The mid-domain effect revisited

We revisit the proposition that boundary constraints on species' ranges cause species richness gradients (the mid-domain effect [MDE] hypothesis). In the absence of environmental gradients, species should not retain their observed range sizes as assumed by MDE models. Debate remains regarding the definition of domain limits, valid predictions for testing the models, and their statistical assessment. Empirical support for the MDE is varied but often weak, suggesting that geometric constraints on species' ranges do not provide a general explanation for richness gradients. Criticism of MDE model assumptions does not, however, imply opposition to the use of null models in ecology.     

The mid-domain effect and species richness patterns:what have we learned so far?

If species' ranges are randomly shuffled within a bounded geographical domain free of environmental gradients, ranges overlap increasingly toward the center of the domain, creating a "mid-domain" peak of species richness. This "mid-domain effect" (MDE) has been controversial both in concept and in application. Empirical studies assess the degree to which the evolutionary, ecological, and historical processes that undeniably act on individual species and clades produce geographical patterns that resemble those produced by MDE models. MDE models that resample empirical range size frequency distributions (RSFDs) balance the risk of underestimating and overestimating the role of MDE, whereas theoretical RSFDs are generally biased toward underestimating MDE. We discuss the inclusion of nonendemic species in MDE models, rationales for setting domain limits, and the validity of one- and two-dimensional MDE models. MDE models, though null models, are not null hypotheses to be simplistically rejected or accepted. They are a means of estimating the expected effect of geometric constraints within the context of multiple causality. We call for assessment of MDE on an equal statistical footing with other candidate explanations for richness gradients. Although some critics have categorically dismissed MDE, an overview of the 21 MDE studies published to date reveals a substantial signature of MDE in natural patterns and justifies continued work.     

Process-based models of species distributions and the mid-domain effect

Null models that place species ranges at random within a bounded geographical domain produce hump-shaped species richness gradients (the "mid-domain effect," or MDE). However, there is debate about the extent to which these models are a suitable null expectation for effects of environmental gradients on species richness. Here, I present a process-based framework for modeling species distributions within a bounded geographical domain. Analysis of null models consistent with the mid-domain hypothesis shows that MDEs are indeed likely to be ubiquitous consequences of geographical domain boundaries. Comparing the probability distributions of range locations for the process-based and randomization-based models reveals that randomization models probably overestimate the contribution of MDEs to empirical patterns of species richness, but it also indicates that other testable predictions from randomization models are likely to be robust. I also show how this process-based framework can be extended beyond null models to incorporate effects of environmental gradients within the domain. This study provides a first step toward an ecological theory of species distributions in geographical space that can incorporate both "geometric constraints" and effects of environmental gradients, and it shows how such a theory can inform our understanding of species richness gradients in nature.     

The missing Madagascan mid-domain effect

Species richness varies enormously across geographical gradients, a well-known phenomenon for which there are many hypothesized explanations. One recent hypothesis uses null models to demonstrate that random re-distribution of species' ranges within a given domain leads to a 'mid-domain effect' (MDE): increasing species richness towards the centre of the area. Madagascar is especially well-suited for empirical evaluation of mid-domain models by virtue of its large endemic fauna and its clearly defined boundaries. Lees et al. [ Biol. J. Linn. Soc. 67 (1999) 529] observed patterns of species richness consistent with MDEs in the Madagascan rainforest (a slim, north–south belt). In this study, we test one-dimensional and two-dimensional mid-domain model predictions for the birds and mammals of the entire island of Madagascar. When only latitudinal extents of species' distribution are considered, patterns of richness in Madagascar show an MDE. However, this pattern disappears for both taxa after accounting for the tendency of latitudinal bands nearer the middle of the country to be larger. Two-dimensional mid-domain model predictions of species richness are qualitatively opposite to observed patterns. Instead, island-wide spatial gradients of species richness in Madagascar relate strongly to patterns of primary productivity and amount of remaining natural habitat. Earlier work that showed a mid-domain peak within the rainforest biome (effectively after controlling for climate and natural habitat) seems likely to have reflected methodological artefacts. The classic case in which MDEs should occur is, in fact, inconsistent with the mid-domain hypothesis.     

