Cassava farmers’ perception on climate change: A case study in Van Yen district, Yen Bai province
ISSN 2588-1299
VJAS 2020; 3(2): 606-611
Vietnam Journal
of Agricultural
Sciences
Cassava Farmers’ Perception on Climate
Change: A Case Study in Van Yen District,
Yen Bai Province
Nguyen Hai Nui1, Vu Thanh Bien2, Nguyen Duc Trung4, Trieu
Hong Lua2, Nguyen Tuan Cuong2, Charles Spillane3, Galina
Brychkova3, Peter McKeown3 & Bui Le Vinh2
1 Faculty of Accounting and Business Management, Vietnam National University of
Agriculture (VNUA), Hanoi 131000, Vietnam
2 Faculty of Land Management, Vietnam National University of Agriculture (VNUA), Hanoi
131000, Vietnam
3 Ryan Institute, National University of Ireland Galway (NUIG), Galway, Ireland
4 Independent expert in climate change research, Vietnam
Abstract
Situated in the Northern Mountain Region, one of the most climate-
vulnerable regions of Vietnam, Yen Bai province is exposed to many
climate risks. This study investigated how well Yen Bai farmers were
aware of the impacts of the changing climate on production and their
livelihoods and how they referred support programs from the central
and local governments to make decisions on adaptation and resilience
strategies. Data were collected through direct interviews of 488 cassava
households in six communes of Van Yen district. Descriptive statistics,
One-way ANOVA, and Chi-square test were used to statisticallyanalyze
the data. In addition, we employed the Partial Least Square Structural
Equation Modelling (PLS-SEM) to study the relationships of three
identified independent variables: (i) understanding of support
programs/policies; (ii) access to weather information; and (iii)
experience of climate risks and impacts, and farmers’ perceptions of
climate impacts. Results from the PLS-SEM model showed that
farmers with higher positive scores in the three independent variables
above had better perceptions of climate change and its possible
impacts, from which better adaptation decisions and strategies could
be derived. These research findings emphasized the need for
improving the understanding of climate change that could impact
farmers’ livelihoods, farmers’ access to accurate near-time and
medium-term weather forecasts, and thoroughly using local
knowledge on climate risks and effective native adaptation measures
for better adaptation and mitigation strategies and actions in rural
climate-vulnerable communities in Vietnam.
Received: June 11, 2020
Accepted: November 27, 2020
Correspondence to
Keywords
ORCID
Nguyen Hai Nui
3088
Cassava farmers, climate change, farmers’ perceptions, climate
impacts
700
Vietnam Journal of Agricultural Sciences
Nguyen Hai Nui et al. (2020)
Findings of Bryan et al. (2013) indicated that
Kenyan farmers and pastoralists with long
farming experiences and from different
agroecologies tended to understand well-
changing temperature and rainfall patterns over a
long period of time. Part of the study of Mulwa
et al. (2017) in Malawi on farmers’ perceptions
of climate variability over the past decade
revealed some major shocks, such as droughts
and hailstorms. These shocks finally led to
negative impacts of crop pests, diseases, and
flooding. In Europe, Li et al. (2017) studied the
perceptions of 1,940 farmers from the
Transdanubian region of Hungary on climate
risks by analyzing complex relationships
between farmers’ perceptions on climate change
and their adaptation behaviors. The study found
out that farmers noticed some climate changes
through water shortages, extreme weather
events, and increased temperature. They only
became more aware of climate risks when seeing
the effects of tested adaptation measures. In Asia,
Alam et al. (2017) and Arunrat et al. (2016)
found that farmers’ perceptions on climate
changes and extreme weather events were quite
in accordance with observed climatic data in
Bangladesh and Thailand, respectively. They
could observe resulting impacts on their
livelihoods and natural resources which they
base their livelihoods on.
