The application of digestates supports soil fertility by restoring soil organic matter (SOM) and supplying nitrogen (N). However, their application can increase greenhouse gas (GHG) emissions from agriculture. Targeted digestate application to soils where erosion has mixed subsoil into topsoil may reduce emissions, as the lower SOM saturation in this diluted topsoil could enhance stabilization of organic inputs. This study investigates whether topsoil dilution through erosion can reduce carbon dioxide (CO2) and nitrous oxide (N2O) emissions following digestate application. We conducted an incubation experiment simulating erosion-induced topsoil dilution. Three different soils from Uckermark region, Germany-non-eroded (LL), moderately eroded (eLL), and strongly eroded (RZ)-were incubated for 26 days in an automated gas exchange system. Topsoil was diluted with 20% subsoil, and digestate applied as organic fertilizer. CO2 and N2O emissions were measured; undiluted, unfertilized soils served as controls. Digestate increased CO2 and significantly raised N2O emissions in all soils. Topsoil dilution reduced CO2 emissions in LL and showed similar trends in eLL and RZ, though the effect weakened with erosion severity, likely due to existing C-undersaturation in these soils. N2O responses varied: emissions decreased in eLL (high clay and reactive mineral content), possibly due to enhanced N stabilization, but increased in RZ (calcareous, high-pH soil likely promoting nitrification) and slightly in LL, possibly due to lowered carbon-to-nitrogen (C: N) ratio. Topsoil dilution can mitigate digestate-induced CO2 but may elevate N2O emissions depending on soil properties. Therefore, site-specific management is key to lowering GHGs in erosion-prone soils.

IntroductionDigital technologies in agriculture are often associated with sophisticated, high-end, or network-capable systems based on robotics, remote sensing, or IoT. These systems, however, remain financially and logistically inaccessible for many researchers and farmers, particularly in remote regions and the Global South. This paper presents a contrasting, yet complementary, bottom-up approach by advocating the adoption of low-cost DIY systems to enable site-specific crop management and support climate-adaptive decisions.MethodsThe Environmental Variables Explorer (EVE) is presented as a low-cost, open-source platform that integrates modular microcontroller-based sensing, reliable low-power operation, timekeeping, and non-volatile data storage. The platform supports two interoperable, end-to-end workflows under full user control: EVE-Offline, a stand-alone logger that stores measurements locally in FRAM and allows wireless data retrieval via a custom Android Bluetooth app; and EVE-Online, an ESP32-based node that transmits data via Wi-Fi to a self-hosted backend providing a web dashboard and CSV export on inexpensive shared hosting. To demonstrate the platform, EVE was implemented in both workflows as a compact weather station recording photosynthetically active radiation (PAR), air temperature, relative humidity (RH), and air pressure at user-defined intervals. Sensor performance was evaluated using co-location tests and independent reference stations.ResultsThe custom low-cost PAR sensor showed strong reproducibility and close agreement with reference measurements. A co-location validation against a TOMST TMS-4 reference confirmed near 1:1 temperature agreement under identical conditions. Field deployments further demonstrated stable temporal dynamics across variables and reliable end-to-end data handling in both offline and online workflows.DiscussionThrough its openly accessible hardware designs, firmware, backend code, and build instructions, EVE provides a practical alternative to locked-in commercial systems. It enables cost-effective, bottom-up monitoring for researchers, farmers, educators, and community initiatives, while its modular platform can be extended with additional sensors and locally validated analyses without changing the underlying workflows. These results show that improving agricultural productivity while minimizing environmental impacts requires not only cutting-edge, data-heavy technologies but also autonomous, customizable tools that support user-driven innovation from the bottom up, particularly in resource-limited contexts.

