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Background: Hospital infections with SARS-CoV-2 continued during the initial waves of the pandemic worldwide. So far, Data on the dynamics of these infections and the economic burden of outbreaks are rare. Methods: We retrospectively analysed SARS-CoV-2 infections in patients, hospital employees and nosocomial infections resulting in outbreaks in two hospitals of a secondary care hospital network in Germany during the initial 3 pandemic waves (03/2020–06/2021). In addition to hospital infections, we evaluated infection prevention strategies and the economic burden of hospital outbreaks. Results: A total of 396 patients with SARS-CoV-2 infection were hospitalized in both hospitals. The risk factors for severe disease and death increased with age, male sex and a CRB-65 score > 0. The most frequent symptom was dyspnoea (30.1%). Sixty-five patients died, most of whom were in the 2nd wave. A total of 182 (12.5%) hospital employees were infected, 63 (34.6%) of whom were involved in outbreaks. An occupational risk of infection during outbreaks was particularly common among nurses and HCWs working on regular wards. Eleven hospital outbreaks led to high economic impact on both hospitals through the loss of manpower as result of infected employees, temporary locked wards, blocked beds, a reduced number of total hospitalized patients and increased personnel costs. Conclusion: Continuously adaptation of infection prevention strategies is a valuable tool to keep hospitals safe places for patients and employees. We do need more analyses of the different pandemic waves and applied infection prevention strategies to learn from weak points. Trial registration: This research was conducted in accordance with the Declaration of Helsinki and national standards. The study protocol was approved by the relevant ethics committee of the Chamber of Physicians Westphalia-Lippe and University of Münster (no. 2021–475-f-S). The study was registered on 25th August 2021 at the German Clinical Trials Register (DRKS00025865). [ABSTRACT FROM AUTHOR]

Climate warming and associated accelerated permafrost thaw in the Arctic lead to a shift in landscape patterns, hydrologic conditions, and release of carbon. In this context, the lateral transport of carbon and shifts therein following thaw remain poorly understood. Crucial hydrologic factors affecting the lateral distribution of carbon include the depth of the saturated zone above the permafrost table with respect to changes in water table and thaw depth and the connectivity of water-saturated zones. Landscape conditions are expected to change in the future due to rising temperatures and polygonal or flat floodplain Arctic tundra areas in various states of degradation; hydrologic conditions will also change. This study is focused on an experimental site near Chersky, northeast Siberia, where a drainage ditch was constructed in 2004 to simulate landscape degradation features that result in drier soil conditions and channeled water flow. We compared water levels and thaw depths in the drained area (dry soil conditions) with those in an adjacent control area (wet soil conditions). We also identified the sources of water at the site via stable water isotope analysis. We found substantial spatiotemporal changes in the water conditions at the drained site: (i) lower water tables resulting in drier soil conditions, (ii) quicker water flow through drier areas, (iii) larger saturation zones in wetter areas, and (iv) a higher proportion of permafrost meltwater in the liquid phase towards the end of the growing season. These findings suggest decreased lateral connectivity throughout the drained area. Shifts in hydraulic connectivity in combination with a shift in vegetation abundance and water sources may impact carbon sources and sinks as well as transport pathways. Identifying lateral transport patterns in areas with degrading permafrost is therefore crucial. [ABSTRACT FROM AUTHOR]

It is known from arid and semi-arid ecosystems that atmospheric water vapor can directly be adsorbed by the soil matrix. Soil water vapor adsorption was typically neglected and only recently received attention because of improvements in measurement techniques. One technique rarely explored for the measurement of soil water vapor adsorption is eddy covariance (EC). Soil water vapor adsorption may be detectable as downwardly directed (i.e., negative) EC latent heat (λE) flux measurements under dry conditions, but a systematic assessment of the use of negative λE fluxes from EC flux stations to characterize adsorption is missing. We propose a classification method to characterize soil water vapor adsorption, excluding conditions of dew and fog when λE derived from EC is not trustworthy due to stable atmospheric conditions. We compare downwardly directed λE fluxes from EC with measurements from weighing lysimeters for 4 years in a Mediterranean savanna ecosystem and 3 years in a temperate agricultural site. Our aim is to assess if overnight water inputs from soil water vapor adsorption differ between ecosystems and how well they are detectable by EC. At the Mediterranean site, the lysimeters measured soil water vapor adsorption each summer, whereas at the temperate site, soil water vapor adsorption was much rarer and was measured predominantly under an extreme drought event in 2018. During 30 % of nights in the 4-year measurement period at the Mediterranean site, the EC technique detected downwardly directed λE fluxes of which 88.8 % were confirmed to be soil water vapor adsorption by at least one lysimeter. At the temperate site, downwardly directed λE fluxes were only recorded during 15 % of the nights, with only 36.8 % of half hours matching simultaneous lysimeter measurement of soil water vapor adsorption. This relationship slightly improved to 61 % under bare-soil conditions and extreme droughts. This underlines that soil water vapor adsorption is likely a much more relevant process in arid ecosystems compared to temperate ones and that the EC method was able to capture this difference. The comparisons of the amounts of soil water vapor adsorption between the two methods revealed a substantial underestimation of the EC compared to the lysimeters. This underestimation was, however, comparable with the underestimation in evaporation by the eddy covariance and improved in conditions of higher turbulence. Based on a random-forest-based feature selection, we found the mismatch between the methods being dominantly related to the site's inherent variability in soil conditions, namely soil water status, and soil (surface) temperature. We further demonstrate that although the water flux is very small with mean values of 0.04 or 0.06 mm per night for EC or lysimeter, respectively, it can be a substantial fraction of the diel soil water balance under dry conditions. Although the two instruments substantially differ with regard to the measured ratio of adsorption to evaporation over 24 h with 64 % and 25 % for the lysimeter and EC methods, they are in either case substantial. Given the usefulness of EC for detecting soil water vapor adsorption as demonstrated here, there is potential for investigating adsorption in more climate regions thanks to the greater abundance of EC measurements compared to lysimeter observations. [ABSTRACT FROM AUTHOR]

Root water uptake depends on soil moisture which is primarily fed by throughfall in forests. Several biotic and abiotic elements shape the spatial distribution of throughfall. It is well documented that throughfall patterns result in reoccurring higher and lower water inputs at certain locations. However, how the spatial distribution of throughfall affects root water uptake patterns remains unresolved. Therefore, we investigate root water uptake patterns by considering spatial patterns of throughfall and soil water in addition to soil and neighboring tree characteristics. In a beech-dominated mixed deciduous forest in a temperate climate, we conducted intensive throughfall sampling at locations paired with soil moisture sensors during the 2019 growing season. We employed a linear mixed-effects model to understand controlling factors in root water uptake patterns. Our results show that soil water patterns and interactions among neighboring trees are the most significant factors regulating root water uptake patterns. Temporally stable throughfall patterns did not influence root water uptake patterns. Similarly, soil properties were unimportant for spatial patterns of root water uptake. We found that wetter locations (rarely associated with throughfall hotspots) promoted greater root water uptake. Root water uptake in monitored soil layers also increased with neighborhood species richness. Ultimately our findings suggest that complementarity mechanisms within the forest stand, in addition to soil water variability and availability, govern root water uptake patterns. [ABSTRACT FROM AUTHOR]

Spatially distributed properties of the subsurface result in varying water saturation and preferential flow paths, which lead to heterogeneous solute transport patterns and heterogeneous microbial environments. This, in turn, influences the distribution of nutrients and energy gradients, microbial biomass, and activity thereof. By their very nature, current field sampling techniques do not resolve subsampling scale heterogeneities in microbial biomass and activity, resulting in inaccurate estimates of microbially mediated carbon and nitrogen turnover in the heterogeneous subsurface. Thus, in this study, we undertook a numerical modeling approach to study the impact of spatial heterogeneity on microbially mediated carbon and nitrogen turnover in the vadose zone. We adapted an established biogeochemical process network that captures a variety of respiration pathways, carbon decomposition strategies, and microbial life processes to simulate microbially mediated carbon and nitrogen turnover in variably saturated spatially heterogeneous settings, using an established numerical tool (OGS#BRNS). The fractionation of microbial communities into active and inactive states, as well as immobile and mobile states followed could be linked to the bulk average saturation. Lastly, we identified three reactive systems, distinguished by the rate ratio of aerobic respiration and transfer of oxygen from the air to the water phase, to evaluate the impact of spatial heterogeneity on carbon and nitrogen removal in subsurface heterogeneous domains. Specifically, when this ratio is approximately 1, there is no impact on carbon removal, while when this ratio is very high, then carbon removal decreases as the domain tends to be oxygen limited. Core Ideas: Spatial heterogeneity leads to spatial variation of saturation in the vadose zone.Spatial heterogeneity leads to variation in the distribution of nutrients in the subsurface.The saturation and flow regime of a subsurface system influence the play‐off between respiration and aeration.Aeration may cause a homogenization effect in spatially heterogeneous domains.The location and activity of microbes can be predicted using average saturation and flow regime. [ABSTRACT FROM AUTHOR]

