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1.
Cross-ecosystem subsidies, such as terrestrial invertebrates and leaf litter falling into water as resources for aquatic communities,
can vary across environmental gradients. We examined whether the effect of terrestrial subsidy inputs on benthic invertebrates
was mediated by resident coastal cutthroat trout (Oncorhynchus clarki) in two representative streams. We experimentally manipulated the input rates (reduced, ambient) of terrestrial subsidies
(terrestrial invertebrates and leaf litter) as well as the presence or absence of cutthroat trout in the two streams. The
hypothesis that the reduction of terrestrial subsidies to the stream influences benthic invertebrate assemblages was supported
by experimental results. The treatments of terrestrial subsidy reduction and cutthroat trout presence had a significant negative
effect on benthic invertebrate community biomass and shredder biomass in East Creek with high natural terrestrial subsidy
input and small amount of large wood in channel. In contrast, results from Spring Creek with low subsidy input and large amount
of large wood in channel showed that only the terrestrial subsidy reduction significantly reduced the biomass of shredders.
The effects of the terrestrial subsidy input and trout predation on benthic invertebrate communities varied between the two
streams. Our results indicate that a subsidy effect on benthic communities can vary between nearby streams differing in canopy
and habitats. This study, with the major finding of highly context-dependent effects of spatial subsidies, suggests that the
interplay of resource subsidies and predators on invertebrate community assemblages can be site-specific and context-dependent
on habitat features. 相似文献
2.
Recognizing spatial distribution patterns of grassland insects: neural network approaches 总被引：2，自引：1，他引：1
WenJun Zhang XiaoQing Zhong GuangHua Liu 《Stochastic Environmental Research and Risk Assessment (SERRA)》2008,22(2):207-216
The main objective of this study was to fit and recognize spatial distribution patterns of grassland insects using various
neural networks, and to analyze the feasibility of neural networks for detecting spatial distribution patterns of grassland
insects. BP neural network, Learning vector quantization (LVQ) neural network, linear neural network and Fisher’s linear discriminant
analysis were used to fit and recognize spatial distribution patterns at different ecological scales. Various comparisons
and analysis were conducted. The results showed that BP, LVQ and linear neural networks were better algorithms for recognizing
spatial distribution patterns of grassland insects. BP neural network was the best algorithm to fit spatial distribution patterns.
BP network may be used to recognize the spatial details of distribution patterns, and the recognition performance of BP network
became better as the increase of the number of hidden layers and neurons. Performance of linear neural network for pattern
recognition was similar to linear discrimination method. Linear neural network would yield better performance in finding the
general trends of distribution patterns. Recognition performance of LVQ network was just between BP network and linear network.
It was found that recognition performance of neural networks depended upon not only the ecological scale but also the criterion
for classification. Under the uniform criterion, recognition efficiency of linear methods tended to be weak as ecological
scale became to be coarser. A joint use of neural networks was suggested in order to achieve both overall and detailed understanding
on spatial distribution patterns. 相似文献
3.
Alisha L. Steward Jonathan C. Marshall Fran Sheldon Bronwyn Harch Satish Choy Stuart E. Bunn Klement Tockner 《Aquatic Sciences - Research Across Boundaries》2011,73(4):551-566
Dry river beds are common worldwide and are rapidly increasing in extent due to the effects of water management and prolonged
drought periods due to climate change. While attention has been given to the responses of aquatic invertebrates to drying
rivers, few studies exist on the terrestrial invertebrates colonizing dry river beds. Dry river beds are physically harsh
and they often differ substantially in substrate, topography, microclimate and inundation frequency from adjacent riparian
zones. Given these differences, we predicted that dry river beds provide a unique habitat for terrestrial invertebrates, and
that their assemblage composition differs from that in adjacent riparian zones. Dry river beds and riparian zones in Australia
and Italy were sampled for terrestrial invertebrates with pitfall traps. Sites differed in substrate type, climate and flow
regime. Dry river beds contained diverse invertebrate assemblages and their composition was consistently different from adjacent
riparian zones, irrespective of substrate, climate or hydrology. Although some taxa were shared between dry river beds and
riparian zones, 66 of 320 taxa occurred only in dry river beds. Differences were due to species turnover, rather than shifts
in abundance, indicating that dry river bed assemblages are not simply subsets of riparian assemblages. Some spatial patterns
in invertebrate assemblages were associated with environmental variables (irrespective of habitat type), but these associations
were statistically weak. We suggest that dry river beds are unique habitats in their own right. We discuss potential human
stressors and management issues regarding dry river beds and provide recommendations for future research. 相似文献
4.
