| As a typical ecosystem, the grasslands of China are of special ecological interests for maintaining the patterns, functions and processes of natural ecosystem. Now, against a background of global changing, the study of productivity and carbon storage of grasslands ecosystem has become a hot issue, and some relative researches have been carried out in the temperate grasslands of northern China and alpine grasslands of the Qinghai-Tibet Plateau, but few researches related to grassland’s carbon circling have been carried out in the southern of China. Taking the southern China’s grasslands as the research objects, the paper classified varieties of grasslands according to the vegetation classification scheme proposed by IGBP and improved Comprehensive Sequence Classification System (CSCS) approach, calculated the relative accurate area and study the spatial and temporal features of grasslands ecosystem. Meanwhile, MODIS data and other climatic data were selected as input data to operate the classification indices model, CASA model, GLO-PEM model, LPA model and BIOME-BGC model, and evaluated the spatial and temporal pattern of NPP and NEP in the southern China’s grasslands. The research was carried out from the aspect of the relationship between carbon source and sink, carbon storage, and some influence factors such as land use and cover change (LUCC), grazing and round enclosing, and precipitation and temperature. The main contents and results are as follows:(1) The distribution of typical forest and grassland ecosystem was greatly influenced by LUCC. From 1990 to 2010, the area of farmlands in Zhangjiagang City decreased sharply from 4.45×104ha to 3.55×104ha, decreased by 20.2%; Urban area has changed from 3.0×104ha to 3.4×104ha, increased by 13.3%; typical forest and grassland area decreased by 20.0%, from 5×103ha to 4×103ha. The land area for transportation was also tended to rise from 1990 to 2010. This meaned that Zhangjiagang City was in the process of accelerated urbanization and becoming a new industrial city from a mostly rural city. We deemed that this change is closely related with synthetic effects of population factor, policy factor, economic growth factor, agricultural structure readjustment and transportation. The typical forest and grasslands ecosystem is a special land cover type, coupling with the specific characteristic of small-medium cities in the southern of China. By analyzing the land use intensity, it found that the LUCC intensity values of typical forest and grassland from 1990 to 1995,1995 to 2000, and 2000 to 2005 were negative. However, the LUCC intensity value from 2000 to 2005 was positive. This demonstrates that typical forest and grassland ecosystem is proceeding along active development and utilization.(2) The pattern of productivity in Zhangjiagang City was greatly influenced by LUCC. Taking Zhangjiagang City as the study area, applying the Modis image data and models related with net primary productivity (NPP) to estimate the act and potential NPP in 2008 and study the characteristics of spatial distribution of the losing NPP caused by LUCC. It found that in the process of urbanization, it lost a lot of NPP for the reason of LUCC in Zhangjiagang City. The NPP in city area decreased sharply, the NPPlucc value of forest and grassland ecosystem was relatively low, and which of agro-ecosystems is minimum for irrigation and fertilization, so have a higher productivity than potential NPP. The NPPlucc in Zhangjiagang appeared to have a decline trend from city to rural area, thereinto have two protuberance peaks on the urban and rural connecting areas and industrial regions in countryside. The results showed that management measures and technology ways could be applied to decrease disturbance to natural ecosystem, then minimized the loss of NPP caused by LUCC and human activities.(3) The dynamics of grasslands resources of Jiangsu Province were monitored in this research. By comparing and analyzing the survey data of the grasslands in Jiangsu Province in 1984 and MOD12Q1 data in 2004, the grasslands resources in Jiangsu Province may be divided into four main regions, respectively northern hilly region, hilly region in Nanjing-Zhenjiang-Yangzhou, hilly and mountainous region in Yixing-Liyang and southeastern coastal region. During the two decades, the meadow area decreased by 18%, from 412708.57ha in 1984 to 337231.39ha in 2004. The main grasslands types included meadow, grass cluster, brush, shrubbery, open forests, Saline meadow, forests pasture and grass nearby farmland. Comparing with 1984, the area of meadow, grass cluster, brush and grass nearby farmland decreased obviously, the area of open forest and saline meadow decreased slightly, and shrubbery remained unchanged, however, the area of forests pasture increased slightly, Palatability and some nutritional indicators of pasture also declined. On the respect of the animal carrying capacity of grasslands, it declined from 183657.7 cattle unit in 1980’s to 125984.5 cattle unit in recently years, decreased by 31.4%. The grasslands of Jiangsu Province are important components of the southern of China, so it is important for the research of whole southern China’s grasslands to analyze the change of grasslands resources of Jiangsu Province in recently two decades and the courses leading to the changes.