Scale-related patterns in the spatial and environmental components of stream macroinvertebrate assemblage variation

Aim We examined the relative contributions of spatial gradients and local environmental conditions to macroinvertebrate assemblages of boreal headwater streams at three hierarchical extents: bioregion, ecoregion and drainage system. We also aimed to identify the environmental variables most strongly related to assemblage structure at each study scale, and to assess how the importance of these variables is related to regional context and spatial structuring at different scales. Location Northern Finland ( 62 – 68° N, 25–32° E). Methods Variation in macroinvertebrate data was partitioned using partial canonical correspondence analysis into components explained by spatial variables (nine terms from the cubic trend surface regression), local environmental variables (15 variables) and spatially structured environmental variation. Results The strength of the relationship between assemblage structure and local environmental variables increased with decreasing spatial extent, whereas assemblage variation related to spatial variables and spatially structured environmental variation showed the opposite pattern. At the largest extents, spatial variation was related to latitudinal gradients, whereas spatial autocorrelation among neighbouring streams was the likely mechanism creating spatial structure within drainage systems. Only stream size and water acidity were consistently important in explaining assemblage structure at all study scales, while the importance of other environmental variables was more context‐dependent. Main conclusions The importance of local environmental factors in explaining macroinvertebrate assemblage structure increases with decreasing spatial extent. This scale‐related pattern is not caused solely by changes in study extent, however, but also by variable sample sizes at different regional extents. The importance of environmental gradients is context‐dependent and few factors are likely to be universally important correlates of macroinvertebrate assemblage structure. Finally, our results suggest that bioassessment should give due attention to spatial structuring of stream assemblages, because important assemblage gradients may not only be related to local factors but also to biogeographical constraints and neighbourhood dispersal processes.     

A model of geographical, environmental and regional variation in vegetation composition of pyrogenic grasslands of Florida

Aim To develop a landscape‐level model that partitions variance in plant community composition among local environmental, regional environmental, and purely spatial predictive variables for pyrogenic grasslands (prairies, savannas and woodlands) throughout northern and central Florida. Location North and central Florida, USA. Methods We measured plant species composition and cover in 271 plots throughout the study region. A variation‐partitioning model was used to quantify components of variation in species composition associated with the main and interaction effects of soil and topographic variables, climate variables and spatial coordinates. Partial correlations of environmental variables with community variation were identified using direct gradient analysis (redundancy analysis and partial redundancy analysis) and Monte Carlo tests of significance. Results Community composition was most strongly related to edaphic variables at local scales in association with topographic gradients, although geographically structured edaphic, climatic and pure spatial effects were also evident. Edaphic variables explained the largest portion of total variation explained (TVE) as a main effect (48%) compared with the main effects of climate (9%) and pure spatial factors (9%). The remaining TVE was explained by the interaction effect of climate and spatial factors (13%) and the three‐way interaction (22%). Correlation analyses revealed that the primary compositional gradient was related to soil fertility and topographic position corresponding to soil moisture. A second gradient represented distinct geographical separation between the Florida panhandle and peninsular regions, concurrent with differences in soil characteristics. Gradients in composition corresponded to species richness, which was lower in the Florida peninsula. Main conclusions Environmental variables have the strongest influence on the species composition of Florida pyrogenic grasslands at both local and regional scales. However, the limited distributions of many plant taxa suggest historical constraints on species distributions from one physiographical region to the other (Florida panhandle and peninsula), although this pattern is partially confounded by regionally spatially structured environmental variables. Our model provides insight into the relative importance of local‐ and regional‐scale environmental effects as well as possible historical constraints on floristic variation in pine‐dominated pyrogenic grasslands of the south‐eastern USA.     

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.     

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.     

