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Yang J, Lu X, Liu Z, Tang X, Yu Q, Wang Y. Atmospheric drought dominates changes in global water use efficiency. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 934:173084. [PMID: 38735314 DOI: 10.1016/j.scitotenv.2024.173084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 05/06/2024] [Accepted: 05/07/2024] [Indexed: 05/14/2024]
Abstract
Water use efficiency (defined as the ratio of gross primary productivity to plant transpiration, WUET) describes the tradeoff between ecosystem carbon uptake and water loss. However, a comprehensive understanding of the impact of soil and atmospheric moisture deficits on WUET across large regions remains incomplete. Solar-induced chlorophyll fluorescence (SIF) serves as an effective signal for measuring both terrestrial vegetation photosynthesis and transpiration, thereby enabling a rapid response to changes in the physiological status of plants under water stress. The objectives of this study were to: 1) mechanistically calculate WUET using top-of-canopy SIF data and meteorological information by using the revised mechanistic light response model and the Penman-Monteith equation; 2) analyze the effects of atmospheric and soil water deficits on SIF-based WUET by using decoupled soil water content (SWC) and vapor pressure deficit (VPD); 3) evaluate estimated SIF-based WUET against data from 28 eddy covariance (EC) flux sites representing eight different vegetation types. Results indicated that the model performed well in ecosystems with dense canopies, explaining 56 % of the daily variability in EC tower-based WUET. For the years 2019-2020, the global average WUET derived from SIF was 3.49 g C/kg H2O. Notably, this value exceeded 4 g C/kg H2O in tropical rainforest regions near the equator and went beyond 5 g C/kg H2O in the high-latitude regions of the Northern Hemisphere. We found that SIF-based WUET was primarily influenced by VPD rather than SWC in over 90 % of the global vegetated area. The model used in this study increased our ability to mechanistically estimate WUET with SIF at the global scale, thereby highlighting the significance of the global response of SIF-based WUET to water stress, and also enhancing our understanding of the water‑carbon cycle in terrestrial ecosystems.
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Affiliation(s)
- Jingjing Yang
- The Research Center of Soil and Water Conservation and Ecological Environment, Chinese Academy of Sciences and Ministry of Education, Yangling, Shaanxi 712100, China; Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling, Shaanxi 712100, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaoliang Lu
- State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Zhunqiao Liu
- State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Xianhui Tang
- The Research Center of Soil and Water Conservation and Ecological Environment, Chinese Academy of Sciences and Ministry of Education, Yangling, Shaanxi 712100, China; Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling, Shaanxi 712100, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qiang Yu
- State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling, Shaanxi 712100, China.
| | - Yunfei Wang
- School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou, Henan 450001, China.
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2
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Lin J, Zhou L, Wu J, Han X, Zhao B, Chen M, Liu L. Water stress significantly affects the diurnal variation of solar-induced chlorophyll fluorescence (SIF): A case study for winter wheat. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 908:168256. [PMID: 37924891 DOI: 10.1016/j.scitotenv.2023.168256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 10/30/2023] [Accepted: 10/30/2023] [Indexed: 11/06/2023]
Abstract
Remote sensing of Solar-induced chlorophyll fluorescence (SIF) has been widely used in estimating Gross Primary Productivity (GPP) and detecting stress in terrestrial ecosystems. Water stress adversely impacts the growth, development, and productivity of a plant. Recently, the characterizing and understanding of the diurnal cycling of plant functioning and ecosystem processes has been explored using SIF. However, the diurnal response of SIF to different levels of water stress remains unclear. This study conducted field experiments on winter wheat by subjecting it to different levels of water stress including well-watered (CK) and, mild, moderate, and severe water stress (D1, D2, D3), and collected the spectral data using an automated SIF measurement system. The results observed the strong SIF-PAR (photosynthetically active radiation) correlations and that these relationships gradually decoupled with increasing water stress, which further decreased the accuracy of temporal upscaling of far-red SIF from an instantaneous to daily scale. To quantify the characteristics of diurnal far-red SIF, five indices including peak time, peak value, curve opening coefficient (leading coefficient of the parabola), and left/right slopes of the peak were proposed. The results demonstrated that diurnal far-red SIF was characterized by an earlier peak time, decreasing peak value, wider curve opening, and flattening right slope from the CK plot to the D3 plot. There were certain mechanisms linking the different indices, for example, between peak size and opening coefficient. Furthermore, the response of far-red SIF to water stress was most pronounced at noon. SIF/PAR exhibited a more significant response to varying water stress compared to far-red SIF, which mitigated the negative influence of PAR variations on diurnal SIF. These findings contribute to the monitoring of plant water dynamics at fine temporal scales.
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Affiliation(s)
- Jingyu Lin
- Key Laboratory of Environmental Change and Natural Disasters of Ministry of Education, Beijing Normal University, Beijing 100875, China; Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Litao Zhou
- Key Laboratory of Environmental Change and Natural Disasters of Ministry of Education, Beijing Normal University, Beijing 100875, China; Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Jianjun Wu
- Key Laboratory of Environmental Change and Natural Disasters of Ministry of Education, Beijing Normal University, Beijing 100875, China; Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China.
| | - Xinyi Han
- Key Laboratory of Environmental Change and Natural Disasters of Ministry of Education, Beijing Normal University, Beijing 100875, China; Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Bingyu Zhao
- Key Laboratory of Environmental Change and Natural Disasters of Ministry of Education, Beijing Normal University, Beijing 100875, China; Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Meng Chen
- Key Laboratory of Environmental Change and Natural Disasters of Ministry of Education, Beijing Normal University, Beijing 100875, China; Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Leizhen Liu
- College of Grassland Science and Technology, China Agricultural University, Beijing 100083, China
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Luo Y, Yang J, Yang S, Wang A, Shuo S, Du L. Assessing the responses of different vegetation types to drought with satellite solar-induced chlorophyll fluorescence over the Yunnan-Guizhou Plateau. OPTICS EXPRESS 2023; 31:35565-35582. [PMID: 38017724 DOI: 10.1364/oe.501964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 09/11/2023] [Indexed: 11/30/2023]
Abstract
The Yunnan-Guizhou Plateau (YGP) is an important ecological region in southwestern China with frequent and severe droughts affecting its vegetation and ecosystem. Many studies have used vegetation indices to monitor drought effects on vegetation across the entire ecosystem. However, the drought response of different vegetation types in the YGP is unclear. This study used solar-induced chlorophyll fluorescence (SIF) and normalized difference vegetation Index (NDVI) data to monitor different vegetation types. The results showed that cropland was most sensitive and woody savanna was most resistant to drought. SIF had a stronger correlation with drought than NDVI, indicating its potential for vegetation monitoring.
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Li W, Pacheco-Labrador J, Migliavacca M, Miralles D, Hoek van Dijke A, Reichstein M, Forkel M, Zhang W, Frankenberg C, Panwar A, Zhang Q, Weber U, Gentine P, Orth R. Widespread and complex drought effects on vegetation physiology inferred from space. Nat Commun 2023; 14:4640. [PMID: 37582763 PMCID: PMC10427636 DOI: 10.1038/s41467-023-40226-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Accepted: 07/12/2023] [Indexed: 08/17/2023] Open
Abstract
The response of vegetation physiology to drought at large spatial scales is poorly understood due to a lack of direct observations. Here, we study vegetation drought responses related to photosynthesis, evaporation, and vegetation water content using remotely sensed data, and we isolate physiological responses using a machine learning technique. We find that vegetation functional decreases are largely driven by the downregulation of vegetation physiology such as stomatal conductance and light use efficiency, with the strongest downregulation in water-limited regions. Vegetation physiological decreases in wet regions also result in a discrepancy between functional and structural changes under severe drought. We find similar patterns of physiological drought response using simulations from a soil-plant-atmosphere continuum model coupled with a radiative transfer model. Observation-derived vegetation physiological responses to drought across space are mainly controlled by aridity and additionally modulated by abnormal hydro-meteorological conditions and vegetation types. Hence, isolating and quantifying vegetation physiological responses to drought enables a better understanding of ecosystem biogeochemical and biophysical feedback in modulating climate change.
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Affiliation(s)
- Wantong Li
- Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany.
| | - Javier Pacheco-Labrador
- Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
| | | | - Diego Miralles
- Hydro-Climate Extremes Lab (H-CEL), Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
| | - Anne Hoek van Dijke
- Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Markus Reichstein
- Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
- Integrative Center for Biodiversity Research (iDIV), Leipzig, Germany
| | - Matthias Forkel
- Institute of Photogrammetry and Remote Sensing, Technische Universität Dresden, Dresden, Germany
| | - Weijie Zhang
- Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Christian Frankenberg
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, 91125, USA
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, 91109, USA
| | - Annu Panwar
- Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Qian Zhang
- School of Geomatics Science and Technology, Nanjing Tech University, Nanjing, China
| | - Ulrich Weber
- Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Pierre Gentine
- Department of Earth and Environmental Engineering, Columbia University, New York, NY, 10027, USA
| | - Rene Orth
- Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
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Wang Y, Liu J, Wennberg PO, He L, Bonal D, Köhler P, Frankenberg C, Sitch S, Friedlingstein P. Elucidating climatic drivers of photosynthesis by tropical forests. GLOBAL CHANGE BIOLOGY 2023. [PMID: 37401204 DOI: 10.1111/gcb.16837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 05/11/2023] [Accepted: 06/02/2023] [Indexed: 07/05/2023]
Abstract
Tropical forests play a pivotal role in regulating the global carbon cycle. However, the response of these forests to changes in absorbed solar energy and water supply under the changing climate is highly uncertain. Three-year (2018-2021) spaceborne high-resolution measurements of solar-induced chlorophyll fluorescence (SIF) from the TROPOspheric Monitoring Instrument (TROPOMI) provide a new opportunity to study the response of gross primary production (GPP) and more broadly tropical forest carbon dynamics to differences in climate. SIF has been shown to be a good proxy for GPP on monthly and regional scales. Combining tropical climate reanalysis records and other contemporary satellite products, we find that on the seasonal timescale, the dependence of GPP on climate variables is highly heterogeneous. Following the principal component analyses and correlation comparisons, two regimes are identified: water limited and energy limited. GPP variations over tropical Africa are more correlated with water-related factors such as vapor pressure deficit (VPD) and soil moisture, while in tropical Southeast Asia, GPP is more correlated with energy-related factors such as photosynthetically active radiation (PAR) and surface temperature. Amazonia is itself heterogeneous: with an energy-limited regime in the north and water-limited regime in the south. The correlations of GPP with climate variables are supported by other observation-based products, such as Orbiting Carbon Observatory-2 (OCO2) SIF and FluxSat GPP. In each tropical continent, the coupling between SIF and VPD increases with the mean VPD. Even on the interannual timescale, the correlation of GPP with VPD is still discernable, but the sensitivity is smaller than the intra-annual correlation. By and large, the dynamic global vegetation models in the TRENDY v8 project do not capture the high GPP seasonal sensitivity to VPD in dry tropics. The complex interactions between carbon and water cycles in the tropics illustrated in this study and the poor representation of this coupling in the current suite of vegetation models suggest that projections of future changes in carbon dynamics based on these models may not be robust.
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Affiliation(s)
- Yuan Wang
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, California, USA
| | - Junjie Liu
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, California, USA
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
| | - Paul O Wennberg
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, California, USA
- Division of Engineering and Applied Science, California Institute of Technology, Pasadena, California, USA
| | - Liyin He
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, California, USA
| | - Damien Bonal
- Université de Lorraine, AgroParisTech, INRAE, UMR Silva, Nancy, France
| | - Philipp Köhler
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, California, USA
| | - Christian Frankenberg
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, California, USA
| | - Stephen Sitch
- College of Life and Environmental Sciences, University of Exeter, Exeter, UK
| | - Pierre Friedlingstein
- College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK
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Balogun O, Bello R, Higuchi K. Terrestrial CO 2 exchange diagnosis using a peatland-optimized vegetation photosynthesis and respiration model (VPRM) for the Hudson Bay Lowlands. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 875:162591. [PMID: 36906026 DOI: 10.1016/j.scitotenv.2023.162591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 12/10/2022] [Accepted: 02/27/2023] [Indexed: 06/18/2023]
Abstract
Satellite-based light use efficiency (LUE) models have been widely used to estimate gross primary production in various terrestrial ecosystems such as forests and croplands, but northern peatlands have received less attention. In particular, the Hudson Bay Lowlands (HBL) which is a massive peatland-rich region in Canada has been largely ignored in previous LUE-based studies. These peatland ecosystems have accumulated large stocks of organic carbon over many millennia, and play a vital role in the global carbon cycle. In this study, we used the satellite data-driven Vegetation Photosynthesis and Respiration Model (VPRM) to examine the suitability of LUE models for carbon flux diagnosis in the HBL. VPRM was driven alternately with the satellite-derived enhanced vegetation index (EVI) and solar-induced chlorophyll fluorescence (SIF). The model parameter values were constrained by eddy covariance (EC) tower observations from the Churchill fen and Attawapiskat River bog sites. The main objectives of the study were to (i) investigate if site-specific parameter optimization improved NEE estimates, (ii) determine which satellite-based proxy of photosynthesis produced more reliable estimates of peatland net carbon exchange, and (iii) examine how LUE and other model parameters vary within and between the study sites. The results indicate that the VPRM mean diurnal and monthly estimates of NEE had significant strong agreements with EC tower fluxes at the two study sites. A comparison of the site-optimized VPRM against a generic peatland-optimized version of the model revealed that the site-optimized VPRM provided better estimates of NEE only during the calibration period at the Churchill fen. The diurnal and seasonal cycles of peatland carbon exchange were better captured by the SIF-driven VPRM, demonstrating that SIF is a more accurate proxy for photosynthesis compared to EVI. Our study suggests that satellite-based LUE models have the potential to be applied on a larger scale to the HBL region.
