Understanding the role of abiotic stress in biosphere-atmosphere exchange of reactive trace gases

The terrestrial biosphere removes carbon dioxide (CO 2 ) from the atmosphere through photosynthesis and is a major sink for atmospheric pollutants like ozone. It is also the main source of biogenic volatile organic compounds (BVOCs) in the atmosphere. In turn, atmospheric conditions such as temperature, precipitation and photosynthetically active radiation regulate the growth and functioning of plants. The role of some environmental factors like temperature and solar radiation in regulating plant physiological processes are well understood and parameterised in land surface models (LSMs) but others like drought stress and ozone damage are poorly understood and hence poorly represented in LSMs. Yet, these LSMs are integral to climate modelling and climate change mitigation measures as they provide estimates of carbon stored in forests currently and how this will change in future. This thesis seeks to bridge the gap between the latest scientific knowledge about the effects of drought stress and ozone damage on plant physiological processes, and how these stressors are currently modelled. The response of plant isoprene emissions and gas exchange to drought stress and ozone damage was investigated using various model parametrisations, and long-term measurements of isoprene mixing ratios and fluxes, carbon dioxide and water fluxes made in a broad range of forest ecosystems. We find that current isoprene emission models are unable to account for stress-induced isoprene emissions during mild or moderate drought stress leading to underestimation of observed isoprene mixing ratios and fluxes. New methods for modelling isoprene emissions during moderate drought were developed and shown to improve model reproduction of observations. Further, it is shown that both drought stress and ozone damage act to reduce plant productivity and gas exchange. However, the impact of drought stress on vegetation was found to outweigh that of ozone damage at individual forest sites in both present day and future climate scenarios but accounting for the impact of both stress factors provided the best model-observation fit. As global climate changes, abiotic stress factors will become increasingly important in regulating biosphere-atmosphere interactions with potentially negative impacts on plant productivity and hence climate mitigation efforts. These findings highlight the need for more observations, especially in remote and data-sparse regions of the world such as the tropics, to improve understanding of how plants will respond to future stress, and how to better model the impacts

FORCAsT-gs:Importance of stomatal conductance parameterisation to estimated ozone deposition velocity

The role of stomata in regulating photosynthesis and transpiration, and hence governing global biogeochemical cycles and climate, is well-known. Less well-understood, however, is the importance of stomatal control to the exchange of other trace gases between terrestrial vegetation and the atmosphere. Yet these gases determine atmospheric composition, and hence air quality and climate, on scales ranging from local to global, and seconds to decades. Vegetation is a major sink for ground-level ozone via the process of dry deposition and the primary source of many biogenic volatile organic compounds (BVOCs). The rate of dry deposition is largely controlled by the rate of diffusion of a gas through the stomata, and this also governs the emission rate of some key BVOCs. It is critical therefore that canopy-atmosphere exchange models capture the physiological processes controlling stomatal conductance and the transfer of trace gases other than carbon dioxide and water vapour. We incorporate three of the most widely used coupled stomatal conductance-photosynthesis models into the one-dimensional multi-layer FORest Canopy-Atmosphere Transfer (FORCAsT1.0) model to assess the importance of choice of parameterisation on simulated ozone deposition rates. Modelled GPP and stomatal conductance across a broad range of ecosystems differ by up to a factor of two between the best and worst performing model configurations. This leads to divergences in seasonal and diel profiles of ozone deposition velocity of up to 30% and deposition rate of up to 13%, demonstrating that the choice of stomatal conductance parameterisation is critical in accurate quantification of ozone deposition

TAMSAT-ALERT v1: a new framework for agricultural decision support

Early warning of weather-related hazards enables farmers, policy makers and aid agencies to mitigate their exposure to risk. We present a new operational framework, Tropical Applications of Meteorology using SATellite data and ground based measurements-AgricuLtural EaRly warning sysTem (TAMSAT-ALERT), which aims to provide early warning for meteorological risk to agriculture. TAMSAT-ALERT combines information on land-surface properties, seasonal forecasts and historical weather to quantitatively assess the likelihood of adverse weather-related outcomes, such as low yield. This article describes the modular TAMSAT-ALERT framework and demonstrates its application to risk assessment for low maize yield in northern Ghana (Tamale). The modular design of TAMSAT-ALERT enables it to accommodate any impact or land-surface model driven with meteorological data. The implementation described here uses the well-established General Large Area Model (GLAM) for annual crops to provide probabilistic assessments of the meteorological hazard for maize yield in northern Ghana (Tamale) throughout the growing season. The results show that climatic risk to yield is poorly constrained in the beginning of the season, but as the season progresses, the uncertainty is rapidly reduced. Based on the assessment for the period 2002–2011, we show that TAMSAT-ALERT can estimate the meteorological risk on maize yield 6 to 8 weeks in advance of harvest. The TAMSAT-ALERT methodology implicitly weights forecast and observational inputs according to their relevance to the metric being assessed. A secondary application of TAMSAT-ALERT is thus an evaluation of the usefulness of meteorological forecast products for impact assessment. Here, we show that in northern Ghana (Tamale), the tercile seasonal forecasts of seasonal cumulative rainfall and mean temperature, which are routinely issued to farmers, are of limited value because regional and seasonal temperature and rainfall are poorly correlated with yield. This finding speaks to the pressing need for meteorological forecast products that are tailored for individual user applications

