Sorghum farmers’ perceptions of climate change, its effects, temperature and precipitation trends, and determinants of adaptation strategies in the central plateau zone of Rwanda

Figures & data

Figure 1. Map showing the study area.

Table 1. Distribution of sample households by cells.

Sample Districts	Sample Sectors	Sample cells	TNHGS	Sample Size
Ruhango	Kinazi	Rubona	169	23
		Gisali	125	17
Gisagara	Musha	Cyimana	142	19
		Gatovu	196	27
Kamonyi	Mugina	Mugina	277	38
		Nteko	289	39
Huye	Rusatira	Kiruhura	340	46
		Gafumba	292	40
Nyanza	Kibirizi	Mututu	381	52
		Cyeru	324	44
Total			2535	345

TNHGS: Total Number of Households Producing Sorghum.

Table 2. Reliability coefficient values of different climate change components.

Climate change components	Reliability coefficient value
Awareness and causes of climate change	0.91
Temperature and rainfall trends	0.84
Shocks and coping strategies	0.86
Effects on sorghum	0.74
Adaptation strategies	0.71

Table 3. Description of independent variables used in the model.

Variable	Description
Age	Age of the household head in years
Sex	Dummy of sex of household head (Yes = 1)
Education	Dummy of education of household head (Yes = 1)
Land size	Total area of the plot in Ha
Family size	Household size
Farming experience	Time spent in farming activities in years
Extension contact	Dummy for being visited by extension agent (Yes = 1)
Cooperative member	Dummy for belonging in to farm cooperative (Yes =1)
Information access	Dummy for having a radio, TV, and phone (Yes= 1)
Credit access	Dummy for accessing credit (Yes = 1)
Off farm income	Dummy for having off-farm activities (Yes =1)

Table 4. Demographic and socioeconomic characteristics of respondents (continues variables).

Variable	Mean	Std. Dev	Min	Max
Age	52.09	13.1240	23	90
Land size (ha)	0.81	0.8222	0.02	5.5
Family size (no.)	5.2	2.1434	1	14
Farming experience	31.59	13.3660	2	70

Table 5. Demographic and socioeconomic characteristics of respondents (discrete variables).

Variable	Frequency (n = 345)	Percentage (%)
Sex	200	58.0
Education level	284	82.3
Extension contact	196	56.8
Cooperative member	220	63.8
Information access	236	68.4
Credit access	155	44.9
Off farm income	29	8.4

Table 6. Farmers’ perceptions on human actions’ causes of climate change.

Human actions causes of climate change	% of all households	% of gender per district
		Huye		Gisagara		Nyanza		Ruhango		Kamonyi
		♂	♀	♂	♀	♂	♀	♂	♀	♂	♀
Deforestation	72.2	18.1	8.0	10.4	3.2	20.1	9.2	2.0	5.6	10.8	12.4
Industry	47.0	18.5	11.7	9.9	4.3	25.9	8.6	3.7	4.9	8.6	3.7
Soil erosion	35.7	7.3	4.1	11.4	3.3	25.2	12.2	2.4	5.7	11.4	17.1
Air pollution/transport	30.4	14.3	6.7	11.4	3.8	26.7	13.3	4.8	5.7	3.8	9.5
Agricultural activities	29.0	13.0	4.0	11.0	3.0	26.0	15.0	2.0	3.0	13.0	10.0
Population increase	25.8	5.6	4.5	15.7	4.5	34.8	15.7	2.2	2.2	5.6	9.0
Livestock activities	23.2	6.3	6.3	7.5	1.3	28.8	17.5	1.3	0.0	18.8	12.5

♂: male; ♀: Female. The sum of the percentage for all households does not add up to 100% because some farmers provided multiple responses. This applies to other tables presented with multiple responses.

Table 7. Farmers’ perceptions on the trends of temperature and rainfall over the period of 30 years.

Trends of temperature and rainfall	% of all households	% of gender per district
		Huye		Gisagara		Nyanza		Ruhango		Kamonyi
		♂	♀	♂	♀	♂	♀	♂	♀	♂	♀
Increase in temperature	69.3	14.2	8.8	9.2	3.3	18.0	10.0	4.6	7.1	12.1	12.6
Decrease in rainfall	56.5	22.1	8.7	7.7	3.6	14.9	10.8	5.1	7.2	10.3	9.7
Changes in times of raining	31.6	11.9	10.1	7.3	5.5	17.4	10.1	5.5	5.5	11.0	15.6
Increase in rainfall	12.2	16.7	7.1	14.3	14.3	7.1	2.4	4.8	11.9	7.1	14.3
Increase in frequency of drought	9.5	12.1	12.1	9.1	3.0	15.2	9.1	6.1	6.1	15.2	12.1
Decrease in temperature	2.6	22.2	0.0	0.0	11.1	11.1	0.0	33.3	11.1	11.1	0.0

Table 8. Sen’s slope values for seasonal and annual rainfall in central plateau zone of Rwanda (1989–2018).

