Field Measurements of Leaf Photosynthetic Capacity (Vcmax) for Carbon Cycle Research

点击翻译按钮获取中文摘要

The current state of the art in global carbon cycle modeling is to assign the leaf maximum photosynthetic capacity (carboxylation rate, Vcmax) as constants by plant functional type (PFT) due to lack of Vcmax observations. This causes large uncertainties in modeled carbon and water cycles because for the same PFT, Vcmax can vary by a factor of 2-3 both spatially and seasonally. Under the support of my previous NSERC and other grants, we have recently produced the first ever global Vcmax map series using satellite solar-induced chlorophyll fluorescence (SIF) data (monthly, 36 km resolution, 2007-2017) and the first ever global leaf chlorophyll content (LCC) map series using the Medium Resolution Imaging Spectrometer (MERIS) satellite data (weakly, 300 m resolution, 2003-2011). Both are published in Remote Sensing of Environment. The main objectives of my recently funded NSERC Discovery Grant (2020-2025) are to acquire a large ground-based dataset of Vcmax, SIF and LCC to validate SIF-derived Vcmax maps and to convert LCC maps into Vcmax maps. In this proposal, funds are requested to purchase a LI-6800F Portable Photosynthesis System for field measurement of leaf Vcmax and fluorescence parameters, while LCC will be measured using our existing wet lab facility. Compared with the obsolete LI-6400, LI-6800F can provide more accurate Vcmax measurements in much shorter time (5 vs 45 minutes for one value), allowing for data collection from large leaf samples. LI-6800F also has a built-in capacity to measure leaf fluorescence parameters, critical for further developing and validating our SIF-based Vcmax retrieval algorithm. Through existing collaborations, measurements of Vcmax, SIF, and LCC will be collected at the broadleaf and conifer tower flux sites near Borden and Turkey Lake, Ontario, so that the usefulness of these parameters for carbon and water cycle modeling can be demonstrated. In addition, a large number of similar datasets will be collected over grassland and cropland in Canada to validate Vcmax maps derived from satellite-based SIF and LCC. These two sets of Vcmax maps will be mutually compared to assess their spatio-temporal reliability and validated using ground-based data and high-resolution remote sensing data (Sentinel, 10-20 m resolution). The derivation of these Vcmax datasets would be a large step forward in reducing the uncertainty in global terrestrial carbon cycle estimation. This requested instrument is also essential for HQP training and will be immediately and intensively used for 1 postdoctoral fellow, 3 PhD students, and additional graduate students in later years for various tasks associated with global Vcmax derivation and validation. The opportunity for these trainees to use this requested instrument will greatly enhance their learning experience and allow them to achieve cutting edge research results. It will also make their skills and knowledge more marketable and attractive to research organizations and companies.