forestexplorR: an R package for the exploration and analysis of stem-mapped forest stand data

Abstract

Stem-mapped forest stands offer important opportunities for investigating the fine-scale spatial processes occurring in forest ecosystems. These stands are areas of the forest where the precise locations and repeated size measurements of each tree are recorded, thereby enabling the calculation of spatially-explicit metrics of individual growth rates and of the entire tree community. The most common use of these datasets is to investigate the drivers of variation in forest processes by modeling tree growth rate or mortality as a function of these neighborhood metrics. However, neighborhood metrics could also serve as important covariates of many other spatially variable forest processes, including seedling recruitment, herbivory and soil microbial community composition. Widespread use of stem-mapped forest stand datasets is currently hampered by the lack of standardized, efficient and easy-to-use tools to calculate tree dynamics (e.g. growth, mortality) and the neighborhood metrics that impact them. We present the forestexplorR package that facilitates the munging, exploration, visualization and analysis of stem-mapped forest stands. By providing flexible, user-friendly functions that calculate neighborhood metrics and implement a recently-developed rapid-fitting tree growth and mortality model, forestexplorR broadens the accessibility of stem-mapped forest stand data. We demonstrate the functionality of forestexplorR by using it to investigate how the species identity of neighboring trees influences the growth rates of three common tree species in Mt Rainier National Park, WA, USA. forestexplorR is designed to facilitate researchers to incorporate spatially-explicit descriptions of tree communities in their studies and we expect this increased diversity of contributors to develop exciting new ways of using stem-mapped forest stand data.