• Energy Research

AbstractSoil is central to the complex interplay among biodiversity, climate, and society. This paper examines the interconnectedness of soil biodiversity, climate change, and societal impacts, emphasizing the urgent need for integrated solutions. Human‐induced biodiversity loss and climate change intensify environmental degradation, threatening human well‐being. Soils, rich in biodiversity and vital for ecosystem function regulation, are highly vulnerable to these pressures, affecting nutrient cycling, soil fertility, and resilience. Soil also crucially regulates climate, influencing energy, water cycles, and carbon storage. Yet, climate change poses significant challenges to soil health and carbon dynamics, amplifying global warming. Integrated approaches are essential, including sustainable land management, policy interventions, technological innovations, and societal engagement. Practices like agroforestry and organic farming improve soil health and mitigate climate impacts. Effective policies and governance are crucial for promoting sustainable practices and soil conservation. Recent technologies aid in monitoring soil biodiversity and implementing sustainable land management. Societal engagement, through education and collective action, is vital for environmental stewardship. By prioritizing interdisciplinary research and addressing key frontiers, scientists can advance understanding of the soil biodiversity–climate change–society nexus, informing strategies for environmental sustainability and social equity.

We develop a general and unifying methodology for ecological economics which integrates philosophical considerations on the foundations of ecological economics with an adequate operationalization. We argue that the subject matter and aims of ecological economics require a specific combination of inter- and transdisciplinary research, and discuss the epistemological position on which this methodology is based. In accordance with this understanding of inter- and transdisciplinarity and the underlying epistemological position, we develop an operationalization which comprises simultaneous analysis on three levels of abstraction: concepts, (generic) models and case studies. This provides a systematic and integral view on ecological economics, and thus allows one to see the relationship between contributions to the field that have so far been perceived as very heterogeneous and largely unrelated. At the same time, this methodological framework may provide orientation for the further development of ecological economics.

Abstract We analyze a dynamic and stochastic ecological–economic model of grazing management in semi-arid rangelands. The ecosystem is driven by stochastic precipitation. A risk averse farmer chooses a grazing management strategy under uncertainty such as to maximize expected utility from farming income. Grazing management strategies are rules about which share of the rangeland is given rest depending on the actual rainfall in that year. In a first step we determine a myopic farmer's optimal grazing management strategy and show that a risk averse farmer chooses a strategy such as to obtain insurance from the ecosystem: the optimal strategy reduces income variability, but yields less mean income than possible. In a second step we analyze the long-run ecological and economic impact of different strategies. We conclude that a myopic farmer, if he is sufficiently risk averse, will choose a sustainable grazing management strategy, even if he does not take into account long-term ecological and economic benefits of conservative strategies.

Formal models are commonly used in natural resource management (NRM) to study human-environment interactions and inform policy making. In the majority of applications, human behaviour is represented by the rational actor model despite growing empirical evidence of its shortcomings in NRM contexts. While the importance of accounting for the complexity of human behaviour is increasingly recognized, its integration into formal models remains a major challenge. The challenges are multiple: i) there exist many theories scattered across the social sciences, ii) most theories cover only a certain aspect of decision-making, iii) they vary in their degree of formalization, iv) causal mechanisms are often not specified. We provide a framework- MoHuB (Modelling Human Behavior) - to facilitate a broader inclusion of theories on human decision-making in formal NRM models. It serves as a tool and common language to describe, compare and communicate alternative theories. In doing so, we not only enhance understanding of commonalities and differences between theories, but take a first step towards tackling the challenges mentioned above. This approach may enable modellers to find and formalize relevant theories, and be more explicit and inclusive about theories of human decision making in the analysis of social ecological systems. (C) 2016 Elsevier B.V. All rights reserved.

