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.

[1] Vegetation acclimation to changing climate, in particular elevated atmospheric concentrations of carbon dioxide (CO 2 ), has been observed to include modifications to the biochemical and ecophysiological functioning of leaves and the structural components of the canopy. These responses have the potential to significantly modify plant carbon uptake and surface energy partitioning, and have been attributed with large-scale changes in surface hydrology over recent decades. While the aggregated effects of vegetation acclimation can be pronounced, they often result from subtle changes in canopy properties that require the resolution of physical, biochemical and ecophysiological processes through the canopy for accurate estimation. In this paper, the first of two, a multilayer canopy-soil-root system model developed to capture the emergent vegetation responses to environmental change is presented. The model incorporates both C3 and C4 photosynthetic pathways, and resolves the vertical radiation, thermal, and environmental regimes within the canopy. The tight coupling between leaf ecophysiological functioning and energy balance determines vegetation responses to climate states and perturbations, which are modulated by soil moisture states through the depth of the root system. The model is validated for three growing seasons each for soybean (C3) and maize (C4) using eddycovariance fluxes of CO 2 , latent, and sensible heat collected at the Bondville (Illinois) Ameriflux tower site. The data set provides an opportunity to examine the role of important environmental drivers and model skill in capturing variability in canopy-atmosphere exchange. Vertical variation in radiative states and scalar fluxes over a mean diurnal cycle are examined to understand the role of canopy structure on the patterns of absorbed radiation and scalar flux magnitudes and the consequent differences in sunlit and shaded source/sink locations through the canopies. An analysis is made of the impact of soil moisture stress on carbon uptake and energy flux partitioning at the canopy-scale and resolved through the canopy, providing insight into the roles of canopy structure and metabolic pathway on the response of each crop to moisture deficits. Model calculations indicate increases in water use efficiency (WUE) with increasing moisture stress, with average maize WUE increases of 45% at the highest levels of plant stress examined here, relative to 20% increases for soybean.Citation: Drewry, D. T., P. Kumar, S. Long, C. Bernacchi, X.-Z. Liang, and M. Sivapalan (2010), Ecohydrological responses of dense canopies to environmental variability: 1. Interplay between vertical structure and photosynthetic pathway,

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Recent studies have utilized coarse spatial and temporal resolution remotely sensed solar‐induced fluorescence (SIF) for modeling terrestrial gross primary productivity (GPP) at regional scales. Although these studies have demonstrated the potential of SIF, there have been concerns about the ecophysiological basis of the relationship between SIF and GPP in different environmental conditions. Launched in 2014, the Orbiting Carbon Observatory‐2 (OCO‐2) has enabled fine‐scale (1.3 by 2.5 km) retrievals of SIF that are comparable with measurements recorded at eddy covariance towers. In this study, we examine the effect of environmental conditions on the relationship of OCO‐2 SIF with tower GPP over the course of a growing season at a well‐characterized natural grassland site. Combining OCO‐2 SIF and eddy covariance tower data with a canopy radiative transfer and an ecosystem model, we also assess the potential of OCO‐2 SIF to constrain the estimates of Vcmax, one of the most important parameters in ecosystem models. Based on the results, we suggest that although environmental conditions play a role in determining the nature of relationship between SIF and GPP, overall, the linear relationship is more robust at ecosystem scale than the theory based on leaf‐level processes might suggest. Our study also shows that the ability of SIF to constrain Vcmax is weak at the selected site.

[1] Estimating transpiration and water flow in trees remains a major challenge for quantifying water exchange between the biosphere and the atmosphere. We develop a finite element tree crown hydrodynamics (FETCH) model that uses porous media equations for water flow in an explicit three-dimensional branching fractal tree-crown system. It also incorporates a first-order canopy-air turbulence closure model to generate the external forcing of the system. We use FETCH to conduct sensitivity analysis of transpirational dynamics to changes in canopy structure via two scaling parameters for branch thickness and conductance. We compare our results with the equivalent parameters of the commonly used resistor and resistor-capacitor representations of tree hydraulics. We show that the apparent temporal and vertical variability in these parameters strongly depends on structure. We suggest that following empirical calibration and validation, FETCH could be used as a platform for calibrating the ''scaling laws'' between tree structure and hydrodynamics and for surface parameterization in meteorological and hydrological models.

