空气微生物群落解析方法:从培养到非培养

随着世界范围内流行性疾病以及我国空气雾霾事件的不断发生,空气生物性污染的研究开始受到高度重视,其研究方法也随着分子生物学技术的快速发展而不断更新,由早期以生化技术为基础的研究方法转变为以现代分子生物学技术为基础的研究方法。综述了空气微生物群落多样性解析方法从培养到非培养的发展过程,包括培养技术法、BIOLOG技术、生物标记法、基因指纹图谱技术、核酸杂交技术、实时荧光定量PCR、空气微生物宏基因组学及基因芯片技术,阐述了这些技术的基本原理,比较了各种技术的优缺点并重点介绍了它们在空气微生物群落多样性研究中的应用概况,最后展望了空气微生物学研究的发展方向。     

北京市三个功能区空气微生物中值直径及粒径分布特征

空气中微生物对人类健康的危害除了与微生物的种类和浓度有关外,还与微生物粒子的大小密切相关,并且不同粒径的空气微生物对人们健康影响的作用机理不同。通过定点试验调查,运用国产安德森生物粒子取样器着重研究北京市3个功能区(文教区-中国科学院生态环境研究中心所在区域、交通干线-西直门和公园绿地-北京植物园)空气微生物的中值直径和粒径分布。结果表明,不同功能区空气微生物的粒径分布相同,空气细菌,真菌与放线菌的粒径分布各不相同。空气细菌粒径呈偏态分布,空气真菌呈对数正态分布,空气放线菌的分布特征与空气真菌相反,主要分布在>8.2μm和<2.0μm级中。不同属真菌的粒径分布也不相同,枝孢属、青霉属和曲霉属呈对数正态分布,链格孢属和无孢菌为偏态分布。空气细菌的中值直径明显大于空气真菌和放线菌。交通干线和公园绿地空气细菌和真菌粒子中值直径明显大于文教区,放线菌粒子中值直径交通干线明显高于文教区和公园绿地。空气微生物中值直径在一年各月中没有明显的变化规律。     

Ragweed presence in Trieste: clinical and aerobiological data

Summary Studies on ragweed have been carried out in the province of Trieste (Northern Italy) in which it is becoming widespread. The floristic records, the increasing amount of airborne pollen monitored and the relevant skin reactivity are reported. This phenomenon, though still at the beginning, is actually showing an upward trend due to man's intervention over wider and wider areas which as a consequence become suitable for the settlement of these anthropophitic species. The aerobiological data are compared to the skin reactivities of allergic subjects.     

青岛市秋季空气微生物群落多样性

采用KC-6120空气综合采样器采集空气微生物样品,通过构建16S/18SrDNA克隆文库方法分析青岛市市区街道秋季空气微生物群落结构特征.结果表明： 空气细菌分布在6大类,分别为变形菌门(78.8%)、厚壁菌门(14.6%)、放线菌门(4.0%)、浮霉菌门(1.3%)、蓝藻门(0.7%)和栖热菌门(0.6%),优势菌属为不动杆菌属(39.7%)、葡萄球菌属(11.3%)、鞘脂单胞菌属(8.6%)和副球菌属(6.0%).空气真菌分布在子囊菌门(97.5%)和担子菌门(2.5%),优势菌属为核腔菌属(76.5%)、炭角菌属(13.6%)和外瓶霉属(2.5%).空气微生物中存在不动杆菌属、鞘脂单胞菌、葡萄球菌等致病菌或条件致病菌,以及引发多种农作物枯萎死亡的麦类核腔菌、团炭角菌和角状平脐疣孢等真菌.     

Airborne pollen in Padua (NE-Italy): A comparison between two pollen samplers

During recent years a gradual decrease inallergenic airborne pollen concentration hasbeen observed in the monitoring station ofPadua (Italy). Because technical checks of thesampler were not able to explain this trend,the results obtained from two twinpollen-samplers (Lanzoni VPPS 2000), placed twometres apart, were compared.An eight-week sampling was carried out duringthe year 2000 from July to September.Subsequent analysis revealed no statisticallysignificant difference between the dataobtained with the two instruments. On the otherhand, both samplers captured high levels offungal spores. We conclude that the observednegative trend in pollen count is real and notrelated to technical biases.     

城市生态系统空气微生物群落研究进展

空气微生物是城市生态系统重要的生物组成部分 ,空气中广泛分布的细菌、真菌孢子、放线菌和病毒等生物粒子不仅具有极其重要的生态功能 ,还与城市空气污染 ,城市环境质量和人体健康密切相关。从生态系统角度出发 ,着重论述了城市微生物气溶胶的粒谱范围、空气微生物的主要类型、空气微生物浓度的时空变化和空气微生物群落结构的影响因素。综述结果表明 :城市微生物气溶胶的粒谱范围为 0 .0 0 2～ 30 μm;在调查的城市中 ,空气细菌有 2 1属 ,其中优势菌属为芽孢杆菌属 (Bacillus)、葡萄球菌属 (Staphylococcus)、微球菌属 (Micrococcus)和微杆菌属 (Microbacterium ) ,真菌有 2 1属 ,其中优势菌属为交链孢属(Alternaria)、青霉属 (Penicillium)、曲霉属 (Aspergillus)和木霉属 (Trichoderma) ,放线菌共有 7属 ;一年中冬季空气微生物浓度最低 ,一天中空气微生物浓度在 8:0 0～ 10 :0 0出现高峰 ,2 :0 0～ 4 :0 0或者 12 :0 0～ 14 :0 0出现低峰 ,交通干线和商业区空气微生物的浓度较高 ,公园绿地较低 ,并且随着高度的增加空气微生物浓度随之减少 ;污染因子 SO2 、NO2 、NO和环境因素风速风向、温度、相对湿度、光照、雨、雪等影响空气微生物的数量和浓度。在经济发达 ,人口流动较多的城市如北京、上海、广     