Biodiversity of stream insects in the Malaysian Peninsula: spatial patterns and environmental constraints

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BIODIVERSITY RESEARCH: Native and introduced fish species richness in Mediterranean streams: the role of multiple landscape influences

Aim To examine the role of multiple landscape factors on the species richness patterns of native and introduced freshwater fish. Location Mediterranean streams, south‐western Iberian Peninsula, Europe (c. 87,000 km²). Methods We used a dataset of fish occurrences from 436 stream sites. We quantified the incremental explanatory power of multiple landscape factors in native, introduced, and overall local species richness using regression analysis. First, we related variation in local species richness across river basins to regional species richness (here, the basin species pool), area and factors of climate and topography. Second, we related within‐river basin local species richness to site’s climate and topography, and spatial structure derived from Principal Coordinates of Neighbour Matrices approach, after testing for species richness spatial autocorrelation; predicted local richness was mapped. Results Patterns of local species richness across river basins were strongly associated with regional species richness for overall, native and introduced species; annual rainfall showed a significant incremental contribution to variation in introduced species richness only. Within river basins, environmental factors were associated with local richness for the three species groups, though their contributions to the total explained variation were inferior to those of spatial factors; rainfall seasonality and stream slope were the most consistent environmental correlates for all species groups, while the influence of spatial factors was most prevalent for native species. Main conclusions Landscape factors operating among and within river basins seem to play a relevant role in shaping local species richness of both native and introduced species, and may be contingent on basin‐specific contexts. Nevertheless, local factors, such as habitat characteristics and biotic interactions and human‐induced disturbances may also be at play. Multiscale approaches incorporating a multitude of factors are strongly encouraged to facilitate a deeper understanding of the biodiversity patterns of Mediterranean streams, and to promote more effective conservation and management strategies.     

Why do mountains support so many species of birds?

Although topographic complexity is often associated with high bird diversity at broad geographic scales, little is known about the relative contributions of geomorphologic heterogeneity and altitudinal climatic gradients found in mountains. We analysed the birds in the western mountains of the New World to examine the two‐fold effect of topography on species richness patterns, using two grains at the intercontinental extent and within temperate and tropical latitudes. Birds were also classified as montane or lowland, based on their overall distributions in the hemisphere. We estimated range in temperature within each cell and the standard deviation in elevation (topographic roughness) based on all pixels within each cell. We used path analysis to test for the independent effects of topographic roughness and temperature range on species richness while controlling for the collinearity between topographic variables. At the intercontinental extent, actual evapotranspiration (AET) was the primary driver of species richness patterns of all species taken together and of lowland species considered separately. In contrast, within‐cell temperature gradients strongly influenced the richness of montane species. Regional partitioning of the data also suggested that range in temperature either by itself or acting in combination with AET had the strongest “effect” on montane bird species richness everywhere. Topographic roughness had weaker “effects” on richness variation throughout, although its positive relationship with richness increased slightly in the tropics. We conclude that bird diversity gradients in mountains primarily reflect local climatic gradients. Widespread (lowland) species and narrow‐ranged (montane) species respond similarly to changes in the environment, differing only in that the richness of lowland species correlates better with broad‐scale climatic effects (AET), whereas mesoscale climatic variation accounts for richness patterns of montane species. Thus, latitudinal and altitudinal gradients in species richness can be explained through similar climatic‐based processes, as has long been argued.     

Spatial nonstationarity and scale-dependency in the relationship between species richness and environmental determinants for the sub-Saharan endemic avifauna

Aim This article aims to test for and explore spatial nonstationarity in the relationship between avian species richness and a set of explanatory variables to further the understanding of species diversity variation. Location Sub‐Saharan Africa. Methods Geographically weighted regression was used to study the relationship between species richness of the endemic avifauna of sub‐Saharan Africa and a set of perceived environmental determinants, comprising the variables of temperature, precipitation and normalized difference vegetation index. Results The relationships between species richness and the explanatory variables were found to be significantly spatially variable and scale‐dependent. At local scales > 90% of the variation was explained, but this declined at coarser scales, with the greatest sensitivity to scale variation evident for narrow ranging species. The complex spatial pattern in regression model parameter estimates also gave rise to a spatial variation in scale effects. Main conclusions Relationships between environmental variables are generally assumed to be spatially stationary and conventional, global, regression techniques are therefore used in their modelling. This assumption was not satisfied in this study, with the relationships varying significantly in space. In such circumstances the average impression provided by a global model may not accurately represent conditions locally. Spatial nonstationarity in the relationship has important implications, especially for studies of species diversity patterns and their scaling.     

