Species diversity variation of Cupressus funebris secondary forest in landslide site after 5.12 Wenchuan Earthquake北大核心CSCD

The characteristics of species diversity in Cupressus funebris secondary forest under the effect of geological hazard were explored by selecting the typical landslide surface of Fenghuang Mountain, Leigu Town, Beichuan County, which was derived from the 5.12 Wenchuan earthquake. The results showed that 93 species belonged to 42 families, and 78 genera were found in the landslide area, where the main families were Compositae, Leguminosae, and Gramineae-based. Further, 97 species in the transition area belonged to 39 families and 80 genera, and the main families were Compositae, Gramineae, and Rosaceae-based. In all, 108 species were recorded in the non-landslide area, which belonged to 59 families and 92 genera, the main families of which were Compositae, Rosaceae, and Gramineae-based. Compositae and Gramineae played important roles in the landslide recovery process after earthquake. The Pielou index (JSW) was the highest in the non-landslide area of the herb layer, whereas the richness index (D) was the lowest; the Shannon-Wiener index (H) and Simpson index (H') showed medium values. In the non-landslide area, the D, H, and H' were the highest in the shrub layer, whereas the JSW was the lowest. Further, the species diversity index of the transitional area was higher than that of the landslide area. In the tree layer, the D and H were both the highest and lowest in the landslide area and transition area, respectively. In contrast, the H' and JSW were the highest in the transition area and the lowest in the non-landslide area. The distribution of vegetation was generally consistent with the distribution of soil nutrients in the spatial distribution of surface soil nutrients. The succession of trees in the landslide area was relatively slow and at the initial stage, and the pioneer species were Coriaria nepalensis, Leptopus chinensis, and Arthraxon lanceolatus in this area. Taken together, the findings suggested that the stability of a plant community can be increased by improving the soil and stabilizing the slope. © 2018 Science Press. All rights reserved.     

水文变异条件下潦河生态流量计算研究

气候变化和高强度人类活动改变了流域的自然水文循环过程,导致水文序列出现变异,严重影响了流域水文生态系统的稳定性.目前,基于水文变异条件下的河道内生态流量计算已成为当前变化环境下生态水文学研究的热点问题之一.以江西鄱阳湖西北部的潦河为例,采用水文时间序列变异检验方法分析径流变异性及成因,应用水文模型对水文变异后的径流进行还原,以Kolmogorov-Smirnov（K-S）、Anderson Darling（A-D）和概率点据相关系数（PPCC）3种检验法确定月径流的最优概率分布函数,进而提出水文变异条件下最适宜的潦河生态流量计算方法.结果表明:①潦河万家埠站径流在1972年发生水文变异,突变点后流域年径流增加了12%,降水量的增加和蒸发量的减少是其主要驱动要素.②采用分布式时变增益模型（DTVGM）对径流进行还原,率定期和验证期的相关系数和Nash-Sutchliffe效率系数均大于0.78,径流模拟值和实测值拟合程度较高,表明基于DTVGM进行径流还原是可行的.③基于还原后的径流,对5种概率分布函数进行拟合优度综合检验,确定逐月最优分布函数,并估算月河道生态流量.与Tennant法、最枯月平均流量法、7Q10法等方法比较,基于最优分布函数的生态流量结果更具确定性与合理性.在气候变化和人类活动引起径流变异的背景下,考虑水文变异的河道内生态需水计算方法能够更科学地体现水文变异对生态需水过程的影响,研究结果可为潦河流域水生态保护和水资源管理提供数据支撑,也可为变化环境下水资源规划和配置提供科学依据.      

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.     

铜陵新桥矿区土壤中耐Cu微生物的筛选研究

选择安徽铜陵新桥矿区富Cu的污染土壤,充分利用微生物受自然环境重金属胁迫而产生耐性这一特点,进行土壤中耐Cu微生物的筛选研究。实验过程中分别配制三种不同的培养基,细菌、真菌和放线菌培养基。在水浴恒温振荡器中对土壤中耐受重金属的微生物进行驯化,将得到的对Cu2+耐受性最高的液体培养基作为菌源,在琼脂平板培养基上进行划线分离,并将得到的纯菌株在光学显微镜下进行形态观察,菌种经试管斜面富集培养后保存在4℃冰箱中以便后续使用。研究发现,土样中细菌和真菌对Cu的耐受性低,最高耐受质量浓度分别只达到500mg·L-1和1100mg·L-1。而放线菌表现出Cu高耐受性,分离得到的放线菌耐受Cu的质量浓度最高达到10000mg·L-1,初步鉴定该放线菌株为链霉菌属。该放线菌菌种可能同时对Cu有吸附降解特性,具有成为污染土壤生物治理的高效耐受吸附菌种的潜力巨大。     

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.     

地震应急避难需求的系统动力学研究

为定量研究地震应急避难人群的规模及变化规律,建立需求分析的系统动力学模型。该模型包括建筑物倒塌,断水和电梯停运3种因素造成的需求。参考汶川地震中板房建设速度和电梯修复速度,以及日本关于地震断水率的研究成果,建立非线性模型拟合各需求的变化规律。采用Vensim软件建立系统动力学模型,分析各需求的综合变化规律。采用上海市徐汇区的数据进行案例演算,并与其他研究方法对比分析仿真误差。仿真结果表明:建筑物损坏对人群数量的影响很大,但是灾后1个月内断水的影响最大;相对于工程技术因素,人因对需求有重要的影响。