Efficient nitrogen (N) use in crops is vital for promoting sustainable and profitable agriculture and has significant implications for greenhouse gas (GHG) mitigation. While urease (UI) and nitrification inhibitors (NI) are known to influence N transformations, soil N availability, and N utilization efficiency (NUE) in ammonium sulfate urea (AS-HS), their impacts on the carbon (C) and water cycles are less well understood. To address this knowledge gap while reflecting realistic agronomic conditions, we conducted an on-farm strip trial in northeastern Germany, focusing on examining potential interactions among nitrogen (N), carbon (C), and water cycling. The trial compared non-fertilized plots with AS-HS, AS-HS+UI, and AS-HS+UI+NI treatments across a maize–wheat–barley rotation. Compared to AS-HS, the application of UI and UI+NI generally reduced cumulative N2O emissions up to 72

Agroforestry represents one of the oldest and most sustainable forms of land use, integrating woody perennials with crops and grasslands to enhance resource efficiency while meeting human requirements for food, timber, and fiber. While its potential to conserve natural resources is well-recognized, a full understanding of the interactions between system components remains limited, particularly regarding the hydrological processes that regulate plant growth, nutrient dynamics, and energy exchange. This study presents ongoing research at a silvoarable experimental site in Gladbacherhof, Hesse, Germany, designed to quantify soil moisture dynamics across multiple spatial scales.To characterize these dynamics at a high resolution, volumetric soil moisture is monitored using sensors installed along three transects oriented perpendicular to apple tree rows at specific distances of 1, 2.5, 6, and 10.5 meters from the trees and at soil depths of 10, 40, and 60 centimeters. These point-scale observations are complemented by field-scale variability captured through cosmic-ray neutron sensing (CRNS). To bridge these disparate scales, the study employs machine learning approaches—including random forest models, multilayer perceptron neural networks, and deep learning techniques—to derive spatially continuous representations of soil moisture at an intermediate scale.Furthermore, the acquisition of high-temporal-resolution data allows for the investigation of hydraulic lift, which is inferred from observed nocturnal increases in soil moisture during prolonged dry periods. Building on these findings, a subsequent phase of the experiment will apply water stable isotope techniques to track the specific spatio-temporal patterns of water uptake by trees, grassland, and arable plants. As an ongoing study, this research aims to clarify the key factors and spatial controls governing soil moisture dynamics, ultimately supporting more informed design and management of resilient, multifunctional agroforestry systems.

Water potential gradients govern water fluxes, and plants respond with species-specific hydraulic traits that influence ecosystem function. While understanding these traits is key to predicting vegetation responses to climate change, traditional methods like the pressure chamber limit temporal resolution and continuity. Additionally, suitable methods for continuous monitoring remain limited. We addressed this gap by evaluating the potential of microtensiometers for continuous stem water potential (psi stem) monitoring in mature forest trees across three temperate sites. We collected psi stem data over the 2023-2024 vegetation periods from 21 microtensiometers installed in Fagus sylvatica, Fraxinus excelsior and Carpinus betulus, alongside high-frequency soil matric potential (psi soil) measurements and meteorological data. Microtensiometers provided realistic daily cycles and good agreement with pressure chamber-derived leaf water potential (psi leaf). Crucially, our results show that psi soil, next to species identity, is one dominant driver of stem water potential across sites. Diurnal patterns showed that psi stem is driven by shallow soil layers during the day, when strong transpirational pull creates more negative psi stem, enabling access to these drier upper soils. At night, when transpiration ceases and psi stem becomes less negative, deeper, wetter soil layers predominantly supply water, reflecting the physical constraints of water flow within the root zone. This soil control was consistent across all species and sites under moderately dry to normal conditions. We further show that psi stem data can support broader physiological analyses, including refining tree water deficit-water potential relations and highlighting spatial variability in root water uptake. Our findings indicate that horizontal and vertical psi soil heterogeneity must be accounted for to avoid oversimplified interpretations of plant water use. This study demonstrates that microtensiometers can provide continuous, nondestructive measurements of plant water status and, when carefully installed and continuously monitored, can reveal meaningful ecological patterns while also requiring attention to methodological constraints. Most notably, we show that species identity and soil moisture regulate stem water potential, underscoring the central role of soil-plant interactions in shaping forest water dynamics under changing climatic conditions.

