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A primary goal of studying climate change adaptation is to identify the adaptation options that are used to improve crop productivity or reduce the negative impacts of climate change. Many of the adjustments in farm management that farmers adopt do not necessarily represent true adaptations to climate change, an issue often ignored in existing literature and resulting in a risk that policy makers are misled to think that adaptation is easier than it actually is, and thereby underestimate the challenge that climate change presents. The overall goal of this study is to identify whether farmers’ adoptions are enhancing food production and adapting to climate change. The identification uses a plot-level panel from a survey of 619 rural households in three provinces in China and county-level weather data. With the use of plot and county-by-year fixed effects as well as instrumental variable approaches, our estimates show that the autonomous adoptions are not effective in improving crop yields. This implies that farmers’ adoptions cannot be always considered adaptations to climate change. The paper provides a possible explanation for the results and concludes with policy implications. [ABSTRACT FROM AUTHOR]

China is the largest wheat-producing country in the world. Wheat is one of the two major staple cereals consumed in the country and about 60% of Chinese population eats the grain daily. To safeguard the production of this important crop, about 85% of wheat areas in the country are under irrigation or high rainfall conditions. However, wheat production in the future will be challenged by the increasing occurrence and magnitude of adverse and extreme weather events. In this paper, we present an analysis that combines outputs from a wide range of General Circulation Models (GCMs) with observational data to produce more detailed projections of local climate suitable for assessing the impact of increasing heat stress events on wheat yield. We run the assessment at 36 representative sites in China using the crop growth model CSM-CropSim Wheat of DSSAT 4.5. The simulations based on historical data show that this model is suitable for quantifying yield damages caused by heat stress. In comparison with the observations of baseline 1996-2005, our simulations for the future indicate that by 2100 the projected increases in heat stress would lead to an ensemble-mean yield reduction of −7.1% (with a probability of 80%) and −17.5% (with a probability of 96%) for winter wheat and spring wheat, respectively, under the irrigated condition. Although such losses can be fully compensated by CO fertilization effect as parameterized in DSSAT 4.5, a great caution is needed in interpreting this fertilization effect because existing crop dynamic models are unable to incorporate the effect of CO acclimation (the growth-enhancing effect decreases over time) and other offsetting forces. [ABSTRACT FROM AUTHOR]

Warming of the climate system is unequivocal, and the change of climate variables will eventually have a great impact on vegetation cover and agricultural practices, especially in the arid area Xinjiang in China, whose agriculture and ecosystems are heavily vulnerable to climate change. In this paper, normalized difference vegetation index (NDVI) was used to study the vegetation growth and its response to climate change in Xinjiang. Firstly, two NDVI datasets (Global Inventory Modeling and Mapping Studies (GIMMS) and Moderate Resolution Imaging Spectroradiometer (MODIS)) were merged through a pixel-wise regression analysis to obtain a long time series of NDVI data, and then, relationships between yearly NDVI and yearly climate variables, and monthly NDVI and monthly climate variables were extensively investigated for grassland and cropland in northern and southern Xinjiang, respectively. Results show the following: (1) there was an increasing trend in NDVI for both grassland and cropland in both northern and southern Xinjiang over the past decades and trends were significant except that for grassland in northern Xinjiang; (2) precipitation and evaporation were more important than temperature for grassland in northern Xinjiang, while precipitation and temperature were more important than evaporation for grassland in southern Xinjiang and cropland in both northern and southern Xinjiang; (3) NDVI was highly correlated with accumulated monthly precipitation instead of monthly precipitation, and there was a lagged effect of precipitation, temperature, and evaporation on NDVI change. However, lagged effects were only significant in specific months. The results could be helpful to agricultural practices; e.g., based on lagged effect of precipitation, irrigation in July is very important for crop growth. [ABSTRACT FROM AUTHOR]

