The distribution of nitrogen isotopes in the biosphere has the potential to offer insights into the past, present and future of the nitrogen cycle, but it is challenging to unravel the processes controlling patterns of mixing and fractionation. We present a mathematical model describing a previously overlooked process: nitrogen isotope fractionation during leaf-atmosphere NH3(g) exchange. The model predicts that when leaf-atmosphere exchange of NH3(g) occurs in a closed system, the atmospheric reservoir of NH3(g) equilibrates at a concentration equal to the ammonia compensation point and an isotopic composition 8.1 parts per thousand lighter than nitrogen in protein. In an open system, when atmospheric concentrations of NH3(g) fall below or rise above the compensation point, protein can be isotopically enriched by net efflux of NH3(g) or depleted by net uptake. Comparison of model output with existing measurements in the literature suggests that this process contributes to variation in the isotopic composition of nitrogen in plants as well as NH3(g) in the atmosphere, and should be considered in future analyses of nitrogen isotope circulation. The matrix-based modelling approach that is introduced may be useful for quantifying isotope dynamics in other complex systems that can be described by first-order kinetics.

Widespread drought-induced mortality of woody plants has recently occurred worldwide, is likely to be exacerbated by future climate change and holds large ecological consequences. Yet despite decades of research on plant water relations, the pathways through which drought causes plant mortality are poorly understood. Recent work on the physiology of tree mortality has begun to reveal how physiological dysfunction induced by water stress leads to plant death; however, we are still far from being able to predict tree mortality using easily observed or modeled meteorological variables. In this review, we contend that, in order to fully understand when and where plants will exceed mortality thresholds when drought occurs, we must understand the entire path by which precipitation deficit is translated into physiological dysfunction and lasting physiological damage. In temperate ecosystems with seasonal climate patterns, precipitation characteristics such as seasonality, timing, form (snow versus rain) and intensity interact with edaphic characteristics to determine when and how much water is actually available to plants as soil moisture. Plant and community characteristics then mediate how quickly water is used and seasonally varying plant physiology determines whether the resulting soil moisture deficit is physiologically damaging. Recent research suggests that drought seasonality and timing matter for how an ecosystem experiences drought. But, mortality studies that bridge the gaps between climatology, hydrology, plant ecology and plant physiology are rare. Drawing upon a broad hydrological and ecological perspective, we highlight key and underappreciated processes that may mediate drought-induced tree mortality and propose steps to better include these components in current research.

Photosynthesis is the process by which plants harvest sunlight to produce sugars from carbon dioxide and water. It is the primary source of energy for all life on Earth; hence it is important to understand how this process responds to climate change and human impact. However, model-based estimates of gross primary production (GPP, output from photosynthesis) are highly uncertain, in particular over heavily managed agricultural areas. Recent advances in spectroscopy enable the space-based monitoring of sun-induced chlorophyll fluorescence (SIF) from terrestrial plants. Here we demonstrate that spaceborne SIF retrievals provide a direct measure of the GPP of cropland and grassland ecosystems. Such a strong link with crop photosynthesis is not evident for traditional remotely sensed vegetation indices, nor for more complex carbon cycle models. We use SIF observations to provide a global perspective on agricultural productivity. Our SIF-based crop GPP estimates are 50-75% higher than results from state-of-the-art carbon cycle models over, for example, the US Corn Belt and the Indo-Gangetic Plain, implying that current models severely underestimate the role of management. Our results indicate that SIF data can help us improve our global models for more accurate projections of agricultural productivity and climate impact on crop yields. Extension of our approach to other ecosystems, along with increased observational capabilities for SIF in the near future, holds the prospect of reducing uncertainties in the modeling of the current and future carbon cycle.

