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.     

Habitat is more important than climate and animal richness at shaping latitudinal variation in plant diversity in China

Species data from 249 National Nature Reserves in China were used to identify potential underlying drivers of latitudinal gradients in plant diversity. We used generalized linear models to assess correlations between predictor and plant species richness. Variance partitioning was then used to decompose the variation in plant richness into different taxonomic levels among the three groups of predictors (i.e., climate, habitat and animal). We found that species richness showed significant latitudinal trends in richness (p?<?0.001). This remained true when examining gymnosperms, angiosperms and ferns individually. Climate and habitat variables explained more variation in richness across different plant groups than did animal richness. Annual precipitation was the best climate variable across different taxonomic plants groups, and soil pH and elevation range were the best habitat variables across different taxonomic plant groups. The independent effects of habitat variables were higher than that of climate and animal variables across different taxonomic plant groups. Finally, climate, habitat heterogeneity, and animal richness explain 48.8% of the variation in total species richness, 28.2% in gymnosperm richness, 44.2% in angiosperm richness, and 38.9% in fern richness.     

Disentangling environmental correlates of vascular plant biodiversity in a Mediterranean hotspot

We determined the environmental correlates of vascular plant biodiversity in the Baetic‐Rifan region, a plant biodiversity hotspot in the western Mediterranean. A catalog of the whole flora of Andalusia and northern Morocco, the region that includes most of the Baetic‐Rifan complex, was compiled using recent comprehensive floristic catalogs. Hierarchical cluster analysis (HCA) and detrended correspondence analysis (DCA) of the different ecoregions of Andalusia and northern Morocco were conducted to determine their floristic affinities. Diversity patterns were studied further by focusing on regional endemic taxa. Endemic and nonendemic alpha diversities were regressed to several environmental variables. Finally, semi‐partial regressions on distance matrices were conducted to extract the respective contributions of climatic, altitudinal, lithological, and geographical distance matrices to beta diversity in endemic and nonendemic taxa. We found that West Rifan plant assemblages had more similarities with Andalusian ecoregions than with other nearby northern Morocco ecoregions. The endemic alpha diversity was explained relatively well by the environmental variables related to summer drought and extreme temperature values. Of all the variables, geographical distance contributed by far the most to spatial turnover in species diversity in the Baetic‐Rifan hotspot. In the Baetic range, climate was the most significant driver of nonendemic species beta diversity, while lithology and climate were the main drivers of endemic beta diversity. Despite the fact that Andalusia and northern Morocco are presently separated by the Atlantic Ocean and the Mediterranean Sea, the Baetic and Rifan mountain ranges have many floristic similarities – especially in their western ranges – due to past migration of species across the Strait of Gibraltar. Climatic variables could be shaping the spatial distribution of endemic species richness throughout the Baetic‐Rifan hotspot. Determinants of spatial turnover in biodiversity in the Baetic‐Rifan hotspot vary in importance between endemic and nonendemic species.     

Phylogenetic conservatism and biogeographic affinity influence woody plant species richness–climate relationships in eastern Eurasia

Mechanisms underlying species richness patterns remain a central yet controversial issue in biology. Climate has been regarded as a major determinant of species richness. However, the relative influences of different evolutionary processes, (i.e. niche conservatism, diversification rate and time for speciation) on species richness–climate relationships remain to be tested. Here, using newly compiled distribution maps for 11 422 woody plant species in eastern Eurasia, we estimated species richness patterns for all species and for families with tropical and temperate affinities separately, and explored the phylogenetic signals in species richness patterns of different families and their relationships with contemporary climate and climate change since the Last Glacial Maximum (LGM). We further compared the effects of niche conservatism (represented by contemporary-ancestral climatic niches differences), diversification rate and time for speciation (represented by family age) on variation in the slopes of species richness–climate relationships. We found that winter coldness was the best predictor for species richness patterns of most tropical families while Quaternary climate change was the best predictor for those of most temperate families. Species richness patterns of closely-related families were more similar than those of distantly-related families within eudicots, and significant phylogenetic signals characterized the slopes of species richness–climate relationships across all angiosperm families. Contemporary-ancestral climatic niche differences dominated variation in the relationships between family-level species richness and most climate variables. Our results indicate significant phylogenetic conservatism in family-level species richness patterns and their relationships with contemporary climate within eudicots. These findings shed light on the mechanisms underlying large-scale species richness patterns and suggest that ancestral climatic niche may influence the evolution of species richness–climate relationships in plants through niche conservatism.     

