Evaluation of discrete host–parasitoid models for diamondback moth and Diadegma semiclausum field time population density series

The performance of discrete mathematical models to describe the population dynamics of diamondback moth (DBM) (Plutella xylostella L.) and its parasitoid Diadegma semiclausum was investigated. The parameter values for several well-known models (Nicholson–Bailey, Hassell and Varley, Beddington, Free and Lawton, May, Holling type 2, 3 and Getz and Mills functional responses) were estimated. The models were tested on 20 consecutive sets of time series data collected at 14 days interval for pest and parasitoid populations obtained from a highland cabbage growing area in eastern Kenya. Model parameters were estimated from minimized squared difference between the numerical solution of the model equations and the empirical data using Powell's method. Maximum calculated DBM growth rates varied between 0.02 and 0.07. The carrying capacity determined at 16.5 DBM/plant by the Beddington et al. model was within the range of field data. However, all the estimated parameter values relating to the parasitoid, including the instantaneous searching rate (0.07–0.28), per capita searching efficiency (0.20–0.27), search time (5.20–5.33), handling time (0.77–0.90), and parasitism aggregation index (0.33), were well outside the range encountered empirically. All models evaluated for DBM under Durbin–Watson criteria, except the May model, were not autocorrelated with respect to residuals. In contrast, the criteria applied to the parasitoid residuals showed strong autocorrelations. Thus, these models failed to estimate parasitoid dynamics. We conclude that the interactions of the DBM with its parasitoid cannot be explained by any of the models tested. Two factors may be associated with this failure. First, the parasitoid in this integrated biological control system may not be playing a major role in regulating DBM population. Second, and perhaps more likely, poor correlations reflect gross inadequacies in the theoretical assumptions that underlie the existing models.     

Spatially explicit modeling of overstory manipulations in young forests: Effects on stand structure and light

Young forests can be manipulated in diverse ways to enhance their ecological values. We used stem maps from two dense, second-growth stands in western Washington and a spatially explicit light model (tRAYci) to simulate effects of five silvicultural manipulations on diameter distribution, species composition, spatial patterning, and light availability. Each treatment removed 30% of the basal area, but differed in how trees were selected for removal. Three primary treatments were thin from below (removing the smallest trees), random thin (removing trees randomly), and gap creation (removing all trees in circles ∼1 tree height in diameter). Two additional treatments combined elements of these approaches: random ecological thin (a mixture of thin from below and random thin) and structured ecological thin (a mixture of thin from below and gap creation).     

Studying ecological communities from a neutral standpoint: A review of models’ structure and parameter estimation

Neutral models provide an alternative to niche-based assembly rules of ecological communities by assuming that communities’ properties are shaped by the stochastic interplay between ecological drift, migration and speciation. The recent and ongoing interest about neutral assumptions has produced many developments on the theoretical side, with nevertheless limited echoes in terms of analyses of real-world data. The present review paper aims to help bridge the widening gap between modellers and field ecologists through two objectives. First, to provide a multi-criteria typology of the main neutral models, including those from population genetics that have not yet been transposed to ecology, by considering how the fundamental processes of ecological drift, speciation and migration are modelled and, specifically, how space is taken into account. Second, to review methods recently proposed to estimate models parameters from field data, a point that should be mastered to allow for broader applications.     

Influence of Landscape Elements in Riparian Buffers on the Conservation of Semiaquatic Amphibians

Abstract:  Studies on riparian buffers have usually focused on the amount of land needed as habitat for the terrestrial life stages of semiaquatic species. Nevertheless, the landscape surrounding wetlands is also important for other key processes, such as dispersal and the dynamics of metapopulations. Multiple elements that influence these processes should therefore be considered in the delineation of buffers. We analyzed landscape elements (forest cover, density of roads, and hydrographic network) in concentric buffers to evaluate the scale at which they influence stream amphibians in 77 distinct landscapes. To evaluate whether our results could be generalized to other contexts, we determined whether they were consistent across the study areas. Amphibians required buffers of 100–400 m of suitable terrestrial habitat, but interspecific differences in the amount of habitat were large. The presence of amphibians was related to roads and the hydrographic network at larger spatial scales (300–1500 m), which suggests that wider buffers are needed with these elements. This pattern probably arose because these elements influence dispersal and metapopulation persistence, processes that occur at large spatial scales. Furthermore, in some cases, analyses performed on different sets of landscapes provided different results, which suggests caution should be used when conservation recommendations are applied to disparate areas. Establishment of riparian buffers should not be focused only on riparian habitat, but should take a landscape perspective because semiaquatic species use multiple elements for different functions. This approach can be complex because different landscape elements require different spatial extents. Nevertheless, a shift of attention toward the management of different elements at multiple spatial scales is necessary for the long-term persistence of populations.     

