Phenological characteristics of net ecosystem carbon exchange of Stipa krylovii steppe in Inner Mongolia, China and its remote sensing monitoring.

To accurately monitor the phenology of net ecosystem carbon exchange (NEE) in grasslands with remote sensing, we analyzed the variations in NEE and its phenology in the Stipa krylovii steppe and discussed the remote sensing vegetation index thresholds for NEE phenology, with the observational data from the Inner Mongolia Xilinhot National Climate Observatory's eddy covariance system and meteorological gradient observation system during 2018-2021, as well as Sentinel-2 satellite data from January 1, 2018 to December 31, 2021. Results showed that, from 2018 to 2021, NEE exhibited seasonal variations, with carbon sequestration occurring from April to October and carbon emission in other months, resulting in an overall carbon sink. The average Julian days for the start date (SCUP) and the end date (ECUP) of carbon uptake period were the 95th and 259th days, respectively, with an average carbon uptake period lasting 165 days. Photosynthetically active radiation showed a negative correlation with daily NEE, contributing to carbon absorption of grasslands. The optimal threshold for capturing SCUP was a 10% threshold of the red-edge chlorophyll index, while the normalized difference vegetation index effectively reflected ECUP with a threshold of 75%. These findings would provide a basis for remote sensing monitoring of grassland carbon source-sink dynamics.

Regulatory effects of Hemin on prevention and rescue of salt stress in rapeseed (Brassica napus L.) seedlings.

BACKGROUND: Salt stress severely restricts rapeseed growth and productivity. Hemin can effectively alleviate salt stress in plants. However, the regulatory effect of Hemin on rapeseed in salt stress is unclear. Here, we analyzed the response and remediation mechanism of Hemin application to rapeseed before and after 0.6% (m salt: m soil) NaCl stress. Experiment using two Brassica napus (AACC, 2n = 38) rapeseed varieties Huayouza 158R (moderately salt-tolerant) and Huayouza 62 (strongly salt-tolerant). To explore the best optional ways to improve salt stress resistance in rapeseed. RESULTS: Our findings revealed that exogenous application of Hemin enhanced morph-physiological traits of rapeseed and significantly attenuate the inhibition of NaCl stress. Compared to Hemin (SH) treatment, Hemin (HS) significantly improved seedlings root length, seedlings height, stem diameter and accumulated more dry matter biomass under NaCl stress. Moreover, Hemin (HS) significantly improved photosynthetic efficiency, activities of antioxidant enzymes such as superoxide dismutase (SOD), peroxidase (POD), ascorbate peroxidase (APX), and decreased electrolyte leakage (EL) and malondialdehyde (MDA) content, thus resulting in the alleviation of oxidative membrane damage. Hemin (HS) showed better performance than Hemin (SH) under NaCl stress. CONCLUSION: Hemin could effectively mitigate the adverse impacts of salt stress by regulating the morph-physiological, photosynthetic and antioxidants traits of rapeseed. This study may provide a basis for Hemin to regulate cultivated rapeseed salt tolerance and explore a better way to alleviate salt stress.

Net ecosystem productivity of Panjin Phragmites australis wetland during 1971 to 2020 and its impact factors.

Coastal estuarine wetland ecosystem has strong ability for carbon (C) storage and sequestration. Accurate assessment of C sequestration and its environmental impact factors is the basis of scientific protection and mana-gement of coastal estuarine wetlands. Taking the Panjin reed (Phragmites australis) wetland as the object, we used terrestrial ecosystem model, together with Mann-Kendall mutation test, statistical analysis methods, and scenario simulation experiment, to analyze the temporal characteristics, stability, changing trend of net ecosystem production (NEP) of wetlands and the contribution rate of environmental impact factors to NEP during 1971 to 2020. The results showed that the annual average NEP of Panjin reed wetland was 415.51 g C·m-2·a-1 during 1971 to 2020, with a steady increase rate of 1.7 g C·m-2·a-1, which would still have a continuous increasing trend in the future. The annual average NEP in spring, summer, autumn, and winter was 33.95, 418.05, -18.71, and -17.78 g C·m-2·a-1, with an increase rate of 0.35, 1.26, 0.14 and -0.06 g C·m-2·a-1, respectively. In the future, NEP would show an increasing trend in both spring and summer, but a declining trend in both autumn and winter. The contribution rates of environmental impact factors to NEP of Panjin reed wetland depended on temporal scale. At the interannual scale, the contribution rate of precipitation was the highest (37.1%), followed by CO2 (28.4%), air temperature (25.1%) and photosynthetically active radiation (9.4%). Precipitation mainly affected NEP in both spring and autumn with the contribution rates of 49.5% and 38.8%, while CO2 concentration (36.9%) and air temperature (-86.7%) were dominant in summer and winter, respectively.

