Network Analysis, Creative System Modelling and Decision Support: The NetSyMoD Approach

This paper presents the NetSyMoD approach – where NetSyMod stands for Network Analysis – Creative System Modelling – Decision Support. It represents the outcome of several years of research at FEEM in the field of natural resources management, environmental evaluation and decision-making, within the Natural Resources Management Research Programme. NetSyMoD is a flexible and comprehensive methodological framework, which uses a suite of support tools, aimed at facilitating the involvement of stakeholders or experts in decision-making processes. The main phases envisaged for the process are: (i) the identification of relevant actors, (ii) the analysis of social networks, (iii) the creative system modelling and modelling of the reality being considered (i.e. the local socio-economic and environmental system), and (iv) the analysis of alternative options available for the management of the specific case (e.g. alternative projects, plans, strategies). The strategies for participation are necessarily context-dependent, and thus not all the NetSyMod phases may be needed in every application. Furthermore, the practical solutions for their implementation may significantly differ from one case to another, depending not only on the context, but also on the available resources (human and financial). The various applications of NetSyMoD have nonetheless in common the same approach for problem analysis and communication within a group of actors, based upon the use of creative thinking techniques, the formalisation of human-environment relationships through the DPSIR framework, and the use of multi-criteria analysis through the mDSS software.Social Network, Integrated Analysis, Participatory Modelling, Decision Support

From CBA to decision trees and cognitive maps: Supplementing costs and benefits to acknowledge uncertainties and complexity in decision making

286 p.Decision making has always been di¿cult due to uncertainty about the future, but humans invented strategies to overcome these di¿culties. Climate change, however, has brought new challenges: on the one hand, many of these strategies have become inappropriate to face impacts of climate change; on the other hand, climate change is extensive which needs a response from everyone, everywhere, at every moment in time. This thesis takes the cost and bene¿t framework as a starting point to show if and how divulging uncertainties and complexities may improve decision-making and project evaluations that are done prior to investments. Overall, the work undertaken here demonstrates that improving decision-making based on costs and bene¿ts is both necessary and feasible. The cost-bene¿t model may bene¿t from being used together with (semi-) qualitative and illustrative methodologies that are better suited to communicate on complexities underlying decision-making and that enable to understand and acknowledge model assumptions. Illustrating complexities may result insightful and complementary. Using the bene¿t-cost model together with other more appropriate evaluation methods may also be more desirable in order to avoid reproducing from the past, what may not be suited for the future. In order to achieve this, economic assessments need also include the participation of actors from di¿erent backgrounds to expose knowledge that would otherwise remain hidden, while valuing democratic participation. Including interactions across various research domains and participants may enable to visualise and highlight the inter-linkages between domains and their complexity, instead of inhibiting what is the very nature of interactions of societies with their environment. This may enable to identify the root causes of vulnerabilities and a more complete range of interventions. This work is anticipated to be a starting point for more sophisticated applications, more participative and interlinked evaluation methods that use several methodologies. In addition, future research can build on di¿erent insights provided by neuroscientists and psychologists. Sound decision-making may not come from methodologies alone, but from humans¿ physical capacity to develop and implement them

FORECASTING CLIMATE AND LAND USE CHANGE IMPACTS ON ECOSYSTEM SERVICES IN HAWAIʻI THROUGH INTEGRATION OF HYDROLOGICAL AND PARTICIPATORY MODELS

Ph.D. Thesis. University of Hawaiʻi at Mānoa 2018

Modelling stakeholder perceptions to assess Green Infrastructures potential in agriculture through fuzzy logic: A tool for participatory governance

