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Gross primary production (GPP) by terrestrial ecosystems is a key quantity in the global carbon cycle. The instantaneous controls of leaf-level photosynthesis are well established, but there is still no consensus on the mechanisms by which canopy-level GPP depends on spatial and temporal variation in the environment. The standard model of photosynthesis provides a robust mechanistic representation for C 3 species; however, additional assumptions are required to "scale up" from leaf to canopy. As a consequence, competing models make inconsistent predictions about how GPP will respond to continuing environmental change. This problem is addressed here by means of an empirical analysis of the light use efficiency (LUE) of GPP inferred from eddy covariance carbon dioxide flux measurements, in situ measurements of photosynthetically active radiation (PAR), and remotely sensed estimates of the fraction of PAR (fAPAR) absorbed by the vegetation canopy. Focusing on LUE allows potential drivers of GPP to be separated from its overriding dependence on light. GPP data from over 100 sites, collated over 20 years and located in a range of biomes and climate zones, were extracted from the FLUXNET2015 database and combined with remotely sensed fAPAR data to estimate daily LUE. Daytime air temperature, vapor pressure deficit, diffuse fraction of solar radiation, and soil moisture were shown to be salient predictors of LUE in a generalized linear mixed-effects model. The same model design was fitted to site-based LUE estimates generated by 16 terrestrial ecosystem models. The published models showed wide variation in the shape, the strength, and even the sign of the environmental effects on modeled LUE. These findings highlight important model deficiencies and suggest a need to progress beyond simple "goodness of fit" comparisons of inferred and predicted carbon fluxes toward an approach focused on the functional responses of the underlying dependencies., (© 2022 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

Accurate estimation of terrestrial gross primary productivity (GPP) is essential for quantifying the net carbon exchange between the atmosphere and biosphere. Light use efficiency (LUE) models are widely used to estimate GPP at different spatial scales. However, difficulties in proper determination of maximum LUE (LUE max ) and downregulation of LUE max into actual LUE result in uncertainties in GPP estimated by LUE models. The recently developed P model, as a LUE-like model, captures the deep mechanism of photosynthesis and simplifies parameterization. Site level studies have proved the outperformance of P model over LUE models. However, the global application of the P model is still lacking. Thus, the effectiveness of 5 water stress factors integrated into the P model was compared. The optimal P model was used to generate a new long-term (1981-2020) global monthly GPP dataset at a spatial resolution of 0.1° × 0.1°, called PGPP. Validation at globally distributed 109 FLUXNET sites indicated that PGPP is better than three widely-used GPP products. R 2 between PGPP and observed GPP equals to 0.75, the corresponding root mean squared error (RMSE) and mean absolute error (MAE) equal to 1.77 g C m -2 d -1 and 1.28 g C m -2 d -1 . During the period from 1981 to 2020, PGPP significantly increased in 69.02% of global vegetated regions (p < 0.05). Overall, PGPP provides a new GPP product choice for global ecology studies and the comparison of various water stress factors provides a new idea for the improvement of GPP model in the future., Competing Interests: Declaration of Competing Interest The authors declare that they have no conflict of interest., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Leaf quantity (i.e., canopy leaf area index, LAI), quality (i.e., per-area photosynthetic capacity), and longevity all influence the photosynthetic seasonality of tropical evergreen forests. However, these components of tropical leaf phenology are poorly represented in most terrestrial biosphere models (TBMs). Here, we explored alternative options for the representation of leaf phenology effects in TBMs that employ the Farquahar, von Caemmerer & Berry (FvCB) representation of CO 2 assimilation. We developed a two-fraction leaf (sun and shade), two-layer canopy (upper and lower) photosynthesis model to evaluate different modeling approaches and assessed three components of phenological variations (i.e., leaf quantity, quality, and within-canopy variation in leaf longevity). Our model was driven by the prescribed seasonality of leaf quantity and quality derived from ground-based measurements within an Amazonian evergreen forest. Modeled photosynthetic seasonality was not sensitive to leaf quantity, but was highly sensitive to leaf quality and its vertical distribution within the canopy, with markedly more sensitivity to upper canopy leaf quality. This is because light absorption in tropical canopies is near maximal for the entire year, implying that seasonal changes in LAI have little impact on total canopy light absorption; and because leaf quality has a greater effect on photosynthesis of sunlit leaves than light limited, shade leaves and sunlit foliage are more abundant in the upper canopy. Our two-fraction leaf, two-layer canopy model, which accounted for all three phenological components, was able to simulate photosynthetic seasonality, explaining ~90% of the average seasonal variation in eddy covariance-derived CO 2 assimilation. This work identifies a parsimonious approach for representing tropical evergreen forest photosynthetic seasonality in TBMs that utilize the FvCB model of CO 2 assimilation and highlights the importance of incorporating more realistic phenological mechanisms in models that seek to improve the projection of future carbon dynamics in tropical evergreen forests., (© 2017 John Wiley & Sons Ltd.)

In the Forestry Experimental Station of Shandong Agricultural University, we determined the photosynthetic physiological and biochemical indexes including photosynthetic parameters, chlorophyll fluorescence, and chlorophyll content of one-year-old poplar seedlings under different doses (0.17, 0.33, 0.67, 1.00, 1.33 and 1.67 g·kg -1 ) of Chaetomium globosmn ND35 fungus fertilizer treatment to study the effects of fungus fertilizer on photosynthesis of poplar in replanted soil. The results showed that with the increase of fungus fertilizer dose, the chlorophyll content of poplar lea-ves (Chl) showed an increasing trend, while the physiological indexes such as electron transport rate (ETR), net photosynthetic rate (P n ), quantum efficiency (Φ), nitrate reductase (NR) activity and root vigor showed an increasing first and then decreasing trend. Meanwhile, the heat dissipation that depended on xanthophyll cycle decreased and non-photochemical quenching (NPQ) increased first and then decreased. When the dose of C. globosmn ND35 fungus fertilizer was 0.67 g·kg -1 or 1.00 g·kg -1 , excess light energy of photosynthetic apparatus was reduced, and photosynthetic apparatus distributed more light energy to the direction of photochemical reactions, which improved the energy use efficiency. Applying an appropriate amount (0.67-1.00 g·kg -1 ) of C. globosmn ND35 fungus fertilizer could improve root physiological activity and light use ability of poplar leaves, which was conducive to the improvement of operating states of photosynthetic apparatus, and then increased the photosynthetic efficiency of the poplar leaves.

Vegetation productivity metrics such as gross primary production (GPP) at the canopy scale are greatly affected by the efficiency of using absorbed radiation for photosynthesis, or light use efficiency (LUE). Thus, close investigation of the relationships between canopy GPP and photosynthetically active radiation absorbed by vegetation is the basis for quantification of LUE. We used multiyear observations over irrigated and rainfed contrasting C3 (soybean) and C4 (maize) crops having different physiology, leaf structure, and canopy architecture to establish the relationships between canopy GPP and radiation absorbed by vegetation and quantify LUE. Although multiple LUE definitions are reported in the literature, we used a definition of efficiency of light use by photosynthetically active "green" vegetation (LUE(green)) based on radiation absorbed by "green" photosynthetically active vegetation on a daily basis. We quantified, irreversible slowly changing seasonal (constitutive) and rapidly day-to-day changing (facultative) LUE(green), as well as sensitivity of LUE(green) to the magnitude of incident radiation and drought events. Large (2-3-fold) variation of daily LUE(green) over the course of a growing season that is governed by crop physiological and phenological status was observed. The day-to-day variations of LUE(green) oscillated with magnitude 10-15% around the seasonal LUE(green) trend and appeared to be closely related to day-to-day variations of magnitude and composition of incident radiation. Our results show the high variability of LUE(green) between C3 and C4 crop species (1.43 g C/MJ vs. 2.24 g C/MJ, respectively), as well as within single crop species (i.e., maize or soybean). This implies that assuming LUE(green) as a constant value in GPP models is not warranted for the crops studied, and brings unpredictable uncertainties of remote GPP estimation, which should be accounted for in LUE models. The uncertainty of GPP estimation due to facultative and constitutive changes in LUE(green) can be considered as a critical component of the total error budget in the context of remotely sensed based estimations of GPP. The quantitative framework of LUE(green) estimation presented here offers a way of characterizing LUE(green) in plants that can be used to assess their phenological and physiological status and vulnerability to drought under current and future climatic conditions and is essential for calibration and validation of globally applied LUE algorithms., (Copyright © 2015 Elsevier GmbH. All rights reserved.)

