[1] A biogeochemical model, Denitrification-Decomposition (DNDC), was modified to enhance its capacity of predicting greenhouse gas (GHG) emissions from paddy rice ecosystems. The major modifications focused on simulations of anaerobic biogeochemistry and rice growth as well as parameterization of paddy rice management. The new model was tested for its sensitivities to management alternatives and variations in natural conditions including weather and soil properties. The test results indicated that (1) varying management practices could substantially affect carbon dioxide (CO 2 ), methane (CH 4 ), or nitrous oxide (N 2 O) emissions from rice paddies; (2) soil properties affected the impacts of management alternatives on GHG emissions; and (3) the most sensitive management practices or soil factors varied for different GHGs. For estimating GHG emissions under certain management conditions at regional scale, the spatial heterogeneity of soil properties (e.g., texture, SOC content, pH) are the major source of uncertainty. An approach, the most sensitive factor (MSF) method, was developed for DNDC to bring the uncertainty under control. According to the approach, DNDC was run twice for each grid cell with the maximum and minimum values of the most sensitive soil factors commonly observed in the grid cell. The simulated two fluxes formed a range, which was wide enough to include the ''real'' flux from the grid cell with a high probability. This approach was verified against a traditional statistical approach, the Monte Carlo analysis, for three selected counties or provinces in China, Thailand, and United States. Comparison between the results from the two methods indicated that 61-99% of the Monte Carlo-produced GHG fluxes were located within the MSAproduced flux ranges. The result implies that the MSF method is feasible and reliable to quantify the uncertainties produced in the upscaling processes. Equipped with the MSF method, DNDC modeled emissions of CO 2 , CH 4 , and N 2 O from all of the rice paddies in China with two different water management practices, i.e., continuous flooding and midseason drainage, which were the dominant practices before 1980 and in 2000, respectively. The modeled results indicated that total CH 4 flux from the simulated 30 million ha of Chinese rice fields ranged from 6.4 to 12.0 Tg CH 4 -C per year under the continuous flooding conditions. With the midseason drainage scenario, the national CH 4 flux from rice agriculture reduced to 1.7-7.9 Tg CH 4 -C. It implied that the water management change in China reduced CH 4 fluxes by 4.2-4.7 Tg CH 4 -C per year. Shifting the water management from continuous flooding to midseason drainage increased N 2 O fluxes by 0.13-0.20 Tg N 2 O-N/yr, although CO 2 fluxes were only slightly altered. Since N 2 O possesses a radiative forcing more than 10 times higher than CH 4 , the increase in N 2 O offset about 65% of the benefit gained by the decrease in CH 4 emissions.INDEX TERMS: 0315 Atmospheric Composition and Structure: Biosphere/atmosphere

[1] Validations of the DeNitrification-DeComposition (DNDC) model against field data sets of trace gases (CH 4 , N 2 O, and NO) emitted from cropping systems in Japan, China, and Thailand were conducted. The model-simulated results were in agreement with seasonal N 2 O emissions from a lowland soil in Japan from 1995 to 2000 and seasonal CH 4 emissions from rice fields in China, but failed to simulate N 2 O and NO emissions from an Andisol in Japan as well as NO emissions from the lowland soil. Seasonal CH 4 emissions from rice cropping systems in Thailand were poorly simulated because of site-specific soil conditions and rice variety. For all of the simulated cases, the model satisfactorily simulated annual variations of greenhouse gas emissions from cropping systems and effects of land management. However, discrepancies existed between the modeled and observed seasonal patterns of CH 4 and N 2 O emissions. By incorporating modifications based on the local soil properties and management, DNDC model could become a powerful tool for estimating greenhouse gas emissions from terrestrial ecosystems.

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h i g h l i g h t s < Multi-year, international efforts for studying aerosol and climate impacts across Southeast Asia. < Aerosol and cloud properties measured from both ground-and satellite-based platforms. < Investigation of aerosolecloud interactions and planning for future experiments.

Insect feeding trials were carried out to determine the effects of a range of mannose-specific lectins on third instar nymphs of the rice brown planthopper (BPH), Nilaparvata lugens. StAl. Dose response curves show that Galanthus nivalis agglutinin (GNA) has the strongest toxic effect of the lectins tested, and is effective at concentrations considerably lower than those previously reported. Narcissus pseudonarcissus agglutinin (NPA) and Allium sativum agglutinin (ASA) exhibit a significant antimetabolic effect towards the insect but were less effective (on a molar basis) than GNA. LCs0 values for GNA, NPA and ASA are approximately 4/zM, 11/zM and >40/zM respectively. These mannose-specific lectins are serologically identical, but differ in the number of subunits per protein molecule; ASA is a dimer, NPA is a trimer and GNA is a tetramer. The results obtained support the hypothesis, that the effectiveness of the mannose-binding lectins as antimetabolites is determined by the number of subunits per molecule. Two N-acetylglucosamine binding lectins, the dimeric Oryza sativa agglutinin (OSA) and the monomeric Urtica dioica agglutinin (UDA), were also tested but at a concentration of 0.1% w/v exhibited no significant antimetabolic effect towards BPH, although the related lectin wheatgerm agglutinin (WGA) has previously been demonstrated to be toxic towards the insect.