Charles Perrings - US grants

Many societies have endured for long periods, successfully coping with uncertainty, disturbance, and change in the environment. Many other societies have failed in this regard. The core question addressed in this interdisciplinary research project is why some social-ecological systems are more successful in dealing with disturbances and change in the environment than others. The investigators, who come from a broad range of composed of social, physical, and engineering science fields, hypothesize that an important factor bearing on this question is a well-known phenomenon in engineering: a system cannot be robust to all classes of disturbances. Thus, in developing mechanisms to address an existing suite of uncertainties and environmental risks (becoming robust to a particular class of disturbances), society necessarily becomes vulnerable to other classes of disturbances. Through the application of several complementary quantitative techniques to a suite of mathematical models based on a large set of case studies, the research team will explore such robustness-fragility trade-offs in a range of simple irrigation societies. The research team will employ methods and insights from applied mathematics, electrical engineering (control), resource economics, archaeology, and ecology to develop an integrated approach to study how societies deal with uncertainty, disturbance, and change. The products from the project will be (1) an empirical database and a suite of formal mathematical models relating to the basic biophysical, social, and institutional characteristics of several irrigation societies, (2) a deeper understanding of how societies may become fragile as they attempt to cope with uncertainty and change in the environment, and (3) new tools for resource managers: a set of design principles for robust institutions that perform well in the face of both social and environmental disturbances.

This project will yield fundamental new knowledge concerning the interaction between human social dynamics and environmental change. It also will improve resource management practice and to enhance mathematical education. By bringing together techniques from a range of disciplines, the investigators will develop new tools for the study of social-ecological systems that are able to cope with more complexity than traditional approaches. The research results have the potential to improve resource management practices by providing tools to help predict when alternative responses to disturbance and environmental change will succeed and how they will most likely fail. Research findings will be translated into practice through the efforts of the Resilience Alliance, an international organization that produces research, educational materials, and practical tools for resource managers. The research project will contribute to ongoing activities at Arizona State University designed to enhance mathematical literacy in the life and social sciences by engaging both graduate and undergraduate students in a problem-focused, interdisciplinary research program involving mathematics, economics, engineering, ecology, and archeology. An award resulting from the FY 2005 NSF-wide competition on Human and Social Dynamics (HSD) supports this project. All NSF directorates and offices are involved in the coordinated management of the HSD competition and the portfolio of HSD awards.

The Millennium Ecosystem Assessment argued that biodiversity loss matters because it compromises the 'ecosystem services' on which human life depends at many different scales. The international biodiversity research program, Diversitas, explores the science behind the linkages between biodiversity, ecosystem services, and human well-being. BESTNet will bring the insights from this work to young researchers in the US through two research-training activities. First, research training workshops will address topics under discussion in Diversitas, including the valuation of ecosystem services, health and biodiversity loss, biodiversity information and community-based use of natural resources, and biodiversity in agricultural landscapes. Second, doctoral students will be funded to spend time in the labs of participating scientists in the US and abroad.

BESTNet will also make a wider contribution to the development of sustainability science and policy. It will (a) develop an interdisciplinary community committed to policy-relevant research into the links between biodiversity change and human activities; (b) enhance the capacity to undertake interdisciplinary research within existing life and social science departments in US universities; (c) synthesize research results on the local consequences of international biodiversity change; and (d) disseminate these results to decision-makers. In addition, it is expected that the network will substantially strengthen US scientific input into the global-change programs and other international initiatives.

PI name: John C. Crittenden
Institution: Arizona State University
Proposal Number: 0836046
EFRI-RESIN: Sustainable Infrastructures for Energy and Water Supply (SINEWS)

The goal of this project is to develop a comprehensive understanding of the sustainability and resilience of the water and energy systems, and to offer solutions that span infrastructure design, management of the physical environment, and socio-economic policy. SINEWS has four major research elements: (1) THE PHYSICAL ENVIRONMENT. The project will model the growth of urban (built and natural) environment and the associated endogenous infrastructure risks. The technological, engineering, and ecological options for mitigating these risks over the life of the infrastructures will be identified. (2) THE INFRASTRUCTURES. The project will examine and model the resilience and sustainability of water and energy supply system options. Benchmarks will be identified for power and water supply systems that are resilient to the expected range of shocks, that are flexible, modular, adaptive, and efficient, and that reflect the interdependency of infrastructures and their environment. (3) THE SOCIO-ECONOMIC ENVIRONMENT. The project will model the infrastructure risks associated with the socio-economic environment - the demographic, economic, institutional and social drivers of water and energy demand, and identify risk management options under different socio-economic conditions. (4) LIFE CYCLE IMPLICATIONS of infrastructure options, e.g., decentralized versus centralized power and water systems. Overall, the proposed research represents a new systems approach to engineering the resilience and sustainability of critical infrastructures in the context of their physical and socio-economic environments. Simulations for integrated regional-scale models for Greater Phoenix will generate insights into the resilience and sustainability of water and energy infrastructures under a range of environmental scenarios. These insights are expected to contribute to a national research agenda for integrated urban sustainability science and engineering.

