In 2013, the community of mathematical scientists and educators focused its collective attention on the mathematics of planet Earth. In the course of the year, a grassroots organization grew into an international partnership of more than 150 scientific societies, universities, research institutes, and organizations. The project, known as “Mathematics of Planet Earth 2013” (MPE2013), received the patronage of UNESCO and was a truly unique event. It brought the challenges facing our planet to the attention of the mathematics research community in numerous lectures, seminars, workshops, and special sessions at conferences of the professional societies; it sponsored the development of curriculum materials for all educational levels; it organized many outreach activities, including an international juried exhibit of virtual and physical displays for use in museums and schools; and it presented a series of public lectures by renowned scientists showing the public how mathematics contributes to our understanding of planet Earth, the nature of the challenges our planet is facing, and how mathematicians contribute to their solution. At the end of the year, MPE2013 morphed into “Mathematics of Planet Earth” (MPE).

Urban environmental measurements and observational statistics should reflect the properties generated over an adjacent area of adequate length where homogeneity is usually assumed. The determination of this characteristic source area that gives sufficient representation of the horizontal coverage of a sensing instrument or the fetch of transported quantities is of critical importance to guide the design and implementation of urban landscape planning strategies. In this study, we aim to unify two different methods for estimating source areas, viz. the statistical correlation method commonly used by geographers for landscape fragmentation and the mechanistic footprint model by meteorologists for atmospheric measurements. Good agreement was found in the intercomparison of the estimate of source areas by the two methods, based on 2-m air temperature measurement collected using a network of weather stations. The results can be extended to shed new lights on urban planning strategies, such as the use of urban vegetation for heat mitigation. In general, a sizable patch of landscape is required in order to play an effective role in regulating the local environment, proportional to the height at which stakeholders’ interest is mainly concerned.

The exploration of environmentally friendly energy resources is one of the major challenges facing society today. The last decade has witnessed rapid developments in renewable energy engineering. Wind and solar power plants with increasing sizes and technological sophistication have been built. Amid this development, meteorological modeling plays an increasingly important role, not only in selecting the sites of wind and solar power plants but also in assessing the environmental impacts of those plants. The permanent land-use changes as a result of the construction of wind farms can potentially alter local climate (Keith et al. [1], Roy and Traiteur [2]). The reduction of wind speed by the presence of wind turbines could affect the preconstruction estimate of wind power potential (e.g., Adams and Keith [3]). Future anthropogenic greenhouse gas emissions are expected to induce changes in the surface wind and cloudiness, which would affect the power production of wind and solar power plants. To quantify these two-way relations between renewable energy production and regional climate change, mesoscale meteorological modeling remains one of the most efficient approaches for research and applications.

Climate change and its interactions with complex socioeconomic dynamics dictate the need for decision makers to move from incremental adaptation toward transformation as societies try to cope with unprecedented and uncertain change. Developing pathways toward transformation is especially difficult in regions with multiple contested resource uses and rights, with diverse decision makers and rules, and where high uncertainty is generated by differences in stakeholders’ values, understanding of climate change, and ways of adapting. Such a region is the Murray-Darling Basin, Australia, from which we provide insights for developing a process to address these constraints. We present criteria for sequencing actions along adaptation pathways: feasibility of the action within the current decision context, its facilitation of other actions, its role in averting exceedance of a critical threshold, its robustness and resilience under diverse and unexpected shocks, its effect on future options, its lead time, and its effects on equity and social cohesion. These criteria could potentially enable development of multiple stakeholder-specific adaptation pathways through a regional collective action process. The actual implementation of these multiple adaptation pathways will be highly uncertain and politically difficult because of fixity of resource-use rights, unequal distribution of power, value conflicts, and the likely redistribution of benefits and costs. We propose that the approach we outline for building resilient pathways to transformation is a flexible and credible way of negotiating these challenges.

Globalization, the process by which local social-ecological systems (SESs) are becoming linked in a global network, presents policy scientists and practitioners with unique and difficult challenges. Although local SESs can be extremely complex, when they become more tightly linked in the global system, complexity increases very rapidly as multi-scale and multi-level processes become more important. Here, we argue that addressing these multi-scale and multi-level challenges requires a collection of theories and models. We suggest that the conceptual domains of sustainability, resilience, and robustness provide a sufficiently rich collection of theories and models, but overlapping definitions and confusion about how these conceptual domains articulate with one another reduces their utility. We attempt to eliminate this confusion and illustrate how sustainability, resilience, and robustness can be used in tandem to address the multi-scale and multi-level challenges associated with global change.

