Spatial Point Pattern Analysis
Methods for spatial
point pattern analysis have undergone a rapid development and are
now being widely used, especially in plant ecology. Of special interest
is to determine whether the pattern (e.g. distribution of plants in
space) is random, clumped (aggregated) or regular (dispersed). Significance
is usually evaluated by comparing the observed pattern with Monte
Carlo envelopes from multiple simulations of a null model. Although
point-pattern analysis has become a standard technique in ecology,
its practical application is often limited by methodological or computational
problems. Using a grid- and simulation-based approach we extended
point pattern analysis to deal with plants of finite size and irregular
shape, and compared the results of our approach to that of the conventional
point approximation. We found that the point approximation may produce
misleading results (i) if plant size varies greatly, (ii) if the scale
of interest is of the same order of magnitude as the size of the plants,
and (iii) if the plants of a given pattern are constrained through
competition for space by the presence of other plants. Our approach
to quantifying small-scale spatial patterns in plant communities has
broad applications, including the study of facilitation and competition.
Keywords:
Community structure, facilitation, neighbourhood effects, null models,
second-order spatial statistics.
Publication:
- Wiegand, T.,
Kissling, W.D., Cipriotti, P.A. & Aguiar, M.R. (2006):
Extending point pattern analysis to objects of finite size and irregular
shape. Journal of Ecology 94: 825–837. [Abstract]
Figure
- Six important effects introduced (or obscured) by conventional point
pattern analysis. Each effect may obscure the real spatial dependence
between objects of finite size and irregular shape. A: Hard
core effect causing regularity at scales smaller than the hard core
distance dH. B: Soft core effect causing regularity at smaller
scales. C: Aggregation effect causing aggregation at small
and intermediate scales. D: Weighting effect causing regularity
or aggregation. E: Real shape effect (dark grey, species 1;
light grey, species 2). F: Space restrictions causing virtual
aggregation (light grey, species 1, black, mask).
