Species turnover in Amazonian frogs: low predictability and large differences among forests

The factors explaining species turnover at different spatial scales have been intensively studied, but most work in Amazonia has mainly focused on plants. For animals, it is not as obvious which environmental variables most affect differences in species composition among sites. We sought to identify what causes anuran turnover in Amazonian terra firme forests, and how the effectiveness of these factors varies among regions and across spatial scales. We sampled frogs in 56 plots along ponds and streams distributed over three terra firme forest areas in Eastern Amazonia. Using multiple regressions on distance matrices, we partitioned the variation in species turnover into components explained by variation in environmental and spatial distances. This was done in parallel for each area separately, and for all areas together, to assess the consistency of results between scales and across areas at the same scale. Each community seemed to respond to a set of factors specific to that area, and the identity of the variables that emerged as significant differed among areas and scales. Both geographical distances and environmental differences had larger explanatory power at the regional scale than at the local scale. The large differences among results from different areas caution against making broad generalizations about species turnover patterns from a single community, as real differences may exist among areas.     

The theory of the nested species–area relationship: geometric foundations of biodiversity scaling

The relationship between sampled area and the number of species within that area, the species–area relationship (SAR), is a major biodiversity pattern and one of a few law‐like regularities in ecology. While the SAR for isolated units (islands or continents) is assumed to result from the dynamics of species colonization, speciation and extinction, the SAR for contiguous areas in which smaller plots are nested within larger sample areas can be attributed to spatial patterns in the distribution of individuals. The nested SAR is typically triphasic in logarithmic space, so that it increases steeply at smaller scales, decelerates at intermediate scales and increases steeply again at continental scales. I will review current theory for this pattern, showing that all three phases of the SAR can be derived from simple geometric considerations. The increase of species richness with area in logarithmic space is generally determined by overall species rarity, so that the rarer the species are on average, the higher is the local slope z. Rarity is scale‐dependent: species occupy only a minor proportion of area at broad spatial scales, leading to upward accelerating shape of the SAR at continental scales. Similarly, species are represented by only a few individuals at fine spatial scales, leading to high SAR slope also at small areas. Geometric considerations reveal links of the SAR to other macroecological patterns, namely patterns of β‐diversity, the species–abundance distribution, and the relationship between energy availability (or productivity) and species richness. Knowledge of the regularities concerning nested SARs may be used for standardizing unequal areas, upscaling species richness and estimating species loss due to area loss, but all these applications have their limits, which also follow from the geometric considerations.     

The imprint of the geographical, evolutionary and ecological context on species-area relationships

Species-area relationships (SAR) are fundamental in the understanding of biodiversity patterns and of critical importance for predicting species extinction risk worldwide. Despite the enormous attention given to SAR in the form of many individual analyses, little attempt has been made to synthesize these studies. We conducted a quantitative meta-analysis of 794 SAR, comprising a wide span of organisms, habitats and locations. We identified factors reflecting both pattern-based and dynamic approaches to SAR and tested whether these factors leave significant imprints on the slope and strength of SAR. Our analysis revealed that SAR are significantly affected by variables characterizing the sampling scheme, the spatial scale, and the types of organisms or habitats involved. We found that steeper SAR are generated at lower latitudes and by larger organisms. SAR varied significantly between nested and independent sampling schemes and between major ecosystem types, but not generally between the terrestrial and the aquatic realm. Both the fit and the slope of the SAR were scale-dependent. We conclude that factors dynamically regulating species richness at different spatial scales strongly affect the shape of SAR. We highlight important consequences of this systematic variation in SAR for ecological theory, conservation management and extinction risk predictions.     

