HS8.3.5

For quantitative land evaluation studies often simulation models are used to express the differences between soil types in terms of water availability or crop productivity. In the Netherlands we developed a land evaluation system specifically for water authorities, provinces and drinking water companies. The system allows answering questions on how water management influences crop development due to too dry or too wet conditions in the unsaturated zone. This system is based on the linked simulation model SWAP (Soil-Water-Atmosphere-Plant) and WOFOST (WOrld FOod STudies). The impact of changes in climate or hydrology can then be studied in terms of effects on crop growth and farm income.

Although SWAP and WOFOST are process based models, the rootzone development is simulated in a straightforward way: the development of the root extension is specified by the user in advance and the root length density distribution is assumed static in time. Because the circumstances within the rootzone is influenced by meteorological, hydrological and soil characteristics it is impossible to design an optimal rootzone development in advance. For a more realistic approach we implemented an adaptive rootzone distribution which will react on the hydrological conditions within the rootzone. This means that newly formed roots will be assigned to regions where there is no or the least stress, and less or no new roots to regions where water stress was experienced. As a result the drought and oxygen stress will be less dependent on the initial root distribution as specified by the user. An example for a regional study will be provided to show the relevance of adaptive rootzone development for assessing land qualities in space and time. 

How to cite: Mulder, M., Heinen, M., and Hack - ten Broeke, M.: Effect of adaptive rootzone development in quantitative land evaluation studies, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1748, https://doi.org/10.5194/egusphere-egu22-1748, 2022.

Stomatal closure allows plants to promptly respond to water shortage. Although the coordination between stomatal regulation, leaf and xylem hydraulics has been extensively investigated, the impact of below-ground hydraulics on stomatal regulation remains unknown.

We used a novel root pressure chamber to measure, during soil drying, the relation between transpiration rate (E) and leaf xylem water pressure (ψ_leaf-x) in tomato shoots grafted onto two contrasting rootstocks, a long and a short one. In parallel, we also measured the E(ψ_leaf-x) relation without pressurization. A soil–plant hydraulic model was used to reproduce the measurements. We hypothesize that (1) stomata close when the E(ψ_leaf-x) relation becomes non-linear and (2) non-linearity occurs at higher soil water contents and lower transpiration rates in short-rooted plants.

The E(ψ_leaf-x) relation was linear in wet conditions and became non-linear as the soil dried. Changing below-ground traits (i.e. root system) significantly affected the E(ψ_leaf-x) relation during soil drying. Plants with shorter root systems required larger gradients in soil water pressure to sustain the same transpiration rate and exhibited an earlier non-linearity and stomatal closure.

We conclude that, during soil drying, stomatal regulation is controlled by below-ground hydraulics in a predictable way. The model suggests that the loss of hydraulic conductivity occurred in soil. These results prove that stomatal regulation is intimately tied to root and soil hydraulic conductances.

How to cite: Abdalla, M., Ahmed, M., Cai, G., Wankmüller, F., Schwartz, N., Litig, O., Javaux, M., and Carminati, A.: Stomatal closure under drought is controlled by below-ground hydraulics, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4367, https://doi.org/10.5194/egusphere-egu22-4367, 2022.

