Climate and history explain the species richness peak at mid-elevation for Schizothorax fishes (Cypriniformes: Cyprinidae) distributed in the Tibetan Plateau and its adjacent regions

Aim  We studied elevational species richness patterns of Schizothorax fishes and identified the roles of ecological and evolutionary factors in shaping the patterns of elevational diversity.
Location  The Tibetan Plateau and its adjacent regions.
Methods  We assembled distribution and altitude data for all Schizothorax species using the literature. We merged ecological and evolutionary approaches to test the relationships between species richness and ecological factors (climate, area, the mid-domain effect) or evolutionary factors (diversification rates and time of colonization).
Results  We found that species richness of Schizothorax fishes peaked at mid-elevations. Rainfall, area, the mid-domain effect and diversification rate were weak predictors of the richness pattern. Temperature showed a nonlinear relationship with species richness. Temperature and time of colonization were the most important variables in explaining the elevational diversity pattern.
Main conclusion  Our findings indicate that the time-for-speciation effect and niche conservatism play important roles in variation of species richness.     

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.     

Epiphytic bryophyte diversity and range distributions along an elevational gradient in Marojejy,Madagascar

Describing spatial variation in species richness and understanding its links to ecological mechanisms are complementary approaches for explaining geographical patterns of richness. The study of elevational gradients holds enormous potential for understanding the factors underlying global diversity. This paper investigates the pattern of species richness and range-size distribution of epiphytic bryophytes along an elevational gradient in Marojejy National Park, northeast Madagascar. The main objectives are to describe bryophyte species composition and endemism in Marojejy National Park, to describe the species richness and distribution patterns of epiphytic bryophytes along an elevational gradient from 250 m to 2050 m and to evaluate the explanatory value of environmental variables for the observed patterns. Bryophyte samples were collected following a nested design with four hierarchical levels: elevational belts, plots, quadrats, and microplots. In total, 254 epiphytic bryophyte species were recorded, comprising 157 liverworts and 97 mosses. Twenty-three of these are endemic to Madagascar. Species richness exhibits a hump-shaped pattern along the elevational gradient, peaking at 1,250 m. Eighty-seven percent of the total recorded species have a range distribution lower than 1,000 m, at which point 36% are restricted to these single elevations. Our results suggest that mean temperature, relative humidity, and vapor pressure deficit play important roles in shaping the richness pattern observed in this study. While the liverwort richness pattern did not correlate to vapor pressure deficit and responded only weakly to relative humidity, the richness pattern shown by mosses correlates well with mean temperature, relative humidity, and vapor pressure deficit.     

Elevational gradients of diversity for lizards and snakes in the Hengduan Mountains,China

Comparing elevational gradients across a wide spectrum of climatic zones offers an ideal system for testing hypotheses explaining the altitudinal gradients of biodiversity. We document elevational patterns of lizard and snake species richness, and explore how land area and climatic factors may affect species distributions of lizards and snakes. Our synthesis found 42 lizard species and 94 snake species known from the Hengduan Mountains. The lizards are distributed between 500 and 3500 m, and the snakes are distributed between 500 and 4320 m. The relationship between species richness and elevation for lizards and snakes is unimodal. Land area explains a significant amount of the variation in lizard and snake species richness. The cluster analysis reveals pronounced distinct assemblages for lizards and snakes to better reflect the vertical profiles of climate in the mountains. Climatic variables are strongly associated with lizard and snake richness along the elevational gradient. The data strongly implicate water availability as a key constraint on lizard species richness, and annual potential evapotranspiration is the best predictor of snake species richness along the elevational gradient in the Hengduan Mountains.     

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.     

