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.     

Geographical expansion and increased prevalence of common species in avian assemblages: implications for large-scale patterns of species richness

Aim The assumption that ecological patterns at large spatial scales originate exclusively from non‐anthropogenic processes is growing more questionable with the increasing domination of the biosphere by humans. Because common and rare species are known to respond differently to anthropogenic activities at local scales these differential responses could, over time, be reflected in distributional patterns of species richness at larger spatial scales. This work tests the hypothesis that modern processes have played a role in shaping these patterns, by examining recent changes in the structure and composition of assemblages of breeding avifauna over a large geographical extent. Location The portion of North America containing the contiguous United States and southern Canada. Methods Changes in the geographical range structure of breeding avifauna in North America from 1968 to 2003 were analysed in regions containing historically moderate levels of anthropogenic activities. Two geographical measures, extent of occurrence and area of occupancy, were used to identify the level of rarity or commonality of individual species and to estimate, based on a vector analysis, patterns of change in geographical range structure for individual species and avian assemblages. Results More species experienced patterns of geographical range expansion (51%) than contraction (28%). The majority of avian assemblages (43%) displayed patterns of geographical range expansion: common species increased in number and proportion (6%) in association with reciprocal losses in rare and moderately rare species, resulting in a constant level of species richness. The minority of avian assemblages (21%) displayed patterns of geographical range contraction: gains occurred for common species as well as for rare and moderately rare species, resulting in substantial increases in species richness and a decline in the proportion of common species (4%). The remaining avian assemblages presented equivocal patterns characterized by gains in the number and proportion (2%) of common species and gains in species richness. Main conclusions Modern processes have played a role in shaping the distribution patterns of species richness at large spatial scales based on the composition of common and rare species. This suggests that anthropogenic activities cannot be ignored as a possible causal factor when considering ecological patterns at large spatial scales.     

Patterns and causes of species richness: a general simulation model for macroecology

Understanding the causes of spatial variation in species richness is a major research focus of biogeography and macroecology. Gridded environmental data and species richness maps have been used in increasingly sophisticated curve‐fitting analyses, but these methods have not brought us much closer to a mechanistic understanding of the patterns. During the past two decades, macroecologists have successfully addressed technical problems posed by spatial autocorrelation, intercorrelation of predictor variables and non‐linearity. However, curve‐fitting approaches are problematic because most theoretical models in macroecology do not make quantitative predictions, and they do not incorporate interactions among multiple forces. As an alternative, we propose a mechanistic modelling approach. We describe computer simulation models of the stochastic origin, spread, and extinction of species’ geographical ranges in an environmentally heterogeneous, gridded domain and describe progress to date regarding their implementation. The output from such a general simulation model (GSM) would, at a minimum, consist of the simulated distribution of species ranges on a map, yielding the predicted number of species in each grid cell of the domain. In contrast to curve‐fitting analysis, simulation modelling explicitly incorporates the processes believed to be affecting the geographical ranges of species and generates a number of quantitative predictions that can be compared to empirical patterns. We describe three of the ‘control knobs’ for a GSM that specify simple rules for dispersal, evolutionary origins and environmental gradients. Binary combinations of different knob settings correspond to eight distinct simulation models, five of which are already represented in the literature of macroecology. The output from such a GSM will include the predicted species richness per grid cell, the range size frequency distribution, the simulated phylogeny and simulated geographical ranges of the component species, all of which can be compared to empirical patterns. Challenges to the development of the GSM include the measurement of goodness of fit (GOF) between observed data and model predictions, as well as the estimation, optimization and interpretation of the model parameters. The simulation approach offers new insights into the origin and maintenance of species richness patterns, and may provide a common framework for investigating the effects of contemporary climate, evolutionary history and geometric constraints on global biodiversity gradients. With further development, the GSM has the potential to provide a conceptual bridge between macroecology and historical biogeography.     