David Dunkerley 《水文研究》2000,14(4):669-678
The interception storage capacity has been measured for a range of dryland plants. Interception losses over time, however, arise in rain events that deliver either less or more than the canopy capacity. The fate of water in these cases depends on the efficiency with which the intercepted water is returned to the atmosphere by evaporation from the plant canopies. Two primary methods to estimate interception losses are (i) calibrated process‐based models of interception and evaporative loss and (ii) direct measurement. Models have been applied only rarely to dryland plant communities, and direct measurement techniques are in need of additional testing and refinement. Most published estimates of interception loss in dryland plant communities therefore appear to be based upon inadequate data and methods. Research needs in this area are highlighted. Copyright © 2000 John Wiley & Sons, Ltd. 相似文献
5.
Models of habitat connectivity, and how network structure and connectivity affects resident populations, are increasingly being developed for terrestrial habitat networks. Rivers, unlike many terrestrial habitat networks, follow a rigid hierarchical branching structure to form dendritic networks. It has been hypothesised that this unique structure must have implications for population processes. We developed a theoretical model to relate local-scale habitat quality and connectivity to landscape-scale population dynamics of mobile organisms (e.g. fish, aquatic invertebrates). River networks were modelled as directed graphs, with nodes being habitat patches, and edges the connections between them. Using population simulation analyses, we investigated the effects of network structure on population abundance and persistence. Network structural complexity affected landscape-scale population abundance, but the apparent effect depended upon how structure was quantified. There were no noticeable effects of dendritic network structure on population persistence. Previous research on the effects of habitat network structure on population persistence has used metapopulation patch occupancy models, which do not directly consider population dynamics. Our results show that spatially-explicit population modelling is possible, and that it provides information beyond that possible with patch occupancy models (e.g. population abundance). More importantly, it calls into question whether metapopulation models provide an adequate representation of population dynamics in dendritic habitat networks. 相似文献
6.
《Limnologica》2015
Abiotic variability is known to structure lotic invertebrate communities, yet its influence on lentic invertebrates is not clear. This study tests the hypothesis that variability of nutrients and macro-ions are structuring invertebrate communities in agricultural drainage ditches. This was determined by investigating invertebrate adaptations to disturbance using insect life-history strategies. Many low-lying agricultural areas contain drainage ditches which potentially provide suitable habitat for aquatic invertebrates. In the province of North Holland (The Netherlands) the extensive network of eutrophic ditches are hydrologically managed, creating seasonal variability of water quality arising from agricultural run-off and the inlet of mineral rich, river derived water. This temporal variability was analysed from monitoring data, collected over a 7 month period (February till August) and covering 84 ditches in three soil regions; sand, clay and peat. Invertebrate diversity was determined as local (α diversity), regional (γ diversity) and species-turnover (β diversity). We ran canonical correspondence analysis and linear mixed models to determine correlations between invertebrate diversity, functional community composition and specific abiotic parameters, including variability (expressed as the Median Absolute Deviation). Invertebrate α diversity was positively correlated to variability in water transparency and negatively correlated to average pH, with the two parameters reflecting a water quality gradient in the environment. Insect life-history strategies expressed adaptations to abiotic variability and harsh (eutrophic) conditions. These adaptations were mainly achieved through good dispersal abilities and developmental trade-offs. The results support measures to reduce influxes of excess nutrients to this network of ditches. 相似文献
7.
H.K. Acharya 《Physics of the Earth and Planetary Interiors》1981,24(1):53-65
The distribution of large shallow earthquakes (magnitude ?5.5) in central Luzon, Philippines, related to the underthrusting of the Eurasian plate, is examined by the technique of pattern recognition. The objective of the study is (1) to forecast restricted zones of seismic activity, (2) to determine geological features which, in combination, are associated with the earthquakes in the environment of subduction, and (3) to determine whether more insight into regional seismicity can be gained by pattern recognition studies than by conventional seismicity studies. It appears from this analysis that large earthquakes occur (a) in a zone between the shallower portion of Manila Trench on its landward side and the belt of volcanoes and (b) on large strike-slip faults in the region such as Verde Island Passage fault and the Philippine fault. In these zones, large earthquakes occur at locations identified by large topographic relief in the vicinity and a high degree of fractured crust. In contrast to characteristics in California and central Asia, the intersection of faults nearby is not a major characteristic for large earthquakes in and near central Luzon. Topography and degree of fractured crust are important characteristics in all areas studied so far. Several earthquakes which are known to have occurred were considered unknown, and control experiments were carried out to determine whether the locations of these earthquakes would be identified as having potential for large earthquakes. The results of control experiments indicate that the pattern recognition technique is fairly successful in spatial forecasting if the known historical record is assumed almost complete for various major zones (85% in this case). It fails to forecast if information is totally lacking about earthquake activity on a tectonic feature. In the present study, a control experiment was able to correctly identify the locations of two of the largest earthquakes known to have occurred in the area. It was better able to identify locations of large earthquakes than a simple contouring of known earthquake locations would suggest. 相似文献
8.
