1
|
Luo Y, Ma N, Zhang Y, Zang C, Szilagyi J, Tian J, Wang L, Xu Z, Tang Z, Wei H. Response of alpine vegetation function to climate change in the Tibetan Plateau: A perspective from solar-induced chlorophyll fluorescence. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 952:175845. [PMID: 39209172 DOI: 10.1016/j.scitotenv.2024.175845] [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: 06/18/2024] [Revised: 08/23/2024] [Accepted: 08/26/2024] [Indexed: 09/04/2024]
Abstract
Vegetation change in the Tibetan Plateau (TP) is a crucial indicator of climate change in alpine regions. Previous studies have reported an overall greening trend in the vegetation structure across the TP, especially in its northeastern part, in response to a warming climate. However, variations in the vegetation function and the possible drivers remain poorly understood. Considering the optimal temperature for plants in TP is usually higher than the current temperature, our hypothesis is the function and structure of alpine vegetation have changed synchronously over past few decades. To test this hypothesis, we analyzed satellite-observed solar-induced chlorophyll fluorescence (SIF) and leaf area index (LAI) in the Yellow River source (YRS) region in the northeastern TP to quantify the long-term trends in vegetation functional and structural states, respectively. The results suggest that from 1982 to 2018, SIF increased significantly in 77.71 % of the YRS area, resulting in a significant upward trend of 0.52 × 10-3 mW m-2 nm-1 sr-1 yr-1 (p < 0.001) for the regional-mean SIF. This represents a 16.1 % increase in SIF, which is close in magnitude to the increase in LAI over the same period. The synchronous changes between vegetation function and structure suggest that improved greenness corresponds to a similar level of change in carbon uptake across YRS. Additionally, we used a multiple regression approach to quantify the contribution of climatic factors to SIF changes in YRS. Our analyses show that the increases in SIF were primarily driven by rising temperatures. Spatially, temperature dominated SIF changes in most parts of YRS, except for certain dry parts in the northern and western YRS, where precipitation had a greater impact. Our results are crucial for a comprehensive understanding of climate regulations on vegetation structure and function in high-elevation regions.
Collapse
Affiliation(s)
- Yiwen Luo
- Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China; School of Geography, South China Normal University, Guangzhou, China
| | - Ning Ma
- Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
| | - Yongqiang Zhang
- Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Chuanfu Zang
- School of Geography, South China Normal University, Guangzhou, China
| | - Jozsef Szilagyi
- Department of Hydraulic and Water Resources Engineering, Budapest University of Technology and Economics, Budapest, Hungary
| | - Jing Tian
- Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Longhao Wang
- Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China
| | - Zhenwu Xu
- Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China
| | - Zixuan Tang
- Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China
| | - Haoshan Wei
- Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China
| |
Collapse
|
2
|
Varghese R, Behera S, Behera MD. Tropical ocean teleconnections with gross primary productivity of monsoon-Asia. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 938:173337. [PMID: 38797406 DOI: 10.1016/j.scitotenv.2024.173337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 05/07/2024] [Accepted: 05/16/2024] [Indexed: 05/29/2024]
Abstract
The intricate oceanic climate interactions with terrestrial primary production of Asian ecosystems exert crucial social-economical-environmental repercussions. Yet, a holistic understanding of tropical sea surface temperature (SST) anomalies associated with the gross primary productivity (GPP) variations of monsoon-Asia remains constrained. This study provides a statistical framework demonstrating how SST perturbations in the tropics influence GPP fluctuations in monsoon-Asia by modulating hydrothermal conditions of different climate system components. Observation evidence explicitly illustrated the characteristic anomalous SST signatures of positive and negative GPP anomalies in South and Southeast Asia during June-August. The SST anomalies of the central-eastern tropical Pacific showed a robust negative impact on the GPP variability of South-Asia. The GPP alterations in maritime-Southeast-Asia exhibited strong connections with SST anomalies of the western Pacific (positive) and eastern equatorial Pacific (negative). The oceanic signals in the GPP variability of South-Asia and maritime-Southeast-Asia mirrored canonical El Niño and La Niña patterns. The detected SST-GPP link is feasible through large-scale atmospheric circulation variability and the consequent regional modulation of heat and moisture fluxes. The anomalous strengthening (weakening) of Walker cell enhances (reduces) water availability to plants for photosynthesis during the La Niña (El Niño) phase of the ENSO cycle and thus elevates (lowers) GPP in South-Asia and Maritime-southeast-Asia. In contrast, the enhanced GPP anomaly in mainland-Southeast-Asia depicts signs of canonical La Niña and Indian Ocean subtropical dipole (IOSD) teleconnections. The positive impact of IOSD was through the modulation of the Mascarene High and the consequent impact on the monsoon. Meanwhile, decreased GPP bears the imprint of El Niño Modoki and warm tropical Indian Ocean SSTs. The atmospheric teleconnections demonstrated the delayed impact of El Niño Modoki on GPP variability through the Indian Ocean capacitor effect. Our findings could be instrumental in forecasting the probable effects on vegetation growth in monsoon-Asia associated with high-frequency tropical oceanic changes.
Collapse
Affiliation(s)
- Roma Varghese
- Centre for Ocean, River, Atmosphere and Land Sciences, Indian Institute of Technology Kharagpur, India.
| | - Swadhin Behera
- Applications Laboratory, Research Institute for Value Added Information Generation, Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan.
| | - Mukunda Dev Behera
- Centre for Ocean, River, Atmosphere and Land Sciences, Indian Institute of Technology Kharagpur, India.
| |
Collapse
|
3
|
Ravi A, Pillai D, Thilakan V, Mathew TA. Methodological advancement in deriving primary productivity and ecosystem respiration fluxes across different biomes. MethodsX 2024; 12:102773. [PMID: 38846432 PMCID: PMC11154699 DOI: 10.1016/j.mex.2024.102773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Accepted: 05/20/2024] [Indexed: 06/09/2024] Open
Abstract
In this paper, we introduce a methodology that can improve the estimations of Gross Primary Productivity (GPP) and ecosystem Respiration (Reco) processes at a regional scale. This method is based on a satellite data-driven approach which is suitable for regions like India where there exists a serious shortage of ground-based observations of biospheric carbon fluxes (e.g., Eddy Covariance (EC) flux measurements). We relied on the Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance for capturing vegetation dynamics in the Light-Use Efficiency (LUE)-based vegetation model. Further, we utilised recently available satellite-based Solar-Induced Fluorescence (SIF) and other variables such as Soil Moisture (SM) and Soil Temperature (ST) to refine the predictions of GPP and Reco. The methodology involves establishing a relationship between SIF and GPP for different vegetation classes over India. The SIF-GPP relationship established across the biomes was then used to correct the GPP fluxes simulated by the LUE-based model. Similarly, the ecosystem respiration estimations by the model have undergone refinement by incorporating ST and SM information. This innovative method shows remarkable potential to improve biospheric CO2 uptake and release, especially for in situ data-constrained regions like India. • SIF-based information is introduced to a light-use efficiency-based vegetation model. • SIF-GPP relationship is established for major biomes across India. • SM and ST information is incorporated into the Reco simulations in the model.
Collapse
Affiliation(s)
- Aparnna Ravi
- Indian Institute of Science Education and Research Bhopal (IISERB), India
- Max Planck Partner Group at IISERB, Bhopal, India
| | - Dhanyalekshmi Pillai
- Indian Institute of Science Education and Research Bhopal (IISERB), India
- Max Planck Partner Group at IISERB, Bhopal, India
| | - Vishnu Thilakan
- Indian Institute of Science Education and Research Bhopal (IISERB), India
- Max Planck Partner Group at IISERB, Bhopal, India
| | - Thara Anna Mathew
- Indian Institute of Science Education and Research Bhopal (IISERB), India
- Max Planck Partner Group at IISERB, Bhopal, India
| |
Collapse
|
4
|
Patel VK, Kuttippurath J, Kashyap R. Increased global cropland greening as a response to the unusual reduction in atmospheric PM₂.₅ concentrations during the COVID-19 lockdown period. CHEMOSPHERE 2024; 358:142147. [PMID: 38677610 DOI: 10.1016/j.chemosphere.2024.142147] [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: 11/23/2023] [Revised: 04/20/2024] [Accepted: 04/24/2024] [Indexed: 04/29/2024]
Abstract
The devastating effects of COVID-19 pandemic have widely affected human lives and economy across the globe. There were significant changes in the global environmental conditions in response to the lockdown (LD) restrictions made due to COVID-19. The direct impact of LD on environment is analysed widely across the latitudes, but its secondary effect remains largely unexplored. Therefore, we examine the changes in particulate matter (PM₂.₅) during LD, and its impact on the global croplands. Our analysis finds that there is a substantial decline in the global PM₂.₅ concentrations during LD (2020) compared to pre-lockdown (PreLD: 2017-2019) in India (10-20%), East China (EC, 10%), Western Europe (WE, 10%) and Nigeria (10%), which are also the cropland dominated regions. Partial correlation analysis reveals that the decline in PM₂.₅ positively affects the cropland greening when the influence of temperature, precipitation and soil moisture are limited. Croplands in India, EC, Nigeria and WE became more greener as a result of the improvement in air quality by the reduction in particulates such as PM₂.₅ during LD, with an increase in the Enhanced Vegetation Index (EVI) of about 0.05-0.1, 0.05, 0.05 and 0.05-0.1, respectively. As a result of cropland greening, increase in the total above ground biomass production (TAGP) and crop yield (TWSO) is also found in EC, India and Europe. In addition, the improvement in PM₂.₅ pollution and associated changes in meteorology also influenced the cropland phenology, where the crop development stage has prolonged in India for wet-rice (1-20%) and maize (1-10%). Therefore, this study sheds light on the response of global croplands to LD-induced improvements in PM₂.₅ pollution. These finding have implications for addressing issues of air pollution, global warming, climate change, environmental conservation and food security to achieve the Sustainable Development Goals (SDGs).
Collapse
Affiliation(s)
- Vikas Kumar Patel
- CORAL, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India
| | | | - Rahul Kashyap
- CORAL, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India
| |
Collapse
|
5
|
Khampa N, Boontanon SK, Aroonsrimorakot S, Boontanon N. Combo chloro-photosynthetic device and applications for greenhouse gas reduction campaign and smart agriculture. Heliyon 2024; 10:e31552. [PMID: 38831824 PMCID: PMC11145496 DOI: 10.1016/j.heliyon.2024.e31552] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 05/13/2024] [Accepted: 05/17/2024] [Indexed: 06/05/2024] Open
Abstract
The increasing carbon dioxide (CO2) levels in the air pose a direct threat to all living organisms and the environment. Leveraging the ability of plants to absorb CO2 is one of the most effective methods for countering these rising CO2 levels. The present study aimes to develop a combo photosynthetic and chlorophyll-a sensor based on Non-Dispersive Infrared (NDIR) spectroscopy and an optical method. This sensor enables simultaneous, intensive measurement of net photosynthesis and chlorophyll-a content and yields accurate information. Comparative analysis of the efficacy of the sensors to that of a commercial instrument demonstrated that the measurement values obtained from the developed photosynthetic and chlorophyll-a sensors were not significantly different from those acquired with the commercial instrument (portable photosynthesis system LI-6400) and chlorophyll metre (SPAD-502), with a 95 % confidence level. Furthermore, the developed photosynthetic sensor could be used as a new correlation unit for chlorophyll-a content and net photosynthesis. Therefore, the sensor can be used to propose effective plantation processes to reduce atmospheric CO2 levels and in smart farming systems to control the quality of yields.
Collapse
Affiliation(s)
- Natsuda Khampa
- Faculty of Environment and Resource Studies, Mahidol University, 999 Phutthamonthon Sai 4 Road, Salaya, Phutthamonthon, Nakhon Pathom, 73170 Thailand
| | - Suwanna Kitpati Boontanon
- Department of Civil and Environmental Engineering, Faculty of Engineering, Mahidol University, 25/25 Phutthamonthon Sai 4 Road, Salaya, Phutthamonthon, Nakhon Pathom, 73170 Thailand
| | - Sayam Aroonsrimorakot
- Faculty of Environment and Resource Studies, Mahidol University, 999 Phutthamonthon Sai 4 Road, Salaya, Phutthamonthon, Nakhon Pathom, 73170 Thailand
| | - Narin Boontanon
- Faculty of Environment and Resource Studies, Mahidol University, 999 Phutthamonthon Sai 4 Road, Salaya, Phutthamonthon, Nakhon Pathom, 73170 Thailand
- Research Center and Technology Development for Environmental Innovation, Faculty of Environment and Resource Studies, Mahidol University, 999 Phutthamonthon Sai 4 Road, Salaya, Phutthamonthon, Nakhon Pathom, 73170 Thailand
| |
Collapse
|
6
|
Wu G, Guan K, Kimm H, Miao G, Yang X, Jiang C. Ground far-red sun-induced chlorophyll fluorescence and vegetation indices in the US Midwestern agroecosystems. Sci Data 2024; 11:228. [PMID: 38388559 PMCID: PMC10883924 DOI: 10.1038/s41597-024-03004-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 01/26/2024] [Indexed: 02/24/2024] Open
Abstract
Sun-induced chlorophyll fluorescence (SIF) provides an opportunity to study terrestrial ecosystem photosynthesis dynamics. However, the current coarse spatiotemporal satellite SIF products are challenging for mechanistic interpretations of SIF signals. Long-term ground SIF and vegetation indices (VIs) are important for satellite SIF validation and mechanistic understanding of the relationship between SIF and photosynthesis when combined with leaf- and canopy-level auxiliary measurements. In this study, we present and analyze a total of 15 site-years of ground far-red SIF (SIF at 760 nm, SIF760) and VIs datasets from soybean, corn, and miscanthus grown in the U.S. Corn Belt from 2016 to 2021. We introduce a comprehensive data processing protocol, including different retrieval methods, calibration coefficient adjustment, and nadir SIF footprint upscaling to match the eddy covariance footprint. This long-term ground far-red SIF and VIs dataset provides important and first-hand data for far-red SIF interpretation and understanding the mechanistic relationship between far-red SIF and canopy photosynthesis across various crop species and environmental conditions.
Collapse
Affiliation(s)
- Genghong Wu
- Agroecosystem Sustainability Center, Institute for Sustainability, Energy, and Environment, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Natural Resources and Environmental Sciences, College of Agricultural, Consumers, and Environmental Sciences, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- DOE Center for Advanced Bioenergy and Bioproducts Innovation, Urbana, IL, 61801, USA
| | - Kaiyu Guan
- Agroecosystem Sustainability Center, Institute for Sustainability, Energy, and Environment, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA.