Achieving food and nutrition security for all in a changing and globalized world remains a critical challenge of utmost importance. The development of solutions benefits from insights derived from modelling and simulating the complex interactions of the agri-food system, which range from global to household scales and transcend disciplinary boundaries. A wide range of models based on various methodologies (from food trade equilibrium to agent-based) seek to integrate direct and indirect drivers of change in land use, environment and socio-economic conditions at different scales. However, modelling such interaction poses fundamental challenges, especially for representing non-linear dynamics and adaptive behaviours. We identify key pieces of the fragmented landscape of food security modelling, and organize achievements and gaps into different contextual domains of food security (production, trade, and consumption) at different spatial scales. Building on in-depth reflection on three core issues of food security – volatility, technology, and transformation – we identify methodological challenges and promising strategies for advancement. We emphasize particular requirements related to the multifaceted and multiscale nature of food security. They include the explicit representation of transient dynamics to allow for path dependency and irreversible consequences, and of household heterogeneity to incorporate inequality issues. To illustrate ways forward we provide good practice examples using meta-modelling techniques, non-equilibrium approaches and behavioural-based modelling endeavours. We argue that further integration of different model types is required to better account for both multi-level agency and cross-scale feedbacks within the food system.

Abstract Wind erosion from agricultural land is an underrated and understudied environmental challenge in Europe. Its societal and policy relevance will likely increase in the near future due to climate change and associated increases in the frequency, severity and patterns of atmospheric events such as droughts. We review the research on this issue and find it to be fragmented, siloed and dominated by natural sciences, leaving important research gaps. The most important gaps that circumscribe a research agenda for the future include specific effects of future climate change on wind erosion, the relevance of wind erosion for public health and ecosystem functioning, farmers' behaviour affecting erosion risk and feedback between land management and environmental change, and appropriate policy approaches to address wind erosion risks. Social science contributions are thus required to make wind erosion research relevant for addressing the related societally most pressing questions. We provide a social–environmental systems perspective to highlight the potential of inter‐ and transdisciplinary research into wind erosion in times of climate change and the increasingly recognized need to transform agriculture towards more sustainability and climate resilience. Read the free Plain Language Summary for this article on the Journal blog.

Summary Management decisions by farmers are influenced by complex interrelations of ecological, economic and social factors. Of equal importance are the individual farmers' objectives. However, their relevance has been rarely considered in analyses of management decisions in farming systems. This study systematically analyses the role of farmers' objectives in their decision‐making under various climatic conditions, with dryland grazing systems as a case study. We develop a generic ecological–economic simulation model to compare the performance of a range of fixed grazing strategies under two objectives: (i) maximizing expected utility under risk aversion and (ii) achieving stochastic viability (‘safety first’). We investigate combined effects of several management components in rotational grazing systems and assess the robustness of the results under different climate scenarios. The two objectives considered have structurally different outcomes. The evaluation under the objective to maximize (risk averse) expected utility indicates a trade‐off between mean income and income variability under which farmers would choose one individually optimal management strategy depending on their risk preferences. In contrast, a whole set of strategies is viable under the safety‐first objective. Thus, it offers a solution space for decision support rather than selecting a single optimal strategy. Under both objectives, economically preferable strategies share common characteristics: short standing time, large paddock number and reasonably high stocking rate improve the efficiency of a farm enterprise in terms of higher mean income, lower variance, coverage of certain minimum income requirements while preserving pasture quality. Synthesis and applications. The outcomes of this study contribute to both management support at the farm scale and policy advice at the regional scale and beyond. An insight of practical relevance for individual farmers is that a strategy type with high‐intensity, short‐duration grazing management appears to be most robust under changing climate and economic conditions. Nevertheless, considering individual farmers' objectives is essential for determining the individually optimal strategy. Furthermore, for policymakers, we provide an approach to evaluate policy programmes governing farming activities in terms of effectiveness and implications (particularly side effects). The explicit consideration of the diversity of individual objectives is crucial for avoiding counterproductive incentives and improving sustainability of land‐use policies.

Abstract Rain-index insurance is strongly advocated in many parts of the developing world to help farmers to cope with climatic risk that prevails in (semi-)arid rangelands due to low and highly uncertain rainfall. We present a modeling analysis of how the availability of rain-index insurance affects the sustainability of rangeland management. We show that a rain-index insurance with frequent payoffs, i.e. a high strike level, leads to the choice of less sustainable grazing management than without insurance available. However, rain-index insurance with a low to medium strike level enhances the farmer's well-being while not impairing the sustainability of rangeland management.