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Affiliation(s)
- Olalekan Balogun
- Graduate Program in Geography, Faculty of Environmental and Urban Change, York University, Toronto, ON M3J 1P3, Canada.
| | - Richard Bello
- Graduate Program in Geography, Faculty of Environmental and Urban Change, York University, Toronto, ON M3J 1P3, Canada
| | - Kaz Higuchi
- Graduate Program in Geography, Faculty of Environmental and Urban Change, York University, Toronto, ON M3J 1P3, Canada
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7
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Sun Y, Wen J, Gu L, Joiner J, Chang CY, van der Tol C, Porcar-Castell A, Magney T, Wang L, Hu L, Rascher U, Zarco-Tejada P, Barrett CB, Lai J, Han J, Luo Z. From remotely-sensed solar-induced chlorophyll fluorescence to ecosystem structure, function, and service: Part II-Harnessing data. GLOBAL CHANGE BIOLOGY 2023; 29:2893-2925. [PMID: 36802124 DOI: 10.1111/gcb.16646] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 02/09/2023] [Accepted: 02/14/2023] [Indexed: 05/03/2023]
Abstract
Although our observing capabilities of solar-induced chlorophyll fluorescence (SIF) have been growing rapidly, the quality and consistency of SIF datasets are still in an active stage of research and development. As a result, there are considerable inconsistencies among diverse SIF datasets at all scales and the widespread applications of them have led to contradictory findings. The present review is the second of the two companion reviews, and data oriented. It aims to (1) synthesize the variety, scale, and uncertainty of existing SIF datasets, (2) synthesize the diverse applications in the sector of ecology, agriculture, hydrology, climate, and socioeconomics, and (3) clarify how such data inconsistency superimposed with the theoretical complexities laid out in (Sun et al., 2023) may impact process interpretation of various applications and contribute to inconsistent findings. We emphasize that accurate interpretation of the functional relationships between SIF and other ecological indicators is contingent upon complete understanding of SIF data quality and uncertainty. Biases and uncertainties in SIF observations can significantly confound interpretation of their relationships and how such relationships respond to environmental variations. Built upon our syntheses, we summarize existing gaps and uncertainties in current SIF observations. Further, we offer our perspectives on innovations needed to help improve informing ecosystem structure, function, and service under climate change, including enhancing in-situ SIF observing capability especially in "data desert" regions, improving cross-instrument data standardization and network coordination, and advancing applications by fully harnessing theory and data.
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Affiliation(s)
- Ying Sun
- School of Integrative Plant Science, Soil and Crop Sciences Section, Cornell University, Ithaca, New York, USA
| | - Jiaming Wen
- School of Integrative Plant Science, Soil and Crop Sciences Section, Cornell University, Ithaca, New York, USA
| | - Lianhong Gu
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
| | - Joanna Joiner
- National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC), Greenbelt, Maryland, USA
| | - Christine Y Chang
- US Department of Agriculture, Agricultural Research Service, Adaptive Cropping Systems Laboratory, Beltsville, Maryland, USA
| | - Christiaan van der Tol
- Affiliation Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, The Netherlands
| | - Albert Porcar-Castell
- Optics of Photosynthesis Laboratory, Institute for Atmospheric and Earth System Research (INAR)/Forest Sciences, Viikki Plant Science Center (ViPS), University of Helsinki, Helsinki, Finland
| | - Troy Magney
- Department of Plant Sciences, University of California, Davis, Davis, California, USA
| | - Lixin Wang
- Department of Earth Sciences, Indiana University-Purdue University Indianapolis (IUPUI), Indianapolis, Indiana, USA
| | - Leiqiu Hu
- Department of Atmospheric and Earth Science, University of Alabama in Huntsville, Huntsville, Alabama, USA
| | - Uwe Rascher
- Institute of Bio- and Geosciences, Forschungszentrum Jülich GmbH, Jülich, Germany
| | - Pablo Zarco-Tejada
- School of Agriculture and Food (SAF-FVAS) and Faculty of Engineering and Information Technology (IE-FEIT), University of Melbourne, Melbourne, Victoria, Australia
| | - Christopher B Barrett
- Charles H. Dyson School of Applied Economics and Management, Cornell University, Ithaca, New York, USA
| | - Jiameng Lai
- School of Integrative Plant Science, Soil and Crop Sciences Section, Cornell University, Ithaca, New York, USA
| | - Jimei Han
- School of Integrative Plant Science, Soil and Crop Sciences Section, Cornell University, Ithaca, New York, USA
| | - Zhenqi Luo
- School of Integrative Plant Science, Soil and Crop Sciences Section, Cornell University, Ithaca, New York, USA
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Chen R, Liu X, Chen J, Du S, Liu L. Solar-induced chlorophyll fluorescence imperfectly tracks the temperature response of photosynthesis in winter wheat. JOURNAL OF EXPERIMENTAL BOTANY 2022; 73:7596-7610. [PMID: 36173362 DOI: 10.1093/jxb/erac388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 09/27/2022] [Indexed: 06/16/2023]
Abstract
Solar-induced fluorescence (SIF) is a promising proxy for photosynthesis, but it is unclear whether it performs well in tracking the gross primary productivity (GPP) under different environmental conditions. In this study, we investigated the dynamics of the two parameters from October 2020 to June 2021 in field-grown winter wheat (Triticum aestivum) and found that the ability of SIF to track GPP was weakened at low temperatures. Accounting for the coupling of light and temperature at a seasonal scale, we found that SIF yield showed a lower temperature sensitivity and had a lower but broader optimal temperature range compared with light-use efficiency (LUE), although both SIF yield and LUE decreased in low-temperature conditions. The discrepancy between the temperature responses of SIF yield and GPP caused an increase in the ratio of SIF/GPP in winter, which indicated the variation in the relationship between them during this period. The results of our study highlight the impact of low temperature on the relationship between SIF and GPP and show the necessity of reconsidering the dynamics of energy distribution inside plants under changing environments.
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Affiliation(s)
- Ruonan Chen
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xinjie Liu
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
| | - Jidai Chen
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Shanshan Du
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
| | - Liangyun Liu
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
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9
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Fusion of UAV Hyperspectral Imaging and LiDAR for the Early Detection of EAB Stress in Ash and a New EAB Detection Index—NDVI(776,678). REMOTE SENSING 2022. [DOI: 10.3390/rs14102428] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Beijing’s One Million Mu Plain Afforestation Project involves planting large areas with the exotic North American tree species Fraxinus pennsylvanica Marsh (ash). As an exotic tree species, ash is very vulnerable to infestations by the emerald ash borer (EAB), a native Chinese wood borer pest. In the early stage of an EAB infestation, attacked trees show no obvious sign. Once the stand has reached the late damage stage, death occurs rapidly. Therefore, there is a need for efficient early detection methods of EAB stress over large areas. The combination of unmanned aerial vehicle (UAV)-based hyperspectral imaging (HI) with light detection and ranging (LiDAR) is a promising practical approach for monitoring insect disturbance. In this study, we identified the most useful narrow-band spectral HI data and 3D LiDAR data for the early detection of EAB stress in ash. UAV-HI data of different infested stages (healthy, light, moderate and severe) of EAB in the 400–1000 nm range were collected from ash canopies and were processed by Partial Least Squares–Variable Importance in Projection (PLS-VIP) to identify the maximally sensitive bands. Band R678 nm had the highest PLS-VIP scores and the most robust classification ability. We combined this band with band R776 nm to develop an innovative normalized difference vegetation index (NDVI(776,678)) to estimate EAB stress. LiDAR data were used to segment individual trees and supplement the HI data. The new NDVI(776,678) identified different stages of EAB stress, with a producer’s accuracy of 90% for healthy trees, 76.25% for light infestation, 58.33% for moderate infestation, and 100% for severe infestation, with an overall accuracy of 82.90% when combined with UAV-HI and LiDAR.
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10
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Assessing the Potential of Downscaled Far Red Solar-Induced Chlorophyll Fluorescence from the Canopy to Leaf Level for Drought Monitoring in Winter Wheat. REMOTE SENSING 2022. [DOI: 10.3390/rs14061357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Solar-induced chlorophyll fluorescence (SIF) from ground, airborne, and satellite-based observations has been increasingly used in drought monitoring recently due to its close relationship with photosynthesis. SIF emissions respond rapidly to droughts, relative to the widely used vegetation indices (VIs), thus indicating their potential for early drought monitoring. The response of SIF to droughts can be attributed to the confounding effects of both the physiology and canopy structure. In order to reduce the reabsorption and scattering effects, the total emitted SIF (SIFtot) was proposed and served as a better tool to estimate GPP compared with the top-of-canopy SIF (SIFtoc). However, the response time and response magnitude of SIFtot to droughts and its relationships with the environmental parameters and soil moisture (SM) (i.e., the knowledge of drought monitoring using SIFtot) remains unclear. Here, the continuous ground data of F760toc (SIFtoc at 760 nm) from a nadir view that was downscaled to F760tot (SIFtot at 760 nm), NIRv, and the NDVI, SM, meteorological, and crop growth parameters were measured from four winter wheat plots with different intensities of drought (well-watered, moderate drought, severe drought, and extreme drought) over 2 months. The results indicated that F760tot was more closely correlated with the SM than the VIs at short time lags but weaker at longer time lags. The daily mean values of F760tot and NIRv were able to distinguish the differences between different drought levels, and F760tot responded quickly to the onset of drought, especially for the moderate drought intensity. These findings demonstrated that F760tot has potential for early drought monitoring and may contribute to mitigating the risk of agricultural drought.
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11
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Solar-Induced Chlorophyll Fluorescence Trends and Mechanisms in Different Ecosystems in Northeastern China. REMOTE SENSING 2022. [DOI: 10.3390/rs14061329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Solar-induced chlorophyll fluorescence (SIF), when used as a proxy for plant photosynthesis, can provide an indication of the photosynthesis rate and has the potential to improve our understanding of carbon exchange mechanisms within an ecosystem. However, the relationships between SIF and vegetation indices (VIs) operating within different ecological contexts and the effect of other environmental factors on SIF remain unclear. This study focused on three ecosystems (cropland, forest, and grassland), with different ecological characteristics, located in Northeast China. These areas provide case studies where numerous relationships can be explored, including the correlations between the Orbiting Carbon Observatory-2 (OCO-2) SIF and MODIS products, meteorological factors, and the differences in the relationships between the three different ecosystems. Some interesting results and conclusions were obtained. First, in different ecosystems, the relationships between SIF and MODIS products show different correlations, whereby the enhanced vegetation index (EVI) has a close relationship with SIF in all the three ecosystems of forest, cropland, and grassland. Second, forest-type ecosystems appear to be sensitive to changes in daily temperature, whereas cropland and grassland areas respond more closely to changes in previous 16-day daily minimum temperature. Compared with forest and cropland areas, grasslands were more sensitive to precipitation (although the R2 value was small). Third, different ecosystems have different mechanisms of photosynthesis. Hence, we suggest that it is better to use SIF in areas exhibiting different ecological characteristics, and different models should be employed while simulating SIF.
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Li R, Lombardozzi D, Shi M, Frankenberg C, Parazoo NC, Köhler P, Yi K, Guan K, Yang X. Representation of Leaf-to-Canopy Radiative Transfer Processes Improves Simulation of Far-Red Solar-Induced Chlorophyll Fluorescence in the Community Land Model Version 5. JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS 2022; 14:e2021MS002747. [PMID: 35865620 PMCID: PMC9285887 DOI: 10.1029/2021ms002747] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 01/18/2022] [Accepted: 02/14/2022] [Indexed: 05/15/2023]
Abstract
Recent advances in satellite observations of solar-induced chlorophyll fluorescence (SIF) provide a new opportunity to constrain the simulation of terrestrial gross primary productivity (GPP). Accurate representation of the processes driving SIF emission and its radiative transfer to remote sensing sensors is an essential prerequisite for data assimilation. Recently, SIF simulations have been incorporated into several land surface models, but the scaling of SIF from leaf-level to canopy-level is usually not well-represented. Here, we incorporate the simulation of far-red SIF observed at nadir into the Community Land Model version 5 (CLM5). Leaf-level fluorescence yield was simulated by a parametric simplification of the Soil Canopy-Observation of Photosynthesis and Energy fluxes model (SCOPE). And an efficient and accurate method based on escape probability is developed to scale SIF from leaf-level to top-of-canopy while taking clumping and the radiative transfer processes into account. SIF simulated by CLM5 and SCOPE agreed well at sites except one in needleleaf forest (R 2 > 0.91, root-mean-square error <0.19 W⋅m-2⋅sr-1⋅μm-1), and captured the day-to-day variation of tower-measured SIF at temperate forest sites (R 2 > 0.68). At the global scale, simulated SIF generally captured the spatial and seasonal patterns of satellite-observed SIF. Factors including the fluorescence emission model, clumping, bidirectional effect, and leaf optical properties had considerable impacts on SIF simulation, and the discrepancies between simulate d and observed SIF varied with plant functional type. By improving the representation of radiative transfer for SIF simulation, our model allows better comparisons between simulated and observed SIF toward constraining GPP simulations.
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Affiliation(s)
- Rong Li
- Department of Environmental SciencesUniversity of VirginiaCharlottesvilleVAUSA
| | - Danica Lombardozzi
- Climate and Global Dynamics LaboratoryNational Center for Atmospheric ResearchBoulderCOUSA
| | - Mingjie Shi
- Pacific Northwest National LaboratoryRichlandWAUSA
| | - Christian Frankenberg
- Division of Geological and Planetary SciencesCalifornia Institute of TechnologyPasadenaCAUSA
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | | | - Philipp Köhler
- Division of Geological and Planetary SciencesCalifornia Institute of TechnologyPasadenaCAUSA
| | - Koong Yi
- Department of Environmental SciencesUniversity of VirginiaCharlottesvilleVAUSA
- Earth and Environmental Sciences AreaLawrence Berkeley National LaboratoryBerkeleyCAUSA
| | - Kaiyu Guan
- College of Agricultural, Consumers, and Environmental SciencesUniversity of Illinois at Urbana‐ChampaignUrbanaILUSA
- National Center of Supercomputing ApplicationsUniversity of Illinois at Urbana‐ChampaignUrbanaILUSA
- Agroecosystem Sustainability Center, Institute for Sustainability, Energy, and Environment (iSEE)University of Illinois at Urbana‐ChampaignUrbanaILUSA
| | - Xi Yang
- Department of Environmental SciencesUniversity of VirginiaCharlottesvilleVAUSA
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Albright R, Corbett A, Jiang X, Creecy E, Newman S, Li K, Liang M, Yung YL. Seasonal Variations of Solar-Induced Fluorescence, Precipitation, and Carbon Dioxide Over the Amazon. EARTH AND SPACE SCIENCE (HOBOKEN, N.J.) 2022; 9:e2021EA002078. [PMID: 35860761 PMCID: PMC9285695 DOI: 10.1029/2021ea002078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 11/20/2021] [Accepted: 11/24/2021] [Indexed: 06/15/2023]
Abstract
Previous studies suggested that the Amazon, the largest rainforest on Earth, changes from a CO2 sink to a CO2 source during the dry/fire season. However, the biospheric contributions to atmospheric CO2 are not well understood during the two main seasons, the dry/fire season and the wet season. In this article, we utilize Orbiting Carbon Observatory 2 (OCO-2) Solar-Induced Fluorescence (SIF) to explore photosynthetic activity during the different seasons. The spatiotemporal variability of OCO-2 SIF, OCO-2 CO2, precipitation, and burned area are investigated over the Amazon from September 2014 to December 2019. Averaging over the entire Amazon region, we found a positive temporal correlation (0.94) between OCO-2 SIF and Global Precipitation Climatology Project precipitation and a negative temporal correlation (-0.64) between OCO-2 SIF and OCO-2 CO2, consistent with the fact that precipitation enhances photosynthesis, which results in higher values for SIF and rate of removal of CO2 from the atmosphere above the Amazon region. We also observed seasonality in the spatial variability of these variables within the Amazon region. During the dry/fire (August-October) season, low SIF values, low precipitation, high vapor pressure deficit (VPD), large burned areas, and high atmospheric CO2 are mainly found over the southern Amazon region. In contrast, during the wet season (January-March), high SIF values, high precipitation, low VPD, smaller burned areas, and low CO2 are found over both the central and southern Amazon regions. The seasonal difference in SIF suggests that photosynthetic activity is reduced during the dry/fire season relative to the wet season as a result of low precipitation and high VPD, especially over the southern Amazon region, which will contribute to more CO2 in the atmosphere during the dry/fire season.
