A framework to categorize forest structure concepts

Forest structure affects ecosystem composition, dynamics, and function. The complexity of forest structure demands that researchers study only particular components of it, such as leaves, branches, or the medium of air that exists in between whole trees. Deciding which components to measure and how to analyze and portray them are determined by how a researcher's perception of the forest is colored by his or her particular questions of interest and by the measurement tools available. We have developed a conceptual framework to categorize how ecologists apparently perceive forest structure when they design and carry out their studies, with the objective of developing a better understanding of forest structure itself. The framework consists of a hierarchical categorization scheme that encompasses as many configurations of forest structural components used by researchers as possible. We first identified forest structural components examined by researchers and separated these into three major representations: groups of components, networks of components, and continuous components. Second, we applied three descriptors to each representation: dimensionality (four types), spatial referencing (three types), and reactiveness (two types). This created 72 potential categories (12 of which were impossible, leaving 60 possible categories). Third, we populated our framework by assigning forest structural components from each of 500 forest structure studies to these categories. Certain categories were much more heavily used than others; only 9 of the 60 possible categories were not populated by any studies. Potential applications of this framework include helping to combine data across categories; exploring associated functional attributes of each category to discern patterns in structure/function relationships; and prioritizing the development of ecoinformatics tools for the most commonly used categories or category combinations. This framework constitutes a new method for conceptualizing perceptions of forest structure and could also be applied to synthesis work, integrating forest structure data with data from other fields, or as a conceptual model for other fields where the structure of constituent components is complex.