Agro-Pastoralists’ Perception of Climate Change and Adaptation in the Qilian Mountains, China

doi:10.21203/rs.3.rs-1117314/v1

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Agro-Pastoralists’ Perception of Climate Change and Adaptation in the Qilian Mountains, China

https://doi.org/10.21203/rs.3.rs-1117314/v1

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Global climate change affects all aspects of human society, especially agricultural and animal husbandry production. Northwest China has detrimentally affected by the climatic variations due to its high exposure to extreme climatic events. A number of studies have reported on agro-pastoralists' perceptions, adaptation and mitigation of climate change, but the current knowledge of agro-pastoralists' perceptions of climate change in China is insufficient. To fill this research gap, this study aims to investigate the cognition level of agro-pastoralists in Northwest China on climate change and related factors. Data were collected using a structured questionnaire based on household surveys of 554 study participants in four counties in Gansu Province, China. Raw data were collected using stratified random sampling. A probit model was used to analyze the respondents' understanding of climate change and its related socio-economic and demographic variables. Our results show that more than 70% of agro-pastoralists are perception of the changes of temperature and precipitation. Socioeconomic and demographic variables such as gender, farming experience, education level, cultivated land size, agricultural income, livestock, village cadre experience, access to weather information of agro-pastoralists are pertinently related to agro-pastoralists' awareness of climate change. Farming experience, education level, household size, grassland size, agricultural income, association membership, village cadre experience has a high impact on agro-pastoralists' adaptation to climate change. The results of this study will help guide government agencies and decision makers, and help arid and semi-arid areas to build sustainable adaptation measures under the framework of climate change.

Environmental Policy

Climate change

Adaptation

Perception

Adaptive capacity

In recent decades, with more and more scholars studying, global warming seems to be an indisputable fact. The IPCC (2014; 2018) report: The continuous intensification of greenhouse effect caused by human activities and greenhouse gas emissions are one of the important causes of global warming. Research shows that China's climate warming is basically synchronous with global warming, but there are significant regional and seasonal differences (Wang et al., 2019; Yang et al., 2020 Gao et al., 2018; The IPCC, 2014). In the face of these changes, it is of practical significance to study the characteristics and trends of temperature change in a certain region, to understand the characteristics of climate change in the region, to predict meteorological and climatic disasters, to rationally develop and utilize climate resources, and to improve the production environment of agriculture and animal husbandry.

Some of the most catastrophic effects of global warming on people's livelihoods will be in countries with a large agricultural population that are ill-equipped to cope with the social and political pressures associated with migration and deteriorating livelihoods. Many developing countries face similar challenges, and many case studies in these regions focus on and document the impact of climate change on livelihoods. Because these populations rely heavily on rain-fed agriculture, the effects of increasing weather change are amplified. Studies in many countries and regions show such climate change effects. Including Bangladesh, China, Ethiopia, Kenya, Tanzania, Nepal...... (Tan et al., 2009; Asare-Nuamah et al., 2019; Ng "ang" a, et al., 2020; Zhu et al., 2015; Roschel et al., 2018; Timilsina et al., 2019).

The perception of climate change varies from person to person, and individuals' awareness and belief about climate change and their political orientation will affect the perception of climate change (Deressa et al., 2009; Deng et al., 2012; Jin et al., 2015; Teferi et al., 2018; Shah and Wang, 2018). Although the way people perceive climate change and their personal understanding may not be accurate or complete, the perception and understanding of climate change can improve the effectiveness of climate change adaptation (Gandure et al., 2013; Tam and Mcdaniels,2013; Alam et al., 2017; Eric et al., 2018). Climate change adaptation is obviously regional and non-replicable, and there are local differences in adaptation capacity and adaptation resources (Aaheim et al., 2012; Lybbert and Sumner,2012; Filho et al., 2021; Tan et al., 2021). Therefore, "bottom-up" adaptation research is more targeted and more practical for local governments to carry out adaptation management and adaptation technical guidance (Bhave et al.,2014; Mhda et al.,2017; Thale and Seebauer, 2019). In the "bottom-up" experimental research, scholars have carried out many targeted studies based on the "perception-adaptation" analytical framework (Apata et al.,2009; Below et al.,2015; Eric et al., 2018), perception is the premise and basis of adaptation decision and choice, but the final adaptation decision and action is also affected by various social, economic, environmental and individual factors. For example, Temesgen et al.(2009) studied farmers' adaptation to climate change in The Nile Basin of Ethiopia and showed that local farmers' adaptation actions were mainly affected by information access, gender, age, education level and other factors. The study of Abid et al.(2014) on Punjab Province in Pakistan showed that education, farming experience, family size, land area, access to market information and the ability to obtain weather forecast information were the main factors affecting the selection of adaptation measures by local farmers. Addisu et al.(2016) found that age, education level, assets, extended agricultural services and distance from health centers were significant influencing factors for local climate change adaptation decisions through investigation and analysis of rural residents in Tana Basin lake region of Ethiopia.

The study area is located in the Qilian Mountains in northwest China, which is a typical area of fragile ecological environment, including the Qilian Mountain National Nature Reserve, also known as the Qilian Mountain National Park. After the establishment of the reserve, the government strictly controlled the number of livestock and strengthened the balance management of grass and livestock, which forced agro-pastoralists to make adaptive changes and reduce the impact of this change on themselves. Based on the data of Participatory Rural Appraisal (PRA), this paper takes four counties involved in the protected area as the research area, and uses qualitative and quantitative methods. The main research contents are as follows :(1) assess the perception of climate change by agro-pastoralists in the research area, and whether the perception of climate change is accurate? (2) Analyze the factors affecting agro-pastoralists' perception of climate change; (3) understand the perception of the impact of climate change on agro-pastoralists' livelihood; (4) explore the impact of agro-pastoralists' characteristics on adaptation to climate change.