Range maps and species richness patterns: errors of commission and estimates of uncertainty

Range maps are often combined into “range overlap maps” to estimate spatial variation in species richness. Range maps are, in most cases, designed to represent a species’ maximum geographical extent and not patterns of occupancy within the range. As a consequence, range maps overestimate occupancy by presenting false occupancy (errors of commission) within the interior of the range. To assess the implications of errors of commission when developing and applying range overlap maps, we used neutral landscapes to simulate range maps and patterns of occupancy within ranges. We explored several scenarios based on combinations of six parameters defining biogeographical and cartographic factors typically encountered by investigators. Our results suggest that, in general, uncertainty is lowest when map resolutions are moderately fine, the majority of species have geographically restricted ranges, species occur throughout their range, patterns of occupancy within the range are not correlated among species, and geographically local and widespread species tend to occupy different regions. Several of these outcomes are associated with broad geographical extents, the scale at which range overlap maps are typically applied. Thus, under most circumstances, reasonably accurate and precise representation of species richness patterns can be achieved. However, these representations can be improved by enhancing occupancy data for widespread species – a primary source of uncertainty – and selecting a map resolution that captures relevant biological and environmental heterogeneity. Hence, by determining where a study is situated within the scenarios examined in our simulations, uncertainty and its sources and implications can be ascertained. With this knowledge, research goals, methods, and data sources can be reassessed and refined and, in the end, conclusions and recommendations can be qualified. Alternatively, unique regional, taxonomic, or cartographic factors could be included in future simulations to provide direct assessments of uncertainty.     

A comparison of methods for mapping species ranges and species richness

Aim  Maps of species richness are the basis for applied research and conservation planning as well as for theoretical research investigating patterns of richness and the processes shaping these patterns. The method used to create a richness map could influence the results of such studies, but differences between these methods have been insufficiently evaluated. We investigate how different methods of mapping species ranges can influence patterns of richness, at three spatial resolutions.
Location  California, USA.
Methods  We created richness maps by overlaying individual species range maps for terrestrial amphibians and reptiles. The methods we used to create ranges included: point-to-grid maps, obtained by overlaying point observations of species occurrences with a grid and determining presence or absence for each cell; expert-drawn maps; and maps obtained through species distribution modelling. We also used a hybrid method that incorporated data from all three methods. We assessed the correlation and similarity of the spatial patterns of richness maps created with each of these four methods at three different resolutions.
Results  Richness maps created with different methods were more correlated at lower spatial resolutions than at higher resolutions. At all resolutions, point-to-grid richness maps estimated the lowest species richness and those derived from species distribution models the highest. Expert-drawn maps and hybrid maps showed intermediate levels of richness but had different spatial patterns of species richness from those derived with the other methods.
Main conclusions  Even in relatively well-studied areas such as California, different data sources can lead to rather dissimilar maps of species richness. Evaluating the strengths and weaknesses of different methods for creating a richness map can provide guidance for selecting the approach that is most appropriate for a given application and region.     

Richness patterns, species distributions and the principle of extreme deconstruction

Aim To analyse the global patterns in species richness of Viperidae snakes through the deconstruction of richness into sets of species according to their distribution models, range size, body size and phylogenetic structure, and to test if environmental drivers explaining the geographical ranges of species are similar to those explaining richness patterns, something we called the extreme deconstruction principle. Location Global. Methods We generated a global dataset of 228 terrestrial viperid snakes, which included geographical ranges (mapped at 1° resolution, for a grid with 7331 cells world‐wide), body sizes and phylogenetic relationships among species. We used logistic regression (generalized linear model; GLM) to model species geographical ranges with five environmental predictors. Sets of species richness were also generated for large and small‐bodied species, for basal and derived species and for four classes of geographical range sizes. Richness patterns were also modelled against the five environmental variables through standard ordinary least squares (OLS) multiple regressions. These subsets are replications to test if environmental factors driving species geographical ranges can be directly associated with those explaining richness patterns. Results Around 48% of the total variance in viperid richness was explained by the environmental model, but richness sets revealed different patterns across the world. The similarity between OLS coefficients and the primacy of variables across species geographical range GLMs was equal to 0.645 when analysing all viperid snakes. Thus, in general, when an environmental predictor it is important to model species geographical ranges, this predictor is also important when modelling richness, so that the extreme deconstruction principle holds. However, replicating this correlation using subsets of species within different categories in body size, range size and phylogenetic structure gave more variable results, with correlations between GLM and OLS coefficients varying from –0.46 up to 0.83. Despite this, there is a relatively high correspondence (r = 0.73) between the similarity of GLM‐OLS coefficients and R² values of richness models, indicating that when richness is well explained by the environment, the relative importance of environmental drivers is similar in the richness OLS and its corresponding set of GLMs. Main conclusions The deconstruction of species richness based on macroecological traits revealed that, at least for range size and phylogenetic level, the causes underlying patterns in viperid richness differ for the various sets of species. On the other hand, our analyses of extreme deconstruction using GLM for species geographical range support the idea that, if environmental drivers determine the geographical distribution of species by establishing niche boundaries, it is expected, at least in theory, that the overlap among ranges (i.e. richness) will reveal similar effects of these environmental drivers. Richness patterns may be indeed viewed as macroecological consequences of population‐level processes acting on species geographical ranges.     

