What is global photosynthesis? History, uncertainties and opportunities
Graphical abstract
Introduction
Fifty years ago when the journal Remote Sensing of Environment was launched, a landmark workshop on photosynthesis and production was held in Trebon, Czechoslovakia (de Wit, 1970). Held during the Cold War, it was one of the last meetings that combined scientists from the Eastern Bloc, Western Bloc, USA, Australia and Asia until the collapse of the Iron Curtain in 1989. At the meeting, C.T. de Wit argued: “Seven-stage simulation models by means of which eco-systems may be explained on basis of the molecular sciences are impossible large and detailed and it is naive to pursue their construction.” He was skeptical about large-scale photosynthesis research as garbage-in, garbage-out. Many heeded his words and were reluctant to upscale research beyond a field crop or forest. However, as we have since learned, there is much need to assess global photosynthesis. Today, new measurement systems enable us to do so regularly with a degree of confidence. Here we evaluate progress in assessing photosynthesis of ecosystems and the globe and ask and answer the question: How much have we advanced global photosynthesis research since then?
Understanding, quantifying and modeling global photosynthesis is crucial for society. Photosynthesis supports production of food, fiber, wood, grain fed to livestock, and fuel for humanity. Global photosynthesis sets the limit of the planetary boundary of production, which has been used widely to quantify how much humans have appropriated global production (Imhoff et al., 2004; Vitousek et al., 1986). Running (2012) proposed net primary productivity (NPP) as a measurable planetary boundary (Rockstrom et al., 2009) and argued that only an additional 5 PgC y−1 is available for humanity, which requires a precise estimate of global photosynthesis. Photosynthesis is the essential driver of the global carbon cycle, strongly coupled with the climate system via numerous feedback processes (Heimann and Reichstein, 2008; Sellers et al., 2018), which are related to extreme climate events such as heat waves, drought and flooding (Seneviratne et al., 2014; Zscheischler et al., 2013). Larger year-to-year variations of global land carbon sinks compared to the ocean inferred from atmospheric CO2 inversions (Gurney et al., 2008) suggest that global land photosynthesis must be quantified accurately. Crop yields and wood production, which must increase with population and economic growth, depend on photosynthesis (Wolf et al., 2015). Hence, if we do not have an accurate estimate for the input of carbon into the carbon cycle, how can we be confident in determining how it is consumed by autotrophs and heterotrophs?
Quantifying global photosynthesis requires meeting multiple grand challenges. It requires understanding the coupled and non-linear biophysical processes that span 14 orders of magnitude in space and time (Jarvis, 1995; Osmond et al., 1980). Over the past several decades, strong collaborations among biochemistry, plant physiological ecology and remote sensing communities have advanced our multiscale understanding of photosynthesis (Beer et al., 2010; Farquhar et al., 1980; Sellers et al., 1997). Substantial uncertainties still remain regarding spatial and temporal patterns of photosynthesis. These arise in part from the chosen model algorithms and the model parameters (Medlyn et al., 2005) and from large discrepancies among multiple remote sensing products and land surface models (Anav et al., 2015).
Studies of photosynthesis at the leaf scale have a long and rich history (Field and Mooney, 1986; Laisk and Oja, 1974; Schulze et al., 1994), whereas canopy photosynthesis was measured less before the 1990s. The emergence of networks of eddy covariance flux towers has significantly advanced our understanding of canopy photosynthesis processes (Baldocchi, 2014; Wofsy et al., 1993). However, it is notable that eddy covariance systems directly measure net ecosystem exchange, which has been used to compute canopy photosynthesis (Reichstein et al., 2005). Furthermore, flux towers do not represent global scales well, particularly in tropical regions, which are assumed to have high photosynthesis, but for which few data exist (Schimel et al., 2015). Upscaling canopy photosynthesis to the global scale requires gridded forcing datasets of vegetation from remote sensing (Baret et al., 2007; Sellers et al., 1996a; Tucker et al., 2005) and meteorology from reconstructed climate or weather datasets. Substantial uncertainties in vegetation indices remain, which could change trend signs (Zhang et al., 2017a).
Advances in satellite remote sensing have played direct and indirect roles in global photosynthesis research. This research field has a relatively short history, given that humanity's first view of the Earth from space came with Sputnik 1 in 1957 (Tatem et al., 2008). Over the last 60 years, a series of satellite missions opened new opportunities to quantify atmospheric radiative transfer processes (Kaufman et al., 1997; Pinker and Laszlo, 1992), vegetation structure and functions (Myneni et al., 2002; Tucker et al., 1986), and land cover types (Hansen et al., 2013; Townshend et al., 1991), all of which provide key constraints on estimates of global photosynthesis. Previous review papers of remote sensing of photosynthesis have focused on specific tools such as light use efficiency (LUE) (Hilker et al., 2008) and sun-induced chlorophyll fluorescence (Porcar-Castell et al., 2014), or made intercomparisons of global photosynthesis maps from state-of-the-art land surface models and bench-mark datasets (Anav et al., 2015). However, to our knowledge, a comprehensive and contemporary historical review of remote sensing of global photosynthesis including different approaches, from leaf to canopy to continental scale, does not exist.