Environmental determinants of geographic butterfly richness pattern in eastern China

A long-standing task for ecologists and biogeographers is to reveal the underlying mechanisms accounting for the geographic pattern of species diversity. The number of hypotheses to explain geographic variation in species diversity has increased dramatically during the past half century. The oldest and the most popular one is environmental determination. However, seasonality, the intra-annual variability in climate variables has been rarely related to species richness. In this study, we assessed the relative importance of three environmental hypotheses: energy, seasonality and heterogeneity in explaining species richness pattern of butterflies in Eastern China. In addition, we also examined how environmental variables affect the relationship between species richness of butterflies and seed plants at geographic scale. All the environmental factors significantly affected butterfly richness, except sampling area and coefficient of variation of mean monthly precipitation. Energy and seasonality hypotheses explained comparable variation in butterfly richness (42.3 vs. 39.3 %), higher than that of heterogeneity hypothesis (25.9 %). Variation partitioning indicated that the independent effect of seasonality was much lower (0.0 %) than that of energy (5.5 %) and heterogeneity (6.3 %). However, seasonality performed better in explaining butterfly richness in topographically complex areas, reducing spatial autocorrelation in butterfly richness, and more strongly affect the association between butterflies and seed plants. The positive relationship between seed plant richness and butterfly richness was most likely the result of environmental variables (especially seasonality) influencing them in parallel. Insufficient sampling may partly explain the low explanatory power of environmental model (52.1 %) for geographic butterfly richness pattern. Our results have important implications for predicting the response of butterfly diversity to climate change.     

Latitudinal diversity gradients in bryophytes and woody plants: Roles of temperature and water availability

It remains unclear whether the latitudinal diversity gradients of micro- and macro-organisms are driven by the same macro-environmental variables. We used the newly completed species catalog and distribution information of bryophytes in China to explore their spatial species richness patterns, and to investigate the underlying roles of energy availability, climatic seasonality, and environmental heterogeneity in shaping these patterns. We then compared these patterns to those found for woody plants. We found that, unlike woody plants, mosses and liverworts showed only weakly negative latitudinal trends in species richness. The spatial patterns of liverwort richness and moss richness were overwhelmingly explained by contemporary environmental variables, although explained variation was lower than that for woody plants. Similar to woody plants, energy and climatic seasonality hypotheses dominate as explanatory variables but show high redundancy in shaping the distribution of bryophytes. Water variables, that is, the annual availability, intra-annual variability and spatial heterogeneity in precipitation, played a predominant role in explaining spatial variation of species richness of bryophytes, especially for liverworts, whereas woody plant richness was affected most by temperature variables. We suggest that further research on spatial patterns of bryophytes should incorporate the knowledge on their ecophysiology and evolution.     

Elevational patterns of species richness and endemism for some important taxa in the Hengduan Mountains, southwestern China

We describe the elevational patterns of species richness and endemism of some important taxa in the Hengduan Mountains, southwest China. Species richness data came from publications, an online database, herbaria and field work. Species richness was estimated by rarefaction and interpolation. The Hengduan Mountains region was divided into a southern and northern subregion, and all species were assigned to four groups based on their distributional range within this region. The conditional autoregressive model (CAR) was used to relate species richness and explanatory variables. The elevational patterns of total, endemic and non-endemic species richness, at subregion and entire region scales, presented to be unimodal and peaked at similar elevations. Area size was strongly related with species richness, and was more powerful in explaining variation in species richness in the northern subregion than in the southern subregion. A single climatic variable (mean annual rainfall, potential evapotranspiration or moisture index) showed a weak relationship with the elevational pattern of species richness. Area and climatic variables together explained more than 67% of the variation in non-endemic richness, 53% in total richness, and 50% in endemic richness. There were three patterns of endemism at the generic level with increasing elevation: namely endemism increased, decreased, or peaked at middle elevations. All selected taxa have experienced rapid speciation and evolution within this region, which plays an important role in the uniform elevational patterns of total, endemic and non-endemic richness, and in the multiform elevational patterns of endemism. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Orchid Species Richness along Elevational and Environmental Gradients in Yunnan,China

