The central question of this special feature is about the decision science needed to address sustainability issues and how it differs from existing decision science. Many decision scientists believe that sustainability is just a label for long-standing research questions, but others argue that a major change is beginning in the science of human use and environmental impacts. The focus on panaceas is a hook for exploring these arguments. Sustainability science is problem-driven and involves understanding the dynamics of coupled social-ecological systems (SESs). It is inconsistent with approaches that are insufficiently specific, such as economists' focus on market solutions for common-pool resources. However, there are cases where market solutions are less helpful, especially when multiple sources of failure exist or when local processes are driven by remote conditions. Progress has been made in developing models and methods to address sustainability problems in coupled SESs. Initiatives like the International Society for Ecological Economics and the Resilience Alliance have helped integrate disciplines, leading to more flexible and adaptive solutions. Globalization trends, including the integration of the global SES, complexity of the system, and growing uncertainty, test particular solutions to sustainability problems. The closer integration of the global SES has social and biophysical dimensions, exemplified by world trade and species dispersion. Problematic solutions often ignore important dimensions of the problem, such as the structure of livestock markets or the incentives of control mechanisms. Many solutions are confounded by the scale at which the problem is evaluated, addressing short-term localized symptoms rather than long-term dispersed drivers of change. There is scope for developing a science of sustainability that integrates both. For example, connecting insights from ecology on species dispersal with insights from economics on world trade can help address the dynamics of coupled systems. The concept of bounded rationality in economics reflects the empirical observation that decision-makers often use simple heuristics when the costs of acquiring complete information are high. In the present state of understanding of coupled SESs, there is fundamental uncertainty about both the structure of the system and the measures of its performance. Bayesian model averaging provides a mechanism for selecting between models with different structural characteristics. The Millennium Ecosystem Assessment concluded that we are next to helpless to predict the consequences of alternative strategies for managing changes in biodiversity. Mitigation and adaptation have fundamentally different implications for the distribution of benefits and science. Mitigation generally implies action now to protect the interests of future generations, while adaptation provides benefits to those who adapt. The principal challenge in building a science of sustainability is the development of predictive models of system change that enable society to evaluate mitigation options alongside adaptation. Building sustainability science is about building capacity, methods, and protocols to analyze problems stemming from the dynamics of complex coupled SESs. One part of that task is figuring out how to break existing disciplinary biases about concepts, methods, and analysis. A second is to induce reappraisal of the rules of thumb that structure both research and decision making. Ostrom and colleagues have already done much to address the first, and they are on theirThe central question of this special feature is about the decision science needed to address sustainability issues and how it differs from existing decision science. Many decision scientists believe that sustainability is just a label for long-standing research questions, but others argue that a major change is beginning in the science of human use and environmental impacts. The focus on panaceas is a hook for exploring these arguments. Sustainability science is problem-driven and involves understanding the dynamics of coupled social-ecological systems (SESs). It is inconsistent with approaches that are insufficiently specific, such as economists' focus on market solutions for common-pool resources. However, there are cases where market solutions are less helpful, especially when multiple sources of failure exist or when local processes are driven by remote conditions. Progress has been made in developing models and methods to address sustainability problems in coupled SESs. Initiatives like the International Society for Ecological Economics and the Resilience Alliance have helped integrate disciplines, leading to more flexible and adaptive solutions. Globalization trends, including the integration of the global SES, complexity of the system, and growing uncertainty, test particular solutions to sustainability problems. The closer integration of the global SES has social and biophysical dimensions, exemplified by world trade and species dispersion. Problematic solutions often ignore important dimensions of the problem, such as the structure of livestock markets or the incentives of control mechanisms. Many solutions are confounded by the scale at which the problem is evaluated, addressing short-term localized symptoms rather than long-term dispersed drivers of change. There is scope for developing a science of sustainability that integrates both. For example, connecting insights from ecology on species dispersal with insights from economics on world trade can help address the dynamics of coupled systems. The concept of bounded rationality in economics reflects the empirical observation that decision-makers often use simple heuristics when the costs of acquiring complete information are high. In the present state of understanding of coupled SESs, there is fundamental uncertainty about both the structure of the system and the measures of its performance. Bayesian model averaging provides a mechanism for selecting between models with different structural characteristics. The Millennium Ecosystem Assessment concluded that we are next to helpless to predict the consequences of alternative strategies for managing changes in biodiversity. Mitigation and adaptation have fundamentally different implications for the distribution of benefits and science. Mitigation generally implies action now to protect the interests of future generations, while adaptation provides benefits to those who adapt. The principal challenge in building a science of sustainability is the development of predictive models of system change that enable society to evaluate mitigation options alongside adaptation. Building sustainability science is about building capacity, methods, and protocols to analyze problems stemming from the dynamics of complex coupled SESs. One part of that task is figuring out how to break existing disciplinary biases about concepts, methods, and analysis. A second is to induce reappraisal of the rules of thumb that structure both research and decision making. Ostrom and colleagues have already done much to address the first, and they are on their