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Modelling the effect of spatially variable soil properties on the distribution of weeds

Author:
Metcalfe, H., Milne, A.E., Coleman, K., Murdoch, A.J., Storkey, J.
Source:
Ecological modelling 2019 v.396 pp. 1-11
ISSN:
0304-3800
Subject:
Alopecurus myosuroides, commercial farms, grain crops, mechanistic models, model validation, precision agriculture, prediction, risk perception, soil properties, soil quality, spraying, weed control, weeds, United Kingdom
Abstract:
The patch spraying of weeds is an area of precision agriculture that has had limited uptake. This is in part due to the perceived risks associated with not controlling individual weeds. Nevertheless, the inherent patchiness of weeds makes them ideal targets for site-specific management. We propose using a mechanistic model to identify areas of a field vulnerable to invasion by weeds, allowing the creation of treatment maps that are risk averse. We developed a spatially-explicit mechanistic model of the life-cycle of Alopecurus myosuroides, a particularly problematic weed of cereal crops in the UK. In the model, soil conditions which vary across the field, affect the life-cycle of A. myosuroides. The model was validated using data on the within-field distribution of A. myosuroides on commercial farms and its co-location with soil properties. We demonstrate the important role played by soil properties in determining the within-field distribution of A. myosuroides. We also show that scale-dependent correlations between A. myosuroides and soil properties observed in the field are an emergent property of the modelled dynamics of the A. myosuroides life-cycle. Our model could therefore support effective site-specific management of A. myosuroides within fields by predicting areas that are vulnerable to A. myosuroides. The usefulness of this model in its ability to predict patch locations for A. myosuroides highlights the possibility of using similar models for other species where data are available on the response of the species to various soil properties.
Agid:
6236399