Vegetation responses to climate extremes recorded by remotely sensed atmospheric formaldehyde.

Accurate monitoring of vegetation stress is required for better modelling and forecasting of primary production, in a world where heatwaves and droughts are expected to become increasingly prevalent. Variability in formaldehyde (HCHO) concentrations in the troposphere is dominated by local emissions of short-lived biogenic (BVOC) and pyrogenic volatile organic compounds. BVOCs are emitted by plants in a rapid protective response to abiotic stress, mediated by the energetic status of leaves (the excess of reducing power when photosynthetic light and dark reactions are decoupled, as occurs when stomata close in response to water stress). Emissions also increase exponentially with leaf temperature. New analytical methods for the detection of spatiotemporally contiguous extremes in remote-sensing data are applied here to satellite-derived atmospheric HCHO columns. BVOC emissions are shown to play a central role in the formation of the largest positive HCHO anomalies. Although vegetation stress can be captured by various remotely sensed quantities, spaceborne HCHO emerges as the most consistent recorder of vegetation responses to the largest climate extremes, especially in forested regions.

Eco-evolutionary optimality as a means to improve vegetation and land-surface models.

Global vegetation and land-surface models embody interdisciplinary scientific understanding of the behaviour of plants and ecosystems, and are indispensable to project the impacts of environmental change on vegetation and the interactions between vegetation and climate. However, systematic errors and persistently large differences among carbon and water cycle projections by different models highlight the limitations of current process formulations. In this review, focusing on core plant functions in the terrestrial carbon and water cycles, we show how unifying hypotheses derived from eco-evolutionary optimality (EEO) principles can provide novel, parameter-sparse representations of plant and vegetation processes. We present case studies that demonstrate how EEO generates parsimonious representations of core, leaf-level processes that are individually testable and supported by evidence. EEO approaches to photosynthesis and primary production, dark respiration and stomatal behaviour are ripe for implementation in global models. EEO approaches to other important traits, including the leaf economics spectrum and applications of EEO at the community level are active research areas. Independently tested modules emerging from EEO studies could profitably be integrated into modelling frameworks that account for the multiple time scales on which plants and plant communities adjust to environmental change.

Changes in climate extremes, fresh water availability and vulnerability to food insecurity projected at 1.5°C and 2°C global warming with a higher-resolution global climate model.

We projected changes in weather extremes, hydrological impacts and vulnerability to food insecurity at global warming of 1.5°C and 2°C relative to pre-industrial, using a new global atmospheric general circulation model HadGEM3A-GA3.0 driven by patterns of sea-surface temperatures and sea ice from selected members of the 5th Coupled Model Intercomparison Project (CMIP5) ensemble, forced with the RCP8.5 concentration scenario. To provide more detailed representations of climate processes and impacts, the spatial resolution was N216 (approx. 60 km grid length in mid-latitudes), a higher resolution than the CMIP5 models. We used a set of impacts-relevant indices and a global land surface model to examine the projected changes in weather extremes and their implications for freshwater availability and vulnerability to food insecurity. Uncertainties in regional climate responses are assessed, examining ranges of outcomes in impacts to inform risk assessments. Despite some degree of inconsistency between components of the study due to the need to correct for systematic biases in some aspects, the outcomes from different ensemble members could be compared for several different indicators. The projections for weather extremes indices and biophysical impacts quantities support expectations that the magnitude of change is generally larger for 2°C global warming than 1.5°C. Hot extremes become even hotter, with increases being more intense than seen in CMIP5 projections. Precipitation-related extremes show more geographical variation with some increases and some decreases in both heavy precipitation and drought. There are substantial regional uncertainties in hydrological impacts at local scales due to different climate models producing different outcomes. Nevertheless, hydrological impacts generally point towards wetter conditions on average, with increased mean river flows, longer heavy rainfall events, particularly in South and East Asia with the most extreme projections suggesting more than a doubling of flows in the Ganges at 2°C global warming. Some areas are projected to experience shorter meteorological drought events and less severe low flows, although longer droughts and/or decreases in low flows are projected in many other areas, particularly southern Africa and South America. Flows in the Amazon are projected to decline by up to 25%. Increases in either heavy rainfall or drought events imply increased vulnerability to food insecurity, but if global warming is limited to 1.5°C, this vulnerability is projected to remain smaller than at 2°C global warming in approximately 76% of developing countries. At 2°C, four countries are projected to reach unprecedented levels of vulnerability to food insecurity.This article is part of the theme issue 'The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'.

A model of plant isoprene emission based on available reducing power captures responses to atmospheric CO2.

