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Electronic databases of landslides seldom include the triggering mechanisms, rendering these inventories unusable for landslide hazard modeling. We present a method for classifying the triggering mechanisms of landslides in existing inventories, thus, allowing these inventories to aid in landslide hazard modeling corresponding to the correct event chain. Our method uses various geometric characteristics of landslides as the feature space for the machine-learning classifier random forest, resulting in accurate and robust classifications of landslide triggers. We applied the method to six landslide inventories spread over the Japanese archipelago in several different tests and training configurations to demonstrate the effectiveness of our approach. We achieved mean accuracy ranging from 67% to 92%. We also provide an illustrative example of a real-world usage scenario for our method using an additional inventory with unknown ground truth. Furthermore, our feature importance analysis indicates that landslides having identical trigger mechanisms exhibit similar geometric properties.
Arctic and alpine aquatic ecosystems are changing rapidly under recent global warming, threatening water resources by diminishing trophic status and changing biotic composition. Macrophytes play a key role in the ecology of freshwaters and we need to improve our understanding of long-term macrophytes diversity and environmental change so far limited by the sporadic presence of macrofossils in sediments.
In our study, we applied metabarcoding using the trnL P6 loop marker to retrieve macrophyte richness and composition from 179 surface-sediment samples from arctic Siberian and alpine Chinese lakes and three representative lake cores.
The surface-sediment dataset suggests that macrophyte richness and composition are mostly affected by temperature and conductivity, with highest richness when mean July temperatures are higher than 12 degrees C and conductivity ranges between 40 and 400 mu S cm(-1). Compositional turnover during the Late Pleistocene/Holocene is minor in Siberian cores and characterized by a less rich, but stable emergent macrophyte community. Richness decreases during the Last Glacial Maximum and rises during wetter and warmer climate in the Late-glacial and Mid-Holocene.
In contrast, we detect a pronounced change from emergent to submerged taxa at 14 ka in the Tibetan alpine core, which can be explained by increasing temperature and conductivity due to glacial runoff and evaporation.
Our study provides evidence for the suitability of the trnL marker to recover modern and past macrophyte diversity and its applicability for the response of macrophyte diversity to lake-hydrochemical and climate variability predicting contrasting macrophyte changes in arctic and alpine lakes under intensified warming and human impact.
Large-scale groundwater models are required to estimate groundwater availability and to inform water management strategies on the national scale.
However, parameterization of large-scale groundwater models covering areas of major river basins and more is challenging due to the lack of observational data and the mismatch between the scales of modeling and measurements.
In this work, we propose to bridge the scale gap and derive regional hydraulic parameters by spectral analysis of groundwater level fluctuations.
We hypothesize that specific locations in aquifers can reveal regional parameters of the hydraulic system.
We first generate ensembles of synthetic but realistic aquifers which systematically differ in complexity. Applying Liang and Zhang's (2013), , semi-analytical solution for the spectrum of hydraulic head time series, we identify for each ensemble member and at different locations representative aquifer parameters.
Next, we extend our study to investigate the use of spectral analysis in more complex numerical models and in real settings.
Our analyses indicate that the variance of inferred effective transmissivity and storativity values for stochastic aquifer ensembles is small for observation points which are far away from the Dirichlet boundary.
Moreover, the head time series has to cover a period which is roughly 10 times as long as the characteristic time of the aquifer. In deterministic aquifer models we infer equivalent, regionally valid parameters. A sensitivity analysis further reveals that as long as the aquifer length and the position of the groundwater measurement location is roughly known, the parameters can be robustly estimated.
Deforestation is currently a widespread phenomenon and a growing environmental concern in the era of rapid climate change.
In temperate regions, it is challenging to quantify the impacts of deforestation on the catchment dynamics and downstream aquatic ecosystems such as reservoirs and disentangle these from direct climate change impacts, let alone project future changes to inform management.
Here, we tackled this issue by investigating a unique catchment-reservoir system with two reservoirs in distinct trophic states (meso- and eutrophic), both of which drain into the largest drinking water reservoir in Germany.
Due to the prolonged droughts in 2015-2018, the catchment of the mesotrophic reservoir lost an unprecedented area of forest (exponential increase since 2015 and ca. 17.1% loss in 2020 alone).