The capacity of forest plants to sequester C is closely linked to soil nitrogen (N) availability, a major control of plant growth and ecosystem functioning. An increase of soil temperature caused by climate change affects C and N cycling in forest soils, but implications for plant available N have remained largely unclear. In recent short-term laboratory incubation studies, an increase in soil temperature has not only led to a significant increase in diffusive N fluxes, but also to a concomitant shift in bioavailable N quality for plant and microbial uptake, i.e. towards a higher proportion of inorganic N forms compared to small organic N forms such as amino acids. However, long-term effects of soil warming on diffusive soil N fluxes in situ remain largely unknown. Applying the microdialysis technique, we quantified in situ diffusive fluxes of amino acids, ammonium and nitrate at the long-term soil warming experimental site Achenkirch (Tyrol, Austria). This site is one of the few climate manipulation experiments operational for more than 15 years and has already provided a wealth of novel insights into the potential effects of global warming on forest ecosystem responses. Results from four sampling campaigns (n = 1152 microdialysis samples) during the growing season showed no effect of warming on diffusive N fluxes. Diffusive ammonium fluxes increased from spring towards autumn while nitrate fluxes followed an opposite trend. Compared to other temperate and boreal forest soils, the proportion of amino acids in the total diffusive N flux in this carbonate soil was low (13 - 30%), while the proportions of ammonium (21 – 67%) and nitrate were high (19 – 58%). In conclusion, our results suggest that in situ diffusive N fluxes, as well as the proportions of different N forms, were unaffected after 15 years of soil warming.  Accordingly, warming may not be expected to increase diffusive soil N supply for root uptake in the topsoil in the long run. Diffusive N availability was mainly determined by seasonal effects and by the small-scale heterogeneity of the soil matrix.

How to cite: Inselsbacher, E., Heinzle, J., Tian, Y., Kwatcho-Kengdo, S., Shi, C., Borken, W., Wanek, W., and Schindlbacher, A.: No effect of long-term soil warming on diffusive soil inorganic and organic nitrogen fluxes in a temperate forest soil, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1596, https://doi.org/10.5194/egusphere-egu22-1596, 2022.

Projections of global climate models suggest that ongoing human-induced climate change will lead to an increase in the frequency of severe droughts in many important agricultural regions of the world. Eco-hydrological models that integrate current understanding of the interacting processes governing soil water balance and plant growth may be useful tools to predict the impacts of climate change on crop production. However, the validation status of these models for making predictions under climate change is still unclear, since few suitable datasets are available for model testing. One promising approach is to test models using data obtained in “space-for-time” substitution experiments, in which samples are transferred among locations with contrasting current climates in order to mimic future climatic conditions. An important advantage of this approach is that the soil type is the same, so that differences in soil properties are not confounded with the influence of climate on water balance and crop growth. In this study, we evaluate the capability of a relatively simple eco-hydrological model to reproduce 6 years (2013-2018) of measurements of soil water contents, water balance components and grass production made in weighing lysimeters located at two sites within the TERENO-SoilCan network in Germany. Three lysimeters are located at an upland site at Rollesbroich with a cool, wet climate, while three others had been moved from Rollesbroich to a warmer and drier climate on the lower Rhine valley floodplain at Selhausen. Four of the most sensitive parameters in the model were treated as uncertain within the framework of the GLUE (Generalized Likelihood Uncertainty Estimation) methodology, while the remaining parameters in the model were set according to site measurements or data in the literature.

The model accurately reproduced the measurements at both sites, and some significant differences in the posterior ranges of the four uncertain parameters were found. In particular, the results indicated greater stomatal conductance as well an increase in dry matter allocation below-ground and a significantly larger maximum root depth for the three lysimeters that had been moved to Selhausen. As a consequence, the apparent water use efficiency (above-ground harvest divided by evapotranspiration) was significantly smaller at Selhausen than Rollesbroich. Data on species abundance on the lysimeters provide one possible explanation for the differences in the plant traits at the two sites derived from model calibration. These observations showed that the plant community at Selhausen had changed significantly in response to the drier climate, with a significant decrease in the abundance of herbs and an increase in the proportion of grass species. The differences in root depth and leaf conductance may also be a consequence of plasticity or acclimation at the species level. Regardless of the reason, we may conclude that such adaptations introduce significant additional uncertainties into model predictions of water balance and plant growth in response to climate change.

How to cite: Jarvis, N., Groh, J., Meurer, K., Lewan, E., Puetz, T., Durka, W., Baessler, C., and Vereecken, H.: Coupled modelling of hydrological processes and grassland production in two contrasting climates, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3466, https://doi.org/10.5194/egusphere-egu22-3466, 2022.

