植物物种多样性与岛屿面积的关系

由于水库蓄水导致千岛湖原有生境的破碎化和岛屿化.研究选取了50个岛屿,共设立样方70个.调查这些岛屿上乔木和灌木的种类及数量,选择9种曲线拟合岛屿面积与物种多样性指数之间的数学关系.结果发现:乔木、灌木和木本物种数与岛屿面积关系拟合较好的是对数函数、幂函数和S型曲线,其中对数函数为最优模型;乔木、木本Shannon-Wiener多样性指数与岛屿面积关系拟合较好的是S型曲线和逆函数,灌木Shannon-Wiener多样性指数与岛屿面积关系拟合不显著,乔木和木本Shannon-Wiener多样性指数与较小岛屿(y小于1 hm2)面积拟合呈S形曲线和逆函数,而灌木Shannon-Wiener多样性指数与较大岛屿(y大于1 hm2)面积拟合呈S形曲线和逆函数;均匀度、优势度指数与面积拟合关系不显著. 在岛屿面积较小时,物种多样性指数随着面积的增加而迅速增加,但在面积增加到一定限度时,物种多样性指数增加的速率就逐渐变缓.植物物种数增加速率的转折点约为4 hm2,乔木、木本Shannon-Wiener多样性指数增加速率的转折点约为1 hm2,对面积小于的1 hm2的岛屿进行拟合时发现,乔木、木本Shannon-Wiener多样性指数增加速率的转折点在0.15～0.2 hm2之间.     

海南橡胶林植物多样性特征

为探讨人工林物种多样性维持机制及人为干扰后人工林群落的多样性恢复机制, 作者依据自然林的核心理论建立了一个1 ha的橡胶(Hevea brasiliensis)林固定样地, 通过研究近自然管理后样地内植物物种组成与分布来探讨近自然管理后橡胶林生物多样性的特征。结果表明: 近自然管理后橡胶林群落物种多样性较高, 1 ha样地内共有植物69科155属183种。在面积为4,000 m²、3,000 m²和2,000 m²时分别包含了样地内大约90%的种、属和科; 逻辑斯蒂模型拟合拟合种-面积曲线效果较好(R²=0.997), 证明了1 ha取样尺度可以满足橡胶林群落物种多样性研究的需要。多度-面积曲线和丰富度-面积曲线与随机分布模型有明显的差异, 表明橡胶林群落内个体数及物种分布呈非随机性。(4)对数级数模型和对数正态模型拟合橡胶林群落的种-多度分布都不理想, 相比而言后者拟合效果稍好。     

生物群落的种-面积关系

种—面积关系主要探讨物种数量随面积扩大而变化的规律, 它联系不同尺度的生物多样性, 是生物多样性尺度转换的重要依据。利用种—面积关系可以估算群落或区域的物种数量、评价区域生物多样性的丧失。由于构建方式、尺度效应以及区域差异, 种—面积关系的具体形式及其普适性还存在争议。本文主要从构建、尺度效应、区域分异以及与种—多度分布的联系等方面综述种—面积关系的主要进展, 并探讨它在不同方面的适用性。最后给出了利用基于组合样方系列构建的种—面积关系来估算秦岭山地物种数的实例, 结果表明估算精度良好。     

The role of spatial scale and the perception of large-scale species-richness patterns

Despite two centuries of exploration, our understanding of factors determining the distribution of life on Earth is in many ways still in its infancy. Much of the disagreement about governing processes of variation in species richness may be the result of differences in our perception of species‐richness patterns. Until recently, most studies of large‐scale species‐richness patterns assumed implicitly that patterns and mechanisms were scale invariant. Illustrated with examples and a quantitative analysis of published data on altitudinal gradients of species richness (n = 204), this review discusses how scale effects (extent and grain size) can influence our perception of patterns and processes. For example, a hump‐shaped altitudinal species‐richness pattern is the most typical (c. 50%), with a monotonic decreasing pattern (c. 25%) also frequently reported, but the relative distribution of patterns changes readily with spatial grain and extent. If we are to attribute relative impact to various factors influencing species richness and distribution and to decide at which point along a spatial and temporal continuum they act, we should not ask only how results vary as a function of scale but also search for consistent patterns in these scale effects. The review concludes with suggestions of potential routes for future analytical exploration of species‐richness patterns.     

空间尺度对地形异质性-物种多样性关系的影响:粒度和幅度

空间尺度是影响我们理解生态学格局和过程的关键因素.目前已有多种关于物种多样性分布格局形成机制的假说且研究者未达成共识,原因之一是空间尺度对物种多样性分布格局的环境影响因子的解释力和相对重要性有重要影响.地形异质性是物种多样性分布格局的重要影响因素.本文综述了在地形异质性-物种多样性关系的研究中,不同空间粒度和幅度对研究...     