Understanding the pathways through which drought stress kills woody vegetation can improve projections of the impacts of climate change on ecosystems and carbon-cycle feedbacks. Continuous in situ measurements of whole trees during drought and as trees die hold promise to illuminate physiological pathways but are relatively rare. We monitored leaf characteristics, water use efficiency, water potentials, branch hydraulic conductivity, soil moisture, meteorological variables, and sap flux on mature healthy and sudden aspen decline-affected (SAD) trembling aspen (Populus tremuloides) ramets over two growing seasons, including a severe summer drought. We calculated daily estimates of whole-ramet hydraulic conductance and modeled whole-ramet assimilation. Healthy ramets experienced rapid declines of whole-ramet conductance during the severe drought, providing an analog for what likely occurred during the previous drought that induced SAD. Even in wetter periods, SAD-affected ramets exhibited fivefold lower whole-ramet hydraulic conductance and sevenfold lower assimilation than counterpart healthy ramets, mediated by changes in leaf area, water use efficiency, and embolism. Extant differences between healthy and SAD ramets reveal that ongoing multi-year forest die-off is primarily driven by loss of whole-ramet hydraulic capability, which in turn limits assimilation capacity. Branch-level measurements largely captured whole-plant hydraulic limitations during drought and mortality, but whole-plant measurements revealed a potential role of other losses in the hydraulic continuum. Our results highlight the importance of a whole-tree perspective in assessing physiological pathways to tree mortality and indicate that the effects of mortality on these forests' assimilation and productivity are larger than expected based on canopy leaf area differences.

The Orbiting Carbon Observatory-2 (OCO-2), scheduled to launch in July 2014, is a NASA mission designed to measure atmospheric CO2. Its main purpose is to allow inversions of net flux estimates of CO2 on regional to continental scales using the total column CO2 retrieved using high-resolution spectra in the 0.76, 1.6, and 2.0 mu m ranges. Recently, it was shown that solar-induced chlorophyll fluorescence (SIP), a proxy for gross primary production (GPP, carbon uptake through photosynthesis), can be accurately retrieved from space using high spectral resolution radiances in the 750 nm range from the Japanese GOSAT and European GOME-2 instruments. Here, we use real OCO-2 thermal vacuum test data as well as a full repeat cycle (16 days) of simulated OCO-2 spectra under realistic conditions to evaluate the potential of OCO-2 for retrievals of chlorophyll fluorescence and also its dependence on clouds and aerosols. We find that the single-measurement precision is 03-0.5 Wm(-2)sr(-1) mu m(-1) (15-25% of typical peak values), better than current measurements from space but still difficult to interpret on a single-sounding basis. The most significant advancement will come from smaller ground-pixel sizes and increased measurement frequency, with a 100-fold increase compared to GOSAT (and about 8 times higher than GOME-2). This will largely decrease the need for coarse spatial and temporal averaging in data analysis and pave the way to accurate local studies. We also find that the lack of full global mapping from the OCO-2 only incurs small representativeness errors on regional averages. Eventually, the combination of net ecosystem exchange (NEE) derived from CO2 source/sink inversions and SIF as proxy for GPP from the same satellite will provide a more process-based understanding of the global carbon cycle. (C) 2014 Elsevier Inc. All rights reseved.

Net photosynthesis is the largest single flux in the global carbon cycle, but controls over its variability are poorly understood because there is no direct way of measuring it at the ecosystem scale. We report observations of ecosystem carbonyl sulfide (COS) and CO2 fluxes that resolve key gaps in an emerging framework for using concurrent COS and CO2 measurements to quantify terrestrial gross primary productivity. At a wheat field in Oklahoma we found that in the peak growing season the flux-weighted leaf relative uptake of COS and CO2 during photosynthesis was 1.3, at the lower end of values from laboratory studies, and varied systematically with light. Due to nocturnal stomatal conductance, COS uptake by vegetation continued at night, contributing a large fraction (29%) of daily net ecosystem COS fluxes. In comparison, the contribution of soil fluxes was small (1-6%) during the peak growing season. Upland soils are usually considered sinks of COS. In contrast, the well-aerated soil at the site switched from COS uptake to emissions at a soil temperature of around 15 degrees C. We observed COS production from the roots of wheat and other species and COS uptake by root-free soil up to a soil temperature of around 25 degrees C. Our dataset demonstrates that vegetation uptake is the dominant ecosystem COS flux in the peak growing season, providing support of COS as an independent tracer of terrestrial photosynthesis. However, the observation that ecosystems may become a COS source at high temperature needs to be considered in global modeling studies.

Genetic and cell biological mechanisms that regulate stomatal development are necessary to generate an appropriate number of stomata and enforce a minimum spacing of one epidermal cell between stomata. The ability to manipulate these processes in a model plant system allows us to investigate the physiological importance of stomatal patterning and changes in density, therein testing underlying theories about stomatal biology.

Stomatal conductance (g(s)) is constrained by the size and number of stomata on the plant epidermis, and the potential maximum rate of g(s) can be calculated based on these stomatal traits (Anatomical g(smax)). However, the relationship between Anatomical g(smax) and operational g(s) under atmospheric conditions remains undefined.

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.