Abundance, species richness and energy availability in the North American avifauna

Aim To determine how species richness, abundance, biomass, energy use and mean number of individuals per species scale with environmental energy availability in wintering and breeding avian assemblages, and to contrast assemblages of (i) common and rare species and (ii) breeding residents and migrants. To assess whether such patterns are compatible with the ‘more individuals hypothesis’ (MIH) that high‐energy areas are species‐rich because they support larger populations that are buffered against extinction. Location The North American continent (latitudinal range 23.4 °?48.1 °N; longitudinal range 124.2°?68.7° W). Methods Avian species richness, abundance, biomass and energy use were calculated for 295 Resident Bird Count plots. Environmental energy availability was measured using ambient temperature and the Normalized Difference Vegetation Index (NDVI), a close correlate of plant productivity. Analyses took plot area into account, and were conducted (with and without taking habitat type into account) using general linear models and spatial mixed models. Results Positive species–energy relationships were exhibited by both wintering and breeding assemblages, but were stronger in the former. The structure of winter assemblages responded more strongly to temperature than NDVI, while breeding assemblages tended to respond more strongly to NDVI. Breeding residents responded to annual measures of energy availability while breeding migrants and the winter assemblage responded more strongly to seasonal measures. In the winter assemblage, rare and common species exhibited species–energy relationships of a similar strength, but common breeding species exhibited a much stronger relationship than rare breeding species. In both breeding and wintering assemblages, abundance, biomass and energy use increased with energy availability and species richness. Energy availability was a poor predictor of the mean number of individuals per species. Main conclusions The nature of the species–energy relationship varies seasonally and with the manner in which energy availability is measured. Our data suggest that residents are less able to respond to seasonal fluxes in resource availability than long‐distance migrants. Increasing species richness and energy availability is associated with increasing numbers of individuals, biomass and energy use. While these observations are compatible with the MIH our data provide only equivocal support for this hypothesis, as the rarest species do not exhibit the strongest species–energy relationships.     

Patterns of woody plant species richness in the Iberian Peninsula: environmental range and spatial scale

Aim Climate‐based models often explain most of the variation in species richness along broad‐scale geographical gradients. We aim to: (1) test predictions of woody plant species richness on a regional spatial extent deduced from macro‐scale models based on water–energy dynamics; (2) test if the length of the climate gradients will determine whether the relationship with woody species richness is monotonic or unimodal; and (3) evaluate the explanatory power of a previously proposed ‘water–energy’ model and regional models at two grain sizes. Location The Iberian Peninsula. Methods We estimated woody plant species richness on grid maps with c. 2500 and 22,500 km² cell size, using geocoded data for the individual species. Generalized additive models were used to explore the relationships between richness and climatic, topographical and substrate variables. Ordinary least squares regression was used to compare regional and more general water–energy models in relation to grain size. Variation partitioning by partial regression was applied to find how much of the variation in richness was related to spatial variables, explanatory variables and the overlap between these two. Results Water–energy dynamics generate important underlying gradients that determine the woody species richness even over a short spatial extent. The relationships between richness and the energy variables were linear to curvilinear, whereas those with precipitation were nonlinear and non‐monotonic. Only a small fraction of the spatially structured variation in woody species richness cannot be accounted for by the fitted variables related to climate, substrate and topography. The regional models accounted for higher variation in species richness than the water–energy models, although the water–energy model including topography performed well at the larger grain size. Elevation range was the most important predictor at all scales, probably because it corrects for ‘climatic error’ due to the unrealistic assumption that mean climate values are evenly distributed in the large grid cells. Minimum monthly potential evapotranspiration was the best climatic predictor at the larger grain size, but actual evapotranspiration was best at the smaller grain size. Energy variables were more important than precipitation individually. Precipitation was not a significant variable at the larger grain size when examined on its own, but was highly significant when an interaction term between itself and substrate was included in the model. Main conclusions The significance of range in elevation is probably because it corresponds to several aspects that may influence species diversity, such as climatic variability within grid cells, enhanced surface area, and location for refugia. The relative explanatory power of energy and water variables was high, and was influenced by the length of the climate gradient, substrate and grain size of the analysis. Energy appeared to have more influence than precipitation, but water availability is also determined by energy, substrate and topographic relief.     