It is known from arid and semi-arid ecosystems that atmospheric water vapor is directly adsorbed by the soil matrix during the night. Soil water vapor adsorption was typically neglected and only recently got attention because of improvements in measurement techniques. One technique rarely explored is eddy covariance (EC). EC nighttime measurements are usually discarded, but soil water vapor adsorption may be detectable as downwards-directed EC latent heat (λ E) flux measurements under dry conditions. We propose a classification method to exclude conditions of dew and fog when λ E derived from EC is not trustworthy due to stable atmospheric conditions. We compare downwards-directed λ E fluxes from EC with measurements from weighable lysimeters for four years in a Mediterranean Savannah ecosystem and three years in a temperate agricultural site. Our aim is to assess if overnight water inputs from soil water vapor adsorption differ between ecosystems and how well they are detectable by EC. At the Mediterranean site, the lysimeters measured soil water vapor adsorption each summer whereas at the temperate site soil water vapor adsorption was much rarer, and measured predominantly under extreme drought. In 30 % of nights in the four-year measurement period at the Mediterranean site, the EC technique detected downward-directed λ E fluxes of which 88.8 % were confirmed to be soil water vapor adsorption by at least one lysimeter. At the temperate site, downward-directed λ E fluxes were only recorded during 15 % of the nights, with only 36.8 % of half-hours matching simultaneous lysimeter measurement of soil water vapor adsorption. Although this relationship slightly improved to 60% under bare soil conditions and extreme droughts, this underlines that soil water vapor adsorption is likely a much more relevant process in arid ecosystems compared to temperate ones and that the EC method was able to capture this difference. The comparisons of the magnitudes between the two methods revealed a substantial underestimation of soil water vapor adsorption with EC. This underestimation was, however, on par with the underestimation in evaporation. Based on a random forest-based feature selection we found the mismatch between the techniques being dominantly related to the site's inherent spatiotemporal variations in soil conditions, namely soil water status, and soil (surface) temperature. We further demonstrate that although the water flux is very small with mean values of 0.04 or 0.06 mm per night depending on either EC or lysimeter detection it can be a substantial fraction of the diel soil water balance under dry conditions. Although the two instruments substantially differ with regard to the evaporative fraction with 64% and 25% for the lysimeter and EC methods, they are in either case substantial. Given the usefulness of EC for detecting soil water vapor adsorption as demonstrated here, there is potential for investigating adsorption in more climate regions at longer timescales thanks to the greater abundance of EC measurements compared to lysimeter observations. [ABSTRACT FROM AUTHOR]

Climate warming and associated accelerated permafrost thaw in the Arctic lead to a shift in landscape patterns, hydrologic conditions and release of carbon. In this context, the lateral transport of carbon, and shifts therein following thaw, remain poorly understood. Crucial hydrologic factors affecting the lateral distribution of carbon include e.g., the depth of the saturated zone above the ice table with respect to changes in water table and thaw depth, and the connectivity of water saturated zones. With changing landscape conditions due to rising temperatures, polygonal or flat floodplain Arctic tundra areas in various states of degradation are expected to become more common in the future, with associated changes in hydrologic conditions. This study centers in an experimental site near Chersky, Northeast Siberia, where a drainage ditch was constructed in 2004 reflecting landscape degradation features that result in drier soil conditions and channeled water flow. We characterized and compared the drained area (dry soil conditions) with an adjacent control area (wet soil conditions) with regard to water levels and thaw depths. We also identified the sources of water at the site via stable water isotope analysis. We found substantial spatiotemporal changes in the water conditions at the drained site: i) lower water tables resulting in drier soil conditions, ii) quicker water flow in drier areas, iii) larger saturation zones in wet areas, and iv) a higher proportion of permafrost melt water in the liquid phase towards the end of the growing season. These findings suggest a decreased lateral connectivity throughout the drained area. Shifts in hydraulic connectivity associated with a shift in vegetation abundance and water sources may impact carbon sources, sinks as well as its transport pathways. Identifying lateral transport patterns in areas with degrading permafrost are therefore of major relevance. [ABSTRACT FROM AUTHOR]

Land-surface models represent exchange processes between soil and atmosphere via the surface by coupling water, energy and carbon fluxes. As it strongly mediates the link between these cycles and, vegetation is an important component of land-surface models. In doing so, some of these models include modules for vegetation dynamics which allow adaptation of vegetation biomass, especially leaf area index, to environmental conditions. Here, we conducted a model-data comparison to investigate whether and how vegetation dynamics in the models improves the representation of vegetation processes and related surface fluxes in two specific models ECLand and Noah-MP in contrast to using prescribed values from look-up tables or satellite-based products. We compare model results with stations from the FLUXNET 2015 dataset covering a range in climate and vegetation types, the MODIS leaf area product, and use more detailed information from the TERENO site "Hohes Holz'. With the current implementation, switching vegetation dynamics on did not enhance representativeness of e.g. leaf area index and net ecosystem exchange in ECLand, while Noah-MP improved it only for some sites. The representation of energy fluxes and soil moisture was almost unaffected for both models. Interestingly, for both models, the performance regarding vegetation- and hydrology-related variables was unrelated, such that the weak performance regarding e.g. leaf area index did not detoriate the performance regarding e.g. latent heat flux. One reason, we showed here, might be that implemented ecosystem processes diverge from the observations in their seasonal patterns and variability. Noah-MP includes a seasonal hysteresis of the relationship between leaf area index and gross primary production that cannot be found in observations. The same relationship is represented by a strong linear response in ECLand which substantially underestimates the variability seen in observations. For both, water and carbon fluxes, the current implemented modules for vegetation dynamics in these two models yielded no better model performance compared to runs with static vegetation and prescribed leaf-area climatology. [ABSTRACT FROM AUTHOR]

Land-surface models represent exchange processes between soil and atmosphere via the surface by coupling water, energy and carbon fluxes. As it strongly mediates the link between these cycles and, vegetation is an important component of land-surface models. In doing so, some of these models include modules for vegetation dynamics which allow adaptation of vegetation biomass, especially leaf area index, to environmental conditions. Here, we conducted a model-data comparison to investigate whether and how vegetation dynamics in the models improves the representation of vegetation processes and related surface fluxes in two specific models ECLand and Noah-MP in contrast to using prescribed values from look-up tables or satellite-based products. We compare model results with stations from the FLUXNET 2015 dataset covering a range in climate and vegetation types, the MODIS leaf area product, and use more detailed information from the TERENO site "Hohes Holz". With the current implementation, switching vegetation dynamics on did not enhance representativeness of e.g. leaf area index and net ecosystem exchange in ECLand, while Noah-MP improved it only for some sites. The representation of energy fluxes and soil moisture was almost unaffected for both models. Interestingly, for both models, the performance regarding vegetation- and hydrology-related variables was unrelated, such that the weak performance regarding e.g. leaf area index did not detoriate the performance regarding e.g. latent heat flux. One reason, we showed here, might be that implemented ecosystem processes diverge from the observations in their seasonal patterns and variability. Noah-MP includes a seasonal hysteresis of the relationship between leaf area index and gross primary production that cannot be found in observations. The same relationship is represented by a strong linear response in ECLand which substantially underestimates the variability seen in observations. For both, water and carbon fluxes, the current implemented modules for vegetation dynamics in these two models yielded no better model performance compared to runs with static vegetation and prescribed leaf-area climatology. [ABSTRACT FROM AUTHOR]

Throughfall heterogeneity induced by the redistribution of precipitation in vegetation canopies has repeatedly been hypothesized to affect the variation in the soil water content and runoff behavior, especially in forests. However, observational studies relating the spatial variation in the soil water content directly to net precipitation are rare, and few confirm modeling hypotheses. Here, we investigate whether throughfall patterns affect the spatial heterogeneity in the soil water response in the main rooting zone. We assessed rainfall, throughfall and soil water content (at two depths, 7.5 and 27.5 cm) on a 1 ha temperate mixed-beech forest plot in Germany during the 2015 and 2016 growing seasons using independent, high-resolution, stratified, random designs. Because the throughfall and soil water content cannot be measured at the same location, we used kriging to derive the throughfall values at the locations where the soil water content was measured. We first explored the spatial variation and temporal stability of throughfall and soil water patterns and subsequently evaluated the effects of input (throughfall), soil properties (field capacity and macroporosity), and vegetation parameters (canopy cover and distance to the next tree) on the soil water content and dynamics. Throughfall spatial patterns were related to canopy density. Although spatial autocorrelation decreased with increasing event sizes, temporally stable throughfall patterns emerged, leading to reoccurring higher- and lower-input locations across precipitation events. Linear mixed-effects model analysis showed that soil water content patterns were poorly related to spatial patterns of throughfall and that they were more influenced by unidentified, but time constant, factors. Instead of the soil water content itself, the patterns of its increase after rainfall corresponded more closely to throughfall patterns: more water was stored in the soil in areas where throughfall was elevated. Furthermore, soil moisture patterns themselves affected the local soil water response, probably by mediating fast drainage and runoff. Locations with a low topsoil water content tended to store less of the input water, indicating preferential flow. In contrast, locations with a high water content stored less water in the subsoil. Moreover, the distance to the next tree and macroporosity modified how much water was retained in soil storage. Overall, throughfall patterns imprinted less on the soil water content and more on the soil water dynamics shortly after rainfall events; therefore, percolation rather than the soil water content may depend on the small-scale spatial heterogeneity in canopy input patterns. [ABSTRACT FROM AUTHOR]