Space-for-time substitution reveals a hump-shaped distribution of dung beetles

Unraveling how climate change impacts the diversity and distribution patterns of organisms is a major concern in ecology, especially with climate-sensitive species, such as dung beetles. Often found in warmer weather conditions, beetles are used as bio-indicators of environmental conditions. By using an altitudinal gradient as a proxy for climate change (i.e., space-for-time substitution), we assessed how changes in climatic variables, such as temperature and precipitation, impact patterns of dung beetle diversity and distribution in the Peruvian Andes. We recorded dung beetle diversity using three different types of baits, feces, carrion, and fruits, distributed in 18 pitfall traps in five different altitudinal sites (from 900 to 2500 m, 400 m apart from each other) in the rainy and dry season. We found that (i) dung beetle richness and abundance were influenced by the climate gradient, (ii) seasonality influenced beetle richness, which was high in the wet season, but did not influence abundance, (iii) dung beetle richness and abundance fit to a hump-shaped distribution pattern along the altitudinal gradient, and (iv) species richness is the beta-diversity component that best describes the composition of dung beetle species along the altitudinal gradient. Our data show that the distribution and diversity of dung beetles are different at larger scales, with different patterns resulting from the response of species to both abiotic and biotic factors.     

黄河流域被子植物和陆栖脊椎动物丰富度格局及其影响因子

生物多样性的大尺度空间分布格局及其形成机制一直是生态学和生物地理学的核心内容。黄河流域是我国重要的生态屏障, 明确该区域动植物多样性分布格局及其影响因素, 对我国黄河流域生态保护和高质量发展具有重要意义。本研究通过收集黄河流域被子植物和陆栖脊椎动物分布数据, 结合气候、环境异质性和人类活动等信息, 探讨了黄河流域被子植物和陆栖脊椎动物物种丰富度格局及其主要影响因素。结果表明, 黄河流域被子植物和陆栖脊椎动物物种丰富度在区域尺度具有相似的分布格局: 南部山地动植物物种丰富度最高, 而东部高寒区和北部干旱区物种丰富度最低。回归树模型表明, 冠层高度范围和净初级生产力范围分别是黄河流域被子植物和陆栖脊椎动物物种丰富度最重要的预测因子; 当移除空间自相关影响后, 环境异质性和气候因子依然对区域尺度的动植物物种丰富度具有较高且相似的解释度。表明环境异质性和气候共同决定了黄河流域被子植物和陆栖脊椎动物物种丰富度格局, 而人类使用土地面积并不是影响黄河流域动植物物种丰富度格局的主要因子。因此, 在未来的研究中若针对不同区域筛选出更精准的环境驱动因子或选用更多不同类别的环境异质性因子进行分析, 将有助于更深入理解物种多样性格局的成因。     

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.     

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.     

Weak links: 'Rapoport's rule' and large-scale species richness patterns

Many hypotheses have been proposed to explain regional species richness patterns. Among these, ‘Rapoport's rule’ has sparked considerable controversy by stating that the latitudinal gradient in species richness can be explained indirectly as a function of narrower geographic ranges for species at low latitudes. Annual climatic variability, or deviation from mean climatic conditions, has been hypothesized to moderate this phenomenon. Furthermore, taxa that avoid much of this seasonality, such as temperate zone insects that enter diapause or species that migrate, were predicted to show reduced latitudinal gradients in richness. I test the suggested link between ‘Rapoport's rule’ and species richness for two higher level insect taxa as well as for the class Mammalia. Although these taxa exhibit the well-known latitudinal gradient in species richness, simple annual climatic variability and deviation from mean annual climatic conditions provide very poor predictions of species richness in each of them. Potential evapotranspiration, a measurement of ambient climatic energy, explains most of the observed variance in regional species richness patterns for all three taxa, consistent with the species richness-energy hypothesis. I find no support for an indirect link between ‘Rapoport's rule’ and terrestrial species richness patterns in North America.     