We present a unifying model for isoprene emission by photosynthesizing leaves based on the hypothesis that isoprene biosynthesis depends on a balance between the supply of photosynthetic reducing power and the demands of carbon fixation. We compared the predictions from our model, as well as from two other widely used models, with measurements of isoprene emission from leaves of Populus nigra and hybrid aspen (Populus tremula × P. tremuloides) in response to changes in leaf internal CO2 concentration (C(i)) and photosynthetic photon flux density (PPFD) under diverse ambient CO2 concentrations (C(a)). Our model reproduces the observed changes in isoprene emissions with C(i) and PPFD, and also reproduces the tendency for the fraction of fixed carbon allocated to isoprene to increase with increasing PPFD. It also provides a simple mechanism for the previously unexplained decrease in the quantum efficiency of isoprene emission with increasing C(a). Experimental and modelled results support our hypothesis. Our model can reproduce the key features of the observations and has the potential to improve process-based modelling of isoprene emissions by land vegetation at the ecosystem and global scales.

A fully integrated isoprenoid emissions model coupling emissions to photosynthetic characteristics.

The lack of a mechanistic basis has hampered modelling isoprene emission responses to environmental drivers, in particular the simulation of isoprene emissions under different CO2 concentrations. Here, we advance previous semi-mechanistic model formulations by introducing a model that explicitly links electron availability for other purpose than carbon assimilation (or available energy for secondary metabolism processes; supply-constraint) and enzyme activity (capacity-constraint) to emissions. We furthermore investigate the sensitivity of the model to variations in photosynthetic and emission-specific parameters. By comparing species-specific simulations with experimental data, we demonstrate that differences in photosynthetic characteristics can explain inter-species differences in emissions. Interestingly, the seasonal development of emissions could also be explained to some degree by the change in energy supply from photosynthesis throughout the season. In addition, we show that the principal responses are not limited to isoprene but can be formulated to describe the emission of other light-dependent volatile species. The proposed model is suitable for implementation into regional and global models, particularly those that already provide species-specific photosynthesis estimates.

Volatile isoprenoid emissions from plastid to planet.

Approximately 1-2% of net primary production by land plants is re-emitted to the atmosphere as isoprene and monoterpenes. These emissions play major roles in atmospheric chemistry and air pollution-climate interactions. Phenomenological models have been developed to predict their emission rates, but limited understanding of the function and regulation of these emissions has led to large uncertainties in model projections of air quality and greenhouse gas concentrations. We synthesize recent advances in diverse fields, from cell physiology to atmospheric remote sensing, and use this information to propose a simple conceptual model of volatile isoprenoid emission based on regulation of metabolism in the chloroplast. This may provide a robust foundation for scaling up emissions from the cellular to the global scale.

A unifying conceptual model for the environmental responses of isoprene emissions from plants.

BACKGROUND AND AIMS: Isoprene is the most important volatile organic compound emitted by land plants in terms of abundance and environmental effects. Controls on isoprene emission rates include light, temperature, water supply and CO2 concentration. A need to quantify these controls has long been recognized. There are already models that give realistic results, but they are complex, highly empirical and require separate responses to different drivers. This study sets out to find a simpler, unifying principle. METHODS: A simple model is presented based on the idea of balancing demands for reducing power (derived from photosynthetic electron transport) in primary metabolism versus the secondary pathway that leads to the synthesis of isoprene. This model's ability to account for key features in a variety of experimental data sets is assessed. KEY RESULTS: The model simultaneously predicts the fundamental responses observed in short-term experiments, namely: (1) the decoupling between carbon assimilation and isoprene emission; (2) a continued increase in isoprene emission with photosynthetically active radiation (PAR) at high PAR, after carbon assimilation has saturated; (3) a maximum of isoprene emission at low internal CO2 concentration (ci) and an asymptotic decline thereafter with increasing ci; (4) maintenance of high isoprene emissions when carbon assimilation is restricted by drought; and (5) a temperature optimum higher than that of photosynthesis, but lower than that of isoprene synthase activity. CONCLUSIONS: A simple model was used to test the hypothesis that reducing power available to the synthesis pathway for isoprene varies according to the extent to which the needs of carbon assimilation are satisfied. Despite its simplicity the model explains much in terms of the observed response of isoprene to external drivers as well as the observed decoupling between carbon assimilation and isoprene emission. The concept has the potential to improve global-scale modelling of vegetation isoprene emission.

State-of-the-art global models underestimate impacts from climate extremes.

Global impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought.

Photochemical reflectance index as an indirect estimator of foliar isoprenoid emissions at the ecosystem level.

Terrestrial plants re-emit around 1-2% of the carbon they fix as isoprene and monoterpenes. These emissions have major roles in the ecological relationships among living organisms and in atmospheric chemistry and climate, and yet their actual quantification at the ecosystem level in different regions is far from being resolved with available models and field measurements. Here we provide evidence that a simple remote sensing index, the photochemical reflectance index, which is indicative of light use efficiency, is a good indirect estimator of foliar isoprenoid emissions and can therefore be used to sense them remotely. These results open new perspectives for the potential use of remote sensing techniques to track isoprenoid emissions from vegetation at larger scales. On the other hand, our study shows the potential of this photochemical reflectance index technique to validate the availability of photosynthetic reducing power as a factor involved in isoprenoid production.