Deep-rooted crops, such as rapeseed have access to deep stored soil moisture unavailable to more shallow-rooted crops. However, it appears that the presence of deep roots in moist soil does not necessarily ensure full water supply and prevent drought stress during progressive soil drying. Thus, there is a need to quantify the contribution of deep roots to water uptake and investigate the role of deep roots in delaying drought stress.

In large parts of Europe, climate change will lead to lower precipitation in the growing season and higher outside the growing season. This imbalance can be levelled out by growing summer crops on winter precipitation. However, it requires crops that a capable of utilizing previous surplus precipitation stored deep in the soil profile.

We grew rapeseed in a large-scale semi-field setup, allowing root growth down to 4 meters depth. We monitored the development in root growth, water uptake, stomatal conductance, leaf ABA, photosynthesis, and soil water content during progressive soil drying. This allowed us to investigate the ability of rapeseed to compensate for a lack of water in the upper root zone with water uptake in the deeper root zone and to identify the onset of stress responses.

How to cite: Rasmussen, C., Rosenqvist, E., Liu, F., Dresbøll, D. B., Thorup-Kristensen, K., and Javaux, M.: Rapeseed reaches 4 meters depth – but does it escape drought stress?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5105, https://doi.org/10.5194/egusphere-egu22-5105, 2022.

Water and nutrient uptake are essential for plant productivity. Therefore, the development of precise functional-structural root models will enable better agricultural management in particular in resource limited environments. In such models water movement is of special importance since the rhizosphere's biochemical reactions are strongly  influenced by water content and water movement. We present a general sink term for larger scale root water uptake models that includes the root-rhizosphere hydraulic architecture.

We derive the new aggregated sink term from a more complex model that describes the rhizosphere around each root segment in dependence of a hydraulic root system model. We use CPlantBox (Schnepf et al. 2018) to represent root architecture, and calculate water movement within the root system using the hybrid analytical solution of Meunier et al. (2017). Around each root segment we represent water movement within the rhizosphere by a 1D axisymmetric model. Such models are flexible in the way the rhizosphere is represented (Mai et al. 2019). They are able to accurately describe water depletion and redistribution, but are computationally expensive. 

To simplify the model we use the analytical solution of the steady rate approximation following (Schröder et al. 2008) for water movement in the 1D axisymmetric models. The analytic solution depends on the matric potentials of the macroscopic soil (which is calculated in 1D, 2D or 3D) and the hydraulic root architecture model, root radial conductivity, and radius of the rhizosphere domain. We use fixed-point iteration to determine the matric potential at the soil root interface and store the solutions in a look up table for speedup.  

Moving to larger scales it is generally not useful to keep track of all root system architectures. Therefore, we aim for a coarser approximation of the root architecture by representing it as detached parallel root segments. Parallel segment conductivities are based on standard uptake fraction (SUF) and root system conductivity (Krs) of the original topology (Couvreur et al. 2012), which was shown by Vanderborght et al. (2021) to be a close approximation of the uptake by the original root topology. This approach makes the computation of the full root hydraulic architecture model superfluous, leading to a stable and performant sink term. 

This new sink term increases the accuracy of water uptake in a suite of larger scale models including crop modes, earth system models, and hydrological models. Using the presented approach, the sink term can be derived directly from 3D root hydraulic architecture. This avoids parameterizations based on proxy information about root system hydraulics and can acknowledge age dependent axial and radial root segment hydraulic conductances. Finally, information about rhizosphere hydraulic properties, which may differ from bulk soil hydraulic properties can be injected effectively in this sink term model.  

References

Schnepf, A., et al. (2018) Annals of botany, 121(5) 1033-1053.

Meunier, F. et al. Applied Mathematical Modelling, 52, 648-663.

Mai, TH., et al. Plant and Soil, 439(1), 273-292.

Schröder, et al. (2008) Vadose Zone Journal 7(3), 1089-1098.

Couvreur, V.,  et al. (2012) Hydrology and Earth System Sciences, 16(8), 2957-2971.

