Dongli Fan

A cross-scale model coupling approach to simulate the risk-reduction effect of natural adaptation on soybean production under climate change

ABSTRACT This study establishes a procedure to couple Decision Support System for Agrotechnology Transfer (DSSAT) and China Agroecological Zone model (AEZ-China). This procedure enables us to quantify the effects of two natural adaptation measures on soybean production in China, concern on which has been growing owing to the rapidly rising demand for soybean and the foreseen global climate change. The parameters calibration and mode verification are based on the observation records of soybean growth at 13 agro-meteorological observation stations in Northeast China and Huang-Huai-Hai Plain over 1981–2011. The calibration of eco-physiological parameters is based on the algorithms of DSSAT that simulate the dynamic bio-physiological processes of crop growth in daily time-step. The effects of shifts in planting day and changes in the length of growth cycle (LGC) are evaluated by the speedy algorithms of AEZ. Results indicate that without adaptation, climate change from the baseline 1961–1990 to the climate of 2050s as specified in the Providing Regional Climate for Impacts Studies-A1B would decrease the potential yield of soybean. By contrast, simulations of DSSAT using AEZ-recommended cultivars with adaptive LGC and also the corresponding adaptive planting dates show that the risk of yield loss could be fully or partially mitigated across majority of grid cells in the major soybean-growing areas.

Changes in production potentials of rapeseed in the Yangtze River Basin of China under climate change: A multi-model ensemble approach

Rapeseed is one of the major oil crops in China and it is very sensitive to climate change. The Yangtze River Basin is the main rapeseed production area in China. Therefore, a better understanding of the impact of climate change on rapeseed production in the basin is of both scientific and practical importance to Chinese oil industry and food security. In this study, based on climate data from 5 General Circulation Models (GCMs) with 4 representative concentration pathways (RCPs) in 2011–2040 (2020s), 2041–2070 (2050s) and 2071–2100 (2080s), we assessed the changes in rapeseed production potential between the baseline climatology of 1981–2010 and the future climatology of the 2020s, 2050s, and 2080s, respectively. The key modelling tool – the AEZ model – was updated and validated based on the observation records of 10 representative sites in the basin. Our simulations revealed that: (1) the uncertainty of the impact of climate change on rapeseed production increases with time; (2) in the middle of this century (2050s), total rapeseed production would increase significantly; (3) the average production potential increase in the 2050s for the upper, middle and lower reaches of the Yangtze River Basin is 0.939, 1.639 and 0.339 million tons respectively; (4) areas showing most significant increases in production include southern Shaanxi, central and eastern Hubei, northern Hunan, central Anhui and eastern Jiangsu.

Simulation of methane emissions from double-rice cropping system in Southern China during the past 50 years by DNDC model

Paddy field is a major source of methane (CH4) emission. Methane emission in paddy fields accounts for 31.5% of agricultural methane emissions in China. Double-rice cropping system is a part of the major paddy systems in China for rice production, accounting for only 27% of the national rice planting area while CH4 emission accounting for 60% of the national CH4 emission. Given the importance of reducing CH4 emission from double rice to mitigate climate warming, it is necessary to investigate the impact of climate change on CH4 emission of double cropping paddy field in the future. In this study, the denitrification–decomposition (DNDC-a process-based biogeochemistry model) model is employed to simulate the CH4 emission from double-rice cropping system in southern China based on the historical meteorological data of the past 50 years (1966-2015) and the observational data of rice agricultural stations in the study area. Then we combined the outputs with Geographic Information System (GIS) technology to analyze the impact of climate change on CH4 emissions from the double rice paddy. The results indicate that change of the average temperature is associated with the change of CH4 emission across the growing period of double rice paddy. Methane has increased by 8.4% in the main producing provinces of double cropping rice in southern China. Zhejiang has increased by up to 20.8%. Anhui, Hubei, Hunan has increased by 10.6%, 10.2% and 11.4%. The relatively small increase in Fujian and Yunnan is only 5%. However, in the low latitudes of Guangxi, and Guangdong province, there was a slight reduction in CH4 emission.

