Institut für Bodenkunde und Standortslehre

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Linking transcriptional dynamics of CH4-cycling grassland soil microbiomes to seasonal gas fluxes
(2022) Täumer, Jana; Marhan, Sven; Groß, Verena; Jensen, Corinna; Kuss, Andreas W.; Kolb, Steffen; Urich, Tim; Täumer, Jana; Institute of Microbiology, Center for Functional Genomics of Microbes, University of Greifswald, Greifswald, Germany; Marhan, Sven; Institute of Soil Science and Land Evaluation, Soil Biology Department, University of Hohenheim, Stuttgart, Germany; Groß, Verena; Institute of Microbiology, Center for Functional Genomics of Microbes, University of Greifswald, Greifswald, Germany; Jensen, Corinna; Human Molecular Genetics Group, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany; Kuss, Andreas W.; Human Molecular Genetics Group, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany; Kolb, Steffen; Thaer Institute, Faculty of Life Sciences, Humboldt University of Berlin, Berlin, Germany; Urich, Tim; Institute of Microbiology, Center for Functional Genomics of Microbes, University of Greifswald, Greifswald, Germany
AbstractSoil CH4 fluxes are driven by CH4-producing and -consuming microorganisms that determine whether soils are sources or sinks of this potent greenhouse gas. To date, a comprehensive understanding of underlying microbiome dynamics has rarely been obtained in situ. Using quantitative metatranscriptomics, we aimed to link CH4-cycling microbiomes to net surface CH4 fluxes throughout a year in two grassland soils. CH4 fluxes were highly dynamic: both soils were net CH4 sources in autumn and winter and sinks in spring and summer, respectively. Correspondingly, methanogen mRNA abundances per gram soil correlated well with CH4 fluxes. Methanotroph to methanogen mRNA ratios were higher in spring and summer, when the soils acted as net CH4 sinks. CH4 uptake was associated with an increased proportion of USCα and γ pmoA and pmoA2 transcripts. We assume that methanogen transcript abundance may be useful to approximate changes in net surface CH4 emissions from grassland soils. High methanotroph to methanogen ratios would indicate CH4 sink properties. Our study links for the first time the seasonal transcriptional dynamics of CH4-cycling soil microbiomes to gas fluxes in situ. It suggests mRNA transcript abundances as promising indicators of dynamic ecosystem-level processes.
Proposal and extensive test of a calibration protocol for crop phenology models
(2023) Wallach, Daniel; Palosuo, Taru; Thorburn, Peter; Mielenz, Henrike; Buis, Samuel; Hochman, Zvi; Gourdain, Emmanuelle; Andrianasolo, Fety; Dumont, Benjamin; Ferrise, Roberto; Gaiser, Thomas; Garcia, Cecile; Gayler, Sebastian; Harrison, Matthew; Hiremath, Santosh; Horan, Heidi; Hoogenboom, Gerrit; Jansson, Per-Erik; Jing, Qi; Justes, Eric; Kersebaum, Kurt-Christian; Launay, Marie; Lewan, Elisabet; Liu, Ke; Mequanint, Fasil; Moriondo, Marco; Nendel, Claas; Padovan, Gloria; Qian, Budong; Schütze, Niels; Seserman, Diana-Maria; Shelia, Vakhtang; Souissi, Amir; Specka, Xenia; Srivastava, Amit Kumar; Trombi, Giacomo; Weber, Tobias K. D.; Weihermüller, Lutz; Wöhling, Thomas; Seidel, Sabine J.; Wallach, Daniel; Institute of Crop Science and Resource Conservation, University of Bonn, Bonn, Germany; Palosuo, Taru; Natural Resources Institute Finland (Luke), Helsinki, Finland; Thorburn, Peter; CSIRO Agriculture and Food, Brisbane, Australia; Mielenz, Henrike; Institute for Crop and Soil Science, Julius Kühn Institute (JKI) – Federal Research Centre for Cultivated Plants, Braunschweig, Germany; Buis, Samuel; INRAE, UMR 1114 EMMAH, Avignon, France; Hochman, Zvi; CSIRO Agriculture and Food, Brisbane, Australia; Gourdain, Emmanuelle; ARVALIS - Institut du végétal Paris, Paris, France; Andrianasolo, Fety; ARVALIS - Institut du végétal Paris, Paris, France; Dumont, Benjamin; Plant Sciences & TERRA Teaching and Research Centre, Gembloux Agro-Bio Tech, University of Liege, Gembloux, Belgium; Ferrise, Roberto; Department of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence, Florence, Italy; Gaiser, Thomas; Institute of Crop Science and Resource Conservation, University of Bonn, Bonn, Germany; Garcia, Cecile; ARVALIS - Institut du végétal Paris, Paris, France; Gayler, Sebastian; Institute of Soil Science and Land Evaluation, Biogeophysics, University of Hohenheim, Stuttgart, Germany; Harrison, Matthew; Tasmanian Institute of Agriculture, University of Tasmania, Launceston, Tasmania, Australia; Hiremath, Santosh; Aalto University School of Science, Espoo, Finland; Horan, Heidi; CSIRO Agriculture and Food, Brisbane, Australia; Hoogenboom, Gerrit; Global Food Systems Institute, University of Florida, Gainesville, USA; Jansson, Per-Erik; Royal Institute of Technology (KTH), Stockholm, Sweden; Jing, Qi; Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, Canada; Justes, Eric; PERSYST Department, CIRAD, Montpellier, France; Kersebaum, Kurt-Christian; Tropical Plant Production and Agricultural Systems Modelling (TROPAGS), University of Göttingen, Göttingen, Germany; Launay, Marie; INRAE, US 1116 AgroClim, Avignon, France; Lewan, Elisabet; Department of Soil and Environment, Swedish University of Agricultural Sciences (SLU), Uppsala, Sweden; Liu, Ke; Tasmanian Institute of Agriculture, University of Tasmania, Launceston, Tasmania, Australia; Mequanint, Fasil; Institute of Soil Science and Land Evaluation, Biogeophysics, University of Hohenheim, Stuttgart, Germany; Moriondo, Marco; CNR-IBE, Firenze, Italy; Nendel, Claas; Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany; Padovan, Gloria; Department