LAUSR

The use of LiDAR in the study of gap regimes has seen significant progress in recent years. Researchers have assumed that canopy gaps that are detected in this manner were ecologically equivalent to gaps sampled in situ by more traditional methods. However, those latter methods usually include canopy gaps only and ignore non-regenerating openings that are produced by causes limiting tree establishment. We developed a predictive model capable of discriminating between canopy gaps and non-regenerating openings using LiDAR-derived data. Selected predictive variables were related to conditions that limit tree establishment, such as zones of moisture accumulation and steep slopes, or to the resulting vegetation physiognomy. The model was applied to three old-growth forests to predict the fractions of canopy openings belonging to these two types. On average, non-regenerating openings represented 19.5% of the total area detected as canopy openings and occupied 1.37% of the sites. Canopy gaps formed 80.5% of the ...