How to allow SAR collapse across local and continental scales: a resolution of the controversy between Storch et al. (2012) and Lazarina et al. (2013)

Up‐scaling species richness from local to continental scales is an unsolved problem of macroecology. Macroecologists hope that proper up‐scaling can uncover the hidden rules that underlie spatial patterns in species richness, but a machinery to up‐scale species richness also has a purely practical side at the scales and for the habitats where direct observations cannot be performed. The species–area relationship (SAR) could provide a tool for up‐scaling, but no valid method has yet been put forward. Such a method would have resulted from Storch et al.'s (2012) suggestion that there is a universal curve to which each rescaled SAR collapses, if Lazarina et al. (2013) had not shown that it does not: both arguments were supported by data analyses. Here we present an analytical model for mainland SAR and argue in favour of the latter authors. We identify 1) the variation in mean species‐range size, 2) the variation in forces that drive SAR at various scales, and 3) the finite‐area effect, as the reasons for the absence of collapse. Finally, we suggest a rescaling that might fix the problem. We conclude, however, that ecologists are still far from finding a practical, robust and easy‐to‐use solution for up‐scaling species richness from SARs.     

Plants on small islands revisited: the effects of spatial scale and habitat quality on the species–area relationship

Understanding how species diversity is related to sampling area and spatial scale is central to ecology and biogeography. Small islands and small sampling units support fewer species than larger ones. However, the factors influencing species richness may not be consistent across scales. Richness at local scales is primarily affected by small‐scale environmental factors, stochasticity and the richness at the island scale. Richness at whole‐island scale, however, is usually strongly related to island area, isolation and habitat diversity. Despite these contrasting drivers at local and island scales, island species–area relationships (SARs) are often constructed based on richness sampled at the local scale. Whether local scale samples adequately predict richness at the island scale and how local scale samples influence the island SAR remains poorly understood. We investigated the effects of different sampling scales on the SAR of trees on 60 small islands in the Raja Ampat archipelago (Indonesia) using standardised transects and a hierarchically nested sampling design. We compared species richness at different grain sizes ranging from single (sub)transects to whole islands and tested whether the shape of the SAR changed with sampling scale. We then determined the importance of island area, isolation, shape and habitat quality at each scale on species richness. We found strong support for scale dependency of the SAR. The SAR changed from exponential shape at local sampling scales to sigmoidal shape at the island scale indicating variation of species richness independent of area for small islands and hence the presence of a small‐island effect. Island area was the most important variable explaining species richness at all scales, but habitat quality was also important at local scales. We conclude that the SAR and drivers of species richness are influenced by sampling scale, and that the sampling design for assessing the island SARs therefore requires careful consideration.     

Relative importance of spatial processes and environmental factors in shaping alpine meadow communities

Aims Spatial processes and environmental control are the two distinct, yet not mutually exclusive forces of community structuring, but the relative importance of these factors is controversial due to the species-specific dispersal ability, sensitivity towards environmental variables, organism's abundance and the effect of spatial scale. In the present paper, we explored spatial versus environmental control in shaping community composition (i.e. β-diversity) and species turnover (i.e. change of β-diversity) at an alpine meadow along a slope aspect gradient on the Qinghai–Tibetan Plateau at different spatial scales of sampling (quadrats and plots), by taking account of seed dispersal mode and abundance.Methods We examined the relative importance of spatial processes and environmental factors using all species and four additional subsets of selected species. Moreover, we attempted to explore the effect of scale (quadrat refers to scale of ~0.3 m and plot of ~8 m) on their counter balance. The data were analyzed both by variation partitioning and multiple regressions on distance matrices. The spatial structure was modelled using Moran's eigenvector maps (MEM).Important findings Both spatial processes and environmental factors were important determinants of the community composition and species turnover. The community composition in the alpine meadow was controlled by spatially structured environment (17.6%), space independent of environment (18.0%) and a negligible effect of environment independent of space (4.4%) at the scale of quadrats. These three components contributed 21.8, 9.9 and 13.9%, respectively, at the scale of plots. The balance between the forces at different spatial scales drove community structures along the slope aspect gradient. The importance of environmental factors on β-diversity at alpine meadow increased with scale while that of spatial processes decreased or kept steady, depending on dispersal mode and abundance of species comprising the subset. But the 'pure' effect of spatial processes on species turnover increased with scale while that of environmental factors decreased. This discrepancy highlights that β-diversity and species turnover were determined jointly by spatial processes and environmental factors. We also found that the relative roles of these processes vary with spatial scale. These results underline the importance of considering species-specific dispersal ability and abundance of species comprising the communities and the appropriate spatial scale in understanding the mechanisms of community assembly.     