Does climate determine broad‐scale patterns of species richness? A test of the causal link by natural experiment

Aim Broad‐scale spatial patterns of species richness are very strongly correlated with climatic variables. If there is a causal link, i.e. if climate directly or indirectly determines patterns of richness, then when the climatic variables change, richness should change in the manner that spatial correlations between richness and climate would predict. The present study tests this prediction using seasonal changes in climatic variables and bird richness. Location We used a grid of equal area quadrats (37 000 km²) covering North and Central America as far south as Nicaragua. Methods Summer and winter bird distribution data were drawn from monographs and field guides. Climatic data came from published sources. We also used remotely sensed NDVI (normalized difference vegetation index — a measure of greenness). Results Bird species richness changes temporally (between summer and winter) in a manner that is close to, but statistically distinguishable from, the change one would predict from models relating the spatial variation in richness at a single time to climatic variables. If one further takes into account the seasonal changes in NDVI and within‐season variability of temperature and precipitation, then winter and summer richness follow congruent, statistically indistinguishable patterns. Main conclusions Our results are consistent with the hypothesis that climatic variables (temperature and precipitation) and vegetation cover directly or indirectly influence patterns of bird species richness.     

中国裸子植物的物种多样性格局及其影响因子

物种多样性的大尺度空间格局是宏观生态学和生物地理学研究的核心问题之一。本文利用中国裸子植物分布数据, 结合气候、地形等环境信息, 分析了中国裸子植物物种多样性的大尺度格局及其影响因素, 比较了不同类群之间物种多样性格局和主导因子的差异, 并探讨了裸子植物在植物区系中所占比重的地理格局。结果表明, 中国裸子植物的物种多样性总体上呈现南高北低的趋势, 物种多样性在横断山区最高。在裸子植物的三个主要类群中, 松柏亚纲的物种多样性格局与整体相似, 买麻藤亚纲的多样性高值区则出现在中国西北部的干旱地区, 苏铁亚纲的分布区较为狭窄, 主要集中在南方地区。线性回归分析结果表明, 空间异质性和降水因子对中国裸子植物多样性格局的解释率最高, 末次冰期以来的气温变化、海拔高差和能量因子次之。这表明中国裸子植物物种多样性的格局受到了多种因素的影响, 其中空间异质性和降水因子影响最大。进一步分析发现, 物种多样性格局的主导因子在不同类群之间具有显著差异, 这可能反映了这些类群的进化历史以及生理适应的差异。裸子植物与被子植物的比例具有明显的空间格局: 在东部、南部气候环境优越的地区, 裸子植物与被子植物的比例低于0.06; 而在西部、北部等气候环境比较恶劣的地区, 裸子植物的比例则显著上升。回归分析表明, 能量和水分因子显著影响了裸子植物与被子植物的比例。随着能量的降低和降水的减少, 裸子植物与被子植物的比例会显著升高, 这可能是由于被子植物在温暖湿润地区具有较强竞争优势, 但裸子植物对极端环境具有更好的适应。     

The environmental basis of North American species richness patterns among Epicauta (Coleoptera: Meloidae)

Understanding regional variability in species richness is necessary for conservation efforts to succeed in the face of large-scale environmental deterioration. Several analyses of North American vertebrates have shown that climatic energy provides the best explanation of contemporary species richness patterns. The paucity of analyses of insect diversity patterns, however, remains a serious obstacle to a general hypothesis of spatial variation in diversity. We collected species distribution data on a North American beetle genus, Epicauta (Coleoptera: Meloidae) and tested several major diversity hypotheses. These beetles are generally grasshopper egg predators as larvae, and angiosperm herbivores as adults. Epicauta richness is highest in the hot, dry American southwest, and decreases north and east, consistent with the species richness-energy hypothesis. Potential evapotranspiration, which is also the best predictor of richness patterns among North American vertebrates, explains 80.2% of the variability in Epicauta species richness. Net primary productivity and variables measuring climatic heat energy only (such as PET) are not generally comparable, though they are sometimes treated as if they were equivalent. We conclude that the species richness-energy hypothesis currently provides a better overall explanation for Epicauta species richness patterns in North America than other major diversity hypotheses. The observed relationship between climatic energy and regional species richness may provide significant insight into the response of ecological communities to climate change.     

