| Literature DB >> 35879410 |
Shuntao Xie1,2, Wenguang Ding3,4, Weifeng Ye1,2, Zhe Deng1.
Abstract
Global climate change affects all aspects of human society, especially agricultural and animal husbandry production. Northwest China has been detrimentally affected by the climatic variations due to its high exposure to extreme climatic events. A number of studies have reported agro-pastoralists' perceptions and adaptation responses to climate change, but the current knowledge of agro-pastoralists' perceptions of climate change in China are insufficient. To fill this research gap, this study aims to investigate the perception 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 the majority of respondents were aware (70%) of the changes in 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. The study recommends institutions targeting households' livelihood improvement and making decisions concerning climate change adaptation need to focus on mass media and information technology, improving locally adapted extension services, improved irrigation, expand loan channels.Entities:
Mesh:
Year: 2022 PMID: 35879410 PMCID: PMC9314332 DOI: 10.1038/s41598-022-17040-2
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.996
Figure 1Map of Gansu Province, China showing the survey area. Map of these distinct was drawn by ArcGIS 10.2(https://www.esri.com/).
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) |
| Jiuquan | 1477.2 | Precipitation (1988–2019) Temperature (1988–2019) |
Descriptive statistics of agro-pastoralist characteristics.
| Variables | Scales | Mean | SD |
|---|---|---|---|
| Gender | 1 = Male | 0.69 | |
| 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 | |
| 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 | |
| 1 = Yes | 0.63 | ||
| Insurance | 0 = No | 0.18 | |
| 1 = Yes | 0.82 | ||
| Association membership | 0 = No | 0.42 | |
| 1 = Yes | 0.58 | ||
| Village cadres | 0 = No | 0. 87 | |
| 1 = Yes | 0.13 | ||
| Weather information | 0 = No | 0.08 | |
| 1 = Yes | 0.92 |
Figure 2Trends of Annual precipitation, Annual rainfall, Annual snow.
Figure 3Trends of annual temperature.
Figure 4Trends of summer mean temperature.
Figure 5Trends of winter mean temperature.
Indicators of observed changes in climate.
| Variable | Increase | Decrease | Unpredictable | No changes | Don’t know |
|---|---|---|---|---|---|
| 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) |
| 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) |
Linear trends (mm/year, ℃/ year) of precipitation/temperature and perception of changes in climate. (RCC: Report of Climate Change; RI: Report Increased Precipitation/Temperature; RD: Report Decreased Precipitation/ Temperature).
| Jiuquan | Yongchang | Wshanling | Sunan | Minle | RCC (%) | RI (%) | RD (%) | |
|---|---|---|---|---|---|---|---|---|
| Sum Pre | 1.65 | 1.2 | 2.81 | 1.04 | 1.9 | 77 | 63 | 14 |
| Win Pre | 0.03 | 0.026 | 0.29 | 0.24 | 0.175 | 73 | 66 | 7 |
| Sum Tem | 0.04 | 0.6 | 0.04 | 0.03 | 0.045 | 83 | 75 | 8 |
| Win Tem | 0 | 0.01 | 0.005 | 0.014 | 0.022 | 69 | 54 | 15 |
Most influential factors determining agro-pastoralists’ perception of climate change.
| Variables | Coefficient | Robust Std. Err | |
|---|---|---|---|
| Gender | 0.13 | 0.02 | |
| Age | 0.075 | 0. 22 | 0.13 |
| Experience | 0.043 | 0.03 | |
| Ethnicity | −0.653 | 0.47 | 0.21 |
| Education | 0.031 | 0.02 | |
| household size | 0.19 | 0.44 | 0.73 |
| Cultivatedland size | 0.14 | 0.01 | |
| Grassland size | 0.23 | 0.59 | 0. 3 |
| Income | 0.29 | 0.74 | 0.56 |
| Agricultural income | 0.00 | 0.03 | |
| Livestock | 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. 16 | 0.00 | |
| Weather information | 0.12 | 0.00 |
**p < 0.01, *p < 0.05.
Significant values are in bold.
Figure 6Agro-pastoralists’ sources of information, about climate change.
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 | 11.73 | 24.9 | 3.15 | ||
| Housing security | 12.36 | 30.09 | 4.68 | ||
| Livestock loss | 15.74 | 18.74 | 5.32 | ||
| Crop/livestock diseases | 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 | 17.66 | 20.73 | 3.71 |
Significant values are in bold.
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 | 0.04 | 0.03 | |
| Ethnicity | − 0.13 | 0.09 | 0.82 |
| Education | 0.04 | 0.00 | |
| household size | − | 0.16 | 0.04 |
| Cultivatedland size | 0.02 | 0.00 | 0.08 |
| Grassland size | 0.00 | 0.00 | |
| Income | − 0.074 | 0.29 | 0.37 |
| Agricultural income | 0.01 | 0.03 | |
| Livestock | 0.037 | 0.40 | 0.12 |
| Association membership | 0. 24 | 0.02 | |
| Village cadres | 0. 36 | 0.00 | |
| Weather information | 0.915 | 0.31 | 0.09 |
Significant values are in bold.
Figure 7Agro-pastoralists’ adaptation strategies to climate change.