Comparing individual-tree approaches for predicting height growth of underplanted seedlings

Key message Individual-tree seeding height growth models developed using tree inventory data were comparable to those requiring the unique observation of point-based canopy structure data at each seedling. Context Quantitative approaches describing the relationship between canopy structure and seedling growth can inform silvicultural decision making regarding the development of tree reproduction beneath a dominant forest canopy. Aims Individual-tree seedling growth models with canopy structure predictors derived from tree inventory data have not been well-explored. This study compared a model framework fit using point-based measures of canopy structure observed at the seedling level to one fit using area-wide canopy structure variables derived from standard inventory plot data. Methods Species-specific models predicting 5-year height growth were fit for cherrybark oak ( Quercus pagoda Raf.), water oak ( Quercus nigra L.), and yellow-poplar ( Liriodendron tulipifera L.) underplanted within a canopy structure gradient created by silvicultural manipulation of a closed-canopy forest in Georgia, USA. Results Though the species varied in shade tolerance and growth rates, the general relationship between the predictor variables and height growth was similar among species and model type. Models highlight the importance of including predictor variables that describe seedling size along with openness and vertical structure of the forest canopy. Conclusion While the two model frameworks had comparable fit statistics, the one with predictors derived from tree inventory data may have enhanced utility as it can be directly integrated into existing individual-tree forest growth simulators.