Improving the representation of smallholder farmers’ adaptive behaviour in agent-based models: Learning-by-doing and social learning

Computational models have been used to investigate farmers’ decision outcomes, yet classical economics assumptions prevail, while learning processes and adaptive behaviour are overlooked. This paper advances the conceptualisation, modelling and understanding of learning-by-doing and social learning, two key processes in adaptive (co-)management literature. We expand a pre-existing agent-based model (ABM) of an agricultural social-ecological system, RAGE (Dressler et al., 2018). We endow human agents with learning-by-doing and social learning capabilities, and we study the impact of their learning strategies on economic, ecological and social outcomes. Methodologically, we contribute to an under-explored area of modelling farmers’ behaviour. Results show that agents who employ learning better match their decisions to the ecological conditions than those who do not. Imitating the learning type of successful agents further improves outcomes. Different learning processes are suited to different goals. We report on conditions under which learning-by-doing becomes dominant in a population with mixed learning approaches

Substantial reductions in non-CO2 greenhouse gas emissions reductions implied by IPCC estimates of the remaining carbon budget

Carbon budgets are quantifications of the total amount of carbon dioxide that can ever be emitted while keeping global warming below specific temperature limits. However, estimates of these budgets for limiting warming to 1.5 °C and well-below 2 °C include assumptions about how much warming can be expected from non-CO2 emissions. Here, we uncover the non-CO2 emissions assumptions that underlie the latest remaining carbon budget estimates by the Intergovernmental Panel on Climate Change and quantify the implication of the world pursuing alternative higher or lower emissions. We consider contributions of methane, nitrous oxide, fluorinated gases, and aerosols and show how pursuing inadequate methane emission reductions causes remaining carbon budgets compatible with the Paris Agreement temperature limits to be exhausted today, effectively putting achievement of the Paris Agreement out of reach

Exploring fishing impacts on the structure and functioning of the Yellow Sea ecosystem using an individual-based modeling approach

The Yellow Sea is a marginal sea in the Northwestern Pacific where the fishery resources have been overfished and the community structure has greatly changed over the past six decades. Ecosystem modeling approaches are valuable tools to uncover potential mechanisms behind the ecosystem changes. Here, we developed ‘OSMOSE-YS’, an individual-based multi-species OSMOSE model that includes important commercial pelagic and demersal fish and invertebrates in the Yellow Sea. Simulations were carried out under three fishing scenarios to investigate how different levels of fishing pressure may have impacted the Yellow Sea ecosystem. Results indicate that the biomass of demersal fish continued to decline during 1970–2014, while the biomass of pelagic fish and invertebrates fluctuated periodically. Long-term fishing pressure has led to the reduction of total biomass, body sizes, and longevity of the modelled species. Under low-fishing condition, the ecosystem biomass is restored and the proportion of elder and larger individuals increases. On the contrary, high-fishing condition further decreases the proportion of high-trophic-level species. OSMOSE-YS serves as a baseline model to investigate ecosystem responses to different fishing strategies, in support of ecosystem-based fisheries management in the Yellow Sea

Water circles—a tool to assess and communicate the water cycle

‘Water circles’ are presented as flexible water cycle diagrams aggregating the flows through a system for a specific region and time period, categorized by flow type and organized by magnitude. Water circles for an entire system and separate storage components can be interpreted as water cycle speedometers and can help compare and communicate different climate and human impacts on different regions, time periods, and storage components. Water circles can facilitate comparisons between hydrological models and other methods for deriving water balances

Translocal social resilience dimensions of migration as adaptation to environmental change

There is growing recognition of the potential of migration to contribute to climate-change adaptation. Yet, there is limited evidence to what degree, under what conditions, for whom, and with which limitations this is effectively the case. We argue that this results from a lack of recognition and systematic incorporation of sociospatiality—the nested, networked, and intersectional nature of migration-as-adaptation. Our central objective is to utilize the translocal social-resilience approach to overcome these gaps, to identify processes and structures that shape the social resilience of translocal livelihood systems, and to illustrate the mechanisms behind the multiplicity of possible resilience outcomes. Translocal livelihood constellations anchored in rural Thailand as well as in domestic and international destinations of Thai migrants serve as illustrative empirical cases. Data were gathered through a multisited and mixed-methods research design. This paper highlights the role of the distinct but interlinked situations and operational logics at places of origin and destination, as well as the different positionalities and resulting vulnerabilities, roles, commitments, and practices of individuals and households with regard to resilience. Based on the empirical results, the paper distills a generalized typology of five broad categories of resilience outcomes, which explicitly considers sociospatiality. Our approach helps to grasp the complexity of migration-as-adaptation and to avoid simplistic conclusions about the benefits and costs of migration for adaptation—both of which are necessary for sound, evidence-based, migration-as-adaptation policymaking

Economic and labour market impacts of migration in Austria: an agent-based modelling approach

