Fluxes of CO2,CH4 and N2O from alpine grassland in the Tibetan Plateau

Using static chamber technique,fluxes of CO2,CH4 and N2O were measured in the alpine grassland area from July 2000 to July 2001,determinations of mean fluxes showed that CO2 and N2O were generally released from the soil,while the alpine grassland accounted for a weak CH4 sink.Fluxes of CO2,CH4 and N2O ranged widely.The highest CO2 emission occurred in August,whereas almost 90?of the whole year emission occurred in the growing season.But the variations of CH4 and N2O fluxes did not show any clear patterns over the one-year-experiment.During a daily variation,the maximum CO2 emission occurred at 16:00,and then decreased to the minimum emission in the early morning.Daily pattern analyses indicated that the variation in CO2 fluxes was positively related to air temperatures(R^2=0.73)and soil temperatures at a depth of 5 cm(R^2=0.86),whereas daily variations in CH4 and N2O fluxes were poorly explained by soil temperatures and climatic variables.CO2 emissions in this area were much lower than other grasslands in plain areas.

利用Tn5gusA5对大豆慢生根瘤菌lrp基因的诱变

通过对重组质粒ｐＧＸＮ３００中的 ２．３ｋｂ ＥｃｏＲＩ片段测序分析发现，其上有一完整的ｌｒｐ基因和部分 ｐｕｔＡ基因，与 Ｋｉｎｇ ＮＤ等［１］报道的 Ｂ．ｊａｐｏｎｉｃｕｍ的ｌｒｐ基因ＤＮＡ序列有 ８８％同源性。利用 Ｔｎ５ ｇｕｓＡ５定位 诱变方法，对质粒ｐＧＸＮ３００进行插入诱变，得到２．３ｋｂ　ＥｃｏＲＩ片段上有Ｔｎ５ｇｕｓＡ５插入位点的质粒ｐＧＸＮ３００－ Ｔ３８，将ｐＧＸＮ３００－Ｔ３８转移到大豆馒生根瘤苗（Ｂ．ｊａｐｏｎｉｃｕｍ）ＧＸ２０１中，得到的ＧＸ２０１转移接合子与不相容 质粒ｐＰＨ１ＪＩ发生同源双交换。通过抗性及ｇｕｓＡ活性检测，筛选到一ｌｒｐ基因突变株。Ｓｏｕｔｈｅｍ杂交分析证 明这突变株的 Ｔｎ５ ｇｕｓＡ５插入确实是同源交换而不是转座产生，表明 Ｔｎ５ ｇｕｓＡ５ 诱变可以应用于大豆慢生根 瘤菌中的突变林筛选。

慢生大豆根瘤菌与竞争结瘤相关的lrp基因的克隆

通过对重组质粒 pGXN30 0中的 2 .3kbEcoRI片段测序分析发现 ,其中含有一完整的lrp基因和部分 putA基因 ,与King等报道的B .japonicum的lrp基因DNA序列有 88%同源性。应用Tn5gusA5定位诱变的方法获得了gusA基因表达的根瘤菌lrp基因突变体GX2 0 10 8。植株试验表明 ,突变株结瘤时间明显推迟 ,竞争结瘤能力也显著下降

CO2 Flux Estimation by Different Regression Methods from an Alpine Meadow on the Qinghai-Tibetan Plateau

National Key Research and Development Program [2010CB833500]; National Natural Science Foundation of China [30590381]; Chinese Academy of Sciences [KZCX2-YW-432]

Short-term effect of increasing nitrogen deposition on CO2, CH4 and N2O fluxes in an alpine meadow on the Qinghai-Tibetan Plateau, China

National Key Research and Development Program [2010CB833500]; Natural Science Foundation of China [30590381]; Knowledge Innovation Project of Chinese Academy of Sciences [KZCX2-YW-432]

Effects of multiple environmental factors on CO2 emission and CH4 uptake from old-growth forest soils

National Key Research and Development Program [2010CB833502]; National Natural Science Foundation of China [30600071, 40601097, 30590381, 30721140307]; Knowledge Innovation Project of the Chinese Academy of Sciences [KZCX2-YW-432, O7V70080SZ, LENOM07LS-01

Potential CO2 Emission Reduction by Development of Non-Grain-Based Bioethanol in China

Assessment of the potential CO2 emission reduction by development of non-grain-based ethanol in China is valuable for both setting up countermeasures against climate change and formulating bioethanol policies. Based on the land occupation property, feedstock classification and selection are conducted, identifying sweet sorghum, cassava, and sweet potato as plantation feedstocks cultivated from low-quality arable marginal land resources and molasses and agricultural straws as nonplantation feedstocks derived from agricultural by-products. The feedstock utilization degree, CO2 reduction coefficient of bioethanol, and assessment model of CO2 emission reduction potential of bioethanol are proposed and established to assess the potential CO2 emission reduction by development of non-grain-based bioethanol. The results show that China can obtain emission reduction potentials of 10.947 and 49.027 Mt CO2 with non-grain-based bioethanol in 2015 and 2030, which are much higher than the present capacity, calculated as 1.95 Mt. It is found that nonplantation feedstock can produce more bioethanol so as to obtain a higher potential than plantation feedstock in both 2015 and 2030. Another finding is that developing non-grain-based bioethanol can make only a limited contribution to China's greenhouse gas emission reduction. Moreover, this study reveals that the regions with low and very low potentials for emission reduction will dominate the spatial distribution in 2015, and regions with high and very high potentials will be the majority in 2030.