coffee farmers´ awareness about climate change

14
Exploring coffee farmers’ awareness about climate change and water needs: Smallholders’ perceptions of adaptive capacity Sonia Quiroga a, *, Cristina Sua ´ rez a , Juan Diego Solı ´s b a Universidad de Alcala ´, Spain b Universidad Nacional Auto ´ noma de Nicaragua, Nicaragua 1. Introduction Climate change is set to modify the geography of coffee crop suitability in the coming decades (Glenn et al., 2013; Laderach et al., 2010, 2013; Rahn et al., 2013; Schroth et al., 2009). This is naturally related to potential damages and benefits that may arise in some countries, which will affect domestic and international policies, trading patterns, the use of resources, regional planning and consequently people’s welfare (Fischer et al., 2005; Lobell et al., 2005). Coffee cultivation engages over 100 million people in production and processing. Smallholder coffee farmers account for over 70% of this labour intensive crop. Deteriorating terms of trade and price volatility have historically threatened coffee production and these problems are exacerbated by the effects of changing climatic conditions. Prolonged droughts, rising temperatures or heavy rains can affect coffee plants directly, by affecting growing conditions, and indirectly, by providing favourable conditions for pests and diseases (Panhuysen and Pierrot, 2014). e n v i r o n m e n t a l s c i e n c e & p o l i c y 4 5 ( 2 0 1 5 ) 5 3 6 6 a r t i c l e i n f o Keywords: Climate change Crop production risk Coffee farmers’ adaptive capacity Nicaragua Water scarcity a b s t r a c t Nicaragua is one of the four countries most affected by climate change, and coffee production is expected to vastly shrink in some critical areas. This can have considerable effects on social structure since nearly a third of its working population depend on coffee for a living. Social perceptions of climate change and water pressures are a key issue in the public’s acceptance of adaptation measures. Furthermore, the existing risk for crop pro- duction is not necessarily correlated with the farmers’ awareness of that threat. This paper focuses on coffee producers’ perception of risk and adaptive capacity for coffee crops in Nicaragua in response to climate change and water availability. We aim to analyze how dependent the producers are on water resources, and if this reliance affects their perception of risk and their expectations with regard to public and private support for dealing with adaptation. A survey of 212 representative farmers of the national population of farms in the country’s two most important production areas was conducted for this purpose. We consider socio-economic and biophysical variables to explain the farmers’ perceptions. Our findings show that experience and technical capacity are relevant to the adaptive capacity although smallholders do not always show high concern and their expectations with regard to external support are very low. The paper can be useful to prioritize the measures necessary for a greater level of involvement from stakeholders. # 2014 Published by Elsevier Ltd. * Corresponding author. Tel.: +34 918856370. E-mail address: [email protected] (S. Quiroga). Available online at www.sciencedirect.com ScienceDirect journal homepage: www.elsevier.com/locate/envsci http://dx.doi.org/10.1016/j.envsci.2014.09.007 1462-9011/# 2014 Published by Elsevier Ltd.

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Page 1: Coffee farmers´ awareness about climate change

Exploring coffee farmers’ awareness about climatechange and water needs: Smallholders’ perceptionsof adaptive capacity

Sonia Quiroga a,*, Cristina Suarez a, Juan Diego Solıs b

aUniversidad de Alcala, SpainbUniversidad Nacional Autonoma de Nicaragua, Nicaragua

e n v i r o n m e n t a l s c i e n c e & p o l i c y 4 5 ( 2 0 1 5 ) 5 3 – 6 6

a r t i c l e i n f o

Keywords:

Climate change

Crop production risk

Coffee farmers’ adaptive capacity

Nicaragua

Water scarcity

a b s t r a c t

Nicaragua is one of the four countries most affected by climate change, and coffee

production is expected to vastly shrink in some critical areas. This can have considerable

effects on social structure since nearly a third of its working population depend on coffee for

a living. Social perceptions of climate change and water pressures are a key issue in the

public’s acceptance of adaptation measures. Furthermore, the existing risk for crop pro-

duction is not necessarily correlated with the farmers’ awareness of that threat. This paper

focuses on coffee producers’ perception of risk and adaptive capacity for coffee crops in

Nicaragua in response to climate change and water availability. We aim to analyze how

dependent the producers are on water resources, and if this reliance affects their perception

of risk and their expectations with regard to public and private support for dealing with

adaptation. A survey of 212 representative farmers of the national population of farms in the

country’s two most important production areas was conducted for this purpose. We

consider socio-economic and biophysical variables to explain the farmers’ perceptions.

Our findings show that experience and technical capacity are relevant to the adaptive

capacity although smallholders do not always show high concern and their expectations

with regard to external support are very low. The paper can be useful to prioritize the

measures necessary for a greater level of involvement from stakeholders.

# 2014 Published by Elsevier Ltd.

Available online at www.sciencedirect.com

ScienceDirect

journal homepage: www.elsevier.com/locate/envsci

1. Introduction

Climate change is set to modify the geography of coffee crop

suitability in the coming decades (Glenn et al., 2013; Laderach

et al., 2010, 2013; Rahn et al., 2013; Schroth et al., 2009). This is

naturally related to potential damages and benefits that may

arise in some countries, which will affect domestic and

international policies, trading patterns, the use of resources,

regional planning and consequently people’s welfare (Fischer

* Corresponding author. Tel.: +34 918856370.E-mail address: [email protected] (S. Quiroga).

http://dx.doi.org/10.1016/j.envsci.2014.09.0071462-9011/# 2014 Published by Elsevier Ltd.

et al., 2005; Lobell et al., 2005). Coffee cultivation engages over

100 million people in production and processing. Smallholder

coffee farmers account for over 70% of this labour intensive

crop. Deteriorating terms of trade and price volatility have

historically threatened coffee production and these problems

are exacerbated by the effects of changing climatic conditions.

Prolonged droughts, rising temperatures or heavy rains can

affect coffee plants directly, by affecting growing conditions,

and indirectly, by providing favourable conditions for pests

and diseases (Panhuysen and Pierrot, 2014).

Page 2: Coffee farmers´ awareness about climate change

e n v i r o n m e n t a l s c i e n c e & p o l i c y 4 5 ( 2 0 1 5 ) 5 3 – 6 654

Changes to crop productivity and production suitability as

a result of global warming have been extensively predicted for

the coming future (Trnka et al., 2011, 2014; Boko et al., 2007;

Anwar et al., 2013; Van Vuuren et al., 2007), with many places

in Latin America set to be hotspots (Flores et al., 2002; Tucker

et al., 2010; FAO, 2011). In the case of Mesoamerica, and

particularly Nicaragua, climate change may reduce coffee crop

suitability by up to 40% (Glenn et al., 2013; Laderach et al., 2010)

(Fig. 1).