(4) Different grazing utilization treatments had significantly different effect on the photosynthesis rate and respiration rate in the alpine steppe meadow of Anhui Province. The net photosynthesis rate showed in an order of lightly grazing treatment> enclosure area> medium grazing> severe grazing, which showed two-peaked curve in daily change, and had a peak in the morning and afternoon, with the increase of intake rate, the peak in the morning of net photosynthesis rate change delayed, the peak value of lightly grazing and enclosure treatment appeared at about 8:00 in the morning, and which of medium grazing appeared at about 9:00 in the morning, however, peak of severe grazing appeared at about 10:00 in the morning. Unlike the photosynthesis rate, the change of respiration rate of grasslands under different grazing intensity showed similar trend, increased at first and followed by a decrease, the peak value of all treatments all appeared at 1:00 in the afternoon. The photorespiration rate of lightly grazing treatment was highest, enclosure treatment was second, and followed by medium grazing, then severe grazing treatment was lowest. It also found that the changes of photosynthesis rate were mainly related to the effective leaf area, light intensity, the Rubisco activity and so on, yet the photorespiration rate was concerned with respiration substrate and environmental temperature. The studies on photosynthesis and respiration under different grazing intensity in grasslands of Southern of China played an exemplary role, and had important meanings for global change, rational utilization of resources and scientific management of grasslands.(5) The grasslands of Southern of China were classified by using the improved CSCS approach. The traditional CSCS approach was improved by keeping the humidity grades unchanged and decreasing the annual accumulated temperature above 0℃ grades from 7 to 5, and merging the original cold-temperate and cool-temperate thermal grades into one thermal grade, consolidating warm-temperate and warn-heat thermal grades into one grade. The grasslands of Southern of China could be classified into four classes, namely tundra grassland class, steppe grassland class, shrubs and steppe mixed grassland class and alpine meadow grassland class. On the type level,9 types of grasslands in the study area were classified, namely forest steppe, sparse forest brush, alpine steppe, grasses-fruticous steppe, temperate meadow steppe, montane meadow, rain tundra, subtropical brush steppe, montane meadow steppe. Comparring with the traditional CSCS approach, the improved CSCS approach was more suitable for the situation of southern China’s grasslands, and classified the most part of evergreen broad-leaved forest based on former CSCS approach into evergreen broad-leaved forest, brush and steppe mixed grassland, alpine meadow and so on. This research futher boosted the development of CSCS approach in practice and had important implications for the classification and area determination of grasslands in the southern of China.(6) The classification indices model was used to estimate the temporal and spatial pattern of grasslands of southern China. It found that the NPP had a trend to decrease from east to west and south to north, and annual mean NPP was 756.3gC.m-2.yr-1. The NPP value of alpine meadow grassland class was relatively high, generally more than 1200gC.m-2.yr-1, the NPP value of shrubs and steppe mixed grassland class was in a range from 1000 to 1200gC.m-2.yr-1, Tundra grassland class was located in southeastern Tibet with high elevation, the value was lowest (<600 gC.m-2.yr-1). The steppe grassland class was distributed in most of area, the value was generally from 600 to 1000gC.m-2.yr-1. The total NPP of grasslands in study area was 68.46TgC. The NPP value of steppe grassland class was the highest (48.44TgC), and shrubs and steppe mixed grassland class was second (16.54TgC), followed by alpine meadow grassland class (3.22TgC), then tundra grassland class was the lowest (0.25TgC). For grasslands types, the total NPP of forest steppe was highest (34.81TgC), following by sparse forest brush (16.54TgC), and the lowest type was montane meadow steppe (0.01TgC).(7) The improved CASA model was used to estimate NPP in the study area. The results showed that the annual NPP in grasslands ecosystem of southern of China in 2001 was 266.75gC.m-2.yr-1, and the annual NPP in the study area in 2010 was 149.71gC.m-2.yr-1. The total NPP in 2001 was 0.22 Pg, and the value in 2010 was 0.11Pg. As a whole, the change trend of total NPP in the southern China’s grasslands was declining during the ten years. Specific to spatial pattern, the average NPP value in Hainan Province was highest (402.68gC.m-2.yr-1), the average NPP in Yunnan Province was second, with the value of 325.44gC.m-2.yr-1, followed by Fujian Province 315.79C.m-2.yr-1), and the value in southeastern Tibet was minimum (188.89gC.m-2.yr-1). Analyzing the average NPP of different types of grasslands, savanna was highest (228.11gC.m-2.yr-1), woods savanna was the second (213.19gC.m-2.yr-1), and followed by typical grasslands (204.40gC.m-2.yr-1), wetlands (201.66gC.m-2.yr-1), open shrubs was minimum (177.53gC.m-2.yr-1). The total NPP of woods savanna was highest (68.52TgC), typical grasslands was the second (44.00 TgC), followed by savanna, open shrubs and wetlands, the values were 13.89,11.47,1.88 TgC respectively.