A recent increase in studies of β diversity has yielded a confusing array of concepts, measures and methods. Here, we provide a roadmap of the most widely used and ecologically relevant approaches for analysis through a series of mission statements. We distinguish two types of β diversity: directional turnover along a gradient vs. non-directional variation. Different measures emphasize different properties of ecological data. Such properties include the degree of emphasis on presence/absence vs. relative abundance information and the inclusion vs. exclusion of joint absences. Judicious use of multiple measures in concert can uncover the underlying nature of patterns in β diversity for a given dataset. A case study of Indonesian coral assemblages shows the utility of a multi-faceted approach. We advocate careful consideration of relevant questions, matched by appropriate analyses. The rigorous application of null models will also help to reveal potential processes driving observed patterns in β diversity.© 2010 Blackwell Publishing Ltd/CNRS.

Deterministic theories in community ecology suggest that local, niche-based processes, such as environmental filtering, biotic interactions and interspecific trade-offs largely determine patterns of species diversity and composition. In contrast, more stochastic theories emphasize the importance of chance colonization, random extinction and ecological drift. The schisms between deterministic and stochastic perspectives, which date back to the earliest days of ecology, continue to fuel contemporary debates (e.g. niches versus neutrality). As illustrated by the pioneering studies of Robert H. MacArthur and co-workers, resolution to these debates requires consideration of how the importance of local processes changes across scales. Here, we develop a framework for disentangling the relative importance of deterministic and stochastic processes in generating site-to-site variation in species composition (β-diversity) along ecological gradients (disturbance, productivity and biotic interactions) and among biogeographic regions that differ in the size of the regional species pool. We illustrate how to discern the importance of deterministic processes using null-model approaches that explicitly account for local and regional factors that inherently create stochastic turnover. By embracing processes across scales, we can build a more synthetic framework for understanding how niches structure patterns of biodiversity in the face of stochastic processes that emerge from local and biogeographic factors.

<p>Beta diversity is an important component of biological diversity, measuring compositional change in species assemblages across temporal and spatial scales. Beta diversity concerns not only a number of ecological and evolutionary issues, but can also guide the selection of protected areas and help to optimize conservation networks. It has thus become a hot topic in biodiversity research in recent years. Researchers have used various measures and analytical methods to investigate patterns of beta diversity and its underlying mechanisms for various taxa and in different regions. Here, we reviewed literature from the past decade pertaining to the following aspects of beta diversity: metrics, temporal and spatial patterns, determinants and applications in biodiversity conservation. Whittaker introduced the term beta diversity in 1960, but defined it vaguely. As the concept of beta diversity evolved, a high variety of measures were developed to quantify the concept. The comparison of results from different studies may be hindered by the variety of measures used to quantify beta diversity. Presently, the most popular methods for measuring beta diversity are similarity/ dissimilarity coefficients such as Jaccard index and S&oslash;rensen index. In the last few years, several methods to quantify beta diversity have emerged, some of which are worth noting. Beta diversity depends on temporal scale, spatial scale and taxonomic scale, and decreases with increasing analytical grain size. There is no consensus among scientists that beta diversity decreases with latitude, i.e. that it is higher in tropics and lower near the poles. Beta diversity is high within mountain ranges and at the interface of biogeographic realms; thus, larger/more reserves are needed in these regions to cover the entire gradient of species turnover. Studies on beta diversity across temporal scales have shown that climatic change has resulted in shifts in species composition through time, and that the migration of species between different continents/regions has led to biotic homogenization. Based on a thorough review of beta diversity literature, we think the following questions might be the focus of future research: (1) the influence of evolutionary history and biological characteristics of different taxonomic groups on their beta diversity; (2) the influence of temporal/spatial scales on beta diversity and its determinants; and (3) the effect of anthropogenic activities on beta diversity.</p>

