Research

Solar induced chlorophyll fluorescence is a small amout of energy emitted during the photosynthesis process. it cantains the information about both the energy absorbed by plants' chlorophyll and the the energy partioning between photochemistry, as a results, SIF shows strong correlation with plant photosynthsis at different scales. Using SIF observations from various plantforms, including satellite, canopy, and leaf level, I investigate the information that can be derived from SIF signal, and the factors that affect the GPP-SIF relationship.

Whether autumn warming would increase or decrease the global carbon uptake is still under debate. I compare the phenology derived from SIF and vegetation indices, and derive a metric that describe the radiation limitation on photosynthesis in spring and autumn. Combined with eddy covariance flux tower data from multiple sites in northern ecosystems, I found that radiation limitation is the main regulator of ecosystem whether fix or release carbon in response to warming. 

This study is recently published in Nature Climate Change. Also see a comment by Dr. Su-Jong Jeong in the same issue, and media coverage on Columbia Engineering.

Vegetation dynamics are not influenced by the concurrent climate, but also by itself in the past. Favourable climate in the past could stimulate vegetation growth to surpass the ecosystem carrying capacity, leaving an ecosystem vulnerable to climate stresses. This phenomenon, known as structural overshoot, could potentially contribute to worldwide drought stress and forest mortality. Using a dynamic statistical learning approach, I identify and characterize ecosystem structural overshoot globally and quantify the associated drought impacts. I find that structural overshoot contributed to around 11% of drought events during 1981–2015 and is often associated with compound extreme drought and heat, causing faster vegetation declines and greater drought impacts compared to non-overshoot related droughts. 

This study is recently published in Nature Ecology & Evolution. Also see a comment by Dr. Miguel A. Zavala in the same issue.

Vegetation Optical Depth (VOD) represents the opacity of vegetation in the microwave band and is strongly linked to the vegetation total water content. It has been demonstrated that using morning and afternoon observations of VOD can get information about plant water dynamics, which can be further link to plant hydraulic strategies. I use the VOD dataset in combination with the in situ based soil moisture measurements, and demonstrated that the VOD changes ar dominated by the vegetation greenness/leaf biomass changes. A new method was also proposed to estimate plant iso/anisohydricity using VOD dataset.

This study is published in Remote Sensing of Environment

The OCO-2 satellite provides unprecedented SIF observation throughput and accuracy. However due to the satellite orbit and sampling strategy, the SIF observations are not continuous in space and time, limiting its application. We use a machine learning algorithm and generate the "Contiguous SIF" dataset during 2000-2018, this dataset has spatially contiguous coverage and low uncertainty compared to the orginal dataset. This dataset has been used in several studies including Wang et al. (2018); Piao et al. (2019) as well as in IPCC-AR6 report. 

I use a light use efficiency model (the vegetation photosynthesis model) to estimate global gross primary productivity at 500m spatial resolution, 8-day temporal resolution during the MODIS era. The VPM model is a novel model that consider the radiation absorbed by plant chlorophyll and a universial light use efficiency at chlorophyll level across all C3 plants. It also uses additional C3/C4 maps to consider the differences in light use efficiency for C3/C4 photosynthesis pathways. The validation using global flux tower sites demonstrated very high accuracy in representing the spatial temporal dynamics.

This global GPP dataset is available at different spatial and temperoal resolutions, and is updated annually by Earth Observing and Modeling Facility at University of Oklahoma.

For detailed information, please see the dataset description paper and the other paper showing the converging LUE for C3 plants.