of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence, Florence, Italy; Qian, Budong; Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, Canada; Schütze, Niels; Institute of Hydrology and Meteorology, Chair of Hydrology, Technische Universität Dresden, Dresden, Germany; Seserman, Diana-Maria; Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany; Shelia, Vakhtang; Global Food Systems Institute, University of Florida, Gainesville, USA; Souissi, Amir; Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, Canada; Specka, Xenia; Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany; Srivastava, Amit Kumar; Institute of Crop Science and Resource Conservation, University of Bonn, Bonn, Germany; Trombi, Giacomo; Department of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence, Florence, Italy; Weber, Tobias K. D.; Faculty of Organic Agriculture, Soil Science Section, University of Kassel, Witzenhausen, Germany; Weihermüller, Lutz; Institute of Bio- and Geosciences - IBG-3, Agrosphere, Forschungszentrum Jülich GmbH, Jülich, Germany; Wöhling, Thomas; Lincoln Agritech Ltd., Hamilton, New Zealand; Seidel, Sabine J.; Institute of Crop Science and Resource Conservation, University of Bonn, Bonn, Germany
A major effect of environment on crops is through crop phenology, and therefore, the capacity to predict phenology for new environments is important. Mechanistic crop models are a major tool for such predictions, but calibration of crop phenology models is difficult and there is no consensus on the best approach. We propose an original, detailed approach for calibration of such models, which we refer to as a calibration protocol. The protocol covers all the steps in the calibration workflow, namely choice of default parameter values, choice of objective function, choice of parameters to estimate from the data, calculation of optimal parameter values, and diagnostics. The major innovation is in the choice of which parameters to estimate from the data, which combines expert knowledge and data-based model selection. First, almost additive parameters are identified and estimated. This should make bias (average difference between observed and simulated values) nearly zero. These are “obligatory” parameters, that will definitely be estimated. Then candidate parameters are identified, which are parameters likely to explain the remaining discrepancies between simulated and observed values. A candidate is only added to the list of parameters to estimate if it leads to a reduction in BIC (Bayesian Information Criterion), which is a model selection criterion. A second original aspect of the protocol is the specification of documentation for each stage of the protocol. The protocol was applied by 19 modeling teams to three data sets for wheat phenology. All teams first calibrated their model using their “usual” calibration approach, so it was possible to compare usual and protocol calibration. Evaluation of prediction error was based on data from sites and years not represented in the training data. Compared to usual calibration, calibration following the new protocol reduced the variability between modeling teams by 22% and reduced prediction error by 11%.
Diagnosing similarities in probabilistic multi-model ensembles: An application to soil–plant-growth-modeling
(2022) Schäfer Rodrigues Silva, Aline; Weber, Tobias K. D.; Gayler, Sebastian; Guthke, Anneli; Höge, Marvin; Nowak, Wolfgang; Streck, Thilo; Schäfer Rodrigues Silva, Aline; Department of Stochastic Simulation and Safety Research for Hydrosystems, Institute for Modelling Hydraulic and Environmental Systems/Cluster of Excellence “Data-Integrated Simulation Science”, University of Stuttgart, Stuttgart, Germany; Weber, Tobias K. D.; Department of Biogeophysics, Institute of Soil Science and Land Evaluation, University of Hohenheim, Stuttgart, Germany; Gayler, Sebastian; Department of Biogeophysics, Institute of Soil Science and Land Evaluation, University of Hohenheim, Stuttgart, Germany; Guthke, Anneli; Junior Research Group for Statistical Model-Data Integration, Cluster of Excellence “Data-Integrated Simulation Science”, University of Stuttgart, Stuttgart, Germany; Höge, Marvin; Department of Systems Analysis, Integrated Assessment and Modelling, Eawag-Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland; Nowak, Wolfgang; Department of Stochastic Simulation and Safety Research for Hydrosystems, Institute for Modelling Hydraulic and Environmental Systems/Cluster of Excellence “Data-Integrated Simulation Science”, University of Stuttgart, Stuttgart, Germany; Streck, Thilo; Department of Biogeophysics, Institute of Soil Science and Land Evaluation, University of Hohenheim, Stuttgart, Germany
There has been an increasing interest in using multi-model ensembles over the past decade. While it has been shown that ensembles often outperform individual models, there is still a lack of methods that guide the choice of the ensemble members. Previous studies found that model similarity is crucial for this choice. Therefore, we introduce a method that quantifies similarities between models based on so-called energy statistics. This method can also be used to assess the goodness-of-fit to noisy or deterministic measurements. To guide the interpretation of the results, we combine different visualization techniques, which reveal different insights and thereby support the model development. We demonstrate the proposed workflow on a case study of soil–plant-growth modeling, comparing three models from the Expert-N library. Results show that model similarity and goodness-of-fit vary depending on the quantity of interest. This confirms previous studies that found that “there is no single best model” and hence, combining several models into an ensemble can yield more robust results.