2.1. Study Area Information

The research area is located at the northern foot of Qilian Mountain and in the central and western part of Gansu Province. The research focuses on 4 deliberately selected counties and some villages under their jurisdiction, mainly villages near qilian Mountain Nature Reserve(figure 1). The study area is generally 2000-3500 meters above sea level, distributed shiyang River, Heihe River, shule River three major water system. It is an arid/semi-arid/sub-humid climate with an average annual temperature of 3.6 and an average annual precipitation of 256.1-411.3mm, which is concentrated in June to September. There are more than 20 ethnic groups, including Han, Yugur, Tibetan, Hui, Mongolian, Tu, Manchu, Dongxiang, Uygur, Hasak and so on。

The main economic activities include: grain crops (wheat, corn, barley, highland barley, beans, potato), cash crops (rape, flaps, beets, Chinese medicinal materials, vegetables, watermelon); Breed structure (sheep, goats, cattle, pigs, chickens, horses and other domestic animals). Due to the increasing climate disasters, grassland ecosystem degrades, grassland biodiversity declines, and even becomes the source of sandstorms. At the same time, the decrease of grassland growth leads to the decrease of livestock capacity, which indirectly leads to the decline of herdsmen's income level. In addition, the occurrence of some extreme climate events has a dual impact on forage supply and livestock, and may lead to the increase of "white disaster" and "black disaster" and dust disaster. There is a serious time dislocation between precipitation and crop growth, which also brings great challenges to agricultural production.

This has prompted government agencies to intervene in the region to raise agro-pastoralists' awareness and adopt climate change risk mitigation strategies through training and capacity-building initiatives. Planting: Adjust the distribution of crop varieties and planting systems according to the trend of climate change, cultivate drought-tolerant crop varieties, improve the multiple cropping index and resist natural disasters. Animal husbandry: implement balance between grass and animal husbandry, promote and popularize quantitative grazing, rest grazing and rotational grazing models based on changes in grassland productivity, optimize the structure of herds, strengthen the construction of forage storage warehouses and insulation sheds and other facilities, promote ecological animal husbandry and "complementary farming and animal husbandry" production mode.

2.2. Sample Selection

Cross-sectional household survey was conducted by Multistage Random Sampling Techniques. Firstly, three cities involved in the protected area were selected (Administrative divisions at the prefecture level, namely Zhangye, Wuwei, Jinchang); then, one or two county (a city or prefecture comprises several unions) was selected from each city; after that, two or three towns (a county comprises several towns) was selected from each county, and 3 villages were chosen randomly from each towns. Finally, the study covers 3prefectures, 4counties, 12towns, and34 villages). During the survey, the study followed the sampling strategy of the Household Income and Expenditure Survey (HIES) and interviewed fifteen to twenty farm households from each village as a sample (RSID, 2008).

The formal investigation took the form of household face-to-face interviews, focusing on interviews with principals and village cadres of specialized agricultural and animal husbandry cooperatives. A total of 34 village-level questionnaires were completed, including 565 sample households, of which 554 households had effective questionnaires, with an effective rate of 98.05%.

The initial research permit was approved by the head of research, including the school, the head of the county government office, the head of the agriculture and Rural Affairs Bureau, the head of the village and the head of the reserve administration, paving the way to seek the consent of the respondents and participants. Seek the oral informed consent of agro-pastoralists and typical figures in the village. Voluntary participation was also insisted upon and respondents/participants received detailed information about the study objectives to avoid deception. In the case of interview, participants choose the place and way of interview, and try to avoid the presence of many people or persons in charge, so that the interviewees can show their true self and be willing to give truthful answers. Face-to-face interviews and telephone interviews were conducted according to the participants' own reasons.

All the agro-pastoralists conducted face-to-face interviews at their homes or designated places. In the case of village leaders, face-to-face and telephone interviews were used. Face-to-face interviews took place in homes, shops, workplaces and farms. Interviews lasted about 25 to 35 minutes and were recorded with the consent of a large group of participants. All the survey interviews agro-pastoralists were conducted in localdialects or minority languages, eventhough some officers used both Mandarin and local dialects.

In addition, before the formal survey, we also selected Huangcheng Town of Sunan Yugur Autonomous County and Haxi Town of Tianzhu Tibetan Autonomous County as the survey areas for the preliminary survey(Table 1), so as to ensure the scientific and practical design of the questionnaire. In addition, in the process of questionnaire survey, centralized inspection and review of each questionnaire should be carried out in time to ensure the completeness and accuracy of questionnaire data.

The structured questionnaire used to collect respondents' information mainly includes five parts: the basic characteristics of agro-pastoralists, awareness of climate change, climate change and disaster effects, and cognition and adoption of coping behaviors of agro-pastoralists; village information structured questionnaire mainly includes three parts, including the basic characteristics of the village, climate change and adaptation measures to support and use situation.

Table 1. Weather stations selected for the purpose of the study

District	Weather Stations	Altitude (meters)	Available data
Tianzhu	Wushaoling	3045.1	Precipitation (1988 – 2019) Temperature (1988 – 2019)
Milne	Milne	2281.4	Precipitation (1988 – 2019) Temperature (1988 – 2019)
Yongchang	Yongchang	1976.9	Precipitation (1988 – 2019) Temperature (1988 – 2019)
Sunan	Sunan	2311.8	Precipitation (1988 – 2019) Temperature (1988 – 2019)
Sunan	Jiuquan	1477.2	Precipitation (1988 – 2019) Temperature (1988 – 2019)

2.3. Data Analysis

The coding and analysis of qualitative and quantitative data used Microsoft Excel and the Statistical Product and Service Solutions (SPSS version 24.0).The meteorological data include diary records to calculate the average climatic values of seasons, months and years. The normality and outlier test are analyzed by using line diagram, box diagram and scatter diagram. In addition, frequency and percentage were used for descriptive statistics, and demographic independent variables (such as age, farming experience, years of education) and dependent variables (perception) were used for reasoning statistics, such as independent sample t-test and one-way analysis of variance (ANOVA)(Asare-Nuamah and Botchway2019).Based on the hypothesis, agro-pastoralists' perception of climate change and its impacts, and their socio-economic characteristics are the main factors influencing agro-pastoralists' adaptation choices. Probit model was used to evaluate the impact of selection variables on the respondents' perception and adaptation level. When the independent variables are composed of continuous variables and dummy variables, probit model is particularly suitable for the analysis of binary dependent variables. Assuming that it can predict the impact of independent variables on dependent variables, it is used to evaluate the impact of perception and socio-economic characteristics on family adaptation.

2.4. Ethics approval

The Lanzhou University Ethical Committee has approved that this study complies with the ethics of scientific research described in the Ethical Review of Biomedical Research Involving People of China and other applicable ethical principles and legislation in China. Ethical approval was granted by the Lanzhou University Research Administration and Advancement, Research Ethics Sector, Ethical Committee.

2.5. Consent to participate

Respondents volunteered to participate autonomously without their identity being recorded. Informed consent was obtained from all the participants in the study. Consent to participate was voluntary and approved by the Lanzhou University Ethical Committee.

