Research

Our research focuses on measuring and modelling greenhouse gas, water, and energy fluxes across a range of spatial and temporal scales. We combine field-based measurements, remote sensing, and modelling to investigate land-atmosphere interactions in our rapidly changing world, with a current emphasis on wetland ecosystems.

Carbon Fluxes in Restored Wetlands

26320059305_5dcfe975d4_c.jpgIn collaboration with several other research groups at UBC, we are measuring greenhouse gas exchange and evapotranspiration over a restoring peatland, Burns Bog. This site is a raised domed peat bog in Metro Vancouver that is undergoing re-wetting as a restoration management following peat harvesting and associated drainage. While restoration can help recover important ecosystems services provided by wetlands, it can also affect the exchange of greenhouse gases between the surface and the atmosphere. By conducting year-round eddy covariance measurements of methane and carbon dioxide, we can quantify the annual greenhouse gas balance of the bog and provide information on land-cover-based emission reduction or offset measures in the greater Vancouver area.

Collaborators:
UBC Ecohydrology Research Group
UBC Biometeorology and Soil Physics Group
Dan Moore’s Research Group, UBC Geography

Blue Carbon Research

Nisqually.pngBlue carbon is the carbon sequestered and stored in coastal ecosystems including tidal marshes, mangroves, and seagrasses. Coastal ecosystems are among the strongest carbon sinks in the biosphere. This coupled with their potential for low methane emissions, has generated widespread interest in these ecosystems for climate change mitigation and adaptation. However, measuring and modelling carbon exchanges in tidal wetlands presents unique challenges due to highly dynamic atmospheric and hydrological fluxes, as well as sensitivities to both terrestrial and marine influences. Our work focuses on making continuous, ecosystem-scale measurements of atmospheric and lateral carbon fluxes at natural and restored tidal wetlands along the Pacific Coast. Our research aims to further our understanding of tidal wetland carbon cycling and how these vulnerable ecosystems are expected to respond to projected changes in climate and anthropogenic influences. By integrating measurements within and across tidal wetlands our goal is to foster standardization, synthesis and knowledge of Blue Carbon dynamics.

Collaborators:
U.S. Geological Survey
Oikawa Lab, California State University, East Bay
The Landscape Research Group, UC Berkeley

 FLUXNET Methane Synthesis

Atmospheric CH4 is the second most important anthropogenic greenhouse gas following CO2. However, uncertainties around global CH4 sources and sinks are quite large and much higher than those for CO2, with uncertainties from natural sources exceeding those from anthropogenic emissions. In particular, the most important source of uncertainty in the global methane budget is related to emissions from wetlands and other inland waters. Eddy covariance measurements of CH4 are important for constraining bottom-up methane budgets, for understanding the responses of CH4 fluxes to environmental drivers and climate, and for creating validation datasets for the land-surface models used to infer global CH4 budgets. However, unlike the well-coordinated efforts for synthesizing CO2 observations, no parallel data synthesis and initiative for CH4 is available. With the increasing number of flux sites measuring CH4 emissions across the globe, the time is right for a data synthesis and initiative for CH4. This opportunity forms the basis of the Global Carbon Project’s (GCP) recent FLUXNET CH4 synthesis activity.

FLUXNET_CH4_map.png

Map of tower sites that report eddy covariance CH4 flux measurements. The color of the markers indicate the vegetation type based on the International Geosphere-Biosphere Programme (IGBP) definition.

This recent GCP CH4 budget activity funded by the Moore Foundation is designed to develop a FLUXNET-type analysis and synthesis for CH4 flux observations. The overall goal is to apply machine learning algorithms to upscale site-level fluxes and develop a new globally gridded CH4 product, similar to what has already been done for CO2 fluxes.  Furthermore, the continuous nature of eddy covariance measurements also offers significant promise for improving our understanding of CH4 flux dynamics, and in particular wetland CH4 dynamics. As such, with funding from the USGS Powell Center, we also aim to synthesize data from the CH4 flux tower community to improve our understanding of short-term, seasonal and interannual wetland CH4 dynamics, and characterize the performance of land-surface models used to estimate global CH4 emissions.

Collaborators:
Jackson Lab, Stanford University
NASA Goddard
Global Carbon Project
Stanford Machine Learning Group