资源异质性环境中植物克隆生长的描述与模拟

植物克隆生长型主要由遗传结构决定，不同的克隆植物具有不同的克隆生长型，同时植物的克隆生长型又依具体生境和个体发育阶段不同而变化。Harper认为植物构件的结构由分枝角度、节间长度和芽的成活率决定。大量的研究表明克隆植物生长型主要由3个形态参数决定：节间长度、分枝角度和分枝强度。 植物的生境条件无论在时间还是空间上都是异质性的，即使在很小的尺度上这种异质性也是存在的。在这种具有异质性的生境条件下几乎所有植物都有表型可塑性。植物的表型可塑性是指植物在不同的环境因子条件下，在形态、生物量、生理等方面产生的一系列不同。表现型可塑性是植物种群克服环境异质性的重要途径，也是克隆植物实现觅养行为的途径。克隆植物的觅养行为是通过根茎或匍匐茎的长度和分枝强度的变化以及生物量的分配来实现其迁移和对生境的选择，从而将分株安置在各种微环境中。 克隆植物构型的可塑性可使它在土壤水分斑块性分布的环境中通过克隆生长，调整对不同斑块的土壤水分获取对策。在一田间实验中，匍匐茎草本蛇莓（Duchesnea indica Focke）经历了不同土壤水分水平（土壤最大含水量的40%、60%、80%、100%等）处理，以研究土壤水分对蛇莓克隆构型的影响。结果表明：间隔子长度、分株密度、分枝角度和分枝强度呈二次曲线变化，土壤含水为最大含水量的80%为最适生境。 克隆植物构型的可塑性可使它在养分斑块性分布的环境中通过克隆生长调整相应于对不同斑块的养分获取对策。在一田间实验中，蛇莓经历了不同土壤养分水平（高、中、低和对照）处理，以研究土壤养分对蛇莓克隆构型的影响。结果表明：随着土壤养分水平的增加，间隔子的长度、分枝角度均逐渐降低，分枝强度和分株密度增加。 克隆植物构型的可塑性可使它在不同光强的环境中通过克隆生长，调整其对不同光强的资源获取对策。在控制性光资源异质性生境（模拟浓密林荫、稀疏林荫、农田间套作、裸地等）下，研究和模拟了光资源的时空异质性和蛇莓的克隆可塑性变化。结果表明：随着光照强度的增加，间隔子长度的长度逐渐降低，分枝角度、分株强度呈二次曲线变化。 克隆植物构型的可塑性可使它在不同海拔的环境中通过克隆生长，调整其对不同海拔的资源获取对策。在一海拔高度实验中，匍匐茎草本蛇莓经历了不同海拔(400 m、800 m、1200 m和1600 m)处理，以研究不同海拔对蛇莓克隆构型的影响。结果表明：随着海拔的增加，间隔子长度、分株密度、分枝角度和分枝强度呈二次曲线变化。 从克隆植物生长环境（小气候）定量分析了克隆植物生长必需资源如水分、养分、光强、海拔等的变化特性。具体描述和分析了异质环境尺度的大小和等级数。在前人研究成果的基础上，验证了克隆植物生长必需资源分布异质性的数学模型并建立相应的运算模块。在不同水分、养分、光强和海拔等异质性生境中，蛇莓克隆构型相关特征的可塑性变化可用动态Logistic模型进行模拟和预测，拟合效果较好。结合植物对环境异质性的利用对策，对所揭示的蛇莓克隆构型可塑性进行了讨论。 用分形技术描述了蛇莓在资源斑块性分布的生境中，通过克隆生长调整相应于对不同斑块的资源获取对策。植物克隆构型的形态特征在一定尺度范围内具有自相似特征。蛇莓克隆构型的分形维数直接反映了在异质性生境中蛇莓克隆生长的差异。蛇莓克隆生长越发达分形维数越高。相对小的分形维数，反映出蛇莓克隆生长相对较弱。基于计算机图像技术和分形理论，建立了植物克隆生长分形度量的计算机模型，实现了对植物克隆生长过程的计算机模拟。模拟的蛇莓克隆生长形态与实际生长不仅具有相近的分形维数，而且形态也非常相似。利用克隆生长模型的预测能力克服实验生态学难以逾越的某些研究盲点，其研究成果将对克隆植物利用资源异质性的生态对策研究具有重要的指导意义。