This article develops a new carbon exchange diagnostic model [i.e. Southampton CARbon Flux (SCARF) model] for estimating daily gross primary productivity (GPP). The model exploits the maximum quantum yields of two key photosynthetic pathways (i.e. C3 and C4 ) to estimate the conversion of absorbed photosynthetically active radiation into GPP. Furthermore, this is the first model to use only the fraction of photosynthetically active radiation absorbed by photosynthetic elements of the canopy (i.e. FAPARps ) rather than total canopy, to predict GPP. The GPP predicted by the SCARF model was comparable to in situ GPP measurements (R(2)  > 0.7) in most of the evaluated biomes. Overall, the SCARF model predicted high GPP in regions dominated by forests and croplands, and low GPP in shrublands and dry-grasslands across USA and Europe. The spatial distribution of GPP from the SCARF model over Europe and conterminous USA was comparable to those from the MOD17 GPP product except in regions dominated by croplands. The SCARF model GPP predictions were positively correlated (R(2)  > 0.5) to climatic and biophysical input variables indicating its sensitivity to factors controlling vegetation productivity. The new model has three advantages, first, it prescribes only two quantum yield terms rather than species specific light use efficiency terms; second, it uses only the fraction of PAR absorbed by photosynthetic elements of the canopy (FAPARps ) hence capturing the actual PAR used in photosynthesis; and third, it does not need a detailed land cover map that is a major source of uncertainty in most remote sensing based GPP models. The Sentinel satellites planned for launch in 2014 by the European Space Agency have adequate spectral channels to derive FAPARps at relatively high spatial resolution (20 m). This provides a unique opportunity to produce global GPP operationally using the Southampton CARbon Flux (SCARF) model at high spatial resolution., (© 2013 John Wiley & Sons Ltd.)

Summary: Theoretically, the PEP‐CK C4 subtype has a higher quantum yield of CO2 assimilation (ΦCO2) than NADP‐ME or NAD‐ME subtypes because ATP required for operating the CO2‐concentrating mechanism is believed to mostly come from the mitochondrial electron transport chain (mETC). However, reported ΦCO2 is not higher in PEP‐CK than in the other subtypes. We hypothesise, more photorespiration, associated with higher leakiness and O2 evolution in bundle‐sheath (BS) cells, cancels out energetic advantages in PEP‐CK species.Nine species (two to four species per subtype) were evaluated by gas exchange, chlorophyll fluorescence, and two‐photon microscopy to estimate the BS conductance (gbs) and leakiness using a biochemical model.Average gbs estimates were 2.9, 4.8, and 5.0 mmol m−2 s−1 bar−1, and leakiness values were 0.129, 0.179, and 0.180, in NADP‐ME, NAD‐ME, and PEP‐CK species, respectively. The BS CO2 level was somewhat higher, O2 level was marginally lower, and thus, photorespiratory loss was slightly lower, in NADP‐ME than in NAD‐ME and PEP‐CK species. Differences in these parameters existed among species within a subtype, and gbs was co‐determined by biochemical decarboxylating sites and anatomical characteristics.Our hypothesis and results partially explain variations in observed ΦCO2, but suggest that PEP‐CK species probably use less ATP from mETC than classically defined PEP‐CK mechanisms. [ABSTRACT FROM AUTHOR]

Photosynthesis drives plant physiology, biomass accumulation, and yield. Photosynthetic efficiency, specifically the operating efficiency of PSII (F q'/ F m'), is highly responsive to actual growth conditions, especially to fluctuating photosynthetic photon fluence rate (PPFR). Under field conditions, plants constantly balance energy uptake to optimize growth. The dynamic regulation complicates the quantification of cumulative photochemical energy uptake based on the intercepted solar energy, its transduction into biomass, and the identification of efficient breeding lines. Here, we show significant effects on biomass related to genetic variation in photosynthetic efficiency of 178 climbing bean (Phaseolus vulgaris L.) lines. Under fluctuating conditions, the F q'/ F m' was monitored throughout the growing period using hand-held and automated chlorophyll fluorescence phenotyping. The seasonal response of F q'/ F m' to PPFR (ResponseG:PPFR) achieved significant correlations with biomass and yield, ranging from 0.33 to 0.35 and from 0.22 to 0.31 in two glasshouse and three field trials, respectively. Phenomic yield prediction outperformed genomic predictions for new environments in four trials under different growing conditions. Investigating genetic control over photosynthesis, one single nucleotide polymorphism (Chr09_37766289_13052) on chromosome 9 was significantly associated with ResponseG:PPFR in proximity to a candidate gene controlling chloroplast thylakoid formation. In conclusion, photosynthetic screening facilitates and accelerates selection for high yield potential. [ABSTRACT FROM AUTHOR]

Summary: In natural ecosystems, plants compete for space, nutrients and light. The optically dense canopies limit the penetration of photosynthetically active radiation and light often becomes a growth‐limiting factor for the understory. The reduced availability of photons in the lower leaf layers is also a major constraint for yield potential in canopies of crop monocultures. Traditionally, crop breeding has selected traits related to plant architecture and nutrient assimilation rather than light use efficiency. Leaf optical density is primarily determined by tissue morphology and by the foliar concentration of photosynthetic pigments (chlorophylls and carotenoids). Most pigment molecules are bound to light‐harvesting antenna proteins in the chloroplast thylakoid membranes, where they serve photon capture and excitation energy transfer toward reaction centers of photosystems. Engineering the abundance and composition of antenna proteins has been suggested as a strategy to improve light distribution within canopies and reduce the gap between theoretical and field productivity. Since the assembly of the photosynthetic antennas relies on several coordinated biological processes, many genetic targets are available for modulating cellular chlorophyll levels. In this review, we outline the rationale behind the advantages of developing pale green phenotypes and describe possible approaches toward engineering light‐harvesting systems. [ABSTRACT FROM AUTHOR]

Light and its spectral characteristics are crucial for plant growth and development. The far-red photon flux mediates many plant processes through the action of phytochrome and also accelerates the photosynthetic electron transfer rate. In this study, we assessed the effects of far-red addition on butterhead lettuce morphology, light use efficiency, optical properties, and phytochemical characteristics. Three-week-old lettuce plants (Lactuca sativa L. cv. Alyssa) were grown for up to 28 days under a 10% blue and 90% red light spectrum (200 µmol m-2 s-1, 16 h photoperiod) to which five different intensities of far-red light (peak at 735 nm) were added (0-9-18-36-72 µmol m-2 s-1). White light-emitting diodes were included as a proxy for sunlight. Increasing supplemental far-red photon flux from zero to 21% increased the light use efficiency (g per mol) by 37% on day 14; 43% on day 21; and 39% on day 28. Measurements of projected head area suggest that this was associated with an increase in leaf expansion and photon capture and not necessarily a direct effect on photosynthesis. Moreover, vegetation indices based on leaf reflectance showed a decrease in chlorophyll-related indices under a high far-red photon flux. This decrease in pigment content was confirmed by chemical analyses, suggesting that the plants may not reach their full potential in terms of photon capture, limiting the overall photosynthetic performance. Furthermore, the stress-related Carter 1 index increased in plants grown under a high far-red photon flux, indicating early plant stress. Far-red tended to decrease the content of total phenolics and increase soluble sugars. The higher sugar levels can be attributed to an improved photochemical efficiency due to photosystem I excitation by far-red wavelengths, also known as the Emerson Enhancement effect. Despite these higher sugar levels, no effect on foliar nitrate content was observed. Our results show that far-red supplementation has the potential to enhance light interception at the early growth stages, although higher intensities of far-red may cause plant stress. [ABSTRACT FROM AUTHOR]

Estimating gross primary productivity (GPP) is important for simulating the subsequent carbon cycle elements and assessing the capacity of terrestrial ecosystems to support the sustainable development of human society. Light use efficiency (LUE) models were widely used to estimate GPP due to their concise model structures. However, quantifying LUEmax (maximum light use efficiency) and representing the responses of photosynthesis to environmental factors are still subject to large uncertainties, which lead to substantial errors in GPP simulations. In this study, we developed a hybrid model based on machine learning and a LUE model for GPP estimates. This hybrid model was built by targeting LUE with a machine learning approach, namely multi-layer perceptron (MLP), and then, estimating GPP within a LUE model framework with the MLP-based LUE and other required inputs. We trained the hybrid LUE (H-LUE) model and then, compared it against two conventional LUE models, the vegetation photosynthesis model (VPM) and vegetation photosynthesis and respiration model (VPRM), regarding GPP estimation, using tower-based daily-scale observations from 180 flux sites that cover nine different plant function types (PFTs). The results revealed better performance (R2 = 0.86 and RMSE = 1.79 gC m−2 d−1 on the test dataset) of the H-LUE model compared to the VPM and VPRM. Evaluations of the three models under four different extreme conditions consistently revealed better performance of the H-LUE model, indicating greater adaptability of the model to varied environments in the context of climate change. Furthermore, we also found that the H-LUE model can reasonably represent the responses of the LUE to meteorological variables. Our study revealed the reliable and robust performance of the developed hybrid LUE when simulating GPP across global biomes, providing references for developing better hybrid GPP models. [ABSTRACT FROM AUTHOR]

Terrestrial primary productivity and carbon cycle impacts of droughts are commonly quantified using vapour pressure deficit (VPD) data and remotely sensed greenness, without accounting for soil moisture. However, soil moisture limitation is known to strongly affect plant physiology. Here, we investigate light use efficiency, the ratio of gross primary productivity (GPP) to absorbed light. We derive its fractional reduction due to soil moisture (fLUE), separated from VPD and greenness changes, using artificial neural networks trained on eddy covariance data, multiple soil moisture datasets and remotely sensed greenness. This reveals substantial impacts of soil moisture alone that reduce GPP by up to 40% at sites located in sub-humid, semi-arid or arid regions. For sites in relatively moist climates, we find, paradoxically, a muted fLUE response to drying soil, but reduced fLUE under wet conditions. fLUE identifies substantial drought impacts that are not captured when relying solely on VPD and greenness changes and, when seasonally recurring, are missed by traditional, anomaly-based drought indices. Counter to common assumptions, fLUE reductions are largest in drought-deciduous vegetation, including grasslands. Our results highlight the necessity to account for soil moisture limitation in terrestrial primary productivity data products, especially for drought-related assessments.

