整合分析中的非参数检验:重复取样检验法的实例应用

整合分析(meta-analysis)是对同一主题下多个独立实验结果进行综合的统计学方法。非参数检验整合分析——重复取样检验(resampling test)不考虑原文献数据的分布形式，故可在不知原文献数据分布形式时使用。其中的靴襻法(bootstrap)可用来给出总效应值的置信区间，但不能检验组内异质性是否显著。靴襻法与随机检验法(randomization test)可以有效弥补这一缺失，判断出组间差异性是否显著。实例应用表明，重复取样检验没有参数检验保守，又与参数检验的结果差异较小。     

产业生态系统多尺度能值整合评价方法

能值分析方法为自然环境资源与人类社会、经济的统一评价提供了新的思路,但面对当今产业生态学发展的实践需求,在多尺度整合分析、动态模型构建等方面仍显薄弱,需要与经济学等其他学科相对成熟的分析方法与模型加以整合。文章以能值综合方法为核心介质,从成本分析与效果分析的整合、能值分析与区域经济分析的整合,以及能值分析表与投入-产出矩阵模型的整合三个方面进行了产业生态学的能值整合研究方法的具体构建,以促进能值理论方法与产业生态学研究需求的进一步耦合。     

能值理论研究中存在的几个问题探讨

能值理论与研究方法是当前生态经济学研究中的一个热点问题.被认为是连接生态学与经济学的桥梁,具有重大的理论和实践意义.尽管能值分析有效的将自然环境的价值纳入了产品的生产,更能真实地揭示产品的真实价值,从而克服了传统能量分析和经济分析的诸多缺陷.但其在理论和研究方法仍存在一些不足之处.综合国内外有关能值理论与研究方法的相关文献,对当前能值理论研究中能值转化率的计算问题、多产品或复合产品系统的能值流计算问题、能值价值论与市场价值论结合问题、能值与可持续发展研究问题等几个方面进行了探讨.     

生态经济系统的一种整合评价方法:能值理论与分析方法

能值理论与分析方法是目前系统生态学和生态经济学发展的新成果，为复合生态系统开拓了一条定量研究途径，是连接生态学和经济学的桥梁。其理论研究与实践应用具有重要的科学意义和应用意义。文章论述了能值分析理论与分析方法的产生背景、过程、主要的基本概念、特点，指出了其需要解决的问题；并以种植业系统为例，简要介绍了能值分析的基本方法和步骤以及能值指标的计算。     

克隆植物生理整合作用的研究方法及其应用

生理整合作用是克隆植物的一个重要特征,克隆植物所表现出的许多独特的生态学行为,均与其所具有的生理整合效应密切相关.本文总结并分析了迄今为止在研究克隆植物生理整合作用方面所采用的各种方法,并将其归纳为直接和间接方法两个大类.通过这些研究方法的综合运用,克隆植物生理整合效应的机制、格局及其影响因素可以得到更加深入的揭示.在不断深化和拓展现有研究方法的基础上,今后在克隆植物生理整合效应的研究方面,还应较多地关注更为精确的研究方法,以及野外或自然条件下的实地研究.参104     

氮沉降下西南亚高山针叶林生长的养分限制特征

长期氮(N)沉降及其诱导的N、磷(P)养分平衡性对森林生长与生产力的生态反馈效应已成为当前森林生态学研究的前沿与热点,但目前大多研究主要基于已有文献数据整合分析,而缺乏野外原位系统性研究与试验证据.以西南亚高山两种典型人工针叶林——云杉(Picea asperata)林和华山松(Pinus armandii)林为对象,...     

国外景观生态学研究的最新动向及进展

以1995年3次国际景观生态学大会、1995年和1996年美国第10届和第11届景观生态学大会以及近两年的文献为依据，综述了国外景观生态学研究的最新的进展，景观生态学是一门内容丰富的宏观应用生态学，除了景观结构、功能与变化、景观异质性、尺度等传统的研究热点外，生物多样性也明显地成为研究热点之一，在进行自然景观或景观的自然方面研究的同时，明显地有研究文化景观或综合研究自然生态系统与人文生态系统，实现人文科学和自然科学交叉的趋势。     

