浑善达克沙地与河北沽源地区土地沙漠化研究

The Otindag sandy land and the Guyuan region of Hebei Province lie in the agro-pastoral zone, where sandy desertification is serious. So they are typical for us to study on. In this paper, detail investigation were made on the Remote Sensing, Hydrochemistry, Chronology, grain size analyzing of research region to monitor sandy desertification and environmental background. The main conclusions are presented as following: 1. According to the diverse natural condition, the research area is divided into three types as sandy land desertification, cultivated land desertification and desertification reflected by lake change. The monitoring result of the first type shows that the main performance way of the sandy desertification in Otindag sandy land is that (1) the expansion of both the shifting dune and the half fixed sandy dune, (2) the reduce of the fixed sandy dune. While the result of the second type shows (1) the desertification land in the Guyuan region has first increasing then reducing change for about 30 years. (2) The sand mainly concentrates west of the research area and small part of wind-drift sand distributes northeast the research area with the spot shape. (3) The meadow area increases obviously. As far as the third type, the Dalai Nur lake area occurs first expanding then reducing change and the wind-drift sand around the lake first reduces then increases. 2. The land cover of the different types change with the same law. It is worth notice that the lake area changes oppositely with that of the wind-drift sand. 3. For about 5,000 a B.P. -2800 a B.P., the well developed palaeosols emerged. After that, three layer palaeosols were founded in the profile of Otindag sandy land. The analyses of grain size show that the sand grains of the south were coarser than that of the north. The sand in the north and middle were well sorted, while the south poor sorted. 4. Both the natural and human impact on the process of sandy desertification. On this research result, different regions have different influences. So the measures to improve sandy desertification should be choosed respectively.

西藏高原草原化嵩草草甸生态系统呼吸及碳平衡

The soil respiration and net ecosystem productivity of Kobresia littledalei meadow ecosystem was investigated at Dangxiong grassland station, one grassland field station of Lhasa Plateau Ecosystem Research Station. Soil respiration and soil heterotrophic respiration were measured at the same time by using Li6400-09 chamber in growing season of year 2004. The response of soil respiration and its components, i.e. microbial heterotrophic respiration and root respiration to biotic and abiotic factors were addressed. We studied the daily and seasonal variation on Net Ecosystem carbon Exchange (NEE) measured by eddy covariance equipments and then the regression models between the NEE and the soil temperature. Based on the researches, we analyzed the seasonal variation in grass biomass and estimated NEE combined the Net Ecosystem Productivity with heterogeneous respiration and then assessed the whether the area is carbon source or carbon sink. 1.Above-ground biomass was accumulated since the grass growth started from May; On early September the biomass reached maximum and then decreased. The aboveground net primary production (ANPP) was 150.88 g m~" in 2004. The under-ground biomass reached maximum when the aboveground start to die back. Over 80% of the grass root distributed at the soil depth from 0 to 20cm. The underground NPP was 1235.04 g m"2.. Therefore annual NPP wasl.385X103kg ha"1, i.e.6236.6 kg C ha"1. 2. The daily variation of soil respiration showed single peak curve with maximum mostly at noon and minimum 4:00-6:00 am. Daily variations were greater in June, July and August than those in September and October. Soil respiration had strong correlation with soil temperature at 5cm depth while had weaker correlation with soil moisture, air temperature, surface soil temperature, and so on. But since early September the soil respiration had a obviously correlation with soil moisture at 5cm depth. Biomass had a obviously linearity correlation with soil respiration at 30th June, 20th August, and the daytime of 27th September except at 23lh October and at nighttime of 27th September. We established the soil respiration responding to the soil temperature and to estimate the respiration variation during monsoon season (from June through August) and dry season (May, September and October). The regression between soil respiration and 5cm soil temperature were: monsoon season (June through August), Y=0.592expfl()932\ By estimating , the soil daily respiration in monsoon season is 7.798gCO2m"2 and total soil respiration is 717.44 gCC^m" , and the value of Cho is 2.54; dry season (May, September and October), Y=0.34exp°'085\ the soil daily respiration is 3.355gCO2m~2 and total soil respiration is 308.61 gCC^m", and the value of Cho is 2.34. So the total soil respiration in the grown season (From May to October) is 1026.1 g CO2IT1"2. 3. Soil heterogeneous respiration had a strong correlation with soil temperature especially with soil temperature at 5cm depth. The variation range in soil heterogeneous respiration was widely. The regression between soil heterogeneous respiration and 5cm soil temperature is: monsoon season, Y=0.106exp ' 3x; dry season, Y=0.18exp°"0833x.By estimating total soil heterotrophic respiration in monsoon season is 219.6 gCC^m"2, and the value of Cho is 3.78; While total soil heterogeneous respiration in dry season is 286.2 gCCbm"2, and the value of Cho is 2.3. The total soil heterotrophic respiration of the year is 1379.4kg C ha"1. 4. We estimated the root respiration through the balance between soil respiration and the soil heterotrophic respiration. The contribution of root respiration to total respiration was different during different period: re-greening period 48%; growing period 69%; die-back period 48%. 5. The Ecosystem respiration was relatively strong from May to October, and of which the proportion in total was 97.4%.The total respiration of Ecosystem was 369.6 g CO2 m" .we got the model of grass respiration respond to the soil temperature at 5cm depth and then estimated the daytime grass respiration, plus the nighttime NEE and daytime soil respiration. But when we estimated the grass respiration, we found the result was negative, so the estimating value in this way was not close. 6. The estimating of carbon pool or carbon sink. The NPP minus the soil heterogeneous respiration was the NEE, and it was 4857.3kg C o ha"1, which indicated that the area was the carbon sink.