3.1. Basic information of interviewees

Table 2 shows the demographic characteristics of agro-pastoralists. More than half of the respondents were males (69%). The respondents were on average 41.3 years old while more than 32 years of farming experience. The study area consists of minorities nationality (Tibetan, Yugur, Mongolian, Hui, etc.) and Han. In most cases, the main livelihood activity of minorities nationality are livestock, while Han main livelihood activities are farming. The majority of respondents (64%) were minority nationality. The vast majority of the agro-pastoralists (86%) have a primary school education or above, even though only 1% of them have Undergraduate education or Above. The results also reveal that 92% of respondents have access to weather information. The averages of 10.23 Mu of cultivatedland and 156.21 Mu Grassland, respectively. The average per family income is RMB78000, and agricultural income s RMB52000.

Due to their long-term farming experience, the agro-pastoralists were expected to have a high-level of understanding of local climate knowledge. Also contributing to this could be the information they receive about climate change and for some, the associated training through agro-pastoralists’ associations. Therefore, they also have a propensity to adapt to adverse conditions resulting from climate change impacts. In addition, the high-level of farming experience, the cultivated-land size, grassland size, Credit loan, Insurance, Village cadres all have a positive impact on the level of agro-pastoralists' adaptation to new climate scenarios.

However, the education level and cadres experience may be the major limiting factors for adopting specific long-term adaptation strategies. Ethnicity and gender are also expected to be key factors influencing awareness and adaptation to climate change. Minorities and Han may observe and understand the change in climate and related impacts differently because of their cultural ecology. (the main livelihood activity of minorities nationality are livestock, while Han main livelihood activities are farming.) In terms of gender, women in rural areas are less mobile and have less access to information and rights. They are also heavily involved in domestic work. However, men may have easier access to information (socializing, going out to work, etc.) Therefore, male headed households are expected to be more likely to adapt to the impact of climate change.

Table 2. Descriptive statistics of agro-pastoralist characteristics

Variables	Scales	Mean	SD
Gender	1 = Male	0.69
Gender	2 = Female	0.31
Age	1 for each year	41.3	15.72
Experience	1 for each year	32.04	14.31
Ethnicity	1= Han nationality	0.36
Ethnicity	2= Minority nationality	0.64
Education	0= Illiterate	0.14
	1=Primary	0.51
	2=Junior	0.23
	3=Senior or Adult education	0.11
	4=Undergraduate or Above	0.01
household size	1 for each person	3.87	1.34
Cultivatedland size	Mu	10.23	3.27
Grassland size	Mu	156.1	38.31
Income	Thousand RMB¥	78	21.76
Agricultural income	Thousand RMB¥	52	19.62
Livestock	1 for each livestock	128.3	34.74
Credit loan	0 = No	0.37
Credit loan	1 = Yes	0.63
Insurance	0 = No	0.18
Insurance	1 = Yes	0.82
Association membership	0 = No	0.42
Association membership	1 = Yes	0.58
Village cadres	0 = No	0. 87
Village cadres	1 = Yes	0.13
Weather information	0 = No	0.08
Weather information	1 = Yes	0.92

3.2. Climate change trend in the study area

Figure 2 shows the trend of annual precipitation, annual rainfall and annual snow at different meteorological stations in the study area. As shown in the figure 2, precipitation, rainfall and snow show an increasing trend, but the increase range of snow (0.0325-0.375/a) is significantly lower than that of precipitation(1.22-3.1/a) and rainfall (1.04-2.81/a). Similarly, through the inspection, it is found that the Multicollinearity among precipitation, rainfall and snow at each meteorological station is obvious (most R² > 0.5, and p < 0.01 or 0.05). The oscillation mode of rainfall shows that most of the highest rainfall over the past 32 years occurs in 2019, Indicating the wettest year , while 1991 was the driest year over the same period (see Figure 2). IPCC AR5 pointed out that the global climate system will continue to warm in the future, global precipitation will increase, and water cycles will accelerate, but there are significant regional differences (IPCC, 2013). From 1960 to 2014, the precipitation increased by 6.95 mm/10a (Wang et al., 2018), and increased largest in summer (Wang et al., 2018; Fu et al., 2018). Studies have shown that the precipitation and its extreme value increased significantly in the eastern and central part of the Qilian Mountains, and the central was most sensitive to climate warming (Jia et al., 2014). IPCC(2014; 2018) pointed out that climate is the limiting factor affecting agricultural production, especially in inland areas. On the one hand, the temperature fluctuates and rises continuously, the sowing date of crops is advanced, and the growth period of crops becomes longer; On the other hand, the annual fluctuation rate of precipitation increases, and the uncertainty of "rainy year" and "dry year" increases the change of crop yield.

In Figure 3, the trends of annual (mean, max, min) temperature are presented. The results show an increase in mean, maximum and minimum temperature. The annual average temperature increases of each station were 0.3/10a (Jiuquan), 0.42/10a(Milne), 0.34/10a (Wushaoling), 0.18/10a (Sunan) and 0.44/10a(Yongchang) , respectively. Overall, this is significant(p＜0.01) for the annual mean temperature, annual maximum temperature and annual minimum temperature in the study area.

Figure 4 also shows rising summer (mean, max, min) temperature and Figure 5 shows rising winter (mean, max, min) temperature. The increasing trend of annual temperature and summer temperature is significant more winter.

These findings are consistent with previous studies which revealed rising temperature in Qilian Mountains(Gao et al., 2018; Guan et al.,2013; Yang et al., 2020; Wang et al., 2019; Xiang et al., 2021 ). The temperature rise provides a favorable environment for carbon 3 and carbon 4 crops, such as wheat, barley, corn and beans. However, the increase of temperature leads to the increase of crop evapotranspiration, which reduces agricultural productivity to a certain extent (IPCC, 2018). The study also reports that rising temperatures have a negative impact on Livestock Reproduction and growth and expose livestock to pasture and water challenges (Rojas-Downing et al., 2017; Feng et al., 2021). The rampant spread of pests and diseases have also been related to climate change ( Jasrotia et al., 2020; Hari et al., 2014; FAO, 2018). The increasing trend of annual temperature and summer temperature is significant more winter.

3.3 Respondents’ perception of climate change

The climate change perception of agro-pastoralists are presented in Table 3. Among the 565 agro-pastoralists, 554 had heard about climate change and about 500 believed that climate is changing. Agro-pastoralists understood climate change by different indicators. In the case of temperature, a vast majority of the respondents (83.03%, summer /68.95%, winter) perceived that there have been changes in temperature in the district. Similarly, there have been changes in rainfall in the district as reported by 77.08%(rainfall)/72.74%(snow) of the respondents. In terms of quantity, the majority of the respondents(39.53%) perceive a decrease in rainfall, the next majority of respondents (37.55%) feel that rainfall is increasing . and about 4.69%/7.58% respondents feel that rainfall is unpredictable in terms of quantity (sometimes high,sometimes low).

