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WISDEM
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WISDEM simulates the variation in multi-species weed populations over time in response to crop rotation, tillage system, and specific weed management tactics and the consequent crop yield loss due to weed competition. Population dynamics of individual weed species are predicted from a limited number of parameters that can be derived from literature sources and expert opinion.

Data to model the population dynamics and crop yield loss of multi-species weed populations is extremely limited as well as expensive and time-consuming to obtain. WISDEM simulates population dynamics of multi-species weed populations in response to crop rotation, tillage system, and specific weed management tactics as well as the resulting crop yield reduction from weed competition.  The model uses an innovative structure for modeling weed population dynamics that requires only a small number of parameters and these can be readily derived from literature sources and regional surveys of weed experts. The structure is based on the general theory of density dependence of plant productivity and the extensive use of rectangular hyperbolic equations for describing crop yield as a function of weed density. Only two density-independent parameters are required for each species to represent differences in seed bank mortality, seedling emergence and maximum seed production. One equation is used to model crop yield loss and density-dependent weed seed production as a function of crop and weed density, relative time of weed and crop emergence and differences among species in competitive ability. WISDEM has been parameterized for 4 crops and 15 weeds of the Great Plains. A preliminary, limited evaluation provides evidence that predictions of yield loss from single species of weeds and the short term trajectories of changes in weed populations are biologically reasonable. We think the accuracy is sufficient for the goal of modeling general trends in population density accurately enough to highlight potential weed problems and solutions when comparing alternative crop management options for a field.


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