- Department of Natural Resources and Environmental Sciences, College of Agricultural, Consumers, and Environmental Sciences, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA.
- DOE Center for Advanced Bioenergy and Bioproducts Innovation, Urbana, IL, 61801, USA.
- National Center of Supercomputing Applications, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA.
| | - Hyungsuk Kimm
- Department of Natural Resources and Environmental Sciences, College of Agricultural, Consumers, and Environmental Sciences, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, 08826, Republic of Korea
| | - Guofang Miao
- Department of Natural Resources and Environmental Sciences, College of Agricultural, Consumers, and Environmental Sciences, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Xi Yang
- Department of Environmental Sciences, University of Virginia, Charlottesville, VA, 22903, USA
| | - Chongya Jiang
- Agroecosystem Sustainability Center, Institute for Sustainability, Energy, and Environment, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Natural Resources and Environmental Sciences, College of Agricultural, Consumers, and Environmental Sciences, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- DOE Center for Advanced Bioenergy and Bioproducts Innovation, Urbana, IL, 61801, USA
| |
Collapse
|
7
|
Liu X, Chu B, Tang R, Liu Y, Qiu B, Gao M, Li X, Xiao J, Sun HZ, Huang X, Desai AR, Ding A, Wang H. Air quality improvements can strengthen China's food security. NATURE FOOD 2024; 5:158-170. [PMID: 38168777 DOI: 10.1038/s43016-023-00882-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 10/31/2023] [Indexed: 01/05/2024]
Abstract
Air pollution exerts crucial influence on crop yields and impacts regional and global food supplies. Here we employ a statistical model using satellite-based observations and flexible functional forms to analyse the synergistic effects of reductions in ozone and aerosols on China's food security. The model consistently shows that ozone is detrimental to crops, whereas aerosol has variable effects. China's maize, rice and wheat yields are projected to increase by 7.84%, 4.10% and 3.43%, respectively, upon reaching two air quality targets (60 μg m-3 for peak-season ozone and 35 μg m-3 for annual fine particulate matter). Average calories produced from these crops would surge by 4.51%, potentially allowing China to attain grain self-sufficiency 2 years earlier than previously estimated. These results show that ozone pollution control should be a high priority to increase staple crop edible calories, and future stringent air pollution regulations would enhance China's food security.
Collapse
Affiliation(s)
- Xiang Liu
- Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing, China
| | - Bowen Chu
- Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing, China
| | - Rong Tang
- Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing, China
| | - Yifan Liu
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, China
| | - Bo Qiu
- Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing, China
| | - Meng Gao
- Department of Geography, Hong Kong Baptist University, Hong Kong SAR, China
| | - Xing Li
- Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea
| | - Jingfeng Xiao
- Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, USA
| | - Haitong Zhe Sun
- Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK
| | - Xin Huang
- Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing, China
- Collaborative Innovation Center of Climate Change, Jiangsu Province, Nanjing, China
- Frontiers Science Center for Critical Earth Material Cycling, Nanjing University, Nanjing, China
| | - Ankur R Desai
- Department of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - Aijun Ding
- Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing, China
- Collaborative Innovation Center of Climate Change, Jiangsu Province, Nanjing, China
- Frontiers Science Center for Critical Earth Material Cycling, Nanjing University, Nanjing, China
- Nanjing-Helsinki Institute in Atmospheric and Earth Sciences, Nanjing University, Nanjing, China
| | - Haikun Wang
- Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing, China.
- Collaborative Innovation Center of Climate Change, Jiangsu Province, Nanjing, China.
- Frontiers Science Center for Critical Earth Material Cycling, Nanjing University, Nanjing, China.
- Nanjing-Helsinki Institute in Atmospheric and Earth Sciences, Nanjing University, Nanjing, China.
| |
Collapse
|
8
|
Zhang Z, Guo J, Han S, Jin S, Zhang L. Establishing a Gross Primary Productivity Model by SIF and PRI on the Rice Canopy. PLANT PHENOMICS (WASHINGTON, D.C.) 2024; 6:0144. [PMID: 38304301 PMCID: PMC10832794 DOI: 10.34133/plantphenomics.0144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 01/06/2024] [Indexed: 02/03/2024]
Abstract
Solar-induced chlorophyll fluorescence (SIF) has shown remarkable results in estimating vegetation carbon cycles, and combining it with the photochemical reflectance index (PRI) has great potential for estimating gross primary productivity (GPP). However, few studies have used SIF combined with PRI to estimate crop canopy GPP. Large temporal and spatial variability between SIF, PRI, and GPP has also been found in remote sensing observations, and the observed PRI and SIF are influenced by the ratio of different observed information (e.g., background, direct sunlit, and shaded leaves) and the physiological state of the vegetation. In this study, the PRI and SIF from a multi-angle spectrometer and the GPP from an eddy covariance system were used to assess the ability of the PRI to enhance the SIF-GPP estimation model. A semi-empirical kernel-driven Bidirectional Reflectance Distribution Function (BRDF) model was used to describe the hotspot PRI/SIF (PRIhs/SIFhs), and a modified two-leaf model was used to calculate the total canopy PRI/SIF (PRItot/SIFtot). We compared the accuracies of PRIhs/SIFhs and PRItot/SIFtot in estimating GPP. The results indicated that the PRItot+SIFtot-GPP model performed the best, with a correlation coefficient (R2) of the validation dataset of 0.88, a root mean square error (RMSE) of 3.74, and relative prediction deviation (RPD) of 2.71. The leaf area index (LAI) had a linear effect on the PRI/SIF estimation of GPP, but the temperature and vapor pressure differences had nonlinear effects. Compared with hotspot PRIhs/SIFhs, PRItot/SIFtot exhibited better consistency with GPP across different time series. Our research demonstrates that PRI is effective in enhancing SIF and PRI for estimating GPP on the rice canopy and also suggests that the two-leaf model would contribute to the vegetation index tracking the real-time crop productivity.
Collapse
Affiliation(s)
- Zhanhao Zhang
- School of Ecology and Applied Meteorology,
Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Jianmao Guo
- School of Ecology and Applied Meteorology,
Nanjing University of Information Science & Technology, Nanjing 210044, China
- Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing 210044, China
| | - Shihui Han
- School of Ecology and Applied Meteorology,
Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Shuyuan Jin
- School of Ecology and Applied Meteorology,
Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Lei Zhang
- National Meteorological Centre, China Meteorological Administration, Beijing 100081, China
| |
Collapse
|
9
|
Kim JE, Wang JA, Li Y, Czimczik CI, Randerson JT. Wildfire-induced increases in photosynthesis in boreal forest ecosystems of North America. GLOBAL CHANGE BIOLOGY 2024; 30:e17151. [PMID: 38273511 DOI: 10.1111/gcb.17151] [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: 06/28/2023] [Revised: 10/11/2023] [Accepted: 12/12/2023] [Indexed: 01/27/2024]
Abstract
Observations of the annual cycle of atmospheric CO2 in high northern latitudes provide evidence for an increase in terrestrial metabolism in Arctic tundra and boreal forest ecosystems. However, the mechanisms driving these changes are not yet fully understood. One proposed hypothesis is that ecological change from disturbance, such as wildfire, could increase the magnitude and change the phase of net ecosystem exchange through shifts in plant community composition. Yet, little quantitative work has evaluated this potential mechanism at a regional scale. Here we investigate how fire disturbance influences landscape-level patterns of photosynthesis across western boreal North America. We use Alaska and Canadian large fire databases to identify the perimeters of wildfires, a Landsat-derived land cover time series to characterize plant functional types (PFTs), and solar-induced fluorescence (SIF) from the Orbiting Carbon Observatory-2 (OCO-2) as a proxy for photosynthesis. We analyze these datasets to characterize post-fire changes in plant succession and photosynthetic activity using a space-for-time approach. We find that increases in herbaceous and sparse vegetation, shrub, and deciduous broadleaf forest PFTs during mid-succession yield enhancements in SIF by 8-40% during June and July for 2- to 59-year stands relative to pre-fire controls. From the analysis of post-fire land cover changes within individual ecoregions and modeling, we identify two mechanisms by which fires contribute to long-term trends in SIF. First, increases in annual burning are shifting the stand age distribution, leading to increases in the abundance of shrubs and deciduous broadleaf forests that have considerably higher SIF during early- and mid-summer. Second, fire appears to facilitate a long-term shift from evergreen conifer to broadleaf deciduous forest in the Boreal Plain ecoregion. These findings suggest that increasing fire can contribute substantially to positive trends in seasonal CO2 exchange without a close coupling to long-term increases in carbon storage.
Collapse
Affiliation(s)
- Jinhyuk E Kim
- Department of Earth System Science, University of California, Irvine, California, USA
| | - Jonathan A Wang
- School of Biological Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Yue Li
- Department of Geography, University of California, Los Angeles, California, USA
| | - Claudia I Czimczik
- Department of Earth System Science, University of California, Irvine, California, USA
| | - James T Randerson
- Department of Earth System Science, University of California, Irvine, California, USA
| |
Collapse
|
10
|
He L, Rosa L, Lobell DB, Wang Y, Yin Y, Doughty R, Yao Y, Berry JA, Frankenberg C. The weekly cycle of photosynthesis in Europe reveals the negative impact of particulate pollution on ecosystem productivity. Proc Natl Acad Sci U S A 2023; 120:e2306507120. [PMID: 37983483 PMCID: PMC10710040 DOI: 10.1073/pnas.2306507120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 10/03/2023] [Indexed: 11/22/2023] Open
Abstract
Aerosols can affect photosynthesis through radiative perturbations such as scattering and absorbing solar radiation. This biophysical impact has been widely studied using field measurements, but the sign and magnitude at continental scales remain uncertain. Solar-induced fluorescence (SIF), emitted by chlorophyll, strongly correlates with photosynthesis. With recent advancements in Earth observation satellites, we leverage SIF observations from the Tropospheric Monitoring Instrument (TROPOMI) with unprecedented spatial resolution and near-daily global coverage, to investigate the impact of aerosols on photosynthesis. Our analysis reveals that on weekends when there is more plant-available sunlight due to less particulate pollution, 64% of regions across Europe show increased SIF, indicating more photosynthesis. Moreover, we find a widespread negative relationship between SIF and aerosol loading across Europe. This suggests the possible reduction in photosynthesis as aerosol levels increase, particularly in ecosystems limited by light availability. By considering two plausible scenarios of improved air quality-reducing aerosol levels to the weekly minimum 3-d values and levels observed during the COVID-19 period-we estimate a potential of 41 to 50 Mt net additional annual CO2 uptake by terrestrial ecosystems in Europe. This work assesses human impacts on photosynthesis via aerosol pollution at continental scales using satellite observations. Our results highlight i) the use of spatiotemporal variations in satellite SIF to estimate the human impacts on photosynthesis and ii) the potential of reducing particulate pollution to enhance ecosystem productivity.
Collapse
Affiliation(s)
- Liyin He
- Department of Global Ecology, Carnegie Institution for Science, Stanford, CA94305
| | - Lorenzo Rosa
- Department of Global Ecology, Carnegie Institution for Science, Stanford, CA94305
| | - David B. Lobell
- Department of Earth System Science, Stanford University, Stanford, CA94305
- Center on Food Security and the Environment, Stanford University, Stanford, CA94305
| | - Yuan Wang
- Department of Earth System Science, Stanford University, Stanford, CA94305
| | - Yi Yin
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA91125
- Department of Environmental Studies, New York University, New York, NY10003
| | - Russell Doughty
- College of Atmospheric and Geographic Sciences, University of Oklahoma, Norman, OK73019
| | - Yitong Yao
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA91125
| | - Joseph A. Berry
- Department of Global Ecology, Carnegie Institution for Science, Stanford, CA94305
| | - Christian Frankenberg
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA91125
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA91109
| |
Collapse
|
11
|
Zhang Y, Desai AR, Xiao J, Hartemink AE. Deeper topsoils enhance ecosystem productivity and climate resilience in arid regions, but not in humid regions. GLOBAL CHANGE BIOLOGY 2023; 29:6794-6811. [PMID: 37731366 DOI: 10.1111/gcb.16944] [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: 01/25/2023] [Revised: 08/16/2023] [Accepted: 08/28/2023] [Indexed: 09/22/2023]
Abstract
Understanding the controlling mechanisms of soil properties on ecosystem productivity is essential for sustaining productivity and increasing resilience under a changing climate. Here we investigate the control of topsoil depth (e.g., A horizons) on long-term ecosystem productivity. We used nationwide observations (n = 2401) of topsoil depth and multiple scaled datasets of gross primary productivity (GPP) for five ecosystems (cropland, forest, grassland, pasture, shrubland) over 36 years (1986-2021) across the conterminous USA. The relationship between topsoil depth and GPP is primarily associated with water availability, which is particularly significant in arid regions under grassland, shrubland, and cropland (r = .37, .32, .15, respectively, p < .0001). For every 10 cm increase in topsoil depth, the GPP increased by 114 to 128 g C m-2 year-1 in arid regions (r = .33 and .45, p < .0001). Paired comparison of relatively shallow and deep topsoils while holding other variables (climate, vegetation, parent material, soil type) constant showed that the positive control of topsoil depth on GPP occurred primarily in cropland (0.73, confidence interval of 0.57-0.84) and shrubland (0.75, confidence interval of 0.40-0.94). The GPP difference between deep and shallow topsoils was small and not statistically significant. Despite the positive control of topsoil depth on productivity in arid regions, its contribution (coefficients: .09-.33) was similar to that of heat (coefficients: .06-.39) but less than that of water (coefficients: .07-.87). The resilience of ecosystem productivity to climate extremes varied in different ecosystems and climatic regions. Deeper topsoils increased stability and decreased the variability of GPP under climate extremes in most ecosystems, especially in shrubland and grassland. The conservation of topsoil in arid regions and improvements of soil depth representation and moisture-retention mechanisms are critical for carbon-sequestration ecosystem services under a changing climate. These findings and relationships should also be included in Earth system models.