When does diversity fit null model predictions? Scale and range size mediate the mid‐domain effect

Aim  Recently, a flurry of studies have focused on the extent to which geographical patterns of diversity fit mid-domain effect (MDE) null models. While some studies find strong support for MDE null models, others find little. We test two hypotheses that might explain this variation among studies: small-ranged groups of species are less likely than large-ranged species to show mid-domain peaks in species richness, and mid-domain null model predictions are less robust for smaller spatial extents than for larger spatial extents.
Location  We analyse data sets from elevational, riverine, continental and other domains from around the world.
Methods  We use a combination of Spearman rank correlations and binomial tests to examine whether differences within and among studies and domains in the predictive power of MDE null models vary with spatial scale and range size.
Results  Small-ranged groups of species are less likely to fit mid-domain predictions than large-ranged groups of species. At large spatial extents, diversity patterns of taxonomic groups with large mean range sizes fit MDE null model predictions better than did diversity patterns of groups with small mean range sizes. MDE predictions were more explanatory at larger spatial extents than at smaller extents. Diversity patterns at smaller spatial extents fit MDE predictions poorly across all range sizes. Thus, MDE predictions should be expected to explain patterns of species richness when ranges and the scale of analysis are both large.
Main conclusions  Taken together, the support for these hypotheses offers a more sophisticated model of when MDE predictions should be expected to explain patterns of species richness, namely when ranges and the scale of analysis are both large. Thus the circumstances in which the MDE is important are finite and apparently predictable.     

The mid-domain effect in ectomycorrhizal fungi: range overlap along an elevation gradient on Mount Fuji,Japan

Mid-domain effect (MDE) models predict that the random placement of species'' ranges within a bounded geographical area leads to increased range overlap and species richness in the center of the bounded area. These models are frequently applied to study species-richness patterns of macroorganisms, but the MDE in relation to microorganisms is poorly understood. In this study, we examined the characteristics of the MDE in richness patterns of ectomycorrhizal (EM) fungi, an ecologically important group of soil symbionts. We conducted intensive soil sampling to investigate overlap among species ranges and the applicability of the MDE to EM fungi in four temperate forest stands along an elevation gradient on Mount Fuji, Japan. Molecular analyses using direct sequencing revealed 302 EM fungal species. Of 73 EM fungal species found in multiple stands, 72 inhabited a continuous range along the elevation gradient. The maximum overlap in species range and the highest species richness occurred at elevations in the middle of the gradient. The observed richness pattern also fit within the 95% confidence interval of the mid-domain null model, supporting the role of the MDE in EM fungal richness. Deviation in observed richness from the mean of the mid-domain null estimation was negatively correlated with some environmental factors, including precipitation and soil C/N, indicating that unexplained richness patterns could be driven by these environmental factors. Our results clearly support the existence of microbial species'' ranges along environmental gradients and the potential applicability of the MDE to better understand microbial diversity patterns.     

The mid‐domain effect and habitat complexity applied to elevational gradients: Moss species richness in a temperate semihumid monsoon climate mountain of China

The utility of elevational gradients as tools to test either ecological hypotheses and delineate elevation‐associated environmental factors that explain the species diversity patterns is critical for moss species conservation. We examined the elevational patterns of species richness and evaluated the effects of spatial and environmental factors on moss species predicted a priori by alternative hypotheses, including mid‐domain effect (MDE), habitat complexity, energy, and environment proposed to explain the variation of diversity. Last, we assessed the contribution of elevation toward explaining the heterogeneity among sampling sites. We observed the hump‐shaped distribution pattern of species richness along elevational gradient. The MDE and the habitat complexity hypothesis were supported with MDE being the primary driver for richness patterns, whereas little support was found for the energy and the environmental factors.     

柴达木盆地水生植物多样性格局及多假说验证

物种多样性格局同时受到多个因子和过程的综合作用。以往对水生植物多样性格局形成机制的研究主要集中在几何限制、水分能量状况或随机过程等少数因子方面。该研究通过野外调查, 研究柴达木盆地水生植物沿经度和纬度梯度的分布格局, 并验证了对物种多样性分布格局影响较大的水分-能量假说、栖息地异质性假说、空间自相关、物种-面积效应和中域效应这5种假说。主要结果表明柴达木盆地水生植物多样性沿经度和纬度梯度均呈现“∩”形单峰格局。回归分析显示中域效应和物种-面积效应显著影响柴达木盆地水生植物多样性格局, 而水分-能量、栖息地异质性假说及空间自相关对该区域水生植物多样性格局影响较小。方差分解显示中域效应对柴达木盆地水生植物多样性经度和纬度格局的单独解释率分别为68.41%和66.91%, 该结果表明柴达木盆地水生植物多样性格局主要受几何限制和扩散限制影响。结合以往研究结果, 该研究进一步证实几何限制和随机效应可能是影响中国干旱区水生植物多样性分布格局的重要自然因素。     