Energy, Density, and Constraints to Species Richness: Ant Assemblages along a Productivity Gradient

Species richness describes the number of species of a given taxon in a given time and space. The energy limitation hypothesis links the species richness of consumer taxa to net primary productivity (NPP) through two relationships: NPP limits a taxon's density, and taxon density limits species richness. We study both relationships with a survey of 15 ground ant assemblages, along a productivity gradient from deserts to rain forests. Ant density (colonies m-2) was a positive, decelerating function of net aboveground productivity (NAP). A stepwise regression suggests that the efficiency with which NAP is converted to ant colonies increases with maximum summer temperature and decreases with precipitation. Ant species richness was a positive decelerating function of density at three spatial scales. This supports the energy limitation hypothesis' assumption that average population densities are higher in environments that are more productive. These two nonlinear functions (NAP-density and density-species richness) combine to create, at a variety of scales, positive, decelerating, productivity-diversity curves for a common, ecologically dominant taxon across the terrestrial productivity gradient. However, variance in the density and diversity explained by NAP decreases with scale, suggesting that energy limitation of diversity predominates at small spatial scales (<1 ha).     

Environmental heterogeneity as a universal driver of species richness across taxa,biomes and spatial scales

Environmental heterogeneity is regarded as one of the most important factors governing species richness gradients. An increase in available niche space, provision of refuges and opportunities for isolation and divergent adaptation are thought to enhance species coexistence, persistence and diversification. However, the extent and generality of positive heterogeneity–richness relationships are still debated. Apart from widespread evidence supporting positive relationships, negative and hump‐shaped relationships have also been reported. In a meta‐analysis of 1148 data points from 192 studies worldwide, we examine the strength and direction of the relationship between spatial environmental heterogeneity and species richness of terrestrial plants and animals. We find that separate effects of heterogeneity in land cover, vegetation, climate, soil and topography are significantly positive, with vegetation and topographic heterogeneity showing particularly strong associations with species richness. The use of equal‐area study units, spatial grain and spatial extent emerge as key factors influencing the strength of heterogeneity–richness relationships, highlighting the pervasive influence of spatial scale in heterogeneity–richness studies. We provide the first quantitative support for the generality of positive heterogeneity–richness relationships across heterogeneity components, habitat types, taxa and spatial scales from landscape to global extents, and identify specific needs for future comparative heterogeneity–richness research.     

Freshwater biodiversity at regional extent: determinants of macroinvertebrate taxonomic richness in headwater streams

We studied spatial variation of macroinvertebrate species richness in headwater streams at two spatial extents, within and across drainage systems, and assessed the relative importance of three groups of variables (local, landscape and regional) at each extent. We specifically asked whether the same variables proposed to control broad‐scale richness patterns of terrestrial organisms (temperature, topographic variability) are important determinants of species richness also in streams, or whether environmental factors effective at mainly local scales (in‐stream heterogeneity, potential productivity) constrain species richness in local communities. We used forward selection with two stopping criteria to identify the key environmental and spatial variables at each study extent. Eigenvector‐based spatial filtering was applied to evaluate spatial patterns in species richness, and variation partitioning was used to assess the amount of variation in richness attributable to purely environmental and spatial components. A prime regulator of richness variation at the bioregion extent was elevation range (increasing richness with higher topographic variability), whereas hydrological stability and temperature were unimportant. Water chemistry variables, particularly water color, exhibited strong spatially‐structured variation across drainage systems. Local environmental variables explained most of the variation in species richness at the drainage‐system extent, reflecting gradients in total phosphorus and water color (negative effect on richness). The importance of the pure spatial component was strongly region‐dependent, with a peak (60%) in one drainage system, suggesting the presence of unmeasured environmental factors. Our results emphasize the need for spatially‐explicit, regional studies to better understand geographical variation of freshwater biodiversity. Future studies need to relate species richness not only to local factors but also to broad‐scale climatic variables, recognizing the presence of spatially‐structured environmental variation.     