Abstract Solutions like Green Infrastructures can restore and maintain key regulative ecosystem services capable of mitigating disaster risk and contributing to climate change adaptation. Given the vulnerabilities that affect agriculture and its role in national economies, GI can play an important role in managing trade-offs between conflicting ecosystem services. However, their use is still lagging behind, and socio-economic dynamics in their uptake in the agricultural sector are partially disregarded. The uncertainty involved in the modelling of ecological processes can be reduced through the use of participatory processes and the involvement of relevant stakeholders to sustain decision-making processes. This article intends to assess stakeholders' perceptions on the implementation of Green Infrastructures in agriculture by capturing critical barriers and facilitators. The implementation of such Green Infrastructures policies is associated to different climate change trends in order to understand the effect of different scenarios on rural development. The study uses fuzzy logic to elicit the stakeholders' needs. The key results show that when there is uncertainty in the state of climate change trends, it is always more efficient to adopt progressive policies investing in the development and diffusion of Green Infrastructures

A structured participatory method to support policy option analysis in a social-ecological system

In this study we demonstrate how to support policy option analysis for a problematic Social-Ecological System (SES) with the help of stakeholder participation. SES sustainability problems 1) are highly complex, 2) may lack reliable data, 3) encompass conflicting interests and 4) may require contradictory management interventions. Our approach uses a structured participatory method combining the Driver-Pressure-State-Impact-Response (DPSIR) model together with Fuzzy Cognitive Mapping (FCM) to capture the complexity of the system and simplify its representation for simulation and policy option analysis. Using this novel mixed-method was useful in dealing with above-mentioned characteristics of the complex SES problems. The method was applied in a case study of water scarcity in Rafsanjan, Iran. FCMs were produced for 60 individual farmers and 40 individual researchers and policy makers. Our mixed-method analysis reveals similarities and differences of stakeholder knowledge and problem perception, and simulates the impacts of alternative policy options according to each group's perception. The final result of our case study indicates that farmers in Rafsanjan strongly believe in the impact of economic diversification on reducing water shortage, but they have a low level of trust in the ability of the government to regulate and control water usage, whereas the policy makers and researchers still believe in the role of government control and monitoring policies to deal with water scarcity in Rafsanjan

Tools and methods in participatory modeling: Selecting the right tool for the job

© 2018 Elsevier Ltd Various tools and methods are used in participatory modelling, at different stages of the process and for different purposes. The diversity of tools and methods can create challenges for stakeholders and modelers when selecting the ones most appropriate for their projects. We offer a systematic overview, assessment, and categorization of methods to assist modelers and stakeholders with their choices and decisions. Most available literature provides little justification or information on the reasons for the use of particular methods or tools in a given study. In most of the cases, it seems that the prior experience and skills of the modelers had a dominant effect on the selection of the methods used. While we have not found any real evidence of this approach being wrong, we do think that putting more thought into the method selection process and choosing the most appropriate method for the project can produce better results. Based on expert opinion and a survey of modelers engaged in participatory processes, we offer practical guidelines to improve decisions about method selection at different stages of the participatory modeling process

Developing a green city assessment system using cognitive maps and the Choquet integral

Equitable human well-being and environmental concerns in urban areas have, over the years, become increasingly challenging issues. This trend is related to both the complexity inherent in the multiple factors to be considered when evaluating eco-friendly cities (i.e., green cities) and the way this type of city’s sustainability depends on many evaluation criteria, which hampers all decision-making processes. Using a multiple criteria decision analysis (MCDA) approach, this study sought to develop a multiple-criteria model that facilitates the evaluation of green cities’ sustainability, based on cognitive mapping techniques and the Choquet integral (CI). Taking a constructivist and process-oriented stance, the research included identifying evaluation criteria and their respective interactions using a panel of experts with specialized knowledge in the subject under analysis. The resulting framework and its application were validated both by the panel members and a parliamentary representative of the Portuguese ecology party “Os Verdes” (The Greens), who confirmed that the evaluation system created distinguishes between cities according to how strongly they adhere to “green” principles. The advantages and limitations of the proposed framework are also discussed.info:eu-repo/semantics/acceptedVersio