We coupled catchment nutrient exports (HYPE) and reservoir ecosystem dynamics (GOTM-WET) models using a process-based modeling approach. The coupled model was validated with datasets spanning periods of rapid deforestation, which makes our future projections highly robust.
Results show that in a short-term time scale (by 2035), increasing nutrient flux from the catchment due to vast deforestation (80% loss) can turn the mesotrophic reservoir into a eutrophic state as its counterpart.
Our results emphasize the more prominent impacts of deforestation than the direct impact of climate warming in impairment of water quality and ecological services to downstream aquatic ecosystems. Therefore, we propose to evaluate the impact of climate change on temperate reservoirs by incorporating a time scale-dependent context, highlighting the indirect impact of deforestation in the short-term scale. In the long-term scale (e.g. to 2100), a guiding hypothesis for future research may be that indirect effects (e.g., as mediated by catchment dynamics) are as important as the direct effects of climate warming on aquatic ecosystems.
Landslides in deglaciated and deglaciating mountains represent a major hazard, but their distribution at the spatial scale of entire mountain belts has rarely been studied. Traditional models of landslide distribution assume that landslides are concentrated in the steepest, wettest, and most tectonically active parts of the orogens, where glaciers reached their greatest thickness.
However, based on mapping large landslides (>0.9 km(2)) over an unprecedentedly large area of Southern Patagonia (similar to 305,000 km(2)), we show that the distribution of landslides can have the opposite trend.
We show that the largest landslides within the limits of the former Patagonian Ice Sheet (PIS) cluster along its eastern margins occupying lower, tectonically less active, and arid part of the Patagonian Andes. In contrast to the heavily glaciated, highest elevations of the mountain range, the peripheral regions have been glaciated only episodically, leaving a larger volume of unstable sedimentary and volcanic rocks that are subject to ongoing slope instability.
The benefits of counting butterflies: recommendations for a successful citizen science project
(2022)
Citizen science (CS) projects, being popular across many fields of science, have recently also become a popular tool to collect biodiversity data. Although the benefits of such projects for science and policy making are well understood, relatively little is known about the benefits participants get from these projects as well as their personal backgrounds and motivations. Furthermore, very little is known about their expectations. We here examine these aspects, with the citizen science project "German Butterfly Monitoring" as an example. A questionnaire was sent to all participants of the project and the responses to the questionnaire indicated the following: center dot Most transect walkers do not have a professional background in this field, though they do have a high educational level, and are close to retirement, with a high number of females; center dot An important motivation to join the project is to preserve the natural environment and to contribute to scientific knowledge; center dot Participants benefit by enhancing their knowledge about butterflies and especially their ability to identify different species (taxonomic knowledge); center dot Participants do not have specific expectations regarding the project beyond proper management and coordination, but have an intrinsic sense of working for a greater good. The willingness to join a project is higher if the project contributes to the solution of a problem discussed in the media (here, insect decline). Based on our findings from the analysis of the questionnaire we can derive a set of recommendations for establishing a successful CS project. These include the importance of good communication, e.g., by explaining what the (scientific) purpose of the project is and what problems are to be solved with the help of the data collected in the project. The motivation to join a CS project is mostly intrinsic and CS is a good tool to engage people during difficult times such as the COVID-19 pandemic, giving participants the feeling of doing something useful.
So far, various studies have aimed at decomposing the integrated terrestrial water storage variations observed by satellite gravimetry (GRACE, GRACE-FO) with the help of large-scale hydrological models. While the results of the storage decomposition depend on model structure, little attention has been given to the impact of the way that vegetation is represented in these models. Although vegetation structure and activity represent the crucial link between water, carbon, and energy cycles, their representation in large-scale hydrological models remains a major source of uncertainty. At the same time, the increasing availability and quality of Earth-observation-based vegetation data provide valuable information with good prospects for improving model simulations and gaining better insights into the role of vegetation within the global water cycle. In this study, we use observation-based vegetation information such as vegetation indices and rooting depths for spatializing the parameters of a simple global hydrological model to define infiltration, root water uptake, and transpiration processes. The parameters are further constrained by considering observations of terrestrial water storage anomalies (TWS), soil moisture, evapotranspiration (ET) and gridded runoff ( Q) estimates in a multi-criteria calibration approach. We assess the implications of including varying vegetation characteristics on the simulation results, with a particular focus on the partitioning between water storage components. To isolate the effect of vegetation, we compare a model experiment in which vegetation parameters vary in space and time to a baseline experiment in which all parameters are calibrated as static, globally uniform values. Both experiments show good overall performance, but explicitly including varying vegetation data leads to even better performance and more physically plausible parameter values. The largest improvements regarding TWS and ET are seen in supply-limited (semi-arid) regions and in the tropics, whereas Q simulations improve mainly in northern latitudes. While the total fluxes and storages are similar, accounting for vegetation substantially changes the contributions of different soil water storage components to the TWS variations. This suggests an important role of the representation of vegetation in hydrological models for interpreting TWS variations. Our simulations further indicate a major effect of deeper moisture storages and groundwater-soil moisture-vegetation interactions as a key to understanding TWS variations. We highlight the need for further observations to identify the adequate model structure rather than only model parameters for a reasonable representation and interpretation of vegetation-water interactions.