城市复合生态系统能值整合分析研究方法论

系统阐述了城市复合生态系统能值分析的基本概念原理与方法步骤,总结了城市可持续发展综合能值评价指标体系。在此基础上,从能值转换率的积累和统一、多尺度研究的整合与尺度推绎、城市功能流分析与空间结构分析的整合、能值成本价值论与使用(市场)价值论的整合等方面,讨论了能值研究方法在城市生态系统研究中的应用前景和发展方向。     

有机毒物对水蚤的急性毒性

对水蚤的毒笥试验数据是被广泛用于评价化合物水生生态效应的重要依据，检测有机化合物的毒性时，需特别注意待测物的难溶性，挥发性及易光解性，检测了多种氯代芳烃的ＥＣ５０值，其１８ｈ的结果与２４ｈ的结果相近，检测了２４种硝基芳烃的毒性，不同方法计算的ＥＣ５０值一致。     

城市生态系统代谢的能值研究进展

城市环境问题的深层原因是城市代谢过程出现了问题.城市代谢研究,是分析城市在人类各种活动影响下,如何将取自生态系统的物质和能量进行转换、利用与处理的过程,成为评价城市可持续发展的重要依据.早在19世纪末,就有有关能量流分析社会代谢的概念;近期最具代表性的是HowardT.Odum.首先从城市代谢研究的兴起和发展出发,然后分环境评价、空间层面、动态模拟三方面,对Odum的能值方法在城市代谢分析中的应用进行了回顾.环境评价方面以生态经济学为理论基础,提出发展具有生物物理基础的能值方法,对城市代谢的生态评估更为恰当;空问层面结合景观生态学,为区域空间规划提供了参考,并指出土地利用变迁与社会代谢间的相关性研究为当前的核心问题;动态层面仍以系统生态学建立整合性系统模型为基础,但空间系统模拟方法的发展仍处于起步阶段.各个学科与方法的整合促进了城市代谢研究的进一步深化.最后,建议未来应用能值研究城市代谢的4个研究方向有:(1)城市代谢与可持续发展之间相互关系的研究;(2)城市代谢与土地利用变迁相互驱动的模型发展;(3)基于代谢过程的城市管理对策研究;(4)全球环境变迁对土地利用和城市代谢的影响.     

Untested assumptions about within-species sample size and missing data in interspecific studies

Phylogenetic comparative studies rely on species-specific data that often contain missing values and/or differ in sample size among species. These phenomena may violate statistical assumptions about the non-random variance component in sampling effort. A major reason why this assumption is often not fulfilled is because the probability of being sampled (i.e., being captured or observed) may depend on species-specific characteristics. Here, we test this assumption by using information on within-species sample sizes and missing data from five independent comparative datasets of European birds. First, we show that the two estimates of data availability (missing values and within-species sample size) are positively correlated and are associated with research effort in general (the number of papers published). Second, we demonstrate biologically meaningful relationships between data availability and phenotypic traits. For example, population size, risk-taking, and habitat specialization independently predicted within-species sample size. The key determinants of missing data were population size and distribution range. However, data availability was not structured by phylogenetic relationships. These results indicate that the accuracy of sampling is repeatable and distributed non-randomly among species, as several species-specific attributes determined the probability of observation. Therefore, data availability seems to be a species-specific trait that can be shaped by ecology, life history, and behavior. Such relationships raise issues about non-random sampling, which requires attention in comparative studies.     

Measuring diversity: the importance of species similarity

Realistic measures of biodiversity should reflect not only the relative abundances of species, but also the differences between them. We present a natural family of diversity measures taking both factors into account. This is not just another addition to the already long list of diversity indices. Instead, a single formula subsumes many of the most popular indices, including Shannon's, Simpson's, species richness, and Rao's quadratic entropy. These popular indices can then be used and understood in a unified way, and the relationships between them are made plain. The new measures are, moreover, effective numbers, so that percentage changes and ratio comparisons of diversity value are meaningful. We advocate the use of diversity profiles, which provide a faithful graphical representation of the shape of a community; they show how the perceived diversity changes as the emphasis shifts from rare to common species. Communities can usefully be compared by comparing their diversity profiles. We show by example that this is a far more subtle method than any relying on a single statistic. Some ecologists view diversity indices with suspicion, questioning whether they are biologically meaningful. By dropping the naive assumption that distinct species have nothing in common, working with effective numbers, and using diversity profiles, we arrive at a system of diversity measurement that should lay much of this suspicion to rest.     