Mesoamerican countries are especially concerned with the

potential local and global impacts of climate change over the

coming decades. Nicaragua, in particular, is already one of the

four countries most affected by climate change, according to

the 2014 Global Climate Risk Index (Kreft and Eckstein, 2013),

and these changes will affect domestic and international

policies, trading patterns, competitiveness for water

resources, regional planning and farmers’ welfare. Nearly a

third of its working population, about 750,000 people, depend

on coffee directly or indirectly for a living. Coffee provides 20%

of GDP and represents 20–25% of export revenues in

Nicaragua. These potential losses have been estimated to

represent almost 20% of Nicaragua’s GDP (Flores et al., 2002),

suggesting that the country’s coffee production is expected to

shrink by 82% between 2010 and 2050 (Laderach et al., 2013).

However, some opportunities to adapt do exist. According

to the Intergovernmental Panel on Climate Change (IPCC)

conceptions, adaptive capacity is defined as a system’s ability

to adjust to climate change in order to reduce or mitigate

potential damage. Adaptive capacity is dynamic, and

depends among other factors on natural and artificial assets,

social benefits and networks, human capital and institutions,

governance, national income, health and technology. Adap-

tation to climate change includes adjustments in natural or

human systems in response to actual or expected climatic

risk, which moderate harm or exploit beneficial opportunities

(IPCC, 2007). These adjustments can be planned or

Fig. 1 – Map of change in suitability for coffee production in Me

Source: International Center for Tropical Agriculture, CIAT, A.Ei

autonomous (IPCC, 2001). Potential responses to climate

change effects on agriculture include farm level adaptation,

through capacity building, financial transfer tools, and

migration to more suitable areas (Iglesias et al., 2012; Anwar

et al., 2013; Baca et al., 2014; Boko et al., 2007). In particular,

coffee production is expected to suffer important migrations

towards southern regions (Laderach et al., 2013).

Unfortunately, there are many cultural, technical and

social obstacles to implementing adaptation measures, and

farmers’ perceptions of climate change risks and their

adaptive capacity are essential for eliminating some of these

barriers. Adaptation to climate change requires that farmers

using traditional techniques of agricultural production first

notice that the climate is changing and that this represents a

threat to their production (Maddison, 2007). This paper does

not attempt to review the current evidence of climate change

impacts on coffee production, but rather to address the

conditioning factors affecting farmers’ perception of their own

adaptive capacity. In this context, farmers’ perceptions about

climate change impacts and their expectations with regard to

receiving resources from external agents – such as govern-

ment, cooperatives or NGOs – may be crucial to understanding

whether coffee farmers adaptation is likely to take place

mostly on an individual basis, or whether they will be

confident about some kind of external intervention (public

or private) designed to promote the adaptation process. In this

paper we explore farmers’ expectations about receiving

external support to promote adaptation measures. Here we

analyze expectations with regard to public support from the

government through any of its programmes and the private

support through farmers associations or cooperatives and

NGOs. We do not consider the role of private external firms,

such as banks, or private insurance companies that can play

an important role as facilitators of valuable financial tools.

Among the current public programmes, Nicaragua has a Social

Safety Net programme designed to address both current and

soamerica.

[email protected], 2014.

Page 3: Coffee farmers´ awareness about climate change

e n v i r o n m e n t a l s c i e n c e & p o l i c y 4 5 ( 2 0 1 5 ) 5 3 – 6 6 55

future poverty via cash transfers intended for households

living in extreme poverty in rural areas (Maluccio, 2005) and

other programmes such as U.S. Agency for International

Development (USAID) programme or the German govern-

ment’s assistance agency (KDR) (Vakis et al., 2004). Also, NGOs

are working to develop a market situation that is sustainable

for workers and the environment (Linton, 2005).

Although coffee farmers still tend to perceive climate risks

as less urgent than those posed by market volatility, declining

prices and institutional changes (Eakin et al., 2006; Gay et al.,

2006), important direct and indirect impacts are likely to occur

in response to climate change, with drivers that are diverse

and complex. For example, increased temperatures directly

affect crop suitability and productivity, and may also favour

the progress of pests and diseases; erosion may determine

quality, etc. Among other factors, water scarcity emerges as

one of the key stressors for coffee suitability in this area

(Laderach et al., 2013). Over the next decades, Nicaragua will

increasingly be affected by global climate change and most

models coincide in predicting a rainfall decrease of more than

100 mm by 2050, which will have a major impact on

Nicaragua’s coffee exports and life conditions in rural areas

(Baca et al., 2014; Anderson et al., 2008; IPCC, 2007).

Water is important for coffee production, and information

about water is relevant to farmers’ perceptions. Nicaragua is

affluent in terms of overall water resources and water for use,

the latter being in excess of 38,668 mm per capita per year

(FAO-Aquastat, 2013). Although this level is above average for

Mesoamerican countries, contamination has meant that the

quality of water is very low, and thus water security is actually

quite low as well (OECD, 2010), water security being the

reliable availability of an acceptable quantity and quality of

water for health, livelihoods and production, coupled with an

acceptable level of water-related risks (Grey and Sadoff, 2007).

This is in part due to low financial resources for maintaining

an adequate quality of water resources; as a result of

governance problems affecting integral water resource man-

agement, this issue clearly influences the adaptation capacity

(Quiroga et al., 2011). In Nicaragua, the 1999–2001 droughts

further compounded the problem of low coffee prices. The

effects are complex and clearly affect small-scale farmers. For

example, in the tropical dry regions, including the northern

departments that we consider in this study, the farmers did

not harvest their subsistence crops that they mix with coffee,

further increasing vulnerability (Bacon, 2005).

The main objectives of this paper are: (i) to understand if

current crop water needs and water risk concerns have an

effect on farmers’ adaptive capacity perception, (ii) to

determine farmers’ expectations with regard to receiving

some public or private funds for adaptation endorsement,

especially related to government, farmers’ cooperatives and

NGO support, (iii) to analyze the sensitivity of these percep-

tions to certain structural factors, such as the labour force and

technology. The article is organized as follows. The second

section provides general and detailed information on our

methodological steps. The third section describes the results

of the estimated adaptive capacity perceptions for two main

coffee production regions in Nicaragua. This section also

shows the estimates of marginal effects and probabilities

forecast for adaptation support perceptions in terms of labour

force and water needs. The final section presents the

conclusions of the paper.

