mapMOG: Assessing Mature and old growth forest using FIA data

Although many species display relationships – both positive and negative –
with various forest successional stages, researchers often rely on
datasets that describe forest presence rather than forest age (i.e.,
National Landcover Database). In 2023, the USDA Forest Service introduced
standardized region-specific mature and old-growth (MOG) forest
definitions for the United States, but these definitions have not been
readily integrated to address questions in ecology and conservation. Here,
we introduce ‘mapMOG’—an open-access R function that applies the recently
adopted federal MOG definitions to Forest Inventory and Analysis (FIA)
plots across the contiguous United States (US). Additionally, our novel
function interpolates MOG status across US forested lands between FIA
plots. To demonstrate the utility of these data for forest landscape
ecological modeling, we compare the predictive power of the MOG covariate
against binary forest/non-forest and percent canopy cover covariates to
examine forest habitat associations across three taxa, geographies, and
modelling frameworks: avian richness in Mid-Atlantic national parks;
Seminole bat (Lasiurus seminolus) occupancy in the Southeastern Coastal
Plain; and Cascade torrent salamander (Rhyacotriton cascadae) distribution
associated with US National Forests in the Pacific Northwest. In all three
cases, our MOG covariate produced by our function explained variation in
the wildlife occurrence data better than the alternative forest metrics.
Finally, we compared imputed results across multiple spatial scales and
found notable but statistically insignificant differences in interpolated
MOG scores.