Introduction
Over the past decades, Vietnam has obtained
remarkable achievements in agriculture, e.g.
obtaining national food security and being the
world’s 2nd rice exporter and top coffee producer
(Bui et al., 2020). Despite these, many
challenges still exist, such as smallholder
farming, limited commodity production
capacities,
value
chain
development,
competitiveness on the international market, and
climate change. Given the fact that Vietnam is
among the five most climate-vulnerable
countries, climate risks play a role as important
limiting factors to the creation of negative
impacts on Vietnam’s overall development (Ngo
et al., 2018; Vu et al., 2018), especially in the
agricultural sector (Huynh et al., 2018). Some
examples are serious erosion and flash floods in
mountainous regions (Nguyen, 2014; Tuan et al.,
2014); salinized arable land triggered by
seawater intrusion in the Mekong River and more
frequent droughts as in 2015-2016 in the Central
Highlands (CGIAR, 2016); and increased pests
and diseases due to global warming (Kiritani,
2013). Meanwhile, the adaptive capacities of the
majority of farmers cannot yet cope with these
impacts, largely because their perceptions of
climate change have not been adequate (Huong
et al., 2017). Understanding how farmers
perceive climate risks, their impacts and their
strategies to adapt to climate change is crucial to
plan adaptation strategies across climate-
vulnerable agroecologies (Dang et al., 2014).
In Vietnam, farmers are becoming more
aware and conscious of climate change and how
its potential impacts can affect their current
production and future livelihoods (Dang et al.,
2013; McKinley et al., 2016). Dang et al. (2014)
found that personal beliefs decide different levels
of climate change perceptions. Those who
believe in the changing climate and have
experienced climate extreme events have a
higher understanding and appreciation of climate
risks than those who do not believe and/or do not
care. The study of Huong et al. (2017) conducted
in six provinces of Northwest Vietnam indicates
farmers’ perceptions of certain prominent risks,
such as increased temperature both in the winter
and summer; decreased rainfall in the winter,
which lead to more droughts in the dry season;
and shorter rainfall durations but higher
intensities in the rainy season. Most of these risks
were also confirmed by interviewed farmers in
At the global scale, many studies have
investigated different farmers’ perceptions of
climate change for adaptation strategies. In
Africa, Gandure et al. (2013) found that farmers
in Gladstone, a rural village near the town of
Thaba Nchu in the Free State Province of
about the impact of weeds, insects and worms
than rainfall and temperature variabilities that, to
them, had
negligible impacts on their
livelihoods. Adaptation strategies, therefore, are
received quite differently among Gladstone
farmers. The youth were not interested in
farming; hence, they were not applying
adaptation measures. Some farmers were not
practicing measures of poorly guided policies.
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Cassava farmers’ perception on climate changes: A case study in Van Yen district, Yen Bai province
the study of Bui et al. (2020) implemented in Van
Yen district, Yen Bai province of the northern
mountain region (NMR) – a representatively
climate-vulnerable province in the region. These
research findings showed the importance of
understanding farmers’ perceptions of climate
impacts and needs for change in making
decisions for climate adaptation, mitigation, and
production actions (FAO, 2013). This study, with
a further focus on Yen Bai, aimed at investigating
Van Yen farmers’ perceptions on climate change
and its impacts based on the following three
research hypotheses: (i) H1 – Accessibility to
weather information decides the farmers’
perceptions of climate change and its impacts;
(ii) H2 – Knowledge depth of support
programs/policies/projects on climate actions
decides the farmers’ perceptions of climate
change and its impacts; and (iii) H3 –
Experiences in encountering extreme weather
events decide the farmers’ perceptions of climate
change and its impacts.
documents to respond to climate change.
Besides, large number of projects
a
(development, research and development) to
tackle climate change have been conducted in
many parts of Vietnam, especially in the most
vulnerable areas. If people were aware of these
mentioned supports, they would perceive climate
change’s existence and its impacts on their
livelihoods.
