北京及周边地区典型站点近地面O3的变化特征

利用2008年6月1日~2009年5月31日在北京城区中国气象局(CMA),及其西南方向固城站(GCH)和东北方向上甸子本底站(SDZ)的近地面O3等观测数据,分析了O3的变化特征及其与其他污染物和气象要素的关系.结果表明,上甸子本底站近地面O3的季节变化和日变化规律与固城和北京城区站存在一定的差异,而固城站和北京城区站的O3变化特征差异较小.相关性分析显示,O3与NO、NO2、NOx、RH多呈负相关,且相关性冬季好于夏季,此外,O3与气温和风速呈正相关,其中北京城区站冬季和夏季O3与风速的相关性差异最明显.O3浓度与地面风向有一定关系,当风向为偏南时,O3浓度较高,当风向为东北时,O3浓度偏低.     

辽宁省背景地区降水化学特征及其与大气传输的关系

为了解辽宁省背景地区降水化学特征及其与大气传输的关系,于2007年2月─2008年1月在辽中县水文监测站进行了降水化学特征观测,测量项目包括降水pH,电导率和离子浓度. 观测期间降水pH为3.4～7.3,降水量加权平均值为4.6,整体呈酸性. 降水中主要阴离子为SO₄2-和NO₃-,浓度分别为154.3和53.4 μeq/L,二者占阴离子总量的76.8%; 主要阳离子为NH₄+和Ca2+,浓度分别为124.6和89.2 μeq/L,占阳离子总量的70.6%. 利用后向气流轨迹分析了降水气团来源对降水化学的影响,结果表明:在辽宁省及周边地区的局地气团影响下,降水中离子浓度最高;而在起源于东亚地区,经朝鲜半岛到达的南-东南气团影响下,降水次数虽最多,但离子浓度最低.      

Deriving state-and-transition models from an image series of grassland pattern dynamics

We present how state-and-transition models (STMs) may be derived from image data, providing a graphical means of understanding how ecological dynamics are driven by complex interactions among ecosystem events. A temporal sequence of imagery of fine scale vegetation patterning was acquired from close range photogrammetry (CRP) of 1 m quadrats, in a long term monitoring project of Themeda triandra (Forsskal) grasslands in north western Australia. A principal components scaling of image metrics calculated on the imagery defined the state space of the STM, and thereby characterised the different patterns found in the imagery. Using the state space, we were able to relate key events (i.e. fire and rainfall) to both the image data and aboveground biomass, and identified distinct ecological ‘phases’ and ‘transitions’ of the system. The methodology objectively constructs a STM from imagery and, in principle, may be applied to any temporal sequence of imagery captured in any event-driven system. Our approach, by integrating image data, addresses the labour constraint limiting the extensive use of STMs in managing vegetation change in arid and semiarid rangelands.     

Modeling the population dynamics of cotton bollworm Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) over a wide area in northern China

The cotton bollworm Helicoverpa armigera (Lepidoptera: Noctuidae) is one of the most serious crop pests in northern China, calling for accurate prediction of pest outbreaks and strategies for pest control. A computer model is developed to simulate the population dynamics of H. armigera over a wide area in northern China. The area considered covers 12 provinces where serious outbreaks of H. armigera have been observed. In this model, pest development is driven by local ambient temperature, and adults migrate long distances between regions and select preferred hosts for oviposition within a region. Six types of host including cotton, wheat, corn, peanut, soybean and a single category composed of all other minor hosts are considered in this model. Survival rates of eggs and larvae are based on life-table data, and simulated as a function of host type, host phenology and temperature. The incidence of diapause depends on temperature and photoperiod experienced during the larval stage. Survival rate of non-diapause pupae is a nonlinear function of rainfall, and overwinter survival rate is a nonlinear function of temperature. Insecticide is applied when population density exceeds the economic threshold on a host crop within a region. Comparisons of model output with light-trap data indicate that our model reflects the pest population dynamics over a wide area, and could potentially be used for testing novel pest control strategies in northern China.     

