Wenjiao Shi

Single rice growth period was prolonged by cultivars shifts, but yield was damaged by climate change during 1981-2009 in China, and late rice was just opposite

Based on the crop trial data during 1981-2009 at 57 agricultural experimental stations across the North Eastern China Plain (NECP) and the middle and lower reaches of Yangtze River (MLRYR), we investigated how major climate variables had changed and how the climate change had affected crop growth and yield in a setting in which agronomic management practices were taken based on actual weather. We found a significant warming trend during rice growing season, and a general decreasing trend in solar radiation (SRD) in the MLRYR during 1981-2009. Rice transplanting, heading, and maturity dates were generally advanced, but the heading and maturity dates of single rice in the MLRYR (YZ_SR) and NECP (NE_SR) were delayed. Climate warming had a negative impact on growth period lengths at about 80% of the investigated stations. Nevertheless, the actual growth period lengths of YZ_SR and NE_SR, as well as the actual length of reproductive growth period (RGP) of early rice in the MLRYR (YZ_ER), were generally prolonged due to adoption of cultivars with longer growth period to obtain higher yield. In contrast, the actual growth period length of late rice in the MLRYR (YZ_LR) was shortened by both climate warming and adoption of early mature cultivars to prevent cold damage and obtain higher yield. During 1981-2009, climate warming and decrease in SRD changed the yield of YZ_ER by -0.59 to 2.4%; climate warming during RGP increased the yield of YZ_LR by 8.38-9.56%; climate warming and decrease in SRD jointly reduced yield of YZ_SR by 7.14-9.68%; climate warming and increase in SRD jointly increased the yield of NE_SR by 1.01-3.29%. Our study suggests that rice production in China has been affected by climate change, yet at the same time changes in varieties continue to be the major factor driving yield and growing period trends.

A review on statistical models for identifying climate contributions to crop yields

Statistical models using historical data on crop yields and weather to calibrate relatively simple regression equations have been widely and extensively applied in previous studies, and have provided a common alternative to process-based models, which require extensive input data on cultivar, management, and soil conditions. However, very few studies had been conducted to review systematically the previous statistical models for indentifying climate contributions to crop yields. This paper introduces three main statistical methods, i.e., time-series model, cross-section model and panel model, which have been used to identify such issues in the field of agrometeorology. Generally, research spatial scale could be categorized into two types using statistical models, including site scale and regional scale (e.g. global scale, national scale, provincial scale and county scale). Four issues exist in identifying response sensitivity of crop yields to climate change by statistical models. The issues include the extent of spatial and temporal scale, non-climatic trend removal, colinearity existing in climate variables and non-consideration of adaptations. Respective resolutions for the above four issues have been put forward in the section of perspective on the future of statistical models finally.

Vulnerability of African maize yield to climate change and variability during 1961–2010

Because of the necessity of feeding growing populations, there is a critical need to assess the variation and vulnerability of crop yields to potential climate change. Databases of maize yields and climate variables in the maize growing seasons were used to assess the vulnerability of African maize yields to climate change and variability with different levels of management at country scale between 1961 and 2010. The ratios of time-series trends or standard deviations of detrended yield deviation and climate variables including temperature (Tmean), precipitation (P) and standardized precipitation evapotranspiration index (SPEI) were used to analyze the vulnerability of maize yields to climate change and variability for each country in Africa. Most countries, where soil fertility had been declining owing to low levels of fertilizer use over many years and limited water resources, had decreasing maize yields. The negative impacts of increasing temperature and decreasing precipitation and SPEI on maize yields progressively increased at the whole continent scale over the time period studied. During the maize growing seasons 1961–2010, each 1°C of Tmean increase resulted in yield losses of over 10% in eight countries and 5-10% in 10 countries, but yields increased by more than 5% in four relatively cool countries. Decreases of 10% average P resulted in more than 5% decreases in yields in 20 countries and each decrease of 0.5 SPEI resulted in over 30% losses of maize yields in 32 countries. Greater Tmean or P or SPEI variability in Africa may also bring about greater fluctuations in yield. In addition, countries with better management, which would be expected to have better yields, may be more vulnerable to yield losses due to adverse physical conditions. Better irrigation and fertilizer application will be important to sustain higher yields in the future, as will the development of maize varieties with greater heat and drought tolerance.