Susceptibility to Changes in Coastal Land Dynamics in Bangladesh

Coastal areas of the world are physically dynamic in nature. The present study contributes new knowledge to studies on coastal land dynamics and land susceptibility to erosion. This study developed a raster GIS-based model namely, Land Susceptibility to Coastal Erosion (LSCE) to assess erosion susceptibility of coastal lands under hydro-climatic changes. The devised model was applied to the entire coastal area of Bangladesh. The model required the characterisation of the nature of land dynamics (i.e. erosion and accretion). The analysis showed a net gain of 237 km² of land over the past thirty years but, constant changes in land dynamics were observed in the area. The study then applied the LSCE model to measure the existing levels of land susceptibility of the coastal area to erosion. The validated model outputs were then used as a baseline for generating four possible scenarios of future land susceptibility to erosion in the coastal area. This allowed the model to ascertain the probable impacts of future hydro-climatic changes on land susceptibility to erosion in the area. Additionally, the study assessed seasonal variations of land susceptibility to erosion by using the same model. The model outputs showed that 276.33 km² of existing coastal lands classified as highly and very highly susceptible to erosion, would substantially increase in the future. Using a Fuzzy Cognitive Mapping (FCM) approach, the study elicited expert views to evaluate the model scenarios and to address uncertainties relevant to erosion susceptibility. This study could allow coastal managers and policymakers to develop effective measures in managing highly erosion susceptible coastal lands in the area

Spatio-temporal correlation of extreme climate indices and river flood discharges

The occurrence of floods is strongly related to specific climatic conditions that favor extreme precipitation events. Although the impact of precipitation and temperature patterns on river flows is a well discussed topic in hydrology, few studies have focused on the rainfall and temperature extremes in their relation with peak discharges. This work presents a comparative analysis of Climate Change Indices (ETCCDI) annual time series, calculated using the NorthWestern Italy Optimal Interpolation (NWIOI) dataset, and annual maximum flows in the Piedmont Region. The Spearman’s rank correlation was used to determine which indices are temporally correlated with peak discharges, allowing to hypothesize the main physical processes involved in the production of floods. The correlation hypothesis was verified with the Spearman’s rank correlation test, considering a Student’s t-distribution with a 5% significance level. Moreover, the influence of climate variability on the tendency of annual maximum discharges was examined by correlating trends of climate indices with trends of the discharge series. These were calculated using the Theil-Sen slope estimator and tested with the Mann-Kendall test at the 5% significance level. The results highlight that while extreme precipitation indices are highly correlated with extreme discharges at the annual timescale, the interannual changes of extreme discharges may be better explained by the interannual changes of the total annual precipitation. This suggests that projections of the annual precipitation may be used as covariates for non-stationary flood frequency analysis

Making sense of changing coastal systems: overcoming barriers to climate change adaptation using fuzzy cognitive mapping

This thesis describes the role and value of Fuzzy Cognitive Mapping (FCM) in undertaking coastal climate change adaptation at the local scale, comparing FCM against existing, scenario-based adaptation methods in overcoming known barriers to adaptation. It describes the attributes and limitations of FCM as a modelling tool, exploring what must be accounted for in considering the use of FCM in mixed stakeholder settings where individual and group knowledge must be integrated to form a view of the system under study, discussing in some detail the facilitation strengths and weaknesses inherent to the method. These issues are then described via reference to case-studies in Ireland and Scotland, drawing inferences regarding the ease with which an FCM-based approach to adaptation might be substituted for orthodox, scenario-based adaptation. This is found to not only be feasible, but preferable, provided there is sufficient facilitation capacity on hand to manage the added complexity that FCM carries over simple narrative scenario development. Adding to the value that FCM offers in adaptation contexts, the thesis also explores its value as both a diagnostic tool for establishing what additional capacity building or data may be required by adaptation decision makers, and also as a tool for gauging the extent to which resilience gains (or losses) might be measured. Although FCM cannot be claimed to provide a robust objective measure of resilience gains or losses, it can nevertheless usefully illustrate to decision makers the strengths and limitations of their own understanding of the systems which they must manage. This is perhaps where the future of FCM-based systems analysis in support of adaptation may ultimately lie