Newest publications
Use of seasonal forecasts in smallholder agricultural decision-making in the Central Rift Valley of Ethiopia
(2025) Kayamo, Samuel Elias; Berger, Thomas
Smallholder farmers in Ethiopia’s Central Rift Valley face pronounced risks from climate variability and erratic rainfall, challenges that threaten agricultural productivity, food security, and rural livelihoods. Rising climate hazards have spurred the promotion of seasonal precipitation forecasts as a promising means of supporting adaptation, yet the translation of such information into tangible adaptive action depends on a complex interplay of local agro-ecological conditions, available adaptation strategies, and behavioral responses.
This thesis provides a comprehensive, interdisciplinary investigation into the economic value, adoption dynamics, and policy implications of seasonal forecast information for smallholder farmers, integrating agent-based modelling, dynamic risk assessment, crop-growth simulation, and framed field experiments. A principal focus of the research is the evaluation of adaptive management strategies for smallholder farmers enabled by seasonal forecasts. Examined strategies include crop and cultivar selection in response to rainfall outlooks, optimized planting dates, forecast-driven fertilizer management, and flexible in-season adjustments (such as crop switching or tied ridging). Each option is rigorously evaluated using observational, experimental and simulated data.
In assessing the practical impacts of integrating seasonal rainfall forecast information into smallholder agricultural decision making, the results of this thesis indicate that forecast-based cultivar selection has the potential to support more effective management strategies for farmers in Ethiopia’s Central Rift Valley. By enabling better alignment of cultivar choices with anticipated seasonal rainfall conditions, farmers can enhance the adaptive capacity of their management practices in the face of climate variability. While the observed financial gains under realistic forecast accuracy are modest, these findings highlight that forecast-based cultivar selection can serve as a valuable decision-support tool. However, realizing the full potential of this approach depends not only on improvements in forecast skill, but also on the availability of reliable evidence regarding cultivar performance under diverse weather conditions and on substantial changes to seed breeding and distribution systems. Only when forecast-matching cultivars are made available to farmers promptly can the benefits of high-accuracy seasonal rainfall forecasts be more fully achieved.
In the subsequent analysis, this thesis applies a state-contingent embedded risk framework to systematically explore how the timing of smallholder management decisions—specifically crop choice, sowing date, tied-ridging, relay cropping, and fertilization—can be optimized in light of seasonal rainfall forecast information. Using multi-stage discrete stochastic programming, the study evaluates adaptive strategies at the whole-farm level by simulating crop yield responses to management choices across 2,400 possible weather trajectories. The results show that forecast-informed management decisions can improve farmer income, but the extent and consistency of these benefits vary across seasons. The findings further reveal that opportunities for in-season adjustment—rather than choices made solely at the start of the season—are especially critical for achieving positive results in response to forecast information. By evaluating the long-term impacts of forecast-based decision making at the whole-farm level in the Central Rift Valley, this study emphasizes the need for more tailored and effective communication and advisory services of seasonal rainfall forecasts. In addition, the analysis highlights the inherent unpredictability of agricultural outcomes under climate uncertainty and demonstrates the continuing importance of building empirical understanding of how management actions and varying weather conditions together shape farm performance. These insights suggest that policy interventions aimed at strengthening real-time advisory systems and supporting farmers’ capacity for flexible, adaptive management are essential for fully realizing the benefits of seasonal rainfall forecasting in smallholder agriculture.
The third component of the thesis explores how smallholder farmers receive, interpret, and act upon seasonal precipitation forecasts, drawing on evidence from framed field experiments conducted in Ethiopia’s Central Rift Valley. The analysis demonstrates that neither improvements in forecast accuracy nor dissemination of information alone are sufficient to induce significant behavioral change among farmers. Adoption is most likely when seasonal precipitation forecasts are communicated repeatedly, presented in clear and actionable formats, and tailored to local realities through trusted channels. The results further indicate that factors such as farmers’ education levels, prior experience with seasonal forecasts, and regular engagement with extension services play a central role in facilitating effective use of such information. The findings highlight the potential of digital innovations, such as smartphone-based advisories and AI-supported tools, to improve the reach and personalization of seasonal precipitation forecasts, provided these solutions are developed through participatory and user-centered approaches. Overall, the study underscores the importance of aligning advisory services with both the informational and contextual needs of smallholder farmers in order to foster more effective and inclusive adaptation to climate variability.
