Statistical Methods for Analyzing Species–Habitat Associations

Author:

Veech Joseph A.

Abstract

Six methods for statistically identifying and quantifying meaningful species–habitat associations are discussed. These are (1) comparison among group means (e.g. ANOVA), (2) multiple linear regression, (3) multiple logistic regression, (4) classification and regression trees, (5) multivariate techniques (principal components analysis and discriminant function analysis), and (6) occupancy modeling. Each method is described in statistical detail and associated terminology is explained. The example of habitat associations of a hypothetical beetle species (from Chapter 8) is used to further explain some of the methods. Assumption, strengths, and weaknesses of each method are discussed. Related statistical constructs and procedures such as the variance–covariance matrix, negative binomial distribution, generalized linear modeling, maximum likelihood estimation, and Bayes’ theorem are also explained. Some historical context is provided for some of the methods.

Publisher

Oxford University Press

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