Suchergebnisse

Problems related to food security and sustainable development are complex (Ericksenet al., 2009) and require consideration of biophysical, economic, political, and social factors, as well as their interactions, at the level of farms, regions, nations, and globally. While the solution to such societal problems may be largely political, there is a growing recognition of the need for science to provide sound information to decision-makers (Meinke et al., 2009). Achieving this, particularly in light of largely uncertain future climate and socio-economic changes, will necessitate integrated assessment approaches and appropriate integrated assessment modeling (IAM) tools to perform them. Recent (Ewertet al., 2009; van Ittersumet al., 2008) and ongoing (Rosenzweiget al., 2013) studies have tried to advance the integrated use of biophysical and economic models to represent better the complex interactions in agricultural systems that largely determine food supply and sustainable resource use. Nonetheless, the challenges for model integration across disciplines are substantial and range from methodological and technical details to an often still-weak conceptual basis on which to ground model integration (Ewertet al., 2009; Janssenet al., 2011). New generations of integrated assessment models based on well-understood, general relationships that are applicable to different agricultural systems across the world are still to be developed. Initial efforts are underway towards this advancement (Nelsonet al., 2014; Rosenzweiget al., 2013). Together with economic and climate models, crop models constitute an essential model group in IAM for large-area cropping systems climate change impact assessments. However, in addition to challenges associated with model integration, inadequate representation of many crops and crop management systems, as well as a lack of data for model initialization and calibration, limit the integration of crop models with climate and economic models (Ewertet al., 2014). A particular obstacle is the mismatch between the temporal and spatial scale of input/output variables required and delivered by the various models in the IAM model chain. Crop models are typically developed, tested, and calibrated for field-scale application (Booteet al., 2013; see also Part 1, Chapter 4 in this volume) and short time-series limited to one or few seasons. Although crop models are increasingly used for larger areas and longer time-periods (Bondeauet al., 2007; Deryng et al., 2011; Elliottet al., 2014) rigorous evaluation of such applications is pending. Among the different sources of uncertainty related to climate and soil data, model parameters, and structure, the uncertainty from methods used to scale-up crop models has received little attention, though recent evaluations indicate that upscaling of crop models for climate change impact assessment and the resulting errors and uncertainties deserve attention in order to advance crop modeling for climate change assessment (Ewertet al., 2014; R¨ otteret al., 2011). This reality is now reflected in the scientific agendas of new international research projects and programs such as the Agricultural Model Intercomparison and Improvement Project (AgMIP; Rosenzweiget al., 2013) and MACSUR (MACSUR, 2014). In this chapter, progress in evaluation of scaling methods with their related uncertainties is reviewed. Specific emphasis is on examining the results of systematic studies recently established in AgMIP and MACSUR. Main features of the respective simulation studies are presented together with preliminary results. Insights from these studies are summarized and conclusions for further work are drawn.

AbstractResilience, vulnerability and adaptability have emerged as dominant concepts in the study of disturbance and change of social-ecological systems. We analyze the conceptual, methodological and operational aspects in using these concepts for the assessment and analysis of agricultural systems and try to identify differences and possible overlaps between them. The analysis is performed considering a number of published studies on agricultural systems over a wide geographical range where these concepts have been applied. Our results show a clear conceptual overlap and often the exchangeable use of the concepts. Furthermore, the driving methodological and operational criteria for their application could not be separated unambiguously. It was, thus, difficult to identify guiding principles for the operational application of the individual concepts. We stress that the operationalization of these concepts requires consistency in the approaches and protocols to ensure their coherent use. We also argue that the conceptual and operational integration of resilience, vulnerability and adaptability would perhaps lead to a more complete portrayal of the behavior of agricultural systems in changing situations. But this requires more research including the development of operational protocols for which the premises of complexity, participation and functionality seem key.

Ecological fragility combined with institutional weakness and political and economic instability make West Africa one of the most vulnerable regions to climate change. The West African Science Service Center on Climate Change and Adapted Land Use (WASCAL) tackles this vulnerability by investigating the interface of climate and rural socia-ecological systems, in order to propose ad hoc adaptation measures. In this context, the characterization of the livelihoods of rural communities is crucial since these constitute the units of evaluation and analysis of ongoing and forthcoming studies. Purposefully, this paper provides a joint description of these livelihoods. Divided in three sections, the first one focuses on the agroecological (biophysical) characteristics, detailing climatic, edaphological and hydrological qualities mainly; the second section, portrays the principal socioeconomic features: demography, culture, and organizational and economic institutions; and the third section, describes the main farming and cropping systems themselves, matching the first sections outcomes with managerial aspects, such as farming practices and regional variations, planting patterns, etc. The paper concludes with an overview on relevant features of the farming and cropping systems, recalling the main limiting factors and the local strategies used to overcome them.