9.
为进一步提高大地电磁非线性反演的稳定性、运算效率及准确度,将遗传神经网络算法引入大地电磁反演.首先针对大地电磁二维地电模型建立BP（Back Propagation）神经网络基本框架进行学习训练,网络输入为已知地电模型的视电阻率参数,输出为该地电模型参数;再利用遗传算法对神经网络学习训练过程进行优化,计算出多种地电模型网络连接权值和阈值的最优解;最后将最优连接权值和阈值对未知模型进行反演测试,网络输入为未知地电模型的视电阻率参数,输出为该地电模型参数.模型实验表明：遗传神经网络算法充分结合了遗传算法的全局寻优性和神经网络的局部寻优性,相比单一神经网络算法,在网络学习训练中提高了解的收敛成功率和计算速度,在反演测试中能更准确地逼近真实模型.将遗传神经网络算法与最小二乘正则化反演进行对比,理论模型和实测数据都验证了遗传神经网络算法在大地电磁反演中的可行性和有效性. 相似文献
10.
A dynamic simulation model of the Ankara central wastewater treatment plant (ACWTP) was evaluated for the prediction of effluent COD concentrations. Firstly, a mechanistic model of the municipal wastewater treatment process was developed based on Activated Sludge Model No. 1 (ASM1) by using a GPS‐X computer program. Then, the mechanistic model was combined with a feed‐forward back‐propagation neural network in parallel configuration. The appropriate architecture of the neural network models was determined through several iterative steps of training and testing of the models. Both models were run with the data obtained from the plant operation and laboratory analysis to predict the dynamic behavior of the process. Using these two models, effluent COD concentrations were predicted and the results were compared for the purpose of evaluation of treatment performance. It was observed that the ASM1 ANN model approach gave better results and better described the operational conditions of the plant than ASM1. 相似文献
11.
Elaine M. FitzGerald Christopher J. Bean & Ronan Reilly 《Geophysical Prospecting》1999,47(6):1031-1044
Borehole-wall imaging is currently the most reliable means of mapping discontinuities within boreholes. As these imaging techniques are expensive and thus not always included in a logging run, a method of predicting fracture frequency directly from traditional logging tool responses would be very useful and cost effective. Artificial neural networks (ANNs) show great potential in this area. ANNs are computational systems that attempt to mimic natural biological neural networks. They have the ability to recognize patterns and develop their own generalizations about a given data set. Neural networks are trained on data sets for which the solution is known and tested on data not previously seen in order to validate the network result. We show that artificial neural networks, due to their pattern recognition capabilities, are able to assess the signal strength of fracture-related heterogeneity in a borehole log and thus fracture frequency within a borehole. A combination of wireline logs (neutron porosity, bulk density, P-sonic, S-sonic, deep resistivity and shallow resistivity) were used as input parameters to the ANN. Fracture frequency calculated from borehole televiewer data was used as the single output parameter. The ANN was trained using a back-propagation algorithm with a momentum learning function. In addition to fracture frequency within a single borehole, an ANN trained on a subset of boreholes in an area could be used for prediction over the entire set of boreholes, thus allowing the lateral correlation of fracture zones. 相似文献
12.
