Measuring the importance of competition: a new formulation of the problem

1.  Currently, there is a debate among plant ecologists on the concepts of the intensity of competition and the importance of competition, which is central to many issues of modern plant population ecology and plant community ecology.
2.  It is problematic that the current measures of intensity and importance of competition, typically, are reported as dimensionless indices because they hide the fact that both indices are functions of plant density and the level of the environmental gradient.
3.  Here, a new formulation of the concepts is suggested, which explicitly highlights the functional dependencies on plant density and the level of the environmental gradient. The new measures are a generalization of the previous indices and correspond to the previous indices in the case of a simple experimental design.
4.  The suggested measures of the intensity and importance of competition are exemplified using data from a response surface competition experiment between Agrostis capillaris and Festuca ovina along a herbicide gradient, where the expected clear effect of plant density was demonstrated.
5.   Synthesis . As the suggested measures of the intensity and importance of competition explicitly highlight the functional dependencies on plant density and the level of the environmental gradient, we think that they will help to ensure a closer connection between experimental plant ecology and the attempts to model plant populations and communities.     

An information-theoretical measure of taxonomic diversity

Traditional diversity indices are computed from the abundances of species present and are insensitive to taxonomic differences between species. However, a community in which most species belong to the same genus is intuitively less diverse than another community with a similar number of species distributed more evenly between genera. In this paper, we propose an information-theoretical measure of taxonomic diversity that reflects both the abundances and taxonomic distinctness of the species. Unlike previous measures of taxonomic diversity, such as Rao's quadratic entropy, in this new measure the analyzed taxonomic properties are associated with the single species instead of species pairs.     

A sensitivity analysis of the volumetric spatial decomposition algorithm

Recently, we proposed a new computational approach for the volumetric spatial decomposition of a three-dimensional bone structure into its basic rod and plate elements. This method was based on an image skeletonization approach, where two model parameters were used to identify an ideal skeleton. The goal of this study was to estimate the sensitivity of local morphometric indices to these two model parameters. Our results showed that the rod derived indices behaved more smoothly than plate derived indices, which suggests that rod derived indices are more trustworthy. The results also demonstrated that it was reasonable to reduce the model to only one parameter by setting the noise parameter n to twice the value of the slenderness parameter s. In conclusion, we found that local morphometric indices are reliable measures showing large differences between samples and thus may shed new light on structural differences of trabecular bone in a local fashion by adequately choosing one single optimization parameter.     

Disturbance–diversity models: what do they really predict and how are they tested?

The intermediate disturbance hypothesis (IDH) and the dynamic equilibrium model (DEM) are influential theories in ecology. The IDH predicts large species numbers at intermediate levels of disturbance and the DEM predicts that the effect of disturbance depends on the level of productivity. However, various indices of diversity are considered more commonly than the predicted number of species in tests of the hypotheses. This issue reaches beyond the scientific community as the predictions of the IDH and the DEM are used in the management of national parks and reserves. In order to compare responses with disturbance among measures of biodiversity, we used two different approaches of mathematical modelling and conducted an extensive meta-analysis. Two-thirds of the surveyed studies present different results for different diversity measures. Accordingly, the meta-analysis showed a narrow range of negative quadratic regression components for richness, but not evenness. Also, the two models support the IDH and the DEM, respectively, when biodiversity is measured as species richness, but predict evenness to increase with increasing disturbance, for all levels of productivity. Consequently, studies that use compound indices of diversity should present logical arguments, a priori, to why a specific index of diversity should peak in response to disturbance.     

Patterns of sensitivity of association measures in numerical taxonomy

Numerical taxonomy and the related methods of multidimensional scaling (MDS) have been applied in a wide range of disciplines in the last twenty-five years. A common feature has been the initial derivation of a measure of association or proximity among pairs of objects from a multivariate data matrix. Although a large number of measures are in use, there has been little systematic study of the sensitivities of these measures to different aspects of character data. I report here a general model, for a class of these measures, that reveals basic patterns of sensitivity that underlie a wide variety of common measures and shows that there is a continuum of potential association measures which exhibit useful combinations of sensitivities. I distinguish between “separation” sensitive and “minimum value” sensitive measures and describe a new measure that is intermediate in exhibiting both minimum value and separation sensitivity. The utility of this new type of measure in three disciplines—ecology, psychology, and systematics—is briefly described.     