Enhancing generic ecological model for short-term prediction of Southern North Sea algal dynamics with remote sensing images

Physically based numerical modelling follows from the basic understanding of the underlying mechanisms and is often represented by a set of (partial differential) equations. It is one of the main approaches in population dynamics modelling. The emphasis of the model introduced in this paper is on the simulation of short-term spatial and temporal dynamics of harmful algal bloom (HAB) events. Total suspended matter (TSM) concentration is one of the dominant factors for harmful algal bloom (HAB) prediction in North Sea. However, the modelling of suspended matter contains a high degree of uncertainty in this area. Therefore, this research aims to achieve a better estimation for the short-term prediction of harmful algal bloom development in both space and time by using spatially distributed TSM retrieved from remotely sensed images as physically based model inputs. In order to supply complete spatially covered datasets for the physically based model instrument: generic ecological model (GEM), this research retrieves TSM information from MERIS images by means of proper estimation techniques including biharmonic splines and self-learning cellular automata. A better estimation of HAB spatial pattern development is achieved by adding spatially distributed TSM data as inputs to original GEM model, and it proved that chlorophyll-a concentration in this area is very sensitive to TSM concentration.     

Influence of low and decreasing food levels on Daphnia-algal interactions: Numerical experiments with a new dynamic energy budget model

Based on numerical experiments with a new physiologically structured population model we demonstrate that predator physiology under low food and under starving conditions can have substantial implications for population dynamics in predator-prey interactions. We focused on Daphnia-algae interactions as model system and developed a new dynamic energy budget (DEB) model for individual daphnids. This model integrates the κ-rule approach common to net assimilation models into a net-production model, but uses a fixed allocation of net-productive energy in juveniles. The new DEB-model agrees well with the results of life history experiments with Daphnia. Compared to a pure κ-rule model the new allocation scheme leads to significant earlier maturation at low food levels and thus is in better agreement with the data. Incorporation of the new DEB-model into a physiologically structured population model using a box-car elevator technique revealed that the dynamics of Daphnia-algae interactions are highly sensitive to the assumptions on the energy allocation of juveniles under low food conditions. Additionally we show that also other energy allocation rules of our DEB-model concerning decreasing food levels and starving conditions at the individual level have strong implications for Daphnia-algae interactions at the population level. With increasing carrying capacity of algae a stable equilibrium with coexistence of Daphnia occurs and algae shifts to limit cycles. The amplitudes of the limit cycles increase with increasing percentage of sustainable weight loss. If a κ-rule energy allocation is applied to juveniles, the stable equilibrium occurs for a much narrower range of algal carrying capacities, the algal concentration at equilibrium is about 2 times larger, and the range of algae carrying capacities at which daphnids become extinct extends to higher carrying capacities than in the new DEB-model. Because predator-prey dynamics are very sensitive to predator physiology under low food and starving conditions, empirical constraints of predator physiology under these conditions are essential when comparing model results with observations in laboratory experiments or in the field.     

Analysis of the global warming dynamics from temperature time series

Global warming is the observed increase of the average temperature of the Earth. The primary cause of this phenomenon is the release of the greenhouse gases by burning of fossil fuels, land cleaning, agriculture, among others, leading to the increase of the so-called greenhouse effect. An approach to deal with this important problem is the time series analysis. In this regard, different techniques can be applied to evaluate the global warming dynamics. This kind of analysis allows one to make better predictions increasing our comprehension of the phenomenon. This article applies nonlinear tools to analyze temperature time series establishing state space reconstruction and prediction. Since noise contamination is unavoidable in data acquisition, it is important to employ robust techniques. The method of delay coordinates is employed for state space reconstruction and delay parameters are evaluated using the method of average mutual information and the method of false nearest neighbors. Afterwards, the simple nonlinear prediction method is employed to estimate temperatures of the future. Temperature time series from different places of the planet are used. Initially, the approach is verified considering known parts of the time series and afterwards, results are extrapolated for future values estimating temperature until 2028. Results show that these techniques are interesting to estimate temperature time history, presenting coherent estimations.     

