Forest regeneration affects dung beetle assemblages (Coleoptera: Scarabaeinae) in the southern Brazilian Atlantic Forest

The Brazilian Atlantic Forest is one of the most diverse environments, but it is also one of the most threatened areas in terms of loss of biodiversity and ecosystem services. Assessment of changes in the community structure during the recovery of forests can be performed using indicator organisms. Dung beetles perform several ecological functions and show high sensitivity to natural and anthropogenic environmental changes. This study aimed to investigate the effect of regeneration time of Atlantic Forest sites on structure of Scarabaeinae assemblages. We sampled dung beetles using ten baited pitfall traps per site, in six sites grouped into three classes of forest regeneration time (~30, ~60 and >80 years) in the southern Brazilian Atlantic Forest, during January 2015. A total of 520 individuals belonging to 16 species and nine genera of dung beetles were sampled. Rarefied species richness did not differ between sites with different regeneration times. Average species richness and abundance of Scarabaeinae was smaller in areas of shorter recovery time. True alpha diversity was higher in areas with intermediate recovery whereas Shannon diversity showed higher values in areas of shorter recovery. Approximately 29?% of the variation in abundance data of Scarabaeinae was explained by environmental variables, with one-third of this variation explained also by spatial predictors. External factors such as landscape management and farming practices in the surroundings must be taken into consideration in management plans and the management of natural areas for the recovery of biodiversity in the Atlantic Forest. These external factors can considerably affect the structure of communities and lead to scenarios of greater diversity in intermediate regeneration sites due to the heterogeneity of the landscape.     

Geographic sampling bias in the South African Frog Atlas Project: implications for conservation planning

Quality conservation planning requires quality input data. However, the broad scale sampling strategies typically employed to obtain primary species distribution data are prone to geographic bias in the form of errors of omission. This study provides a quantitative measure of sampling bias to inform accuracy assessment of conservation plans based on the South African Frog Atlas Project. Significantly higher sampling intensity near to cities and roads is likely to result in overstated conservation priority and heightened conservation conflicts in urban areas. Particularly well sampled protected areas will also erroneously appear to contribute highly to amphibian biodiversity targets. Conversely, targeted sampling in the arid northwest and along mountain ranges is needed to ensure that these under-sampled regions are not excluded from conservation plans. The South African Frog Atlas Project offers a reasonably accurate picture of the broad scale west-to-east increase in amphibian richness and abundance, but geographic bias may limit its applicability for fine scale conservation planning. The Global Amphibian Assessment species distribution data offered a less biased alternative, but only at the cost of inflated commission error.     

Geographic patterns in the distribution of Palearctic songbirds

A database was created of digitized equal area distribution maps of 3,036 phylogenetic species of Palearctic songbirds. Biogeographic patterns are reported for two data sets: (1) including all passeriform bird species reported as breeding within the boundaries of our study map, (2) passeriform species restricted in their distribution to our study region, thus excluding the partly extra-limital taxa. With respect to the data set excluding partly extra-limital taxa, the average range size is 238 grid cells (grid cell area: 4,062 km²). Analysis of the geographic distribution of species richness for the full data set showed several hotspot regions, mostly located in mountainous areas. The index of range-size rarity identified similar hotspot regions as that for species richness, albeit that the range-size rarity de-emphasized the central Siberian hotspot. Range-size rarity hotspots that are not evident on the measure of species richness concern a great number of islands. Much more prominent on the index of range-size rarity are the Atlas Mountains of northern Africa, the Jabal al Akhdar region in NE Libya, and the eastern border of the Mediterranean. Restricting the analysis of geographic variation to the 25% of the species with smallest ranges resulted in a greatly simplified pattern of hotspots. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

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。     

Between-group differences in the Iberian dung beetle species-area relationship (Coleoptera: Scarabaeidae)