We document the response of a 2 day wildfire smoke event on a moist temperate coniferous old‐growth forest in the western U.S. Wildfire smoke increased air temperature and suppressed relative humidity and total incoming radiation. Despite these conditions a ∼10% increase in ecosystem photosynthesis was observed. This was explained by a large increase (41%) in ecosystem‐scale stomatal conductance, inferred from measurements of carbonyl sulfide. Increased stomatal conductance contradicts expected stomatal closure at high vapor pressure deficit and was likely caused by an increase in diffuse light and thus shade leaf insolation. Higher ecosystem productivity and transpiration were linked to a greater drawdown of soil moisture. Ecosystem‐scale measurements across a diverse range of ecosystems are needed to better understand the canopy response to wildfire smoke, which is an increasingly common phenomenon across large parts of the world, including the forests of western North America. Plain Language Summary: Increases in wildfire intensity have been observed and projected for large parts of western North America, but the impact of smoke from these wildfires on carbon and water fluxes in different ecosystems is not well understood. In this study, we document the response of an old growth coniferous forest located in Pacific Northwestern U.S. to smoke from a nearby wildfire. During this event, the forest experienced warmer, drier and darker conditions. Using measurements of trace gases in the air we observe that the forest canopy increased photosynthesis and transpiration rates. This was due to an increase in scattering of light by smoke particles and facilitated by abundant soil moisture. Increased water‐use by trees also reduced the temperature of canopy leaves, potentially preventing them from damaging temperatures. We suggest continued measurements at the ecosystem scale to understand the response of diverse ecosystems to wildfire smoke, an increasingly common phenomenon for large parts of the world, including western North America. Key Points: Smoke from a nearby fire warmed and dried the air above an old‐growth forest and decreased incoming radiationSmoke led to higher canopy photosynthesis and transpiration rates, estimated from eddy covariance and carbonyl sulfide profile measurements, respectivelyThese increased fluxes are also facilitated by available deep soil moisture at the site [ABSTRACT FROM AUTHOR]

Earth observation‐based estimates of global gross primary production (GPP) are essential for understanding the response of the terrestrial biosphere to climatic change and other anthropogenic forcing. In this study, we attempt an ecosystem‐level physiological approach of estimating GPP using an asymptotic light response function (LRF) between GPP and incoming photosynthetically active radiation (PAR) that better represents the response observed at high spatiotemporal resolutions than the conventional light use efficiency approach. Modelled GPP is thereafter constrained with meteorological and hydrological variables. The variability in field‐observed GPP, net primary productivity and solar‐induced fluorescence was better or equally well captured by our LRF‐based GPP when compared with six state‐of‐the‐art Earth observation‐based GPP products. Over the period 1982–2015, the LRF‐based average annual global terrestrial GPP budget was 121.8 ± 3.5 Pg C, with a detrended inter‐annual variability of 0.74 ± 0.13 Pg C. The strongest inter‐annual variability was observed in semi‐arid regions, but croplands in China and India also showed strong inter‐annual variations. The trend in global terrestrial GPP during 1982–2015 was 0.27 ± 0.02 Pg C year−1, and was generally larger in the northern than the southern hemisphere. Most positive GPP trends were seen in areas with croplands whereas negative trends were observed for large non‐cropped parts of the tropics. Trends were strong during the eighties and nineties but levelled off around year 2000. Other GPP products either showed no trends or continuous increase throughout the study period. This study benchmarks a first global Earth observation‐based model using an asymptotic light response function, improving simulations of GPP, and reveals a stagnation in the global GPP after the year 2000. [ABSTRACT FROM AUTHOR]

Diffuse radiation produces a higher light use efficiency (LUE) than does direct radiation. However, light components and their impacts on interannual variations of photosynthesis in China have not been intensively studied. We estimated gross primary production (GPP) from a two‐leaf LUE model that incorporates a diffuse radiation effect and compared it with a big‐leaf LUE model that ignores the diffuse radiation impact. The results show that a dimming occurred in China—the estimated annual photosynthetically active radiation (PAR) declined by −1.79 MJ m−2 yr−1. However, the diffuse fraction and diffuse PAR increased over this interval. Both GPP models simulated an increasing trend of GPP in China from 2000 to 2017. The big‐leaf GPP model underestimated the increasing trend of GPP from the two‐leaf GPP model by 6.4%. The diffuse fraction change during the dimming exerted an embedded positive impact relative to the big‐leaf GPP trend in China. To evaluate the impact of total PAR versus its components on GPP, annual anomaly percentage (Ap) of GPP shows that the big‐leaf GPP model had a positive correlation between Ap of GPP and PAR across China. Considering the diffuse radiation impact, Ap of two‐leaf GPP was negatively correlated with PAR in southern China, which had a higher leaf area index (2.02) and a greater diffuse fraction (0.63). Strong diffuse radiation effects in southern China produced GPP anomalies in opposition to the direction of the PAR changes. These findings highlight the distinctive impact of light components on interannual variations of plant photosynthesis. Key Points: A two‐leaf GPP model predicts that diffuse radiation effects offset the impact of dimming on photosynthesis over 2000–2017 in ChinaDue to strong diffuse radiation impact, the annual anomaly of modeled two‐leaf GPP shows a negative correlation with PAR in southern ChinaA big‐leaf GPP model underestimates the increasing trend attributed to the dimming in China [ABSTRACT FROM AUTHOR]

Light use efficiency (LUE) is a critical parameter, on which we rely to quantify the vegetation's capability to harvest solar energy and thus the photosynthesis carbon uptake. However, our understanding on its magnitude, global pattern, and climatic drivers remains uncertain. In this study, we investigated global mean annual LUE during 1980–2013 based on state‐of‐the‐art estimates from scaled‐up eddy covariance measurements (data‐driven models) and 10 process‐based models used in Global Carbon Project. We found comparable global LUE estimates from data‐driven models (0.90 ± 0.25 g C MJ−1) and process‐based models (0.73 ± 0.22 g C MJ−1), with individual model estimates ranging from 0.49 to 0.98 g C MJ−1. While both types of models agreed on highest LUE over the tropical evergreen forests, discrepancies remained over middle and high latitudes of the Northern Hemisphere, which probably resulted from different response of LUE to climatic factors. Spatial analyses revealed that LUE variations were more driven by temperature and precipitation than by solar radiation. While the response of LUE to precipitation was almost always positive globally, the response of LUE to temperature was only positive in part of the nontropical regions. Process‐based models showed that precipitation strongly regulated the response of LUE to temperature, which shifted from negative to positive when mean annual precipitation was larger than 1,000 mm yr−1. Our results provide converging global LUE estimates and highlight the need to take fully account of interactive effects of climatic factors in regulating LUE and thus the response of photosynthesis to climate change. Key Points: Data‐driven and process‐based models consistently estimate global light use efficiency (LUE, 0.9 ± 0.3 and 0.7 ± 0.2 g C MJ−1, respectively)Discrepancies in LUE estimates were found in middle and high latitudes, probably resulting from different LUE response to climate variationsPrecipitation regulates LUE response to temperature, changing from negative to positive when annual precipitation is larger than 1,000 mm [ABSTRACT FROM AUTHOR]

• Stream metabolism essential to carbon cycling and food-web studies. • Hydropower plants can physically supersaturate water with dissolved gases. • New method using O 2 :Ar ratio allows estimation of metabolism in tail water ecosystems. • Results were in good agreements with concomitant changes in dissolved CO 2 • New method more applicable with portable mass inlet mass spectrometers (MIMS). The estimation of whole stream metabolism, as determined by photosynthesis and respiration, is critical to our understanding of carbon cycling and carbon subsidies to aquatic food-webs. The mass development of aquatic plants is a worldwide problem for human activities and often occurs in regulated rivers, altering biodiversity and ecosystem functions. Hydropower plants supersaturate water with gases and prevent the use of common whole stream metabolism models to estimate ecosystem respiration. Here we used the inert noble gas argon to parse out biological from physical processes in stream metabolism calculations. We coupled the O 2 :Ar ratio determined by gas chromatography in grab samples with in-situ oxygen concentrations measured by an optode to estimate aquatic plant photosynthesis and ecosystem respiration during supersaturation events through a parsimonious approach. The results compared well with a more complicated two-station model based on O 2 mass balances in non-supersatured water, and with associated changes in dissolved CO 2 (or dissolved inorganic carbon). This new method provides an independent approach to evaluate alternative corrections of dissolved oxygen data (e.g. through the use of total dissolved gases) in long term studies. The use of photosynthesis-irradiance models allows the determination of light parameters such as the onset of light saturation or low light use efficiency, which could be used for inverse modelling. The use of the O 2 :Ar approach to correct for oversaturation may become more applicable with the emergence of portable mass inlet mass spectrometers (MIMS). Photosynthesis was modest (2.9-5.8 g O 2 m2 day−1) compared to other rivers with submerged vegetation, likely indicating nutrient co-limitations (CO 2 , inorganic N and P). Respiration was very low (-2.1 to -3.9 g O 2 m2 day−1) likely due to a lack of allochthonous carbon supply and sandy sediment. [Display omitted] [ABSTRACT FROM AUTHOR]