Forests play a major role in the global carbon cycle, and droughts have been shown to explain much of the interannual variability in the terrestrial carbon sink capacity. The quantification of drought legacy effects on ecosystem carbon fluxes is a challenging task, and research on the ecosystem scale remains sparse. In this study we investigate the delayed response of an extreme drought event on the carbon cycle in the mixed deciduous forest site 'Hohes Holz' (DE-HoH) located in Central Germany, using the measurements taken between 2015 and 2020. Our analysis demonstrates that the extreme drought and heat event in 2018 had strong legacy effects on the carbon cycle in 2019, but not in 2020. On an annual basis, net ecosystem productivity was ∼ 16 % higher in 2018 ( ∼ 424 g C m - 2 ) and ∼ 25 % lower in 2019 ( ∼ 274 g C m - 2 ) compared to pre-drought years ( ∼ 367 g C m - 2 ). Using spline regression, we show that while current hydrometeorological conditions can explain forest productivity in 2020, they do not fully explain the decrease in productivity in 2019. Including long-term drought information in the statistical model reduces overestimation error of productivity in 2019 by nearly 50 % . We also found that short-term drought events have positive impacts on the carbon cycle at the beginning of the vegetation season, but negative impacts in later summer, while long-term drought events have generally negative impacts throughout the growing season. Overall, our findings highlight the importance of considering the diverse and complex impacts of extreme events on ecosystem fluxes, including the timing, temporal scale, and magnitude of the events, and the need to use consistent definitions of drought to clearly convey immediate and delayed responses. [ABSTRACT FROM AUTHOR]

Eddy covariance sites are ideally suited for the study of extreme events on ecosystems as they allow the exchange of trace gases and energy fluxes between ecosystems and the lower atmosphere to be directly measured on a continuous basis. However, standardized definitions of hydroclimatic extremes are needed to render studies of extreme events comparable across sites. This requires longer datasets than are available from on-site measurements in order to capture the full range of climatic variability. We present a dataset of drought indices based on precipitation (Standardized Precipitation Index, SPI), atmospheric water balance (Standardized Precipitation Evapotranspiration Index, SPEI), and soil moisture (Standardized Soil Moisture Index, SSMI) for 101 ecosystem sites from the Integrated Carbon Observation System (ICOS) with daily temporal resolution from 1950 to 2021. Additionally, we provide simulated soil moisture and evapotranspiration for each site from the Mesoscale Hydrological Model (mHM). These could be utilised for gap-filling or long-term research, among other applications. We validate our data set with measurements from ICOS and discuss potential research avenues. [ABSTRACT FROM AUTHOR]

Throughfall is the largest source of water entering the soil in forests, and its spatial distribution depends on several biotic and abiotic factors. It is well documented that the distribution of throughfall results in reoccurring higher and lower water inputs at certain locations. However, the role of horizontal root water uptake patterns in understanding the effects of throughfall patterns on subsurface water dynamics remains unresolved. Therefore, here we investigate root water uptake patterns by considering spatial patterns of throughfall and soil water patterns in addition to soil and neighboring tree characteristics. In a beech- dominated mixed deciduous forest in a temperate climate, we conducted weekly intensive throughfall sampling at locations paired with soil moisture sensors during the 2019 growing season. We employed a linear mixed effects model to understand controlling factors for root water uptake patterns. Our results show that soil water patterns and interactions among neighbouring trees are the most significant factors regulating root water uptake patterns. Temporally stable throughfall patterns did not influence root water uptake patterns. Similarly, soil properties were unimportant for spatial patterns of root water uptake. We found that wetter locations (rarely associated with throughfall hotspots) promoted greater root water uptake. Root water uptake in monitored soil layers also increased with neighbourhood species richness. Ultimately our findings suggest that complementarity mechanisms within the forest stand, in addition to soil water variability and availability, govern root water uptake patterns. [ABSTRACT FROM AUTHOR]

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Throughfall heterogeneity induced by the redistribution of precipitation in vegetation canopies has repeatedly been hypothesized to affect the variation of soil water content and runoff behavior, especially in forests. However, we are not aware of any observational study relating the spatial variation of soil water content directly to net precipitation to confirm modelling hypotheses. Here, we investigate whether throughfall patterns affect the spatial heterogeneity of soil water response in the main rooting zone. We assessed rainfall, throughfall and soil water contents (two depths: 7.5 cm and 27.5 cm) on a 1-ha temperate mixed beech forest plot in Germany 2015 - 2016 during the growing seasons in independent high-resolution stratified random designs. Because throughfall and soil water content cannot be measured at the same location, we used kriging to derive the throughfall values at the locations where soil water content was measured. We first explore the spatial variation and temporal stability of throughfall and soil water patterns, and next evaluate the effects of input (throughfall), soil properties (field capacity and air capacity), and vegetation parameters (canopy cover and distance to the next tree) on soil water content and dynamics. Throughfall spatial patterns were related to canopy density. Although spatial auto-correlation decreased with increasing event sizes, temporally stable throughfall patterns emerged, leading to reoccurring high and lower input locations across precipitation events. A linear mixed effect model analysis showed, that soil water content patterns were only poorly linked to throughfall spatial patterns, and it was rather shaped by unidentified but time constant factors. Instead of soil water content itself, the patterns of its increase after rainfall corresponded more closely to throughfall patterns, in that more water was stored in the soil where throughfall was elevated. Furthermore, soil moisture patterns themselves enhanced or decreased water storage in the soil, and probably fast drainage and runoff components. Locations with low topsoil water content tended to store less of the input water, indicating preferential flow. In contrast in subsoil, locations with high water content stored less water. Also, distance to the next tree and air capacity modified how much water was retained in soil storage. In this comprehensive study we show that throughfall patterns imprint less on soil water contents and more on soil water dynamics shortly after rainfall events, therefore only partly confirming previous modelling with data. Our findings highlight at the same time systematic patterns of times and locations where the capacity to store water is reduced and water probably conducted quickly to greater depth. Our results indicate that not soil moisture patterns but rather percolation may depend on small scale spatial heterogeneity of canopy input patterns. [ABSTRACT FROM AUTHOR]

Sap flow encodes information about how plants regulate the opening and closing of stomata in response to varying soil water supply and atmospheric water demand. This study leverages this valuable information with model–data integration and deep learning to estimate canopy conductance in a hybrid catchment-scale model for more accurate hydrological simulations. Using data from three consecutive growing seasons, we first highlight that integrating canopy conductance inferred from sap flow data in a hydrological model leads to more realistic soil moisture estimates than using the conventional Jarvis–Stewart equation, particularly during drought conditions. The applicability of this first approach is, however, limited to the period where sap flow data are available. To overcome this limitation, we subsequently train a recurrent neural network (RNN) to predict catchment-averaged sap velocities based on standard hourly meteorological data. These simulated velocities are then used to estimate canopy conductance, allowing simulations for periods without sap flow data. We show that the hybrid model, which uses the canopy conductance from the machine learning (ML) approach, matches soil moisture and transpiration equally as well as model runs using observed sap flow data and has good potential for extrapolation beyond the study site. We conclude that such hybrid approaches open promising avenues for parametrizations of complex water–plant dynamics by improving our ability to incorporate novel or untypical data sets into hydrological models. [ABSTRACT FROM AUTHOR]

Germany's 2018–2020 consecutive drought events resulted in multiple sectors – including agriculture, forestry, water management, energy production, and transport – being impacted. High-resolution information systems are key to preparedness for such extreme drought events. This study evaluates the new setup of the one-kilometer German drought monitor (GDM), which is based on daily soil moisture (SM) simulations from the mesoscale hydrological model (mHM). The simulated SM is compared against a set of diverse observations from single profile measurements, spatially distributed sensor networks, cosmic-ray neutron stations, and lysimeters at 40 sites in Germany. Our results show that the agreement of simulated and observed SM dynamics in the upper soil (0–25 cm) are especially high in the vegetative active period (0.84 median correlation R) and lower in winter (0.59 median R). The lower agreement in winter results from methodological uncertainties in both simulations and observations. Moderate but significant improvements between the coarser 4 km resolution setup and the ≈ 1.2 km resolution GDM in the agreement to observed SM dynamics is observed in autumn (+ 0.07 median R) and winter (+ 0.12 median R). Both model setups display similar correlations to observations in the dry anomaly spectrum, with higher overall agreement of simulations to observations with a larger spatial footprint. The higher resolution of the second GDM version allows for a more detailed representation of the spatial variability of SM, which is particularly beneficial for local risk assessments. Furthermore, the results underline that nationwide drought information systems depend both on appropriate simulations of the water cycle and a broad, high-quality, observational soil moisture database. [ABSTRACT FROM AUTHOR]