(8) We adopted GLO-PEM model to simulate NPP in southern China’s grasslands and analyze the temporal and spatial dynamics from 1981 to 2000. The results showed that the annual mean NPP was 1082gC.m-2.yr-1, and the highest value (1798gC.m-2.yr-1) was in Hainan province, and the lowest value (500gC.m-2.yr-1) was in southwestern Tibet. On the level of grasslands types, The highest mean NPP values were in the permanent wetlands (1193gC.m-2.yr-1) and savannas (1137gC.m-2.yr-1), woods savannas had a median value (mean=1087), and the lowest NPP occurred in typical grasslands and open shrubs, the mean values respectively were 709 and 689gC.m-2.yr-1. There was a good correlation between measured and simulated values (R2=0.84). Temporally, the total NPP increased slightly in the 20-year period, especially during 1981 to 1990 (R2=0.47). The mean NPP total amount in the 20 years was 0.758PgC.yr-1(1Pg=1015g), Inter-annual variation of total NPP was mainly driven by annual mean temperature rather than annual mean precipitation. These suggest that the grasslands ecosystems in the southern of China may be a huge carbon sink.(9) To simulate the NPP in Southern China’s grasslands, we built a land portfolio assessment (LPA) model according to the framework and theory of this model. The model was driven by two parameters:leaf area index and photosynthesis accumulation (PA). PA is represented by the amount of net photosynthetic production based on fixed-point observation and the inner implication of NPP. The model was driven by the monthly meteorological data derived from a meteorological station. Data on the normalised difference vegetation index (NDVI) were obtained from the Earth Observing System/Moderate-Resolution Imaging Spectroradiometer-NDVI. The results showed that the NPP values in the study area had a decreasing trend from east to west and south to north and that the average NPP was 389.14g.C.m-2.yr-1. Correlation analysis showed that the coefficient between NPP and temperature was higher than that between NPP and precipitation. Using trial and error, the LPA model accurately simulated the NPP dynamics of Southern China’s grassland ecosystem, and the results were biologically realistic.(10) The improved BIOME-BGC model was used to estimate the NPP and NEP of Southern of China’s typical grasslands from 2001 to 2010. The results showed that the mean NPP and NEP of alpine steppe meadow were 357.17and 3.25gC.m-2.yr-1 respectively, and which of typical grrasslan mountain and slope in Weining of Guizhou Province were 232.40 and 21.28gC.m-2.yr-1, and which of alpine meadow in Hongyuan of Sichuan Province were 191.96 and 81.96gC.m-2.yr-1. Correlation analysis showed that the coefficient between the NPP, NEP of the three typical grasslands and annual temperature was significant, however, the correlation between precipitation and productivity index (NPP, NEP) was not evident. The tendency of NPP and NEP were predicted by using BIOME-BGC model under future climate change scenarios. The results showed that under C1P-1T1 scenario (CO2 doubling, precipitation decreasing by 10%, temperature increasing by 2℃) which might be the most probable climate pattern, the NPP and NEP of alpine steppe meadow increased by 26.93% and 160%, and which of typical grassland mountain and slope increased by 62.20% and 153% repectively, and which of alpine meadow increased by 135% and 206% respectively. The relationship between carbon source and sink of different types of grasslands was distinct, and the features of carbon corcing under future climate change scenarios were predicted in this research.(11) Carbon storage of different types of grasslands from 2001 to 2010 was estimated by using a remote sensing parameter model. The grasslands in the study area may be classified into five types based on land cover and classification scheme proposed by IGBP. The results showed that the total area of southern China’s grasslands was 729136km2, and open shrubs accounted for 2.16%, woods savanna accounted for 53.54%, savanna accounted for 1.45%, typical grasslands accounted for 38.90%, permanent wetlands accounted for 3.96%. The Biomass of carbon density of different types of grasslands was 198.87,244.35,237.72, 174.60,178.57gC.m-2. The total carbon storage was 155.69TgC, of which open shrubs accounted for 2.01%(3.13TgC), woods savanna accounted for 61.27%(95.39TgC), savanna accounted for 1.61%(2.51TgC), typical grasslands accounted for 27.41%(49.52TgC), permanent wetlands accounted for 2.80%(5.15TgC).As for the innovation of this text, first, the researches on the integration of spatial and temporal pattern, classification, productivity (NPP and NEP) and relative influence factors (LUCC and grazing utilization methods), carbon storage and so on were carried out in the southern of China’s grasslands, and the fundmental scientific problems on the estimation of productivity and carbon storage of Southern China’s grasslands were sloved at home and abroad for the first time. Second, the vegetation in the southern of China were classified into most part of forest, and the pratical prasslands can not be distinguished from the vegetation based on traditional CSCS approach. So the traditional CSCS approach was improved. The southern China’s grasslands may be classified into four classes and nine types. Comparring with the traditional CSCS approach, the improved CSCS approach was more suitable for the situation of southern China’s grasslands. Third, five models were used to analyzed the spatial and temporal pattern of NPP in the southern of China. By comparing with the results simulated by five different models, LPA model was identified as a suitable model for evaluating the grasslands NPP. Meanwhile, BIOME-BGC model was also used to estimate the NEP and variation trend of different types of grasslands under future climate change scenarios.In short, the features of grasslands resources, classification, productivity and carbon storage were estimated by using mathematical model on the palform of some geo-spatial softwares. |
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