Beta多样性度量时空尺度上物种组成的变化, 是生物多样性的重要组成部分, 与许多生态学和进化生物学问题密切相关, 并且其信息可用于保护区选址和布局规划, 因此在最近10年间成为生物多样性研究的热点问题之一。多年来, 学者们利用各种度量方式和分析方法, 在不同地理区域, 对许多生物类群beta多样性的时空格局和形成机制进行了大量研究。本文主要从beta多样性的度量方法、时空格局、形成机制及其在生物多样性保护中的应用等几个方面, 总结了最近10多年来相关研究的进展。Whittaker(1960)最初提出beta多样性概念时就缺乏严格的定义, 随着概念的不断演化, 度量方法也同样呈现出多样化, 而度量手段的多样化非常不利于不同研究之间的比较。目前应用最普遍的度量方法是采用相似性指数, 如Jaccard和S&oslash;rensen指数。最近几年, 新的度量方法还在不断出现, 其中一些方法非常值得注意。Beta多样性具有时空尺度和分类尺度依赖性, 一般随分析粒度(grain)的增加而降低。虽然有些研究表明beta多样性随纬度增加而降低, 但学者们并没有达成共识。山区和生物地理区的交界处beta多样性都比较高, 因而需要在这些地区增加保护区的面积或者数量以囊括物种变化梯度。对时间尺度上beta多样性的研究表明, 气候变化确实导致了物种组成在时间上的变化, 并且物种在不同大陆和地区间的迁移导致了生物同质化。扩散过程和生态位过程共同决定了beta多样性, 只是这两个过程的相对重要性依尺度、地理区域和物种类群的不同而有所差异。综上所述, 我们认为未来beta多样性研究的热点问题是：(1)不同生物类群的进化历史和生物学特征对beta多样性的影响; (2)不同的时空尺度对beta多样性及其维持机制的影响; (3)人类活动对beta多样性的影响。

We conducted a study to test the predictions of Walter's two-layer model in the shortgrass steppe of northeastern Colorado. The model suggests that grasses and woody plants use water resources from different layers of the soil profile. Four plant removal treatments were applied in the spring of 1996 within a plant community codominated by Atriplex canescens (a C shrub) and Bouteloua gracilis (a C grass). During the subsequent growing season, soil water content was monitored to a depth of 180 cm. In addition, stem and leaf tissue of Atriplex, Bouteloua and the streamside tree Populus sargentii were collected monthly during the growing seasons of 1995 and 1996 for analysis of the δO value of plant stem water (for comparison with potential water sources) and the δC value of leaves (as an indicator of plant water status). Selective removal of shrubs did not significantly increase water storage at any depth in the measured soil profile. Selective removal of the herbaceous understory (mainly grasses) increased water storage in the top 60 cm of the soil. Some of this water gradually percolated to lower layers, where it was utilized by the shrubs. Based on stem water δO values, grasses were exclusively using spring and summer rain extracted from the uppermost soil layers. In contrast, trees were exclusively using groundwater, and the consistent δC values of tree leaves over the course of the summer indicated no seasonal changes in gas exchange and therefore minimal water stress in this life-form. Based on anecdotal rooting-depth information and initial measurements of stem water δO, shrubs may have also had access to groundwater. However, their overall δO values indicated that they mainly used water from spring and summer precipitation events, extracted from subsurface soil layers. These findings indicate that the diversity of life-forms found in this shortgrass steppe community may be a function of the spatial partitioning of soil water resources, and their differential use by grasses, shrubs, and trees. Consequently, our findings support the two-layer model in a broad sense, but indicate a relatively flexible strategy of water acquisition by shrubs.

A plant community is an assemblage of plant populations that live in certain area, and interact with and adapt to one another in the context of long-term environmental changes. Plant communities maintain global ecosystem functions, and provide food and habitats for animals and other organisms. Plant communities also provide primary resources for human survival and development, and are therefore indispensable to human societies. China is among the countries with the most diverse plant communities in the world. However, no systematic national inventory has been conducted for Chinese plant communities. This fact obstructs exploitation and protection of China&rsquo;s plant resources, and also hampers the development of the fields of Chinese ecology and geography. There is an urgent need to survey Chinese plant communities using consis-tent methods and protocols. In this paper, we review major concepts in plant community ecology, and pro-pose a framework for developing plant community inventories based on recent progress in community ecol-ogy and our own experience with long-term field surveys. Our framework provides protocols for site selec-tion and plot design, items to be measured in a plot, and measurements of functional traits of dominant spe-cies. We also review protocols for field surveys of large, long-term plots. The protocols proposed in this pa-per are expected to be a base for standardizing methodology for inventory of Chinese plant communities.