Improvement of the Barometric Process Separation (BaPS) technique to measure microbial C and N transformation rates in arable high-pH soils
(2023) Munz, Hannah; Streck, Thilo
The Barometric Process Separation (BaPS) technique provides a simple way to determine the rates of heterotrophic microbial respiration, gross nitrification and denitrification in soils by crossbalancing CO2 and O2 production and consumption rates in a closed incubation system via gas balances. The BaPS measuring system has some methodological limitations, especially in soils of pH above 6.5. In these soils, the CO2 balance of the incubation system is strongly influenced by abiotic fluxes driven by thermodynamic equilibration of the CO2 - carbonate system of the soil solution, i.e. a non-negligible fraction of CO2 produced via respiration is buffered by the soil solution. Correct quantification of this flux is necessary to correctly determine the microbial process rates. It has been shown that the thermodynamic calculation of CO2 dissolution does not deliver accurate results, leading to uncertainty in and considerable over- and underestimations of the microbial process rates. In this dissertation, this problem has been solved by developing a method to experimentally determine abiotic CO2 buffering, the Sterilization-CO2-Injection (SCI) method. Moreover, the soil specific adaptation of the Respiratory Quotient (RQ) has been studied in detail in order to reestablishes the advantage of the BaPS of operating isotope-free. Furthermore, in this dissertation we present an easy on-site calibration method for the BaPS sensor set in order to garantee optimal data quality although the maintenance service by the manufacturer has been canceled. Overall, the presented adaptations and improvements enhance the accuracy of BaPS measurements and might enhance its value as a tool for measuring gross nitrification rates in the future.
Seed dispersal by wind decreases when plants are water‐stressed, potentially counteracting species coexistence and niche evolution
(2021) Zhu, Jinlei; Lukić, Nataša; Rajtschan, Verena; Walter, Julia; Schurr, Frank M.
Hydrology is a major environmental factor determining plant fitness, and hydrological niche segregation (HNS) has been widely used to explain species coexistence. Nevertheless, the distribution of plant species along hydrological gradients does not only depend on their hydrological niches but also depend on their seed dispersal, with dispersal either weakening or reinforcing the effects of HNS on coexistence. However, it is poorly understood how seed dispersal responds to hydrological conditions. To close this gap, we conducted a common‐garden experiment exposing five wind‐dispersed plant species (Bellis perennis, Chenopodium album, Crepis sancta, Hypochaeris glabra, and Hypochaeris radicata) to different hydrological conditions. We quantified the effects of hydrological conditions on seed production and dispersal traits, and simulated seed dispersal distances with a mechanistic dispersal model. We found species‐specific responses of seed production, seed dispersal traits, and predicted dispersal distances to hydrological conditions. Despite these species‐specific responses, there was a general positive relationship between seed production and dispersal distance: Plants growing in favorable hydrological conditions not only produce more seeds but also disperse them over longer distances. This arises mostly because plants growing in favorable environments grow taller and thus disperse their seeds over longer distances. We postulate that the positive relationship between seed production and dispersal may reduce the concentration of each species to the environments favorable for it, thus counteracting species coexistence. Moreover, the resulting asymmetrical gene flow from favorable to stressful habitats may slow down the microevolution of hydrological niches, causing evolutionary niche conservatism. Accounting for context‐dependent seed dispersal should thus improve ecological and evolutionary models for the spatial dynamics of plant populations and communities.
Effects of farmland conversion to orchard or agroforestry on soil organic carbon fractions in an arid desert oasis area
(2022) Wang, Weixia; Ingwersen, Joachim; Yang, Guang; Wang, Zhenxi; Alimu, Aliya
In southern Xinjiang province, northwest China, farmland is undergoing rapid conversion to orchards or agroforestry. This has improved land-use efficiency but has also caused drastic ecological changes in this region. This study investigated the effects of farmland conversion to orchard or agroforestry on soil total organic carbon (TOC) and several soil labile fractions: readily oxidizable carbon (ROC), light fraction organic carbon (LFOC), and dissolved organic carbon (DOC). Soil samples were collected from seven cropping treatments: a monocultured wheat field (Mono), a 5-year-old jujube orchard (5 J), a 5-year-old jujube/wheat alley cropping system (5 JW), a 10-year-old jujube orchard (10 J), a 10-year-old jujube/wheat alley cropping system (10 JW), a 15-year-old jujube orchard (15 J), and a 15-year-old jujube/wheat alley cropping system (15 JW). The results show that the ROC concentrations varied from 0.17 ± 0.09 g/kg to 2.35 ± 0.05 g/kg across all land-use types and soil depths studied. It was higher in the 0–10 cm and 10–20 cm layers of treatment 10 JW than in other treatments and significantly greater than in the Mono treatment. The highest value of DOC was reached at 593.04 mg/kg in the 15 JW treatment at 0–10 cm. Labile organic carbon decreased with increasing depth in all treatments. The proportion of ROC and LFOC to TOC decreased with increasing soil depth. In all treatments, the ratio of DOC to TOC generally decreased initially and then increased again with increasing depth. Correlation analysis showed that ROC, LFOC, and DOC were closely correlated with TOC (p < 0.01). The ROC, LFOC, and DOC concentrations were significantly correlated with each other (p < 0.01). Following conversion of farmland to jujube orchard or agroforestry, the content and activity of soil organic carbon tended to increase due to augmentation of plant residues. Thus, jujube orchards and agroforestry systems are effective methods to restore soil organic carbon.
