This presentation was made by Dr. Ndeye Seynabou Diouf, M&E Manager-CINSERE/USAID project, at the WASCAL Science Symposium, 19-21 June 2018, Tang Palace Hotel, Accra, Ghana

1. WASCAL SCIENCE SYMPOSIUM, 19 –21 June 2018, Accra, Ghana
Gendered sensitive access to
climate information services for
farmers in Senegal
Diouf, NS., Ouedraogo, I., Zougmore, R., Ouédraogo, M., and Partley, S.,
Email: S.diouf@cgiar.org
Diouf, NS., Ouedraogo, I., Zougmore, R., Ouédraogo, M. and Partley, S.
Correspondence: s.diouf@cgiar.org

2. OUTLINE
1. Background
2. Objectives
3. Materiel & Methods
4. Results & Discussions
5. Recommendations

3. 1. BACKGROUND
 Climate variability has become a
major issue in African countries
(Agriculture)
 Affects differently men and women
around the world. For instance:
 Women are dependent on local
natural resources for their
livelihood
 In agriculture sector, they make up
60% of labour force
 limited access to, and control over,
key assets, information and inputs
 disadvantaged in terms of ability,
flexibility and means to change
their agricultural practices to adapt
to a changing climate (1998, Patt
et al. 2009, Bryan et al. 2012).
Rainfall
CIAT, 2015

4. 1. BACKGROUND
- Therefore, the identification of
gender roles in climate-related
practices and policies is
essential.
- Moreover, studies have shown
that the use and access of
climate information services
(CIS) helps manage the climate
change effects and empowers
people to make appropriate
decision (eg. Roudier, Muller et
al. 2014, Zougmoré and Ndiaye
2015, J, DM et al. 2016, Etwire,
Buah et al. 2017)

5. 2. OBJECTIVES
General objective:
Explore the gendered sensitive access to and
use of climate information services for farmers
in Senegal
Specific objectives
 Identify the needs of climate information for
men and women
 Examine the most adapted dissemination
channel
 Determine the factors that influence the access
to CI

6. Quantitative Data:
• Sampling of stratified two stage random (communes and farmers)
• 1170 farmers interviewed in 10 Districts
• Content: individual information on the socio-economic
characteristics of farmers, agricultural production, needs and
access to climate information, perceptions and attitudes towards
climate change.
Materiels and Methods
Qualitative Data:
Ten focus group in each districts with resource persons and
producers organizations
Content: focused on specific themes including training and
knowledge, knowledge on climate information, needs on climate
information, perceptions and beliefs about climate

7. 3. Materiels and Methods
𝑝𝑖 = 𝑃𝑟𝑜𝑏 𝑦𝑖 = 1 𝑥𝑖 = 𝐹𝑥𝑖 𝛽
 Two probit regression was
performed to calculate the
determinants of exposure
to climate information.
 Content method used for
the analysis of qualitative
data

