Climate change impact perception and agricultural adaptation in a coastal region

BACKGROUND AND OBJECTIVES: Climate change perception plays a significant role in shaping agricultural households'' adaptation strategies. However, empirical research on the relationship between perception and adaptation remains limited. This study aims to explore how farmers'' perceptions of climate change influence livelihood adaptation behaviors in Vietnam''s Mekong Delta, specifically investigating psychological factors as key determinants of adaptive capacity. The study seeks to address the gap in understanding perception-based adaptation mechanisms in climate-vulnerable agricultural systems.METHODS: This cross-sectional study was conducted in Thanh Phu District, Ben Tre Province, Vietnam. The district is strategically located between the Ham Luong and Co Chien rivers. The district spans 425.7 square kilometers with a population density of 300 people per square kilometers. It is highly vulnerable to climate change. Projections suggest that 45 percent of residents could face flooding by 2100 due to sea level rise. Primary data were collected in January 2024 through a structured questionnaire survey. The survey was administered to 200 agricultural households. Five communes representing three distinct ecological zones were selected using simple random sampling. The study targeted household heads engaged in crop cultivation, livestock, aquaculture, and mixed farming systems. The 33-item questionnaire covered demographic characteristics, livelihood activities, climate change perceptions, and adaptation strategies. Data analysis applied multivariate logistic regression. This explored relationship between 32 independent variables categorized into five domains. These domains included socio-economic factors, perceived resource quality status, perception of climate change manifestations, perception of climate impacts on natural resources, and impacts of climate change on livelihoods. Seven binary coded dependent variables representing adaptation strategies were analyzed. These included change in production, increased production cost, increased labor input, livelihood transition, change in location, livelihood maintenance, and other adaptations. Model performance was evaluated using Nagelkerke R², Area under the curve from receiver operating characteristic analysis, and percentage correct classification. Statistical significance was considered at the p < 0.05 level.FINDINGS: Results demonstrate that perception of climate impacts on livelihoods is the strongest predictor of adaptation behavior. It shows strong negative associations (Odds ratio = 0.254-0.552, p < 0.001) across multiple strategies. Conversely, perception of climate change manifestations correlates positively (Odds ratio = 2.007-2.401, p < 0.05) with adaptive strategies. Traditional socioeconomic variables exhibited minimal influence compared to perceptual factors. The models achieved strong performance indicators (Nagelkerke R² = 0.70-0.75; Area under the curve = 74-89 in percent). Production-focused strategies demonstrated highest predictive accuracy.CONCLUSION: The results emphasize perception as a primary driver of adaptation. This outweighs socioeconomic factors. These findings advocate for enhanced climate communication and education to foster proactive adaptation. The study offers empirical evidence to inform sustainable policy design for Vietnam''s coastal delta regions. Climate change adaptation remains limited in these areas.

Institutions

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-10-01
DOI
https://doi.org/10.22034/gjesm.2025.04.19
Primary Topic
Climate change impacts on agriculture
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Climate change impact perception and agricultural adaptation in a coastal region

SHILAP Revista de lepidopterología
Climate change impacts on agriculture
article

Climate change impact perception and agricultural adaptation in a coastal region

article en

Abstract

BACKGROUND AND OBJECTIVES: Climate change perception plays a significant role in shaping agricultural households'' adaptation strategies. However, empirical research on the relationship between perception and adaptation remains limited. This study aims to explore how farmers'' perceptions of climate change influence livelihood adaptation behaviors in Vietnam''s Mekong Delta, specifically investigating psychological factors as key determinants of adaptive capacity. The study seeks to address the gap in understanding perception-based adaptation mechanisms in climate-vulnerable agricultural systems.METHODS: This cross-sectional study was conducted in Thanh Phu District, Ben Tre Province, Vietnam. The district is strategically located between the Ham Luong and Co Chien rivers. The district spans 425.7 square kilometers with a population density of 300 people per square kilometers. It is highly vulnerable to climate change. Projections suggest that 45 percent of residents could face flooding by 2100 due to sea level rise. Primary data were collected in January 2024 through a structured questionnaire survey. The survey was administered to 200 agricultural households. Five communes representing three distinct ecological zones were selected using simple random sampling. The study targeted household heads engaged in crop cultivation, livestock, aquaculture, and mixed farming systems. The 33-item questionnaire covered demographic characteristics, livelihood activities, climate change perceptions, and adaptation strategies. Data analysis applied multivariate logistic regression. This explored relationship between 32 independent variables categorized into five domains. These domains included socio-economic factors, perceived resource quality status, perception of climate change manifestations, perception of climate impacts on natural resources, and impacts of climate change on livelihoods. Seven binary coded dependent variables representing adaptation strategies were analyzed. These included change in production, increased production cost, increased labor input, livelihood transition, change in location, livelihood maintenance, and other adaptations. Model performance was evaluated using Nagelkerke R², Area under the curve from receiver operating characteristic analysis, and percentage correct classification. Statistical significance was considered at the p < 0.05 level.FINDINGS: Results demonstrate that perception of climate impacts on livelihoods is the strongest predictor of adaptation behavior. It shows strong negative associations (Odds ratio = 0.254-0.552, p < 0.001) across multiple strategies. Conversely, perception of climate change manifestations correlates positively (Odds ratio = 2.007-2.401, p < 0.05) with adaptive strategies. Traditional socioeconomic variables exhibited minimal influence compared to perceptual factors. The models achieved strong performance indicators (Nagelkerke R² = 0.70-0.75; Area under the curve = 74-89 in percent). Production-focused strategies demonstrated highest predictive accuracy.CONCLUSION: The results emphasize perception as a primary driver of adaptation. This outweighs socioeconomic factors. These findings advocate for enhanced climate communication and education to foster proactive adaptation. The study offers empirical evidence to inform sustainable policy design for Vietnam''s coastal delta regions. Climate change adaptation remains limited in these areas.

SHILAP Revista de lepidopterología
Ho Chi Minh City University of Social Sciences and Humanities (VN), Ministry of Agriculture and Rural Development (VN)
Climate action
Openalex Percentile: Top 30%
Climate change impacts on agriculture
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.