Geographical patterns of community‐based tree species richness in Chinese mountain forests: the effects of contemporary climate and regional history

The relationship between climate/productivity and historical/regional contingency and their relative influence on geographical patterns of species richness (GPSR) are still unresolved. Based on field data from 1494 plots from forests on 63 mountains across China, we document the GPSR for forest communities. Regression tree and generalized linear models were used to explore the discreteness and gradient of the distribution of tree species richness (α‐diversity), and to estimate the correlations of climate, historical floristic region, and local habitat with species richness. The collinearity between climatic variables and region were further disentangled; and the spatial autocorrelation in the patterns of α‐diversity and the residuals of alternative predictive models were compared. Overall, 75% of variation in plot‐based α‐diversity of trees was accounted for by all variables included, and about 66.5%, 64.5% and 27.9% by climate, region, and local habitat respectively. Importantly, the explanatory power of these variables differed in particular for coniferous, deciduous broadleaved and evergreen broadleaved species. Ambient temperature was more important for α‐diversity of trees than were the other climatic variables across China. Spatial autocorrelation in the pattern of α‐diversity could be accounted for mainly by spatial variation climate. The concordance between tree α‐diversity, historical flora, contemporary climate, and Quaternary climate change mode suggests the climate/productivity and historical/regional contingency both contribute to the GPSR in a complimentary manner. Taken together, our results provide unique evidence to link of the effects of contemporary climate and historical climate change on species richness across scales.     

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.     

中国蚂蚁丰富度地理分布格局及其与环境因子的关系

物种丰富度分布格局及其形成机制的研究对于生物多样性保护具有重要意义。为了了解中国蚂蚁物种丰富度分布格局,利用中国省级尺度蚂蚁物种分布数据和环境信息,结合GIS和数理统计方法,探讨蚂蚁物种丰富度的地理分布格局与环境因子之间的关系。研究结果表明:(1)蚂蚁丰富度随纬度增加呈逐渐递减趋势,但缺乏显著的经度梯度。丰富度最高的地区主要集中在南方省份,我国北方、西北干旱区和青藏高原北部地区丰富度较低;(2)简单线性回归分析表明,能量、水分和季节性因素中,影响蚂蚁物种丰富度最强的因子分别为最冷月均温(TEMmin)(R2adj=0.532)、年均降水量(PREC)(R2adj=0.376)和年温度变化范围(TEMvar)(R2adj=0.539),而单个生境异质性因子对蚂蚁物种丰富度的影响均不显著;(3)最优模型由年均温(TEM)、海拔变化范围(ELErange)和年温度变化范围(TEMvar)组成,能够解释68.4%的蚂蚁丰富度地理分异。鉴于海拔变化范围更多地反映与温度相关的生境异质性,因此温度是限制中国蚂蚁分布的最重要因素。另外,分析结果还表明,海南、贵州、江西、四川、安徽和山西等6省蚂蚁区系调查最不充分,是未来发现蚂蚁新分布的热点地区。     

Climate stability is more important than water–energy variables in shaping the elevational variation in species richness

Changes in climate variables have an important impact on the prediction and protection of elevational biodiversity. Gaps exist in our understanding of the elevational distribution patterns in seed plant species richness. Our study examines the importance of climate variables in shaping the elevational variation in species richness. The importance of boundary constraint was also taken into account. Model selection based on Akaike's information criterion was used to select the best explaining climate models. Variation partitioning was used to assess the independent and joint effects of water–energy, physiological tolerance, and environmental stability variables on species richness. Our results revealed that: (a) Both raw (boundary constraint unreduced) and estimated (boundary constraint reduced) species richness showed large elevational variation, with the peak species richness seen at midelevations. The environmental variables were better at explaining the distribution pattern of species richness along the elevation, when the effect of boundary constraint was reduced; (b) the physiological tolerance and environmental stability variables explained more variation in raw and estimated species richness compared with the water–energy variables. Estimated species richness was better explained (98.6%) by the environmental variables than raw species richness (94%); (c) the water‐related variables generally had the highest independent effect on raw and estimated species richness and were dominant in shaping the elevational variation in species richness. Our findings quantify the influence of boundary constraint on the distribution pattern of species along an altitudinal gradient and compare the relative contributions of environmental stability and water–energy in explaining the altitude gradient distribution pattern of plant seed species.     