Do agricultural advisory services in Europe have the capacity to support the transition to healthy soils?
(2022) Ingram, Julie; Mills, Jane; Black, Jasmine E.; Chivers, Charlotte-Anne; Aznar-Sánchez, José A.; Elsen, Annemie; Frac, Magdalena; López-Felices, Belén; Mayer-Gruner, Paula; Skaalsveen, Kamilla; Stolte, Jannes; Tits, Mia
The need to provide appropriate information, technical advice and facilitation to support farmers in transitioning towards healthy soils is increasingly clear, and the role of the Agricultural Advisory Services (AAS) in this is critical. However, the transformation of AAS (plurality, commercialisation, fragmentation, decentralisation) brings new challenges for delivering advice to support soil health management. This paper asks: To what extent do agricultural advisory services have the capacity to support the transition to healthy soils across Europe? Using the ‘best fit’ framework, analytical characteristics of the AAS relevant to the research question (governance structures, management, organisational and individual capacities) were identified. Analysis of 18 semi-structured expert interviews across 6 case study countries in Europe, selected to represent a range of contexts, was undertaken. Capacities to provide soil health management (SHM) advice are constrained by funding arrangements, limited adviser training and professional development, adviser motivations and professional cultures, all determined by institutional conditions. This has resulted in a narrowing down of access and content of soil advice and a reduced capacity to support the transition in farming to healthy soils. The extent to which emerging policy and market drivers incentivise enhanced capacities in AAS is an important area for future research.
A new framework to assess sustainability of soil improving cropping systems in Europe
(2022) Alaoui, Abdallah; Hallama, Moritz; Bär, Roger; Panagea, Ioanna; Bachmann, Felicitas; Pekrun, Carola; Fleskens, Luuk; Kandeler, Ellen; Hessel, Rudi
Assessing agricultural sustainability is one of the most challenging tasks related to expertise and support methodologies because it entails multidisciplinary aspects and builds on cultural and value-based elements. Thus, agricultural sustainability should be considered a social concept, reliable enough to support decision makers and policy development in a broad context. The aim of this manuscript was to develop a methodology for the assessment of the sustainability of soil improving cropping systems (SICS) in Europe. For this purpose, a decision tree based on weights (%) was chosen because it allows more flexibility. The methodology was tested with data from the SoilCare Horizon 2020 study site in Germany for the assessment of the impact of the integration of cover crops into the crop rotation. The effect on the environmental indicators was slightly positive, but most assessed properties did not change over the short course of the experiment. Farmers reported that the increase in workload was outweighed by a reputation gain for using cover crops. The incorporation of cover crops reduced slightly the profitability, due to the costs for seeds and establishment of cover crops. The proposed assessment methodology provides a comprehensive summary to assess the agricultural sustainability of SICS.
Soil-improving cropping systems for sustainable and profitable farming in Europe
(2022) Hessel, Rudi; Wyseure, Guido; Panagea, Ioanna ; Alaoui, Abdallah; Reed, Mark S.; van Delden, Hedwig; Muro, Melanie; Mills, Jane; Oenema, Oene; Areal, Francisco; van den Elsen, Erik; Verzandvoort, Simone; Assinck, Falentijn; Elsen, Annemie; Lipiec, Jerzy; Koutroulis, Aristeidis; O’Sullivan, Lilian; Bolinder, Martin A.; Fleskens, Luuk; Kandeler, Ellen; Montanarella, Luca; Heinen, Marius; Toth, Zoltan; Hallama, Moritz; Cuevas, Julián; Baartman, Jantiene E. M.; Piccoli, Ilaria; Dalgaard, Tommy; Stolte, Jannes; Black, Jasmine E.; Chivers, Charlotte-Anne
Soils form the basis for agricultural production and other ecosystem services, and soil management should aim at improving their quality and resilience. Within the SoilCare project, the concept of soil-improving cropping systems (SICS) was developed as a holistic approach to facilitate the adoption of soil management that is sustainable and profitable. SICS selected with stakeholders were monitored and evaluated for environmental, sociocultural, and economic effects to determine profitability and sustainability. Monitoring results were upscaled to European level using modelling and Europe-wide data, and a mapping tool was developed to assist in selection of appropriate SICS across Europe. Furthermore, biophysical, sociocultural, economic, and policy reasons for (non)adoption were studied. Results at the plot/farm scale showed a small positive impact of SICS on environment and soil, no effect on sustainability, and small negative impacts on economic and sociocultural dimensions. Modelling showed that different SICS had different impacts across Europe—indicating the importance of understanding local dynamics in Europe-wide assessments. Work on adoption of SICS confirmed the role economic considerations play in the uptake of SICS, but also highlighted social factors such as trust. The project’s results underlined the need for policies that support and enable a transition to more sustainable agricultural practices in a coherent way.
