Pyrodiversity Calculation
We calculate pyrodiversity using a measure of functional dispersion
(FDis) defined by Laliberté and Legendre (2010), and applied via the
“FD” R package (Laliberté et al. 2014). FDis is similar to
Rao’s quadratic entropy and is analogous to the univariate weighted mean
absolute deviation. It is independent of species richness (Laliberté &
Legendre 2010), which is preferable when the boundaries between species
are unclear and the number of species varies among communities. FDis
measures the mean multidimensional distance of unique species from the
centroid of a community, weighted by abundance (Fig. 1a). In the case of
pyrodiversity, unique combinations of fire regime traits (fire
histories) are considered individual species, a landscape is considered
the community of interest, and the abundance is calculated as the
frequency (number of pixels) of each unique history. A functional
diversity approach is an improvement on more traditional measures of
diversity (e.g. richness and Simpson’s diversity) because it
incorporates information about distance of individuals in
multidimensional trait-space rather than assuming each unique
combination of fire histories are equally and fully distinct. For
example, when using Simpson’s diversity index, two points burned by the
same fires but with slightly different severity would be considered
unique, as well as equally different from a pixel with no recent fire
history despite the two burned pixels supporting relatively similar
habitat. Functional richness, as measured by the volume of the minimum
convex hull, can also be a useful metric of pyrodiversity (Hempsonet al. 2018), but is sensitive to outliers and thus not a
reliable estimator of dispersion (Laliberté & Legendre 2010). Finally,
FDis allows for differential weighting of traits, which allows explicit
testing of the relative importance of different components of
pyrodiversity.