Between-group α- and β-diversity differences were derived from species-area relationships fitted to field data. The accuracy of spatial richness variation predictions based on area size was also checked. The log-log model (log S = c + z log A) was found to be the best-fit linear model, with slopes (z) ranging from 0.089 to 0.142. Between-group comparisons of z (slope) and q (intercept) parameters, using the S = q + cA^z curvilinear regression model, corroborated early results, indicating a lower β-diversity (slope) for Scarabaeinae than for Geotrupinae and Aphodiinae. The latter group, probably more sensitive to environmental heterogeneity, should contribute more to species richness in large areas. α-Diversity is greater for Aphodiinae, more relevant to local diversity (1 km²), than for Scarabaeinae and considerably greater for these two groups than for Geotrupinae. As earlier results show that the richness of a single dung pat is rather more a function of the Scarabaeinae species pool, richness on dung pat scales is probably due more to the between-dropping mobile Scarabaeinae, while Aphodiinae contribute mainly to local and regional pool richness. Nearly 88 % of the total richness variance is explained by area size. This percentage decreases to 37 % when the spatial structure of area size and species number are extracted. The corresponding figures for Scarabaeinae, Aphodiinae and Geotrupinae are 44, 22 and 31 %, respectively.     

Sampling effort and species richness assessment: a case study on Brazilian spiders

The knowledge on the geographical distribution of species is essential for building biogeographical and macroecological hypotheses. However, information on this regard is not distributed uniformly in space and usually come from biased sampling. The aim of this study is to quantify the influence of spatial distribution of sampling effort on the assessment of spider species richness in Brazil. We used a database of spider distribution records in Brazil, based on the taxonomic and biodiversity survey literature. The results show that the Atlantic Forest was better sampled and had the highest spider species richness among the Brazilian biomes. The Amazon, though having large collecting gaps and high concentration of records around major cities and rivers, showed the second highest number of species. The Pampa had a large number of records, but these are concentrated near a major city in the transition zone with the Atlantic Forest. The Cerrado, Caatinga and Pantanal had shown to be poorly sampled and, consequently, were among the lesser known biomes regarding the spider fauna. A linear regression analysis showed that the spider species richness in Brazil is strongly correlated to the number of records. However, we have identified areas potentially richest in species, which strongly deviate from the predicted by our analyses. Our results show that it is possible to access the spatial variation in species richness, as long as the variation in sampling effort is taken into account.     

Altitudinal gradients in stream fish diversity and the prevalence of diadromy in the Sixaola River basin,Costa Rica

Landscape-scale patterns of freshwater fish diversity and assemblage structure remain poorly documented in many areas of Central America, while aquatic ecosystems throughout the region have been impacted by habitat degradation and hydrologic alterations. Diadromous fishes may be especially vulnerable to these changes, but there is currently very little information available regarding their distribution and abundance in Central American river systems. We sampled small streams at 20 sites in the Sixaola River basin in southeastern Costa Rica to examine altitudinal variation in the diversity and species composition of stream fish assemblages, with a particular focus on diadromous species. A set of environmental variables was also measured in the study sites to evaluate how changes in fish assemblage structure were related to gradients in stream habitat. Overall, fish diversity and abundance declined steeply with increasing elevation, with very limited species turnover. The contribution of diadromous fishes to local species richness and abundance increased significantly with elevation, and diadromous species dominated assemblages at the highest elevation sites. Ordination of the sampling sites based on fish species composition generally arranged sites by elevation, but also showed some clustering based on geographic proximity. The dominant gradient in fish community structure was strongly correlated with an altitudinal habitat gradient identified through ordination of the environmental variables. The variation we observed in stream fish assemblages over relatively small spatial scales has significant conservation implications and highlights the ecological importance of longitudinal connectivity in Central American river systems.     