2. Methods

2.1. Methodological framework

The methodological approach used here integrates different

components affecting individuals’ perceptions about adaptive

capacity in order to identify their main drivers. The method-

ology includes the following three steps: (i) we estimate

ordered probit models to characterize the main drivers

affecting farmers’ perceptions of their own adaptive capacity.

Ordered probit models have proven useful as a public

participation method to evaluate the effects of socio-econom-

ic characteristics on stakeholder insights, and particularly to

understand individual perceptions about environmental

issues and climate change concern (Bosselmann, 2012; Drake

et al., 2013; Garcıa de Jalon et al., 2013; Layton and Brown, 2000;

Maddison, 2007). Here we analyze the drivers for adaptive

capacity perceptions. Our analysis process includes the link

between objective factors – such as labour or capital – and

subjective factors – such as current crop water needs,

expectations about climate change or water scarcity risk –

so as to analyze current farmers’ perceptions. For this purpose,

we estimate the marginal effects of the considered determi-

nants on the estimated probability of farmers’ responses. (ii) In

a second phase, we try to distinguish between the different

sources of expected funding for climate change adaptation. To

do so, we analyze the likely role of the government, farmers’

cooperatives and NGOs. (iii) Finally, we simulate some

potential structural adjustments. We use the estimated

models to simulate the cumulative probability of farmers’

responses in terms of changes to labour force and water needs.

Fig. 2 shows a summary of this analysis structure.

2.2. Data collection

Data collection was done through a survey. For the sample

selection process, we considered the population of 1624 coffee

farmers from the departments of Jinotega and Estelı, who are

registered at the Ministry of Agriculture and Forestry of

Nicaragua (MAGFOR). We chose these departments because

coffee production is centred in the northern part of the central

highlands north and east of Estelı, and also in the hilly volcanic

region around Jinotega. From this population, a stratified

random sampling proportional to farmer type was assigned.

The representative sample size was estimated by considering

a sampling error limit of 6.34% and a 95% confidence level. The

sample size subsequently contained 215 farmers. Complete

information was obtained from 212 farmers. Table 1 shows the

sample distribution in the considered departments.

The main objective of the questionnaire was to obtain

information about the coffee farmers’ perceptions of their

adaptive capacity, as well as the socio-economic variables

affecting this perception. We divided the questionnaire items

into two separate categories: (i) general characteristics of farm

exploitation, including data on the labour force, capital, etc.

and (ii) subjective opinion or perceptions on climate change

Page 4: Coffee farmers´ awareness about climate change

Fig. 2 – Description of the study.

e n v i r o n m e n t a l s c i e n c e & p o l i c y 4 5 ( 2 0 1 5 ) 5 3 – 6 656

risks and adaptive capacity. Farmers were asked to rate the

relevance of certain items associated with perceptions on

climate change risks and adaptive capacity using an equidis-

tant four-point Likert scale.

Data collection was conducted in several steps: (i) organi-

zation and management; (ii) focus group and pilot tests; and

(iii) face-to-face field surveys. A detailed analysis of these

steps is given below.

(i) For the organization and management of the field survey

collection, the first step was to present a research proposal

and work plan to authorities at the Universidad Nacional

Autonoma de Nicaragua (UNAN-Leon). The aim was to

achieve the institutional endorsement needed to obtain

technical support from the MAGFOR delegates at the

national and departmental levels.

(ii) We conducted a focus group session in which a number of

experts in the Ministry were informed about the goals of

our analysis. They were asked about the target population

in the selected departments, and asked for comments and

suggestions on a draft questionnaire. The valuable

information they provided (i.e. farmers registration lists

Table 1 – Sample distribution among the departments.

Departments Total numberof registered

farmers

Percentageof total

Estelı 1020 0.63

Jinotega 604 0.37

Total 1624 1.00

by municipalities, important amendments to the ques-

tions, etc.) was considered when improving the data

collection. Pilot testing of the survey instrument was

conducted prior to the main survey. Along with expert

judgement, the results from the pilot study were used to

polish the questions asked in the main survey. The pilot

tests were used to evaluate how a sample of people – five

technicians and five farmers – from the same sector

responded to the questionnaire.

(iii) The survey process was carried out between 5 March and

10 April 2013 in two of the three main coffee production

departments in Nicaragua – Estelı and Jinotega. There are

a total of 1624 farmers in these two departments. From the

total population, a sample of 212 farmers was randomly

selected by considering the current distribution of the

farmer population in terms of size, i.e. the same

proportion of small, medium and large farms. We used

a Likert scale for most of the questions. Interviews were

conducted face-to-face on the farms, and took an average

of 35 min to complete. The first 5 min were used to explain

the purpose of the survey research, i.e. that it was non-

commercial and non-political.

Sampleselectedfarmers

Successfulsurveys

% Completed

135 133 95.5

80 79 98.8

215 212 98.6

Page 5: Coffee farmers´ awareness about climate change

e n v i r o n m e n t a l s c i e n c e & p o l i c y 4 5 ( 2 0 1 5 ) 5 3 – 6 6 57

2.3. Description of variables

Table 2 describes the variables included in this study, as

well as the descriptive statistics of the data. We have

included reported data about harvested area, labour force,

labour experience, capital availability, water needs, and

some variables analysing climate risk concern for the

212 individual farmers. Descriptive statistics include

the mean and standard deviation for the quantitative

Table 2 – Rationale, description and descriptive statistics of thquantitative variables and frequency of qualitative variables).

Name Rationale Description

Dependent variables

Y1i Adaptive capacity

perceptions

Do farmers perceive that they

to adapt to cope with the po

climate change? (Annex 1, Q14

Y2i Perceptions of

adaptation

government funds

Do farmers perceive that they

support (funding) from the go

with the potential impacts? (A

Y3i Perceptions

of farm adaptation

association funds

Do farmers perceive that they

support (funding) from the far

cope with the potential impact

(Annex 1, Q18). (*)

Y4i Perceptions of

adaptation NGOs

funds

Do farmers perceive that they

support (funding) from the NGO

potential impacts?

(Annex 1, Q19). (*)

Independent variables

Li Farm size, labour force Total workers hired by the farm

Techi Technology used Total number of machines (An

Lexpi Labour experience Workers with experience equa

years (Annex 1, Q7)

Erosioni Erosion risk

perception

Farmers description of potenti

their farm (Annex 1, Q11).