Understanding the drivers of plant community stability is crucial for predicting ecosystem responses to extreme drought events. In grasslands, drought resistance supports the maintenance of key functions such as above-ground primary productivity, making the identification of resistance drivers essential to guide management under climate change. Proposed factors contributing to grassland stability include multiple diversity facets, functional traits and long-term climate, but most assessments focus on temporal invariability under historical disturbance regimes, leaving mechanisms of extreme drought resistance and their variation across climatic contexts relatively underexplored. Here, we analysed data from 54 grassland sites of the International Drought Experiment to examine the resistance of above-ground net primary productivity to a short-term (i.e. 1 year) extreme drought. We investigated the relative importance and joint influence of functional composition (i.e. community-weighted means of leaf and root traits), plant diversity facets (taxonomic, functional and phylogenetic) and climate (aridity and rainfall variability) on drought resistance. We used structural equation models to disentangle direct, indirect, and moderating pathways linking these drivers to drought resistance. Long-term aridity appeared as one of the most important drivers of grassland resistance to drought, with more arid sites showing lower resistance. Moreover, aridity impacted resistance through indirect effects by shaping functional composition and plant diversity, and by moderating the influence of plant diversity and functional composition. Functional composition related to dehydration avoidance and dehydration tolerance was also positively associated with resistance, while diversity had a weaker relationship with resistance, mostly through functional and phylogenetic facets. Interannual rainfall variability also influenced resistance, with different effects in more arid versus humid and less arid sites. Synthesis. Widely studied stability drivers such as plant diversity and functional composition have only partial explanatory power for short-term drought resistance of above-ground productivity in grasslands at a global scale. The abiotic context, particularly long-term aridity, is crucial for understanding ecosystem responses to rainfall variation and can improve predictive models for advancing the study of ecosystem resistance to drought. Along with management practices that target high species diversity or specific traits, restoration and conservation practices should support vulnerable sites experiencing high aridity Compreender os fatores que determinam a estabilidade de comunidades vegetais & eacute; fundamental para prever as respostas dos ecossistemas a eventos de seca extrema. Em ecossistemas dominados por gram & iacute;neas, a resist & ecirc;ncia & agrave; seca & eacute; importante para a manuten & ccedil;& atilde;o de fun & ccedil;& otilde;es como a produtividade prim & aacute;ria a & eacute;rea. Assim, identificar os fatores que promovem essa resist & ecirc;ncia & eacute; crucial para orientar o manejo em um cen & aacute;rio de mudan & ccedil;as clim & aacute;ticas. Entre os principais determinantes da estabilidade em sistemas dominados por gram & iacute;neas est & atilde;o diferentes facetas da diversidade, atributos funcionais das esp & eacute;cies e o clima. No entanto, a maioria dos estudo foca na invariabilidade temporal sob regimes hist & oacute;ricos de dist & uacute;rbio, enquanto os mecanismos de resist & ecirc;ncia & agrave; seca extrema e a sua varia & ccedil;& atilde;o ao longo de gradientes clim & aacute;ticos permanecem relativamente pouco explorados. Neste estudo, analisamos dados de 54 s & iacute;tios do Experimento Internacional de Seca para avaliar a resist & ecirc;ncia da produtividade prim & aacute;ria l & iacute;quida a & eacute;rea a uma seca extrema de curta dura & ccedil;& atilde;o (um ano). Investigamos a import & acirc;ncia relativa e os efeitos conjuntos da composi & ccedil;& atilde;o funcional (isto & eacute;, m & eacute;dias ponderadas da comunidade de atributos funcionais de folhas e ra & iacute;zes), de diferentes facetas da diversidade de plantas (taxon & ocirc;mica, funcional e filogen & eacute;tica) e do clima (aridez e variabilidade interanual da precipita & ccedil;& atilde;o) sobre a resist & ecirc;ncia & agrave; seca. Usamos modelos de equa & ccedil;& otilde;es estruturais para discriminar os efeitos diretos, indiretos e de modera & ccedil;& atilde;o que conectam esses fatores & agrave; resist & ecirc;ncia & agrave; seca. A aridez destacou-se como um dos principais fatores geradores de resist & ecirc;ncia & agrave; seca, com locais mais & aacute;ridos apresentando menor resist & ecirc;ncia. Al & eacute;m disso, a aridez tamb & eacute;m influenciou a resist & ecirc;ncia de forma indireta, ao afetar a composi & ccedil;& atilde;o funcional e a diversidade de plantas, al & eacute;m de moderar a efeito da diversidade de plantas e da composi & ccedil;& atilde;o funcional na resist & ecirc;ncia. A composi & ccedil;& atilde;o funcional associada a estrat & eacute;gias de evita & ccedil;& atilde;o e toler & acirc;ncia & agrave; desidrata & ccedil;& atilde;o tamb & eacute;m apresentou rela & ccedil;& atilde;o positiva com a resist & ecirc;ncia, enquanto a diversidade de plantas mostrou associa & ccedil;& atilde;o mais fraca, contribuindo principalmente por meio das facetas funcionais e filogen & eacute;ticas. A variabilidade interanual da precipita & ccedil;& atilde;o tamb & eacute;m influenciou a resist & ecirc;ncia, com efeitos distintos entre locais mais & aacute;ridos e locais h & uacute;midos ou menos & aacute;ridos S & iacute;ntese. Fatores amplamente estudados como determinantes da estabilidade, como a diversidade das plantas e a composi & ccedil;& atilde;o funcional, explicam apenas parcialmente a resist & ecirc;ncia da produtividade a & eacute;rea a secas de curta dura & ccedil;& atilde;o em ecossistemas dominados por gram & iacute;n Em conjunto com pr & aacute;ticas de manejo voltados ao aumento da diversidade de esp & eacute;cies ou & agrave; promo & ccedil;& atilde;o de determinados atributos funcionais, a & ccedil;& otilde;es de restaura & ccedil;& atilde;o e conserva & ccedil;& atilde;o devem focar em & aacute;reas mais vulner & aacute;veis sob maior aridez.