The family Orchidaceae is not only one of the most diverse families of flowering plants, but also one of the most endangered plant taxa. Therefore, understanding how its species richness varies along geographical and environmental gradients is essential for conservation efforts. However, such knowledge is rarely available, especially on a large scale. We used a database extracted from herbarium records to investigate the relationships between orchid species richness and elevation, and to examine how elevational diversity in Yunnan Province, China, might be explained by mid-domain effect (MDE), species–area relationship (SAR), water–energy dynamics (WED), Rapoport’s Rule, and climatic variables. This particular location was selected because it is one of the primary centers of distribution for orchids. We recorded 691 species that span 127 genera and account for 88.59% of all confirmed orchid species in Yunnan. Species richness, estimated at 200-m intervals along a slope, was closely correlated with elevation, peaking at 1395 to 1723 m. The elevational pattern of orchid richness was considerably shaped by MDE, SAR, WED, and climate. Among those four predictors, climate was the strongest while MDE was the weakest for predicting the elevational pattern of orchid richness. Species richness showed parabolic responses to mean annual temperature (MAT) and mean annual precipitation (MAP), with maximum richness values recorded at 13.7 to 17.7°C for MAT and 1237 to 1414 mm for MAP. Rapoport’s Rule also helped to explain the elevational pattern of species richness in Yunnan, but those influences were not entirely uniform across all methods. These results suggested that the elevational pattern of orchid species richness in Yunnan is collectively shaped by several mechanisms related to geometric constraints, size of the land area, and environments. Because of the dominant role of climate in determining orchid richness, our findings may contribute to a better understanding of the potential effects of climate change on orchid diversity, and the development of conservation strategies for orchids.     

物种丰富度垂直分布格局及影响机制

物种丰富度分布格局是一定地域内物种丰富度沿三维空间的立体分布,包括物种丰富度在经度、纬度和垂直梯度(海拔高度和海水深度)三个维度上的空间分异。近年来物种多样性的垂直分布格局与机制研究得到了生物地理学家和生态学家的重视。物种丰富度的垂直分布格局存在多种类型,但随海拔增加而物种数减少的单调递减模型和中海拔物种丰富度最高的单峰模型较为常见。目前在机制研究中验证较多的是气候稳定性、生物因子(种间相互作用)、能量、生境异质性、干扰、进化时间、物种分化速率、面积、中域效应(mid-domain effect)、生态位保守性(niche conservatism)等假说和机制。物种丰富度的分布格局是多方面因素综合作用的结果;由于地理、地形、气候、地质演化历史、物种库和进化历史、物种分化速率、干扰等差异,在不同地区存在着特别的物种丰富度空间分布格局和机制;处于同一地区的不同类群的物种也因进化扩散历史和生态适应能力不同而呈现多样化的分布格局。因此,对不同地区和类群的物种丰富度格局和机制进行研究应具体分析后才能得到可信结论。     

Water–energy,land‐cover and heterogeneity drivers of the distribution of plant species richness in a mountain region of the European Alps

Aim To evaluate the relative importance of water–energy, land‐cover, environmental heterogeneity and spatial variables on the regional distribution of Red‐Listed and common vascular plant species richness. Location Trento Province (c. 6200 km²) on the southern border of the European Alps (Italy), subdivided regularly into 228 3′ × 5′ quadrants. Methods Data from a floristic inventory were separated into two subsets, representing Red‐Listed and common (i.e. all except Red‐Listed) plant species richness. Both subsets were separately related to water–energy, land‐cover and environmental heterogeneity variables. We simultaneously applied ordinary least squares regression with variation partitioning and hierarchical partitioning, attempting to identify the most important factors controlling species richness. We combined the analysis of environmental variables with a trend surface analysis and a spatial autocorrelation analysis. Results At the regional scale, plant species richness of both Red‐Listed and common species was primarily related to energy availability and land cover, whereas environmental heterogeneity had a lesser effect. The greatest number of species of both subsets was found in quadrants with the largest energy availability and the greatest degree of urbanization. These findings suggest that the elevation range within our study region imposes an energy‐driven control on the distribution of species richness, which resembles that of the broader latitude gradient. Overall, the two species subsets had similar trends concerning the relative importance of water–energy, land cover and environmental heterogeneity, showing a few differences regarding the selection of some predictors of secondary importance. The incorporation of spatial variables did not improve the explanatory power of the environmental models and the high original spatial autocorrelation in the response variables was reduced drastically by including the selected environmental variables. Main conclusions Water–energy and land cover showed significant pure effects in explaining plant species richness, indicating that climate and land cover should both be included as explanatory variables in modelling species richness in human‐affected landscapes. However, the high degree of shared variation between the two groups made the relative effects difficult to separate. The relatively low range of variation in the environmental heterogeneity variables within our sampling domain might have caused the low importance of this complex factor.     

