Land use adaptation to climate change: Economic damages from land-falling hurricanes in the Atlantic and gulf States of the USA, 1900-2005

Global climate change, especially the phenomena of global warming, is expected to increase the intensity of land-falling hurricanes. Societal adaptation is needed to reduce vulnerability from increasingly intense hurricanes. This study quantifies the adaptation effects of potentially policy driven caps on housing densities and agricultural cover in coastal (and adjacent inland) areas vulnerable to hurricane damages in the Atlantic and Gulf Coastal regions of the U.S. Time series regressions, especially Prais-Winston and Autoregressive Moving Average (ARMA) models, are estimated to forecast the economic impacts of hurricanes of varying intensity, given that various patterns of land use emerge in the Atlantic and Gulf coastal states of the U.S. The Prais-Winston and ARMA models use observed time series data from 1900 to 2005 for inflation adjusted hurricane damages and socio-economic and land-use data in the coastal or inland regions where hurricanes caused those damages. The results from this study provide evidence that increases in housing density and agricultural cover cause significant rise in the de-trended inflation-adjusted damages. Further, higher intensity and frequency of land-falling hurricanes also significantly increase the economic damages. The evidence from this study implies that a medium to long term land use adaptation in the form of capping housing density and agricultural cover in the coastal (and adjacent inland) states can significantly reduce economic damages from intense hurricanes. Future studies must compare the benefits of such land use adaptation policies against the costs of development controls implied in housing density caps and agricultural land cover reductions. © 2012 by the authors

Navigating Trade-Offs in Complex Systems: Deliberative Multi Criteria Decision Analysis of CCMPO Metropolitan Transportation Plan, 2010-2035

Metropolitan Planning Organizations (MPOs) are required by Federal law to develop a long-range Metropolitan Transportation Plan (MTP) at least every five years. This research focuses on assessing the trade-offs between business-as-usual MTP scenario of gasoline driven transportation infrastructure and suburban growth with two alternate sustainable community design scenarios in Chittenden County Metropolitan Planning Area (CCMPO). The CCMPO adopted its last longrange transportation plan in 2005 for a temporal horizon of 2005 to 2025 and is currently updating 2025 MTP to 2035 MTP. We implemented two focus groups with multiple stakeholder representatives of the regional transportation planning network and conducted numerous interviews to implement a participatory multi-criteria evaluation of 2035 MTP scenarios. Three MTP scenarios are evaluated on twelve decision criteria: operational performance, sustainable land-use, safety and accessibility, minimize time and total costs, protect built and natural environs, community development, access and mobility, transportation system efficiency, energy efficiency and conservation, improve alternate travel modes, public education and cost effective and inclusiveness. Our analysis reveals that the underlying expected value functions of all stakeholder representatives in the regional transportation planning network overwhelmingly reject business-asusual MTP scenario. Instead, a more sustainable, growth contained community design scenario emerges with the highest expected value for all stakeholder groups. Formal implementation of sustainable community design scenario would, however, require CCMPO and regional transportation planning network actors to overcome a series of legal, political and economic challenges. We discuss the implications of these trade-offs, challenges and opportunities on the development and implementation of sustainable community designs

Mainstreaming Early Warning Systems in Development and Planning Processes: Multilevel Implementation of Sendai Framework in Indus and Sahel

The third UN World Congress on Disaster Risk Reduction, held in Sendai, Japan in March 2015, agreed on a new framework to guide disaster risk reduction policy and practice for the next 15 years. The Sendai Framework for Disaster Risk Reduction 2015–2030 (SFDRR) leaves important implementation issues unspecified and potentially creates both problems and opportunities for complex, multilevel governance systems in coping with hazards and disastrous events. Early warning systems (EWS), if built into the mainstream of planning for development and disaster relief and recovery, could present a significant opportunity to realize many SFDRR goals. We explore the complexities of using hydrometeorological EWS to prepare for drought and flood disasters in the densely populated communities of Pakistan’s Indus River Basin in contrast to the African Sahel’s less densely settled grasslands. Multilevel governance systems are often dominated by a top-down, technocentric, centralized management bias and have great difficulty responding to the needs of peripheral and vulnerable populations. People-centered, bottom-up approaches that incorporate disaggregated communities with local knowledge into a balanced, multilevel disaster risk management and governance structure have a dramatically better chance of realizing the SFDRR goals for disaster risk reduction

Governance informatics: Managing the performance of inter-organizational governance networks

This article introduces an informatics approach to managing the performance of inter-organizational governance networks that are designed to create, implement and evaluate public policies and the range of activities undertaken by practicing public administrators. We label this type of information flow process management governance informatics and lay out a range of theoretical constructs that may be used to collect, categorize, and analyze performance in inter-organizational governance networks. We discuss how governance informatics may be able to assess and re-design the accountability and transparency regimes of information flows in inter-organizational governance networks. The integration of a governance informatics-driven performance management system into an existing regional transportation planning network is presented as an application of the framework

