A new index and four new graphical displays, termed “red–blue” plots, are presented to study and measure clustering in spatially referenced count data. The index can detect clusters in the form of patches, comprising several nearby large counts, and in the form of gaps, comprising several nearby small counts. The new methods quantify the degree to which the count for each sample unit contributes towards the overall degree of clustering, either as part of a patch or as a gap; provide tests of nonrandomness to detect clustering; and facilitate a comprehensive definition of the size and dimension of a cluster. The methods are illustrated using aphid field data.

The spatio‐temporal dynamics of two aphid species (Metopolophium dirhodum and Sitobion avenae) and a generalist predator (Pterostichus melanarius) were observed in a field‐scale study using a grid of 256 sampling locations with a 12‐m spacing. Using Spatial Analysis by Distance Indices we demonstrate that populations show ephemeral spatial pattern at the field scale. We observed a positive, lagged beetle response to this aphid pattern; conversely, the aphids displayed a negative, lagged response to beetle spatial pattern. Examination of the local structure of the spatio‐temporal dynamics revealed a strong response by the beetle population to aphid patches. The temporal structure of spatial associations between the species shows a strong correspondence with those from a conceptual model of predator–prey spatial interaction. The spatially coupled dynamics were sufficiently strong for the predator to have a negative effect on the intrinsic rate of increase of their prey.

The within-field spatial distribution of some common farmland arthropods from the Carabidae, Araneae and Collembola was assessed using two-dimensional grids of pitfall traps distributed across whole winter wheat fields. In the first year, the extent to which arthropod capture was influenced by location within the field and sampling intensity was examined using a nested grid design (1.5 m, 7.5 m and 30 m spacings). In the second year, distributions within two different-sized winter wheat fields were compared. Spatial pattern and association between arthropods and weed cover were analysed using SADIE and trend surfaces were used to visualize distributions. Many of these arthropod groups exhibited aggregated distributions within the fields in clusters larger than 30 m across, demonstrating that the numbers captured will vary depending on the location of sampling within a field. Amara species, Bembidion lampros Herbst, Carabidae and Lycosidae were predominantly found within 60 m of the field edge. Nebria brevicollis Fabricius and Pterostichus madidus Illiger were found within the field in patches of one and two hectares, respectively. Linyphiidae were relatively homogeneously distributed across the fields. There was some evidence of clustering by Collembola. The spermophagous Carabidae and Lycosidae were positively associated with the degree of weed cover. SADIE analytical techniques were useful for identifying the importance and location of patches with greater and less than average numbers, although a minimum of 36 sample points is recommended.

Abstract. 1. Polyphagous predator densities were manipulated in a wheat crop using polythene exclusion barriers. 2. The rates at which aphids fell to the ground and subsequently climbed and returned to the crop canopy were measured. 3. Peak aphid density was highest when polyphagous predator density was lowest. 4. Similar rates of aphid fall‐off were measured in each plot, but aphid climbing rate was highest when predator densities were lowest. 5. It was concluded that ground‐zone predators reduced the rate at which aphids return to the crop canopy.

The spatial and temporal distribution of the grain aphid Sitobion avenae F. (Homoptera: Aphididae) was studied within a field of winter wheat during the summer of 1996. Sampling was done using four nested grids comprising 133 locations. Analysis by Taylor's power law gave results typical for insect populations. Analysis by SADIE (Spatial Analysis by Distance Indices) showed spatial pattern due to edge effects and sampling scale, and positive but mild spatial association, although spatial patterns were ephemeral. Reasons for these findings and the implications for integrated crop management are discussed.