8. 4. Results & Discussion
Variables Men (%) Women (%)
All (Men and
Women)
Difference (%)
Socio economics characteristics
Age 52 (0,4) 46 (0,78) 51 (0,4) 6 (0,9)***
Ethnic group (Peulh) 52 (0,016) 30,5 (0,03) 47,78 (0,01) 21,6 (0,04)***
Ethnic group (Diola) 2,24 (0,005) 23,6 (0,03) 6,5 (0,007) -21,4 (0,02)***
Literate 55,3 (0,016) 27,5 (0,03) 49,74 (0,015) 27,81 (0,036)***
Not educated 36 (0,02) 59,66 (0,03) 40,77 (0,014) -23,58 (0,035)***
Native 96,7 (0,006) 91,85 (0,02) 95,73 (0,006) 4,85 (0,015)***
Household Size 14 (0,3) 12 (0,4) 14 (0,28) 1,96 (0,69)***
Net Income (log) 12,46 (0,04) 11,4 (0,08) 12,25 (0,04) 1 (0,084)***
Cultivated area 3,4 (0,14) 2,12 (0,14) 3,15 (0,12) 1,28 (0,3)***
Localities
North 46 (0,016) 19,3 (0,026) 40,68 (0,014) 26,68 (0,035)***
Est 21,78 (0,013) 3,4 (0,012) 18,12 (0,011) 18, 34 (0,027)***
South 20,9 (0,01) 59,65 (0,03) 28,6 (0,013) -38,74 (0,03)***
Sine saloum 11,3 (0,01) 17,59 (0,025) 12,56 (0,01) -6,28 (0,024)**
Social Capital
Membership of an
organization
67 (0,02) 84 (0,02) 70,4 (0,013) -17 (0,03)***
Attitudes, adaptation practices and risk perceptions on climate change
Training 4,2 (0,006) 13,7 (0,02) 6,06 (0,007) -9,57 (0,017)
Willingness 47 (0,02) 47 (0,032) 47 (0,01) 0 (0,04)
Risk Perceptions 30 (0,01) 28,7 (0,03) 29,8 (0,013) 1,3 (0,03)
Note. ***, ** and * respectively denote significant levels of 1%, 5%, and 10%. () standard Err; Source: Surveys (2017).
Table 1: Socio-demographic characteristics of respondents

9. Type of climate
information
Men (%) Women (%) Diff (%)
Onset date 89,65 (0,01) 94,85 (0,01) -5,2 (0,02)**
Cessation date 90,39 (0,01) 94,85 (0,01) -4,45 (0,02)**
Cumulative
rainfall
85,49 (0,011) 88,84 (0,02) -3,36 (0,025)
Daily rain
forecast
87,19 (0,01) 93,13 (0,017) -5,94 (0,023)**
Dry spells 84,2 (0,011) 92,27 (0,018) 8 (0,025)**
Wet spells 82,28 (0,012) 77,25 (0,027) 5 (0,028)*
Off seasons
rains
87,5 (0,01) 87,98 (0,021) -<1 (0,024)
Temperature
forecast
87,3 (0,01) 87,12 (0,022) -<1 (0,024)
Wind forecast 86,02 (0,011) 87,55 (0,02) -1,5 (0,02)
Note. ***, ** and * respectively denote significant levels of 1%, 5%, and 10%.
() standard Err
Source: Surveys (2017).
Table 2: Needs for CI
4. Results & Discussion

10. 4. Results & Discussion
Type of CI
received
Men Women Diff
Onset date 33,4 (0,02) 29 (0,03) 4,2 (0,03)
Cessation date 28,5 (0,01) 25,3 (0,03) 3,1 (0,03)
Cumulative rainfall 20,9 (0,01) 12 (0,02) 8,9 (0,03)***
Daily rain forecast 20 (0,01) 16 (0,02) 3,76 (0,028)
Dry spells 16,5 (0,012) 19 (0,03) -2,78 (0,027)
Wet spells 13,7 (0,01) 4,7 (0,013) 8,93 (0,02)***
Off seasons rains 21,2 (0,01) 12,4 (0,02) 8,79 (0,03)***
Temperature
forecast
16 (0,01) 8,1 (0,02) 7,96 (0,03)***
Access to at least
one CI
37,2 (0,016) 32,19 (0,03) 5 (0,035)*
Note. ***, ** and * respectively denote significant levels of 1%, 5%, and 10%.
() standard Err
Source: Surveys (2017).
Table 3: Access to CI for men and women