The distribution and diversity of Chironomidae (Insecta: Diptera) in western Finnish Lapland, with special emphasis on shallow lakes

Aim Predictions of aquatic ecosystem change with global warming require basic data that accurately reflect the environmental conditions underlying species distributions. However, in remote arctic areas such baseline data are scarce. We assess the influence of environmental variables on chironomid distribution and taxon richness in shallow, isothermal lakes in a poorly studied arctic region. We pay particular attention to community variation along the treeline ecotonal zone where many environmental variables change abruptly in a relatively small area. Location Lake transect in Finnish Lapland spanning from boreal coniferous forest to arctic tundra. Methods Chironomid assemblages were determined from surface‐sediment samples of 50 shallow (< 10 m) natural lakes. Abundance and taxon richness data were related to 24 limnological variables using canonical ordination techniques (DCA, CCA, RDA). A Monte Carlo permutation procedure was used to assess the explanatory power of single variables. Between‐vegetation zone differences of richness were tested for statistical significance using one‐way anova . Results In total, 7771 chironomid head capsules were identified, consisting of 13 species, 10 species groups, four subgenera, 41 genera, four genus groups, five types and three with uncertain taxonomic affiliation. A hump‐shaped relationship between taxon richness and elevation was noted along the study transect with a peak in taxon richness occurring in mountain birch woodland lakes at middle elevations, decreasing then towards both warmer and colder ends of the elevation/temperature gradient. Of the individual parameters, sediment organic content, total organic carbon, pH, and lake‐specific air temperature accounted for the greatest amount of variation in the chironomid data. Main conclusions Maximum taxon richness occurred at mid‐elevations where aquatic algae also reached their maximum diversity. This area coincides with an ecotonal transitional zone, which seems more likely to account for the peak in species richness. Our study demonstrates that the factors most strongly affecting chironomids in Finnish Lapland (i.e. temperature, and ecosystem features) are those that with great probability will also change as a result of future climate change. This will likely have an effect on the distribution of chironomids in subarctic and arctic areas.     

Global concordance in diversity patterns of vascular plants and terrestrial vertebrates

The factors that determine large-scale patterns of species richness are poorly understood. In particular, biologists have not determined the relative roles of taxon-specific characteristics that influence diversification and distribution, and region-specific features that promote and constrain diversity. We show that the numbers of species of vascular plants and of four terrestrial vertebrate taxa (mammals, birds, reptiles and amphibians) vary in parallel across 296 geographic areas covering most of the globe, even after accounting for sample area, climate, topographic heterogeneity and differences between continents. Thus, a common set of regional characteristics and processes appears to shape patterns of species richness in a diverse set of taxa, despite substantial differences in their biological traits.     

Mapping patterns of ferns species richness through the use of herbarium data

This paper aims to analyse the spatial patterns of sampling effort and species richness of pteridophyte in a well-investigated region as Tuscany, Italy, by using data stored from a geodatabase storing information on the specimens preserved in the main herbaria of the region. A total of 6,905 records about pteridophyte specimens were extracted from the geodatabase, and 5,638 of such specimens were studied through the use of spatial statistical techniques. The data about the sampling effort and species richness were analysed in relation to topographical variables to assess any significant relationship. Specimen-based rarefaction techniques were used to compare areas with different number of detected species. The analysis of the sampling effort data showed a nonhomogeneous distribution of herbarium data, with some areas being intensively sampled and others being almost unsampled. Thus, the geographical distribution of specimens was extremely clustered. The comparison across geographical areas through specimen-based rarefaction curves showed great differences in species richness and sampling completeness. The analysis of the residuals of species–area relationships evidenced that the distance to water bodies was the only significant topographical variable in controlling species diversity.     