Two comparable sites with uneven-aged mixed forest stands with more than 20% Douglas-fir in the growing stock at an altitude of 650 m a.s.l. were selected. The physiological response of young trees to different light intensities was measured during the main growing season in three consecutive years, and four different light categories, which were determined from hemispherical photographs. The four light intensity categories were defined according to Indirect Site Factor (ISF%): in the open (A-ISF > 35%), at the outer forest edge (B-25% < ISF < 35%), at the inner forest edge (C-15% < ISF < 25%), and under complete canopy under mature forest stand (D-ISF < 15%). Climate data were obtained from the Royal Netherlands Meteorological Institute ‘Climate Explorer’ website. For the intensive micrometeorological observations, four monitoring sites were established along the elevation gradient at each site during summer and late fall to record relative humidity (RH%) and temperature (°C) with a 30 min recording interval sequence. Measured assimilation responses (A) and light use efficiency (Φ) at one site followed the expected pattern, while humidity combined with microsite conditions proved significant in explaining the specific response of young Douglas-fir to the different light intensity at the other site. For higher survival and optimal future development of Douglas-fir in the changing environment, microsites with higher capacity for storage moisture and favorable microclimate should generally be preferred to exposed and dry sites.

Highlights • Studies on green light effects in tall, canopy forming crops (e.g. tomato) are rare. • Partially replacing a red:blue spectrum by green increased biomass by up to 6.5%. • Green tended to increase leaf biomass, specific leaf area, stem biomass and length. • In the middle of the canopy, carotenoid concentrations increased under green light. • Photosynthetic efficiency per waveband cannot explain effects on growth under several wavebands. Abstract Effects of green light on plant growth are relatively understudied, and published results are contradictory. Although per unit leaf area, green light drives photosynthesis less efficiently than does red light, on a whole-plant level green light may increase growth due to changes in vertical light distribution, leaf light acclimation and canopy architecture. As most studies were conducted on small plants with compact stems, positive effects may have remained unnoticed. In a greenhouse experiment, a tomato (Solanum lycopersicum) crop was exposed to 7, 20 or 39% of green light in a background of narrow bandwidth red and blue light, as well as sunlight, for 76 days. The intensity supplied by lamps (171 μmol m−2 s−1) and the red:blue ratio were similar between treatments. Adding green light (+32%) to the spectrum significantly and linearly increased plant biomass and yield (+6.5%). With increasing green light percentage, there were tendencies for linear increases in leaf biomass (P = 0.06), specific leaf area (P = 0.09), stem biomass (P = 0.07), stem length (P = 0.05) and number of internodes (P = 0.05). In the top and middle leaf layers of the canopy, net photosynthesis rate, stomatal conductance and leaf thickness were unaffected by the treatment while in leaves in the middle leaf layer, chlorophyll a : b ratio and carotenoid concentrations increased with the percentage of green light. This study shows that partial replacement of red by green light increases growth of plants in dense canopies and suggests that the combined effects of a light spectrum on plant growth are more than the sum of wavelength effects on photosynthetic efficiency. [ABSTRACT FROM AUTHOR]

Abstract Due to its close link to the photosynthetic process, sun-induced chlorophyll fluorescence (F) opens new possibilities to study dynamics of photosynthetic light reactions and to quantify CO 2 assimilation rates. Although recent studies show that F is linearly related to gross primary production (GPP) on coarse spatial and temporal scales, it is argued that this relationship may be mainly driven by seasonal changes in absorbed photochemical active radiation (APAR) and less by the plant light use efficiency (LUE). In this work a high-resolution spectrometer was used to continuously measure red and far-red fluorescence and different reflectance indices within a sugar beet field during the growing season in 2015. Diurnal and seasonal developments were compared to eddy covariance derived GPP. Additionally, part of the time series coincided with a heatwave. The induced drought stress allowed us to observe F and its relationship to GPP under changing environmental conditions during the seasonal cycle. Across the season a strong linear relationship between GPP and F 760 was found. This relationship however, was mainly driven by changes in APAR and was strongly reduced under drought conditions. We could show that far-red fluorescence yield can explain 59% of the diurnal and 79% of the seasonal variance in the light use efficiency. However, an even stronger relationship between FY 760 and the structural vegetation index MTVI2 was found, implying that FY 760 is affected by seasonal structural changes of the canopy. Nevertheless, the seasonally de-trended FY 760 and PRI show that they share strong interdependencies with seasonal and diurnal LUE, in particular under drought stress conditions. Highlights • An extensive dataset was measured during the 2015 heat wave. • Under stress condition the relationship between F and GPP degreases significantly. • A revised PRI is proposed as indicator for diurnal changes in NPQ. • Seasonally de-trended rFY 760 and rPRI showed strong diurnal link to LUE. [ABSTRACT FROM AUTHOR]

Understanding plant photosynthesis, or Gross Primary Production (GPP), is a crucial aspect of quantifying the terrestrial carbon cycle. Remote sensing approaches, in particular multi-angular spectroscopy, have proven successful for studying relationships between canopy-reflectance and plant-physiology processes, thus providing a mechanism to scale up. However, many different instrumentation designs exist and few cross-comparisons have been undertaken. This paper discusses the design evolution of the Automated Multiangular SPectro-radiometer for Estimation of Canopy reflectance (AMSPEC) series of instruments. Specifically, we assess the performance of the PP-Systems Unispec-DC and Ocean Optics JAZ-COMBO spectro-radiometers installed on an updated, tower-based AMSPEC-III system. We demonstrate the interoperability of these spectro-radiometers, and the results obtained suggest that JAZ-COMBO can successfully be used to substitute more expensive measurement units for detecting and investigating photosynthesis and canopy spectra. We demonstrate close correlations between JAZ-COMBO and Unispec-DC measured canopy radiance (0.75 ≤ R2 ≤ 0.85) and solar irradiance (0.95 ≤ R2 ≤ 0.96) over a three month time span. We also demonstrate close agreement between the bi-directional distribution functions obtained from each instrument. We conclude that cost effective alternatives may allow a network of AMSPEC-III systems to simultaneously monitor various vegetation types in different ecosystems. This will allow to scale and improve our understanding of the interactions between vegetation physiology and spectral characteristics, calibrate broad-scale observations to stand-level measurements, and ultimately lead to improved understanding of changing vegetation spectral features from satellite.

In plant factories, light is fully controllable for crop production but involves a cost. For efficient lighting, light use efficiency (LUE) should be considered as part of light environment design. The objectives of this study were to evaluate and interpret the light interception, photosynthetic rate, and LUE of lettuces under electrical lights using ray-tracing simulation. The crop architecture model was constructed by 3D scanning, and ray-tracing simulation was used to interpret light interception and photosynthesis. For evaluation of simulation reliability, measured light intensities and photosynthetic rates in a growth chamber were compared with those obtained by simulation at different planting densities. Under several scenarios modeling various factors affecting light environments, changes in light interception and LUE were interpreted. The light intensities and photosynthetic rates obtained by simulation showed good agreement with the measured values, with R2 > 0.86. With decreasing planting density, the light interception of the central plant increased by approximately 18.7%, but that of neighboring plants decreased by approximately 5.5%. Under the various scenarios, shorter lighting distances induced more heterogenetic light distribution on plants and caused lower light interception. Under a homogenous light distribution, the light intensity was optimal at approximately 360 μmol m−2 s−1 with an LUE of 6.5 g MJ−1. The results of this study can provide conceptual insights into the design of light environments in plant factories.

The gross primary production (GPP) in tropical terrestrial ecosystems plays a critical role in the global carbon cycle and climate change. The strong 2015–2016 El Niño event offers a unique opportunity to investigate how GPP in the tropical terrestrial ecosystems responds to climatic forcing. This study uses two GPP products and concurrent climate data to investigate the GPP anomalies and their underlying causes. We find that both GPP products show an enhanced GPP in 2015 for the tropical terrestrial ecosystem as a whole relative to the multiyear mean of 2001–2015, and this enhancement is the net result of GPP increase in tropical forests and decrease in nonforests. We show that the increased GPP in tropical forests during the El Nino event is consistent with increased photosynthesis active radiation as a result of a reduction in clouds, while the decreased GPP in nonforests is consistent with increased water stress as a result of a reduction of precipitation and an increase of temperature. These results reveal the strong coupling of ecosystem and climate that is different in forest and nonforest ecosystems and provide a test case for carbon cycle parameterization and carbon‐climate feedback simulation in models. Key Points: The two gross primary production (GPP) products show an enhanced GPP in 2015 for the tropical terrestrial ecosystem as a whole relative to the mean of 2001–2015The enhancement in tropical GPP in 2015 is the net result of GPP increase in forests (GPPF) and decrease in nonforested areas (GPPN)The increased GPPF is consistent with increased photosynthesis active radiation, and the reduced GPPN is in line with increased water stress and temperature [ABSTRACT FROM AUTHOR]