Regarding the changes in temperature, the majority of respondents have noticed the rising summer temperature (71.3%), while 11.73% of the respondents perceive that the decreasing summer temperature. For the winter temperature, nearly 32.31% perceive that winter is becoming colder while nearly equal percentage of the respondents (36.64%) perceive that winter is getting warmer. In our study, there are 3.25% - 7.58% of respondents who do not perceive any changes in temperature; yet this is nearly equal compared to those who did not perceive any changes in rainfall. Climate variables particularly rainfall and temperature have been extensively studied as they are perceived to be significant to the agricultural activities of agro-pastoralists (Zhu et al., 2018; Teresiah, 2020 ;Yang et al., 2021).

Table 3. Indicators of observed changes in climate

Variable

Increase

Decrease

Unpredictable

No changes

Don’t know

A. Precipitation

Rainfall

37.55

(208)

39.53

(219)

9.57

(53)

5.78

(32)

7.58

(42)

Snow

47.29

(262)

25.45

(141)

19.13

(106)

3.43

(19)

4.69

(26)

B. Temperature

Summer

71.30

(395)

11.73

(65)

5.23

(29)

8.48

(47)

3.25

(18)

Winter

36.64

(203)

32.31

(179)

14.26

(79)

9.21

(51)

7.58

(42)

3.4 Agro-pastoralists’ sources of climate change information

Availability and accessibility of information on climate change are assumed to be key determinants of the extent of agro-pastoralist awareness, understanding and knowledge of climate change impacts (Ajayi 2014). This research, therefore, explored the different ways that agro-pastoralists received information about climate change. The results are reported in Fig. 6. Figure 6 reveals that the respondents received information about climate change mainly from personal experience (73.37%), internet(53.25%), television(42.06%). Other sources such as radio(12.27%), family/friends (15.34%), association/extension (5.78%), newspaper/magazine(3.79%) and Other(1.44%) were far less important. Recently, communication devices (e.g., mobile phones, computers) that provide access to the internet play an important role for socioeconomic development in agro-pastoralist areas and may be relevant to spread information about climate change among agro-pastoralists.

3.5 Determinants of agro-pastoralists’ perception

In order to further understand the relationship between Agro-pastoralist population characteristics and climate change perception, multiple regression (probit) analysis was used(table 4).With the increase of experience, education, cultivatedland size, agricultural income, livestock, village cadres, access to weather information, agro-pastoralists' awareness of climate change has increased significantly. The results also show that female are more sensitive to climate change than male.

The gender of respondents is a significant explanatory determinant(p-value is 0.02, coefficient is 0.325). In other words, women have more information and experience than men. This may be because in agricultural production, particularly in the planting and livestock sectors, women work significantly longer hours than men and are more sensitive to climate change(Ding et al.,2018). The dependent variable significance of farming experience and their awareness of climate change (p-value 0.000, coefficient positive 0.39) indicates that experienced agro-pastoralists are more aware of climate change than inexperienced agro-pastoralists. These results are consistent with the findings of Eric et al. (2018).These results are consistent with the findings of Funatsu et al. (2019). The variables of respondents' education level were highly significant (P value 0.01, coefficient 0.023). This means that agro-pastoralists are exposed to more climate events as their education level improves. This may be because well-educated agro-pastoralists are more sensitive to climate change because they are more scientific and technologically literate. These results are consistent with the findings of Maddison (2007) and Fahad et al. (2020).

The variables cultivatedland size, agricultural income and livestock have indicated a significant relationship with dependent variable at (p-value 0.01 and coefficient 0.023), (p-value 0.03 and coefficient 0.01) and (p-value 0.02 and coefficient 0.001), respectively. This reveals that with the increase of cultivatedland size, agricultural income and livestock, agro-pastoralists are more likely to be aware of climate change. These results are consistent with the findings of Oduniyi(2014) , Mudombi et al.(2014) and Huong et al. (2018).

Village cadres and access to weather information variables have showed (coefficient 0.309, 0.233 and p-value 0.00, 0.00, respectively), which indicate that the agro-pastoralists who have the experience of serving as village cadres and have sufficient information or knowledge about climate change have higher awareness of climate change. Compared with ordinary agro-pastoralists, village cadres have a higher level of education and a richer social network, which can help collect and analyze information and improve understanding. In the interviewed areas, the main sources of information mentioned by agro-pastoralists are personal experience, internet and television. Our research findings are in line with (Ellis, 2000; Deressa et al., 2009; Pondorfer,2019)

Table 4. Most influential factors determining agro-pastoralists’ perception of climate change

Variables	Coefficient	Robust Std. Err.	p-value
Gender	0.325*	0.13	0.02
Age	0.075	0. 22	0.13
Experience	0.174*	0.043	0.03
Ethnicity	-0.653	0.47	0.21
Education	0.069*	0.031	0.02
household size	0.19	0.44	0.73
Cultivatedland size	0.023 **	0.14	0.01
Grassland size	0.23	0.59	0. 3
Income	0.29	0.74	0.56
Agricultural income	0.01*	0.00	0.03
Livestock	0.001*	0.00	0.02
Credit loan	1.578	0.53	0.32
Insurance	1.13	0.65	0.14
Association membership	0.542	0.34	0.00
Village cadres	0.309**	0. 16	0.00
Weather information	0.233**	0.12	0.00
*p < 0.01, p < 0.05

3.6. Agro-pastoralists’ perceptions of climate change impacts

The research investigated how respondents perceived the impact of climate change on their livelihoods, especially on crop planting area, pasture quality, housing security, livestock loss, crop/livestock diseases, harvest time, seeding/calving time and agricultural income. Respondents were asked to explain to what extent variability in rainfall and temperature affected their livelihoods. The response frequency is reported in Table 4(where 5 =High, 4=Medium, 3= low,2=No and 1=Don't know).

Respondents have different views on the impact of climate change(table 5). More than 50% of respondents said that climate change had a medium or above impact on pasture quality housing security livestock loss crop / livestock diseases agricultural income, and these variables were greatly affected by climate change. As for the planting area, the agro-pastoralists who are mainly planting are the most affected. Among the respondents, nearly 15% disclosed that they have abandoned part of the land or are ready to abandon it; With regard to harvest time and harvesting / calving time, more than 70% said that the impact was small or not, but the survey showed that nearly 10 people said that the seeding time was ahead of schedule, and the calving time also changed, which may be related to the introduction of new varieties.