Temperate forest ecosystems play a crucial role in governing global carbon and water cycles. However, unprecedented global warming presents fundamental alterations to the ecological functions (e.g., carbon uptake) and biophysical variables (e.g., leaf area index) of forests. The quantification of forest carbon uptake, gross primary productivity (GPP), as the largest carbon flux has a direct consequence on carbon budget estimations. Part of this assimilated carbon stored in leaf biomass is related to the leaf area index (LAI), which is closely linked to and is of critical significance in the water cycle. There already exist a number of models to simulate dynamics of LAI and GPP; however, the level of complexity, demanding data, and poorly known parameters often prohibit the model applicability over data-sparse and large domains. In addition, the complex mechanisms associated with coupling the terrestrial carbon and water cycles poses a major challenge for integrated assessments of interlinked processes (e.g., accounting for the temporal dynamics of LAI for improving water balance estimations and soil moisture availability for enhancing carbon balance estimations). In this study, we propose a parsimonious forest canopy model (PCM) to predict the daily dynamics of LAI and GPP with few required inputs, which would also be suitable for integration into state-of-the-art hydrologic models. The light use efficiency (LUE) concept, coupled with a phenology submodel, is central to PCM (v1.0). PCM estimates total assimilated carbon based on the efficiency of the conversion of absorbed photosynthetically active radiation into biomass. Equipped with the coupled phenology submodel, the total assimilated carbon partly converts to leaf biomass, from which prognostic and temperature-driven LAI is simulated. The model combines modules for the estimation of soil hydraulic parameters based on pedotransfer functions and vertically weighted soil moisture, considering the underground root distribution, when soil moisture data are available. We test the model on deciduous broad-leaved forest sites in Europe and North America, as selected from the FLUXNET network. We analyze the model's parameter sensitivity on the resulting GPP and LAI and identified, on average, 10 common sensitive parameters at each study site (e.g., LUE and SLA). The model's performance is evaluated in a validation period, using in situ measurements of GPP and LAI (when available) at eddy covariance flux towers. The model adequately captures the daily dynamics of observed GPP and LAI at each study site (Kling–Gupta efficiency, KGE, varies between 0.79 and 0.92). Finally, we investigate the cross-location transferability of model parameters and derive a compromise parameter set to be used across different sites. The model also showed robustness with the compromise single set of parameters, applicable to different sites, with an acceptable loss in model skill (on average ±8 %). Overall, in addition to the satisfactory performance of the PCM as a stand-alone canopy model, the parsimonious and modular structure of the developed PCM allows for a smooth incorporation of carbon modules to existing hydrologic models, thereby facilitating the seamless representation of coupled water and carbon cycle components, i.e., prognostic simulated vegetation leaf area index (LAI) would improve the representation of the water cycle components (i.e., evapotranspiration), while GPP predictions would benefit from the simulated soil water storage from a hydrologic model. [ABSTRACT FROM AUTHOR]

The input of liquid water to terrestrial ecosystems is composed of rain and non-rainfall water (NRW). The latter comprises dew, fog, and the adsorption of atmospheric vapor on soil particle surfaces. Although NRW inputs can be relevant to support ecosystem functioning in seasonally dry ecosystems, they are understudied, being relatively small, and therefore hard to measure. In this study, we apply a partitioning routine focusing on NRW inputs over 1 year of data from large, high-precision weighing lysimeters at a semi-arid Mediterranean site. NRW inputs occur for at least 3 h on 297 d (81 % of the year), with a mean diel duration of 6 h. They reflect a pronounced seasonality as modulated by environmental conditions (i.e., temperature and net radiation). During the wet season, both dew and fog dominate NRW, while during the dry season it is mostly the soil adsorption of atmospheric water vapor. Although NRW contributes only 7.4 % to the annual water input, NRW is the only water input to the ecosystem during 15 weeks, mainly in the dry season. Benefitting from the comprehensive set of measurements at our experimental site, we show that our findings are in line with (i) independent measurements and (ii) independent model simulations forced with (near-) surface energy and moisture measurements. Furthermore, we discuss the simultaneous occurrence of soil vapor adsorption and negative eddy-covariance-derived latent heat fluxes. This study shows that NRW inputs can be reliably detected through high-resolution weighing lysimeters and a few additional measurements. Their main occurrence during nighttime underlines the necessity to consider ecosystem water fluxes at a high temporal resolution and with 24 h coverage. [ABSTRACT FROM AUTHOR]

Canopies shape net precipitation patterns, which are spatially heterogeneous and control soil moisture response to rainfall. The vast majority of studies on canopy water fluxes were conducted in forests. In contrast, grassland canopies are often assumed to be spatially homogeneous, therefore likely not inducing patches of heterogeneity at and below the soil surface. However, some studies on short‐structured vegetation, such as grasslands, proposed the importance of canopy‐induced heterogeneity for net precipitation. Still, systematic investigations on the effects on soil wetting patterns are missing. Therefore, in this study, we investigated soil moisture response to rainfall in a managed temperate grassland by exploring the individual impacts of spatially varying throughfall, vegetation height, and antecedent soil moisture status on the soil wetting patterns. We applied linear mixed effects models to disentangle the role of grassland canopy versus abiotic drivers. The spatial average soil water response showed diminishing water amounts stored in the upper parts of the soil as the growing season progressed and the soils dried, indicating bypass flow. Spatial variation of grass height was a significant driver of soil wetting patterns along with precipitation and antecedent soil moisture status. Soil wetting was suppressed in locations with tall canopies, although surprisingly, this was not directly related to throughfall patterns. Instead, our results suggest that seasonally drier conditions and the spatial difference in grass development amplify fast flow processes. Ultimately, our results confirm that spatial variation of the canopy affects soil moisture wetting patterns not only in forests but indicate a strong influence of preferential flow on soil water patterns in managed grassland as well. [ABSTRACT FROM AUTHOR]

Temperate forest ecosystems play a crucial role in governing global carbon and water cycles. However, unprecedented global warming poses fundamental alterations to forest ecological functions (e.g. carbon uptake) and forest biophysical variables (e.g. leaf area index). Quantification of forest carbon uptake, gross primary productivity (GPP), as the largest carbon flux has a direct consequence on carbon budget estimations. Part of this assimilated carbon stored in leaf biomass is related to the leaf area index (LAI), which is of critical significance in and closely linked to water cycle. There already exist a number of models to simulate dynamics of LAI and GPP, however, the level of complexity, demanding data, and poorly known parameters often prohibit the model applicability over data-sparse and large domains. In addition, the complex mechanism associated with coupling the terrestrial carbon and water cycles poses a major challenge for integrated assessments of interlinked processes (e.g. accounting for temporal dynamic of LAI for improving water balance estimations and soil moisture availability for enhancing carbon balance estimations). In this study, we propose a parsimonious forest canopy model (PCM) to predict daily dynamics of LAI and GPP with few required input which is also suitable for integration into state-of-the-art hydrologic models. The light use efficiency (LUE) concept is central to PCM (v1.0), coupled with a phenology submodel. PCM estimates total assimilated carbon based on conversion efficiency of absorbed photosynthetically active radiation into biomass. Equipped with the coupled phenology submodel, the total assimilated carbon partly converts to leaf biomass from which prognostic and temperature-driven LAI is simulated. The model combines modules for estimation of soil hydraulic parameters based on the so-called pedotransfer functions and vertically weighted soil moisture considering the underground root distribution, when soil moisture data is available. We test the model on deciduous broad-leaved forest sites in Europe and North America selected from the FLUXNET network. We analyze the model parameter sensitivity on the resulting GPP and LAI and identified on average 10 common sensitive parameters at each study site (e.g., LUE, SLA, etc). Model performance is evaluated in a verification period using in situ measurements of GPP and LAI (when available) at eddy covariance flux towers. The model adequately captures the daily dynamics of observed GPP and LAI at each study site (Kling-Gupta-Efficiency; KGE varies between 0.79 and 0.92). Finally, we investigate the cross-location transferability of model parameters and derive a compromise parameter set to be used across different sites. The model also showed robustness with the compromise single set of parameters, applicable to different sites, with an acceptable loss in model skill (on average ± 8%). Overall, in addition to the satisfactory performance of the PCM as a stand-alone canopy model, the parsimonious and modular structure of the developed PCMallows for a smooth incorporation of carbon modules to existing hydrologic models. Thereby, it facilitates the seamless representation of coupled water and carbon cycle components, i.e. prognostic simulated vegetation leaf area index (LAI) would improve the representation of the water cycle components (e.g., evapotranspiration), while GPP predictions would benefit from simulated soil water storage from a hydrologic model. [ABSTRACT FROM AUTHOR]

Sap flow encodes information about how plants regulate opening and closing of stomata in response to varying soil water supply and atmospheric water demand. This study leverages this valuable information with data-model integration and deep learning to estimate canopy conductance in a hybrid catchment-scale model for more accurate hydrological simulations. Using data from three consecutive growing seasons, we first highlight that integrating canopy conductance inferred from sap flow data in a hydrological model leads to more realistic soil moisture estimates than using the conventional Jarvis-Stewart equation, particularly during drought conditions. The applicability of this first approach is, however, limited to the period where sap flow data are available. To overcome this limitation, we subsequently train a deep learning network to predict catchment-averaged sap velocities based on standard hourly meteorological data. These simulated velocities are then used to estimate canopy conductance, allowing simulations for periods without sap flow data. We show that the hybrid model, which uses the canopy conductance from the machine learning approach, matches soil moisture and transpiration equally well as model runs using observed sap flow data and has good potential for extrapolation beyond the study site. We conclude that such hybrid approaches open promising perspectives for more parsimonious process parametrizations by improving our ability to incorporate novel or untypical data sets into hydrological models. [ABSTRACT FROM AUTHOR]

