How well do light-use efficiency models capture large-scale drought impacts on vegetation productivity compared with data-driven estimates?. (February 2023)
- Record Type:
- Journal Article
- Title:
- How well do light-use efficiency models capture large-scale drought impacts on vegetation productivity compared with data-driven estimates?. (February 2023)
- Main Title:
- How well do light-use efficiency models capture large-scale drought impacts on vegetation productivity compared with data-driven estimates?
- Authors:
- Lv, Yiming
Liu, Jinxiu
He, Wei
Zhou, Yanlian
Tu Nguyen, Ngoc
Bi, Wenjun
Wei, Xiaonan
Chen, Hui - Abstract:
- Highlights: Five LUE models were evaluated against data-driven GPP products and ancillary data. Data-driven models are able to reasonably well represent GPP dynamics at site levels. The simulated GPP by LUE models reasonably responded to droughts at regional scales. Considerable differences existed in the amplitude and phase of GPP seasonal anomalies. LUE models consistently exhibited a likely misrepresentation of drought legacy effects. Abstract: Remote sensing driven light-use efficiency (LUE) models are an important tool for estimating vegetation gross primary productivity (GPP) and assessing climate change impacts on the terrestrial carbon cycle, but their capacity in representing drought impact on GPP over large-scales is not fully explored. Here, we evaluated a suite of LUE models, i.e., VPM, TL-LUE, CASA, EC-LUE and MuSyQ, against two data-driven flux products (GOSIF-GPP and FluxSat), with the aids of environmental variables and eddy covariance flux measurements over North America. The two data-driven GPP products were firstly validated against with eddy covariance flux measurements, suggesting that they are able to reasonably indicate drought impacts at site scales. They were then used as a reference to evaluate these LUE models for indicating the drought impacts in 2011 and 2012 over North America at regional scales. In general, the simulated GPP by these models reasonably responded to droughts, but showed considerable differences in the seasonal anomalies for bothHighlights: Five LUE models were evaluated against data-driven GPP products and ancillary data. Data-driven models are able to reasonably well represent GPP dynamics at site levels. The simulated GPP by LUE models reasonably responded to droughts at regional scales. Considerable differences existed in the amplitude and phase of GPP seasonal anomalies. LUE models consistently exhibited a likely misrepresentation of drought legacy effects. Abstract: Remote sensing driven light-use efficiency (LUE) models are an important tool for estimating vegetation gross primary productivity (GPP) and assessing climate change impacts on the terrestrial carbon cycle, but their capacity in representing drought impact on GPP over large-scales is not fully explored. Here, we evaluated a suite of LUE models, i.e., VPM, TL-LUE, CASA, EC-LUE and MuSyQ, against two data-driven flux products (GOSIF-GPP and FluxSat), with the aids of environmental variables and eddy covariance flux measurements over North America. The two data-driven GPP products were firstly validated against with eddy covariance flux measurements, suggesting that they are able to reasonably indicate drought impacts at site scales. They were then used as a reference to evaluate these LUE models for indicating the drought impacts in 2011 and 2012 over North America at regional scales. In general, the simulated GPP by these models reasonably responded to droughts, but showed considerable differences in the seasonal anomalies for both amplitude and phase. Especially, these models consistently showed a clearly earlier trough (about 1 ∼ 2 months) of flux reduction than those in data-driven models over both entire drought-impacted regions and individual ecosystems (mostly pronounced for grasslands), indicating a likely misrepresentation of drought legacy effects, which needs to be considered in developing new-generation LUE models. Among the grass-dominated drought areas, TL-LUE and VPM performed best in indicating the impacts of the 2011 and 2012 droughts on regional GPP, respectively, while EC-LUE showed a significant underestimation of the impacts in both events, which may be attributed to the different representations of water stress factors in models. This study could provide some useful hints toward improving LUE models in characterizing drought impacts on regional GPP. … (more)
- Is Part Of:
- Ecological indicators. Volume 146(2023)
- Journal:
- Ecological indicators
- Issue:
- Volume 146(2023)
- Issue Display:
- Volume 146, Issue 2023 (2023)
- Year:
- 2023
- Volume:
- 146
- Issue:
- 2023
- Issue Sort Value:
- 2023-0146-2023-0000
- Page Start:
- Page End:
- Publication Date:
- 2023-02
- Subjects:
- Gross primary productivity (GPP) -- Light-use efficiency models -- Data-driven models -- Drought impact -- Terrestrial carbon cycle
Environmental monitoring -- Periodicals
Environmental management -- Periodicals
Environmental impact analysis -- Periodicals
Environmental risk assessment -- Periodicals
Sustainable development -- Periodicals
333.71405 - Journal URLs:
- http://www.sciencedirect.com/science/journal/1470160X/ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.ecolind.2022.109739 ↗
- Languages:
- English
- ISSNs:
- 1470-160X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3648.877200
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25341.xml