INTRODUCTION Reliable estimation of gross primary production (GPP) from landscape to global scales is pivotal to a wide range of ecological research areas, such as carbon-climate feedbacks, and agricultural applications, such as crop yield and drought monitoring. However, measuring GPP at these scales remains a major challenge. Solar-induced chlorophyll fluorescence (SIF) is a signal emitted directly from the core of photosynthetic machinery. SIF integrates complex plant physiological functions in vivo to reflect photosynthetic dynamics in real time. The advent of satellite SIF observation promises a new era in global photosynthesis research. The Orbiting Carbon Observatory-2 (OCO-2) SIF product is a serendipitous but critically complementary by-product of OCO-2’s primary mission target—atmospheric column CO 2 ( X CO 2 ). OCO-2 SIF removes some important roadblocks that prevent wide and in-depth applications of satellite SIF data sets and offers new opportunities for studying the SIF-GPP relationship and vegetation functional gradients at different spatiotemporal scales. RATIONALE Compared with earlier satellite missions with SIF capability, the OCO-2 SIF product has substantially improved spatial resolution, data acquisition, and retrieval precision. These improvements allow satellite SIF data to be validated, for the first time, directly against ground and airborne measurements and also used to investigate the SIF-GPP relationship and terrestrial ecosystem functional dynamics with considerably better spatiotemporal credibility. RESULTS Coordinated airborne measurements of SIF with the Chlorophyll Fluorescence Imaging Spectrometer (CFIS) were used to validate OCO-2 retrievals. The validation shows close agreement between OCO-2 and CFIS SIF, with a regression slope of 1.02 and R 2 of 0.71. Landscape gradients in SIF emission, corresponding to differences in vegetation types, were clearly delineated by OCO-2, a capability that was lacking in previous satellite missions. The SIF-GPP relationships at eddy covariance flux sites in the vicinity of OCO-2 orbital tracks were found to be more consistent across biomes than previously suggested. Finally, empirical orthogonal function (EOF) analyses on OCO-2 SIF and available GPP products show highly consistent spatiotemporal correspondence in their leading EOF modes across the globe, suggesting that SIF and GPP are governed by similar dynamics and controlled by similar environmental and biological conditions. CONCLUSION OCO-2 represents a major advance in satellite SIF remote sensing. Our analyses suggest that SIF is a powerful proxy for GPP at multiple spatiotemporal scales and that high-quality satellite SIF is of central importance to studying terrestrial ecosystems and the carbon cycle. Although the possibility of a universal SIF-GPP relationship across different biome types cannot be dismissed, in-depth process-based studies are needed to unravel the true nature of covariations between SIF and GPP. Of critical importance in such efforts are the potential coordinated dynamics between the light-use efficiencies of CO 2 assimilation and fluorescence emission in response to changes in climate and vegetation characteristics. Eventual synergistic uses of SIF with atmospheric CO 2 enabled by OCO-2 will lead to more reliable estimates of terrestrial carbon sources and sinks—when, where, why, and how carbon is exchanged between land and atmosphere—as well as a deeper understanding of carbon-climate feedbacks. The marked ecological gradients depicted by OCO-2’s high-resolution SIF measurements along a transect of temperate deciduous forests, crops, and urban area from Indiana to suburban Chicago, Illinois.

Summary Recent progress in observing sun‐induced Chl fluorescence (SIF) provides an unprecedented opportunity to advance photosynthesis research in natural environments. However, we still lack an analytical framework to guide SIF studies and integration with the well‐developed active fluorescence approaches. Here, we derive a set of coupled fundamental equations to describe the dynamics of SIF and its relationship with C3 and C4 photosynthesis. These equations show that, although SIF is dynamically as complex as photosynthesis, the measured SIF simplifies photosynthetic modeling from the perspective of light reactions by integrating over the dynamic complexities of photosynthesis. Specifically, the measured SIF contains direct information about the actual electron transport from photosystem II to photosystem I, giving a quantifiable link between light and dark reactions. With much‐reduced requirements on inputs and parameters, the light‐reactions‐centric, SIF‐based biophysical model complements the traditional, dark‐reactions‐centric biochemical model of photosynthesis. The SIF–photosynthesis relationship, however, is nonlinear. This is because photosynthesis saturates at high light whereas SIF has a stronger tendency to keep increasing, as fluorescence quantum yield has a relatively muted sensitivity to light levels. Successful applications of the SIF‐based model of photosynthesis will depend on a predictive understanding of several previously underexplored physiological and biophysical processes. Advances can be facilitated by coordinated efforts in plant physiology, remote sensing, and eddy covariance flux observations.

