Complex dynamics and evolution of weed populations
Weeds undergo complex life-cycle dynamics involving the buried seedbank, emerged populations, reproduction, dispersal, gene flow and genetic change. Individual-based models (IBMs) of plant populations have been an integral part of the programme since the late 1990s, finding specific use by predicting coexistence of GM and non-GM traits and trait shifts due to environment and management.
The IBMs developed here have their base in flux-based studies of crop production: each individual explores the environment for a finite resource on which it grows, reproduces and disperses. The emergent properties of the resulting populations are measured in terms of mass, resource, abundance, etc. A range of other approaches are used, including machine-learning techniques for mining large datasets.
Funding: Scottish Government Strategic Research Programme Land Use Theme 2011-16, EU FP7 PURE project.
Previous funding includes: BBSRC Gene flow in Agriculture, University of Abertay; BBSRC LINK on farmland diversity; PhD studentships; EU FP6 SIGMEA project.
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