Collapse
Affiliation(s)
- Yakun Zhang
- FD Hole Soils Lab, Department of Soil Science, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Ankur R Desai
- Department of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Jingfeng Xiao
- Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, New Hampshire, USA
| | - Alfred E Hartemink
- FD Hole Soils Lab, Department of Soil Science, University of Wisconsin-Madison, Madison, Wisconsin, USA
| |
Collapse
|
12
|
Bansal S, Creed IF, Tangen BA, Bridgham SD, Desai AR, Krauss KW, Neubauer SC, Noe GB, Rosenberry DO, Trettin C, Wickland KP, Allen ST, Arias-Ortiz A, Armitage AR, Baldocchi D, Banerjee K, Bastviken D, Berg P, Bogard MJ, Chow AT, Conner WH, Craft C, Creamer C, DelSontro T, Duberstein JA, Eagle M, Fennessy MS, Finkelstein SA, Göckede M, Grunwald S, Halabisky M, Herbert E, Jahangir MMR, Johnson OF, Jones MC, Kelleway JJ, Knox S, Kroeger KD, Kuehn KA, Lobb D, Loder AL, Ma S, Maher DT, McNicol G, Meier J, Middleton BA, Mills C, Mistry P, Mitra A, Mobilian C, Nahlik AM, Newman S, O’Connell JL, Oikawa P, van der Burg MP, Schutte CA, Song C, Stagg CL, Turner J, Vargas R, Waldrop MP, Wallin MB, Wang ZA, Ward EJ, Willard DA, Yarwood S, Zhu X. Practical Guide to Measuring Wetland Carbon Pools and Fluxes. WETLANDS (WILMINGTON, N.C.) 2023; 43:105. [PMID: 38037553 PMCID: PMC10684704 DOI: 10.1007/s13157-023-01722-2] [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: 06/12/2023] [Accepted: 07/24/2023] [Indexed: 12/02/2023]
Abstract
Wetlands cover a small portion of the world, but have disproportionate influence on global carbon (C) sequestration, carbon dioxide and methane emissions, and aquatic C fluxes. However, the underlying biogeochemical processes that affect wetland C pools and fluxes are complex and dynamic, making measurements of wetland C challenging. Over decades of research, many observational, experimental, and analytical approaches have been developed to understand and quantify pools and fluxes of wetland C. Sampling approaches range in their representation of wetland C from short to long timeframes and local to landscape spatial scales. This review summarizes common and cutting-edge methodological approaches for quantifying wetland C pools and fluxes. We first define each of the major C pools and fluxes and provide rationale for their importance to wetland C dynamics. For each approach, we clarify what component of wetland C is measured and its spatial and temporal representativeness and constraints. We describe practical considerations for each approach, such as where and when an approach is typically used, who can conduct the measurements (expertise, training requirements), and how approaches are conducted, including considerations on equipment complexity and costs. Finally, we review key covariates and ancillary measurements that enhance the interpretation of findings and facilitate model development. The protocols that we describe to measure soil, water, vegetation, and gases are also relevant for related disciplines such as ecology. Improved quality and consistency of data collection and reporting across studies will help reduce global uncertainties and develop management strategies to use wetlands as nature-based climate solutions. Supplementary Information The online version contains supplementary material available at 10.1007/s13157-023-01722-2.
Collapse
Affiliation(s)
- Sheel Bansal
- U.S. Geological Survey, Northern Prairie Wildlife Research Center, Jamestown, ND USA
| | - Irena F. Creed
- Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON Canada
| | - Brian A. Tangen
- U.S. Geological Survey, Northern Prairie Wildlife Research Center, Jamestown, ND USA
| | - Scott D. Bridgham
- Institute of Ecology and Evolution, University of Oregon, Eugene, OR USA
| | - Ankur R. Desai
- Department of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, Madison, WI USA
| | - Ken W. Krauss
- U.S. Geological Survey, Wetland and Aquatic Research Center, Lafayette, LA USA
| | - Scott C. Neubauer
- Department of Biology, Virginia Commonwealth University, Richmond, VA USA
| | - Gregory B. Noe
- U.S. Geological Survey, Florence Bascom Geoscience Center, Reston, VA USA
| | | | - Carl Trettin
- U.S. Forest Service, Pacific Southwest Research Station, Davis, CA USA
| | - Kimberly P. Wickland
- U.S. Geological Survey, Geosciences and Environmental Change Science Center, Denver, CO USA
| | - Scott T. Allen
- Department of Natural Resources and Environmental Science, University of Nevada, Reno, Reno, NV USA
| | - Ariane Arias-Ortiz
- Ecosystem Science Division, Department of Environmental Science, Policy and Management, University of California, Berkeley, CA USA
| | - Anna R. Armitage
- Department of Marine Biology, Texas A&M University at Galveston, Galveston, TX USA
| | - Dennis Baldocchi
- Department of Environmental Science, Policy and Management, University of California, Berkeley, CA USA
| | - Kakoli Banerjee
- Department of Biodiversity and Conservation of Natural Resources, Central University of Odisha, Koraput, Odisha India
| | - David Bastviken
- Department of Thematic Studies – Environmental Change, Linköping University, Linköping, Sweden
| | - Peter Berg
- Department of Environmental Sciences, University of Virginia, Charlottesville, VA USA
| | - Matthew J. Bogard
- Department of Biological Sciences, University of Lethbridge, Lethbridge, AB Canada
| | - Alex T. Chow
- Earth and Environmental Sciences Programme, The Chinese University of Hong Kong, Shatin, Hong Kong SAR China
| | - William H. Conner
- Baruch Institute of Coastal Ecology and Forest Science, Clemson University, Georgetown, SC USA
| | - Christopher Craft
- O’Neill School of Public and Environmental Affairs, Indiana University, Bloomington, IN USA
| | - Courtney Creamer
- U.S. Geological Survey, Geology, Minerals, Energy and Geophysics Science Center, Menlo Park, CA USA
| | - Tonya DelSontro
- Department of Earth and Environmental Sciences, University of Waterloo, Waterloo, ON Canada
| | - Jamie A. Duberstein
- Baruch Institute of Coastal Ecology and Forest Science, Clemson University, Georgetown, SC USA
| | - Meagan Eagle
- U.S. Geological Survey, Woods Hole Coastal & Marine Science Center, Woods Hole, MA USA
| | | | | | - Mathias Göckede
- Department for Biogeochemical Signals, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Sabine Grunwald
- Soil, Water and Ecosystem Sciences Department, University of Florida, Gainesville, FL USA
| | - Meghan Halabisky
- School of Environmental and Forest Sciences, University of Washington, Seattle, WA USA
| | | | | | - Olivia F. Johnson
- U.S. Geological Survey, Northern Prairie Wildlife Research Center, Jamestown, ND USA
- Departments of Biology and Environmental Studies, Kent State University, Kent, OH USA
| | - Miriam C. Jones
- U.S. Geological Survey, Florence Bascom Geoscience Center, Reston, VA USA
| | - Jeffrey J. Kelleway
- School of Earth, Atmospheric and Life Sciences and Environmental Futures Research Centre, University of Wollongong, Wollongong, NSW Australia
| | - Sara Knox
- Department of Geography, McGill University, Montreal, Canada
| | - Kevin D. Kroeger
- U.S. Geological Survey, Woods Hole Coastal & Marine Science Center, Woods Hole, MA USA
| | - Kevin A. Kuehn
- School of Biological, Environmental, and Earth Sciences, University of Southern Mississippi, Hattiesburg, MS USA
| | - David Lobb
- Department of Soil Science, University of Manitoba, Winnipeg, MB Canada
| | - Amanda L. Loder
- Department of Geography, University of Toronto, Toronto, ON Canada
| | - Shizhou Ma
- School of Environment and Sustainability, University of Saskatchewan, Saskatoon, SK Canada
| | - Damien T. Maher
- Faculty of Science and Engineering, Southern Cross University, Lismore, NSW Australia
| | - Gavin McNicol
- Department of Earth and Environmental Sciences, University of Illinois Chicago, Chicago, IL USA
| | - Jacob Meier
- U.S. Geological Survey, Northern Prairie Wildlife Research Center, Jamestown, ND USA
| | - Beth A. Middleton
- U.S. Geological Survey, Wetland and Aquatic Research Center, Lafayette, LA USA
| | - Christopher Mills
- U.S. Geological Survey, Geology, Geophysics, and Geochemistry Science Center, Denver, CO USA
| | - Purbasha Mistry
- School of Environment and Sustainability, University of Saskatchewan, Saskatoon, SK Canada
| | - Abhijit Mitra
- Department of Marine Science, University of Calcutta, Kolkata, West Bengal India
| | - Courtney Mobilian
- O’Neill School of Public and Environmental Affairs, Indiana University, Bloomington, IN USA
| | - Amanda M. Nahlik
- Office of Research and Development, Center for Public Health and Environmental Assessments, Pacific Ecological Systems Division, U.S. Environmental Protection Agency, Corvallis, OR USA
| | - Sue Newman
- South Florida Water Management District, Everglades Systems Assessment Section, West Palm Beach, FL USA
| | - Jessica L. O’Connell
- Department of Ecosystem Science and Sustainability, Colorado State University, Fort Collins, CO USA
| | - Patty Oikawa
- Department of Earth and Environmental Sciences, California State University, East Bay, Hayward, CA USA
| | - Max Post van der Burg
- U.S. Geological Survey, Northern Prairie Wildlife Research Center, Jamestown, ND USA
| | - Charles A. Schutte
- Department of Environmental Science, Rowan University, Glassboro, NJ USA
| | - Changchun Song
- Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China
| | - Camille L. Stagg
- U.S. Geological Survey, Wetland and Aquatic Research Center, Lafayette, LA USA
| | - Jessica Turner
- Freshwater and Marine Science, University of Wisconsin-Madison, Madison, WI USA
| | - Rodrigo Vargas
- Department of Plant and Soil Sciences, University of Delaware, Newark, DE USA
| | - Mark P. Waldrop
- U.S. Geological Survey, Geology, Minerals, Energy and Geophysics Science Center, Menlo Park, CA USA
| | - Marcus B. Wallin
- Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Zhaohui Aleck Wang
- Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA USA
| | - Eric J. Ward
- U.S. Geological Survey, Wetland and Aquatic Research Center, Lafayette, LA USA
| | - Debra A. Willard
- U.S. Geological Survey, Florence Bascom Geoscience Center, Reston, VA USA
| | - Stephanie Yarwood
- Environmental Science and Technology, University of Maryland, College Park, MD USA
| | - Xiaoyan Zhu
- Key Laboratory of Songliao Aquatic Environment, Ministry of Education, Jilin Jianzhu University, Changchun, China
| |
Collapse
|
13
|
Song G, Wang Q, Zhuang J, Jin J. Timely estimation of leaf chlorophyll fluorescence parameters under varying light regimes by coupling light drivers to leaf traits. PHYSIOLOGIA PLANTARUM 2023; 175:e14048. [PMID: 37882289 DOI: 10.1111/ppl.14048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 10/02/2023] [Indexed: 10/27/2023]
Abstract
Unveiling informative chlorophyll a fluorescence (ChlF) parameters and leaf morphological/biochemical traits under varying light conditions is important in ecological studies but has less been investigated. In this study, the trait-ChlF relationship and regressive estimation of ChlF parameters from leaf traits under varying light conditions were investigated using a dataset of synchronous measurements of ChlF parameters and leaf morphological/biochemical traits in Mangifera indica L. The results showed that the relationships between ChlF parameters and leaf traits varied across light intensities, as indicated by different slopes and intercepts, highlighting the limitations of using leaf traits alone to capture the dynamics of ChlF parameters. Light drivers, on the other hand, showed a better predictive ability for light-dependent ChlF parameters compared to leaf traits, with light intensity having a large effect on light-dependent ChlF parameters. Furthermore, the responses of ФF and NPQ to light drivers differed between leaf types, with light intensity having an effect on ФF in shaded leaves, whereas it had a primary effect on NPQ in sunlit leaves. These results facilitate and deepen our understanding of how the light environment affects leaf structure and function and, therefore, provide the theoretical basis for understanding plant ecological strategies in response to the light environment.
Collapse
Affiliation(s)
- Guangman Song
- Faculty of Agriculture, Shizuoka University, Shizuoka, Japan
| | - Quan Wang
- Faculty of Agriculture, Shizuoka University, Shizuoka, Japan
| | - Jie Zhuang
- Graduate School of Science and Technology, Shizuoka University, Shizuoka, Japan
| | - Jia Jin
- Institute of Geography and Oceanography, Nanning Normal University, P. R. China
| |
Collapse
|
14
|
Panwar A, Migliavacca M, Nelson JA, Cortés J, Bastos A, Forkel M, Winkler AJ. Methodological challenges and new perspectives of shifting vegetation phenology in eddy covariance data. Sci Rep 2023; 13:13885. [PMID: 37620417 PMCID: PMC10449856 DOI: 10.1038/s41598-023-41048-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Accepted: 08/18/2023] [Indexed: 08/26/2023] Open
Abstract
While numerous studies report shifts in vegetation phenology, in this regard eddy covariance (EC) data, despite its continuous high-frequency observations, still requires further exploration. Furthermore, there is no general consensus on optimal methodologies for data smoothing and extracting phenological transition dates (PTDs). Here, we revisit existing methodologies and present new prospects to investigate phenological changes in gross primary productivity (GPP) from EC measurements. First, we present a smoothing technique of GPP time series through the derivative of its smoothed annual cumulative sum. Second, we calculate PTDs and their trends from a commonly used threshold method that identifies days with a fixed percentage of the annual maximum GPP. A systematic analysis is performed for various thresholds ranging from 0.1 to 0.7. Lastly, we examine the relation of PTDs trends to trends in GPP across the years on a weekly basis. Results from 47 EC sites with long time series (> 10 years) show that advancing trends in start of season (SOS) are strongest at lower thresholds but for the end of season (EOS) at higher thresholds. Moreover, the trends are variable at different thresholds for individual vegetation types and individual sites, outlining reasonable concerns on using a single threshold value. Relationship of trends in PTDs and weekly GPP reveal association of advanced SOS and delayed EOS to increase in immediate primary productivity, but not to the trends in overall seasonal productivity. Drawing on these analyses, we emphasise on abstaining from subjective choices and investigating relationship of PTDs trend to finer temporal trends of GPP. Our study examines existing methodological challenges and presents approaches that optimize the use of EC data in identifying vegetation phenological changes and their relation to carbon uptake.