CCriski Long-term impacts

of climate change

awareness

Do farmers think that climate

will affect their farm in the lon

10 years from now?) (Annex 1,

Wi Current water

needs

Farmers description of current

coffee production

(Annex 1, Q15)

Wriski Water scarcity

expectations due

to climate change

Do farmers think climate chan

that is affecting or is going

availability for coffee productio

(*) Measured with the Likert scale.

variables, and the frequency of the qualitative dummy

variables.

The survey data shown in Table 2 indicates that about

31.31% of the farmers show no adaptive capacity at all, while

30.84% show a high capacity perception to adaptation. About

half of the farmers surveyed do not have any perception of

support in terms of the government, farmers’ cooperatives

and NGOs funding for climate change adaptation. The

majority of farmers do not have perceptions of erosion risk

e variables (mean and standard deviation for the

Unit Mean Stddev.

have the capacity

tential impacts of

) (*)

0 = no capacity 31.31

1 = low capacity 16.82

2 = medium capacity 21.03

3 = high capacity 30.84

will have the

vernment to cope

nnex 1, Q17) (*).

0 = no support 53.02

1 = low support 13.02

2 = medium support 13.02

3 = high support 20.93

will have the

ms cooperatives to

s?

0 = no support 66.98

1 = low support 18.60

2 = medium support 12.56

3 = high support 1.86

will have the

s to cope with the

0 = no support 56.74

1 = low support 20.47

2 = medium support 14.42

3 = high support 8.37

. (Annex 1, Q4) Number 12.22 11.00

nex 1, Q8) Number 6.16 6.40

l to or more than 4 1 = Yes 83.72

0 = No 16.28

al erosion risk on 1 = Yes 19.53

0 = No 80.47

change impacts

g term? (More than

Q13)

1 = Yes 29.76

0 = No 70.24

water needs for High 53.02

Medium 19.08

Low 27.90

ge is something

to affect water

n? (Annex 1, Q16)

1 = Yes 73.02

0 = No 26.98

Page 6: Coffee farmers´ awareness about climate change

e n v i r o n m e n t a l s c i e n c e & p o l i c y 4 5 ( 2 0 1 5 ) 5 3 – 6 658

due to climate change or long-term impacts of climate change.

However, almost 53% agreed that the current need for

irrigation is high, and moreover, almost 73% believe that

there will be water scarcity due to climate change.

2.4. Econometric model for farmers’ perception estimates

In order to examine the factors that influence the farmers’

perceptions, this study used an ordered probit model (Greene,

2012) as shown in Eq. (1):

Y�i ¼ b0Xi þ ei (1)

where Y�i is a latent measure of climate change adaptive

capacity perceptions; Xi is a vector of factors that influence

the farmers’ perceptions; b is a vector of parameters to be

estimated; and ei is the error term and is assumed to have

standard normal distribution. Since we cannot observe Y�i , we

can only observe the categories of responses as follows:

Y ¼

1 if Y�i � 02 if 0 < Y�i � m1

3 if m1 < Y�i � m2

4 if m2 � Y�i

8>><>>:

(2)

The maximum likelihood technique that provides consis-

tent and asymptotic estimators can be used to jointly estimate

the vector of parameters b and thresholds m. Thresholds m

indicate an array of normal distribution related to the definite

values of the explanatory variables. Parameters b denote the

influence of variation in response variables on the principal

scale. According to Greene (2012), the positive sign of

parameter b implies greater adaptive capacity as the value

of related variable increases. To complete the process of

variable selection, we tested for collinearity problems.

The probabilities of the ordered probit model estimated in

this study are shown below:

PrðYi ¼ 0jXÞ ¼ Fð�b0XiÞPrðYi ¼ 1jXÞ ¼ Fðm1 � b0XiÞ � Fð�b0XiÞPrðYi ¼ 2jXÞ ¼ Fðm2 � b0XiÞ � Fðm1 � b0XiÞPrðYi ¼ 3jXÞ ¼ 1 � Fðm2 � b0XiÞwhere F is the cumulative density function (CDF) of a standard

normal random variable. For all probabilities to be positive, we

must have: 0 < m1 < m2.

The marginal effects of changes in response variables are

obtained once coefficients of the ordered probit model are

estimated:

@PrðYi ¼ 0 XÞj@X

¼ �fðb0XiÞb

@PrðYi ¼ 1 XÞj@X

¼ ½fð�b0XiÞ � fðm1 � b0XiÞ�b

@PrðYi ¼ 2 XÞj@X

¼ ½fðm1 � b0XiÞ � fðm2 � b0XiÞ�b

@PrðYi ¼ 3 XÞj@X

¼ fðm2 � b0XiÞb

2.5. Water needs scenarios

Under climate change, drought events are likely to increase in

frequency, duration and intensity, thereby affecting crop

production.

In the considered departments (Estelı and Jinotega), water

is mainly superficial and unregulated, and is therefore directly

related to run-off, which varies greatly from year to year

(between 1500 and 6000 mm per year). An aqueduct that would

increase access to an improved water supply in the city of

Estelı in the next 25 years is currently being completed with

the aid of EU funds. However, the main priority of this project

is increasing the urban supply to match expected increases in

population over time, and thus the water needed for irrigation

in rural areas will not be affected (WHO and OPS, 2006).

Providing smallholder coffee farmers with access to water is

increasingly difficult due to environmental degradation and

climate change, in addition to distortions in property rights

and the inappropriate use of water resources. The experience

levels of farms are a key factor in improving water manage-

ment in order to achieve optimal use of water resources. The

reason is the role that water plays in the growth and

development of the coffee plant. The experience can be used

for better water management (Carr, 2001).

As a result of the increased scarcity of water supplies, water

management and water policy becomes even more crucial,

and farmers’ awareness of future water risks represent a

driving factor for water management improvement. We do not

analyze climate change scenarios such as run-off here, but we

do explore policy implications in which water risk perception

is set to increase. Information about the consequences of

changes to water allocation for irrigation and changes on

irrigated land is relevant during the decision-making process.

Here we present methods to deal with these alternatives,

including: (i) an increase in coffee production water needs and

(ii) an increase in the water risk concern due to climate change.

We present the results for the different types of perception of

water limitations, as well as what we think is the first

necessary step to discuss the synergy between potential

adaptation and water policies.

3. Results and discussion

3.1. Adaptive capacity perceptions responding to currentwater needs

Table 3 shows the results from the ordered probit model on the

estimation of farmers’ perception of adaptive capacity drivers.