Multiple facets of stream macroinvertebrate alpha diversity are driven by different ecological factors across an extensive altitudinal gradient

Environmental filtering and spatial structuring are important ecological processes for the generation and maintenance of biodiversity. However, the relative importance of these ecological drivers for multiple facets of diversity is still poorly understood in highland streams. Here, we examined the responses of three facets of stream macroinvertebrate alpha diversity to local environmental, landscape‐climate and spatial factors in a near‐pristine highland riverine ecosystem. Taxonomic (species richness, Shannon diversity, and evenness), functional (functional richness, evenness, divergence, and Rao's Quadratic entropy), and a proxy of phylogenetic alpha diversity (taxonomic distinctness and variation in taxonomic distinctness) were calculated for macroinvertebrate assemblages in 55 stream sites. Then Pearson correlation coefficient was used to explore congruence of indices within and across the three diversity facets. Finally, multiple linear regression models and variation partitioning were employed to identify the relative importance of different ecological drivers of biodiversity. We found most correlations between the diversity indices within the same facet, and between functional richness and species richness were relatively strong. The two phylogenetic diversity indices were quite independent from taxonomic diversity but correlated with functional diversity indices to some extent. Taxonomic and functional diversity were more strongly determined by environmental variables, while phylogenetic diversity was better explained by spatial factors. In terms of environmental variables, habitat‐scale variables describing habitat complexity and water physical features played the primary role in determining the diversity patterns of all three facets, whereas landscape factors appeared less influential. Our findings indicated that both environmental and spatial factors are important ecological drivers for biodiversity patterns of macroinvertebrates in Tibetan streams, although their relative importance was contingent on different facets of diversity. Such findings verified the complementary roles of taxonomic, functional and phylogenetic diversity, and highlighted the importance of comprehensively considering multiple ecological drivers for different facets of diversity in biodiversity assessment.     

Species richness of woody plants in the landscapes of Central Spain: the role of management disturbances,environment and non‐stationarity

Questions: How important is management disturbance on gamma species richness of woody plants at intermediate landscape scales? How is species richness related to other climatic and biotic factors in the study area? How does the assumption of spatial stationarity affect assessment of relationships among species richness and explanatory variables (e.g. management, biotic and climatic factors) across extensive study areas? Location: Central Spain (regions of Castilla y León, Madrid and Castilla‐La Mancha). Scale: Extent: 150 000 km². Grain: 25 km² (5 × 5‐km cells). Methods: Information from 21 064 plots from the 3SNFI was used to evaluate richness of tree and shrub species at intermediate landscape scales. In addition to variables well known to explain biodiversity, e.g. environmental and biotic factors, effect of management treatments was evaluated by assessing clearcutting, selection cutting, stand improvement treatments and agrosilvopastoral systems (dehesas). Results from GWR techniques were compared with those from OLS regression. Results: Patterns of gamma species richness, although strongly affected by both environmental and biotic variables, were also significantly modified by management factors. Species richness increased with percentage of selection cutting stands and improvement treatments but decreased with percentage of clearcutting stands. Reduced species richness of woody plants was associated with agrosilvopastoral practices. Species richness for trees was closely related to basal area, annual precipitation and topographic complexity; species richness for shrubs was closely related to topographic complexity and agrosilvopastoral systems. Most relationships between species richness and environmental or biotic factors were non‐stationary. Relationships between species richness and management effects tended to be stationary, with a few exceptions. Conclusions: Landscape models of biodiversity in Central Spain were more informative when they accounted for effects of management practices, at least at intermediate scales. In the context of current rural abandonment, silvicultural disturbances of intermediate intensity increased gamma species richness of woody plants. Exclusion of factors such as agrosilvopastoral systems from models could have led to spurious relationships with other spatially co‐varying factors (e.g. summer precipitation). Patterns of spatial variation in relationships, provided by GWR models, allowed formulating hypotheses about potential ecological processes underlying them, beyond generalizations resulting from global (OLS) models.     

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.     