植物群落是不同植物在长期环境变化中相互作用、相互适应而形成的组合。它提供着人类赖以生存的主要物质资源, 维系着地球生态系统的健康和功能, 也为各种动物和其他生物提供食物来源和栖息地, 是人类生存和发展不可或缺的物质基础, 具有不可替代的作用。我国植物群落类型多样, 在世界上首屈一指, 但我国至今尚没有一次全面和系统的植物群落清查, 不仅影响了人们对我国植物资源的了解、利用和保护, 也不利于我国生态学、环境科学和地理学等相关学科的发展。采用统一的方法体系和技术规范开展我国植物群落的清查工作势在必行, 并具有紧迫性。本文基于作者长期的野外工作实践和国内外的群落调查方法, 首先简要定义了与植物群落清查有关的重要概念, 在此基础上, 论述了调查样地的设置原则和体系、群落清查的技术指标和方法、主要优势种生态属性的测定方法和规范, 并介绍了大样地调查的主要步骤。通过本文的介绍、归纳和总结, 试图为制定我国植物群落清查的技术规范提供基础材料和技术储备。

It was recently suggested that beta diversity can be partitioned into contributions of single sites to overall beta diversity (LCBD) or into contributions of individual species to overall beta diversity (SCBD). We explored the relationships of LCBD and SCBD to site and species characteristics, respectively, in stream insect assemblages. We found that LCBD was mostly explained by variation in species richness, with a negative relationship being detected. SCBD was strongly related to various species characteristics, such as occupancy, abundance, niche position and niche breadth, but was only weakly related to biological traits of species. In particular, occupancy and its quadratic terms showed a very strong unimodal relationship with SCBD, suggesting that intermediate species in terms of site occupancy contribute most to beta diversity. Our findings of unravelling the contributions of sites or species to overall beta diversity are of high importance to community ecology, conservation and bioassessment using stream insect assemblages, and may bear some overall generalities to be found in other organism groups.

1. The environmental filtering hypothesis predicts that the abiotic environment selects species with similar trait values within communities. Testing this hypothesis along multiple - and interacting - gradients of climate and soil variables constitutes a great opportunity to better understand and predict the responses of plant communities to ongoing environmental changes. 2. Based on two key plant traits, maximum plant height and specific leaf area (SLA), we assessed the filtering effects of climate (mean annual temperature and precipitation, precipitation seasonality), soil characteristics (soil pH, sand content and total phosphorus) and all potential interactions on the functional structure and diversity of 124 dryland communities spread over the globe. The functional structure and diversity of dryland communities were quantified using the mean, variance, skewness and kurtosis of plant trait distributions. 3. The models accurately explained the observed variations in functional trait diversity across the 124 communities studied. All models included interactions among factors, i.e. climate - climate (9% of explanatory power), climate - soil (24% of explanatory power) and soil - soil interactions (5% of explanatory power). Precipitation seasonality was the main driver of maximum plant height, and interacted with mean annual temperature and precipitation. Soil pH mediated the filtering effects of climate and sand content on SLA. Our results also revealed that communities characterized by a low variance can also exhibit low kurtosis values, indicating that functionally contrasting species can co-occur even in communities with narrow ranges of trait values. 4. We identified the particular set of conditions under which the environmental filtering hypothesis operates in drylands worldwide. Our findings also indicate that species with functionally contrasting strategies can still co-occur locally, even under prevailing environmental filtering. Interactions between sources of environmental stress should be therefore included in global trait-based studies, as this will help to further anticipate where the effects of environmental filtering will impact plant trait diversity under climate change.