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。     

Energy–water and seasonal variations in climate underlie the spatial distribution patterns of gymnosperm species richness in China

Studying the pattern of species richness is crucial in understanding the diversity and distribution of organisms in the earth. Climate and human influences are the major driving factors that directly influence the large‐scale distributions of plant species, including gymnosperms. Understanding how gymnosperms respond to climate, topography, and human‐induced changes is useful in predicting the impacts of global change. Here, we attempt to evaluate how climatic and human‐induced processes could affect the spatial richness patterns of gymnosperms in China. Initially, we divided a map of the country into grid cells of 50 × 50 km² spatial resolution and plotted the geographical coordinate distribution occurrence of 236 native gymnosperm taxa. The gymnosperm taxa were separated into three response variables: (a) all species, (b) endemic species, and (c) nonendemic species, based on their distribution. The species richness patterns of these response variables to four predictor sets were also evaluated: (a) energy–water, (b) climatic seasonality, (c) habitat heterogeneity, and (d) human influences. We performed generalized linear models (GLMs) and variation partitioning analyses to determine the effect of predictors on spatial richness patterns. The results showed that the distribution pattern of species richness was highest in the southwestern mountainous area and Taiwan in China. We found a significant relationship between the predictor variable set and species richness pattern. Further, our findings provide evidence that climatic seasonality is the most important factor in explaining distinct fractions of variations in the species richness patterns of all studied response variables. Moreover, it was found that energy–water was the best predictor set to determine the richness pattern of all species and endemic species, while habitat heterogeneity has a better influence on nonendemic species. Therefore, we conclude that with the current climate fluctuations as a result of climate change and increasing human activities, gymnosperms might face a high risk of extinction.     

Exploring anthropogenic and natural processes shaping fern species richness along elevational gradients

Aim (1) To explore the impact of land use, climate and environmental heterogeneity on fern species richness along a complete elevational gradient, and (2) to evaluate the relative importance of the three groups of variables within different elevational intervals. Location A temperate mountain region (55,507 km²) of Italy on the southern border of the European Alps divided into a regular grid of 1476 cells (grain 35.7 km²). Methods We applied multiple regression (spatial and non‐spatial) to determine the relative influence of the three groups of variables on species richness, including variation partitioning at two scales. We considered the whole gradient (all 1476 cells) to explain the overall elevational pattern of species richness, and we grouped the cells into elevational intervals of 500 m in order to evaluate the explanatory power of the predictors within different zones along the gradient. Results Species richness showed a hump‐shaped pattern with elevation, forming a plateau between 800 and 1500 m. The lowest species richness was found in warm and relatively dry disturbed lowlands. Moving upwards, the greatest species richness was found in forest‐dominated mid‐elevations with high environmental heterogeneity. At high elevations dominated by open natural habitats, where temperature and precipitation were relatively low, species richness declined but less sharply than in the lowlands. Although it was impossible to separate the effects of the three groups of predictors along the whole gradient, the analysis of separate elevational intervals shed light on their relative importance. The decline of species richness within lowlands was mainly related to a combined effect of deforestation and low environmental heterogeneity. In the middle part of the gradient, habitat heterogeneity and topographic roughness were positively associated with species richness. The richness decline within high‐elevation areas was related mostly to climatic constraints. Main conclusions Human impact due to land‐use modifications strongly affects the elevational pattern of species richness. It is therefore increasingly important to adopt a multiple‐hypothesis approach, taking anthropogenic effects explicitly into account when describing ecological processes along elevational gradients.     

