Improving the Interpretability of the Floristic Quality Index to Assess Prairie Vegetation across Multiple Sites

Author

Martin, R Adam

Publication Year

2026

Region

Puget Trough/Lowlands

Habitat

Upland Prairie

Topic

Flora, Invasives, Monitoring, Native Plants, Restoration & Management

Full Citation

R. Adam Martin "Improving the Interpretability of the Floristic Quality Index to Assess Prairie Vegetation across Multiple Sites," Natural Areas Journal 46(3), 214-225, (22 July 2026). https://doi.org/10.3375/2162-4399-46.3.6

Evaluating vegetation management outcomes is challenging because plant community datasets can be summarized in multiple ways, and the chosen metric strongly shapes conclusions. The Floristic Quality Index (FQI), which combines mean species conservatism values (mean C_nat) with measures of species richness or nativity, provides a useful framework for monitoring management outcomes. However, averaging C-values across species reduces the metric’s sensitivity and limits its ability to detect change. Using plot data from 23 South Sound prairie sites in Washington State, I assessed the efficacy of a modified FQI equation (FQI_cmax) that used the maximum C-value (max C) instead of the mean C_nat, weighted by conservatism-weighted cover-based nativity (nativity_c-val). First, I evaluated whether species with high C-values tended to co-occur more often than expected by chance and whether max C correlated positively with the cover and richness of high-fidelity prairie taxa. Second, I evaluated the correlation between max C and mean C_nat, native richness, nativity_c-val, and three formulations of FQI. Mean C_nat was not correlated with max C, could distinguish only two community states, and was heavily influenced by species richness and the regional C-value distribution. In contrast, FQI_cmax identified seven community quality states, was independent of species richness and nativity_c-val, and was less affected by the regional C-value distribution. Lastly, FQI_cmax was better able to detect directional responses to four management interventions than the three other FQI equations. The components of FQI_cmax also revealed a trade-off among species conservatism, native richness, and native cover in relation to herbicide use. These findings suggest that a simple change to the FQI formula can significantly enhance its sensitivity and clarity when assessing management impacts.