A reduced protein diet (RPD) is known to increase the level of intramuscular lipid in pig meat with a smaller effect on the amount of subcutaneous adipose tissue. This might be due to tissue-specific activation of the expression of lipogenic enzymes by the RPD. The present study investigated the effect of a RPD, containing palm kernel oil, soyabean oil or palm oil on the activity and expression of one of the major lipogenic enzymes, stearoyl-CoA desaturase (SCD) and on the level of total lipids and the fatty acid composition of muscle and subcutaneous adipose tissue in pigs. The RPD significantly increased SCD protein expression and activity in muscle but not in subcutaneous adipose tissue. The level of MUFA and total fatty acids in muscle was also elevated when the RPD was fed, with only small changes in subcutaneous adipose tissue. A positive significant correlation between SCD protein expression and total fatty acids in muscle was found. The results suggest that an increase in intramuscular but not subcutaneous adipose tissue fatty acids under the influence of a RPD is related to tissue-specific activation of SCD expression. It is suggested that the SCD isoform spectra in pig subcutaneous adipose tissue and muscle might be different.

N 2 O is an important greenhouse gas and the primary stratospheric ozone depleting substance. Its deleterious effects on the environment have prompted appeals to regulate emissions from agriculture, which represents the primary anthropogenic source in the global N 2 O budget. Successful implementation of mitigation strategies requires robust bottom-up inventories that are based on emission factors (EFs), simulation models, or a combination of the two. Top-down emission estimates, based on tall-tower and aircraft observations, indicate that bottom-up inventories severely underestimate regional and continental scale N 2 O emissions, implying that EFs may be biased low. Here, we measured N 2 O emissions from streams within the US Corn Belt using a chamber-based approach and analyzed the data as a function of Strahler stream order (S). N 2 O fluxes from headwater streams often exceeded 29 nmol N 2 O-N m −2 ·s −1 and decreased exponentially as a function of S. This relation was used to scale up riverine emissions and to assess the differences between bottom-up and top-down emission inventories at the local to regional scale. We found that the Intergovernmental Panel on Climate Change (IPCC) indirect EF for rivers (EF 5r ) is underestimated up to ninefold in southern Minnesota, which translates to a total tier 1 agricultural underestimation of N 2 O emissions by 40%. We show that accounting for zero-order streams as potential N 2 O hotspots can more than double the agricultural budget. Applying the same analysis to the US Corn Belt demonstrates that the IPCC EF 5r underestimation explains the large differences observed between top-down and bottom-up emission estimates.aquatic nitrous oxide fluxes | IPCC emission factors | river emission hotspots | regional emission upscaling N 2 O is projected to remain the dominant stratospheric ozonedepleting substance of the 21st century (1) and is a powerful greenhouse gas (GHG) that currently accounts for about 6% of the net radiative forcing associated with long-lived anthropogenic GHGs (2). The detrimental environmental impacts of N 2 O have stimulated appeals to regulate emissions from agricultural lands (1, 3), which account for nearly 80% of the global anthropogenic N 2 O budget (4, 5). The successful regulation and mitigation of N 2 O emissions requires a sound understanding of the direct and indirect emission processes and reduced uncertainty regarding the emission factors (EFs) (6).The Intergovernmental Panel on Climate Change (IPCC) tier 1 approach uses EFs to provide first-order approximations of annual N 2 O emissions based on mechanistic and empirical information that have been constrained by field studies. These EFs are widely used in bottom-up inventories such as the Emission Database for Global Atmospheric Research (EDGAR) (7) and the Global Emissions Initiative (GEIA) (8). These inventories are essential tools for tracking country specific emission trends, assessing thresholds for international treaties, and evaluating the impacts of mitigation policies. Recent i...

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