Collapse
Affiliation(s)
- Annu Panwar
- Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Hans-Knöll-Straße 10, 07745, Jena, Germany.
| | - Mirco Migliavacca
- European Commission, Joint Research Centre (JRC), Ispra, Lombardia, Italy
| | - Jacob A Nelson
- Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Hans-Knöll-Straße 10, 07745, Jena, Germany
| | - José Cortés
- Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Hans-Knöll-Straße 10, 07745, Jena, Germany
| | - Ana Bastos
- Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Hans-Knöll-Straße 10, 07745, Jena, Germany
| | - Matthias Forkel
- TUD Dresden University of Technology, Faculty of Environmental Sciences, Dresden, Germany
| | - Alexander J Winkler
- Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Hans-Knöll-Straße 10, 07745, Jena, Germany
| |
Collapse
|
15
|
Li X, Ryu Y, Xiao J, Dechant B, Liu J, Li B, Jeong S, Gentine P. New-generation geostationary satellite reveals widespread midday depression in dryland photosynthesis during 2020 western U.S. heatwave. SCIENCE ADVANCES 2023; 9:eadi0775. [PMID: 37531429 PMCID: PMC10396307 DOI: 10.1126/sciadv.adi0775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Accepted: 06/29/2023] [Indexed: 08/04/2023]
Abstract
Emerging new-generation geostationary satellites have broadened the scope for studying the diurnal cycle of ecosystem functions. We exploit observations from the Geostationary Operational Environmental Satellite-R series to examine the effect of a severe U.S. heatwave in 2020 on the diurnal variations of ecosystem photosynthesis. We find divergent responses of photosynthesis to the heatwave across vegetation types and aridity gradients, with drylands exhibiting widespread midday and afternoon depression in photosynthesis. The diurnal centroid and peak time of dryland gross primary production (GPP) substantially shift toward earlier morning times, reflecting notable water and heat stress. Our geostationary satellite-based method outperforms traditional radiation-based upscaling methods from polar-orbiting satellite snapshots in estimating daily GPP and GPP loss during heatwaves. These findings underscore the potential of geostationary satellites for diurnal photosynthesis monitoring and highlight the necessity to consider the increased diurnal asymmetry in GPP under stress when evaluating carbon-climate interactions.
Collapse
Affiliation(s)
- Xing Li
- Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea
| | - Youngryel Ryu
- Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea
- Department of Landscape Architecture and Rural Systems Engineering, College of Agriculture and Life Sciences, Seoul National University, South Korea
| | - Jingfeng Xiao
- Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, USA
| | - Benjamin Dechant
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
- Leipzig University, Leipzig, Germany
| | - Jiangong Liu
- Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea
| | - Bolun Li
- Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea
| | - Sungchan Jeong
- Department of Landscape Architecture and Rural Systems Engineering, College of Agriculture and Life Sciences, Seoul National University, South Korea
| | - Pierre Gentine
- Department of Earth and Environmental Engineering, Columbia University, New York, NY, USA
| |
Collapse
|
16
|
Wang M, Zhang L. Synchronous Changes of GPP and Solar-Induced Chlorophyll Fluorescence in a Subtropical Evergreen Coniferous Forest. PLANTS (BASEL, SWITZERLAND) 2023; 12:plants12112224. [PMID: 37299202 DOI: 10.3390/plants12112224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 05/27/2023] [Accepted: 05/29/2023] [Indexed: 06/12/2023]
Abstract
Using in situ near-surface observations of solar-induced chlorophyll fluorescence (SIF) and gross primary productivity (GPP) of a subtropical evergreen coniferous forest in southern China, this study analyzed the dynamics of SIF, GPP and their environmental responses, and explored the potential of SIF in characterizing the variation of GPP. The results showed that SIF and GPP have similar diurnal and seasonal variation and both reach the highest value in summer, indicating that the SIF can be applied to indicate the seasonal variation of GPP for the subtropical evergreen co-niferous. With the increase in temporal scale, the correlation between SIF and GPP becomes more linear. The diurnal variations of both SIF and GPP were characterized by photosynthetically active radiation (PAR), the seasonal variations of SIF and GPP were influenced by air temperature (Ta) and PAR. Probably due to the absent of drought stress during the study period, no significant correlation was detected between soil water content (SWC) and either SIF or GPP. With the in-crease in Ta, PAR or SWC, the linear correlation between the SIF and GPP gradually decreased, and when Ta or PAR was relatively higher, the correlation between SIF and GPP become weakly. Further research is still needed to illustrate the relationship between SIF and GPP under drought condition which occurred frequently in this region based on longer observation.
Collapse
Affiliation(s)
- Mingming Wang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Leiming Zhang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| |
Collapse
|
17
|
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.
Collapse
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
| |
Collapse
|
18
|
Sun Y, Gu L, Wen J, van der Tol C, Porcar-Castell A, Joiner J, Chang CY, 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 I-Harnessing theory. GLOBAL CHANGE BIOLOGY 2023; 29:2926-2952. [PMID: 36799496 DOI: 10.1111/gcb.16634] [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] [Accepted: 11/08/2022] [Indexed: 05/03/2023]
Abstract
Solar-induced chlorophyll fluorescence (SIF) is a remotely sensed optical signal emitted during the light reactions of photosynthesis. The past two decades have witnessed an explosion in availability of SIF data at increasingly higher spatial and temporal resolutions, sparking applications in diverse research sectors (e.g., ecology, agriculture, hydrology, climate, and socioeconomics). These applications must deal with complexities caused by tremendous variations in scale and the impacts of interacting and superimposing plant physiology and three-dimensional vegetation structure on the emission and scattering of SIF. At present, these complexities have not been overcome. To advance future research, the two companion reviews aim to (1) develop an analytical framework for inferring terrestrial vegetation structures and function that are tied to SIF emission, (2) synthesize progress and identify challenges in SIF research via the lens of multi-sector applications, and (3) map out actionable solutions to tackle these challenges and offer our vision for research priorities over the next 5-10 years based on the proposed analytical framework. This paper is the first of the two companion reviews, and theory oriented. It introduces a theoretically rigorous yet practically applicable analytical framework. Guided by this framework, we offer theoretical perspectives on three overarching questions: (1) The forward (mechanism) question-How are the dynamics of SIF affected by terrestrial ecosystem structure and function? (2) The inference question: What aspects of terrestrial ecosystem structure, function, and service can be reliably inferred from remotely sensed SIF and how? (3) The innovation question: What innovations are needed to realize the full potential of SIF remote sensing for real-world applications under climate change? The analytical framework elucidates that process complexity must be appreciated in inferring ecosystem structure and function from the observed SIF; this framework can serve as a diagnosis and inference tool for versatile applications across diverse spatial and temporal scales.
Collapse
Affiliation(s)
- Ying Sun
- 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
| | - Jiaming Wen
- School of Integrative Plant Science, Soil and Crop Sciences Section, Cornell University, Ithaca, New York, 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
| | - 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
| | - 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
| |
Collapse
|
19
|
Lee B, Kwon H, Zhao P, Tenhunen J. Improved gross primary production estimation in rice fields through integrated multi-scale methodologies. PLANT-ENVIRONMENT INTERACTIONS (HOBOKEN, N.J.) 2023; 4:163-174. [PMID: 37362422 PMCID: PMC10290427 DOI: 10.1002/pei3.10109] [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: 01/03/2023] [Revised: 04/15/2023] [Accepted: 05/01/2023] [Indexed: 06/28/2023]
Abstract
Understanding productivity in agricultural ecosystems is important, as it plays a significant role in modifying regional carbon balances and capturing carbon in the form of agricultural yield. This study in particular combines information from flux determinations using the eddy covariance (EC) methodology, process-based modeling of carbon gain, remotely (satellite) sensed vegetation indices (VIs), and field surveys to assess the gross primary production (GPP) of rice, which is a primary food crop worldwide. This study relates two major variables determining GPP. The first is leaf area index (LAI) and carboxylation capacity of the rice canopy (Vcuptake), and the second being MODIS remotely sensed vegetation indices (VIs). Success in applying such derived relationships has allowed GPP to be remotely determined over the seasonal course of rice development. The relationship to VIs of both LAI and Vcuptake was analyzed first by using the regression approaches commonly applied in remote sensing studies. However, the resultant GPP estimations derived from these generic models were not consistently accurate and led to a large proportion of underestimations. The new, alternative approach developed to estimate LAI and Vcuptake uses consistent development curves for rice (i.e., relies on consistent biological regulations of plant development). The modeled GPP based on this consistent development curve for both LAI and Vcuptake agreed with R 2 from 0.76 to 0.92 (within the 95% confidence interval). The results of this study demonstrate that improved linkages between ground-based survey data, eddy flux measurements, process-based models, and remote sensing data can be constructed to estimate GPP in rice paddies. This study suggests further that the conceptual application of the consistent development curve, such as the combining of different scale measurements, has the potential to predict GPP better than the common practice of utilizing simple linear models, when seeking to estimate the critical parameters that influence carbon gain and agricultural yields.
Collapse
Affiliation(s)
- Bora Lee
- Warm Temperate and Subtropical Forest Research CenterNational Institute of Forest ScienceSeogwipo‐si63582South Korea
| | - Hyojung Kwon
- Forest Ecosystems & SocietyOregon State UniversityCovallisOregonUSA
| | - Peng Zhao
- Department of Health and Environmental Sciences, Plant EcologyJiaotong‐Liverpool UniversityXi'an, SuzhouP.R. China
| | | |
Collapse
|
20
|
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.
Collapse
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
| |
Collapse
|
21
|
Zhang Z, Cescatti A, Wang YP, Gentine P, Xiao J, Guanter L, Huete AR, Wu J, Chen JM, Ju W, Peñuelas J, Zhang Y. Large diurnal compensatory effects mitigate the response of Amazonian forests to atmospheric warming and drying. SCIENCE ADVANCES 2023; 9:eabq4974. [PMID: 37235657 DOI: 10.1126/sciadv.abq4974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 04/25/2023] [Indexed: 05/28/2023]
Abstract
Photosynthesis and evapotranspiration in Amazonian forests are major contributors to the global carbon and water cycles. However, their diurnal patterns and responses to atmospheric warming and drying at regional scale remain unclear, hindering the understanding of global carbon and water cycles. Here, we used proxies of photosynthesis and evapotranspiration from the International Space Station to reveal a strong depression of dry season afternoon photosynthesis (by 6.7 ± 2.4%) and evapotranspiration (by 6.1 ± 3.1%). Photosynthesis positively responds to vapor pressure deficit (VPD) in the morning, but negatively in the afternoon. Furthermore, we projected that the regionally depressed afternoon photosynthesis will be compensated by their increases in the morning in future dry seasons. These results shed new light on the complex interplay of climate with carbon and water fluxes in Amazonian forests and provide evidence on the emerging environmental constraints of primary productivity that may improve the robustness of future projections.
Collapse
Affiliation(s)
- Zhaoying Zhang
- Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, International Institute for Earth System Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
- Yuxiu Postdoctoral Institute, Nanjing University, Nanjing, Jiangsu 210023, China
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu 210023, China
| | | | - Ying-Ping Wang
- CSIRO, Oceans and Atmosphere, Private Bag 1, Aspendale, Victoria 3195, Australia
| | - Pierre Gentine
- Department of Earth and Environmental Engineering, Columbia University, New York, NY, USA
| | - Jingfeng Xiao
- Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, USA
| | - Luis Guanter
- Research Institute of Water and Environmental Engineering (IIAMA), Department of Applied Physics, Polytechnic University of Valencia, Valencia, Spain
| | - Alfredo R Huete
- School of Life Sciences, University of Technology Sydney, Sydney, New South Wales, Australia
| | - Jin Wu
- School of Biological Sciences, The University of Hong Kong, Pokfulam, Hong Kong
- State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong, China
| | - Jing M Chen
- Department of Geography and Planning, University of Toronto, Toronto, Ontario, Canada
| | - Weimin Ju
- Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, International Institute for Earth System Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Josep Peñuelas
- CSIC, Global ecology Unit CREAF-CSIC-UAB, Bellaterra 08193, Catalonia, Spain
- CREAF, Cerdanyola del Vallès 08193, Catalonia, Spain
| | - Yongguang Zhang
- Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, International Institute for Earth System Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu 210023, China
- International Joint Carbon Neutrality Laboratory, Nanjing University, Nanjing, Jiangsu 210023 China
| |
Collapse
|
22
|
Zhang W, Jin H, Jamali S, Duan Z, Wu M, Ran Y, Ardö J, Eklundh L, Jönsson AM, Sun H, Hu G, Wu X, Yun H, Wu Q, Fu Z, Yu K, Tian F, Tagesson T, Li X, Xiao J. Convergence and divergence emerging in climatic controls of polynomial trends for northern ecosystem productivity over 2000-2018. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 874:162425. [PMID: 36870485 DOI: 10.1016/j.scitotenv.2023.162425] [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: 01/01/2023] [Revised: 02/17/2023] [Accepted: 02/19/2023] [Indexed: 06/18/2023]
Abstract
Recent rapid warming has caused uneven impacts on the composition, structure, and functioning of northern ecosystems. It remains unknown how climatic drivers control linear and non-linear trends in ecosystem productivity. Based on a plant phenology index (PPI) product at a spatial resolution of 0.05° over 2000-2018, we used an automated polynomial fitting scheme to detect and characterize trend types (i.e., polynomial trends and no-trends) in the yearly-integrated PPI (PPIINT) for northern (> 30°N) ecosystems and their dependence on climatic drivers and ecosystem types. The averaged slope for the linear trends (p < 0.05) of PPIINT was positive across all the ecosystems, among which deciduous broadleaved forests and evergreen needle-leaved forests (ENF) showed the highest and lowest mean slopes, respectively. More than 50% of the pixels in ENF, arctic and boreal shrublands, and permanent wetlands (PW) had linear trends. A large fraction of PW also showed quadratic and cubic trends. These trend patterns agreed well with estimates of global vegetation productivity based on solar-induced chlorophyll fluorescence. Across all the biomes, PPIINT in pixels with linear trends showed lower mean values and higher partial correlation coefficients with temperature or precipitation than in pixels without linear trends. Overall, our study revealed the emergence of latitudinal convergence and divergence in climatic controls on the linear and non-linear trends of PPIINT, implying that northern shifts of vegetation and climate change may potentially increase the non-linear nature of climatic controls on ecosystem productivity. These results can improve our understanding and prediction of climate-induced changes in plant phenology and productivity and facilitate sustainable management of ecosystems by accounting for their resilience and vulnerability to future climate change.
