In the 21st century, the surge in natural and human-induced disasters necessitates robust disaster managementframeworks. This research addresses a critical gap, exploring dynamics in the successful implementation andp...In the 21st century, the surge in natural and human-induced disasters necessitates robust disaster managementframeworks. This research addresses a critical gap, exploring dynamics in the successful implementation andperformance monitoring of disaster management. Focusing on eleven key elements like Vulnerability and RiskAssessment, Training, Disaster Preparedness, Communication, and Community Resilience, the study utilizesScopus Database for secondary data, employing Text Mining and MS-Excel for analysis and data management.IBM SPSS (26) and IBM AMOS (20) facilitate Exploratory Factor Analysis (EFA) and Structural Equation Modeling(SEM) for model evaluation.The research raises questions about crafting a comprehensive, adaptable model, understanding the interplaybetween vulnerability assessment, training, and disaster preparedness, and integrating effective communicationand collaboration. Findings offer actionable insights for policy, practice, and community resilience against disasters. By scrutinizing each factor's role and interactions, the research lays the groundwork for a flexible model.Ultimately, the study aspires to cultivate more resilient communities amid the escalating threats of an unpredictable world, fostering effective navigation and thriving.展开更多
Apple occupies a dominant position in fruit production globally, and has become the main income source of local smallholder farmers in Luochuan County in the Loess Plateau area, one of the largest apple production are...Apple occupies a dominant position in fruit production globally, and has become the main income source of local smallholder farmers in Luochuan County in the Loess Plateau area, one of the largest apple production areas in China. However, the annual productivity of apple orchards in this region remains low and has gradually declined over the years. The distinction and correlation of production constraints can contribute to the promotion of apple orchard productivity and the development of a sustainable orchard system. In the present study, survey data from 71 smallholder farmers were analyzed using a yield gap model to distinguish the production constraints and determine their correlation with the yield gap based on the structural equation model(SEM). The results indicated that the average apple yield in Luochuan County was 29.9 t ha^–1 yr^–1, while the attainable yield(Yatt;the highest yield obtained from the on-farm surveys) was 58.1 t ha^–1 yr^–1. The average explained and unexplainable yield gaps were 26.3 and 1.87 t ha^–1 yr^–1. According to the boundary line analysis, crop load,number of sprayings and base fertilizer N were the top three constraints on apple production in 9.8, 7.8 and 7.8% of the plots, respectively. Among the production constraints, crop load and fruit weight affected apple yield through direct pathways,whereas other constraints influenced apple yield through an indirect pathway based on the SEM, explaining 51% of the yield variance by all the main production constraints. These results can improve the current understanding of production constraints and contribute to the development of management strategies and policies for improving apple yield.展开更多
文摘In the 21st century, the surge in natural and human-induced disasters necessitates robust disaster managementframeworks. This research addresses a critical gap, exploring dynamics in the successful implementation andperformance monitoring of disaster management. Focusing on eleven key elements like Vulnerability and RiskAssessment, Training, Disaster Preparedness, Communication, and Community Resilience, the study utilizesScopus Database for secondary data, employing Text Mining and MS-Excel for analysis and data management.IBM SPSS (26) and IBM AMOS (20) facilitate Exploratory Factor Analysis (EFA) and Structural Equation Modeling(SEM) for model evaluation.The research raises questions about crafting a comprehensive, adaptable model, understanding the interplaybetween vulnerability assessment, training, and disaster preparedness, and integrating effective communicationand collaboration. Findings offer actionable insights for policy, practice, and community resilience against disasters. By scrutinizing each factor's role and interactions, the research lays the groundwork for a flexible model.Ultimately, the study aspires to cultivate more resilient communities amid the escalating threats of an unpredictable world, fostering effective navigation and thriving.
基金funded by the National Key Research and Development Program of China (2016YFD0201137 and 2016YFE0101100)the Innovative Group Grant of the National Science Foundation of China (31421092)
文摘Apple occupies a dominant position in fruit production globally, and has become the main income source of local smallholder farmers in Luochuan County in the Loess Plateau area, one of the largest apple production areas in China. However, the annual productivity of apple orchards in this region remains low and has gradually declined over the years. The distinction and correlation of production constraints can contribute to the promotion of apple orchard productivity and the development of a sustainable orchard system. In the present study, survey data from 71 smallholder farmers were analyzed using a yield gap model to distinguish the production constraints and determine their correlation with the yield gap based on the structural equation model(SEM). The results indicated that the average apple yield in Luochuan County was 29.9 t ha^–1 yr^–1, while the attainable yield(Yatt;the highest yield obtained from the on-farm surveys) was 58.1 t ha^–1 yr^–1. The average explained and unexplainable yield gaps were 26.3 and 1.87 t ha^–1 yr^–1. According to the boundary line analysis, crop load,number of sprayings and base fertilizer N were the top three constraints on apple production in 9.8, 7.8 and 7.8% of the plots, respectively. Among the production constraints, crop load and fruit weight affected apple yield through direct pathways,whereas other constraints influenced apple yield through an indirect pathway based on the SEM, explaining 51% of the yield variance by all the main production constraints. These results can improve the current understanding of production constraints and contribute to the development of management strategies and policies for improving apple yield.