[Temporal and spatial variations of net primary productivity (NPP) and its climate driving effect in the Qinghai-Tibet Plateau, China from 2000 to 2020]. / 2000­2020å¹´é’è—é«˜åŽŸæ¤è¢«å‡€åˆçº§ç”Ÿäº§åŠ›æ—¶ç©ºå˜åŒ–åŠå ¶æ°”å€™é©±åŠ¨ä½œç”¨.

Qinghai-Tibet Plateau is a "climate change laboratory" for China and the world. Driven by climate change, net primary productivity (NPP) in the Qinghai-Tibet Plateau has significant variations. Using the data of normalized difference vegetation index, digital elevation, annual precipitation, and annual temperature, we explored the temporal and spatial variation characteristics of NPP and its correlation with climate factors on the Qinghai Tibet Plateau from 2000 to 2020. The results showed that NPP of the Qinghai-Tibet Plateau increased significantly from 2000 to 2020, with an increase rate of 1.67 g C·m-2·a-1. The NPP was significantly positively correlated with temperature and precipitation. The climate trend of warming and wetting was an important driving force to promote the significant increase of NPP. The increases of NPP would continue if the climate become warmer and wetter.

[Effects of warming, photoperiod, and nitrogen addition on the main phenological phases of Quercus mongolica]. / å¢žæ¸©ã€å ‰ç §æ—¶é—´å’Œæ°®æ·»åŠ å¯¹è’™å¤æ Žä¸»è¦ç‰©å€™æœŸçš„å½±å“.

With a large artificial climate chamber, we examined the effects of warming (control, +1.5 ℃, +2.0 ℃), photoperiod (10, 14, 18 h) and nitrogen addition (0, 5, 10, 20 g N·m-2·a-1) on the main phenological phases of Quercus mongolica in Northeast China. The results showed that 1.5 and 2.0 ℃ warming significantly advanced the bud swelling stage and delayed the leaf fully coloring stage, which prolonged the growing season. The extended days increased with the increases of warming range. Photoperiod significantly affected autumn phenology (leaf coloration onset stage, leaf coloration in general stage, leaf fully coloring stage). Compared with photoperiod of 14 h, short photoperiod (10 h) significantly delayed leaf coloration onset stage by 7.0 d, and prolonged the peak of growth season. Nitrogen addition significantly advanced the bud swelling stage, bud opening stage, first leaf unfolding stage and full leaf unfolding stage. The leaf fully coloring stage was significantly delayed by 9.5 d only at the high nitrogen level of 20 g N·m-2·a-1, indicating that high nitrogen addition prolonged the growing season of Q. mongolica. The synergistic effects of warming and high nitrogen addition (20 g N·m-2·a-1) significantly delayed the leaf fully coloring stage, which prolonged leaf coloration stage, and the synergistic effects of warming and short photoperiod, the synergistic effects of nitrogen addition and short photoperiod. The synergistic effects of warming, nitrogen addition and short photoperiod all significantly delayed the leaf coloration onset stage, which relatively prolonged the peak of growing season.

Photosynthetically physiological mechanism of Stipa krylovii withered and yellow phenology response to precipitation under the background of warming.