GC Insights: Diversifying the geosciences in higher education: a manifesto for change

There is still a significant lack of diversity and equity in geoscience education, even after decades of work and widespread calls for improvement and action. We join fellow community voices in calls for improved diversity, equity, inclusion, and justice in the geosciences. Here, in this manifesto, we present a list of opportunities for educators to bring about this cultural shift within higher education: (1) advocating for institutional change, (2) incorporating diverse perspectives and authors in curricula, (3) teaching historical and socio-political contexts of geoscience information, (4) connecting geoscience principles to more geographically diverse locations, (5) implementing different communication styles that consider different ways of knowing and learning, and (6) empowering learner transformation and agency

Continuous isoprene measurements in a UK temperate forest for a whole growing season: effects of drought stress during the 2018 heatwave

Isoprene concentrations were measured at four heights below, within and above the forest canopy in Wytham Woods (UK) throughout the summer of 2018 using custom-built gas chromatographs (the iDirac). These observations were complemented with selected ancillary variables, including air temperature, photosynthetically active radiation (PAR), occasional leaf gas exchange measurements and satellite retrievals of normalized difference vegetation and water indices (NDVI and NDWI). The campaign overlapped with a long and uninterrupted heatwave accompanied by moderate drought. Peak isoprene concentrations during the heatwave-drought were up to a factor of 4 higher than those before or after. Higher temperatures during the heatwave could not account for all the observed isoprene; the enhanced abundances correlated with drought stress. Leaf-level emissions confirmed this and also included compounds associated with ecosystem stress. This work highlights that a more in-depth understanding of the effects of drought stress is required to better characterize isoprene emissions

Improvement of modeling plant responses to low soil moisture in JULESvn4.9 and evaluation against flux tower measurements

Drought is predicted to increase in the future due to climate change, bringing with it myriad impacts on ecosystems. Plants respond to drier soils by reducing stomatal conductance in order to conserve water and avoid hydraulic damage. Despite the importance of plant drought responses for the global carbon cycle and local and regional climate feedbacks, land surface models are unable to capture observed plant responses to soil moisture stress. We assessed the impact of soil moisture stress on simulated gross primary productivity (GPP) and latent energy flux (LE) in the Joint UK Land Environment Simulator (JULES) vn4.9 on seasonal and annual timescales and evaluated 10 different representations of soil moisture stress in the model. For the default configuration, GPP was more realistic in temperate biome sites than in the tropics or high-latitude (cold-region) sites, while LE was best simulated in temperate and high-latitude (cold) sites. Errors that were not due to soil moisture stress, possibly linked to phenology, contributed to model biases for GPP in tropical savanna and deciduous forest sites. We found that three alternative approaches to calculating soil moisture stress produced more realistic results than the default parameterization for most biomes and climates. All of these involved increasing the number of soil layers from 4 to 14 and the soil depth from 3.0 to 10.8 m. In addition, we found improvements when soil matric potential replaced volumetric water content in the stress equation (the “soil14_psi” experiments), when the critical threshold value for inducing soil moisture stress was reduced (“soil14_p0”), and when plants were able to access soil moisture in deeper soil layers (“soil14_dr*2”). For LE, the biases were highest in the default configuration in temperate mixed forests, with overestimation occurring during most of the year. At these sites, reducing soil moisture stress (with the new parameterizations mentioned above) increased LE and increased model biases but improved the simulated seasonal cycle and brought the monthly variance closer to the measured variance of LE. Further evaluation of the reason for the high bias in LE at many of the sites would enable improvements in both carbon and energy fluxes with new parameterizations for soil moisture stress. Increasing the soil depth and plant access to deep soil moisture improved many aspects of the simulations, and we recommend these settings in future work using JULES or as a general way to improve land surface carbon and water fluxes in other models. In addition, using soil matric potential presents the opportunity to include plant functional type-specific parameters to further improve modeled fluxes