EFFECTS OF ISLAND GROUPS,DEPTH, AND EXPOSURE TO OCEAN WAVES ON SUBTIDAL MACROALGAL ASSEMBLAGES IN THE RECHERCHE ARCHIPELAGO,WESTERN AUSTRALIA1

Temperate Australia has a speciose highly endemic algal flora. This study explored the influence of geographical isolation between islands, depth and exposure to ocean swells on the diversity of macroalgae in the Recherche Archipelago (Western Australia). Macroalgae were harvested (0.25‐m² quadrats) from sites at two exposures (sheltered and exposed to wave energy), three depths (<10, 10–20, and 21–28 m), and two island groups (three islands within Esperance Bay and three islands outside the bay). A total of 220 species were collected. Species richness and biomass were significantly different at the smallest spatial scale (0.25 m²), and density of overstory species decreased with depth. Results from analysis of similarity tests suggested that macroalgal assemblages differed with depth, exposure and to a lesser extent with island group. Assemblage differences were often associated with particular overstory or understory taxa and not the entire assemblage composition. Average species richness·0.25 m^?2 ranged from 13 to 29 species, typically with a few species contributing more than 50% of average biomass. Species richness was maintained by species turnover at the 0.25‐m² spatial scale. Our results suggest that richness in temperate Australia is maintained by turnover of broadly distributed species. More dominant species in assemblages were associated with differences in depth and exposure to ocean swells. Our findings support the hypothesis of a geographical transition of dominant species from kelp‐dominated in the west to a fucalean‐dominated assemblage in the Recherche Archipelago and east of the Great Australian Bight.     

Cross‐scale variation in species richness–environment associations

Aim The scale dependence of many ecological patterns and processes implies that general inference is reliant on obtaining scale‐response curves over a large range of grains. Although environmental correlates of richness have been widely studied, comparisons among groups have usually been applied at single grains. Moreover, the relevance of environment–richness associations to fine‐grain assemblages has remained surprisingly unclear. We present a first global cross‐scale assessment of environment–richness associations for birds, mammals and amphibians from 2000 km down to c. 20 km. Location World‐wide. Methods We performed an extensive survey of the literature for well‐sampled terrestrial vertebrate inventories over clearly defined small extents. Coarser grain richness was estimated from the intersection of extent‐of‐occurrence range maps with concentric equal‐distance circles around fine‐grain assemblage location centroids. General linear and simultaneous autoregressive models were used to relate richness at the different grains to environmental correlates. Results The ability of environmental variables to explain species richness decreases markedly toward finer grains and is lowest for fine‐grained assemblages. A prominent transition in importance occurs between productivity and temperature at increased grains, which is consistent with the role of energy affecting regional, but not local, richness. Variation in fine‐grained predictability across groups is associated with their purported grain of space use, i.e. highest for amphibians and narrow‐ranged and small‐bodied species. Main conclusions We extend the global documentation of environment–richness associations to fine‐grained assemblages. The relationship between fine‐grained predictability of a group and its ecological characteristics lends empirical support to the idea that variation in species fine‐grained space use may scale up to explain coarse‐grained diversity patterns. Our study exposes a dramatic and taxonomically variable scale dependence of environment–richness associations and suggests that environmental correlates of richness may hold limited information at the level of communities.     

Elevational gradients in species abundance,assemblage structure and energy use of rainforest birds in the Australian Wet Tropics bioregion

Elevational patterns of species richness, local abundance and assemblage structure of rainforest birds of north‐eastern Australia were explored using data from extensive standardized surveys throughout the region. Eighty‐two species of birds were recorded with strong turnover in assemblage structure across the elevational gradient and high levels of regional endemism in the uplands. Both species richness and bird abundance exhibited a humped‐shaped pattern with elevation with the highest values being between 600 and 800 m elevation. While much of the variability in species richness could be explained by the species–area relationship, analyses of net primary productivity (NPP) and total daily energy consumption of the bird community (energy use) suggest that ecosystem energy flow or constraints may be a significant determinant of species richness. Species richness is positively correlated with local bird abundance which itself is closely related to total energy use of the bird community. We suggest the hypothesis that lower NPP limits bird abundance and energy use in the uplands (>500 m) and that low bird energy use and species richness in the lowlands is limited by a seasonal bottleneck in available primary productivity and/or a species pool previously truncated by an extinction filter imposed by the almost complete disappearance of rainforest in the lowlands during the glacial maxima. We suggest that some of the previously predicted impacts of global warming on biodiversity in the uplands may be partially ameliorated by increases in NPP because of increasing temperatures. However, these relationships are complex and require further data specifically in regard to direct estimates of primary productivity and detailed estimates of energy flow within the assemblage.     