Vanderborght, J.,  et al. (2021) Hydrology and Earth System Sciences, 25(9), 4835-4860.

How to cite: Leitner, D., Schnepf, A., and Vanderborght, J.: A new root water uptake sink term including root-rhizosphere hydraulic architecture, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7304, https://doi.org/10.5194/egusphere-egu22-7304, 2022.

3D models of root growth, architecture and function are becoming important tools to aid the design of agricultural management schemes and the selection of beneficial root traits. While benchmarking is common for water and solute transport models in soil, 3D root-soil interaction models have not yet been systematically analysed. Several interacting processes might induce disagreement between models: root growth, sink term definitions of root water and solute uptake and representation of the rhizosphere. Schnepf et al. (2020) proposed a framework for quantitatively comparing such models. It builds upon benchmark scenarios that test individual components, followed by benchmark scenarios for the coupled root-rhizosphere-soil system.

Here we present the results of benchmarking different well-known models (“simulators”) with respect to water flow in soil, water flow in roots, and water flow and root water uptake in a coupled soil-root system for the case of a given prescribed root architecture as observed from an MRI experiment. The participating simulators are

CPlantBox and DuMux (Koch et al. 2021; Mai et al. 2019), R-SWMS (Javaux et al. 2008), OpenSimRoot (Postma et al. 2017) and ArchiSimple, RootTyp and SRI (Beudez et al. 2013; Pagès et al. 2014; Pagès et al. 2004).

In the benchmark scenarios that represent individual modules, the different simulators solved the same mathematical model but with different numerical approaches; all perform well with respect to the given analytical reference solution. For the coupled problem of root water uptake from a drying soil, the different simulators make different choices for the coupling of the different sub-problems. Thus, the results of the different simulators show a larger heterogeneity amongst each other.

We expect that this benchmarking will result in improved models, with which we can simulate various scenarios with greater confidence, avoiding that future work is based on accidental results caused by bugs, numerical errors or conceptual misunderstandings and will set a standard for model development.

Beudez N, Doussan C, Lefeuve-Mesgouez G, Mesgouez A (2013) Procedia Environmental Sciences 19: 37-46. doi:

Javaux M, Schröder T, Vanderborght J, Vereecken H (2008) Vadose Zone Journal 7: 1079-1088.

Koch T, Wu H, Schneider M (2021) Journal of Computational Physics: 110823.

Mai TH, Schnepf A, Vereecken H, Vanderborght J (2019) Plant and Soil 439: 273-292. doi: 10.1007/s11104-018-3890-4.

Pagès L, Bécel C, Boukcim H, Moreau D, Nguyen C, Voisin A-S (2014) Ecological Modelling 290: 76-84.

Pagès L, Vercambre G, Drouet J-L, Lecompte F, Collet C, Le Bot J (2004) Plant and Soil 258: 103-119.

Postma JA, Kuppe C, Owen MR, Mellor N, Griffiths M, Bennett MJ, Lynch JP, Watt M (2017) New Phytologist 215: 1274-1286.

Schnepf A, Black CK, Couvreur V, et al. (2020) Frontiers in Plant Science 11.

How to cite: Schnepf, A., Couvreur, V., Delory, B., Doussan, C., Javaux, M., Khare, D., Koch, A., Koch, T., Kuppe, C., Leitner, D., Lobet, G., Meunier, F., Postma, J., Schäfer, E., Vanderborght, J., and Vereecken, H.: Quantitative comparison of root water uptake simulated by functional-structural root architecture models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8524, https://doi.org/10.5194/egusphere-egu22-8524, 2022.

