• Energy Research
• 2. Zero hunger close
• CH close
• English close

Aim: Climate warming and biodiversity loss both alter plant productivity, yet we lack an understanding of how biodiversity regulates the responses of ecosystems to warming. In this study, we examine how plant diversity regulates the responses of grassland productivity to experimental warming using meta-analytic techniques. Location: Global Major taxa studied: Grassland ecosystems Methods: Our meta-analysis is based on warming responses of 40 different plant communities obtained from 20 independent studies on grasslands across five continents. Results: Our results show that plant diversity and its responses to warming were the most important factors regulating the warming effects on plant productivity, among all the factors considered (plant diversity, climate and experimental settings). Specifically, warming increased plant productivity when plant diversity (indicated by effective number of species) in grasslands was lesser than 10, whereas warming decreased plant productivity when plant diversity was greater than 10. Moreover, the structural equation modelling showed that the magnitude of warming enhanced plant productivity by increasing the performance of dominant plant species in grasslands of diversity lesser than 10. The negative effects of warming on productivity in grasslands with plant diversity greater than 10 were partly explained by diversity-induced decline in plant dominance. Main Conclusions: Our findings suggest that the positive or negative effect of warming on grassland productivity depends on how biodiverse a grassland is. This could mainly owe to differences in how warming may affect plant dominance and subsequent shifts in interspecific interactions in grasslands of different plant diversity levels.

Supplementary material for the publication " Agricultural biogas plants as a hub to foster circular economy and bioenergy: An assessment using material substance and energy flow analysis" Burg, V., b, Rolli, C., Schnorf, V., Scharfy, D., Anspach, V., Bowman, G. Today's agro-food system is typically based on linear fluxes (e.g. mineral fertilizers importation), when a circular approach should be privileged. The production of biogas as a renewable energy source and digestate, used as an organic fertilizer, is essential for the circular economy in the agricultural sector. This study investigates the current utilization of wet biomass in agricultural anaerobic digestion plants in Switzerland in terms of mass, nutrients, and energy flows, to see how biomass use contributes to circular economy and climate change mitigation through the substitution effect of mineral fertilizers and fossil fuels. We quantify the system and its benefits in details and examine future developments of agricultural biogas plants using different scenarios. Our results demonstrate that agricultural anaerobic digestion could be largely increased, as it could provide ten times more biogas by 2050, while saving significant amounts of mineral fertilizer and GHG emissions.

Climate change in temperate mountain systems and associated increase in temperature and decrease in precipitation are expected to have strong implications for vegetation productivity, species diversity and carbon turnover in subalpine grasslands. Little is known, however, about the interaction between the effects of climate change and those of local land use management and possible changes in landscape structure. Pasture woodlands in the Swiss Jura Mountains are a traditional landscape, resulting from a long-lived sustainable use of grasslands and woodlands, and as such provide a suite of important ecosystem services to human society. These range from carbon sequestration and biodiversity preservation, to provision of timber and forage for livestock, and last but not least an aesthetic value, much appreciated by tourism. In this thesis various aspects of ecosystem functioning have been studied, investigating the combined effects of experimental climate change and land use on structurally different wooded pastures. An altitudinal gradient method has been used to simulate future climate change conditions, by imposing warmer and drier climate on subalpine turfs transplanted at lower elevation. The resulting gradient in mean annual temperature and precipitation – ranging from cold and wet in the subalpine zone, to warm and dry in the colline zone – has allowed for the detection of tipping points and altered states of ecosystem functioning in response to the treatments. The method employed provided also the possibility for a direct comparison of three land use types: unwooded pastures, sparsely wooded pastures, and densely wooded pastures (the result of pasture management intensity), in their response to climate perturbation. During the four years of experimental work, a series of observations have been made at the plot scale (square metre) in terms of plant performance and biogeochemical cycles, as well as at the landscape scale (hectare) in terms of forage production. A general threshold level for ecosystem resistance to experimental climate change was detected between the moderate IPCC scenario (+2 K mean annual temperature; -20 % annual precipitation) and the intensive IPCC scenario (+4 K mean annual temperature; -40 % annual precipitation). A concomitant gradient in ecosystem response to climate change was observed across the three land use types. The intensively