Suitability regionalization of Chinese medicinal yam under the impact of climate change simulated by CMIP5 multi-model ensemble projections

Chinese yam (Dioscorea opposita Thunb.) is consumed and regarded as medicinal food in traditional Chinese herbal medicine, Chinese medicinal yam especially is one of the most important Chinese herbal medicines and its medicinal needs have been increasing in recent decades1. Furthermore, Chinese medicinal yam is susceptible to climate conditions during the growth period. Therefore, a better understanding of the suitability regionalization of Chinese medicinal yam under the impact of climate change is of both scientific and practical importance to spacial development and reasonable layout of Chinese yam in China. In this study, based on the Coupled Model Inter-comparison Project, Phase 5 (CMIP5) climate model projections with 5 Global Circulation Models (GCMs) developed by the Inter-Sectoral Impact Model Inter-comparison Project (ISIMIP) driven by 4 Representative Concentration Pathways (RCPs), we assessed the changes of potential planting area of Chinese medicinal yam between the baseline climatology of 1981-2010 and the future climatology of the 2050s (2041-2070) under the RCP 4.5 scenario by the Geographic Information System (GIS) technology. Results indicate that regions with high ecological similarity to the Geo-authentic producing areas of Chinese medicinal yam include northeastern Henan, southeastern Hebei and western Shandong, mainly distribute in the lower reaches of the Yellow River basin and other major floodplains. In the future, the climate suitability of Chinese medicinal yam in these areas will be weakened, but that will still be the main suitable planting regions.

Crop Water Demand for Rain-Fed Maize in Northeast of China

Drought risk is one of the main constraint for stabling high maize production in the Northeast of China (NEC), where about 30% of the national maize is produced. Maize in the NEC is especially vulnerable to climate change and extreme weather. Previous studies on water demand of maize are based on field experiments by crop model, but water demand of different maize growth stages is rarely studied. Given the importance of NEC in Chinas food security, it is crucial to optimize the irrigation schedule to mitigate the negative effects of drought. In this study, we use the AEZ model to examine the climate change impacts on maize water demand in NEC. This model is employed to simulate the future maize water demand on climate scenario from NorESM1-M model driven by 2 Representative Concentration Pathways (RCP2.6 and RCP8.5). Results indicate that climate change will affect water demand of mazie in NEC. The increasing frequency and rising amount of water demand in the western part of NEC where should be given priority for soil moisture monitoring and irrigation.

Impacts of climate change on peanut yield in China simulated by CMIP5 multi-model ensemble projections

Peanut is one of the major edible vegetable oil crops in China, whose growth and yield are very sensitive to climate change. In addition, agriculture climate resources are expected to be redistributed under climate change, which will further influence the growth, development, cropping patterns, distribution and production of peanut. In this study, we used the DSSAT-Peanut model to examine the climate change impacts on peanut production, oil industry and oil food security in China. This model is first calibrated using site observations including 31 years’ (1981-2011) climate, soil and agronomy data. This calibrated model is then employed to simulate the future peanut yield based on 20 climate scenarios from 5 Global Circulation Models (GCMs) developed by the InterSectoral Impact Model Intercomparison Project (ISIMIP) driven by 4 Representative Concentration Pathways (RCPs). Results indicate that the irrigated peanut yield will decrease 2.6% under the RCP 2.6 scenario, 9.9% under the RCP 4.5 scenario and 29% under the RCP 8.5 scenario, respectively. Similarly, the rain-fed peanut yield will also decrease, with a 2.5% reduction under the RCP 2.6 scenario, 11.5% reduction under the RCP 4.5 scenario and 30% reduction under the RCP 8.5 scenario, respectively.

A Study of the Impact on Soybean Potential under Climate Change

Soybean is one of the important oil crops in China. However the supply and demand of soybean is at stake currently. The demand keeps increasing and the self-sufficient keeps decreasing. More seriously, climate change will bring obvious impact on the growth and development, planting pattern, planting area, potential production of soybean, etc. Therefore, assessment of the impact of soybean production under climate change is quite essential for improving the self-sufficient and guaranteeing the safety of oil crops. This study will extend and improve the parameters of soybean in agricultural ecology zone (AEZ) based on the 22 soybean observation stations in the major planting area from 1981-2011 to achieve China-AEZ. And then simulate the impact of climate change on soybean. The results show that: the simulation of China-AEZ has been improved a lot. In 2050s, the total soybean potential will increased by 7123 thousand tons. The total suitable planting area will increased by 3589 thousand hectare. But the average potential will decreased by 55 kg/ha. From the spatial scale, the soybean potential will increase in Northeast China and Northwest China. Soybean potential will decrease in the other area of China under climate change.