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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.

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.

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.

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.

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.

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.

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.

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.

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

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

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

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

Extreme weather events are occurring more frequently, and research has shown that plant diversity can help mitigate impacts of climate change by increasing plant productivity and ecosystem stability1,2. Although soil temperature and its stability are key determinants of essential ecosystem processes related to water and nutrient uptake3 as well as soil respiration and microbial activity4, no study has yet investigated whether plant diversity can buffer soil temperature fluctuations. Using 18 years of a continuous dataset with a resolution of 1 minute (∼795,312,000 individual measurements) from a large-scale grassland biodiversity experiment, we show that plant diversity buffers soil temperature throughout the year. Plant diversity helped to prevent soil heating in hot weather, and cooling in cold weather. Moreover, this effect of plant diversity increased over the 18-year observation period with the aging of experimental communities and was even stronger under extreme conditions, i.e., on hot days or in dry years. Using structural equation modelling, we found that plant diversity stabilized soil temperature by increasing soil organic carbon concentrations and, to a lesser extent, by increasing the plant leaf area index. We suggest that the diversity-induced stabilization of soil temperature may help to mitigate the negative effects of extreme climatic events such as soil carbon release, thus slow global warming.

Critical to the reliable application of gridded soil moisture products is a thorough assessment of their quality at spatially compatible scales. While previous studies have attempted to evaluate different soil moisture products, comprehensive assessments at the appropriate scale remain challenging and rare. This study explores the potential of the Cosmic-Ray Soil Moisture Observation System (COSMOS) in Germany for effectively mitigating the scale mismatch between soil moisture products and reference measurements. A newly released extensive COSMOS data set provides time series of hectare-scale soil moisture of the main root zone at different locations in Germany and offers a unique opportunity for a comprehensive quality assessment of 15 commonly-used coarse-scale soil moisture products. Those are either satellite-based (AMSR2 LPRM, ASCAT H115/H116, Sentinel-1 SSM, SMAP L3E, SMOS L3, ASCAT/Sentinel-1 SWI, SMAP/Sentinel-1 L2, CCI Combined, and NOAA SMOPS) or model-based (ERA5-Land, GLDAS-Noah, ASCAT H141/H142, GLEAM, SMAP L4, and SMOS L4). We compared the temporal dynamics of the soil moisture products against that of the COSMOS soil moisture estimates at 21 sites of different land cover types over six years (2015–2020), including the drought of 2018. We found that the model-based products generally yield a higher correlation (0.74) and lower unbiased root-mean-square differences (0.05 m^3m^-3) than the satellite-based products (0.60 and 0.07 m^3m^-3, respectively) against the COSMOS data in Germany. Notably, the application of the exponential filter significantly improves the performance of the products. Conversely, deseasonalized time series of all selected products demonstrate lower performances across all COSMOS sites. Most products show a considerable positive bias, which limits their usability for the assessment of absolute soil water storage. We also found that the land cover type, mean annual soil moisture, and vertical support have notable influences on the p

Replying to: Hagan, J. G., Henn, J. J. & Osterman, W. H. A. Nature Ecology & Evolution https://doi.org/10.1038/s41559-022-01920-x (2023).

Reconstructing the climate of the past requires archives that bear proxy information on temperature, precipitation, or atmospheric composition, for example. In this study we use contour marks as potential water level marks in mud sediments to reconstruct local evaporation rates at the Bromacker lagerstaette site in the Early Permian. The measured values indicate a daily evaporation of 1.5–3.75 mm with a median value of 2.25 mm/day. The calculated evaporation rates are compared with modern ones to estimating moisture, precipitation and seasonal climate. For evaluating reconstructed precipitation and evapotranspiration rates, values simulated by global climate models and calculated from geochemical datasets are furthermore incorporated. For the first time, quantitative data and models elucidate the climate of the Tambach Formation and Bromacker lagerstaette against the background of the pivotal transition from the Carboniferous Ice House to the Permian Hothouse climate. Our results suggest a strongly seasonal climate with wet summers and dry winters in a mountainous region based on unexpectedly low temperatures (10.9–15.0 °C) considering the palaeo-location of the site in the tropical belt during the Early Permian. According to the modern vegetation model by Holdridge a moist forest biome is suggested for the Bromacker lagerstaette.

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