Soil pollution from neutral and ionizable compounds poses a significant threat to water resources management and food production. The development of numerical models to describe their reactive transport in the soil-plant domain is of paramount importance to elaborate mitigation strategies. However, most existing models simplify the description of physicochemical processes in soil and plants, mass transfer processes between soil and plants and in plants, and transformation in plants. To fill this scientific gap, we first coupled the widely used hydrological model, HYDRUS, with a multi-compartment dynamic plant uptake model, which accounts for differentiated multiple metabolization pathways in plant’s tissues. The model, which is able to simulate the reactive transport of neutral compounds, has been successfully validated against experimental data, and integrated in the Graphical User Interface of the HYDRUS software suite. To further extend its domain of applicability, we have recently adapted its theoretical framework to simulate the translocation of ionizable compounds. The new modeling framework connects a biophysical multi-organelles model to describe processes at the cell level with a semi-mechanistic soil-plant model, and accounts for dissociation processes and electrical interactions with cell biomembranes. Validation against experimental data showed encouraging results and opens new perspectives for its use for predictive and explanatory purposes.

References

Šimůnek, J., G. Brunetti, and R. Kodešová, Modeling the translocation and transformation of chemicals in the soil-plant continuum: A dynamic plant uptake module for the HYDRUS model, AGU Annual Meeting, ID 810092, New Orleans, Louisiana, December 13-17, 2021.

How to cite: Brunetti, G., Šimůnek, J., and Kodešová, R.: Modeling the translocation and transformation of chemicals in the soil-plant continuum: a dynamic plant uptake module for the HYDRUS model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1962, https://doi.org/10.5194/egusphere-egu22-1962, 2022.

The knowledge of crop evapotranspiration is crucial for several hydrological processes, including those related to the management of agricultural water sources. Among indirect methods to estimate actual evapotranspiration, ET_a, the measurements of latent heat fluxes acquired with Eddy Covariance (EC) tower have been largely used. However, the malfunctioning of the commonly installed sensors can cause the loss of data, compromising the temporal continuity of the acquisitions. Machine learning (ML) algorithms can represent a powerful tool to perform gap-filling procedures and provide accurate predictions of missing data.

The objective of the research was to assess different ML algorithms to fill daily actual evapotranspiration measurements acquired in a Mediterranean citrus orchard, by using a combination of in-situ or ERA5-Land reanalysis agro-meteorological data and two vegetation indices (VIs) retrieved by the Sentinel 2 platform.

The experimental layout consisted of a standard weather station, an EC tower containing an open-patch gas-analyzer, a three-dimension sonic anemometer, a four-component net radiometer. Four “drill and drop” probes (Sentek Pty Ltd, Stepney, Australia) were also installed in the field. Six different algorithms of machine learning were tested, using in input, as climate variables the global solar radiation, mean air temperature and relative air humidity, as well as two VIs (NDVI e NDWI) characterized by a spatial resolution of 10 m and, finally, the average soil water content measured in the root zone (0-50 cm). The number of daily ET_a measurements, acquired from March 2019 to September 2021, resulted in about 70% of the total days of the period; the missing data were caused by the malfunctioning of installed instruments, which occurred during the lockdown restrictions caused by the pandemic.

Among the different ML algorithms, the best performance was associated with the Gaussian Process Regression (GPR) based on nonparametric kernel probabilistic function (Rasmussen, 2006) when, with the other input variables, the average soil water content was included; in this case, the values of root mean square error (RMSE) and determination coefficient (R²) associated with the cross-validation resulted equal to 0.42 mm/d and 0.85, respectively. However, suitable results were also associated with the GPR model, when assuming, as input variables, on-site meteorological data and VIs (RMSE=0.49 mm/d and R²=0.78), or when considering the ERA5-Land meteorological variables (RMSE=0.56 mm/d and R²=0.73). The joint use of agro-meteorological and remote sensing data, associated with a GPR model, can therefore provide the opportunity to fill the gaps of ETa time-series.

How to cite: Ippolito, M., De Caro, D., and Provenzano, G.: Assessing Machine Learning algorithms to fill gaps of daily evapotranspiration measured in a citrus orchard using a combination of agro-meteorological and remote sensing data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3533, https://doi.org/10.5194/egusphere-egu22-3533, 2022.