The subsurface is a temporally dynamic and spatially heterogeneous compartment of the Earth's critical zone, and biogeochemical transformations taking place in this compartment are crucial for the cycling of nutrients. The impact of spatial heterogeneity on such microbially mediated nutrient cycling is not well known, which imposes a severe challenge in the prediction of in situ biogeochemical transformation rates and further of nutrient loading contributed by the groundwater to the surface water bodies. Therefore, we used a numerical modelling approach to evaluate the sensitivity of groundwater microbial biomass distribution and nutrient cycling to spatial heterogeneity in different scenarios accounting for various residence times. The model results gave us an insight into domain characteristics with respect to the presence of oxic niches in predominantly anoxic zones and vice versa depending on the extent of spatial heterogeneity and the flow regime. The obtained results show that microbial abundance, distribution, and activity are sensitive to the applied flow regime and that the mobile (i.e. observable by groundwater sampling) fraction of microbial biomass is a varying, yet only a small, fraction of the total biomass in a domain. Furthermore, spatial heterogeneity resulted in anaerobic niches in the domain and shifts in microbial biomass between active and inactive states. The lack of consideration of spatial heterogeneity, thus, can result in inaccurate estimation of microbial activity. In most cases this leads to an overestimation of nutrient removal (up to twice the actual amount) along a flow path. We conclude that the governing factors for evaluating this are the residence time of solutes and the Damköhler number (Da) of the biogeochemical reactions in the domain. We propose a relationship to scale the impact of spatial heterogeneity on nutrient removal governed by the log 10Da. This relationship may be applied in upscaled descriptions of microbially mediated nutrient cycling dynamics in the subsurface thereby resulting in more accurate predictions of, for example, carbon and nitrogen cycling in groundwater over long periods at the catchment scale. [ABSTRACT FROM AUTHOR]

Vegetation plays a vital role in the Earth system by sequestering carbon, producing food and oxygen, and providing evaporative cooling. Vegetation productivity extremes have multi-faceted implications, for example on crop yields or the atmospheric CO 2 concentration. Here, we focus on productivity extremes as possible impacts of coinciding, potentially extreme hydrometeorological anomalies. Using monthly global satellite-based Sun-induced chlorophyll fluorescence data as a proxy for vegetation productivity from 2007–2015, we show that vegetation productivity extremes are related to hydrometeorological hazards as characterized through ERA5-Land reanalysis data in approximately 50 % of our global study area. For the latter, we are considering sufficiently vegetated and cloud-free regions, and we refer to hydrometeorological hazards as water- or energy-related extremes inducing productivity extremes. The relevance of the different hazard types varies in space; temperature-related hazards dominate at higher latitudes with cold spells contributing to productivity minima and heat waves supporting productivity maxima, while water-related hazards are relevant in the (sub-)tropics with droughts being associated with productivity minima and wet spells with the maxima. Alongside single hazards compound events such as joint droughts and heat waves or joint wet and cold spells also play a role, particularly in dry and hot regions. Further, we detect regions where energy control transitions to water control between maxima and minima of vegetation productivity. Therefore, these areas represent hotspots of land–atmosphere coupling where vegetation efficiently translates soil moisture dynamics into surface fluxes such that the land affects near-surface weather. Overall, our results contribute to pinpointing how potential future changes in temperature and precipitation could propagate to shifting vegetation productivity extremes and related ecosystem services. [ABSTRACT FROM AUTHOR]

The input of liquid water to terrestrial ecosystems is composed of rain and non-rainfall water input (NRWI). The latter comprises dew, fog, and adsorption of atmospheric vapor on soil particle surfaces. Although NRWIs can be relevant to support ecosystem functioning in seasonally dry ecosystems, they are understudied, being relatively small, and therefore hard to measure. In this study, we test a routine for analyzing lysimeter data specifically to determine NRWI. We apply it on one year of data from large high-precision weighing lysimeters at a semi-arid Mediterranean site and quantify that NRWIs occur for at least 3 h on 297 days (81% of the year) with a mean diel duration of 6 hours.They reflect a pronounced seasonality as modulated by environmental conditions (i.e., temperature and net radiation). During the wet season, both dew and fog dominate NRWI, while during the dry season it is soil adsorption of atmospheric vapor. Although NRWI contributes only 7.4% to the annual water input NRWI is the only water input to the ecosystem during 15weeks, mainly in the dry season. Benefitting from the comprehensive set of measurements at the Majadas instrumental site, we show that our findings are in line with (i) independent model simulations forced with (near-) surface energy and moisture measurements and (ii) eddy covariance-derived latent heat flux estimates. This study shows that NRWI can be reliably quantified through high-resolution weighing lysimeters and a few additional measurements. Their main occurrence during night-time underlines the necessity to consider ecosystem water fluxes at high temporal resolution and with 24-hour coverage. [ABSTRACT FROM AUTHOR]

Vegetation plays a vital role in the Earth system by sequestering carbon, producing food and oxygen, and providing evaporative cooling. Vegetation productivity extremes have multi-faceted implications, for example on crop yields or the atmospheric CO[sub 2] concentration. Here, we focus on productivity extremes as possible impacts of coinciding, potentially extreme hydrometeorological anomalies. Using monthly global satellite-based Sun-induced chlorophyll fluorescence data as a proxy for vegetation productivity from 2007 - 2015, we show that vegetation productivity extremes are related to hydrometeorological hazards as characterized through ERA5-Land reanalysis data in approximately 50% of our global study area. For the latter, we are considering sufficiently vegetated and cloud-free regions; and we refer to hydrometeorological hazards as water or energy related extremes inducing productivity extremes. The relevance of the different hazard types varies in space; temperature-related hazards dominate at higher latitudes with cold spells contributing to productivity minima and heat waves supporting productivity maxima, while water-related hazards are relevant in the (sub)tropics with droughts being associated with productivity minima and wet spells with the maxima. Next to single hazards also compound events such as joint droughts and heat waves or joint wet and cold spells play a role, particularly in dry and hot regions. Further, we detect regions where energy control transitions to water control between maxima and minima of vegetation productivity. Therefore, these areas represent hot spots of land-atmosphere coupling where vegetation efficiently translates soil moisture dynamics into surface fluxes such that the land affects near-surface weather. Overall, our results contribute to pinpoint how potential future changes in temperature and precipitation could propagate to shifting vegetation productivity extremes and related ecosystem services. [ABSTRACT FROM AUTHOR]

The 2018-2020 consecutive drought events in Germany resulted in impacts related with several sectors such as agriculture, forestry, water management, industry, energy production and transport. A major national operational drought information system is the German Drought Monitor (GDM), launched in 2014. It provides daily soil moisture (SM) simulated with the mesoscale hydrological model (mHM) and its related soil moisture index at a spatial resolution of 4×4 km² . Key to preparedness for extreme drought events are high-resolution information systems. The release of the new soil map BUEK200 allowed to increase the model resolution to Ëœ1.2×1.2 km², which is used in the second version of the GDM. In this paper, we explore the ability to provide drought information on the one-kilometer scale in Germany. Therefore, we compare simulated SM dynamics using homogenized and deseasonalized SM observations to evaluate the high-resolution drought simulations of the GDM. These SM observations are obtained from single profile measurements, spatially distributed sensor networks, cosmic-ray neutron stations and lysimeters at 40 sites in Germany. The results show that the agreement of simulated and observed SM dynamics is especially high in the vegetation period (0.84 median correlation R) and lower in winter (0.59 median R). Lower agreement in winter results from methodological uncertainties in simulations as well as in observations. Moderate but significant improvements between the first and second GDM version to observed SM were found in correlations for autumn (+0.07 median R) and winter (+0.12 median R). The annual drought intensity ranking and the spatial structure of drought events over the past 69 years is comparable for the two GDM versions. However, the higher resolution of the second GDM version allows a much more detailed representation of the spatial variability of SM, which is particularly beneficial for local risk assessments. Furthermore, the results underline that nationwide drought information systems depend both on appropriate simulations of the water cycle and a broad, high-quality observational soil moisture database. [ABSTRACT FROM AUTHOR]

