一种新型旋风气幕式排风罩数值模拟研究

利用Fluent计算流体力学软件对新型旋风气幕式排风罩工作流场及有害物分布进行了数值模拟,并与传统排风罩进行了对比。结果表明:旋转射流屏蔽作用下的抽吸流场具有中部压力较低和提高抽吸能力的作用;新型旋风气幕式排风罩不仅能有效地控制有害物扩散,而且可以实现远距离捕集有害物及以较小的排风速度排放有害物。     

长江口水体中PAHs的基本生态风险特征

通过对2007年4月24—30日采集于长江口水体7个不同采样点18个水样中的4种典型多环芳烃类化合物(PAHs)的浓度分析,依据3个基础营养级水平(藻、、鱼)的毒性效应〔L(E)C50和NOEC〕,采用欧盟适用于现有化学物质与新化学物质的风险评价技术指南(TGD)中的商值法对长江口水体中的萘、菲、蒽、荧蒽进行了生态风险评价. 结果表明,4种PAHs除蒽外的环境浓度/无影响浓度(PEC/PNEC)都小于1. 说明长江口水体中4种PAHs只有蒽存在一定生态风险,其他3种均未对长江口生态造成威胁.      

Impact of wildflower strips on biological control of cabbage lepidopterans

In a 2-year experiment we investigated whether wildflower strips can be used to enhance the control of cabbage moth, Mamestra brassicae L., and cabbage white butterfly, Pieris rapae L. At two sites, including six organically cultivated fields, M. brassicae egg parasitism and predation rates were determined along with an assessment of larval parasitism rates in M. brassicae and P. rapae using a DNA-based approach. Within each field, plots with and without wildflower strips were sampled and a grid design of 3 m × 3 m was used to analyze the spatial pattern of parasitism. The provision of wildflower strips provided an idiosyncratic effect on the control of lepidopterans: parasitism rates in M. brassicae eggs and larvae were not affected, whereas parasitism rates of larval P. rapae were significantly enhanced by the wildflower strips at one of the two sites. Moreover, at one site predation rates on M. brassicae eggs were significantly enhanced in the wildflower strip plots. Geostatistical analysis showed no distinct spatial patterns in parasitism rates. These results demonstrate that the provision of wildflower strips does not necessarily enhance biological control of lepidopteran cabbage pests and suggest that site-specific environmental factors strongly affect the impact of wildflower strips.     

矿山强酸性多金属污染土壤修复及麻疯树植物复垦条件研究

采用温室盆栽实验,研究了在不同剂量(质量分数分别为0、0.10%、0.25%、0.5%和1.0%)石灰石改良条件下,大宝山矿强酸性多金属不同污染程度土壤中麻疯树的生长状况和吸收金属特征,并探讨了麻疯树在酸性土壤中生长的抑制因素和石灰石改良适宜剂量.研究表明,在低污染酸性土壤中,Cu和Pb的高活性可能是抑制麻疯树生长的主要因素;而在高污染酸性土壤中,Cd、Cu、Zn等金属的高活性及由强酸引起的Al毒也可能是抑制麻疯树生长的主要因素;石灰石通过提高土壤pH值和降低多金属的生物有效态含量,促进了麻疯树在低污和高污土壤中的生长,其最佳剂量分别为0.25%和0.5%;石灰石可以不同程度地降低麻疯树地上部和地下舔的Cd、Cu、Pb、Zn和Al含量,同时随石灰石用量的增加,其金属含量基本呈降低趋势;麻疯树地下部金属含量高于地上部,且石灰石对麻疯树地下部金属(除Cd外)含量降低幅度较地上部大.因此,种植麻疯树与石灰石改良是联合修复大宝山矿酸性多金属污染土壤的有效措施之一.     

水解酸化-SBR-BAF工艺处理中药废水

分析现有中药废水处理工艺及废水特点,并考虑到废水处理技术改造的要求,采用水解酸化-SBR-BAF法联合处理该中药废水,研究了SBR反应器的曝气时间、温度及原水pH值对系统处理效果的影响。系统进水ρ(COD)为1 249.4~1 444.5 mg/L、ρ(BOD5)为201.2~292.8 mg/L、ρ(SS)为208.7~310.6 mg/L、色度为70~100倍,曝气时间为14 h、温度为20℃、pH值为7时,出水ρ(COD)为123.4~140.8 mg/L、ρ(BOD5)为19.4~26.1 mg/L、ρ(SS)为32.7~60.4 mg/L、色度为36~50倍,COD、BOD5、SS的平均去除率分别达到90.3%、90.7%、81.8%,表明HAT-SBR-BAF法处理该中药废水是可行的。     

Modelling plant species richness using functional groups

Conservation biologists increasingly rely on spatial predictive models of biodiversity to support decision-making. Therefore, highly accurate and ecologically meaningful models are required at relatively broad spatial scales. While statistical techniques have been optimized to improve model accuracy, less focus has been given to the question: How does the autecology of a single species affect model quality? We compare a direct modelling approach versus a cumulative modelling approach for predicting plant species richness, where the latter gives more weight to the ecology of functional species groups. In the direct modelling approach, species richness is predicted by a single model calibrated for all species. In the cumulative modelling approach, the species were partitioned into functional groups, with each group calibrated separately and species richness of each group was cumulated to predict total species richness. We hypothesized that model accuracy depends on the ecology of individual species and that the cumulative modelling approach would predict species richness more accurately. The predictors explained plant species richness by ca. 25%. However, depending on the functional group the deviance explained varied from 3 to 67%. While both modelling approaches performed equally well, the models of the different functional groups highly varied in their quality and their spatial richness pattern. This variability helps to improve our understanding on how plant functional groups respond to ecological gradients.     