managed unwooded pasture type was consistently more affected by the experimental treatment and rarely exhibited signs of resistance, especially under the intense climate change scenario. A drastic loss of plant species diversity, reduction of herbaceous biomass, impaired litter decomposition and soil microbial metabolic activity have all contributed to the altered state of ecosystem functioning. In contrast, the two extensively managed wooded pasture types showed considerable resistance to climate perturbation in terms of both above and belowground ecosystem processes. The reported inter-annual variation in herbaceous diversity and biomass production within these land use types demonstrated their resilience (recovery) potential too. Using a modelling approach for upscaling these results to the heterogeneous landscape of pasture woodlands in the Swiss Jura Mountains, has proven that extensively used wooded pastures could grant sustainable ecosystem services in terms of forage provision for cattle under climate change. Considering that the two experimental climate change intensities implemented this study are the projected ‘best’ and ‘worst’ case scenarios for the coming decades, the reported resistance of wooded pastures to climate change has to be embraced, and sustainable land use set as a goal in high altitude mountain pastures.

This thesis presents a methodology for energy management in large companies and its implementation through a web application and through a prototype of a simulation platform. By combining existing tools in an innovative manner and by making use of recent web technology developments, the methodology adopted provides engineers and managers with tools capable of guaranteeing an efficient and sustainable energy management. Although the methodology presented in this work is based on the experience acquired in the food industry, it can be easily applied in other industrial sectors. The methodology is based on two fundamental approaches commonly used to analyse energy consumption in industrial contexts: the top-down approach and the bottom-up approach. The top-down approach is used in the first place to identify the factories and the specific areas within the factories in which the largest improvement potentials can be achieved. In turn, the bottom-up approach builds on the results from the top-down approach to identify and quantify the energy saving potentials. The top-down approach is implemented through a web application in collaboration with an industrial partner. This application encompasses a modular factory model –accessible to engineers in factories through a user-friendly interface– which enables each factory to define its energy usage, allocate energy costs among the different energy consumers and compute key performance indicators. For a rational cost allocation in multi-service energy conversion units, an exergy-based methodology is presented. The efficiency of energy conversion units defined in the factory model, such as the boilerhouse or the air heaters, is assessed using thermodynamic models. The latter are simplified parametric models derived from accurate thermodynamic models developed in a general flow-sheeting and simulation software to comply with computation time and reliability requirements of the web application. The different factory models defined in the web application can be browsed as part of the proposed top-down approach: starting from a high level overview of the factory –targeted mainly at managers– users can then focus on a specific area of the factory. Strategies are developed to guide users in identifying factories or specific areas within the factories with the largest improvement potentials. They include the use of mechanism to rate the quality of a performance indicator as well as a benchmarking module that allows to compare performance indicators across factories worldwide. In sum, the modular and adaptive aspects of the web application guarantee its long-lasting use. In order to quantify energy saving potentials in the energy conversion units defined in a factory model, "what if?" scenarios are performed in a web-based simulation platform prototype developed in this thesis. This platform acts as a decision-support tool by providing graphical representations of profitability and risk analysis. The platform can be accessed by human users through a web browser while other applications, such as the web application described above, may use the simulation functions through a web service. Statistical tools that can help engineers in defining the factory model described above are also presented. They are used to correlate energy consumption with factors such as production volumes or the climate. Tests to validate the developed correlations are also described. The application of this technique in a factory shows that more than 50% of the energy consumption does not have a direct correlation with production factors and allows to identify improvement potentials. Finally, the concept of a bottom-up approach to identify and quantify energy saving potentials in the different production processes of a factory is presented. A triple representation of the requirements of a process is introduced and applied to process integration in a concrete example. The 80/20 rule is also applied to reduce the complexity of the problem. The optimal integration of cogeneration engines and heat pumps using multi-objective optimisation is also presented.