Spatial and environmental determinants of vascular plant species richness distribution in the Iberian Peninsula and Balearic Islands

Using an exhaustive data compilation, Iberian vascular plant species richness in 50 times 50 UTM grid cells was regressed against 24 explanatory variables (spatial, geographical, topographical, geological, climatic, land use and environmental diversity variables) using Generalized Linear Models and partial regression analysis in order to ascertain the relative contribution of primary, heterogeneous and spatially structured variables. The species richness variation accounted for by these variables is reasonably high (65% of total deviance). Little less than half of this variation is accounted for spatially structured variables. A purely spatial component of variation is hardly significant. The most significant variables are those related to altitude, and particularly maximum altitude, whose cubic response reflects the occurrence of the maximum number of species at the highest altitudes. This result highlighted the importance of Iberian mountains as hotspots of diversity and the relevance of large and small scale historical factors in contemporary plant distribution patterns. Climatic or energy-related variables contributed little, whereas geological (calcareous and acid rocks) and, to a lesser extent, environmental heterogeneity variables (land use diversity and altitude range) seem to be more important.     

Gradients in stream fish assemblages across a Mediterranean landscape: contributions of environmental factors and spatial structure

1. Despite wide recognition that fish assemblages are influenced by factors operating over a range of spatial scales, little effort has been devoted to quantifying large‐scale variation and the multiscale dependencies of assemblage patterns and processes. This is particularly true for Mediterranean streams, where seasonally predictable drying‐up may lead to a strong association between assemblage attributes and large‐scale factors affecting the distribution of population sources and extinction likelihood. 2. The contribution of large‐scale factors to stream fish assemblage variation was quantified across a Mediterranean landscape, in south‐west Portugal. Fish abundance and species composition were estimated at 166 sites across third‐ to sixth‐order streams, in March–July 1998. Variance partitioning by redundancy analyses was used to analyse assemblage variation against three sets of predictor variables: environmental (catchment position, and geomorphic and hydrological factors), large‐scale spatial trends and neighbourhood effects. 3. Environmental variables and spatial trends accounted for 34.6% of the assemblage variation across the entire region, and for 36.6 and 57.8% within the two largest catchments (Mira and Seixe). Neighbourhood effects were analysed at the catchment scale, increasing the explained variation to 56.1% (Mira) and 70.7% (Seixe). 4. A prevailing environmental gradient was reflected in an increase in the abundance of all species and size‐classes in relation to catchment position, with more fish present in larger streams and in downstream reaches. Variables describing geomorphic and hydrological settings were less important in explaining assemblage variation. 5. Spatial trends always accounted for the smallest fraction of assemblage variation, and they were probably associated with historical barriers to fish dispersal. The strong neighbourhood effects may be related to spatially autocorrelated habitat conditions, but they are also a likely consequence of fish emigration/extinction and colonisation processes. 6. These results emphasise that a substantial proportion of fish assemblage variation in Mediterranean streams may be explained by large‐scale factors, irrespective of microhabitats and local biotic interactions. It is suggested that this pattern results to a large extent from the seasonal drying‐up, with the summer shortage of surface water limiting fish occurrence in headwaters, and consequently the key core areas for fish concentrating in larger streams and tributaries adjacent to large streams because of neighbourhood effects.     

Environmental factors influencing spatial patterns of shrub diversity in chaparral,Santa Ynez Mountains,California

We examined patterns of shrub species diversity relative to landscape‐scale variability in environmental factors within two watersheds on the coastal flank of the Santa Ynez Mountains, California. Shrub species richness and dominance was sampled at a hierarchy of spatial units using a high‐powered telescope from remote vantage points. Explanatory variables included field estimates of total canopy cover and percentage rock cover, and modeled distributions of slope, elevation, photosynthetically active radiation, topographic moisture index, and local topographic variability. Correlation, multiple regression, and regression tree analyses showed consistent relationships between field‐based measurements of species richness and dominance, and topographically‐mediated environmental variables. In general, higher richness and lower dominance occurred where environmental conditions indicated greater levels of resource limitation with respect to soil moisture and substrate availability. Maximum richness in shrub species occurred on high elevation sites with low topographic moisture index, rocky substrate, and steep slopes. Maximum dominance occurred at low elevation sites with low topographic variability, high potential solar insolation, and high total shrub canopy cover. The observed patterns are evaluated with respect to studies on species‐environment relations, resource use, and regeneration of shrubs in chaparral and coastal sage scrub. The results are discussed in the context of existing species‐diversity hypotheses that hinge on reduced competitive dominance and increased resource heterogeneity under conditions of resource limitation.     

