Multi-scale Modelling of Adapting European Farming Systems

European farming systems are challenged by an increasing global population, income growth, dietary changes and last, but not least, by a changing climate threatening future harvests, especially through increased frequency and severity of extreme events such as drought and heat waves. Therefore, there is a clear need to sustainably intensify and effectively adapt agricultural systems to climate change. Yet, increase in food production and adaptation are just two of many claims on agriculture, which is also supposed to meet growing demands on feed, fibre and fuel and to play a key role in mitigating climate change. The multiple claims on ecosystem services expected from agri-ecological systems call for an integrated assessment and modelling (IAM) of agricultural systems to adequately evaluate the multiple dimensions of the potential impacts as well as promising adaptation and mitigation options. This includes agriculture's responses to global change in the context of other sustainability aspects. Biophysical and socioeconomic analyses need to be integrated across different disciplines and spatiotemporal scales. In recent years the agricultural systems modelling community has made great efforts to use harmonized climate change, socio-economic and agricultural development scenarios and run them through a chain of models, e.g. by selected ensembles of biophysical and economic models at multiple scales, from farm to global. In phase 2 (2015-17) the European MACSUR knowledge hub has put its main focus on the regional (sub-national) level in the EU, with due consideration of the whole farm context. The aim of this paper is to compare three regional cases from the pool of MACSUR case studies across Europe, i.e. North Savo region in Finland, the Mostviertel region in Austria and the Oristanese region in Sardinia (Italy) representing different European farming systems along a north-south climatic gradient in Europe. These case studies represent a sample of some prominent farming systems, though only a fraction of a much larger diversity of farming and environmental conditions prevailing in Europe. We describe how adaptation options are analysed within an integrated set of linked models or model outputs combining information from different spatial scales, i.e. from region-specific crop, animal and farm level models to an analysis at regional and national level changes in agriculture and food production. First results show that adaptation to climate change affects agricultural production and farm income very differently. For some regions, e.g. in Finland there are both negative and positive effects while for the Sardinian case study adaptation to climate change have negative effects on farm income. Biophysical models, especially crop simulation models are first applied to analyse climate change impacts on yield, water use, biomass etc. and provide the outputs (i.e. delta changes) as input to economic models that contain the regional specificities of the case studies. Likewise, biophysical models are applied to analyse effects of various adaptation and mitigation options to provide information on effects of management changes on reducing damage/loss or taking opportunities from climate (adaptation) or reducing greenhouse gas emissions (mitigation). The economic models analyse economic impacts, for example the viability of management changes at farm and regional scales. Farm and regional scale economic models, backed by more detailed data and regional expert knowledge, can supply better representations of developments in each of the regions than this could be done by larger-scale (e.g. EU-wide or global) models. Sector or national economy-wide models are less specific in technical changes in agriculture, productivity changes, or in its use of inputs, due to higher level of aggregation. Nevertheless the market level view offered by sector models put the farm level changes and adaptations in a wider global context. Agricultural markets are highly integrated globally and the analyses for the case study regions also require information on global and European market developments. For example, significant changes in food demand due to changes in tastes and preferences, including aspects of climate change mitigation, may imply major changes for regional production structures. In MACSUR, this information – although not fully implemented in the case studies yet – is provided by the economic agricultural sector model CAPRI. The main strength of CAPRI in this context is that it is a global model with European focus. As such CAPRI can capture global developments and translate them to the regional level in the EU. The coupled analysis using global, EU and national level models side by side with farm level models provides unique results and much more insights on future possibilities and challenges for farmers and the food chain, than separating and restricting the analyses to either low or high aggregation level analyses. Market and policy changes often dominate longer term climate change considerations in the decision making of food chain actors, even if unfavourable weather events have become more common in recent years. Socio-economic scenarios from global to national and regional levels are needed to put adaptation and mitigation strategies in a wider context. Models, especially those that are able to accommodate biophysical, economic and policy changes are needed to show the value added from adaptations to climate change. Benefits and costs of mitigation strategies may be highly dependent on market developments. The current integrated assessment and modelling approach of MACSUR focusses on adaptation scenarios. It will be extended for the analysis and impact of mitigation policies in a later phase