Functional rarefaction: estimating functional diversity from field data

Studies in biodiversity-ecosystem function and conservation biology have led to the development of diversity indices that take species' functional differences into account. We identify two broad classes of indices: those that monotonically increase with species richness (MSR indices) and those that weight the contribution of each species by abundance or occurrence (weighted indices). We argue that weighted indices are easier to estimate without bias but tend to ignore information provided by rare species. Conversely, MSR indices fully incorporate information provided by rare species but are nearly always underestimated when communities are not exhaustively surveyed. This is because of the well-studied fact that additional sampling of a community may reveal previously undiscovered species. We use the rarefaction technique from species richness studies to address sample-size-induced bias when estimating functional diversity indices. Rarefaction transforms any given MSR index into a family of unbiased weighted indices, each with a different level of sensitivity to rare species. Thus rarefaction simultaneously solves the problem of bias and the problem of sensitivity to rare species. We present formulae and algorithms for conducting a functional rarefaction analysis of the two most widely cited MSR indices: functional attribute diversity (FAD) and Petchey and Gaston's functional diversity (FD). These formulae also demonstrate a relationship between three seemingly unrelated functional diversity indices: FAD, FD and Rao's quadratic entropy. Statistical theory is also provided in order to prove that all desirable statistical properties of species richness rarefaction are preserved for functional rarefaction.     

声景生态学研究进展和展望

声景生态学以景观中的声音为研究对象, 探讨其在不同时空维度上的分布和变化模式, 从而揭示自然环境、野生动物和人类活动的相互作用关系。本文通过系统检索声景生态学研究的相关文献, 回顾了该学科的研究框架和研究方法, 总结了目前常用的声学指标, 重点归纳了声景生态学的研究内容, 包括声景组成和各组分间的相互作用, 声景的时空格局, 以及声景生态学在生物多样性监测中的应用。目前, 声景监测中存在的问题主要包括监测的生态系统类型和物种类群有限、声学指标效力有待提高等。建议未来着重推进建立系统性的声景监测网络和数据管理平台, 开发和完善音频数据采集、分析方法和评估指标, 并重视声景数据的采集, 将声景视作一种资源进行研究和保护。     

利用PHI数据进行区域性植物生理信息探测与分析

本次试验研究选择两个实验区 :沼泽地和植被茂盛区。利用 2 0 0 0年 9月上旬在黑龙江省大兴安岭地区获取的推帚式超光谱成像 ,(PHI,pushbroomhyperspectralimager)数据进行区域性植物生理量 (主要是叶绿素 )的探测与生态分析。在叶绿素含量探测中 ,结合所获取的成像光谱PHI数据的特点 ,在比较不同技术方法的基础之上 ,选用了有效而简单可靠的RARS(Ratioanalysisofreflectancespectra)指数。该色素指数与植物叶绿素a、b含量拟合的相关系数 (R)达 0 .8以上。利用PHI数据和野外实测植物光谱分别建立沼泽地和植被茂盛区的RARS指数模式 ,分别得到具有指示两试验区的叶绿素a (Chla)、叶绿素b (Chlb)以及类胡萝卜素 (Cars)的参数图像。更进一步地利用Blackburn(1998)所建立的RARS指数与叶绿素浓度之间的强拟合方程 ,相对定量估算了叶绿素a、b浓度的区域性分布 ,清晰地反映出植被生态状况和差异。这与野外实地考察较为一致。     

A measure of sexual dimorphism in populations which are univariate normal mixtures

Measures of sexual dimorphism have been used extensively to predict the social organization and ecology of animal and human populations. There is, however, no universally accepted measure of phenotypic differences between the sexes. Most indices of sexual dimorphism fail to incorporate all of the information contained in a random data set. In an attempt to have a better alternative, an index is proposed to measure sexual dimorphism in populations that are distributed according to a probabilistic mixture model with two normal components. The index calculates the overlap between two functions that represent the contribution of each sex in the mixture. In order to assess such an index, sample means, variances and sizes of each sex are needed. As a consequence, the sample information used is greater than that used by other indices that take intrasexual variability into account. By evaluating some examples, our proposed index appears to be a more realistic measure of sexual dimorphism than other measures currently used.     

Sensitivity Profiles of Diversity Indices

The author previously described special sensitivity measures for diversity indices. These measures make possible on analytical treatment of the index sensitivity. In the article a detailed analysis of sensitivity properties of the Hurlbert indices is presented. In the first step the abundances n_k were sequenced in an increasing order. Plotting the sensitivity against n_k or log n_k, essential sensitivity properties can be observed. For example, one can study the sensitivities to changes in the dominant and subdominant abundances, the site of the “nearly neutral” abundance and the site of local sensitivity maxima in the domain of the relatively rare categories. The observations are supported by mathematical reasoning.     