Endemic regions of the vascular flora of the peninsula of Baja California,Mexico

Question: Can we recognize areas of high endemism and high endemic richness, using data from collections, and what are the ecological variables that best explain these areas? Location: Peninsula of Baja California, Mexico. Methods: We analysed the distribution of 723 endemic vascular plants species along the peninsula of Baja California and neighbouring islands distributed in 218 cartographic cells 15’ x 20’ in size. By means of a residual analysis, we identified areas of significantly high endemic species richness, and we calculated the degree of endemicity (or rarity) in each cell by giving to each species a weight factor inversely proportional to the land area it covers. Results: Nine regions of high‐endemicity and/or high endemic species richness were found. Discussion and conclusions: The analyses of rarity and endemic species richness showed two contrasting scenarios: High endemicity values in oceanic and sky islands accounts for a high number of species with a restricted distribution, promoted most likely by genetic isolation and high environmental heterogeneity. High endemic richness along the peninsular coast is related to ecotonal transition along vegetation types. After correcting for collection effort (i.e. the number of specimens collected within a cell), we found the phytogeographic region and altitudinal heterogeneity to be the variables that best predicted endemic richness. Both high endemism and high endemic richness have distinct geographic patterns within our study region. The nine endemic regions provide elements for priority definitions in future conservation programs.     

Iberian–Balearic fern regions and their explanatory variables

This article delineates the compositional regions present in the Iberian–Balearic fern flora and compares these regions to previously proposed biogeographic units. It also assesses the extent to which environmental variables could explain the regions and the fern species richness gradients found within them. A combination of 40 previously published and new maps were used to compile the distribution of 123 pteridophytes on a 50 × 50 km UTM grid. Cluster analysis of the resulting 257 squares was used to classify 10 regions based on fern species assemblages. Discriminant function analysis identified the environmental variables that best explained these fern composition regions. Using generalized linear models; the number of species in each square was regressed against topography, climate, geology, environmental diversity, land use and spatial variables within each region. Two main latitudinal pteridophyte zones can be recognized in the Iberian Peninsula. These two zones are longitudinally subdivided into two sub zones. The 10 regions established significantly differ both in species richness and influential environmental variables. Climatic variables discriminate the most among regions, followed by topography, heterogeneity and geology. Pteridophyte richness varies, with richer areas being located along the coast and the main mountain ranges and the poorest areas being in the central plateaus and some north eastern and south western river basins. Species richness variation in Iberia is positively correlated with altitude range, precipitation, maximum altitude and area with siliceous soils. It is negatively correlated with the total annual days of sun, however. The fact that species richness is explained by different variables within each of the 10 regions indicates that the specific factors determining the spatial distribution of species richness vary from region to region. Some coastal regions are poorly explained by the model, and display a negative correlation with the selected causal factors. This finding suggests that persistent historic effects might play a local role in determining species assemblages in these regions. An erratum to this article can be found at     

Squamate richness in the Brazilian Cerrado and its environmental–climatic associations

We investigate patterns of species richness of squamates (lizards, snakes, and amphisbaenians) in the Brazilian Cerrado, identifying areas of particularly high richness, and testing predictions of large‐scale richness hypotheses by analysing the relationship between species richness and environmental climatic variables. We used point localities from museum collections to produce maps of the predicted distributions for 237 Cerrado squamate species, using niche‐modelling techniques. We superimposed distributions of all species on a composite map, depicting richness across the ecosystem. Then, we performed a multiple regression analysis using eigenvector‐based spatial filtering (Principal Coordinate of Neighbour Matrices) to assess environmental–climatic variables that are best predictors of species richness. We found that the environmental–climatic and spatial filters multiple regression model explained 78% of the variation in Cerrado squamate richness (r² = 0.78; F = 32.66; P < 0.01). Best predictors of species richness were: annual precipitation, precipitation seasonality, altitude, net primary productivity, and precipitation during the driest quarter. A model selection approach revealed that several mechanisms related to the different diversity hypothesis might work together to explain richness variation in the Cerrado. Areas of higher species richness in Cerrado were located mainly in the south‐west, north, extreme east, and scattered areas in the north‐west portions of the biome. Partitioning of energy among species, habitat differentiation, and tolerance to variable environments may be the primary ecological factors determining variation in squamate richness across the Cerrado. High richness areas in northern Cerrado, predicted by our models, are still poorly sampled, and biological surveys are warranted in that region. The south‐western region of the Cerrado exhibits high species richness and is also undergoing high levels of deforestation. Therefore, maintenance of existing reserves, establishment of ecological corridors among reserves, and creation of new reserves are urgently needed to ensure conservation of species in these areas.     

