Determining sub-continental patterns of biotic resistance: A North American forest case study
The biotic resistance hypothesis predicts that communities having fewer open niches are more resistant to invasions. Support for this hypothesis, however, seems contingent on both the scale and the ecological context in which it is tested, as well as on how niche usage and invasion are quantified. The aim of this investigation was to determine (1) if the direction of associations between metrics of invasion and biotic resistance (i.e. niche usage) are scale and/or location dependent; (2) the extent to which the importance of different biotic resistance metrics vary with scale and location; and (3) the extent to which these associations change for different invasion metrics. We compiled data on native tree biomass and diversity (taxonomic and evolutionary), and on the absence/presence, species richness, and cover of invasive plants from approximately 46,000 plots of a national-level forest monitoring program located throughout the eastern USA. With large datasets, even extremely small, biologically meaningless relationships can be deemed statistically significant. Therefore, we employed an alternative statistical approach. For each invasion measure, we constructed a separate statistical model for the entire study region. These models treated the 91 ecological sections found nested within the study region as random effects having independent slope estimates.
Plotting the distributions of random slope estimates revealed invasion metrics to be negatively associated to both native tree biomass and metrics of evolutionary diversity in 88% to 100% of the 91 nested ecological sections. Mapping slope estimates further revealed the strongest associations to be aggregated within, or near, the Appalachian Mountains; although spatial variability among metrics occurred. In contrast, invasion metrics were positively related to native tree species richness in 93 to 98% of the nested ecological sections. The strongest of these associations were somewhat scattered throughout our study region. The negative relationships that did occur, although weak, were aggregated in the south central part of our study region. Additionally, with regards to the metrics of biotic resistance most strongly associated with invasion metrics, our analysis revealed the following ranking: evolutionary diversity > biomass > species richness, and that associations with both invader absence/presence and cover were stronger than those with invasive species richness. These results suggest that, at larger scales, biomass and evolutionary diversity are both better indicators of niche usage/biotic resistance than species richness, and that the size of associations between niche usage/biotic resistance and invasion depend upon how, and where, these characteristics are measured.