On the importance of intraspecific variability for the quantification of functional diversity

Functional diversity (FD) is a key facet of biodiversity used to address central questions in ecology. Despite recent methodological advances, FD remains a complex concept and no consensus has been reached either on how to quantify it, or on how it influences ecological processes. Here we define FD as the distribution of trait values within a community. When and how to account for intraspecific trait variability (ITV) when measuring FD remains one of the main current debates. It remains however unclear to what extent accounting for population‐level ITV would modify FD quantification and associated conclusions. In this paper, we address two critical questions: (1) How sensitive are different components of FD to the inclusion of population‐level ITV? (2) Does the omission of ITV obscure the understanding of ecological patterns? Using a mixture of empirical data and simulation experiments, we conducted a sensitivity analysis of four commonly used FD indices (community weighted mean traits, functional richness, Rao's quadratic entropy, Petchey and Gaston's FD index) and their relationships with environmental gradients and species richness, by varying both the extent (plasticity or not) and the structure (contingency to environmental gradient due to local adaptation) of population‐level ITV. Our results suggest that ITV may strongly alter the quantification of FD and the detection of ecological patterns. Our analysis highlights that 1) species trait values distributions within communities are crucial to the sensitivity to ITV, 2) ITV structure plays a major role in this sensitivity and 3) different indices are not evenly sensitive to ITV, the single‐trait FD from Petchey and Gaston being the most sensitive among the four metrics tested. We conclude that the effects of intraspecific variability in trait values should be more systematically tested before drawing central conclusions on FD, and suggest the use of simulation studies for such sensitivity analyses.     

长白山阔叶红松林结构多样性的初步研究

在林业可持续发展的背景下,对森林实施生态系统管理,必须保护和维持森林的生物多样性。这就要求在森林调查和经营过程中增加林分结构多样性方面的内容,因此必须充分认识森林结构包括的内容,并研究制订简便实用的结构多样性指标。本文采用目测分层盖度结合无样地点四分法取样进行林分结构因子调查,设计了一套简便的林分结构指标体系,并对长白山红松阔叶混交林及其次生林进行了林分结构多样性的测定研究。结果表明：基于分层盖度构建的林分垂直多样性指数和水平结构异质性指数,可以较好地表示林分的基本结构特征,同时借助点四分法测定的物种多样性指数和对倒木、站干、林隙等的统计,可以较全面地描述阔叶红松林的林分结构因素。应用该方法测定不同的原始林样地的林分结构,得到的林分结构指标与其他林分结构因素的描述,同常规林学调查结论一致并更全面;同时对不同采伐方式的林分结构进行了测定,结合相应的常规指标测定对比,表明该结构指数不但能较好地表示群落的空间结构特征,同时也能对比不同经营方式对林分结构造成的影响,如择伐方式比皆伐方式对林分的结构影响相对较小而且结构恢复时间较短,从而说明对阔叶红松林这种复层异龄混交林的森林类型而言,择伐是一种更适合的通过结构调控进行生态系统管理的方式。在对生态系统进行经营管理过程中,采用该方法能有效地说明林分的垂直结构复杂性和水平结构异质性及重要的林分结构因子存在状况,因而更适合当前森林生态系统管理的要求。文章进一步分析了林分结构指标待改进的部分与研究方向。     

群落结构复杂性的测度方法研究进展

该文对群落结构复杂性的测度方法的研究进展状况进行了综述。根据测度方法建立的方法基础,将现有的方法分成3类:基于多样性的复杂性测度、基于计算复杂性的测度和基于几何学特征的复杂性测度。对每类测度方法进行了介绍,对其优缺点进行了评述。同时提出了未来研究中应给予重视的问题。结果表明,现有群落结构复杂性的测度方法普遍存在区分能力差的问题,对于基于多样性的结构复杂性测度,目前还缺乏确定各测度属性权重的客观方法;现有的一些基于计算复杂性的结构测度与多样性指标关系过于密切,还不完善,同时其生态学的意义还不明确,而另一些计算复杂性指标还缺乏实际检验。今后,如何建立既具有区分力、又与多样性在概念和数值上都有一定区别的群落结构的计算复杂性的测度方法、如何科学合理地确定复杂性测度中的属性权重以及如何建立结构复杂性的测度和功能过程之间的联系等都是需要深入和系统研究的。由于方法的相似性,有关群落结构复杂性的测度方法也可以应用到其它尺度上的结构复杂性的研究中。     