Traditionally, the evaluation of pollen-based quantitative paleoclimate reconstructions focuses on the ability of calibration sets to infer present climatic conditions and/or the similarity between fossil and modern assemblages. Objective criteria for choosing the most appropriate climate parameter(s) to be reconstructed at a specific site are thus lacking. Using a novel approach for testing the statistical significance of a quantitative reconstruction using random environmental data, in combination with the advantageous large environmental gradients, abundant vegetation types and comprehensive modern pollen databases in China, we describe a new procedure for pollen-based quantitative paleoclimatic reconstructions. First, the most significant environmental variable controlling the fossil pollen assemblage changes is identified. Second, a calibration set to infer changes in this targeted variable is built up, by limiting the modern ranges of other environmental variables. Finally, the pollen-based quantitative reconstruction is obtained and its statistical significance assessed. This novel procedure was used to reconstruct the mean annual precipitation ( P ) from Gonghai Lake in the Lvliang Mountains, and Tianchi Lake in the Liupan Mountains, on the eastern and western fringe of the Chinese Loess Plateau, respectively. Both P reconstructions are statistically significant ( p<0.001), and a sound and stable correlation relationship exists in their common period, showing a rapid precipitation decrease since 3300 cal yr BP. Thus, we propose that this procedure has great potential for reducing the uncertainties associated with pollen-based quantitative paleoclimatic reconstructions in China. [ABSTRACT FROM AUTHOR]

China's large population and deteriorating environment have created great concern related to the sustainability of food production, especially since details related to this topic remain poorly studied. Thus, an integrated analysis of both crop yield and cultivated area is essential for gaining a better understanding of cereal grain production in China and for making corresponding policies designed to achieve food security. In this study, we adopt trend analysis of both provincial yield and cultivated area to assess the subsequent provincial-level cereal production sustainability between 1980 and 2011 with the goal of providing a better understanding of regional agricultural development. The results indicate that while maize shows the most promise for yield improvement, rice and wheat production is experiencing substantial yield stagnation among most provinces across mainland China. In addition, the trends in spatial patterns are prominently different from those of yields. The sizes of the main rice- and wheat-growing areas in China have declined greatly, suggesting that the related production of these cereals should attract more attention from land management planners and farmers. Specifically, the south-eastern coastal provinces have largely failed to sustain both crop yield and area, while the north-eastern provinces have witnessed thriving agricultural production during the last three decades. Moreover, we find that cereal production in China is significantly affected by governmental policies related to the agricultural sector. Thus, this analysis of food production in China will help policymakers to better understand how the potential implications of food security in China may be applicable to countries worldwide. [ABSTRACT FROM AUTHOR]

Examining the direct and indirect effects of climatic factors on vegetation growth is critical to understand the complex linkage between climate change and vegetation dynamics. Based on the Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data and meteorological data (temperature and precipitation) from 2001 to 2012, the trend of vegetation dynamics were examined in the Ziya-Daqing basins, China. The path analysis was used to obtain the information on the relationships among climatic factors and their effects on vegetation growth. It was found that the trends of growing season NDVI were insignificant in most plain dry land, while the upward trends were significant in forest, grass and dry land in Taihang Mountains. According to the path analysis, in 23% of the basins the inter-annual NDVI variation was dominated by the direct effect of precipitation, in 5% by the direct effects of precipitation and temperature, and in less than 1% by the direct effect of temperature or indirect effects of these two climatic factors. It indicated that precipitation significantly affected the vegetation growth in the whole basins, and this effect was not regulated by temperature. Precipitation increase (especially in July, August and September) was favorable to greenness enhancement. Summer temperature rising showed negative effect on plant productivity enhancement, but temperature rise in April was beneficial for the vegetation growth. When April temperature increases by 1°C, the onset date of greenness for natural vegetation will be 2 days in advance. There was a lag-time effect of precipitation or temperature on monthly NDVI for all land use types except grass. [ABSTRACT FROM AUTHOR]

Fossil pollen records from 45 sites across China were evaluated and synthesized to document vegetation and climate change during Marine Isotope Stage 3 (MIS 3) at 60-27 ka and to understand the large-scale controls. During MIS3, vegetation type was dominantly forest in eastern China, forest steppe/meadow in the north and Tibetan Plateau, and steppe desert in northwestern arid China. We developed a semi-quantitative vegetation index to reflect change in plant abundance (by inferring the general climate conditions), with a vegetation score from 1 to 3 based on the different vegetation types inferred from pollen data at individual sites at intervals of 2,000 years. The reconstructed vegetation index shows higher values during MIS 3, especially during the period 53-40 ka, than at the Last Glacial Maximum. Our results also suggest that climate on the basis of vegetation change was cooler and drier during MIS 3 than during the Holocene optimum; however, MIS 3 vegetation was probably similar to modern vegetation. The close relationship between vegetation change, insolation and Asian summer monsoon strength suggests that climate variations, probably in both temperature and precipitation, are the primary drivers of regional vegetation change. Additional well-dated, high-resolution palaeoclimate records from many locations across China will be needed to understand the vegetation change and climate forcings on millennial and centennial scales within MIS 3. [ABSTRACT FROM AUTHOR]