Individual‐centered analysis of mapped point patterns representing multi‐species assemblages

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Abstract
On the basis of Ripley's combined count‐distance method, Juhász‐Nagy's information theoretical functions and the proposition of Williams et al. for the study of small‐scale community pattern, a new procedure is suggested for elucidating multi‐species point patterns based on digitized field data. The method utilizes nested circular plots with increasing radii drawn around each individual and determines changes in floristic composition along this space series. The information provided by detecting the species composition around the sample plant is calculated, and its observed mean for all individuals is compared, for each radius, to the expectation under the null model, i.e. for complete spatial randomness of all points. The departure from randomness is illustrated by conventional profile diagrams and is tested for significance based on confidence envelopes simulated by Monte Carlo methods. One advantage of the individual‐centered sampling strategy is that the role of each species in influencing its own neighbourhood can be analyzed separately, providing information for the assessment of guild structure and assembly rules in communities. The performance of the method is evaluated using artificial and simulated point patterns.

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