Neutral community dynamics, the mid-domain effect and spatial patterns in species richness

The mid‐domain effect (MDE) aims to explain spatial patterns in species richness invoking only stochasticity and geometrical constraints. In this paper, we used simulations to show that its main qualitative prediction, a hump‐shaped pattern in species richness, converges to the expectation of a spatially bounded neutral model when communities are linked by short‐distance migration. As these two models can be linked under specific situations, neutral theory may provide a mechanistic population level basis for MDE. This link also allows establishing in which situations MDE patterns are more likely to be found. Also, in this situation, MDE models could be used as a first approximation to understand the role of both stochastic (ecological drift and migration) and deterministic (adaptation to environmental conditions) processes driving the spatial structure of species richness.     

Dependence of broad-scale geographical variation in fleshy-fruited plant species richness on disperser bird species richness

Aim We analysed the interdependence of avian frugivore‐ and fruited plant‐species richness at the scale of major river basins across Europe, taking into account several environmental factors along different spatial gradients. Location Continental Europe and the British Isles. Methods We focused on wintering birds and autumn/winter fruiting plants, and used major river basins as geographical units and Structural Equation Modelling as the principal analytical tool. Results The statistical influence of disperser species richness on fleshy‐fruited plant species richness is roughly double that of the reverse. Broad‐scale variation in frugivore richness is more dependent on environmental factors than on fruited plant richness. However, the influence of disperser richness on plant richness is four times higher than the influence of environmental factors. Environmental influences on both birds and plants are greater than purely spatial influences. Main conclusions Our results are interpreted as indicating that biotic dispersal of fruits strongly affects broad‐scale geographical trends of fleshy‐fruited plant species richness, whereas richness of fruited plants moderately affects frugivore richness.     

Spatial nonstationarity and scale-dependency in the relationship between species richness and environmental determinants for the sub-Saharan endemic avifauna

Aim This article aims to test for and explore spatial nonstationarity in the relationship between avian species richness and a set of explanatory variables to further the understanding of species diversity variation. Location Sub‐Saharan Africa. Methods Geographically weighted regression was used to study the relationship between species richness of the endemic avifauna of sub‐Saharan Africa and a set of perceived environmental determinants, comprising the variables of temperature, precipitation and normalized difference vegetation index. Results The relationships between species richness and the explanatory variables were found to be significantly spatially variable and scale‐dependent. At local scales > 90% of the variation was explained, but this declined at coarser scales, with the greatest sensitivity to scale variation evident for narrow ranging species. The complex spatial pattern in regression model parameter estimates also gave rise to a spatial variation in scale effects. Main conclusions Relationships between environmental variables are generally assumed to be spatially stationary and conventional, global, regression techniques are therefore used in their modelling. This assumption was not satisfied in this study, with the relationships varying significantly in space. In such circumstances the average impression provided by a global model may not accurately represent conditions locally. Spatial nonstationarity in the relationship has important implications, especially for studies of species diversity patterns and their scaling.     

The relationships between local and regional species richness and spatial turnover

Aim To determine the empirical relationships between species richness and spatial turnover in species composition across spatial scales. These have remained little explored despite the fact that such relationships are fundamental to understanding spatial diversity patterns. Location South‐east Scotland. Methods Defining local species richness simply as the total number of species at a finer resolution than regional species richness and spatial turnover as turnover in species identity between any two or more areas, we determined the empirical relationships between all three, and the influence of spatial scale upon them, using data on breeding bird distributions. We estimated spatial turnover using a measure independent of species richness gradients, a fundamental feature which has been neglected in theoretical studies. Results Local species richness and spatial turnover exhibited a negative relationship, which became stronger as larger neighbourhood sizes were considered in estimating the latter. Spatial turnover and regional species richness did not show any significant relationship, suggesting that spatial species replacement occurs independently of the size of the regional species pool. Local and regional species richness only showed the expected positive relationship when the size of the local scale was relatively large in relation to the regional scale. Conclusions Explanations for the relationships between spatial turnover and local and regional species richness can be found in the spatial patterns of species commonality, gain and loss between areas.     