Neutrons on rails
(2021)
Large-scale measurements of the spatial distribution of water content in soils and snow are challenging for state-of-the-art hydrogeophysical methods. Cosmic-ray neutron sensing (CRNS) is a noninvasive technology that has the potential to bridge the scale gap between conventional in situ sensors and remote sensing products in both, horizontal and vertical domains. In this study, we explore the feasibility and potential of estimating water content in soils and snow with neutron detectors in moving trains. Theoretical considerations quantify the stochastic measurement uncertainty as a function of water content, altitude, resolution, and detector efficiency. Numerical experiments demonstrate that the sensitivity of measured water content is almost unperturbed by train materials. Finally, three distinct real-world experiments provide a proof of concept on short and long-range tracks. With our results a transregional observational soil moisture product becomes a realistic vision within the next years.
Quantifying root water uptake is essential to understanding plant water use and responses to different environmental conditions. However, non-destructive measurement of water transport and related hydraulics in the soil-root system remains a challenge.
Neutron imaging, with its high sensitivity to hydrogen, has become an unparalleled tool to visualize and quantify root water uptake in vivo. In combination with isotopes (e.g., deuterated water) and a diffusion-convection model, root water uptake and hydraulic redistribution in root and soil can be quantified.
Here, we review recent advances in utilizing neutron imaging to visualize and quantify root water uptake, hydraulic redistribution in roots and soil, and root hydraulic properties of different plant species.
Under uniform soil moisture distributions, neutron radiographic studies have shown that water uptake was not uniform along the root and depended on both root type and age. For both tap (e.g., lupine [Lupinus albus L.]) and fibrous (e.g., maize [Zea mays L.]) root systems, water was mainly taken up through lateral roots. In mature maize, the location of water uptake shifted from seminal roots and their laterals to crown/nodal roots and their laterals.
Under non-uniform soil moisture distributions, part of the water taken up during the daytime maintained the growth of crown/nodal roots in the upper, drier soil layers. Ultra-fast neutron tomography provides new insights into 3D water movement in soil and roots. We discuss the limitations of using neutron imaging and propose future directions to utilize neutron imaging to advance our understanding of root water uptake and soil-root interactions.
Wildfires, as a key disturbance in forest ecosystems, are shaping the world's boreal landscapes. Changes in fire regimes are closely linked to a wide array of environmental factors, such as vegetation composition, climate change, and human activity. Arctic and boreal regions and, in particular, Siberian boreal forests are experiencing rising air and ground temperatures with the subsequent degradation of permafrost soils leading to shifts in tree cover and species composition. Compared to the boreal zones of North America or Europe, little is known about how such environmental changes might influence long-term fire regimes in Russia. The larch-dominated eastern Siberian deciduous boreal forests differ markedly from the composition of other boreal forests, yet data about past fire regimes remain sparse. Here, we present a high-resolution macroscopic charcoal record from lacustrine sediments of Lake Khamra (southwest Yakutia, Siberia) spanning the last ca. 2200 years, including information about charcoal particle sizes and morphotypes. Our results reveal a phase of increased charcoal accumulation between 600 and 900 CE, indicative of relatively high amounts of burnt biomass and high fire frequencies. This is followed by an almost 900-year-long period of low charcoal accumulation without significant peaks likely corresponding to cooler climate conditions. After 1750 CE fire frequencies and the relative amount of biomass burnt start to increase again, coinciding with a warming climate and increased anthropogenic land development after Russian colonization. In the 20th century, total charcoal accumulation decreases again to very low levels despite higher fire frequency, potentially reflecting a change in fire management strategies and/or a shift of the fire regime towards more frequent but smaller fires. A similar pattern for different charcoal morphotypes and comparison to a pollen and non-pollen palynomorph (NPP) record from the same sediment core indicate that broad-scale changes in vegetation composition were probably not a major driver of recorded fire regime changes. Instead, the fire regime of the last two millennia at Lake Khamra seems to be controlled mainly by a combination of short-term climate variability and anthropogenic fire ignition and suppression.
