With fully saturated dose response curves (DRCs), meaningful D0 values were assumed for De estimation.
These values were assumed to remain constant throughout the period of the modeled analysis.
Previously, extreme end-member states were chosen, and intermediary values were assumed to vary linearly.
The porosity and permeability values were assumed to be unchanged by mineral dissolution or precipitation reactions.
Large Q values were assumed to correspond to higher rock integrity and strength.
Applying this model-averaged function to each pixel in the study area revealed habitat suitability for bobcats across the entire study area, with suitability scores ranging between −1.69 and 1.44, where higher values were assumed to represent higher quality habitat.
Missing values were assumed to result from areas falling below limits of detection.
For each of five parameters, three values were assumed as described in the legend of Fig. 6.
The mean and standard deviation obtained from the monte-carlo sensitivity analysis was used to estimate the underlying OSSC distribution (N = 500 points) where the OSSC values were assumed to be normally distributed.
PROC MODECLUS uses kernel density estimation to generate an idealized, multidimensional density landscape (technically, the smoothed hyperdimensional probability density function) from which coordinate values were assumed to have been sampled.
In line with previously published studies (e.g. 2), Tr values were assumed to be equal to values for Ta, and velocity (v) was set at walking speed, 1.2 m/s.
