Handbook of Spatial Point Pattern Analysis in Ecology
Understand how to analyze and interpret information in ecological point patterns
Although a broad array of statistical methods for analyzing spatial point patterns have been available for several decades, they haven’t been extensively applied in an ecological context. Addressing this gap, the Handbook of Spatial Point Pattern Analysis in Ecology shows how the techniques of point pattern analysis are useful for tackling ecological problems. Within an ecological framework, the book guides readers through a variety of methods for different data types and aids in the interpretation of the results obtained by point pattern analysis.
Access here a pdf with additions to the book and errata
Ideal for empirical ecologists who want to avoid advanced theoretical literature, the book covers statistical techniques for analyzing and interpreting the information contained in ecological patterns. It presents methods used to extract information hidden in spatial point pattern data that may point to the underlying processes. The authors focus on point processes and null models that have proven their immediate utility for broad ecological applications, such as cluster processes.
Along with the techniques, the handbook provides a comprehensive selection of real-world examples. Most of the examples are analyzed using Programita, a continuously updated software package based on the authors’ many years of teaching and collaborative research in ecological point pattern analysis. Programita is tailored to meet the needs of real-world applications in ecology. The software and a manual are available online.
- Focuses on the application of spatial point pattern analysis in an ecological context
- Helps ecologists unfamiliar with advanced statistics select the proper analysis method
- Emphasizes the formulation of appropriate null models and point processes for describing the features of point patterns and testing ecological hypotheses of spatial dependence
- Provides the Programita software package on the first author’s website, enabling readers to perform analyses with their own point pattern data
- Includes a collection of real-world examples
- Offers suggestions on how to use the book for teaching graduate students