The effect of shrub canopy upon surface temperatures and evaporation in the Negev Desert 总被引：2，自引：0，他引：2
Giora J. Kidron 《地球表面变化过程与地形》2009,34(1):123-132
Although known as ‘islands of fertility’ or ‘resource islands’, information regarding the effect of shrubs upon microclimate in deserts is scarce. Here we report on measurements of evaporation and temperatures that were carried out in and around a pair of shrubs at the Nizzana research site in the western Negev Desert during 1993–94 and during the growing season (November–March) of 1994–95 and 1996–1997. Whereas evaporation was measured monthly using mini‐atmometers (10 cm diameter and 10 cm tall) at an exposed site and under and around the shrub (at the eastern, southern, western and northern aspects), temperature was measured under a shrub canopy, at its northern aspect, and at an exposed habitat. Evaporation was aspect dependent with increasing rates in the following order: exposed > south‐facing > west‐facing ≈ east‐facing > north‐facing > under canopy. Except from the northern aspect, the under‐canopy habitat showed substantially lower rates of evaporation in comparison with all other habitats. The differences between the under‐canopy and the exposed habitat were larger during wintertime (with the under‐canopy habitat having 0·53 times the evaporation rate than that of the exposed habitat) although higher differences in temperatures characterized both habitats in summertime (up to 14·4 °C in summer as compared with 6·9 °C only in winter). The results were explained by extended surface wetness that characterized the under‐canopy habitat following rainstorms. While already being dried out at the exposed habitat, surface wetness at the under canopy habitat persisted for several days afterwards, resulting, following one rainstorm, in vapour pressure of 2·15–2·39 kPa in comparison with only 0·82–0·83 kPa of the exposed habitat. The substantially lower evaporation rates that characterize the under‐canopy habitat may thus play a pivotal role in providing preferential conditions for lush under‐canopy annual growth. Copyright © 2008 John Wiley and Sons, Ltd. 相似文献
13.
王道阔 《CT理论与应用研究》2012,21(1):43-52
本文利用计算机辅助进行在役管线焊故障缝缺陷检测,在缺陷特征提取中提出圆形度、长宽比、填充度、尖部尖锐度、对称度、灰度比以及缺陷的重心坐标相对焊缝中心的位置等7个参数作为缺陷的特征值,可有效地分类识别不同故障缺陷。在缺陷分类的解决方案上,采用具有自组织、自适应的3层前馈式神经网络,运用改进的BP算法,以焊缝缺陷的特征参数作为神经网络的训练样本。本文还通过实验的方法,分析了初始权值、隐含层的神经元数量、动量系数、误差水平及学习速率对网络训练的影响。 相似文献
14.
D. L. Dunkerley 《水文研究》2008,22(12):1985-1995
Interception losses from the canopies of dryland plant taxa remain poorly understood, especially the relative contributions of intra‐storm and post‐storm evaporative losses. Employing a new measuring apparatus, this study uses low‐intensity simulated rain, matched to the properties of local rain, to explore interception processes in bluebush shrubs at an Australian dryland site. Five shrub specimens were exposed to simulated rain for 60–90 min. Experiments were repeated at three rainfall intensities (10, 15, and 20 mm h?1). Canopy evaporation was found from the difference between the flux of water delivered to the shrub and the flux of throughfall, once equilibrium had been established. The results show that evaporation from the wet foliage during rain proceeds at an average rate of 3·6 mm h?1. This figure is for relatively cool spring‐season conditions; evaporation rates in hot summer conditions would be larger. Intra‐storm evaporation is shown to exceed post‐rain evaporation from interception storage on the shrubs, and this differentiates dryland shrub interception processes from those of the better‐studied wet forest environment. Implications of the high dryland shrub canopy evaporation rates for aspects of dryland ecology are highlighted. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
15.
北黄海盆地是我国近海海域尚未取得油气勘探突破的盆地之一.在海洋环境中应用海底油气藏的烃渗漏现象寻找油气有利区具有良好应用前景,为了给该区的含油气远景评价及下一步油气勘探缩小靶区提供地球物理依据,本文利用磁法这一经济、有效的油气渗漏异常地球物理判别手段,开展了识别海底烃渗漏引发磁异常的方法研究.给出一种根据“有导师”的模式识别技术,在充分利用磁异常多种数值特征及纹理特征的基础上,提取烃渗漏蚀变带磁异常的方法.通过已知约束信息（如见油井位等）的点、线、面三种基元及其邻近数据网格点组成基类,将其提取的模式或特征向量作为待识别异常匹配或学习的模板,利用加权欧氏距离函数计算待识别异常特征向量与模板向量之间的相似性,进行模式匹配,从而识别出与模板相似程度较高的异常.应用此方法圈定了北黄海盆地的烃渗漏“磁亮点”分布,从“磁亮点”异常区与中生代地层的分布以及地球化学异常（低层大气烃类检测和海底微生物异常）的对应情况来看,表明该识别方法是识别烃渗漏弱磁异常的一种有效手段.对研究区构造特征、磁异常及地球化学异常特征的综合分析表明,位于北黄海研究区东部和北部的“磁亮点”异常区可能是北黄海盆地较好的含油气远景区. 相似文献
16.
人工神经网络及其在地震预报中的应用 总被引：7，自引：3，他引：7
文概述了人工神经网络的原理和算法，利用１９８５－１９９２年全国年度趋势会商报告的资料来训练的检验神经网络。结果表明，网络经训练后具有较高的识别能力，在地震预报中有深入研究和进一步应用的价值。最后讨论了神经网络中几个重要参数的取值问题。 相似文献
17.
