An optimality-based model of the coupled soil moisture and root dynamics

The main processes determining soil moisture dynamics are infiltration, percolation, evaporation and root water uptake. Modelling soil moisture dynamics therefore requires an interdisciplinary approach that links hydrological, atmospheric and biological processes. Previous approaches treat either root water uptake rates or root distributions and transpiration rates as given, and calculate the soil moisture dynamics based on the theory of flow in unsaturated media. The present study introduces a different approach to linking soil water and vegetation dynamics, based on vegetation optimality. Assuming that plants have evolved mechanisms that minimise costs related to the maintenance of the root system while meeting their demand for water, we develop a model that dynamically adjusts the vertical root distribution in the soil profile to meet this objective. The model was used to compute the soil moisture dynamics, root water uptake and fine root respiration in a tropical savanna over 12 months, and the results were compared with observations at the site and with a model based on a fixed root distribution. The optimality-based model reproduced the main features of the observations such as a shift of roots from the shallow soil in the wet season to the deeper soil in the dry season and substantial root water uptake during the dry season. At the same time, simulated fine root respiration rates never exceeded the upper envelope determined by the observed soil respiration. The model based on a fixed root distribution, in contrast, failed to explain the magnitude of water use during parts of the dry season and largely over-estimated root respiration rates. The observed surface soil moisture dynamics were also better reproduced by the optimality-based model than the model based on a prescribed root distribution. The optimality-based approach has the potential to reduce the number of unknowns in a model (e.g. the vertical root distribution), which makes it a valuable alternative to more empirically-based approaches, especially for simulating possible responses to environmental change

An optimality-based model of the dynamic feedbacks between natural vegetation and the water balance

The hypothesis that vegetation adapts optimally to its environment gives rise to a novel framework for modeling the interactions between vegetation dynamics and the catchment water balance that does not rely on prior knowledge about the vegetation at a particular site. We present a new model based on this framework that includes a multilayered physically based catchment water balance model and an ecophysiological gas exchange and photosynthesis model. The model uses optimization algorithms to find those static and dynamic vegetation properties that would maximize the net carbon profit under given environmental conditions. The model was tested at a savanna site near Howard Springs (Northern Territory, Australia) by comparing the modeled fluxes and vegetation properties with long-term observations at the site. The results suggest that optimality may be a useful way of approaching the prediction and estimation of vegetation cover, rooting depth, and fluxes such as transpiration and CO2 assimilation in ungauged basins without model calibration

Root growth dynamics and allocation as a response to rapid and local changes in soil moisture

Roots exhibit plasticity in morphology and physiology when exposed to fluctuating nutrient and water availability. However, the dynamics of daily timescale adjustments to changes in water availability are unclear, and experimental evidence of the rates of such adjustments is needed. In this study, we investigated how the root system responds within days to a sudden and localized increase in soil moisture (“hydromatching”). Root systems of maize plants were grown in soil columns divided into four layers by vaseline barriers and continuously monitored using magnetic resonance imaging (MRI) technology. We found that, within 48 h after application of water pulses in a given soil layer, root growth rates in that layer increased, while root growth rates in other layers decreased. Our results indicate local root growth was guided by local changes in soil moisture and potentially even by changes in soil moisture occurring in other parts of the soil profile, which would result in a coordinated response of the entire root system. Hydromatching in maize appears to be a dynamic and reversible phenomenon, for which the investment in biomass is continuously promoted in wet soil volumes and/or halted in drier soil volumes. This sheds new light onto the plasticity of root systems of maize plants and their ability to adjust to local and sudden changes in soil moisture, as would be expected due to patchy infiltration after rainfall or irrigation events.</p

Wind effects on leaf transpiration challenge the concept of &quot;potential evaporation&quot;

Transpiration is commonly conceptualised as a fraction of some potential rate, driven by so-called "atmospheric evaporative demand". Therefore, atmospheric evaporative demand or "potential evaporation" is generally used alongside with precipitation and soil moisture to characterise the environmental conditions that affect plant water use. Consequently, an increase in potential evaporation (e.g. due to climate change) is believed to cause increased transpiration and/or vegetation water stress. In the present study, we investigated the question whether potential evaporation constitutes a meaningful reference for transpiration and compared sensitivity of potential evaporation and leaf transpiration to atmospheric forcing. A physically-based leaf energy balance model was used, considering the dependence of feedbacks between leaf temperature and exchange rates of radiative, sensible and latent heat on stomatal resistance. Based on modelling results and supporting experimental evidence, we conclude that stomatal resistance cannot be parameterised as a factor relating transpiration to potential evaporation, as the ratio between transpiration and potential evaporation not only varies with stomatal resistance, but also with wind speed, air temperature, irradiance and relative humidity. Furthermore, the effect of wind speed in particular implies increase in potential evaporation, which is commonly interpreted as increased "water stress", but at the same time can reduce leaf transpiration, implying a decrease in water demand at leaf scale

The future of metabolomics in ELIXIR.

Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the "Future of metabolomics in ELIXIR" was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community. The workshop established metabolite identification as the critical area, where a maximal impact of computational metabolomics and data management on other fields could be achieved. In particular, the existing four ELIXIR Use Cases, where the metabolomics community - both industry and academia - would benefit most, and which could be exhaustively mapped onto the current five ELIXIR Platforms were discussed. This opinion article is a call for support for a new ELIXIR metabolomics Use Case, which aligns with and complements the existing and planned ELIXIR Platforms and Use Cases

Increasing stomatal conductance inresponse to rising atmospheric CO2

Background and Aims: Studies have indicated that plant stomatal conductance (gs) decreases in response to elevated atmospheric CO2, a phenomenon of significance for the global hydrological cycle. However, gs increases across certain CO2 ranges have been predicted by optimisation models. The aim of this work was to demonstrate that under certain environmental condition, gs can increase in response to elevated CO2. Methods: When using (i) an extensive, up-to-date, synthesis of gs responses in FACE experiments, (ii) in situ measurements across four biomes showing dynamic gs responses to a CO2 rise of ~50ppm (characterising the change in this greenhouse gas over the past three decades) and (iii) a photosynthesis-stomatal conductance model, it is demonstrated that gs can in some cases increase in response to increasing atmospheric CO2. Key Results: Field observations are corroborated by an extensive synthesis of gs responses in FACE experiments showing that 11.8% of gs responses under experimentally elevated CO2 are positive. They are further supported by a strong data-model fit (r2=0.607) using a stomatal optimization model applied to the field gs dataset. A parameter space identified in the Farquhar-Ball-Berry photosynthesis-stomatal conductance model confirms field observations of increasing gs under elevated CO2 in hot dry conditions. It was shown that contrary to the general assumption, positive gs responses to elevated CO2, although relatively rare, are a feature of woody taxa adapted to warm, low-humidity conditions, and that this response is also demonstrated in global simulations using the Community Land Model (CLM4). Conclusions: The results contradict the over-simplistic notion that global vegetation always responds with decreasing gs to elevated CO2, a finding that has important implications for predicting future vegetation feedbacks on the hydrological cycle at the regional level.Irish Research CouncilScience Foundation Irelan

Advancing catchment hydrology to deal with predictions under change

Throughout its historical development, hydrology as an earth science, but especially as a problem-centred engineering discipline has largely relied (quite successfully) on the assumption of stationarity. This includes assuming time invariance of boundary conditions such as climate, system configurations such as land use, topography and morphology, and dynamics such as flow regimes and flood recurrence at different spatio-temporal aggregation scales. The justification for this assumption was often that when compared with the temporal, spatial, or topical extent of the questions posed to hydrology, such conditions could indeed be considered stationary, and therefore the neglect of certain long-term non-stationarities or feedback effects (even if they were known) would not introduce a large error. However, over time two closely related phenomena emerged that have increasingly reduced the general applicability of the stationarity concept: the first is the rapid and extensive global changes in many parts of the hydrological cycle, changing formerly stationary systems to transient ones. The second is that the questions posed to hydrology have become increasingly more complex, requiring the joint consideration of increasingly more (sub-) systems and their interactions across more and longer timescales, which limits the applicability of stationarity assumptions. Therefore, the applicability of hydrological concepts based on stationarity has diminished at the same rate as the complexity of the hydrological problems we are confronted with and the transient nature of the hydrological systems we are dealing with has increased. The aim of this paper is to present and discuss potentially helpful paradigms and theories that should be considered as we seek to better understand complex hydrological systems under change. For the sake of brevity we focus on catchment hydrology. We begin with a discussion of the general nature of explanation in hydrology and briefly review the history of catchment hydrology. We then propose and discuss several perspectives on catchments: as complex dynamical systems, self-organizing systems, co-evolving systems and open dissipative thermodynamic systems. We discuss the benefits of comparative hydrology and of taking an information-theoretic view of catchments, including the flow of information from data to models to predictions. In summary, we suggest that these perspectives deserve closer attention and that their synergistic combination can advance catchment hydrology to address questions of change

The NORMAN Association and the European Partnership for Chemicals Risk Assessment (PARC): let’s cooperate! [Commentary]