DESCRIPTION (provided by applicant): Globalization has increased the likelihood that susceptible and infected individuals of many species will be brought into contact, so increasing the disease risks for humans and animals alike. For human diseases, contact depends on choices that people make that bring susceptible and infected individuals together. For domesticated and wild animals, contact depends on the transactions people make that bring susceptible animals into contact with infectious agents. The spread of emerging infectious zoonotic diseases, depends on both things. While epidemiologists recognize the importance of human behavior in the spread of diseases they do not model the decision processes involved. Embedding these decision processes in the contact function in compartmental epidemiological models is expected to enhance their capacity to predict the introduction and spread of infectious diseases, and to provide an opportunity to evaluate incentive based disease management policies (Fenichel et al, 2011). The research will incorporate the economic drivers of 'contact'into dynamic models of emerging human and animal infectious disease systems, and analyze the system dynamics with and without adaptive responses. The models will be calibrated for a set of diseases where people's trade and travel decisions are potentially important (initially H1N1, H5N1,FMD). The aim is to strengthen the power of compartmental epidemiological models (a) to predict the likelihood that diseases of particular types will be introduced and the course of diseases once introduced, and (b) to evaluate the potential for incentive-based policy responses to disease threats and disease outbreaks. The research team has been built over a number of years through collaboration in three networks: an RCN - BESTNet;the international biodiversity science program DIVERSITAS;and a NIMBIOS working group - SPIDER. It comprises mathematical epidemiologists (Castillo-Chavez and Chowell at ASU), ecologists (Daszak, EcoHEALTH;Kilpatrick, UCSC;Smith, Brown;Kinzig, ASU;Levin, Princeton) and resource economists (Perrings, Kuminoff and Fenichel at ASU;Horan, MSU;Springborn, UCD and Finnoff, UW). PUBLIC HEALTH RELEVANCE: We expect the research to benefit regulatory bodies responsible for disease risk assessment and management (e.g. NIH;NCID, CDC and the Communicable Diseases Working Group on Emergencies (CD-WGE) at WHO and the OIE). The models will provide 'test-beds'for the evaluation of alternative incentive-based disease management tools of potential value in managing outbreaks and controlling introduction risks.

World trade is a boon to economic development but it also increases the risk of dispersing human, animal, and plant diseases. Disease impacts on crop yields and livestock put global food supplies at risk and newly emergent diseases that move from animals to humans can threaten human health. But because trade is also one of the main drivers of economic development, it is important that it not be disrupted unnecessarily by measures to protect against disease risk. Striking the right balance is currently difficult to achieve, however, because trade impacts are not systematically incorporated into national and international disease risk assessments. This award supports an interdisciplinary and international team who seek to solve that problem by developing new tools for evaluating the disease risks of world trade. The risk assessment tools produced by the project will provide animal, plant, and human health authorities at national and international levels with the capacity to make improved assessment of the disease risks associated with imports, and of the consequences of alternative trade responses. Improving disease risk management will enhance national security and economic well-being by reducing both disease dispersal and the losses caused by trade interdictions. The project also will strengthen collaborations between US and UK scientists and train graduate students and post-doctoral scientists in research.

The researchers will compile data from multiple secondary sources. Data on plant diseases, livestock and wildlife diseases, disease outbreaks, and global emerging diseases, will be provided by such sources as the National Plant Protection Organizations in the United States and the United Kingdom, the United States Department of Agriculture's Animal and Plant Health Inspection Service, and the UK Food and Environment Research Agency. Public domain databases will provide time series data on trade, including trade volumes, trade values, sanitary and phtyosanitary conditions along trade pathways in exporting and importing countries, as well as Gross Domestic Product (GDP) data to estimate national value at risk. These data will be used to parameterize econometric profit maximization risk models to assess the effects of trader decisions and trade networks on the transmission of disease. The models will consider the intervention in trade at three spatial scales (local, national, and global) on incidence of disease transport and effects of altered trade on economic development. The models will be incorporated into a virtual laboratory decision support system to help evaluate alternative incentive-based trade management practices and the effects of decisions on the risk of disease spread.