Small holder farmers’ perception and response mechanisms to climate change: Lesson from Tekeze lowland goat and sorghum livelihood zone, Ethiopia

Figures & data

Figure 1. The conceptual framework

Figure 2. The study area

Table 1. Farmers’ climate change perception levels disaggregated by age, education and sex (n = 260)

Change category		Overall perception	Perception by age groups				Perception by education			Perception by sex
			≤35	36–64	≥ 65	p value	Literate	Illiterate	p value	Male	Female	p value
Changes in climate		86.54 (224)	5.77	74.23	6.54	0.676	23.46	62.69	0.179	77.69	8.46	0.458
Changes in weather		92.31 (240)	6.92	78.08	7.31	0.810	23.85	68.46	0.935	82.69	9.62	0.953
Temperature	Increased	76.79 (172)	4.91	66.07	5.80	0.037**	17.86	58.93	0.052*	69.2	7.59	0.903
	Decreased	7.14 (16)	0.00	6.70	0.45		2.23	4.91		6.25	0.89
	No change	16.08 (36)	2.23	12.94	0.89		7.15	8.90		14.74	1.34
Rainfall	Increased	2.23 (5)	1.34	0.89	0.00	0.073*	0.89	1.34	0.185	2.23	0.00	0.750
	Decreased	83.48 (187)	5.80	72.77	4.91		20.54	62.95		74.55	7.14
	No change	14.29 (32)	0.00	12.06	2.23		5.80	8.49		13.40	2.68
Wind direction	Changed	61.66 (156)	5.93	50.59	5.14	0.016***	17.79	43.87	0.047**	54.94	6.72	0.008***
	No change	7.50 (19)	0.00	7.51	0.00		1.58	5.93		6.72	0.79
	Don’t know	30.83 (78)	1.19	27.67	1.98		6.72	24.11		27.67	3.16

Note: ***, ** and * are significant levels at 1%, 5% and 10% probability, respectively; n = total sample size

Figure 3. Mean annual temperature trends of the district (1997–2016)

Figure 4. Mean annual rainfall trends of the district (1997–2016)

Table 2. Perception on climate change causes, indicators and effects (combined responses of 5-point Likert item statement), n = 260

Likert item statements	Likert scale mean	Percentage of responses			Difference between adaptors/nonadaptors
		Disagree	Neutral	Agree	χ^2	p value
Climate change indicators
Frequent drought	4.35	4.7	6.5	88.8	22.47	0.000***
Erratic rainfall	2.57	56.2	21.2	22.6	5.08	0.280
Shortage of rainfall	4.32	7.0	3.8	89.2	35.49	0.000***
Higher temperature	4.30	5.4	8.1	86.5	14.39	0.006***
Short rainy season	3.39	26.5	26.5	47	30. 34	0.000***
Climate change causes
Rapid population growth	3.09	35.4	30.4	34.2	26.36	0.000***
Increased deforestation	4.28	4.2	9.6	86.2	18.47	0.001***
Poor natural resource management	3.94	36.2	13.8	50	42.68	0.000***
Pressure on nature	3.56	8.8	10.8	80.4	19.75	0.000***
Lack of soil and water conservation	3.69	31.9	21.5	46.6	3.53	0.473
Climate change effects
Reduce in livestock productivity	4.46	6.1	20.4	73.4	22.85	0.000***
Decline in crop yield	3.93	3.9	2.7	93.4	20.84	0.000***
Livestock/human disease outbreak	3.82	3.5	15.4	81.1	17.18	0.000***
Decrease in amount of water	3.72	11.9	32.7	55.4	8.99	0.061*
Wind storm	3.93	8.9	13.8	77.3	2.76	0.599
Conflict due to grazing land	4.01	34.2	14.6	51.2	2.58	0.028**
Food shortage (insecurity)	3.18	29.2	30.4	40.4	21.96	0.000***

Note: ***, ** and * significant levels at 1%, 5% and 10% respectively; χ²: chi-square

Table 3. Classification of farmers’ response mechanisms to climate change, multiple responses

Groups	Description	Response measures	%
Crop related	Diversification of crop varieties and types on top of improving land use system to sustain productivity	Planting drought resistant crops	20.4
		Using short season varieties	14.6
		Intercropping	14.2
		Soil and water conservation	12.7
		Practicing agro-forestry	7.3
		Use of irrigation	6.2
Livestock related	Management aspects to maintain livestock productivity through production intensification	Diversifying livestock types	20.4
		Reducing flock size in dry season	16.2
		Feed preservation	11.5
		Purchasing supplementary feed	25.4
		Modifying goat reproduction season	21.5
		Keep locally adapted breeds	25.4
		Practicing area closure	20.4
		Exercising transhumance	26.2
Nonagriculture-related activities	Shifting from farming to nonfarm livelihood sorts to abate risks linked to climate change	Involving in any income generating activities (IGAs)	11.5
		Seasonal migration for labor work	9.6
		Looking for credit	16.9
		Looking for aid	10.0
		Sending children to school	7.3