Table 5. Agro-pastoralists’ perceptions of climate change impacts

Variables	High	Medium	low	No	Don't know
Crop area	15.8	29.27	42.5	10.09	2.34
Pasture quality	38.4	21.82	11.73	24.9	3.15
Housing security	35.27	17.6	12.36	30.09	4.68
Livestock loss	27.9	32.3	15.74	18.74	5.32
Crop/livestock diseases	29.6	34.6	13.47	19.52	2.81
Harvest time	12.1	8.4	43.75	29.48	6.27
Seeding/calving time	7.8	16.9	31.26	41.91	2.13
Agricultural income	22.3	35.6	17.66	20.73	3.71

3.7. Factors affecting agro-pastoralists' adaptation to climate change

In the face of the impact of climate change, agro-pastoralists in the study area will take a variety of measures to cope with the impact of climate change. In order to describe the diversification degree of agro-pastoralists' adaptation strategies to climate change, the adjustment strategies adopted by agro-pastoralists in the study area are selected to evaluate their livelihood adaptability. Firstly, each adaptation measure of agro-pastoralists is assigned a value of 1. For example, if respondents adopt two adaptation measures of planting/breeding structure and improved varieties, the diversification index of adaptation strategies is 2, and the value is the livelihood adaptability of a single respondent. The indicators of respondents' livelihood adaptability include adjusting planting/breeding structure, land transfer, learning new technologies, improving varieties, regulating irrigation, storing forage, treating livestock, building pens, building greenhouses, dumping farms, digging Wells, going out to work, borrowing money and buying insurance.

The probit model is used to evaluate the impact of selected variables on livelihood adaptability to the impact of climate change. A summary of the results is given in Table 6. The results in Table 6 show that the age, education, household size, grassland size, agricultural income, Association membership and village cadres significantly affect the adaptability of respondents.

Experience has a positive and significant impact on adaptation to climate change. Probit analysis showed that experience increased the adaptation similarity of respondents by 5.3%. Households headed with rich agricultural experience are more likely to adapt to the impact of climate change. Our findings are consistent with (Maddison ,2007; Thoai et al., 2018; Ojo et al., 2021; Shahid et al., 2021),who revealed that farming experience and relevant adaptation measures have a significant impact on the adoption of adaptation measures.

Education is considered an important factor in adapting to climate change. Table 6 shows that education has a significant positive impact on respondents' adaptation to climate change impacts. An increase in formal education by one level was associated with a 8.1% increase in the likelihood of family adaptation. Our findings are consistent with (Fosu-Mensah et al., 2012; Thoai et al., 2018; Khanal et al., 2018, 2019),who revealed that education level is an important factor affecting the possibility of agro-pastoralists' adaptation to climate change.

The variable of household size shows that the ability of respondents to adapt to climate change increases with the increase of household size. Our findings are consistent with (Khanal et al., 2019; Jha and Gupta, 2021; Shahid et al., 2021),who revealed that household size affects respondents' adaptive decision-making. However, our findings are in disagreement with (Fahad et al., 2020) who reported an inverse relationship of household size with adaptability.

Table 6 shows a significant positive correlation between Grassland size, Agricultural income and adaptation. Respondents with a high Grassland size are more likely to adapt to climate change. The higher Agricultural income is, the more chance the family has to adapt to climate change. Our findings are consistent with (Roco et al., 2014; Arunrat, et al., 2017),who revealed that household size affects respondents' adaptive decision-making.

Association membership positively and significantly affects adaptation to climate change impacts. Table 6 shows that Association membership has a significant positive impact on respondents' adaptation to climate change. When one Association is added, the family's adaptive capacity increases by 87.8 percent. Our findings are consistent with (Roco et al., 2014; Johnson and Brown, 2017), who revealed that intensity of adaptation is greatly affected by farm organizations or associations.

The experience of village cadres has a significant positive effect on climate change adaptation. When one Association is added, the family's adaptive capacity increases by 87.8 percent.

The experience of village cadres has a significant positive effect on climate change adaptation. If there is village cadre experience, adaptability increases by more than one. It is easier for village cadres to take advantage of their positions to obtain information and take adaptive measures

In order to reduce the negative impacts of climate change and maintain the livelihoods of rural households, it is necessary to improve the education level of agro-pastoralists, strengthen the capacity of community organization building and information dissemination services, and help agro-pastoralists better implement appropriate climate change management strategies.

Table 6. Most influential factors determinants agro-pastoralists’ adaptation to climate change

Variables	Coefficient	Robust Std. Err.	p-value
Gender	-0.023	0.03	0.57
Age	0.047	0.37	0.11
Experience	0.053*	0.04	0.03
Ethnicity	-0.13	0.09	0.82
Education	0.081**	0.04	0.00
household size	-0.31*	0.16	0.04
Cultivatedland size	0.02	0.00	0.08
Grassland size	0.00**	0.00	0.00
Income	-0.074	0.29	0.37
Agricultural income	0.017*	0.01	0.03
Livestock	0.037	0.40	0.12
Association membership	0.878*	0. 24	0.02
Village cadres	1.073**	0. 36	0.00
Weather information	0.915	0.31	0.09

Agro-pastoralists' perception level is affected by several factors, such as socioeconomic factors and demographic factors. In this study, a random sampling method was used to sample 400 agro-pastoralists from four counties of Gansu province in northwest China. Our results show that the majority of respondents in the survey area (study area) are aware of climate change. The findings indicate that respondents who are severely affected by the adverse effects of climate change are more likely to be aware of climate change. The main factors that significantly affect respondents' understanding of climate change are gender, Farming experience, education level, cultivated land size, agricultural income, Livestock, village cadre experience, access to weather information. We further investigated agro-pastoralists' perception of climate change and their adaptation behaviors. Among the variables of study participants and adaptability, farming experience, education level, household size, grassland size, agricultural income, association membership, Village cadre experience is closely related to the adaptability of agricultural and pastoral personnel. In addition, our findings indicate that agro-pastoralists surveyed indicated that they had adopted aggressive adaptation strategies. In addition, our analysis of respondents' adaptive and perceived behavior provides a comprehensive understanding of the importance of climate in determining the effectiveness of agricultural programs. Moreover, our findings could help government officials and agricultural extension workers expand their services and raise awareness of climate change in areas most vulnerable to climate hazards.