According to Van der Linden (2014),
personal experience with extreme weather
phenomena impacts is the most important factor
affecting climate change risk perception. In this
research, this structure was measured by the
impacts of four dominant disasters, namely hot
spells, acid rain, drought, and cold spells, which
were perceived by cassava farmers.
Several studies explored the causal
relationships between the amount of weather
information farmers received and their
perception of climate change (Reyes et al., 2009;
Bloodhart et al., 2015; Simelton et al., 2017).
They concluded that weather forecast was
associated with their beliefs and concerns about
climate change. Therefore, natural disaster
forecasts, crops calendar, daily weather forecast
news, and extreme weather events were selected
as the variables to measure farmers’ access to
weather information.
Materials and Methods
Conceptual framework
The conceptual framework in this study is
described in Figure 1. The term “perceptions”
refers to knowledge, beliefs, attitudes, concern,
affect, and perceptions (Whitmarsh & Capstick,
2018). The perception process consists of three
stages, namely selection, organization, and
interpretation (Ou, 2017). Perception of climate
change is the perception of all components
related to climate change, including climate
change platform, government policies and
support agencies, climate change information,
and its impact (Dal et al., 2014; Nyanga et al.,
2011; Whitmarsh & Capstick, 2018).
Study site and data collection
Van Yen (Figure 2c), a well-performed
cassava producing district, has an average
elevation of 500m a.s.l, an average annual
temperature of 21-23oC, and an average annual
rainfall of 1800mm. A survey was conducted in
six communes representing three main areas
located in the southeast, center, and northwest of
Van Yen district from October to December
2019. In each area, two cassava communes were
selected, including Mau Dong and Ngoi A in the
southeast; An Binh and Quang Minh in the
center; and Lang Thip and Chau Que Ha in the
northwest (Figure 2). Sample size for farmer
interviews was determined using equation (1) of
Iarossi (2006):
Climate change is a matter that is of great
interest to the whole world and all nations (IPCC,
2018). At the national level, countries set
policies, strategies, and action plans to respond
to climate change. Following the national
guidelines, policies, and programs, the local
governments, i.e., provincial or district
authorities, have also issued a system of legal
Vietnam Journal of Agricultural Sciences
702
Nguyen Hai Nui et al. (2020)
Figure 1. Research conceptual framework
(
Southeast
Center group
Northwest group
(
(
Figure 2. Study area in Van Yen district (c), Yen Bai province (b) of the NMR of Vietnam (a)
Out of 26 communes and 01 town of Van Yen, 13 communes (c) have cassava plantations (Bui et al., 2020)
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Cassava farmers’ perception on climate changes: A case study in Van Yen district, Yen Bai province
household education (Jawlik, 2016). The one-
푧2. 푆2
푒2 + 푧2. 푆
way analysis of variance (ANOVA) was used to
explore different mean values for more than two
groups (Jawlik, 2016), equivalent to different
research sites. Internal consistency was
calculated using Cronbach’s Alpha (Table 1),
with a value higher than 0.60 being an acceptable
cut-off point for reliability (Peterson, 1994).
푛 =
2
푁
(1)
n: sample size
N: total observations (population size)
z: reliability value
e: expected error
To develop theories in the exploratory
research, we employed Partial Least Square
Structural equation modeling (PLS-SEM). PLS-
SEM approach has become a key research
method in the social sciences in recent decades
for having some advantages. For example, the
method can be applied to a small sample size,
data without normal distribution, or case studies
with many latent and manifest variables that can
only be estimated (Hair et al., 2016). In this
research, we applied the Smart PLS 3.0 software
for data analysis. All constructs were modeled as
a formative measurement which was tested
through variance inflation factor (VIF), outer
weight, and outer loading. All VIFs were below
the value of 5, indicating that collinearity among
indicators is not an issue in SEM model. Four out
of 15 outer weights were insignificant; however,
their corresponding item loadings were
significant and higher than the threshold 5. All
manifest variables were, therefore, retained in the
model (Hair et al., 2016).