11. 4. Results & Discussion
Factors that influence access :
- Both: ethnic group, localities,
risk-perception on climate
change
- Men: literacy, secondary
activity, adaptation practices
- Women: Origin (Native),
willingness to act against
climate change,
VARIABLES
Women Men All
Probit regression Marginal effects Probit regression Marginal effects Probit regression
Marginal
effects
Socio economic characteristics
Age
0.019* 0.006* 0.004 0.002 0.006* 0.002*
(0.010) (0.003) (0.004) (0.001) (0.004) (0.001)
Ethnic group (Peulh)
0.048 0.015 -0.095 -0.035 -0.101 -0.037
(0.341) (0.105) (0.111) (0.041) (0.105) (0.038)
Ethnic group (Diola)
2.454*** 0.778*** 2.166*** 0.623*** 1.978*** 0.634***
(0.372) (0.073) (0.388) (0.038) (0.203) (0.034)
Married
-0.547 -0.186 -0.392 -0.153 -0.527*** -0.204***
(0.382) (0.142) (0.270) (0.107) (0.188) (0.075)
Literated
0.573 0.188 0.328** 0.121** 0.377*** 0.136***
(0.351) (0.123) (0.146) (0.053) (0.131) (0.047)
Not educated
0.054 0.016 0.246 0.092 0.216 0.079
(0.326) (0.098) (0.153) (0.058) (0.136) (0.050)
Secondary activity
1.300*** 0.319*** 1.410*** 0.313***
(0.367) (0.042) (0.370) (0.033)
Native
-1.001** -0.365** -0.394 -0.154 -0.590*** -0.229**
(0.416) (0.157) (0.273) (0.109) (0.226) (0.089)
Sex
-0.232 -0.082
(0.151) (0.051)
Cultivated area 0.213 0.067 0.120 0.044 0.156 0.056
(0.295) (0.096) (0.146) (0.052) (0.123) (0.043)
Size 0.003 0.001 -0.008* -0.003* -0.008* -0.003*
(0.018) (0.005) (0.005) (0.002) (0.005) (0.002)
Cultivated area 0.007 0.002 -0.010 -0.004 -0.012 -0.004
(0.087) (0.026) (0.010) (0.004) (0.010) (0.004)
Net income -0.000 -0.000 0.000 0.000 0.000 0.000
(0.000) (0.000) (0.000) (0.000) (0.000) (0.000)
Localities
Sud -1.428*** -0.450*** -1.077*** -0.331*** -1.090*** -0.339***
(0.446) (0.135) (0.193) (0.045) (0.171) (0.043)
Nord 0.579 0.195 -0.105 -0.039 -0.023 -0.008
(0.509) (0.183) (0.175) (0.065) (0.161) (0.058)
Est -0.841 -0.178* -0.074 -0.027 -0.060 -0.022
(0.829) (0.105) (0.168) (0.062) (0.157) (0.056)
Attitudes, adaptation practices and risk perceptions on climate change
Training 0.227 0.073 0.235 0.090 0.141 0.052
(0.376) (0.126) (0.223) (0.088) (0.180) (0.068)
Adaptation Practices -0.184 -0.059 0.332** 0.117*** 0.308** 0.106**
(0.480) (0.161) (0.132) (0.044) (0.128) (0.041)
Wiilingness 0.584** 0.178** 0.036 0.013 0.100 0.036
(0.262) (0.078) (0.105) (0.039) (0.095) (0.035)
Risk perception 1.124*** 0.380*** 0.415*** 0.158*** 0.487*** 0.182***
(0.263) (0.089) (0.115) (0.044) (0.104) (0.039)
Constant -0.684 -1.527*** -1.528***
(0.925) (0.564) (0.529)
0.227 0.073 0.235 0.090
Observations 233 233 937 937 1,170 1,170
Log pseudolikelihood -89 -545,87 -645,30
Wald chi2 88,32 135,52 242,6
Pseudo R2 0,39 0,12 0,16
% of Correctly
classified
88,3 76,46

12. • Develop tailored CIS that meet
the needs for both men and
women
• Use the community radio as the
main channel of dissemination
• Train farmers to understand the
negative effects of climate
change
• In Senegal in particular, increase
the awareness raising in other
locations where there is a low
probability of access
• Use the producer organization as
channel for CIS dissemination
and as entity for sharing and
discussing issues related to CIS
5. Recommendations

13. Questions
Answers
&
THANK YOU !