In the previous chapters, we have dealt primarily with organisms that have a discrete microhabitat that serves as a natural choice of sampling unit. Data may consist of the number of insects on a plant, the number of eggs in a nest, or the number of leaves on a plant. In other cases, the organisms were distributed in a continuum and a contrived sampling unit was employed. Examples include the numbers of plants in a quadrat in a prairie grass region, the number of birds in a transect, or the number of fish in a seine. These methods often work in a continuum if we are interested in estimating the population density of the organisms. However, sometimes the focus of attention is the pattern of the organisms within the continuum. Locations of nests in a breeding colony, of trees in a forest, and of weeds in a prairie are examples of biological patterns. A data set of this type is called a spatial point pattern, and the locations are referred to as events. Spatial patterns may exhibit complete spatial randomness (csr), aggregation, or regularity.
KeywordsSpatial Pattern Study Region Statistical Ecology Point Pattern Monte Carlo Test
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