Stronger Tests of Mechanisms Underlying Geographic Gradients of Biodiversity: Insights from the Dimensionality of Biodiversity

Inference involving diversity gradients typically is gathered by mechanistic tests involving single dimensions of biodiversity such as species richness. Nonetheless, because traits such as geographic range size, trophic status or phenotypic characteristics are tied to a particular species, mechanistic effects driving broad diversity patterns should manifest across numerous dimensions of biodiversity. We develop an approach of stronger inference based on numerous dimensions of biodiversity and apply it to evaluate one such putative mechanism: the mid-domain effect (MDE). Species composition of 10,000-km² grid cells was determined by overlaying geographic range maps of 133 noctilionoid bat taxa. We determined empirical diversity gradients in the Neotropics by calculating species richness and three indices each of phylogenetic, functional and phenetic diversity for each grid cell. We also created 1,000 simulated gradients of each examined metric of biodiversity based on a MDE model to estimate patterns expected if species distributions were randomly placed within the Neotropics. For each simulation run, we regressed the observed gradient onto the MDE-expected gradient. If a MDE drives empirical gradients, then coefficients of determination from such an analysis should be high, the intercept no different from zero and the slope no different than unity. Species richness gradients predicted by the MDE fit empirical patterns. The MDE produced strong spatially structured gradients of taxonomic, phylogenetic, functional and phenetic diversity. Nonetheless, expected values generated from the MDE for most dimensions of biodiversity exhibited poor fit to most empirical patterns. The MDE cannot account for most empirical patterns of biodiversity. Fuller understanding of latitudinal gradients will come from simultaneous examination of relative effects of random, environmental and historical mechanisms to better understand distribution and abundance of the current biota.     

Three-dimensional mid-domain predictions: geometric constraints in North American amphibian, bird, mammal and tree species richness patterns

The "mid-domain effect" (MDE) has received much attention as a candidate explanation for patterns in species richness over large geographic areas. Mid-domain models generate a central peak in richness when species ranges are placed randomly within a bounded geographic area (i.e. the domain). Until now, domain limits have been described mostly in one-dimension, usually latitude or elevation, and only occasionally in two-dimensions. Here we test 1-D, 2-D and, for the first time, 3-D mid-domain models and assess the effects of geometric constraints on species richness in North American amphibian, bird, mammal and tree species. Using spatially lagged simultaneous autoregressive models, empirical richness was predicted quite well by the mid-domain predictions and the spatial autoregressive term (45–92% R²). However, our results show that empirical species richness peaks do deviate from those of the MDE predictions in 3 dimensions. Variation explained (R²) by MDE predictions generally increased with increasing mean range size of the different biotic groups (from amphibian, to tree, mammal and finally bird data), and decreased with increasing dimensions being accounted for in the models. The results suggest geometric constraints alone can explain much of the variation in species richness with elevation, specifically with respect to the larger-range taxa, birds and mammals. Our analysis addresses many of the recent methodological criticisms directed at studies testing the MDE, and our results support the hypothesis that species diversity patterns are influenced by geometric constraints.     

One,two and three‐dimensional geometric constraints and climatic correlates of North American tree species richness

The ‘mid‐domain effect’ (MDE) has received much attention recently as a candidate explanation for patterns in species richness over large geographic areas. Mid‐domain models generate a central peak in richness when species ranges are randomly placed within a bounded geographic area (i.e. the domain). The most common terrestrial mid‐domain models published to date have been 1‐D latitude or elevation models and 2‐D latitude‐longitude models. Here, we test 1‐D, 2‐D and 3‐D mid‐domain models incorporating latitude, longitude and elevation, and assess independent and concurrent effects of geometric constraints and climatic variables on species richness of North American trees. We use both the traditional ‘global’ regression models as well as geographically weighted regressions (‘local’ models) to examine local variation in the contribution of MDE and climatic variables to species richness across the domain. Our results show that in some dimensions the contribution of MDE to patterns of species richness can be quite substantial, and we show that in most cases a combination of MDE and climate predicted empirical species richness best in both local and global models. For the North American domain, MDE in the elevation dimension is clearly important in describing patterns of empirical species richness. We also show that the assumption of stationarity in global models is not met in the North American domain and that results of these models mask complex patterns in both the effect of MDE on richness and the response of species richness to climate. In particular we show the increased explanatory role of MDE in predicting species richness as domain edges are approached. Our results support the hypothesis that geometric constraints contribute to species richness patterns and we suggest the mid‐domain effect should be considered alongside more traditional environmental correlates in understanding patterns of species diversity.     