Overall, the results of this thesis emphasize that the benefits of seasonal rainfall forecasts can only be fully realized through an integrated approach. This requires the combination of advances in forecast technology, adaptive input systems, effective communication, and supportive policy environments. Comprehensive and locally tailored adaptation packages—linking seasonal rainfall forecast information to improved access to seed and inputs, credit, training, and extension services—emerge as the most effective strategy for strengthening resilience. Ultimately, by connecting quantitative modeling, empirical experimentation, and policy analysis, this thesis provides a robust foundation for scaling up inclusive, impactful advisory systems based on seasonal rainfall forecasts to better equip smallholder farmers for managing risks associated with increasing rainfall variability.
Production and use of forages from permanent pastures in grazing-based dairy cattle systems in Southwest Germany
(2024) Velasco Gutierez, Elizabeth; Dickhoefer, Uta
A steadily growing world population and its rising standard of living are putting pressure on agricultural systems to provide food of good quality while minimizing environmental impacts. As a result, traditional practices such as grazing are becoming more popular in dairy systems.
Permanent grasslands cover 34 % of the agricultural area in the European Union (EU). Semi-natural grasslands (SNG) are defined as permanent grasslands formerly used for mowing or grazing that have not been substantially modified by agricultural practices. The federal State of Baden-Wuerttemberg in Germany has a great proportion of SNG compared to other federal States in the country. The use of forage on SNG in grazing-based dairy cattle systems has the potential to produce milk sustainably, by respecting the environment, closing nutrient cycles, and promoting animal welfare, while ensuring high-quality forage production. However, there is limited data on the performance and practical use of SNG in grazing-based dairy cattle systems. This doctoral thesis aims at characterizing, evaluating, and quantifying the forage on SNG in grazing-based dairy cattle systems in Southwest Germany focusing on (1) forage availability, (2) feed energy self-sufficiency, and (3) feed supplementation in on-farm approach
To characterize grazing-based dairy cattle systems and evaluate the potential of SNG for grazing and milk production, semi-quantitative interviews were conducted on 27 farms in the summer of 2018. Above-ground forage biomass from pastures was harvested and analyzed for nutrient composition. Farms differed regarding land endowment and use, dairy herd size, and thus stocking rates. Farmers implemented rotational (n = 12), short-grass (n = 10), continuous (n = 3), or strip (n = 2) grazing systems with < 8 h (n = 4), 8-12 h (n = 14), and > 12 h (n = 9) of daily pasture access during the grazing season. During the summer of 2018, available pasture forage (kg dry matter (DM)/ha) ranged from only 122 to 1,208. Crude protein (CP) and metabolizable energy (ME) concentrations varied greatly with 85 to 282 g and 7.9 to 11.0 MJ/kg DM, respectively. Diet digestibility estimated from fecal CP content ranged from 59.2 to 72.2 g/100 g organic matter (OM). Some farms succeeded in maintaining milk yields constant despite the lack of rainfall in that year.
