Thesis Information
Title: Using Terrestrial Laser Scanning to Estimate Leaf Area Index in Peatland Conifers Under a Climate Manipulation
Program: Master of Science in Geosciences
Advisor: Dr. Nancy Glenn, Geosciences
Committee Members: Dr. Anna Bergstrom, Geosciences; and Dr. Jeffrey Warren, Geosciences
Abstract
Northern peatlands are major terrestrial carbon sinks, storing 415 Gt of carbon. The composition of peatland vegetation affects this carbon storage capacity. Ground layer vegetation, such as Sphagnum sp. moss contributes greatly to carbon storage capacity. In forested or treed peatlands, the tree canopy structure directly influences peatland solar insolation, soil temperature, and water table levels. Each of these factors impacts the ground layer vegetation. Little is known about how the peatland tree canopy structure is influenced by elevated levels of carbon dioxide (CO2) and temperature. Providing canopy structural metrics in a nondestructive, spatially comprehensive way across different temperature and CO2 treatments is challenging for traditional methods such as destructive harvesting, Digital Hemispherical Photography (DHP), and allometric regressions. Terrestrial Laser Scanning (TLS) is well-suited to provide non-destructive detailed horizontal and vertical canopy structural information that does not rely on other allometric relationships.
As part of the Spruce and Peatland Responses Under Changing Environments (SPRUCE) study located in northern Minnesota, USA, we use TLS to evaluate leaf area index (LAI), leaf area density, and leaf inclination angle over time (2015 – 2022) and space of two conifer species, Picea mariana (black spruce) and Larix laricina (eastern larch). The SPRUCE site is located in a treed peatland bog under elevated CO2 and temperature conditions. The research questions of this study are 1) How accurately can we predict the LAI of the spruce and larch trees using TLS data? 2) To what degree are the spruce and larch tree canopy structures within 12 SPRUCE plots changing from 2015 – 2022? We expected 1) A volumetric pixel based model (VCP) will predict LAI with an accuracy of 90% as validated by destructively harvested and DHP LAI estimates 2) The spruce and larch trees will respond with opposing trends for each metric under the same treatment and leaf density will decrease more rapidly in lower canopies under elevated temperature and CO2 treatments. Using TLS data, we develop a modified VCP model that uses measures of point contact frequency to estimate Leaf Area Index (LAI), leaf inclination angles, and leaf area density. The results indicate that the model predicts LAI with a coefficient of determination of 0.89 (R2 = 0.89), a RMSE of 0.98, and a nRMSE = 0.17. Our canopy structural results show that the spruce and larch trees generally have opposing LAI and leaf area density growth trends. Leaf inclination angle, however, tends to shift from a more vertical distribution to a symmetrical distribution in both species under treatment conditions other than ambient. These findings indicate that there are differences in species level canopy changes over time and space which may affect carbon emission predictions being made by the larger SPRUCE ecosystem model. Quantifying the responses of the spruce and larch species broadens the extent of research showing that species will not respond uniformly to climate change, meaning that some species will have different thresholds of survival and adaptation as CO2 and temperatures rise. Additionally, they show the greater utility of TLS in making species-level canopy structural estimations where other methods often fail to do so at the same spatial scale.