Uncertainty about ecological variables can affect risk designations for species at risk of extinction. This study evaluated the effect of quantitatively characterizing ecological uncertainty on species at risk decision-making, using the Committee on the Status of Endangered Wildlife in Canada (COSEWIC) as a case study. Fifty senior authors of COSEWIC assessments of vertebrate species were invited to use a confidential web-based survey to quantitatively characterize uncertainty in their expert opinions for 17 COSEWIC ecological variables. Probability distributions for the 17 variables provided by each of 16/50 (32.0%) respondents were used with Monte Carlo sampling to generate sets of point estimates used as input for a computer algorithm that emulated COSEWIC decision-making for risk designation. The effect of uncertainty on risk designation was measured as a Monte Carlo-generated probability for the same risk designation as that determined by the mean point estimates only. Analysis of uncertainty revealed plausible alternative designations for seven of the 16 species. Although the majority of these cases were affected in a relatively minor way, there were cases where the explicit characterization of uncertainty caused major differences in risk designation. From these results, it can be concluded that characterization of uncertainty can have important effects on species at risk decision-making. Responsible agencies should explicitly incorporate uncertainty in their decision-making by (1) requiring explicit characterization of uncertainty for input ecological variables and output risk designations and (2) developing rational methods to incorporate the uncertainty in decision-making.