内蒙古草地植被群落生物量的梯度特征研究

Relationship between biology and environment is always the theme of ecology. Transect is becoming one of the important methods in studies on relationship between global change and terrestrial ecosystems, especially for analysis of its driving factors. Inner Mongolia Grassland is the most important in China Grassland Transect brought forward by Yu GR. In this study, changes in grassland community biomass along gradients of weather conditions in Inner Mongolia was researched by the method of transect. Methods of regression about biomass were also compared. The transect was set from Eerguna county to Alashan county (38° 07' 35" ~50° 12' 20" N, 101° 55' 25" -120° 20' 46" E) in Inner Mongolia, China. The sample sites were mainly chosen along the gradient of grassland type, meadow steppe-* typical steppe-*desert steppe-*steppification desert-^desert. The study was carried out when grassland community biomass got the peak in August or September, 2003 and 2004. And data of 49 sample sites was gotten, which included biomass, mean annual temperature, annual precipitation, accumulated temperature above zero, annual hours of sunshine and other statistical and descriptive data. The aboveground biomass was harvested, and the belowground biomass was obtained by coring (30 cm deep). Then all the biomass samples were dried within (80 + 5) °C in oven and weighted. The conclusion is as follows: 1) From the northeast to the southwest in Inner Mongolia, along the gradient of grassland type, meadow steppe-*typical steppe-*desert steppe-*steppification desert-* desert, the cover degree of vegetation community reduces. 2) By unitary regression analysis, biomass is negatively correlated with mean annual temperature, s^CTC accumulated temperature, ^10°C accumulated temperature and annual hours of sunshine, among which mean annual temperature is crucial, and positively with mean annual precipitation and mean annual relative humidity, and the correlation coefficient between biomass and mean annual relative humidity is higher. Altitude doesn't act on it evidently. Result of multiple regression analysis indicates that as the primary restrictive factor, precipitation affects biomass through complicated way on large scale, and its impaction is certainly important. Along the gradient of grassland type, total biomass reduces. The proportion of aboveground biomass to total biomass reduces and then increases after desert steppe. The trend of below ground biomass's proportion to total biomass is adverse to that of aboveground biomass. 3) Precipitation is not always the only driving factor along the transect for below-/aboveground biomass ratio of different vegetation type composed by different species, and distribution of temperature and precipitation is more important, which is much different among climatic regions, so that the trend of below-/aboveground biomass ratio along the grassland transect may change much through the circumscription of semiarid region and arid region. 4) Among reproductive allocation of aboveground biomass, only the proportion of stem in total biomass notably correlates to the given parameters. Stem/leaf biomass ratio decreases when longitude and latitude increase, caloric variables decrease, and variables about water increase from desert to meadow steppe. The change trends are good modeled by logarithm or binomial equations. 5) 0'-10 cm belowground biomass highly correlates to environmental parameters, whose proportion to total biomass changes most distinctly and increases along the gradient from the west to the east. The deeper belowground biomass responses to the environmental change on the adverse trend but not so sensitively as the surface layer. Because the change value of 0~10 cm belowground biomass is always more than that of below 10 cm along the gradient, the deference between them is balanced by aboveground biomass's change by the resource allocation equilibrium hypothesis.