We examined the photosynthetically physiological mechanism of Stipa krylovii response to warming and precipitation changes, based on an experiment with the treatments of warming by infrared radiator and precipitation treatments by irrigation water. Under the warming background, precipi-tation was the main influencing factor of the withered and yellow phenology. Increasing precipitation postponed the occurrence time of both the beginning and the peak of the withered and yellow phenology, and prolonged the duration of the withered and yellow phenology. The effect of decreasing precipitation on prolonging the duration of the withered and yellow phenology was much stronger. Under the background of warming, the changes of precipitation markedly affected the physiological and ecological characteristics of the withered and yellow phenology, with the effect being the most significant at the beginning of the withered and yellow phenology. The net photosynthetic rate (Pn), stomatal conductance (gs), transpiration rate (Tr), and the maximum ribulose 1,5-bisphosphate (RuBP) carboxylation rate (Vc max), RuBP regeneration capacity (Jmax) were positively correlated with precipitation. Results of the pathway analysis showed that the photosynthetically physiological mechanism of withered and yellow phenology of S. krylovii would be different under different conditions of precipitation and temperature. Under the current environmental condition, Jmax was the main influencing factor of the withered and yellow phenology, and Vc max was the main limiting factor. Under the scenarios of warm and dry climate and warm and wet climate, Vc max become the main influencing factor of the withered and yellow phenology. Jmax would be the main limiting factor in the warm and dry climate conditions, and there would be no limiting factor in the warm and wet climate conditions. Our findings indicated that the withered and yellow phenological changes of S. krylovii depend on the photosynthetical capacity limitation resulted from meteorological conditions.

[Climate suitability of Ziziphus mauritiana in the main planting areas of Fujian Province, China]. / 台湾青枣在福建主产区的气候适宜度.

Taiwan green jujube (Ziziphus mauritiana) is a new fruit variety, with remarkable economic benefit. To achieve high quality and high yield of jujube in Fujian Province, we quantified the climate suitability model parameters of the jujube in main production areas of Fujian, and analyzed climate suitability characteristics and change trend of main production areas, based on the yield and meteorological data, combined with literature and phenological observation data and agricultural climate suitability model. The results showed that the model based on the equal weight summation method had the highest reliability. The climate suitability of jujube in main production areas of Fujian was higher, with most years being suitable or much suitable. From 1996 to 2013, the influence of climate conditions on jujube growth was generally in a good trend, which was conducive to the development of jujube production. The suitability of the main production areas in the whole growing season was ranked as temperature suitability>comprehensive climate suitability>sunshine suitability>precipitation suitability. September and October are the key period of water management. Our results are important in guiding production management and long-term planning of Taiwan green jujube in Fujian Province.

[Climatic suitability for the distribution of Vitis heyneana and V. davidii in China]. / 中国毛葡萄和刺葡萄分布的气候适宜性.

Vitis heyneana and V. davidii are two wild wine grape varieties that originate from China. In this study, we used the principle of maximum entropy in terms of sufficiency and necessity to identify the dominant climatic factors (among the many climatic factors that were brought up by previous relevant studies) affecting the planting distribution of both varieties in China. Based on the probability of planting distribution determined by the comprehensive effect of these dominant climatic factors, we further analyzed the climatic suitability in China for both wild varieties. The results showed that the four dominant climatic factors affecting the spatial distribution of both varieties were annual sunshine duration, precipitation during the flowering stage in May, annual extreme minimum temperature, and average temperature during the coldest month of January. The optimal wine grape-growing subregions for both varieties were mainly located in the western and southern parts of Hunan, the north-central part of Guangxi, the southeastern part of Guizhou, and the central part of Chongqing. The areas of optimal, suitable, and sub-suitable subregions for planting V. heyneana and V. davidii accounted for 2%, 14%, and 16% of the total area of the research region, respectively. In the optimal/suitable subregions for planting both varieties, annual sunshine duration was between 1200-1800 h, annual extreme minimum temperature was above -8 ℃, average temperature during the coldest month of January was between 2-13 ℃, and monthly precipitation in May was between 110-320 mm.

[Fraction of absorbed photosynthetically active radiation over summer maize canopy estimated by hyperspectral remote sensing under different drought conditions.] / ä¸åŒå¹²æ—±æ¡ä»¶ä¸‹å¤çŽ‰ç±³å ¨ç”Ÿè‚²æœŸå† å±‚å¸æ”¶å ‰åˆæœ‰æ•ˆè¾å°„æ¯”çš„é«˜å ‰è°±é¥æ„Ÿåæ¼”.