To quantify the forage availability of SNG as well as the feed energy self-sufficiency in seven commercial organic dairy cattle farms in Southwest Germany during the grazing season of 2019 and 2020, exclusion cages were set up in dairy cattle paddocks. Pasture samples were collected inside and outside the exclusion cages every 30 to 65 d, and analyzed by near-infrared reflectance spectroscopy for DM, CP, neutral detergent fiber (NDF), acid detergent fiber (ADF), apparent total tract digestibility organic matter (dOM), and ME. The results showed that SNG have the potential to produce a forage biomass up to 10,959 kg DM/ha and a with concentrations of CP, NDF, ADF up to 232 g/kg DM, 395 g/kg DM, and 214 g/kg DM, respectively. The concentrations of dOM and ME were up to 771 g/kg OM and 10.7 MJ/kg DM, respectively. The potential of grazing on SNG for dairy milk production was not fully exploited, although on some farms and at some times during the grazing season, grazing on SNG provided 100 % of the energy requirements of lactating dairy cattle, while on other farms, grazing on SNG provided only 2.8 % of the energy requirements. The differences in milk production from grazing SNG observed between farms were mainly due to management factors such as stocking rate and feed supplementation, while environmental factors played a minor role.
To evaluate the effects of feed supplementation in grazing-based dairy cattle systems, three feeding experiments were conducted to compare feed supplementation under grazing conditions of (1) grass hay versus fresh grass-clover mixtures, (2) grass hay before or after grazing, and (3) timing of concentrate supplementation on two organic commercial dairy cattle farms in Southwest Germany in two periods in 2019 and 2020. Experiment 1 showed that the dairy cattle supplemented with fresh grass-clover mixtures had lower fecal nitrogen (N) excretion compared to the dairy cattle supplemented with grass hay. Experiment 2 demonstrated that grass hay supplementation before grazing led to a decrease in pasture organic matter intake (OMI), while grass hay supplementation in the morning (i.e., hay AM) decreased fecal N excretion in dairy cattle. Experiment 3 showed that offering less concentrate to dairy cattle before grazing resulted in higher pasture OMI in period 1, but also higher N intake and, lower fecal N excretion. The results of the feeding experiments demonstrate that simple management practices, such as the timing of feed supplementation can influence individual N utilization.
The results of this doctoral thesis demonstrated that forage of SNG has the potential to produce forage biomass, adequate nutrient content, and energy concentration even under dry conditions. To maximize the use of SNG for grazing, the dynamics between forage biomass and supplemented feed should be considered, to maximize the use of SNG. Grazing management decisions play an important role in the use of forage of SNG for grazing in dairy cattle systems. The present thesis provides insights into grazing-based dairy cattle systems and valuable information on on-farm conditions in Central Europe. Future studies should be carried out in other countries and regions to obtain a more comprehensive panorama of the potential of the forage on SNG for milk production.
Impaired metal perception and regulation of associated human foliate papillae tongue transcriptome in long-COVID-19
(2024) Danzer, Barbara; Jukic, Mateo; Dunkel, Andreas; Andersen, Gaby; Lieder, Barbara; Schaudy, Erika; Stadlmayr, Sarah; Lietard, Jory; Michel, Timm; Krautwurst, Dietmar; Haller, Bernhard; Knolle, Percy; Somoza, Mark; Lingor, Paul; Somoza, Veronika; Danzer, Barbara; School of Life Science, Technical University of Munich, Freising, Germany; Jukic, Mateo; Department of Neurology, School of Medicine and Health, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany; Dunkel, Andreas; Leibniz Institute for Food Systems Biology at the Technical University of Munich, Freising, Germany; Andersen, Gaby; Leibniz Institute for Food Systems Biology at the Technical University of Munich, Freising, Germany; Lieder, Barbara; Department of Physiological Chemistry, Faculty of Chemistry, University of Vienna, Vienna, Austria; Schaudy, Erika; Department of Inorganic Chemistry, Faculty of Chemistry, University of Vienna, Vienna, Austria; Stadlmayr, Sarah; Department of Physiological Chemistry, Faculty of Chemistry, University of Vienna, Vienna, Austria; Lietard, Jory; Department of Inorganic Chemistry, Faculty of Chemistry, University of Vienna, Vienna, Austria; Michel, Timm; School of Life Science, Technical University of Munich, Freising, Germany; Krautwurst, Dietmar; Leibniz Institute for Food Systems Biology at the Technical University of Munich, Freising, Germany; Haller, Bernhard; Institute of AI and Informatics in Medicine, School of Medicine and Health, Technical University of Munich, Munich, Germany; Knolle, Percy; Institute of Molecular Immunology, School of Medicine and Health, Technical University of Munich, Munich, Germany; Somoza, Mark; Leibniz Institute for Food Systems Biology at the Technical University of Munich, Freising, Germany; Lingor, Paul; Department of Neurology, School of Medicine and Health, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany; Somoza, Veronika; Leibniz Institute for Food Systems Biology at the Technical University of Munich, Freising, Germany
