Xuebiao Pan

Impacts of climate change on net primary productivity of grasslands in Inner Mongolia

Net primary productivity (NPP) of grasslands is a key variable for characterising carbon cycles in grassland ecosystems. The prediction of NPP in Inner Mongolia is important for adaptation to future climate change, food security and sustainable use of the grassland resources. The output from two models, potentially suitable for simulating NPP in response to climate change, was tested against observed aboveground forage mass of dry matter at eight sites in Inner Mongolia from 1995 to 2005. The Classification Indices-Based Model (CIBM) showed an acceptable agreement with field measurements. The impact of climate change on the NPP of grasslands was subsequently analysed by CIBM using future climate projections from a Global Circulation Model based on three greenhouse gas emission scenarios: A2 (medium-high emission), A1B (medium emission) and B2 (medium-low emission) differing in assumptions about patterns of global social and economic development. Generally, significant increases in NPP, compared with the baseline NPP of 3.6 tonnes ha–1 for 1961–90, were predicted. The magnitude of the increase in NPP depended on the emission scenario, as well as on the time frame and region considered. Overall the predicted NPP stimulation increased with the level of emissions assumed, being 4.8 tonnes ha–1 in the A2 scenario, 4.3 tonnes ha–1 in the B2 scenario and 4.5 tonnes ha–1 in the A1B scenario in the 2080s (2071–2100). The increase in NPP in response to climate change differed between regions and there was an interaction with emission scenario. For the A2 and the B2 emission scenarios, the western region of Inner Mongolia was predicted to exhibit the strongest NPP increases, but, under the A1B scenario for the 2050s, the south-eastern region exhibited the greatest increase in NPP. It is concluded that the productivity of grassland in Inner Mongolia is likely to increase in response to climate change but these predicted effects are sensitive to emission scenarios and differ regionally. This will provide opportunities but also challenges for herders and policy makers in adapting to this change.

Impact of climate change on maize potential productivity and the potential productivity gap in southwest China

The impact of climate change on maize potential productivity and the potential productivity gap in Southwest China (SWC) are investigated in this paper. We analyze the impact of climate change on the photosynthetic, light-temperature, and climatic potential productivity of maize and their gaps in SWC, by using a crop growth dynamics statistical method. During the maize growing season from 1961 to 2010, minimum temperature increased by 0.20°C per decade (p < 0.01) across SWC. The largest increases in average and minimum temperatures were observed mostly in areas of Yunnan Province. Growing season average sunshine hours decreased by 0.2 h day−1 per decade (p < 0.01) and total precipitation showed an insignificant decreasing trend across SWC. Photosynthetic potential productivity decreased by 298 kg ha-1 per decade (p < 0.05). Both light-temperature and climatic potential productivity decreased (p < 0.05) in the northeast of SWC, whereas they increased (p < 0.05) in the southwest of SWC. The gap between light-temperature and climatic potential productivity varied from 12 to 2729 kg ha−1, with the high value areas centered in northern and southwestern SWC. Climatic productivity of these areas reached only 10%–24% of the light-temperature potential productivity, suggesting that there is great potential to increase the maize potential yield by improving water management in these areas. In particular, the gap has become larger in the most recent 10 years. Sensitivity analysis shows that the climatic potential productivity of maize is most sensitive to changes in temperature in SWC. The findings of this study are helpful for quantification of irrigation water requirements so as to achieve maximum yield potentials in SWC.

Comparison of the impacts of climate change on potential productivity of different staple crops in the agro-pastoral ecotone of North China

The aim of this study is to compare the impacts of climate change on the potential productivity and potential productivity gaps of sunflower (Helianthus annuus), potato (Solanum tuberosum), and spring wheat (Triticumaestivum Linn) in the agro-pastoral ecotone (APE) of North China. A crop growth dynamics statistical method was used to calculate the potential productivity affected by light, temperature, precipitation, and soil fertility. The growing season average temperature increased by 0.47, 0.48, and 0.52°C per decade (p < 0.05) for sunflower, potato, and spring wheat, respectively, from 1981 to 2010. Meanwhile, the growing season solar radiation showed a decreasing trend (p < 0.05) and the growing season precipitation changed non-significantly across APE. The light–temperature potential productivity increased by 4.48% per decade for sunflower but decreased by 1.58% and 0.59% per decade for potato and spring wheat. The climate–soil potential productivity reached only 31.20%, 27.79%, and 20.62% of the light–temperature potential productivity for sunflower, potato, and spring wheat, respectively. The gaps between the light–temperature and climate–soil potential productivity increased by 6.41%, 0.97%, and 1.29% per decade for sunflower, potato, and spring wheat, respectively. The increasing suitability of the climate for sunflower suggested that the sown area of sunflower should be increased compared with potato and spring wheat in APE under future climate warming.

