Emergy Assessment of a Wheat-Maize Rotation System with Different Water Assignments in the North China Plain

Sustainable water use is seriously compromised in the North China Plain (NCP) due to the huge water requirements of agriculture, the largest use of water resources. An integrated approach which combines the ecosystem model with emergy analysis is presented to determine the optimum quantity of irrigation for sustainable development in irrigated cropping systems. Since the traditional emergy method pays little attention to the dynamic interaction among components of the ecological system and dynamic emergy accounting is in its infancy, it is hard to evaluate the cropping system in hypothetical situations or in response to specific changes. In order to solve this problem, an ecosystem model (Vegetation Interface Processes (VIP) model) is introduced for emergy analysis to describe the production processes. Some raw data, collected by investigating or observing in conventional emergy analysis, may be calculated by the VIP model in the new approach. To demonstrate the advantage of this new approach, we use it to assess the wheat-maize rotation cropping system at different irrigation levels and derive the optimum quantity of irrigation according to the index of ecosystem sustainable development in NCP. The results show, the optimum quantity of irrigation in this region should be 240-330 mm per year in the wheat system and no irrigation in the maize system, because with this quantity of irrigation the rotation crop system reveals: best efficiency in energy transformation (transformity = 6.05E + 4 sej/J); highest sustainability (renewability = 25%); lowest environmental impact (environmental loading ratio = 3.5) and the greatest sustainability index (Emergy Sustainability Index = 0.47) compared with the system in other irrigation amounts. This study demonstrates that application of the new approach is broader than the conventional emergy analysis and the new approach is helpful in optimizing resources allocation, resource-savings and maintaining agricultural sustainability.

土壤-作物体系黄曲霉种群分布及其毒素污染

在辽宁地区开展土壤-作物体系黄曲霉种群分布及其毒素污染研究，结果表明：黄曲霉是辽宁地区土壤和作物当中存在的优势种，L品系是主要品系；在黄曲霉种群构成及黄曲霉品系分布上具有地域特征。土壤黄曲霉菌落数在作物不同生育期具有显著差异。分别从土壤、玉米当中分离到的黄曲霉产毒率是22％和46％，土壤～作物体系中黄曲霉产毒率是39％。试验中未检出强产毒菌株，说明辽宁地区土壤一作物体系中黄曲霉菌株具有较低的产毒能力。依据我国现行的粮食中黄曲霉毒素允许标准，辽宁地区的玉米黄曲霉毒素污染处于低水平，平均黄曲霉毒素含量为0.89μg．kg-1，符合粮食安全标准。但少数样本超出了一些发达国家颁布的严格限定，表明该区仍需对玉米黄曲霉毒素污染加以控制。从区域分布看，干旱较重的辽西地区黄曲霉毒素污染较湿润的辽东和辽中地区严重。黄曲霉毒素污染随着玉米储藏时间延长有增加的趋势。土壤黄曲霉菌落数与玉米黄曲霉毒素污染呈正相关关系，用土壤黄曲霉菌落数能较好地反映该地区的黄曲霉毒素污染状况。轮作对一减少土壤中黄曲霉数量具有显著影响。在田间管理中应当实施合理轮作及适时灌溉，可预防黄曲霉侵染及降低黄曲霉毒素污染。

旱地冬小麦氮磷自然供给能力及其吸收氮磷来源的长期定位试验

利用在黄土旱塬上布置的 13年小麦连作肥料定位试验资料 ,研究了旱地冬小麦氮磷的自然供给能力和吸收来源于肥料和土壤的氮磷相对比例。结果表明 ,旱地冬小麦氮素的自然供给能力为 2 6 6 8～ 2 7 4 9kg/hm2 ,平均为 2 7 2kg/hm2 ;磷素自然供给能力为 5 2 1～ 8 4 9kg/hm2 ,平均为 7 31kg/hm2 。小麦吸收氮素有 51 9%～ 76 8%来自氮肥 ,平均为 6 6 6 % ;而来自土壤为2 3 2 %～ 4 8 1% ,平均 33 4 %。小麦吸收磷素来源于肥料的为 13 6 %～ 4 7 8% ,平均为2 8 7% ;来源于土壤为 52 2 %～ 86 4 % ,平均为 71 3%。同一肥底基础上 ,随肥料用量的增加 ,小麦吸收氮或磷素来源于肥料的比例也增大 ,而来源于土壤的比例逐渐减少。本试验条件下 ,氮肥利用率变幅为 32 6 %～ 6 6 0 % ,平均为 51 1% ;磷肥利用率变幅为 1 72 %～ 14 0 2 % ,平均为 7 0 %

Monitoring and simulation of water, heat,and CO2 fluxes in terrestrial ecosystems based on the APEIS-FLUX system

The Integrated Environmental Monitoring (IEM) project, part of the Asia-Pacific Environmental Innovation Strategy (APEIS) project, developed an integrated environmental monitoring system that can be used to detect, monitor, and assess environmental disasters, degradation, and their impacts in the Asia-Pacific region. The system primarily employs data from the moderate resolution imaging spectrometer (MODIS) sensor on the Earth Observation System- (EOS-) Terra/Aqua satellite,as well as those from ground observations at five sites in different ecological systems in China. From the preliminary data analysis on both annual and daily variations of water, heat and CO2 fluxes, we can confirm that this system basically has been working well. The results show that both latent flux and CO2 flux are much greater in the crop field than those in the grassland and the saline desert, whereas the sensible heat flux shows the opposite trend. Different data products from MODIS have very different correspondence, e.g. MODIS-derived land surface temperature has a close correlation with measured ones, but LAI and NPP are quite different from ground measurements, which suggests that the algorithms used to process MODIS data need to be revised by using the local dataset. We are now using the APEIS-FLUX data to develop an integrated model, which can simulate the regional water,heat, and carbon fluxes. Finally, we are expected to use this model to develop more precise high-order MODIS products in Asia-Pacific region.