Fraction of absorbed photosynthetically active radiation (fAPAR) is one of the important remote sensing model parameters of vegetation productivity. However, the crop canopy fAPAR estimation during growing season under different drought conditions has not been reported yet. In this study, the characteristics of summer maize canopy fAPAR and spectral reflectance during growing season under different drought stresses and the relationships of fAPAR with reflectance, the first derivative spectral reflectance and vegetation indices were examined based on the hyperspectral reflectance and fAPAR data from the summer maize drought manipulation experiment with five irrigation levels in 2015. Under mild water stress and sufficient water supply conditions, fAPAR was higher, with the maximum value of 0.7. Under severe water stress and severe persistent drought, fAPAR was lower, with the minimum value of 0.06. Reflectance of visible and shortwave bands increased and near infrared reflectance decreased with increasing drought. The fAPAR was negatively related with visible bands and shortwave bands, but positively correlated with near infrared. Visible and shortwave band reflectance had significant correlation with fAPAR, especially at 383, 680 and 1980 nm, with all the correlation coefficients being more than -0.87. The strong and stable relationship between the first derivative spectral reflectance and fAPAR appeared at 580, 720 and 1546 nm, with the correlation coefficients being -0.91, 0.89 and 0.88, respectively. There were linear or logarithm relationships between fAPAR with nine vegetation indices. Among the nine indices, the enhanced vegetation index (EVI), renormalized difference vegetation index (RDVI), soil adjusted vegetation index (SAVI), and modified soil adjusted vegetation index (MSAVI) performed well with the correlation coefficient being higher than 0.88, and the average relative error (RMAE) 16.6%, 16.6%, 16.7% and 16.2%, respectively. Based on the logarithmic relationship between first derivative spectral reflectance and fAPAR, the simulation effect was best at the band of (720±5) nm, with a correlation coefficient of 0.86. The correlation coefficient of the relationship between fAPAR and reflectance was less than 0.81. The results could provide fAPAR simulation for remote sensing model of vegetation productivity and drought warning.

[Influencing factors and their simulation of summer maize land surface-air temperature difference under drought conditions]. / 干旱条件下夏玉米地-æ°”æ¸©å·®çš„å½±å“å› ç´ åŠå ¶æ¨¡æ‹Ÿ.

Crop water deficit status characterized by land surface-air temperature difference (Ts-Ta) has been widely investigated. However, empirical evidence for characteristics and impact factors of Ts-Ta considering the process of crop growth are less yet, which restricts the accurate simulation of Ts-Ta. Here, the data of Ts-Ta during the process of maize growth were obtained from five irrigation water control experiments after the period of summer maize 3-leaf stage in 2014 and jointing stage in 2015. The results showed that Ts-Ta of summer maize cropland was significantly affected by soil water content. Ts-Ta increased with the deficit of soil water. During summer maize water treatments, the normalized difference vegetation index (NDVI) was the main impact factor of Ts-Ta, with a significant linear relationship. However, during different growth stages, some additional factors including meteorological, biological and soil factors could also affect Ts-Ta, including canopy photosynthetic active radiation absorption ratio (fAPAR) after 3-leaf stage, relative soil water content (RSWC), and air relative humidity (RH) from 3-leaf stage to jointing stage. Then, the growth duration simulation model of Ts-Ta, vegetative growth simulation model of Ts-Ta and reproductive growth simulation model of Ts-Ta were established in terms of the data in 2014. Those simulation models were validated based on the experimental data of five irrigation water treatments after summer maize jointing stage in 2015. The results showed that the growth duration simulation mode of Ts-Ta could explain 63% variation of Ts-Ta in 2015. However, 79% variation of Ts-Ta could be explained by the simulation results of the vegetative growth simulation model of Ts-Ta and the reproductive growth simulation model of Ts-Ta. The results provided the basis for the quantitative evaluation of crop drought based on Ts-Ta.

Estimating leaf SPAD values of freeze-damaged winter wheat using continuous wavelet analysis.

Freeze injury, one of the most destructive agricultural disasters caused by climate, has a significant impact on the growth and production of winter wheat. Chlorophyll content is an important indicator of a plant's growth status. In this study, we analyzed the hyperspectral reflectance of normal and freeze-stressed leaves of winter wheat using a spectro-radiometer in a laboratory. The response of the chlorophyll spectra of plants under freeze stress was analyzed to predict the severity of freeze injury. A continuous wavelet transform (CWT) was conducted in conjunction with a correlation analysis, which generated a correlation scalogram that summarized the correlation between the chlorophyll content (SPAD value) and wavelet power at different wavelengths and decomposition scales. A linear regression model was established to relate the SPAD values and wavelet power coefficients. The results indicated that the most sensitive wavelet feature (region E: 553 nm, scale 5, R(2) = 0.8332) was located near the strong pigment absorption bands, and the model based on this feature could estimate the SPAD value with a high coefficient of determination (R(2) = 0.7444, RMSE = 7.359). The data revealed that the chlorophyll content of leaves under different low temperatures treatments could be accurately estimated using CWT. Also, this emerging spectral analytical approach can be applied to other complex datasets, including a broad range of species, and may be adapted to estimate basic leaf biochemical elements, such as nitrogen, cellulose, and lignin.