Previous studies showed that Chaetomium globosum ND35 fungus fertilizer can improve the microbial community structure and enzyme activities of replanted soil. However, it remains unclear whether can improve the physiological and ecological characteristics of plants under successive rotation. In this study, we investigated the photosynthetic, physiological, and biochemical indexes including photosynthetic parameters, chlorophyll fluorescence, and chlorophyll content of 1-year-old poplar seedlings under seven different doses (range from 0 to 1.67 g kg−1) of C. globosum ND35 fungus fertilizer to study the effects of fungus fertilizer on photosynthesis of Poplar. Our results showed that: (1) With increasing application of fungus fertilizer in replanted soil, chlorophyll content of poplar leaves (Chl) increased, while physiological indexes such as electron transport rate (ETR), net photosynthetic rate (Pn), quantum efficiency (Φ), nitrate reductase (NR) activity and root vigor initially increased and then declined. Meanwhile, heat dissipation that depended on the xanthophyll cycle declined and non-photochemical quenching (NPQ) initially increased and then decreased. When the dose of C. globosum ND35 fungus fertilizer was 0.67 g kg−1 (T3) and 1.00 g kg−1 (T4), excess light energy of photosynthetic apparatus was reduced, and photosynthetic apparatus distributed more light energy to the direction of photochemical reactions, which improved the efficiency of energy use. Plant height and biomass of leaves, stems, and roots were maximum at T3. We conclude that applying appropriate amounts of C. globosum ND35 fungus fertilizer can improve root physiological activity and capacity for use of light by poplar leaves. This can improve the operating states of the photosynthetic apparatus and lead to increased photosynthetic efficiency of poplar leaves and accumulation of dry matter. This suggests a strategy to alleviate the successive rotation obstacle of soil nutrient depletion. [ABSTRACT FROM AUTHOR]

Radiation Use Efficiency (RUE) defines the productivity with which absorbed photosynthetically active radiation (APAR) is converted to plant biomass. Readily used in crop growth models to predict dry matter accumulation, RUE is commonly determined by elaborate static sensor measurements in the field. Different definitions are used, based on total absorbed PAR (RUEtotal) or PAR absorbed by the photosynthetically active leaf tissue only (RUEgreen). Previous studies have shown that the fraction of PAR absorbed (fAPAR), which supports the assessment of RUE, can be reliably estimated via remote sensing (RS), but unfortunately at spatial resolutions too coarse for experimental agriculture. UAV-based RS offers the possibility to cover plant reflectance at very high spatial and temporal resolution, possibly covering several experimental plots in little time. We investigated if (a) UAV-based low-cost camera imagery allowed estimating RUEs in different experimental plots where maize was cultivated in the growing season of 2016, (b) those values were different from the ones previously reported in literature and (c) there was a difference between RUEtotal and RUEgreen. We determined fractional cover and canopy reflectance based on the RS imagery. Our study found that RUEtotal ranges between 4.05 and 4.59, and RUEgreen between 4.11 and 4.65. These values are higher than those published in other research articles, but not outside the range of plausibility. The difference between RUEtotal and RUEgreen was minimal, possibly due to prolonged canopy greenness induced by the stay-green trait of the cultivar grown. The procedure presented here makes time-consuming APAR measurements for determining RUE especially in large experiments superfluous. [ABSTRACT FROM AUTHOR]

Spatially and temporally continuous estimation of plant photosynthetic carbon fixation (or gross primary production, GPP) is crucial to our understanding of the global carbon cycle and the impact of climate change. Besides spatial, seasonal and interannual variations, GPP also exhibits strong diurnal variations. Satellite retrieved solar-induced chlorophyll fluorescence (SIF) provides a spatially continuous, but temporally discrete measurement of plant photosynthesis, and has the potential to be used to estimate GPP at global scale. However, it remains unclear whether the seasonal time series of SIF snapshots taken at a fixed time of the day can be used to infer daily total GPP variation at spatial and seasonal scales. In this study, we first used GPP estimates from 135 eddy covariance flux sites, covering a wide range of geographic locations and biome types, to investigate the relationship between the instantaneous GPP (GPP inst ) and daily GPP (GPP daily ) on the seasonal course for different times of the day. Latitudinal and diurnal patterns were found to correspond to variations in photosynthetically active radiation (PAR) and light use efficiency (LUE), respectively. We then used the Soil-Canopy Observation Photosynthesis and Energy Balance (SCOPE) model and the FluxCom GPP product to investigate the instantaneous and daily SIF-GPP relationships at five flux tower sites along a latitudinal gradient and at a global scale for different biome types. The results showed that daily SIF had a stronger linear correlation with daily GPP than instantaneous SIF at the seasonal scale, with an instantaneous to daily SIF conversion factor following the latitudinal and seasonal pattern driven by PAR. Our study highlights the necessity to take the latitudinal and diurnal factors into consideration for SIF-GPP relationship analyses or for physiological phenology analyses based on SIF. [ABSTRACT FROM AUTHOR]

Abstract: Recent development of sun‐induced chlorophyll fluorescence (SIF) technology is stimulating studies to remotely approximate canopy photosynthesis (measured as gross primary production, GPP). While multiple applications have advanced the empirical relationship between GPP and SIF, mechanistic understanding of this relationship is still limited. GPP:SIF relationship, using the standard light use efficiency framework, is determined by absorbed photosynthetically active radiation (APAR) and the relationship between photosynthetic light use efficiency (LUE) and fluorescence yield (SIFy). While previous studies have found that APAR is the dominant factor of the GPP:SIF relationship, the LUE:SIFy relationship remains unclear. For a better understanding of the LUE:SIFy relationship, we deployed a ground‐based system (FluoSpec2), with an eddy‐covariance flux tower at a soybean field in the Midwestern U.S. during the 2016 growing season to collect SIF and GPP data simultaneously. With the measurements categorized by plant growth stages, light conditions, and time scales, we confirmed that a strong positive GPP:SIF relationship was dominated by an even stronger linear SIF:APAR relationship. By normalizing both GPP and SIF by APAR, we found that under sunny conditions our soybean field exhibited a clear positive SIFy:APAR relationship and a weak negative LUE:SIFy relationship, opposite to the positive LUE:SIFy relationship reported previously in other ecosystems. Our study provides a first continuous SIF record over multiple growth stages for agricultural systems and reveals a distinctive pattern related to the LUE:SIFy relationship compared with previous work. The observed positive relationship of SIFy:APAR at the soybean site provides new insights of the previous understanding on the SIF's physiological implications. [ABSTRACT FROM AUTHOR]

Solar-induced chlorophyll fluorescence (SIF) opens a new perspective on the monitoring of vegetation photosynthesis from space, and has been recently used to estimate gross primary productivity (GPP). However, previous studies on SIF were mainly based on satellite observations from the Greenhouse Gases Observing Satellite (GOSAT) and Global Ozone Monitoring Experiment-2 (GOME-2), and the evaluation of these coarse-resolution SIF measurements using GPP derived from eddy covariance (EC) flux towers has been hindered by the scale mismatch between satellite and tower footprints. We use new far-red SIF observations from the Orbiting Carbon Observatory-2 (OCO-2) with much finer spatial resolution and GPP data from EC flux towers from 2014 to 2016 to examine the relationship between GPP and SIF for temperate forests. The OCO-2 SIF tracked tower GPP well, and had strong correlation with tower GPP at both retrieval bands (757 nm and 771 nm) and both instantaneous (mid-day) and daily timescales, with the strongest relationship for the 757 nm band (SIF 757 ) at the daily timescale. Daily SIF 757 exhibited much stronger correlation with tower GPP compared to the enhanced vegetation index (EVI) and normalized difference vegetation index (NDVI) based on the surface reflectance product derived from the moderate resolution imaging spectroradiometer (MODIS) onboard either Terra or Aqua satellite and had a similarly strong relationship as EVI based on the bidirectional reflectance distribution function (BRDF) corrected reflectance product (MCD43A4) based on data from both Terra and Aqua. Absorbed photosynthetically active radiation (APAR) explained 85% of the variance in SIF 757 , while the product of APAR and two environmental scalars - f T min and f VPD (representing minimum temperature stress and water stress) explained higher variance (92%) in SIF 757 . This suggests that SIF mainly depends on APAR and is also affected by environmental stresses that determine photosynthetic light use efficiency. The BRDF-corrected EVI also has advantages over SIF in that EVI has spatially and temporally continuous coverage and has a much longer record (2000-present). The OCO-2 SIF 757 estimated GPP well (R 2 = 0.81, p < 0.0001; RMSE = 1.11 gC m − 2 d − 1 ), and its performance was comparable to or slightly better than that of the MODIS GPP algorithm, a GPP model based on the light use efficiency logic. With intensive OCO-2 observations acquired in the Target mode around Park Falls, a calibration/validation site for OCO-2, we also generated gridded SIF and then estimated GPP on a per-pixel basis at the landscape scale. Our findings demonstrate the strong ability of chlorophyll fluorescence observed by OCO-2 in estimating GPP for temperate forests and reveal its potential and limitations in future ecosystem functioning and carbon cycling studies. [ABSTRACT FROM AUTHOR]