Beta diversity can be measured in different ways. Among these, the total variance of the community data table Y can be used as an estimate of beta diversity. We show how the total variance of Y can be calculated either directly or through a dissimilarity matrix obtained using any dissimilarity index deemed appropriate for pairwise comparisons of community composition data. We addressed the question of which index to use by coding 16 indices using 14 properties that are necessary for beta assessment, comparability among data sets, sampling issues and ordination. Our comparison analysis classified the coefficients under study into five types, three of which are appropriate for beta diversity assessment. Our approach links the concept of beta diversity with the analysis of community data by commonly used methods like ordination and anova. Total beta can be partitioned into Species Contributions (SCBD: degree of variation of individual species across the study area) and Local Contributions (LCBD: comparative indicators of the ecological uniqueness of the sites) to Beta Diversity. Moreover, total beta can be broken up into within- and among-group components by manova, into orthogonal axes by ordination, into spatial scales by eigenfunction analysis or among explanatory data sets by variation partitioning. © 2013 John Wiley & Sons Ltd/CNRS.

The classical environmental control model assumes that species distribution is determined by the spatial variation of underlying habitat conditions. This niche-based model has recently been challenged by the neutral theory of biodiversity which assumes that ecological drift is a key process regulating species coexistence. Understanding the mechanisms that maintain biodiversity in communities critically depends on our ability to decompose the variation of diversity into the contributions of different processes affecting it. Here we investigated the effects of pure habitat, pure spatial, and spatially structured habitat processes on the distributions of species richness and species composition in a recently established 24-ha stem-mapping plot in the subtropical evergreen broad-leaved forest of Gutianshan National Nature Reserve in East China. We used the new spatial analysis method of principal coordinates of neighbor matrices (PCNM) to disentangle the contributions of these processes. The results showed that (1) habitat and space jointly explained approximately 53% of the variation in richness and approximately 65% of the variation in species composition, depending on the scale (sampling unit size); (2) tree diversity (richness and composition) in the Gutianshan forest was dominantly controlled by spatially structured habitat (24%) and habitat-independent spatial component (29%); the spatially independent habitat contributed a negligible effect (6%); (3) distributions of richness and species composition were strongly affected by altitude and terrain convexity, while the effects of slope and aspect were weak; (4) the spatial distribution of diversity in the forest was dominated by broad-scaled spatial variation; (5) environmental control on the one hand and unexplained spatial variation on the other (unmeasured environmental variables and neutral processes) corresponded to spatial structures with different scales in the Gutianshan forest plot; and (6) five habitat types were recognized; a few species were statistically significant indicators of three of these habitats, whereas two habitats had no significant indicator species. The results suggest that the diversity of the forest is equally governed by environmental control (30%) and neutral processes (29%). In the fine-scale analysis (10 x 10 m cells), neutral processes dominated (43%) over environmental control (20%).

Site-to-site variation in species composition (β-diversity) generally increases from low- to high-diversity regions. Although biogeographical differences in community assembly mechanisms may explain this pattern, random sampling effects can create this pattern through differences in regional species pools. Here, we compared assembly mechanisms between spatially extensive networks of temperate and tropical forest plots with highly divergent species pools (46 vs. 607 species). After controlling for sampling effects, β-diversity of woody plants was similar and higher than expected by chance in both forests, reflecting strong intraspecific aggregation. However, different mechanisms appeared to explain aggregation in the two forests. In the temperate forest, aggregation reflected stronger environmental correlations, suggesting an important role for species-sorting (e.g. environmental filtering) processes, whereas in the tropics, aggregation reflected stronger spatial correlations, more likely reflecting dispersal limitation. We suggest that biogeographical differences in the relative importance of different community assembly mechanisms contribute to these striking gradients in global biodiversity.© 2012 Blackwell Publishing Ltd/CNRS.

Predictable geographic patterns in the distribution of species richness, especially the latitudinal gradient, are intriguing because they suggest that if we knew what the controlling factors were we could predict species richness where empirical data is lacking (e.g. tropics). Based on analyses of the macro‐scale distribution of woody plant species richness in Southern Africa, one controlling factor appears to be climate‐based water‐energy dynamics. Using the regression models of climate's relationship to species richness in Southern Africa, I was able to describe an Interim General Model (IGM) and to predict first‐order macro‐scale geographic variations in woody plant species richness for the continent of Africa, as well as elsewhere in the world—exemplified using South America, the United States and China.