The Partnership for Chemicals Risk Assessment (PARC) is currently under development as a joint research and innovation programme to strengthen the scientific basis for chemical risk assessment in the EU. The plan is to bring chemical risk assessors and managers together with scientists to accelerate method development and the production of necessary data and knowledge, and to facilitate the transition to next-generation evidence-based risk assessment, a non-toxic environment and the European Green Deal. The NORMAN Network is an independent, well-established and competent network of more than 80 organisations in the field of emerging substances and has enormous potential to contribute to the implementation of the PARC partnership. NORMAN stands ready to provide expert advice to PARC, drawing on its long experience in the development, harmonisation and testing of advanced tools in relation to chemicals of emerging concern and in support of a European Early Warning System to unravel the risks of contaminants of emerging concern (CECs) and close the gap between research and innovation and regulatory processes. In this commentary we highlight the tools developed by NORMAN that we consider most relevant to supporting the PARC initiative: (i) joint data space and cutting-edge research tools for risk assessment of contaminants of emerging concern; (ii) collaborative European framework to improve data quality and comparability; (iii) advanced data analysis tools for a European early warning system and (iv) support to national and European chemical risk assessment thanks to harnessing, combining and sharing evidence and expertise on CECs. By combining the extensive knowledge and experience of the NORMAN network with the financial and policy-related strengths of the PARC initiative, a large step towards the goal of a non-toxic environment can be taken

The NORMAN Association and the European Partnership for Chemicals Risk Assessment (PARC): let’s cooperate!

The Partnership for Chemicals Risk Assessment (PARC) is currently under development as a joint research and innovation programme to strengthen the scientific basis for chemical risk assessment in the EU. The plan is to bring chemical risk assessors and managers together with scientists to accelerate method development and the production of necessary data and knowledge, and to facilitate the transition to next-generation evidence-based risk assessment, a non-toxic environment and the European Green Deal. The NORMAN Network is an independent, well-established and competent network of more than 80 organisations in the field of emerging substances and has enormous potential to contribute to the implementation of the PARC partnership. NORMAN stands ready to provide expert advice to PARC, drawing on its long experience in the development, harmonisation and testing of advanced tools in relation to chemicals of emerging concern and in support of a European Early Warning System to unravel the risks of contaminants of emerging concern (CECs) and close the gap between research and innovation and regulatory processes. In this commentary we highlight the tools developed by NORMAN that we consider most relevant to supporting the PARC initiative: (i) joint data space and cutting-edge research tools for risk assessment of contaminants of emerging concern; (ii) collaborative European framework to improve data quality and comparability; (iii) advanced data analysis tools for a European early warning system and (iv) support to national and European chemical risk assessment thanks to harnessing, combining and sharing evidence and expertise on CECs. By combining the extensive knowledge and experience of the NORMAN network with the financial and policy-related strengths of the PARC initiative, a large step towards the goal of a non-toxic environment can be taken.</p

An annotation database for chemicals of emerging concern in exposome research

International audienceBackground: Chemicals of Emerging Concern (CECs) include a very wide group of chemicals that are suspected to be responsible for adverse effects on health, but for which very limited information is available. Chromatographic techniques coupled with high-resolution mass spectrometry (HRMS) can be used for non-targeted screening and detection of CECs, by using comprehensive annotation databases. Establishing a database focused on the annotation of CECs in human samples will provide new insight into the distribution and extent of exposures to a wide range of CECs in humans.Objectives: This study describes an approach for the aggregation and curation of an annotation database (CECscreen) for the identification of CECs in human biological samples.Methods: The approach consists of three main parts. First, CECs compound lists from various sources were aggregated and duplications and inorganic compounds were removed. Subsequently, the list was curated by standardization of structures to create "MS-ready" and "QSAR-ready" SMILES, as well as calculation of exact masses (monoisotopic and adducts) and molecular formulas. The second step included the simulation of Phase I metabolites. The third and final step included the calculation of QSAR predictions related to physicochemical properties, environmental fate, toxicity and Absorption, Distribution, Metabolism, Excretion (ADME) processes and the retrieval of information from the US EPA CompTox Chemicals Dashboard.Results: All CECscreen database and property files are publicly available (DOI: https://doi.org/10.5281/zenodo.3956586). In total, 145,284 entries were aggregated from various CECs data sources. After elimination of duplicates and curation, the pipeline produced 70,397 unique "MS-ready" structures and 66,071 unique QSAR-ready structures, corresponding with 69,526 CAS numbers. Simulation of Phase I metabolites resulted in 306,279 unique metabolites. QSAR predictions could be performed for 64,684 of the QSAR-ready structures, whereas information was retrieved from the CompTox Chemicals Dashboard for 59,739 CAS numbers out of 69,526 inquiries. CECscreen is incorporated in the in silico fragmentation approach MetFrag.Discussion: The CECscreen database can be used to prioritize annotation of CECs measured in non-targeted HRMS, facilitating the large-scale detection of CECs in human samples for exposome research. Large-scale detection of CECs can be further improved by integrating the present database with resources that contain CECs (metabolites) and meta-data measurements, further expansion towards in silico and experimental (e.g., MassBank) generation of MS/MS spectra, and development of bioinformatics approaches capable of using correlation patterns in the measured chemical features