• Energy Research
• 13. Climate action close
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Understanding the relationship between climate and crop productivity is a key component of projections of future food production, and hence assessments of food security. Climate models and crop yield datasets have errors, but the effects of these errors on regional scale crop models is not well categorized and understood. In this study we compare the effect of synthetic errors in temperature and precipitation observations on the hindcast skill of a process-based crop model and a statistical crop model. We find that errors in temperature data have a significantly stronger influence on both models than errors in precipitation. We also identify key differences in the responses of these models to different types of input data error. Statistical and process-based model responses differ depending on whether synthetic errors are overestimates or underestimates. We also investigate the impact of crop yield calibration data on model skill for both models, using datasets of yield at three different spatial scales. Whilst important for both models, the statistical model is more strongly influenced by crop yield scale than the process-based crop model. However, our results question the value of high resolution yield data for improving the skill of crop models; we find a focus on accuracy to be more likely to be valuable. For both crop models, and for all three spatial scales of yield calibration data, we found that model skill is greatest where growing area is above 10-15 %. Thus information on area harvested would appear to be a priority for data collection efforts. These results are important for three reasons. First, understanding how different crop models rely on different characteristics of temperature, precipitation and crop yield data allows us to match the model type to the available data. Second, we can prioritize where improvements in climate and crop yield data should be directed. Third, as better climate and crop yield data becomes available, we can predict how crop model skill should improve.

AbstractMultinational conservation initiatives that prioritize investment across a region invariably navigate trade-offs among multiple objectives. It seems logical to focus where several objectives can be achieved efficiently, but such multi-objective hotspots may be ecologically inappropriate, or politically inequitable. Here we devise a framework to facilitate a regionally cohesive set of marine-protected areas driven by national preferences and supported by quantitative conservation prioritization analyses, and illustrate it using the Coral Triangle Initiative. We identify areas important for achieving six objectives to address ecosystem representation, threatened fauna, connectivity and climate change. We expose trade-offs between areas that contribute substantially to several objectives and those meeting one or two objectives extremely well. Hence there are two strategies to guide countries choosing to implement regional goals nationally: multi-objective hotspots and complementary sets of single-objective priorities. This novel framework is applicable to any multilateral or global initiative seeking to apply quantitative information in decision making.

Much of the debate on sustainability is predicated on the belief that environmental demands lead to the production of sustainable technologies that induce environmental benefits. This fails to account for the influential ways technologies are used in practice, and the interactions between users and technologies that shape their environmental effects. This article uses the example of how cars and their drivers together accomplish the practice of driving through their interactions with each other, and explores the implications this has for generating environmental outcomes. We draw on a body of literature that argues how together, users and technologies participate in carrying out practices that actively shape outcomes, and we show how and why this applies to sustainability. The article presents the case of the Toyota Prius, analyzing Toyota’s intent in designing a sustainable car and contrasting it with the perspectives of thirty-eight of its drivers. We find that the possibility for fuel and carbon reduction is coproduced and is a result of complex interactions between technology, drivers, and driving practice.

Due to the ability to produce sustainably carbon-based chemicals and fuels, CO2 electrolysis and the closely related CO electrolysis are advancing rapidly from fundamental studies toward industrial applications.

Tanzania's dairy sector is poorly developed, creating reliance on imports for processed, value-added dairy products and threatening food security, particularly when supply chains are disrupted due to market volatility or armed conflicts. The Tanzanian Dairy Development Roadmap is a domestic development initiative that aims to achieve dairy self-sufficiency by 2030. Here, we model different outcomes of the roadmap, finding that adoption of high-yield cattle breeds is essential for reducing dairy import dependency. Avoided land use change resulting from fewer, higher yielding dairy cattle would lead to lower greenhouse gas emissions. Dairy producers' average incomes could increase despite capital expenditure and land allocation required for the adoption of high-yield breeds. Our findings demonstrate the importance of bottom-up development policies for sustainable food system transformations, which also support food sovereignty, increase incomes for smallholder farmers and contribute towards Tanzania's commitments to reduce greenhouse gas emissions.

An integrated understanding of both social and ecological aspects of environmental issues is essential to address pressing sustainability challenges. An integrated social-ecological systems perspective is purported to provide a better understanding of the complex relationships between humans and nature. Despite a threefold increase in the amount of social-ecological research published between 2010 and 2015, it is unclear whether these approaches have been truly integrative. We conducted a systematic literature review to investigate the conceptual, methodological, disciplinary, and functional aspects of social-ecological integration. In general, we found that overall integration is still lacking in social-ecological research. Some social variables deemed important for addressing sustainability challenges are underrepresented in social-ecological studies, e.g., culture, politics, and power. Disciplines such as ecology, urban studies, and geography are better integrated than others, e.g., sociology, biology, and public administration. In addition to ecology and urban studies, biodiversity conservation plays a key brokerage role in integrating other disciplines into social-ecological research. Studies founded on systems theory have the highest rates of integration. Highly integrative studies combine different types of tools, involve stakeholders at appropriate stages, and tend to deliver practical recommendations. Better social-ecological integration must underpin sustainability science. To achieve this potential, future social-ecological research will require greater attention to the following: the interdisciplinary composition of project teams, strategic stakeholder involvement, application of multiple tools, incorporation of both social and ecological variables, consideration of bidirectional relationships between variables, and identification of implications and articulation of clear policy recommendations.

PurposeValue chain analysis (VCA) can expose strategic and operational misalignments within chains, and the consequential misallocation of resources, and hence opportunities for improvements which create value and economic sustainability. This paper's purpose is to argue why and how VCA needs to integrate the social and environmental aspects of sustainability in pursuit of sustainable competitive advantage.Design/methodology/approachBased on a review of existing methods and case studies, the paper proposes three dimensions of VCA, which illustrate the flaws in narrow tools, and the need to broaden the boundaries of VCA, the interpretation of “value” and relationships along the chain in order to highlight opportunities for creating sustainable value chains.FindingsTo date VCA has largely focused on economic sustainability and paid inadequate attention to social and environment consequences of firm behaviour and the (re) allocation of resources within and between firms in the chain. This risks producing recommendations which either ignore the competitive advantage offered from improving environmental management and social welfare, or have such detrimental external consequences as to render any proposals unsustainable when exposed to government or broader (public) scrutiny.Research limitations/implicationsVCA variants need to be developed which incorporate all three pillars of sustainability. Some initial experiences are presented and ideas for future research and applications proposed.Practical implicationsThe development of sustainable VCA tools should identify business opportunities consistent with Porter and Kramer's imperative for value chains to create shared value between business and society.Originality/valueAdopting the broader dimensions identified will allow VCA to become more widely applicable, and more relevant in business scenarios where there is a growing imperative to include social and environmental impacts into “mainstream” business strategies.