The subsurface is a temporally dynamic and spatially heterogeneous compartment of the Earth's Critical Zone, and biogeochemical transformations taking place in this compartment are crucial for the cycling of nutrients. The impact of spatial heterogeneity on such microbially mediated nutrient cycling is not well known which imposes a severe challenge in the prediction of in situ biogeochemical transformation rates and further of nutrient loading contributed by the groundwater to the surface water bodies. Therefore, we undertake a numerical modelling approach to evaluate the sensitivity of groundwater microbial biomass distribution and nutrient cycling to spatial heterogeneity in different scenarios accounting for various residence times. The model results gave us an insight into domain characteristics with respect to presence of oxic niches in predominantly anaerobic zones and vice versa depending on the extent of spatial heterogeneity and the flow regime. The obtained results show that microbial abundance, distribution, and activity are sensitive to the applied flow regime and that the mobile (i.e., observable by groundwater sampling) fraction of microbial biomass is a varying, yet only a small, fraction of the total biomass in a domain. Furthermore, spatial heterogeneity resulted in anaerobic niches in the domain and shifts of microbial biomass between active and inactive states. The lack of consideration of spatial heterogeneity, thus, can result in inaccurate estimation of microbial activity. In most cases this leads to an overestimation of nutrient removal (up to twice the actual amount) along a flow path. We conclude that the governing factors for evaluating this are the residence time of solutes and the Damköhler number (Da) of the biogeochemical reactions in the domain. We propose a relationship to scale the impact of spatial heterogeneity on nutrient removal governed by the log10Da. This relationship may be applied in upscaled descriptions of microbially mediated nutrient cycling dynamics in the subsurface thereby resulting in more accurate predictions of e.g., carbon and nitrogen cycling in groundwater over long periods at the catchment scale. [ABSTRACT FROM AUTHOR]

Plant diversity is an important driver of below‐ground ecosystem functions, such as root growth, soil organic matter (SOM) storage and microbial metabolism, mainly by influencing the interactions between plant roots and soil. Dissolved organic matter (DOM), as the most mobile form of SOM, plays a crucial role for a multitude of soil processes that are central for ecosystem functioning. Thus, DOM is likely to be an important mediator of plant diversity effects on soil processes. However, the relationships between plant diversity and DOM have not been studied so far.We investigated the mechanisms underlying plant diversity effects on concentrations of DOM using continuous soil water sampling across 6 years and 62 plant communities in a long‐term grassland biodiversity experiment in Jena, Germany. Furthermore, we investigated plant diversity effects on the molecular properties of DOM in a subset of the samples.Although DOM concentrations were highly variable over the course of the year with highest concentrations in summer and autumn, we found that DOM concentrations consistently increased with plant diversity across seasons. The positive plant diversity effect on DOM concentrations was mainly mediated by increased microbial activity and newly sequestered carbon in topsoil. However, the effect of soil microbial activity on DOM concentrations differed between seasons, indicating DOM consumption in winter and spring, and DOM production in summer and autumn. Furthermore, we found increased contents of small and easily decomposable DOM molecules reaching deeper soil layers with high plant diversity.Synthesis. Our findings suggest that plant diversity enhances the continuous downward transport of DOM in multiple ways. On the one hand, higher plant diversity results in higher DOM concentrations, on the other hand, this DOM is less degraded. This study indicates, for the first time, that higher plant diversity enhances the downward transport of dissolved molecules that likely stimulate soil development in deeper layers and therefore increase soil fertility. [ABSTRACT FROM AUTHOR]

Although stemflow oftentimes only represents a small portion of net precipitation in forests, it creates hot spots of water input that can affect subsurface storm-flow dynamics. The distribution of stemflow over different trees is assumed to be temporally stable, yet often unknown. Therefore, it is essential to know the systematic factors driving stemflow patterns. Several drivers have been identified in the past, mainly related to tree traits. However, less attention has been paid to tree neighbourhood interactions impacting stemflow generation and creating stand patches with enhanced or reduced stemflow. We recorded stemflow during 26 precipitation events on 65 trees, growing in 11 subplots (100 m 2 each), in a temperate mixed beech forest in the Hainich National Park, Germany. We used linear mixed effects models to investigate how traits of individual trees (tree size, tree species, number of neighbouring trees, their basal area and their relative height) affect stemflow and how stemflow is affected by stand properties (stand, biomass and diversity metrics). As expected, stemflow increased with event and tree size. Stemflow was highly variable at both the tree and subplot scale. Especially in large rainfall events (>10 mm), the tree/subplot ranking was almost identical between events, probably due to fully developed flow paths bringing out the full stemflow potential of each tree. Neighbourhood and stand structure were increasingly important with event size (15 % of fixed effects on the tree scale and ca. 65 % on the subplot scale for large events). Subplot-scale stemflow was especially enhanced by a higher proportion of woody surface, expressed by a high number of trees, low leaf area and a large maximum tree size. The Simpson diversity index contributed positively to stemflow yield for large events, probably by allowing more efficient space occupation. Furthermore, our models suggest that the neighbourhood impacts individual tree morphology, which may additionally increase stemflow in dense, species diverse neighbourhoods. Unexpectedly, rain shading within the canopy had little impact on the stemflow spatial variation. Overall, we find a strong cross-scale temporal stability. Tree size and tree density were the main drivers, independently increasing stemflow, creating forest patches with strongly enhanced or reduced stemflow. Our results show that, besides tree metrics, forest structure and tree diversity also affect stemflow patterns and the potentially associated biogeochemical hot spots. [ABSTRACT FROM AUTHOR]

Although stemflow oftentimes represents only a small portion of net precipitation in forests, it creates hot spots of water input that can affect subsurface stormflow dynamics. The distribution of stemflow over different trees is assumed to be temporally stable, yet often unknown. Therefore, it is essential to know the systematic factors driving stemflow patterns. Several drivers have been identified in the past, mainly related to tree traits. Less attention has yet been paid to tree neighbourhood interactions impacting stemflow generation and creating stand patches with enhanced or reduced stemflow. We recorded stemflow in 26 precipitation events on 65 trees, growing in 11 subplots (100 m² each), in a temperate mixed beech forest in the Hainich National Park, Germany. We used linear mixed effects models to investigate how traits of individual trees (tree size, tree species, number of neighbouring trees, their basal area, and their relative height) affect stemflow and how stemflow is affected by stand properties (stand, biomass and diversity metrics). As expected, stemflow increased with event and tree size. Stemflow was highly variable at both tree and subplot scale. Especially in large rainfall events (> 10 mm), tree/subplot ranking was almost identical between events, probably due to fully developed flow paths bringing out the full stemflow potential for each tree. Neighbourhood and stand structure were increasingly important with event size (15 % of fixed effects on the tree scale, ca. 65 % on the subplot scale for large events). Subplot scale stemflow was especially enhanced by a higher proportion of woody surface, expressed by a high number of trees, low leaf area and a large maximum tree size. Simpson's diversity index contributed positively to stemflow yield in large events, probably by allowing more efficient space occupation. Also, our models suggest that neighbourhood impacts individual tree morphology, which may additionally increase stemflow in dense, species diverse neighbourhoods. Unexpectedly, rain shading within the canopy had little impact on stemflow spatial variation. Overall, we find a strong cross-scale temporal stability. Tree size and tree density were the main drivers, independently increasing stemflow, creating forest patches with strongly enhanced or reduced stemflow. Our results show that, besides tree metrics, also forest structure and potentially diversity affect stemflow patterns and associated potentially biogeochemical hotspots. [ABSTRACT FROM AUTHOR]

The temporal and spatial dynamics of soil water are closely interlinked with terrestrial ecosystems functioning. The interaction between plant community properties such as species composition and richness and soil water mirrors fundamental ecological processes determining above‐ground–below‐ground feedbacks. Plant–water relations and water stress have attracted considerable attention in biodiversity experiments. Yet, although soil scientific research suggests an influence of ecosystem productivity on soil hydraulic properties, temporal changes of the soil water content and soil hydraulic properties remain largely understudied in biodiversity experiments. Thus, insights on how plant diversity—productivity relationships affect soil water are lacking.Here, we determine which factors related to plant community composition (species and functional group richness, presence of plant functional groups) and soil (organic carbon concentration) affect soil water in a long‐term grassland biodiversity experiment (The Jena Experiment).Both plant species richness and the presence of particular functional groups affected soil water content, while functional group richness played no role. The effect of species richness changed from positive to negative and expanded to deeper soil with time. Shortly after establishment, increased topsoil water content was related to higher leaf area index in species‐rich plots, which enhanced shading. In later years, higher species richness increased topsoil organic carbon, likely improving soil aggregation. Improved aggregation, in turn, dried topsoils in species‐rich plots due to faster drainage of rainwater. Functional groups affected soil water distribution, likely due to plant traits affecting root water uptake depths, shading, or water‐use efficiency. For instance, topsoils in plots containing grasses were generally drier, while plots with legumes were moister.Synthesis. Our decade‐long experiment reveals that the maturation of grasslands changes the effects of plant richness from influencing soil water content through shading effects to altering soil physical characteristics in addition to modification of water uptake depth. Functional groups affected the soil water distribution by characteristic shifts of root water uptake depth, but did not enhance exploitation of the overall soil water storage. Our results reconcile previous seemingly contradictory results on the relation between grassland species diversity and soil moisture and highlight the role of vegetation composition for soil processes. The effect of plant species richness on soil water content in the Jena Experiment changed with time after establishment, and was related at the beginning to aboveground (canopy) and later to belowground (soil organic carbon, roots) processes. In contrast, each plant functional group affected soil water distribution in a characteristic fashion that did not change with time, but varied in strength between years. Overall, the analysis suggests that recovery of soil functions after abandonment of arable farming may benefit from higher grassland diversity as a follow up land use, which likely feeds back on other ecosystem functions. [ABSTRACT FROM AUTHOR]

