Comparing patterns in forest stand structure following variable harvests using airborne laser scanning data

Understanding landscape patterns that result from natural disturbances in the mixedwood boreal forests of Canada is a critical precursor to advancing sustainable forestry practices and ecosystem-based land management initiatives. However, monitoring changes in boreal forest structure following disturbance is difficult due to restricted access and the spatial scale at which these disturbances occur. Airborne Laser Scanning (ALS) measures the three-dimensional distribution of vegetation across large areas with high sampling intensities, enabling the detection of small changes in vegetation structure in stands of otherwise similar composition and age. In this paper we compare the suitability of three suites of ALS metrics to discriminate changes in vegetation structure across a gradient of forest harvest retention levels (100% retention (uncut control), 75%, 50%, 20%, 10%, and 0% (clear cut)) for four boreal forest stand types: conifer, deciduous, mixed, and deciduous with conifer understorey. Specifically, we focus on three key types of ALS metric: plot-based point cloud metrics, canopy volumes, and curve-fitting approaches; and evaluate the sensitivity of these metrics to changes in forest stand architecture in response to the harvest treatments or lack thereof. From the three types of metrics, height based point cloud metrics show the most significant separation by treatments and stand-types, followed by canopy volume profiles. Airborne laser scanning has strong utility for distinguishing responses in silvicultural treatments and cover types, revealing characteristics not captured by traditional measurements like crown closure or basal area.