Allometry and structural volume change of standing dead southern pine trees using non-destructive terrestrial LiDAR
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Tree mortality from major disturbances can greatly increase dead wood in forested areas, affecting fire intensity and behavior, wildlife habitat, and carbon dynamics. Accurately quantifying regional standing dead tree (SDT) pools, as conducted by the U.S. Forest Service Forest Inventory and Analysis (FIA) program, remains a prominent challenge. Little empirical work has been done accounting for structural changes in SDT volume across decay classes due to measurement and sampling challenges associated with SDT. Light-detection-and-ranging (LiDAR) represents a remote sensing technology with the potential to improve sampling efficacy and provide volume estimates of SDT via non-destructive sampling. Following this, the goal of this study was to explore the feasibility of empirically quantifying and assessing structural volume in southern pine SDT by decay class using terrestrial LiDAR. To meet this goal, we addressed three objectives, 1) construct empirical volume estimates of SDT by decay class using terrestrial LiDAR and a voxel-based, volume calculation algorithm capable of accounting for occlusion and point cloud quality, 2) develop allometric relationships of aboveground SDT component volumes by decay class and assess error in models and predictions, and 3) quantify proportion-remaining volume of SDT components from terrestrial LiDAR-derived volumes relative to predicted intact tree volumes. This study represents the first to develop empirically-based, terrestrial LiDAR-derived allometric volume relationships and proportion-remaining volume of SDT by decay class. Results indicate that terrestrial LiDAR-derived volumes of SDT produced robust allometric equations by decay class for total above-stump and stem-plus-bark components (adjusted R=0.940.98). Allometric relationships for tops-and-branches comprised more variability, likely impacted by scan quality, having adjusted R values of ~0.520.59. Notably, the inclusion of height in allometric relationships for total above-stump volume precluded the need for decay class as a covariate, accounting for the variability inherent in each decay class. Importantly, this means that total above-stump allometric equations could be effective under different decay class systems or, more broadly, where no decay classes were measured, thus providing broad utility. Empirically-derived proportion-remaining volume of SDT components followed expected decreasing trends by decay class. Interestingly, proportion-remaining volume for tops-and-branches closely matched theoretically-derived values from a previous FIA-related study. Ultimately, terrestrial LiDAR was critical for efficiently measuring volume of southern pine SDT by decay class and for developing SDT-specific allometric relationships of volume and estimates of structural change by decay class. This study showcases the feasibility of LiDAR-derived, SDT-specific tools for improved accounting of SDT resources in FIA and other inventories.