Satellite-derived vegetation indices (VIs) have been widely used to approximate or estimate gross primary productivity (GPP). However, it remains unclear how the VI-GPP relationship varies with indices, biomes, timescales, and the bidirectional reflectance distribution function (BRDF) effect. We examined the relationship between VIs and GPP for 121 FLUXNET sites across the globe and assessed how the VI-GPP relationship varied among a variety of biomes at both monthly and annual timescales. We used three widely-used VIs: normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and 2-band EVI (EVI2) as well as a new VI - NIRV and used surface reflectance both with and without BRDF correction from the moderate resolution imaging spectroradiometer (MODIS) to calculate these indices. The resulting traditional (NDVI, EVI, EVI2, and NIRV) and BRDF-corrected (NDVIBRDF, EVIBRDF, EVI2BRDF, and NIRV, BRDF) VIs were used to examine the VI-GPP relationship. At the monthly scale, all VIs were moderate or strong predictors of GPP, and the BRDF correction improved their performance. EVI2BRDF and NIRV, BRDF had similar performance in capturing the variations in tower GPP as did the MODIS GPP product. The VIs explained lower variance in tower GPP at the annual scale than at the monthly scale. The BRDF-correction of surface reflectance did not improve the VI-GPP relationship at the annual scale. The VIs had similar capability in capturing the interannual variability in tower GPP as MODIS GPP. VIs were influenced by temperature and water stresses and were more sensitive to temperature stress than to water stress. VIs in combination with environmental factors could improve the prediction of GPP than VIs alone. Our findings can help us better understand how the VI-GPP relationship varies among indices, biomes, and timescales and how the BRDF effect influences the VI-GPP relationship.

Global retrieval of solar-induced chlorophyll fluorescence (SIF) using remote sensing by means of satellites has been developed rapidly in recent years. Exploring how SIF could improve the characterization of photosynthesis and its role in the land surface carbon cycle has gradually become a very important and active area. However, compared with other gross primary production (GPP) models, the robustness of the parameterization of the SIF model under different circumstances has rarely been investigated. In this study, we examined and compared the effects of temporal aggregation and meteorological conditions on the stability of model parameters for the SIF model ( ε / S I F yield ), the one-leaf light-use efficiency (SL-LUE) model ( ε max ), and the two-leaf LUE (TL-LUE) model ( ε msu and ε msh ). The three models were parameterized based on a maize–wheat rotation eddy-covariance flux tower data in Yucheng, Shandong Province, China by using the Metropolis–Hasting algorithm. The results showed that the values of the ε / S I F yield and ε max were similarly robust and considerably more stable than ε msu and ε msh for all temporal aggregation levels. Under different meteorological conditions, all the parameters showed a certain degree of fluctuation and were most affected at the mid-day scale, followed by the monthly scale and finally at the daily scale. Nonetheless, the averaged coefficient of variation ( C V ) of ε / S I F yield was relatively small (15.0%) and was obviously lower than ε max ( C V = 27.0%), ε msu ( C V = 43.2%), and ε msh ( C V = 53.1%). Furthermore, the SIF model’s performance for estimating GPP was better than that of the SL-LUE model and was comparable to that of the TL-LUE model. This study indicates that, compared with the LUE-based models, the SIF-based model without climate-dependence is a good predictor of GPP and its parameter is more likely to converge for different temporal aggregation levels and under varying environmental restrictions in croplands. We suggest that more flux tower data should be used for further validation of parameter convergence in other vegetation types.

Remote sensing of high-latitude forests phenology is essential for understanding the global carbon cycle and the response of vegetation to climate change. The normalized difference vegetation index (NDVI) has long been used to study boreal evergreen needleleaf forests (ENF) and deciduous broadleaf forests. However, the NDVI-based growing season is generally reported to be longer than that based on gross primary production (GPP), which can be attributed to the difference between greenness and photosynthesis. Instead of introducing environmental factors such as land surface or air temperature like previous studies, this study attempts to make VI-based phenology more consistent with photosynthesis dynamics through applying a light use efficiency model. NDVI (MOD13C2) was used as a proxy for both fractional of absorbed photosynthetically active radiation (APAR) and light use efficiency at seasonal time scale. Results show that VI-based phenology is improved towards tracking seasonal GPP changes more precisely after applying the light use efficiency model compared to raw NDVI or APAR, especially over ENF. [ABSTRACT FROM AUTHOR]

Remote sensing of plant carbon uptake, or gross primary production (GPP), in a repeatable and consistent manner remains a key element of a comprehensive understanding of the role of vegetation within the global carbon cycle. To further this understanding at a landscape level or global scale, accurate remote sensing of photosynthetic light-use efficiency (LUE) is required to understand photosynthetic down-regulation and environmental constraints to plant photosynthesis. The past decade has seen advances in detecting both leaf- and canopy-level physiological stress behaviours using the photochemical reflectance index (PRI), a narrow-waveband normalized difference index that relates LUE to a xanthophyll-induced absorption feature at 531 nm. To date, however, much of this research has occurred using top of canopy measurements, while our understanding of the vertical distribution of LUE within the crown is limited. In this study, we demonstrate an approach which could be used to scale photosynthetic behaviour of vegetation vertically and horizontally using estimates of vertical canopy structure obtained from terrestrial Light Detection and Ranging (LiDAR) data to predict proportions of shaded and sunlit canopy which are then linked to predictions of LUE. We apply the approach over a mature Aspen study site located in central Saskatchewan, Canada utilising full-waveform LiDAR data provided by the ground-based laser scanner system and canopy spectra obtained by the AMSPEC II spectro-radiometer. Agreement between predictions of Gross Primary Productivity (GPP) using the developed approach compared to independent observations was highly significant at hourly intervals (R 2 = 0.80, p < 0.01) under clear sky conditions. A range of LUE vertical profiles for different stand structures across the growing season were developed providing estimations of how crown structure can impact LUE vertically in the crown. We conclude with a recommendation for ongoing research to verify these types of trends using concurrently acquired, independently derived leaf LUE from photosynthesis light-response curves, and forest structure variation from LiDAR, to provide a more exact quantification of these patterns. [ABSTRACT FROM AUTHOR]

We investigated the radiative energy budgets of a heterogeneous photosynthetic coral reef sediment and a compact uniform cyanobacterial biofilm on top of coastal sediment. By combining electrochemical, thermocouple and fiber-optic microsensor measurements of O2, temperature and light, we could calculate the proportion of the absorbed light energy that was either dissipated as heat or conserved by photosynthesis. We show, across a range of different incident light regimes, that such radiative energy budgets are highly dominated by heat dissipation constituting up to 99.5% of the absorbed light energy. Highest photosynthetic energy conservation efficiency was found in the coral sediment under low light conditions and amounted to 18.1% of the absorbed light energy. Additionally, the effect of light directionality, i.e., diffuse or collimated light, on energy conversion efficiency was tested on the two surface-associated systems. The effects of light directionality on the radiative energy budgets of these phototrophic communities were not unanimous but, resulted in local spatial differences in heat-transfer, gross photosynthesis, and light distribution. The light acclimation index, Ek, i.e., the irradiance at the onset of saturation of photosynthesis, was >2 times higher in the coral sediment compared to the biofilm and changed the pattern of photosynthetic energy conservation under light-limiting conditions. At moderate to high incident irradiances, the photosynthetic conservation of absorbed energy was highest in collimated light; a tendency that changed in the biofilm under sub-saturating incident irradiances, where higher photosynthetic efficiencies were observed under diffuse light. The aim was to investigate how the physical structure and light propagation affected energy budgets and light utilization efficiencies in loosely organized vs. compact phototrophic sediment under diffuse and collimated light. Our results suggest that the optical properties and the structural organization of phytoelements are important traits affecting the photosynthetic efficiency of biofilms and sediments. [ABSTRACT FROM AUTHOR]

Non-photosynthetic components within the canopy (e.g., dry leaves and stem) contribute little to photosynthesis and therefore, remote sensing of gross primary production (GPP) could be improved by the removal of these components. A scaled enhanced vegetation index (EVI), which is usually regarded as a linear function of EVI, was found to have the strongest relationship with chlorophyll level fraction of absorbed photosynthetically active radiation (FPARchl) and can help improve GPP estimation in croplands compared to canopy level FPAR (FPARcanopy). However, the application of the FPARchl theory to other plant functional types (PFTs) and the underlying reasons remain largely unknown. In this study, based on standard MODIS algorithm we comprehensively assessed the performances of FPARcanopy, scaled EVI (FPARchl1), normalized difference vegetation index (NDVI), scaled NDVI (FPARchl2) and EVI as proxies of FPAR for estimating GPP at four forest and six non-forest sites (e.g., grasslands, croplands and wetlands) from ChinaFLUX, representing a wide range of ecosystems with different canopy structures and eco-climatic zones. Our results showed that the scaled EVI (FPARchl1) as FPAR effectively improved the accuracy of estimated GPP for the entire PFTs. FPARchl1 substantially improved forest GPP estimations with higher coefficient of determination (R 2 ), lower root mean square error (RMSE) and lower bias. In comparison, for non-forest PFTs, the improvement in R 2 between estimated GPP based on FPARchl1 (GPPchl1) and flux tower GPP was less evident than those between flux GPP and GPP estimations from FPARcanopy (GPPcanopy), FPARchl2, NDVI and EVI. The temperature and water attenuation scalars played important roles in reducing the difference of various GPP and indirectly reducing the impact of different FPARs on GPP in non-forest PFTs. Even so, FPARchl1 is an ecologically more meaningful parameter since FPARchl1 and flux tower GPP dropped to zero more synchronously in both forest and non-forest sites. In particular, we found that the improvement of GPPchl1 relative to GPPcanopy was positively correlated with the maximum leaf area index (LAI), implying the importance of site characteristic in regulating the strength of the improvement. This is encouraging for remote sensing of GPP for which vegetation parameter retrieval has often been found to be less successful at high LAI due to saturations in reflective and scattering domains. Our results demonstrate the significance of accurate and ecologically meaningful FPAR parameterization for improving our current capability in GPP modeling. [ABSTRACT FROM AUTHOR]