Collapse
Affiliation(s)
- Wenxin Zhang
- Department of Physical Geography and Ecosystem Science, Lund University, SE-22362 Lund, Sweden.
| | - Hongxiao Jin
- Department of Physical Geography and Ecosystem Science, Lund University, SE-22362 Lund, Sweden
| | - Sadegh Jamali
- Department of Technology and Society, Lund University, SE-221 00 Lund, Sweden
| | - Zheng Duan
- Department of Physical Geography and Ecosystem Science, Lund University, SE-22362 Lund, Sweden
| | - Mousong Wu
- International Institute for Earth System Sciences, Nanjing University, Nanjing, China; Jiangsu Provincial Key Laboratory of Geographic Information Technology, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Youhua Ran
- Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China; University of the Chinese Academy Sciences, No. 19A Yuquan Road, Shijingshan District, Beijing 100049, China
| | - Jonas Ardö
- Department of Physical Geography and Ecosystem Science, Lund University, SE-22362 Lund, Sweden
| | - Lars Eklundh
- Department of Physical Geography and Ecosystem Science, Lund University, SE-22362 Lund, Sweden
| | - Anna Maria Jönsson
- Department of Physical Geography and Ecosystem Science, Lund University, SE-22362 Lund, Sweden
| | - Huaiwei Sun
- School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Guojie Hu
- Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, 320 West Donggang Road, Lanzhou 730000, China
| | - Xiaodong Wu
- University of the Chinese Academy Sciences, No. 19A Yuquan Road, Shijingshan District, Beijing 100049, China; Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, 320 West Donggang Road, Lanzhou 730000, China
| | - Hanbo Yun
- Beiluhe Observation Station of Frozen Soil Environment and Engineering, State Key Laboratory of Frozen Soil Engineering, Northwest Institute of Eco-environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
| | - Qingbai Wu
- University of the Chinese Academy Sciences, No. 19A Yuquan Road, Shijingshan District, Beijing 100049, China; Beiluhe Observation Station of Frozen Soil Environment and Engineering, State Key Laboratory of Frozen Soil Engineering, Northwest Institute of Eco-environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
| | - Ziteng Fu
- University of the Chinese Academy Sciences, No. 19A Yuquan Road, Shijingshan District, Beijing 100049, China; Beiluhe Observation Station of Frozen Soil Environment and Engineering, State Key Laboratory of Frozen Soil Engineering, Northwest Institute of Eco-environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
| | - Kailiang Yu
- High Meadows Environmental Institute, Princeton University, Princeton, NJ 08544, USA
| | - Feng Tian
- School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
| | - Torbern Tagesson
- Department of Physical Geography and Ecosystem Science, Lund University, SE-22362 Lund, Sweden; Department of Geosciences and Natural Resource Management, University of Copenhagen, Øster Voldgade 10, DK-1350 Copenhagen, Denmark
| | - Xing Li
- Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea
| | - Jingfeng Xiao
- Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA
| |
Collapse
|
23
|
Fang J, Li X, Xiao J, Yan X, Li B, Liu F. Vegetation photosynthetic phenology dataset in northern terrestrial ecosystems. Sci Data 2023; 10:300. [PMID: 37208404 DOI: 10.1038/s41597-023-02224-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 05/10/2023] [Indexed: 05/21/2023] Open
Abstract
Vegetation phenology can profoundly modulate the climate-biosphere interactions and thus plays a crucial role in regulating the terrestrial carbon cycle and the climate. However, most previous phenology studies rely on traditional vegetation indices, which are inadequate to characterize the seasonal activity of photosynthesis. Here, we generated an annual vegetation photosynthetic phenology dataset with a spatial resolution of 0.05 degrees from 2001 to 2020, using the latest gross primary productivity product based on solar-induced chlorophyll fluorescence (GOSIF-GPP). We combined smoothing splines with multiple change-point detection to retrieve the phenology metrics: start of the growing season (SOS), end of the growing season (EOS), and length of growing season (LOS) for terrestrial ecosystems above 30° N latitude (Northern Biomes). Our phenology product can be used to validate and develop phenology or carbon cycle models and monitor the climate change impacts on terrestrial ecosystems.
Collapse
Affiliation(s)
- Jing Fang
- CAS Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, China
- Center of Plant Ecology, Core Botanical Gardens, Chinese Academy of Sciences, Wuhan, 430074, China
| | - Xing Li
- Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea
| | - Jingfeng Xiao
- Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, USA
| | - Xiaodong Yan
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China
| | - Bolun Li
- Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea
| | - Feng Liu
- CAS Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, China.
- Center of Plant Ecology, Core Botanical Gardens, Chinese Academy of Sciences, Wuhan, 430074, China.
| |
Collapse
|
24
|
Kashyap R, Kuttippurath J, Patel VK. Improved air quality leads to enhanced vegetation growth during the COVID-19 lockdown in India. APPLIED GEOGRAPHY (SEVENOAKS, ENGLAND) 2023; 151:102869. [PMID: 36619606 PMCID: PMC9805897 DOI: 10.1016/j.apgeog.2022.102869] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 12/28/2022] [Accepted: 12/29/2022] [Indexed: 06/17/2023]
Abstract
The direct effect of pandemic induced lockdown (LD) on environment is widely explored, but its secondary impacts remain largely unexplored. Therefore, we assess the response of surface greenness and photosynthetic activity to the LD-induced improvement of air quality in India. Our analysis reveals a significant improvement in air quality marked by reduced levels of aerosols (AOD, -19.27%) and Particulate Matter (PM 2.5, -23%) during LD (2020)from pre-LD (March-September months for the period 2017-2019). The vegetation exhibits a positive response, reflected by the increase in surface greenness [Enhanced Vegetation Index (EVI, +10.4%)] and photosynthetic activity [Solar Induced Fluorescence (SiF, +11%)], during LD from pre-LD that coincides with two major agricultural seasons of India; Zaid (March-May) and Kharif (June-September). In addition, the croplands show a higher response [two-fold in EVI (14.45%) and four-fold in SiF (17.7%)] than that of forests. The prolonged growing period (phenology) and high rate of photosynthesis (intensification) led to the enhanced greening during LD owing to the reduced atmospheric pollution. This study, therefore, provides new insights into the response of vegetation to the improved air quality, which would give ideas to counter the challenges of food security in the context of climate pollution, and combat global warming by more greening.
Collapse
Affiliation(s)
- Rahul Kashyap
- CORAL, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India
| | - J Kuttippurath
- CORAL, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India
| | - V K Patel
- CORAL, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India
| |
Collapse
|
25
|
Li F, Hao D, Zhu Q, Yuan K, Braghiere RK, He L, Luo X, Wei S, Riley WJ, Zeng Y, Chen M. Vegetation clumping modulates global photosynthesis through adjusting canopy light environment. GLOBAL CHANGE BIOLOGY 2023; 29:731-746. [PMID: 36281563 PMCID: PMC10100496 DOI: 10.1111/gcb.16503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Accepted: 10/10/2022] [Indexed: 06/16/2023]
Abstract
The spatial dispersion of photoelements within a vegetation canopy, quantified by the clumping index (CI), directly regulates the within-canopy light environment and photosynthesis rate, but is not commonly implemented in terrestrial biosphere models to estimate the ecosystem carbon cycle. A few global CI products have been developed recently with remote sensing measurements, making it possible to examine the global impacts of CI. This study deployed CI in the radiative transfer scheme of the Community Land Model version 5 (CLM5) and used the revised CLM5 to quantitatively evaluate the extent to which CI can affect canopy absorbed radiation and gross primary production (GPP), and for the first time, considering the uncertainty and seasonal variation of CI with multiple remote sensing products. Compared to the results without considering the CI impact, the revised CLM5 estimated that sunlit canopy absorbed up to 9%-15% and 23%-34% less direct and diffuse radiation, respectively, while shaded canopy absorbed 3%-18% more diffuse radiation across different biome types. The CI impacts on canopy light conditions included changes in canopy light absorption, and sunlit-shaded leaf area fraction related to nitrogen distribution and thus the maximum rate of Rubisco carboxylase activity (Vcmax ), which together decreased photosynthesis in sunlit canopy by 5.9-7.2 PgC year-1 while enhanced photosynthesis by 6.9-8.2 PgC year-1 in shaded canopy. With higher light use efficiency of shaded leaves, shaded canopy increased photosynthesis compensated and exceeded the lost photosynthesis in sunlit canopy, resulting in 1.0 ± 0.12 PgC year-1 net increase in GPP. The uncertainty of GPP due to the different input CI datasets was much larger than that caused by CI seasonal variations, and was up to 50% of the magnitude of GPP interannual variations in the tropical regions. This study highlights the necessity of considering the impacts of CI and its uncertainty in terrestrial biosphere models.
Collapse
Affiliation(s)
- Fa Li
- Department of Forest and Wildlife EcologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Dalei Hao
- Atmospheric Sciences and Global Change DivisionPacific Northwest National LaboratoryRichlandWashingtonUSA
| | - Qing Zhu
- Climate and Ecosystem Sciences Division, Climate Sciences DepartmentLawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA
| | - Kunxiaojia Yuan
- Climate and Ecosystem Sciences Division, Climate Sciences DepartmentLawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA
| | - Renato K. Braghiere
- Division of Geological and Planetary SciencesCalifornia Institute of TechnologyPasadenaCaliforniaUSA
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCaliforniaUSA
| | - Liming He
- Canada Centre for Mapping and Earth ObservationNatural Resources CanadaOttawaOntarioCanada
| | - Xiangzhong Luo
- Department of GeographyNational University of SingaporeSingaporeSingapore
| | - Shanshan Wei
- Centre for Remote Imaging, Sensing and ProcessingNational University of SingaporeSingaporeSingapore
| | - William J. Riley
- Climate and Ecosystem Sciences Division, Climate Sciences DepartmentLawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA
| | - Yelu Zeng
- Department of Forest and Wildlife EcologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Min Chen
- Department of Forest and Wildlife EcologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| |
Collapse
|
26
|
Shi X, Chen F, Shi M, Ding H, Li Y. Construction and application of Optimized Comprehensive Drought Index based on lag time: A case study in the middle reaches of Yellow River Basin, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 857:159692. [PMID: 36302417 DOI: 10.1016/j.scitotenv.2022.159692] [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: 08/15/2022] [Revised: 09/29/2022] [Accepted: 10/20/2022] [Indexed: 06/16/2023]
Abstract
Drought is a complex and dynamic natural phenomenon. A single drought index can hardly reflect the multi-type characteristics of drought, and comprehensive drought indices that incorporate data from multiple sources have been proposed recently. In this study, an Optimized Comprehensive Drought Index (OCDI) was constructed by taking into account the lag time of meteorological drought, agricultural drought and hydrological drought. The Standardized Precipitation Evapotranspiration Index (SPEI), Vegetation Condition Index (VCI), and Water Storage Deficit Index (WSDI) represented the three types of droughts, respectively. Specifically, we used the Solar-induced Chlorophyll Fluorescence (SIF) to characterize the vegetation condition instead of the Normalized Difference Vegetation Index (NDVI). The application results of the proposed drought index in the middle reaches of Yellow River basin (MRYRB) showed that the lag time of different types of drought indices had seasonal differences, with a shorter lag time in summer (0-4 months) and a longer lag time in winter and spring (> 4 months). For typical drought events, the drought intensity and duration identified by OCDI were compatible with the drought evolution characteristics and consistent with the historical records, therefore, OCDI is more suitable for drought monitoring in the study area. Based on the monitoring results of the OCDI, the average number of droughts in the MRYRB was 16 times, with a duration of 2.8 months and an average drought intensity of 0.28 (at moderate drought grade). Drought times and intensity were higher in the northwestern part of the study area, and spring was a high-frequency period for drought occurrences.
Collapse
Affiliation(s)
- Xiaoliang Shi
- College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China
| | - Fei Chen
- College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China.
| | - Mengqi Shi
- College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China
| | - Hao Ding
- College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China
| | - Yi Li
- College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China
| |
Collapse
|
27
|
Yu T, Jiapaer G, Long G, Li X, Jing J, Liu Y, De Maeyer P, Van de Voorde T. Interannual and seasonal relationships between photosynthesis and summer soil moisture in the Ili River basin, Xinjiang, 2000-2018. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 856:159191. [PMID: 36195150 DOI: 10.1016/j.scitotenv.2022.159191] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 09/21/2022] [Accepted: 09/29/2022] [Indexed: 06/16/2023]
Abstract
Soil moisture (SM) is essential for controlling terrestrial carbon uptake, as it directly provides moisture for photosynthesis, especially in arid and semiarid regions. We selected the arid and semiarid Ili River basin (IRB) of Xinjiang as the study area, and investigated the spatial and temporal characteristics and interrelationships with SM and photosynthesis from 2000 to 2018 using the ERA5 products and solar-induced chlorophyll fluorescence (SIF). SM and photosynthesis showed a decreasing trend during the study period. Compared with those in spring and autumn, the variation of summer SM and SIF was more consistent with the interannual variation. Anomaly analysis showed that negative SM anomalies were most profound in 2012-2015, 2008, and 2014. Additionally, we quantified the effect of seasonal SM deficits on photosynthesis by performing model-based experiments. The results indicated that the gross primary productivity (GPP) simulated by the P-model could capture the characteristics of photosynthesis in the IRB, which had a high correlation with SIF (R2 = 0.82, p < 0.001). In 2012-2015, 2008, and 2014, SM deficits caused more GPP reduction in the summers than in the springs or the autumns. The trends were mainly visible in the northern IRB, where GPP was below 40 % of the multi-year mean, and SM was below 23 %. GPP decreased more significantly in grassland than in the forest under the influence of SM deficit. This study reveals seasonal differences in the effects of SM deficit on photosynthesis and emphasizes that the summer SM deficit was the main factor responsible for decreases in GPP in the IRB during the study period. These findings contribute to a better understanding of the relationships between photosynthesis and environmental factors, and provide a reference for an accurate assessment of the regional carbon cycle.
Collapse
Affiliation(s)
- Tao Yu
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; University of Chinese Academy of Sciences, Beijing 100049, China; Department of Geography, Ghent University, Ghent 9000, Belgium
| | - Guli Jiapaer
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; CAS Research Center for Ecology and Environment of Central Asia, Urumqi 830011, China; Sino-Belgian Laboratory for Geo-Information, Ghent 9000, Belgium.
| | - Gang Long
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xu Li
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jingyu Jing
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ying Liu
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; CAS Research Center for Ecology and Environment of Central Asia, Urumqi 830011, China
| | - Philippe De Maeyer
- Department of Geography, Ghent University, Ghent 9000, Belgium; Sino-Belgian Laboratory for Geo-Information, Ghent 9000, Belgium
| | - Tim Van de Voorde
- Department of Geography, Ghent University, Ghent 9000, Belgium; Sino-Belgian Laboratory for Geo-Information, Ghent 9000, Belgium
| |
Collapse
|
28
|
Chen J, Shao Z, Huang X, Zhuang Q, Dang C, Cai B, Zheng X, Ding Q. Assessing the impact of drought-land cover change on global vegetation greenness and productivity. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 852:158499. [PMID: 36058327 DOI: 10.1016/j.scitotenv.2022.158499] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Revised: 08/29/2022] [Accepted: 08/30/2022] [Indexed: 06/15/2023]
Abstract
Drought-land cover change (D-LCC) is considered to be an important stress factor that affects vegetation greenness and productivity (VG&P) in global terrestrial ecosystems. Understanding the effects of D-LCC on VG&P benefits the development of terrestrial ecosystem models and the prediction of ecosystem evolution. However, till today, the mechanism remains underexploited. In this study, based on the Theil-Sen median estimator and Mann-Kendall test, Hurst exponent evaluation and rescaled range analysis (R/S), Pearson and Partial correlation coefficient analyses, we explore the spatiotemporal distribution characteristics and future trends of Leaf area index (LAI), Net primary productivity (NPP), Solar-induced chlorophyll fluorescence (SIF), Standardized precipitation evapotranspiration index (SPEI), Soil moisture (SM), Land cover type (LC), and the impact mechanism of D-LCC on global VG&P. Our results provide four major insights. First, three independent satellite observations consistently indicate that the world is experiencing an increasing trend of VG&P: LAI (17.69 %), NPP (20.32 %) and SIF (16.46 %). Nonetheless, productivity-reducing trends are unfolding in some tropical regions, notably the Amazon rainforest and the Congo basin. Second, from 2001 to 2020, the frequency, severity, duration, and scope of global droughts have been increasing. Third, the impact of land cover change on global VG&P is region-dependent. Finally, our results indicate that the continuous growth of VG&P in the global vegetation area is likely to become more difficult to maintain.
