Using inventory based field attributes to characterize carbon stocks and carbon stock changes within eddy-flux covariance tower footprints

Forests are an important part of the global carbon (C) cycle, and understanding and quantifying forest C dynamics is necessary for informed forest management decisions and accurate C budget accounting. This thesis contributes to the understanding of forest C dynamics by comparing biometric measurements of C stock changes (ΔC) and eddy covariance (EC) flux-tower measurements of cumulative net ecosystem productivity (ΣNEP) at three sites at the Fluxnet Canada Research Network British Columbia Flux Station; a young (near-end-of-rotation) forest established in 1949 (DF1949), a pole sapling stand established in 1988 (HDF1988), and a recent clearcut established in 2000 (HDF2000). To address spatial variability in stand and tower footprint conditions, first, light detection and ranging (lidar) remote sensing data were used to quantify large tree and snag aboveground mass (TSAM) at DF1949 (r²=0.75, SEE=29.68 Mg/ha). Next, for all three sites, remote sensing estimates were combined with advanced GIS data to estimate the spatial distribution of C stocks that are more difficult to measure directly using only remote sensing data. The resulting spatial representation of forest structure was combined with published EC flux-tower footprint probability distributions to enable a comparison between biometric ΔC stocks and tower ΣNEP. Where biometric ΔC stocks were difficult to resolve, changes were modeled using parameters from the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3). The best agreement between biometric ΔC stocks and tower ΣNEP was at DF1949 (mean = 15.18 ± 7.94 MgC/ha/4 years ΔC; 13.63 MgC/ha/4 years ΣNEP). The other two sites followed the same rank but had larger divergences and differences of sign (HDF1988: mean = 11.52 ± 1.17 MgC/ha/4 years ΔC and -1.93 MgC/ha/4 years ΣNEP; HDF2000: 3.59 ± 1.59 MgC/ha/4 years ΔC and -20.08 MgC/ha/4 years ΣNEP). An unaccounted source of respiration at the more recently disturbed sites may be related to stump, coarse root, and logging-slash decomposition. This study develops an approach and methodology that may be applied at other EC flux-tower sites where researchers wish to compare biometric-based measurements with micrometeorological-based measurements.Forestry, Faculty ofGraduat

Public participation to estimate forest fuels loading : the development and testing of an application for remote sensing

Advances in mobile computing provide an increasing number of possibilities for public participation in scientific research (PPSR). For example, a growing number of people have access to mobile computing devices, such as smartphones, equipped with sensors including a camera, global positioning system, the ability to record observations, and the ability transfer them over a network for collection and analysis. Literature has shown that PPSR-based approaches can have positive outcomes for volunteers (e.g., opportunities to pursue interests, develop skills, and influence decisions), for resource management (by providing data to inform management strategies), and for science. The objective of this dissertation is to explore how volunteers can use smartphones to collect data to inform forest management in a remote sensing project. The management of wildfires in communities near forested areas was chosen as a case study, and a smartphone application was developed and tested for collecting observations of the amount and arrangement of forest fuels by participants with a range of forestry experience living in fire-affected communities. First, to establish context, other projects using smartphones to collect Earth observation data were reviewed including related terms, concepts, challenges, and opportunities to identify methods of data collection and data processing. Second, questionnaires were given to the volunteers before and after using the application to collect data and were analyzed to understand the social and management considerations including the volunteers’ motivations, attitudes, and behaviours, and the potential of using a PPSR approach for wildfire management. Third, the locations where volunteers submitted data were re-measured and the quality of the data were assessed to provide guidelines for ensuring attribute accuracy and logical consistency. Fourth, the smartphone data was combined with multispectral remote sensing data and topography data to make estimates over broader areas. Finally, a framework was presented to direct future efforts using volunteered remote sensing data. This dissertation demonstrates an approach with potential to apply technology to help inform forest management in communities, with potentially positive outcomes for volunteers, communities, and forest managers.Forestry, Faculty ofGraduat