Climate Variability and Land-use Change in Danangou Watershed, China—Examples of Small-Scale Farmers' Adaptation

Abstract

With global concern on climate change impacts, developing countries are given special attention due their susceptibility. In this paper, change and variability in climate, land use and farmers' perception, adaptation and response to change are examined in Danangou watershed in the Chinese Loess Plateau. The first focus is to look at how climate data recorded at meteorological stations recently have evolved, and how farmers perceived these changes. Further, we want to see how the farmers respond and adapt to climate variability and what the resulting impact on land use is. Finally, other factors causing change in land use are considered. Local precipitation and temperature instrumental data and interview data from farmers were used. The instrumental data shows that the climate is getting warmer and drier, the latter despite large interannual variability. The trend is seen on the local and regional level. Farmers' perception of climatic variability corresponds well with the data record. During the last 20 years, the farmers have become less dependent on agriculture by adopting a more diversified livelihood. This adaptation makes them less vulnerable to climate variability. It was found that government policies and reforms had a stronger influence on land use than climate variability. Small-scale farmers should therefore be considered as adaptive to changing situations, planned and non-consciously planned.

Forest Dependent Indigenous Communities’ Perception and Adaptation to Climate Change through Local Knowledge in the Protected Area—A Bangladesh Case Study

“…is very impressive as they interact directly with the nature. Similar observations have also been found by Mahmood et al [7], Anik and Khan [9], Chaudhary and Bawa [16], Byg and Salick [45], Mertz et al [46] and Apata [47], all of which indicate that climate is changing, while some other studies, such as Chaudhary and Bawa [16], Chaudhary et al [17], Hageback et al [48], Cabrera et al [49], Thomas et al [50] and Shrestha et al [51] have validated community perception with scientific evidence. Interestingly, indigenous people from tropical forest areas have reported that natural signals that were used to trigger activities in the past are now less reliable as the weather becomes hotter and the rainy season comes earlier or later than usual, which can lead to a disorientation of people in their daily lives [52].…”

Andean Land Use and Biodiversity: Humanized Landscapes in a Time of Change

“…2). Small-scale farmers studied in China by Hageback et al (2005) showed considerable potential adaptation to climate change, including the diversification of livelihoods. Bates (2002) found that another common response is out-migration by people from areas under environmental stress.…”

Local Perceptions and Responses to Climate Change and Variability: The Case of Laikipia District, Kenya

“…Local knowledge is based on practice and assists farmers to make informed decisions about how to respond to environmental changes and how to improve the amount and quality of their yield [13,[32][33][34][35][36][37][38]. The validity of local knowledge has been shown by scientists through comparison with quantitative climate data analysis [39][40][41][42]. The majority of studies show that farmers' resourcefulness matches quantitative data analysis: local knowledge is used to respond to the vagaries of climate such as droughts, famines, floods and other stresses that threaten crops and livestock [38,[39][40][41][43][44][45][46][47][48][49][50].…”

“…The validity of local knowledge has been shown by scientists through comparison with quantitative climate data analysis [39][40][41][42]. The majority of studies show that farmers' resourcefulness matches quantitative data analysis: local knowledge is used to respond to the vagaries of climate such as droughts, famines, floods and other stresses that threaten crops and livestock [38,[39][40][41][43][44][45][46][47][48][49][50]. However, there have also been cases where local knowledge failed to match quantitative climate data, making local knowledge seem unreliable, e.g., as reported from Kenya by Rao et al [51].…”