	Seasons
Stations	Short dry season	Long rain season	Long dry season	Short rain season	Annual
Kinazi	−2.29	−4.00	−0.42	−1.20	−7.00
Gikonko	−1.59	−1.60	−0.22	2.00	−1.60
Mugina	−4.44	−4.00	0.73	−4.15	−7.00
Rubona	−1.83	−1.91	−0.26	−0.33	−4.16
Busoro	−1.29	−3.30	0.00	−1.35	−4.25

Table 9. Farmers’ perceptions on climate change shocks, shocks’ effects, and coping strategies.

Farmers’ perceptions	% of all households	% of gender per district
		Huye		Gisagara		Nyanza		Ruhango		Kamonyi
		♂	♀	♂	♀	♂	♀	♂	♀	♂	♀
Farmers’ perceptions on climate change induced shocks
Drought	87.0	17.7	10.0	7.7	3.3	18.3	11.3	4.7	6.0	10.7	10.3
Too much rain	29.3	19.8	8.9	9.9	6.9	9.9	6.9	10.9	9.9	5.0	11.9
Floods	12.8	13.6	4.5	22.7	9.1	9.1	2.3	11.4	6.8	6.8	13.6
Erratic rainfall	27.8	25.0	13.5	6.3	2.1	26.0	12.5	2.1	7.3	3.1	2.1
Hailstorm	21.4	44.6	18.9	13.5	4.1	2.7	4.1	4.1	4.1	0.0	4.1
Landslide	6.7	17.4	8.7	4.3	0.0	0.0	4.3	26.1	26.1	4.3	8.7
Effects of climate change shocks on sorghum
Decline in crop yield	72.2	20.5	12.4	7.6	3.6	19.3	9.2	2.8	4.4	8.4	11.6
Food shortage	37.4	21.7	11.6	7.0	2.3	27.9	17.8	2.3	3.9	2.3	3.1
Food price increase	32.5	23.2	9.8	14.3	6.3	25.0	16.1	0.9	2.7	1.8	0.0
Loss of entire crop	12.8	4.5	0.0	9.1	2.3	15.9	25.0	9.1	4.5	25.0	4.5
Loss of income	12.2	23.8	19.0	7.1	4.8	7.1	11.9	2.4	9.5	9.5	4.8
Sorghum farmers’ coping strategies for climate change induced shocks
Sell livestock	29.0	20.0	8.0	13.0	5.0	22.0	15.0	0.0	1.0	11.0	5.0
Eat less	24.9	16.3	11.6	4.7	2.3	32.6	16.3	3.5	8.1	3.5	1.2
Borrow money	22.9	26.6	8.9	7.6	2.5	19.0	13.9	1.3	1.3	8.9	10.1
Alternative food	19.1	10.6	12.1	3.0	1.5	34.8	18.2	6.1	9.1	1.5	3.0
No coping measure	17.1	11.9	11.9	5.1	5.1	10.2	3.4	13.6	13.6	5.1	20.3
Off-farm employment	11.3	20.5	20.5	0.0	0.0	15.4	12.8	0.0	7.7	10.3	12.8
Different foods	9.6	9.1	6.1	9.1	3.0	42.4	15.2	3.0	0.0	6.1	6.1

Table 10. Farmers’ perceptions on the effects of climate change on sorghum.

