不同返青休牧期土壤微生物碳代谢特征及其影响因素研究

返青期休牧可以有效保护草地生态环境,研究不同休牧期可对休牧措施进行可行性分析,尤其是在三江源区高寒草甸生态系统。土壤微生物碳代谢功能对不同返青休牧期的响应及其与土壤和微生物的作用机制研究,可为评估休牧措施及草地土壤环境提供科学依据。在返青期设置了放牧(CK)和4个休牧期(20、30、40、50 d)共5个试验处理,采用Biolog-Eco微平板的方法分析了不同返青休牧期下土壤碳代谢的变化,同时测定了土壤性质和土壤微生物生物量碳氮等指标。结果表明:不同返青期休牧下土壤微生物利用碳源能力有CK30 d40 d50 d20 d的趋势,但差异不显著。对不同种类碳源的利用能力依次为羧酸类氨基酸类糖类酯类醇类胺类,且不同返青期休牧处理下微生物对醇类的代谢差异显著(P=0.028),休牧20 d显著高于40 d和50 d。培养第1天在休牧20 d处理下Simpson(D)、Shannon(H)、McIntosh指数(U)都较其他处理高。培养第11天CK处理下,碳代谢功能多样性较高。土壤理化性质及微生物生物量碳氮解释了微生物群落碳代谢的91.1%的变异,其中土壤有机碳解释了8%的变异,且显著影响微生物群落碳代谢(P=0.038)。在试验初期,不同休牧期土壤碳代谢特征差异不显著,且放牧措施有提高碳源利用活性,仅醇类代谢差异显著。土壤有机碳是显著影响微生物群落碳代谢的因素。     

鄱阳湖枯水期CDOM光吸收特性与DOC浓度的定量关系研究

研究了2015年枯水期鄱阳湖水体(包括河口区、鄱阳湖主湖开阔区)有色可溶性有机物(CDOM)的光吸收特性,并讨论了CDOM光吸收特性与溶解性有机碳(DOC)浓度之间的关系。结果表明,整个鄱阳湖水体中CDOM在254、280、350和440 nm波长处的吸收系数分别为7.86~20.24、5.64~14.58、1.46~4.41和0.36~1.06 m-1;表征CDOM相对分子质量大小的M值(CDOM在波长250和365 nm处吸收系数比值)变化范围为5.27~7.66。枯水期湿地对鄱阳湖水体CDOM的影响较大,而5大入湖河流贡献不大。在各项参数中,光谱斜率比值(SR)更能体现枯水期鄱阳湖水体CDOM光吸收特征。枯水期鄱阳湖水体ρ(DOC)在1.61~4.86 mg·L~(-1)之间变化,其平均值为2.31 mg·L~(-1)。枯水期鄱阳湖水体CDOM光吸收系数(a254,x)与DOC浓度(y)呈显著正相关,回归方程为y=-0.53+0.27x(调整决定系数R2=0.76,P0.01),2016年1月的实测值验证显示利用枯水期鄱阳湖水体CDOM光吸收特性研究DOC浓度具有可行性。这意味着研究枯水期鄱阳湖水体CDOM光吸收特性对研究碳库具有指示作用。     

大气致污指数与总悬浮微粒重量浓度相关性的研究

本文采用一种简易的方法,测定了大气的烟雾系数(COH)。根据测定结果,研究了杭州市流动大气中总悬浮微粒(TSP)的重量浓度与COH之间的相关关系,求得相关系数为0.955,直线回归方程式为:y=20.50x+1.65。对COH测定误差所作的分析,其相对标准偏差小于10.9％。     