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Affiliation(s)
- Ronald Albright
- Department of Earth & Atmospheric SciencesUniversity of HoustonHoustonTXUSA
| | - Abigail Corbett
- Department of Earth & Atmospheric SciencesUniversity of HoustonHoustonTXUSA
- SeekOps IncAustinTXUSA
| | - Xun Jiang
- Department of Earth & Atmospheric SciencesUniversity of HoustonHoustonTXUSA
| | - Ellen Creecy
- Department of Earth & Atmospheric SciencesUniversity of HoustonHoustonTXUSA
| | - Sally Newman
- Bay Area Air Quality Management DistrictSan FranciscoCAUSA
| | - King‐Fai Li
- Department of Environmental SciencesUniversity of CaliforniaRiversideCAUSA
| | | | - Yuk L. Yung
- Division of Geological and Planetary Sciences, California Institute of TechnologyPasadenaCAUSA
- Jet Propulsion LaboratoryPasadenaCAUSA
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Zhang Z, Ju W, Zhou Y. The effect of water stress on net primary productivity in northwest China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:65885-65898. [PMID: 34327647 DOI: 10.1007/s11356-021-15314-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 07/01/2021] [Indexed: 06/13/2023]
Abstract
Net primary productivity (NPP) has been widely used as the indicator of vegetation function and exhibits large spatial and temporal variations caused by numerous factors. Northwest China (NWC) is one of the driest regions in China, and water supply is the key determinant of NPP here. However, studies on the effects of water stress on NPP in NWC at the regional scale are still relatively lacking. Thus, in this study, based on a set of Moderate-Resolution Imaging Spectroradiometer (MODIS) NPP and evapotranspiration (ET) datasets, we quantified the response of NPP to water stress, which is indicated by crop water stress index (CWSI). Regional average of annual NPP in NWC showed an increasing trend during the study period, at a rate of 0.84 g C m-2 yr-1. At the province level, the NPP increase rates increased in the order of Ningxia (7.7%), Shaanxi (6.5%), Gansu (4.5%), Qinghai (3.8%), and Xinjiang (1.7%). NPP was negatively correlated with CWSI (p<0.05) in 73% of areas, indicating the key role of water stress in constraining NPP over this arid region. The effect of water stress on NPP changes with elevation. Water stress has the strongest negative impact on NPP in areas with elevations around 2000 m. In elevations above 5000 m, NPP is not limited by water stress, mostly positively correlated with CWSI. Our findings further clarify the importance of water stress in dryland ecosystems, while highlighting that elevation gradients can significantly affect the correlation between NPP and water stress.
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Affiliation(s)
- Zhenyu Zhang
- International Institute of Earth System Science, Nanjing University, Nanjing, 210023, China
- School of Geography and Ocean Science, Nanjing University, Nanjing, 210023, China
- State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, Zhejiang, 311300, Hangzhou, China
| | - Weimin Ju
- International Institute of Earth System Science, Nanjing University, Nanjing, 210023, China.
| | - Yanlian Zhou
- School of Geography and Ocean Science, Nanjing University, Nanjing, 210023, China
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Yang X, Wu J, Chen X, Ciais P, Maignan F, Yuan W, Piao S, Yang S, Gong F, Su Y, Dai Y, Liu L, Zhang H, Bonal D, Liu H, Chen G, Lu H, Wu S, Fan L, Gentine P, Wright SJ. A comprehensive framework for seasonal controls of leaf abscission and productivity in evergreen broadleaved tropical and subtropical forests. Innovation (N Y) 2021; 2:100154. [PMID: 34901903 PMCID: PMC8640595 DOI: 10.1016/j.xinn.2021.100154] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 08/18/2021] [Indexed: 11/16/2022] Open
Abstract
Relationships among productivity, leaf phenology, and seasonal variation in moisture and light availability are poorly understood for evergreen broadleaved tropical/subtropical forests, which contribute 25% of terrestrial productivity. On the one hand, as moisture availability declines, trees shed leaves to reduce transpiration and the risk of hydraulic failure. On the other hand, increases in light availability promote the replacement of senescent leaves to increase productivity. Here, we provide a comprehensive framework that relates the seasonality of climate, leaf abscission, and leaf productivity across the evergreen broadleaved tropical/subtropical forest biome. The seasonal correlation between rainfall and light availability varies from strongly negative to strongly positive across the tropics and maps onto the seasonal correlation between litterfall mass and productivity for 68 forests. Where rainfall and light covary positively, litterfall and productivity also covary positively and are always greater in the wetter sunnier season. Where rainfall and light covary negatively, litterfall and productivity are always greater in the drier and sunnier season if moisture supplies remain adequate; otherwise productivity is smaller in the drier sunnier season. This framework will improve the representation of tropical/subtropical forests in Earth system models and suggests how phenology and productivity will change as climate change alters the seasonality of cloud cover and rainfall across tropical/subtropical forests. Three climate-phenology regimes are identified across tropical and subtropical forest biomes Where light and water limit plant in dry season, litterfall and productivity peak in sunny wet season Where light or water alternately limits plant, productivity peaks in wet season with low litterfall Where water does not limit plant, litterfall and productivity peak in sunny dry season
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Affiliation(s)
- Xueqin Yang
- Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University & Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China.,Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China
| | - Jianping Wu
- Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China
| | - Xiuzhi Chen
- Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University & Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif sur Yvette, France
| | - Fabienne Maignan
- Laboratoire des Sciences du Climat et de l'Environnement, IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif sur Yvette, France
| | - Wenping Yuan
- Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University & Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
| | - Shilong Piao
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Song Yang
- Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University & Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
| | - Fanxi Gong
- Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University & Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China.,Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China.,College of Earth Sciences, Chengdu University of Technology, Chengdu 610000, China
| | - Yongxian Su
- Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China
| | - Yuhang Dai
- Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University & Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China.,Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China.,College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510000, China
| | - Liyang Liu
- Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University & Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China.,Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China.,Laboratoire des Sciences du Climat et de l'Environnement, IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif sur Yvette, France
| | - Haicheng Zhang
- Department of Geoscience, Environment & Society, Université Libre de Bruxelles, Bruxelles, Belgium
| | - Damien Bonal
- INRA, UMR " Ecologie et Ecophysiologie Forestières", Université de Lorraine-INRA, 54280 Champenoux, France
| | - Hui Liu
- South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510650, China
| | - Guixing Chen
- Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University & Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
| | - Haibo Lu
- Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University & Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
| | - Shengbiao Wu
- School of Biological Sciences, The University of Hong Kong, Pokfulam, Hong Kong
| | - Lei Fan
- Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China
| | - Pierre Gentine
- Department of Earth & Environmental Engineering, Columbia University, New York, NY 10027, USA
| | - S Joseph Wright
- Smithsonian Tropical Research Institute, Apartado 0843-03092, Balboa, Panama
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Ecosystem Productivity and Evapotranspiration Are Tightly Coupled in Loblolly Pine (Pinus taeda L.) Plantations along the Coastal Plain of the Southeastern U.S. FORESTS 2021. [DOI: 10.3390/f12081123] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Forest water use efficiency (WUE), the ratio of gross primary productivity (GPP) to evapotranspiration (ET), is an important variable to understand the coupling between water and carbon cycles, and to assess resource use, ecosystem resilience, and commodity production. Here, we determined WUE for managed loblolly pine plantations over the course of a rotation on the coastal plain of North Carolina in the eastern U.S. We found that the forest annual GPP, ET, and WUE increased until age ten, which stabilized thereafter. WUE varied annually (2–44%), being higher at young plantation (YP, 3.12 ± 1.20 g C kg−1 H2O d−1) compared to a mature plantation (MP, 2.92 ± 0.45 g C kg−1 H2O d−1), with no distinct seasonal patterns. Stand age was strongly correlated with ET (R2 = 0.71) and GPP (R2 = 0.64). ET and GPP were tightly coupled (R2 = 0.86). Radiation and air temperature significantly affected GPP and ET (R2 = 0.71 − R2 = 0.82) at a monthly scale, but not WUE. Drought affected WUE (R2 = 0.35) more than ET (R2 = 0.25) or GPP (R2 = 0.07). A drought enhanced GPP in MP (19%) and YP (11%), but reduced ET 7% and 19% in MP and YP, respectively, resulting in a higher WUE (27–32%). Minor seasonal and interannual variation in forest WUE of MP (age > 10) suggested that forest functioning became stable as stands matured. We conclude that carbon and water cycles in loblolly pine plantations are tightly coupled, with different characteristics in different ages and hydrologic regimes. A stable WUE suggests that the pine ecosystem productivity can be readily predicted from ET and vice versa. The tradeoffs between water and carbon cycling should be recognized in forest management to achieve multiple ecosystem services (i.e., water supply and carbon sequestration).
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Hikosaka K. Photosynthesis, chlorophyll fluorescence and photochemical reflectance index in photoinhibited leaves. FUNCTIONAL PLANT BIOLOGY : FPB 2021; 48:815-826. [PMID: 33832552 DOI: 10.1071/fp20365] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Accepted: 03/10/2021] [Indexed: 05/03/2023]
Abstract
Solar-induced chlorophyll (chl) fluorescence (SIF) has been shown to be positively correlated with vegetation photosynthesis, suggesting that it is a useful signal for understanding of environmental responses and spatial heterogeneity of photosynthetic activity at various scales from leaf to the globe. Photosynthesis is often inhibited in stressful environments (photoinhibition), but how photoinhibition influences the relationship between photosynthesis and chl fluorescence remains unclear. Here, I studied light energy allocation among photosynthesis, chl fluorescence and heat dissipation in photoinhibited leaves and tested whether photosynthesis in photoinhibited leaves can be evaluated from chl fluorescence and reflectance spectra in remote sensing. Chl fluorescence and reflection spectra were examined with the pulse amplified modulation (PAM) system and spectroradiometer, respectively. Photoinhibited leaves had lower photosynthetic rates and quantum yields of photochemistry (ΦP) and higher chl fluorescence yields. Consequently, photosynthesis was negatively correlated with chl fluorescence, which contrasts the positive relationships between photosynthesis and SIF observed in past remote sensing studies. This suggests that vegetation photosynthesis evaluated solely from chl fluorescence may be overestimated if the vegetation is dominated by severely photoinhibited leaves. When a model of energy allocation was applied, ΦP estimated from chl fluorescence and photochemical reflectance index (PRI) significantly correlated with the observed ΦP, suggesting that the model is useful to evaluate photosynthetic activities of photoinhibited leaves by remote sensing.
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Affiliation(s)
- Kouki Hikosaka
- Graduate School of Life Sciences, Tohoku University, Aoba, Sendai 980-8578, Japan
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18
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Noda HM, Muraoka H, Nasahara KN. Plant ecophysiological processes in spectral profiles: perspective from a deciduous broadleaf forest. JOURNAL OF PLANT RESEARCH 2021; 134:737-751. [PMID: 33970379 PMCID: PMC8245376 DOI: 10.1007/s10265-021-01302-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Accepted: 04/09/2021] [Indexed: 06/12/2023]
Abstract
The need for progress in satellite remote sensing of terrestrial ecosystems is intensifying under climate change. Further progress in Earth observations of photosynthetic activity and primary production from local to global scales is fundamental to the analysis of the current status and changes in the photosynthetic productivity of terrestrial ecosystems. In this paper, we review plant ecophysiological processes affecting optical properties of the forest canopy which can be measured with optical remote sensing by Earth-observation satellites. Spectral reflectance measured by optical remote sensing is utilized to estimate the temporal and spatial variations in the canopy structure and primary productivity. Optical information reflects the physical characteristics of the targeted vegetation; to use this information efficiently, mechanistic understanding of the basic consequences of plant ecophysiological and optical properties is essential over broad scales, from single leaf to canopy and landscape. In theory, canopy spectral reflectance is regulated by leaf optical properties (reflectance and transmittance spectra) and canopy structure (geometrical distributions of leaf area and angle). In a deciduous broadleaf forest, our measurements and modeling analysis of leaf-level characteristics showed that seasonal changes in chlorophyll content and mesophyll structure of deciduous tree species lead to a seasonal change in leaf optical properties. The canopy reflectance spectrum of the deciduous forest also changes with season. In particular, canopy reflectance in the green region showed a unique pattern in the early growing season: green reflectance increased rapidly after leaf emergence and decreased rapidly after canopy closure. Our model simulation showed that the seasonal change in the leaf optical properties and leaf area index caused this pattern. Based on this understanding we discuss how we can gain ecophysiological information from satellite images at the landscape level. Finally, we discuss the challenges and opportunities of ecophysiological remote sensing by satellites.
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Affiliation(s)
- Hibiki M Noda
- Earth System Division, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki, 305-8506, Japan.
| | - Hiroyuki Muraoka
- River Basin Research Center, Gifu University, 1-1 Yanagido, Gifu, 501-1193, Japan
| | - Kenlo Nishida Nasahara
- Faculty of Life and Environment Sciences, University of Tsukuba, 1-1-1 Tennohdai, Tsukuba, Ibaraki, 305-8572, Japan
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Liu Y, Dang C, Yue H, Lyu C, Dang X. Enhanced drought detection and monitoring using sun-induced chlorophyll fluorescence over Hulun Buir Grassland, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 770:145271. [PMID: 33513493 DOI: 10.1016/j.scitotenv.2021.145271] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2020] [Revised: 01/05/2021] [Accepted: 01/15/2021] [Indexed: 06/12/2023]
Abstract
Drought is one of the most damaging events in the grassland ecosystem. The detection and monitoring of drought are very important to maintain the balance of the grassland ecosystem. The potential of Sun-induced Chlorophyll Fluorescence (SIF) for drought detection and monitoring were explored in this study. Based on significant negative anomalies of self-calibrating Palmer drought severity index (scPDSI), precipitation (PPT), soil moisture (SM),surface water storage (SWS), and a significant positive anomaly of land surface temperature (LST), a severe drought event was accurately detected from June to August in 2016 over Hulun Buir Grassland. The far-red SIF was decomposed into its mechanical parts such as SIF, absorbed photosynthetically active radiation (APAR), normalized by APAR (SIFyield), physiological SIF emission yield (SIFpey), and total emitted SIF (SIFte), which were more sensitive to drought than the vegetation indices (VIs), including normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), modified soil adjusted vegetation index (MSAVI2), and near-infrared reflectance of vegetation (NIRV). SIF and NIRV represented the SIF indicators and the VIs, respectively, which were most affected by drought, with a decrease of -2.67% and 4.19% in June, 50.93% and 31.76% in July, and 55.58% and 39.44% in August. The correlations between anomalies of SIF indicators, VIs, and anomalies of LST, wind speed (WS) were a strong negative correlation, indicating that their reduction was caused by the anomalies of LST and WS. Moreover, the SIF indicators had a shorter lag time in response to meteorological drought than VIs. Besides, the correlations between SIF-based drought indices such as drought fluorescence monitoring index (DFMI), SIF health index (SHI), and SM were - 0.709 and - 0.783 (P < 0.01), respectively, higher than the conventional drought indices. Moreover, DFMI and SHI could reflect the changes of SM in advance, while the conventional drought indices mostly lagged behind the changes of SM. This study shows that SIF can enhance drought detection, and the SIF-based drought index can be well suitable for drought monitoring.