The mid‐domain effect matters: simulation analyses of range‐size distribution data from Mount Kinabalu,Borneo

Aim In simulation exercises, mid‐domain peaks in species richness arise as a result of the random placement of modelled species ranges within simulated geometric constraints. This has been called the mid‐domain effect (MDE). Where close correspondence is found between such simulations and empirical data, it is not possible to reject the hypothesis that empirical species richness patterns result from the MDE rather than being the outcome (wholly or largely) of other factors. To separate the influence of the MDE from other factors we therefore need to evaluate variables other than species richness. The distribution of range sizes gives different predictions between models including the MDE or not. Here, we produce predictions for species richness and distribution of range sizes from one model without the MDE and from two MDE models: a classical MDE model encompassing only species with their entire range within the domain (range‐restricted MDE), and a model encompassing all species with the theoretical midpoint within the domain (midpoint‐restricted MDE). These predictions are compared with observations from the elevational pattern of range‐size distributions and species richness of vascular plants. Location Mount Kinabalu, Borneo. Methods The data set analysed comprises more than 28,000 plant specimens with information on elevation. Species ranges are simulated with various assumptions for the three models, and the species simulated are subsequently subjected to a sampling that simulates the actual collection of species on Mount Kinabalu. The resulting pattern of species richness and species range‐size distributions are compared with the observed pattern. Results The comparison of simulated and observed patterns indicates that an underlying monotonically decreasing trend in species richness with elevation is essential to explain fully the observed pattern of richness and range size. When the underlying trend is accounted for, the MDE model that restricts the distributions of theoretical midpoints performs better than both the classical MDE model and the model that does not incorporate geometric constraints. Main conclusions Of the three models evaluated here, the midpoint‐restricted MDE model is found to be the best for explaining species richness and species range‐size distributions on Mount Kinabalu.     

Small mammal species richness and turnover along elevational gradient in Yulong Mountain,Yunnan, Southwest China

Understanding the species diversity patterns along elevational gradients is critical for biodiversity conservation in mountainous regions. We examined the elevational patterns of species richness and turnover, and evaluated the effects of spatial and environmental factors on nonvolant small mammals (hereafter “small mammal”) predicted a priori by alternative hypotheses (mid‐domain effect [MDE], species–area relationship [SAR], energy, environmental stability, and habitat complexity]) proposed to explain the variation of diversity. We designed a standardized sampling scheme to trap small mammals at ten elevational bands across the entire elevational gradient on Yulong Mountain, southwest China. A total of 1,808 small mammals representing 23 species were trapped. We observed the hump‐shaped distribution pattern of the overall species richness along elevational gradient. Insectivores, rodents, large‐ranged species, and endemic species richness showed the general hump‐shaped pattern but peaked at different elevations, whereas the small‐ranged species and endemic species favored the decreasing richness pattern. The MDE and the energy hypothesis were supported, whereas little support was found for the SAR, the environmental stability hypothesis, and the habitat complexity. However, the primary driver(s) for richness patterns differed among the partitioning groups, with NDVI (the normalized difference vegetation index) and MDE being the most important variables for the total richness pattern. Species turnover for all small mammal groups increased with elevation, and it supported a decrease in community similarity with elevational distance. Our results emphasized for increased conservation efforts in the higher elevation regions of the Yulong Mountain.     

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.     

Adding energy gradients and long‐distance dispersal to a neutral model improves predictions of Madagascan bird diversity

Macroecological patterns are likely the result of both stochastically neutral mechanisms and deterministic differences between species. In Madagascar, the simplest stochastically neutral hypothesis – the mid‐domain effects (MDE) hypothesis – has already been rejected. However, rejecting the MDE hypothesis does not necessarily refute the existence of all other neutral mechanisms. Here, we test whether adding complexity to a basic neutral model improves predictions of biodiversity patterns. The simplest MDE model assumes that: (1) species' ranges are continuous and unfragmented, (2) are randomly located throughout the landscape, and (3) can be stacked independently and indefinitely. We designed a simulation based on neutral theory that allowed us to weaken each of these assumptions incrementally by adjusting the habitat capacity as well as the likelihood of short‐ and long‐distance dispersal. Simulated outputs were compared to four empirical patterns of bird diversity: the frequency distributions of species richness and range size, the within‐island latitudinal diversity gradient, and the distance‐decay of species compositional similarity. Neutral models emulated empirical diversity patterns for Madagascan birds accurately. The frequency distribution of range size, latitudinal diversity gradient, and the distance‐decay of species compositional similarity could be attributed to stochastic long‐distance migration events and zero‐sum population dynamics. However, heterogenous environmental gradients improved predictions of the frequency distribution of species richness. Patterns of bird diversity in Madagascar can broadly be attributed to stochastic long‐distance migration events and zero‐sum population dynamics. This implies that rejecting simple hypotheses, such as MDE, does not serve as evidence against stochastic processes in general. However, environmental gradients were necessary to explain patterns of species richness and deterministic differences between species are probably important for explaining the distributions of narrow‐range and endemic species.     