[Maize biomass simulation based on dynamic photosynthate allocation.] / åŸºäºŽå ‰åˆäº§ç‰©åŠ¨æ€åˆ†é çš„çŽ‰ç±³ç”Ÿç‰©é‡æ¨¡æ‹Ÿ.

Photosynthate allocation is critical to crop growth and biomass formation, and it is also a key part of crop simulation. A photosynthate allocation model of maize was established based on photosynthate allocation mechanisms as well as the photosynthate allocation characteristics of maize at different stages. This model was then coupled with the CO2 assimilation module of WOFOST crop model to simulate the biomass dynamics of different organs of maize on daily scale. It was validated by 5 years' field experiment data of spring maize from Jinzhou Agricultural Ecosystem Research Station. The results showed that, the model could explain about 95.4% of maize's total biomass change, while 87.0%, 85.3%, 67.9%, 76.5% and 87.5% of vegetative, leaf, root, stem, and ear biomass variations, respectively. This model could fulfill accurate simulation of different organ biomass dynamics of maize.

[Soil moisture estimation method based on both ground-based remote sensing data and air temperature in a summer maize ecosystem.] / 基于地面遥感信息与气温的夏玉米土壤水分估算方法.

Soil moisture is an important component of the soil-vegetation-atmosphere continuum (SPAC). It is a key factor to determine the water status of terrestrial ecosystems, and is also the main source of water supply for crops. In order to estimate soil moisture at different soil depths at a station scale, based on the energy balance equation and the water deficit index (WDI), a soil moisture estimation model was established in terms of the remote sensing data (the normalized difference vegetation index and surface temperature) and air temperature. The soil moisture estimation model was validated based on the data from the drought process experiment of summer maize (Zea mays) responding to different irrigation treatments carried out during 2014 at Gucheng eco-agrometeorological experimental station of China Meteorological Administration. The results indicated that the soil moisture estimation model developed in this paper was able to evaluate soil relative humidity at different soil depths in the summer maize field, and the hypothesis was reasonable that evapotranspiration deficit ratio (i.e., WDI) linearly depended on soil relative humidity. It showed that the estimation accuracy of 0-10 cm surface soil moisture was the highest (R2=0.90). The RMAEs of the estimated and measured soil relative humidity in deeper soil layers (up to 50 cm) were less than 15% and the RMSEs were less than 20%. The research could provide reference for drought monitoring and irrigation management.

[Leaf economics spectrum among different plant functional types in Beijing Botanical Garden, China.] / 北京植物园不同功能型植物叶经济谱.

We measured leaf photosynthetic and chlorophyll fluorescence parameters as well as leaf area, dry biomass, and nitrogen content of different plant functional types (PFTs) at the Beijing Botanical Garden, and analyzed the leaf economics spectrum (LES) among different PFTs. The results showed that the plants with the life form of grasses, those with an annual type of life history, and with a C4 photosynthetic pathway might provide a quick return on investment for the species located at one end of the LES. Similarly, the plants with a life form of trees and shrubs, with a perennial type of life history, and with a C3 photosynthetic pathway might provide a slower return on investment for the species located at the other end of the LES. This indicated that plants with different PFTs might have diverse strategies that allowed them to adapt to the environment through a trade-off among leaf traits. The results showed that the LES existed among different PFTs. Remarkable diffe-rences were observed in most of the leaf traits among different PFTs. The various life forms analyzed here were ranked in the order of grasses > vines > shrubs > trees based on specific leaf area (SLA), mass-based nitrogen concentration (Nmass), mass-based photosynthetic capacity (Amass), and photosynthetic nitrogen use efficiency (PNUE). Among the different life histories, SLA, Nmass, Amass, and PNUE in annual species were significantly higher than those in perennial species. In addition, Amass, PNUE, and the quantum yield of PS2 electron transport (ΦPS2) were higher in C4 species than in C3 species. Nmass, Amass, and SLA were significantly positively correlated with each other. SLA was significantly negatively correlated with the photochemical efficiency of PS2 in the light (Fv'/Fm'), whereas it was significantly positively correlated with PNUE.

