Survey data on livelihood assets, activities and outcomes of smallholder farm households in China's Loess Plateau

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Data in Brief 39 (2021) 107638
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Data in Brief
journal homepage: www.elsevier.com/locate/dib
Data Article
Survey data on livelihood assets, activities and
outcomes of smallholder farm households in
China’s Loess Plateau
Qirui Li a , b , c , d , ∗
a State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Water and Soil
Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling 712100, China
b Leibniz-Centre for Agricultural Landscape Research (ZALF), EberswalderStraße 84, 15374 Müncheberg, Germany
c Africa Multiple Cluster of Excellence, University of Bayreuth, 95440 Bayreuth, Germany
d Climatology Research Group, University of Bayreuth, 95447 Bayreuth, Germany
a r t i c l e
i n f o
Article history:
Received 22 September 2021
Revised 26 October 2021
Accepted 22 November 2021
Available online 25 November 2021
Keywords:
Land use
Payments for ecosystem services
Sustainable livelihood
Farm typology
Dryland agriculture
Social-ecological systems
a b s t r a c t
Smallholders’ decisions on land use and their activities and
strategies of livelihoods are the critical source of uncertainty
in natural resource use and an essential determinant of sus-
tainability challenges. This data article provides a selection
of quantitative data from a questionnaire survey on liveli-
hood assets, activities and outcomes of smallholder farm
households in Yan’he Township, which lies in the middle
part of China’s Loess Plateau, one of the representative Grain
for Green Project areas [1] . Data include land-use decisions
and agronomic practices, fertilisation, use of pesticides, ma-
chine and irrigation, farm and non-farm activities, financial
performance, and the levels of household income, wellness,
and total consumption of food, energy, and education and
health care. The survey also covered geographical, demo-
graphic and socioeconomic background information on the
respondents and their perceptions, incentives, propensities
and subjective wellbeing. The survey has supported a cou-
ple of research articles that build indicators and indexes
for economic, environmental and socio-cultural sustainabil-
ity dimensions and the resilience building of coupled social-
ecological systems. The data presented in this article were
∗Corresponding author.
E-mail addresses: leolee8612@gmail.com , qirui.li@uni-bayreuth.de
Social media:
https://doi.org/10.1016/j.dib.2021.107638
2352-3409/© 2021 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license
( http://creativecommons.org/licenses/by/4.0/ )

2
Q. Li / Data in Brief 39 (2021) 107638
analysed using descriptive and inferential statistics and pro-
vided at the Mendeley Repository. The data will assist studies
on the interrelationships of smallholder livelihoods, ecosys-
tem conservation, interventionist policy and market support,
and community capacity building in sustainability science.
© 2021 The Author(s). Published by Elsevier Inc.
This is an open access article under the CC BY license
( http://creativecommons.org/licenses/by/4.0/ )
Specifications Table
Subject
Agricultural Sciences
Specific subject area
Agricultural Economics
Type of data
Primary data, Tables, Images
How data were acquired
Questionnaire survey
Data format
Raw, Analysed, Filtered (descriptive and inferential statistics)
Parameters for data collection
The survey data contain 247 households in China’s Loess Plateau. The
dataset consists of 242 valid observations after checking for missing
values, potential errors, outliers and correlations. It covers the
households in V-shaped valley areas and riparian (floodplain) areas
with different altitudes and market distances.
Description of data collection
The data was collected through direct on-site interviews with
household heads between February and May 2014. The author
conducted the entire survey, who designed the semi-structured
questionnaire for data accuracy and coherence.
Data source location
City/Town/Region: Yanhe Township in Ansai County of Yan’an City,
Shaanxi Province
Country: China
Latitude and longitude: 36.48 and 109.22
Data accessibility
Dataset is uploaded on Mendeley Repository Name:
Li, Qirui (2021), “Survey data on livelihood assets, activities and
outcomes of smallholder farm households in China’s Loess Plateau”,
Mendeley Data, V1, doi: https://doi.org/10.17632/b2sjykvfgy.1
Related research article
Q. Li, H. Ma, Z. Xu, H. Feng, S. D. Bellingrath-Kimura, Balancing
socioeconomic development with ecological conservation towards rural
sustainability: A case study in semi-arid rural China, International
Journal of Sustainable Development & World Ecology.