Population Variability and Extinction Risk

Abstract: Population models generally predict increased extinction risk (ER) with increased population variability (  PV  ), yet some empirical tests have provided contradictory findings. We resolve this conflict by attributing negative measured relationships to a statistical artifact that arises because PV tends to be underestimated for populations with short persistence. Such populations do not go extinct quickly as a consequence of low intrinsic variability; instead, the measured variability is low because they go extinct so quickly. Consequently, any underlying positive relationship between PV and ER tends to be obscured. We conducted a series of analyses to evaluate this claim. Simulations showed that negative measured relationships are to be expected, despite an underlying positive relationship. Simulations also identified properties of data, minimizing this bias and thereby permitting meaningful analysis. Experimental data on laboratory populations of a bruchid beetle (Callosobruchus maculatus) supported the simulation results. Likewise, with an appropriate statistical approach (Cox regression on untransformed data), reanalysis of a controversial data set on British island bird populations revealed a significant positive association between PV and ER (p = 0.03). Finally, a similar analysis of time series for naturally regulated animal populations revealed a positive association between PV and quasiextinction risk (p < 0.01). Without exception, our simulation results, experimental findings, reanalysis of published data, and analysis of quasiextinction risk all contradict previous reports of negative or equivocal relationships. Valid analysis of meaningful data provides strong evidence that increased population variability leads to increased extinction risk.     

Statistische Aus- und Bewertung immissionsbedingter Bodenbelastungen

The contamination of soils with pollutants by human activities has increased over a period of some decades. Deposited pollutants are immobilized in different ways depending on their chemical properties, or they are biologically available. This potential hazard requires a permanent control. An extensive investigation of topsoil in the surroundings of the fertilizer factory at Dorndorf-Steudnitz (Thuringia) was carried out to assess the size and extension of contamination and to estimate the potential risk which originates from the deposited pollutants. The fertilizer factory at Dorndorf-Steudnitz was one of the biggest dust emission sources in the middle part of the Saale river valley. Considerable damages of vegetation could be noticed already in the seventies and eighties. The trees and other plants in the neighbourhood of the factory died. The loadings of the investigated area may be attributed to a direct influence of gaseous and also of dustlike pollutants on the vegetation and resorption from the soil. Frequently, the content of pollutants in soils varies considerably. For this reason a univariate statistical evaluation of the data is not usually adequate. The use of geostatistical methods permits the characterization of the spatial structure of the investigated area and the undistorted assessment of the pollutant contents at unsampled points. The degree and extension of the contamination can be determined on the basis of the kriging estimation. The classification of analyzed features in regard to common sources of contamination can be realized by means of methods of multivariate data analysis.     

Formal modelling of predator preferences using molecular gut-content analysis

The literature on modelling a predator’s prey selection describes many intuitive indices, few of which have both reasonable statistical justification and tractable asymptotic properties. Here, we provide a simple model that meets both of these criteria, while extending previous work to include an array of data from multiple species and time points. Further, we apply the expectation–maximisation algorithm to compute estimates if exact counts of the number of prey species eaten in a particular time period are not observed. We conduct a simulation study to demonstrate the accuracy of our method, and illustrate the utility of the approach for field analysis of predation using a real data set, collected on wolf spiders using molecular gut-content analysis.     

Using simulation to explore the functional relationships of terrestrial carnivore population indices

Population indices based on visits to detection stations commonly are used to monitor wildlife populations. Inferences about populations are based on 1 of 2 measures: (1) change in the proportion of stations visited at least once or (2) change in the cumulative number of visits by unique individuals. The functional relationships between index responses and population density is poorly understood and can lead to misinterpretation of index data when an incorrect functional relationship (e.g. linear) is assumed. We created a flexible simulation environment to study the response of detection-based population indices under a wide variety of conditions meant to reflect species life history and study design. Proportional indices exhibited non-linear saturating responses to changes in population density while cumulative indices responded linearly. Shapes of responses were functions of home range sizes, individual detection probabilities, and spatial arrangement of animals and sampling stations. Non-linear relationships of proportional indices lead to under-estimation of mean population density when data are aggregated from multiple detection stations deployed in a heterogeneous landscape. Cumulative indices have significant statistical advantages over proportional indices including smaller sample sizes required to detect density change, linearity, consistent index responses across a wide range of densities, and ability to aggregate data to meet minimum sample size requirements. Our simulation provides a flexible tool for the interpretation of station-based population indices.     