Abstract: Efficient extraction of soil water is essential for the productivity of plant communities. However, research on the complementary use of resources in mixed plant communities, and especially the impact of plant species richness on root water uptake, is limited. So far, these investigations have been hindered by a lack of methods allowing for the estimation of root water uptake profiles. The overarching aim of our study was to determine whether diverse grassland plant communities in general exploit soil water more deeply and whether this shift occurs all the time or only during times of enhanced water demand. Root water uptake was derived by analysing the diurnal decrease in soil water content separately at each measurement depth, thus yielding root water uptake profiles for 12 experimental grasslands communities with two different levels of species richness (4 and 16 sown species). Additional measurements of leaf water potential, stomatal conductance, and root traits were used to identify differences in water relations between plant functional groups. Although the vertical root distribution did not differ between diversity levels, root water uptake shifted towards deeper layers (30 and 60 cm) in more diverse plots during periods of high vapour pressure deficit. Our results indicate that the more diverse communities were able to adjust their root water uptake, resulting in increased water uptake per root area compared to less diverse communities (52% at 20 cm, 118% at 30 cm, and 570% at 60 cm depth) and a more even distribution of water uptake over depth. Tall herbs, which had lower leaf water potential and higher stomatal conductance in more diverse mixtures, contributed disproportionately to dynamic niche partitioning in root water uptake. This study underpins the role of diversity in stabilizing ecosystem function and mitigating drought stress effects during future climate change scenarios. Furthermore, the results provide evidence that root water uptake is not solely controlled by root length density distribution in communities with high plant diversity but also by spatial shifts in water acquisition. A plain language summary is available for this article. [ABSTRACT FROM AUTHOR]

Evaporation from wet-canopy ( $$E_\mathrm{C}$$ ) and stem ( $$E_\mathrm{S}$$ ) surfaces during rainfall represents a significant portion of municipal-to-global scale hydrologic cycles. For urban ecosystems, $$E_\mathrm{C}$$ and $$E_\mathrm{S}$$ dynamics play valuable roles in stormwater management. Despite this, canopy-interception loss studies typically ignore crown-scale variability in $$E_\mathrm{C}$$ and assume (with few indirect data) that $$E_\mathrm{S}$$ is generally $${<}2\%$$ of total wet-canopy evaporation. We test these common assumptions for the first time with a spatially-distributed network of in-canopy meteorological monitoring and 45 surface temperature sensors in an urban Pinus elliottii tree row to estimate $$E_\mathrm{C}$$ and $$E_\mathrm{S}$$ under the assumption that crown surfaces behave as 'wet bulbs'. From December 2015 through July 2016, 33 saturated crown periods (195 h of 5-min observations) were isolated from storms for determination of 5-min evaporation rates ranging from negligible to 0.67 $$\hbox {mm h}^{-1}$$ . Mean $$E_\mathrm{S}$$ (0.10 $$\hbox {mm h}^{-1}$$ ) was significantly lower ( $$p < 0.01$$ ) than mean $$E_\mathrm{C}$$ (0.16 $$\hbox {mm h}^{-1}$$ ). But, $$E_\mathrm{S}$$ values often equalled $$E_\mathrm{C}$$ and, when scaled to trunk area using terrestrial lidar, accounted for 8-13% (inter-quartile range) of total wet-crown evaporation ( $$E_\mathrm{S}+E_\mathrm{C}$$ scaled to surface area). $$E_\mathrm{S}$$ contributions to total wet-crown evaporation maximized at 33%, showing a general underestimate (by 2-17 times) of this quantity in the literature. Moreover, results suggest wet-crown evaporation from urban tree rows can be adequately estimated by simply assuming saturated tree surfaces behave as wet bulbs, avoiding problematic assumptions associated with other physically-based methods. [ABSTRACT FROM AUTHOR]

Plant diversity influences many ecosystem functions including root decomposition. However, due to the presence of multiple pathways via which plant diversity may affect root decomposition, our mechanistic understanding of their relationships is limited. In a grassland biodiversity experiment, we simultaneously assessed the effects of three pathways-root litter quality, soil biota, and soil abiotic conditions-on the relationships between plant diversity (in terms of species richness and the presence/absence of grasses and legumes) and root decomposition using structural equation modeling. Our final structural equation model explained 70% of the variation in root mass loss. However, different measures of plant diversity included in our model operated via different pathways to alter root mass loss. Plant species richness had a negative effect on root mass loss. This was partially due to increased Oribatida abundance, but was weakened by enhanced root potassium (K) concentration in more diverse mixtures. Equally, grass presence negatively affected root mass loss. This effect of grasses was mostly mediated via increased root lignin concentration and supported via increased Oribatida abundance and decreased root K concentration. In contrast, legume presence showed a net positive effect on root mass loss via decreased root lignin concentration and increased root magnesium concentration, both of which led to enhanced root mass loss. Overall, the different measures of plant diversity had contrasting effects on root decomposition. Furthermore, we found that root chemistry and soil biota but not root morphology or soil abiotic conditions mediated these effects of plant diversity on root decomposition. [ABSTRACT FROM AUTHOR]

Soil water content is a key variable for biogeochemical and atmospheric coupled processes. Its small-scale heterogeneity impacts the partitioning of precipitation (e.g., deep percolation or transpiration) by triggering threshold processes and connecting flow paths. Forest hydrologists frequently hypothesized that throughfall and stemflow patterns induce soil water content heterogeneity, yet experimental validation is limited. Here, we pursued a pattern-oriented approach to explore the relationship between net precipitation and soil water content. Both were measured in independent high-resolution stratified random designs on a 1-ha temperate mixed beech forest plot in Germany. We recorded throughfall (350 locations) and stemflow (65 trees) for 16 precipitation events in 2015. Soil water content was measured continuously in topsoil and subsoil (210 profiles). Soil wetting was only weakly related to net precipitation patterns. The precipitation-induced pattern quickly dissipates and returns to a basic pattern, which is temporally stable. Instead, soil hydraulic properties (by the proxy of field capacity) were significantly correlated with this stable soil water content pattern, indicating that soil structure more than net precipitation drives soil water content heterogeneity. Also, both field capacity and soil water content were lower in the immediate vicinity of tree stems compared to further away at all times, including winter, despite stemflow occurrence. Thus, soil structure varies systematically according to vegetation in our site. We conclude that enhanced macroporosity increases gravity-driven flow in stem proximal areas. Therefore, although soil water content patterns are little affected by net precipitation, the resulting soil water fluxes may strongly be affected. Specifically, this may further enhance the channelling of stemflow to greater depth and beyond the rooting zone. [ABSTRACT FROM AUTHOR]

Dual permeability models are widely used to simulate water fluxes and solute transport in structured soils. However, so far obtaining necessary data for model calibration is a problem due to the large set of unconstrained parameters. Therefore, this study presents a simplified 1D dual permeability model whose structure is similar to the MACRO model together with a calibration scheme that allows constraining the parameters using time series of soil water content. The inversion scheme consists of four consecutive steps: First, the parameters of three different water retention functions were assessed using vertical soil water content profiles assuming hydraulic equilibrium. Second, the soil sorptivity and diffusivity functions were estimated from Boltzmann-transformed soil water content data of a drying period. Third, the parameters governing macropore flow were determined using the most dynamic part of the soil water content time series during the first 12h after a precipitation event. The model was calibrated using data of artificial, homogeneous and shallow soils from mesocosms. The resulting retention functions predicted similar values as pedotransfer functions apart from for very dry conditions. The predicted soil water content time series were in good agreement with measurements at 5 and 12cm soil depth. Predicted macropore seepage fluxes exhibited high uncertainty and differed between water retention functions, but average predictions were close to measurements for two of the three water retention functions. The study demonstrates the feasibility of calibrating a 1D dual permeability model with soil water content time series. [ABSTRACT FROM AUTHOR]

Flooding is expected to increase in frequency and severity in the future. The ecological consequences of flooding are the combined result of species-specific plant traits and ecological context. However, the majority of past flooding research has focused on individual model species under highly controlled conditions., An early summer flooding event in a grassland biodiversity experiment in Jena, Germany, provided the opportunity to assess flooding responses of 60 grassland species in monocultures and 16-species mixtures. We examined plant biomass, species-specific traits (plant height, specific leaf area (SLA), root aerenchyma, starch content) and soil porosity., We found that, on average, plant species were less negatively affected by the flood when grown in higher-diversity plots in July 2013. By September 2013, grasses were unaffected by the flood regardless of plant diversity, and legumes were severely negatively affected regardless of plant diversity. Plants with greater SLA and more root aerenchyma performed better in September. Soil porosity was higher in higher-diversity plots and had a positive effect on plant performance., As floods become more frequent and severe in the future, growing flood-sensitive plants in higher-diversity communities and in soil with greater soil aeration may attenuate the most negative effects of flooding. [ABSTRACT FROM AUTHOR]

