Capturing Ecosystem Services, Stakeholders' Preferences and Trade-Offs in Coastal Aquaculture Decisions : A Bayesian Belief Network Application

Aquaculture activities are embedded in complex social-ecological systems. However, aquaculture development decisions have tended to be driven by revenue generation, failing to account for interactions with the environment and the full value of the benefits derived from services provided by local ecosystems. Trade-offs resulting from changes in ecosystem services provision and associated impacts on livelihoods are also often overlooked. This paper proposes an innovative application of Bayesian belief networks - influence diagrams - as a decision support system for mediating trade-offs arising from the development of shrimp aquaculture in Thailand. Senior experts were consulted (n = 12) and primary farm data on the economics of shrimp farming (n = 20) were collected alongside secondary information on ecosystem services, in order to construct and populate the network. Trade-offs were quantitatively assessed through the generation of a probabilistic impact matrix. This matrix captures nonlinearity and uncertainty and describes the relative performance and impacts of shrimp farming management scenarios on local livelihoods. It also incorporates export revenues and provision and value of ecosystem services such as coastal protection and biodiversity. This research shows that Bayesian belief modeling can support complex decision-making on pathways for sustainable coastal aquaculture development and thus contributes to the debate on the role of aquaculture in social-ecological resilience and economic development

Uncertainty Analysis in Predicting Ecological Impacts of Management Scenarios in the Chehl-Chai Watershed, Gorganrood River Basin

Implementing watershed management without considering all aspects may lead to instability, exacerbating unfavorable conditions. Adopting an integrated management approach is necessary for any watershed system. An important consideration in decision making and planning process is to quantify ecological impacts of management using landscape ecology framework. In this regard, uncertainty quantification is of great significance. This paper presents the concept of uncertainty and also the implication of uncertainty analysis for landscape ecology structure indices and also for weights assigned to the indices in a Multi-Criteria Decision Making (MCDM) technique in the Chehel-Chai Watershed. This watershed with an area of 256 km2 is located in the east of Golestan Province and in the upstream of the Gorganrood River Basin. The watershed is one of the most affected areas due to the land use change in the north of Iran. That is why it was chosen as the study the area. Based on the analysis, the highest and lowest uncertainty levels were identified for Edge Density (ED) and Riparian Proportion Index (RPI), respectively. In addition, the uncertainty analysis suggests that the weight assigned to Weighted Land Cover Area Index (WLCAI) has the highest uncertainty while the weight assigned to ED shows the lowest uncertainty. It is necessary to identify and quantify uncertainty so that more accurate and applicable inferences from research findings can be drawn

Assessment of seasonal variations of chemical characteristics in surface water using multivariate statistical methods

Water pollution has become a growing threat to human society and natural ecosystems in the recent decades. Assessment of seasonal changes in water quality is important for evaluating temporal variations of river pollution. In this study, seasonal variations of chemical characteristics of surface water for the Chehelchay watershed in northeast of Iran was investigated. Various multivariate statistical techniques, including multivariate analysis of variance, discriminant analysis, principal component analysis and factor analysis were applied to analyze river water quality data set containing 12 parameters recorded during 13 years within 1995-2008. The results showed that river water quality has significant seasonal changes. Discriminant analysis identified most important parameters contributing to seasonal variations of river water quality. The analysis rendered a dramatic data reduction using only five parameters: electrical conductivity, chloride, bicarbonate, sulfate and hardness, which correctly assigned 70.2 % of the observations to their respective seasonal groups. Principal component analysis / factor analysis assisted to recognize the factors or origins responsible for seasonal water quality variations. It was determined that in each season more than 80 % of the total variance is explained by three latent factors standing for salinity, weathering-related processes and alkalinity, respectively. Generally, the analysis of water quality data revealed that the Chehelchay River water chemistry is strongly affected by rock water interaction, hydrologic processes and anthropogenic activities. This study demonstrates the usefulness of multivariate statistical approaches for analysis and interpretation of water quality data, identification of pollution sources and understanding of temporal variations in water quality for effective river water quality management