Energy flux, body size and density in relation to bird species richness along an elevational gradient in Taiwan

Aim To examine the species richness of breeding birds along a local elevational gradient and to test the following assumptions of the energy limitation hypothesis: (1) the energy flux through birds is positively correlated with above‐ground net primary productivity, (2) bird density is positively correlated with total energy flux, and (3) bird species richness is positively correlated with bird density. Location An elevational gradient from 1400 to 3700 m on Mt. Yushan, the highest mountain in Taiwan (23°28′30″ N, 120°54′00″ E), with a peak of 3952 m a.s.l. Methods We established 50 sampling stations along the elevational gradient. From March to July 1992, we estimated the density of each bird species using the variable circular‐plot method. Above‐ground net primary productivity was modelled using monthly averages from weather data for the years 1961–90. Results Bird species richness had a hump‐shaped relationship with elevation and with net primary productivity. Bird energy flux was positively correlated with net primary productivity and bird species richness was positively correlated with bird density. The relationship between bird density and energy flux was hump‐shaped, which does not support one assumption of the energy limitation hypothesis. Main conclusions The results supported two essential assumptions of the energy limitation hypothesis. However, when energy availability exceeded a certain level, it could decrease species richness by increasing individual energy consumption, which reduced bird density. Thus, energy availability is a primary factor influencing bird species richness at this scale, but other factors, such as body size, could also play important roles.     

A global model of island biogeography

Aim The goal of our study was to build a global model of island biogeography explaining bird species richness that combines MacArthur and Wilson's area–isolation theory with the species–energy theory. Location Global. Methods We assembled a global data set of 346 marine islands representing all types of climate, topography and degree of isolation on our planet, ranging in size from 10 ha to 800,000 km². We built a multiple regression model with the number of non‐marine breeding bird species as the dependent variable. Results We found that about 85–90% of the global variance in insular bird species richness can be explained by simple, contemporary abiotic factors. On a global scale, the three major predictors — area, average annual temperature and the distance separating the islands from the nearest continent — all have constraining (i.e. triangular rather than linear) relationships with insular bird species richness. We found that the slope of the species–area curve depends on both average annual temperature and total annual precipitation, but not on isolation. Insular isolation depends not only on the distance of an island from the continent, but also on the presence or absence of other neighbouring islands. Range in elevation — a surrogate for diversity of habitats — showed a positive correlation with bird diversity in warmer regions of the world, while its effect was negative in colder regions. We also propose a global statistical model to quantify the isolation‐reducing effect of neighbouring islands. Main conclusions The variation in avian richness among islands worldwide can be statistically explained by contemporary environmental variables. The equilibrium theory of island biogeography of MacArthur and Wilson and the species–energy theory are both only partly correct. Global variation in richness depends about equally upon area, climate (temperature and precipitation) and isolation. The slope of the species richness–area curve depends upon climate, but not on isolation, in contrast to MacArthur and Wilson's theory.     

Multi-species richness of boreal agricultural landscapes: effects of climate, biotope, soil and geographical location