北京地区不同植被类型空气负离子浓度及其影响因素分析

为研究城市内常见植被的空气负离子浓度水平及其影响因素,选取了北京市内几种常见的植被类型,以无植被覆盖的开阔地为参照对象,采用曲线图、散点图、回归分析等手段研究了不同植被类型的空气负离子浓度差异,并分析了外部环境对空气负离子浓度的影响。结果表明,(1)有林地区空气负离子浓度水平远高于无林地区,北京不同植被类型的空气负离子日平均浓度差异明显,5类样地的日平均空气负离子浓度波动范围在300~1 800 ion·cm-3之间,从高到低排序为:阔叶林针阔叶混交林针叶林灌木林无植被覆盖开阔地,且波动范围也逐渐变小,日平均空气负离子浓度分别达到了1 198、1 069、710、599、516 ion·cm-3。最高值一般出现在早晨或者晚上,最低值一般出现在中午。(2)空气负离子含量受天气变化影响显著,4种天气状况下的空气负离子浓度由高到低依次为:雷雨天晴天阴天雾霾天。(3)空气负离子浓度与温度呈负相关,回归方程为:y=-0.018 9x+40.157(r=-0.848,f=53.782,t=-7.334,P=0.001);与相对湿度呈正相关,回归方程为:y=0.058 0x+16.475(r=0.810,f=40.176,t=6.338,P=0.001)。(4)人类活动对空气负离子浓度影响较大,空气负离子浓度与人流量车流量均呈负相关,空气负离子浓度从中心城区向外逐渐升高,万泉河路、香山路、新平北路3个样地的日平均空气负离子浓度分别为:367、485、548 ion·cm-3。(5)空气负离子浓度室外明显高于室内。(6)空气质量与空气负离子浓度关系显著,空气负离子浓度与空气质量指数、PM2.5浓度均呈负相关。这些结果给城市绿地规划及大气治理提供了一些参考,并对后续进一步的研究做了铺垫。     

Cu2+,Cd2+和Cr(Ⅵ)抑制沼泽红假单胞菌生长的毒性效应

运用标准方法进行有毒化学品对水生生物急性毒性实验 ,得到Cu2 + ,Cd2 + ,Cr(Ⅵ )对光合细菌沼泽红假单胞菌生长抑制作用的 96h剂量反应方程 ,分别为 :y =- 1.72 6 7x +8.70 0 4 ,R2 =0 .96 5 5c(Cu2 + ) ;y =$C1.15 5 1x +8.9996 ,R2 =0 .92 5 2c(Cd2 + ) ;y=$C1.342 7x +10 .785 ,R2 =0 .975 8c〔Cr(Ⅵ )〕 ,由此计算出Cu2 + ,Cd2 + ,Cr(Ⅵ )的 96h -EC50 分别为 2 .172× 10 -6mol/L ,2 .5 6 6× 10 -5mol/L和 3.92 6× 10 -4mol/L .从而得出它们对沼泽红假单胞菌生长毒性作用大小的顺序为Cu2 + >Cd2 + >Cr(Ⅵ ) .表 2参 11     

异味阈值与分子结构特征关系的研究进展

异味阈值和分子结构间的关系,受到阈值准确识别和嗅觉产生机制研究的制约,是一个非常复杂的问题.本文简要介绍了多元线性回归、拓扑指数、神经网络和分子生物学等几种研究异味阈值和分子结构关系的方法,探讨了目前存在的问题以及未来的发展趋势.     

化学农药对生态环境安全评价研究——ⅩⅢ.农药在土壤中的吸附与解吸

本文详述了上壤对农药吸附与解吸的试验方法,并以呋喃丹、甲基对硫磷、γ—666三种农药,以及东北黑土、太湖水稻土、广东红壤等三种类型的土壤进行了农药在土壤中吸附与解吸性能的比较试验。结果表明:影响农药吸附与解吸的主要土壤因素为有机质的含量;以呋喃丹为例,其吸附常数k与土壤有机质含量的关系式为y=0.0205+0.4426x(r=0.9349,p<0.05),利用该方程式可预测呋喃丹在其它土壤中的吸附状况。农药在水体中的溶解度对吸附作用影响很大,其影响程度大于土壤性质的影响因素。     

几种土壤的基本理化性质与Cu2+吸附的关系

研究了大冶市几种类型土壤的基本性质及与Cu2+吸附的关系,结果表明,土壤对Cu2+的吸附量随其CEC值(记为CEC)而变化,供试土壤的Cu2+吸附量由大到小的顺序为石灰土→水稻土→潮土→棕红壤.加入铜浓度为5 mmol·L-1时11个土壤对铜的吸附量x((mol·g-1)与CEC的直线相关方程为x(Cu2+) = 2.018×CEC + 24.4 (r=0.7066).而影响CEC的因素,如Ph、粘粒含量及其组成、有机质、比表面等,也是决定Cu2+吸附量的重要因素.     