S: tandard deviation
S2: population variance
There were a total of 33,247 households (N)
in Van Yen district, with S = 15%, z = 99%, and
e = 1.8%. Computation of sample size showed
the need of 455 households for the survey. The
total sample in this study is 488 households (Bui
et al., 2020).
The questionnaire answered by respondents
was the main data collection tool employed in
this study. Most of the questions used a Likert
scale (Likert, 1932) which is a popular method
used to measure knowledge and perceptions. The
questionnaire contained questions about farmers’
perception of climate change and its impacts,
farmers’ understanding of climate change
adaptation plans and disaster prevention,
farmers’ access to weather-related information,
and climate phenomena impacts. The target
group of the survey was cassava farmers.
Macroscopic inspection on the liver surfaces
Results and Discussion
The study used means and rates of the
descriptive statistical analysis method to describe
socio-economic characteristics of cassava
farmers. Frequencies were compared using Chi-
squared test. In this study, the χ2 test (for
independence) was used to test whether
categorical variables (three sites) were
independent or associated with demographic
characteristics, i.e., wealthy ranking and
Characteristics of the surveyed farmers’
households
Table 2 presents the socio-economic
characteristics of surveyed farmers. The rate of
the poor increased from the southeast to the
northwest. This is partly explained by the fact
that the southeast is the district center and is
closely linked to national highways and provincial
Table 1. Result of reliability analysis
Variable
Cronbach’s Alpha
Farmers’ perception on climate change and its impacts
0.80
Farmers’ understanding of government implementation about climate change adaption
Farmers’ access to weather information
0.80
0.87
0.61
Farmers’ experiences of climate phenomena impacts
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704
Nguyen Hai Nui et al. (2020)
Table 2. Surveyed farmer household’s characteristics
Criteria
Total numbers of surveyed households
Poor (%)
Northwest
194
Center
196
Southeast
Grand total
488
98
22.16
67.53
10.31
15.31
66.84
17.86
5.10
15.98
Normal (%)
Wealth ranking
Rich (%)
69.39
25.51
67.62
16.39
p-value (Pearson chi Square-2 sided) by area = 0.00
Members
4.28
4.41
4.15
4.31
Household size
HHH’s sex
p-value (Bartlett's test) by area = 0.77
Male (%)
88.66
11.34
91.84
8.16
89.80
10.20
90.16
9.84
Female (%)
p-value (Pearson chi Square-2 sided) by area = 0.57
Years
43.21
45.52
49.17
45.33
HHH’s years old
p-value (Bartlett's test) by area = 0.053
Kinh (%)
Tay (%)
27.32
25.77
46.91
20.92
7.14
92.86
0.00
7.14
37.91
13.11
48.98
HHH’s ethnic
Others (%)
71.94
p-value (Pearson chi Square-2 sided) by area = 0.00
Illiterate (%)
22.16
24.23
23.20
24.23
6.19
19.90
24.49
28.57
21.43
5.61
0.00
16.80
22.34
27.46
26.02
7.38
Lower than primary school (%)
Lower than secondary school (%)
Lower than high school (%)
14.29
33.67
38.78
13.27
HHH’s education
High school and higher eduction (%)
p-value (Pearson chi Square-2 sided) by area = 0.00
Note: HHH = household head
roads, creating favorable conditions for
economic development activities. Meanwhile,
the northwest region has difficult transportation
conditions and belongs to extremely difficult
commune group (Bui et al., 2020). In addition,
Kinh people are the majority in the southern part
of the research site compared to the rest.
Concerning the education level, respondents
from the southeast have higher average education
background than in the northwest and the center.
Statistically significant differences were found in
the criteria of the wealth ranking, household
education levels, ethnicity of households, and
average age of household head among three parts
(P< 0.01). On average, there were 4.31 members
in each household and more than 90% of the
household heads were male; however, the
differences of the above mentioned indicators in
three parts were not significant (P> 0.05).
