A - Papers appearing in refereed journals
Bohan, D. A., Powers, S. J., Champion, G., Haughton, A. J., Hawes, C., Squire, G., Cussans, J. and Mertens, S. K. 2011. Modelling rotations: can crop sequences explain arable seedbank abundance? Weed Research. 51 (4), pp. 422-432.
|Authors||Bohan, D. A., Powers, S. J., Champion, G., Haughton, A. J., Hawes, C., Squire, G., Cussans, J. and Mertens, S. K.|
We investigated the effects of crop sequences on monocotyledon, dicotyledon and total weed seedbank abundance. Using seedbank data sampled from the conventionally cropped part of the GB farm-scale evaluations of genetically modified, herbicide-tolerant (GMHT) crops, we asked whether it is possible to identify crop sequence effects, to identify their duration and to simplify crop sequences into crop management classes with similar effects on weed seedbanks. This work showed that it is possible to detect historical effects of past crops, sown in sequence, on weed seedbanks for up to 3 years and that crop sequences may be simplified to crop management classes describing the season of sowing, crop type and weed target for herbicide application. Model estimates for the seedbanks were validated against an independent, follow-up seedbank data set. The analysis provided abundance estimates that ranged over 3 and 1.7 orders of magnitude for the monocotyledon and dicotyledon weed seedbanks for different crop sequences. This work yields a methodology for estimating seedbank abundance in current crop sequences, potentially allowing sequences to be identified that better reconcile the competing needs for weed control to maintain crop productivity and the demand for increased farmland biodiversity.
|Keywords||Agronomy; Plant Sciences|
|Year of Publication||2011|
|Journal citation||51 (4), pp. 422-432|
|Digital Object Identifier (DOI)||doi:10.1111/j.1365-3180.2011.00860.x|
|Open access||Published as non-open access|
|Funder||Biotechnology and Biological Sciences Research Council|
|Funder project or code||Centre for Sustainable Pest and Disease Management (PDM)|
|Centre for Mathematical and Computational Biology (MCB)|
|Application of statistical methods to predictive biology|
Permalink - https://repository.rothamsted.ac.uk/item/8q92z/modelling-rotations-can-crop-sequences-explain-arable-seedbank-abundance