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Testing Spatial Segregation Using a Nearest‐Neighbor Contingency Table
Author(s) -
Dixon Philip
Publication year - 1994
Publication title -
ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.144
H-Index - 294
eISSN - 1939-9170
pISSN - 0012-9658
DOI - 10.2307/1941598
Subject(s) - contingency table , k nearest neighbors algorithm , table (database) , statistics , square (algebra) , test (biology) , null hypothesis , spatial ecology , ecology , mathematics , biology , computer science , artificial intelligence , data mining , geometry
Segregation of species occurs when a species tends to be found near conspecifics. This is frequently investigated using a contingency table, classifying each point by its species and the species of its nearest neighbor. Pielou proposed using a 1—df chisquare test of independence as a test of segregation. This test is inappropriate if all locations within a study area are mapped. For completely mapped data, I derive the expectations and variances of the cell counts in the nearest—neighbor contingency table under the null hypothesis that species labels are randomly assigned to points. The properties of the cell counts suggest a new 2—df chi—square test of spatial segregation, a pair of species—specific tests, and a pair of species—specific measures of segregation. In small samples, the proposed tests have the appropriate size, unlike the Pielou test. The new test is illustrated with three examples: Pielou's Douglas—fir/ponderosa pine data, a realization of a mother—daughter process, and the locations of male and female water tupelo trees.