珠三角河网浮游植物物种丰富度时空特征

对2012年珠三角河网浮游植物物种丰富度的时空特征进行了系统阐析。季节上,枯水期的物种丰度差异大,丰水期差异小;空间上,广州周边及河网中部个别站位的总种数高于其他站位。不同季节的空间特征显示,枯水期的物种丰度自西江沿线、河网中部、广州周边呈递增趋势;而丰水期呈现三角洲两侧的物种丰富度高于河网中部。各类群相对组成结果显示,硅藻在枯水季节占绝对优势,丰水期优势下降;空间上广州周边站位硅藻百分比明显低于其他站位。分析原因,径流相关的补充和稀释作用和水体搅动引起的底层藻类的悬浮补充不仅影响物种丰富度的季节变动,也影响不同类群的相对组成;水体交换能力和营养盐分别是决定丰水期和枯水期物种丰富度空间分布的关键因素。     

生物多样性分布格局的地史成因假说

生物多样性的大尺度分布格局是现代环境与地史过程共同作用的结果。本文从影响机制、参数选择及与现代气候假说的关系等方面回顾了地史成因假说的最新进展, 并得出以下认识: (1) 地史过程对生物多样性的分布格局有显著影响, 但地史过程与现代环境之间强烈的共线性使得两者的影响常叠加在一起; (2) 与广域物种的多样性相比, 地史过程更有利于解释狭域物种(或特有物种)的多样性; (3) 地史过程的参数选择是地史假说所面临的挑战之一, 目前所用的指标与现代环境具有显著的共线性, 难以直观地体现地史过程对生物多样性的影响, 对不同区域内物种系统发育过程的对比或者物种形成速率及灭绝速率分布格局的分析可能有助于评价地史成因假说的影响。     

Determinants of avian species richness at different spatial scales

ABSTRACT. Studies of factors influencing avian biodiversity yield very different results depending on the spatial scale at which species richness is calculated. Ecological studies at small spatial scales (plot size 0.0025–0.4 km²) emphasize the importance of habitat diversity, whereas biogeographical studies at large spatial scales (quadrat size 400–50,000 km²) emphasize variables related to available energy such as temperature. In order to bridge the gap between those two approaches the bird atlas data set of Lake Constance was used to study factors determining avian species diversity at the intermediate spatial scales of landscapes (quadrat size 4–36 km²). At these spatial scales bird species richness was influenced by habitat diversity and not by variables related to available energy probably because, at the landscape scale, variation in available energy is small. Changing quadrat size between 4 and 36 km², but keeping the geographical extension of the study constant resulted in profound changes in the degree to which the amount of different habitat types was correlated with species richness. This suggests that high species diversity is achieved by different management regimes depending on the spatial scale at which species richness is calculated. However, generally, avian species diversity seems to be determined by spatial heterogeneity at the corresponding spatial scale. Thus, protecting the diversity of landscapes and ecosystems appears to ensure also high levels of species diversity.     

Macroecological explanations for differences in species richness gradients: a canonical analysis of South American birds