Type and spatial structure of distribution data and the perceived determinants of geographical gradients in ecology: the species richness of African birds

Aim Studies exploring the determinants of geographical gradients in the occurrence of species or their traits obtain data by: (1) overlaying species range maps; (2) mapping survey‐based species counts; or (3) superimposing models of individual species’ distributions. These data types have different spatial characteristics. We investigated whether these differences influence conclusions regarding postulated determinants of species richness patterns. Location Our study examined terrestrial bird diversity patterns in 13 nations of southern and eastern Africa, spanning temperate to tropical climates. Methods Four species richness maps were compiled based on range maps, field‐derived bird atlas data, logistic and autologistic distribution models. Ordinary and spatial regression models served to examine how well each of five hypotheses predicted patterns in each map. These hypotheses propose productivity, temperature, the heat–water balance, habitat heterogeneity and climatic stability as the predominant determinants of species richness. Results The four richness maps portrayed broadly similar geographical patterns but, due to the nature of underlying data types, exhibited marked differences in spatial autocorrelation structure. These differences in spatial structure emerged as important in determining which hypothesis appeared most capable of explaining each map's patterns. This was true even when regressions accounted for spurious effects of spatial autocorrelation. Each richness map, therefore, identified a different hypothesis as the most likely cause of broad‐scale gradients in species diversity. Main conclusions Because the ‘true’ spatial structure of species richness patterns remains elusive, firm conclusions regarding their underlying environmental drivers remain difficult. More broadly, our findings suggest that care should be taken to interpret putative determinants of large‐scale ecological gradients in light of the type and spatial characteristics of the underlying data. Indeed, closer scrutiny of these underlying data — here the distributions of individual species — and their environmental associations may offer important insights into the ultimate causes of observed broad‐scale patterns.     

面积、温度及分布区限制对物种丰富度海拔格局的影响: 以秦岭太白山为例

 物种丰富度的分布格局及其形成机制是生态学研究的热点。以往的研究主要描述丰富度的格局, 而对其形成机制研究较少, 且主要集中于探讨单个因子或过程的影响。物种丰富度同时受到多个因子和过程的综合作用, 面积、温度及物种分布区限制被认为是控制山地物种丰富度海拔格局的主要因素, 三者同时沿海拔梯度而变化, 同时作用于丰富度的海拔格局。幂函数种-面积关系(SAR)、生态学代谢理论(MTE)及中域效应假说(MDE)分别基于以上3个因素, 从机制上解释了物种丰富度 的海拔格局。探讨这些假说的相对影响对研究物种丰富度的大尺度格局及其形成机制具有重要意义。方差分离方法有利于分解不同因素的影响, 为此, 该文以秦岭太白山的植物物种丰富度为例, 采用方差分离和逐步回归方法, 分析了SAR、MTE及MDE对物种丰富度海拔格局的影响。结果表明, 太白山的植物物种丰富度沿海拔梯度呈单峰分布格局, 但丰富度峰值存在类群差异; 对太白山所有植物物种丰富度的垂直格局而言, SAR、MTE及MDE分别解释了其物种丰富度随海拔变化的66.4%、19.8%和37.9%, 共同解释了84.6%, 在消除其他因素的影响后, SAR和MTE的独立影响较高(分别为25.5%和17.7%), 而MDE的独立影响不显著; 分类群研究则发现, 苔藓植物丰富度的海拔格局主要受MDE的影响, 蕨类植物丰富度的海拔格局同时受到SAR、MTE以及MDE的影响, 而种子植物物种丰富度的海拔格局主要受SAR和MTE影响。     

What drives elevational patterns of diversity? A test of geometric constraints,climate and species pool effects for pteridophytes on an elevational gradient in Costa Rica