The magnitude and sign of the estimated coefficients do not

have a direct impact in this probit model, but we can say that

an increase in a variable with a positive coefficient increases

the probability of the dependent variable being in the highest

category (high adaptive capacity), yet decreases the probabili-

ty of it being in the lowest category (no adaptive capacity). The

relationship between farmers’ perceptions of adaptive capac-

ity and current water needs is clearly stated. This further

underlines the idea of water instruments being crucial to deal

with climate change adaptation measures. Some other

variables, such as farm characteristics, are also important,

as is awareness of global warming. Table 4 shows the marginal

effects of the estimated determinants affecting the probability

of the farmers’ responses. The marginal effects are calculated

for each outcome by considering the mean of the continuous

variables and the zero value of the dummy variables. This

Page 7: Coffee farmers´ awareness about climate change

Table 3 – Ordered probit regression on farmers’ percep-tions of adaptive capacity drivers.

Dependentvariable: Y1i

Coef Std. err

Log(L) 0.2306** 0.1104

Log(Tech) �0.2035** 0.1013

Lexp �0.1530 0.2606

Erosion 0.4878** 0.2606

CCrisk 0.7410*** 0.1719

WH �1.7030*** 0.3121

WM �1.4453*** 0.2852

Wrisk �0.3072 0.1906

Log likelihood �229.82

LR x2(8) 112.03***

* Significant coefficient at 10%.** Significant coefficient at 5%.*** Significant coefficient at 1%.

e n v i r o n m e n t a l s c i e n c e & p o l i c y 4 5 ( 2 0 1 5 ) 5 3 – 6 6 59

marginal effect provides the continuous variables – a measure

of the relative effect that a unit increase in the explanatory

variables will have on the probability of being in either group;

while for the dummy variables they provide a measure of the

effect that belonging to a category has on the probability of

being in either group.

As expected, the estimated models suggest that size

(measured by the logarithm of the number of workers) and

technology (measured by the logarithm of the amount of

machinery) are important factors in explaining farmers’

perceptions of adaptive capacity. They are both statistically

significant at a 1% level, but each has a different sign. This

suggests that as the number of workers on a farm increases

(not in a linear way), the perception of adaptive capacity also

increases. On the other hand, as farms increase their

technology, the perception of adaptive capacity decreases.

Therefore, concentration processes based on increasing the

labour force are likely to favour adaptive capacity in terms of

farmers’ perceptions. However, the greater the level of

technical development, the lower the perception of being

able to adapt to climate change. Since technology is widely

Table 4 – Estimated marginal effects on adaptive capacity per

Mar

Pr(outcome 0) = 0.029 Pr(outcome 1) = 0.061

Coef Std. err Coef Std. er

Log(L) �0.0151 0.0125 �0.0222* 0.0125

Log(Tech) 0.0133 0.0124 0.0196 0.0123

Lexpa 0.0116 0.0186 0.0158 0.0261

Erosiona �0.0202 0.0206 �0.0359 0.0254

CCriska �0.0245 0.0233 �0.0465* 0.0278

WHa 0.3928*** 0.0767 0.1581*** 0.0527

WMa 0.2956*** 0.0870 0.1555*** 0.0440

Wriska 0.0268 0.0255 0.0337 0.0231

a Calculated for discrete change of dummy variable from 0 to 1.* Significant coefficient at 10%.** Significant coefficient at 5%.*** Significant coefficient at 1%.

considered as a necessary factor for coping with climate

change risks (Quiroga and Iglesias, 2009; Smit et al., 2000;

Vedenev et al., 2007), this can be seen as paradoxical result.

In our view, however, two factors can explain this percep-

tion: (i) if the current level of technology is higher, the cost

of improvement is also greater, and farmers will be aware of

this and aware of their inability to achieve this and (ii) even

though the correlation between technology and climate

change awareness is low, it is positive, so the most

technically equipped farms also have more information

about climate change potential impacts, and are thus more

worried about their adaptive capacity. We have tested

alternative specifications of the model, including the farm

size (in hectares), as factors affecting perceptions, but we

did not find a significant effect. This is probably because

there are not enough differences in farm size between the

farmers in the region.

Erosion risk perception due to climate change and the

perception of the long-term impacts of climate change

increase the perception of adaptive capacity in farmers. For

instance, if a farmer has a perception of the risk of erosion due

to climate change, the probability of observing high adaptive

capacity increases by 0.114 when keeping the other variables

constant; whereas having a perception of the long-term

impacts of climate change increases the probability of

observing a high adaptive capacity by 0.198.

Current water needs is a crucial factor for farmers’

perception of adaptive capacity, as seen in Tables 3 and 4.

As suggested by the Wald test (x2(2) = 31.4), we can reject the

hypothesis that parameters are jointly zero (H0:

bWH¼ bWM

¼ 0), i.e. that having different levels of current

water needs does not affect adaptive capacity perceptions. As

these variables present negative signs and are significant in

the regression, we can conclude that when current water

needs are low, farmers are more conscious of their adaptive

capacity. A similar conclusion can be observed for the effect of

water scarcity expectations due to climate change: the more

worried about climate change farmers are, the lesser their

perceptions of adaptive capacity.

ceptions.

ginal effects

Pr(outcome 2) = 0.213 Pr(outcome 3) = 0.697

r Coef Std. err Coef Std. err

�0.0430* 0.0224 0.0803** 0.0376

0.0379* 0.0197 �0.0708* 0.0370

0.0278 0.0489 �0.0552 0.0917

�0.0885** 0.0432 0.1445* 0.0813

�0.1265*** 0.0352 0.1976** 0.0774

0.0295 0.1012 �0.5803*** 0.1127

0.0702 0.1043 �0.5212*** 0.0997

0.0537 0.0363 �0.1142 0.0722

Page 8: Coffee farmers´ awareness about climate change

Table 5 – Ordered probit regression on farmers’ perceptions of adaptation funds by source.

Government funds (Y2i) Farms association (Y3i) NGOs (Y4i)

Coef Std. err Coef Std. err Coef Std. err

Log(L) 0.3176*** 0.1166 �0.1684 0.1196 0.1008 0.1114

Log(Tech) 0.0624 0.1023 �0.0561 0.1066 0.0049 0.0998

Lexp �0.9909*** 0.2251 �0.4606** 0.2291 �0.4014* 0.2174

Erosion �0.1236 0.2503 0.3520 0.2469 0.1204 0.2385

CCrisk 0.5676*** 0.1947 0.2106 0.2021 0.2801 0.1882

WH 1.2191*** 0.2839 1.3760*** 0.2953 1.3315*** 0.2744

WM 1.4880*** 0.2506 1.0613*** 0.2680 1.0627*** 0.2427

Wrisk �0.5103** 0.2001 �0.0523 0.2052 �0.2101 0.1922

Log likelihood �214.13 �178.47 �223.67

LR x2(8) 82.89*** 35.34*** 37.59***

* Significant coefficient at 10%.** Significant coefficient at 5%.*** Significant coefficient at 1%.