DOI: https://doi.org/10.1080/13504509.2021.1990157
Value of the Data
• This unique dataset about smallholders’ land-use practices and livelihoods in China’s Loess
Plateau represents the adaptation and transformation of local social-ecological systems (SES)
under the rapid urbanisation and the implementation of a large-scale payment for ecosystem
services (PES) program [1] .
• The data will be helpful for researchers who would like to investigate local livelihoods, in-
dividual decision making, the effect of PES, feedback of human behaviour to ecosystem and
policy interventions, and the transformation approaches towards sustainability in drylands.
• The data will be valuable to examine human behaviour and decision-making at the farm
household level in response to policy interventions and changes in environmental and socioe-
conomic conditions, perform the impact assessment of land-use change, and conduct studies
on resilience building and sustainability assessments.
• The data give insights into household demographics, local physical and geographic condi-
tions, landholdings and transfers, household capital and assets, farming and non-farm activi-
ties and incomes, and household final consumption expenditure, characterised by sustainable
livelihood principles and impact-feedback loops.

Q. Li / Data in Brief 39 (2021) 107638
3
• In terms of policymaking and planning, key factors can be extracted to design farm man-
agement, community-based strategies and capacity building, and policy interventions and
market support relevant to local agricultural production, food security, availability and con-
sumption of ecosystem services, ecological conservation, rural infrastructure, social welfare
and human capital, among others.
1. Data Description
The data consist of five dataset tables, a semi-structured questionnaire, eight images about
the location of the interviewed farm households and study area ( Fig. 1 ). The household data
table has 242 observations, including 104 variables that are generated from descriptive and in-
ferential statistical analysis and connected to a question in the survey questionnaire. The ques-
tionnaire is divided into seven parts: 1) “Household Status” about the geographical and demo-
cratic information the household, 2) “Grain for Green Project” concerning the participation of the
Grain for Green Project (GGP) implemented in 1999 to set aside sloping farmland ( > 25 °) against
soil and water erosion, 3) “Resource Availability” regarding the availability, allocation and utili-
sation of land, water, labour and capital, 4) “Cropping” including detailed information (e.g. price
and timing) about seeds, sowing, planting, fertilisation, and the use of fertiliser, machine, pesti-
cides, family and hired labour, and energy in terms of annual and perennial crops, 5) “Livestock
Breeding” containing inputs and outputs of livestock breeding over various seasons and animal
species. 6) “Off-farm Work” is the information of household members who engaged in off-farm
work regarding age, gender, education, skills, wages, investments, duration, and destination, and
7) “Livelihood and Total Consumption” covering total consumption of food, energy, education
Fig. 1. An overview of the survey data.

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Q. Li / Data in Brief 39 (2021) 107638
and health care. The survey has already supported studies on sustainability assessment and the
resilience building of SES [1–4] .
The data presented here has been used for the latest study on rural sustainability by bal-
ancing socioeconomic development with ecological conservation [5] . The data consist of vari-
ables with an uncountable set of values, binary response options (primarily coded as 1 = “yes”
and 0 = “no”), and multivariate response options coded according to the number of alternatives
and metric response options. Observations with missing values were dismissed. All variables are
named in the dataset table and can be easily linked to respective questions in the survey ques-
tionnaire.
2. Experimental Design, Materials and Methods
2.1. Questionnaire development and survey sampling
The survey was conducted in 15 of 28 villages in Yanhe Township between February and May
2014. The Township represents the smallholder farm household in China’s Loess Plateau regard-
ing population density, topography, semi-arid climates, and the GGP scheme [ 1 , 2 ]. It followed a
three-stage stratified sampling procedure, with a confidence interval of 6 at a 95% confidence
level and a population (total households) of 3,390. Districts constitute the strata, covering two
types of landscape—floodplain and V-shaped valley. Primary sampling units are villages. The
survey villages account for 10,400 (62%) of the population of the Township, with different al-
titudes and market distances ( Table 1 ). 20% of the households in each village were randomly
interviewed.
A semi-structured questionnaire [6] was designed for information on household demograph-
ics, local physical and geographic conditions, landholdings and transfers, household capital and
assets, farming and non-farm activities and incomes, and household final consumption expendi-
tures. The interviews were carried out on-site with the help of a local guide (driver) in Man-
darin Chinese. During the interview, Global Positioning System trackers were used to record
the geospatial coordinates and elevations of household locations and main infrastructures (e.g.,
township centres and paved roads). All respondents were anonymised and plotted on soil maps
to retrieve data on landscape elements. The soil maps were taken from the Soil Testing and For-
mulated Fertilization System (Ansai Agro-Tech Extension, Service Station 2010), including 4,314
soil samples tested in Ansai County in 2009.
