Vietnamese smallholders’ perspectives on causes, indicators and determinants of climate change: implication for adaptation strategies

• Published in: Climatic change Vol. 162; no. 3; pp. 1127 - 1142
• Main Author: Hoang, Hung Gia
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.10.2020; Springer Nature B.V
• Subjects: Adaptation; Agricultural wastes; Air pollution; Atmospheric Sciences; Chi-square test; Climate adaptation; Climate change; Climate change adaptation; Climate change causes; Climate Change/Climate Change Impacts; Communication; Community involvement; Community participation; Deforestation; Dependent variables; Determinants; Drought; Earth and Environmental Science; Earth Sciences; Empirical analysis; Flood frequency; Gender; Independent variables; Indicators; Mitigation; Rain; Rainfall; Rainfall amount; Rainfall distribution; Regression analysis; Regression models; Urbanization; Vietnam; Climate change; Determinants; Vietnam; ICT; Indicators; Smallholders
• ISSN: 0165-0009; 1573-1480
• DOI: 10.1007/s10584-020-02827-x

In order to facilitate the adoption of climate change adaptation and mitigation practices by smallholders, it is essential to understand their perspectives on climate change. However, few empirical studies have considered how smallholders perceive climate change in Central Vietnam. This research investigates the Vietnamese smallholders’ views on the causes and indicators of climate change and factors that affect their perceptions of it in Central Vietnam. A sample size of 170 was drawn from a total of 297 smallholders and a structured questionnaire was developed to collect data. Descriptive, chi-square (χ 2 ) and logistic regression analyses were used. The research results revealed that most smallholders perceived urbanization (93.5%), followed by deforestation (85.3%), air pollution (84.4%) and unappropriated dealing with agricultural wastes (82.4%) are the causes of climate change. A majority of smallholders perceived that excessive lightening (91.2%), followed by change in rainfall season length (90.6%), frequent droughts (90%), change in temperature (88.2%), uneven rainfall distribution (85.9%), rainfall amount (84.1%) and frequent floods (82.9%) are the most noted indicators of climate change. The success of regression model overall prediction is reported by model χ 2  = 92.69, p  < 0.000, showing that the independent variables significantly explained the dependent variable. Among the independent variables, farming practice, information communication and technology (ICT) owned, community-based organisation participation, gender, type of household, credit programme participation and education level are significantly important determinants of smallholders’ perception on climate change.