Although quantifying the massive exchange of carbon that takes place over the Amazon Basin remains a challenge, progress is being made as the remote sensing community moves from using traditional, reflectance-based vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), to the more functional Photochemical Reflectance Index (PRI). This new index, together with satellite-derived estimates of canopy light interception and Sun-Induced Fluorescence (SIF), provide improved estimates of Gross Primary Production (GPP). This paper traces the development of these new approaches, compares the results of their analyses from multiple years of data acquired across the Amazon Basin and suggests further improvements in instrument design, data acquisition and processing. We demonstrated that our estimates of PRI are in generally good agreement with eddy-flux tower measurements of photosynthetic light use efficiency (ε) at four sites in the Amazon Basin: r² values ranged from 0.37 to 0.51 for northern flux sites and to 0.78 for southern flux sites. This is a significant advance over previous approaches seeking to establish a link between global-scale photosynthetic activity and remotely-sensed data. When combined with measurements of Sun-Induced Fluorescence (SIF), PRI provides realistic estimates of seasonal variation in photosynthesis over the Amazon that relate well to the wet and dry seasons. We anticipate that our findings will steer the development of improved approaches to estimate photosynthetic activity over the tropics. [ABSTRACT FROM AUTHOR]

The development of spectral methods of remote sensing, including measurement of a photochemical reflectance index (PRI), is a prospective trend in precision agriculture. There are many works which have investigated the connection between photosynthetic parameters and PRI; however, their results varied and were sometimes contradictory. For this paper, we performed a meta-analysis of works in this field. Here, only linear correlations of PRI with photosynthetic parameters—including quantum yield of photosystem II (ΔF/Fm’), nonphotochemical quenching of chlorophyll fluorescence (NPQ), and light use efficiency (LUE)—were investigated. First, it was shown that the correlations were dependent on conditions of PRI measurements (leaf or canopy; artificial light or sunlight). Second, it was shown that a minimal level of the photosynthetic stress, and the variation of this level among investigated plants, can influence the linear correlation of PRI with ΔF/Fm’ and NPQ; the effect was dependent on conditions of measurements. In contrast, the distribution of LUE among plants did not influence its correlation with PRI. Thus, the meta-analysis shows that the distribution of photosynthetic parameters among investigated plants can be an important factor that influences the efficiency of remote sensing on the basis of the PRI measurement.

Accurate estimation of the gross primary production (GPP) of terrestrial ecosystems is vital for a better understanding of the spatial-temporal patterns of the global carbon cycle. In this study, we estimate GPP in North America (NA) using the satellite-based Vegetation Photosynthesis Model (VPM), MODIS images at 8-day temporal and 500 m spatial resolutions, and NCEP-NARR (National Center for Environmental Prediction-North America Regional Reanalysis) climate data. The simulated GPP (GPP VPM ) agrees well with the flux tower derived GPP (GPP EC ) at 39 AmeriFlux sites (155 site-years). The GPP VPM in 2010 is spatially aggregated to 0.5 by 0.5° grid cells and then compared with sun-induced chlorophyll fluorescence (SIF) data from Global Ozone Monitoring Instrument 2 (GOME-2), which is directly related to vegetation photosynthesis. Spatial distribution and seasonal dynamics of GPP VPM and GOME-2 SIF show good consistency. At the biome scale, GPP VPM and SIF shows strong linear relationships (R 2 > 0.95) and small variations in regression slopes (4.60–5.55 g C m − 2 day − 1 /mW m − 2 nm − 1 sr − 1 ). The total annual GPP VPM in NA in 2010 is approximately 13.53 Pg C year − 1 , which accounts for ~ 11.0% of the global terrestrial GPP and is within the range of annual GPP estimates from six other process-based and data-driven models (11.35–22.23 Pg C year − 1 ). Among the seven models, some models did not capture the spatial pattern of GOME-2 SIF data at annual scale, especially in Midwest cropland region. The results from this study demonstrate the reliable performance of VPM at the continental scale, and the potential of SIF data being used as a benchmark to compare with GPP models. [ABSTRACT FROM AUTHOR]

Peatland net ecosystem production is a key variable to assess changes in the functional role of peatlands in the global carbon cycle. Light use efficiency (LUE) models in combination with satellite data have been used to estimate production for most major ecosystems, but peatlands have been largely ignored. The objectives of this study were: 1) to examine how the LUE parameter epsilon, ε (the amount of carbon fixed or converted to biomass per unit absorbed photosynthetically active radiation), varies between and within four different peatlands; 2) to examine how the variations in ε relate to variations in environmental conditions; and 3) to evaluate a LUE-based model for estimation of ε in peatlands. We achieve these objectives using a combination of eddy covariance flux measurements, climate data and satellite data and estimate ε using the LUE-based vegetation photosynthesis model (VPM). The results show that: 1) mean site-specific flux-derived ε values (± standard deviation) were split into three statistically different groups: lowest values at the two colder fens, Kaamanen and Sandhill (0.22 ± 0.18 and 0.23 ± 0.20 g C MJ − 1 , respectively), highest values at the treed fen La Biche (0.47 ± 0.27 g C MJ − 1 ) and intermediate values at the bog, Mer Bleue (0.34 ± 0.18 g C MJ − 1 ); 2) Variations in monthly ε within sites related mainly to air temperature, while variations in annual ε within sites related mainly to wetness variables; 3) relative mean absolute errors of estimates of ε for the four sites ranged between 19% and 35%, with r 2 values ranging between 72% and 93%. LUE models are appealing as they are relatively simple formulations of variables that are easily obtained from satellite data. Challenges associated with the use of satellite data derived input variables are further discussed in the paper. [ABSTRACT FROM AUTHOR]

Light wavelengths preferentially absorbed by chlorophyll (chl) often display steep absorption gradients. This oversaturates photosynthesis in upper chloroplasts and deprives lower chloroplasts of blue and red light. Reducing chl content could create a more even leaf light distribution and thereby increase leaf light-use efficiency and overall canopy photosynthesis. This was tested on soybean cultivar 'Clark' (WT) and a near-isogenic chl b deficient mutant, Y11y11, grown in controlled environment chambers and in the field. Light attenuation was quantified using a novel approach involving light sheet microscopy. Leaf adaxial and abaxial surfaces were illuminated separately with blue, red, and green wavelengths, and chl fluorescence was detected orthogonally to the illumination plane. Relative fluorescence was significantly greater in deeper layers of the Y11y11 mesophyll than in WT, with the greatest differences in blue, then red, and finally green light when illuminated from the adaxial surface. Modeled relative photosynthesis based on chlorophyll profiles and Beer's Law predicted less steep gradients in mutant relative photosynthesis rates compared to WT. Although photosynthetic light-use efficiency was greater in the field-grown mutant with ~50% lower chl, light-use efficiency was lower in the mutant when grown in chambers where chl was ~80% reduced. This difference is probably due to pleiotropic effects of the mutation that accompany very severe reductions in chlorophyll and may warrant further testing in other low-chl lines. [ABSTRACT FROM AUTHOR]

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Light use efficiency (LUE) plays a vital role in determination of crop biomass and yield. Important components of LUE, i.e. canopy structure, nitrogen distribution, photosynthetic capacity and CO 2 diffusion conductance were investigated in paddy rice grown under low, normal and high supplemental nitrogen (0, 115, and 180 kg N ha −1 ). Photosynthetic characteristics varied linearly with leaf nitrogen content (N a ), independent of treatment and canopy position, so differences in photosynthesis were due to differences in N allocation. CO 2 diffusion resistances were significant and constrained LUE (more during late season), but there were no differences between treatments. Early in the season (tillering stage) leaves in the fertilized treatments had higher photosynthetic rates due to higher leaf N content leading to larger amounts of rate-limiting photosynthetic proteins, which gave them an early head start and boost in productivity and leaf area index (LAI), bringing increases in canopy light interception. Later during the growth season, differences in leaf N a and photosynthetic characteristics between treatments were slight. Enhanced LAI in fertilized plots throughout the growing season was related to greater leaf number and leaf area per planted bundle and a larger leaf area in the upper canopy (LAUC). Fertilized treatments had a higher LAUC with high leaf nitrogen concentration and reduced mesophyll diffusion limitation but greater exposure to full sunlight that led to improved nitrogen use efficiency and efficient carbon gain. In conclusion, differences in carbon gain and biomass accumulation under differing N fertilization were associated primarily with resource allocation associated with canopy leaf area development rather than leaf morphological or physiological properties. The results provide new insights with respect to the multidimensional coordinated structural and physiological adjustments governing LUE over the course of rice crop development. [ABSTRACT FROM AUTHOR]