Aim To assess the relative importance of climate, biotope and soil variables as well as geographical location for the species richness of plants, butterflies, day‐active macromoths and wild bees in boreal agricultural landscapes. Location A total of 68 agricultural landscapes located in southern Finland. Methods Generalized linear mixed models were used to analyse the effects of environmental (climate, biotope and soil) and spatial (latitude and longitude) variables on species richness of four taxa in 136 study squares of 0.25 km². Using partial regression, the variation in species richness was decomposed into the purely environmental fraction; the spatially structured environmental fraction; and the purely spatial fraction, including variables retained in cubic trend surface regression. Results Species richness of all taxa was positively correlated with temperature. Species richness of plants and butterflies was also positively correlated with the heterogeneity of landscape. The extent of low‐intensity agricultural land and forest had a positive effect, and the extent of cultivated field a negative effect on the species richness of these taxa. The effect of soil characteristics on the number of observed species was negligible for all taxa. The greatest part of the explained variation for all taxa was accounted for by the pure effect of geographical location. To a somewhat lesser extent, the species richness of plants, butterflies and bees was also related to the effects of spatially structured environmental variables, and the species richness of macromoths to the effects of environmental variables. Main conclusions Multi‐species richness of boreal agricultural landscapes at the scale of 0.25 km² was associated with the heterogeneity of the local landscape. However, large‐scale geographical variation in species richness was also observed, which indicates the importance of climate and geographical location for the taxa studied. These results highlight the fact that, even on a landscape scale, geographical factors should be taken into account in biodiversity studies. Heterogeneous agricultural landscapes, including forest and non‐crop biotopes, should be preserved or restored to maintain biodiversity.     

Species–energy relationship in the deep sea: a test using the Quaternary fossil record

Little is known about the processes regulating species richness in deep‐sea communities. Here we take advantage of natural experiments involving climate change to test whether predictions of the species–energy hypothesis hold in the deep sea. In addition, we test for the relationship between temperature and species richness predicted by a recent model based on biochemical kinetics of metabolism. Using the deep‐sea fossil record of benthic foraminifera and statistical meta‐analyses of temperature‐richness and productivity‐richness relationships in 10 deep‐sea cores, we show that temperature but not productivity is a significant predictor of species richness over the past c. 130 000 years. Our results not only show that the temperature‐richness relationship in the deep‐sea is remarkably similar to that found in terrestrial and shallow marine habitats, but also that species richness tracks temperature change over geological time, at least on scales of c. 100 000 years. Thus, predicting biotic response to global climate change in the deep sea would require better understanding of how temperature regulates the occurrences and geographical ranges of species.     

Plant species diversity and environmental heterogeneity: spatial scale and competing hypotheses

Questions: What is the observed relationship between plant species diversity and spatial environmental heterogeneity? Does the relationship scale predictably with sample plot size? What are the relative contributions to diversity patterns of variables linked to productivity or available energy compared to those corresponding to spatial heterogeneity? Methods: Observational and experimental studies that quantified relationships between plant species richness and within‐sample spatial environmental heterogeneity were reviewed. Effect size in experimental studies was quantified as the standardized mean difference between control (homogeneous) and heterogeneous treatments. For observational studies, effect sizes in individual studies were examined graphically across a gradient of plot size (focal scale). Relative contributions of variables representing spatial heterogeneity were compared to those representing available energy using a response ratio. Results: Forty‐one observational and 11 experimental studies quantified plant species diversity and spatial environmental heterogeneity. Observational studies reported positive species diversity‐spatial heterogeneity correlations at all points across a plot size gradient from ～1.0 × 10^?1 to ～1.0 × 10¹¹ m², although many studies reported spatial heterogeneity variables with no significant relationships to species diversity. The cross‐study effect size in experimental studies was not significantly different from zero. Available energy variables explained consistently more of the variance in species richness than spatial heterogeneity variables, especially at the smallest and largest plot sizes. Main conclusions: Species diversity was not related to spatial heterogeneity in a way predictable by plot size. Positive heterogeneity‐diversity relationships were common, confirming the importance of niche differentiation in species diversity patterns, but future studies examining a range of spatial scales in the same system are required to determine the role of dispersal and available energy in these patterns.     

Different responses of avian feeding guilds to spatial and environmental factors across an elevation gradient in the central Himalaya