Farmers’ perception of climate change and its
impacts
Description of farmers’ perceptions of
climate change and its impacts is presented in
Table 3. Farmers tended to agree and strongly
agree that climate change is a natural
phenomenon with various types, i.e. global
warming, melting ice, and sea-level rise. The
majority (approximately 70%) of the interview
respondents were aware of changes in
temperature and rainfall variabilities as impacts
of climate change. The resulting test shows that
the difference was statistically significant among
their responses (P< 0.01). Regarding climate
change consequences, 86.89% of the households
stated that climate change has negative impacts
on their agricultural production activities.
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Cassava farmers’ perception on climate changes: A case study in Van Yen district, Yen Bai province
Table 3. Farmer households’ perception of the platform of climate change
Percent of respondents (%)
p-
value*
Farmers’ perceptions of climate change (CC) and its impacts
1
0
2
3
4
5
CC is a natural phenomenon, e.g. global warming, melting
ice, and rising sea levels
0.20
32.58
48.16
19.06
0.015
0.018
0.001
CC is reflected in changes in the temperature, rain, and
natural disasters
0
0.20
1.43
30.12
11.27
51.43
57.38
18.24
29.51
CC has a great impact on agricultural production activities of
farmers
0.41
Note: Likert scale: 1 (totally disagreed) to 5 (totally agreed)
* p-value from Pearson chi Square-2 sided by area
Table 4. Farmer households’ perceptions of supporting climate actions
Percent of respondents (%)
Perceptions
p-value*
1
2
3
4
5
Adaptation plans related to climate change and disaster
prevention at district level
33.61
27.05
25.41
5.12
8.81
8.20
9.22
0.000
0.000
0.000
Policies to enhance adaptation to climate change and
33.20
11.89
21.52
42.01
31.35
4.71
4.10
disaster risk reduction for farmers
Some projects to help farmers adapt to climate change
33.81
and mitigate natural disaster risks
Note: Likert scale: 1 (totally unknown) to 5 (totally known)
* p-value from Pearson chi Square-2 sided by area
barren land, etc. Beneficiaries from these
programs were local people but not all. In
general, those who benefited from the
programs/projects were aware of what the local
government/non-government organizations were
implementing, others also understood through
social communication or media.
Farmers’
knowledge
depth
of
programs/policies/projects supporting climate
actions
Table 4 shows the survey results of farmers’
response to Van Yen’s activities on climate
change adaptation. Most farmers in this survey
had a homogeneous understanding of climate
change adaptation plans and disaster prevention
issued by the government. In general, the
respondents’ perceptions of government policies
and support agencies on climate change
adaptation were limited. Only 13.93% of
surveyed farmers knew climate change
adaptation plans and disaster prevention at the
district level. A majority (87.1%) of farmers did
not know the policies that support the
enhancement of climate change adaptation and
disaster risk reduction. Most farmers did not
know much about projects that could help them
build adaptive capacities and resilience to
climate change and mitigate natural disaster
risks. To address climate-related issues, Van Yen
district government had issued several climate
change adaptation strategies/programs, e.g.
sustainable farming on sloping land and greening
Farmers’ accessibility to weather-related
information
A good weather information system plays a
crucial role in farming systems. Useful weather
information is one of the factors that affect
farmers’ decision-making in farming (Reyes et
al., 2009; Simelton et al., 2017). In this research,
the results as shown in Figure 3 indicate that
farmers often received warnings of extreme
weather events (59.84%), daily weather forecast
news (69.67%), seasonal calendar (53.69%), and
natural disaster forecasts (56.77%). While
television was a usual source of climate
information, many used other technological
means available to receive forecast updates, such
as web-based applications which could be
accessed using smartphones and/or computers.
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706
Nguyen Hai Nui et al. (2020)
Figure 3. Farmers’ accessibility to weather-related information
Figure 4. Farmers’ experiences of extreme weather events
create a complex and dynamic information
environment.