Relationships between climate, species composition, and species richness are of particular importance for understanding how boreal ecosystems will respond to ongoing climate change. This study aims to reconstruct changes in terrestrial vegetation composition and taxa richness during the glacial Late Pleistocene and the interglacial Holocene in the sparsely studied southeastern Yakutia (Siberia) by using pollen and sedimentary ancient DNA (sedaDNA) records. Pollen and sedaDNA metabarcoding data using the trnL g and h markers were obtained from a sediment core from Lake Bolshoe Toko. Both proxies were used to reconstruct the vegetation composition, while metabarcoding data were also used to investigate changes in plant taxa richness. The combination of pollen and sedaDNA approaches allows a robust estimation of regional and local past terrestrial vegetation composition around Bolshoe Toko during the last similar to 35,000 years. Both proxies suggest that during the Late Pleistocene, southeastern Siberia was covered by open steppe-tundra dominated by graminoids and forbs with patches of shrubs, confirming that steppe-tundra extended far south in Siberia. Both proxies show disturbance at the transition between the Late Pleistocene and the Holocene suggesting a period with scarce vegetation, changes in the hydrochemical conditions in the lake, and in sedimentation rates. Both proxies document drastic changes in vegetation composition in the early Holocene with an increased number of trees and shrubs and the appearance of new tree taxa in the lake's vicinity. The sedaDNA method suggests that the Late Pleistocene steppe-tundra vegetation supported a higher number of terrestrial plant taxa than the forested Holocene. This could be explained, for example, by the "keystone herbivore" hypothesis, which suggests that Late Pleistocene megaherbivores were able to maintain a high plant diversity. This is discussed in the light of the data with the broadly accepted species-area hypothesis as steppe-tundra covered such an extensive area during the Late Pleistocene.
After a century of semi-restricted floodplain development, Southern Alberta, Canada, was struck by the devastating 2013 Flood. Aging infrastructure and limited property-level floodproofing likely contributed to the $4-6 billion (CAD) losses. Following this catastrophe, Alberta has seen a revival in flood management, largely focused on structural protections. However, concurrent with the recent structural work was a 100,000+ increase in Calgary's population in the 5 years following the flood, leading to further densification of high-hazard areas. This study implements the novel Stochastic Object-based Flood damage Dynamic Assessment (SOFDA) model framework to quantify the progression of the direct-damage flood risk in a mature urban neighborhood after the 2013 Flood. Five years of remote-sensing data, property assessment records, and inundation simulations following the flood are used to construct the model. Results show that in these 5 years, vulnerability trends (like densification) have increased flood risk by 4%; however, recent structural mitigation projects have reduced overall flood risk by 47% for this case study. These results demonstrate that the flood management revival in Southern Alberta has largely been successful at reducing flood risk; however, the gains are under threat from continued development and densification absent additional floodproofing regulations.
Phytoliths in particulate matter released by wind erosion on arable land in La Pampa, Argentina
(2022)
Silicon (Si) is considered a beneficial element in plant nutrition, but its importance on ecosystems goes far beyond that. Various forms of silicon are found in soils, of which the phytogenic pool plays a decisive role due to its good availability. This Si returns to the soil through the decomposition of plant residues, where they then participate in the further cycle as biogenic amorphous silica (bASi) or so-called phytoliths. These have a high affinity for water, so that the water holding capacity and water availability of soils can be increased even by small amounts of ASi. Agricultural land is a considerable global dust source, and dust samples from arable land have shown in cloud formation experiments a several times higher ice nucleation activity than pure mineral dust. Here, particle sizes in the particulate matter fractions (PM) are important, which can travel long distances and reach high altitudes in the atmosphere. Based on this, the research question was whether phytoliths could be detected in PM samples from wind erosion events, what are the main particle sizes of phytoliths and whether an initial quantification was possible.Measurements of PM concentrations were carried out at a wind erosion measuring field in the province La Pampa, Argentina. PM were sampled during five erosion events with Environmental Dust Monitors (EDM). After counting and classifying all particles with diameters between 0.3 and 32 mu m in the EDMs, they are collected on filters. The filters were analyzed by Scanning Electron Microscopy and Energy Dispersive X-Ray analysis (SEM-EDX) to investigate single or ensembles of particles regarding composition and possible origins.The analyses showed up to 8.3 per cent being phytoliths in the emitted dust and up to 25 per cent of organic origin. Particles of organic origin are mostly in the coarse dust fraction, whereas phytoliths are predominately transported in the finer dust fractions. Since phytoliths are both an important source of Si as a plant nutrient and are also involved in soil C fixation, their losses from arable land via dust emissions should be considered and its specific influence on atmospheric processes should be studied in detail in the future.