Aim To evaluate how spatial variation of species richness in different bird orders responds to environmental gradients and determine which order level trait best predicts these relationships. Location South America. Methods A canonical correlation analysis was performed between the species richness in each of 17 bird orders and eight environmental variables in 374, 220 × 220 km cells. Loadings associated with the first two canonical variables were regressed against six order‐level predictors, including diversification level (number of species in each order), body size, median geographical range size and characteristics included in the model to control Type I error rates (the phylogenetic relationship among orders and levels of local‐scale spatial autocorrelation). Results Richness patterns of 14 bird orders were highly correlated with the first canonical axis, indicating that most orders respond similarly to energy‐water gradients (primarily actual evapotranspiration, minimum temperature and potential evapotranspiration). In contrast, species richness within Trochiliformes, Apodiformes and Galliformes were also correlated with the second canonical variable, representing measures of mesoscale climatic variation (range in elevation within cells, minimum temperature, and the interaction term between them) and landcover (habitat diversity). We also found that total diversification within orders was the best predictor of the loadings associated with the first canonical axis, whereas body size of each order best predicted loadings on the second axis. Conclusion Our results broadly support climatic‐related hypotheses as explanations for spatial variation in species richness of different orders. However, both historical (order‐specific variation in speciation rates) and ecological (dispersal of species that evolved by independent processes into areas amenable to birds) processes can explain the relationship between order level traits, such as body size and diversification level, and magnitude of response to current environment, furnishing then guidelines for a further and deeper understanding of broad‐scale diversity gradients.     

Null models and spatial patterns of species richness in South American birds of prey

In this paper, we used geostatistical approaches to describe bi-dimensional spatial patterns in species richness of South American birds of prey (Falconiformes and Strigiformes). They indicated strong spatial patterns both across latitude and longitude, for the two groups. These patterns were then correlated with those expected by a bi-dimensional null model constructed to take into account South America continental edges. As considerable departures from the null model were observed, there may be other ecological or evolutionary explanations for spatial patterns in species richness. Variation seems to be related to habitat heterogeneity across the continent, especially when considering differences between habitats in the central and south-eastern portion of the continent and in the Andean region. This supports previous conclusions that habitat type and heterogeneity affect species richness and abundance at different spatial scales.     

The relative importance of environment, human activity and space in explaining species richness of South African bird orders

Aim To assess the relative importance of environmental (climate, habitat heterogeneity and topography), human (population density, economic prosperity and land transformation) and spatial (autocorrelation) influences, and the interactions between these predictor groups, on species richness patterns of various avifaunal orders. Location South Africa. Methods Generalized linear models were used to determine the amount of variation in species richness, for each order, attributable to each of the different predictor groups. To assess the relationships between species richness and the various predictor groups, a deviance statistic (a measure of goodness of fit for each model) and the percentage deviation explained for the best fitting model were calculated. Results Of the 12 avifaunal orders examined, spatially structured environmental deviance accounted for most of the variation in species richness in 11 orders (averaging 28%), and 50% or more in seven orders. However, orders comprising mostly water birds (Charadriiformes, Anseriformes, Ciconiformes) had a relatively large component of purely spatial deviance compared with spatially structured environmental deviance, and much of this spatial deviance was due to higher‐order spatial effects such as patchiness, as opposed to linear gradients in species richness. Although human activity, in general, offered little explanatory power to species richness patterns, it was an important correlate of spatial variation in species of Charadriiformes and Anseriformes. The species richness of these water birds was positively related to the presence of artificial water bodies. Main conclusions Not all bird orders showed similar trends when assessing, simultaneously, the relative importance of environmental, human and spatial influences in affecting bird species richness patterns. Although spatially structured environmental deviance described most of the variation in bird species richness, the explanatory power of purely spatial deviance, mostly due to nonlinear geographical effects such as patchiness, became more apparent in orders representing water birds. This was especially true for Charadriiformes, where the strong anthropogenic relationship has negative implications for the successful conservation of this group.     