This study examines the potential economic and labour market impacts of a hypothetical but plausible migration scenario of 250,000 new migrants inspired by Austria’s experience in 2015. Using the agent-based macroeconomic model developed by Poledna et al. (Eur Econ Rev, 151:104306, 2023. 10.1016/j.euroecorev.2022.104306, the study explores the detailed labour market outcomes for different groups in Austria’s population and the macroeconomic effects of the migration scenario. The analysis suggests that Austria’s economy and labour market have the potential to be resilient to the simulated migration influx. The results indicate a positive impact on GDP due to increased aggregate consumption and investment. The labour market experiences an increase in the unemployment rates of natives and previous migrants. In some industries, the increase in the unemployment rates is more significant, potentially indicating competition among different groups of migrants. This research provides insights for policymakers and stakeholders in Austria and other countries that may face the challenge of managing large-scale migration in the near future

The Tail End of Migration: Assessing the Climate Resilience of Migrant Households in Ethiopia

Climate change is associated with increasing frequencies and intensities of extreme weather events. These can, directly and indirectly, shape human (im)mobility. While most research on migration in the context of climate change focuses on climate as a migration driver in origin areas, there is a gap in knowledge on the role of migration for climate resilience in the destination areas. Consequently, this paper aims to study differences in resilience (resistance and recovery) to climatic shocks between migrant and non-migrant households at migration destination areas in Ethiopia, a country that is highly exposed and vulnerable to climate change. We use longitudinal data from the Living Standards Measurement Study (LSMS) conducted by the World Bank to construct a comprehensive Well-Being Index, which is used to analyze the impacts of climatic shocks and identify households that are more or less able to resist and recover from shocks. We use fixed effect panel regression approaches to model the impacts of climatic shocks on well-being over time for migrant and non-migrant households. Further explorative mediation analyses yield insights into mechanisms explaining differences between households. We find that migrant households have an overall lower climate resistance as they experience double as high well-being impacts when exposed to climatic shocks compared to non-migrant households. Climatic shocks significantly reduce the food security of all affected households and, in addition, negatively impact access to basic infrastructures and health for migrant households. Mediation analyses suggest that these differential climatic impacts are mainly driven by characteristics of migrant-origin regions, including poverty. Migrant households originating from less prosperous regions still face disadvantages even if they now reside in more prosperous regions. This contrasts the experience of non-migrant households whose resilience benefits from increased prosperity in their region of residence. While migrant households show a lower resistance to climate shocks, they recover faster from climatic shocks, which can be associated with diversified livelihoods and remittances that take time to unfold. This research is highly relevant to policy as it improves the understanding of underlying factors shaping differential vulnerability to climate change impacts and supports targeted interventions to increase the resilience of affected households

Tracing fossil-based plastics, chemicals and fertilizers production in China

Phasing down fossil fuels is crucial for climate mitigation. Even though 80-90% of fossil fuels are used to provide energy, their use as feedstock to produce plastics, fertilizers, and chemicals, is associated with substantial CO2 emissions. However, our understanding of hard-to-abate chemical production remains limited. Here we developed a chemical process-based material flow model to investigate the non-energy use of fossil fuels and CO2 emissions in China. Results show in 2017, the chemical industry used 0.18 Gt of coal, 88.8 Mt of crude oil, and 12.9 Mt of natural gas as feedstock, constituting 5%, 15%, and 7% of China's respective total use. Coal-fed production of methanol, ammonia, and PVCs contributes to 0.27 Gt CO2 emissions ( ~ 3% of China's emissions). As China seeks to balance high CO2 emissions of coal-fed production with import dependence on oil and gas, improving energy efficiency and coupling green hydrogen emerges as attractive alternatives for decarbonization

Fertility decline and age-structure in China and India

China and India, two Asian countries that experienced a rapid decline in fertility since the middle of the twentieth century, are the focus of this paper. Although there is no doubt that lower fertility levels have many positive effects on the economy, development and sustainability, little is known about the optimal transition from high to medium or even low levels of fertility. Firstly, implementing policies that have the potential to reduce fertility is costly. Secondly, additional costs arise from adapting the infrastructure to a population that fluctuates quickly not only in terms of size but also with respect to the age structure. We apply an intertemporal optimisation model that takes the costs and benefits of fertility decline into account. The optimal time path depends on the cost structure, the planning horizon and the initial conditions. In the case of a long planning horizon and high initial fertility, it may even be optimal to reduce fertility temporarily below replacement level in order to slow down population growth at an early stage. A key finding of our formal investigation is that, under the same plausible parameter settings, the optimal paths for China and India differ substantially. Moreover, our analysis shows that India, where the fertility decline emerged as a consequence of societal and economic developments, followed a path closer to the optimal fertility transition than China, where the fertility decline was state-imposed. The mathematical approach deployed for this analysis provides insights into the optimal long-term development of fertility and allows for policy conclusions to be drawn for other countries that are still in the fertility transition process

Assessing multidimensional food system risks in Asia and the Pacific : INsights on Food SystEm Risks – INFER

This working paper introduces INFER (INsights on Food SystEm Risks), a risk assessment framework that provides insights into multidimensional risks to three food system outcomes: human health and nutrition; ecosystem health and sustainability; and shared prosperity. It spans six dimensions of food security. Building on publicly available data, INFER enables tracking of risk over time and comparison across countries. It therefore strengthens the tools available for food systems monitoring and for ensuring that food systems resilience-building strategies are risk-informed. The results of applying INFER for Asia and the Pacific are presented, including profiles for Bangladesh, Fiji, Kazakhstan, Lao People’s Democratic Republic, Pakistan, Sri Lanka and Uzbekistan, which have been prepared using international, rather than national, data sources