Abstract.Various aspects of the biochemistry of photosynthetic carbon assimilation in C3 plants are integrated into a form compatible with studies of gas exchange in leaves. These aspects include the kinetic properties of ribulose bisphosphate carboxylaseoxygenase; the requirements of the photosynthetic carbon reduction and photorespiratory carbon oxidation cycles for reduced pyridine nucleotides; the dependence of electron transport on photon flux and the presence of a temperature dependent upper limit to electron transport. The measurements of gas exchange with which the model outputs may be compared include those of the temperature and partial pressure of CO2(p(CO2) ) dependencies of quantum yield, the variation of compensation point with temperature and partial pressure of O2(p(O2)), the dependence of net CO 2 assimilation rate on p(CO2) and irradiance, and the influence of p(CO2) and irradiance on the temperature dependence of assimilation rate.

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Chlorophyll a fluorescence (ChlF) has been used for decades to study the organization, functioning, and physiology of photosynthesis at the leaf and subcellular levels. ChlF is now measurable from remote sensing platforms. This provides a new optical means to track photosynthesis and gross primary productivity of terrestrial ecosystems. Importantly, the spatiotemporal and methodological context of the new applications is dramatically different compared with most of the available ChlF literature, which raises a number of important considerations. Although we have a good mechanistic understanding of the processes that control the ChlF signal over the short term, the seasonal link between ChlF and photosynthesis remains obscure. Additionally, while the current understanding of in vivo ChlF is based on pulse amplitude-modulated (PAM) measurements, remote sensing applications are based on the measurement of the passive solar-induced chlorophyll fluorescence (SIF), which entails important differences and new challenges that remain to be solved. In this review we introduce and revisit the physical, physiological, and methodological factors that control the leaf-level ChlF signal in the context of the new remote sensing applications. Specifically, we present the basis of photosynthetic acclimation and its optical signals, we introduce the physical and physiological basis of ChlF from the molecular to the leaf level and beyond, and we introduce and compare PAM and SIF methodology. Finally, we evaluate and identify the challenges that still remain to be answered in order to consolidate our mechanistic understanding of the remotely sensed SIF signal.

Atmospheric general circulation models used for climate simulation and weather forecasting require the fluxes of radiation, heat, water vapor, and momentum across the land-atmosphere interface to be specified. These fluxes are calculated by submodels called land surface parameterizations. Over the last 20 years, these parameterizations have evolved from simple, unrealistic schemes into credible representations of the global soil-vegetation-atmosphere transfer system as advances in plant physiological and hydrological research, advances in satellite data interpretation, and the results of largescale field experiments have been exploited. Some modern schemes incorporate biogeochemical and ecological knowledge and, when coupled with advanced climate and ocean models, will be capable of modeling the biological and physical responses of the Earth system to global change, for example, increasing atmospheric carbon dioxide.Until the early 1980s, global atmospheric general circulation models (AGCMs) incorporated very simple land surface parameterizations (LSPs) to estimate the exchanges of energy, heat, and momentum between the land surface and the atmosphere. These have since evolved into a family of schemes that can realistically describe a comprehensive range of land-atmosphere interactions. These advanced schemes will be needed to understand the response of the biosphere and the climate system to global change, for example, increasing atmospheric CO 2 (1-3).Three generations of models have taken us from the early LSPs to where we stand now. The first, developed in the late 1960s and 1970s, was based on simple aerodynamic bulk transfer formulas and often uniform prescriptions of surface parameters (albedo, aerodynamic roughness, and soil moisture availability) over the continents (4). In the early 1980s, a second generation of models explicitly recognized the effects of vegetation in the calculation of the surface energy balance (5, 6). At the same time, global, spatially varying data of land surface properties were assembled from ecological and geographical surveys published in the scientific literature (7). The latest (third generation) models use modern theories relating photosynthesis and plant water relations to provide a consistent description of energy exchange, evapotranspiration, and carbon exchange by plants (8-10). Some are beginning to incorporate treatments of nutrient dynamics and biogeography, so that vegetation systems can move in response to climate shifts. A series of largescale field experiments have been executed to validate the process models and scaling assumptions involved in land-atmosphere schemes (3). These experiments have also accelerated the development of methods for translating satellite data into global surface parameter sets for the models. Theoretical Background and the First-Generation ModelsIt has been understood for nearly 200 years that the continents and the atmosphere exchange energy, water, and carbon with each other. However, it was not until the late 1960s with the construct...

[1] Photosynthesis and respiration impart distinct isotopic signatures to the atmosphere that are used to constrain global carbon source/sink estimates and partition ecosystem fluxes. Increasingly, the ''Keeling plot'' method is being used to determine the carbon isotope composition of ecosystem respiration (d 13 C R ) in order to better understand the processes controlling ecosystem isotope discrimination. In this paper we synthesize emergent patterns in d 13 C R by analyzing 146 Keeling plots constructed at 33 sites across North and South America. In order to interpret results from disparate studies, we discuss the assumptions underlying the Keeling plot method and recommend standardized methods for determining d 13 C R . These include the use of regression calculations that account for error in the x variable, and constraining estimates of d 13 C R to nighttime periods. We then recalculate d 13 C R uniformly for all sites. We found a high degree of temporal and spatial variability in C 3 ecosystems, with individual observations ranging from À19.0 to À32.6%. Mean C 3 ecosystem discrimination was 18.3%. Precipitation was a major driver of both temporal and spatial variability of d 13 C R , suggesting (1) a large influence of recently fixed carbon on ecosystem respiration and (2) a significant effect of previous climatic effects on d 13 C R . These results illustrate the importance of water availability as a key control on atmospheric 13 CO 2 and highlight the potential of d 13 C R as a useful tool for integrating environmental effects on dynamic canopy and ecosystem processes.