Identification of nonlinear models of biological membranes using the voltage-clamp method

The method for identification of nonlinear systems proposed in 1952 by Hodgkin and Huxley is mathematically justified. A procedure for the application of this method is developed, including the development of the structure of a mathematical model, carrying out a series of tests with special chosen signals, and determination of unknown parameters. Basic requirements for the admissible sets of input and output signals and to the system operator have been determined. It is shown that this operator should be totally continuous and that the minimum number of unknown parameters and the minimum complexity of the operator structure should give an approximation of the necessary quality. The pros and cons of the Hodgkin-Huxley and Noble mathematical models and the methods used for their development are discussed. A structure for the operator for the identification of mathematical models of excitable membranes with a large number of membrane currents is proposed. It is found that the nonlinear electrical properties of biological membranes can be identified using tests with other types of “clamped” parameters, such as the current, ramp voltage, etc.     

Seasonal cycles and persistence in an acarine predator-prey system on cassava in Africa

We applied time series analysis and a mechanistic predator-prey model to long-term data of monthly population counts of the herbivorous pest mite Mononychellus tanajoa and its introduced phytoseiid predator Typhlodromalus aripo from a cassava field in Benin, West Africa. In this approach, we determined the extent to which the main features of the observed predator-prey fluctuations in cassava fields can be explained from biotic traits inherent to the biology of predator and prey, and the extent of the significance of abiotic factors in determining population levels. The time series analyses with cross-correlation showed that the period of predator-prey fluctuations coincided with the annual pattern of intense rainfall and onset of dry season. A pronounced M. tanajoa peak followed after a short lag (2 weeks) by a T. aripo peak coincided with a trough in rainfall intensity. Both the prey and predator had local and lower peaks that coincided with high rainfall intensity, but with a considerably longer lag (ca. 3 months) compared with the high peaks occurring at the onset of the dry season. Regression of log-transformed data series (over a 7-year period) showed that—except for the first year after predator release—M. tanajoa fluctuated around an almost time-invariant mean population density, while T. aripo densities showed a consistent decline over the full observation period. To explain observed trends and periodic components in the data-series of predator and prey densities, we review hypotheses that are based on (1) the annual patterns and trends in abiotic factors, (2) mechanisms endogenous to the predator-prey system and (3) a combination of exogenous and endogenous factors.     

Distribution patterns of boreal marshland birds: modelling the relationships to land cover and climate

Aim The aims of this work were (1) to study how well land‐cover and climatic data are capable of explaining distribution patterns of ten bird species breeding and/or feeding primarily on marshes and other wetlands and (2) to compare the differences between red‐listed and common marshland species in explanatory variables, and to study the predictability of their distribution patterns. Location Finland, northern Europe. Methods The data of the bird atlas survey carried out in 1986–89 using a 10 × 10 km uniform grid system in Finland were used in the analyses. Land‐cover data based on CORINE (Coordination of Information on the Environment) classification and climatic variables were compiled using the same 10 × 10 km grid. Generalized additive models (GAM) with a stepwise selection procedure were used to select relevant explanatory variables and to examine the complexity of the response shapes of the different species to each variable. The original data set was randomly divided into model training (70%) and model evaluation (30%) sets. The final models of common and red‐listed bird species richness were validated by fitting them to the model evaluation set, and the correlation between observed and predicted species richness was calculated. We assessed the discrimination ability of the binary models (single species) with the area under the curve (AUC) of a receiver operating characteristic (ROC) plot and the Kappa coefficient. Results Cover of marshland, shoreline length and mean temperature in April–June were significantly (P < 0.01) related to the common marshland species richness. Cover and clumping of marshland and mean temperature and precipitation in April–June were selected in the model of red‐listed marshland species richness. The level of discrimination in our single species models varied in ROC from fair to excellent (AUC values 0.70–0.95). Cover of marshland was included in all GAM models built for the target species, but clumping of marshland, shoreline length and cover of mires also appeared as important predictors in single species models. Seven species had statistically significant relationships with climatic variables in the multivariate GAMs. Cover of marshland was highest in squares in which the red‐listed bittern Botaurus stellaris, marsh harrier Circus aeruginosus and great reed warbler Acrocephalus arundinaceus and the water rail Rallus aquaticus were observed. Main conclusions Cover of marshland was the only variable which was included in all the models, reinforcing the close connection between the studied species and marshlands. Broad‐scale clumping of marshlands was important for the red‐listed species, probably due to the much lower population sizes of red‐listed species than those of common species. Land‐cover data produced in CORINE seems to be well suited for modelling the distribution patterns of marshland birds. Although climatic variables also strongly affect the studied marshland birds, habitat availability plays a crucial role in their occurrence. The distribution patterns of marshland birds at the scale of 10 × 10 km reflect the interplay between habitat availability and direct climatic variables.     