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Affiliation(s)
- Ying Liu
- College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China
| | - Chaoya Dang
- College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China
| | - Hui Yue
- College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China.
| | - Chunguang Lyu
- Shandong Provincial Key Laboratory of Water and Soil Conservation and Environmental Protection, College of Resources and Environment, Linyi University, Linyi 276005, China
| | - Xuehui Dang
- First Crust Monitoring and Application Center, China Earthquake Administration, Tianjin 300000, China
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20
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Capturing the Impact of the 2018 European Drought and Heat across Different Vegetation Types Using OCO-2 Solar-Induced Fluorescence. REMOTE SENSING 2020. [DOI: 10.3390/rs12193249] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
The European heatwave of 2018 led to record-breaking temperatures and extremely dry conditions in many parts of the continent, resulting in widespread decrease in agricultural yield, early tree-leaf senescence, and increase in forest fires in Northern Europe. Our study aims to capture the impact of the 2018 European heatwave on the terrestrial ecosystem through the lens of a high-resolution solar-induced fluorescence (SIF) data acquired from the Orbiting Carbon Observatory-2 (OCO-2) satellite. SIF is proposed to be a direct proxy for gross primary productivity (GPP) and thus can be used to draw inferences about changes in photosynthetic activity in vegetation due to extreme events. We explore spatial and temporal SIF variation and anomaly in the spring and summer months across different vegetation types (agriculture, broadleaved forest, coniferous forest, and mixed forest) during the European heatwave of 2018 and compare it to non-drought conditions (most of Southern Europe). About one-third of Europe’s land area experienced a consecutive spring and summer drought in 2018. Comparing 2018 to mean conditions (i.e., those in 2015–2017), we found a change in the intra-spring season SIF dynamics for all vegetation types, with lower SIF during the start of spring, followed by an increase in fluorescence from mid-April. Summer, however, showed a significant decrease in SIF. Our results show that particularly agricultural areas were severely affected by the hotter drought of 2018. Furthermore, the intense heat wave in Central Europe showed about a 31% decrease in SIF values during July and August as compared to the mean over the previous three years. Furthermore, our MODIS (Moderate Resolution Imaging Spectroradiometer) and OCO-2 comparative results indicate that especially for coniferous and mixed forests, OCO-2 SIF has a quicker response and a possible higher sensitivity to drought in comparison to MODIS’s fPAR (fraction of absorbed photosynthetically active radiation) and the Normalized Difference Vegetation Index (NDVI) when considering shorter reference periods, which highlights the added value of remotely sensed solar-induced fluorescence for studying the impact of drought on vegetation.
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21
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Zhuang J, Wang Y, Chi Y, Zhou L, Chen J, Zhou W, Song J, Zhao N, Ding J. Drought stress strengthens the link between chlorophyll fluorescence parameters and photosynthetic traits. PeerJ 2020; 8:e10046. [PMID: 33024649 PMCID: PMC7520092 DOI: 10.7717/peerj.10046] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Accepted: 09/04/2020] [Indexed: 01/13/2023] Open
Abstract
Chlorophyll fluorescence (ChlF) has been used to understand photosynthesis and its response to climate change, particularly with satellite-based data. However, it remains unclear how the ChlF ratio and photosynthesis are linked at the leaf level under drought stress. Here, we examined the link between ChlF ratio and photosynthesis at the leaf level by measuring photosynthetic traits, such as net CO2 assimilation rate (An), the maximum carboxylation rate of Rubisco (Vcmax), the maximum rate of electron transport (Jmax), stomatal conductance (gs) and total chlorophyll content (Chlt). The ChlF ratio of the leaf level such as maximum quantum efficiency of PSII (Fv/Fm) is based on fluorescence kinetics. ChlF intensity ratio (LD685/LD740) based on spectrum analysis was obtained. We found that a combination of the stomatal limitation, non-stomatal limitation, and Chlt regulated leaf photosynthesis under drought stress, while Jmax and Chlt governed the ChlF ratio. A significant link between the ChlF ratio and An was found under drought stress while no significant correlation in the control, which indicated that drought stress strengthens the link between the ChlF ratio and photosynthetic traits. These results suggest that the ChlF ratio can be a powerful tool to track photosynthetic traits of terrestrial ecosystems under drought stress.
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Affiliation(s)
- Jie Zhuang
- College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua, Zhejiang, China
| | - Yonglin Wang
- College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua, Zhejiang, China
| | - Yonggang Chi
- College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua, Zhejiang, China
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Lei Zhou
- College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua, Zhejiang, China
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Jijing Chen
- College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua, Zhejiang, China
| | - Wen Zhou
- College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua, Zhejiang, China
| | - Jun Song
- College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua, Zhejiang, China
| | - Ning Zhao
- College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua, Zhejiang, China
| | - Jianxi Ding
- College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua, Zhejiang, China
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22
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Pinto F, Celesti M, Acebron K, Alberti G, Cogliati S, Colombo R, Juszczak R, Matsubara S, Miglietta F, Palombo A, Panigada C, Pignatti S, Rossini M, Sakowska K, Schickling A, Schüttemeyer D, Stróżecki M, Tudoroiu M, Rascher U. Dynamics of sun-induced chlorophyll fluorescence and reflectance to detect stress-induced variations in canopy photosynthesis. PLANT, CELL & ENVIRONMENT 2020; 43:1637-1654. [PMID: 32167577 DOI: 10.1111/pce.13754] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/11/2018] [Revised: 02/14/2020] [Accepted: 02/17/2020] [Indexed: 05/24/2023]
Abstract
Passive measurement of sun-induced chlorophyll fluorescence (F) represents the most promising tool to quantify changes in photosynthetic functioning on a large scale. However, the complex relationship between this signal and other photosynthesis-related processes restricts its interpretation under stress conditions. To address this issue, we conducted a field campaign by combining daily airborne and ground-based measurements of F (normalized to photosynthetically active radiation), reflectance and surface temperature and related the observed changes to stress-induced variations in photosynthesis. A lawn carpet was sprayed with different doses of the herbicide Dicuran. Canopy-level measurements of gross primary productivity indicated dosage-dependent inhibition of photosynthesis by the herbicide. Dosage-dependent changes in normalized F were also detected. After spraying, we first observed a rapid increase in normalized F and in the Photochemical Reflectance Index, possibly due to the blockage of electron transport by Dicuran and the resultant impairment of xanthophyll-mediated non-photochemical quenching. This initial increase was followed by a gradual decrease in both signals, which coincided with a decline in pigment-related reflectance indices. In parallel, we also detected a canopy temperature increase after the treatment. These results demonstrate the potential of using F coupled with relevant reflectance indices to estimate stress-induced changes in canopy photosynthesis.
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Affiliation(s)
- Francisco Pinto
- Institute of Bio and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, Jülich, Germany
| | - Marco Celesti
- Remote Sensing of Environmental Dynamics Laboratory, Department of Earth and Environmental Sciences (DISAT), University of Milano-Bicocca, Milan, Italy
| | - Kelvin Acebron
- Institute of Bio and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, Jülich, Germany
| | - Giorgio Alberti
- Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, Udine, Italy
- Institute of BioEconomy (IBE), National Research Council (CNR), Rome, Italy
| | - Sergio Cogliati
- Remote Sensing of Environmental Dynamics Laboratory, Department of Earth and Environmental Sciences (DISAT), University of Milano-Bicocca, Milan, Italy
| | - Roberto Colombo
- Remote Sensing of Environmental Dynamics Laboratory, Department of Earth and Environmental Sciences (DISAT), University of Milano-Bicocca, Milan, Italy
| | - Radosław Juszczak
- Meteorology Department, Poznan University of Life Sciences, Poznań, Poland
| | - Shizue Matsubara
- Institute of Bio and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, Jülich, Germany
| | - Franco Miglietta
- Institute of BioEconomy (IBE), National Research Council (CNR), Rome, Italy
- FoxLab Joint CNR-FEM Initiative, San Michele all'Adige, Italy
| | - Angelo Palombo
- Institute of Methodologies for Environmental Analysis (IMAA), National Research Council (CNR), Rome, Italy
| | - Cinzia Panigada
- Remote Sensing of Environmental Dynamics Laboratory, Department of Earth and Environmental Sciences (DISAT), University of Milano-Bicocca, Milan, Italy
| | - Stefano Pignatti
- Institute of Methodologies for Environmental Analysis (IMAA), National Research Council (CNR), Rome, Italy
| | - Micol Rossini
- Remote Sensing of Environmental Dynamics Laboratory, Department of Earth and Environmental Sciences (DISAT), University of Milano-Bicocca, Milan, Italy
| | - Karolina Sakowska
- Institute of BioEconomy (IBE), National Research Council (CNR), Rome, Italy
- Sustainable Agro-Ecosystems and Bioresources Department, Research and Innovation Centre-Fondazione Edmund Mach, San Michele all'Adige (TN), Italy
- University of Innsbruck, Institute of Ecology, Innsbruck, Austria
| | - Anke Schickling
- Institute of Bio and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, Jülich, Germany
| | | | - Marcin Stróżecki
- Meteorology Department, Poznan University of Life Sciences, Poznań, Poland
| | - Marin Tudoroiu
- Institute of BioEconomy (IBE), National Research Council (CNR), Rome, Italy
- European Space Agency (ESA), ESTEC, Noordwijk, The Netherlands
- University of Natural Resources and Life Sciences, Vienna, Austria
| | - Uwe Rascher
- Institute of Bio and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, Jülich, Germany
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23
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OCO-2 Solar-Induced Chlorophyll Fluorescence Variability across Ecoregions of the Amazon Basin and the Extreme Drought Effects of El Niño (2015–2016). REMOTE SENSING 2020. [DOI: 10.3390/rs12071202] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Amazonian ecosystems are major biodiversity hotspots and carbon sinks that may lose species to extinction and become carbon sources due to extreme dry or warm conditions. We investigated the seasonal patterns of high-resolution solar-induced chlorophyll fluorescence (SIF) measured by the satellite Orbiting Carbon Observatory-2 (OCO-2) across the Amazonian ecoregions to assess the area´s phenology and extreme drought vulnerability. SIF is an indicator of the photosynthetic activity of chlorophyll molecules and is assumed to be directly related to gross primary production (GPP). We analyzed SIF variability in the Amazon basin during the period between September 2014 and December 2018. In particular, we focused on the SIF drought response under the extreme drought period during the strong El Niño in 2015–2016, as well as the 6-month drought peak period. During the drought´s peak months, the SIF decreased and increased with different intensities across the ecoregions of the Amazonian moist broadleaf forest (MBF) biome. Under a high temperature, a high vapor pressure deficit, and extreme drought conditions, the SIF presented differences from −31.1% to +17.6%. Such chlorophyll activity variations have been observed in plant-level measurements of active fluorescence in plants undergoing physiological responses to water or heat stress. Thus, it is plausible that the SIF variations in the ecoregions’ ecosystems occurred as a result of water and heat stress, and arguably because of drought-driven vegetation mortality and collateral effects in their species composition and community structures. The SIF responses to drought at the ecoregional scale indicate that there are different levels of resilience to drought across MBF ecosystems that the currently used climate- and biome-region scales do not capture. Finally, we identified monthly SIF values of 32 ecoregions, including non-MBF biomes, which may give the first insights into the photosynthetic activity dynamics of Amazonian ecoregions.
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24
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Feasibility of Using MODIS Products to Simulate Sun-Induced Chlorophyll Fluorescence (SIF) in Boreal Forests. REMOTE SENSING 2020. [DOI: 10.3390/rs12040680] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Solar-induced chlorophyll fluorescence (SIF) is a novel approach to gain information about plant activity from remote sensing observations. However, there are currently no continuous SIF data produced at high spatial resolutions. Many previous studies have discussed the relationship between SIF and gross primary production (GPP) and showed a significant correlation between them, but few researchers have focused on forests, which are one the most important terrestrial ecosystems. This study takes Greater Khingan Mountains, a typical boreal forest in China, as an example to explore the feasibility of using MODerate resolution Imaging Spectroradiometer (MODIS) products and Orbiting Carbon Observatory-2 (OCO-2) SIF data to simulate continuous SIF at higher spatial resolutions. The results show that there is no significant correlation between SIF and MODIS GPP at a spatial resolution of 1 km; however, significant correlations between SIF and the enhanced vegetation index (EVI) were found during growing seasons. Furthermore, the broadleaf forest has a higher SIF than coniferous forest because of the difference in leaf and canopy bio-chemical and structural characteristic. When using MODIS EVI to model SIF, linear regression models show average performance (R2 = 0.58, Root Mean Squared Error (RMSE) = 0.14 from Julian day 145 to 257) at a 16-day time scale. However, when using MODIS EVI and temperature, multiple regressions perform better (R2 = 0.71, RMSE = 0.13 from Julian day 145 to 241). An important contribution of this paper is the analysis of the relationships between SIF and vegetation indices at different spatial resolutions and the finding that the relationships became closer with a decrease in spatial resolution. From this research, we conclude that the SIF of the boreal forest investigated can mainly be explained by EVI and air temperature.
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25
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Bandopadhyay S, Rastogi A, Juszczak R. Review of Top-of-Canopy Sun-Induced Fluorescence (SIF) Studies from Ground, UAV, Airborne to Spaceborne Observations. SENSORS (BASEL, SWITZERLAND) 2020; 20:E1144. [PMID: 32093068 PMCID: PMC7070282 DOI: 10.3390/s20041144] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/18/2020] [Revised: 02/10/2020] [Accepted: 02/14/2020] [Indexed: 11/16/2022]
Abstract
Remote sensing (RS) of sun-induced fluorescence (SIF) has emerged as a promising indicator of photosynthetic activity and related stress from the leaf to the ecosystem level. The implementation of modern RS technology on SIF is highly motivated by the direct link of SIF to the core of photosynthetic machinery. In the last few decades, a lot of studies have been conducted on SIF measurement techniques, retrieval algorithms, modeling, application, validation, and radiative transfer processes, incorporating different RS observations (i.e., ground, unmanned aerial vehicle (UAV), airborne, and spaceborne). These studies have made a significant contribution to the enrichment of SIF science over time. However, to realize the potential of SIF and to explore its full spectrum using different RS observations, a complete document of existing SIF studies is needed. Considering this gap, we have performed a detailed review of current SIF studies from the ground, UAV, airborne, and spaceborne observations. In this review, we have discussed the in-depth interpretation of each SIF study using four RS platforms. The limitations and challenges of SIF studies have also been discussed to motivate future research and subsequently overcome them. This detailed review of SIF studies will help, support, and inspire the researchers and application-based users to consider SIF science with confidence.