有机物对紫外光照下亚硝氮生成的影响

通过静态间歇试验,对紫外光照下水中无机氮的转化进行了研究,重点考察了有机物在反应过程中对亚硝氮生成的促进作用,分类比较了不同有机物的作用效果.结果表明:在紫外光照下,氨氮不能转化为亚硝氮,硝氮可以转化为亚硝氮;有机物的投加可以促进亚硝氮的生成;不同有机物对亚硝氮形成的促进作用大小与有机物的还原性有关,还原性愈强,促进作用愈大;有机物促进作用大小的顺序如下:相同碳链醇>醛>酸>酮、官能团愈多促进作用愈大,相同官能团碳链愈长促进作用愈大.     

华南典型侵蚀区土壤有机碳流失机制模拟研究

土壤侵蚀条件下的碳流失问题是目前全球碳循环研究中的新点,也是土壤侵蚀基础性研究中的弱点。目前对于土壤侵蚀的研究多侧重于侵蚀造成养分流失及土地退化方面,关于土壤侵蚀对碳循环的影响研究较少。针对华南红壤侵蚀区的碳流失问题,采用室内人工模拟降雨的方法,探讨了华南典型侵蚀区两种土壤类型(林地、弃耕荒地)的有机碳流失过程,主要取得以下一些成果,(1)土壤有机碳的流失主要以侵蚀泥沙为载体,两种土壤(林地、弃耕荒地)坡面的泥沙有机碳含量均表现出随降雨历时逐渐减小的趋势,但雨强和坡度对侵蚀泥沙中有机碳含量的影响没有明显规律;林地土壤坡面的侵蚀泥沙中有机碳含量明显高于弃耕荒地土壤坡面的侵蚀泥沙中有机碳含量。(2)林地土壤的泥沙有机碳富集比大于弃耕荒地的泥沙有机碳富集比,林地土壤有机碳富集比变化范围为0.99~1.65,而弃耕荒地土壤有机碳富集比变化范围为0.86~1.07;林地土壤的有机碳流失率大于弃耕荒地的有机碳流失率。林地土壤的有机碳流失率变化范围为1.6%~18.9%,弃耕荒地土壤的为2.2%~10.4%。土壤有机碳流失率随降雨雨强的增加而增大,坡度对土壤有机碳流失率的影响不显著。(3)土壤有机碳流失强度与侵蚀强度呈明显的线性正相关关系,试验条件下(不同地类土壤、雨强、坡度)土壤有机碳流失强度与侵蚀强度间的函数关系可表达为:y(SOC)=5.104x(Erosion)+0.036(r2=0.984)。     

Chaos and pattern formation in a spatial tritrophic food chain

The model of Hastings and Powell describes a tritrophic food chain that exhibits chaotic dynamics. The model assumes that the populations are homogeneously mixed, so that the probability that any two individuals interact is uniform and space can be ignored. In this paper we propose a spatial version of the Hastings and Powell model in which predators seek their preys only in a finite neighborhood of their home location, breaking the mixing hypothesis. Treating both space and time as discrete variables we derive a set of coupled equations that describe the evolution of the populations at each site of the spatial domain. We show that the introduction of local predator–prey interactions result in qualitatively distinct dynamics of predator and prey populations. The evolution equations for the predators involve averages over the local density of preys, whereas the equations for the preys involve double averages, where the local density of both preys and predators appear. Our numerical simulations show that local predation also leads to spontaneous pattern formation and to qualitative changes in the global dynamics of the system. In particular, depending on the size of the predation neighborhoods, the chaotic strange attractor present in the original model of Hastings and Powell can be replaced by a stable fixed point or by an attractor of simpler topology.     

