Adaptive conservation of natural resources determines the sustainable livelihood strategies of farmers in the semi-arid Loess Plateau region of China

doi:10.1016/j.regsus.2025.100244

Abstract

Abstract:

Livelihood improvement and sustainable natural resource utilization are among the United Nations Sustainable Development Goals; however, most farm households either randomly select or just imitate livelihood strategies being practiced in other areas. As the livelihoods of farm households are vulnerable to several challenges in ecologically fragile areas, identifying the livelihood strategies of farm households in arid and semi-arid areas will help for promoting both livelihood security and environmental conservation. Hence, in this study, we constructed a sustainable evaluation index system for the livelihood of farmers in the Loess Plateau region of China by conducting field research and interviews. We employed the composite index method to measure the livelihood capital and the livelihood strategies chosen by farmers, and then analyzed the resource endowment of farmers under different livelihood strategies using logistic regression and structural equation modeling. The results revealed that under the combined influences of livelihood capital and government policy, farm households in the Loess Plateau region selected agro-dependent, agro-pastoral, agro-industrial, non-agricultural livelihood strategies. The key factors influencing the selection of these household livelihood strategies included the household labor capacity, the farmland owned per household, the number of livestock, and the grassland forage-supply ratio. The grassland forage-supply ratio was a crucial factor influencing the choice between agricultural and non-agricultural livelihood strategies. In this context, the grassland forage-supply ratio increased with the stocking rate. However, once the stocking rate exceeded 56.5 sheep/hm², the grassland forage-supply ratio no longer increased rapidly under the agriculture-based livelihood strategy. The strategy of ecological resource conservation and moderate utilization based on the quality and quantity of natural resources ensures win-win benefits for the environment and human well-being in arid and semi-arid areas. Moderate grazing therefore has the potential to improve farmers’ livelihoods without causing grassland degradation. These results contribute to the synergistic co-adaptation of livelihood improvement and ecological conservation in arid and semi-arid areas.

Key words: Livelihood strategies, Livelihood capital, Farm household, Grassland forage-supply ratio, Structural equation modeling (SEM), Arid and semi-arid areas, Loess Plateau

MA Shengli, XU Mingxiang. Adaptive conservation of natural resources determines the sustainable livelihood strategies of farmers in the semi-arid Loess Plateau region of China[J]. Regional Sustainability, 2025, 6(4): 100244.

Figures/Tables 10

Fig. 1.

Table 1

Measurement indicators and assignment of livelihood capital."

Type	Explanatory variable	Unit	Implication of variables
Natural capital (N)	Farmland owned per household (N1)	hm²	This variable is used to measure the area of farmland that households are currently cultivating, after deducting land converted under the Grain-for-Green Program and land that has been abandoned.
Natural capital (N)	Grassland area per household (N2)	hm²	This variable measures the area of sloping cropland that the household has converted to forest or grassland through the Sloping Land Conversion Program.
Human capital (H)	Household size (H1)	-	This variable represents household size using categorical values: 0.25 for households with two or fewer members, 0.50 for those with three to five members, 0.75 for those with six to eight members, and 1.00 for those with nine or more members.
	Household labor capacity (H2)	-	This variable quantifies the household’s total labor capacity by summing labor scores assigned to each member: 0.00 for non-labor individuals (children too young to work, elderly too old to work, and those unable to work due to illness); 0.50 for half-labor individuals (children or elderly capable of simple household tasks or light farm work); and 1.00 for full-labor individuals (healthy adults able to perform normal farm work).
	Education level (H3)	-	This variable measures household educational attainment by calculating the mean score of all members, assigned as follows: 0.00 for illiterate or preschool, 0.25 for primary school, 0.50 for junior high school, 0.75 for senior high school, and 1.00 for college or university.
Physical capital (P)	Production and living assets (P1)	%	This variable measures the proportion of fixed-asset categories (both productive and domestic) owned by the household.
	Housing quality (P2)	-	This variable measures housing quality using a score derived from total floor area and material coefficients: 1.00 for concrete or multi-story structure, 0.75 for masonry, 0.50 for timber, and 0.25 for Mongolian yurts.
	Number of livestock (P3)		The main livestock species include hog, cattle, horse, and sheep. We adopted the following conversion coefficient: 1 horse=1.0, 1 cattle=0.8, 1 hog=0.3, and 1 sheep=0.3. The values of all livestock are then summed up.
Financial capital (F)	Annual income per capita (F1)	RMB	This variable is used to assess the household’s annual income per capita derived primarily from agricultural, secondary, and tertiary sector activities.
Financial capital (F)	Access to bank loan or usury (F2)	-	This variable is used to assess whether farmers are able to borrow money from banks. If they are able to borrow, they are assigned a value of 1; if they are unable to borrow, they are assigned a value of 0.
Social capital (S)	Social relationships (S1)	-	This variable is used to assess the number of relatives serving as township or village officials or other government employees, coded as follows: 1.00 for households with four or more such relatives, 0.75 for three, 0.50 for two, 0.25 for one, and 0.00 for none.
Social capital (S)	Social spending (S2)	RMB	This variable is used to assess the household’s social expenditures, i.e., spending primarily directed at important social events.
Geographical advantage	Distance	km	This variable measures the distance from the household to the nearest town.
Stocking rate	Stocking rate	sheep/hm²	Stocking rate is calculated as the number of livestock divided by the cropland area.
Forage supply	Grassland forage-supply ratio	%	This variable measures grassland forage supply. Specifically, the forage-supply ratio is calculated as the shortfall between total annual fodder demand and the combined quantity of cultivated and commercial fodder, expressed as a proportion of total annual demand.