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

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

Diversity and distribution of amphibians in Romania

Nineteen species of amphibians inhabit Romania, 9 of which reach their range limit on this territory. Based on published occurrence reports, museum collections and our own data we compiled a national database of amphibian occurrences. We georeferenced 26779 amphibian species occurrences, and performed an analysis of their spatial patterns, checking for hotspots and patterns of species richness. The results of spatial statistic analyses supported the idea of a biased sampling for Romania, with clear hotspots of increased sampling efforts. The sampling effort is biased towards species with high detectability, protected areas, and large cities. Future sampling efforts should be focused mostly on species with a high rarity score in order to accurately map their range. Our results are an important step in achieving the long-term goals of increasing the efficiency of conservation efforts and evaluating the species range shifts under climate change scenarios.     

Ice age legacies in the geographical distribution of tree species richness in Europe

Aim This study uses a high‐resolution simulation of the Last Glacial Maximum (LGM) climate to assess: (1) whether LGM climate still affects the geographical species richness patterns in the European tree flora and (2) the relative importance of modern and LGM climate as controls of tree species richness in Europe. Location The parts of Europe that were unglaciated during the LGM. Methods Atlas data on the distributions of 55 tree species were linked with data on modern and LGM climate and climatic heterogeneity in a geographical information system with a 60‐km grid. Four measures of species richness were computed: total richness, and richness of the 18 most restricted species, 19 species of medium incidence (intermediate species) and 18 most widespread species. We used ordinary least‐squares regression and spatial autoregressive modelling to test and estimate the richness–climate relationships. Results LGM climate constituted the best single set of explanatory variables for richness of restricted species, while modern climate and climatic heterogeneity was best for total and widespread species richness and richness of intermediate species, respectively. The autoregressive model with all climatic predictors was supported for all richness measures using an information‐theoretic approach, albeit only weakly so for total species richness. Among the strongest relationships were increases in total and intermediate richness with climatic heterogeneity and in restricted richness with LGM growing‐degree‐days. Partial regression showed that climatic heterogeneity accounted for the largest unique variation fraction for intermediate richness, while LGM climate was particularly important for restricted richness. Main conclusions LGM climate appears to still affect geographical patterns of tree species richness in Europe, albeit the relative importance of modern and LGM climate depends on range size. Notably, LGM climate is a strong richness control for species with a restricted range, which appear to still be associated with their glacial refugia.     

Using potential distributions to explore determinants of Western Palaearctic migratory songbird species richness in sub-Saharan Africa

Aim  Although the breeding ranges of most Western Palaearctic migratory passerines are well documented in Europe, their overwintering ranges and patterns of species richness in Africa remain poorly understood. To illustrate potential patterns of species richness despite severely limited data, we extrapolated species ranges from a new and unique data bank of locality records that documents overwintering locations of these birds in Africa.
Location  Sub-Saharan Africa.
Methods  We predicted potential geographical distributions of 60 species of passerine birds based on overwintering records using bioclimatic models. We then combined these predictions to estimate potential species richness and explored response shapes using spatial linear regression. We also evaluated the evidence for a mid-domain effect using a one-dimensional null model.
Results  Spatial linear regression analyses of the species richness pattern revealed non-linear relationships to seasonality in precipitation, minimum net primary productivity, minimum average temperature, habitat heterogeneity, percentage of tree cover, distance from the Sahara Desert and inter-annual variability in net primary productivity. The explanatory power of these variables decreased with geographic range size. The one-dimensional null model of species richness based on distance from the Sahara Desert did not show evidence of a mid-domain effect.
Main conclusions  Distributions of migrants seem generally strongly determined by distance from the Sahara Desert working in concert with climatic effects, but this cannot adequately explain richness patterns of species with small ranges in Africa, many of which are of substantial conservation concern.     