Progressive Watershed Management Approaches in Iran

Expansionism and ever-increasing population menace all different resources worldwide. The issue, hence, is critical in developing countries like Iran where new technologies are rapidly luxuriated and unguardedly applied, resulting in unexpected outcomes. However, uncommon and comprehensive approaches are introduced to take all the different aspects involved into consideration. In the last decade, few approaches such as community-based, stakeholders-oriented, adaptive and ultimately integrated management, have emerged and are developing for efficient, Co-management or best management, economic and sustainable development and management of watershed resources in Iran. In the present paper, an attempt has been made to focus on state-of-the-art approaches for the management of watershed resources applied in Iran. The study has been then supported by reports of some case studies conducted throughout the country involving previously mentioned approaches. Scrutinizing results of the researches verified a progressive tendency of the managerial approaches in watershed management strategies leading to a general approaching balance situation. The approaches are firmly rooted in educational, research, executive, legal and policy-making sectors leading to some recuperation at different levels. However, there is a long way ahead to naturalize detrimental effects of unscientific, illegal and over exploitation of the watershed resources in Iran

Application of Bayesian networks for sustainability assessment in catchment modeling and management (Case study: The Hablehrood river catchment)

Catchment management is a process which increases the sustainable development and management of all catchment resources in order to maximize the balance among socioeconomic welfare and the sustainability of vital ecosystems. The increase of anthropogenic activities within river catchments causes degradation and serious problems for stakeholders and managers, particularly in arid and semi-arid regions. Although there are many techniques for solving these problems, it is not easy for catchment managers to apply them. An integrated Bayesian network model framework was applied to evaluate the sustainability of a semi-arid river catchment located in the Iranian Central Plateau river basin encompassing 32.6 km2 area on the Hablehrood river catchment, located in the northern part of the Iranian Central Plateau river basin. The research illustrated the assessment of the relevant management problems, the model framework, and the techniques applied to extract input data. Results for the study area implementation and a suggestion for management are described and discussed

Bayesian Network Modelling for assessing the biophysical and socio-economic impacts of dryland salinity management

Improving dryland salinity management at catchment scales requires an integrated modelling approach, in which the dominant bio-physical and socio-economic drivers, processes and impacts are considered. This paper presents and evaluates the use of a Bayesian Decision Network (BDN) model as an integrated approach for considering the trade-offs associated with the management of dryland salinity, a major environmental problem in Australia. The ability and effectiveness of the BDN approach in building integrated catchment assessment and management tools are demonstrated through a case study in the Little River Catchment (LRC) in the upper Macquarie River basin, NSW. This integrated model was developed to co-ordinate the various disciplines involved in salinity problems, integrate available data and information, and to allow the investigation of the potential outcomes arising from implementing salinity management options at the catchment scale. A conceptual model framework underlying the BDN for salinity management in the LRC was developed. This framework incorporates ecological, physical, economic and social aspects of dryland salinity problems in the catchment. To complete the BDN model, a range of techniques, data and information was used. Various outcomes of implementing 32 possible salinity management scenarios at the catchment scale are investigated and discussed. The investigation was conducted based on the following indices from different disciplines: surface runoff, baseflow, stream salt concentration, terrestrial habitat condition, community attitude, establishment costs, and total gross margin. The BDN approach implemented in this research serves as a valuable tool to represent the catchment system as a whole, to incorporate output from models and expert judgment, to examine the trade-offs among outcomes necessary for decision-making, and to communicate uncertainty of the parameters in the BDN model. The analysis of the trade-offs presented in this paper also shows that due to the influences of the various possible outcomes on decision-making analysis, as well as the diversity in the factors influencing the characteristics of stream flow, blanket solutions for managing the quality and quantity of stream flow cannot be suggested. To reach informed and feasible decisions for salinity management the social and economic preferences and priorities, along with the ecological and hydrological consequences of salinity management options, need to be considered in quantifying the trade-offs among salinity management outcomes