While the study was limited to Gansu province in northwest China, the results of the study could be applied to other regions where adaptation to climate change remains ineffective. The study's recommendations help policy makers and researchers develop the necessary strategies and provide respondents with facilities to deal with climate risks. However, necessary action is needed to raise awareness of climate change. These efforts could focus on deep-seated adaptation measures, such as the use of high-yielding varieties and diversification of agro-pastoral operations. To strengthen such actions, policies and adequately supported approaches are needed to strengthen the capacity of agro-pastoralists to invest in adaptation strategies. It is suggested that agro-pastoralists' understanding of climate change and adaptation measures should be supported by mass media and information technology through agricultural and animal husbandry associations.

Declaration of competing interest

The authors declare no conflict of interest.

Acknowledgements

This work was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (grant no.XDA20100102), the National Key Research and Development Program (grant no.2019YFC0507405). We honor the contribution of people in the research site for their responses and support during the data collection.

Aaheim, A. , Amundsen, H. , Dokken, T. , Wei, T. , 2012. Impacts and adaptation to climate change in European economies, Global Environ. Change 22(4), 959-968, https://doi.org/10.1016/j.gloenvcha.2012.06.005.
Abid, M. , Scheffran, J. , Schneider, U. A. , Ashfaq, M. , 2015. Farmers' perceptions of and adaptation strategies to climate change and their determinants: the case of punjab province, pakistan. Earth Syst. Dynam. 6(1), 225-243. https://doi.org/10.5194/esdd-5-1359-2014.
Addisu, S. , Fissha, G. , Gediff, B. , Asmelash, Y. , 2016. Perception and adaptation models of climate change by the rural people of lake tana sub-basin, ethiopia. Environ. Syst. Res. 5(1), 1-10. https://doi.org/10.1186/s40068-016-0059-0.
Alam, G. , Alam, K. , Mushtaq, S. ,2017. Climate change perceptions and local adaptation strategies of hazard-prone rural households in Bangladesh, Clim. Risk Manag. 17, 52-63, https://doi.org/10.1016/j.crm.2017.06.006.
Apata, T. G. , Samuel, K. D. , Adeola, A. O. ., 2009. Analysis of Climate Change Perception and Adaptation among Arable Food Crop Farmers in South Western Nigeria. 2009 Conference, August 16-22, 2009, Beijing, China. International Association of Agricultural Economists. https://doi.org/10.22004/ag.econ.51365.
Arunrat, N. , Wang, C. , Pumijumnong, N. , Sereenonchai, S. , Cai, W. ,2017. Farmers' intention and decision to adapt to climate change: A case study in the Yom and Nan basins, Phichit province of Thailand. J. Clean. Prod. 143, 672-685, https://doi.org/10.1016/j.jclepro.2016.12.058.
Asare-Nuamah, P., Botchway, E.,2019. Comparing smallholder farmers' climate change perception with climate data: the case of adansi north district of ghana. Heliyon 5(12): 1-12, https://doi.org/10.1016/j.heliyon.2019.e03065.
Below, T. B. , Schmid, J. C. , Sieber, S. ,2015. Farmers' knowledge and perception of climatic risks and options for climate change adaptation: a case study from two tanzanian villages. Reg. Environ. Change 15(7), 1169-1180, https://doi.org/10.1007/s10113-014-0620-1.
Bhave, A. G. , Mishra, A. , Raghuwanshi, N. S. ,2013. A combined bottom-up and top-down approach for assessment of climate change adaptation options. J. Hydrol. 518( Part A), 150-161. https://doi.org/10.1016/j.jhydrol.2013.08.039.
Deng, M. , Qin, D. , Zhang, H. , 2012. Public perceptions of climate and cryosphere change in typical arid inland river areas of China: Facts, impacts and selections of adaptation measures. Quat. Int. 282, 48-57, https://doi.org/10.1016/j.quaint.2012.04.033.
Deressa, T. T. , Hassan, R. M. , Ringler, C. , Alemu, T. , Yesuf, M. , 2009. Determinants of farmers’ choice of adaptation methods to climate change in the Nile Basin of Ethiopia, Global Environ. Change 19(2), 248-255, https://doi.org/10.1016/j.gloenvcha.2009.01.002.
Ding, W. , He, L. , Zewudie, D. , Zhang, H. , Zafar, T. B. , Liu, X. ,2019. Gender and renewable energy study in Tibetan pastoral areas of China. Renew. Energ. 133, 901-913, https://doi.org/10.1016/j.renene.2018.10.065.
Eric, W. , Daniel, O. , William, O. ,2018. Perceptions of climate change variability and adaptation strategies on smallholder dairy farming systems: Insights from Siaya Sub-County of Western Kenya. Environ. Dev. 27: 14-25, https://doi.org/10.1016/j.envdev.2018.08.001.
FAO, 2018. Briefing Note on FAO Actions on Fall Armyworm in Africa. Rome, Italy.
Feng, X. , Qiu, H. , Pan, J. , Tang, J. , 2021. The impact of climate change on livestock production in pastoral areas of China. Sci. Total Environ. 770: 144838. https://doi.org/10.1016/j.scitotenv.2020.144838.
Filho, W. L. , Balogun, A. L. , Olayide, O. E. , Azeiteiro, U. M. , Ayal, D. Y. , Muñoz, P. D. C. , Nagy, G. J. , Bynoe, P. , Oguge, O. , Toamukum, N. Y. , Saroar, M. , Li, C. , 2019. Assessing the impacts of climate change in cities and their adaptive capacity: Towards transformative approaches to climate change adaptation and poverty reduction in urban areas in a set of developing countries, Sci. Total Environ. 692, 1175-1190, https://doi.org/10.1016/j.scitotenv.2019.07.227.
Fosu-Mensah, B. Y., Vlek, P. L. G., MacCarthy, D. S. , 2012. Farmers’ perception and adaptation to climate change: a case study of Sekyedumase district in Ghana Environment. Dev. Sustain. 14, 495–505, https ://doi.org/10.1007/s1066 8-012-9339-7.