Table 4. Estimation of independent variables in probit model, n = 260

Explanatory variables	Coefficient	Standard error	Marginal effect	P-value
Sex	−0.2175	0.385	−0.0433	0.573
Age	0.0147	0.024	0.0032	0.537
Educational status	0.3423	0.084	0.0751	0.000***
Family size	−0.1769	0.126	−0.0388	0.159
Farming experience	0.0157	0.021	0.0034	0.463
Farm income	0.0001	0.001	0.0001	0.000***
Nonfarm income	−0.0006	0.002	−0.0002	0.017**
Farm land size	−0.0567	0.139	−0.0125	0.684
Total livestock (TLU)	0.0052	0.026	0.0012	0.841
Access to information	1.7664	0.331	0.4121	0.000***
Access to credit	−0.0893	0.282	−0.0194	0.751
Extension contact	0.6429	0.298	0.1411	0.031**
Training access	0.9067	0.379	0.1716	0.017**
Perception level	0.8363	0.289	0.2395	0.004*
Number of observations Wald χ^2 (15) p value pseudo R^2 Log pseudo likelihood	260 77.26 0.0000*** 0.6390 –61.25

Note: ***, ** significant at 1% and 5% significant levels, respectively

Table A5. Likert statements’ reliability test statistics

Cronbach’s alpha	Cronbach’s alpha based on standardized items	Number of items
0.735	0.788	19

Figure 5. Barriers to climate change adaptation

Table A1. Sample households’ socioeconomic characteristics, n = 260

Characteristics	Adapters	Nonadapters	Overall	SD	t ratio	p value
Age (years)	46.2	44.2	45.4	9.83	−1.597*	0.056
Family size	4.0	3.7	3.9	1.44	−1.623*	0.053
Education level	2.7	0.1	1.8	3.06	−7.120***	0.000
Land size in ha	1.4	1.3	1.4	0.89	−0.694	0.244
Farming experience	19.7	16.4	18.5	9.61	−2.629***	0.005
Farm income	29527.9	21215.3	26490.6	8458.9	−8.650***	0.000
Nonfarm income	3449.5	3126.1	3244.2	6163.5	0.407	0.342
Total livestock (TLU)	15.1	10.6	13.5	6.89	−2.388***	0.009

*** and * Significant at 1% and 10% respectively, n = total sample

Table A2. Sample households’ institutional features, n = 260

Characteristics	Category	Percentage points		Overall	χ^2	p value
		Adapters	Nonadapters
Gender	Male	58.85	27.37	86.22
	Female	4.62	9.22	13.84	4.699**	0.030
Access to climate information	Yes	49.23	3.85	53.08
	No	14.23	32.69	46.92	108.8***	0.000
Contact with extension agent	< Six (6)	28.08	27.31	55.38
	≥ Six (6)	35.38	9.23	44.62	22.69***	0.000
Climate change perception level	Perceived	55.00	29.62	84.62
	Neutral	2.69	0.38	3.08
	Not perceived	5.77	6.54	12.31	6.015**	0.049
Access to credit	Yes	43.08	16.92	60.00
	No	20.38	19.62	40.00	11.68***	0.001
Group membership	Yes	63.46	36.15	99.62
	No	0.00	0.38	0.38	1.744	0.187
Access to training	Yes	32.31	1.92	34.23
	No	31.15	34.62	65.77	55.79**	0.000

***** significant at 5% and 10% respectively, n = total samples

Table A3. Multicollinearity test of continuous explanatory variables

Variables	VIF	1/VIF
Age	2.56	0.389920
Farm experience	2.06	0.485278
Family size	2.03	0.493669
Livestock in TLU	1.18	0.845297
Farm income	1.17	0.852280
Land size	1.17	0.856236
Goat flock size	1.11	0.899101
Nonfarm income	1.09	0.913442
Education level	1.09	0.916770
Mean VIF	1.50

Table A4. Multicollinearity test of dummy explanatory variables

	Gender	Credit access	Frequency of contact	Training access	Information access	Perception level
Gender	1.0000
Credit access	0.1853	1.0000
Contact frequency	0.0773	0.1643	1.0000
Training access	0.1127	0.0927	0.2983	1.0000
Information access	0.1852	0.3020	0.1927	0.3860	1.0000
Perception level	−0.0018	−0.0132	0.1170	0.1215	0.2094	1.0000

Table A6. Climate data of Abergelle district (1997–2016)

Years	Mean annual temperature and rainfall
	Temperature (^°C)	Rainfall (mm)
1997	33.3	658.5
1998	32.8	590.8
1999	31.6	660.7
2000	32.9	547.6
2001	33.4	589.3
2002	34.6	638.9
2003	30.9	490.5
2004	32.3	456.2
2005	34.8	486.3
2006	37.8	613.6
2007	39.5	429.4
2008	38.2	410.5
2009	40.2	600.6
2010	41.0	390.2
2011	39.5	348.5
2012	38.3	560.9
2013	41.4	289.7
2014	43.7	456.5
2015	42.5	265.8
2016	43.6	419.6

Source: National metrology service agency (2016)