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Climate variability and change coupled with small landholdings, low land productivity and water scarcity in arid and semi-arid regions contribute to environmental degradation, reduced agricultural productivity, and increased vulnerability to the rural communities. With the aid of the fuzzy cognitive maps constructed by 427 community groups with 4–5 members in each group, drawn from 96 villages in 12 districts of arid and semi-arid India, the paper evaluates the effectiveness of various adaptation pathways. The ongoing adaptations in arid and semi-arid India face adaptation deficits. The FCM-based simulations revealed that integrated adaptation measures that embrace nature-based solutions, including integrated water resource management, natural farming-assisted soil rejuvenation, and improved agricultural productivity are most likely to enhance the resilience of small and marginalised farming communities to climate variability and change. Facilitation of such adaptation measures requires inclusive and adaptive local institutions, sufficient financial assistance, and climate information services. Besides, gender-nuanced, inclusive, and adaptive governance and processes would be helpful for the implementation of appropriate adaptation interventions in arid and semi-arid drylands worldwide. Hence policy-makers must enable polycentric and adaptive governance, and inclusive institutions and processes. The emphasis on multiple factors in a socio-ecological system often makes it difficult to understand the critical role of a particular factor. However, the FCM-based simulations in this study helped us overcome such limitations. Image 1 • FCM-based simulations used to examine the effectiveness of current adaptations. • Current adaptations face adaptation deficit and provide limited resilience. • Integrated adaptations embracing nature-based solutions could provide resilience. • Lack of finance, technology, and locally relevant information are the key barriers. • Polycentric-adaptive governance and inclusive institutions & processes are crucial. [ABSTRACT FROM AUTHOR]

Every development and production process needs to operate within a circular economy to keep the human being within a safe limit of the planetary boundary. Policymakers are in the quest of a powerful and easy-to-use tool for representing the perceived causal structure of a complex system that could help them choose and develop the right strategies. In this context, fuzzy cognitive maps (FCMs) can serve as a soft computing method for modelling human knowledge and developing quantitative dynamic models. FCM-based modelling includes the aggregation of knowledge from a variety of sources involving multiple stakeholders, thus offering a more reliable final model. The average aggregation method for weighted interconnections among concepts is widely used in FCM modelling. In this research, we applied the OWA (ordered weighted averaging) learning operators in aggregating FCM weights, assigned by various participants/ stakeholders. Our case study involves a complex phenomenon of poverty eradication and socio-economic development strategies in rural areas under the DAY-NRLM (Deendayal Antyodaya Yojana-National Rural Livelihoods Mission) in India. Various scenarios examining the economic sustainability and livelihood diversification of poor women in rural areas were performed using the FCM-based simulation process implemented by the "FCMWizard" tool. The objective of this study was three-fold: (i) to perform a brief comparative analysis between the proposed aggregation method called "OWA learning aggregation" and the conventional average aggregation method, (ii) to identify the significant concepts and their impact on the examined FCM model regarding poverty alleviation, and (iii) to advance the knowledge of circular economy in the context of poverty alleviation. Overall, the proposed method can support policymakers in eliciting accurate outcomes of proposed policies that deal with social resilience and sustainable socio-economic development strategies. [ABSTRACT FROM AUTHOR]