggest that a very high degree of spatial uniformity may not be necessary to achieve a major increase in weed suppression by cereal crops. Rows represent a very high degree of spatial aggregation. Decreasing this aggregation increased weed suppression almost as much as sowing the crop in a highly uniform spatial pattern. While the random pattern produced as much crop biomass and suppressed weeds almost as well as the uniform pattern, the uniform pattern gave the highest yield.     

Chaos, strange attractors, and fractal basin boundaries in nonlinear dynamics

Recently research has shown that many simple nonlinear deterministic systems can behave in an apparently unpredictable and chaotic manner. This realization has broad implications for many fields of science. Basic developments in the field of chaotic dynamics of dissipative systems are reviewed in this article. Topics covered include strange attractors, how chaos comes about with variation of a system parameter, universality, fractal basin boundaries and their effect on predictability, and applications to physical systems.