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Affiliation(s)
- Subhajit Bandopadhyay
- Laboratory of Bioclimatology, Department of Ecology and Environmental Protection, Faculty of Environmental Engineering and Spatial Management, Poznan University of Life Sciences, 60-649 Poznan, Poland;
| | | | - Radosław Juszczak
- Laboratory of Bioclimatology, Department of Ecology and Environmental Protection, Faculty of Environmental Engineering and Spatial Management, Poznan University of Life Sciences, 60-649 Poznan, Poland;
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26
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Wang X, Qiu B, Li W, Zhang Q. Impacts of drought and heatwave on the terrestrial ecosystem in China as revealed by satellite solar-induced chlorophyll fluorescence. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 693:133627. [PMID: 31377349 DOI: 10.1016/j.scitotenv.2019.133627] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2019] [Revised: 07/23/2019] [Accepted: 07/26/2019] [Indexed: 06/10/2023]
Abstract
Droughts and heatwaves have been and will continue to bring large risks to terrestrial ecosystems. However, the understanding of how plants respond to drought and heatwave over broad spatial scales is still limited. In this paper, we use the 2009/2010 drought in Yunnan and the 2013 heatwave over southern China as case studies to investigate the potential of using satellite-observed solar-induced chlorophyll fluorescence (SIF) to monitor vegetation responses to drought and heatwave over broad spatial scales. The 2009/2010 drought onset follows a strong soil moisture deficit due to the yearlong below-normal precipitation in Yunnan from the autumn of 2009 to the spring of 2010. In the summer of 2013, southern China experienced the strongest heatwave due to the sudden temperature increase and rainfall deficit. The results show that SIF can reasonably capture the spatial and temporal dynamics of drought and heatwave development, as indicated by the large reduction in fluorescence yield (SIFyield). Moreover, SIFyield demonstrates a significant reduction and earlier response than traditional vegetation indices (enhanced vegetation index, EVI) during the early stages of drought and heatwave events. For both study areas, the spatial and temporal correlation analysis demonstrates that the SIFyield anomalies are more sensitive to a high vapor pressure deficit (VPD) than low soil moisture. This study implies that satellite observations of SIF have great potential for accurate and timely monitoring of drought and heatwave developments.
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Affiliation(s)
- Xiaorong Wang
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Sciences, Nanjing University, Nanjing, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China
| | - Bo Qiu
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Sciences, Nanjing University, Nanjing, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China.
| | - Wenkai Li
- Key Laboratory of Meteorological Disaster, Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, China
| | - Qian Zhang
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Sciences, Nanjing University, Nanjing, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China
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27
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Albert LP, Restrepo-Coupe N, Smith MN, Wu J, Chavana-Bryant C, Prohaska N, Taylor TC, Martins GA, Ciais P, Mao J, Arain MA, Li W, Shi X, Ricciuto DM, Huxman TE, McMahon SM, Saleska SR. Cryptic phenology in plants: Case studies, implications, and recommendations. GLOBAL CHANGE BIOLOGY 2019; 25:3591-3608. [PMID: 31343099 DOI: 10.1111/gcb.14759] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2018] [Revised: 06/13/2019] [Accepted: 06/16/2019] [Indexed: 06/10/2023]
Abstract
Plant phenology-the timing of cyclic or recurrent biological events in plants-offers insight into the ecology, evolution, and seasonality of plant-mediated ecosystem processes. Traditionally studied phenologies are readily apparent, such as flowering events, germination timing, and season-initiating budbreak. However, a broad range of phenologies that are fundamental to the ecology and evolution of plants, and to global biogeochemical cycles and climate change predictions, have been neglected because they are "cryptic"-that is, hidden from view (e.g., root production) or difficult to distinguish and interpret based on common measurements at typical scales of examination (e.g., leaf turnover in evergreen forests). We illustrate how capturing cryptic phenology can advance scientific understanding with two case studies: wood phenology in a deciduous forest of the northeastern USA and leaf phenology in tropical evergreen forests of Amazonia. Drawing on these case studies and other literature, we argue that conceptualizing and characterizing cryptic plant phenology is needed for understanding and accurate prediction at many scales from organisms to ecosystems. We recommend avenues of empirical and modeling research to accelerate discovery of cryptic phenological patterns, to understand their causes and consequences, and to represent these processes in terrestrial biosphere models.
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Affiliation(s)
- Loren P Albert
- Department of Ecology and Evolutionary Biology, The University of Arizona, Tucson, AZ, USA
- Institute at Brown for Environment and Society, Brown University, Providence, RI, USA
| | - Natalia Restrepo-Coupe
- Department of Ecology and Evolutionary Biology, The University of Arizona, Tucson, AZ, USA
- School of Life Science, University of Technology Sydney, Ultimo, NSW, Australia
| | - Marielle N Smith
- Department of Ecology and Evolutionary Biology, The University of Arizona, Tucson, AZ, USA
| | - Jin Wu
- Biological, Environmental & Climate Sciences Department, Brookhaven National Laboratory, New York, NY, USA
- School of Biological Sciences, The University of Hong Kong, Pokfulam, Hong Kong
| | - Cecilia Chavana-Bryant
- Environmental Change Institute, School of Geography and the Environment, University of Oxford, Oxford, UK
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- Department of Environmental Science, Policy and Management, UC Berkeley, Berkeley, CA, USA
| | - Neill Prohaska
- Department of Ecology and Evolutionary Biology, The University of Arizona, Tucson, AZ, USA
| | - Tyeen C Taylor
- Department of Ecology and Evolutionary Biology, The University of Arizona, Tucson, AZ, USA
| | - Giordane A Martins
- Ciências de Florestas Tropicais, Instituto Nacional de Pesquisas da Amazônia (INPA), Manaus, Brazil
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, Institut Pierre Simon Laplace, Gif sur Yvette, France
| | - Jiafu Mao
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - M Altaf Arain
- School of Geography and Earth Sciences & McMaster Centre for Climate Change, McMaster University, Hamilton, ON, Canada
| | - Wei Li
- Laboratoire des Sciences du Climat et de l'Environnement, Institut Pierre Simon Laplace, Gif sur Yvette, France
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Tsinghua University, Beijing, China
| | - Xiaoying Shi
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Daniel M Ricciuto
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Travis E Huxman
- Ecology and Evolutionary Biology & Center for Environmental Biology, University of California, Irvine, CA, USA
| | - Sean M McMahon
- Smithsonian Institution's Forest Global Earth Observatory & Smithsonian Environmental Research Center, Edgewater, MD, USA
| | - Scott R Saleska
- Department of Ecology and Evolutionary Biology, The University of Arizona, Tucson, AZ, USA
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28
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Nitrogen and Phosphorus effect on Sun-Induced Fluorescence and Gross Primary Productivity in Mediterranean Grassland. REMOTE SENSING 2019. [DOI: 10.3390/rs11212562] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Sun-Induced fluorescence at 760 nm (F760) is increasingly being used to predict gross primary production (GPP) through light use efficiency (LUE) modeling, even though the mechanistic processes that link the two are not well understood. We analyzed the effect of nitrogen (N) and phosphorous (P) availability on the processes that link GPP and F760 in a Mediterranean grassland manipulated with nutrient addition. To do so, we used a combination of process-based modeling with Soil-Canopy Observation of Photosynthesis and Energy (SCOPE), and statistical analyses such as path modeling. With this study, we uncover the mechanisms that link the fertilization-driven changes in canopy nitrogen concentration (N%) to the observed changes in F760 and GPP. N addition changed plant community structure and increased canopy chlorophyll content, which jointly led to changes in photosynthetic active radiation (APAR), ultimately affecting both GPP and F760. Changes in the abundance of graminoids, (%graminoids) driven by N addition led to changes in structural properties of the canopy such as leaf angle distribution, that ultimately influenced observed F760 by controlling the escape probability of F760 (Fesc). In particular, we found a change in GPP–F760 relationship between the first and the second year of the experiment that was largely driven by the effect of plant type composition on Fesc, whose best predictor is %graminoids. The P addition led to a statistically significant increase on light use efficiency of fluorescence emission (LUEf), in particular in plots also with N addition, consistent with leaf level studies. The N addition induced changes in the biophysical properties of the canopy that led to a trade-off between surface temperature (Ts), which decreased, and F760 at leaf scale (F760leaf,fw), which increased. We found that Ts is an important predictor of the light use efficiency of photosynthesis, indicating the importance of Ts in LUE modeling approaches to predict GPP.
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29
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TROPOMI reveals dry-season increase of solar-induced chlorophyll fluorescence in the Amazon forest. Proc Natl Acad Sci U S A 2019; 116:22393-22398. [PMID: 31611384 DOI: 10.1073/pnas.1908157116] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Photosynthesis of the Amazon rainforest plays an important role in the regional and global carbon cycles, but, despite considerable in situ and space-based observations, it has been intensely debated whether there is a dry-season increase in greenness and photosynthesis of the moist tropical Amazonian forests. Solar-induced chlorophyll fluorescence (SIF), which is emitted by chlorophyll, has a strong positive linear relationship with photosynthesis at the canopy scale. Recent advancements have allowed us to observe SIF globally with Earth observation satellites. Here we show that forest SIF did not decrease in the early dry season and increased substantially in the late dry season and early part of wet season, using SIF data from the Tropospheric Monitoring Instrument (TROPOMI), which has unprecedented spatial resolution and near-daily global coverage. Using in situ CO2 eddy flux data, we also show that cloud cover rarely affects photosynthesis at TROPOMI's midday overpass, a time when the forest canopy is most often light-saturated. The observed dry-season increases of forest SIF are not strongly affected by sun-sensor geometry, which was attributed as creating a pseudo dry-season green-up in the surface reflectance data. Our results provide strong evidence that greenness, SIF, and photosynthesis of the tropical Amazonian forest increase during the dry season.
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30
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Schimel D, Schneider FD. Flux towers in the sky: global ecology from space. THE NEW PHYTOLOGIST 2019; 224:570-584. [PMID: 31112309 DOI: 10.1111/nph.15934] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2019] [Accepted: 04/29/2019] [Indexed: 05/25/2023]
Abstract
Global ecology - the study of the interactions among the Earth's ecosystems, land, atmosphere and oceans - depends crucially on global observations: this paper focuses on space-based observations of global terrestrial ecosystems. Early global ecology relied on an extrapolation of detailed site-level observations, using models of increasing complexity. Modern global ecology has been enabled largely by vegetation indices (greenness) from operational space-based imagery but current capabilities greatly expand scientific possibilities. New observations from spacecraft in orbit allowed an estimation of gross carbon fluxes, photosynthesis, biomass burning, evapotranspiration and biomass, to create virtual eddy covariance sites in the sky. Planned missions will reveal the dimensions of the diversity of life itself. These observations will improve our understanding of the global productivity and carbon storage, land use, carbon cycle-climate feedback, diversity-productivity relationships and enable improved climate forecasts. Advances in remote sensing challenge ecologists to relate information organised by biome and species to new data arrayed by pixels and develop theory to address previously unobserved scales.
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Affiliation(s)
- David Schimel
- Jet Propulsion Lab, California Institute of Technology, Pasadena, CA, 91101, USA
| | - Fabian D Schneider
- Jet Propulsion Lab, California Institute of Technology, Pasadena, CA, 91101, USA
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31
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Mohammed GH, Colombo R, Middleton EM, Rascher U, van der Tol C, Nedbal L, Goulas Y, Pérez-Priego O, Damm A, Meroni M, Joiner J, Cogliati S, Verhoef W, Malenovský Z, Gastellu-Etchegorry JP, Miller JR, Guanter L, Moreno J, Moya I, Berry JA, Frankenberg C, Zarco-Tejada PJ. Remote sensing of solar-induced chlorophyll fluorescence (SIF) in vegetation: 50 years of progress. REMOTE SENSING OF ENVIRONMENT 2019; 231:111177. [PMID: 33414568 PMCID: PMC7787158 DOI: 10.1016/j.rse.2019.04.030] [Citation(s) in RCA: 100] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Remote sensing of solar-induced chlorophyll fluorescence (SIF) is a rapidly advancing front in terrestrial vegetation science, with emerging capability in space-based methodologies and diverse application prospects. Although remote sensing of SIF - especially from space - is seen as a contemporary new specialty for terrestrial plants, it is founded upon a multi-decadal history of research, applications, and sensor developments in active and passive sensing of chlorophyll fluorescence. Current technical capabilities allow SIF to be measured across a range of biological, spatial, and temporal scales. As an optical signal, SIF may be assessed remotely using highly-resolved spectral sensors and state-of-the-art algorithms to distinguish the emission from reflected and/or scattered ambient light. Because the red to far-red SIF emission is detectable non-invasively, it may be sampled repeatedly to acquire spatio-temporally explicit information about photosynthetic light responses and steady-state behaviour in vegetation. Progress in this field is accelerating with innovative sensor developments, retrieval methods, and modelling advances. This review distills the historical and current developments spanning the last several decades. It highlights SIF heritage and complementarity within the broader field of fluorescence science, the maturation of physiological and radiative transfer modelling, SIF signal retrieval strategies, techniques for field and airborne sensing, advances in satellite-based systems, and applications of these capabilities in evaluation of photosynthesis and stress effects. Progress, challenges, and future directions are considered for this unique avenue of remote sensing.