The ability of Nature Reserves to conserve medicinal plant resources: A case study in northeast China

Medicinal plants are important resources and are under serious threat due to human interference and climate change. We used species richness maps to find hotspots of medicinal plant localities and then modeled the environmental variables with a large effect on their distribution. We began by using a combination of species distribution models (SDMs) and geographic information system (GIS) tools to generate species richness maps of medicinal plants in northeast China. First, we conducted a detailed investigation of 2884 study plots in northeast China and selected 49 medicinal plant species for further analysis. The field surveys performed for this study spanned four years and identified a large number of new populations of medicinal plants in the forests of northeast China. We modeled and mapped the potential distributions of these 49 species and found that species richness hotspots are concentrated in the eastern and northeastern areas of the study region. We then analyzed the results of jackknife tests and found that the most important environmental variables on medicinal plant distribution are related to precipitation. Finally, we used the geographic distribution of medicinal plant richness to evaluate the ability of existing Nature Reserves to conserve these plants. By acquiring model data and using SDM and GIS to evaluate the current distribution and richness of medicinal plants, we are able to evaluate their current protection status and make recommendations about their utilization. This analysis could be expanded to assess medicinal plant populations in other regions where there are adequate records of the current distribution of medicinal plants.     

Primates as Predictors of Mammal Community Diversity in the Forest Ecosystems of Madagascar

The geographic distribution of species is the typical metric for identifying priority areas for conservation. Since most biodiversity remains poorly studied, a subset of charismatic species, such as primates, often stand as surrogates for total biodiversity. A central question is therefore, how effectively do primates predict the pooled species richness of other mammalian taxa? We used lemurs as indicator species to predict total non-primate mammal community richness in the forest ecosystems of Madagascar. We combine environmental and species occurrence data to ascertain the extent to which primate diversity can predict (1) non-primate mammal α-diversity (species richness), (2) non-primate complementarity, and (3) non-primate β-diversity (species turnover). Our results indicate that primates are effective predictors of non-primate mammal community diversity in the forest ecosystems of Madagascar after controlling for habitat. When individual orders of mammals are considered, lemurs effectively predict the species richness of carnivorans and rodents (but not afrosoricids), complementarity of rodents (but not carnivorans or afrosoricids), and all individual components of β-diversity. We conclude that lemurs effectively predict total non-primate community richness. However, surrogate species alone cannot achieve complete representation of biodiversity.     

Precipitation of the warmest quarter and temperature of the warmest month are key to understanding the effect of climate change on plant species diversity in Southern African savannah

In this study, we test for the key bioclimatic variables that significantly explain the current distribution of plant species richness in a southern African ecosystem as a preamble to predicting plant species richness under a changed climate. We used 54,000 records of georeferenced plant species data to calculate species richness and spatially interpolated climate data to derive nineteen bioclimatic variables. Next, we determined the key bioclimatic variables explaining variation in species richness across Zimbabwe using regression analysis. Our results show that two bioclimatic variables, that is, precipitation of the warmest quarter (R² = 0.92, P < 0.001) and temperature of the warmest month (R² = 0.67, P < 0.001) significantly explain variation in plant species richness. In addition, results of bioclimatic modelling using future climate change projections show a reduction in the current bio‐climatically suitable area that supports high plant species richness. However, in high‐altitude areas, plant richness is less sensitive to climate change while low‐altitude areas show high sensitivity. Our results have important implications to biodiversity conservation in areas sensitive to climate change; for example, high‐altitude areas are likely to continue being biodiversity hotspots, as such future conservation efforts should be concentrated in these areas.     