基于小波分析的大豆叶绿素a含量高光谱反演模型

 2003和2004年分别在长春市良种场和中国科学院海伦黑土生态实验站实测了大田耕作与水肥耦合作用下大豆（Glycine max）冠层高光谱反射率 与叶绿素a含量数据,对光谱反射率、微分光谱与叶绿素a含量进行了相关分析;采用归一化植被指数(Normalized diffe rence vegetation index, NDVI)、土壤调和植被指数(Soil-adjusted vegetation index, SAVI)、再归一植被指数(Renormalized difference vegetation index, RDVI)、第二修正比值植被指数(Modified second ratio index, MSRI)等建立了大豆叶绿素a反演模型;应用小波分析对采集的光谱反 射率数据进行了能量系数提取,并以小波能量系数作为自变量进行了单变量与多变量回归分析,对大豆叶绿素a进行了估算。研究结果表明,大 豆叶绿素a 与可见光光谱反射率相关性较好,并在红光波段取得最大值(R²>0.70),但在红边处,微分光谱与大豆叶绿素a的相关性较反射率好 得多,在其它波段则相反;由NDVI、SAVI、RDVI、MSRI等植被指数建立的估算模型可以提高大豆叶绿素a的估算精度（R²>0.75）;小波能量系 数回归模型可以进一步提高大豆叶绿素a含量的估算水平,以一个特定小波能量系数作为自变量的回归模型,大豆叶绿素a回归决定系数R²高达 0.78;多变量回归分析结果表明,大豆叶绿素a实测值与预测值的线性回归决定系数R²均高达0.85。以上结果表明, 小波分析可以对高光谱进 行特征变量提取,并可在一定程度上提高大豆生理参数反演精度。     

Linear selection indices for non-linear profit functions

Summary Two methods of deriving linear selection indices for non-linear profit functions have been proposed. One is by linear approximation of profit, and another is the graphical method of Moav and Hill (1966). When profit is defined as the function of population means, the graphical method is optimal. In this paper, profit is defined as the function of the phenotypic values of individual animals; it is then shown that the graphical method is not generally optimal. We propose new methods for constructing selection indices. First, a numerical method equivalent to the graphical method is proposed. Furthermore, we propose two other methods using quadratic approximation of profit: one is based on Taylor series about means before selection, and the other is based on Tayler series about means after selection. Among these different methods, it is shown that the method using quadratic approximation based on Taylor series about means after selection is the most efficient.     

Cover versus biomass as an estimate of species abundance: does it make a difference to the conclusions?

Abstract. Different measures of species abundance, particularly cover and biomass, are often used as if they were interchangeable. We ask to what extent the measure of abundance affects conclusions reached in plant community ecology. The test data comprised 35 plots, each 1 m × 1 m, on serpentine vegetation in Tuscany, Italy, in which both cover and biomass were measured. The measure of abundance used made rather little difference when plots were examined in terms of the rank abundance of the species present, and little difference to the results of a DCA-ordination. Likewise, species showed similar variation across plots in cover as in biomass. In calculating species diversity, agreement between measures of abundance was lower, but still good. For evenness, the correlation between cover and biomass results was lower again, though more so with some indices than with others. For the shape of the RAD (Relative Abundance Distribution), cover and biomass gave quite different results, the Zipf-Mandelbrot RAD model most commonly giving the best fit to the cover data, but the General lognormal model to the biomass data. These tendencies can be related to the intrinsic characteristics of cover and biomass as measures of abundance. The parameters of the model fits also differed between abundance measures. We conclude that the importance of using biomass as the measure of abundance depends on the ecological feature being examined. The difference between the two measures may be greater in other vegetation; very little information is available. In the current state of knowledge it is dangerous to use another measure as a surrogate for biomass.     

遥感主体图的准确度对景观生态学研究的影响

用各种案例系统地解释了遥感数据分类误差对景观指数误差的必然影响。一方面 ,遥感数据在各种时间和空间尺度上为景观生态学研究提供必需的土地类型数据 ;另一方面 ,遥感技术的灵活性和复杂性可以产生出各种质量的土地类型数据。但景观生态学方面的用户对土地类型数据基本上是没有选择地使用 ,甚至是不知好坏地使用 ,所以景观生态学的发现和结论具有不可避免的任意性。总结了在各种情况下景观指数的变动区间 ,指出了现实较低的遥感数据的分类准确度会引起更低的景观指数的准确度 ,当进行景观变化分析时 ,这种误差的放大效应将更加明显。当前 ,人们对除面积以外的景观指数的误差仍然束手无策 ,尽可能地提高遥感数据的分类准确度是唯一力所能及的办法。