This article provides an overview about the Bode River catchment that was selected as the hydrological observatory and main region for hydro-ecological research within the TERrestrial ENvironmental Observatories Harz/Central German Lowland Observatory. It first provides information about the general characteristics of the catchment including climate, geology, soils, land use, water quality and aquatic ecology, followed by the description of the interdisciplinary research framework and the monitoring concept with the main components of the multi-scale and multi-temporal monitoring infrastructure. It also shows examples of interdisciplinary research projects aiming to advance the understanding of complex hydrological processes under natural and anthropogenic forcings and their interactions in a catchment context. The overview is complemented with research work conducted at a number of intensive research sites, each focusing on a particular functional zone or specific components and processes of the hydro-ecological system. [ABSTRACT FROM AUTHOR]

Plant diversity enhances many ecosystem functions, including root biomass production, which drives soil carbon input. Although root decomposition accounts for a large proportion of carbon input for soil, little is known about plant diversity effect on this process. Plant diversity may affect root decomposition in two non-exclusive ways: by providing roots of different substrate quality (e.g. root chemistry) and/or by altering the soil environment (e.g. microclimate)., To disentangle these two pathways, we conducted three decomposition experiments using a litter-bag approach in a grassland biodiversity experiment. We hypothesized that: (i) plant species richness negatively affects substrate quality (indicated by increased C:N ratios), which we tested by decomposing roots collected from each experimental plot in one common plot; (ii) plant species richness positively affects soil environment (indicated by increased soil water content), which we tested by decomposing standardized roots in all experimental plots; (iii) the overall effect of plant species richness on root decomposition, due to the contrast between quality and environmental effects, is neutral, which we tested by decomposing community roots in their 'home' plots., Plant species richness negatively affected root decomposition in all three experiments. The negative effect of plant species richness on substrate quality was largely explained by increased root C:N ratios along the diversity gradient. Functional group presence explained more variance in substrate quality than species richness. Here, the presence of grasses negatively affected substrate quality and root C:N ratios, while the presence of legumes and small herbs had positive effects. Plant species richness had a negative effect on soil environment despite its positive effect on soil water content which is known to stimulate decomposition. We argue that - instead of soil water content - a combined effect of soil temperature and seasonality might drive environmental effect of plant diversity on decomposition in our plant communities, but this remains to be tested., Synthesis. Our results demonstrate that both substrate quality and soil environment contribute to the net negative effect of plant diversity on root decomposition. This study promotes our mechanistic understanding of increased soil carbon accumulation in more diverse grassland plant communities. [ABSTRACT FROM AUTHOR]

Climate change is projected to increase the frequency of extreme events, such as flooding and droughts, which are anticipated to have negative effects on the biodiversity of primary producers and consequently the associated consumer communities. Here we assessed the effects of an extreme early summer flooding event in 2013 on ant colonies along an experimental gradient of plant species richness in a temperate grassland. We tested the effects of flood duration, plant species richness, plant cover, soil temperature, and soil porosity on ant occurrence and abundance. We found that the ant community was dominated by Lasius niger, whose presence and abundance after the flood was not significantly affected by any of the tested variables, including plant species richness. We found the same level of occupation by L. niger at the field site after the flood (surveyed in 2013) as before the flood (surveyed in 2006). Thus, there were no negative effects of the flood on the presence of L. niger in the plots. We can exclude recolonisation as a possible explanation of ant presence in the field site due to the short time period between the end of the flood and survey as well as to the absence of a spatial pattern in the occupancy data. Thus, the omnipresence of this dominant ant species 1 month after the flood indicates that the colonies were able to survive a 3-week summer flood. The observed ant species proved to be flood resistant despite experiencing such extreme climatic events very rarely. [ABSTRACT FROM AUTHOR]

Trees concentrate rainfall to near-stem soils via stemflow. When canopy structures are organized appropriately, stemflow can even induce preferential flow through soils, transporting nutrients to biogeochemically active areas. Bark structure significantly affects stemflow, yet bark-stemflow studies are primarily qualitative. We used a LaserBark to compute bark microrelief (MR), ridge-to-furrow amplitude (R) and slope (S) metrics per American Society of Mechanical Engineering standards (ASME-B46.1–2009) for two morphologically contrasting species (Fagus sylvatica L. (European beech), Quercus robur L. (pendunculate oak)) under storm conditions with strong bark water storage capacity (BWSC) influence in central Germany. Smaller R and S for F. sylvatica significantly lowered BWSC, which strongly and inversely correlated to maximum funnelling ratios and permitted stemflow generation at lower rain magnitudes. Larger R and S values in Q. robur reduced funnelling, diminishing stemflow drainage for larger storms. Quercus robur funnelling and stemflow was more reliant on intermediate rain intensities and intermittency to maintain bark channel-dependent drainage pathways. Shelter provided by Q. robur's ridged bark also appears to protect entrained water, lengthening mean intrastorm dry periods necessary to affect stemflow. Storm conditions where BWSC plays a major role in stemflow accounted for much of 2013's rainfall at the nearest meteorological station (Wulferstedt). Editor M.C. Acreman; Associate editor not assigned [ABSTRACT FROM AUTHOR]

The impact of species richness and functional diversity of plants on ecosystem water vapor fluxes has been little investigated. To address this knowledge gap, we combined a lysimeter setup in a controlled environment facility (Ecotron) with large ecosystem samples/monoliths originating from a long-term biodiversity experiment (The Jena Experiment) and a modeling approach. Our goals were (1) quantifying the impact of plant species richness (four vs. 16 species) on day- and nighttime ecosystem water vapor fluxes; (2) partitioning ecosystem evapotranspiration into evaporation and plant transpiration using the Shuttleworth and Wallace ( SW) energy partitioning model; and (3) identifying the most parsimonious predictors of water vapor fluxes using plant functional-trait-based metrics such as functional diversity and community weighted means. Daytime measured and modeled evapotranspiration were significantly higher in the higher plant diversity treatment, suggesting increased water acquisition. The SW model suggests that, at low plant species richness, a higher proportion of the available energy was diverted to evaporation (a non-productive flux), while, at higher species richness, the proportion of ecosystem transpiration (a productivity-related water flux) increased. While it is well established that LAI controls ecosystem transpiration, here we also identified that the diversity of leaf nitrogen concentration among species in a community is a consistent predictor of ecosystem water vapor fluxes during daytime. The results provide evidence that, at the peak of the growing season, higher leaf area index ( LAI) and lower percentage of bare ground at high plant diversity diverts more of the available water to transpiration, a flux closely coupled with photosynthesis and productivity. Higher rates of transpiration presumably contribute to the positive effect of diversity on productivity. [ABSTRACT FROM AUTHOR]

We combine ecohydrological observations of sap flow and soil moisture with thermodynamically constrained estimates of atmospheric evaporative demand to infer the dominant controls of forest transpiration in complex terrain. We hypothesize that daily variations in transpiration are dominated by variations in atmospheric demand, while site-specific controls, including limiting soil moisture, act on longer timescales. We test these hypotheses with data of a measurement setup consisting of five sites along a valley cross section in Luxembourg. Both hillslopes are covered by forest dominated by European beech (Fagus sylvatica L.). Two independent measurements are used to estimate stand transpiration: (i) sap flow and (ii) diurnal variations in soil moisture, which were used to estimate the daily root water uptake. Atmospheric evaporative demand is estimated through thermodynamically constrained evaporation, which only requires absorbed solar radiation and temperature as input data without any empirical parameters. Both transpiration estimates are strongly correlated to atmospheric demand at the daily timescale. We find that neither vapor pressure deficit nor wind speed add to the explained variance, supporting the idea that they are dependent variables on land-atmosphere exchange and the surface energy budget. Estimated stand transpiration was in a similar range at the north-facing and the south-facing hillslopes despite the different aspect and the largely different stand composition. We identified an inverse relationship between sap flux density and the site-average sapwood area per tree as estimated by the site forest inventories. This suggests that tree hydraulic adaptation can compensate for heterogeneous conditions. However, during dry summer periods differences in topographic factors and stand structure can cause spatially variable transpiration rates. We conclude that absorption of solar radiation at the surface forms a dominant control for turbulent heat and mass exchange and that vegetation across the hillslope adjusts to this constraint at the tree and stand level. These findings should help to improve the description of land-surface-atmosphere exchange at regional scales. [ABSTRACT FROM AUTHOR]

Background and aims: Soil hydraulic properties drive water distribution and availability in soil. There exists limited knowledge of how plant species diversity might influence soil hydraulic properties. Methods: We quantified the change in infiltration capacity affected by soil structural variables (soil bulk density, porosity and organic carbon content) along a gradient of soil texture, plant species richness (1, 2, 4, 8, 16 and 60) and functional group composition (grasses, legumes, small herbs, tall herbs). We conducted two infiltration measurement campaigns (May and October 2012) using a hood infiltrometer. Results: Plant species richness significantly increased infiltration capacity in the studied grasslands. Both soil porosity (or inversely bulk density) and organic carbon played an important role in mediating the plant species richness effect. Soil texture did not correlate with infiltration capacity. In spring 2012, earthworm biomass increased infiltration capacity, but this effect could not be attributed to changes in soil structural variables. Conclusions: We experimentally identified important ecological drivers of infiltration capacity, suggesting complex interactions between plant species richness, earthworms, and soil structural variables, while showing little impact of soil texture. Changes in plant species richness may thus have significant effects on soil hydraulic properties with potential consequences for surface run-off and soil erosion. [ABSTRACT FROM AUTHOR]