Natural forests are the habitat of many plant and animal species and are the main source of genetic reserves. In addition to preserving biodiversity, forests play an important role in the livelihood and income of many indigenous communities. But, in the last few decades, due to the lack of proper management of the beneficiaries, they have been exposed to destruction, so that their protection requires the participation of all members of the society, especially the local people. Therefore, the main goal of this research was to discover the determinant factors on the intention of local communities to protect forests in Iran. An extended theory of planned behavior (TPB) by adding the variables of “risk perception” (RP) and “sense of belonging to place” (SBP) was used as the theoretical framework of the research. This research was done using the questionnaire survey method and with the help of structural equation modeling (SEM). The statistical population of this study included all the rural communities living in the Arasbaran forests (located in the northwest of Iran). The research findings indicated that the original TPB explains 66.9% of the variance of the behavioral intentions of locals toward forest protection. The three main constructs of the original TPB included attitude, perceived behavioral control (PBC) and subjective norms (SN), all of which had positive effects on the intention of local communities. Most importantly, the extended TPB by including RP and SBP increases the ability of the model to explain the intentions of local communities to forest protection by 11.8%. In this study, the variable of RP was identified as the most important factor, so it is suggested to the policy-makers of this field to increase the RP of local communities in relation to forest destruction using communication media. It is also suggested to promote safe behaviors in these natural areas through developing forest protection organizations and properly training locals on the protection of forest areas.

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Application of the extended theory of planned behavior in predicting the behavioral intentions of Iranian local communities toward forest conservation

Rangeland are one of the most important natural habitats for the protection of living and non-living organisms. Degradation of rangeland is one of the biggest threats to biodiversity loss. Ranchers’, as the most important key stakeholders who have a direct relationship with rangelands, have put a lot of pressure on the rangeland sector in recent years, so that this natural habitat has been destroyed. Therefore, existing rangelands must be preserved to protect biodiversity. One of the most important strategies to protect rangeland is to change the behavior of ranchers to friendly and ecological behaviors in the environment. In this regard, this study was conducted with the general aim of explaining the ranchers’ behavior of rangeland conservation in western Iran. The main research tool was a questionnaire whose validity was confirmed by a panel of experts and its reliability was confirmed by Cronbach’s alpha coefficient. In this study, value-belief-norm (VBN) was used to identify research variables. The results showed that ranchers have used different behaviors to protect rangelands and egoistic behaviors are the main cause of the destruction of this natural habitat. In addition, the results of this study showed that the framework used was an efficient theory because it explains 53.9% of rangeland conservation behavior. Finally, in this study, based on the research findings, applied policies for the protection of natural rangelands were presented so that in addition to rangeland conservation, biodiversity can also be preserved.

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Explaining the ranchers’ behavior of rangeland conservation in western Iran

The improvement of rural households' livability in drought conditions has always been an important challenge for all countries, especially developing countries, because consecutive droughts have reduced the resilience of these households and may even inflict irreparable damages to rural and agricultural communities if there are no systems in place for mitigating the risk of drought. This research explored the effects of social capital on the livability of rural families in Iran. The statistical population was composed of all rural-farmer families in Kerman province in the southeast of Iran. The study site was selected based on the severity of droughts. The results show that the studied households are not at an optimal level in livability indices and past droughts have severely reduced their livability level. If no comprehensive plan is adopted for drought management in the coming years, most villages in the southeast of Iran will be desolated. Furthermore, it is revealed that the dimension of social capital (social awareness, participation and collective action, membership in groups, social trust, and social participation) can account for 74.1% of the variance in rural households' livability in drought conditions. In general, the results can provide policymakers with new insights into how to supply conditions for the sustainability of rural families’ livelihood in drought conditions. 

The effect of social capital in mitigating drought impacts and improving livability of Iranian rural households

Effective factors to increase rural households' resilience under drought conditions in Iran

Climate change, population growth and urban sprawl have put a strain on water supplies across the world, making it difficult to meet water demand, especially in city regions where more than half of the world’s population now reside. Due to the complex urban fabric, conventional techniques should be developed to diagnose water shortage risk (WSR) by engaging crowdsourcing. This study aims to develop a novel approach based on public participation (PP) with a geographic information system coupled with machine learning (ML) in the urban water domain. The approach was used to detect (WSR) in two ways, namely, prediction using ML models directly and using the weighted linear combination (WLC) function in GIS. Five types of ML algorithm, namely, support vector machine (SVM), multilayer perceptron, K-nearest neighbour, random forest and naïve Bayes, were incorporated for this purpose. The Shapley additive explanation model was added to analyse the results. The Water Evolution and Planning system was also used to predict unmet water demand as a relevant criterion, which was aggregated with other criteria. The five algorithms that were used in this work indicated that diagnosing WSR using PP achieved good-to-perfect accuracy. In addition, the findings of the prediction process achieved high accuracy in the two proposed techniques. However, the weights of relevant criteria that were extracted by SVM achieved higher accuracy than the weights of the other four models. Furthermore, the average weights of the five models that were applied in the WLC technique increased the prediction accuracy of WSR. Although the uncertainty ratio was associated with the results, the novel approach interpreted the results clearly, supporting decision makers in the proactive exploration processes of urban WSR, to choose the appropriate alternatives at the right time.

https://www.mdpi.com/2220-9964/11/12/606/pdf?version=1670317572

A Novel Approach Based on Machine Learning and Public Engagement to Predict Water-Scarcity Risk in Urban Areas

Dealing with a growing population and a shortage of drinking water is a major challenge for politicians and planners. A key factor in ensuring a sustainable water supply is water conservation at the household level, which can increase productivity and save water resources. Therefore, promoting water consumption curtailment behavior will contribute significantly to reducing the global water crisis, especially in arid and semi-arid regions. Water consumption curtailment behaviors depend on individuals' encouragement to choose and adopt voluntary behaviors and cannot be enforced by any political or planning power. In order to encourage water conservation those social and psychological factors should be considered that influence individuals to participate or adopt water consumption curtailment behaviors. Therefore, the study of factors influencing rural households' water consumption curtailment behaviors is of great importance. This study aimed to describe the socio-psychological factors influencing water consumption curtailment behaviors among rural households in southwestern Iran. The extended theory of planned behavior (ETPB) was used as a theoretical framework in this study along with descriptive norms (DN), moral norms (MN), habits, and justification. Data were collected using a questionnaire and analyzed using structural equation modeling (SEM). The results showed that ETPB can explain 35% and 54% of intention and water consumption curtailment behaviors among rural households in Iran. Our findings may assist policymakers in reducing domestic water consumption. 

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Socio-psychological determinants of Iranian rural households' adoption of water consumption curtailment behaviors

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Hamed Izadi

Papers

Socio-psychological determinants of Iranian rural households' adoption of water consumption curtailment behaviors

Socio-psychological determinants of Iranian rural households' adoption of water consumption curtailment behaviors