Do current biomass equations for Alnus glutinosa and Betula pubescens misestimate carbon stocks at peatland sites?

Accurate estimation of forest carbon stocks is essential for climate change mitigation, particularly in peatland ecosystems known for their high soil organic carbon content. However, biomass equations currently used in Germany, such as the ^"regular" biomass equation of the National Forest Inventory integrated in the TapeS R package, are primarily calibrated for mineral soil sites and may misestimate biomass in peatland forests. This study evaluates the applicability of existing biomass equations for Alnus glutinosa and Betula pubescens in forested peatlands across Germany by comparing estimates of the biomass equation of the National Forest Inventory with a set of alternative allometric functions, including peatland-specific equations. Using data from 65 forests at peatland and 1266 forests at mineral soil sites, we assessed tree growth patterns, aboveground biomass, and carbon stocks. Results indicate significant differences in growth dynamics between peatland and mineral sites, with trees at peatland sites exhibiting lower heights and biomass at a given diameter. Despite this, stand level carbon estimates by the standard biomass equation of the National Forest Inventory aligned closely with the mean of all equations for both species and did not show a consistent bias, although it overestimated individual tree biomass for Betula pubescens. Notably, peatland-specific functions show high variability and no clear advantage over the biomass equation of the National Forest Inventory. We conclude that while the equation of the National Forest Inventory currently provides robust estimates for the carbon stock of peatland forests in Germany on stand level for Betula pubescens and Alnus glutinosa, future recalibration may be needed as restoration efforts and climate change alter site conditions. For local-scale applications, especially in intact or rewetted peatlands, site-adapted equations are recommended to account for the high spatial heterogeneity and complex growth dynamics of these ecosystems.