Predicting long-term sapling dynamics and canopy recruitment in northern hardwood forests

Abstract

Prediction of forest composition and structure over multiple generations of trees is often hampered by limited data on understory tree dynamics and the highly variable process of canopy recruitment in forest openings. In this paper, we describe a model of sapling dynamics and overstory recruitment for CANOPY, a spatially explicit, crown-based, individual-tree model of gap dynamics. The model incorporates gap size as a predictor of sapling recruitment and height growth, and it mimics the processes of sapling release, gap capture, and lateral gap closure. Calibration data were derived from 12 data sets with a wide range of stand ages and disturbance history in northern hardwood stands in the Great Lakes region, USA. The model accounted for 30%–62% of the variation in sapling density, composition, and growth rates. Predicted effects of increasing gap size on growth rate were similar to observed trends. Growth equations that included gap size as an independent variable generally gave better predictions of sapling density, species composition, and growth rates than equations based on conventional plot-level competition metrics. Long-term, 1000-year simulations produced estimates of stand basal areas and tree density in each size class that are close to the mean observed values for old-growth stands in the region.