Carrots and Sticks in Private Climate Governance

When public governance fails to address important environmental threats— such as climate change—private governance by firms, not-for-profits, individuals, and households can produce significant reductions in greenhouse gas emissions. Private governance can take the form of either a carrot or a stick, using incentives or punishments. Shareholder activism as a form of private governance of corporations has largely been confrontational, leading most climate-related actions to fail. This Article examines the potential for private governance to take a more collaborative approach and to frame shareholder engagement with management in terms of opportunity. It also examines private governance successes at reducing household emissions and finds that these too emphasize making it attractive and convenient for households to act

Agricultural adaptation to drought in the Sri Lankan dry zone

Droughts affect more people than any other natural disaster. Drought severity is not merely a function of precipitation; it emerges from a web of interrelations between human and natural systems. The impacts of drought are equally complex, shifting across temporal scales, economic sectors, and regions. Even in regions with similar hydroclimatic characteristics, there is tremendous variation in the effects of drought. This study combines satellite imagery, geospatial data, and qualitative data to identify the multi-scalar factors that drive variations in agricultural responses to drought. We analyzed eleven years of remotely sensed imagery to identify agricultural areas in which cultivation occurred during an extreme drought in Sri Lanka. We visited a subset of these communities and conducted interviews with officials and farmers to identify the factors that influenced agricultural adaptation. Results suggest that though structural factors such as infrastructural capacity and physical environment significantly affect agricultural adaptation, dynamic factors such as local control of water supply, perceived risk, community cohesion, and farmer experience explain significant variation in the adaptive capacity of agricultural systems

Betting and Belief: Prediction Markets and Attribution of Climate Change

Despite much scientific evidence, a large fraction of the American public doubts that greenhouse gases are causing global warming. We present a simulation model as a computational test-bed for climate prediction markets. Traders adapt their beliefs about future temperatures based on the profits of other traders in their social network. We simulate two alternative climate futures, in which global temperatures are primarily driven either by carbon dioxide or by solar irradiance. These represent, respectively, the scientific consensus and a hypothesis advanced by prominent skeptics. We conduct sensitivity analyses to determine how a variety of factors describing both the market and the physical climate may affect traders' beliefs about the cause of global climate change. Market participation causes most traders to converge quickly toward believing the "true" climate model, suggesting that a climate market could be useful for building public consensus.Comment: All code and data for the model is available at http://johnjnay.com/predMarket/. Forthcoming in Proceedings of the 2016 Winter Simulation Conference. IEEE Pres

Applications of percolation theory to fungal spread with synergy

There is increasing interest in the use of the percolation paradigm to analyze and predict the progress of disease spreading in spatially-structured populations of animals and plants. The wider utility of the approach has been limited, however, by several restrictive assumptions, foremost of which is a strict requirement for simple nearest-neighbour transmission, in which the disease history of an individual is in uenced only by that of its neighbours. In a recent paper the percolation paradigm has been generalised to incorporate synergistic interactions in host infectivity and susceptibility and the impact of these interactions on the invasive dynamics of an epidemic has been demonstrated. In the current paper we elicit evidence that such synergistic interactions may underlie transmission dynamics in real-world systems by rst formulating a model for the spread of a ubiquitous parasitic and saprotrophic fungus through replicated populations of nutrient sites and subsequently tting and testing the model using data from experimental microcosms. Using Bayesian computational methods for model tting, we demonstrate that synergistic interactions are necessary to explain the dynamics observed in the replicate experiments. The broader implications of this work in identifying disease control strategies that de ect epidemics from invasive to non-invasive regimes are discussed

Macro-Risks: The Challenge for Rational Risk Regulation

Drawing on the recent financial crisis, we introduce the concept of macro-risk. We distinguish between micro-risks, which can be managed within conventional economic frameworks, and macro-risks, which threaten to disrupt economic systems so much that a different approach is required. We argue that catastrophic climate change is a prime example of a macro-risk. Research by climate scientists suggests disturbingly high likelihoods of temperature increases and sea level rises that could cause the kinds of systemic failures that almost occurred with the financial system. We suggest that macro-risks should be the principal concern of rational risk assessment and management, but they are not. The principal analytical tool, cost-benefit analysis using expected values, is far less valuable for addressing macro-risks than micro-risks because it fails to adequately treat tail-risks that are capable of disrupting the entire economy. We note the difficulty of assessing and responding to macro-risks such as catastrophic climate change, and we offer several proposals for improving macro-risk assessment methods and the information available to policy makers

Topic Modeling the President: Conventional and Computational Methods

Legal and policy scholars modeling direct actions into substantive topic classifications thus far have not employed computational methods. To compare the results of their conventional modeling methods with the computational method, we generated computational topic models of all direct actions over time periods other scholars have studied using conventional methods, and did the same for a case study of environmental-policy direct actions. Our computational model of all direct actions closely matched one of the two comprehensive empirical models developed using conventional methods. By contrast, our environmental-case-study model differed markedly from the only empirical topic model of environmental-policy direct actions using conventional methods, revealing that the conventional methods model included trivial categories and omitted important alternative topics. Provided a sufficiently large corpus of documents is used, our findings support the assessment that computational topic modeling can reveal important insights for legal scholars in designing and validating their topic models of legal text. To be sure, computational topic modeling used alone has its limitations, some of which are evident in our models, but when used along with conventional methods, it opens doors towards reaching more confident conclusions about how to conceptualize topics in law. Drawing from these results, we offer several use cases for computational topic modeling in legal research. At the front end, researchers can use the method to generate better and more complete topic-model hypotheses. At the back end, the method can effectively be used, as we did, to validate existing topic models. And at a meta-scale, the method opens windows to test and challenge conventional legal theory. Legal scholars can do all of these without the machines, but there is good reason to believe we can do it better with them in the toolkit