Global climate change is among the most important and severe challenges the international community has ever faced. Existing evidence shows that climatic changes will have far-reaching repercussions for ecosystems and humans alike. For instance, projections expect climate change to induce mass population movements due to hazards like droughts, sea level rise, or extreme weather events, particularly in low-income countries with limited capacity to protect themselves and adapt to such climatic changes. However, these projections are largely based on extrapolations from the population at risk of experiencing adverse climatic events. The recent literature therefore highlights that projections on climate-related migration should account for the possibility that people can adapt to changing climatic conditions. This is particularly relevant for slow-onset environmental changes such as droughts, salinization, or erosion, which individuals and societies can anticipate and adapt to. This dissertation contributes to a better understanding of whether, when, and how environmental changes lead to human migration. Theoretically, I link environmental changes to individual-level migration decisions by applying the aspirations-capabilities framework. I argue that exposure to environmental changes can increase someone’s aspirations to move away, while such exposure also has the potential of eroding the capability to move. People will move if they have both the aspiration and the capability to move. If one of the two is lacking, people remain immobile. Importantly, this concept also allows to differentiate “involuntary non-migrants” who would like to move away but lack the capability to do so from “voluntary non-migrants” who could move away but do not want to. Empirically, I employ a novel, self-collected panel data set of around 1700 household heads residing along the Jamuna River in northern Bangladesh, an area affected by riverbank erosion and flooding during the yearly recurring monsoon season. Through a multi-stage clustered sampling design, I obtained a sample representative of the rural population in the case study region. In a quasi-experimental approach, I surveyed respondents at a similar baseline risk of being affected before the environmental changes occurred. By re-interviewing both affected and unaffected respondents after the environmental changes have materialized, and both those who migrated and those who stayed, I can link any differences I observe between affected and unaffected respondents to the environmental shocks. This causal link makes a major empirical contribution to the literature on environmental migration that overwhelmingly applies secondary or retrospective data. In the empirical chapter I, I examine how the populations along the Jamuna perceive environmental and climatic changes and I compare these perceptions to objectively measured data. I find that perceptions of long-term temperature changes are more in line with meteorological evidence than those of precipitation. This finding is remarkable given that most of the respondents do not know the term climate change. Further, respondents grossly overestimate the extent of erosion that has occurred in their village in the previous year. Since human behavior is shaped by their perceptions rather than by objective data, this underlines the importance of considering people’s perceptions rather than exclusively relying on natural scientific data. Chapters II and III study how affectedness by riverbank erosion and flooding influences migration aspirations and migration behavior, respectively. The results suggest that riverbank erosion has a significant positive impact on both aspirations and the likelihood of migration. The effect of flood affectedness, by contrast, remains largely insignificant. This can be linked to the important role of flooding for the livelihood cycle of riverine populations, while erosion only has negative and potentially very detrimental effects on livelihoods. Lastly, chapter IV studies immobility in the context of environmental changes. I show that a majority (83%) of those who stay put after the monsoon season qualify as “voluntary/acquiescent non-migrants”, while 17% of the non-migrants can be classified as “involuntary”. Environmental shocks increase the respondents’ migration aspirations while reducing their capability to move. Hence, they might lead to “trapped populations” – a term which describes individuals who would like to move away but cannot. This dissertation provides valuable insights of broader relevance into whether and how societies react, or could react, to slow-onset climatic changes such as sea-level rise, drought, and soil/water salinity. Moreover, the methodology developed in the project can be applied to other cases and thereby inform prediction models of future climate-induced migration. Similarly, the findings could be utilized by institutional actors at local, national, and international levels when seeking to identify policy options to increase the adaptive capacity of populations vulnerable to climatic changes – supporting both those who would like to move and those who prefer to stay put.