Niche and neutral theories emphasize different processes contributing to the maintenance of species diversity. In this study, we calculated the local contribution to beta diversity (LCBD) of every cell, using variation partitioning in combination with spatial distance and environmental variables of the 25-ha Badagongshan plot (BDGS), to determine the contribution of environmentally-related variation versus pure spatial variation. We used topography and soil characteristics as environmental variables, distance-based Moran's eigenvectors maps (dbMEM) to describe spatial relationships among cells and redundancy analysis (RDA) to apportion the variation in beta diversity into three components: pure environmental, spatially-structured environmental, and pure spatial. Results showed LCBD values were negatively related to number of common species and positively related to number of rare species. Environment and space jointly explained similar to 60% of the variation in species composition; soil variables alone explained 21.6%, slightly more than the topographic variables that explained 15.7%; topography and soil together explained 27%, slightly inferior to spatial variables that explained 34%. The BDGS forest was controlled both by the spatial and environmental variables, and the results were consistent across different life forms and life stages.

Geographic, climatic, and soil factors are major drivers of plant beta diversity, but their importance for dryland plant communities is poorly known. This study aims to: i) characterize patterns of beta diversity in global drylands, ii) detect common environmental drivers of beta diversity, and iii) test for thresholds in environmental conditions driving potential shifts in plant species composition.224 sites in diverse dryland plant communities from 22 geographical regions in six continents.Beta diversity was quantified with four complementary measures: the percentage of singletons (species occurring at only one site), Whittake's beta diversity (β(W)), a directional beta diversity metric based on the correlation in species occurrences among spatially contiguous sites (β(R)), and a multivariate abundance-based metric (β(MV)). We used linear modelling to quantify the relationships between these metrics of beta diversity and geographic, climatic, and soil variables.Soil fertility and variability in temperature and rainfall, and to a lesser extent latitude, were the most important environmental predictors of beta diversity. Metrics related to species identity (percentage of singletons and β(W)) were most sensitive to soil fertility, whereas those metrics related to environmental gradients and abundance ((β(R)) and β(MV)) were more associated with climate variability. Interactions among soil variables, climatic factors, and plant cover were not important determinants of beta diversity. Sites receiving less than 178 mm of annual rainfall differed sharply in species composition from more mesic sites (> 200 mm).Soil fertility and variability in temperature and rainfall are the most important environmental predictors of variation in plant beta diversity in global drylands. Our results suggest that those sites annually receiving ~ 178 mm of rainfall will be especially sensitive to future climate changes. These findings may help to define appropriate conservation strategies for mitigating effects of climate change on dryland vegetation.

Understanding the spatial pattern of plant species diversity and the influencing factors has important implications for the conservation and management of ecosystem biodiversity. The transitional zone between biomes in desert ecosystems, however, has received little attention in that regard. In this study, we conducted a quantitative field survey (including 187 sampling plots) in a 40-km2 study area to determine the spatial pattern of plant species diversity and analyze the influencing factors in a Gobi Desert within the Heihe River Basin, Northwest China. A total of 42 plant species belonging to 16 families and 39 genera were recorded. Shrub and semi-shrub species generally represented the major part of the plant communities (covering 90% of the land surface), while annual and perennial herbaceous species occupied a large proportion of the total recorded species (71%). Patrick richness index (R), Shannon-Wiener diversity index (H'), Simpson’s dominance index (D), and Pielou’s evenness index (J) were all moderately spatially variable, and the variability increased with increasing sampling area. The semivariograms for R and H' were best fitted with Gaussian models while the semivariograms for D and J were best fitted with exponential models. Nugget-to-still ratios indicated a moderate spatial autocorrelation for R, H', and D while a strong spatial autocorrelation was observed for J. The spatial patterns of R and H' were closely related to the geographic location within the study area, with lower values near the oasis and higher values near the mountains. However, there was an opposite trend for D. R, H', and D were significantly correlated with elevation, soil texture, bulk density, saturated hydraulic conductivity, and total porosity (P<0.05). Generally speaking, locations at higher elevations tended to have higher species richness and diversity and the higher elevations were characterized by higher values in sand and gravel contents, bulk density, and saturated hydraulic conductivity and also by lower values in total porosity. Furthermore, spatial variability of plant species diversity was dependent on the sampling area.