Anthropogenic forcing on the spatial dynamics of an agricultural weed: the case of the common sunflower

R. Humston, D.A. Mortensen and O.N. Bjørnstad: Anthropogenic forcing on the spatial dynamics of an agricultural weed: the case of the common sunflower.

Journal of Applied Ecology (2005) 42: 863-872.


1. Establishment and spread are central in pest weed invasion. In this study we quantify the impact of harvest and weed management practices on these processes in row-crop agriculture. Quantifying the dynamics of patch expansion can direct management aimed at containment of pest weed populations. 2. We assessed annual patterns of common sunflower (Helianthus annuus L.) seedling recruitment to determine the influence of management on seed dispersal and patch expansion. Weed seed banks were sowed at three initial densities and exposed to either high or low intensity weed management. Fields were maintained in a maize-soybean crop rotation, with cultivation and harvest oriented in a single direction. We analyzed spatial pattern in annual seedling recruitment using geostatistics and an integro-difference model to determine treatment effects on spatial dynamics. 3. The two spatial analyses allowed us to separate and quantify the contributions of natural and anthropogenic dispersal to seedling emergence and patch expansion. Expansion was predominantly isotropic, and estimated rates of isotropic spread (i.e., diffusion) were consistent between analysis methods. 4. We also confirm that directional management practices can effect significant anisotropy in dispersal and expansion. Crop rotation had the most significant impact on expansion; anisotropy in patch expansion was more pronounced in maize compared with soybean. However, the scale of weed seed dispersal by combine was greater following harvest of soybean. Simulation of patch dynamics indicates that harvest can increase expansion rate nearly 4-fold. 5. Synthesis and applications. We conclude that a combined approach of spatial modeling and geostatistics is particularly effective for quantifying admixed modes of dispersal from sequential data of population distribution. Independence of the two methods provides a system for cross-validating model assumptions and estimated parameters. The scales of spatial dynamics we assessed were well suited to these methods, and are most relevant in directing individual farm management strategies.

Keywords: anisotropy, cross-correlation, geostatistics, integro-difference, seed dispersal, weed management