浑善达克沙地几种优势植物的生态适应

浑善达克沙地是我国北方干旱半干旱区的主要沙地和严重荒漠化地区之一。同时也是我国内陆沙尘的主要源区之一。研究当地植物对沙地环境的适应方式有助于当地的荒漠化治理，加快生态环境恢复。本文应用（温室和野外）实验生态学方法研究了沙地植物对水分、沙埋和养分异质性环境的生态适应对策。 浑善达克沙地属于半干旱区域。在一次降雨过后，适合植物生长的湿沙层逐渐下降，或者说不适合植物生长的干沙层逐渐加厚。为了能够有效地从沙层中获得水分，植物的根系的伸长的速度必须大于湿沙层下降的速度。因此，当地分布的植物的根系则应该具有相应的形态、生长和生物量投资方面的可塑性。羊柴（Hedysarum laeve Maxim. (Leguminosae) ）是当地的主要半灌木和固沙植物。我们研究了羊柴幼苗对不同土壤含水量和不同模拟降雨量的反应格局，以及移动沙丘生长季节的土壤含水量变动规律。发现，大于3％土壤含水量适合羊柴幼苗生长。最适土壤含水量为12%－20% 。在生长季节早期，羊柴幼苗比较容易在沙丘上定居。如果没有充分的后续降雨的话，萌发后的幼苗在沙丘顶部、落沙坡中部和后部定居比较困难。降雨量越大，根系越深、总根长越大、根系直径越大、侧根越多、根冠比越低。 在干旱半干旱区域的沙地，种子萌发的时间和地点对于植物的定居和存活具有关键作用。通过温室实验，研究了小叶锦鸡儿和羊柴的种子萌发和出苗对不同深度的沙埋的反应，及其与种子大小的关联。结果表明，小叶锦鸡儿和羊柴的种子萌发和出苗对浑善达克沙地的自然生境表现出相似的生态适应。这两个种的种子萌发的适宜温度为10-15ºC, 这是当地春季的平均温度。由于这两个种的种子萌发是光敏感的，所以它们的种子萌发受土壤含水量和光照强度二者之间的平衡调节。2 cm 的较浅沙埋最有利于种子萌发和出苗。种子埋得越深，种子的萌发率和出苗率越低，更多的种子受胁迫休眠保存在土壤中作为种子库。不同大小的种子的不同萌发能力也是一种重要的生态适应，这可以调节种子在合适的时间和合适的沙埋深度萌发和出苗。 冰草（Agropyron cristatum (L.) Gaertn）是浑善达克沙地植物群落中占优势的多年生根茎草本植物之一。种子在合适的地点和时间萌发以及幼苗在合适的地点和时间生长，对于冰草在沙地环境条件下生存和分布具有重要意义。本文研究了浑善达克沙地4-10月份土壤含水量变动情况和冰草种子萌发、出苗和幼苗生长对土壤含水量的响应。结果表明，4月下旬至5月上中旬的土壤含水量对冰草种子萌发、出苗和定居极为关键。控制条件下，冰草种子萌发的最适土壤含水量是12%-20%，出苗以及幼苗生长的最适土壤含水量是12%-16%。当土壤含水量低于3%，冰草种子不能萌发，土壤含水量低于6%时，幼苗不能出土和定居。当土壤含水量达到16%时，冰草幼苗生物量有所下降。在6%-8%的土壤含水量条件下，植株将更多的生物量投资于根的生长。 本文对浑善达克沙地低湿滩地、滩地-风沙沉积过渡区到风沙沉积区的赖草（Leymus secalinus （Georgi） Tzvel.）分株数、地上生物量、土壤水分和养分异质性进行了研究。结果表明，从低湿滩地、滩地-风沙沉积过渡区到风沙沉积区，随着土壤养分的降低，赖草分株数和地上生物量反而增加。赖草的分株数在三种生境中都存在空间自相关。并且，从低湿滩地、过渡区到风沙沉积区空间自相关的变程逐渐增加。地上生物量同样存在空间自相关，但变程以过渡区最大，风沙沉积区最低。土壤水分仅仅在风沙沉积区存在空间自相关。在三种生境条件下，土壤全氮和有机质的空间分布格局相似，都在低湿滩地和过渡区存在空间自相关且变程相似。在风沙沉积区不存在空间自相关。赖草的空间分布格局在低湿滩地为偏离随机适度聚集的分布格局，在过渡区近似于聚居分布，而在风沙沉积区为均匀分布格局。 豆科锦鸡儿属（Caragana ）植物因其可以生物固氮而在草原生态系统当中具有特殊的地位。定量分析小叶锦鸡儿（Caragana microphylla ）灌丛在浑善达克沙地不同生境条件下的分布格局，有助于理解植被与土壤养分循环之间的关系和合理制定退化沙地的恢复对策。本文采用地统计学中的半方差分析和分形分析两种方法研究了浑善达克沙地小叶锦鸡儿灌丛的空间分布格局，分析了不同生境中小叶锦鸡儿灌丛的植被、土壤水分和养分间的相关性。结果表明（1）小叶锦鸡儿灌丛在三种生境条件下（滩地、固定沙丘和半固定沙丘）的盖度、土壤有机质和全氮的空间分布符合球状模型，空间自相关显著;（2）土壤pH值在滩地和固定沙丘的空间分布符合球状模型且空间自相关显著，但在半固定沙丘空间自相关不显著;（3）土壤水分在三种生境中的空间分布都符合线性模型，空间自相关显著。（4）植被的变异尺度（变程）小于各个土壤要素的变异尺度。植被（小叶锦鸡儿灌丛）的分布和形成过程决定了土壤养分的分布和形成过程。当地的豆科植物在养分“沃岛”现象的形成中起了重要作用，合理的利用和布局当地的豆科植物，可以更加有效地补充草地生态系统的养分，从而有利于加快当地生态系统的恢复进程。