Parasite species richness in carnivores: effects of host body mass, latitude, geographical range and population density

Aim  Comparative studies have revealed strong links between ecological factors and the number of parasite species harboured by different hosts, but studies of different taxonomic host groups have produced inconsistent results. As a step towards understanding the general patterns of parasite species richness, we present results from a new comprehensive data base of over 7000 host–parasite combinations representing 146 species of carnivores (Mammalia: Carnivora) and 980 species of parasites.
Methods  We used both phylogenetic and non-phylogenetic comparative methods while controlling for unequal sampling effort within a multivariate framework to ascertain the main determinants of parasite species richness in carnivores.
Results  We found that body mass, population density, geographical range size and distance from the equator are correlated with overall parasite species richness in fissiped carnivores. When parasites are classified by transmission mode, body mass and home range area are the main determinants of the richness of parasites spread by close contact between hosts, and population density, geographical range size and distance from the equator account for the diversity of parasites that are not dependent on close contact. For generalist parasites, population density, geographical range size and latitude are the primary predictors of parasite species richness. We found no significant ecological correlates for the richness of specialist or vector-borne parasites.
Main conclusions  Although we found that parasite species richness increases instead of decreases with distance from the equator, other comparative patterns in carnivores support previous findings in primates, suggesting that similar ecological factors operate in both these independent evolutionary lineages.     

Species richness, species range size and ecological specialisation among African primates: geographical patterns and conservation implications

The geographical distribution of species richness and species range size of African anthropoid primates (catarrhines) is investigated and related to patterns of habitat and dietary niche breadth. Catarrhine species richness is concentrated in the equatorial regions of central and west Africa; areas that are also characterised by low average species range sizes and increased ecological specificity. Species richness declines with increasing latitude north and south of the equator, while average species range size, habitat and dietary breadth increase. Relationships between species richness, species range size and niche breadth remain once latitudinal and longitudinal effects have been removed. Among areas of lowest species richness, however, there is increased variation in terms of average species range size and niche breadth, and two trends are identified. While most such areas are occupied by a few wide-ranging generalists, others are occupied by range-restricted specialist species. That conservation efforts increasingly focus on regions of high species richness may be appropriate if these regions are also characterised by species that are more restricted in both their range size and their ecological versatility, although special consideration may be required for some areas of low species richness.     

Ecological correlates of geographical range occupancy in North American birds

Aim  The degree to which a species is predictably encountered within its range varies tremendously across species. Understanding why some species occur less frequently within their range than others has important consequences for conservation and for analyses of ecological patterns based on range maps. We examined whether patterns in geographical range occupancy can be explained by species-level traits.
Location  North America.
Methods  We used survey data from 1993 to 2002 from the North American Breeding Bird Survey along with digital range maps produced by NatureServe to calculate range occupancy for 298 species of terrestrial birds. We tested whether species traits explained variation in range occupancy values using linear regression techniques.
Results  We found three species traits that together explained more than half of the variation in range occupancy. Population density and niche breadth were positively correlated with occupancy, while niche position was negatively correlated with occupancy.
Main conclusions  Our results suggest that high range occupancy will occur in species that are common at sites on which they occur, that tolerate a relatively wide range of ecological conditions and that tend to have ranges centred on areas with common environmental conditions. Furthermore, it appears that niche-based characteristics may explain patterns of distribution and abundance from local habitats up to the scale of geographical ranges.     

Sensitivity of macroecological patterns of South American parrots to differences in data sources

A criticism of macroecological studies has been their extensive use of secondary data sources. In this note we evaluate how different data sources affect macroecological patterns for the parrots of South America. We mapped extents of parrot occurrence based on four sources of range maps. We compared basic statistics for geographical range size distribution (mean, variance and skew) and calculated correlations between geographical range size estimates and grid cell species richness estimates. Finally, results from multiple regression analyses of species richness against six environmental variables were also compared. We found that patterns were very robust to the data source, with only relatively slight quantitative differences. Our results reinforce the notion that patterns emerging from macroecological analyses are robust to variations in data sources and cannot be merely artefacts resulting from low data quality, notably poorly defined mapping and conflicting taxonomy.     