Although elevational patterns of species richness have been well documented, how the drivers of richness gradients vary across ecological guilds has rarely been reported. Here, we examined the effects of spatial factors (area and mid‐domain effect; MDE) and environmental factors, including metrics of climate, productivity, and plant species richness on the richness of breeding birds across different ecological guilds defined by diet and foraging strategy. We surveyed 12 elevation bands at intervals of 300 m between 1,800 and 5,400 m a.s.l using line‐transect methods throughout the wet season in the central Himalaya, China. Multiple regression models and hierarchical partitioning were used to assess the relative importance of spatial and environmental factors on overall bird richness and guild richness (i.e., the richness of species within each guild). Our results showed that richness for all birds and most guilds displayed hump‐shaped elevational trends, which peaked at an elevation of 3,300–3,600 m, although richness of ground‐feeding birds peaked at a higher elevation band (4,200–4,500 m). The Normalized Difference Vegetation Index (NDVI)—an index of primary productivity—and habitat heterogeneity were important factors in explaining overall bird richness as well as that of insectivores and omnivores, with geometric constraints (i.e., the MDE) of secondary importance. Granivore richness was not related to primary production but rather to open habitats (granivores were negatively influenced by habitat heterogeneity), where seeds might be abundant. Our findings provide direct evidence that the richness–environment relationship is often guild‐specific. Taken together, our study highlights the importance of considering how the effects of environmental and spatial factors on patterns of species richness may differ across ecological guilds, potentially leading to a deeper understanding of elevational diversity gradients and their implications for biodiversity conservation.     

Bird diversity patterns in Neotropical temperate farmlands: The role of environmental factors and trophic groups in the spring and autumn

Productivity, habitat heterogeneity and environmental similarity are of the most widely accepted hypotheses to explain spatial patterns of species richness and species composition similarity. Environmental factors may exhibit seasonal changes affecting species distributions. We explored possible changes in spatial patterns of bird species richness and species composition similarity. Feeding habits are likely to have a major influence in bird–environment associations and, given that food availability shows seasonal changes in temperate climates, we expect those associations to differ by trophic group (insectivores or granivores). We surveyed birds and estimated environmental variables along line‐transects covering an E‐W gradient of annual precipitation in the Pampas of Argentina during the autumn and the spring. We examined responses of bird species richness to spatial changes in habitat productivity and heterogeneity using regression analyses, and explored potential differences between seasons of those responses. Furthermore, we used Mantel tests to examine the relationship between species composition similarity and both the environmental similarity between sites and the geographic distance between sites, also assessing differences between seasons in those relationships. Richness of insectivorous birds was directly related to primary productivity in both seasons, whereas richness of seed‐eaters showed a positive association with habitat heterogeneity during the spring. Species composition similarity between assemblages was correlated with both productivity similarity and geographic proximity during the autumn and the spring, except for insectivore assemblages. Diversity within main trophic groups seemed to reflect differences in their spatial patterns as a response to changes between seasons in the spatial patterns of food resources. Our findings suggest that considering different seasons and functional groups in the analyses of diversity spatial pattern could contribute to better understand the determinants of biological diversity in temperate climates.     

Human impacts on environment–diversity relationships: evidence for biotic homogenization from butterfly species richness patterns

Aim Broad‐scale spatial variation in species richness relates to climate and physical heterogeneity but human activities may be changing these patterns. We test whether climate and heterogeneity predict butterfly species richness regionally and across Canada and whether these relationships change in areas of human activity. Location Canada. Methods We modelled the ranges of 102 butterfly species using genetic algorithms for rule‐set production (GARP). We then measured butterfly species richness and potentially important aspects of human activity and the natural environment. These were included in a series of statistical models to determine which factors are likely to affect butterfly species richness in Canada. We considered patterns across Canada, within predominantly natural areas, human‐dominated areas and particular ecozones. We examined independent observations of butterfly species currently listed under Canada's endangered species legislation to test whether these were consistent with findings from statistical models. Results Growing season temperature is the main determinant of butterfly species richness across Canada, with substantial contributions from habitat heterogeneity (measured using elevation). Only in the driest areas does precipitation emerge as a leading predictor of richness. The slope of relationships between all of these variables and butterfly species richness becomes shallower in human‐dominated areas, but butterfly richness is still highest there. Insecticide applications, habitat loss and road networks reduce butterfly richness in human‐dominated areas, but these effects are relatively small. All of Canada's at‐risk butterfly species are located in these human‐dominated areas. Main conclusions Temperature affects butterfly species richness to a greater extent than habitat heterogeneity at fine spatial scales and is generally far more important than precipitation, supporting both the species richness–energy and habitat heterogeneity hypotheses. Human activities, especially in southern Canada, appear to cause surprisingly consistent trends in biotic homogenization across this region, perhaps through range expansion of common species and loss of range‐restricted species.     

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

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

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.