Fig. 3 – Cumulative probability distribution of expected

adaptation support from the government, farmers’

cooperatives and NGOs.

e n v i r o n m e n t a l s c i e n c e & p o l i c y 4 5 ( 2 0 1 5 ) 5 3 – 6 660

3.2. Factors affecting adaptation policy expectations interms of funding sources

Table 5 shows the results of the estimated ordered probit

models used to explain the influence of water needs on

adaptation funds expectations when responding to a wide

range of variables. The government, farmers associations and

NGOs’ cooperation with climate change adaptation is ana-

lyzed in terms of farmers’ perceptions, and can largely be

explained by current water needs. Labour experience is also an

important factor determining public support. As outlined in

our methodological approach, we tested the adequacy of the

functions to represent farmers’ perceptions.

Fig. 3 shows the estimated cumulative probability distri-

bution of expected adaptation support from the government,

farmers’ cooperatives and NGOs. We can see that, despite the

differences, farmers are generally more confident about

government funding than about other sources, since there

is a greater probability of expected public support. We can

observe in Fig. 3 that the predicted probabilities for farmers’

cooperatives and NGOs for the low, medium and high support

categories tend to be less than 0.25. NGOs aim to influence

social responsibility and market capitalism (Linton, 2005) and

coffee cooperatives seek to develop exports and coffee

processing services aimed at differentiated markets, but

coffee farmers do not perceive that there will be funds

specifically allocated to support climate change adaptation.

The high expectation for governmental support can be

explained by the government’s promotion of policies aimed

at increasing smallholders’ access to credits in recent years

(2007–2011). The Banco de Fomento – a state institution that

manages farmers’ credits – has increased Rural Development

Credit Funds in the last few years, which constitutes an

important financial support to smallholders (i.e. in 2010, credit

concessions to smallholder coffee farmers grew 1.6 times

more than in earlier periods) (PNDH, 2012). As well, the Social

Safety Net programme was designed to cash transfers aimed

at households living in extreme poverty in rural areas

(Maluccio, 2005).

Table 6 shows the estimated marginal effects of govern-

ment funding expectations. We can see that the bigger the

farm size, the lower the expectation of perceiving government

support. Technology is also negatively affected. Farmers more

concerned about climate change risks and who have high and

medium current water needs are less confident that public

policies or funds will sustain climate change adaptation.

Farm size (measured by the logarithm of number of

workers) is an important factor in adaptation to government

funding perception (but not in the case of the other funding

Page 9: Coffee farmers´ awareness about climate change

Table 6 – Estimated marginal effects of adaptation to government funding perception.

Marginal effects

Pr(outcome 0) = 0.516 Pr(outcome 1) = 0.175 Pr(outcome 2) = 0.154 Pr(outcome 3) = 0.155

Coef Std. err Coef Std. err Coef Std. err Coef Std. err

Log(L) �0.1266*** 0.0465 0.0148 0.0173 0.0362** 0.0165 0.0756** 0.0368

Log(Tech) �0.0249 0.0408 0.0029 0.0054 0.0071 0.0116 0.0148 0.0254

Lexp 0.3327*** 0.0920 �0.0922*** 0.0274 �0.1080*** 0.0318 �0.1324** 0.0663

Erosiona 0.0490 0.0991 �0.0069 0.0152 �0.0145 0.0295 �0.0276 0.0564

CCriska �0.2171*** 0.0732 �0.0013 0.0301 0.0463 0.0288 0.1721** 0.0706

WHa �0.3968*** 0.1065 �0.0586 0.0417 0.0298 0.0525 0.4257*** 0.0906

WMa �0.4422*** 0.1056 �0.0877** 0.0435 0.0032 0.0602 0.5267*** 0.0738

Wriska 0.1930** 0.0766 �0.0406* 0.0235 �0.0610** 0.0256 �0.0914* 0.0506

* Significant coefficient at 10%.** Significant coefficient at 5%.*** Significant coefficient at 1%.a Calculated for discrete change of dummy variable from 0 to 1.

e n v i r o n m e n t a l s c i e n c e & p o l i c y 4 5 ( 2 0 1 5 ) 5 3 – 6 6 61

sources). It is positive and statistically significant at a 1% level.

This suggests that as the number of workers on a farm

increases (not in a linear way), their perception of adaptation

to government funding also increases. As a result, when farms

are bigger in terms of labour force, they are more confident

about government support. This is surprising given that the

government’s rural development policy is now primarily

focused on small producers. Therefore, the more the labour

experience (Lexp), the less the perception on counting on

funding for adaptation support. Current water needs are also

important in determining farmers’ perception of adaptation

funds expectation (see Tables 5 and 6). We can reject the

hypothesis that the parameters are jointly zero (H0:

Table 7 – Potential benefits of adaptation measures, by instru

Instruments Adaptation measures Potential fundingsources

Local capacity

building

Shadow crop planting; fight

crop diseases; changes in

harvesting dates and

processing; water storage

Farms

Government

Cooperatives

NGOs

Financial

transfer tools

Crop insurance programmes Government

Cooperatives

Financial

transfer tools

Micro-credit programmes NGOs

Government

Cooperatives

Financial

transfer tools

Crop rotation Farmers

Alternative

coffee markets

Introduction of organic

and Fair

Trade coffees

NGOs

Cooperatives

Farmers

Alternative

coffee markets

Eco-labels Government

Alternative

coffee markets

High quality gourmet

coffee and sustainability

Cooperatives

Farmers (for

example through

Specialty Coffee

Association of

America)

Changes in

agro-climatic

zones

Migration to southern

areas

Farmers

bWH¼ bWM

¼ 0) in the three specifications, as suggested by

Wald tests (x2(2) = 35.5 for the government funds model,

x2(2) = 22.6 for the farm association funds model and

x2(2) = 25.8 for the NGOs funds model). As these variables

present positive signs and are significant in the estimation, we

can conclude that when current water needs are higher,

farmers are more convinced about funds expectations. For

instance, if farmers have high current water needs the

probability that they will perceive more support from the

government increases by 0.426 when keeping the other

variables constant.

Our results suggest that bigger farms with higher current

water needs are those perceiving more potential for public

ment and type of support requirements.