贵州喀斯特地区不同土地利用方式土壤CO_2体积分数变化及影响因素

为了解不同土地利用方式对土壤剖面CO2体积分数的影响,采用气相色谱法对贵州喀斯特地区土壤不同深度空气CO2体积分数进行观测。结果表明：不同土地利用对土壤平均CO2体积分数影响较大,其次序为：次生林（0.35%±0.06%）〉草地（0.34%±0.05%）〉人工林（0.27%±0.03%）〉农田（0.16%±0.03%）。次生林、草地与农田之间土壤CO2体积分数差异性显著,而人工林与农田之间无显著性差异。不同土地利用方式土壤剖面CO2体积分数的时空变化特征比较一致：从春季到夏季逐渐增加而从秋季到冬季又逐渐降低,与该区域的温度和降雨量变化趋势一致。同时随着土壤剖面深度增加CO2体积分数逐渐增大,但在土层12 cm处有突然降低现象（农田除外）。不同土地利用方式土壤空气CO2体积分数变化与大气、土壤温度密切相关（r=0.602~0.886,P〈0.05）,土壤温度升高会导致土壤CO2体积分数上升。土壤湿度虽然也在一定程度上影响了剖面CO2体积分数,但相关性分析表明二者之间并不显著（r=0.105~0.393,P〉0.05）,说明在贵州喀斯特地区,土壤温度对土壤空气CO2体积分数的影响大于土壤湿度。     

深圳湾浮游植物的季节变化

2008年2月至11月对深圳湾的浮游植物和理化环境因子进行了4个季度月的调查,结果共检出浮游植物150种（包括变种和变型）：春季66种、夏季72种、秋季54种、冬季50种,其中硅藻门36属108种,甲藻门14属36种,绿藻门3属3种,蓝藻门2属3种。优势种共有湖沼圆筛藻Coscinodiscus lacustris、中肋骨条藻Skeletonema costatum、夜光藻Noctiluca scientillans 3种：春季1种、夏季1种、秋季1种、冬季2种,优势种群由春夏季的湖沼圆筛藻演替至秋季的中肋骨条藻、冬季的中肋骨条藻和夜光藻,没有全年广布优势种;4季均出现的种类共有9种,其中硅藻8种,甲藻1种,各季节间共有种类数在13～31种,Jaccard种类相似性指数范围在0.12~0.35,季节更替明显。多样性指数和均匀度的变化范围分别为0.006~1.724和0.001~0.306,群落结构较脆弱。细胞密度在1.25×107~217.90×107 cells.m-3,夏季最高,春季次之,冬季最低,属季节单峰型变化,与一般亚热带春、秋季出现密度高峰不一致,这与深圳湾陆源营养物质的扰动有关,其无机氮和活性磷酸盐含量均劣于国家海水水质标准的四类水,因此,该海域水质营养类型属于亚热带富营养型。细胞密度与硅酸盐呈极显著的负相关,相关系数为-0.446（p〈0.01,n=36,双尾）,与水温呈显著的正相关,相关系数为0.371（p〈0.05,n=36,双尾）,与其他因子的相关性不明显。从优势种的种类数和多样性指数分析,深圳湾浮游植物的群落结构已趋于单一化,生态系统抗干扰能力极为脆弱。     

An Observation Method for Analyzing Operators’ Routine Activity in Computerized Control Rooms

An activity analysis method was developed for studying the structure and dynamics of control room operators’ activity during normal operation based on directly observable elements of the operators’ behavior. The method assesses current activity along three dimensions in each 5-min period of the shift. Intensity characterizes arousal level, direction shows whether the activity is directed predominantly at the process control task, at something else, or miscellaneous. Motivation reflects if the activity is driven by intrinsic or extrinsic motivation. A case study is presented, in which 3 morning, 3 afternoon, and 3 night shifts of a Nuclear Power Plant operator crew are involved. The obtained results gave a deeper understanding of the operators’ activity and also revealed an “arousal compensation” tendency.