Bayesian multi-purpose modelling of plant growth and development across scales
(2024) Viswanathan, Michelle; Streck, Thilo
Crop models are invaluable tools for predicting the impact of climate change on crop production and assessing the fate of agrochemicals in the environment. To ensure robust predictions of crop yield, for example, models are usually calibrated to observations of plant growth and phenological development using different methods. However, various sources of uncertainty exist in the model inputs, parameters, equations, observations, etc., which need to be quantified, especially when model predictions influence decision-making. Bayesian inference is suitable for this purpose since it enables different uncertainties to be taken into account, while also incorporating prior knowledge. Thus, Bayesian methods are used for model calibration to improve the model and enhance prediction quality. However, this improvement in the model and its prediction quality does not always occur due to the presence of model errors. These errors are a result of incomplete knowledge or simplifying assumptions made to reduce model complexity and computational costs. For instance, crop models are used for regional scale simulations thereby assuming that these point-based models are able to represent processes that act at regional scale. Additionally, simple statistical assumptions are made about uncertainty in model errors during Bayesian calibration. In this work, the problems arising from such applications are analysed and other Bayesian approaches are investigated as potential solutions. A conceptually simple Bayesian approach of sequentially updating a maize phenology model, an important component in plant models, was investigated as yearly observation data were gathered. In this approach, model parameters and their uncertainty were estimated while accounting for observation uncertainty. As the model was calibrated to increasing amounts of observation data, the uncertainty in the model parameters reduced as expected. However, the prediction quality of the calibrated model did not always improve in spite of more data being available for potentially improving the model. This discrepancy was attributed to the presence of errors in the model structure, possibly due to missing environmental dependencies that were ignored during calibration. As a potential solution, the model was calibrated using Bayesian multi-level modelling which could account for model errors. Furthermore, this approach accounted for the hierarchical data structure of cultivars nested within maize ripening groups, thus simultaneously obtaining model parameter estimates for the species, ripening groups and cultivars. Applying this approach improved the model's calibration quality and further aided in identifying possible model deficits related to temperature effects in the post-flowering phase of development and soil moisture. As another potential solution, an alternative calibration strategy was tested which accounted for model errors by relaxing the strict statistical assumptions in classical Bayesian inference. This was done by first acknowledging that due to model errors, different data sets may yield diverse solutions to the calibration problem. Thus, instead of fitting the model to all data sets together and finding a compromise solution, a fit was found to each data set. This was implemented by modifying the likelihood, a term that accounts for information content of the data. An additive rather than the classical multiplicative strategy was used to combine likelihood values from different data sets. This approach resulted in conservative but more reliable predictions than the classical approach in most cases. The classical approach resulted in better predictions only when the prediction target represented an average of the calibration data. The above-mentioned results show that Bayesian methods with representative error assumptions lead to improved model performance and a more realistic quantification of uncertainties. This is a step towards the effective application of process-based crop models for developing suitable adaptation and mitigation strategies.
Microbial drivers of plant richness and productivity in a grassland restoration experiment along a gradient of land‐use intensity
(2022) Abrahão, Anna; Marhan, Sven; Boeddinghaus, Runa S.; Nawaz, Ali; Wubet, Tesfaye; Hölzel, Norbert; Klaus, Valentin H.; Kleinebecker, Till; Freitag, Martin; Hamer, Ute; Oliveira, Rafael S.; Lambers, Hans; Kandeler, Ellen
Plant–soil feedbacks (PSFs) underlying grassland plant richness and productivity are typically coupled with nutrient availability; however, we lack understanding of how restoration measures to increase plant diversity might affect PSFs. We examined the roles of sward disturbance, seed addition and land‐use intensity (LUI) on PSFs. We conducted a disturbance and seed addition experiment in 10 grasslands along a LUI gradient and characterized plant biomass and richness, soil microbial biomass, community composition and enzyme activities. Greater plant biomass at high LUI was related to a decrease in the fungal to bacterial ratios, indicating highly productive grasslands to be dominated by bacteria. Lower enzyme activity per microbial biomass at high plant species richness indicated a slower carbon (C) cycling. The relative abundance of fungal saprotrophs decreased, while pathogens increased with LUI and disturbance. Both fungal guilds were negatively associated with plant richness, indicating the mechanisms underlying PSFs depended on LUI. We show that LUI and disturbance affect fungal functional composition, which may feedback on plant species richness by impeding the establishment of pathogen‐sensitive species. Therefore, we highlight the need to integrate LUI including its effects on PSFs when planning for practices that aim to optimize plant diversity and productivity.
Sanitized human urine (Oga) as a fertilizer auto-innovation from women farmers in Niger
(2021) Moussa, Hannatou O.; Nwankwo, Charles I.; Aminou, Ali M.; Stern, David A.; Haussmann, Bettina I. G.; Herrmann, Ludger
Poor soil chemical fertility and climate change restrict pearl millet grain yield in Niger Republic. Apart from the seedball technology, which targets majorly early phosphorus supply to the plants, the recommended practices of mineral fertilization and seed treatments (coating and priming) are barely affordable to the local farmers in particular. In the case of female farmers, who usually have chemically infertile farmlands often located far away from their homestead, low pearl millet grain yield can be exacerbated. In quest for a cheap, affordable, and effective solution, we hypothesized that the application of sanitized human urine (Oga), in combination with organic manure (OM) or solely, increases pearl millet panicle yield in women’s fields and on different local soils. In on-farm large-N trials (N = 681) with women farmers in two regions of Niger (Maradi, Tillabery), pearl millet panicle yields were compared between the control (farmer practice), and a combination of Oga and OM in the first and second year, and Oga alone in the third year. Our results showed an average panicle yield increase of about +30%, representing +200 to +300 kg ha−1. Major factors determining the yield effect are season, village, and local soil type. This study shows for the first time that Oga innovation can be used to increase pearl millet panicle yield particularly in the low fertile soils of women’s farmlands in Niger. Oga innovation is affordable, locally available, and does not pose a risk to resource-poor female farmers of Niger.