This paper proposes the use of neural networks to predict damage due to earthquakes from the indices of recorded ground motion. Since the relationship between ground motion indices and resulting damage is difficult to express in mathematical form, neural networks are conveniently applied for this problem. Simulated earthquake ground motions are used to have a well-distributed data set and the ductility factor from non-linear analysis of two single-degree-of-freedom structural models is used to represent the damage. A sensitivity analysis procedure is described to identify qualitatively the input parameters that have a greater influence on the damage. The result of the trained neural network is then verified by using several recorded earthquake ground motions. It is found that some instability in the prediction can occur. Instability occurs when input values exceed the range of the training data. The neural network model using PGA and SI as input give the best performance in the recall tests using actual earthquake ground motion, demonstrating the usefulness of neural network models for the quick estimation of damage through earthquake intensity monitoring. 相似文献
18.
Comparative study of morphometric measurements was undertaken on populations of Palaemonetes antennarius from two freshwater habitat zones (lacustrine pelagic and lacustrine littoral) and from the fluvial littoral habitat zone of three estuaries of north-western Greece. Multivariate statistical analyses (principal component analysis and discriminant function analysis) revealed clear morphometric differences between sexes and sampling sites. The observed differences are expressed mainly thought the measurements related to the body heights (carapace height and second pleon height), as a result of sexual dimorphism, High values for the female body heights seem to be correlated to specific fecundity profile and reproductive strategy. On the other hand, morphometrical variables related mainly to body lengths, such as rostral, telson and pleon lengths, were observed to be correlated to the study sites. Characters related to the summing capacity (telson length, telson width and pleon lengths) were generally found to have higher values in the specimens from habitats with high reophilic profile. 相似文献
19.
Yoon-Seok Timothy Hong Byeong-Cheon Paik 《Stochastic Environmental Research and Risk Assessment (SERRA)》2012,26(5):695-707
Developing a mathematical model for predicting fecal coliform bacteria concentration is very important because it can provide a basis for water quality management decisions that can minimize microbial pollution risk to the public. This paper introduces a hybrid modeling methodology which is a combined use of a neural network-based pattern analysis and an evolutionary process model induction system. The neural network-based pattern analysis technique is applied to extract knowledge on inter-relationships between fecal coliform concentrations and other measurable variables in a sewer system. Based on the result of neural network-based pattern analysis, an evolutionary process model induction system is used to derive mathematical inference models that can predict fecal coliform bacteria concentration from easily measurable variables instead of directly measuring fecal coliform bacteria concentration in a sewer system. The neural network-based pattern analysis extracts that temperature and ammonia concentration are the most important driving forces leading to an increase in fecal coliform bacteria concentration in the sewer system at Paraparaumu City, New Zealand. Fecal coliform bacteria concentration is also positively correlated with dissolved phosphorus and inversely with flow rate. The multivariate inference models that are able to predict fecal coliform bacteria concentration are successfully derived as functions of flow rate, temperature, ammonia, and dissolved phosphorus in the form of understandable mathematical formulae using the evolutionary process model induction system, even if a priori mathematical knowledge of the dynamic nature of fecal coliform bacteria is poor. The multivariate inference models evolved by the evolutionary process model induction system produce a slightly better performance than the multi-layer perceptron neural network model. 相似文献
20.
J. Uria-Diez R. Ib��?ez J. Mateu 《Stochastic Environmental Research and Risk Assessment (SERRA)》2013,27(1):59-76
This study attempts to understand the dependence on abiotic factors and on the biotic process of the population development. We used three spatial point process models (Poisson, Area-Interaction and shot-noise Cox processes) in both homogenous and inhomogeneous versions to model the distribution of three Carex remota cohorts in wet zones of a temperate forest in the north of Spain. The cohorts studied were adults and seedlings born in two consecutive years. With the use of these models we are able to simulate separately and jointly the effect on plant distribution of a homogeneous or heterogeneous habitat, and the absence or presence of some biotic processes, as seed dispersal and/or density-dependent interactions. The result of the bivariate function analysis does not reveal sufficient evidences, but suggests a weak positive relation between adults and seedlings that survived a dry period in the first summer. Models from the three cohorts show a decreasing degree of clustering from seedlings to adults. Besides, the results show that the importance of the main factors that explain the population structure changes along the development of Carex stages. Compared to seedlings, the adults pattern shows an increasing dependence on abiotic factors. 相似文献