Crowdsourced Delphis: Designing solutions to complex environmental problems with broad stakeholder participation

There is a well-established need for increased stakeholder participation in the generation of adaptive management approaches and specific solutions to complex environmental problems. However, integrating participant feedback into current science, research, and decision-making processes is challenging. This paper presents a novel approach that marries a rigorous Delphi method, borrowed from policy and organizational sciences, with contemporary “crowdsourcing” to address the complex problems of water pollution exacerbated by climate change in the Lake Champlain Basin. In an online Delphi forum that occurred over a six-week period during the Spring of 2014, fifty-three participants proposed and commented on adaptive solutions to address water quality in the context of climate change. In a follow up Multi-Stakeholder workshop, thirty-eight stakeholders participated in refining and synthesizing the results from the forum. To inform modeling and policy dialogue, the resulting list of interventions was analyzed by time horizon, domain, type of adaptation action, and priority level. The interventions suggested by stakeholders within the crowdsourcing forum have contributed to the current policy dialogue in Vermont including legislation to address phosphorus loading to Lake Champlain. This stakeholder approach strengthens traditional modeling scenario development to include solutions and priorities that have been collectively refined and vetted

Modeling the influence of public risk perceptions on the adoption of green stormwater infrastructure: An application of bayesian belief networks versus logistic regressions on a statewide survey of households in vermont

There is growing environmental psychology and behavior literature with mixed empirical evidence about the influence of public risk perceptions on the adoption of environmentally friendly “green behaviors”. Adoption of stormwater green infrastructure on residential properties, while costlier in the short term compared to conventional greywater infrastructure, plays an important role in the reduction of nutrient loading from non-point sources into freshwater rivers and lakes. In this study, we use Bayesian Belief Networks (BBNs) to analyze a 2015 survey dataset (sample size = 472 respondents) about the adoption of green infrastructure (GSI) in Vermont’s residential areas, most of which are located in either the Lake Champlain Basin or Connecticut River Basin. Eight categories of GSI were investigated: roof diversion, permeable pavement, infiltration trenches, green roofs, rain gardens, constructed wetlands, tree boxes, and others. Using both unsupervised and supervised machine learning algorithms, we used Bayesian Belief Networks to quantify the influence of public risk perceptions on GSI adoption while accounting for a range of demographic and spatial variables. We also compare the effectiveness of the Bayesian Belief Network approach and logistic regression in predicting the pro-environmental behaviors (adoption of GSI). The results show that influencing factors for current adoption differ by the type of GSI. Increased perception of risk from stormwater issues is associated with the adoption of rain gardens and infiltration trenches. Runoff issues are more likely to be considered the governments’ (town, state, and federal agencies) responsibility, whereas lawn erosion is more likely to be considered the residents’ responsibility. When using the same set of variables to predict pro-environmental behaviors (adoption of GSI), the BBN approach produces more accurate predictions compared to logistic regression. The results provide insights for further research on how to encourage residents to take measures for mitigating stormwater issues and stormwater management

DOES OWNERSHIP CONCENTRATION MODERATES CORPORATE SOCIAL RESPONSIBILITY-FIRM PERFORMANCE RELATIONSHIP?

CSR is basically a commitment demanded from companies to protect stakeholder interests, enhance societal conditions, and contribute to sustainable development. This study investigated the relationship between corporate social responsibility and firm financial performance with a particular focus on measuring the moderating impact of ownership concentration on the CSR-performance relationship. The data is collected from the companies’ annual reports, State Bank of Pakistan database and the Pakistan Stock Exchange for the period 2014-2020. The fixed effect regression model is used to measure the impact of CSR on firm financial performance. The results of the study revealed that CSR has a significant negative impact on firm financial performance. Furthermore, ownership concentration also negatively moderates the relationship between CSR and firm financial performance

Conjoint analysis of farmers\u27 response to conservation incentives

Environmental degradation threatens the long term resiliency of the US food and farming system. While USDA has provided conservation incentives for the adoption of best management practices (BMPs), only a small percentage of farms have participated in such conservation programs. This study uses conjoint analysis to examine Vermont farmers\u27 underlying preferences and willingness-to-accept (WTA) incentives for three common BMPs. Based on the results of this survey, we hypothesize that federal cost share programs\u27 payments are below preferred incentive levels and that less familiar and more complex BMPs require a higher payment. Our implications focus on strategies to test these hypotheses and align incentive payments and other non-monetary options to increase BMP adoption