Collapse
Affiliation(s)
- Jinlong Chen
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072, China
| | - Zhenfeng Shao
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072, China.
| | - Xiao Huang
- Department of Geosciences, University of Arkansas, Fayetteville, AR 72701, USA
| | - Qingwei Zhuang
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072, China
| | - Chaoya Dang
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072, China
| | - Bowen Cai
- School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China
| | - Xueke Zheng
- School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, China
| | - Qing Ding
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072, China
| |
Collapse
|
29
|
Quantifying the impacts of land cover change on gross primary productivity globally. Sci Rep 2022; 12:18398. [PMID: 36319733 PMCID: PMC9626452 DOI: 10.1038/s41598-022-23120-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 10/25/2022] [Indexed: 11/06/2022] Open
Abstract
Historically, humans have cleared many forests for agriculture. While this substantially reduced ecosystem carbon storage, the impacts of these land cover changes on terrestrial gross primary productivity (GPP) have not been adequately resolved yet. Here, we combine high-resolution datasets of satellite-derived GPP and environmental predictor variables to estimate the potential GPP of forests, grasslands, and croplands around the globe. With a mean GPP of 2.0 kg C m-2 yr-1 forests represent the most productive land cover on two thirds of the total area suitable for any of these land cover types, while grasslands and croplands on average reach 1.5 and 1.8 kg C m-2 yr-1, respectively. Combining our potential GPP maps with a historical land-use reconstruction indicates a 4.4% reduction in global GPP from agricultural expansion. This land-use-induced GPP reduction is amplified in some future scenarios as a result of ongoing deforestation (e.g., the large-scale bioenergy scenario SSP4-3.4) but partly reversed in other scenarios (e.g., the sustainability scenario SSP1-1.9) due to agricultural abandonment. Comparing our results to simulations from state-of-the-art Earth System Models, we find that all investigated models deviate substantially from our estimates and from each other. Our maps could be used as a benchmark to reduce this inconsistency, thereby improving projections of land-based climate mitigation potentials.
Collapse
|
30
|
Effects of Low Temperature on the Relationship between Solar-Induced Chlorophyll Fluorescence and Gross Primary Productivity across Different Plant Function Types. REMOTE SENSING 2022. [DOI: 10.3390/rs14153716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Solar-induced chlorophyll fluorescence (SIF) has been recognized as a proxy of gross primary production (GPP) across various terrestrial biomes. However, the effects of low temperature on SIF and GPP among different plant function types (PFTs) have not yet been well-explored. To gain a better understanding of the relationship between SIF and GPP, we investigated the variation in the GPP/SIF ratio in response to low-temperature conditions using satellite and tower-based datasets. Based on the TROPOMI SIF product and FLUXCOM GPP data, we found that the SIF and GPP exhibited consistent seasonal and spatial patterns, while the GPP/SIF ratio differed for different PFTs. The GPP/SIF ratio for forest types was generally higher than 10 gC·d−1·mw−1·nm·sr, whereas the GPP/SIF ratio for grass and crop types was generally lower than 10 gC·d−1·mw−1·nm·sr. In addition, there were noticeable differences in the seasonal pattern of the GPP/SIF ratio between the selected samples that experienced low-temperature stress (below 10 °C, defined as group A) and those that grew under relatively warm conditions (above 10 °C throughout the year, defined as group B). The GPP/SIF ratio for group A generally exhibited a “hump-shaped” seasonal pattern, and that for group B showed a slightly “bowl-shaped” seasonal pattern, which means it is important to consider the effects of temperature on the SIF-GPP relationship. Through linear regression and correlation analysis, we demonstrate that there was a positive correlation between the GPP/SIF ratio and temperature for group A, with a wide temperature range including low-temperature conditions, indicating that, in this case, temperature affected the SIF–GPP relationship; however, for group B—with a temperature higher than 10 °C throughout the year—the GPP/SIF ratio was not consistently affected by temperature. The response of GPP/SIF to low temperature stress was confirmed by tower-based observations at a C3 cropland (C3CRO) site and a boreal evergreen needleleaf forest (BoENF) site. Although the relationship between the GPP/SIF ratio and temperature differed among PFTs, the GPP/SIF ratio decreased under low-temperature conditions for PFTs. Therefore, the GPP/SIF ratio was not constant and was largely influenced by low temperature for different PFTs, thus highlighting the importance of incorporating temperature into SIF-based GPP estimation.
Collapse
|
31
|
Fu YH, Li X, Chen S, Wu Z, Su J, Li X, Li S, Zhang J, Tang J, Xiao J. Soil moisture regulates warming responses of autumn photosynthetic transition dates in subtropical forests. GLOBAL CHANGE BIOLOGY 2022; 28:4935-4946. [PMID: 35642473 DOI: 10.1111/gcb.16227] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 03/10/2022] [Accepted: 04/24/2022] [Indexed: 06/15/2023]
Abstract
Autumn phenology plays a key role in regulating the terrestrial carbon and water balance and their feedbacks to the climate. However, the mechanisms underlying autumn phenology are still poorly understood, especially in subtropical forests. In this study, we extracted the autumn photosynthetic transition dates (APTD) in subtropical China over the period 2003-2017 based on a global, fine-resolution solar-induced chlorophyll fluorescence (SIF) dataset (GOSIF) using four fitting methods, and then explored the temporal-spatial variations of APTD and its underlying mechanisms using partial correlation analysis and machine learning methods. We further predicted the APTD shifts under future climate warming conditions by applying process-based and machine learning-based models. We found that the APTD was significantly delayed, with an average rate of 7.7 days per decade, in subtropical China during 2003-2017. Both partial correlation analysis and machine learning methods revealed that soil moisture was the primary driver responsible for the APTD changes in southern subtropical monsoon evergreen forest (SEF) and middle subtropical evergreen forest (MEF), whereas solar radiation controlled the APTD variations in the northern evergreen-broadleaf deciduous mixed forest (NMF). Combining the effects of temperature, soil moisture and radiation, we found a significantly delayed trend in APTD during the 2030-2100 period, but the trend amplitude (0.8 days per decade) was much weaker than that over 2003-2017. In addition, we found that machine learning methods outperformed process-based models in projecting APTD. Our findings generate from different methods highlight that soil moisture is one of the key players in determining autumn photosynthetic phenological processes in subtropical forests. To comprehensively understand autumn phenological processes, in-situ manipulative experiments are urgently needed to quantify the contributions of different environmental and physiological factors in regulating plants' response to ongoing climate change.
Collapse
Affiliation(s)
- Yongshuo H Fu
- College of Water Sciences, Beijing Normal University, Beijing, China
- Plants and Ecosystems, Department of Biology, University of Antwerp, Antwerp, Belgium
| | - Xinxi Li
- College of Water Sciences, Beijing Normal University, Beijing, China
| | - Shouzhi Chen
- College of Water Sciences, Beijing Normal University, Beijing, China
| | - Zhaofei Wu
- College of Water Sciences, Beijing Normal University, Beijing, China
| | - Jianrong Su
- Institute of Highland Forest Science, Chinese Academy of Forestry, Kunming, China
- Pu'er Forest Ecosystem Research Station, National Forestry and Grassland Administration of China, Pu'er, China
| | - Xing Li
- Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea
| | - Shuaifeng Li
- Institute of Highland Forest Science, Chinese Academy of Forestry, Kunming, China
- Pu'er Forest Ecosystem Research Station, National Forestry and Grassland Administration of China, Pu'er, China
| | - Jing Zhang
- College of Water Sciences, Beijing Normal University, Beijing, China
| | - Jing Tang
- Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
- Terrestrial Ecology Section, Department of Biology, University of Copenhagen, Copenhagen Ø, Denmark
- Centre for Permafrost (CENPERM), University of Copenhagen, Copenhagen K, Denmark
| | - Jingfeng Xiao
- Earth Systems Research Center, Institute for the Study of Earth, Oceans and Space, University of New Hampshire, Durham, New Hampshire, USA
| |
Collapse
|
32
|
Wang X, Pan S, Pan N, Pan P. Grassland productivity response to droughts in northern China monitored by satellite-based solar-induced chlorophyll fluorescence. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 830:154550. [PMID: 35302027 DOI: 10.1016/j.scitotenv.2022.154550] [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: 11/17/2021] [Revised: 02/26/2022] [Accepted: 03/09/2022] [Indexed: 06/14/2023]
Abstract
Solar-induced chlorophyll fluorescence (SIF) has been applied to a wide range of ecological studies, such as monitoring and assessing drought, vegetation productivity, and crop yield. Previous studies have shown that SIF is highly related to gross primary production (GPP), but its correlation with aboveground biomass (AGB) still needs further exploration. In this study, we explored the potential of SIF for monitoring and assessing the effects of climate change and meteorological drought on grassland AGB changes in the northern grassland of China. By examining the relationship between the Orbiting Carbon Observatory 2 (OCO-2) SIF and drought indices, we assessed the response of northern grassland productivity to meteorological drought conditions. The results show that SIF is very sensitive to meteorological drought and can capture drought events and the dynamics of grassland growth in different grassland types. The correlation between SIF, drought indices, and AGB varied with grassland type. A gradient boosting decision tree (GBDT) was used to explore the relationships between SIF and the impact variables in the grassland ecosystem. We found that climatic factors (e.g., annual mean growing season precipitation, annual mean growing season temperature, and annual mean vapor pressure deficit) and human activity (e.g., grazing intensity) significantly impacted the interannual variability of grassland productivity. Our results indicate that SIF changes can reflect the seasonal dynamics of vegetation growth in the northern grassland of China. Therefore, SIF can be used as benchmark data for evaluating the performance of terrestrial ecosystem models in simulating ecosystem productivity in this region. The high sensitivity of SIF to drought suggests that it is a useful tool for monitoring and assessing drought events.
Collapse
Affiliation(s)
- Xinyun Wang
- School of Ecology and Environmental Sciences, Ningxia University, Yinchuan, Ningxia 750021, China; Breeding Base for State Key Laboratory of Land Degradation and Ecological Restoration of Northwest China, Ningxia University, Yinchuan, Ningxia 750021, China; Key Laboratory for Restoration and Reconstruction of Degraded Ecosystem in Northwestern China of Ministry of Education, Ningxia University, Yinchuan, Ningxia 750021, China; Key Lab. for Restoration of Degraded Ecosystems in Ningxia Province, Ningxia University, Yinchuan, Ningxia 750021, China; International Center for Climate and Global Change Research, School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL 36830, USA.
| | - Shufen Pan
- International Center for Climate and Global Change Research, School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL 36830, USA
| | - Naiqing Pan
- International Center for Climate and Global Change Research, School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL 36830, USA; State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Peipei Pan
- College of Resources and Environmental Science, Hebei Normal University, Shijiazhuang, Hebei 050024, China.
| |
Collapse
|
33
|
Comparison of Vegetation Phenology Derived from Solar-Induced Chlorophyll Fluorescence and Enhanced Vegetation Index, and Their Relationship with Climatic Limitations. REMOTE SENSING 2022. [DOI: 10.3390/rs14133018] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Satellite-based vegetation datasets enable vegetation phenology detection at large scales, among which Solar-Induced Chlorophyll Fluorescence (SIF) and Enhanced Vegetation Index (EVI) are widely used proxies for detecting phenology from photosynthesis and greenness perspectives, respectively. Recent studies have revealed the divergent performances of SIF and EVI for estimating different phenology metrics, i.e., the start of season (SOS) and the end of season (EOS); however, the underlying mechanisms are unclear. In this study, we compared the SOS and EOS of natural ecosystems derived from SIF and EVI in China and explored the underlying mechanisms by investigating the relationships between the differences of phenology derived from SIF and EVI and climatic limiting factors (i.e., temperature, water and radiation). The results showed that the differences between phenology generated using SIF and EVI were diverse in space, which had a close relationship with climatic limitations. The increasing climatic limitation index could result in larger differences in phenology from SIF and EVI for each dominant climate-limited area. The phenology extracted using SIF was more correlated with climatic limiting factors than that using EVI, especially in water-limited areas, making it the main cause of the difference in phenology from SIF and EVI. These findings highlight the impact of climatic limitation on the differences of phenology from SIF and EVI and improve our understanding of land surface phenology from greenness and photosynthesis perspectives.
Collapse
|
34
|
Investigating the Performance of Red and Far-Red SIF for Monitoring GPP of Alpine Meadow Ecosystems. REMOTE SENSING 2022. [DOI: 10.3390/rs14122740] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Alpine meadow ecosystems are extremely vulnerable to climate change and serve an essential function in terrestrial carbon sinks. Accurately estimating their gross primary productivity (GPP) is essential for understanding the global carbon cycle. Solar-induced chlorophyll fluorescence (SIF), as a companion product directly related to plant photosynthesis process, has become an attractive pathway for estimating GPP accurately. To date, the quantitative SIF-GPP relationship in terrestrial ecosystems is not yet clear. Especially, red SIF and far-red SIF present differences in their ability to track GPP under different environmental conditions. In this study, we investigated the performance of SIF at both red and far-red band in monitoring the GPP of an alpine meadow ecosystem based on continuous tower-based observations in 2019 and 2020. The results show that the canopy red SIF (SIFRed) and far-red SIF (SIFFar-red) were both strongly correlated with GPP. SIFRed was comparable to SIFFar-red for monitoring GPP based on comparisons of both half-hourly averaged and daily averaged datasets. Moreover, the relationship between SIFRed and GPP was linearly correlated, while the relationship between SIFFar-red and GPP tended to be nonlinear. At a diurnal scale, dramatic changes in photosynthetically active radiation (PAR), air temperature (Ta), and vapor pressure deficit (VPD) all had effects on the slope of the linear fitted line with zero intercept for SIFRed-GPP and SIFFar-red-GPP, and the effect on the slope of the linear fitted line with zero intercept for SIFFar-red-GPP was obviously stronger than that for SIFRed-GPP. PAR was the dominant factor among the three environmental factors in determining the diurnal variation of the slope of SIF-GPP. At a seasonal scale, the SIFFar-red/GPP was susceptible to PAR, Ta, and VPD, while the SIFRed/GPP remained relatively stable at different levels of Ta and VPD, and it was only weakly affected by PAR, suggesting that SIFRed was more consistent than SIFFar-red with GPP in response to seasonal variations in environmental factors. These results indicate that SIFRed has more potential than SIFFar-red for monitoring the GPP of alpine meadow ecosystems and can also assist researchers in gaining a more comprehensive understanding of the diversity of SIF-GPP relationships in different ecosystems.