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Affiliation(s)
| | - Roberto Colombo
- Remote Sensing of Environmental Dynamics Lab., University of Milano - Bicocca, Milan, Italy
| | | | - Uwe Rascher
- Forschungszentrum Jülich, Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Jülich, Germany
| | - Christiaan van der Tol
- University of Twente, Faculty of Geo-Information Science and Earth Observation, Enschede, The Netherlands
| | - Ladislav Nedbal
- Forschungszentrum Jülich, Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Jülich, Germany
| | - Yves Goulas
- CNRS, Laboratoire de Météorologie Dynamique (LMD), Ecole Polytechnique, Palaiseau, France
| | - Oscar Pérez-Priego
- Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Alexander Damm
- Department of Geography, University of Zurich, Zurich, Switzerland
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Duebendorf, Switzerland
| | - Michele Meroni
- European Commission, Joint Research Centre (JRC), Ispra (VA), Italy
| | - Joanna Joiner
- NASA/Goddard Space Flight Center, Greenbelt, Maryland, United States
| | - Sergio Cogliati
- Remote Sensing of Environmental Dynamics Lab., University of Milano - Bicocca, Milan, Italy
| | - Wouter Verhoef
- University of Twente, Faculty of Geo-Information Science and Earth Observation, Enschede, The Netherlands
| | - Zbyněk Malenovský
- Department of Geography and Spatial Sciences, School of Technology, Environments and Design, College of Sciences and Engineering, University of Tasmania, Hobart, Australia
| | | | - John R. Miller
- Department of Earth and Space Science and Engineering, York University, Toronto, Canada
| | - Luis Guanter
- German Research Center for Geosciences (GFZ), Remote Sensing Section, Potsdam, Germany
| | - Jose Moreno
- Department of Earth Physics and Thermodynamics, University of Valencia, Valencia, Spain
| | - Ismael Moya
- CNRS, Laboratoire de Météorologie Dynamique (LMD), Ecole Polytechnique, Palaiseau, France
| | - Joseph A. Berry
- Department of Global Ecology, Carnegie Institution of Washington, Stanford, California, United States
| | - Christian Frankenberg
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, United States
| | - Pablo J. Zarco-Tejada
- European Commission, Joint Research Centre (JRC), Ispra (VA), Italy
- Instituto de Agriculture Sostenible (IAS), Consejo Superior de Investigaciones Científicas (CSIC), Córdoba, Spain
- Department of Infrastructure Engineering, Melbourne School of Engineering, University of Melbourne, Melbourne, Victoria, Australia
- School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Melbourne, Victoria, Australia
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32
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The Impacts of Growth and Environmental Parameters on Solar-Induced Chlorophyll Fluorescence at Seasonal and Diurnal Scales. REMOTE SENSING 2019. [DOI: 10.3390/rs11172002] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Solar-induced chlorophyll fluorescence (SIF) is considered to be a potential indicator of photosynthesis. However, the impact of growth and environmental parameters on SIF at different time-scales remains unclear, which has greatly restricted the application of SIF in detecting photosynthesis variations. Thus, in this study, the impact of growth and environmental parameters on SIF was thoroughly clarified. Here, continuous time series of canopy SIF (760 nm, F760) over wheat and maize was measured based on an automated spectroscopy system. Meanwhile, field measurements of growth and environmental parameters were also collected using commercial-grade devices. Relationships of these parameters with F760, apparent SIF (F760/solar radiance, AF760), and SIF yield (F760/canopy radiance of 685 nm, Fy760) were analyzed using principal component analysis (PCA) and Pearson correlation to reveal their impacts on SIF. Results showed that F760 at seasonal and diurnal scales were mainly driven by solar radiation (SWR), leaf area index (LAI), chlorophyll content (Chl), mean leaf inclination angle (MTA), and relative water content (RWC). Other environmental parameters, including air temperature (Ta), relative humidity (Rh), vapor pressure deficit (VPD), and soil moisture (SM), contribute less to the variation of seasonal or diurnal F760. AF760 and Fy760 are likely to be less dependent on Ta, Rh, and VPD due to the removal of the impact from SWR, but an enhanced relationship of AF760 (and Fy760) with SM was observed, particularly under water stress. Compared with F760, wheat AF760 was better correlated to LAI and RWC as expected, while maize AF760 did not show an enhanced relationship with all growth parameters, probably due to its complicated canopy structure. The relationship of wheat Fy760 with canopy structure parameters was further reduced, except for maize measurements. Furthermore, SM-induced water stress and phenological stages should be taken into consideration when we interpret the seasonal and diurnal patterns of SIF since they were closely related to photosynthesis and plant growth (e.g., LAI in our study). To our knowledge, this is the first exploration of the impacts of growth and environmental parameters on SIF based on continuous ground measurements, not only at a seasonal scale but also at a diurnal scale. Our results could provide deep insight into the variation of SIF signals and also promote the further application of SIF in the health assessments of terrestrial ecosystems.
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Evaluating the Performance of Satellite-Derived Vegetation Indices for Estimating Gross Primary Productivity Using FLUXNET Observations across the Globe. REMOTE SENSING 2019. [DOI: 10.3390/rs11151823] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Satellite-derived vegetation indices (VIs) have been widely used to approximate or estimate gross primary productivity (GPP). However, it remains unclear how the VI-GPP relationship varies with indices, biomes, timescales, and the bidirectional reflectance distribution function (BRDF) effect. We examined the relationship between VIs and GPP for 121 FLUXNET sites across the globe and assessed how the VI-GPP relationship varied among a variety of biomes at both monthly and annual timescales. We used three widely-used VIs: normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and 2-band EVI (EVI2) as well as a new VI - NIRV and used surface reflectance both with and without BRDF correction from the moderate resolution imaging spectroradiometer (MODIS) to calculate these indices. The resulting traditional (NDVI, EVI, EVI2, and NIRV) and BRDF-corrected (NDVIBRDF, EVIBRDF, EVI2BRDF, and NIRV, BRDF) VIs were used to examine the VI-GPP relationship. At the monthly scale, all VIs were moderate or strong predictors of GPP, and the BRDF correction improved their performance. EVI2BRDF and NIRV, BRDF had similar performance in capturing the variations in tower GPP as did the MODIS GPP product. The VIs explained lower variance in tower GPP at the annual scale than at the monthly scale. The BRDF-correction of surface reflectance did not improve the VI-GPP relationship at the annual scale. The VIs had similar capability in capturing the interannual variability in tower GPP as MODIS GPP. VIs were influenced by temperature and water stresses and were more sensitive to temperature stress than to water stress. VIs in combination with environmental factors could improve the prediction of GPP than VIs alone. Our findings can help us better understand how the VI-GPP relationship varies among indices, biomes, and timescales and how the BRDF effect influences the VI-GPP relationship.
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Vrtílek M, Žák J, Polačik M, Blažek R, Reichard M. Rapid growth and large body size in annual fish populations are compromised by density-dependent regulation. JOURNAL OF FISH BIOLOGY 2019; 95:673-678. [PMID: 31102276 DOI: 10.1111/jfb.14052] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2019] [Accepted: 05/17/2019] [Indexed: 06/09/2023]
Abstract
We tested the effect of population density on maximum body size in three sympatric species of annual killifishes Nothobranchius spp. from African ephemeral pools. We found a clear negative effect of population density on body size, limiting their capacity for extremely fast development and rapid growth. This suggests that density-dependent population regulation and the ephemeral character of their habitat impose contrasting selective pressures on the life history of annual killifishes.
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Affiliation(s)
- Milan Vrtílek
- The Czech Academy of Sciences, Institute of Vertebrate Biology, Brno, Czech Republic
| | - Jakub Žák
- The Czech Academy of Sciences, Institute of Vertebrate Biology, Brno, Czech Republic
- Department of Zoology, Faculty of Sciences, Charles University, Praha, Czech Republic
| | - Matej Polačik
- The Czech Academy of Sciences, Institute of Vertebrate Biology, Brno, Czech Republic
| | - Radim Blažek
- The Czech Academy of Sciences, Institute of Vertebrate Biology, Brno, Czech Republic
| | - Martin Reichard
- The Czech Academy of Sciences, Institute of Vertebrate Biology, Brno, Czech Republic
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35
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Baker IT, Denning A, Dazlich DA, Harper AB, Branson MD, Randall DA, Phillips MC, Haynes KD, Gallup SM. Surface-Atmosphere Coupling Scale, the Fate of Water, and Ecophysiological Function in a Brazilian Forest. JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS 2019; 11:2523-2546. [PMID: 31749898 PMCID: PMC6851591 DOI: 10.1029/2019ms001650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/04/2019] [Revised: 05/10/2019] [Accepted: 07/16/2019] [Indexed: 06/10/2023]
Abstract
Tropical South America plays a central role in global climate. Bowen ratio teleconnects to circulation and precipitation processes far afield, and the global CO2 growth rate is strongly influenced by carbon cycle processes in South America. However, quantification of basin-wide seasonality of flux partitioning between latent and sensible heat, the response to anomalies around climatic norms, and understanding of the processes and mechanisms that control the carbon cycle remains elusive. Here, we investigate simulated surface-atmosphere interaction at a single site in Brazil, using models with different representations of precipitation and cloud processes, as well as differences in scale of coupling between the surface and atmosphere. We find that the model with parameterized clouds/precipitation has a tendency toward unrealistic perpetual light precipitation, while models with explicit treatment of clouds produce more intense and less frequent rain. Models that couple the surface to the atmosphere on the scale of kilometers, as opposed to tens or hundreds of kilometers, produce even more realistic distributions of rainfall. Rainfall intensity has direct consequences for the "fate of water," or the pathway that a hydrometeor follows once it interacts with the surface. We find that the model with explicit treatment of cloud processes, coupled to the surface at small scales, is the most realistic when compared to observations. These results have implications for simulations of global climate, as the use of models with explicit (as opposed to parameterized) cloud representations becomes more widespread.
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Affiliation(s)
- Ian T. Baker
- Atmospheric Science DepartmentColorado State UniversityFort CollinsCOUSA
| | - A.Scott Denning
- Atmospheric Science DepartmentColorado State UniversityFort CollinsCOUSA
| | - Don A. Dazlich
- Atmospheric Science DepartmentColorado State UniversityFort CollinsCOUSA
| | - Anna B. Harper
- College of Engineering, Mathematics, and Physical SciencesUniversity of ExeterExeterEngland
| | - Mark D. Branson
- Atmospheric Science DepartmentColorado State UniversityFort CollinsCOUSA
| | - David A. Randall
- Atmospheric Science DepartmentColorado State UniversityFort CollinsCOUSA
| | - Morgan C. Phillips
- Atmospheric Science DepartmentColorado State UniversityFort CollinsCOUSA
| | | | - Sarah M. Gallup
- Atmospheric Science DepartmentColorado State UniversityFort CollinsCOUSA
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36
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Spatiotemporal Patterns and Phenology of Tropical Vegetation Solar-Induced Chlorophyll Fluorescence across Brazilian Biomes Using Satellite Observations. REMOTE SENSING 2019. [DOI: 10.3390/rs11151746] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Solar-induced fluorescence (SIF) has been empirically linked to gross primary productivity (GPP) in multiple ecosystems and is thus a promising tool to address the current uncertainties in carbon fluxes at ecosystem to continental scales. However, studies utilizing satellite-measured SIF in South America have concentrated on the Amazonian tropical forest, while SIF in other regions and vegetation classes remain uninvestigated. We examined three years of Orbiting Carbon Observatory-2 (OCO-2) SIF data for vegetation classes within and across the six Brazilian biomes (Amazon, Atlantic Forest, Caatinga, Cerrado, Pampa, and Pantanal) to answer the following: (1) how does satellite-measured SIF differ? (2) What is the relationship (strength and direction) of satellite-measured SIF with canopy temperature (Tcan), air temperature (Tair), and vapor pressure deficit (VPD)? (3) How does the phenology of satellite-measured SIF (duration and amplitude of seasonal integrated SIF) compare? Our analysis shows that OCO-2 captures a significantly higher mean SIF with lower variability in the Amazon and lower mean SIF with higher variability in the Caatinga compared to other biomes. OCO-2 also distinguishes the mean SIF of vegetation types within biomes, showing that evergreen broadleaf (EBF) mean SIF is significantly higher than other vegetation classes (deciduous broadleaf (DBF), grassland (GRA), savannas (SAV), and woody savannas (WSAV)) in all biomes. We show that the strengths and directions of correlations of OCO-2 mean SIF to Tcan, Tair, and VPD largely cluster by biome: negative in the Caatinga and Cerrado, positive in the Pampa, and no correlations were found in the Pantanal, while results were mixed for the Amazon and Atlantic Forest. We found mean SIF most strongly correlated with VPD in most vegetation classes in most biomes, followed by Tcan. Seasonality from time series analysis reveals that OCO-2 SIF measurements capture important differences in the seasonal timing of SIF for different classes, details masked when only examining mean SIF differences. We found that OCO-2 captured the highest base integrated SIF and lowest seasonal pulse integrated SIF in the Amazon for all vegetation classes, indicating continuous photosynthetic activity in the Amazon exceeds other biomes, but with small seasonal increases. Surprisingly, Pantanal EBF SIF had the highest total integrated SIF of all classes in all biomes due to a large seasonal pulse. Additionally, the length of seasons only accounts for about 30% of variability in total integrated SIF; thus, integrated SIF is likely captures differences in photosynthetic activity separate from structural differences. Our results show that satellite measurements of SIF can distinguish important functioning and phenological differences in vegetation classes and thus has the potential to improve our understanding of productivity and seasonality in the tropics.
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37
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Du S, Liu L, Liu X, Guo J, Hu J, Wang S, Zhang Y. SIFSpec: Measuring Solar-Induced Chlorophyll Fluorescence Observations for Remote Sensing of Photosynthesis. SENSORS (BASEL, SWITZERLAND) 2019; 19:E3009. [PMID: 31288443 PMCID: PMC6651194 DOI: 10.3390/s19133009] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/16/2019] [Revised: 07/04/2019] [Accepted: 07/05/2019] [Indexed: 11/16/2022]
Abstract
Solar-induced chlorophyll fluorescence (SIF) is regarded as a proxy for photosynthesis in terrestrial vegetation. Tower-based long-term observations of SIF are very important for gaining further insight into the ecosystem-specific seasonal dynamics of photosynthetic activity, including gross primary production (GPP). Here, we present the design and operation of the tower-based automated SIF measurement (SIFSpec) system. This system was developed with the aim of obtaining synchronous SIF observations and flux measurements across different terrestrial ecosystems, as well as to validate the increasing number of satellite SIF products using in situ measurements. Details of the system components, instrument installation, calibration, data collection, and processing are introduced. Atmospheric correction is also included in the data processing chain, which is important, but usually ignored for tower-based SIF measurements. Continuous measurements made across two growing cycles over maize at a Daman (DM) flux site (in Gansu province, China) demonstrate the reliable performance of SIF as an indicator for tracking the diurnal variations in photosynthetically active radiation (PAR) and seasonal variations in GPP. For the O2-A band in particular, a high correlation coefficient value of 0.81 is found between the SIF and seasonal variations of GPP. It is thus concluded that, in coordination with continuous eddy covariance (EC) flux measurements, automated and continuous SIF observations can provide a reliable approach for understanding the photosynthetic activity of the terrestrial ecosystem, and are also able to bridge the link between ground-based optical measurements and airborne or satellite remote sensing data.
