The hierarchical continuum concept

TitleThe hierarchical continuum concept
Publication TypeJournal Article
Year of Publication1993
AuthorsCollins, SL, Glenn, SM, Roberts, DW
JournalJournal of Vegetation Science
Pagination149 -156
Accession NumberKNZ00393
Keywordscommunity structure, Continuum model, Gradient analysis, Hierarchical structure

Two general models have been proposed to explain the structure of the plant community: the community-unit model of Clements and the continuum model of Whittaker and Curtis, the latter based on Gleason's individualistic distribution of species. It is generally assumed that most ecologists now accept the continuum model. Empirical evidence suggests, however, that the continuum in its current form does not fully describe the observed patterns of vegetation along environmental gradients. In this paper, we introduce the hierarchical continuum as a general concept to represent dynamic community structure along regional spatial gradients. The hierarchical continuum is derived from a combination of the individualistic distribution of species, hierarchical assemblage structure, and the core-satellite species hypothesis. The hierarchical continuum concept predicts that the distribution of species across sites in a region will be polymodal, which reflects hierarchical structure, and that the distribution and abundance of species within and between sites will be spatially and temporally dynamic. Regional distribution of plant species in North American tallgrass prairie, southeastern flood-plain hardwood forests, northern upland hardwood forests, and boreal forests were either bimodal or polymodal as predicted by the hierarchical continuum concept. Species in tallgrass prairie were spatially and temporally dynamic with an average turnover of 8–9 species per 50 m2 yr1. In addition, the hierarchical continuum concept predicts the potential for fractal (self-similar) patterns of community structure, and provides a framework for testable hypotheses concerning species distributions along environmental gradients.