[Effects of future climate change on climatic suitability of rubber plantation in China].

Global warming may seriously affect the climatic suitability distribution of rubber plantation in China. Five main climate factors affecting rubber planting were mean temperature of the coldest month, mean extremely minimum temperature, the number of monthly, mean temperature ≥18 °C, annual mean temperature and annual mean precipitation. Climatic suitability areas of rubber plantation in 1981-2010, 2041-2060, 2061-2080 were analyzed by the maximum entropy model based on the five main climate factors and the climate data of 1981-2010 and RCP4.5 scenario data. The results showed that under the background of the future climate change, the climatic suitability area of rubber plantation would have a trend of expansion to the north in 2041-2060, 2061-2080. The climatic suitability areas of rubber plantation in 2041-2060 and 2061-2080 increased more obviously than in 1981-2010. The suitable area and optimum area would increase, while the less suitable area would decrease. The climatic suitability might change in some areas, such as the total suitable area would decrease in Yunnan Province, and the suitability grade in both Jinghong and Mengna would change from optimum area to suitable area. However, the optimum area of rubber plantation would increase significantly in Hainan Island and Leizhou Peninsula of Guangdong Province, and a new less suitable area of rubber planting would appear in Taiwan Island due to the climate change.

[Optimum field observation data for simulating maize leaf area index].

Leaf area index is a key indicator of leaf area change of crop population, and also, an important parameter for studying crop photosynthesis, transpiration, and biomass formation, etc. How to establish an optimum leaf area index (LAI) dynamic model with the minimum field observation data is of great significance for accurately simulating crop growth and yield. Based on the field experiment data of various spring maize varieties from the Jinzhou Agricultural Ecosystem Research Station in Northeast China in 2005-2011, in combination with the universal maize LAI dynamic model, this paper discussed the optimum field observation data for accurately simulating the dynamics of maize LAI. It was suggested that for the accurate simulation of the dynamics of maize LAI, the field observation should be no less than 3 years, with at least 4 times observation during the growth period each year. The proper four observation times during maize growth period were suggested as about 20 d after seedling emergence for the first observation, and monthly thereafter for the other three observations. This study could provide reference for conducting an effective observation on leaf area index and its dynamic modeling.

Spatial patterns and climate drivers of carbon fluxes in terrestrial ecosystems of China.

Understanding the dynamics and underlying mechanism of carbon exchange between terrestrial ecosystems and the atmosphere is one of the key issues in global change research. In this study, we quantified the carbon fluxes in different terrestrial ecosystems in China, and analyzed their spatial variation and environmental drivers based on the long-term observation data of ChinaFLUX sites and the published data from other flux sites in China. The results indicate that gross ecosystem productivity (GEP), ecosystem respiration (ER), and net ecosystem productivity (NEP) of terrestrial ecosystems in China showed a significantly latitudinal pattern, declining linearly with the increase of latitude. However, GEP, ER, and NEP did not present a clear longitudinal pattern. The carbon sink functional areas of terrestrial ecosystems in China were mainly located in the subtropical and temperate forests, coastal wetlands in eastern China, the temperate meadow steppe in the northeast China, and the alpine meadow in eastern edge of Qinghai-Tibetan Plateau. The forest ecosystems had stronger carbon sink than grassland ecosystems. The spatial patterns of GEP and ER in China were mainly determined by mean annual precipitation (MAP) and mean annual temperature (MAT), whereas the spatial variation in NEP was largely explained by MAT. The combined effects of MAT and MAP explained 79%, 62%, and 66% of the spatial variations in GEP, ER, and NEP, respectively. The GEP, ER, and NEP in different ecosystems in China exhibited 'positive coupling correlation' in their spatial patterns. Both ER and NEP were significantly correlated with GEP, with 68% of the per-unit GEP contributed to ER and 29% to NEP. MAT and MAP affected the spatial patterns of ER and NEP mainly by their direct effects on the spatial pattern of GEP.