Geostatistical analysis of chlorophyll a in freshwater ecosystems

Horizontal spatial patterns of chlorophyll a in Meiziya Reservoir, Hubei Province, China were analyzed once each month during May, June and July 1997. Two geostatistical techniques, semivariance and fractal analysis, were used to determine variation in chlorophyll a over the whole study area (isotropic) and in different directions (anisotropic). Both techniques provided useful information for detecting and assessing spatial pattern changes of chlorophyll a in freshwater environments. Based on our case study, the distribution of chlorophyll a shifted from aggregated to random distribution in the case of small rainfall event, and then returned to the aggregated distribution after a large rainfall event. On the other hand, the distribution of chlorophyll a became more heterogeneous or random in the direction of water flow (S-N direction) when rainfall events occurred, which was enhanced by rainfall intensity. In contrast, the influence of water flow on the spatial patterns was weak in the E-W direction, and thus the distribution of chlorophyll a remained aggregate with a moderate spatial heterogeneity.

Quantitative structure-property relationships for octanol-air partition coefficients of polychlorinated naphthalenes, chlorobenzenes and p,p '-DDT

The octanol-air partition coefficient (K-OA) is a key descriptor of chemicals partitioning between the atmosphere and environmental organic phases. Quantitative structure-property relationships (QSPR) are necessary to model and predict KOA from molecular structures. Based on 12 quantum chemical descriptors computed by the PM3 Hamiltonian, using partial least squares (PLS) analysis, a QSPR model for logarithms of K-OA to base 10 (log K-OA) for polychlorinated naphthalenes (PCNs), chlorobenzenes and p,p'-DDT was obtained. The cross-validated Q(cum)(2) value of the model is 0.973, indicating a good predictive ability of the model. The main factors governing log K-OA of the PCNs, chlorobenzenes, and p,p'-DDT are, in order of decreasing importance, molecular size and molecular ability of donating/accepting electrons to participate in intermolecular interactions. The intermolecular dispersive interactions play a leading role in governing log K-OA. The more chlorines in PCN and chlorobenzene molecules, the greater the log K-OA values. Increasing E-LUMO (the energy of the lowest unoccupied molecular orbital) of the molecules leads to decreasing log K-OA values, implying possible intermolecular interactions between the molecules under study and octanol molecules. (C) 2002 Elsevier Science Ltd. All rights reserved.