残渣食物链物质和能量的转化利用

本文研究了稻草—平菇—蚯蚓—黄鳝食物链中物质和能量的转化利用。结果表明，该食物链中物质和能量的转化利用率，平茹和黄鳝比蚯蚓高。文中还讨论了残渣食物链的适宜搭配。     

虚拟生态产业链的稳定性研究

以虚拟产业链的稳定性作为研究的着力点,对影响虚拟产业链的稳定性的风险因素进行分析,其中包括市场风险因素、技术成本风险因素、交易风险因素等,针对这些影响因素,并给出风险防范体系,即虚拟产业链的风险防范内生体系和外生体系:内生体系是指在虚拟产业链的本身内部网络中建立的风险防范机制、对策、方法措施等,如检查机制、激励机制、利润/风险分担机制和清算机制,而外生体系是指对虚拟生态产业链的风险起防范作用的法律法规、信用和传媒等社会体系的总和。从而从生态产业链内外部整体资源的协同利用和利益相关者的协同效用两方面来提高虚拟产业链的稳定性。     

三种纳米金颗粒对聚合酶链式反应扩增效率和特异性的影响

比较了采用柠檬酸三钠(Trisodium citrate,Na3Ct)还原法、聚乙烯吡咯烷酮(Polyvinylpyrrolidone,PVP)包裹法和巯基丙酸-同型半胱氨酸(Mercaptopropionic Acid-Homocystine,MPA-HCys)包裹法制备的3种纳米金颗粒(Gold nanoparticles,AuNPs)对聚合酶链式反应(Polymerase Chain Reaction,PCR)扩增效率及特异性的影响,以评估金纳米材料表面性质与DNA生物大分子之间的相互作用.实验结果显示,3种AuNPs均能显著提高PCR效率,它们提高PCR效率的能力依次为:Na3 Ct-AuNPs(12 nm)MPA-HCys-AuNPs(12 nm)PVP-AuNPs(4 nm),而且这种增强效应与其浓度和尺寸相关.相同实验条件下,具有相似尺寸大小的Na3Ct-AuNPs比MPA-HCys-AuNPs更能有效提高PCR效率,这说明AuNPs的表面性质也是影响PCR效率的重要因素之一.另外,3种AuNPs均能有效消除竞争性引物对PCR的抑制作用,并且这种作用与其浓度密切相关.上述研究结果表明,具有不同表面性质的3种AuNPs均能有效提高PCR效率和特异性,并且这种作用与其浓度、尺寸和表面性质密切相关.     

Social network analysis and valid Markov chain Monte Carlo tests of null models

Analyses of animal social networks derived from group-based associations often rely on randomisation methods developed in ecology (Manly, Ecology 76:1109–1115, 1995) and made available to the animal behaviour community through implementation of a pair-wise swapping algorithm by Bejder et al. (Anim Behav 56:719–725, 1998). We report a correctable flaw in this method and point the reader to a wider literature on the subject of null models in the ecology literature. We illustrate the importance of correcting the method using a toy network and use it to make a preliminary analysis of a network of associations among eagle rays.

Embodied energy and emergy evaluation of a typical biodiesel production chain in China

Biodiesel from non-grain feedstock has been considered as one of the proper substitutes for fossil fuels associated with a series of activities emerging in China in order to meet the resource shortage and develop the energy crops. This paper presents an ecological accounting framework based on embodied energy, emergy, and CO₂ emission for the whole production chain of biodiesel made from Jatropha curcas L. (JCL) oil. The energy and materials invested in and CO₂ emission from the whole process, including cropping, transportation, extraction, and production, are accounted and calculated. Also, E_mCO₂, the ratio of real CO₂ released to the emergy-based sustainability indicator per joule biodiesel, is proposed in this paper to present a new goal function for low-carbon system optimization. Finally, the results are compared with those of the bioethanol (wheat) production in Henan Province, China, and bioethanol (corn) production in Italy in view of the indices of embodied energy, emergy and CO₂ emissions and E_mCO₂.     