Natural bogs have high water level (WL) that prevents peat decomposition and promotes bog-specific vegetation. Especially in rewetted bogs, increasing tree encroachment is observed in combination with low WL. Simultaneously, a general shift in vegetation and microform distribution is visible. The effects of this development on evapotranspiration (ET) are not clear.Two sites were established at a former peat extraction site, one with high WL and a Sphagnum-dominated vegetation (open site), one with varying and lower WL and a dense birch population (tree site). Energy and CO2 exchange were measured with eddy covariance towers. For one growing season, ET of the different microforms (hummocks and hollows) and birches was measured with closed chambers to model their contribution to growing season ET.ET was lower at the tree site in all months and consequently in all three investigation years (620 and 387 mm at the open and tree site, respectively, averaged over 3 years). ET of birches was 104 mm, which was 28% of growing season site ET, while microform ET was strongly reduced at the tree site. ET at the open site was high due to high Sphagnum cover and WL. The open site generally had a higher proportion of latent heat, leading to a lower Bowen ratio, while the water use efficiency was higher at the tree site. Consequently, the birches are not the primary cause of the lower WL, but rather the additional water loss due to site conditions and incomplete rewetting. Therefore, despite the higher ET, the open site is in a better state of conservation.

Consecutive dry periods (e.g., 2014–2016, 2018–2019, 2022) led to persistent long-term impairments in maintaining tree functions such as growth and canopy structure thereby exacerbating drought stress and mortality in temperate forests. Despite growing attention to compound drought impacts on forest ecosystems, the role of deep-water sources at varying positions on hillslopes remains unclear.In this study, we investigated how hillslope position influences growth dynamics and water-use strategies of co-occurring tree species in an unmanaged, structurally diverse forest stand in Lower Saxony, Germany. The stand is composed of the broadleaf deciduous tree species Fagus sylvatica (L.), Carpinus betulus (L.), Fraxinus excelsior (L.), and Quercus robur (L.) which differ in their root structure, stomatal regulation and growth strategies. Over the three years (2023-2025) we employed continuous point-dendrometer, sap flow and soil moisture measurements to monitor growth, soil and stand water use and water potential. Further destructive samples for verifying water potential and stable carbon isotopes of phloem sap were measured.We found that growth patterns were strongly species-specific and closely aligned with contrasting tree water-use strategies. Despite similar climatic conditions in 2023 and 2024, pronounced interannual differences in growth were observed. These differences suggest a delayed recovery from previous long-term drought events (2018-2022), particularly for the shallow-rooted species F. sylvatica, C. betulus and F. excelsior, compared to deep-rooted Q. robur, highlighting long-term effects of compound droughts on productivity. It was notable that the species were able to adapt their strategies according to their position. Additionally, we observed in F. excelsior and Q. robur that high growth rates can be supported by using water storage (e.g., via deep roots and access to deep water sources or via stem water use) or by maintaining high transpiration rates during drought at the risk of cavitation. In conclusion, we postulate that drought mitigation strategies not only depend on species traits, but also on tree positioning and climatic conditions.