Collapse
|
35
|
Pandiyan S, Govindjee G, Meenatchi S, Prasanna S, Gunasekaran G, Guo Y. Evaluating the Impact of Summer Drought on Vegetation Growth Using Space-Based Solar-Induced Chlorophyll Fluorescence Across Extensive Spatial Measures. BIG DATA 2022; 10:230-245. [PMID: 33983846 DOI: 10.1089/big.2020.0350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Drought is the primary and dominant natural cause of stress on vegetation, and thus, it needs our full attention. Current understanding of drought across extensive spatial measures, around the world, is considerably limited. As case studies to evaluate the feasibility of utilizing space-based solar-induced chlorophyll fluorescence (SIF) across extensive spatial measures, here, we have used data from 2007 to 2017 in Heilongjiang and Jiangsu provinces of China. The onset of the 2015 drought was accompanied by a substantial response of SIF from vegetation in both the provinces; these data were associated with changes in soil moisture, standardized precipitation evapotranspiration index, and emissivity. Our findings suggest that SIF can effectively provide the spatial and temporal progress of drought, as inferred through substantial associations with SIF normalized by absorbed photosynthetically active radiation (related to ΦF) and by photosynthetically active radiation (SIFpar). For the depiction of onset to drought, SIF, ΦF, and SIFpar provide a significant association and a quicker response than the leaf area index and the normalized difference vegetation index. Furthermore, we found that the correlation between gross primary productivity and SIF is highly substantial in both Heilongjiang (R2 = 0.85, p < 0.001) and Jiangsu (R2 = 0.75, p < 0.001) during the drought period. Our results indicate that continuing evaluation from space-based SIF can indeed provide an understanding of the seasonal differences in vegetation for evaluating the impact of drought across extensive spatial measures.
Collapse
Affiliation(s)
- Sanjeevi Pandiyan
- Key Laboratory of Advanced Process Control for Light Industry, Ministry of Education, Jiangnan University, Wuxi, China
| | - Govindjee Govindjee
- Department of Plant Biology, Department of Biochemistry, and Center of Biophysics & Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - S Meenatchi
- School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India
| | - S Prasanna
- School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India
| | - G Gunasekaran
- School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India
| | - Ya Guo
- Key Laboratory of Advanced Process Control for Light Industry, Ministry of Education, Jiangnan University, Wuxi, China
- Department of Bioengineering, University of Missouri, Columbia, Missouri, USA
| |
Collapse
|
36
|
Han J, Chang CYY, Gu L, Zhang Y, Meeker EW, Magney TS, Walker AP, Wen J, Kira O, McNaull S, Sun Y. The physiological basis for estimating photosynthesis from Chla fluorescence. THE NEW PHYTOLOGIST 2022; 234:1206-1219. [PMID: 35181903 DOI: 10.1111/nph.18045] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 02/09/2022] [Indexed: 06/14/2023]
Abstract
Solar-induced Chl fluorescence (SIF) offers the potential to curb large uncertainties in the estimation of photosynthesis across biomes and climates, and at different spatiotemporal scales. However, it remains unclear how SIF should be used to mechanistically estimate photosynthesis. In this study, we built a quantitative framework for the estimation of photosynthesis, based on a mechanistic light reaction model with the Chla fluorescence of Photosystem II (SIFPSII ) as an input (MLR-SIF). Utilizing 29 C3 and C4 plant species that are representative of major plant biomes across the globe, we confirmed the validity of this framework at the leaf level. The MLR-SIF model is capable of accurately reproducing photosynthesis for all C3 and C4 species under diverse light, temperature, and CO2 conditions. We further tested the robustness of the MLR-SIF model using Monte Carlo simulations, and found that photosynthesis estimates were much less sensitive to parameter uncertainties relative to the conventional Farquhar, von Caemmerer, Berry (FvCB) model because of the additional independent information contained in SIFPSII . Once inferred from direct observables of SIF, SIFPSII provides 'parameter savings' to the MLR-SIF model, compared to the mechanistically equivalent FvCB model, and thus avoids the uncertainties arising as a result of imperfect model parameterization. Our findings set the stage for future efforts to employ SIF mechanistically to improve photosynthesis estimates across a variety of scales, functional groups, and environmental conditions.
Collapse
Affiliation(s)
- Jimei Han
- School of Integrative Plant Science, Soil and Crop Science Section, Cornell University, Ithaca, NY, 14850, USA
| | - Christine Y-Y Chang
- School of Integrative Plant Science, Soil and Crop Science Section, Cornell University, Ithaca, NY, 14850, USA
- USDA, Agricultural Research Service, Adaptive Cropping Systems Laboratory, Beltsville, MD, 20705, USA
| | - Lianhong Gu
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Yongjiang Zhang
- School of Biology and Ecology, University of Maine, Orono, ME, 04469, USA
| | - Eliot W Meeker
- Department of Chemical Engineering, University of California, Davis, CA, 95616, USA
| | - Troy S Magney
- Department of Plant Sciences, University of California, Davis, CA, 95616, USA
| | - Anthony P Walker
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Jiaming Wen
- School of Integrative Plant Science, Soil and Crop Science Section, Cornell University, Ithaca, NY, 14850, USA
| | - Oz Kira
- School of Integrative Plant Science, Soil and Crop Science Section, Cornell University, Ithaca, NY, 14850, USA
- Department of Civil and Environmental Engineering, Ben-Gurion University of the Negev, Negev, 8410501, Israel
| | - Sarah McNaull
- Cornell Botanic Gardens, Cornell University, Ithaca, NY, 14850, USA
| | - Ying Sun
- School of Integrative Plant Science, Soil and Crop Science Section, Cornell University, Ithaca, NY, 14850, USA
| |
Collapse
|
37
|
Evaluation of Plant Stress Monitoring Capabilities Using a Portable Spectrometer and Blue-Red Grow Light. SENSORS 2022; 22:s22093411. [PMID: 35591102 PMCID: PMC9099694 DOI: 10.3390/s22093411] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 04/11/2022] [Accepted: 04/21/2022] [Indexed: 11/25/2022]
Abstract
Remote sensing offers a non-destructive method to detect plant physiological response to the environment by measuring chlorophyll fluorescence (CF). Most methods to estimate CF require relatively complex retrieval, spectral fitting, or modelling methods. An investigation was undertaken to evaluate measurements of CF using a relatively straightforward technique to detect and monitor plant stress with a spectroradiometer and blue-red light emitting diode (LED). CF spectral response of tomato plants treated with a photosystem inhibitor were assessed and compared to traditional reflectance-based indices: normalized difference vegetation index (NDVI) and photochemical reflectance index (PRI). The blue-red LEDs provided input irradiance and a “window” in the CF emission range of plants (~650 to 850 nm) sufficient to capture distinctive “two-peak” spectra and to distinguish plant health from day to day of the experiment, while within day differences were noisy. CF-based metrics calculated from CF spectra clearly captured signs of vegetation stress earlier than reflectance-based indices and by visual inspection. This CF monitoring technique is a flexible and scalable option for collecting plant function data, especially for indicating early signs of stress. The technique can be applied to a single plant or larger canopies using LED in dark conditions by an individual, or a manned or unmanned vehicle for agricultural or military purposes.
Collapse
|
38
|
Kyaw TY, Siegert CM, Dash P, Poudel KP, Pitts JJ, Renninger HJ. Using hyperspectral leaf reflectance to estimate photosynthetic capacity and nitrogen content across eastern cottonwood and hybrid poplar taxa. PLoS One 2022; 17:e0264780. [PMID: 35271605 PMCID: PMC8912144 DOI: 10.1371/journal.pone.0264780] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 02/16/2022] [Indexed: 02/05/2023] Open
Abstract
Eastern cottonwood (Populus deltoides W. Bartram ex Marshall) and hybrid poplars are well-known bioenergy crops. With advances in tree breeding, it is increasingly necessary to find economical ways to identify high-performing Populus genotypes that can be planted under different environmental conditions. Photosynthesis and leaf nitrogen content are critical parameters for plant growth, however, measuring them is an expensive and time-consuming process. Instead, these parameters can be quickly estimated from hyperspectral leaf reflectance if robust statistical models can be developed. To this end, we measured photosynthetic capacity parameters (Rubisco-limited carboxylation rate (Vcmax), electron transport-limited carboxylation rate (Jmax), and triose phosphate utilization-limited carboxylation rate (TPU)), nitrogen per unit leaf area (Narea), and leaf reflectance of seven taxa and 62 genotypes of Populus from two study plantations in Mississippi. For statistical modeling, we used least absolute shrinkage and selection operator (LASSO) and principal component analysis (PCA). Our results showed that the predictive ability of LASSO and PCA models was comparable, except for Narea in which LASSO was superior. In terms of model interpretability, LASSO outperformed PCA because the LASSO models needed 2 to 4 spectral reflectance wavelengths to estimate parameters. The LASSO models used reflectance values at 758 and 935 nm for estimating Vcmax (R2 = 0.51 and RMSPE = 31%) and Jmax (R2 = 0.54 and RMSPE = 32%); 687, 746, and 757 nm for estimating TPU (R2 = 0.56 and RMSPE = 31%); and 304, 712, 921, and 1021 nm for estimating Narea (R2 = 0.29 and RMSPE = 21%). The PCA model also identified 935 nm as a significant wavelength for estimating Vcmax and Jmax. Therefore, our results suggest that hyperspectral leaf reflectance modeling can be used as a cost-effective means for field phenotyping and rapid screening of Populus genotypes because of its capacity to estimate these physicochemical parameters.
Collapse
Affiliation(s)
- Thu Ya Kyaw
- Department of Forestry, Forest and Wildlife Research Center, Mississippi State University, Starkville, Mississippi, United States of America
- * E-mail:
| | - Courtney M. Siegert
- Department of Forestry, Forest and Wildlife Research Center, Mississippi State University, Starkville, Mississippi, United States of America
| | - Padmanava Dash
- Department of Geosciences, Mississippi State University, Starkville, Mississippi, United States of America
| | - Krishna P. Poudel
- Department of Forestry, Forest and Wildlife Research Center, Mississippi State University, Starkville, Mississippi, United States of America
| | - Justin J. Pitts
- Department of Forestry, Forest and Wildlife Research Center, Mississippi State University, Starkville, Mississippi, United States of America
| | - Heidi J. Renninger
- Department of Forestry, Forest and Wildlife Research Center, Mississippi State University, Starkville, Mississippi, United States of America
| |
Collapse
|
39
|
Wang Y, Xiao J, Li X, Niu S. Global evidence on the asymmetric response of gross primary productivity to interannual precipitation changes. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 814:152786. [PMID: 34990664 DOI: 10.1016/j.scitotenv.2021.152786] [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: 09/17/2021] [Revised: 12/24/2021] [Accepted: 12/26/2021] [Indexed: 06/14/2023]
Abstract
Understanding gross primary productivity (GPP) response to precipitation (PPT) changes is essential for predicting land carbon uptake under increasing PPT variability and extremes. Previous studies found that ecosystem GPP may have an asymmetric response to PPT changes, leading to the inconsistency of GPP gains in wet years compared to GPP declines in dry years. However, it is unclear how the asymmetric responses vary among vegetation types and under different PPT variabilities. This study evaluated the global patterns of asymmetries of GPP response to different PPT changes using two state-of-science global GPP datasets. The result shows that under mild PPT changes (|ΔPPT| ≤ 25%), grasslands, savannas, shrublands, and tundra show positive asymmetric responses (i.e., larger GPP gains in wet years than GPP losses in dry years), while other vegetation types show negative asymmetric responses (i.e., larger GPP losses in dry years than GPP gains in wet years). Conversely, all vegetation types show negative GPP asymmetric responses to moderate (25% < |ΔPPT| ≤ 50%) and extreme (|ΔPPT| > 50%) PPT changes. Thus, we propose a new non-linear asymmetric GPP-PPT model that incorporates three modes with regards to vegetation types. Meanwhile, we found that the spatial patterns of asymmetry were mainly driven by PPT amount and variability. Stronger and negative asymmetries were found in areas with smaller PPT amount and variability, while positive asymmetries were found in areas with higher PPT variability. These findings promote our understanding of carbon dynamics under increased PPT variability and extremes and provide new insights for land models to better predict future carbon uptake and its feedback to climate change.