[Effects of dynamic aerodynamic parameters on simulating the land-atmosphere flux exchange in maize field: a case study of BATS1e model].

Based on the continuous observations on the land-atmosphere flux exchange and the meteorological and biological elements in a maize field at the Jinzhou Agricultural Ecosystem Research Station in Liaoning Province of Northeast China from 2006 to 2008, and by using the dynamic roughness (z0) and zero-displacement (d) parameterization scheme considering the effects of leaf area index, canopy height and wind speed at different developmental stages of maize, the BATS1e model was modified, and applied to investigate the effects of dynamic aerodynamic parameters on the flux exchange between maize agroecosystem and atmosphere. Compared with the original model, the drag coefficient (C(D)) simulated by the modified model increased, and its diurnal variation was more obvious with increasing vegetation coverage, which was more accordant with practical circumstances. The simulation accuracies of sensible heat (H), latent heat (lambdaE) and soil heat flux were improved in varying degree, and the Nash-Sutcliffes (NSs) were increased by 0.0569, 0.0194 and 0. 0384, with the improvement quantities in the growth season being 0.9%, 1.1% and 1.2% of global radiation, respectively. The dynamic parameterizations of z0 and d played a more remarkable role to increase the simulation accuracies of H and lambdaE with the actual observation of soil water content introduced into the improved model. This research proved that more reasonable dynamic aerodynamic parameterizations could fulfill an obvious function to improve the land surface processes simulation.

[Relationships of forest fire with lightning in Daxing' anling Mountains, Northeast China].

Forest fire is an important factor affecting forest ecosystem succession. Recently, forest fire, especially forest lightning fire, shows an increasing trend under global warming. To study the relationships of forest fire with lightning is essential to accurately predict the forest fire in time. Daxing' anling Mountains is a region with high frequency of forest lightning fire in China, and an important experiment site to study the relationships of forest fire with lightning. Based on the forest fire records and the corresponding lightning and meteorological observation data in the Mountains from 1966 to 2007, this paper analyzed the relationships of forest fire with lightning in this region. In the period of 1966-2007, both the lightning fire number and the fired forest area in this region increased significantly. The meteorological factors affecting the forest lighting fire were related to temporal scales. At yearly scale, the forest lightning fire was significantly correlated with precipitation, with a correlation coefficient of -0.489; at monthly scale, it had a significant correlation with air temperature, the correlation coefficient being 0.18. The relationship of the forest lightning fire with lightning was also related to temporal scales. At yearly scale, there was no significant correlation between them; at monthly scale, the forest lightning fire was strongly correlated with lightning and affected by precipitation; at daily scale, a positive correlation was observed between forest lightning fire and lightning when the precipitation was less than 5 mm. According to these findings, a fire danger index based on ADTD lightning detection data was established, and a forest lightning fire forecast model was developed. The prediction accuracy of this model for the forest lightning fire in Daxing' anling Mountains in 2005-2007 was > 80%.

[Climatic suitability of single cropping rice planting region in China].

To clarify the leading climate factors affecting the distribution of single cropping rice planting region in China at national and annual temporal scales and to reveal the potential distribution and climatic suitability divisions of this planting region in China could not only provide scientific basis for optimizing the allocation of single cropping rice production, modifying planting pattern, and introducing fine varieties, but also ensure the food security of China. In this paper, the potential climate factors affecting the single cropping rice distribution in China at regional and annual scales were selected from related literatures, and the single cropping rice geographic information from the national agro-meteorological observation stations of China Meteorological Administration (CMA), together with the maximum entropy model (MaxEnt) and spatial analyst function of Arc-GIS software, were adopted to clarify the leading climate factors affecting the potential distribution of single cropping rice planting region in China, and to construct a model about the relationships between the potential distribution of the planting region and the climate. The results showed that annual precipitation, moisture index, and days of not less than 18 degrees C stably were the leading climate factors affecting the potential distribution of single cropping rice planting region in China, with their cumulative contribution rate reached 94.5% of all candidate climate factors. The model constructed in this paper could well simulate the potential distribution of single cropping rice planting region in China. According to the appearance frequency, the low, medium and high climatic suitability divisions of single cropping rice planting region in China were clarified, and the climate characteristics of the planting region in each climatic suitability division were analyzed.