Net primary productivity and seasonality of temperature and precipitation are predictors of the species richness of the Damselflies in the Amazon

Several hypotheses have been proposed to explain the mechanisms that generate temporal and spatial species richness patterns. We tested four common hypotheses (water, energy, climatic heterogeneity and net primary productivity) to evaluate which factors best explain patterns of Zygoptera species richness. Of these, we predicted that climatic heterogeneity would be the most important predictor for Zygoptera richness patterns. We sampled communities of adult Zygoptera in 100 small Amazonian streams. Based on generalized linear mixed models (GLMM), we found that net primary productivity and climatic heterogeneity comprised the best model of Zygoptera species richness in Amazonian streams, with an pseudo r² of 39.5%. Results indicate that species richness increases by one species per 1 kg of biomass per square meter in NPP, or with an increase of 2 °C in air temperature variability. Our work corroborates a recent study with other taxa in Brazilian Bioms. This suggests that temporal variation in climate and net primary productivity are important predictors of the macroecological patterns of richness for aquatic organisms in tropical regions.     

Species distribution modelling as a macroecological tool: a case study using New World amphibians

Although species distribution modelling (SDM) is widely accepted among the scientific community and is increasingly used in ecology, conservation biology and biogeography, methodological limitations generate potential problems for its application in macroecology. Using amphibian species richness in North and South America, we compare species richness patterns derived from SDM maps and ‘expert’ maps to evaluate if: 1) richness patterns derived from SDM are biased toward climate‐based explanations for diversity when compared to expert maps, since SDM methods are typically based on climatic variables; and 2) SDM is a reliable tool for generating richness maps in hyperrich regions where point occurrence data are limited for many species. We found that although three widely used SDM methods overestimated amphibian species richness in grid cells when compared to expert richness maps in both North and South America due to systematic overestimation of range sizes, diversity gradients were reasonably robust at broad scales. Further, climatic variables statistically explained patterns of richness at similar levels among the different richness sources, although climatic relationships were stronger in the much better known North America than in South America. We conclude that in the face of the high deforestation rates coupled with incomplete data on species distributions, especially in the tropics, SDM represents a useful macroecological tool for investigating broad‐scale richness patterns and the dynamics between species richness and climate.     

Factors controlling the spatial species richness pattern of four groups of terrestrial vertebrates in an area between two different biogeographic regions in northern Spain

Aim To examine the influence of environmental variables on species richness patterns of amphibians, reptiles, mammals and birds and to assess the general usefulness of regional atlases of fauna. Location Navarra (10,421 km²) is located in the north of the Iberian Peninsula, in a territory shared by Mediterranean and Eurosiberian biogeographic regions. Important ecological patterns, climate, topography and land‐cover vary significantly from north to south. Methods Maps of vertebrate distribution and climatological and environmental data bases were used in a geographic information systems framework. Generalized additive models and partial regression analysis were used as statistical tools to differentiate (A) the purely spatial fraction, (B) the spatially structured environmental fraction and (C) the purely environmental fraction. In this way, we can evaluate the explanatory capacity of each variable, avoiding false correlations and assessing true causality. Final models were obtained through a stepwise procedure. Results Energy‐related features of climate, aridity and land‐cover variables show significant correlation with the species richness of reptiles, mammals and birds. Mammals and birds exhibit a spatial pattern correlated with variables such as aridity index and vegetation land‐cover. However, the high values of the spatially structured environmental fraction B and the low values of the purely environmental fraction A suggest that these predictor variables have a limited causal relationship with species richness for these vertebrate groups. An increment in land‐cover diversity is correlated with an increment of specific richness in reptiles, mammals and birds. No variables were found to be statistically correlated with amphibian species richness. Main conclusions Although aridity and land‐cover are the best predictor variables, their causal relationship with species richness must be considered with caution. Historical factors exhibiting a similar spatial pattern may be considered equally important in explaining the patterns of species richness. Also, land‐cover diversity appears as an important factor for maintaining biological diversity. Partial regression analysis has proved a useful technique in dealing with spatial autocorrelation. These results highlight the usefulness of coarsely sampled data and cartography at regional scales to predict and explain species richness patterns for mammals and birds. The accuracy of models appears to be related to the range perception of each group and the scale of the information.