中国北方典型生态区表土孢粉组合特征及其与现代植被和气候的关系

Surface pollen assemblages and their relationhips with the modern vegetation and climate provide a foundation for investigating palaeo-environment conditions by fossil pollen analysis. A promising trend of palynology is to link pollen data more closely with ecology. In this study, I summarized the characteristics of surface pollen assemblages and their quantitative relation with the vegetation and climate of the typical ecological regions in northern China, based on surface pollen analysis of 205 sites and investigating of modern vegetation and climate. The primary conclusions are as follows:The differences in surface pollen assemblages for different vegetation regions are obvious. In the forest communities, the arboreal pollen percentages are more than 30%, herbs less than 50% and shrubs less than 10%; total pollen concentrations are more than 106 grains/g. In the steppe communities, arboreal pollen percentages are generally less than 5%; herb pollen percentages are more than 90%, and Artemisia and Chenopodiaceae are dominant in the pollen assemblages; total pollen concentrations range from 103 to 106 grains/g. In the desert communities, arboreal pollen percentages are less than 5%. Although Chenopodiaceae and Artemisia still dominate the pollen assemblages, Ephedra, Tamaricaceae and Nitraria are also significant important in the pollen assemblages; total pollen concentrations are mostly less than 104grains/g. In the sub-alpine or high and cold meadow communities, arboreal pollen percentages are less than 30%. and Cyperaceae is one of the most significant-taxa in the pollen assemblages. In the shrub communities, the pollen assemblages are consistent with the zonal vegetation; shrub pollen percentages are mostly less than 20%, except for Artemisia and Hippophae rhamnoides communities.There are obvious trends for the pollen percentage ratios of Artemisia to Chenopodiaceae (A/C), Pinus to Artemisia (P/A) and arbor to non-arbor (AP/NAP) in the different ecological regions. In the temperate deciduous broad-leaved forest region, the P/A ratios are generally higher than 0.1, the A/C ratios higher than 2 and the AP/NAP ratios higher than 0.3. In the temperate steppe regions, the P/A ratios are generally less than 0.1, the A/C ratios higher than 1 and the AP/NAP ratios less than 0.1. In the temperate desert regions, the P/A ratios are generally less than 0.1, the A/C ratios less than 1, and the AP/NAP ratios less than 0.1.The study on the representation and indication of pollen to vegetation shows that Pinus, Artemisia, Betula, Chenopodiaceae, Ephedra, Selaginella sinensis etc. are over-representative in the pollen assemblages and can only indicate the regional vegetation. Some pollen types, such as Quercus, Carpinus, Picea, Abies, Elaeagus, Larix, Salix, Pterocelis, Juglans, Ulmus, Gleditsia, Cotinus, Oleaceae, Spiraea, Corylus, Ostryopsis, Vites, Tetraena, Caragana, Tamaricaceae, Zygophyllum, Nitraria, Cyperaceae, Sanguisorba etc. are under-representative in the pollen assemblages, and can indicate the plant communities well. Populus, Rosaceae, Saxifranaceae, Gramineae, Leguminosae, Compositae, Caprifoliaceae etc. can not be used as significant indicators to the plants.The study on the relation of pollen percentages with plant covers shows that Pinus pollen percentages are more than 30% where pine trees exist in the surrounding region. The Picea+Abies pollen percentages are higher than 20% where the Picea+Abies trees are dominant in the communities, but less than 5% where the parent plants are sparse or absent. Larix pollen percentages vary from 5% to 20% where the Larix trees are dominant in the communities, but less than 5% where the parent plants are sparse or absent. Betula pollen percentages are higher than 40% where the Betula trees are dominant in the communities" but less than 5% where the parent plants are sparse or absent. Quercus pollen percentages are higher than 10% where the Quercus trees are dominant in the communities, but less than 1% where the parent plants sparse or absent. Carpinus pollen percentages vary from 5% to 15% where the Carpinus trees are dominant in the communities, but less than 1% where the parent plants are sparse or absent. Populus pollen percentages are about 0-5% at pure Populus communities, but cannot be recorded easily where the Populus plants mixed with other trees in the communities. Juglans pollen accounts for 25% to 35% in the forest of Juglans mandshurica, but less than 1% where the parent plants are sparse or absent. Pterocelis pollen percentages are less than 15% where the Pterocelis trees are dominant in the communities, but cannot be recorded easily where the parent plants are sparse or absent. Ulmus pollen percentages are more than 8% at Ulmus communities, but less than 1% where the Ulmus plants mixed with other trees in the communities. Vitex pollen percentages increase along with increasing of parent plant covers, but the maximum values are less than 10 %. Caragana pollen percentages are less than 20 % where the Caragana plant are dominant in the communities, and cannot be recorded easily where the parent plants are sparse or absent. Spiraea pollen percentages are less than 16 % where the Spiraea plant are dominant in the communities, and cannot be recorded easily where the parent plants are sparse or absent.The study on the relation of surface pollen assemblages with the modern climate shows that, in the axis 1 of DCA, surface samples scores have significant correlation with the average annual precipitations, and the highest determination coefficient (R2) is 0.8 for the fitting result of the third degree polynomial functions. In the axis 2 of DCA, the samples scores have significant correlation with the average annual temperatures, average July temperatures and average January temperatures, and the determination coefficient falls in 0.13-0.29 for the fitting result of the third degree polynomial functions with the highest determination coefficient for the average July temperature.The sensitivity of the different pollen taxa to climate change shows that some pollen taxa such as Pinus, Quercus, Carpinus, Juglans, Spiraea, Oleaceae, Gramineae, Tamariaceae and Ephedra are only sensitive to the change in precipitation.