Table 1

Table 2

Fig. 2.

Fig. 3.

Table 3

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Table 4

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Fig. 6.

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Demographic information		Ansai District	Guyuan City	Shenmu City	Wuqi County	Mean
Gender (%)	Male	84.15	99.12	92.50	100.00	93.69
Gender (%)	Female	15.85	0.88	7.50	0.00	6.31
Education level (%)	Illiteracy	20.73	45.13	12.50	16.67	26.81
	Primary school	64.63	23.89	66.25	66.67	50.79
	Junior middle school	9.76	25.66	17.50	11.90	17.67
	Senior middle school	3.66	2.66	3.75	4.76	4.73
	University or college	1.22	2.65	0.00	0.00	0.00
Age (years)		59	50	63	60	58
Family size (persons)		2.90	5.15	2.44	4.38	3.72
Farmland owned per household (hm²)		1.12	2.26	1.48	1.07	1.48
Annual household income (RMB)		67,240.30	89,682.48	87,073.88	89,498.81	83,373.87
Annual household cost (RMB)		28,229.93	43,358.65	28,984.44	37,115.26	34,422.07
Number of goats		48.51	44.67	60.54	21.07	43.00

Region	Percentage of livelihood strategy (%)
Region	Agro-pastoral livelihood strategy	Non-agricultural livelihood strategy	Agro-industrial livelihood strategy	Agro-dependent livelihood strategy
Ansai District	47.56	13.41	28.05	10.98
Guyuan City	46.90	7.08	36.28	9.73
Shenmu City	61.25	7.50	16.25	15.00
Wuqi County	11.90	57.14	21.43	9.52

Explanatory variable	Non-agricultural livelihood strategy		Agro-industrial livelihood strategy		Agro-dependent livelihood strategy
Explanatory variable	Regression coefficient	Odds ratio	Regression coefficient	Odds ratio	Regression coefficient	Odds ratio
N1	-0.34	0.72	-2.81^**	0.06	-1.03	0.36
N2	0.90	1.09	-0.59	0.55	0.94	2.56
H1	0.27	1.31	-1.10	0.33	-1.18	0.31
H2	1.17^***	3.21	1.05^***	2.85	-0.91	0.40
H3	0.89	2.44	0.45	1.57	-0.33	0.72
P1	6.00^*	402.39	2.71	15.05	7.32	1503.00
P2	0.01	1.01	0.01	1.01	-0.01	0.99
P3	-0.44^***	0.65	-0.07^*	0.94	0.14	1.16
F1	0.77^*	2.17	0.25^*	1.29	-3.25^***	0.04
F2	-0.86	0.42	0.17	1.18	-3.24^*	0.04
S1	-2.17	0.11	0.52	1.69	3.21	24.76
S2	0.01	1.01	0.02	1.02	-0.08^*	0.93
Distance	-0.03	0.98	-0.00	1.00	-0.02	0.98
Stocking rate	0.13	1.14	-0.09	0.92	0.08	1.08
Grassland forage-supply ratio	-2.11	0.12	1.09	2.98	-17.55^**	0.00