Development of a surface modeling method for mapping soil properties

High accuracy surface modeling (HASM) is a method which can be applied to soil property interpolation. In this paper, we present a method of HASM combined geographic information for soil property interpolation (HASM-SP) to improve the accuracy. Based on soil types, land use types and parent rocks, HASM-SP was applied to interpolate soil available P, Li, pH, alkali-hydrolyzable N, total K and Cr in a typical red soil hilly region. To evaluate the performance of HASM-SP, we compared its performance with that of ordinary kriging (OK), ordinary kriging combined geographic information (OK-Geo) and stratified kriging (SK). The results showed that the methods combined with geographic information including HASM-SP and OK-Geo obtained a lower estimation bias. HASM-SP also showed less MAEs and RMSEs when it was compared with the other three methods (OK-Geo, OK and SK). Much more details were presented in the HASM-SP maps for soil properties due to the combination of different types of geographic information which gave abrupt boundary for the spatial variation of soil properties. Therefore, HASM-SP can not only reduce prediction errors but also can be accordant with the distribution of geographic information, which make the spatial simulation of soil property more reasonable. HASM-SP has not only enriched the theory of high accuracy surface modeling of soil property, but also provided a scientific method for the application in resource management and environment planning.

Surface modeling of soil antibiotics

Large numbers of livestock and poultry feces are continuously applied into soils in intensive vegetable cultivation areas, and then some veterinary antibiotics are persistent existed in soils and cause health risk. For the spatial heterogeneity of antibiotic residues, developing a suitable technique to interpolate soil antibiotic residues is still a challenge. In this study, we developed an effective interpolator, high accuracy surface modeling (HASM) combined vegetable types, to predict the spatial patterns of soil antibiotics, using 100 surface soil samples collected from an intensive vegetable cultivation area located in east of China, and the fluoroquinolones (FQs), including ciprofloxacin (CFX), enrofloxacin (EFX) and norfloxacin (NFX), were analyzed as the target antibiotics. The results show that vegetable type is an effective factor to be combined to improve the interpolator performance. HASM achieves less mean absolute errors (MAEs) and root mean square errors (RMSEs) for total FQs (NFX+CFX+EFX), NFX, CFX and EFX than kriging with external drift (KED), stratified kriging (StK), ordinary kriging (OK) and inverse distance weighting (IDW). The MAE of HASM for FQs is 55.1 μg/kg, and the MAEs of KED, StK, OK and IDW are 99.0 μg/kg, 102.8 μg/kg, 106.3 μg/kg and 108.7 μg/kg, respectively. Further, RMSE simulated by HASM for FQs (CFX, EFX and NFX) are 106.2 μg/kg (88.6 μg/kg, 20.4 μg/kg and 39.2 μg/kg), and less 30% (27%, 22% and 36%), 33% (27%, 27% and 43%), 38% (34%, 23% and 41%) and 42% (32%, 35% and 51%) than the ones by KED, StK, OK and IDW, respectively. HASM also provides better maps with more details and more consistent maximum and minimum values of soil antibiotics compared with the measured data. The better performance can be concluded that HASM takes the vegetable type information as global approximate information, and takes local sampling data as its optimum control constraints.

Impact of chilling injury and global warming on rice yield in Heilongjiang Province

This study is focused on indexes for the rice chilling injury in Heilongjiang Province during 1960–2009. Firstly, we compared a new derived climate data weighted by rice planting density with the traditional method, and found that the new one is more reasonable to assess the impact of climate change on crop yields. Considering the frequency and intensity of rice chilling in the province, secondly, chilling indexes defined by meteorological, national and international levels were assessed. The result showed that the meteorological standards were suitable for the delayed-type injury, while the international one, so-called sum of Growing Degree Day below threshold (GDDn−), characterized best the sterile-type chilling injury for rice. The explanation ability of the rice yield time series model including both injury types as two independent variables reached approximately 92% (p < 0.05). Finally, we concluded that the contribution rates of human and weather factors to rice yields are about 87.2% and 12.8% respectively, and as light increasing trend for sterile-type chilling injury was found during heading to flowing period in recent years, indicating a high chilling risk for rice planting in Heilongjiang Province in the future global warming.