Desertification risk assessment and management program

Risk assessment provides the possibility of planning and management to prevent and reduce the risk of desertification. The present study is aimed to assess the hazard and risk of desertification and to develop management programs in the semi-arid western regions of Golestan Province in Iran. Desertification rate was obtained using the Iranian model of desertification potential assessment. Since the rating system was considered for the indicators, data analyses were carried out according to the Mann-Whitney test. The risk of desertification was calculated based on hazard, elements at risk and vulnerability assessment maps. The intensity of desertification was estimated to be medium. Among the factors affecting desertification, agriculture by the weighted average of 3.22 had the highest effect, followed by soil, vegetation, water and wind erosion criteria by weighted averages of 2.45, 2.32, 2.15 and 1.6 respectively. Desertification risk assessment results also showed that about 78% of central and northern parts of the region, with the largest population and residential centers, surface and underground water resources, agriculture and horticulture, is confronted with a high to very high degree of risk. Management plans and control measures, based on risk values were presented in four activities (with two management priorities under critical and non-critical conditions). For the management program with the largest area. Control measures and strategies such as the establishment of halophytic and xerophytic plants, drainage networks, resilient facilities and infrastructure were proposed. Reducing the risk of desertification, could play a crucial role in the sustainable development of drylands and desert ecosystems

Analysis of adaptation determinants of domestic rainwater harvesting systems (DRWHs) in Golestan province, Iran

Abstract Most residences of the northern parts of Golestan Province, have historically used rooftop rainwater for drinking. Its adoption rate and continued use have declined in recent years for various reasons. Based on a survey of 380 cases, this research attempted to identify what factors are contributing to the adoption of these systems. The results demonstrated that the adoption changes in response to five factors: access to water, existence of specialized organizational sector, previous experience, direct observation and integration into the domestic distribution system, with the odds ratios of 10.5, 2.16, 0.12, 2.7, and 4 respectively (P<0.01). One of the factors that is likely to intensify in the region is reduced access to safe drinking water (every unit increase in this factor would increase the adoption by a factor of 10). It seems necessary to develop a governmental sector, specialized in the field of domestic rainwater harvesting, to not only help technically and financially to the construction of these systems, but to offer consultations and hygienic safety packages, such as chlorine stock solutions or modernization of equipment. Modernization of these systems could also help remove the concern over the integration of these systems into the domestic water distribution piping. Lack of experience and less frequent contact with these systems have also resulted in low level DRWHs adoption. It appears mass media and non-governmental organizations could also facilitate improving these two factors. Results of this study could inform decision making to better encourage the use of DRWHs in Golestan Province

Perspectives on confronting issues of scale in systems modeling

Issues of scale pervade every aspect of socio-environmental systems (SES) modeling. They can stem from the context of both the modeling process, and the purpose of the integrated model. A webinar hosted by the National Socio-Environmental Synthesis Center (SESYNC), The Integrated Assessment Society (TIAS) and the journal Socio-Environmental Systems Modelling (SESMO) explored how model stakeholders can address issues of scale. Four key considerations were raised: (1) being aware of our influence on the modeling pathway, and developing a shared language to overcome cross-disciplinary communication barriers; (2) that localized effects may aggregate to influence behavior at larger scales, necessitating the consideration of multiple scales; (3) that these effects are “patterns” that can be elicited to capture understanding of a system (of systems); and (4) recognition that the scales must be relevant to the involved stakeholders and decision makers. Key references in these four areas of consideration are presented to complement the discussion of confronting scale as a grand challenge in socio-environmental modeling. By considering these aspects within the integrated modeling process, we are better able to confront the issues of scale in socio-environmental modeling