Forests are a major contributor to the global carbon cycle with the ability to sequester carbon via uptake (photosynthesis) and storage (growth). Short-term carbon storage is tied to foliar biomass. Long-term carbon storage via growth can be allocated to the above-ground in tree growth (height and trunk diameter) and below-ground in roots (biomass, density, and width). The amount of carbon sequestered and allocated to above- or below-ground is driven by environmental conditions and stresses. This can have an impact on overall carbon cycle contributions and how much and where carbon is stored.
Canada and New Brunswick (NB) contains a large proportion of temperate and boreal forests that have major carbon sequestration potential. Because of vast forest coverage, there is a need to develop scalable techniques to accurately map and quantify carbon cycle dynamics of forests. NB provides further challenges due to the complexity of its mixed forests containing several species (>10), thus requiring evaluation of species-specific carbon cycle dynamics.
This project will develop and test a remote sensing toolset to evaluate carbon sequestration in mixed Acadian forests in NB. The project goals are to 1) establish long-term above- and below-ground dendrometers to measure tree and root growth as indicators of carbon storage; 2) leverage drone-based remote sensing for monitoring multispectral and LiDAR parameters to assess tree physiology (photosynthesis) and structure (growth); and 3) evaluate satellite-based remote sensing to upscale ground-based methods.
The expected outcome of this project is the establishment of a long-term dendrometer plot for tracking above- and below-ground carbon storage and the development of a remote sensing toolset for assessing carbon uptake and storage of trees. Results will enable scalable techniques for quantifying carbon sequestration of NB forests to assist in assessing nature-based solutions for quantifying carbon removal and storage.
Lead Researcher: Christopher Wong, University of New Brunswick
Project Partners: Jasen Golding, University of New Brunswick; and Dr. Jan Eitel, University of Idaho