Multi-scale Modelling of Adapting European Farming Systems

European farming systems are challenged by an increasing global population, income growth, dietary changes and last, but not least, by a changing climate threatening future harvests, especially through increased frequency and severity of extreme events such as drought and heat waves. Therefore, there is a clear need to sustainably intensify and effectively adapt agricultural systems to climate change. Yet, increase in food production and adaptation are just two of many claims on agriculture, which is also supposed to meet growing demands on feed, fibre and fuel and to play a key role in mitigating climate change. The multiple claims on ecosystem services expected from agri-ecological systems call for an integrated assessment and modelling (IAM) of agricultural systems to adequately evaluate the multiple dimensions of the potential impacts as well as promising adaptation and mitigation options. This includes agriculture's responses to global change in the context of other sustainability aspects. Biophysical and socioeconomic analyses need to be integrated across different disciplines and spatiotemporal scales. In recent years the agricultural systems modelling community has made great efforts to use harmonized climate change, socio-economic and agricultural development scenarios and run them through a chain of models, e.g. by selected ensembles of biophysical and economic models at multiple scales, from farm to global. In phase 2 (2015-17) the European MACSUR knowledge hub has put its main focus on the regional (sub-national) level in the EU, with due consideration of the whole farm context. The aim of this paper is to compare three regional cases from the pool of MACSUR case studies across Europe, i.e. North Savo region in Finland, the Mostviertel region in Austria and the Oristanese region in Sardinia (Italy) representing different European farming systems along a north-south climatic gradient in Europe. These case studies represent a sample of some prominent farming systems, though only a fraction of a much larger diversity of farming and environmental conditions prevailing in Europe. We describe how adaptation options are analysed within an integrated set of linked models or model outputs combining information from different spatial scales, i.e. from region-specific crop, animal and farm level models to an analysis at regional and national level changes in agriculture and food production. First results show that adaptation to climate change affects agricultural production and farm income very differently. For some regions, e.g. in Finland there are both negative and positive effects while for the Sardinian case study adaptation to climate change have negative effects on farm income. Biophysical models, especially crop simulation models are first applied to analyse climate change impacts on yield, water use, biomass etc. and provide the outputs (i.e. delta changes) as input to economic models that contain the regional specificities of the case studies. Likewise, biophysical models are applied to analyse effects of various adaptation and mitigation options to provide information on effects of management changes on reducing damage/loss or taking opportunities from climate (adaptation) or reducing greenhouse gas emissions (mitigation). The economic models analyse economic impacts, for example the viability of management changes at farm and regional scales. Farm and regional scale economic models, backed by more detailed data and regional expert knowledge, can supply better representations of developments in each of the regions than this could be done by larger-scale (e.g. EU-wide or global) models. Sector or national economy-wide models are less specific in technical changes in agriculture, productivity changes, or in its use of inputs, due to higher level of aggregation. Nevertheless the market level view offered by sector models put the farm level changes and adaptations in a wider global context. Agricultural markets are highly integrated globally and the analyses for the case study regions also require information on global and European market developments. For example, significant changes in food demand due to changes in tastes and preferences, including aspects of climate change mitigation, may imply major changes for regional production structures. In MACSUR, this information – although not fully implemented in the case studies yet – is provided by the economic agricultural sector model CAPRI. The main strength of CAPRI in this context is that it is a global model with European focus. As such CAPRI can capture global developments and translate them to the regional level in the EU. The coupled analysis using global, EU and national level models side by side with farm level models provides unique results and much more insights on future possibilities and challenges for farmers and the food chain, than separating and restricting the analyses to either low or high aggregation level analyses. Market and policy changes often dominate longer term climate change considerations in the decision making of food chain actors, even if unfavourable weather events have become more common in recent years. Socio-economic scenarios from global to national and regional levels are needed to put adaptation and mitigation strategies in a wider context. Models, especially those that are able to accommodate biophysical, economic and policy changes are needed to show the value added from adaptations to climate change. Benefits and costs of mitigation strategies may be highly dependent on market developments. The current integrated assessment and modelling approach of MACSUR focusses on adaptation scenarios. It will be extended for the analysis and impact of mitigation policies in a later phase

Engineers of Life? A Critical Examination of the Concept of Life in the Debate on Synthetic Biology