中国大陆鸟类和兽类物种多样性的空间变异

生物多样性科学的研究重心之一是大尺度生物多样性空间分布规律及其形成机制。中国是世界上物种特丰富国家之一,了解我国物种多样性在空间上的变异情况,对于进一步认识大尺度上的生物多样性有重要意义。我们收集了全国205个自然保护区的鸟类和兽类物种分布信息,以G-F指数作为物种多样性的测度指标,利用地统计学方法分析了大陆鸟类和兽类物种多样性的空间变异特征。G-F指数是一种基于香农-威纳指数的信息测度,测度了研究地区环境分化程度和实际利用这种生态环境分化的生物类群多样性, 是一种对共同起源,相似生境需求的物种类群多样性的标准化多样性测度。结果发现,在东部季风区、西北干旱区和青藏高寒区内我国大陆鸟类多样性变异大部分都是由随机因素所引起的。兽类多样性的分布,在东部季风区和西北干旱区内是由随机因素所产生的,而在青藏高寒区,兽类多样性的总变异中99.9%是由空间依赖性所引起的,主要表现在71,492~1,020,000m空间尺度上,其分布表现出了强空间相关性。据此,大尺度上的物种多样性空间分布具有特定的规律,在生物多样性的保护行动中应加以考虑。     

基于植物-地形关系的物种丰富度空间格局预测——GAMs途径的一种应用

将基于样本调查数据的群落-生境因子回归分析与GIS支持下的植物属性空间格局预测结合起来,是国际上植被-环境关系定量研究的新途径。通用可加性模型（GAM）的非参数属性使之具有对不同数据类型的广泛适应性,成为这种“回归分析＋空间预测”途经的有效手段;不同程度上依赖于数字高程模型的环境空间数据集是实现空间预测的必要条件。介绍了这一新的研究途径,并应用于案例研究区域植物多样性指标空间格局的预测和分析。野外调查的一组样方地形特征指标和植物多样性指标（包括样方物种丰富度及乔木、灌木、草本、常绿木本、珍稀种类的丰富度）,分别作为预测变量和响应变量,建立GAM模型。结合研究区域10m分辨率的数字高程模型,对该区域植物物种丰富度的空间格局进行空间预测,并对预测模型和结果进行统计分析和检验。结果表明：（1）不同的多样性指标具有不同的模型结构和模拟效果,重复模拟的结果稳定性也不同,反映了所受地形因子影响的差异;（2）影响各多样性指标空间格局的地形变量主要是坡位和坡度等小尺度特征,大尺度海拔因素的影响并不显著;（3）模拟结果与独立检验数据的相关分析表明,对乔木种、草本种、珍稀种的模拟全部有效;对常绿种和样方物种总数的模拟部分有效;而对灌木种丰富度的预测基本失败。（4）模型预测变量有效性和全面性决定了模型对数据的解释能力,样本大小对模型的稳定性和可靠性也有显著影响。就地形因子对生境条件的代表性、模拟误差的来源及GAMs模型的优缺点和应用前景进行了讨论。     

Spatial autocorrelation and red herrings in geographical ecology

Aim Spatial autocorrelation in ecological data can inflate Type I errors in statistical analyses. There has also been a recent claim that spatial autocorrelation generates ‘red herrings’, such that virtually all past analyses are flawed. We consider the origins of this phenomenon, the implications of spatial autocorrelation for macro‐scale patterns of species diversity and set out a clarification of the statistical problems generated by its presence. Location To illustrate the issues involved, we analyse the species richness of the birds of western/central Europe, north Africa and the Middle East. Methods Spatial correlograms for richness and five environmental variables were generated using Moran's I coefficients. Multiple regression, using both ordinary least‐squares (OLS) and generalized least squares (GLS) assuming a spatial structure in the residuals, were used to identify the strongest predictors of richness. Autocorrelation analyses of the residuals obtained after stepwise OLS regression were undertaken, and the ranks of variables in the full OLS and GLS models were compared. Results Bird richness is characterized by a quadratic north–south gradient. Spatial correlograms usually had positive autocorrelation up to c. 1600 km. Including the environmental variables successively in the OLS model reduced spatial autocorrelation in the residuals to non‐detectable levels, indicating that the variables explained all spatial structure in the data. In principle, if residuals are not autocorrelated then OLS is a special case of GLS. However, our comparison between OLS and GLS models including all environmental variables revealed that GLS de‐emphasized predictors with strong autocorrelation and long‐distance clinal structures, giving more importance to variables acting at smaller geographical scales. Conclusion Although spatial autocorrelation should always be investigated, it does not necessarily generate bias. Rather, it can be a useful tool to investigate mechanisms operating on richness at different spatial scales. Claims that analyses that do not take into account spatial autocorrelation are flawed are without foundation.     