Quantitative relationships between molecular structures, environmental temperatures and octanol-air partition coefficients of PCDD/Fs

A concise quantitative model that incorporates information on both environmental temperature M and molecular structures, for logarithm of octanol-air partition coefficient (K-OA) to base 10 (logK(OA)) of PCDDs, was developed. Partial least squares (PLS) analysis together with 14 quantum chemical descriptors were used to develop the quantitative relationships between structures, environmental temperatures and properties (QRSETP) model. It has been validated that the obtained QRSETP model can be used to predict logK(OA) of other PCDDs. Molecular size, environmental temperature (T), q(+) (the most positive net atomic charge on hydrogen or chlorine atoms in PCDD molecules) and E-LUMO (the energy of the lowest unoccupied molecular orbital) are main factors governing logK(OA) of PCDD/Fs under study. The intermolecular dispersive interactions and thus the size of the molecules play a leading role in governing logK(OA). The more chlorines in PCDD molecules, the greater the logK(OA) values. Increasing E-LUMO values of the molecules leads to decreasing logK(OA) values, implying possible intermolecular interactions between the molecules under study and octanol molecules. Greater q(+) values results in greater intermolecular electrostatic repulsive interactions between PCDD and octanol molecules and smaller logK(OA) values. (C) 2002 Elsevier Science B.V. All rights reserved.

Quantitative structure-property relationships for octanol-air partition coefficients of polychlorinated biphenyls

Based on nine quantum chemical descriptors computed by PM3 Hamiltonian, using partial least squares analysis, a significant quantitative structure-property relationship for the logarithm of octanol-air partition coefficients (log K-OA) of polychlorinated biphenyls (PCBs) was obtained. The cross-validated Q(cum)(2) value of the model is 0.962, indicating a good predictive ability. The intermolecular dispersive interactions and thus the size of the PCB molecules play a key role in governing log K-OA. The greater the size of PCB molecules, the greater the log K-OA values. Increasing E-LUMO (the energy of the lowest unoccupied molecular orbital) values of the PCBs leads to decreasing log K-OA values, indicating possible interactions between PCB and octanol molecules. Increasing Q(Cl)(+) (the most positive net atomic charges on a chlorine atom) and Q(C)(-) (the largest negative net atomic charge on a carbon atom) values of PCBs results in decreasing log K-OA values, implying possible intermolecular electrostatic interactions between octanol and PCB molecules. (C) 2002 Elsevier Science Ltd. All rights reserved.

Quantitative structure-property relationships (QSPRs) on direct photolysis of PCDDs

By the use of partial least squares (PLS) method and 27 quantum chemical descriptors computed by PM3 Hamiltonian, a statistically significant QSPR were obtained for direct photolysis quantum yields (Y) of selected Polychlorinated dibenzo-p-dioxins (PCDDs). The QSPR can be used for prediction. The direct photolysis quantum yields of the PCDDs are dependent on the number of chlorine atoms bonded with the parent structures, the character of the carbon-oxygen bonds, and molecular polarity. Increasing bulkness and polarity of PCDDs lead to decrease of log Y values. Increasing the frontier molecular orbital energies (E-lumo and E-homo) and heat of formation (HOF) values leads to increase of log Y values. (C) 2001 Elsevier Science Ltd. All rights reserved.

Quantitative structure-property relationship study on reductive dehalogenation of selected halogenated aliphatic hydrocarbons in sediment slurries

In this study, by the use of partial least squares (PLS) method and 26 quantum chemical descriptors computed by PM3 Hamiltonian, a quantitative structure-property relationship (QSPR) model was developed for reductive dehalogenation rate constants of 13 halogenated aliphatic compounds in sediment slurry under anaerobic conditions. The model can be used to explain the dehalogenation mechanism. Halogenated aliphatic compounds with great energy of the lowest unoccupied molecular orbital (E-lumo), total energy (TE), electronic energy (EE), the smallest bond order of the carbon-halogen bonds (BO) and the most positive net atomic charges on an atom of the molecule (q(+)) values tend to be reductively dehalogenated slow, whereas halogenated aliphatic compounds with high values of molecular weight (Mw), average molecular polarizability (a) and core-core repulsion energy (CCR) values tend to be reductively dehalogenated fastest. (C) 2001 Published by Elsevier Science Ltd.

Quantitative structure-property relationship studies on n-octanol/water partitioning coefficients of PCDD/Fs

Based on some fundamental quantum chemical descriptors computed by PM3 Hamiltonian, by the use of partial least-squares (PLS) analysis, a significant quantitative structure-property relationship (QSPR) model for logK(ow) of polychlorinated dibenzo-p-dioxins and dibenzo-p-furans (PCDD/Fs) was obtained. The QSPR can be used for prediction. The intermolecular dispersive interactions and thus the bulkness of the PCDD/Fs are the main factors affecting the logK(ow). The more chlorines in the PCDD/F molecule, the greater the logK(ow) values. (C) 2001 Elsevier Science Ltd. All rights reserved.

