Biomass of California Tree Species

Using TLS to Determine Aboveground Biomass of California Tree Species

Presenter: Paris Krause

Co-Presenter(s):
Brieanne Forbes, Alex Barajas-Ritchie, Sarah Arroyo-Chavez, Jolene Markarian, Lauren Webster, Lauryn Calderon, Kristi Faro, Renzo Grimaldi, Karishma Patel, Zane Cooper, Alanna Post, Matthew Clark, Lisa Patrick Bentley

Presenter Status: Graduate student

Academic Year: 20-21

Semester: Spring

Faculty Mentor: Lisa Bentley

Department: Biology

Funding Source/Sponsor: RSCAP

Other Funding Source/Program: CALFIRE, CSU ARI

President's Strategic Plan Goal: Sustainability and Environmental Inquiry

Screenshot URL: https://drive.google.com/uc?id=1oD2n5BcZH7DiAV9pcYZ22ppcWjuvrRUT

Abstract:
With increasing wildfire severity and frequency in California, accurate quantification of greenhouse gas emissions and carbon sequestration of forests is more important than ever. A crucial part of carbon accounting is to quantify a tree’s aboveground biomass (AGB) using allometric equations. Unfortunately, species-specific equations are limited because data to inform these equations, which requires many trees to be destructively harvested, are difficult and time-consuming to collect. As such, our objective was to use terrestrial laser scanning (TLS) to non-destructively estimate AGB of four native tree species in California (231 individuals), and develop new allometric equations for each species using volumes obtained from quantitative structure models (QSMs). We hypothesize that AGB estimates will differ between methods (TLS vs existing allometric equations) for underrepresented species (Quercus agrifolia and Quercus garryana), yet be similar for well-studied species (Abies concolor and Sequoia sempervirens). We collected TLS data on species of interest at Latour Demonstration State Forest (Shasta County), Pepperwood Preserve and Saddle Mountain Preserve (Sonoma County) using a Riegl VZ-400i scanner. 3D point clouds of trees were extracted from TLS scans and AGB was calculated using QSMs, where parameters were optimized to the height of the tree. Preliminary results indicate AGB estimates from QSMs are similar to AGB estimates using published allometric equations for all species except Q. agrifolia. As AGB impacts both carbon sequestration and fire risk, TLS can provide land managers with updated data to inform decisions regarding management of these species in the face of climate change.