Species distribution models and ecological theory: A critical assessment and some possible new approaches

Given the importance of knowledge of species distribution for conservation and climate change management, continuous and progressive evaluation of the statistical models predicting species distributions is necessary. Current models are evaluated in terms of ecological theory used, the data model accepted and the statistical methods applied. Focus is restricted to Generalised Linear Models (GLM) and Generalised Additive Models (GAM). Certain currently unused regression methods are reviewed for their possible application to species modelling.A review of recent papers suggests that ecological theory is rarely explicitly considered. Current theory and results support species responses to environmental variables to be unimodal and often skewed though process-based theory is often lacking. Many studies fail to test for unimodal or skewed responses and straight-line relationships are often fitted without justification.Data resolution (size of sampling unit) determines the nature of the environmental niche models that can be fitted. A synthesis of differing ecophysiological ideas and the use of biophysical processes models could improve the selection of predictor variables. A better conceptual framework is needed for selecting variables.Comparison of statistical methods is difficult. Predictive success is insufficient and a test of ecological realism is also needed. Evaluation of methods needs artificial data, as there is no knowledge about the true relationships between variables for field data. However, use of artificial data is limited by lack of comprehensive theory.Three potentially new methods are reviewed. Quantile regression (QR) has potential and a strong theoretical justification in Liebig's law of the minimum. Structural equation modelling (SEM) has an appealing conceptual framework for testing causality but has problems with curvilinear relationships. Geographically weighted regression (GWR) intended to examine spatial non-stationarity of ecological processes requires further evaluation before being used.Synthesis and applications: explicit theory needs to be incorporated into species response models used in conservation. For example, testing for unimodal skewed responses should be a routine procedure. Clear statements of the ecological theory used, the nature of the data model and sufficient details of the statistical method are needed for current models to be evaluated. New statistical methods need to be evaluated for compatibility with ecological theory before use in applied ecology. Some recent work with artificial data suggests the combination of ecological knowledge and statistical skill is more important than the precise statistical method used. The potential exists for a synthesis of current species modelling approaches based on their differing ecological insights not their methodology.     

石油污染对土壤-植物系统的生态效应

伴随着石油的工业化生产和利用,石油污染已经成为一个严重的环境问题.本文从土壤、植物个体、植物群落与生态系统等层次对石油污染的生态效应进行了系统总结.含有多环芳烃(Polycyclic aromatic hydrocarbons,PAHs)、苯系物(Benzene、toluene、ethylbenzene和xylene,BTEX)等多种有毒物质的石油及其化工产品进入土壤-植物系统后会发生迁移.这不仅对土壤-植物系统的组成、结构、功能和服务产生影响,也会通过食物链危害人类健康.石油污染影响土壤水分状况、孔隙度等物理性质,土壤碳含量、养分含量等化学性质,以及土壤微生物群落组成和多样性、土壤酶活性等生物学性质.通常,石油污染会对大多数植物形成氧化胁迫,影响细胞膜透性,影响光合作用等生理活动,抑制植物生长,影响植物萌发、开花和结实.由于石油污染对植物个体的不同效应以及植物个体对石油污染的不同响应,石油污染对植物群落的影响存在3种基本模式,并最终导致植物群落生物量下降,物种多样性降低,植被盖度降低.进一步影响生态系统的生产力、稳定性和健康,最终危及生态系统的功能和服务.利用微生物、植物及其联合体菌根可以对石油污染物进行生物修复和降解,添加外源营养物质和通气等措施可以强化生物修复过程.应用植被指数和红边效应等遥感方法进行石油污染的生态效应监测具有较大的潜力.总之,如何把土壤-植物系统各水平上不同指标对石油污染物的响应与石油污染的生态效应联系起来,是目前石油污染生态效应研究的重点和难点之一.因此,亟需开展多尺度的系统研究,把室内控制实验、野外控制实验和野外调查有机地结合起来,构建多层次的石油污染标志物体系,全面认识石油污染对土壤-植物系统的生态效应,为石油污染的生态风险评价、治理和控制提供理论基础和实践指导.