Terrestrial gastropod diversity in an alpine region: disentangling effects of elevation,area, geometric constraints,habitat type and land‐use intensity

Elevational gradients have proven to be useful to examine key factors shaping species diversity patterns. This study examines the effects of elevation, area, geometric constraints, habitat type, environmental factors and land‐use intensity on terrestrial gastropod diversity patterns in Val Müstair, an alpine region influenced by different types of agricultural land use in the eastern Alps, Switzerland. Gastropods were sampled using a standardized method in 180 sites spanning an elevational range from 1215 to 2770 m and covering 11 different habitat types. A total of 11 102 specimens representing 70 species were recorded. Observed species richness, statistically estimated true richness (Chao) and geographically interpolated observed richness were used as measures of local species richness. The comparison of three alternative models (environmental, geometric constraints and gastropod abundance models) revealed that the environmental model explained most of the variation in all measures of local diversity. The best model combining the predictors of all three models showed that elevation, soil pH and habitat type affected all measures of local species richness. Similar analyses conducted at the level of 150‐m elevational bands showed that elevation was again the best predictor of species richness, while the area of the elevational band did not have any influence. However, in one out of the two measures of band species richness, the best model indicated that geometric constraints may also contribute to the observed pattern. At both spatial scales, all measures of species richness decreased with increasing elevation. An analysis of species‐specific life‐history traits showed that adult shell size of land snails decreased with increasing elevation. Most species with large shells were confined to lower elevations. The results indicate that environmental factors might be most important in shaping the observed patterns.     

Global species–energy relationship in forest plots: role of abundance,temperature and species climatic tolerances

Aim To evaluate the strength of evidence for hypotheses explaining the relationship between climate and species richness in forest plots. We focused on the effect of energy availability which has been hypothesized to influence species richness: (1) via the effect of productivity on the total number of individuals (the more individuals hypothesis, MIH); (2) through the effect of temperature on metabolic rate (metabolic theory of biodiversity, MTB); or (3) by imposing climatic limits on species distributions. Location Global. Methods We utilized a unique ‘Gentry‐style’ 370 forest plots data set comprising tree counts and individual stem measurements, covering tropical and temperate forests across all six forested continents. We analysed variation in plot species richness and species richness controlled for the number of individuals by using rarefaction. Ordinary least squares (OLS) regression and spatial regressions were used to explore the relative performance of different sets of environmental variables. Results Species richness patterns do not differ whether we use raw number of species or number of species controlled for number of individuals, indicating that number of individuals is not the proximate driver of species richness. Productivity‐related variables (actual evapotranspiration, net primary productivity, normalized difference vegetation index) perform relatively poorly as correlates of tree species richness. The best predictors of species richness consistently include the minimum temperature and precipitation values together with the annual means of these variables. Main conclusion Across the world's forests there is no evidence to support the MIH, and a very limited evidence for a prominent role of productivity as a driver of species richness patterns. The role of temperature is much more important, although this effect is more complex than originally assumed by the MTB. Variation in forest plot diversity appears to be mostly affected by variation in the minimum climatic values. This is consistent with the ‘climatic tolerance hypothesis’ that climatic extremes have acted as a strong constraint on species distribution and diversity.     

Influences of interpolation of species ranges on elevational species richness gradients

Interpolation of species ranges has been a common approach to compensate for the unevenness or incompleteness in sampling effort in studies of geographic species richness gradients. However, potential biases introduced by this estimation method remain unclear. Here, we presented an explicit examination of the influences of one‐dimensional interpolation on elevational species richness gradients, and discussed potential causes and processes of these influences. We conducted intensive surveys of birds along the elevational gradients of the Ailao Mountains, southwestern China, and compared richness patterns based on interpolation with raw data as well as estimated data from rarefaction and Chao1 non‐parametric estimator; we also compared results of multiple linear regressions and hierarchical partitioning analyses explaining these four measures of richness. Actual evapotranspiration (AET) and the mid‐domain effect (MDE) were highly correlated and separately provided a good potential explanation for the unimodal richness pattern in the Ailao Mountains, with modifying and suppressive effects of other variables such as area. Interpolation consistently and significantly increased the effects of AET/MDE, while it reduced contributions of area and human disturbance. Our results demonstrated that while compensating for biases in sampling effort, interpolation may also spuriously fill genuine distribution gaps, and tend to underestimate the effects of the non‐monotonic or discontinuous influencing factors that are responsible for these gaps, and overestimate the effects of other factors actually suppressed by these factors. These influences were most strong for species with relatively medium elevational ranges. We conclude that at the regional scale, interpolation method is a potential source of bias in identifying and explaining species richness gradients and should be used with careful consideration. It may be advantageous to adopt other robust estimation methods besides interpolation to gain a more accurate assessment of species richness and a more objective understanding of their underlying mechanisms.     