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Affiliation(s)
- Shanshan Du
- Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Liangyun Liu
- Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China.
| | - Xinjie Liu
- Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
| | - Jian Guo
- Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
- College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China
| | - Jiaochan Hu
- Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shaoqiang Wang
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Yongguang Zhang
- International Institute for Earth System Sciences, Nanjing University, Nanjing 21002, China
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Ni Z, Lu Q, Huo H, Zhang H. Estimation of Chlorophyll Fluorescence at Different Scales: A Review. SENSORS (BASEL, SWITZERLAND) 2019; 19:E3000. [PMID: 31288380 PMCID: PMC6651496 DOI: 10.3390/s19133000] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/24/2019] [Revised: 06/19/2019] [Accepted: 06/24/2019] [Indexed: 11/16/2022]
Abstract
Measuring chlorophyll fluorescence is a direct and non-destructive way to monitor vegetation. In this paper, the fluorescence retrieval methods from multiple scales, ranging from near the ground to the use of space-borne sensors, are analyzed and summarized in detail. At the leaf-scale, the chlorophyll fluorescence is measured using active and passive technology. Active remote sensing technology uses a fluorimeter to measure the chlorophyll fluorescence, and passive remote sensing technology mainly depends on the sun-induced chlorophyll fluorescence filling in the Fraunhofer lines or oxygen absorptions bands. Based on these retrieval principles, many retrieval methods have been developed, including the radiance-based methods and the reflectance-based methods near the ground, as well as physically and statistically-based methods that make use of satellite data. The advantages and disadvantages of different approaches for sun-induced chlorophyll fluorescence retrieval are compared and the key issues of the current sun-induced chlorophyll fluorescence retrieval algorithms are discussed. Finally, conclusions and key problems are proposed for the future research.
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Affiliation(s)
- Zhuoya Ni
- Key Laboratory of Radiometric Calibration and Validation for Environment Satellites, National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China
| | - Qifeng Lu
- Key Laboratory of Radiometric Calibration and Validation for Environment Satellites, National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China
| | - Hongyuan Huo
- College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100124, China.
| | - Huili Zhang
- Jiangxi Technical College Of Manufacturing, Nanchang 330095, China
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Effects of the Temporal Aggregation and Meteorological Conditions on the Parameter Robustness of OCO-2 SIF-Based and LUE-Based GPP Models for Croplands. REMOTE SENSING 2019. [DOI: 10.3390/rs11111328] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Global retrieval of solar-induced chlorophyll fluorescence (SIF) using remote sensing by means of satellites has been developed rapidly in recent years. Exploring how SIF could improve the characterization of photosynthesis and its role in the land surface carbon cycle has gradually become a very important and active area. However, compared with other gross primary production (GPP) models, the robustness of the parameterization of the SIF model under different circumstances has rarely been investigated. In this study, we examined and compared the effects of temporal aggregation and meteorological conditions on the stability of model parameters for the SIF model ( ε / S I F yield ), the one-leaf light-use efficiency (SL-LUE) model ( ε max ), and the two-leaf LUE (TL-LUE) model ( ε msu and ε msh ). The three models were parameterized based on a maize–wheat rotation eddy-covariance flux tower data in Yucheng, Shandong Province, China by using the Metropolis–Hasting algorithm. The results showed that the values of the ε / S I F yield and ε max were similarly robust and considerably more stable than ε msu and ε msh for all temporal aggregation levels. Under different meteorological conditions, all the parameters showed a certain degree of fluctuation and were most affected at the mid-day scale, followed by the monthly scale and finally at the daily scale. Nonetheless, the averaged coefficient of variation ( C V ) of ε / S I F yield was relatively small (15.0%) and was obviously lower than ε max ( C V = 27.0%), ε msu ( C V = 43.2%), and ε msh ( C V = 53.1%). Furthermore, the SIF model’s performance for estimating GPP was better than that of the SL-LUE model and was comparable to that of the TL-LUE model. This study indicates that, compared with the LUE-based models, the SIF-based model without climate-dependence is a good predictor of GPP and its parameter is more likely to converge for different temporal aggregation levels and under varying environmental restrictions in croplands. We suggest that more flux tower data should be used for further validation of parameter convergence in other vegetation types.
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40
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Contrasting the Performance of Eight Satellite-Based GPP Models in Water-Limited and Temperature-Limited Grassland Ecosystems. REMOTE SENSING 2019. [DOI: 10.3390/rs11111333] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Models constitute the primary approaches for predicting terrestrial ecosystem gross primary production (GPP) at regional and global scales. Many satellite-based GPP models have been developed due to the simple algorithms and the low requirements of model inputs. The performances of these models are well documented at the biome level. However, their performances among vegetation subtypes limited by different environmental stresses within a biome remains largely unexplored. Taking grasslands in northern China as an example, we compared the performance of eight satellite-based GPP models, including three light-use efficiency (LUE) models (vegetation photosynthesis model (VPM), modified VPM (MVPM), and moderate resolution imaging spectroradiometer GPP algorithm (MODIS-GPP)) and five statistical models (temperature and greenness model (TG), greenness and radiation model (GR), vegetation index model (VI), alpine vegetation model (AVM), and photosynthetic capacity model (PCM)), between the water-limited temperate steppe and the temperature-limited alpine meadow based on 16 site-year GPP estimates at four eddy covariance (EC) flux towers. The results showed that all the GPP models performed better in the alpine meadow, particularly in the alpine shrub meadow (R2 ≥ 0.84), than in the temperate steppe (R2 ≤ 0.68). The performance varied greatly among the models in the temperate steppe, while slight intermodel differences existed in the alpine meadow. Overall, MVPM (of the LUE models) and VI (of the statistical models) were the two best-performing models in the temperate steppe due to their better representation of the effect of water stress on vegetation productivity. Additionally, we found that the relatively worse model performances in the temperate steppe were seriously exaggerated by drought events, which may occur more frequently in the future. This study highlights the varying performances of satellite-based GPP models among vegetation subtypes of a biome in different precipitation years and suggests priorities for improving the water stress variables of these models in future efforts.
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41
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Huang M, Piao S, Ciais P, Peñuelas J, Wang X, Keenan TF, Peng S, Berry JA, Wang K, Mao J, Alkama R, Cescatti A, Cuntz M, De Deurwaerder H, Gao M, He Y, Liu Y, Luo Y, Myneni RB, Niu S, Shi X, Yuan W, Verbeeck H, Wang T, Wu J, Janssens IA. Air temperature optima of vegetation productivity across global biomes. Nat Ecol Evol 2019; 3:772-779. [PMID: 30858592 PMCID: PMC6491223 DOI: 10.1038/s41559-019-0838-x] [Citation(s) in RCA: 117] [Impact Index Per Article: 23.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2018] [Accepted: 02/05/2019] [Indexed: 11/02/2022]
Abstract
The global distribution of the optimum air temperature for ecosystem-level gross primary productivity ([Formula: see text]) is poorly understood, despite its importance for ecosystem carbon uptake under future warming. We provide empirical evidence for the existence of such an optimum, using measurements of in situ eddy covariance and satellite-derived proxies, and report its global distribution. [Formula: see text] is consistently lower than the physiological optimum temperature of leaf-level photosynthetic capacity, which typically exceeds 30 °C. The global average [Formula: see text] is estimated to be 23 ± 6 °C, with warmer regions having higher [Formula: see text] values than colder regions. In tropical forests in particular, [Formula: see text] is close to growing-season air temperature and is projected to fall below it under all scenarios of future climate, suggesting a limited safe operating space for these ecosystems under future warming.
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Affiliation(s)
- Mengtian Huang
- Sino-French Institute for Earth System Science, Peking University, Beijing, China
| | - Shilong Piao
- Sino-French Institute for Earth System Science, Peking University, Beijing, China.
- Key Laboratory of Alpine Ecology and Biodiversity, Chinese Academy of Sciences, Beijing, China.
- Center for Excellence in Tibetan Earth Science, Chinese Academy of Sciences, Beijing, China.
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, Gif-sur-Yvette, France
| | - Josep Peñuelas
- Centre for Research on Ecology and Forestry Applications, Barcelona, Spain
- CSIC, Global Ecology Unit CREAF-CSIC-UAB, Barcelona, Spain
| | - Xuhui Wang
- Sino-French Institute for Earth System Science, Peking University, Beijing, China
| | - Trevor F Keenan
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- Department of Environmental Science Policy and Management, UC Berkeley, Berkeley, CA, USA
| | - Shushi Peng
- Sino-French Institute for Earth System Science, Peking University, Beijing, China
| | - Joseph A Berry
- Department of Global Ecology, Carnegie Institution for Science, Stanford, CA, USA
| | - Kai Wang
- Sino-French Institute for Earth System Science, Peking University, Beijing, China
| | - Jiafu Mao
- Climate Change Science Institute and Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Ramdane Alkama
- European Commission, Joint Research Centre (JRC), Ispra, Italy
| | | | - Matthias Cuntz
- Université de Lorraine, INRA, AgroParisTech, UMR Silva, Nancy, France
| | - Hannes De Deurwaerder
- CAVElab Computational and Applied Vegetation Ecology, Ghent University, Gent, Belgium
| | - Mengdi Gao
- Sino-French Institute for Earth System Science, Peking University, Beijing, China
| | - Yue He
- Sino-French Institute for Earth System Science, Peking University, Beijing, China
| | - Yongwen Liu
- Sino-French Institute for Earth System Science, Peking University, Beijing, China
| | - Yiqi Luo
- Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA
| | - Ranga B Myneni
- Department of Earth and Environment, Boston University, Boston, MA, USA
| | - Shuli Niu
- Key Laboratory of Ecosystem Network Observation and Modeling, Chinese Academy of Sciences, Beijing, China
| | - Xiaoying Shi
- Climate Change Science Institute and Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Wenping Yuan
- School of Atmospheric Sciences, Sun Yat-Sen University, Guangzhou, China
| | - Hans Verbeeck
- CAVElab Computational and Applied Vegetation Ecology, Ghent University, Gent, Belgium
| | - Tao Wang
- Key Laboratory of Alpine Ecology and Biodiversity, Chinese Academy of Sciences, Beijing, China
- Center for Excellence in Tibetan Earth Science, Chinese Academy of Sciences, Beijing, China
| | - Jin Wu
- Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, NY, USA
- School of Biological Sciences, University of Hong Kong, Pokfulam, Hong Kong
| | - Ivan A Janssens
- Centre of Excellence - Plants and Vegetation Ecology, University of Antwerp, Wilrijk, Belgium
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Chen S, Huang Y, Gao S, Wang G. Impact of physiological and phenological change on carbon uptake on the Tibetan Plateau revealed through GPP estimation based on spaceborne solar-induced fluorescence. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 663:45-59. [PMID: 30708216 DOI: 10.1016/j.scitotenv.2019.01.324] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2018] [Revised: 01/18/2019] [Accepted: 01/20/2019] [Indexed: 06/09/2023]
Abstract
Although gross primary production (GPP) is an essential proxy for reflecting terrestrial ecosystem function, GPP estimation at regional scale on the Tibetan Plateau (TP) is constrained by the lack of ground observations. Moreover, how climate-induced phenological and physiological change further affects carbon uptake in this region remains unclear. In this study, we first estimated GPP at 8-day intervals and a 0.5° resolution from 2007 to 2015 over the TP based on an improved approach and GOME-2 sun-induced fluorescence (SIF) retrievals. The obtained SIF-based GPP coincided well with flux observations and two state of the art GPP products, with a regional carbon uptake of 0.62 ± 0.04 PgC year-1 or 307 ± 22 gC m-2 year-1. With the SIF-based GPP, two phenological indicators (start and end date of the growing season, i.e., SGS and EGS) and one physiological indicator (maximum photosynthesis capacity, GPPmax) were identified and their relative contributions to inter-annual GPP variability were further quantitatively separated using a multiple regression model. Advanced SGS, delayed EGS, and increasing GPPmax can all enhance carbon uptake and a combination of the three indicators can explain 72 ± 20% of GPP inter-annual variability. The response of annual GPP to phenological and physiological variations has significant altitude dependence, as the decline of annual GPP in most of the area is dominated by the GPPmax decline, while the increase of annual GPP in the high-altitude area is dominated by the advanced SGS. The response of all three indicators to both temperature and precipitation variation has great spatial heterogeneity. Our study suggests that remote sensing of SIF can provide a unique opportunity to estimate GPP in regions with a lack of ground observations and that our enhanced understanding of the impact of the climate-induced phenological and physiological change on GPP variability in alpine ecosystems can improve GPP estimation in a changing climate.
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Affiliation(s)
- Shiliu Chen
- State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China.
| | - Yuefei Huang
- State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China; State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining, Qinghai 810016, China.
| | - Shuai Gao
- State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China
| | - Guangqian Wang
- State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China
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Widespread Decline in Vegetation Photosynthesis in Southeast Asia Due to the Prolonged Drought During the 2015/2016 El Niño. REMOTE SENSING 2019. [DOI: 10.3390/rs11080910] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
El Niño events are known to be associated with climate extremes and have substantial impacts on the global carbon cycle. The drought induced by strong El Niño event occurred in the tropics during 2015 and 2016. However, it is still unclear to what extent the drought could affect photosynthetic activities of crop and forest in Southeast Asia. Here, we used the satellite solar-induced chlorophyll fluorescence (SIF), which is a proxy of actual photosynthesis, along with traditional vegetation indices (Enhanced Vegetation Index, EVI) and total water storage to investigate the impacts of El Niño–induced droughts on vegetation productivity of the forest and crop in the Southeast Asia. We found that SIF was more sensitive to the water stress than traditional vegetation indices (EVI) to monitor drought for both evergreen broadleaf forest and croplands in Southeast Asia. The higher solar radiation partly offset the negative effects of droughts on the vegetation productivity, leading to a larger decrease of SIF yield (SIFyield) than SIF. Therefore, SIFyield had a larger reduction and was more sensitive to precipitation deficit than SIF during the drought. The comparisons of retrieved column-average dry-air mole fraction of atmospheric carbon dioxide with SIF demonstrated the reduction of CO2 uptake by vegetation in Southeast Asia during the drought. This study highlights that SIF is more beneficial than EVI to be an indicator to characterize and monitor the dynamics of drought in tropical vegetated regions.
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44
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Ecosystem Productivity and Water Stress in Tropical East Africa: A Case Study of the 2010–2011 Drought. LAND 2019. [DOI: 10.3390/land8030052] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Characterizing the spatiotemporal patterns of ecosystem responses to drought is important in understanding the impact of water stress on tropical ecosystems and projecting future land cover transitions in the East African tropics. Through the analysis of satellite measurements of solar-induced chlorophyll fluorescence (SIF) and the normalized difference vegetation index (NDVI), soil moisture, rainfall, and reanalysis data, here we characterize the 2010–2011 drought in tropical East Africa. The 2010–2011 drought included the consecutive failure of rainy seasons in October–November–December 2010 and March–April–May 2011 and extended further east and south compared with previous regional droughts. During 2010–2011, SIF, a proxy of ecosystem productivity, showed a concomitant decline (~32% lower gross primary productivity, or GPP, based on an empirical SIF–GPP relationship, as compared to the long-term average) with water stress, expressed by lower precipitation and soil moisture. Both SIF and NDVI showed a negative response to drought, and SIF captured the response to soil moisture with a lag of 16 days, even if it had lower spatial resolution and much smaller energy compared with NDVI, suggesting that SIF can also serve as an early indicator of drought in the future. This work demonstrates the unique characteristics of the 2010–2011 East African drought and the ability of SIF and NDVI to track the levels of water stress during the drought.