Fu, J. , Cao, G. , Li, L. , Cao, S. , Tang, Z. , Yang, X. ,Jiang, G. ,Yu, M . , Yuan, .J. , Diao, E. , 2018. Analysis of Temporal and Spatial Variation Characteristics of Precipitation in the South Slope of Qilian Mountains and Its Nearby RegionsDueing 1960 - 2014. Res. Soil Water Conserv. 25(04):152-161, https://doi.org/10.13869/j.cnki.rswc.2018.04.023.
Funatsu, B. M. , Dubreuil, V. , A Racapé, Debortoli, N. S. , Tourneau, F. , 2019. Perceptions of climate and climate change by Amazonian communities. Global Environ. Change, 57, 101923, https://doi.org/10.1016/j.gloenvcha.2019.05.007.
Gandure, S. Walker, S. ,Botha, J. J. , 2013. Farmers' perceptions of adaptation to climate change and water stress in a South African rural community. Environ. Dev. 5, 39-53, https://doi.org/10.1016/j.envdev.2012.11.004.
Gao, L. , Gou, X. , Deng, Y. , Wang, Z. , Gu, F. , Wang, F. , 2018. Increased growth of Qinghai spruce in northwestern China during the recent warming hiatus. Agric. For. Meteorol. 260–261: 9-16. https://doi.org/10.1016/j.agrformet.2018.05.025.
Gao, X. , Huang, X. , Lo, K. , Dang, Q. , Wen, R. , 2021. Vegetation responses to climate change in the qilian mountain nature reserve, northwest china. Glob. Ecol. Conserv. 28: e01698. https://doi.org/10.1016/j.gecco.2021.e01698.
Guan, X. , Huang, J. , Guo, R. , 2017. Changes in aridity in response to the global warming hiatus. J. Meteorol. Res. 31(1), 117–125. https://doi.org/10.1007/s13351-017-6038-1.
Hagen, B. , 2013. Public Perceptions Of Climate Change: Risk, Trust, and Policy. Arizona State University: Doctoral Dissertation.
Hari C. Sharma, Chandra S. Prabhakar, 2014. Chapter 2 - Impact of Climate Change on Pest Management and Food Security: Integrated Pest Management. Academic Press, 23-36. https://doi.org/10.1016/B978-0-12-398529-3.00003-8.
Huong, N. T. L. , Yao, S. , & Fahad, S. , 2018. Assessing household livelihood vulnerability to climate change: the case of northwest vietnam. Hum. Ecol. Risk Assess. 25:5, 1157-1175. . https://doi.org/10.1080/10807039.2018.1460801.
IPCC. Summary for policymakers. In: Stocker, T.F., Qin, D., Plattner, G. K., Midgley, P. M. ,2013. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge Univ. Press, Cambridge, UK, and New York, 2013, 1535 pp.
IPCC, 2014. Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part B: Regional Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge.
IPCC, 2018. IPCC Special Report on the Impacts of Global Warming of 1.5℃ - Summary for Policy Makers. Incheon, Korea.
Jasrotia, P. , Yadav, J. , Kashyap, P. L. , Bhardwaj, A. K. , Singh, G. P. , 2020. Chapter 13 - Impact of climate change on insect pests of rice-wheat cropping system: recent trends and mitigation strategies. Woodhead Publishing, 225-239. https://doi.org/10.1016/B978-0-12-821316-2.00013-3.
Jha, C. K. , Gupta, V. , 2021. Farmer’s perception and factors determining the adaptation decisions to cope with climate change: An evidence from rural India. Environ. Sustain. Indic. 10(1): 100112, https://doi.org/10.1016/j.indic.2021.100112.
Jin, J. , Wang, X. , Gao, Y. , 2015. Gender differences in farmers' responses to climate change adaptation in Yongqiao District, China, Sci. Total Environ. 538, 942-948. https://doi.org/10.1016/j.scitotenv.2015.07.027.
Jia, W. , Zhang, Y. , Li, Z. ,2014. Spatial and Temporal Change of Precipitation Extremes in Qilian Mountains and Hexi Corridor in Recent Fifty Years. Scientia Geographica Sinica. 34(08), 1002-1009, https://doi.org/10.13249/j.cnki.sgs.2014.08.002.
Johnson, K. , Brown, M. E. , 2014. Environmental risk factors and child nutritional status and survival in a context of climate variability and change. Appl. Geogr. 54, 209-221, https://doi.org/10.1016/j.apgeog.2014.08.007.
Kang, X. , Shi, J. , Zhang, W. , Gai, Z. ,2018. Research on the current situation of the livelihood capital of the herdsman and its factors influencing the background of grazing prohibition subsidy policy inInner Mongolia. J. Arid Land Resour. Environ. 32(11):59-65. https://doi.org/10.13448/j.cnki.jalre.2018.334.
Khanal, U. , Wilson, C. , Hoang, V. N. , Lee, B. , 2018. Farmers' Adaptation to Climate Change, Its Determinants and Impacts on Rice Yield in Nepal. Ecol. Econ. 144, 139-147, https://doi.org/10.1016/j.ecolecon.2017.08.006.
Lybbert, T. J. , Sumner, D. A. , 2012. Agricultural technologies for climate change in developing countries: policy options for innovation and technology diffusion. Food Policy 37(1), 114-123, https://doi.org/10.1016/j.foodpol.2011.11.001.
Ma, Y., Zhao, X. , Lan, H. , Xue, B. ,2020. Livelihood risk multi-dimensional perception and influencing factors in key ecological function area: a case of the Yellow River Water Supply Area of Gannan. Acta Ecol. Sin. 40(5):1810-1824. https://doi.org/10.5846/stxb201902210307.
Maddison, D. , 2007. The perception of and adaptation to climate change in Africa (Vol.4308). Policy Research Working Paper Series.
Mhda, D. , Mlb, D. , Phb, D. , Fvc, D. , 2017. Why the ipcc should evolve in response to the unfccc bottom-up strategy adopted in paris? an opinion from the french association for disaster risk reduction - sciencedirect. Environ. Sci. Policy 78, 142-148, https://doi.org/10.1016/j.envsci.2017.10.001.
Mudombi, S. , Nhamo, G. , Muchie, M. , 2014. Socio-economic determinants of climate change awareness among communal farmers in two districts of zimbabwe. Africa Insight 44(2), 2-15. https://doi.org/10.10520/EJC164288.
Ng'Ang'A, T. W., Coulibaly, J. Y. , Crane, T. A. , Gachene, C. K. , Kironchi, G., 2020. Propensity to adapt to climate change: Insights from pastoralist and agro-pastoralist households of Laikipia County, Kenya. Clim. Change 161(3):393-413, https://doi.org/10.1007/s10584-020-02696-4.
Oduniyi, O.S., 2014. Climate Change Awareness: a Case Study of Small Scale Maize Farmers in Mpumalanga Province, South Africa. Master Thesi, University of South Africa. http://uir.unisa.ac.za/bitstream/handle/10500/13677/dissertation_oduniyi_os.pdf?seque.