Airborne Laser Scanning as a Tool for Lowland Floodplain Vegetation Monitoring

Monitoring of three-dimensional floodplain vegetation structure is essential for ecological studies, as well as for hydrodynamic modelling of rivers. Height and density of submerged vegetation and density of emergent vegetation are the key characteristics from which roughness parameters in hydraulic models are derived. Airborne laser scanning is a technique with broad applications in vegetation structure mapping, which therefore may be a promising tool in monitoring floodplain vegetation for river management applications. This paper first provides an introduction to the laser scanning technique, and reviews previous studies on the extraction of vegetation height and density of forests, low vegetation and meadows or unvegetated areas. Reliable predictions using laser scan data have been reported for forest height (R²=0.64–0.98), parameters related to forest density, such as stem number, stem diameter, biomass, timber volume or basal area (R²=0.42–0.93), and herbaceous vegetation height (summer condition; R²=0.75–0.89). No empirical relations have been reported on density of herbaceous vegetation. Laser data of meadows and unvegetated areas show too much noise to predict vegetation structure correctly. In a case study for the lower Rhine river, the potential of laser scan mapping of vegetation structure was further explored for winter conditions. Three laser-derived metrics that are often reported in the literature have been applied to characterize local vertical distributions of laser reflections. The laser data clearly show the large structural differences both between and within vegetation units that currently are the basis of floodplain vegetation and roughness mapping. The results indicate that airborne laser scanning is a promising technique for extraction of 3D-structure of floodplain vegetation in winter, except for meadows and unvegetated areas.     

遥感在生物多样性研究中的应用进展

随着人口的持续增长, 人类经济活动对自然资源的利用强度不断升级以及全球气候变暖, 全球物种正以前所未有的速度丧失, 生物多样性成为了全球关注的热点问题。传统生物多样性研究以地面调查方法为主, 重点关注物种或样地水平, 但无法满足景观尺度、区域尺度以及全球尺度的生物多样性保护和评估需求。遥感作为获取生物多样性信息的另一种手段, 近年来在生物多样性领域发展迅速, 其覆盖广、序列性以及可重复性等特点使之在大尺度生物多样性监测和制图以及评估方面具有极大优势。本文主要通过文献收集整理, 从观测手段、研究尺度、观测对象和生物多样性关注点等方面综述了遥感在生物多样性研究中的应用现状, 重点分析不同遥感平台的技术优势和局限性, 并探讨了未来遥感在生物多样性研究的应用趋势。遥感平台按观测高度可分为近地面遥感、航空遥感和卫星遥感, 能够获取样地-景观-区域-洲际-全球尺度的生物多样性信息。星载平台在生物多样性研究中应用最多, 航空遥感的应用研究偏少主要受飞行成本限制。近地面遥感作为一个新兴平台, 能够直接观测到物种的个体, 获取生物多样性关注的物种和种群信息, 是未来遥感在生物多样性应用中的发展方向。虽然遥感技术在生物多样性研究中的应用存在一定的局限性, 未来随着传感器发展和多源数据融合技术的完善, 遥感能更好地从多个尺度、全方位地服务于生物多样性保护和评估。     

Canopy closure estimation in a temperate forest using airborne LiDAR and LANDSAT ETM+ data

Aims　Forest canopy closure is one of the essential factors in forest survey, and plays an important role in forest ecosystem management. It is of great significance to study how to apply LiDAR (light detection and ranging) data efficiently in remote sensing estimation of forest canopy closure. LiDAR can be used to obtain data fast and accurately and therefore be used as training and validation data to estimate forest canopy closure in large spatial scale. It can compensate for the insufficiency (e.g. labor-intensive, time-consuming) of conventional ground survey, and provide foundations to forest inventory.Methods　In this study, we estimated canopy closure of a temperate forest in Genhe forest of Da Hinggan Ling area, Nei Mongol, China, using LiDAR and LANDSAT ETM+ data. Firstly, we calculated the canopy closure from ALS (Airborne Laser Scanning) high density point cloud data. Then, the estimated canopy closure from ALS data was used as training and validation data to modeling and inversion from eight vegetation indices computed from LANDSAT ETM+ data. Three approaches, multi-variable stepwise regression (MSR), random forest (RF) and Cubist, were developed and tested to estimate canopy closure from these vegetation indices, respectively.Important findings The validation results showed that the Cubist model yielded the highest accuracy compared to the other two models (determination coefficient (R²) = 0.722, root mean square error (RMSE) = 0.126, relative root mean square error (rRMSE) = 0.209, estimation accuracy (EA) = 79.883%). The combination of LiDAR data and LANDSAT ETM+ showed great potential to accurately estimate the canopy closure of the temperate forest. However, the model prediction capability needs to be further improved in order to be applied in larger spatial scale. More independent variables from other remotely sensed datasets, e.g. topographic data, texture information from high-resolution imagery, should be added into the model. These variables can help to reduce the influence of optical image, vegetation indices, terrain and shadow and so on. Moreover, the accuracy of the LiDAR-derived canopy closure needs to be further validated in future studies.