Climate change effects on sorghum	% of all households	% of gender per district
		Huye		Gisagara		Nyanza		Ruhango		Kamonyi
		♂	♀	♂	♀	♂	♀	♂	♀	♂	♀
Grain yied reduction	95.7	15.8	9.1	9.4	3.6	17.9	10.9	4.5	6.1	11.2	11.5
Varieties disappearance	84.3	14.8	8.2	9.6	4.1	19.9	12.4	3.4	5.2	11.7	10.7
Presence of fall armyworms	78.8	15.4	9.9	8.5	3.3	18.8	12.5	2.6	4.4	12.1	12.5
Presence of honeydew/grain	77.1	11.7	9.8	10.2	4.1	20.7	13.2	4.9	6.4	10.9	8.3
Presence of stem borer	63.2	10.6	5.0	9.2	4.1	20.2	13.3	6.0	7.3	10.6	13.8
Lodging of sorghum plants	55.1	11.1	6.3	7.4	3.2	23.2	14.7	4.7	5.8	11.1	12.6
Sorghum plants senescence	52.5	5.0	2.8	10.5	5.0	26.0	18.2	3.9	3.9	16.0	8.8
Presence of aphids	50.7	7.4	5.1	10.3	4.6	29.7	20.0	2.9	2.3	12.0	5.7
Presence of rust	40.3	12.9	3.6	11.5	4.3	34.5	20.9	2.9	5.0	0.7	3.6
Biomass decrease	39.4	5.1	4.4	9.6	2.2	27.9	22.8	1.5	2.2	14.7	9.6

Table 11. Sorghum farmers’ adaptation strategies.

Adaptation strategies	% of all households	% of gender per district
		Huye		Gisagara		Nyanza		Ruhango		Kamonyi
		♂	♀	♂	♀	♂	♀	♂	♀	♂	♀
Early maturing variety	67.0	17.3	10.8	12.1	4.3	22.1	12.6	2.6	3.5	8.7	6.1
Adjusting planting date	50.1	23.7	9.2	11.6	4.6	24.9	13.9	2.3	0.6	4.6	4.6
Drought tolerant variety	46.7	11.8	5.0	12.4	5.0	21.1	14.3	3.7	5.0	9.9	11.8
Soil conservation practices	38.3	11.4	9.1	10.6	5.3	28.0	12.9	0.8	2.3	12.1	7.6
Crop diversification practices	32.8	16.8	11.5	10.6	2.7	21.2	17.7	0.9	0.9	10.6	7.1

Table 12. Results of multivariate probit model for adoption of climate change adaptation strategies.

	Early maturing varieties		Adjusting sowing date		Drought tolerant varieties		Soil conservation practices		Crop diversification
Variables	Coef	z	Coef	Z	Coef	z	Coef	z	Coef	z
Age	0.0057	0.37	0.0551	2.43**	0.0354	2.04**	−0.0154	−0.79	0.0021	0.12
Sex	0.1245	0.79	0.2574	1.17	−0.2491	−1.4	−0.0061	−0.04	0.0364	0.23
Education level	1.6255	6.83***	−0.4924	−1.59	−0.0887	−0.41	0.0987	0.43	−0.3217	−1.53
Land size	−0.2023	−1.77*	−0.1439	−1.1	−0.0558	−0.54	0.1503	1.62	−0.0989	−1.07
Family size	−0.034	−0.92	−0.0677	−1.23	0.0378	0.96	−0.0405	−1.05	0.0191	0.55
Farming experience	−0.0012	−0.08	−0.032	−1.51	−0.0205	−1.19	0.0364	1.9*	0.0133	0.79
Extension agents contact	0.8986	5.48***	3.4516	12.38***	0.4779	2.64***	0.6334	3.6	0.4066	2.56**
Cooperative membership	0.0553	0.31	0.1267	0.56	2.3432	9.47	0.1669	0.93	−0.2533	−1.53
Information access	−0.1741	−0.95	0.085	0.35	−0.1744	−0.86	1.7035	6.44***	0.2154	1.2
Credit access	0.4987	2.67***	0.5829	2.68***	0.3878	2.17**	0.5714	3.18***	0.5443	3.35***
Off farm income	0.0457	0.14	0.1986	0.53	0.2749	0.77	0.3207	1.14	0.2657	0.99
rho21	0.2942	2.38**		Multivariate probit (SML, # draws = 5)
rho31	0.3756	3.86***		Log pseudo likelihood = −708.97984
rho41	0.2954	2.99***		Number of obs. = 345
rho51	0.3758	3.97***		Wald chi2(60) = 531.19
rho32	0.2094	1.77*		Prob > chi^2 = 0.0000
rho42	0.3205	2.45**
rho52	0.2673	2.73***
rho43	0.2577	2.77***
rho53	0.3565	4.19***
rho54	0.4988	6.04***

Likelihood ratio test of rho21 = rho31 = rho41 = rho51 = rho32 = rho42 = rho52 = rho43 =rho53 = rho54 = 0: chi² (10) = 81.0655.

Prob > chi² = 0.0000. rho shows correlation between dependent variables.

^***,**,* significant at the 1, 5 and 10 percent probability levels, respectively.