The role of crop management practices and adaptation options to minimize the impact of climate change on maize (Zea mays L.) production for Ethiopia
(2023) Feleke, Hirut Getachew; Savage, Michael J.; Fantaye, Kindie Tesfaye; Rettie, Fasil Mequanint
Climate change impact assessment along with adaptation measures are key for reducing the impact of climate change on crop production. The impact of current and future climate change on maize production was investigated, and the adaptation role of shifting planting dates, different levels of nitrogen fertilizer rates, and choice of maize cultivar as possible climate change adaptation strategies were assessed. The study was conducted in three environmentally contrasting sites in Ethiopia, namely: Ambo, Bako, and Melkassa. Future climate data were obtained from seven general circulation models (GCMs), namely: CanESM2, CNRM-CM5, CSIRO-MK3-6-0, EC-EARTH, HadGEM2-ES, IPSL-CM5A-MR, and MIROC5 for the highest representative concentration pathway (RCP 8.5). GCMs were bias-corrected at site level using a quantile-quantile mapping method. APSIM, AquaCrop, and DSSAT crop models were used to simulate the baseline (1995–2017) and 2030s (2021–2050) maize yields. The result indicated that the average monthly maximum air temperature in the 2030s could increase by 0.3–1.7 °C, 0.7–2.2 °C, and 0.8–1.8 °C in Ambo, Bako, and Melkassa, respectively. For the same sites, the projected increase in average monthly minimum air temperature was 0.6–1.7 °C, 0.8–2.3 °C, and 0.6–2.7 °C in that order. While monthly total precipitation for the Kiremt season (June to September) is projected to increase by up to 55% (365 mm) for Ambo and 75% (241 mm) for Bako respectively, whereas a significant decrease in monthly total precipitation is projected for Melkassa by 2030. Climate change would reduce maize yield by an average of 4% and 16% for Ambo and Melkassa respectively, while it would increase by 2% for Bako in 2030 if current maize cultivars were grown with the same crop management practice as the baseline under the future climate. At higher altitudes, early planting of maize cultivars between 15 May and 1 June would result in improved relative yields in the future climate. Fertilizer levels increment between 23 and 150 kg ha−1 would result in progressive improvement of yields for all maize cultivars when combined with early planting for Ambo. For a mid-altitude, planting after 15 May has either no or negative effect on maize yield. Early planting combined with a nitrogen fertilizer level of 23–100 kg ha−1 provided higher relative yields under the future climate. Delayed planting has a negative influence on maize production for Bako under the future climate. For lower altitudes, late planting would have lower relative yields compared to early planting. Higher fertilizer levels (100–150 kg ha−1) would reduce yield reductions under the future climate, but this varied among maize cultivars studied. Generally, the future climate is expected to have a negative impact on maize yield and changes in crop management practices can alleviate the impacts on yield.
Soil water status shapes nutrient cycling in agroecosystems from micrometer to landscape scales
(2022) Bauke, Sara L.; Amelung, Wulf; Bol, Roland; Brandt, Luise; Brüggemann, Nicolas; Kandeler, Ellen; Meyer, Nele; Or, Dani; Schnepf, Andrea; Schloter, Michael; Schulz, Stefanie; Siebers, Nina; von Sperber, Christian; Vereecken, Harry
Soil water status, which refers to the wetness or dryness of soils, is crucial for the productivity of agroecosystems, as it determines nutrient cycling and uptake physically via transport, biologically via the moisture‐dependent activity of soil flora, fauna, and plants, and chemically via specific hydrolyses and redox reactions. Here, we focus on the dynamics of nitrogen (N), phosphorus (P), and sulfur (S) and review how soil water is coupled to the cycling of these elements and related stoichiometric controls across different scales within agroecosystems. These scales span processes at the molecular level, where nutrients and water are consumed, to processes in the soil pore system, within a soil profile and across the landscape. We highlight that with increasing mobility of the nutrients in water, water‐based nutrient flux may alleviate or even exacerbate imbalances in nutrient supply within soils, for example, by transport of mobile nutrients towards previously depleted microsites (alleviating imbalances), or by selective loss of mobile nutrients from microsites (increasing imbalances). These imbalances can be modulated by biological activity, especially by fungal hyphae and roots, which contribute to nutrient redistribution within soils, and which are themselves dependent on specific, optimal water availability. At larger scales, such small‐scale effects converge with nutrient inputs from atmospheric (wet deposition) or nonlocal sources and with nutrient losses from the soil system towards aquifers. Hence, water acts as a major control in nutrient cycling across scales in agroecosystems and may either exacerbate or remove spatial disparities in the availability of the individual nutrients (N, P, S) required for biological activity.
Nitrogen dynamics of grassland soils with differing habitat quality: high temporal resolution captures the details
(2023) Kukowski, Sina; Ruser, Reiner; Piepho, Hans‐Peter; Gayler, Sebastian; Streck, Thilo
Excessive nitrogen (N) input is one of the major threats for species‐rich grasslands. The ongoing deterioration of habitat quality highlights the necessity to further investigate underlying N turnover processes. Our objectives were (1) to quantify gross and net rates of mineral N production (mineralization and nitrification) and consumption in seminatural grasslands in southwest Germany, with excellent or poor habitat quality, (2) to monitor the temporal variability of these processes, and (3) to investigate differences between calcareous and decalcified soils. In 2016 and 2017, gross N turnover rates were measured using the 15N pool dilution technique in situ on four Arrhenatherion meadows in biweekly cycles between May and November. Simultaneously, net rates of mineralization and nitrification, soil temperature, and moisture were measured. The vegetation was mapped, and basic soil properties were determined. The calcareous soils showed higher gross nitrification rates compared with gross mineralization. In contrast, nitrification was inhibited in the decalcified soils, most likely due to the low pH, and mineralization was the dominant process. Both mineralization and nitrification were characterized by high temporal variability (especially the former) and short residence times of N in the corresponding pools (<2 days) at all sites. This illustrates that high temporal resolution is necessary during the growing season to detect N mineralization patterns and capture variability. Parallel determination of net N turnover rates showed almost no variability, highlighting that net rates are not suitable for drawing conclusions about actual gross turnover rates. During the growing season, the data show no clear relationship between soil temperature/soil moisture and gross N turnover rates. For future experiments, recording of microbial biomass, dissolved organic matter, and root N uptake should be considered.