This study is focused on fluxes of water and energy associated with the plant transpiration in a temperate montane forest of Central Europe. The research is based on the long-term monitoring of basic hydrological and meteorological variables at two adjacent forest sites, covered with Norway spruce and European beech. The analysis of the observed variables is combined with the numerical modeling of soil-plant hydraulics.

Among the monitored variables, sap flow in tree xylem is measured continuously by thermal dissipation probes. Soil water pressure and soil water content are monitored by tensiometers and FDR sensors at several depths. Catchment discharge observations, reflecting the subsurface responses to major rainfall events, are used together with the soil water content data to provide the relevant information on the catchment water balance, which constrains the long-term cumulative transpiration amount.

A one-dimensional soil water flow model, involving vertically distributed macroscopic root water uptake and whole-plant hydraulic capacitance algorithm to account for the transient xylem water storage, is used to simulate the temporal variations of water fluxes in the soil-plant-atmosphere system.

The observed sap flow rates are compared with the simulated transpiration fluxes. A particular attention is paid to the different behavior of spruce and beech trees during periods with extreme transpiration demand (summer midday conditions). The results of the comparisons confirm the expected isohydric response of spruce in contrast to a more anisohydric behavior of beech trees.

The comparison of the modeling results with the in-situ observations reveals a complex interplay of soil and plant hydraulic properties determining the specific responses of spruce and beech forest stands to the same weather conditions.

The research is supported by the Czech Science Foundation Project No. 20-00788S.

How to cite: Vogel, T., Skalova, V., Dohnal, M., Votrubova, J., and Tesar, M.: Measuring and modeling water fluxes across soil-plant-atmosphere continuum in a temperate forest environment, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10218, https://doi.org/10.5194/egusphere-egu22-10218, 2022.

Despite most macroscopic models for root water uptake considering root length density (RLD) to describe root water uptake (RWU) distribution, there are numerous studies demonstrating inconsistencies between soil water content profile and RLD that can be attributed to the inability of some roots to extract water. In fact, the physical relationship between RWU and the root system ignores the hydraulic characteristics of the root. To cope with this rigid assumption, the activity of a root system can be defined as the portion of the root system extracting majority of soil water. Root water uptake activity depends on the hydraulic head gradient between root-soil interface and xylem and on root segment conductance, which are terms not considered in macroscopic models. Therefore, both soil and root hydraulic properties are critical in determining RWU activity. Yet, in real root systems, active root fraction is continuously changing due to root development, root adaptation and soil moisture heterogeneity, which are not possible to be assessed considering the currently available experimental facilities. Therefore, our aim in this study is threefold: (1) establish a theoretical framework to investigate root water uptake activity; (2) Investigate with 0D hydraulic architecture model and 3D architectural soil-root water flow model to estimate the active root fraction and to find the effective parameters on active root fraction and finally (3) demonstrate and provide orders of magnitude of active root fraction for real situations. The initial results showed that RWU activity for a single segment depends on radial hydraulic conductivity distribution if xylem conductance is not limiting. The active fraction of the root for fibrous and taproot systems at different ages with their realistic root hydraulic properties was investigated under equilibrium and realistic soil water potential and compared with some existing values in literature. The simulated active root fraction and obtained ones from the previous studies rarely exceed 30% of the whole root system. The active root fraction is therefore an important factor to know and characterize to properly estimate soil resistance and stress onset.

How to cite: Javaux, M. and Mehmandoostkotlar, A.: Root activity for water uptake: a hydraulic approach, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10372, https://doi.org/10.5194/egusphere-egu22-10372, 2022.

Forest dieback can be both a consequence and a cause of climate change. The changing climate does not only lead to temperature increases but also changes in the precipitation regime. Extreme events have increased sharply in recent years, making drought and heat waves ubiquitous. Meanwhile, for temperate forests, drought stress is considered one of the most serious impacts of climate change. In this context, forest soils are of great importance in their hydrological functions, as well as their feedbacks with ground vegetation. In this context, biological soil crusts are key drivers of functional processes and ecosystem development, also under forest, where they have been less studied so far. Bryophyte and lichen dominated communities can importantly affect e.g. water storage and discharge as well as soil development and stabilization. Moreover, they contribute to carbon and nitrogen cycling and play an important role in biogeochemical processes. Their species composition depends on soil properties such as texture and pH, on microclimate and as poikilohydric plants, their ecophysiology is strongly dependent on water availability, differing in time and space.