Beyond Wickedness: Managing Complex Systems and Climate Change

This Article examines the argument that climate change is a super wicked problem. It concludes that the wicked problem concept is best viewed as a rhetorical device that served a valuable function in arguing against technocratic hubris in the early 1970s but is unhelpful and possibly counterproductive as a tool for modern climate policy analysis. Richard Lazarus improved on this analysis by emphasizing the urgency of a climate response in his characterization of the climate problem as super wicked. We suggest another approach based on Charles Lindblom\u27s science of muddling through. The muddling through approach supports the rhetorical points for which the original wicked problem concept was introduced and provides greater practical guidance for developing new laws and policies to address climate change and other complex and messy environmental problems

Beyond Gridlock

Private climate governance can achieve major greenhouse gas (“GHG”) emissions reductions while governments are in gridlock. Despite the optimism that emerged from the Earth Summit in Rio de Janeiro, Brazil in 1992, almost a quarter century later the federal legislative process and international climate negotiations are years from a comprehensive response. Yet Microsoft, Google and many other companies have committed to become carbon neutral. Wal-Mart has partnered with the Environmental Defense Fund to secure 20 million tons of GHG emissions reductions from its suppliers around the world, an amount equal to almost half the emissions from the US iron and steel industry. Investors holding roughly $90 trillion in assets have pressured large corporations to disclose and reduce their carbon footprints, and participating companies report having reduced emissions by an amount equal to a major emitting nation. Private forest certification programs have taken steps to reduce the GHG emissions from deforestation. Household carbon regulation is off the table in many countries, but private advocacy groups and corporations have reduced household emissions through home energy disclosure, eco-driving campaigns, employee programs, voluntary carbon offsets, and other initiatives. To explain the importance of private climate governance, this Article is structured around three propositions. The first is the need for urgency... The second proposition is that the barriers to adopting and implementing a carbon price are unlikely to be overcome in the next decade... The third proposition is that unlocking the potential of private governance will require a conceptual shift by scholars, philanthropists, and corporate and NGO managers... Private initiatives cannot keep global emissions on track to achieve the most widely adopted climate target, but they can achieve a private governance wedge: they can reduce emissions by roughly 1,000 million tons (a gigaton) of CO2 per year between 2016 and 2025. When combined with other efforts, this private governance wedge offers a reasonable chance of buying a decade to resolve the current government gridlock

Essay: Forks In the Road

This Essay outlines a simple heuristic that will enable public and private policymakers to focus on the most important climate change mitigation strategies. Policymakers face a dizzying array of information, pressure from advocacy groups, and policy options, and it is easy to lose sight of the forest for the trees. Many policy options are attractive on the surface but either fail to meaningfully address the problem or are unlikely to be adopted in the foreseeable future. If policymakers make the right decision when confronting three essential choices or forks in the road, though, the result will be 60% to 70% reductions in greenhouse gas emissions, an amount that will keep widely-adopted climate mitigation goals in reach. The three options are decarbonization of the electrical grid, electrification of the motor vehicle fleet, and electrification of buildings. International, national, and subnational officials, philanthropists, corporate executives, advocacy group leaders, and households all have the ability to prioritize these three options in their regulatory, purchasing, and other actions. If they choose these three decarbonatization options, many other mistakes can be made without jeopardizing the achievement of widely adopted emissions targets. If they make the wrong choice, however, few combinations of other viable options can achieve the necessary reductions. In the face of a growing consensus that immediate, major emissions reductions are required, the forks in the road heuristic can provide policymakers with the framework necessary to make smart decisions and ignore the noise surrounding climate law and policy

Application of machine learning to prediction of vegetation health

This project applies machine learning techniques to remotely sensed imagery to train and validate predictive models of vegetation health in Bangladesh and Sri Lanka. For both locations, we downloaded and processed eleven years of imagery from multiple MODIS datasets which were combined and transformed into two-dimensional matrices. We applied a gradient boosted machines model to the lagged dataset values to forecast future values of the Enhanced Vegetation Index (EVI). The predictive power of raw spectral data MODIS products were compared across time periods and land use categories. Our models have significantly more predictive power on held-out datasets than a baseline. Though the tool was built to increase capacity to monitor vegetation health in data scarce regions like South Asia, users may include ancillary spatiotemporal datasets relevant to their region of interest to increase predictive power and to facilitate interpretation of model results. The tool can automatically update predictions as new MODIS data is made available by NASA. The tool is particularly well-suited for decision makers interested in understanding and predicting vegetation health dynamics in countries in which environmental data is scarce and cloud cover is a significant concern