SREL Reprint #2316

 

 

 

WHEN DOES THE SPATIAL PATTERN OF WEEDS MATTER?  PREDICTIONS FROM NEIGHBORHOOD MODELS

KAREN A. GARRETT1,2 AND PHILIP M. DIXON2

1Department of Botany and Plant Pathology, Oregon State University, Corvallis, Oregon 97331-2902 USA
2Savannah River Ecology Laboratory , University of Georgia, Aiken, South Carolina 29802 USA

Abstract. Good management models for postemergence weed control require good estimates of which weed density produces an economic threshold yield. Because intraweed competition increases if weeds are aggregated, weed spatial pattern may be an important factor for inclusion in management models. Mathematical models of weed-crop competition have demonstrated that this may be the case, but the small number of field studies examining the effect of weed spatial pattern have given variable results. These studies have used sampling units at arbitrary spatial scales for determining the level of aggregation in weed counts. We suggest that the neighborhood size for weed-crop competition is a natural scale for considering spatial pattern. We modeled crop yield resulting from weed competition as a function of the economic threshold, the level of competition within the neighborhood, neighborhood size, and the type and scale of weed pattern. From the model results, we predicted which weed traits would produce large shifts in threshold weed density as weed spatial pattern varies. For these weed species, consideration of spatial pattern in weed management models is predicted to be important. The systems most sensitive to weed spatial pattern are those with low economic thresholds, less competitive weeds, smaller neighborhoods, and aggregation at the scale of the neighborhood.

Key words: aggregation; area of influence; competition; economic thresholds; interference; neighborhood models; spatial pattern; spatial scale; weed-crop interaction.

SREL Reprint #2316

Garrett, K.A. and P.M. Dixon. 1998. When does the spatial pattern of weeds matter? Predictions from neighborhood models. Ecological Applications 8:1250-1259.

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