This research assesses the effect of greenhouse gas (GHG) emission constraints imposed in biofuel importing countries on the export potential of biofuel producing countries. Several countries are promoting the introduction of biofuels on their energy matrix through ambitious biofuel mandates but also specify a certain level of GHG emission reduction that biofuels should fulfil. Biofuel producing countries focused on the international market should comply with this criterion in order to supply biofuels to those countries. Biofuel producers should then report the GHG emission saving (GES) of the biofuel they supply. A critical issue in this assessment is the inclusion of GHG emissions from land-use change (LUC) induced by the production of feedstock for biofuels. Focusing on the Argentinean case, this thesis analyses the soybean-based biodiesel export potential of Argentina to the European Union (EU), including the GES threshold imposed in the EU Renewable Energy Directive (RED). The thesis therefore focuses on estimating the biofuel GES based on the impact of soybean production on direct land-use changes (dLUC) at the country level. Key factors influencing this result include the policy framework regulating the biofuel supply chain, the evolution of prices and demand for soybean-based products and the feedstock production patterns. The thesis proposes a modeling approach to assess the effect of these factors on soybean-based biodiesel production and exports. The approach is based on a market analysis of soybean and of higher value-added products, a conceptual modeling framework and a simulation model. The market analysis serves as a background study to define the modeling foundations. The conceptual modeling framework specifies the main interaction among producers in the biodiesel supply chain and their link to international markets, land-use changes and GHG emissions. Simulations are then performed to assess how those key factors affect the Argentinean (AR) biodiesel export potential to the EU. To this end, a system dynamics simulation model is developed. The simulation model includes a life cycle assessment model used to estimate the biofuel GES. The research explicitly addresses the allocation of biodiesel production between two types of producers and two market destinations, provided that specific policies regulate the domestic biodiesel industry. Land supply for soybean production is estimated based on the evolution of demand for soybean, competing and higher value-added products. Dynamics in the international markets are addressed through a scenario-based approach to define a plausible scenario of the market evolution. Feedstock production patterns are accounted for by disaggregating soybean production in four different regions (Centre, South-East, North-East and North-West). In each region, the expansion of managed lands is modeled based on the current share of three soybean cultivation methods and seven unmanaged land types. The biofuel GES is finally compared with the EU-RED GES threshold to estimate the biofuel export potential under GHG emission constraints. Results indicate that the impact of biodiesel production on soybean land supply was small compared with the effect of soybean oil and meal exports. While biodiesel production affects mainly soybean oil exports, this effect is still marginal given the biodiesel production level and the economic value attached to soybean meal for the given scenario. Land supply for soybean production therefore seems to depend more on how Argentinean soybean meal exports affect the price of soybean in the international market. Despite the large share of Argentina in the soybean meal export market, this market is likely to be competitive. Biodiesel domestic policy instruments significantly affect the biodiesel export potential, especially when different domestic blending targets are applied. With respect to the national biodiesel mandate large firms are mainly export oriented while small and medium firms exclusively supply the domestic market. Moreover, export taxes seemed to significantly affect the biodiesel export potential through its direct effect on producer profits. Feedstock production patterns largely influence dLUC from soybean production. The supply of cropland for soybean cultivation differs among regions. Higher land productivities and the application of first-occupation no-tillage farming in the Central region led to higher net returns to land and lower land requirements. Soybean cultivation in the Central region leads mainly to displacement of other crops and pastures, given constraints in land availability. Cropland supply in other regions resulted in higher dLUC due to lower land productivities and the application of conventional tillage that lead to lower yields. In the South-East and North- East regions cropland expanded mainly into mixed land, grassland and shrubland. In the North-West region, cropland expansion into forests resulted in significant GHG emissions from dLUC. The allocation of dLUC from cropland expansion to biodiesel resulted in different biodiesel export potentials. Producers located in the C region seemed to be those with the highest potential for exporting biodiesel, given their higher profits and higher GES compared with other regions. Producers in the C region can supply biodiesel to the export market with a GES of 45% complying with the EU-RED GES threshold, at least until 2017. If no dLUC occurs, the GES for biodiesel produced in this region rises to 57%. Supply by other regions to the international market is constrained by the non compliance with the GES threshold. Perspectives for further research include additional simulations to assess the biofuel GES and the export potential under other market scenarios and policy contexts. The modeling framework may be extended to the individual producer level and may also be linked to a global approach to improve the modeling of market interactions in the world economy and the accounting of indirect land-use change. Finally, the extension to geographic information systems (GIS) can improve the representation of land heterogeneity and the induced land-use changes from soybean production.