The dataset includes 242 households after reviewing the data for missing values, potential er-
rors, outliers and correlations. Nevertheless, the author acknowledges that the survey data can-
not provide any information once the GGP is terminated in 2020. It would be updated after the
COVID-19 pandemic.
2.2. Methods of data analysis
The database in Excel Table consists of five dataset tables in Excel sheets ( Fig. 1 ), concerning
the information of 242 households (i.e., “Data of 242 households”) and temperature and pre-
cipitation (in the other four sheets). The household data include 104 variables derived from the
descriptive and inferential statistical analysis. Some variables are composed and calculated by
using specific methods and parameters. For instance, total assets are items owned by the farm
household for farming and non-farm work ( Table 2 ). For valuing assets, cost value and market
value of current, intermediate farm (1-10 years) and long-term ( > 10 years) assets are taken into
account. The cost value is the initial and improvement costs of assets minus depreciation. Mar-
ket value is an estimate of what the asset would sell for subtracting the associated selling cost.
Current assets include cash and other assets that can be easily converted to cash, such as cash
invested in growing crops and prepaid expenses. Intermediate farm assets are those assets with

Q. Li / Data in Brief 39 (2021) 107638
5
Table 1
Description of survey sampling across villages, in Mean (Standard Deviation)
Village
Topography
Altitude
(meters)
Distance to
markets
(km)
Farmland
per capita
(ha)
Ratio of
farmland
rented in
Ratio of
farmland
rented out
Variety of
crop
Ratio of
abandoned
land to total
arable land
Ratio of legume
sown area to
total sown area
Net income
per capita
(RMB)
Duration
off-farm
work (days)
Numer
(share) of
samples (%)
Houjiagou
V-shaped
valley
1110.67
(10.97)
8.50 (0.01)
0.29 (0.21)
0.17 (0.34)
0
4.0 0 (1.0 0)
0.52 (1.56)
0.12 (0.15)
11033.33
(11421.47)
175.56
(223.43)
9 (3.72)
Siyaoxian
V-shaped
valley
1197.46
(18.97)
12.15 (0.11) 0.24 (0.15)
0.07 (0.24)
0.05 (0.17)
4.08 (1.61)
0
0.18 (0.21)
22158.97
(21179.52)
186.92
(224.70)
13 (5.37)
Yanta
V-shaped
valley
1114.86
(3.08)
8.30 (0)
0.27 (0.12)
0.16 (0.20)
0
4.43 (1.40)
0.05 (0.14)
0.15 (0.12)
7061.90
(6979.66)
174.29
(250.27)
7 (2.89)
Yujiahe
V-shaped
valley
1190.93
(13.22)
16.55 (0.33) 0.39 (0.29) 0.05 (0.12)
0.07 (0.27)
3.43 (1.34)
0.02 (0.06) 0.01 (0.03)
19853.57
(18778.98)
14.88
(166.93)
14 (5.79)
Zhaiziwan
V-shaped
valley
1173.57
(19.68)
13.24 (1.19) 0.34 (0.23) 0.07 (0.14)
0.01 (0.05)
3.57 (1.02)
0.02 (0.04) 0.02 (0.04)
16214.29
(22398.02)
155.00
(187.93)
14 (5.79)
Gaojiamao
V-shaped
valley
1115.26
(21.23)
11.90 (2.84) 0.26 (0.26) 0.09 (0.20) 0.06 (0.21)
3.43 (2.06) 0.07 (0.21)
0.02 (0.05)
17302.17
(18759.90)
193.70
(215.23)
23 (9.50)
Yayao
V-shaped
valley
1133.43
(12.73)
10.43 (1.52) 0.26 (0.12)
0
0.07 (0.27)
4.14 (1.79)
0.05 (0.15)
0.05 (0.06)
23484.52
(14550.87)
225.86
(214.49)
14 (5.79)
Zhuanyaogou
V-shaped
valley
1049.73
(19.32)
3.04 (0.33) 0.17 (0.17)
0.23 (0.33)
0.06 (0.14)
2.0 0 (1.0 0)
0.24 (0.30)
0.02 (0.07)
14690.91
(14906.74)
124.55
(143.48)
11 (4.55)
Fangjiahe
V-shaped
valley
1068.29
(14.63)
5.24 (0.02)
0.20 (0.13)
0.13 (0.19)
0.14 (0.30)
3.21 (1.58)
0.23 (0.28) 0.15 (0.18)
22642.86
(22324.90)
140.71
(175.91)
14 (5.79)
