A unifying framework for biological invasions: the state factor model

Abstract

Biological invasions are a fixture in our landscapes, with consequent losses in endemic biota and shifts in ecosystem function. Despite the historical recognition of exotic species success in novel environs, this phenomenon lacks a holistic-descriptive framework. Recent attempts to explain biological invasions are based largely on identifying the inherent invasive qualities of successful exotic species (i.e., invasiveness), or characterizing the susceptibility of a habitat to an introduced species (i.e., invasibility), with few studies examining their interaction or additional contributing factors (e.g., time since introduction). We propose unifying the ’points of entry’ into biological invasions with a state factor model that incorporates all contributing variables—not just species or habitats—into a quantifiable, factorial model amenable to hypothesis testing. State factors are phenomenological variables describing the state of a system—historically used in soil and vegetation science. Our state factor equation relates any quantifiable property of an invasion (i) as a function of propagule pressure (p), introduced habitat (h), invader autecology (a), source environment (s), and time since introduction (t). By manipulating state factors singly, or in interaction, targeted variation can be related to quantifiable properties of exotic species while controlling, or at minimum accounting for, remaining factors contributing variation to the system. This holistic factor-function paradigm extends research on invasions from beyond the limits imposed by current theory, fosters novel empirical approaches, elucidates knowledge gaps in our understanding of resident invasions, and allows for variable accounting via a factor matrix. Here we briefly outline the ontogeny of state factors in soil and vegetation science, detail our proposed ’phast’ framework for biological invasions, including notation, and examine a case study in state factor utility.