空间尺度对地形异质性-物种多样性关系的影响:粒度和幅度

空间尺度是影响我们理解生态学格局和过程的关键因素.目前已有多种关于物种多样性分布格局形成机制的假说且研究者未达成共识,原因之一是空间尺度对物种多样性分布格局的环境影响因子的解释力和相对重要性有重要影响.地形异质性是物种多样性分布格局的重要影响因素.本文综述了在地形异质性-物种多样性关系的研究中,不同空间粒度和幅度对研究...     

Global habitat suitability models of terrestrial mammals

Detailed large-scale information on mammal distribution has often been lacking, hindering conservation efforts. We used the information from the 2009 IUCN Red List of Threatened Species as a baseline for developing habitat suitability models for 5027 out of 5330 known terrestrial mammal species, based on their habitat relationships. We focused on the following environmental variables: land cover, elevation and hydrological features. Models were developed at 300 m resolution and limited to within species' known geographical ranges. A subset of the models was validated using points of known species occurrence. We conducted a global, fine-scale analysis of patterns of species richness. The richness of mammal species estimated by the overlap of their suitable habitat is on average one-third less than that estimated by the overlap of their geographical ranges. The highest absolute difference is found in tropical and subtropical regions in South America, Africa and Southeast Asia that are not covered by dense forest. The proportion of suitable habitat within mammal geographical ranges correlates with the IUCN Red List category to which they have been assigned, decreasing monotonically from Least Concern to Endangered. These results demonstrate the importance of fine-resolution distribution data for the development of global conservation strategies for mammals.     

Interpreting biogeographical boundaries among Afrotropical birds: spatial patterns in richness gradients and species replacement

Aim We analyse the geographical distribution of 1911 Afrotropical bird species using indices of three simple biogeographic patterns. The first index, the frequency of species with range edges (T_e), is formulated to map directly the density of species distribution limits, for comparison with the results of traditional biogeographical classification and ordination procedures, in order to show variations in the strength and breadth of transition zones. The other two indices are formulated to seek to distinguish as directly as possible between two components within these transition-zone patterns: contributions from gradients in species richness (T_g); and contributions from replacements among species (T_r). We test the ability of these indices to discover the same boundaries among Afrotropical bird faunas as one popular procedure for classifying areas (TWINSPAN) and then use them to look for geographical trends in the different kinds of transition zones. Location The analysis is restricted to the sub-Saharan or Afrotropical region, excluding the Arabian Peninsula, Madagascar and all offshore islands. Methods We record the presence of each species in 1961 1°×1° grid cells of the map. To apply the three indices, each (core) grid cell in turn is compared with its neighbouring eight cells in the grid. The range edges index (T_e) counts the number of species with range edges between the core cell and the surrounding cells. The richness gradients index (T_g) counts the largest difference in species richness measured diametrically across the core cell in any direction when there is a consistent trend in richness along this line of three cells. The species replacements index (T_r) counts the number of species pairs recorded within a nine-cell neighbourhood that are not corecorded within any of the cells. Values for each of the 1961 grid cells are calculated and used to produce colour-scale maps of transition zones. Results Large-scale spatial patterns of variation in density of range edges (T_e) are consistent with classifications of the same data and with most previous biogeographical classifications proposed for the region. Variation in richness gradients (T_g) and species replacements (T_r) explain different parts of this pattern, with transition zones around humid forests in the equatorial region being dominated by species replacement, and transition zones around deserts (most extensive in the north and south) being dominated by richness gradients. Main conclusions The three indices distinguish the spatial arrangement and intensity of different kinds of transition zones, thereby providing a first step towards a more rigorous mechanistic understanding of the different processes by which they may have arisen and are maintained. As an example of one such pattern shown by our analyses of Afrotropical birds, there is evidence for a broad latitudinal trend in the nature of transition zones in faunal composition (following the latitudinal distribution of the different kinds of habitat transitions), from being dominated by species replacements near the equator to being dominated by richness gradients further from the equator.     