厚藤ASR基因克隆及功能初步分析

通过对厚藤(Ipomoea pes-caprae(Linn.)Sweet.)cDNA文库的筛选,获得了一个编码厚藤ASR(ABA-stress-ripening)基因的全长cDNA,命名为IpASR。研究结果显示,IpASR编码区全长648 bp,共编码215个氨基酸;蛋白质等电点为5.42,分子量为24.57 k D。通过在酵母中表达,发现IpASR能够提高转基因酵母的耐盐性及抗氧化能力。进一步以厚藤成年植株及幼苗为材料进行实时荧光定量PCR分析,结果表明,IpASR基因在厚藤成年植株各组织中广泛表达;高盐、甘露醇胁迫和ABA处理可诱导该基因在厚藤幼苗中的表达。结合GFP融合蛋白的亚细胞定位和生物信息学分析,发现IpASR蛋白为核蛋白,推测IpASR基因参与了厚藤生长发育的调控,并可响应ABA和非生物胁迫的诱导。     

Involvement of polyamines in plant response to abiotic stress

Environmental stresses are the major cause of crop loss worldwide. Polyamines are involved in plant stress responses. However, the precise role(s) of polyamine metabolism in these processes remain ill-defined. Transgenic approaches demonstrate that polyamines play essential roles in stress tolerance and open up the possibility to exploit this strategy to improve plant tolerance to multiple environmental stresses. The use of Arabidopsis as a model plant enables us to carry out global expression studies of the polyamine metabolic genes under different stress conditions, as well as genome-wide expression analyses of insertional-mutants and plants over-expressing these genes. These studies are essential to dissect the polyamine mechanism of action in order to design new strategies to increase plant survival in adverse environments.     

渭河底栖动物性状和功能对空间尺度环境变量响应的生态区差异性

以我国中部渭河南部流域山区和平原生态区的底栖动物为研究对象,通过计算29个生物性状类别和7个功能多样性指数,比较了不同生态区的生物性状组成和功能与性状多样性指数差异性;应用综合RLQ和fourth-corner方法探索底栖动物生物性状组成与土地利用和理化变量的关系;通过广义线性模型(GLM)比较不同空间尺度环境变量对底栖动物功能与性状多样性指数影响的生态区差异性。研究发现,共18个底栖动物性状组成在山区和平原间存在显著差异性,其中具有无庇护所和以叶片为庇护所材料、外骨骼轻微骨化和骨化良好、草食性、捕食性等生物性状的底栖动物栖息于栖境状况较好的山区,体壁呼吸、虫体柔软、集食者等生物性状更多的集中在人类活动较严重的平原区。除了功能均匀度指数外,山区的性状和功能多样性指数均显著高于平原,说明平原环境干扰显著降低了底栖动物性状和功能多样性。综合RLQ和fourth-corner方法表明底栖动物生物性状对环境胁迫的响应存在可预测性。GLM模型结果表明,山区和平原生物性状和功能多样性指数受到不同空间尺度土地利用和理化环境变量的影响:流域尺度城镇用地、水温和TN含量是影响山区功能和性状多样性指数模型的重要环境变量,但平原区河段尺度农业用地面积百分比和平均水深是影响功能和性状多样性的主要因子。     

黄土残塬沟壑区流域次生植被物种分布的地形响应

研究流域次生植被物种对地形因子的响应规律,识别影响次生植被物种分布的主要地形因子,是流域近自然植被生态恢复和重建的基础。采用ArcGIS空间分析模块和地形分析模块TauDEM,并与统计软件SPLUS2000中的GRASP工具相结合,建立了位于黄土高原残垣沟壑区山西省吉县蔡家川流域次生植被各个物种分布基于地形因子的广义相加模型(GAM)。模型中的地形因子包括:海拔、坡向、坡度、平面曲率、坡位指数(SPI)、地形湿度指数(TWI)、单宽汇水面积(SCA)等。受试者操作特征曲线(ROC)测试中AUC值表明:大部分测试物种(约62%)拟合模型效果较好,且模型较为稳定。总体来看,研究流域次生植被物种分布体现了水分限制的空间分异特征:阴坡各物种分布概率较大,且随海拔升高而减小。影响研究流域次生植被物种空间分布的潜在重要因子为海拔和坡向,而单宽汇水面积(SCA)和地形湿度指数(TWI)虽然是多个物种响应模型的预测因子,但受高一级尺度海拔的影响,SCA与TWI对物种分布的影响作用较小;坡度影响作用最小。据此,在流域植被恢复和防护林建设目标区选择及立地条件划分时应首先以海拔和坡向为依据,单宽汇水面积(SCA)和地形湿度指数(TWI)则可以作为次一级立地分类依据,而坡度则仅能作为最后一级的分类依据。