Ojo, T. O. , Adetoro, A. A. , Ogundeji, A. A. , Belle, J. A. , 2021. Quantifying the determinants of climate change adaptation strategies and farmers' access to credit in South Africa. Sci. Total Environ. 792(1): 148499, https://doi.org/10.1016/j.scitotenv.2021.148499.
Pondorfer, A. , 2019. The perception of climate change: Comparative evidence from the small-island societies of Bougainville and Palawan. Environ. Dev. 30, 21-34. https://doi.org/10.1016/j.envdev.2019.04.002.
Reser, J. P. , Bradley, G. L. , 2020. The nature, significance, and influence of perceived personal experience of climate change. WIREs: Clim Chang11:e668, https://doi.org/10.1002/wcc.668.
Röschel, L., Graef, F. , Dietrich, O. , Schäfer, M. P. , Haase, D. , 2018. Individual Local Farmers’ Perceptions of Environmental Change in Tanzania. Water 10(4):525, https://doi.org/10.3390/w10040525 .
Roco, L. , Engler, A. , Bravo-Ureta, B. , Jara-Rojas, R. , 2014. Farm level adaptation decisions to face climatic change and variability: Evidence from Central Chile. Environ. Sci. Policy 44, 86-96, https://doi.org/10.1016/j.envsci.2014.07.008.
Rojas-Downing, M. M. , Nejadhashemi, A. P. , Harrigan, T. , Woznicki, S. A. , 2017. Climate change and livestock: Impacts, adaptation, and mitigation. Clima. Risk Manag. 16, 145-163, https://doi.org/10.1016/j.crm.2017.02.001.
RSID (Rural Socioeconomic Investigation Department, National Bureau of Statistics of China), 2008. The yearly statistical book of rural China 2008. Beijing: China Statistics Press.
Shah, F. , Wang, J. , 2018. Farmers' risk perception, vulnerability, and adaptation to climate change in rural pakistan. Land Use Policy 79, 301-309. https://doi.org/10.1016/j.landusepol.2018.08.018.
Shahid, R. , Li, S. , Shahid, S. , Altaf, M. A. , Shahid, H. ,2021. Determinants of reactive adaptations to climate change in semi-arid region of Pakistan. J. Arid Environ. 193(1), 104580, https://doi.org/10.1016/j.jaridenv.2021.104580.
Soubry, B. , Sherren, K. , Thornton, T. F. ,2020. Are we taking farmers seriously? A review of the literature on farmer perceptions and climate change,2007–2018. J. Rural Stud. 74:210-222.https://doi.org/10.1016/j.jrurstud.2019.09.005
Tam, J. , Mcdaniels, T. L. ., 2013. Understanding individual risk perceptions and preferences for climate change adaptations in biological conservation. Environ. Sci. Policy 27, 114-123, https://doi.org/10.1016/j.envsci.2012.12.004.
Tan, X. , Zhu, K. , Meng, X. , Gu, B. , Wang, Y. , Meng, F. , Liu, G. , Tu, T. , Li, H. , 2021. Research on the status and priority needs of developing countries to address climate change. J. Clean. Prod. 289, 125669, https://doi.org/10.1016/j.jclepro.2020.125669.
Tan, Y. , Feng, Z., Niu, B., Pan, X. , 2009. Investigation and analysis of villagers’ cognition and acts to the climate change in agro-pastoral ecotone. Chin. Agric. Sci. Bull. 25(23):413-419, https://doi.org/Y2009/V25/I23/413.
Teferi, M. G. , Degefa, T. , Negussie, S. , 2018. Perception and adaptation strategies of rural people against the adverse effects of climate variability: A case study of Boset District, East Shewa, Ethiopia. Environ. Dev. 27, 2-13, https://doi.org/10.1016/j.envdev.2018.07.005.
Thaler, T. , Seebauer, S. , 2019. Bottom-up citizen initiatives in natural hazard management: why they appear and what they can do?. Environ Sci Policy 94, 101-111. https://doi.org/10.1016/j.envsci.2018.12.012.
Thoai, T. Q. , Rañola. , R. F. , Camacho, L. D. , Simelton, E. , 2018. Determinants of farmers’ adaptation to climate change in agricultural production in the central region of Vietnam. Land Use Policy 70: 224-231, https://doi.org/10.1016/j.landusepol.2017.10.023.
Timilsina, A. P. , Malla, G. , Paudel, B. P. , Sharma, A. , Bhandari, H. , 2019. Farmer's perception on climate change and its consequences inkapilvastu district. Nepal. Int. J. Curr. Res. 11(5):3558-3561, https://doi.org/ 10.24941/ijcr.35138.05.2019.
Wang, X. , Chen, R. , Han, C. , Yang, Y. , Liu, J. , Liu, Z. , Song, Y. , 2019. Response of frozen ground under climate change in the qilian mountains, china. Quat. Int. 523:10-15. https://doi.org/10.1016/j.scitotenv.2020.143532.
Wang, X. , Pang, G. , Yang, M. , Wan, G. , Liu, Z. ,2018. Precipitation changes in the Qilian Mountains associated with the shifts of regional atmospheric water vapour during 1960-2014. Int. J. Climatol. 38(12),4355-4368, https://doi.org/10.1002/joc.5673.
Yang, L. , Feng, Q. , Adamowski, J. F. , Alizadeh, M. R. , Zhu, M. , 2020. The role of climate change and vegetation greening on the variation of terrestrial evapotranspiration in northwest china's qilian mountains. Sci. Total Environ. 759:143532. https://doi.org/10.1016/j.scitotenv.2020.143532.
Yang, S. , Yu, L. , Leng, G. , 2021. Livestock farmers’ perception and adaptation to climate change: panel evidence from pastoral areas in China. Clim. Change 164: 21, https://doi.org/10.1007/s10584-021-02992-7.
Zhu, G. , Qin D. , Ren, J. , Liang, F. , Tong, H. , 2018. Assessment of perception and adaptation to climate-related glacier changes in the arid Rivers Basin in northwestern China. Theor. Appl. Climatol. 133: 243–252 https://doi.org/10.1007/s00704-017-2181-y.
Zhu, G.F., Qin, D.H., Ren, J.W., Zheng, L.M., Liu, Y.F., Liang, F., Yang, L., Li, J,F., Hu, P.F., 2015. Perceptions and adaptation of herdsmen in typical mountainous minorty areas to climatic change：a case study of minority townships in Qilian Mountains. Clim. Chang Res. 11(05):371-378, https://doi.org/10.3969/j.issn.1673-1719.2015.05.011.

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Agro-Pastoralists’ Perception of Climate Change and Adaptation in the Qilian Mountains, China

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