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Since the long-term sustainability of garden ecosystems is dependent on maintaining the soil quality, knowing the condition of the soils and investigating the effects of the activities on the soil properties is very important and effective in ecosystem management. To investigate the soil quality index of almond (Prunus dulcis) orchards under different managed methods in ChaharMahal va Bakhtiari province, soil samples were collected from three points in each orchard and finally classified into 6 groups (Saman, Ben, Shahrekord, Kiar, Ardel, and Farsan). To determine the soil quality index, soil characteristics including pH, EC, total and water-soluble organic carbon, basal and substrate-derived respiration, rhizosphere microbial population, and available soil P and K were analyzed. The results showed that almond orchard management in different regions affected the soil characteristics and the processes evaluated in this study. The monitoring of soil properties showed that pH 7.05 - 8.48, EC 0.23 - 2.91 dS/m, microbial respiration 0.44 - 8.57 mg CO2.100 g-1 .day-1, organic carbon 2.09 - 44.79 g/kg, available phosphorus 1.5 - 122.3 mg/kg, and available potassium were between 91.2 - 3038 mg/kg. Soil quality index components including chemical components, microbial activity, microbial population, and soil organic carbon were determined. The contribution of soil salinity to soil quality obtained using factorial analysis was the highest (31%), followed by microbial carbon mineralization coefficient (27%), rhizosphere microbial population (24%), and water-soluble organic carbon (18%). The soil quality index values for Saman, Ben, Shahrekord, Kiar, Ardal, and Farsan almond orchards were 0.46, 0.40, 0.51, 0.67, 0.54, and 0.37, respectively. These values showed that the evaluated soils are suitable for almond production in Shahrekord, Kiar, and Ardal, and for Saman, Ben, and Farsan, there is a need for serious management measures to improve soil quality and increase the sustainability of these agricultural ecosystems. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to propose an approach for identifying and prioritizing ecosystem indicators for effective ecosystem management. Specifically, fuzzy Delphi and fuzzy DEMATEL approaches are used to define ecosystem management goals and indicators, rank the importance of quality attributes in ecosystem management, and rank the effectiveness of each indicator in each pillar of ecosystem management. The ultimate goal is to provide a tool to decision-makers that can help in allocating resources more effectively and efficiently toward achieving sustainability. Design/methodology/approach: The proposed approach involves a three-phase framework. Phase 1 involves identifying and determining the indicators affecting ecosystem management. This has been performed by studying theoretical articles, reviewing systematic literature, and searching previous studies to identify different indicators for each pillar of ecosystem management. A list of indicators and factors affecting each of the pillars of ecosystem management has been determined accordingly, and an initial categorization has been created using library studies. Phase 2 involves using a fuzzy Delphi method to rank the most important indicators in each pillar of ecosystem management. Experts have been asked to indicate their proposed indicators in a questionnaire based on fuzzy variables, and the degree of proportionality of the proposed factors. Phase 3 involves using a fuzzy DEMATEL approach to rank the effectiveness of each indicator in each pillar of ecosystem management. This approach handles imprecise or subjective data and can be replicated for different cities. Overall, this methodology aims to provide a comprehensive approach for identifying and prioritizing ecosystem indicators that can be used by decision-makers in environmental management and policy-making. Findings: Findings imply that the integrated approach of the Fuzzy Delphi Method and the Fuzzy DEMATEL can be used to identify and rank the importance of quality attributes in ecosystem management, and to rank the effectiveness of each indicator in each pillar of the ecosystem management. A total of 36 indicators were identified across four pillars of ecosystem management, i.e., economic, social, environmental and institutional. The results indicated that the most important indicators for each pillar were science and technology and innovation for the economic pillar; air quality, waste treatment and energy efficiency for the environmental pillar; poverty, health, and safety and security for the social pillar; and transparent sharing of information and political stability for institutional pillar. It was also found that there was a strong interrelationship between different pillars of ecosystem management. For example, the institutional pillar had serious effects on most of the other identified EM pillars. In addition, the economic pillar was the second most influential factor. Moreover, the institutional pillar profoundly influenced the environmental pillar. Finally, the economic pillar highly affected the environmental pillar, which doubled the complexity of ecosystem management. Research limitations/implications: Several limitations and implications have been addressed for future research. The number of participating experts was limited, which could affect the results and limit the possibility of their summarization. Expert bias may have influenced the results of the study. Such limitations imply that further research with a larger and more diverse group of experts is necessary to validate and expand upon such findings. This study was limited in scope to a particular ecosystem or region and the identified indicators as a result may not apply and be generalizable to other ecosystems or regions. Based on the cause-and-effect relationships between the studied elements, a hypothesis can be expanded and validated using a larger sample. Future studies could replicate this methodology in different contexts to test its applicability