Quantitative relationship between chromatographic retentions and molecular structures of polychlorinated dibenzo-p-dioxins (PCDDs)

A new approach to study the quantitative relationships between chromatographic retentions and molecular structures of polychlorinated dibenzo-p-dioxins (PCDDs) is described. The retention equations of PCDDs log k' = A + B/T in gas chromatography (GC) are used to evaluate the properties of the regression coefficients A and B, which have been widely accepted as highly reliable chromatographic retentions. The quantitative relationships between the A, B values and the molecular structures are found. The molecular descriptors given for the first time in this article are very effective. As a result, the regression equations are derived with correlation coefficients greater than 0.9995. The A, B values of PCDDs with no standards available have been predicted according to these relationships. They are very useful in chromatographic identification. The retention times of all PCDDs can be conveniently predicted at any temperature program. Compared with the data obtained from the relevant experiments, the results of prediction are very accurate. (C) 2000 Elsevier Science Ltd. All rights reserved.

Correcting the systematic error of the density functional theory calculation: the alternate combination approach of genetic algorithm and neural network

The alternate combinational approach of genetic algorithm and neural network (AGANN) has been presented to correct the systematic error of the density functional theory (DFT) calculation. It treats the DFT as a black box and models the error through external statistical information. As a demonstration, the AGANN method has been applied in the correction of the lattice energies from the DFT calculation for 72 metal halides and hydrides. Through the AGANN correction, the mean absolute value of the relative errors of the calculated lattice energies to the experimental values decreases from 4.93% to 1.20% in the testing set. For comparison, the neural network approach reduces the mean value to 2.56%. And for the common combinational approach of genetic algorithm and neural network, the value drops to 2.15%. The multiple linear regression method almost has no correction effect here.

Study on growth mechanism of low-temperature prepared microcrystalline Si thin films

Microcrystalline silicon thin films at different growth stages were prepared by hot wire chemical vapor deposition. Atomic force microscopy has been applied to investigate the evolution of surface topography of these films. According to the fractal analysis I it was found that, the growth of Si film deposited on glass substrate is the zero-diffused stochastic deposition; while for the film on Si substrate, it is the finite diffused deposition on the initial growth stage, and transforms to the zero-diffused stochastic deposition when the film thickness reaches a certain value. The film thickness dependence of island density shows that a maximum of island density appears at the critical film thickness for both substrates. The data of Raman spectra approve that, on the glass substrate, the a-Si: H/mu c-Si:H transition is related to the critical film thickness. Different substrate materials directly affect the surface diffusion ability of radicals, resulting in the difference of growth modes on the earlier growth stage.

安达市碱性草地土壤颗粒的分维特征

运用土壤颗粒质量分形模型计算松嫩平原低平地安达试区植被分布区和碱斑区样点土壤颗粒的分形维数,并建立分形维数与土壤颗粒不同粒级间的回归关系,以探讨土地碱化后土壤粒径分布的分形特征及其与土壤物理性状的关系。结果表明:安达试区土壤颗粒分形维数较高,平均分别仅有48.7×10-5cm/s(Pit A)和4.30×10-6cm/s(Pit B),反映了该区土壤细颗粒含量高、土壤大孔隙数量少、土壤饱和导水率低的特征;土壤颗粒分形维数与黏粒含量呈对数正相关关系,而与粉粒和砂粒含量相关性不显著,说明在安达试区,影响土壤颗粒分形维数的主要因素是黏粒含量;羊草地土壤颗粒分形维数在土壤垂直剖面上的变异较大,说明植被生长促进了土壤质地的变异;碱斑地土壤颗粒分形维数明显大于羊草地,细颗粒含量高,饱和导水率低,说明碱斑的形成恶化了土壤物理性质;土壤颗粒分形维数可以反映安达市土壤物理性质的好坏,能作为土壤退化和生态环境恶化的评价指标。研究结果可为安达市以及松嫩平原盐碱地生态环境的修复和治理提供科学依据。

云雾山自然保护区优势植物种群分布格局的分形特征

对宁夏云雾山草原自然保护区植物种群分布格局的分形计盒维数进行了研究。结果表明:本氏针茅、铁杆蒿和百里香是该区的优势种。3种优势种的计盒维数在1.7左右,表明它们具有较大的空间占据能力。但是它们的计盒维数最大值出现的时间不同,本氏针茅、百里香计盒维数最大值出现在封育20a的样地中,铁杆蒿出现在封育25a的样地中。