Exploring new strategies for ozone-risk assessment:a dynamic-threshold case study

Tropospheric ozone is a dangerous atmospheric pollutant for forest ecosystems when it penetrates stomata. Thresholds for ozone-risk assessment are based on accumulated stomatal ozone fluxes such as the Phytotoxic Ozone Dose (POD). In order to identify the effect of ozone on a Holm oak forest in central Italy, four flux-based ozone impact response functions were implemented and tested in a multi-layer canopy model AIRTREE and evaluated against Gross Primary Productivity (GPP) obtained from observations of Eddy Covariance fluxes of CO2. To evaluate if a clear phytotoxic threshold exists and if it changes during the year, six different detoxifying thresholds ranging between 0 and 5 nmol O3 m-2 s-1 were tested. The use of species-specific rather than more general response functions based on plant functional types (PFT) increased model accuracy (RMSE reduced by up to 8.5%). In the case of linear response functions, a threshold of 1 nmol m-2 s-2 produced the best results for simulations of the whole year, although the tolerance to ozone changed seasonally, with higher tolerance (5 nmol m-2 s-1 or no ozone impact) for Winter and Spring and lower thresholds in Summer and Fall (0-1 nmol m-2 s-1). A “dynamic threshold” obtained by extracting the best daily threshold values from a range of different simulations helped reduce model overestimation of GPP by 213 g C m-2 y-1 and reduce RMSE up to 7.7%. Finally, a nonlinear ozone correction based on manipulative experiments produced the best results when no detoxifying threshold was applied (0 nmol O3 m-2 s-1), suggesting that nonlinear functions fully account for ozone detoxification. The evidence of seasonal changes in ozone tolerance points to the need for seasonal thresholds to predict ozone damage and highlights the importance of performing more species-specific manipulative experiments to derive response functions for a broad range of plant species

Continuous isoprene measurements in a UK temperate forest for a whole growing season:effects of drought stress during the 2018 heatwave

Isoprene concentrations were measured at four heights below, within, and above the forest canopy in Wytham Woods (United Kingdom) throughout the summer of 2018 using custom‐built gas chromatographs (the iDirac). These observations were complemented with selected ancillary variables, including air temperature, photosynthetically active radiation, occasional leaf gas exchange measurements, and satellite retrievals of normalized difference vegetation and water indices. The campaign overlapped with a long and uninterrupted heatwave accompanied by moderate drought. Peak isoprene concentrations during the heatwave‐drought were up to a factor of 4 higher than those before or after. Higher temperatures during the heatwave could not account for all the observed isoprene; the enhanced abundances correlated with drought stress. Leaf‐level emissions confirmed this and also included compounds associated with ecosystem stress. This work highlights that a more in‐depth understanding of the effects of drought stress is required to better characterize isoprene emissions

Modelling the effect of the 2018 summer heatwave and drought on isoprene emissions in a UK woodland

Projected future climatic extremes such as heatwaves and droughts are expected to have major impacts on emissions and concentrations of biogenic volatile organic compounds (bVOCs) with potential implications for air quality, climate, and human health. While the effects of changing temperature and photosynthetically active radiation (PAR) on the synthesis and emission of isoprene, the most abundant of these bVOCs, are well-known, the role of other environmental factors such as soil moisture stress are not fully understood and are therefore poorly represented in land surface models. As part of the Wytham Isoprene iDirac Oak Tree Measurements (WIsDOM) campaign, continuous measurements of isoprene mixing ratio were made throughout the summer of 2018 in Wytham Woods, a mixed deciduous woodland in southern England. During this time, the United Kingdom experienced a prolonged heatwave and drought, and isoprene mixing ratios were observed to increase by more than 400% at Wytham Woods under these conditions. We applied the state-of-the-art FORest Canopy-Atmosphere Transfer (FORCAsT) canopy exchange model to investigate the processes leading to these elevated concentrations. We found that although current isoprene emissions algorithms reproduced observed mixing ratios in the canopy before and after the heatwave, the model underestimated observations by ~40% during the heatwave-drought period implying that models may substantially underestimate the release of isoprene to the atmosphere in future cases of mild or moderate drought. Stress-induced emissions of isoprene based on leaf temperature and soil water content were incorporated into current emissions algorithms leading to significant improvements in model output. A combination of soil water content, leaf temperature and rewetting emission bursts provided the best model- measurement fit with a 50% improvement compared to the baseline model. Our results highlight the need for more long-term ecosystem-scale observations to enable improved model representation of atmosphere-biosphere interactions in a changing global climate