Urban air pollution is a substantial threat to human health. Traffic emissions remain a large contributor to air pollution in urban areas. The mobility restrictions put in place in response to the COVID-19 pandemic provided a large-scale real-world experiment that allows for the evaluation of changes in traffic emissions and the corresponding changes in air quality. Here we use observational data, as well as modelling, to analyse changes in nitrogen dioxide, ozone, and particulate matter resulting from the COVID-19 restrictions at the height of the lockdown period in Spring of 2020. Accounting for the influence of meteorology on air quality, we found that reduction of ca. 30-50 % in traffic counts, dominated by changes in passenger cars, corresponded to reductions in median observed nitrogen dioxide concentrations of ca. 40 % (traffic and urban background locations) and a ca. 22 % increase in ozone (urban background locations) during weekdays. Lesser reductions in nitrogen dioxide concentrations were observed at urban background stations at weekends, and no change in ozone was observed. The modelled reductions in median nitrogen dioxide at urban background locations were smaller than the observed reductions and the change was not significant. The model results showed no significant change in ozone on weekdays or weekends. The lack of a simulated weekday/weekend effect is consistent with previous work suggesting that NOx emissions from traffic could be significantly underestimated in European cities by models. These results indicate the potential for improvements in air quality due to policies for reducing traffic, along with the scale of reductions that would be needed to result in meaningful changes in air quality if a transition to sustainable mobility is to be seriously considered. They also confirm once more the highly relevant role of traffic for air quality in urban areas.
We traced diatom composition and diversity through time using diatom-derived sedimentary ancient DNA (sedaDNA) from eastern continental slope sediments off Kamchatka (North Pacific) by applying a short, diatom-specific marker on 63 samples in a DNA metabarcoding approach. The sequences were assigned to diatoms that are common in the area and characteristic of cold water. SedaDNA allowed us to observe shifts of potential lineages from species of the genus Chaetoceros that can be related to different climatic phases, suggesting that pre-adapted ecotypes might have played a role in the long-term success of species in areas of changing environmental conditions. These sedaDNA results complement our understanding of the long-term history of diatom assemblages and their general relationship to environmental conditions of the past. Sea-ice diatoms (Pauliella taeniata [Grunow] Round & Basson, Attheya septentrionalis [ostrup] R. M. Crawford and Nitzschia frigida [Grunow]) detected during the late glacial and Younger Dryas are in agreement with previous sea-ice reconstructions. A positive correlation between pennate diatom richness and the sea-ice proxy IP25 suggests that sea ice fosters pennate diatom richness, whereas a negative correlation with June insolation and temperature points to unfavorable conditions during the Holocene. A sharp increase in proportions of freshwater diatoms at similar to 11.1 cal kyr BP implies the influence of terrestrial runoff and coincides with the loss of 42% of diatom sequence variants. We assume that reduced salinity at this time stabilized vertical stratification which limited the replenishment of nutrients in the euphotic zone.
Ranking local climate policy
(2021)
Climate mitigation and climate adaptation are crucial tasks for urban areas and can involve synergies as well as trade-offs. However, few studies have examined how mitigation and adaptation efforts relate to each other in a large number of differently sized cities, and therefore we know little about whether forerunners in mitigation are also leading in adaptation or if cities tend to focus on just one policy field. This article develops an internationally applicable approach to rank cities on climate policy that incorporates multiple indicators related to (1) local commitments on mitigation and adaptation, (2) urban mitigation and adaptation plans and (3) climate adaptation and mitigation ambitions. We apply this method to rank 104 differently sized German cities and identify six clusters: climate policy leaders, climate adaptation leaders, climate mitigation leaders, climate policy followers, climate policy latecomers and climate policy laggards. The article seeks explanations for particular cities' positions and shows that coping with climate change in a balanced way on a high level depends on structural factors, in particular city size, the pathways of local climate policies since the 1990s and funding programmes for both climate mitigation and adaptation.
