Fine-scale spatial structure in a grassland community: quantifying the plant’s-eye view

Authors

  • D. W. Purves,

    Corresponding author
    1. Biology Department, University of York, Heslington, York, UK
      D.W. Purves, Department of Ecology and Evolutionary Biology, Princeton University, NJ 08544, USA (tel. 609-258-2088/609-258-3828; fax 609-258-6818; e-mail dpurves@princeton.edu).
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  • R. Law

    1. Biology Department, University of York, Heslington, York, UK
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D.W. Purves, Department of Ecology and Evolutionary Biology, Princeton University, NJ 08544, USA (tel. 609-258-2088/609-258-3828; fax 609-258-6818; e-mail dpurves@princeton.edu).

Summary

  • 1The fine-scale spatial patterns of Agrostis stolonifera, Holcus lanatus and Lolium perenne were recorded in an English lowland grassland as presence/absence maps from 400-cell quadrats at two different scales (2 × 2 cm or 8 × 8 cm cells).
  • 2Local spatial structure in these patterns was quantified using spatial covariance functions. Distance- and direction-dependent components were examined separately for both intra- and interspecific patterns. The significance of departures from randomness was determined using Monte Carlo techniques.
  • 3The smaller-scale data showed that all three species were significantly aggregated, Agrostis to a greater distance (8 cm) than Holcus or Lolium(4 cm). The intensity of aggregation decreased in the order Lolium > Holcus > Agrostis. The larger-scale data suggested that this aggregation extended to greater distances, and that it was most intense in Agrostis.
  • 4Despite the lack of visual directionality in the environment, Agrostis showed a directional pattern at both scales, with Lolium varying in the same direction at the larger scale.
  • 5Only Agrostis and Lolium showed a significant interspecific relationship (segregated to 2 cm at the small scale, but aggregated to 8 cm at the larger scale). There was no evidence of directionality in the interspecific components of pattern.
  • 6The nature of spatial structure appears to depend on the scale of observation, but the smaller-scale data are more likely to provide a biologically interpretable measure of local spatial structure in this community.

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