DIAGNOSTIC ANALYSIS OF TERRESTRIAL GROSS PRIMARY PRODUCTIVITY USING REMOTE SENSING AND IN SITU OBSERVATIONS
| dc.contributor.advisor | Xiao, Xiangming | |
| dc.contributor.author | Zhang, Yao | |
| dc.contributor.committeeMember | Basara, Jeffrey | |
| dc.contributor.committeeMember | McCarthy, Heather | |
| dc.contributor.committeeMember | Souza, Lara | |
| dc.contributor.committeeMember | Hong, Yang | |
| dc.date.accessioned | 2017-11-21T20:42:03Z | |
| dc.date.available | 2017-11-21T20:42:03Z | |
| dc.date.issued | 2017-12 | |
| dc.date.manuscript | 2017-12 | |
| dc.description.abstract | Vegetation play a critical role in the interactions between atmosphere and biosphere. CO2 fixed by plants through photosynthesis process at ecosystem scale is termed as gross primary production (GPP). It is also the first step CO2 entering the biosphere from the atmosphere. It not only fuels the ecosystem functioning, but also drives the global carbon cycle. Accurate estimation of the ecosystem photosynthetic carbon uptake at a global scale can help us better understand the global carbon budget, and the ecosystem sensitivity to the global climate change. Satellite observations have the advantage of global coverage and high revisit cycle, hence, are ideal for global GPP estimation. The simple production efficiency model that utilize the remote sensing imagery and climate data can provide reasonably well estimates of GPP at a global scale. With the solar induced chlorophyll fluorescence (SIF) being retrieved from satellite observations, new opportunities emerge in directly estimating photosynthesis from the energy absorption and partitioning perspective. In this thesis, by combining observations from both in situ and remotely acquired, I tried to (1) investigate the GPP SIF relationship using data from observations and model simulations; (2) improve a production efficiency model (vegetation photosynthesis model, VPM) and apply it to the regional and global scale; (3) investigate the GPP and SIF sensitivity to drought at different ecosystems; (4) explore the global interannual variation of GPP and its contributing factors. Chapter 2 uses site level observations of both SIF and GPP to explore their linkage at both leaf and canopy/ecosystem scale throughout a growing season. Two drought events happened during this growing season also highlight the advantage of SIF in early drought warning and its close linkage to photosynthetic activity. Chapter 3 compares the GPP and SIF relationships using both instantaneous and daily integrated observations, the daily GPP and satellite retrieved SIF are latitudinal dependent and time-of-overpass dependent. Daily integrated SIF estimation shows better correlation with daily GPP observations. Chapter 4 compares different vegetation indices with SIF to get an empirical estimation of fraction of photosynthetically active radiation by chlorophyll (fPARchl). By comparing this fPARchl estimation with ecosystem light use efficiency retrieved from eddy covariance flux towers, the light use efficiency based on light absorption by chlorophyll shows narrower range of variation that can be used for improving production efficiency models. Chapter 5 investigates the drought impact on GPP through the change of vegetation canopy optical properties and physiological processes. Forest and non-forest ecosystems shows very different responses in terms of these two limitation and need to be treated differently in GPP modelling. Chapter 6 applies the improved VPM to North America and compared with SIF retrieval from GOME-2 instrument. The comparison shows good consistency between GPP and SIF in both spatial and seasonal variation. Chapter 7 uses an ensemble of GPP product to explore the cause of hot spots of GPP interannual variability. GPP in semiarid regions are strongly coupled with evapotranspiration and show high sensitivity to interannual variation of precipitation. The results demonstrate the importance of precipitation in regional carbon flux variability. | en_US |
| dc.identifier.uri | https://hdl.handle.net/11244/52420 | |
| dc.language | en_US | en_US |
| dc.subject | remote sensing | en_US |
| dc.subject | light use efficiency | en_US |
| dc.subject | gross primary production | en_US |
| dc.thesis.degree | Ph.D. | en_US |
| dc.title | DIAGNOSTIC ANALYSIS OF TERRESTRIAL GROSS PRIMARY PRODUCTIVITY USING REMOTE SENSING AND IN SITU OBSERVATIONS | en_US |
| ou.group | College of Arts and Sciences::Department of Microbiology and Plant Biology | en_US |
| shareok.nativefileaccess | restricted | en_US |
| shareok.orcid | 0000-0002-7468-2409 | en_US |