Maize is one of the most important crops cultivated on the global scale. Accurate estimation of maize Gross Primary Production (GPP) can provide valuable information for regional and global carbon budget studies. From site level to regional/global scales, GPP estimation depends on remote sensing or eddy covariance flux data. In this research, the 8-day composite GPP of maize was estimated by Moderate Resolution Imaging Spectroradiometer (MODIS) and flux tower data at eight study sites using a Regional Production Efficiency Model (REG-PEM). The performance of the model was assessed by analyzing the linearly regression of GPP estimated from the REG-PEM model (GPPEST) with the GPP predicted from the eddy covariance data (GPPEC). The coefficient of determination, root mean squared error and mean absolute error of the regression model were calculated. The uncertainties of the model are also discussed in this research. The seasonal dynamics (phases and magnitudes) of the GPPEST reasonably agreed with those of GPPEC, indicating the potential of the satellite-driven REG-PEM model for up-scaling the GPP in maize croplands. Furthermore, the maize GPP estimated by this model is more accurate than the MODIS GPP products (MOD17A2). In particular, MOD17A2 significantly underestimated the GPP of maize croplands. The uncertainties in the REG-PEM model are mostly contributed by the maximum light use efficiency and the fraction of photosynthetically active radiation. [ABSTRACT FROM AUTHOR]

The high energy consumption of a plant factory is the biggest issue in its rapid expansion, especially for lighting electricity, which has been solved to a large extent by light-emitting diodes (LED). However, the remarkable potential for further energy savings remains to be further investigated. In this study, an optical system applied just below the LED was designed. The effects of the system on the growth and photosynthesis of butterhead lettuce (Lactuca sativa var. capitata) were examined, and the performance of the optical improvement in energy savings was evaluated by comparison with the traditional LED illumination mode. The irradiation patterns used were LED with zoom lenses (Z-LED) and conventional non-lenses LED (C-LED). The seedlings in both treatments were exposed to the same light environment over the entire growth period. The improvement saved over half of the light source electricity, while prominently lowering the temperature. Influenced by this, the rate of photosynthesis sharply decreased, causing reductions in plant yield and nitrate content, while having no negative effects on morphological parameters and photosynthetic pigment contents. Nevertheless, the much higher light use efficiency of Z-LEDs makes this system a better approach to illumination in a plant factory with artificial lighting. [ABSTRACT FROM AUTHOR]

Understanding plant photosynthesis, or Gross Primary Production (GPP), is a crucial aspect of quantifying the terrestrial carbon cycle. Remote sensing approaches, in particular multi-angular spectroscopy, have proven successful for studying relationships between canopy-reflectance and plant-physiology processes, thus providing a mechanism to scale up. However, many different instrumentation designs exist and few cross-comparisons have been undertaken. This paper discusses the design evolution of the Automated Multiangular SPectro-radiometer for Estimation of Canopy reflectance (AMSPEC) series of instruments. Specifically, we assess the performance of the PP-Systems Unispec-DC and Ocean Optics JAZ-COMBO spectro-radiometers installed on an updated, tower-based AMSPEC-III system. We demonstrate the interoperability of these spectro-radiometers, and the results obtained suggest that JAZ-COMBO can successfully be used to substitute more expensive measurement units for detecting and investigating photosynthesis and canopy spectra. We demonstrate close correlations between JAZ-COMBO and Unispec-DC measured canopy radiance (0.75 ≤ R² ≤ 0.85) and solar irradiance (0.95 ≤ R² ≤ 0.96) over a three month time span. We also demonstrate close agreement between the bi-directional distribution functions obtained from each instrument. We conclude that cost effective alternatives may allow a network of AMSPEC-III systems to simultaneously monitor various vegetation types in different ecosystems. This will allow to scale and improve our understanding of the interactions between vegetation physiology and spectral characteristics, calibrate broad-scale observations to stand-level measurements, and ultimately lead to improved understanding of changing vegetation spectral features from satellite. [ABSTRACT FROM AUTHOR]

Although quantifying the massive exchange of carbon that takes place over the Amazon Basin remains a challenge, progress is being made as the remote sensing community moves from using traditional, reflectance-based vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), to the more functional Photochemical Reflectance Index (PRI). This new index, together with satellite-derived estimates of canopy light interception and Sun-Induced Fluorescence (SIF), provide improved estimates of Gross Primary Production (GPP). This paper traces the development of these new approaches, compares the results of their analyses from multiple years of data acquired across the Amazon Basin and suggests further improvements in instrument design, data acquisition and processing. We demonstrated that our estimates of PRI are in generally good agreement with eddy-flux tower measurements of photosynthetic light use efficiency (ε) at four sites in the Amazon Basin: r2 values ranged from 0.37 to 0.51 for northern flux sites and to 0.78 for southern flux sites. This is a significant advance over previous approaches seeking to establish a link between global-scale photosynthetic activity and remotely-sensed data. When combined with measurements of Sun-Induced Fluorescence (SIF), PRI provides realistic estimates of seasonal variation in photosynthesis over the Amazon that relate well to the wet and dry seasons. We anticipate that our findings will steer the development of improved approaches to estimate photosynthetic activity over the tropics.

In this study, the evidence of a relationship between the physiological state and leaf optical properties led us to investigate the behaviour of two species – Betula pendula Roth and Carpinus betulus L. – in order to determine if the vegetation is affected by the heavy metal load of the soil from a former mining area, Rosia Montana, Romania (46°18′47″N, 23°10′15″E). Two non-destructive techniques (leaf transmittance and reflectance) were compared to assess the physiological state of the plants, and 27 vegetation indices for estimating foliar pigment content were tested. For chlorophyll assessment, the reflectance ratios R NIR / R 550 and R NIR / R 700 were the most reliable for an accurate estimation of the pigment content of the leaves. The light use efficiency (LUE) indices were within normal values, except the Red Green Ratio, indicating that the overall reactions of photosynthesis are not impaired by the specific conditions of the habitat. Differences in leaf optical properties are minimal between the two studied species and the values of the vegetation indices are showing similar trends. Both techniques performed consistently well and yielded accurate estimations of pigment content, supporting their interoperability. [ABSTRACT FROM AUTHOR]

The Photochemical Reflectance Index (PRI) of green leaves is an indicator of photosynthetic downregulation: when the photosynthetic apparatus is close to the saturation limit, PRI becomes dependent on light conditions. Therefore, by measuring the PRI of leaves under different local irradiance conditions, it should be possible to determine the saturation level of the leaves and obtain information on the light use efficiency (LUE) of a vegetation canopy. The dependence of PRI on the ratio of sunlit to shaded foliage (quantified by the canopy shadow fraction) in the field of view of an instrument has been used to remotely measure canopy LUE on clear days. However, besides photosynthetic downregulation, the dependence of canopy PRI on shadow fraction is affected by the blue sky radiation caused by scattering in the atmosphere. To quantify this effect on remotely sensed PRI, we present the underlying definitions relating leaf and canopy PRI and perform the required calculations for typical midsummer conditions in Central Finland. We demonstrate that the effect of blue sky radiation on the variation of PRI with canopy shadow fraction is similar in shape and magnitude to that of LUE variations reported in literature. [ABSTRACT FROM AUTHOR]

Climate and physiological controls of vegetation gross primary production (GPP) vary in space and time. In many ecosystems, GPP is primary limited by absorbed photosynthetically-active radiation; in others by canopy conductance. These controls further vary in importance over daily to seasonal time scales. We propose a simple but effective conceptual model that estimates GPP as the lesser of a conductance-limited ( F c ) and radiation-limited ( Fr ) assimilation rate. F c is estimated from canopy conductance while Fr is estimated using a light use efficiency model. Both can be related to vegetation properties observed by optical remote sensing. The model has only two fitting parameters: maximum light use efficiency, and the minimum achieved ratio of internal to external CO 2 concentration. The two parameters were estimated using data from 16 eddy covariance flux towers for six major biomes including both energy- and water-limited ecosystems. Evaluation of model estimates with flux tower-derived GPP compared favourably to that of more complex models, for fluxes averaged; per day (r 2 = 0.72, root mean square error, RMSE = 2.48 μmol C m 2 s − 1 , relative percentage error, RPE = − 11%), over 8-day periods (r 2 = 0.78 RMSE = 2.09 μmol C m 2 s − 1 ,RPE = − 10%), over months (r 2 = 0.79, RMSE = 1.93 μmol C m 2 s − 1 , RPE = − 9%) and over years (r 2 = 0.54, RMSE = 1.62 μmol C m 2 s − 1 , RPE = − 9%). Using the model we estimated global GPP of 107 Pg C y − 1 for 2000–2011. This value is within the range reported by other GPP models and the spatial and inter-annual patterns compared favourably. The main advantages of the proposed model are its simplicity, avoiding the use of uncertain biome- or land-cover class mapping, and inclusion of explicit coupling between GPP and plant transpiration. [ABSTRACT FROM AUTHOR]