Exploratory analysis of multivariate data: Applications of parallel coordinates in ecology

Abstract

Exploratory analysis of biological communities and their environmental factors requires specialized tools to identify associations among variables and generate hypotheses about their causal relationships. Despite the ubiquity of multivariate data in ecology, the visualization and interpretation of such data can be challenging. This study introduces the application of parallel coordinates to ecologists, illustrating the utility of this tool to visualize and explore different types of multivariate data. We demonstrate this tool with two case studies in Canada to (i) explore water-quality associations with benthic macroinvertebrate indicators of stream condition in the St. Lawrence drainage basin, and (ii) identify environmental conditions that contribute to invasive zebra mussel (Dreissena polymorpha) proliferation across inland lakes of Ontario. We offer a novel demonstration of how parallel coordinates provide a practical alternative to current tools in the ecologist's toolbox for visualizing and exploring multivariate data, identifying hypotheses about causal relationships, and communicating science via interactive, web-based applications.