Transforming food systems involves five action tracks: i) access to safe and nutritious food, ii) sustain- able consumption, iii) nature-positive production, iv) equitable livelihood, and v) resilience to shocks and stress. Action Track 5 of the Food Systems Summit aims to ensure food system resilience in the face of in- creasing stresses from climate change, population growth and conflict over limited natural resources. We identify five distinct capacities that are key to a resilient food system in the face of these shocks: (i) to anticipate, (ii) to prevent, (iii) to absorb, (iv) to adapt to an evolving risk and (v) to transform in cases where the current food system is no longer sustainable. Resilience at the individual, community, government and global food system level must be built in such a way that the economic, social and environmental bases to generate food security and nutrition for current and future generations are not compromised anywhere in the world. This means that it is equitable in a financial sense (economic resilience), it is supportive of the entire community (social resilience), and it minimizes harmful impacts on the natural environment (ecological resilience). There are a number of key trade-offs which must be navigated as we strive to achieve greater food system resilience. These include the need to deliver short term humanitarian aid without jeopardizing long run development, mitigation of rising global temperatures even as the food system adapts to the inevitable changes in the earth's climate, taking advantage of the benefits of globalization while avoiding the downsides, and encouraging agricultural production and boosting rural incomes while also protecting the environment. All of these trade-offs become more pronounced in the context of small farms operating in marginal environments. In order to address these trade-offs, cooperation and coordination across policy makers, local communities and public and private institutions and investors will be required. A range of local, regional, national and global solutions covering different parts and contexts of the food system have been reviewed to understand progress and challenges in building resilience to improve food security. The resilience framework is helpful to conceptualise complex problems related to food security and allows us to point to important challenges that need to be overcome. From this analysis we conclude that developing an operational resilience approach is always context-specific and requires the involvement of relevant local, national and international actors, organisations and agencies. Hence, there is no single game changing solution that will ensure resilience across multiple food security challenges. Instead, adopting resilience as a systems approach to support the conceptualisation and operationalization considering the respective actors will contribute to the development of context-specific solutions. Beyond that, much will be gained by highlighting successful solutions and facilitating exchange of tools, data, information and knowledge and capacity. This will also contribute to the further develop of the resilience approach as a key concept to achieve food security.

Correspondance: wery@supagro.inra.fr ; International audience ; Introduction : Agricultural technologies and agricultural, environmental and rural development policies are increasingly designed to contribute to the sustainability of cropping and farming systems and to enhance their contributions to sustainable development at large. The effectiveness and efficiency of such policies and technological developments in realizing desired impacts could be greatly enhanced if the quality oftheir ex-ante assessments were improved. Four key challenges and requirements to make research tools more useful for integrated assessment in the European Union have been defined (Van I.ttersum et al., 2008): (a) overcome the gap between micro-macro level analysis, (b) decrease the bias in integrated assessments towards either economic or environmental issues, (c) ensure reusability of models and their use for indicator assessment and (d) overcome hindrances in technical linkage of models. Tools for: integrated assessment must have multi-scale capabilities and preferably allow application to a broad variety of policy questions. At the same time, to be useful for scientists, the framework must facilitate state-of-the-art science both on aspects of the agricultural systems and on integration. This paper presents the design of a framework for agricultural systems (SEAMLESS Integrated Fratnework) and discusses the implications for cropping and farming systems modelling.

Correspondance: wery@supagro.inra.fr ; International audience ; Introduction : Agricultural technologies and agricultural, environmental and rural development policies are increasingly designed to contribute to the sustainability of cropping and farming systems and to enhance their contributions to sustainable development at large. The effectiveness and efficiency of such policies and technological developments in realizing desired impacts could be greatly enhanced if the quality oftheir ex-ante assessments were improved. Four key challenges and requirements to make research tools more useful for integrated assessment in the European Union have been defined (Van I.ttersum et al., 2008): (a) overcome the gap between micro-macro level analysis, (b) decrease the bias in integrated assessments towards either economic or environmental issues, (c) ensure reusability of models and their use for indicator assessment and (d) overcome hindrances in technical linkage of models. Tools for: integrated assessment must have multi-scale capabilities and preferably allow application to a broad variety of policy questions. At the same time, to be useful for scientists, the framework must facilitate state-of-the-art science both on aspects of the agricultural systems and on integration. This paper presents the design of a framework for agricultural systems (SEAMLESS Integrated Fratnework) and discusses the implications for cropping and farming systems modelling.

Introduction : Agricultural technologies and agricultural, environmental and rural development policies are increasingly designed to contribute to the sustainability of cropping and farming systems and to enhance their contributions to sustainable development at large. The effectiveness and efficiency of such policies and technological developments in realizing desired impacts could be greatly enhanced if the quality oftheir ex-ante assessments were improved. Four key challenges and requirements to make research tools more useful for integrated assessment in the European Union have been defined (Van I.ttersum et al., 2008): (a) overcome the gap between micro-macro level analysis, (b) decrease the bias in integrated assessments towards either economic or environmental issues, (c) ensure reusability of models and their use for indicator assessment and (d) overcome hindrances in technical linkage of models. Tools for: integrated assessment must have multi-scale capabilities and preferably allow application to a broad variety of policy questions. At the same time, to be useful for scientists, the framework must facilitate state-of-the-art science both on aspects of the agricultural systems and on integration. This paper presents the design of a framework for agricultural systems (SEAMLESS Integrated Fratnework) and discusses the implications for cropping and farming systems modelling.