Chemosensory impairment is an outstanding symptom of SARS-CoV-2 infections. We hypothesized that measured sensory impairments are accompanied by transcriptomic changes in the foliate papillae area of the tongue. Hospital personnel with known SARS-CoV-2 immunoglobulin G (IgG) status completed questionnaires on sensory perception ( n = 158). A subcohort of n = 141 participated in forced choice taste tests, and n = 43 participants consented to donate tongue swabs of the foliate papillae area for whole transcriptome analysis. The study included four groups of participants differing in IgG levels (≥ 10 AU/mL = IgG + ; < 10 AU/mL = IgG - ) and self-reported sensory impairment (SSI ± ). IgG + subjects not detecting metallic taste had higher IgG + levels than IgG + participants detecting iron gluconate ( p = 0.03). Smell perception was the most impaired biological process in the transcriptome data from IgG + /SSI + participants subjected to gene ontology enrichment. IgG + /SSI + subjects demonstrated lower expression levels of 166 olfactory receptors (OR) and 9 taste associated receptors (TAS) of which OR1A2, OR2J2, OR1A1, OR5K1 and OR1G1, as well as TAS2R7 are linked to metallic perception. The question raised by this study is whether odorant receptors on the tongue (i) might play a role in metal sensation, and (ii) are potential targets for virus-initiated sensory impairments, which needs to be investigated in future functional studies.
Projecting the impact of climate change on honey bee plant habitat distribution in Northern Ethiopia
(2024) Gebremedhn, Haftom; Gebrewahid, Yikunoamlak; Haile, Gebremedhin Gebremeskel; Hadgu, Gebre; Atsbha, Tesfay; Hailu, Teweldemedhn Gebretinsae; Bezabih, Gebreamlak; Gebremedhn, Haftom; Ghent University, Ghent, Belgium; Gebrewahid, Yikunoamlak; Tigray Agricultural Research Institute, Mekelle, Ethiopia; Haile, Gebremedhin Gebremeskel; Department of Earth and Environmental Sciences, Wesleyan University, Middletown, USA; Hadgu, Gebre; Tigray Agricultural Research Institute, Mekelle, Ethiopia; Atsbha, Tesfay; Tigray Agricultural Research Institute, Mekelle, Ethiopia; Hailu, Teweldemedhn Gebretinsae; Institute of Animal Science, University of Hohenheim, Stuttgart, Germany; Bezabih, Gebreamlak; Tigray Agricultural Research Institute, Mekelle, Ethiopia
Climate change significantly affects the diversity, growth, and survival of indigenous plant species thereby influencing the nutrition, health and productivity of honey bees ( Apis mellifera ). Hypoestes forskaolii (Vahl) is one of the major honey bee plant species in Ethiopia’s Tigray region. It is rich in pollen and nectar that typically provides white honey, which fetches a premium price in both local and inter-national markets. Despite its socio-economic and apicultural significance, the distribution of H. forskaolii has been declining, raising concerns regarding its conservation efforts. However, there is limited knowledge on how environmental and climatic factors affect its current distribution and response to future climate change. The study investigates the current and projected (the 2030s, 2050s, 2070s, and 2090s) habitat distributions of H. forskaolii under three future climate change scenarios (ssp126, ssp245, and ssp585) using the Maximum Entropy Model (MaxEnt). The results show that land use (50.1%), agro-ecology (28%), precipitation during the Driest Quarter (11.2%) and soil texture (6.1%) predominantly influence the distribution of H. forskaolii, collectively explaining 95.4% of the model's predictive power. Habitats rich in evergreen trees and mosaic herbaceous with good vegetation cover are identified as the most suitable for H. forskaolii . The spatial distribution of H. forskaolii is concentrated in the highlands and mid-highlands of the eastern and southern parts of Tigray, characterized by a colder temperature. Across the three climate change scenarios, the size of suitable habitat for H. forskaolii is projected to decrease over the four time periods studied. Predictions under the ssp585 scenario reveal alarming results, indicating a substantial decrease in the suitable habitat for H. forskaolii from 4.26% in the 2030s to 19.09% in the 2090s. Therefore, given the challenges posed by climate change, research efforts should focus on identifying and evaluating new technologies that can help the H. forskaolii species in adapting and mitigating the effects of climate change.
