Defining the habitat niche of Alopecurus myosuroides at the field scale

Abstract

SummaryThe distribution of Alopecurus myosuroides (black‐grass) in fields is patchy. The locations of these patches can be influenced by the environment. This presents an opportunity for precision management through patch spraying. We surveyed five fields on various types of soil using a nested sampling design and recorded both A. myosuroides seedlings in autumn and seed heads in summer. We also measured soil properties at those sampling locations. We found that the patches of seed heads within a field were smaller than the seedling patches, suggesting that techniques for patch spraying based on maps of heads in the previous season could be inherently risky. We also found that the location of A. myosuroides patches within fields can be predicted through their relationship with environmental properties and that these relations are consistent across fields on different soil types. This improved understanding of the relations between soil properties and A. myosuroides seedlings could allow farmers to use pre‐existing or suitably supplemented soil maps already in use for the precision application of fertilisers as a starting point in the creation of herbicide application maps.

Spatial Modelling of Within-Field Weed Populations; a Review

“…Similarly, ecological factors may interact in spatially explicit ways, for example, predators affect weed distribution and density, just as weed distribution and density also influences predator population density [88]. In addition, environmental and ecological drivers of spatial heterogeneity may interact, as not only are weeds affected by soil characteristics [89], but they can themselves, in turn, affect the quality of the soil [90][91][92]. Persistent weedy patches will influence both future weed invasions, and crop yields.…”

Spatial and Temporal Distribution of Ecballium elaterium in Almond Orchards

“…The observed patchy pattern is the result of heterogeneous environmental conditions (e.g., soil spatial heterogeneity, microclimatic conditions) [8,9], or of processes such as the dispersal rate and distance from the parent plant [10], competition between species or facilitation processes in which species mitigate the environmental condition and thus benefit other species (e.g., nurse plants [11]), or a combination of these factors [12,13]. Patchiness in weed distributions might also reflect differences in local management actions (e.g., seed dispersal and movement by farm equipment [14] and direction of tillage and irrigation furrows [15]).…”

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

“…However, the decreasing number of chemical products available for use, and increasing economic and environmental pressures to reduce herbicide use puts a growing emphasis on the optimisation of current techniques and finding alternative approaches (Grundy, 2003). The within-field distribution of A. myosuroides is patchy (Wilson and Brain, 1991, Krohmann et al, 2006, Metcalfe et al, 2016, Metcalfe et al, 2018b) and as such this presents an opportunity for site-specific management.…”

“…It has been shown that the patchy distribution of A. myosuroides in fields can be related to variation in soil properties (Holm et al, 1997, Lutman et al, 2002, Murdoch et al, 2014, Metcalfe et al, 2016, Metcalfe et al, 2018b), particularly soil organic matter, pH, and water. Metcalfe et al (2018b) demonstrated that these relationships are strongest at coarse scales (>20 m), making them ideal for the implementation of precision management. This provides a basis upon which to identify weed vulnerable zones within fields for this species.…”

“…It also introduces stochasticity into the system providing a more realistic range of possible outcomes than could a deterministic model. By modifying the life-cycle of the plant according to known responses to variation in soil properties (including texture, organic matter, water and pH) we tested the hypothesis that scale-dependent relationships between soil properties (including soil organic matter, water content and pH) and the density of A. myosuroides observed in fields by Metcalfe et al (2018b) can be modelled. Our model strikes a balance between tractability and complexity—processes are only modelled mechanistically to capture the effect of different soil properties.…”