We quantified the spatio-temporal patterns of land cover/land use (LCLU) change to document and evaluate the daytime surface urban heat island (SUHI) for five hot subtropical desert cities (Beer Sheva, Israel; Hotan, China; Jodhpur, India; Kharga, Egypt; and Las Vegas, NV, USA). Sequential Landsat images were acquired and classified into the USGS 24-category Land Use Categories using object-based image analysis with an overall accuracy of 80% to 95.5%. We estimated the land surface temperature (LST) of all available Landsat data from June to August for years 1990, 2000, and 2010 and computed the urban-rural difference in the average LST and Normalized Difference Vegetation Index (NDVI) for each city. Leveraging non-parametric statistical analysis, we also investigated the impacts of city size and population on the urban-rural difference in the summer daytime LST and NDVI. Urban expansion is observed for all five cities, but the urbanization pattern varies widely from city to city. A negative SUHI effect or an oasis effect exists for all the cities across all three years, and the amplitude of the oasis effect tends to increase as the urban-rural NDVI difference increases. A strong oasis effect is observed for Hotan and Kharga with evidently larger NDVI difference than the other cities. Larger cities tend to have a weaker cooling effect while a negative association is identified between NDVI difference and population. Understanding the daytime oasis effect of desert cities is vital for sustainable urban planning and the design of adaptive management, providing valuable guidelines to foster smart desert cities in an era of climate variability, uncertainty, and change.

Social roles are thought to play an important role in determining the capacity for collective action in a community regarding the use of shared resources. Here we report on the results of a study using a behavioral experimental approach regarding the relationship between social roles and the performance of social-ecological systems. The computer-based irrigation experiment that was the basis of this study mimics the decisions faced by farmers in small-scale irrigation systems. In each of 20 rounds, which are analogous to growing seasons, participants face a two-stage commons dilemma. First they must decide how much to invest in the public infrastructure, e.g., canals and water diversion structures. Second, they must decide how much to extract from the water made available by that public infrastructure. Each round begins with a 60-second communication period before the players make their investment and extraction decisions. By analyzing the chat messages exchanged among participants during the communication stage of the experiment, we coded up to three roles per participant using the scheme of seven roles known to be important in the literature: leader, knowledge generator, connector, follower, moralist, enforcer, and observer. Our study supports the importance of certain social roles (e.g., connector) previously highlighted by several case study analyses. However, using qualitative comparative analysis we found that none of the individual roles was sufficient for groups to succeed, i.e., to reach a certain level of group production. Instead, we found that a combination of at least five roles was necessary for success. In addition, in the context of upstream-downstream asymmetry, we observed a pattern in which social roles assumed by participants tended to differ by their positions. Although our work generated some interesting insights, further research is needed to determine how robust our findings are to different action situations, such as biophysical context, social network, and resource uncertainty.

Large-N comparative studies have helped common pool resource scholars gain general insights into the factors that influence collective action and governance outcomes. However, these studies are often limited by missing data, and suffer from the methodological limitation that important information is lost when we reduce textual information to quantitative data. This study was motivated by nine case studies that appeared to be inconsistent with the expectation that the presence of Ostrom’s Design Principles increases the likelihood of successful common pool resource governance. These cases highlight the limitations of coding and analyzing Large-N case studies.

We examine two issues: 1) the challenge of missing data and 2) potential approaches that rely on context (which is often lost in the coding process) to address inconsistencies between empirical observations theoretical predictions. For the latter, we conduct a post-hoc qualitative analysis of a large-N comparative study to explore 2 types of inconsistencies: 1) cases where evidence for nearly all design principles was found, but available evidence led to the assessment that the CPR system was unsuccessful and 2) cases where the CPR system was deemed successful despite finding limited or no evidence for design principles. We describe inherent challenges to large-N comparative analysis to coding complex and dynamically changing common pool resource systems for the presence or absence of design principles and the determination of “success”. Finally, we illustrate how, in some cases, our qualitative analysis revealed that the identity of absent design principles explained inconsistencies hence de-facto reconciling such apparent inconsistencies with theoretical predictions. This analysis demonstrates the value of combining quantitative and qualitative analysis, and using mixed-methods approaches iteratively to build comprehensive methodological and theoretical approaches to understanding common pool resource governance in a dynamically changing context.

Institutions, the rules of the game that shape repeated human interactions, clearly play a critical role in helping groups avoid the inefficient use of shared resources such as fisheries, freshwater, and the assimilative capacity of the environment. Institutions, however, are intimately intertwined with the human, social, and biophysical context within which they operate. Scholars typically are careful to take this context into account when studying institutions and Ostrom’s Institutional Design Principles are a case in point. Scholars have tested whether Ostrom’s Design Principles, which specify broad relationships between institutional arrangements and context, actually support successful governance of shared resources. This article further contributes to this line of research by leveraging the notion of institutional design to outline a research trajectory focused on coupled infrastructure systems in which institutions are seen as one class of infrastructure among many that dynamically interact to produce outcomes over time.

In this article we consider the current educational needs for science and policy in marine resource management, and we propose a way to address them. The existing literature on cross-disciplinary education in response to pressing environmental problems is vast, particularly in conservation biology. However, actual changes in doctoral-level marine science programs lag behind this literature considerably. This is in part because of concerns about the time investment in cross-disciplinary education and about the job prospects offered by such programs. There is also a more fundamental divide between educational programs that focus on knowledge generation and those that focus on professional development, which can reinforce the gap in communication between scientists and marine resource managers. Ultimately, transdisciplinary graduate education programs need not only to bridge the divide between disciplines, but also between types of knowledge. Our proposed curriculum aligns well with these needs because it does not sacrifice depth for breadth, and it emphasizes collaboration and communication among diverse groups of students, in addition to development of their individual knowledge and skills.