and effectiveness. Practical implications: Decision-makers in environmental management and policy-making can use the methodology presented in this study to identify and prioritize ecosystem indicators. By using an integration of the Fuzzy Delphi Method and the Fuzzy DEMATEL, decision-makers can identify the most important indicators for each pillar of ecosystem management and evaluate their effectiveness. This information can be used to allocate resources more effectively and efficiently toward achieving sustainability. Decision-makers could use this methodology to evaluate different ecosystem management practices and policies, and develop new policies or modify existing ones to better address the needs of different stakeholders. Overall, this study provides a useful tool for decision-makers in environmental management and policy-making by providing a comprehensive approach to identifying and prioritising ecosystem indicators. Social implications: This study highlights the importance of considering social factors in ecosystem management. The study identifies several social indicators, such as poverty and material deprivation, education level, public awareness and training, gender equality, and social participation. By prioritizing such indicators in ecosystem management, decision-makers can ensure that the needs and perspectives of different stakeholders are taken into account. This can help to promote social equity and cohesion, which are important for achieving sustainable development. Furthermore, by involving a wide range of stakeholders in the decision-making process, including local communities and marginalized groups, decision-makers can ensure that ecosystem management policies are more inclusive and responsive to the needs of all members of society. Overall, this study highlighted the importance of considering social factors in ecosystem management and provides a useful framework for identifying and prioritizing social indicators. Originality/value: The main contribution of this study is the application of the integrated approaches of the Fuzzy Delphi Method and the Fuzzy DEMATEL to identify and rank the importance of quality attributes in ecosystem management. This methodology is innovative because it allows decision-makers to handle imprecise or subjective data, which is often encountered in ecosystem management. The study provides a three-phase framework for identifying and prioritizing ecosystem indicators, which can be replicated for different cities. Findings indicated that science and technology, air quality, poverty, and transparent sharing of information were identified as the most important quality indicators in their respective pillars of ecosystem management alternatives. This implies that decision-makers and policymakers should consider allocating more resources toward improving such areas. Overall, this study provided a useful tool for decision-makers in environmental management and policy-making by providing a comprehensive approach to identifying and prioritizing ecosystem indicators. [ABSTRACT FROM AUTHOR]

Introduction: Flood is a phenomenon that occurs almost in most regions of the world and causes significant damage to human life and ecosystem. Forests are one of the necessary things to prevent damages caused by floods, but the conditions are not enough. Therefore, it is important to use an economic tool to manage and protect the Hyrcanian forest ecosystem in order to reduce flood damage in the coming years. Currently, there are various tools in this field that must be carefully chosen and it is not possible to use one tool in all ecosystems of the world. Payment for forest ecosystem services (PES) is one of the economic tools of forest management and protection by providing direct incentives to stakeholders to improve its ecosystem functions and services. Therefore, in comparison with other market instruments of environmental protection such as environmental taxes which may cause a reduction in the production of various economic sectors and as a result reduce the income of producers and finally lose their motivation. The Payment for Forest Ecosystem Services (PES) program not only does not reduce income, but also increases income for the beneficiaries of forest ecosystem services and thus creates incentives. Payment for ecosystem services is a two-way transaction and is completely voluntary. In this transaction, there must be at least one buyer and one ecosystem service provider provided that the ecosystem service provider continues to offer that service. The logic of PES schemes is that the beneficiaries (people who benefit from ecosystem services) are asked to protect the providers of ecosystem services (such as public or private organizations) who work to protect, restore and natural ecosystem management is to pay for better management and protection of these ecosystems. This payment may take place at the local, national and global level. Studies show that among the various factors influencing the occurrence of floods, excessive exploitation of forests and changes in the use of forest lands are the main causes of floods. But few studies have been conducted on the role of PES plans to protect natural ecosystems to prevent natural hazards such as floods. Therefore, considering the importance and extraordinary value of natural forests in the region in reducing flood damage, the purpose of this study is to investigate the preferences of residents affected by recent floods in Mazandaran province in the form of payment for ecosystem services (PES) scheme and to identify the factors affecting the acceptance of PES scheme to reduce flood damage by conservation the Hyrcanian forests ecosystem using the choice modeling approach (Choice Experiment (CE) and the multinomial econometric model. The Choice Experiment is one of the methods of valuing stated preferences, which is very suitable for analyzing the importance of different features of a product or a policy. Materials and Methods: To achieve this goal, the Choice Experiment method and multinomial logit econometric model were used. The features