Supportrequirements

Adaptation potentials

Public

Private

Biodiversity conservation, hurricane

protection, productivity increase,

avoid losses produced by infections,

reduce water pressures

Private

Public

Reduction of income vulnerability

Private

Public

To cope with extreme events and

natural disasters in the short term

Autonomous Diversification of incomes to diminish

losses associated with climate risk

and coffee markets’ volatility

Private

Autonomous

Development of markets and reduce

price volatility

Public Reduce biodiversity losses and land erosion

Private

Autonomous

Promote the orientation to high quality

coffee to reduce vulnerability through

a more established demand

Autonomous Avoid the productivity losses by

changing to more suitable areas

Page 10: Coffee farmers´ awareness about climate change

e n v i r o n m e n t a l s c i e n c e & p o l i c y 4 5 ( 2 0 1 5 ) 5 3 – 6 662

support. Support from farmers associations or cooperatives

and NGOs is really low in general. Table 7 summarizes the

potential benefits of adaptation for coffee production in the

region and its classification by type of support requirements.

Since the more confident the farmers are about the source of

funding the more acceptable the measures will be, we can

conclude that the measures including public or autonomous

adaptation is more likely to be successful in Nicaragua. Private

support should make an effort to involve stakeholders’ needs.

3.3. Current water needs and water risk perceptionscenarios

In this section, we simulate some potential responses to

structural adjustments in terms of current water needs and

water risk perception scenarios. Farmers’ responses to

changes in labour force (size) and technology were simulated

for the different levels of current water needs and water risk

perception. Figs. 4 and 5 plot the predicted probabilities for

each outcome and the different current water needs against

labour force and technology, respectively, for the two

scenarios of water risk perceptions. The graphs for low

current water needs indicate the maximum probability for

high adaptive capacity perspectives. We can observe how this

probability increases as the labour force increases, but then

decreases with technology. When the current water needs are

medium or high, then the maximum probability is a feeling of

not having any adaptive capacity, which decreases as the

0.000.100.200.300.400.500.600.700.800.901.00

0 10 20 30 40 50 60 70

Prob

abili

ty

Labou r force

0.000.100.200.300.400.500.600.700.800.901.00

0 10 20 30

Prob

abili

ty

Labou r for

0.000.100.200.300.400.500.600.700.800.901.00

0 10 20 30 40 50 60 70

Prob

abili

ty

Labou r force

0.000.100.200.300.400.500.600.700.800.901.00

0 10 20 30

Prob

abili

ty

Labou r for

No

Pr( L

(a) Farmers witho ut water risk percep�on

Low water needs

Low water needs

Med wate

Med wate

(b) Farmers with water risk percep�on

Pr( No capacity) Pr( Medium capacity)

Fig. 4 – Probability sensitivity to labour force variations for differ

(0, 1).

labour force increases but increases with technology. Being

aware of water risks reduces the probability of feeling a high

capacity to adapt in every scenario. It can be noted that for

farmers with current high water needs, sensitivity to size and

technology is low. This means that their low expectations as to

their adaptation capacity vary slightly when the structural

factors alter; they are more concerned about the climate risks.

As we have mentioned, Nicaragua is a country with high

vulnerability to global change: it is susceptible to risks and

dangers relating to people, biodiversity and natural resources,

which have irreversible long-term effects. By aiming to

improve land use distribution in a sustainable way, regional

and local governments have implemented general policies

relating to environmental conservation, linked to rural

development. From 2007, public policies have been more

oriented to the Millennium goals (UN, 2013), and more focused

on smallholders and the poorest families. In the Human

Development Plan 2012–2016, which is still under public

consultation, priority has been given to labour increases and

the reduction of inequality (PNDH, 2012; UNDP, 2013). One of

the strategies mentioned is to assist the exchange of property

rights in rural areas in order to facilitate rural workers’ access

to their own property (in this case, small farms). This policy

goal indicates that future perspectives are concerned more

with the reduction of farm size at the national level. On the

other hand, the Plan mentions that public policies intend to

strengthen productive capacities in terms of education

and technology in the 26 most vulnerable municipalities

40 50 60 70

ce

0.000.100.200.300.400.500.600.700.800.901.00

0 10 20 30 40 50 60 70

Prob

abili

ty

Labou r force

40 50 60 70

ce

ow

0.000.100.200.300.400.500.600.700.800.901.00

0 10 20 30 40 50 60 70

Prob

abili

ty

Labou r force

r needs

r needs

High water needs

High water needs

Pr( Low capacity)Pr( High capacity)

ent water needs (low, med, high) and water risk perception

Page 11: Coffee farmers´ awareness about climate change

0.000.100.200.300.400.500.600.700.800.901.00

0 10 20 30 40

Prob

abili

ty

Techno log y

0.000.100.200.300.400.500.600.700.800.901.00

0 10 20 30 40

Prob

abili

ty

Techno log y

Pr( No capacity)Pr( Low

0.000.100.200.300.400.500.600.700.800.901.00

0 10 20 30 40

Prob

abili

ty

Techno log y

0.000.100.200.300.400.500.600.700.800.901.00

0 10 20 30 40

Prob

abili

ty

Techno log y

0.000.100.200.300.400.500.600.700.800.901.00

0 10 20 30 40

Prob

abili

ty

Techno log y

0.000.100.200.300.400.500.600.700.800.901.00

0 10 20 30 40

Prob

abili

ty

Techno log y

(a) Farmers witho ut water risk percep�on

Low water needs

Low

Med water needs

Med water needswater needs

High water needs

High water needs

(b) Farmers with water risk percep�on

Pr( No capacity) Pr( Low capacity)Pr( Medium capacity) Pr( High capacity)

Fig. 5 – Probability sensitivity to technology variations for different water needs (low, med, high) and water risk perception

(0, 1).

e n v i r o n m e n t a l s c i e n c e & p o l i c y 4 5 ( 2 0 1 5 ) 5 3 – 6 6 63

(Estelı and Jinotega among them) within 20 years. As such, the

technological framework is likely to increase. Considering this

context in which we expect farm size to be reduced and the

introduction of technology to be more generalized, our model

predicts that adaptive capacity perceptions among coffee

smallholders are likely to be reduced in the near future.