The recent rise of food cost in world markets has accelerated the research examining the underlying factors for this rise. The present research investigated the separate and combined impacts of three factors thought to contribute to the price rise: adverse weather events, strong and sustained growth in high populated countries, and increased biofuels production. The research further analysed the effects of these price rises on consumption expenditures in Brazil, China and India. Analyses were carried out using a partial equilibrium trade model with a focus on the 2004 to 2007 period. The modelling suggests that the most important factor behind the price rise depends on the commodity, with maize/corn, oilseeds, and sugar most affected by biofuels, while some meats and dairy products are more affected by income growth.

with malnutrition are increasing, along with devastating results for the social-ecological environments, showing the unsustainability of the currently dominant food systems. The complex set of food-related problems requires multidimensional perspectives, using inter- and transdisciplinary methodologies, to address social-ecological aspects over a mere focus on productivity. This article introduces a hands-on Food Sustainability Assessment Framework (FoodSAF) that allows non-academic actors to identify pathways for making food systems more sustainable through collective transformations in a “spiral of change”. The emphasis is on making the concept of “food sustainability” operational and applicable, by exploring transdisciplinary methodologies, encourage genuine participation of actors at the local level, and elevate their solutions in the direction of decision-making spaces, where policy makers have a key role in supporting change. The results provide evidence-based scientific knowledge for the promotion of innovation strategies and policy options that improve the sustainability of food systems with the specific aim of strengthening local food systems in a long-term process to co-create transformations. Social Innovations Journal, 5 (64) ISSN:2692-2053

Conflicts between increasing food demands and adverse effects of agricultural intensification on the environment, together with frequent and severe drought, are threatening global food production and food security. Therefore, agricultural systems have to be more productive, sustainable, and resilient in the context of global change. Organic farming and conservation tillage have been widely implemented as means of ecological intensification due to their ecological benefits, such as enhancing biodiversity, reducing greenhouse gas emissions, and improving soil fertility. However, how these cropping systems can potentially compensate drought effects on food production and functioning of ecosystems was scarcely reported in arable lands. Therefore, as introduced in Chapter 1, this doctoral thesis focuses on the capability of different cropping systems to mitigate drought effects on ecosystem functioning, including crop yields and total N uptake, crop phenology, plant water uptake, litter decomposition, and soil nitrate availability. As introduced in Chapter 2, all the experiments in this thesis were conducted using the FAST (Farming Systems and Tillage Experiment) trial, which compares organic farming vs. conventional farming with different tillage depth, resulting in a total of four cropping systems, i.e. i) organic farming with intensive tillage, ii) organic farming with reduced tillage, iii) conventional farming with intensive tillage, and iv) conventional farming with no-tillage. During major crop growth stages, summer drought treatments were applied with portable rain shelters for all four cropping systems. Crop phenology helps schedule management practices and acts as a biological indicator integrating the information from both environmental drivers and management options. However, the study on crop phenology as affected by smallholder management practices is often limited by the temporal and spatial resolution of phenological observations. Therefore, the goal of Chapter 3 was to investigate the feasibility of PhenoCams, i.e. time-lapse cameras, for tracking crop phenology and to assess how cropping systems affect crop phenology and estimating yields at harvest with phenology observations. During the years 2018 and 2019, we monitored vegetation changes among four cropping systems during two crop growing seasons, i.e. pea-barley mixture and winter wheat monoculture. The results indicated that early-season phenological