However, weather forecasts did not win all
farmers' trust in the survey due to (i) their large
geographical coverages. A young farmer stated
that “the weather information usually targets the
entire region. It is vague in my specific location”;
(ii) The heterogeneity of respondents (i.e.
education, ethnicity, and age) could also be the
reason that not all people believed in weather
forecast information, which was confirmed by
previous studies such as Harris (2007) and Lazo
(2009); (iii) due to the variety of weather
Farmers’ experiences encountering extreme
weather events
Van Yen has a high level of vulnerability to
climate risks, mainly hot spells, acid rain,
drought, and cold spells. They have been greatly
affecting socio-economic activities and human
safety there (Bui et al., 2020).
Figure 4 lists some impacts of climate
phenomena in the study area. A larger number of
farmers (84.43%) pointed out that hot spells had
information
providers
and
multiple
communication channels, this situation might
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Cassava farmers’ perception on climate changes: A case study in Van Yen district, Yen Bai province
Figure 5. Significant pathways in the structural equation model
serious impacts on theire livelihood. Two
farmers stated that “In summer 2019, many trees
died due to temperatures reaching 40°C’ (male,
45); ‘heat has an effect on livestock, as buffalos
do not want to graze and spend time in the
shade’. Approximately 60% of the surveyed
households responded that droughts were having
negative effects on agricultural systems, lives,
and livelihoods alike. The following quotes
illustrate some of the famers’ responses “In the
first quarter of 2019, a period when plants
needed a lot of water to grow, I could not irrigate
due to lack of rain” (male, 55); “rice seedlings
had withered due to drought” (female, 43); ‘it
was hard for me to irrigate proactively as there
was no rain at all in early 2019’ (female, 35).
More than 80% of the interviewees reported that
acid rain had a weaker influence on their
livelihoods. Some said acid rains had negative
impacts on production, such as changed leaf
color of grapefruit and oranges, finally
destroying the harvests.
Structure equation model
SEM results (Figure 5) show that the model
is compatible with data research and conceptual
framework. Overall, weather-related information
had the largest influence on farmers' perception
of climate change (β = 0.277, P< 0.05). That is,
the more weather forecast information they
received, the more they perceived about climate
change. This result is in line with a previous
finding (Bloodhart et al., 2015). Moreover,
whether farmers perceived climate phenomena
impacts and whether they were aware of
government implementations about climate
change adaptation positively influenced farmers’
perception of climate change (β = 0.268, P< 0.05;
and β = 0.119, P< 0.05, respectively). These
findings correlate fairly well with those of Van
der Linden (2014) and Myers et al. (2013).
Household wealth rank had a larger direct effect
on farmers’ understanding of policies related to
climate change mitigation and adaptation (β =
0.223, P< 0.05) than farmers’ perception of
Vietnam Journal of Agricultural Sciences
708
Nguyen Hai Nui et al. (2020)
climate change (β = 0.119, P< 0.05). This finding
indicates that well-off farmers had a better
understanding of climate change and government
supports to tackle climate change.
“Scaling climate-smart villages in Yen Bai
province to promote implementation of climate-
smart agriculture and One Commune One
Product (OCOP) initiative of the National Target
Program on New Rural Development”.
The Irish Aid under the Embassy of Ireland
in Hanoi through the VIBE 2018.05 project “NUI
Galway – Vietnam National University of
Agriculture (VNUA) Vietnam Ireland Bilateral
Education Exchange (VIBE) Programme on
Conclusions
The results of this study showed that cassava
farmers, in general, perceived climate change’s
existence and its impacts. Among the three
independent variables, accessibility to weather
information had the greatest influence on
farmers’ perceptions (marginal value = 0.277),
followed by farmers’ experience of extreme
weather events (0.268) and their knowledge of
supporting programs/policies/projects (0.119).
Understanding these relationships is important
for future relevant research.
Climate
Resilient
Agriculture
and
Environmentally Sustainable Landscapes”.
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