Research Highlights: This study advances the effort to accurately estimate the biomass of trees in peatlands, which cover 13% of Canada’s land surface. Background and Objectives: Trees remove carbon from the atmosphere and store it as biomass. Terrestrial laser scanning (TLS) has become a useful tool for modelling forest structure and estimating the above ground biomass (AGB) of trees. Allometric equations are often used to estimate individual tree AGB as a function of height and diameter at breast height (DBH), but these variables can often be laborious to measure using traditional methods. The main objective of this study was to develop allometric equations using TLS-measured variables and compare their accuracy with that of other widely used equations that rely on DBH. Materials and Methods: The study focusses on small black spruce trees (<5 m) located in peatland ecosystems of the Taiga Plains Ecozone in the Northwest Territories, Canada. Black spruce growing in peatlands are often stunted when compared to upland black spruce and having models specific to them would allow for more precise biomass estimates. One hundred small trees were destructively sampled from 10 plots and the dry weight of each tree was measured in the lab. With this reference data, we fitted biomass models specific to peatland black spruce using DBH, crown diameter, crown area, height, tree volume, and bounding box volume as predictors. Results: Our best models had crown size and height as predictors and outperformed established AGB equations that rely on DBH. Conclusions: Our equations are based on predictors that can be measured from above, and therefore they may enable the plotless creation of accurate biomass reference data for a prominent tree species in a common ecosystem (treed peatlands) in North America’s boreal.

&lt;p&gt;Buttressed trees have one of the largest sources of variation in volume or biomass estimates in tropical forests. Buttresses provide mechanical support for trees and offer other essential ecological functions such as nutrient acquisition. Here, we use an Alpha Shape Algorithm (ASA) based on a 3D point cloud to estimate the volume of 30 buttressed trees collected using Terrestrial Photogrammetry (TP). We also calculated the buttresses volume using allometric models developed using the Diameter Above the Buttress (DAB) and the Diameter computed from non-convex (D&lt;sub&gt;area130&lt;/sub&gt;) and convex area (D&lt;sub&gt;convex130&lt;/sub&gt;) at breast height (1.3 m). To demonstrate the broader generalization of our allometric models, we validated the developed models using independent data obtained by Terrestrial Laser Scanning (TLS) and destructive measurement. Volume estimated by the ASA showed a high agreement with the reference volume acquired by the Smalian formula (RRMSE of 0.08 and R&lt;sup&gt;2 &lt;/sup&gt;= 0.99 regardless of species effect). Our results suggest that the DAB seems to be the most advanced predictor for volume, with the lowest Akaike information criterion (AIC) of -62.4 than the D&lt;sub&gt;area130&lt;/sub&gt; (49.2)&lt;sub&gt;&lt;/sub&gt;and the D&lt;sub&gt;convex130&lt;/sub&gt; (30.3). At the same time, the DAB (RRMSE of 0.2) and D&lt;sub&gt;area130&lt;/sub&gt; (RRMSE of 0.2) show similar performance when validated with independent data sets. Our results indicate that the ASA is more reliable and efficient than allometric models for buttress modelling. Our results also provide a solid foundation for buttress modelling, as we use more buttressed trees (45) for allometric model development than previous studies. Furthermore, the proposed non-destructive method can help to correct the bias in present and past estimates of volume and biomass of large trees, which are keystone components to understanding biomass allocation and dynamics in tropical forests.&lt;/p&gt;

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