取代芳烃对发光菌的毒性及定量结构与活性相关

通过测定取代芳烃对发光菌毒性，用Ｆｒｅｅ－Ｗｉｌｓｏｎ法和分子连接性法研究了取代芳烃结构与活性的相关性，取代基的毒性顺序为：－Ｂｒ＞－ＣＯＯＨ＞－ＮＯ２≈－Ｃｌ＞－ＣＨ３＞ＮＨ２。建立了ＥＣ５０与ＬＣ５０的相关性，并预测一些化合物的ＬＣ５０值，结果和实测值符合较好。     

新型结构ABR的设计与水力特性研究

针对ABR自身的缺点,设计出一种新型结构的ABR.该反应器为双层结构,共有5部分组成,各部分容积各不相同.该反应器的设计思想是将ABR与生物滤池以及活性炭吸附等工艺相联合.这种设计能够最大程度地发挥各工艺的优势,进而达到更好的处理效果.通过脉冲响应实验对该反应器的水力特性进行研究,得出不同水力停留时间(HRT)下的停留...     

全尾砂絮凝沉降参数GA-SVM优化预测模型研究

为了得到经济、高效的絮凝沉降参数,建立GA_SVM预测模型进行优化选择。在优选过程中,以供砂浓度、絮凝剂单耗和絮凝剂添加浓度作为输入因子,以沉降速度作为综合输出因子,通过室内试验,建立训练、验证样本集;建立支持向量机（SVM）回归预测模型,用训练集对模型进行训练,进而以验证集预测值的均方误差作为适应度函数,通过遗传算法（GA）对SVM模型参数进行优化选择,应用优化得到的SVM模型对絮凝沉降参数进行预测、优化。以湖南某铅锌银矿为例,通过建立的GA_SVM模型对全尾砂絮凝沉降参数进行预测,优选出该矿最佳絮凝沉降参数为:供砂浓度20%-25%,絮凝剂单耗8g/t,添加浓度009%。经实验对比,该模型对絮凝沉降参数预测结果的相对误差能控制在5%左右,精确度较高,可以作为絮凝沉降参数优选的一种新思路     

基于信息融合与GM的石油罐区安全监控预测模型

近年来,石油罐区安全事故发生频率呈不断上升趋势。为有效增强罐区安全监控预警系统监测数据的可靠性,并实现对事故的早期预警,基于多传感器信息融合技术和灰色模型(GM)理论,建立出石油罐区安全监控预测模型。首先,研究了基于递推最小二乘法改进的最优加权融合算法,并将其作为一级(特征级)融合模型,其次,介绍分析了灰色预测理论及GM(1,1)模型的实现过程,最后建立出基于GA-BP神经网络算法的二级(决策级)数据融合模型,并得到石油罐区安全监控预测模型。     

基于灰色神经网络优化组合模型的火灾预测研究

为了提高火灾事故预测的精度,根据我国火灾事故数据样本较小,波动性较大的特点,将遗传算法优化的灰色无偏预测模型与遗传算法优化的BP神经网络模型结合起来,建立灰色神经网络优化组合模型,充分发挥无偏灰色预测模型适用于小样本的数据预测的优势与BP神经网络处理非线性问题的优点。分别采用遗传算法优化后的无偏灰色GM（1,1）模型、遗传算法优化的BP神经网络预测模型与灰色神经网络优化组合模型对我国1998-2008年的火灾事故进行拟合,并对2009-2011年的火灾事故发生数进行预测。结果表明:灰色神经网络优化组合模型的预测误差最小,精度最高,适用于火灾事故的预测。