哀牢山亚热带中山湿性常绿阔叶林树种beta多样性格局形成的驱动力

Beta多样性通常指群落在时间和空间上物种组成的差异, 包括物种周转组分和物种丰富度差异组分。驱动beta多样性格局形成的生态过程决定了群落的时空动态, 然而关于beta多样性及其两个组分格局形成的驱动力还存在较多争议。以往研究表明, beta多样性的格局存在取样尺度的依赖性, 驱动其形成的生态过程在不同取样尺度下的相对重要性也随之改变。本研究以哀牢山亚热带中山湿性常绿阔叶林20 ha动态监测样地为研究对象, 在不同取样尺度上, 将样方间的Bray-Curtis指数分解为物种周转组分和物种丰富度差异组分, 通过典范冗余分析和方差分解的方法揭示环境过滤和扩散限制对于beta多样性及其两个组分格局形成的相对重要性及其尺度依赖性。结果表明: (1) beta多样性、物种周转组分和物种丰富度差异组分均随取样尺度的增大而减小。在不同取样尺度下, 物种周转组分对于beta多样性的贡献始终占主导地位。(2)随着取样尺度的增大, 环境过滤驱动beta多样性格局形成的相对重要性逐渐增加, 而扩散限制的相对重要性逐渐降低。本研究进一步证实了取样尺度在beta多样性格局形成及其驱动力定量评价中的重要性, 今后的研究需要进一步解析上述尺度效应的形成机制。     

Spatial variation in the climatic predictors of species compositional turnover and endemism

Previous research focusing on broad‐scale or geographically invariant species‐environment dependencies suggest that temperature‐related variables explain more of the variation in reptile distributions than precipitation. However, species–environment relationships may exhibit considerable spatial variation contingent upon the geographic nuances that vary between locations. Broad‐scale, geographically invariant analyses may mask this local variation and their findings may not generalize to different locations at local scales. We assess how reptile–climatic relationships change with varying spatial scale, location, and direction. Since the spatial distributions of diversity and endemism hotspots differ for other species groups, we also assess whether reptile species turnover and endemism hotspots are influenced differently by climatic predictors. Using New Zealand reptiles as an example, the variation in species turnover, endemism and turnover in climatic variables was measured using directional moving window analyses, rotated through 360°. Correlations between the species turnover, endemism and climatic turnover results generated by each rotation of the moving window were analysed using multivariate generalized linear models applied at national, regional, and local scales. At national‐scale, temperature turnover consistently exhibited the greatest influence on species turnover and endemism, but model predictive capacity was low (typically r² = 0.05, P < 0.001). At regional scales the relative influence of temperature and precipitation turnover varied between regions, although model predictive capacity was also generally low. Climatic turnover was considerably more predictive of species turnover and endemism at local scales (e.g., r² = 0.65, P < 0.001). While temperature turnover had the greatest effect in one locale (the northern North Island), there was substantial variation in the relative influence of temperature and precipitation predictors in the remaining four locales. Species turnover and endemism hotspots often occurred in different locations. Climatic predictors had a smaller influence on endemism. Our results caution against assuming that variability in temperature will always be most predictive of reptile biodiversity across different spatial scales, locations and directions. The influence of climatic turnover on the species turnover and endemism of other taxa may exhibit similar patterns of spatial variation. Such intricate variation might be discerned more readily if studies at broad scales are complemented by geographically variant, local‐scale analyses.     

Community Functional Responses to Soil and Climate at Multiple Spatial Scales: When Does Intraspecific Variation Matter?