Since the consequences of climate change are expected to be

very important for Nicaragua, an awareness of adaptive capacity

flaws is essential to develop the National Adaptation Plan

Strategies (MAGFOR, 2013). The national adaptation plan for the

agricultural sector was developed with the collaboration of

coffee, sugar and agro-ecological farmers, with the aim of

protecting soils from erosion and degradation, conserving water

andnatural habitats andreducingemission of greenhouse gases;

it also envisaged different measures for the adaptation and

mitigation of climate change. The plan intends to endorse

technical assistance to help poor smallholder producers to

adapt, strengthen public institutions and policies, and improve

weather information systems (CCAFS, 2014). The current

strategy 2010–2015 is based on the following five pillars: (i) to

recognize the traditional knowledge and good practices from

rural producers, (ii) to consider the ecosystem based approach as

part of the climate change adaptation strategy, (iii) to consider

the synergies among mitigation and adaptation (iv) to promote

the inclusion and participation of stakeholders, strengthening

the existing associations and cooperatives, and (v) to prioritize

coffee production among other agricultural sectors and focus on

the areas with more food insecurity. This plan is based on the

community and the associative model and the efforts are

oriented to food security and environmental values, encouraging

the traditional and ancient cultures oriented to more sustainable

production (MARENA, 2010; OJLG, 2011, 2012; MAGFOR, 2009).

Some of the actions are difficult to implement, so the

involvement of stakeholders is essential. They are aware of

the difficulties in supporting the adaptation actions. As

mentioned in Milan (2010), it is essential for Nicaragua to

increase its population’s awareness of climate change vulnera-

bility so everyone may assist in the decision-making process.

Since the simulations vary according to current water

needs and water risk scenarios (Fig. 5), our analysis might

suggest the desirability of a greater orientation of adaptation

policies towards water instruments such as promoting small-

scale water capture and storage systems that can help farmers

to improve the ability to store and manage water for

agriculture. For example, the Latin American Fund for

Irrigated Rice (FLAR) and the International Centre for Tropical

Agriculture (CIAT) have a successful 14 micro-dam pilot

project in Nicaragua (Gourdji et al., 2014).

4. Conclusions

In this paper, we have focused on an evaluation of adaptive

capacity perceptions and potential sources of funding for this.

Page 12: Coffee farmers´ awareness about climate change

e n v i r o n m e n t a l s c i e n c e & p o l i c y 4 5 ( 2 0 1 5 ) 5 3 – 6 664

We link socio-economic factors and risk awareness as the

main drivers of adaptive capacity perceptions. The results

provide information about current perspectives on funding

capacity for coffee producers, which will be relevant to their

current investments and capacity building. The models were

used to calculate the cumulated probability in terms of labour

force and technology by taking into account the current water

needs. Water risk awareness emerges as a key factor for

greater concern on the part of farmers with regard to their

adaptive capacity; as such, an effort to provide more

information on water risks can be a determinant of small-

holders’ acceptance of adaptation measures.

Other structural and policy factors, such as farm size and

technological development, seem to have significant impor-

tance as well. The Nicaraguan context seems to suggest a

trend for reductions in farm size and an increase in

technology. Our model simulations suggest that adaptive

capacity perceptions among coffee smallholders are likely

to be reduced in this scenario, since when farm size is

reduced and technology increases, the probability of having

low adaptive capacity perceptions is increased and the

probability of having high adaptive capacity perceptions is

reduced. In this context, adaptation plans should include

more efforts in educational programmes to instruct the

Appendix A. Questionnaire

Questions in relation to support for adopting climate change

I. GENERAL INFORMATION ABOUT THE FARM

1. Department

2. Municipality

3. Exploitation area (Ha):

4. How many people were working on this farm

during this period (2011–2012)?

5. Can you divide them in terms of gender?

(Indicate the total number of males and females):

6. Can you classify them in terms of type of

contract (fixed-term versus permanent)?

(Indicate the total number of fixed-term contracts

and the total number of permanent contracts).

7. Please indicate the total number of workers in

this farm that have more than four years experience.

8. Indicate the total number of machines that are

available for use on this farm.

9. Does this farm receive funding from: Bank

Farm

NGO

10. The investment in this farm in the last five

years could be defined as:

High

Med

Low

11. How would you describe the erosion risk

on this farm?

Yes,

a sig

No,

have

population about their own adaptation potential. Since

farmers have shown that they are not confident about

receiving external support and on the other hand their

perception of potential autonomous adaptation is going to

be lower, the country could suffer a substantial rural land

abandonment, or massive migration to higher areas instead

of implementing other adaptation measures in their farms

which would require greater confidence in external support

and their own possibilities.

Our analysis might suggest the desirability of stronger

orientation of adaptation policies towards water instruments,

as also suggested in former recent studies on Nicaragua (see

case studies confronting water scarcity in Gourdji et al., 2014).

This is important because water management is a very

important strategy among the adaptation measures proposed

in the national adaptation plan for the agricultural sector

(MAGFOR, 2013).

Acknowledgements

This research work was supported by the AECID (Spanish

Agency for International Development Cooperation) as part of

a local development programme for Leon, Nicaragua.

adaptation measures (N = 212).

Answers (weighting value)

_____________

_____________

Indicates the total number

Indicates the total number

Males

Females

Fixed term contracts

Permanent contracts

Indicates the total number

Indicates the total number

s: Yes

No

s co-ops Yes

No

s Yes

No

ium

I think this farm have

nificant risk of erosion.

I do not think this farm

a significant risk of erosion.

Page 13: Coffee farmers´ awareness about climate change

II. PERCEPTIONS ON CLIMATE CHANGE IMPACTS AND ADAPTIVE CAPACITY

12. How worried are you about global warming? Very worried

Somewhat worried

Not very worried

Not at all worried

13. Do you think that climate change impacts will affect this farm

in the future?

In the short term (less than 10 years from now)

In the long term (more than 10 years from now)

14. Assuming climate change is happening, Do you perceive that

you have the capacity to adapt to cope with the potential impacts

of climate change?

No capacity to adapt

Low capacity to adapt

Medium capacity to adapt

High capacity to adapt

15. How would you describe your current water needs for the coffee

production?

High

Medium

Low

16. Do you think climate change is something that is affecting or

is going to affect water availability for coffee production?

Yes, I think water availability is going to be reduced

No, I think water availability is not going to be affected.

17. Assuming climate change is happening, do you think

you will have the support (funding) from the government

to cope with the potential impacts?

No support

Low support

Medium support

High support

18. Assuming climate change is happening, do you think you will

have the support (funding) from farmer cooperatives to cope with

the potential impacts?

No support

Low support

Medium support

High support

19. Assuming climate change is happening, do you think you will

have support (funding) from NGOs (non-governmental

organizations) to cope with the potential impacts?

No support

Low support

Medium support

High support

e n v i r o n m e n t a l s c i e n c e & p o l i c y 4 5 ( 2 0 1 5 ) 5 3 – 6 6 65

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