Combining a weed traits database with a population dynamics model predicts shifts in weed communities.

A functional approach to predicting shifts in weed floras in response to management or environmental change requires the combination of data on weed traits with analytical frameworks that capture the filtering effect of selection pressures on traits. A weed traits database (WTDB) was designed, populated and analysed, initially using data for 19 common European weeds, to begin to consolidate trait data in a single repository. The initial choice of traits was driven by the requirements of empirical models of weed population dynamics to identify correlations between traits and model parameters. These relationships were used to build a generic model, operating at the level of functional traits, to simulate the impact of increasing herbicide and fertiliser use on virtual weeds along gradients of seed weight and maximum height. The model generated 'fitness contours' (defined as population growth rates) within this trait space in different scenarios, onto which two sets of weed species, defined as common or declining in the UK, were mapped. The effect of increasing inputs on the weed flora was successfully simulated; 77% of common species were predicted to have stable or increasing populations under high fertiliser and herbicide use, in contrast with only 29% of the species that have declined. Future development of the WTDB will aim to increase the number of species covered, incorporate a wider range of traits and analyse intraspecific variability under contrasting management and environments.

Influence of crop management on take-all development and disease cycles on winter wheat.

ABSTRACT Wheat was assessed at four crop growth stages for take-all (Gaeumannomyces graminis var. tritici) in a series of field trials that studied the effects of five wheat management practices: sowing date, plant density, nitrogen fertilizer dose and form, and removal/burial of cereal straw. An equation expressing disease level as a function of degree days was fitted to the observed disease levels. This equation was based on take-all epidemiology and depended on two parameters reflecting the importance of the primary and secondary infection cycles, respectively. Early sowing always increased disease frequency via primary infection cycle; its influence on the secondary cycle was variable. Primary infection and earliness of disease onset were increased by high density; however, at mid-season take-all was positively correlated to the root number per plant, which was itself negatively correlated to plant density. At late stages of development, neither plant density nor root number per plant had any influence on disease. A high nitrogen dose increased both take-all on seminal roots and severity of primary infection cycle but decreased take-all on nodal roots and secondary infection cycle. Ammonium (versus ammonium nitrate) fertilizer always decreased disease levels and infection cycles, whereas straw treatment (burial versus removal of straw from the previous cereal crop) had no influence.