allodb | A database of allometric equations for ForestGEO

allodb is a R library. allodb has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. You can download it from GitHub.

Allometric equations for calculation of tree aboveground biomass (AGB) form the basis for estimates of forest carbon storage and exchange with the atmosphere. While standard models exist to calculate forest biomass across the tropics, we lack a standardized tool for computing AGB across the global extratropics. allodb was conceived as a framework to standardize and simplify the biomass estimation process across globally distributed extratropical forests (mainly temperate and boreal forests). With allodb we aimed to: a) compile relevant published and unpublished allometries, focusing on AGB but structured to handle other variables (e.g., height); b) objectively select and integrate appropriate available equations across the full range of tree sizes; and c) serve as a platform for future updates and expansion to other research sites. The allodb package contains a dataset of systematically selected published allometric equations. This dataset was built based on 701 woody species identified at 24 large ForestGEO forest dynamic plots representing all major extratropical forest types. A total of 570 parsed allometric equations to estimate individual tree biomass were retrieved, checked, and combined using a weighting function designed to ensure optimal equation selection over the full tree size range with smooth transitions across equations. The equation dataset used can be customized with built-in functions that subset the original dataset and add new equations. The package provides functions to estimate tree biomass based on user-provided census data (tree diameter, taxonomic identification, and plot coordinates). New allometric equations are calibrated for each species and location by resampling the original equations; equations with a larger sample size and/or higher taxonomic and climatic similarity with the species and location in question are given a higher weight in this process.