吉林蛟河阔叶红松林样地种-面积关系

种-面积关系是群落生态学的核心问题之一,是生物多样性尺度转换的重要依据。利用吉林蛟河阔叶红松林30 hm~2的样地数据,采用随机取样与巢式取样方法,分别在10、20、30 hm~2尺度上建立对数模型(Logarithmic function)、幂函数模型(Power function)和逻辑斯蒂模型(Logistic function)拟合局域种-面积关系,并利用赤池信息准则(AIC)进行拟合结果优度检验。结果表明,取样方法对种-面积关系的构建有显著影响,随机取样优于巢式取样。种-面积关系的构建与尺度(取样上限)密切相关:在小尺度上(10 hm~2),对数模型与逻辑斯蒂模型拟合效果优于幂函数模型;在中尺度和大尺度上(20、30 hm~2),相对于对数模型和幂函数模型,逻辑斯蒂模型能更好地拟合阔叶红松林的种-面积关系。据AIC值可知,随机取样下的逻辑斯蒂模型拟合效果最好,是拟合30 hm~2阔叶红松林样地种-面积关系的最适模型。因此研究时需要根据区域森林群落的实际情况选择种-面积模型。     

A new relationship for rarefaction

All diversity indices are functions of the vector of the numbers of individuals in different species in a statistical population. So they are also functions of the number of species. It is well known, from the species-area curve and from collector's curves, that the number of species is a function of sampling effort. The rarefaction and Coleman functions are both functions that allow comparisons to be made at the same number of individuals, but have different mathematical forms. We show that the numerical difference between them, in the samples we have studied, is negligibly small. We show how to modify the Coleman function to allow for sampling without replacement, and show that the modified function is identical to the hypergeometric rarefaction function. Rarefaction should always be used, with any index, when comparing diversity in different size samples, but the number of species is the preferred index. Suggestions for comparing rarefaction curves from different samples are made.     

太白山几类植物群落灌木及草本层的最小取样面积研究

采用2条非饱和与2条饱和曲线方程对太白山7种类型植物群落(Ⅰ.锐齿栎林、Ⅱ.铁橡树林、Ⅲ.红桦林、Ⅳ.巴山冷杉-牛皮桦林、Ⅴ.巴山冷杉林、Ⅵ.太白红杉林和Ⅶ.头花杜鹃-大毛状薹草灌草丛)灌木及草本层拟合的种-面积曲线,计算研究精度要求分别为60%、70%、80%、90%时各群落各层的最小取样面积,并进行分析比较.结果表明,不同群落灌木及草本层最小取样面积均随研究精度增高而增大,群落Ⅰ~Ⅶ灌木层的取样面积分别为96、35、73、63、75、1701、8 m2时,草本层为91、91、57、59、71、657、m2时,可满足精度80%以下的研究要求;灌木层的取样面积为163、62、122、104、120、296、35 m2时,草本层为150、151、109、110、126、1192、9 m2时,可满足精度90%的研究要求.方差分析表明,不同群落灌木及草本层最小取样面积存在差异,有些差异达显著水平(P<0.05).因此,在野外调查时应根据研究精度要求和群落类型合理设置最小取样面积.     

On the generation of diversity in archipelagos: a re-evaluation of the Quinn-Harrison 'saturation index'

Aim Quinn & Harrison (1988; Oecologia, 75, 132) suggested that several small, isolated islands generally bore a higher diversity than fewer (or single) larger islands. They proposed a method by which the cumulative diversity of islands arranged small-to-large (‘STOL’) and large-to-small (‘LTOS’) could be used to identify how island area and species distributions interact to produce the system-wide or ensemble diversity. From these curves, an ‘index of saturation’ (SI) was calculated to summarize the way in which diversity is generated on a given archipelago. Unfortunately, the method did not allow statistical judgements to be made. Our paper considers the reliability of the Quinn-Harrison approach, especially in light of the inconsistency of its implications compared with ‘nestedness’ analyses. Location Three example data sets are used: reptiles from the archipelagos of the Sea of Cortéz, breeding land-birds from the Canary Islands, and stream invertebrates occupying rocks in the Steavenson River of central Victoria, Australia. Methods We refine the Quinn-Harrison technique to produce a method by which the difference between the STOL and LTOS cumulative diversity curves can be gauged statistically (the ξ statistic). We also propose an alternative statistic (η)—which we believe to be more intuitive—that preferentially weights species occurring on few patches and that can be statistically assessed by using Monte Carlo simulation. Results The basic Quinn-Harrison technique is not reliable for diagnosing whether systems are characterized by STOL or LTOS patterns. The three example data sets provide the range of options for faunal-diversity generation (STOL overlies LTOS, LTOS overlies STOL, and coincident). However, statistical analyses indicate that the patterns all are generated by the rarer species occupying larger islands. The results of the revised ξ statistic and especially the η statistic are consistent with this deduction, which in turn relate well with faunal-nestedness analyses. Main conclusions There was a contradiction between the Quinn-Harrison analyses, which suggested that most rarer taxa occurred in impoverished, smaller islands, and results of nestedness analyses, which indicated that the rarer taxa occurred on more speciose, larger islands. The resolution to this dilemma is that the Quinn-Harrison diagram and saturation index are so flawed that they yield unreliable results vis a vis the generation of diversity on archipelagos.