Abstract. Terrestrial biosphere models typically abstract the immense diversity of vegetation forms and functioning into a relatively small set of predefined semi-empirical plant functional types (PFTs). There is growing evidence, however, from the field ecology community as well as from modelling studies that current PFT schemes may not adequately represent the observed variations in plant functional traits and their effect on ecosystem functioning. In this paper, we introduce the Jena Diversity-Dynamic Global Vegetation Model (JeDi-DGVM) as a new approach to terrestrial biosphere modelling with a richer representation of functional diversity than traditional modelling approaches based on a small number of fixed PFTs. JeDi-DGVM simulates the performance of a large number of randomly generated plant growth strategies, each defined by a set of 15 trait parameters which characterize various aspects of plant functioning including carbon allocation, ecophysiology and phenology. Each trait parameter is involved in one or more functional trade-offs. These trade-offs ultimately determine whether a strategy is able to survive under the climatic conditions in a given model grid cell and its performance relative to the other strategies. The biogeochemical fluxes and land surface properties of the individual strategies are aggregated to the grid-cell scale using a mass-based weighting scheme. We evaluate the simulated global biogeochemical patterns against a variety of field and satellite-based observations following a protocol established by the Carbon-Land Model Intercomparison Project. The land surface fluxes and vegetation structural properties are reasonably well simulated by JeDi-DGVM, and compare favourably with other state-of-the-art global vegetation models. We also evaluate the simulated patterns of functional diversity and the sensitivity of the JeDi-DGVM modelling approach to the number of sampled strategies. Altogether, the results demonstrate the parsimonious and flexible nature of a functional trade-off approach to global vegetation modelling, i.e. it can provide more types of testable outputs than standard PFT-based approaches and with fewer inputs. The approach implemented here in JeDi-DGVM sets the foundation for future applications that will explore the impacts of explicitly resolving diverse plant communities, allowing for a more flexible temporal and spatial representation of the structure and function of the terrestrial biosphere.

To meet emerging bioenergy demands, significant areas of the large-scale agricultural landscape of the Midwestern United States could be converted to second generation bioenergy crops such as miscanthus and switchgrass. The high biomass productivity of bioenergy crops in a longer growing season linked tightly to water use highlight the potential for significant impact on the hydrologic cycle in the region. This issue is further exacerbated by the uncertainty in the response of the vegetation under elevated CO 2 and temperature. We use a mechanistic multilayer canopy-root-soil model to (i) capture the eco-physiological acclimations of bioenergy crops under climate change, and (ii) predict how hydrologic fluxes are likely to be altered from their current magnitudes. Observed data and Monte Carlo simulations of weather for recent past and future scenarios are used to characterize the variability range of the predictions. Under present weather conditions, miscanthus and switchgrass utilized more water than maize for total seasonal evapotranspiration by approximately 58% and 36%, respectively. Projected higher concentrations of atmospheric CO 2 (550 ppm) is likely to decrease water used for evapotranspiration of miscanthus, switchgrass, and maize by 12%, 10%, and 11%, respectively. However, when climate change with projected increases in air temperature and reduced summer rainfall are also considered, there is a net increase in evapotranspiration for all crops, leading to significant reduction in soil-moisture storage and specific surface runoff. These results highlight the critical role of the warming climate in potentially altering the water cycle in the region under extensive conversion of existing maize cropping to support bioenergy demand.R apidly growing energy demand, worldwide depletion of fossil fuels, and global warming are raising an interest in expanding clean and renewable bioenergy production. In the United States, the current starch-based bioethanol production only contributes a small portion of total energy needs (1, 2), but it is raising new challenges related to environmental issues (3-6) and a competition with food production on available fertile land (7). Bioenergy extracted from lignocellulosic feedstocks offers the possible use of marginal land (8), along with many energy, environmental, and economic advantages over current biofuel sources (9), and is being considered as a promising alternative to sustainably meet the US Department of Energy target for bioenenergy and biobased products in the future (10). At present, Miscanthus × giganteus (miscanthus) and Panicum virgatum (switchgrass) are considered as the two perennial grasses with the highest potential for lignocellulosic bioenergy production in the Midwest with high biofuels yield per unit land area, reduced requirement of nutrient inputs (11, 12), and low net CO 2 emissions (13-16). However, if large portions of the landscape in the Midwestern United States are converted to these crops for meeting bioenergy demands, for example, by using l...

Here we demonstrate a novel method to physically integrate radiometric surface temperature (T R ) into the Penman-Monteith (PM) formulation for estimating the terrestrial sensible and latent heat fluxes (H and kE) in the framework of a modified Surface Temperature Initiated Closure (STIC). It combines T R data with standard energy balance closure models for deriving a hybrid scheme that does not require parameterization of the surface (or stomatal) and aerodynamic conductances (g S and g B ). STIC is formed by the simultaneous solution of four state equations and it uses T R as an additional data source for retrieving the ''near surface'' moisture availability (M) and the Priestley-Taylor coefficient (a). The performance of STIC is tested using high-temporal resolution T R observations collected from different international surface energy flux experiments in conjunction with corresponding net radiation (R N ), ground heat flux (G), air temperature (T A ), and relative humidity (R H ) measurements. A comparison of the STIC outputs with the eddy covariance measurements of kE and H revealed RMSDs of 7-16% and 40-74% in half-hourly kE and H estimates. These statistics were 5-13% and 10-44% in daily kE and H. The errors and uncertainties in both surface fluxes are comparable to the models that typically use land surface parameterizations for determining the unobserved components (g S and g B ) of the surface energy balance models. However, the scheme is simpler, has the capabilities for generating spatially explicit surface energy fluxes and independent of submodels for boundary layer developments.