Understanding water fluxes in agricultural ecosystems is fundamental to securing food production under increasing water scarcity. This study investigates the dynamics of evapotranspiration (ET) and its stable water isotopic composition (d 18 O, d 2 H) in a heterogeneous cropland cultivated with winter oil rapeseed and winter wheat. By coupling a fully automated chamber system with high-resolution in-situ laser spectroscopy, we implemented a novel observational approach that achieved the continuous monitoring of ambient water vapor, precipitation, and ET isotopic compositions at an unprecedented temporal resolution over two growing seasons. We found the isotopic composition of ET to serve as a sensitive indicator of crop phenology and physiological response to changing environmental conditions and observed a distinct seasonal shift from evaporation-dominated to transpiration-dominated fluxes. High transpiration rates strongly affected the ambient water vapor diurnally and seasonally, challenging common ecohydrological assumptions. Furthermore, we demonstrate that a data-driven Random Forest model can successfully predict the complex, non-linear dynamics of isotopic compositions using standard micrometeorological variables and easily measurable ambient water vapor compositions. We conclude that high-resolution monitoring linked with machine learning offers a robust pathway to disentangle spatio-temporal dynamics of soil-plant-atmosphere interactions and improves our ability to predict crop water dynamics under changing environmental conditions.

Croplands are among the land systems most vulnerable to shifts in precipitation regimes and prolonged droughts, particularly in temperate climates. Characterizing root water uptake patterns is therefore essential to understand how crops maintain function and sustain transpiration under drought stress. We investigated water uptake patterns of winter cereals (wheat, barley) across two contrasting growing seasons (2024, 2025) at a temperate cropland in Central Germany. Within the footprint of an eddy covariance (EC) tower, we sampled plant leaves, precipitation, soil water, and groundwater for stable water isotope analysis at natural abundance and estimated xylem water isotope composition using the Craig–Gordon model. Soil moisture was monitored at nine depths (5–100 cm) at three profiles. Using multi-layer soil moisture time series and a dual-isotope mixing model, we identified the contribution of different water sources to transpiration, and quantified water uptake depth patterns.In 2024, more frequent rainfall maintained wetter soil layers and higher evapotranspiration (ET), whereas 2025 was marked by longer dry spells and consistently lower ET, although average water-use efficiency remained similar with greater variability in 2025. Both crop types exhibited flexibility in water uptake depth in response to dry spells, including access to deeper soil layers (> 60 cm). However, the median uptake depth ranged from 20–60 cm for wheat in 2024, whereas barley met transpiration demand primarily from 10–40 cm despite drier conditions in 2025. Our findings suggest that water uptake strategies are tightly linked to plant traits, access to deeper water sources, and dry spell characteristics, which together shape root plasticity and modulate the impact of drought on transpiration and ecosystem productivity.

As droughts become longer and more intense, impacts on terrestrial primary productivity are expected to increase progressively. Yet, some ecosystems appear to acclimate to multiyear drought, with constant or diminishing reductions in productivity as drought duration increases. We quantified the combined effects of drought duration and intensity on aboveground productivity in 74 grasslands and shrublands distributed globally. Ecosystem acclimation with multiyear drought was observed overall, except when droughts were extreme (i.e., ≤1-in-100-year likelihood of occurrence). Productivity losses after four consecutive years of extreme drought increased by ~2.5-fold compared with those of the first year. These results portend a foundational shift in ecosystem behavior if drought duration and intensity increase, from maintenance of reduced functioning over time to progressive and profound losses of productivity when droughts are extreme.