Zhifanggou V-shaped
valley
1053.00
(6.84)
9.74 (0.03)
0.24 (0.18)
0.55 (0.31)
0
3.50 (1.87)
0.08 (0.15)
0.16 (0.14)
48991.67
(75880.90)
221.00
(220.14)
6 (2.48)
Chafang
Riparian
area
1052.15
(8.63)
7.23 (0.08)
0.06 (0.03) 0.07 (0.18)
0.22 (0.30) 2.05 (0.94) 0
0.43 (0.37)
23307.50
(14615.51)
299.50
(216.08)
20 (8.26)
Yunping
Riparian
area
1038.53
(7.68)
8.43 (0.02) 0.06 (0.04) 0.16 (0.37)
0.30 (0.35)
2.05 (0.78) 0.44 (1.91)
0.27 (0.26)
17517.54
(14286.75)
268.03
(286.42)
19 (7.85)
Hougoumen Riparian
area
1030.80
(3.59)
7.20 (0.01)
0.09 (0.05) 0.10 (0.19)
0.26 (0.28) 1.15 (0.59)
0.31 (0.22)
0.20 (0.34)
22765.00
(33366.65)
281.94
(213.75)
20 (8.26)
Yanjiawan
Riparian
area
1008.18
(9.22)
5.72 (0.02)
0.10 (0.09)
0.01 (0.04)
0.50 (0.40) 1.94 (1.34)
0.08 (0.23) 0.06 (0.14)
23464.71
(19749.78)
340.88
(270.00)
17 (7.04)
Lijiawan
Riparian
area
1005.62
(6.01)
1.70 (0)
0.11 (0.10)
0.05 (0.12)
0.64 (0.38) 0.91 (1.24)
0.15 (0.33)
0.15 (0.07)
34224.74
(10612.06)
510.22
(191.89)
23 (9.50)
Yangjiagou
Riparian
area
1052.15
(8.63)
7.23 (0.08)
0.06 (0.03) 0.07 (0.18)
0.22 (0.30) 2.05 (0.94) 0.23 (0.28) 0.43 (0.37)
23307.50
(14615.51)
299.50
(216.08)
20 (8.26)

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Q. Li / Data in Brief 39 (2021) 107638
Table 2
Item category in valuing total assets
Items
Farming
Non-farm work
Household
Current assets
GGP subsidy in 2013, received rent,
allowance, crop for feed, crop for
seed, crop for sale, animal for sale,
self-seed, self-manure, mulch
subsidy, fertiliser subsidy, the first
purchase of animal, value of feed
animal products, and value of
pasture.
Wage
Saving, allowance of health
insurance, credit, family gain,
allowance, pension, and vegetables,
fruits, eggs and animal meat for
food.
Intermediate
assets
GGP subsidy within ten years, pipe,
water tank, pump, lamp, animal for
breeding, machinery value, and
animal stock value.
Value of
equipment
Value of traffic tools.
Long-term
assets
Grassland, forest, fallow and
abandoned land, harvester, annual
cropland, perennial cropland,
seedlings, orchard, and tillage.
Investment
Value of drinking water system.
Fig. 2. Net income of off-farm work per capita in 2013.
a useful life of 1 to 10 years (e.g., machinery and breeding livestock), whereas long-term farm
assets have a useful life of more than ten years and usually can not be sold without disrupting
the business (e.g., land and buildings).
Moreover, crop frequency depicts the ratio of the months that farmland used in crop produc-
tion to one year. It is the inverse of fallow farmland ploughed and harrowed but left for months
without being sown. Farmers’ engagement in off-farm work ( Fig. 2 ) is analysed by destination
(i.e., work in local villages and communities, in the county and cities) and duration (i.e., migrant
and non-migrant). In particular, migrant work means that a household member leaves for work
for at least six consecutive months in a year. In addition, the calculation of total active work-
force in person-day equivalents, farmland fragmentation, family labour in per-capita equivalents,
livestock unit, net incomes and net margins, amount of nitrogen, phosphorus and potassium,
liquidity and solvency, and protein intake is described in the previous publications [1–4] . Farm
prices, which vary across households, were taken into account for goods and services.