For a better understanding of ecohydrological and soil stabilizing functions of biological soil crusts within forest ecosystems, their spatial and temporal activity needs to be linked with microclimate and monitored continuously in the field. Therefore, we investigate the microclimatic conditions and activity of bryophyte-lichen-dominated biological soil crusts on sandy soils in Linde, Brandenburg and silty-clayey soils in the Schönbuch Nature Park, Baden-Württemberg, Germany. Water regimes within mosses and substrates are continuously determined with a novel biocrust wetness probe (BWP). Moreover, the interactions between mosses and soils are investigated in infiltration boxes with cultivated moss species. It could be shown so far, that moss-dominated biological soil crusts decrease infiltration and soil water availability in the dry sandy soils in Brandenburg and further comparative investigations will now be processed. We thus contribute to the study of effects of bryophyte-lichen communities on soil water retention, soil structure, with a focus on drought resistance of forest stands, as well as soil development at disturbance sites in temperate forest ecosystems.

How to cite: Seitz, S. and Veste, M.: Bryophyte-lichens dominated biological soil crusts affect soils and ecohydrology in temperate forests in Germany, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12352, https://doi.org/10.5194/egusphere-egu22-12352, 2022.

Plants play an important role in regulating the land-atmosphere water and carbon flux through stomata control. To avoid excess water loss, the stomatal conductance is reduced during low soil water availability or high water demand from the atmosphere. Atmospheric evaporative demand is projected to increase through an increase in vapour pressure deficit (VPD) in response to global warming. Stomatal conductance models used in earth system models often rely on empirical parameters. However, since VPD and soil moisture content often are correlated, it can be difficult to disentangle the effect of each driver in studies using field data. In this study, we evaluate the effect of VPD and soil moisture on stomatal conductance independently by conducting an experiment in controlled growth conditions. In the experiment, we will subject groups of dwarf birch (Betula nana) to increasing VPD in both well-watered and drying soil conditions and measure the effect on stomatal conductance and leaf scale water and carbon gas exchange. Dwarf birch is selected as it is widespread in high latitutes and our study focuses on land-atmosphere exchange in this region. The experimental design allows us to evaluate existing parametrizations of stomatal conductance and test hypotheses on how sensitive the parameters are to drought history.  The experiment will provide important knowledge on how to improve parameterization of water and carbon exchange in high latitude ecosystems. This presentation will show the first results of the experiment. This work is a contribution to the Strategic Research Initiative ‘Land Atmosphere Interaction in Cold Environments’ (LATICE) of the University of Oslo and the EMERALD research project.  

How to cite: Vatne, A., Vollsnes, A. V., Pirk, N., and Tallaksen, L. M.: Parameterization of Stomatal Conductance in a Subarctic Deciduous Shrub, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11346, https://doi.org/10.5194/egusphere-egu22-11346, 2022.