A single-chain-based multidimensional Markov chain model for subsurface characterization

Multidimensional Markov chain models in geosciences were often built on multiple chains, one in each direction, and assumed these 1-D chains to be independent of each other. Thus, unwanted transitions (i.e., transitions of multiple chains to the same location with unequal states) inevitably occur and have to be excluded in estimating the states at unobserved locations. This consequently may result in unreliable estimates, such as underestimation of small classes (i.e., classes with smaller than average areas) in simulated realizations. This paper presents a single-chain-based multidimensional Markov chain model for estimation (i.e., prediction and conditional stochastic simulation) of spatial distribution of subsurface formations with borehole data. The model assumes that a single Markov chain moves in a lattice space, interacting with its nearest known neighbors through different transition probability rules in different cardinal directions. The conditional probability distribution of the Markov chain at the location to be estimated is formulated in an explicit form by following the Bayes’ Theorem and the conditional independence of sparse data in cardinal directions. Since no unwanted transitions are involved, the model can estimate all classes fairly. Transiogram models (i.e., 1-D continuous Markov transition probability diagrams) are used to provide transition probability input with needed lags to generalize the model. Therefore, conditional simulation can be conducted directly and efficiently. The model provides an alternative for heterogeneity characterization of subsurface formations.

Chemical characteristics of arsenic in a marine food chain

The various chemical forms of ⁷⁴As accumulated from either water or food by the marine food chain [Fucus spiralis (L.) Littorina littoralis (L.)Nucella lapillus] have been separated and characterized. Arsenic components were separated by differential extraction followed by high-voltage paper electrophoresis/paper chromatography of the water-soluble fraction and thin-layer chromatography of the lipid-soluble fraction. The algae assimilates arsenic mainly (60%) as one lipid-soluble compound with R_f=0.18, and 12 water-soluble organo-arsenic compounds as minor components. On the other hand, the snails, whether labelled from water or food, produce predominantly one major water-soluble organo-arsenic compound with R_f=0.66. This water-soluble arsenic compound was produced by the snails and not by intestinal microbes. Time-course studies on the relative proportions of labelled arsenic compounds in algal tissue indicate a transition from arsenate through water-soluble organo-arsenic components to a lipid-soluble arsenic compound. The water-soluble organo-arsenic compounds in the food chain studied were different from those previously found or proposed in marine organisms.     

A combined ecosystem and value chain modeling approach for evaluating societal cost and benefit of fishing

We describe a combined ecological and economic approach aimed at giving more equal emphasis to both disciplines, while being integrated so that design, analysis, data entry and storage, and result capabilities are developed with emphasis on deriving a user-friendly, easily accessible tool. We have thus developed the approach as an integrated module of the freely available Ecopath with Ecosim scientific software; the world's most widely applied ecological modeling tool. We link the trophic ecosystem model to a value-chain approach where we explicitly and in considerable detail keep track of the flow (amounts, revenue, and costs) of fish products from sea through to the end consumer. We also describe the social aspects of the fish production and trade, by evaluating employment and income diagnostics. This is done with emphasis on distribution income while accounting for social aspects of the fishing sector. From a management perspective, one of the interesting aspects of the approach we introduce here, is that it opens for direct evaluation of what impact management interventions, e.g., quota settings, effort regulation, or area closures, may have on the ecosystem, the economy and the social setting, as well as on food availability for the consumer.     

Isomorphic chain graphs for modeling spatial dependence in ecological data

Graphical models (alternatively, Bayesian belief networks, path analysis models) are increasingly used for modeling complex ecological systems (e.g., Lee, In: Ferson S, Burgman M(eds) Quantative methods for conservation biology. Springer, Berlin Heilin Heideslperk New York, pp.127–147, 2000; Borsuk et al., J Water Res Plann Manage 129:271–282, 2003). Their implementation in this context leverages their utility in modeling interrelationships in multivariate systems, and in a Bayesian implementation, their intuitive appeal of yielding easily interpretable posterior probability estimates. However, methods for incorporating correlational structure to account for observations collected through time and/or space—features of most ecological data—have not been widely studied; Haas et al. (AI Appl 8:15–27, 1994) is one exception. In this paper, an “isomorphic” chain graph (ICG) model is introduced to account for correlation between samples by linking site-specific Bayes network models. Several results show that the ICG preserves many of the Markov properties (conditional and marginal dependencies) of the site-specific models. The ICG model is compared with a model that does not account for spatial correlation. Data from several stream networks in the Willamette River valley, Oregon (USA) are used. Significant correlation between sites within the same stream network is shown with an ICG model.