Aim We studied pteridophyte species richness between 100 m and 3400 m along a Neotropical elevational gradient and tested competing hypotheses for patterns of species richness. Location Elevational transects were situated at Volcán Barva in the Braulio Carrillo National Park and La Selva Biological Station (100–2800 m) and Cerro de la Muerte (2700–3400 m), both on the Atlantic slope of Costa Rica, Central America. Method We analysed species richness on 156 plots of 20 × 20 m and measured temperature and humidity at four elevations (40, 650, 1800 and 2800 m). Species richness patterns were regressed against climatic variables (temperature, humidity, precipitation and actual evapotranspiration), regional species pool, area and predicted species number of a geometric null model (the mid‐domain effect, MDE). Results The species richness of the 484 recorded species showed a hump‐shaped pattern with elevation with a richness peak at mid‐elevations (c. 1700 m). The MDE was the single most powerful explanatory variable in linear regression models, but species richness was also associated strongly with climatic variables, especially humidity and temperature. Area and species pool were associated less strongly with observed richness patterns. Main conclusions Geometric models and climatic models exclusive of geometric constraints explained comparable amounts of the elevational variation in species richness. Discrimination between these two factor complexes is not possible based on model fits. While overall fits of geometric models were high, large‐ and small‐ranged species were explained by geometric models to different extents. Species with narrow elevational ranges clustered at both ends of the gradient to a greater extent than predicted by the MDE null models used here. While geometric models explained much of the pattern in species richness, we cannot rule out the role of climatic factors (or vice versa) because the predicted peak in richness from geometric models, the empirical peak in richness and the overlap in favourable environmental conditions all coincide at middle elevations. Mid‐elevations offer highest humidity and moderate temperatures, whereas at high elevations richness is reduced due to low temperatures, and at low elevations by reduced water availability due to high temperatures.     

Continental and regional ranges of North American mammals: Rapoport's rule in real and null worlds

Aim To assess the relationship between species richness and distribution within regions arranged along a latitudinal gradient we use the North American mammalian fauna as a study case for testing theoretical models. Location North America. Methods We propose a conceptual framework based on a fully stochastic mid‐domain model to explore geographical patterns of range size and species richness that emerge when the size and position of species ranges along a one‐dimensional latitudinal gradient are randomly generated. We also analyse patterns for the mammal fauna of North America by comparing empirical results from a biogeographical data base with predictions based on randomization null models. Results We confirmed the validity of Rapoport's rule for the mammals of North America by documenting gradients in the size of the continental ranges of species. Additionally, we demonstrated gradients of mean regional range size that parallel those of continental range. Our data also demonstrated that mean range size, measured both as a continental or a regional variable, is significantly correlated with the geographical pattern in species richness. All these patterns deviated sharply from null models. Main conclusions Rapoport's statement of an areographic relationship between species distribution and richness is highly relevant in modern discussions about ecological patterns at the geographical scale.     

The elevational gradient in Andean bird species richness at the local scale: a foothill peak and a high-elevation plateau

A monotonic decline in species richness with increasing elevation has often been considered a general pattern, but recent evidence suggests that the dominant pattern is hump-shaped with maximum richness occurring at some mid-elevation point. To analyse the relationship between species richness and elevation at a local scale we surveyed birds from lowlands to timberline in the Bolivian Andes. We divided the transect into 12 elevational belts of 250 m and standardized species richness in each belt with both individual- and sample-based rarefaction and richness estimation. The empirical data were then correlated to four explanatory variables: 1) area per elevational belt, 2) elevation (also representing ecosystem productivity), 3) a mid-domain effect (MDE) null model of geometrically constrained empirical range sizes, and 4) a hump-shaped model derived empirically for South American birds representing the regional species pool hypothesis. Local species richness peaked at ca 1000 m elevation, declined sharply to ca 1750 m, and then remained roughly constant. Elevation was the best single predictor, accounting for 78–85% of the variance in the empirical data. A multiple regression model with elevation, area, and MDE explained 85–90% of the variance. Monte Carlo simulations showed that the richness peak at 1000 m is the result of an overlap of two distinct avifaunas (lowland and highland) and that the correlation to MDE in the multiple regression was likely spurious. We recommend complementing correlation analyses involving MDE predictions with an examination of the distribution of range midpoints. The steep decline at mid-elevations was mainly due to a rapid loss of lowland species. The high-elevation plateau is striking and unexpected, but has also been found previously. It cannot be explained at present and exemplifies that despite several decades of research elevational gradients are still not well understood.