studied in this method include forest management, watershed management, land use management (preventing forest land use change), payment method, contract duration and payment amount (price). Also, the statistical population of the study includes the affected-floods residents in three parts of the center, east and west of Mazandaran province. Research data were obtained by field survey, random sampling and 110 choice experiment questionnaires in summer 2020. Socio-economic variables in the study include age, gender, job, education, PES awareness, expenses and income of the affected-floods residents. Results and Conclusion: Based on the study results, the willingness to pay of households affected by floods for conserving the Hyrcanian forest ecosystem to reduce flooding through land use management is as follows: for changing the status quo, it is 36,140 Rial per month; for improvement status, it is 68,910 Rial per month. Additionally, for contract duration and payment method, the willingness to pay is 150,150 Rial per month. The study findings also indicate that affected-floods residents prefer to make cash payments in the long-term to conserve the forest ecosystem and mitigate flooding. Furthermore, when examining the impact of various socio-economic variables on the residents' willingness to pay, it was found that age, gender, education, expenses, income, and awareness of Payment for Ecosystem Services (PES) have a direct positive effect on their willingness to pay. Considering these results, it is recommended that forest conservation programs in the Northern provinces place importance on the mentioned factors to encourage people's participation in forest conservation projects. This will facilitate the implementation of the PES scheme and enhance the success of forest conservation efforts. [ABSTRACT FROM AUTHOR]

Planning and providing appropriate tools to reduce the adverse effects of natural hazards including floods is inevitable. Achieving the above goal depends on having sufficient and accurate knowledge and information about the vulnerability of different ecosystems (watersheds) to various destructive factors. Vulnerability assessment by identifying potential stresses and disturbances (natural and man-made) as well as estimating the sensitivity of watersheds allows for predicting the effects and selecting appropriate solutions for the sustainable management of these ecosystems. Therefore, this study has been designed to identify and rank vulnerable sub-watersheds to floods in the Ardabil plain, taking into account social, economic, infrastructural, and ecological dimensions. First, the indicators and criteria of each dimension were identified taking into account the conditions prevailing in Ardabil plain. Then, information and data on climatic, hydrological, demographic, economic, infrastructure, and land use were obtained from relevant authorities. Then, the mentioned criteria were standardized and the weight according to their importance was calculated based on the BWM method the data obtained from this stage were performed using the TOPSIS technique to rank flood vulnerability for different sub-watersheds in Ardabil plain for the period 2007-2017. Finally, a map of Ardabil's plain vulnerability to floods was prepared and presented. According to the results, the criteria of building density, rainfall, population density, and the unemployment rate were the most important criteria of vulnerability and among the studied dimensions, the infrastructure dimension is too significant in flood vulnerability in Ardabil plain. Based on the comprehensive vulnerability map, sub-watershed 7 in Ardabil plain was identified as the most vulnerable sub-watershed in the study area. [ABSTRACT FROM AUTHOR]

Understanding effects of environment on the distribution of economic fish is a fundamental step in the ecosystem-based management and ultimately a standard approach in management policies. Bigeye tuna (Thunnus obesus) is one of the most important aquatic species harvested in the Indian Ocean. The present study investigated the association of different variables effecting the rate of catch and distribution of bigeye tune, using generalized additive model (GAM) and maximum entropy (MaxEnt) and satellite derived environmental variables in the Indian Ocean. Results highlighted the importance of temporal and spatial variables along with the eddy kinetic energy, sea level height, depth of 20°C isotherm and sea surface temperature on the distribution of the species. The most suitable habitat predicted by MaxEnt model was observed around the latitudes of 0 to 5 degrees of north and south, mainly in the western part of the Indian Ocean and longitude of 45 to 70 degrees east. Using satellite data, the present study determinied the important factors and suitable habitats for the species, which can be useful for Iranian fisheries managers to increase the fishing efficiency and implementing of ecosystem-based fisheries management in the shared exploited stocks of the Indian Ocean.

The quintuple helix innovation model has been introduced by E.G. Carayannis and F.J. Campbell. The natural environments of society and the economy are major drivers of this innovation model. The third generation university (the convergence of government, industry and university), the fourth generation universities (the convergence of government, industry, university and civil society) and the fifth generation university (the convergence of government, industry, university, civil society and bio-environment) perform within Triple Helix, Quadruple Helix and Quintuple Helix models, respectively. According to the viewpoints of Carayannis and Campbell, the cardinal characteristics of the fifth generation university could be conceptualized as a knowledge-based innovation system which is sensitive to natural environment of society, produces knowledge within the mode 3 knowledge production framework, supports co-evolution and co-existence of different knowledge paradigms, shapes co-opetitive ecosystem for knowledge management and promotes knowledge democracy. [ABSTRACT FROM AUTHOR]