A review of recent developments in HASM

Ground observation is able to obtain highly accurate data with high temporal resolution at observation points, but these observation points are too sparsely to satisfy the application requirements at regional scale. Satellite remote sensing can frequently supply spatially continuous information on earth surface, which is impossible from ground-based investigations, but remote sensing description is not able to directly obtain process parameters. In fact, in terms of fundamental theorem of surfaces, a surface is uniquely defined by the first fundamental coefficients, about the details of the surface observed when we stay on the surface, and the second fundamental coefficients, the change of the surface observed from outside the surface. A method for high accuracy surface modeling (HASM) has been developed initiatively to find solutions for error problem and slow-speed problem of earth surface modeling since 1986. HASM takes global approximate information (e.g., remote sensing images or model simulation results) as its driving field and local accurate information (e.g., ground observation data and/or sampling data) as its optimum control constraints. Its output satisfies the iteration stopping criterion which is determined by application requirement for accuracy. This paper reviews problems to be solved in every development stage and applications of HASM.

Spatio-temporal distributions of climate disasters and the response of wheat yields in China from 1983 to 2008

Climate disasters are now on the rise and more likely to increase in frequency and/or severity under climate change in the future. To clearly illustrate spatial–temporal distributions of climate disasters and the response of wheat yields to disasters over the past three decades, several disaster indices including the impact of climate disasters, the sensitivity to climate disasters and the response index of wheat yield losses to climate disasters were defined and calculated. The impact and sensitivity indices were examined by the agricultural production losses due to climate disasters, and the response of wheat yields to climate disasters was assessed by wheat yield loss compared with the 5-year moving average. The results showed that the indices of climate disaster impacts and sensitivities as well as response index of wheat yields to climate disasters could represent the spatial–temporal distributions of climate disasters well in the whole China. Droughts in northern China had higher impacts and sensitivities than those in southern China during the period 1983–2008, but the impacts of floods were opposite. In northern China, although impacted area by drought was larger than that by flood, the flood sensitivities were larger than drought sensitivities when flood happened. Although drought significantly affected wheat yields in most of the regions with drier conditions during 1983–2008 in major wheat-producing regions, better management practices like irrigation and drought-tolerant cultivars applied in the Huang-Huai-Hai Plain can adapt to climate disasters especially droughts. To ensure the stability of agricultural production, future food security will need to be achieved through quantifying the relative effects of climate disasters and effective adaptation to increasingly frequent extreme climate events.

Spatio-temporal characteristics of intra-urban land cover in the cities of China and USA from 1978 to 2010

Urban land cover has major impacts on a city’s ecosystem services and the inherent quality of its urban residential environment. The spatio-temporal distribution of impervious surface area and green areas in Chinese cities has exhibited a significantly marked difference in comparison with USA cities. This study focused on monitoring and comparing the spatio-temporal dynamics, land cover patterns and characteristics of functional regions in six Chinese (n=3) and USA (n=3) cities. The study data were collated from Landsat TM/MSS imagery during the period 1978–2010. Results indicate that Chinese cities have developed compactly over the past three decades, while development has been notably dispersed among USA cities. Mean vegetation coverage in USA cities is approximately 2.2 times that found amongst Chinese urban agglomerations. Land use types within Chinese cities are significantly more complex, with a higher density of impervious surface area. Conversely, the central business district (CBD) and residential areas within USA cities were comprised of a lower proportion of impervious surface area and a higher proportion of green land. Results may be used to contribute to future urban planning and administration efforts in both China and the USA.

Contributions of climate, varieties, and agronomic management to rice yield change in the past three decades in China

The long-term field experiment data at four representative agro-meteorological stations, together with a crop simulation model, were used to disentangle the contributions of climate change, variety renewal, and fertilization management to rice yield change in the past three decades. We found that during 1981–2009 varieties renewal increased rice yield by 16%–52%, management improvement increased yield by 0–16%, and the contributions of climate change to rice yield varied from — 16% to 10%. Varieties renewal and management improvement offset the negative impacts of climate change on rice production. Among the major climate variables, decreases in solar radiation reduced rice yield on average by 0.1%per year. The impact of temperature change had an explicit spatial pattern. It increased yield by 0.04%–0.4% per year for single rice at Xinbin and Ganyu station and for late rice at Tongcheng station, by contrast reduced yield by 0.2%–0.4% per year for single rice at Mianyang station and early rice at Tongcheng station. During 1981–2009, rice varieties renewal was characterized by increases in thermal requirements, grain number per spike and harvest index. The new varieties were less sensitive to climate change than old ones. The development of high thermal requirements, high yield potential and heat tolerant rice varieties, together with improvement of agronomic management, should be encouraged to meet the challenges of climate change and increasing food demand in future.