Knowing the source and runout of debris flows can help in planning strategies aimed at mitigating these hazards. Our research in this paper focuses on developing a novel approach for optimizing runout models for regional susceptibility modelling, with a case study in the upper Maipo River basin in the Andes of Santiago, Chile. We propose a two-stage optimization approach for automatically selecting parameters for estimating runout path and distance. This approach optimizes the random-walk and Perla et al.'s (PCM) two-parameter friction model components of the open-source Gravitational Process Path (GPP) modelling framework. To validate model performance, we assess the spatial transferability of the optimized runout model using spatial crossvalidation, including exploring the model's sensitivity to sample size. We also present diagnostic tools for visualizing uncertainties in parameter selection and model performance. Although there was considerable variation in optimal parameters for individual events, we found our runout modelling approach performed well at regional prediction of potential runout areas. We also found that although a relatively small sample size was sufficient to achieve generally good runout modelling performance, larger samples sizes (i.e. >= 80) had higher model performance and lower uncertainties for estimating runout distances at unknown locations. We anticipate that this automated approach using the open-source R software and the System for Automated Geoscientific Analyses geographic information system (SAGA-GIS) will make process-based debris-flow models more readily accessible and thus enable researchers and spatial planners to improve regional-scale hazard assessments.
We present a chronology framework named LegacyAge 1.0 containing harmonized chronologies for 2831 pollen records (downloaded from the Neotoma Paleoecology Database and the supplementary Asian datasets) together with their age control points and metadata in machine-readable data formats.
All chronologies use the Bayesian framework implemented in Bacon version 2.5.3. Optimal parameter settings of priors (accumulation.shape, memory.strength, memory.mean, accumulation.rate, and thickness) were identified based on information in the original publication or iteratively after preliminary model inspection.
The most common control points for the chronologies are radiocarbon dates (86.1 %), calibrated by the latest calibration curves (IntCal20 and SHCal20 for the terrestrial radiocarbon dates in the Northern Hemisphere and Southern Hemisphere and Marine20 for marine materials).
The original publications were consulted when dealing with outliers and inconsistencies. Several major challenges when setting up the chronologies included the waterline issue (18.8% of records), reservoir effect (4.9 %), and sediment deposition discontinuity (4.4 %).
Finally, we numerically compare the LegacyAge 1.0 chronologies to those published in the original publications and show that the reliability of the chronologies of 95.4% of records could be improved according to our assessment.
Our chronology framework and revised chronologies provide the opportunity to make use of the ages and age uncertainties in synthesis studies of, for example, pollen-based vegetation and climate change.
The LegacyAge 1.0 dataset, including metadata, datings, harmonized chronologies, and R code used, is openaccess and available at PANGAEA (https://doi.org/10.1594/PANGAEA.933132; Li et al., 2021) and Zenodo (https://doi.org/10.5281/zenodo.5815192; Li et al., 2022), respectively.
Drought and the availability of mineable phosphorus minerals used for fertilization are two of the important issues agriculture is facing in the future. High phosphorus availability in soils is necessary to maintain high agricultural yields. Drought is one of the major threats for terrestrial ecosystem performance and crop production in future. Among the measures proposed to cope with the upcoming challenges of intensifying drought stress and to decrease the need for phosphorus fertilizer application is the fertilization with silica (Si). Here we tested the importance of soil Si fertilization on wheat phosphorus concentration as well as wheat performance during drought at the field scale. Our data clearly showed a higher soil moisture for the Si fertilized plots. This higher soil moisture contributes to a better plant performance in terms of higher photosynthetic activity and later senescence as well as faster stomata responses ensuring higher productivity during drought periods. The plant phosphorus concentration was also higher in Si fertilized compared to control plots. Overall, Si fertilization or management of the soil Si pools seem to be a promising tool to maintain crop production under predicted longer and more serve droughts in the future and reduces phosphorus fertilizer requirements.