Agro-pastoralists' perception of climate change and adaptation in the Qilian Mountains of northwest China.

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.

Interannual variability of vegetation sensitivity to climate in China.

Many studies have assessed the relative sensitivity of ecosystems to climate change, and even optimized climate states from long-term averages to infer short-term changes, but how ecosystem sensitivity and its relationships with climate variability vary over time remains elusive. By combining the vegetation sensitivity index (VSI) and a 15 year moving window, we analyzed interannual variability in spatiotemporal patterns of vegetation sensitivity to short-term climate variability and its correlations with climatic factors in China over the past three decades (1982-2015). We demonstrated that vegetation sensitivity shows high spatial heterogeneity, and varies with vegetation type and climate region. Generally, vegetation in the southwest and mountainous regions was more sensitive, especially coniferous forests and isolated shrubland patches. Comparatively, vegetation in dry regions was less sensitive to climate variability than in wetter climates. Due to frequent climate variability in the early 1990s, a large increase in the VSI was detected in 1996. Significant increases in the interannual variability of vegetation sensitivity were observed in greater than 23.7% of vegetated areas and decreases in only 4.2%. Solar radiation was the dominant climate driver of vegetation sensitivity, followed by temperature and precipitation. However, climate controls are not invariable across a range of climatic conditions, such as precipitation exerted an increasing influence on changes of vegetation sensitivity. Quantitative analyses of ecosystem sensitivity to climate variability such as ours are vital to identify which regions and vegetation are most vulnerable to future climate variability.

Spatiotemporal dynamics of habitat suitability for the Ethiopian staple crop, Eragrostis tef (teff), under changing climate.

Teff (Eragrostis tef (Zucc.) Trotter) is a staple, ancient food crop in Ethiopia. Its growth is affected by climate change, so it is essential to understand climatic effects on its habitat suitability in order to design countermeasures to ensure food security. Based on the four Representative Concentration Pathway emission scenarios (i.e., RCP2.6, RCP4.5, RCP6.0 and RCP8.5) set by the Intergovernmental Panel on Climate Change (IPCC), we predicted the potential distribution of teff under current and future scenarios using a maximum entropy model (Maxent). Eleven variables were selected out of 19, according to correlation analysis combined with their contribution rates to the distribution. Simulated accuracy results validated by the area under the curve (AUC) had strong predictability with values of 0.83-0.85 for current and RCP scenarios. Our results demonstrated that mean temperature in the coldest season, precipitation seasonality, precipitation in the cold season and slope are the dominant factors driving potential teff distribution. Proportions of suitable teff area, relative to the total study area were 58% in current climate condition, 58.8% in RCP2.6, 57.6% in RCP4.5, 59.2% in RCP6.0, and 57.4% in RCP8.5, respectively. We found that warmer conditions are correlated with decreased land suitability. As expected, bioclimatic variables related to temperature and precipitation were the best predictors for teff suitability. Additionally, there were geographic shifts in land suitability, which need to be accounted for when assessing overall susceptibility to climate change. The ability to adapt to climate change will be critical for Ethiopia's agricultural strategy and food security. A robust climate model is necessary for developing primary adaptive strategies and policy to minimize the harmful impact of climate change on teff.

Diverse response of vegetation growth to multi-time-scale drought under different soil textures in China's pastoral areas.

The pastoral areas of China are mainly located in ecologically fragile regions, where its ecosystems are highly sensitive to drought trends. Although numerous studies have been carried out on the response of vegetation to droughts, it is not entirely clear whether soil properties can influence this relationship. Using the Normalized Difference Vegetation Index (NDVI) and the Standardized Precipitation Evapotranspiration Index (SPEI), covering the period 1982 to 2015, we carefully analyzed drought impacts on vegetation in China's pastoral areas, to determine the effects of vegetation communities and soil types on vegetation response to multi-time-scale drought. Significantly positive correlations between NDVI and SPEI were observed in most regions, properly indicating that vegetation was largely influenced by drought, particularly the pastures in Inner Mongolia. Generally, forest was sensitive to longer time-scales of droughts, while grassland and cropland showed a close relationship with shorter or median drought time-scales. However, noticeable differences were found on the Tibetan Plateau, mainly because drought was not the main factor affecting vegetation growth in the region. The NDVI-SPEI correlations and the corresponding SPEI time-scales of each soil texture differed considerably, even in areas of the same land cover type, revealing that soil properties, here mainly refer to soil texture (classified by fractions of each separate soil, i.e., sand, silt, and clay), can assuredly affect the resistance and resilience of vegetation to drought stress. The underlying mechanism is the difference in particle size and permeability which can alter the storage and position of available soil water, thus affecting water absorption by the root system. Our results highlight the considerable importance of properly integrating edaphic factors when exploring the impact of likely climate change on ecosystems.