Der Überschuss der Stickstoff-Gesamtbilanz der Landwirtschaft in Deutschland beträgt jährlich 1,55 Millionen Tonnen N, was rund 93 kg N/ha LF (Mittel 2016 bis 2018) entspricht. Rund 90 % des Nitrat-Eintrags in das Grundwasser, 95 % der Ammoniak- und 80 % der Lachgas-Emissionen in die Atmosphäre stammen aus der Landwirtschaft. Der Anteil der Landwirtschaft an den Phosphoreinträgen in die Nord‐ und Ostsee beträgt zwischen 50 % und 63 %. Eine nachhaltige Düngegesetzgebung bildet ein zentrales Element, um die Nährstoffeinträge aus der Landwirtschaft in alle Ökosystembereiche soweit zu reduzieren, dass zukünftig die gesetzlichen Vorgaben eingehalten werden. Mit Hilfe der Stoffstrombilanz sollen die Nährstoffflüsse in landwirtschaftlichen Betrieben transparent und überprüfbar abgebildet werden. Die Stoffstrombilanzverordnung (StoffBilV) regelt, wie betriebliche Bilanzen für Stickstoff und Phosphor zu erstellen sind und welche Obergrenzen für die betrieblichen Nährstoffüberschüsse gelten. Im Jahr 2021 soll der Geltungsbereich der StoffBilV auf alle Betriebe mit mehr als 20 Hektar landwirtschaftlicher Nutzfläche oder mehr als 50 Großvieheinheiten je Betrieb ausgeweitet werden. Im Zuge dieser Novellierung ist auch die Obergrenze der betrieblichen N-Überschüsse neu festzusetzen, für den P-Überschuss ist erstmalig ein Grenzwert festzulegen. Mit der vorliegenden Stellungnahme wird ein Konzept für die Begrenzung der betrieblichen N- und P-Überschüsse in der StoffBilV vorgelegt, das einen umweltgerechten, nachhaltigen und ressourceneffizienten Umgang mit Nährstoffen sicherstellt und das gleichzeitig der ökonomisch nachhaltigen Anpassungsfähigkeit der Betriebe Rechnung trägt. Mit der langfristigen Festlegung der Zielwerte erhalten die landwirtschaftlichen Betriebe Planungssicherheit für ihre Betriebsentwicklung und eindeutige Vorgaben für die zukünftige Gestaltung ihres Nährstoffmanagements.

MACSUR — Modelling European Agriculture with Climate Change for Food Security — is a knowledge hub that was formally created in June 2012 as a European scientific network. The strategic aim of the knowledge hub is to create a coordinated and globally visible network of European researchers and research groups, with intra- and interdisciplinary interaction and shared expertise creating synergies for the development of scientific resources (data, models, methods) to model the impacts of climate change on agriculture and related issues. This objective encompasses a wide range of political and sociological aspects, as well as the technical development of modelling capacity through impact assessments at different scales and assessing uncertainties in model outcomes. We achieve this through model intercomparisons and model improvements, harmonization and exchange of data sets, training in the selection and use of models, assessment of benefits of ensemble modelling, and cross-disciplinary linkages of models and tools. The project engages with a diverse range of stakeholder groups and to support the development of resources for capacity building of individuals and countries. Commensurate with this broad challenge, a network of currently 300 scientists (measured by the number of individuals on the central e-mail list) from 18 countries evolved from the original set of research groups selected by FACCE. In the spirit of creating and maintaining a network for intra- and interdisciplinary knowledge exchange, network activities focused on meetings of researchers for sharing expertise and, depending on group resources (both financial and personnel), development of collaborative research activities. The outcome of these activities is the enhanced knowledge of the individual researchers within the network, contributions to conference presentations and scholarly papers, input to stakeholders and the general public, organised courses for students, junior and senior scientists. The most visible outcome are the scientific results of the network activities, represented in the contributions of MACSUR members to the impressive number of more than 200 collaborative papers in peer-reviewed publications. Here, we present a selection of overview and cross-disciplinary papers which include contributions from MACSUR members. It highlights the major scientific challenges addressed, and the methodological solutions and insights obtained. Over and above these highlights, major achievements have been reached regarding data collection, data processing, evaluation, model testing, modelling assessments of the effects of agriculture on ecosystem services, policy, and development of scenarios. Details on these achievements in the context of MACSUR can be found in our online publication FACCE MACSUR Reports at http://ojs.macsur.eu.