In this review, we first cover historical achievements in photosynthesis research at a decadal interval from leaf, canopy to the global land (Fig. 1), as this information needs to be coupled to produce accurate bottom up estimates of global photosynthesis. We review key studies in theory, modeling and observations of photosynthesis across scales, which in the end converge to the remote sensing of global terrestrial photosynthesis. Then we identify key uncertainties in global terrestrial photosynthesis research, and discuss new opportunities presented by the emergence of novel remote sensing data sets.
Section snippets
Pre-1970s: few data exist, but theory and modeling are mature
Important theories in photosynthesis were established during this period. At the biochemical level, C3 (Calvin and Benson, 1948) and C4 photosynthetic pathways (Hatch and Slack, 1966; Kortschak et al., 1965) were discovered. To understand photosynthesis at the canopy level, it is crucial to quantify canopy architecture and light environments. Two important achievements were made by a Japanese group, who introduced Beer's Law to quantify light penetration through canopies (Monsi and Saeki, 1953,
Uncertainties
In spite of substantial advances in theory, observation and modeling of photosynthesis over more than five decades, global photosynthesis estimates are still highly uncertain (Fig. 3). One recent review of global photosynthesis estimates from diverse remote sensing products and land surface models reported that annual sum values ranged from 112 to 169 PgC y−1, interannual variability ranged from 0.8 to 4.4 PgC y−1, and trends varied from 0.005 to 0.621 PgC y−2 (Anav et al., 2015). In a
Opportunities
We are entering a phase of satellite remote sensing that offers unprecedented big data information in terms of spatial, temporal, and spectral domains. This will further advance our understanding of global photosynthesis estimates.
Conclusion
In the Introduction, we raised the question: how much have we advanced global photosynthesis research since the Photosynthesis and Production Workshop held in Trebon, 1969? We argue that most important theories, observations and modeling, though not conducted at a global scale, had been conceived before the workshop. Since then, key advances have been made in preparing input data and constraining parameters better for photosynthesis models from satellite remote sensing across Landsat, AVHRR,
Acknowledgements
We appreciate all the great scientists whose achievements over multiple decades have enabled us to write this review. We thank Richard Waring, Tiit Nilson, John Norman, Steve Running and late Paul Jarvis for sharing history of photosynthesis and canopy structure studies. We thank Benjamin Dechant for internal review, Chongya Jiang for processing the GPP dataset, Remi Luo for sharing global SiF time series from his paper, Yorum Hwang for making Fig. 2, and John Gamon for sharing his opinion on
References (361)
Retrieval of seasonal Rubisco-limited photosynthetic capacity at global FLUXNET sites from hyperspectral satellite remote sensing: impact on carbon modelling
Agric. For. Meteorol.
(2017)Decadal trends in photosynthetic capacity and leaf area index inferred from satellite remote sensing for global vegetation types
Agric. For. Meteorol.
(2018)- et al.
Spectroscopy of canopy chemicals in humid tropical forests
Remote Sens. Environ.
(2011) - et al.
Quantifying forest canopy traits: imaging spectroscopy versus field survey
Remote Sens. Environ.
(2015) - et al.
Rapid measurement of the three-dimensional distribution of leaf orientation and the leaf angle probability density function using terrestrial LiDAR scanning
Remote Sens. Environ.
(2017) - et al.
On using eco-physiological, micrometeorological and biogeochemical theory to evaluate carbon dioxide, water vapor and trace gas fluxes over vegetation: a perspective
Agric. For. Meteorol.
(1998) - et al.
LAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION - part 1: principles of the algorithm
Remote Sens. Environ.
(2007) - et al.
Phosphoglycolate production catalyzed by ribulose diphosphate carboxylase
Biochem. Biophys. Res. Commun.
(1971) - et al.
Daily canopy photosynthesis model through temporal and spatial scaling for remote sensing applications
Ecol. Model.
(1999) - et al.
Global mapping of foliage clumping index using multi-angular satellite data
Remote Sens. Environ.
(2005)
Physiological and environmental regulation of stomatal conductance, photosynthesis and transpiration: a model that includes a laminar boundary layer
Agric. For. Meteorol.
Remote sensing of foliar chemistry
Remote Sens. Environ.
Far-red sun-induced chlorophyll fluorescence shows ecosystem-specific relationships to gross primary production: an assessment based on observational and modeling approaches
Remote Sens. Environ.