Comprehensive assessment of climate extremes in high-resolution CMIP6 projections for Ethiopia
(2023) Rettie, Fasil M.; Gayler, Sebastian; Weber, Tobias K. D.; Tesfaye, Kindie; Streck, Thilo
Climate extremes have more far-reaching and devastating effects than the mean climate shift, particularly on the most vulnerable societies. Ethiopia, with its low economic adaptive capacity, has been experiencing recurrent climate extremes for an extended period, leading to devastating impacts and acute food shortages affecting millions of people. In face of ongoing climate change, the frequency and intensity of climate extreme events are expected to increase further in the foreseeable future. This study provides an overview of projected changes in climate extremes indices based on downscaled high-resolution (i.e., 10 × 10 km2) daily climate data derived from global climate models (GCMs). The magnitude and spatial patterns of trends in the projected climate extreme indices were explored under a range of emission scenarios called Shared Socioeconomic Pathways (SSPs). The performance of the GCMs to reproduce the observed climate extreme trends in the base period (1983–2012) was evaluated, the changes in the climate projections (2020–2100) were assessed and the associated uncertainties were quantified. Overall, results show largely significant and spatially consistent trends in the projected temperature-derived extreme indices with acceptable model performance in the base period. The projected changes are dominated by the uncertainties in the GCMs at the beginning of the projection period while by the end of the century proportional uncertainties arise both from the GCMs and SSPs. The results for precipitation-related extreme indices are heterogeneous in terms of spatial distribution, magnitude, and statistical significance coverage. Unlike the temperature-related indices, the uncertainty from internal climate variability constitutes a considerable proportion of the total uncertainty in the projected trends. Our work provides a comprehensive insight into the projected changes in climate extremes at relatively high spatial resolution and the related sources of projection uncertainties.
Increasing plant species richness by seeding has marginal effects on ecosystem functioning in agricultural grasslands
(2023) Freitag, Martin; Hölzel, Norbert; Neuenkamp, Lena; van der Plas, Fons; Manning, Peter; Abrahão, Anna; Bergmann, Joana; Boeddinghaus, Runa; Bolliger, Ralph; Hamer, Ute; Kandeler, Ellen; Kleinebecker, Till; Knorr, Klaus‐Holger; Marhan, Sven; Neyret, Margot; Prati, Daniel; Le Provost, Gaëtane; Saiz, Hugo; van Kleunen, Mark; Schäfer, Deborah; Klaus, Valentin H.
Experimental evidence shows that grassland plant diversity enhances ecosystem functioning. Yet, the transfer of results from controlled biodiversity experiments to naturally assembled ‘real world’ ecosystems remains challenging due to environmental variation among sites, confounding biodiversity ecosystem functioning relations in observational studies. To bridge the gap between classical biodiversity‐ecosystem functioning experiments and observational studies of naturally assembled and managed ecosystems, we created regionally replicated, within‐site gradients of species richness by seeding across agricultural grasslands differing in land‐use intensity (LUI) and abiotic site conditions. Within each of 73 grassland sites, we established a full‐factorial experiment with high‐diversity seeding and topsoil disturbance and measured 12 ecosystem functions related to productivity, and carbon and nutrient cycling after 4 years. We then analysed the effects of plant diversity (seeded richness as well as realized richness), functional community composition, land use and abiotic conditions on the ecosystem functions within (local scale) as well as among grassland sites (landscape scale). Despite the successful creation of a within‐site gradient in plant diversity (average increase in species richness in seeding treatments by 10%–35%), we found that only one to two of the 12 ecosystem functions responded to realized species richness, resulting in more closed nitrogen cycles in more diverse plant communities. Similar results were found when analysing the effect of the seeding treatment instead of realized species richness. Among sites, ecosystem functioning was mostly driven by environmental conditions and LUI. Also here, the only functions related to plant species richness were those associated with a more closed nitrogen cycle under increased diversity. The minor effects of species enrichment we found suggest that the functionally‐relevant niche space is largely saturated in naturally assembled grasslands, and that competitive, high‐functioning species are already present. Synthesis: While nature conservation and cultural ecosystem services can certainly benefit from plant species enrichment, our study indicates that restoration of plant diversity in naturally assembled communities may deliver only relatively weak increases in ecosystem functioning, such as a more closed nitrogen cycle, within the extensively to moderate intensively managed agricultural grasslands of our study.
The need to decipher plant drought stress along the soil-plant-atmosphere continuum
(2023) Schweiger, Andreas H.; Zimmermann, Telse; Poll, Christian; Marhan, Sven; Leyrer, Vinzent; Berauer, Bernd J.
