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.