Assessing impacts of crop area expansion and crop-livestock integration on ecosystem functions in African savannas using the coupled LUCIA and LIVSIM models
(2025) Gutai, Benjamin; Marohn, Carsten; Bateki, Christian Adjogo; Asch, Folkard; Gutai, Benjamin; Institute of Agricultural Sciences in the Tropics (Hans-Ruthenberg-Institute), University of Hohenheim, Garbenstr. 13, 70599, Stuttgart, Germany; Marohn, Carsten; Institute of Agricultural Sciences in the Tropics (Hans-Ruthenberg-Institute), University of Hohenheim, Garbenstr. 13, 70599, Stuttgart, Germany; Bateki, Christian Adjogo; Section Animal Husbandry in the Tropics and Subtropics, University of Kassel and University of Göttingen, Steinstr. 19, 37213, Witzenhausen, Germany; Asch, Folkard; Institute of Agricultural Sciences in the Tropics (Hans-Ruthenberg-Institute), University of Hohenheim, Garbenstr. 13, 70599, Stuttgart, Germany
Large-scale land use change (LUC) of African Guinea savannas to crop fields is expected to cause negative impacts on ecosystem functions (ESF) and long term land productivity. The complex interactions of key processes in savannas evoked by LUC calls for a process-based modelling approach. We employed the dynamically coupled Land Use Change Impact Assessment (LUCIA) model and the Livestock Simulator (LIVSIM) which represent LUC impacts on soil processes, landscape-scale matter fluxes, seasonal grass and crop growth, and livestock nutrition, production and reproduction, depending on seasonal feed availability and quality on accessible pastures. For a rangeland in Borana, Ethiopia, two different LUC scenarios were evaluated in comparison to the baseline of traditional pasture-based land use. In the intensive LUC scenario 52% of grassland was converted into unfertilized maize fields, inaccessible for livestock. The integrated LUC scenario of the same grassland conversion rate allowed feeding maize straw and provided high-quality feed reserves from seasonally managed pastures. LUC in the intensive LUC scenario led to declining yields in the second year after conversion. Feed production on the remaining rangeland patches was insufficient for livestock nutrition, causing drops of herd body weight and herd size particularly in drought years. Resilience of herd performance to LUC was enhanced in the integrated LUC scenario when feeding maize straw and high-quality feed reserves. In both LUC scenarios, topsoil organic carbon storage decreased after ploughing shrub grassland for cultivation, and so did soil water storage capacity due to soil pore destruction. Soil erosion of less than one cm after 10 years occurred under cultivation. The simulation results indicated that the well validated model framework could predict impacts of LUC and simple crop-livestock integration on savanna ESFs, grass growth dynamics and livestock production during seasonal and inter-annual rainfall variation. This study lays the foundation for further land use scenario simulations to improve the understanding of benefits and risks caused by savanna grassland conversion.