Energy determines broad pattern of plant distribution in Western Himalaya

Several factors describe the broad pattern of diversity in plant species distribution. We explore these determinants of species richness in Western Himalayas using high‐resolution species data available for the area to energy, water, physiography and anthropogenic disturbance. The floral data involves 1279 species from 1178 spatial locations and 738 sample plots of a national database. We evaluated their correlation with 8‐environmental variables, selected on the basis of correlation coefficients and principal component loadings, using both linear (structural equation model) and nonlinear (generalised additive model) techniques. There were 645 genera and 176 families including 815 herbs, 213 shrubs, 190 trees, and 61 lianas. The nonlinear model explained the maximum deviance of 67.4% and showed the dominant contribution of climate on species richness with a 59% share. Energy variables (potential evapotranspiration and temperature seasonality) explained the deviance better than did water variables (aridity index and precipitation of the driest quarter). Temperature seasonality had the maximum impact on the species richness. The structural equation model confirmed the results of the nonlinear model but less efficiently. The mutual influences of the climatic variables were found to affect the predictions of the model significantly. To our knowledge, the 67.4% deviance found in the species richness pattern is one of the highest values reported in mountain studies. Broadly, climate described by water–energy dynamics provides the best explanation for the species richness pattern. Both modeling approaches supported the same conclusion that energy is the best predictor of species richness. The dry and cold conditions of the region account for the dominant contribution of energy on species richness.     

Patterns of species richness for vascular plants in China's nature reserves

Explaining the heterogeneous distribution of biodiversity across the Earth has long been a challenge to ecologists and biogeographers. Here, we document the patterns of plant species richness for different taxonomic groups in China's nature reserves, and discuss their possible explanations at national and regional scales, using vascular plant richness data coupled with information on climate and topographical variables. We found that water deficit, energy and elevation range (a surrogate of habitat heterogeneity) represent the primary explanations for variation in plant species richness of the nature reserves across China. There are consistent relationships between species richness and climate and habitat heterogeneity for different taxonomic vascular plant groups at the national scale. Habitat heterogeneity is strongly associated with plant richness in all regions, whereas climatic constraints to plant diversity vary regionally. In the regions where energy is abundant or water is scarce, plant richness patterns were determined by water and habitat heterogeneity, whereas in the region with low energy inputs, water interacting with energy, and habitat heterogeneity determined its species richness pattern. Our results also suggest that energy variables alone do not represent the primary predictor of plant richness.     

Saprotrophic and ectomycorrhizal fungi exhibit contrasting richness patterns along elevational gradients in cool-temperate montane forests

Increasing evidence suggests that elevational gradients of soil fungal richness are highly variable, but few studies have examined how diversity components of each guild contribute to overall fungal diversity. Here, we aimed to disentangle the relationships between total, saprotrophic, and ectomycorrhizal fungal richness, and environmental factors across elevational gradients in cool-temperate montane forests. We observed that total and saprotrophic richness decreased but ectomycorrhizal richness increased with increase in elevation. Elevational range size and nestedness analyses illustrated that saprotrophic and ectomycorrhizal source communities were located at lower and higher elevations, respectively. The observed total and saprotrophic richness were directly influenced by soil properties and indirectly influenced by climate and plant communities. Ectomycorrhizal fungal richness was affected by climate and the dominance of ectomycorrhizal trees. We highlight that two directional source–sink dynamics lead to opposite elevational patterns between saprotrophic and ectomycorrhizal fungal richness, shaping the variation in elevational richness gradients.