Collapse
Affiliation(s)
- Yiheng Wang
- Key Laboratory of Ecosystem Network Observation and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; School of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jingfeng Xiao
- Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA
| | - Xing Li
- Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea
| | - Shuli Niu
- Key Laboratory of Ecosystem Network Observation and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; School of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China.
| |
Collapse
|
40
|
A Reconstructed Global Daily Seamless SIF Product at 0.05 Degree Resolution Based on TROPOMI, MODIS and ERA5 Data. REMOTE SENSING 2022. [DOI: 10.3390/rs14061504] [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
Satellite-derived solar-induced chlorophyll fluorescence (SIF) has been proven to be a valuable tool for monitoring vegetation’s photosynthetic activity at regional or global scales. However, the coarse spatiotemporal resolution or discrete space coverage of most satellite SIF datasets hinders their full potential for studying carbon cycle and ecological processes at finer scales. Although the recent TROPOspheric Monitoring Instrument (TROPOMI) partially addresses this issue, the SIF still has drawbacks in spatial insufficiency and spatiotemporal discontinuities when gridded at high spatiotemporal resolutions (e.g., 0.05°, 1-day or 2-day) due to its nonuniform sampling sizes, swath gaps, and clouds contaminations. Here, we generated a new global SIF product with Seamless spatiotemporal coverage at Daily and 0.05° resolutions (SDSIF) during 2018–2020, using the random forest (RF) approach together with TROPOMI SIF, MODIS reflectance and meteorological datasets. We investigated how the model accuracy was affected by selection of explanatory variables and model constraints. Eventually, models were trained and applied for specific continents and months given the similar response of SIF to environmental variables within closer space and time. This strategy achieved better accuracy (R2 = 0.928, RMSE = 0.0597 mW/m2/nm/sr) than one universal model (R2 = 0.913, RMSE = 0.0653 mW/m2/nm/sr) for testing samples. The SDSIF product can well preserve the temporal and spatial characteristics in original TROPOMI SIF with high temporal correlations (mean R2 around 0.750) and low spatial residuals (less than ±0.081 mW/m2/nm/sr) between them two at most regions (80% of global pixels). Compared with the original SIF at five flux sites, SDSIF filled the temporal gaps and was better consistent with tower-based SIF at the daily scale (the mean R2 increased from 0.467 to 0.744. Consequently, it provided more reliable 4-day SIF averages than the original ones from sparse daily observations (e.g., the R2 at Daman site was raised from 0.614 to 0.837), which resulted in a better correlation with 4-day tower-based GPP. Additionally, the global coverage ratio and local spatial details had also been improved by the reconstructed seamless SIF. Our product has advantages in spatiotemporal continuities and details over the original TROPOMI SIF, which will benefit the application of satellite SIF for understanding carbon cycle and ecological processes at finer spatial and temporal scales.
Collapse
|
41
|
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.
Collapse
|
42
|
Remotely Monitoring Vegetation Productivity in Two Contrasting Subtropical Forest Ecosystems Using Solar-Induced Chlorophyll Fluorescence. REMOTE SENSING 2022. [DOI: 10.3390/rs14061328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Subtropical forests can sequester a larger amount of atmospheric carbon dioxide (CO2) relative to other terrestrial ecosystems through photosynthetic activity and act as an important role in mitigating global climate warming. Compared with the model-based gross primary production (GPP) products, satellite-derived solar-induced fluorescence (SIF) opens a new window for quantification. Here, we used the remotely sensed SIF retrievals, two satellite-driven GPP products including MODIS (GPPMOD) and BESS (GPPBESS), and tower-based GPP measurements at two contrasting subtropical forests to provide a systematic analysis. Our results revealed that GPP and the associated environmental factors exhibited distinct seasonal patterns. However, the peak GPP values had large differences, with stronger GPP in the evergreen needleleaf forest site (8.76 ± 0.71 g C m−2 d−1) than that in the evergreen broadleaf forest site (5.71 ± 0.31 g C m−2 d−1). The satellite-derived SIF retrievals showed great potential in quantifying the variability in GPP, especially for the evergreen needleleaf forest with r reaching up to 0.909 (p < 0.01). GPPMOD and GPPBESS showed distinctly different performances for the two subtropical forests, whereas the GPP estimates by exclusive use of satellite-based SIF data promised well to the tower-based GPP observations. Multi-year evaluation again confirmed the good performance of the SIF-based GPP estimates. These findings will provide an alternative framework for quantifying the magnitude of forest GPP and advance our understanding of the carbon sequestration capacity of subtropical forest ecosystems.
Collapse
|
43
|
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.
Collapse
|
44
|
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.
Collapse
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
| |
Collapse
|
45
|
Dang C, Shao Z, Huang X, Qian J, Cheng G, Ding Q, Fan Y. Assessment of the importance of increasing temperature and decreasing soil moisture on global ecosystem productivity using solar-induced chlorophyll fluorescence. GLOBAL CHANGE BIOLOGY 2022; 28:2066-2080. [PMID: 34918427 DOI: 10.1111/gcb.16043] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Accepted: 12/03/2021] [Indexed: 06/14/2023]
Abstract
The accurate assessment of the global gross primary productivity (GPP) of vegetation is the key to estimating the global carbon cycle. Temperature (Ts) and soil moisture (SM) are essential for vegetation growth. It is acknowledged that the global Ts has shown an increasing trend, yet SM has shown a decreasing trend. However, the importance of SM and Ts changes on the productivity of global ecosystems remains unclear, as SM and Ts are strongly coupled through soil-atmosphere interactions. Using solar-induced chlorophyll fluorescence (SIF) as a proxy for GPP and by decoupling SM and Ts changes, our investigation shows Ts plays a more important role in SIF in 60% of the vegetation areas. Overall, increased Ts promotes SIF by mitigating the resistance from SM's reduction. However, the importance of SM and Ts varies, given different vegetation types. The results show that in the humid zone, the variation of Ts plays a more important role in SIF, but in the arid and semi-arid zones, the variation of SM plays a more important role; in the semi-humid zone, the disparity in the importance of SM and Ts is difficult to unravel. In addition, our results suggest that SIF is very sensitive to aridity gradients in arid and semi-arid ecosystems. By decoupling the intertwined SM-Ts impact on SIF, our study provides essential evidence that benefits future investigation on the factors the influence ecosystem productivity at regional or global scales.
Collapse
Affiliation(s)
- Chaoya Dang
- State Key Laboratory Information Engineering Survey Mapping and Remote Sensing, Wuhan University, Wuhan, China
| | - Zhenfeng Shao
- State Key Laboratory Information Engineering Survey Mapping and Remote Sensing, Wuhan University, Wuhan, China
| | - Xiao Huang
- Department of Geosciences, University of Arkansas, Fayetteville, Arkansas, USA
| | - Jiaxin Qian
- State Key Laboratory Information Engineering Survey Mapping and Remote Sensing, Wuhan University, Wuhan, China
| | - Gui Cheng
- State Key Laboratory Information Engineering Survey Mapping and Remote Sensing, Wuhan University, Wuhan, China
| | - Qing Ding
- State Key Laboratory Information Engineering Survey Mapping and Remote Sensing, Wuhan University, Wuhan, China
| | - Yewen Fan
- State Key Laboratory Information Engineering Survey Mapping and Remote Sensing, Wuhan University, Wuhan, China
| |
Collapse
|
46
|
Characteristic of Stomatal Conductance and Optimal Stomatal Behaviour in an Arid Oasis of Northwestern China. SUSTAINABILITY 2022. [DOI: 10.3390/su14020968] [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
Stomatal conductance (gs), the process that governs plant carbon uptake and water loss, is fundamental to most Land Surface Models (LSMs). With global change accelerating, more attention should be paid to investigating stomatal behavior, especially in extremely arid areas. In this study, gas exchange measurements and environmental/biological variables observations during growing seasons in 2016 and 2017 were combined to investigate diurnal and seasonal characteristics of gs and the applicability of the optimal stomatal conductance model in a desert oasis vineyard. The results showed that the responses of gs to environmental factors (photosynthesis active radiation, PAR; vapor pressure deficit, VPD; and temperature, T) formed hysteresis loops in the daytime. The stomatal conductance slope, g1, a parameter in the unified stomatal optimal model, varied in different growing seasons and correlated with the soil-to-leaf hydraulic conductance (KL). These results indicated the potential bias when using a constant g1 value to simulate gs and highlighted that the water-use strategy of oasis plants might not be consistent throughout the entire growing season. Our findings further help to achieve a better understanding of stomata behavior in responding to climate change and encourage future efforts toward a more accurate parameterization of gs to improve the modeling of LSMs.
Collapse
|
47
|
Cao J, An Q, Zhang X, Xu S, Si T, Niyogi D. Is satellite Sun-Induced Chlorophyll Fluorescence more indicative than vegetation indices under drought condition? THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 792:148396. [PMID: 34465046 DOI: 10.1016/j.scitotenv.2021.148396] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 06/07/2021] [Accepted: 06/08/2021] [Indexed: 05/25/2023]
Abstract
Droughts represent one of the most severe abiotic stress factors that could result in great crop yield loss. Numerous vegetation indices have been proposed for monitoring the vegetation condition under stress and assessing drought impacts on yield loss. However, the understanding and comparison between traditional vegetation indices (VIs) and the newly emerging satellite Sun-Induced Chlorophyll Fluorescence (SIF) for monitoring vegetation condition is still limited especially under drought stress and at multiple spatial scales. In this study, the potential of satellite observation SIF for monitoring corn response to drought was investigated based on the 2012 drought in the US Corn Belt. The standardized precipitation evapotranspiration index (SPEI) was used here to quantify drought. We found that all SPEI were above -1, except for July (-1.27), August (-1.39) and September (-1.14) in 2012, indicating the severity of this drought. We examined the relationship between satellite measurements of SIF, SIFyield, VIs (e.g., NDVI and EVI) and SPEI. Results indicated that SIFyield was sensitive to drought and SIF captured the stress more accurately both at the regional and state scales for the US Corn Belt. Quantitatively, SIFyield had a high correlation with SPEI (r = 0.987, p < 0.05) over the entire Corn Belt, and it indicated losses in response to drought approximately one month earlier than SIF/NDVI/EVI. Furthermore, our results demonstrated that SIF could be trusted as an effective indicator to study the relationship between GPP (R2 ≥ 0.8664, p < 0.01) under drought conditions across the Corn Belt. This study highlighted the advantage of using satellite SIF observations to monitor the drought stress on crop growth especially GPP at regional scale.
Collapse
Affiliation(s)
- Junjun Cao
- College of Urban and Environmental Sciences, Central China Normal University, Wuhan 430079, China; Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China; Department of Agronomy, Purdue University, West Lafayette, IN 47907, USA; Key Laboratory for Geographical Process Analysis & Simulation of Hubei Province, Wuhan 430079, China
| | - Qi An
- College of Urban and Environmental Sciences, Central China Normal University, Wuhan 430079, China; Key Laboratory for Geographical Process Analysis & Simulation of Hubei Province, Wuhan 430079, China
| | - Xiang Zhang
- National Engineering Research Center of Geographic Information System, China University of Geosciences (Wuhan), Wuhan 430074, China; School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan 430074, China.
| | - Shan Xu
- Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Tong Si
- Shandong Provincial Key laboratory of Dryland Farming Technology, College of Agronomy, Qingdao Agricultural University, Qingdao 266109, China
| | - Dev Niyogi
- Department of Geological Sciences, Jackson School of Geosciences, University of Texas at Austin, Austin, TX 78712, USA; Department of Agronomy, Purdue University, West Lafayette, IN 47907, USA; Department of Civil, Architecture, and Environmental Engineering, University of Texas at Austin, Austin, TX 78712, USA
| |
Collapse
|
48
|
Chen A, Mao J, Ricciuto D, Lu D, Xiao J, Li X, Thornton PE, Knapp AK. Seasonal changes in GPP/SIF ratios and their climatic determinants across the Northern Hemisphere. GLOBAL CHANGE BIOLOGY 2021; 27:5186-5197. [PMID: 34185345 DOI: 10.1111/gcb.15775] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 05/24/2021] [Indexed: 06/13/2023]
Abstract
Satellite-derived sun-induced chlorophyll fluorescence (SIF) has been increasingly used for estimating gross primary production (GPP). However, the relationship between SIF and GPP has not been well defined, impeding the translation of satellite observed SIF to GPP. Previous studies have generally assumed a linear relationship between SIF and GPP at daily and longer time scales, but support for this assumption is lacking. Here, we used the GPP/SIF ratio to investigate seasonal variations in the relationship between SIF and GPP over the Northern Hemisphere (NH). Based on multiple SIF products and MODIS and FLUXCOM GPP data, we found strong seasonal hump-shaped patterns for the GPP/SIF ratio over northern latitudes, with higher values in the summer than in the spring or autumn. This hump-shaped GPP/SIF seasonal variation was confirmed by examining different SIF products and was evident for most vegetation types except evergreen broadleaf forests. The seasonal amplitude of the GPP/SIF ratio decreased from the boreal/arctic region to drylands and the tropics. For most of the NH, the lowest GPP/SIF values occurred in October or September, while the maximum GPP/SIF values were evident in June and July. The most pronounced seasonal amplitude of GPP/SIF occurred in intermediate temperature and precipitation ranges. GPP/SIF was positively related to temperature in the early and late parts of the growing season, but not during the peak growing months. These shifting relationships between temperature and GPP/SIF across different months appeared to play a key role in the seasonal dynamics of GPP/SIF. Several mechanisms may explain the patterns we observed, and future research encompassing a broad range of climate and vegetation settings is needed to improve our understanding of the spatial and temporal relationships between SIF and GPP. Nonetheless, the strong seasonal variation in GPP/SIF we identified highlights the importance of incorporating this behavior into SIF-based GPP estimations.
Collapse
Affiliation(s)
- Anping Chen
- Department of Biology and Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO, USA
| | - Jiafu Mao
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Daniel Ricciuto
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Dan Lu
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Jingfeng Xiao
- Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, USA
| | - Xing Li
- Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, USA
| | - Peter E Thornton
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Alan K Knapp
- Department of Biology and Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO, USA
| |
Collapse
|
49
|
The spatial heterogeneity of the relationship between gross primary production and sun-induced chlorophyll fluorescence regulated by climate conditions during 2007–2018. Glob Ecol Conserv 2021. [DOI: 10.1016/j.gecco.2021.e01721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
|
50
|
The Impact of Seasonality and Response Period on Qualifying the Relationship between Ecosystem Productivity and Climatic Factors over the Eurasian Steppe. REMOTE SENSING 2021. [DOI: 10.3390/rs13163159] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
As climate change intensifies, surface vegetation productivity and carbon exchange between terrestrial ecosystems and the atmosphere are significantly affected by the variation of climatic factors. Due to the sensitivity of grasslands to these climatic factors, it is crucial to understand the response of vegetation greenness, or carbon exchange within grasslands, to environment factor dynamics. In this study, we used solar-induced chlorophyll fluorescence (SIF), precipitation (P), vapor pressure deficit (VPD), evaporative stress (ES), and root zone soil moisture (RSM) derived from remote sensing, reanalysis, and assimilation datasets to explore the response of vegetation greenness within Eurasian Steppe to climatic factors. Our results indicated deseasonlization based on the Seasonal-Trend decomposition using Loess (STL) method, which was an effective means to remove the seasonality disturbances that affect the qualification of the relationship between SIF and the four climatic factors. The response of SIF had a time lag effect on these climatic factors, and the longer the response period, the greater the impact on the correlation of SIF with P, VPD, ES, and RSM. We also found, among the four factors, that the response of SIF to ES was the timeliest. The findings of this study emphasized the impact of the seasonality and time lag effect on the dynamic response between variables, and provided references to the attribution and monitoring of vegetation greenness and ecosystem productivity.
Collapse
|