Estimation of photosynthesis traits from leaf reflectance spectra: correlation to nitrogen content as the dominant mechanism
Remote Sens. Environ.
Regional mapping of gross light-use efficiency using MODIS spectral indices
Remote Sens. Environ.
Theoretical uncertainty analysis of global MODIS, CYCLOPES, and GLOBCARBON LAI products using a triple collocation method
Remote Sens. Environ.
Models describing the kinetics of ribulose biphosphate carboxylase-oxygenase
Arch. Biochem. Biophys.
3.10 - solar induced chlorophyll fluorescence: origins, relation to photosynthesis and retrieval A2 - Liang, Shunlin
The Chlorophyll Fluorescence Imaging Spectrometer (CFIS), mapping far red fluorescence from aircraft
Remote Sens. Environ.
MODIS collection 5 global land cover: algorithm refinements and characterization of new datasets
Remote Sens. Environ.
A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency
Remote Sens. Environ.
NDWI-A Normalized Difference Water Index for remote sensing of vegetation liquid water from space
Remote Sens. Environ.
The photochemical reflectance index (PRI) and the remote sensing of leaf, canopy and ecosystem radiation use efficiencies: a review and meta-analysis
Remote Sens. Environ.
The relationship between the quantum yield of photosynthetic electron transport and quenching of chlorophyll fluorescence
Biochim. Biophys. Acta Gen. Subj.
Google earth engine: planetary-scale geospatial analysis for everyone
Remote Sens. Environ.
Normalized difference vegetation index measurements from the advanced very high resolution radiometer
Remote Sens. Environ.
Data-intensive science: the Terapixel and MODISAzure projects
Int. J. High Perform. Comput. Appl.
Water, Energy, and Carbon with Artificial Neural Networks (WECANN): a statistically based estimate of global surface turbulent fluxes and gross primary productivity using solar-induced fluorescence
Biogeosciences
Global-scale environmental control of plant photosynthetic capacity
Ecol. Appl.
Spatiotemporal patterns of terrestrial gross primary production: a review
Rev. Geophys.
HAPEX—MOBILHY: a hydrologic atmospheric experiment the study of water budget and evaporation flux at the climatic scale
Bull. Am. Meteorol. Soc.
EOS Reference Handbook
Estimates of the annual net carbon and water exchange of forests: the EUROFLUX methodology
Adv. Ecol. Res.
Canopy near-infrared reflectance and terrestrial photosynthesis
Sci. Adv.
Measuring fluxes of trace gases and energy between ecosystems and the atmosphere - the state and future of the eddy covariance method
Glob. Chang. Biol.
The physics and ecology of mining carbon dioxide from the atmosphere by ecosystems
Glob. Chang. Biol.
Canopy photosynthesis and water-use efficiency in a deciduous forest
J. Appl. Ecol.
Strategies for measuring and modelling carbon dioxide and water vapour fluxes over terrestrial ecosystems
Glob. Chang. Biol.
FLUXNET: a new tool to study the temporal and spatial variability of ecosystem-scale carbon dioxide, water vapor, and energy flux densities
Bull. Am. Meteorol. Soc.
A model predicting stomatal conductance and its contribution to the control of photosynthesis under different environmental conditions
A gas-exchange system for measuring the productivity of plant populations in controlled environments
Can. J. Bot.
Field spectroscopy of agricultural crops
IEEE Trans. Geosci. Remote Sens.
Meteorological approach to the exchange of CO2 between the atmosphere and vegetation, particularly forest stands
Photosynthetica
Terrestrial gross carbon dioxide uptake: global distribution and covariation with climate
Science
An introduction to himawari-8/9 - Japan's new-generation geostationary meteorological satellites
J. Meteorol. Soc. Jpn.
Reflection of visible and infrared radiation from leaves of different ecological groups
Am. J. Bot.
Effect of low concentrations of carbon dioxide on photosynthesis rates of two races of oxyria
Science
The effect of oxygen concentration on photosynthesis in higher plants
Physiol. Plant.
Adaptability of the photosynthetic apparatus to light intensity in ecotypes from exposed and shaded habitats
Physiol. Plant.
Annual cycles of water vapour and carbon dioxide fluxes in and above a boreal aspen forest
Glob. Chang. Biol.
Cited by (273)
Estimating leaf photosynthetic capacity using hyperspectral reflectance: Model variability and transferability
2024, Computers and Electronics in AgricultureContrasting responses of relationship between solar-induced fluorescence and gross primary production to drought across aridity gradients
2024, Remote Sensing of EnvironmentWater availability and atmospheric dryness controls on spaceborne sun-induced chlorophyll fluorescence yield
2024, Remote Sensing of Environment