A new insight in root growth dynamics is presented in this study, where pictures of root growth were taken with personal mobile phones and analysed by the machine learning based program RootPainter (Smith et al. 2020). Todays’ smartphones provide high-quality photos and user-friendly free software enables rapid processing of these images. We aimed to explore 1) how accurate the results are of the deep learning segmentation models created for assessing root growth, 2) how the changes in relative air humidity and dominating soil nitrogen source and their interactions influence root growth.
Picea abies trees were grown separately in transparent boxes in growth chambers in moderate or elevated air humidity and on nitrate or ammonium soil source. The pictures of roots were made from each side of boxes every week, together six sessions. The pictures were analysed with RootPainter twice, one where total root projection area was measured, second with only young white roots.
The total root growth was highest in trees growing in moderate air humidity and on ammonium source, lowest in elevated air humidity grown on nitrate source, 9.4 ± 1.9 and 3.9 ± 0.6 cm2, respectively. The young root projection area was highest in the beginning of experiment, and was affected by the soil nitrogen source. The amount of lignified roots increased over time and was affected by the air humidity treatment. The F measure was 0.88, when we compared a subset of automatically measured pictures to manually annotated pictures. We will further discuss about the magnitude of the errors 1) where the program identified “root as soil” and “soil as root”, and 2) where the root projection area of young roots was greater than the total root projection area. We did not discover treatment-specific bias in our error measurements. We conclude that the combination of smartphone images and RootPainter gives accurate and reliable results and is easy to use in plant growth manipulation experiments in the future.

Smith AG, Han E, Petersen J, Olsen NAF, Giese C, Athmann M, Dresbøll DB, Thorup-Kristensen K. 2020. RootPainter: Deep learning segmentation of biological images with corrective annotation. bioRxiv, doi:10.1101/2020.04.16.044461

How to cite: Sell, M., Smith, A. G., Burdun, I., Rohula-Okunev, G., Kupper, P., and Ostonen, I.: Application of deep learning segmentation techniques in smartphone images to assess growth of fine roots of spruce seedlings manipulated by air humidity and soil nitrogen source, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12379, https://doi.org/10.5194/egusphere-egu22-12379, 2022.

Root exudates alter the rhizosphere’s physical properties, but the impact these changes have on solute transport is largely unknown. Additionally, root exudates enhance the microbial activity in soil, which may further change the rhizosphere’s physical properties, including solute transport. In this study, we tested the effects of chia mucilage and wheat root exudates on the transport of iodide in saturated soil. Solute breakthrough experiments, conducted in loamy sand soil or coarser textured quartz sand, revealed that increasing the exudate concentration in soil resulted in non-equilibrium solute transport. This behavior was demonstrated by an initial solute breakthrough after fewer pore volumes and the arrival of the peak solute concentration after greater pore volumes in soil mixed with exudates compared to soil without exudates. These patterns were more pronounced for the coarser textured quartz sand than for the loamy sand soil and in soil mixed with mucilage than in soil mixed wheat root exudates. Parameter fits to these breakthrough curves with a mobile-immobile transport model indicated the fraction of immobile water increased as the concentration of exudates increased. For example, in quartz sand, the estimated immobile fraction increased from 0 without exudates to 0.75 at a mucilage concentration of 0.2%. Saturated breakthrough experiments were also conducted in a loamy sand soil mixed with mucilage and incubated at 25 ºC for different time periods of up to 28 days. In this set of experiments, mucilage at a concentration of 0.2% in the soil had no effect on the iodide breakthrough curve prior to soil incubation, while 0.4% mucilage concentration altered the transport pattern (as described above), and its breakthrough curve pattern remained stable for the entire incubation period. However, after a 7-day incubation period, the breakthrough curve of soil with 0.2% mucilage concentration was also altered, again showing earlier breakthrough and later arrival of the peak iodide concentration compared to the breakthrough curve before incubation. This breakthrough pattern persisted for the remainder of the incubation period. The results of this study indicate that root exudates alter the rhizosphere’s transport properties and that enhanced microbial activity following root exudation may further affect solute transport. We hypothesize that this is due to exudates creating low-conducting flow paths that result in a physical non-equilibrium solute transport. Additionally, we hypothesize that enhanced microbial activity following root exudation results in secretion of extracellular polymeric substances and generation of biofilm that further affect the flow paths in soil, thus potentially altering solute transport in the rhizosphere with time.   

How to cite: Paporisch, A., Bavli, H., Strickman, R. J., Neumann, R. B., and Schwartz, N.: The Co-Effect of Root Exudates and Incubation Time on Solute Transport in the Rhizosphere, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12979, https://doi.org/10.5194/egusphere-egu22-12979, 2022.