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45
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Monitoring Drought Effects on Vegetation Productivity Using Satellite Solar-Induced Chlorophyll Fluorescence. REMOTE SENSING 2019. [DOI: 10.3390/rs11040378] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Around the world, the increasing drought, which is exacerbated by climate change, has significant impacts on vegetation carbon assimilation. Identifying how short-term climate anomalies influence vegetation productivity in a timely and accurate manner at the satellite scale is crucial to monitoring drought. Satellite solar-induced chlorophyll fluorescence (SIF) has recently been reported as a direct proxy of actual vegetation photosynthesis and has more advantages than traditional vegetation indices (e.g., the Normalized Difference Vegetation Index, NDVI and the Enhanced Vegetation Index, EVI) in monitoring vegetation vitality. This study aims to evaluate the feasibility of SIF in interpreting drought effects on vegetation productivity in Victoria, Australia, where heat stress and drought are often reported. Drought-induced variations in SIF and absorbed photosynthetically active radiation (APAR) estimations based on NDVI and EVI were investigated and validated against results indicated by gross primary production (GPP). We first compared drought responses of GPP and vegetation proxies (SIF and APAR) during the 2009 drought event, considering potential biome-dependency. Results showed that SIF exhibited more consistent declines with GPP losses induced by drought than did APAR estimations during the 2009 drought period in space and time, where APAR had obvious lagged responses compared with SIF, especially in evergreen broadleaf forest land. We then estimated the sensitivities of the aforementioned variables to meteorology anomalies using the ARx model, where memory effects were considered, and compared the correlations of GPP anomaly with the anomalies of vegetation proxies during a relatively long period (2007–2013). Compared with APAR, GPP and SIF are more sensitive to temperature anomalies for the general Victoria region. For crop land, GPP and vegetation proxies showed similar sensitivities to temperature and water availability. For evergreen broadleaf forest land, SIF anomaly was explained better by meteorology anomalies than APAR anomalies. GPP anomaly showed a stronger linear relationship with SIF anomaly than with APAR anomalies, especially for evergreen broadleaf forest land. We showed that SIF might be a promising tool for effectively evaluating short-term drought impacts on vegetation productivity, especially in drought-vulnerable areas, such as Victoria.
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Hikosaka K, Noda HM. Modeling leaf CO 2 assimilation and Photosystem II photochemistry from chlorophyll fluorescence and the photochemical reflectance index. PLANT, CELL & ENVIRONMENT 2019; 42:730-739. [PMID: 30321458 DOI: 10.1111/pce.13461] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2017] [Accepted: 09/24/2018] [Indexed: 06/08/2023]
Abstract
We present a simple model to assess the quantum yield of photochemistry (ΦP ) and CO2 assimilation rate from two parameters that are detectable by remote sensing: chlorophyll (chl) fluorescence and the photochemical reflectance index (PRI). ΦP is expressed as a simple function of the chl fluorescence yield (ΦF ) and nonphotochemical quenching (NPQ): ΦP = 1-bΦF (1 + NPQ). Because NPQ is known to be related with PRI, ΦP can be remotely assessed from solar-induced fluorescence and the PRI. The CO2 assimilation rate can be assessed from the estimated ΦP value with either the maximum carboxylation rate (Vcmax ), the intercellular CO2 concentration (Ci ), or parameters of the stomatal conductance model. The model was applied to experimental data obtained for Chenopodium album leaves under various environmental conditions and was able to successfully predict ΦF values and the CO2 assimilation rate. The present model will improve the accuracy of assessments of gas exchange rates and primary productivity by remote sensing.
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Affiliation(s)
- Kouki Hikosaka
- Graduate School of Life Sciences, Tohoku University, Sendai, Japan
| | - Hibiki M Noda
- Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan
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47
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Diurnal and Seasonal Solar Induced Chlorophyll Fluorescence and Photosynthesis in a Boreal Scots Pine Canopy. REMOTE SENSING 2019. [DOI: 10.3390/rs11030273] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Solar induced chlorophyll fluorescence has been shown to be increasingly an useful proxy for the estimation of gross primary productivity (GPP), at a range of spatial scales. Here, we explore the seasonality in a continuous time series of canopy solar induced fluorescence (hereafter SiF) and its relation to canopy gross primary production (GPP), canopy light use efficiency (LUE), and direct estimates of leaf level photochemical efficiency in an evergreen canopy. SiF was calculated using infilling in two bands from the incoming and reflected radiance using a pair of Ocean Optics USB2000+ spectrometers operated in a dual field of view mode, sampling at a 30 min time step using custom written automated software, from early spring through until autumn in 2011. The optical system was mounted on a tower of 18 m height adjacent to an eddy covariance system, to observe a boreal forest ecosystem dominated by Scots pine. (Pinus sylvestris) A Walz MONITORING-PAM, multi fluorimeter system, was simultaneously mounted within the canopy adjacent to the footprint sampled by the optical system. Following correction of the SiF data for O2 and structural effects, SiF, SiF yield, LUE, the photochemicsl reflectance index (PRI), and the normalized difference vegetation index (NDVI) exhibited a seasonal pattern that followed GPP sampled by the eddy covariance system. Due to the complexities of solar azimuth and zenith angle (SZA) over the season on the SiF signal, correlations between SiF, SiF yield, GPP, and LUE were assessed on SZA <50° and under strictly clear sky conditions. Correlations found, even under these screened scenarios, resulted around ~r2 = 0.3. The diurnal responses of SiF, SiF yield, PAM estimates of effective quantum yield (ΔF/Fm′), and meteorological parameters demonstrated some agreement over the diurnal cycle. The challenges inherent in SiF retrievals in boreal evergreen ecosystems are discussed.
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48
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Chen X, Mo X, Hu S, Liu S. Relationship between fluorescence yield and photochemical yield under water stress and intermediate light conditions. JOURNAL OF EXPERIMENTAL BOTANY 2019; 70:301-313. [PMID: 30299499 PMCID: PMC6305194 DOI: 10.1093/jxb/ery341] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/22/2018] [Accepted: 09/24/2018] [Indexed: 05/11/2023]
Abstract
The dynamics between fluorescence (Fs) yield and photochemical (P) yield in a changing environment are essential for understanding the relationship between photosynthesis and fluorescence. The ratio of Fs yield and P yield tends to be constant under high light intensity, but the relationship between these two yields, and its response to environmental conditions, need to be explored further under intermediate and low light. In this study, we performed leaf-scale measurements of fluorescence parameters by pulse-amplitude modulation (PAM) technology in summer maize (Zea mays L.) plants grown under intermediate light conditions in a climate chamber. Plants were treated as moderately water stressed and non-water stressed. Results showed that a decrease in P yield was accompanied by increases in Fs yield and non-photochemical quenching (NPQ) yield in response to moderate water stress under intermediate and low light conditions. Fs yield was negatively correlated with P yield under intermediate and low light conditions when there was sufficient soil water in the root zone. Under water stress, the correlation between Fs yield and P yield was negative in low light, but became positive under higher light levels. Fs yield was negatively related to P yield when NPQ yield was low; however, they were synergistically and positively associated when excessive light dissipation was dominated by NPQ.
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Affiliation(s)
- Xuejuan Chen
- Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Chaoyang District, Beijing, China
- University of Chinese Academy of Sciences, Shijingshan District, Beijing, China
| | - Xingguo Mo
- Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Chaoyang District, Beijing, China
- College of Resources and Environment/Sino-Danish Center, University of Chinese Academy of Sciences, Shijingshan District, Beijing, China
| | - Shi Hu
- Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Chaoyang District, Beijing, China
| | - Suxia Liu
- Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Chaoyang District, Beijing, China
- College of Resources and Environment/Sino-Danish Center, University of Chinese Academy of Sciences, Shijingshan District, Beijing, China
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49
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Köehler P, Frankenberg C, Magney TS, Guanter L, Joiner J, Landgraf J. Global retrievals of solar induced chlorophyll fluorescence with TROPOMI: first results and inter-sensor comparison to OCO-2. GEOPHYSICAL RESEARCH LETTERS 2018; 45:10456-10463. [PMID: 33104094 PMCID: PMC7580822 DOI: 10.1029/2018gl079031] [Citation(s) in RCA: 65] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2018] [Accepted: 09/27/2018] [Indexed: 05/19/2023]
Abstract
UNLABELLED In recent years, solar-induced chlorophyll fluorescence (SIF) retrieved from space borne spectrometers has been extensively used as a proxy for terrestrial photosynthesis at relatively sparse temporal and spatial scales. The near-infrared band of the recently launched TROPOspheric Monitoring Instrument (TROPOMI) features the required spectral resolution and signal-to-noise ratio to retrieve SIF in a spectral range devoid of atmospheric absorption features. We find that initial TROPOMI spectra meet high expectations for a substantially improved spatio-temporal resolution (up to 7 km × 3.5 km pixels with daily revisit), representing a step change in SIF remote sensing capabilities. However, interpretation requires caution, as the broad range of viewing-illumination geometries covered by TROPOMI's 2600 km wide swath needs to be taken into account. A first inter-sensor comparison with OCO-2 (Orbiting Carbon Observatory-2) SIF shows excellent agreement, underscoring the high quality of TROPOMI's SIF retrievals and the notable radiometric performance of the instrument. PLAIN LANGUAGE SUMMARY Photosynthesis is the most essential process for life on Earth, but gradually changing environmental conditions such as increasing concentrations of atmospheric trace gases, rising temperatures or reduced water availability could adversely affect the photosynthetic productivity. The recently launched TROPOspheric Monitoring Instrument (TROPOMI) is designed to monitor atmospheric trace gases and air pollutants with an unprecedented resolution in space and time, while its radiometric performance also permits us to see a weak electromagnetic signal emitted by photosynthetically active vegetation - solar induced chlorophyll fluorescence (SIF). Mounting evidence suggests that SIF observations from satellite instruments augment our abilities to track the photosynthetic performance and carbon uptake of terrestrial vegetation. In this study, we present the first TROPOMI SIF retrievals, largely outperforming previous and existing capabilities for a spatial continuous monitoring of SIF from space.
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Affiliation(s)
- Philipp Köehler
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA
| | - Christian Frankenberg
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Troy S. Magney
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Luis Guanter
- Helmholtz Centre Potsdam, German Research Center for Geosciences (GFZ), Potsdam, Germany
| | - Joanna Joiner
- NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | - Jochen Landgraf
- SRON Netherlands Institute for Space Research, Utrecht, Netherlands
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50
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Anderson LO, Ribeiro Neto G, Cunha AP, Fonseca MG, Mendes de Moura Y, Dalagnol R, Wagner FH, de Aragão LEOEC. Vulnerability of Amazonian forests to repeated droughts. Philos Trans R Soc Lond B Biol Sci 2018; 373:20170411. [PMID: 30297476 PMCID: PMC6178446 DOI: 10.1098/rstb.2017.0411] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/31/2018] [Indexed: 11/12/2022] Open
Abstract
Extreme droughts have been recurrent in the Amazon over the past decades, causing socio-economic and environmental impacts. Here, we investigate the vulnerability of Amazonian forests, both undisturbed and human-modified, to repeated droughts. We defined vulnerability as a measure of (i) exposure, which is the degree to which these ecosystems were exposed to droughts, and (ii) its sensitivity, measured as the degree to which the drought has affected remote sensing-derived forest greenness. The exposure was calculated by assessing the meteorological drought, using the standardized precipitation index (SPI) and the maximum cumulative water deficit (MCWD), which is related to vegetation water stress, from 1981 to 2016. The sensitivity was assessed based on the enhanced vegetation index anomalies (AEVI), derived from the newly available Moderate Resolution Imaging Spectroradiometer (MODIS)/Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC) product, from 2003 to 2016, which is indicative of forest's photosynthetic capacity. We estimated that 46% of the Brazilian Amazon biome was under severe to extreme drought in 2015/2016 as measured by the SPI, compared with 16% and 8% for the 2009/2010 and 2004/2005 droughts, respectively. The most recent drought (2015/2016) affected the largest area since the drought of 1981. Droughts tend to increase the variance of the photosynthetic capacity of Amazonian forests as based on the minimum and maximum AEVI analysis. However, the area showing a reduction in photosynthetic capacity prevails in the signal, reaching more than 400 000 km2 of forests, four orders of magnitude larger than areas with AEVI enhancement. Moreover, the intensity of the negative AEVI steadily increased from 2005 to 2016. These results indicate that during the analysed period drought impacts were being exacerbated through time. Forests in the twenty-first century are becoming more vulnerable to droughts, with larger areas intensively and negatively responding to water shortage in the region.This article is part of a discussion meeting issue 'The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.
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Affiliation(s)
- Liana Oighenstein Anderson
- National Centre for Monitoring and Early Warning of Natural Disasters-Cemaden, Ministry of Science, Technology, Innovation and Communication MCTIC, Brazil, Estrada Doutor Altino Bondesan, 500 - Distrito de Eugênio de Melo, São José dos Campos CEP:12.247-016, Brazil
| | - Germano Ribeiro Neto
- National Centre for Monitoring and Early Warning of Natural Disasters-Cemaden, Ministry of Science, Technology, Innovation and Communication MCTIC, Brazil, Estrada Doutor Altino Bondesan, 500 - Distrito de Eugênio de Melo, São José dos Campos CEP:12.247-016, Brazil
| | - Ana Paula Cunha
- National Centre for Monitoring and Early Warning of Natural Disasters-Cemaden, Ministry of Science, Technology, Innovation and Communication MCTIC, Brazil, Estrada Doutor Altino Bondesan, 500 - Distrito de Eugênio de Melo, São José dos Campos CEP:12.247-016, Brazil
| | - Marisa Gesteira Fonseca
- National Institute for Space Research - INPE, Brazil, Remote Sensing Division, Av. Dos Astronautas 1758, Jardim da Granja, São José dos Campos/SP CEP:12.227-010, Brazil
| | - Yhasmin Mendes de Moura
- Department of Biological Sciences, Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK
| | - Ricardo Dalagnol
- National Institute for Space Research - INPE, Brazil, Remote Sensing Division, Av. Dos Astronautas 1758, Jardim da Granja, São José dos Campos/SP CEP:12.227-010, Brazil
| | - Fabien Hubert Wagner
- National Institute for Space Research - INPE, Brazil, Remote Sensing Division, Av. Dos Astronautas 1758, Jardim da Granja, São José dos Campos/SP CEP:12.227-010, Brazil
| | - Luiz Eduardo Oliveira E Cruz de Aragão
- National Institute for Space Research - INPE, Brazil, Remote Sensing Division, Av. Dos Astronautas 1758, Jardim da Granja, São José dos Campos/SP CEP:12.227-010, Brazil
- College of Life and Environmental Sciences, University of Exeter, Rennes Drive, Exeter EX4 4RJ, UK
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