The stable isotope ratios of hydrogen (δ2H) and oxygen (δ18O) are useful for studying ecohydrological dynamics in forests. However, most isotope-based eco-hydrological studies are limited to single sites, resulting in a lack of large-scale isotope data for understanding tree water uptake. Here, we provide a first systematic isotope dataset for soil and stem xylem water collected during two pan-European sampling campaigns at 40 beech (Fagus sylvatica), spruce (Picea abies), or mixed beech-spruce forest sites in spring and summer 2023 (https://doi.org/10.16904/envidat.542, Lehmann et al., 2024). The dataset is complemented by additional site-, soil-, and tree-specific metadata. The samples and metadata were collected by different researchers across Europe following a standardized protocol. Soil samples were taken at up to 5 depths (ranging from 0 to 90 cm) and stem xylem samples from the trunks of three beech and/or spruce trees per site. All samples were sent to a single laboratory, where all analytical work was conducted. Water was extracted using cryogenic vacuum distillation and analyzed with an isotope laser spectrometer. Additionally, a subset of the samples was analyzed with an isotope ratio mass spectrometer. Data quality checks revealed a high mean total extraction efficiency, mean water amount (>1 mL), accuracy, and precision. The isotopic signature of soil and stem xylem water varied as a function of the geographic origin and changed from spring to summer across all sites. While δ2H and δ18O were strongly correlated, the soil water data plotted closer to the Global Meteoric Water Line (GMWL) than the stem xylem water. Specifically, the δ2H values of the xylem water were more enriched than those of the soil water, leading to a systematic deviation from the GMWL. Isotopic enrichment of the stem xylem water at mixed forest sites was larger for spruce trees than for beech trees. This dataset is particularly useful for large-scale studies on plant water use, ecohydrological model testing, and isotope mapping across Europe.

Dual-isotope eddy covariance measurements offer a novel approach for studying water fluxes in ecosystems, providing detailed insights into evapotranspiration (ET) and its components, evaporation (E) and transpiration (T). During the 2024 growing season, a dual-isotope eddy covariance system was deployed over a winter wheat cropland in central Germany, integrating a Los Gatos Research (LGR) Water Vapor Isotope Analyzer with a conventional eddy covariance setup. This system continuously measured isotopic fluxes (δD and δ18O) alongside water vapor, carbon dioxide, and energy fluxes at high temporal resolution. These measurements were supplemented by soil water profiles, biometeorological observations, and vegetation indices.The isotopic flux data revealed diurnal and seasonal dynamics of water vapor isotopes, linked to environmental drivers such as vapor pressure deficit, soil moisture, and crop phenology. Preliminary results show a diurnal cycle of isotope fluxes of ET, characterized by isotopic enrichment during the middle of the day, with δ18OET reaching -12‰ and δDET reaching -110‰ (both against VSMOW). The results suggest that transpiration dominates ET during peak growth stages, while evaporation increases following precipitation events or during early crop development.Key challenges include correcting for high-frequency dampening effects and addressing the analyzer’s sensitivity to water vapor concentration under different conditions, particularly during low-flux periods. Despite these challenges, dual-isotope techniques give valuable insights into crop water use strategies and responses to environmental drivers, offer the opportunity for isotope-based flux partitioning, and give a unique dataset for validating isotope-enabled land surface models.

Transforming agricultural landscapes to be more sustainable and resilient requires integrated and multidisciplinary approaches. Linking automated experimental platforms with living labs can accelerate knowledge gain, enhance interdisciplinary collaboration, and support real-world change by addressing key challenges in current agricultural systems.