Copro-necrophagous beetle (Coleoptera: Scarabaeidae) diversity in an agroecosystem in Yucatan, Mexico

Scarabaeinae are sensitive to structural habitat changes caused by disturbance. We compared copronecrophagous beetle (Scarabaeinae) community structure in three differently managed zones within an agroeco-system of the northern Yucatan Peninsula, Mexico. We placed dung and carrion traps once a month from June 2004 through May 2005. The beetle community included 17 species from the genera Canthon, Canthidium, Deltochilum, Pseudocanthon, Malagoniella, Onthophagus, Phanaeus, Copris, Uroxys, Sisyphus and Ateuchus. The secondary vegetation had a higher beetle diversity than the other two zones. Species richness was highest in the Brosimum alicastrum plantation. The pasture had the lowest species diversity and richness, but exhibited the highest abundance of Scarabaeinae in the dry season. The two zones with extensive tree cover were the most diverse. Roller beetles were dominant over burrower species and small-sized species outnumbered large species. Our data show two important issues: beetle species in the pasture extended their activity to the beginning of the dry season, while abundances dropped in the other, unirrigated zones; and the possibility that the Scarabaeinae living in neotropical forests are opportunistic saprophages and have specialized habits for resources other than dung. The B. alicastrum plantation is beneficial to the entire ranch production system because it functions as a dispersion and development area for stenotopic species limited to tree cover.     

Species richness coincidence: conservation strategies based on predictive modelling

The present-day geographic distribution of individual species of five taxonomic groups (plants, dragonflies, butterflies, herpetofauna and breeding birds) is relatively well-known on a small scale (5 × 5 km squares) in Flanders (north Belgium). These data allow identification of areas with a high diversity within each of the species groups. However, differences in mapping intensity and coverage hamper straightforward comparisons of species-rich areas among the taxonomic groups. To overcome this problem, we modelled the species richness of each taxonomic group separately using various environmental characteristics as predictor variables (area of different land use types, biotope diversity, topographic and climatic features). We applied forward stepwise multiple regression to build the models, using a subset of well-surveyed squares. A separate set of equally well-surveyed squares was used to test the predictions of the models. The coincidence of geographic areas with high predicted species richness was remarkably high among the four faunal groups, but much lower between plants and each of the four faunal groups. Thus, the four investigated faunal groups can be used as relatively good indicator taxa for one another in Flanders, at least for their within-group species diversity. A mean predicted species diversity per mapping square was also estimated by averaging the standardised predicted species richness over the five taxonomic groups, to locate the regions that were predicted as being the most species-rich for all five investigated taxonomic groups together. Finally, the applicability of predictive modelling in nature conservation policy both in Flanders and in other regions is discussed.     

Modelling the species richness distribution of French dung beetles (Coleoptera, Scarabaeidae) and delimiting the predictive capacity of different groups of explanatory variables

Aim To predict French Scarabaeidae dung beetle species richness distribution, and to determine the possible underlying causal factors. Location The entire French territory has been studied by dividing it into 301 grid cells of 0.72 × 0.36 degrees. Method Species richness distribution was predicted using generalized linear models to relate the number of species with spatial, topographic and climate variables in grid squares previously identified as well sampled (n = 66). The predictive function includes the curvilinear relationship between variables, interaction terms and the significant third‐degree polynomial terms of latitude and longitude. The final model was validated by a jack‐knife procedure. The underlying causal factors were investigated by partial regression analysis, decomposing the variation in species richness among spatial, topographic and climate type variables. Results The final model accounts for 86.2% of total deviance, with a mean jack‐knife predictive error of 17.7%. The species richness map obtained highlights the Mediterranean as the region richest in species, and the less well‐explored south‐western region as also being species‐rich. The largest fraction of variability (38%) in the number of species is accounted for by the combined effect of the three groups of explanatory variables. The spatially structured climate component explains 21% of variation, while the pure climate and pure spatial components explain 14% and 11%, respectively. The effect of topography was negligible. Conclusions Delimiting the adequately inventoried areas and elaborating forecasting models using simple environmental variables can rapidly produce an estimate of the species richness distribution. Scarabaeidae species richness distribution seems to be mainly influenced by temperature. Minimum mean temperature is the most influential variable on a local scale, while maximum and mean temperature are the most important spatially structured variables. We suggest that species richness variation is mainly conditioned by the failure of many species to go beyond determined temperature range limits.     

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.