Trait-based species richness: ecology and macroevolution

Understanding the origins of species richness patterns is a fundamental goal in ecology and evolutionary biology. Much research has focused on explaining two kinds of species richness patterns: (i) spatial species richness patterns (e.g. the latitudinal diversity gradient), and (ii) clade-based species richness patterns (e.g. the predominance of angiosperm species among plants). Here, I highlight a third kind of richness pattern: trait-based species richness (e.g. the number of species with each state of a character, such as diet or body size). Trait-based richness patterns are relevant to many topics in ecology and evolution, from ecosystem function to adaptive radiation to the paradox of sex. Although many studies have described particular trait-based richness patterns, the origins of these patterns remain far less understood, and trait-based richness has not been emphasised as a general category of richness patterns. Here, I describe a conceptual framework for how trait-based richness patterns arise compared to other richness patterns. A systematic review suggests that trait-based richness patterns are most often explained by when each state originates within a group (i.e. older states generally have higher richness), and not by differences in transition rates among states or faster diversification of species with certain states. This latter result contrasts with the widespread emphasis on diversification rates in species-richness research. I show that many recent studies of spatial richness patterns are actually studies of trait-based richness patterns, potentially confounding the causes of these patterns. Finally, I describe a plethora of unanswered questions related to trait-based richness patterns.     

Elevational species richness patterns for vascular plants on Mount Kinabalu, Borneo

Aim  We quantify the elevational patterns of species richness for all vascular plants and some functional and taxonomic groups on a regional scale on a tropical mountain and discuss some possible causes for the observed patterns.
Location  Mount Kinabalu, Sabah, Borneo.
Methods  A data base containing elevational information on more than 28,000 specimens was analysed for vascular plant distribution, taking into account sampling effort. The total species richness pattern was estimated per 300-m elevational interval by rarefaction analyses. The same methods were also applied to quantify species richness patterns of trees, epiphytes, and ferns.
Results  Total species richness has a humped relationship with elevation, and a maximum species richness in the interval between 900 and 1200 m. For ferns and epiphytes the maximum species richness is found at slightly higher elevations, whereas tree species did not have a statistically significant peak in richness above the lowest interval analysed.
Main conclusions  For the first time a rigorous estimate of an elevational pattern in species richness of the whole vascular plant flora of a tropical mountain has been quantified. The pattern observed depends on the group studied. We discuss the differences between the groups and compare the results with previous studies of elevational patterns of species richness from other tropical areas. We also discuss the methods used to quantify the richness pattern and conclude that rarefaction gives an appropriate estimate of the species richness pattern.     

Species richness, species range size and ecological specialisation among African primates: geographical patterns and conservation implications

The geographical distribution of species richness and species range size of African anthropoid primates (catarrhines) is investigated and related to patterns of habitat and dietary niche breadth. Catarrhine species richness is concentrated in the equatorial regions of central and west Africa; areas that are also characterised by low average species range sizes and increased ecological specificity. Species richness declines with increasing latitude north and south of the equator, while average species range size, habitat and dietary breadth increase. Relationships between species richness, species range size and niche breadth remain once latitudinal and longitudinal effects have been removed. Among areas of lowest species richness, however, there is increased variation in terms of average species range size and niche breadth, and two trends are identified. While most such areas are occupied by a few wide-ranging generalists, others are occupied by range-restricted specialist species. That conservation efforts increasingly focus on regions of high species richness may be appropriate if these regions are also characterised by species that are more restricted in both their range size and their ecological versatility, although special consideration may be required for some areas of low species richness.