The plant-available water (PAW) capacity is determined from the soil water retention (WR) curve as the difference between the water content at field capacity (FC) and the permanent wilting point (WP). To increase the PAW of arable soils, application of amorphous silicate (ASi) has been suggested from results of laboratory studies using standard values of FC and WP. Here, we analyzed effects of a 1% ASi application on PAW of soils from an arable field after one cropping period. Soil WR and hydraulic conductivity functions were fitted to data obtained with Evaporation-based system (HYPROP) and WPC4 devices on intact soil core. The PAW of soil from plots at hilltop and depression positions was compared for matric potentials at WP (h(WP)) and at FC (h(FC)), assuming h(WP) values for a variety of crops and h(FC) values for coarser textured soils (-63 hPa) and finer textured soils (-316 hPa). The ASi-amended soil had larger PAW contents when assuming h(FC) at -316 hPa. The soil at depression plots tended to more PAW after ASi application. The matric flux potential was larger at the same water content. The extension of the WR curve in the dry range with data of dew point PotentiaMeter (WPC4) method helped quantifying PAW values for crop-specific h(WP) values. Results tentatively confirmed that ASi application could lead to increased PAW also under field conditions; present conclusions are limited regarding longer term effects and more practical field applications of ASi. Plain Language Summary The amount of plant-available soil water is characterized by water retention and hydraulic conductivity functions that refer to the amount and mobility of water in soil pores. In variably saturated soil, the pore water in a pressure head range between field capacity (i.e., resisting against gravity drainage) and wilting point (i.e., resisting against further root uptake) is usually considered available to plants. Soil amendments have been suggested to improve the water availability and were often tested in the laboratory. In the present field study, amorphous silicate (ASi) was applied, and soil hydraulic properties were determined after one cropping period. The ASi-amended soil showed mostly larger plant-available soil water as compared to control. Also, crop-specific soil water storage capacities were estimated using dew point-based extended water retention data.

Wetland ecosystems exhibit large spatial and temporal variability in terms of greenhouse gas (GHG) fluxes, necessitating new technologies to ensure that they are well-monitored. Both manual and automated chamber-based approaches are currently costly and thus limited either in spatial or temporal resolution. Following on from Wang et al. (2022), we propose a new, inexpensive autochamber (TraceCatch) for long-term outdoor installation. Costs for one unit are less than 800€ in total, making it affordable and scalable for long-term ecological research, also in lower income countries such as the global south. The system is based on gathering gas samples over two weeks into four gas bags on a high-frequency sampling schedule. TraceCatch is controlled using an Arduino Uno, connected to a peristaltic pump for sampling of chamber headspace air as well as a number of sensors for air temperature and humidity (SHT-41), air pressure (BMP280), and CO2 concentrations (K30FR; 0–5,000 ppm, 30 ppm resolution). The latter are used to track the sealing condition of the chamber. We validated the system using defined injection amounts of technical gas (100% CO2). In addition, the system was applied to measure GHG fluxes from three wetland cores placed inside three ecotrons (UGT EcoLab flex, manufactured by Umwelt-Geräte-Technik GmbH, Germany). Gas samples were collected 4 times a day for 2 weeks during a 1 hour chamber closure time at t0, t20, t40, t60 and subsequently analyzed using gas chromatography (Nexis GC-2030, manufactured by Shimadzu Corporation, Japan). Average GHG fluxes determined over the two-week period were then compared to single measurements obtained using multi-gas sensors (LI-COR LI-7820 and LI-7810 analyzers, manufactured by LI-COR Biosciences, USA). If adopted, the system’s low cost, scale and robustness for permanent field deployments could help improve wetland GHG monitoring, offering a cost-efficient and practical alternative to traditional methods for global-scale biogeochemical cycle assessments.

IntroductionIncreasing greenhouse gas emissions pose a strong threat due to accelerating global warming. N2O emissions are highly important in this regard as N2O is a very powerful greenhouse gas. Agriculture is the main human-induced source for N2O emissions, contributing roughly 60% to total N2O emissions. Soil amorphous silica (ASi) contents are reduced in arable soils due to yearly exports by crop harvest as most crops are silicon accumulator plants. Most recently it has been shown that ASi is increasing water and nutrient availability in soils. Both factors are known to directly and indirectly affect N2O emissions from agroecosystems.MethodsIn this study we conducted a field plot trial on arable soil depleted in ASi and fertilized this soil to its pre-agricultural ASi level.ResultsOur data clearly shows that increasing soil ASi to a pre-agricultural level decreased seasonal N2O emissions by ∼30%.DiscussionThis reduction of N2O emissions due to ASi might be of global relevance as agricultural practice has reduced the ASi content in agricultural soils. If future studies confirm the effect of ASi on N2O emissions, the soil ASi depletion by agricultural practice in the last decades may have led to a substantial increase of N2O emissions.