Hot,dry and different: Australian lizard richness is unlike that of mammals,amphibians and birds

Aims (1) To map the species richness of Australian lizards and describe patterns of range size and species turnover that underlie them. (2) To assess the congruence in the species richness of lizards and other vertebrate groups. (3) To search for commonalities in the drivers of species richness in Australian vertebrates. Location Australia. Methods We digitized lizard distribution data to generate gridded maps of species richness and β‐diversity. Using similar maps for amphibians, mammals and birds, we explored the relationship between species richness and temperature, actual evapotranspiration, elevation and local elevation range. We used spatial eigenvector filtering and geographically weighted regression to explore geographical patterns and take spatial autocorrelation into account. We explored congruence between the species richness of vertebrate groups whilst controlling for environmental effects. Results Lizard richness peaks in the central deserts (where β‐diversity is low) and tropical north‐east (where β‐diversity is high). The intervening lowlands have low species richness and β‐diversity. Generally, lizard richness is uncorrelated with that of other vertebrates but this low congruence is strongly spatially structured. Environmental models for all groups also show strong spatial heterogeneity. Lizard richness is predicted by different environmental factors from other vertebrates, being highest in dry and hot regions. Accounting for environmental drivers, lizard richness is weakly positively related to richness of other vertebrates, both at global and local scales. Main conclusions Lizard species richness differs from that of other vertebrates. This difference is probably caused by differential responses to environmental gradients and different centres of diversification; there is little evidence for inter‐taxon competition limiting lizard richness. Local variation in habitat diversity or evolutionary radiations may explain weak associations between taxa, after controlling for environmental variables. We strongly recommend that studies of variation in species richness examine and account for non‐stationarity.     

Effects of geographical extent on the determinants of woody plant diversity

Despite a long history of study, the mechanisms underlying the geographical patterns of species richness are still controversial. Patterns and determinants of species richness are well‐known to vary with spatial scale. However, most studies on the effects of scale have focused on grain size whereas the quantitative effects of geographical extent are rarely tested. Here, using distribution maps of 11 405 woody species found in China and associated environmental data to the domain, we investigated the influence of geographical extent on the determinants of species richness patterns. Our results revealed consistent extent dependence of all species, narrow‐ and wide‐ranged species: with the expansion of geographical extents, the explanatory power of climate (i.e. environmental energy, water availability and climatic seasonality) increased, while the explanatory power of habitat heterogeneity and human activities decreased. Although the primary determinant of species richness patterns varied significantly at small to meso‐geographical extent, we showed that species richness was predominantly determined by environmental energy at large extent. Our findings indicate that differences in geographical extent may have led to the controversies regarding the primary determinants of richness patterns in previous studies, and that a multi‐scale perspective not only with regard to grain‐size but also extent is likely to shed new light on this old debate of what determines richness patterns.     

The performance of range maps and species distribution models representing the geographic variation of species richness at different resolutions

Aim The method used to generate hypotheses about species distributions, in addition to spatial scale, may affect the biodiversity patterns that are then observed. We compared the performance of range maps and MaxEnt species distribution models at different spatial resolutions by examining the degree of similarity between predicted species richness and composition against observed values from well‐surveyed cells (WSCs). Location Mexico. Methods We estimated amphibian richness distributions at five spatial resolutions (from 0.083° to 2°) by overlaying 370 individual range maps or MaxEnt predictions, comparing the similarity of the spatial patterns and correlating predicted values with the observed values for WSCs. Additionally, we looked at species composition and assessed commission and omission errors associated with each method. Results MaxEnt predictions reveal greater geographic differences in richness between species rich and species poor regions than the range maps did at the five resolutions assessed. Correlations between species richness values estimated by either of the two procedures and the observed values from the WSCs increased with decreasing resolution. The slopes of the regressions between the predicted and observed values indicate that MaxEnt overpredicts observed species richness at all of the resolutions used, while range maps underpredict them, except at the finest resolution. Prediction errors did not vary significantly between methods at any resolution and tended to decrease with decreasing resolution. The accuracy of both procedures was clearly different when commission and omission errors were examined separately. Main conclusions Despite the congruent increase in the geographic richness patterns obtained from both procedures as resolution decreases, the maps created with these methods cannot be used interchangeably because of notable differences in the species compositions they report.