Q. Li / Data in Brief 39 (2021) 107638
7
Fig. 3. Temperature and precipitation data of the study area from 1997 to 2014. a. annual maximum daily precipita-
tion and the two-period moving average; b. annual maximum and minimum temperature and the two-period moving
average; c. monthly maximum and minimum temperature and the two-period moving average; d. average annual pre-
cipitation and the two-period moving average.
Data about temperature and precipitation ( Fig. 3 ) of the study area is available from 1997 to
2014. It consists of annual maximum daily precipitation, annual maximum and minimum tem-
perature, average monthly temperature, monthly maximum and minimum temperature, average
monthly precipitation, and average annual precipitation. The data is observed and collected by
the weather station of the Institute of Water and Soil Conservation, Chinese Academy of Sciences
and Ministry of Water Resources.
Ethics Statement
This paper does not involve studies with animals and humans. The work of this paper meets
the ethical requirements for publication in Data in Brief ( https://www.elsevier.com/authors/
journal- authors/policies- and- ethics ).
Declaration of Competing Interest
The field survey did not receive financial support from any institution. The author declares
that he has no known competing financial interests or personal relationships that could have
influenced the work reported in this paper.

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Q. Li / Data in Brief 39 (2021) 107638
CRediT Author Statement
Qirui Li: Conceptualization, Methodology, Software, Data curation, Visualization, Investiga-
tion, Writing – review & editing.
Acknowledgments
The work of this paper was supported by the Institute of Water and Soil Conservation, Chi-
nese Academy of Sciences and Ministry of Water Resources, grant number A314021402-2018 .
The author is also supported by the Deutsche Forschungsgemeinschaft (DFG, German Research
Foundation) under Germany’s Excellence Strategy—EXC 2052/1—390713894 at the University of
Bayreuth. Technical and training support provided by the Leibniz Centre for Agricultural Land-
scape Research (ZALF) and Humboldt-Universität zu Berlin (HU) are greatly appreciated. The au-
thor thanks Dr. Peter Zander, Prof. Klaus Müller, Prof. Jijun Wang, Prof. Hao Feng, Prof. Sonoko D.
Bellingrath-Kimura and anonymous referees for their help and support. In particular, the author
is also grateful to all of the farmers who cooperated in the household survey.
References
[1] Q. Li, P. Zander, Resilience building of rural livelihoods in PES programmes: a case study in China’s Loess Hills, Ambio
49 (2020) 962–985, doi: 10.1007/s13280- 019- 01236- 4 .
[2] Q. Li, T.S. Amjath Babu, S. Sieber, P. Zander, Assessing divergent consequences of payments for ecosystem services on
rural livelihoods: a case-study in China’s Loess Hills, Land Degrad. Dev. 29 (2018) 3549–3570, doi: 10.1002/ldr.3082 .
[3] Q. Li, T.S. Amjath-Babu, P. Zander, Role of capitals and capabilities in ensuring economic resilience of land conser-
vation effort s: a case study of the grain for green project in China’s Loess Hills, Ecol. Indicators 71 (2016) 636–644,
doi: 10.1016/j.ecolind.2016.07.027 .
[4] Q. Li, T. Amjath-Babu, P. Zander, Z. Liu, K. Müller, Sustainability of Smallholder Agriculture in Semi-Arid Areas un-
der Land Set-aside Programs: a Case Study from China’s Loess Plateau, Sustainability 8 (2016) 395, doi: 10.3390/
su8040395 .
[5] Q. Li, H. Ma, Z. Xu, H. Feng, S. Bellingrath-Kimura, Balancing socioeconomic development with ecological conserva-
tion towards rural sustainability: a cas, Int. J. Sustain. Dev. World Ecol.(n.d.) 18. doi: 10.1080/13504509.2021.1990157 .
[6] Q. Li, Survey data on livelihood assets, activities and outcomes of smallholder farm households in China’s Loess
Plateau, (n.d.). doi: 10.17632/b2sjykvfgy.1 .