Impacts of climate change on cotton yield in China from 1961 to 2010 based on provincial data

To develop scientific countermeasures, the impacts of climate change on cotton yield during 1961–2010 in three major cotton-producing regions of China were studied by using the available provincial data. The results indicate that (1) a rise in average temperature increased the cotton yield in most provinces of Northwest China and the Yellow River valley; however, the rise in average temperature decreased the cotton yield in the Yangtze River valley. Moreover, cotton production across the entire study region was reduced by approximately 0.1% relative to the average during 1961–2010. (2) A decrease in diurnal temperature range (DTR) reduced cotton yield in some provinces, while a beneficial DTR effect was observed in the other provinces. Changes in DTR resulted in an average decrease in production by approximatly 5.5% across the entire study region. (3) A change in the amount of precipitation increased the cotton yield in some provinces; however, it caused a decrease in other provinces. The decrease in average production due to the change in precipitation was approximately 1.1%. We concluded that the changes in temperature and precipitation decreased cotton yields in China, while beneficial effects of temperature and precipitation existed in the cotton-growing regions of Northwest China during 1961–2010.

Measurement and simulation of diurnal variations in water use efficiency and radiation use efficiency in an irrigated wheat-maize field in the North China Plain

Abstract Quantifying diurnal patterns of water use efficiency (WUE) and radiation use efficiency (RUE) for wheat and maize is important for assessing water use by plants and crop productivity. Water and carbon dioxide fluxes from an irrigated wheat-maize double-crop field from November 2002 to October 2003 were measured using the Eddy Covariance method. Evident differences were observed between the diurnal patterns of WUE for wheat and maize. The WUE values of wheat peaked near 9, 15 and 12 mg CO2 g H2O in the morning, and then decreased linearly with time and recovered in the late afternoon (4:00pm) before sunset in March, April and May, respectively. The WUE of maize increased after sunrise and retained stable values of 6, 14 and 12 mg CO2 g H2O from mid-morning to mid-afternoon (10:00am –2:00pm) and then decreased slowly with time until sunset in July, August and September, respectively. Similar patterns were observed in the RUE of wheat and maize. Over the three months of the study, averaged RUE was 1.76 g C MJ−1 for the wheat crop and 1.87 g C MJ−1 for the maize crop. A coupled photosynthesis and transpiration model was used to simulate the diurnal variations in WUE under variable climate conditions. Measurement results and sensitivity analysis show that the difference in the diurnal variation pattern in WUE between wheat and maize resulted from the different carbon fixing mechanisms of wheat and maize.

A quantitative method for risk assessment of agriculture due to climate change

Climate change has greatly affected agriculture. Agriculture is facing increasing risks as its sensitivity and vulnerability to climate change. Scientific assessment of climate change-induced agricultural risks could help to actively deal with climate change and ensure food security. However, quantitative assessment of risk is a difficult issue. Here, based on the IPCC assessment reports, a quantitative method for risk assessment of agriculture due to climate change is proposed. Risk is described as the product of the degree of loss and its probability of occurrence. The degree of loss can be expressed by the yield change amplitude. The probability of occurrence can be calculated by the new concept of climate change effect-accumulated frequency (CCEAF). Specific steps of this assessment method are suggested. This method is determined feasible and practical by using the spring wheat in Wuchuan County of Inner Mongolia as a test example. The results show that the fluctuation of spring wheat yield increased with the warming and drying climatic trend in Wuchuan County. The maximum yield decrease and its probability were 3.5 and 64.6%, respectively, for the temperature maximum increase 88.3%, and its risk was 2.2%. The maximum yield decrease and its probability were 14.1 and 56.1%, respectively, for the precipitation maximum decrease 35.2%, and its risk was 7.9%. For the comprehensive impacts of temperature and precipitation, the maximum yield decrease and its probability were 17.6 and 53.4%, respectively, and its risk increased to 9.4%. If we do not adopt appropriate adaptation strategies, the degree of loss from the negative impacts of multiclimatic factors and its probability of occurrence will both increase accordingly, and the risk will also grow obviously.

Responses of aboveground biomass and soil organic carbon to projected future climate change in Inner Mongolian grasslands

Understanding the impacts of future climate change on the grassland ecosystems of Inner Mongolia is important for adaptation of natural resource planning, livestock industries and livelihoods. The CENTURY model was validated against observed climate data from 1981 to 2010 for 16 sites. It simulated grass productivity and soil fertility with acceptable agreement, with the coefficient of the root-mean-square error calculated as 41.0% for biomass and 19.5% for soil organic carbon. The model was then used to assess changes to 2100 in aboveground biomass and soil organic carbon under two different climate-change scenarios that were developed for the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. The first scenario, RCP4.5 is an intermediate scenario for climate change, incorporating policies and technologies that stabilise growth in greenhouse-gas emissions. The second, RCP8.5, assumes continuing, high demand for energy and increasing greenhouse-gas emissions. Aboveground biomass of meadow and desert steppes responded positively to both scenarios, whereas the typical steppe showed a negative response to RCP4.5 but a positive response to RCP 8.5. Soil organic carbon showed a negative response for all steppe types. The simulations indicated that aboveground biomass and soil organic carbon of Inner Mongolian steppes were sensitive to projected emission scenarios. The CENTURY model predicted aboveground biomass to be 8.5% higher in the longer term (2081–2100) than baseline (1986–2005) under RCP4.5, and 24.3% higher under RCP8.5. Soil organic carbon was predicted to undergo small but significant decreases on average across all sites (1.2% for RCP4.5. 2.9% for RCP8.5). Our results could help decision makers to appreciate the consequences of climate change and plan adaptation strategies.