Lacking comparability among rainfall manipulation studies is still a major limiting factor for generalizations in ecological climate change impact research. A common framework for studying ecological drought effects is urgently needed to foster advances in ecological understanding the effects of drought. In this study, we argue, that the soil–plant–atmosphere‐continuum (SPAC), describing the flow of water from the soil through the plant to the atmosphere, can serve as a holistic concept of drought in rainfall manipulation experiments which allows for the reconciliation experimental drought ecology. Using experimental data, we show that investigations of leaf water potential in combination with edaphic and atmospheric drought – as the three main components of the SPAC – are key to understand the effect of drought on plants. Based on a systematic literature survey, we show that especially plant and atmospheric based drought quantifications are strongly underrepresented and integrative assessments of all three components are almost absent in current experimental literature. Based on our observations we argue, that studying dynamics of plant water status in the framework of the SPAC can foster comparability of different studies conducted in different ecosystems and with different plant species and can facilitate extrapolation to other systems, species or future climates.
Linking horizontal crosshole GPR variability with root image information for maize crops
(2023) Lärm, Lena; Bauer, Felix Maximilian; van der Kruk, Jan; Vanderborght, Jan; Morandage, Shehan; Vereecken, Harry; Schnepf, Andrea; Klotzsche, Anja
Non‐invasive imaging of processes within the soil–plant continuum, particularly root and soil water distributions, can help optimize agricultural practices such as irrigation and fertilization. In this study, in‐situ time‐lapse horizontal crosshole ground penetrating radar (GPR) measurements and root images were collected over three maize crop growing seasons at two minirhizotron facilities (Selhausen, Germany). Root development and GPR permittivity were monitored at six depths (0.1–1.2 m) for different treatments within two soil types. We processed these data in a new way that gave us the information of the “trend‐corrected spatial permittivity deviation of vegetated field,” allowing us to investigate whether the presence of roots increases the variability of GPR permittivity in the soil. This removed the main non‐root‐related influencing factors: static influences, such as soil heterogeneities and rhizotube deviations, and dynamic effects, such as seasonal moisture changes. This trend‐corrected spatial permittivity deviation showed a clear increase during the growing season, which could be linked with a similar increase in root volume fraction. Additionally, the corresponding probability density functions of the permittivity variability were derived and cross‐correlated with the root volume fraction, resulting in a coefficient of determination (R2) above 0.5 for 23 out of 46 correlation pairs. Although both facilities had different soil types and compaction levels, they had similar numbers of good correlations. A possible explanation for the observed correlation is that the presence of roots causes a redistribution of soil water, and therefore an increase in soil water variability.
Effectiveness of bio-effectors on maize, wheat and tomato performance and phosphorus acquisition from greenhouse to field scales in Europe and Israel: a meta-analysis
(2024) Nkebiwe, Peteh Mehdi; Stevens Lekfeldt, Jonas D.; Symanczik, Sarah; Thonar, Cécile; Mäder, Paul; Bar-Tal, Asher; Halpern, Moshe; Biró, Borbala; Bradáčová, Klára; Caniullan, Pedro C.; Choudhary, Krishna K.; Cozzolino, Vincenza; Di Stasio, Emilio; Dobczinski, Stefan; Geistlinger, Joerg; Lüthi, Angelika; Gómez-Muñoz, Beatriz; Kandeler, Ellen; Kolberg, Flora; Kotroczó, Zsolt; Kulhanek, Martin; Mercl, Filip; Tamir, Guy; Moradtalab, Narges; Piccolo, Alessandro; Maggio, Albino; Nassal, Dinah; Szalai, Magdolna Zita; Juhos, Katalin; Fora, Ciprian G.; Florea, Andreea; Poşta, Gheorghe; Lauer, Karl Fritz; Toth, Brigitta; Tlustoš, Pavel; Mpanga, Isaac K.; Weber, Nino; Weinmann, Markus; Yermiyahu, Uri; Magid, Jakob; Müller, Torsten; Neumann, Günter; Ludewig, Uwe; de Neergaard, Andreas
Biostimulants (Bio-effectors, BEs) comprise plant growth-promoting microorganisms and active natural substances that promote plant nutrient-acquisition, stress resilience, growth, crop quality and yield. Unfortunately, the effectiveness of BEs, particularly under field conditions, appears highly variable and poorly quantified. Using random model meta-analyses tools, we summarize the effects of 107 BE treatments on the performance of major crops, mainly conducted within the EU-funded project BIOFECTOR with a focus on phosphorus (P) nutrition, over five years. Our analyses comprised 94 controlled pot and 47 field experiments under different geoclimatic conditions, with variable stress levels across European countries and Israel. The results show an average growth/yield increase by 9.3% (n=945), with substantial differences between crops (tomato > maize > wheat) and growth conditions (controlled nursery + field (Seed germination and nursery under controlled conditions and young plants transplanted to the field) > controlled > field). Average crop growth responses were independent of BE type, P fertilizer type, soil pH and plant-available soil P (water-P, Olsen-P or Calcium acetate lactate-P). BE effectiveness profited from manure and other organic fertilizers, increasing soil pH and presence of abiotic stresses (cold, drought/heat or salinity). Systematic meta-studies based on published literature commonly face the inherent problem of publication bias where the most suspected form is the selective publication of statistically significant results. In this meta-analysis, however, the results obtained from all experiments within the project are included. Therefore, it is free of publication bias. In contrast to reviews of published literature, our unique study design is based on a common standardized protocol which applies to all experiments conducted within the project to reduce sources of variability. Based on data of crop growth, yield and P acquisition, we conclude that application of BEs can save fertilizer resources in the future, but the efficiency of BE application depends on cropping systems and environments.

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