Models and Methods in Social Network Analysis presents the most important developments in quantitative models and methods for analyzing social network data that have appeared during the 1990s. Intended as a complement to Wasserman and Faust’s Social Network Analysis: Methods and Applications, it is a collection of original articles by leading methodologists reviewing recent advances in their particular areas of network methods. Reviewed are advances in network measurement, network sampling, the analysis of centrality, positional analysis or blockmodeling, the analysis of diffusion through networks, the analysis of affiliation or “two-mode” networks, the theory of random graphs, dependence graphs, exponential families of random graphs, the analysis of longitudinal network data, graphic techniques for exploring network data, and software for the analysis of social networks.

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Models and methods in social network analysis

Research practice, funding agencies and global science organizations suggest that research aimed at addressing sustainability challenges is most effective when ‘co-produced’ by academics and non-academics. Co-production promises to address the complex nature of contemporary sustainability challenges better than more traditional scientific approaches. But definitions of knowledge co-production are diverse and often contradictory. We propose a set of four general principles that underlie high-quality knowledge co-production for sustainability research. Using these principles, we offer practical guidance on how to engage in meaningful co-productive practices, and how to evaluate their quality and success.

Principles for knowledge co-production in sustainability research

Indigenous Research Methodologies

This paper distills core lessons about how researchers (scientists, engineers, planners, etc.) interested in promoting sustainable development can increase the likelihood of producing usable knowledge. We draw the lessons from both practical experience in diverse contexts around the world and from scholarly advances in understanding the relationships between science and society. Many of these lessons will be familiar to those with experience in crafting knowledge to support action for sustainable development. However, few are included in the formal training of researchers. As a result, when scientists and engineers first venture out of the laboratory or library with the goal of linking their knowledge with action, the outcome has often been ineffectiveness and disillusionment. We therefore articulate here a core set of lessons that we believe should become part of the basic training for researchers interested in crafting usable knowledge for sustainable development. These lessons entail at least four things researchers should know, and four things they should do. The knowing lessons involve understanding the coproduction relationships through which knowledge making and decision making shape one another in social–environmental systems. We highlight the lessons that emerge from examining those coproduction relationships through the ICAP lens, viewing them from the perspectives of Innovation systems, Complex systems, Adaptive systems, and Political systems. The doing lessons involve improving the capacity of the research community to put its understanding of coproduction into practice. We highlight steps through which researchers can help build capacities for stakeholder collaboration, social learning, knowledge governance, and researcher training.

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Crafting usable knowledge for sustainable development

Two foundational questions about sustainability are "How are ecosystems and the services they provide going to change in the future?" and "How do human decisions affect these trajectories?" Answering these questions requires an ability to forecast ecological processes Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure Effective forecasting will also require changes in scientific training, culture, and institutions The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward

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Iterative near-term ecological forecasting: Needs, opportunities, and challenges

Coproduction of knowledge is believed to be an effective way to produce usable climate science knowledge through a process of collaboration between scientists and decision makers. While the general principles of coproduction—establishing long-term relationships between scientists and stakeholders, ensuring two-way communication between both groups, and keeping the focus on the production of usable science—are well understood, the mechanisms for achieving those goals have been discussed less. It is proposed here that a more deliberate approach to building the relationships and communication channels between scientists and stakeholders will yield better outcomes. The authors present five approaches to collaborative research that can be used to structure a coproduction process that each suit different types of research or management questions, decision-making contexts, and resources and skills available to contribute to the process of engagement. By using established collaborative research approaches scientists can be more effective in learning from stakeholders, can be more confident when engaging with stakeholders because there are guideposts to follow, and can assess both the process and outcomes of collaborative projects, which will help the whole community of stakeholder-engaged climate-scientists learn about coproduction of knowledge.

https://journals.ametsoc.org/doi/pdf/10.1175/WCAS-D-14-00050.1

Moving toward the Deliberate Coproduction of Climate Science Knowledge

Moving Toward the Deliberate Co-Production of Climate Science Knowledge

Continuing progress in the fields of meteorology, climatology, and fire ecology has enabled more proactive and risk-tolerant wildland fire management practices in the United States. Recent institutional changes have also facilitated the incorporation of more advanced climate and weather research into wildland fire management. One of the most significant changes was the creation of Predictive Services in 1998, a federal interagency group composed, in part, of meteorologists who create climate- and weather-based fire outlooks tailored to fire manager needs. Despite the numerous forecast products now available to fire managers, few studies have examined how these products have affected their practices. In this paper the authors assess how fire managers in the Southwest region of the United States perceive and incorporate different types of information into their management practices. A social network analysis demonstrates that meteorologists have become central figures in disseminating information in...

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Wildfire Management and Forecasting Fire Potential: The Roles of Climate Information and Social Networks in the Southwest United States

The Southwestern United States is home to 182 federally recognized tribes (Federal Register 2010, Figure 17.1). California has the largest number of tribes (109), and the largest Native American population in the country (Table 17.1). Arizona, New Mexico, Colorado, and Utah are also home to seven of the most populous tribes, with populations ranging from 10,000 to over 300,000 (U.S. Census 2010). Nine tribes in the Southwest are considered “large land-holding tribes,” five of which are among the ten largest reservations in the United States, ranging in size from 600,000 to 15 million acres (Federal Register 2010). More than one-third of the land in Arizona is tribal land.

https://www.swcarr.arizona.edu/sites/default/files/ACCSWUS_Ch17.pdf

Unique Challenges Facing Southwestern Tribes

http://udallcenter.arizona.edu/publications/sites/default/files/47_en.pdf

Daniel B. Ferguson

Papers

Moving toward the Deliberate Coproduction of Climate Science Knowledge

Moving Toward the Deliberate Co-Production of Climate Science Knowledge

Wildfire Management and Forecasting Fire Potential: The Roles of Climate Information and Social Networks in the Southwest United States

Unique Challenges Facing Southwestern Tribes

Science and socio-ecological resilience: examples from the Arizona-Sonora Border