Distribution patterns of plants explained by human movement behaviour

Distribution patterns of plants are affected by human activities such as creation, destruction or modification of habitats. However, another important question is to what extent humans shape plant distributions by acting as dispersal vectors. In order to answer this question we developed a simulation model for the spread of plant species between human settlements. This was done on the basis of extensive sociological and ecological data on a regional scale. With regard to the sociological data, human movement behaviour defined the amount of exchange between the settlements. Gardening types represented the potential habitat in our model. The ecological data was derived from a vegetation survey carried out in 2003, which was a repeat of a survey between 1974 and 1981 along the same transects. From these surveys, we studied the distributions of 13 species in 67 settlements. In our model, the earlier survey provided the data for the initial distribution. The simulated pattern was consequently compared with the distribution pattern in 2003. In the model, dispersal kernels based on patterns of human movement between settlements led to a better match with the distribution patterns than a null model simulating pure distance dependent dispersal for all species. This was statistically significant for seven of the thirteen species. A striking result was that alien species seem to benefit more from human dispersal than native species. We emphasize the importance of the sociological data on human movement behaviour in parameterizing our regional scale model. This study provides quantitative evidence on the impact of human movement behaviour on the distribution of plant species in suburban areas.     

Modelling with uncertainty: Introducing a probabilistic framework to predict animal population dynamics

Predictive population models designed to assist managers and policy makers require an explicit treatment of inherent uncertainty and variability. These are particular concerns when modelling non-native and reintroduced species, when data have been collected within one geographical or ecological context but predictions are required for another, or when extending models to predict the consequences of environmental change (e.g., climate or land-use). We present an aspatial, probabilistic framework of hierarchical process models for predicting population growth even when data are sparse or of poor quality. Insight into the factors affecting population dynamics in real landscapes can be provided and Kullback–Leibler distances are used to compare the relative output of models. This flexible yet robust framework gives easily interpretable results, allowing managers as well as modellers to invalidate anomalous models and apply others to real-life scenarios.We illustrate the framework’s power with a meta-analysis of European wild boar (Sus scrofa) data. We test hypotheses about the effect of geographic region, hunting and mast years on wild boar population growth, to build models of wild boar dynamics for the UK. The framework quantifies the importance of hunting pressure as a driver of population growth, and confirms that reproductive success is greatly decreased in poor mast years, suggesting that the key to predicting wild boar dynamics is to ascertain local hunting pressure and to better understand changing food availability. Geography had no significant effect, indicating that it is not a good proxy for modelling the impact of change in climate or land-use on wild boar populations at the European scale. We use the framework to predict population abundance 9 years after an isolated population of wild boar established in the UK; in a comparison with the only field data and two independent modelling exercises, our framework provides the most robust and informative results.     

Invasion versus Isolation: Trade-Offs in Managing Native Salmonids with Barriers to Upstream Movement

Abstract: Conservation biologists often face the trade‐off that increasing connectivity in fragmented landscapes to reduce extinction risk of native species can foster invasion by non‐native species that enter via the corridors created, which can then increase extinction risk. This dilemma is acute for stream fishes, especially native salmonids, because their populations are frequently relegated to fragments of headwater habitat threatened by invasion from downstream by 3 cosmopolitan non‐native salmonids. Managers often block these upstream invasions with movement barriers, but isolation of native salmonids in small headwater streams can increase the threat of local extinction. We propose a conceptual framework to address this worldwide problem that focuses on 4 main questions. First, are populations of conservation value present (considering evolutionary legacies, ecological functions, and socioeconomic benefits as distinct values)? Second, are populations vulnerable to invasion and displacement by non‐native salmonids? Third, would these populations be threatened with local extinction if isolated with barriers? And, fourth, how should management be prioritized among multiple populations? We also developed a conceptual model of the joint trade‐off of invasion and isolation threats that considers the opportunities for managers to make strategic decisions. We illustrated use of this framework in an analysis of the invasion‐isolation trade‐off for native cutthroat trout (Oncorhynchus clarkii) in 2 contrasting basins in western North America where invasion and isolation are either present and strong or farther away and apparently weak. These cases demonstrate that decisions to install or remove barriers to conserve native salmonids are often complex and depend on conservation values, environmental context (which influences the threat of invasion and isolation), and additional socioeconomic factors. Explicit analysis with tools such as those we propose can help managers make sound decisions in such complex circumstances.