The concept of life plays a crucial role in the debate on synthetic biology. The first part of this chapter outlines the controversial debate on the status of the concept of life in current science and philosophy. Against this background, synthetic biology and the discourse on its scientific and societal consequences is revealed as an exception. Here, the concept of life is not only used as buzzword but also discussed theoretically and links the ethical aspects with the epistemological prerequisites and the ontological consequences of synthetic biology. The second part examines this point of intersection and analyses some of the issues which are discussed in terms of the concept of life. The third part turns to the history of the concept of life. It offers an examination of scientific and philosophical discourses on life at the turn of the 20th century and suggests a surprising result: In the light of this history, synthetic biology leads to well-known debates, arguments, notions and questions. But it is concluded that the concept of life is too ambiguous and controversial to be useful for capturing the actual practice of synthetic biology. In the fourth part I argue that with regard to the ethical evaluation of synthetic biology, the ambiguity of the concept of life is not as problematic as sometimes held because other challenges are more important. The question whether the activity of synthetic biological systems should be conceived as life or not is primarily theoretical

Shedding light on plant litter decomposition: Advances, implications and new directions in understanding the role of photodegradation

Litter decomposition contributes to one of the largest fluxes of carbon (C) in the terrestrial biosphere and is a primary control on nutrient cycling. The inability of models using climate and litter chemistry to predict decomposition in dry environments has stimulated investigation of non-traditional drivers of decomposition, including photodegradation, the abiotic decomposition of organic matter via exposure to solar radiation. Recent work in this developing field shows that photodegradation may substantially influence terrestrial C fluxes, including abiotic production of carbon dioxide, carbon monoxide and methane, especially in arid and semi-arid regions. Research has also produced contradictory results regarding controls on photodegradation. Here we summarize the state of knowledge about the role of photodegradation in litter decomposition and C cycling and investigate drivers of photodegradation across experiments using a meta-analysis. Overall, increasing litter exposure to solar radiation increased mass loss by 23% with large variation in photodegradation rates among and within ecosystems. This variation was tied to both litter and environmental characteristics. Photodegradation increased with litter C to nitrogen (N) ratio, but not with lignin content, suggesting that we do not yet fully understand the underlying mechanisms. Photodegradation also increased with factors that increased solar radiation exposure (latitude and litter area to mass ratio) and decreased with mean annual precipitation. The impact of photodegradation on C (and potentially N) cycling fundamentally reshapes our thinking of decomposition as a solely biological process and requires that we define the mechanisms driving photodegradation before we can accurately represent photodegradation in global C and N models. © 2012 US Government

Reduction in primary production followed by rapid recovery of plant biomass in response to repeated mid-season droughts in a semiarid shrubland

The frequency and severity of extreme weather events, including droughts, are expected to increase due to the climate change. Climate manipulation field experiments are widely used tools to study the response of key parameters like primary production to the treatments. Our study aimed to detect the effect of drought on the aboveground biomass and primary production both during the treatments as well as during the whole growing seasons in semiarid vegetation. We estimated aboveground green biomass of vascular plants in a Pannonian sand forest-steppe ecosystem in Hungary. We applied non-destructive field remote sensing method in control and drought treatments. Drought treatment was carried out by precipitation exclusion in May and June, and was repeated in each year from 2002. We measured NDVI before the drought treatment, right after the treatment, and at the end of the summer in 2011 and 2013. We found that the yearly biomass peaks, measured in control plots after the treatment periods, were decreased or absent in drought treatment plots, and consequently, the aboveground net primary production was smaller than in the control plots. At the same time, we did not find general drought effects on all biomass data. The studied ecosystem proved resilient, as the biomass in the drought-treated plots recovered by the next drought treatment. We conclude that the effect of drought treatment can be overestimated with only one measurement at the time of the peak biomass, while multiple within-year measurements better describe the response of biomass

Northward shift of the agricultural climate zone under 21st-century global climate change

As agricultural regions are threatened by climate change, warming of high latitude regions and increasing food demands may lead to northward expansion of global agriculture. While socio-economic demands and edaphic conditions may govern the expansion, climate is a key limiting factor. Extant literature on future crop projections considers established agricultural regions and is mainly temperature based. We employed growing degree days (GDD), as the physiological link between temperature and crop growth, to assess the global northward shift of agricultural climate zones under 21st-century climate change. Using ClimGen scenarios for seven global climate models (GCMs), based on greenhouse gas (GHG) emissions and transient GHGs, we delineated the future extent of GDD areas, feasible for small cereals, and assessed the projected changes in rainfall and potential evapotranspiration. By 2099, roughly 76% (55% to 89%) of the boreal region might reach crop feasible GDD conditions, compared to the current 32%. The leading edge of the feasible GDD will shift northwards up to 1200 km by 2099 while the altitudinal shift remains marginal. However, most of the newly gained areas are associated with highly seasonal and monthly variations in climatic water balances, a critical component of any future land-use and management decisions