Bin ranges for input variables used to produce a stratified map of the region over which carbon modeling was performed (see methods).

Twenty total bands were dispersed non-randomly according to the strength of each variable in predicting carbon stocks, which has been shown to be an effective stratification method in previous studies (e.g., [17]). Thereafter, the input variables were subset by quantiles to determine bin ranges for the bands. These class combinations were subsequently intersected with a 134-class habitat map as described in the methods, resulting in 8,035 unique classes within the focal area of the present study. A hard bracket indicates values “greater than or equal to”, while a parenthesis indicates values that are “less than”.