differences established by cropping systems in winter wheat can be well translated into changes in crop yields and total N uptake under ambient rainfall conditions. The response of crops to drought can be very different depending on the crop species and growth stages. Timely observation of vegetation changes can monitor drought effects on crop development over time. In Chapter 4, the crop yields, total N uptake and phenology in response to drought among different cropping systems were investigated. The drought response of phenology was not consistent among crops, with up to 6 days earlier onset of several phenological metrics in pea-barley, but no such shifts of these metrics in winter wheat. Temporal interactions of systems with drought on phenology were shown for both pea-barley and winter wheat. Compare to control, drought treatments caused 20–27% and 16–21% reductions of grain yields and total N uptake for pea-barley mixture and winter wheat, respectively. The findings of this chapter indicate that cropping systems cannot compensate the negative effects of drought on phenology nor crop yields or total N uptake. Plants can shift their growth stages to escape from unfavorable conditions (drought escape mechanism), or avoid drought by developing deeper roots or utilizing water in a deeper soil layer (drought avoid mechanism), or can be both. To better understand the mechanisms of crops in response to drought, in Chapter 5, the soil depths of pea-barley water sources among all cropping systems combined with drought treatment were investigated using stable water isotopes. Pea plants prefer shallower soil water as compared to barley plants. As affected by drought, both pea and barley relied more on shallower soil water (0-20 cm) across all cropping systems than the control treatment, but cropping systems did not shift the soil water sources of both pea and barley. Thus, adapting cropping systems could not mitigate the drought effect on plant water use strategy. Drought can not only lead to phenological shifts and physiological failures on plant-level but also inhibit ecosystem processes and functions in soil. Litter decomposition releases nutrients from organic matter to the atmosphere, soil organisms and crops and can be primarily inhibited under drought. However, it is unclear to what extent organic farming and conservation tillage can alleviate drought effects on litter decomposition. Therefore, in Chapter 6, the effect of drought on litter decomposition was examined in four cropping systems across three crop growing seasons, including pea-barley mixture, maize monoculture, and winter wheat monoculture. Using two standard tea litters with distinct quality, i.e., high-quality green tea with a narrow C: N ratio and low-quality rooibos tea with a wide C: N ratio, it was possible to assess the effects of cropping systems on litter decomposition and especially on the resistance (i.e., the ability to withstand a disturbance) and the resilience (i.e., the ability to return to undisturbed conditions). Cropping systems had no effect on litter decomposition, regardless of litter quality and drought treatment. The decomposition of high-quality litter was less resistant but more resilient to drought, and vice versa for low-quality litter. Soil nitrate availability was also strongly decreased by drought (by 32 to 86%). The positive correlation of soil nitrate availability with litter decomposition was significant for pea-barley but not for winter wheat during drought, but this correlation disappeared upon rewetting. In summary, the results of this chapter reveal neither adaptation of organic farming nor conservation tillage can sustain early-stage litter decomposition in response to severe drought. As synthesized in Chapter 7, this doctoral thesis studied the resistance and resilience of ecosystem functions of different cropping systems to drought, in terms of crop productivity, crop phenology, plant water uptake pattern, litter decomposition and soil nitrate availability. The results suggest that stabilizing crop yields and ecosystem functioning in response to drought may not be possible when applying organic farming and conservation tillage for short terms (less than 10 years). For further study, as PhenoCams observe crop phenology in real time, also regarding phases that are not visible for human observers, it is possible to test various management options, such as cover crops or precise irrigation or fertilization on specific crop growth phases to improve current cropping systems.