Assessment of the relationships of geographic variation in species richness to climate and landscape variables within and among lineages of North American freshwater fishes

Aim Geographic variation in species richness is a well‐studied phenomenon. However, the unique response of individual lineages to environmental gradients in the context of general patterns of biodiversity across broad spatial scales has received limited attention. The focus of this research is to examine relationships between species richness and climate, topographic heterogeneity and stream channel characteristics within and among families of North American freshwater fishes. Location The United States and Canada. Methods Distribution maps of 828 native species of freshwater fishes were used to generate species richness estimates across the United States and Canada. Variation in species richness was predicted using spatially explicit models incorporating variation in climate, topography and/or stream channel length and stream channel diversity for all 828 species as well as for the seven largest families of freshwater fishes. Results The overall gradient of species richness in North American freshwater fishes is best predicted by a model incorporating variables describing climate and topography. However, the response of species richness to particular climate or landscape variables differed among families, with models possessing the highest predictive ability incorporating data on climate, topography and/or stream channel characteristics within a region. Main conclusions The correlations between species richness and abiotic variables suggest a strong influence of climate and physical habitat on the structuring of regional assemblages of North American freshwater fishes. However, the relationship between these variables and species richness varies among families, suggesting the importance of phylogenetic constraints on the regulation of geographic distributions of species.     

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.     

Modelling geographical patterns in species richness using eigenvector-based spatial filters

Aim To test the mechanisms driving bird species richness at broad spatial scales using eigenvector‐based spatial filtering. Location South America. Methods An eigenvector‐based spatial filtering was applied to evaluate spatial patterns in South American bird species richness, taking into account spatial autocorrelation in the data. The method consists of using the geographical coordinates of a region, based on eigenanalyses of geographical distances, to establish a set of spatial filters (eigenvectors) expressing the spatial structure of the region at different spatial scales. These filters can then be used as predictors in multiple and partial regression analyses, taking into account spatial autocorrelation. Autocorrelation in filters and in the regression residuals can be used as stopping rules to define which filters will be used in the analyses. Results Environmental component alone explained 8% of variation in richness, whereas 77% of the variation could be attributed to an interaction between environment and geography expressed by the filters (which include mainly broad‐scale climatic factors). Regression coefficients of environmental component were highest for AET. These results were unbiased by short‐scale spatial autocorrelation. Also, there was a significant interaction between topographic heterogeneity and minimum temperature. Conclusion Eigenvector‐based spatial filtering is a simple and suitable statistical protocol that can be used to analyse patterns in species richness taking into account spatial autocorrelation at different spatial scales. The results for South American birds are consistent with the climatic hypothesis, in general, and energy hypothesis, in particular. Habitat heterogeneity also has a significant effect on variation in species richness in warm tropical regions.     

The variation of tree beta diversity across a global network of forest plots

Aims With the aim of understanding why some of the world's forests exhibit higher tree beta diversity values than others, we asked: (1) what is the contribution of environmentally related variation versus pure spatial and local stochastic variation to tree beta diversity assessed at the forest plot scale; (2) at what resolution are these beta‐diversity components more apparent; and (3) what determines the variation in tree beta diversity observed across regions/continents? Location World‐wide. Methods We compiled an unprecedented data set of 10 large‐scale stem‐mapping forest plots differing in latitude, tree species richness and topographic variability. We assessed the tree beta diversity found within each forest plot separately. The non‐directional variation in tree species composition among cells of the plot was our measure of beta diversity. We compared the beta diversity of each plot with the value expected under a null model. We also apportioned the beta diversity into four components: pure topographic, spatially structured topographic, pure spatial and unexplained. We used linear mixed models to interpret the variation of beta diversity values across the plots. Results Total tree beta diversity within a forest plot decreased with increasing cell size, and increased with tree species richness and the amount of topographic variability of the plot. The topography‐related component of beta diversity was correlated with the amount of topographic variability but was unrelated to its species richness. The unexplained variation was correlated with the beta diversity expected under the null model and with species richness. Main conclusions Because different components of beta diversity have different determinants, comparisons of tree beta diversity across regions should quantify not only overall variation in species composition but also its components. Global‐scale patterns in tree beta diversity are largely coupled with changes in gamma richness due to the relationship between the latter and the variation generated by local stochastic assembly processes.