Despite increasing evidence of the importance of intraspecific trait variation in plant communities, its role in community trait responses to environmental variation, particularly along broad-scale climatic gradients, is poorly understood. We analyzed functional trait variation among early-successional herbaceous plant communities (old fields) across a 1200-km latitudinal extent in eastern North America, focusing on four traits: vegetative height, leaf area, specific leaf area (SLA), and leaf dry matter content (LDMC). We determined the contributions of species turnover and intraspecific variation to between-site functional dissimilarity at multiple spatial scales and community trait responses to edaphic and climatic factors. Among-site variation in community mean trait values and community trait responses to the environment were generated by a combination of species turnover and intraspecific variation, with species turnover making a greater contribution for all traits. The relative importance of intraspecific variation decreased with increasing geographic and environmental distance between sites for SLA and leaf area. Intraspecific variation was most important for responses of vegetative height and responses to edaphic compared to climatic factors. Individual species displayed strong trait responses to environmental factors in many cases, but these responses were highly variable among species and did not usually scale up to the community level. These findings provide new insights into the role of intraspecific trait variation in plant communities and the factors controlling its relative importance. The contribution of intraspecific variation to community trait responses was greatest at fine spatial scales and along edaphic gradients, while species turnover dominated at broad spatial scales and along climatic gradients.     

At what spatial scales does resource selection vary? A case study of koalas in a semi‐arid region

The conservation of any species requires understanding and predicting the distribution of its habitat and resource use, including the effects of scale‐dependent variation in habitat and resource quality. Consequently, testing for resource selection at the appropriate scales is critical. We investigated how the resource selection process varies across scales, using koalas in a semi‐arid landscape of eastern Australia as a case study. We asked: at what scales does tree selection by koalas vary across regions? We tested the importance of the variation of our ecological predictors at the following scales: (i) the site‐scale (a stand of trees representing an individual koala's perception of local habitat); (ii) the landscape‐scale (10 × 10 km area representing a space within which a population of koalas exists); and (iii) a combination of these scales. We used a mixed‐modelling approach to quantify variation in selection of individual trees by koalas among sites and landscapes within a 1600 km² study area. We found that tree species, and tree height, were the most important factors influencing tree selection, and that their effect did not vary across scales. In contrast, preferences for trees of different condition, which is the state of tree canopy health, did vary across landscapes, indicating spatial variation in the selection of trees with respect to tree condition at the landscape‐scale, but not at the site‐scale. We conclude that resource selection processes can depend on the quality of those resources at different scales and their heterogeneous nature across landscapes, highlighting the consequence of scale‐dependent ecological processes. Designing studies that capture the heterogeneity in habitat and resources used by species that have an extensive distribution is an important prerequisite for effective conservation planning and management.     

Global pattern and local variation in species–area relationships

Aim We conducted a meta‐analysis of species–area relationships (SARs) by combining several data sets and important covariates such as types of islands, taxonomic groups, latitude and spatial extent, in a hierarchical model framework to study global pattern and local variation in SARs and its consequences for prediction. Location One thousand nine hundred and eighteen islands from 94 SAR studies from around the world. Methods We developed a generalization of the power‐law SAR model, the HSARX model, which allows: (1) the inclusion of multiple focal parameters (intercept, slope, within‐study variance), (2) use of multiple effect modifiers based on a collection of SAR studies, and (3) modelling of the between‐ and within‐study variability. Results The global pattern in the SAR was the average of local SARs and had wide confidence intervals. The global SAR slope was 0.228 with 90% confidence limits of 0.059 and 0.412. The intercept, slope and within‐study variability of local SARs showed great heterogeneity as a result of the interaction of modifying covariates. Confidence intervals for these SAR parameters were narrower when other covariates in addition to area were accounted for, thus increasing the accuracy of the predictions for species richness. The significant effect of latitude and the interaction of latitude, taxa and island type on the SAR slope indicated that the ‘typical’ latitudinal diversity gradient can be reversed in isolated systems. Main conclusions The power‐law relationship underlying the HSARX model provides a good fit for non‐nested SARs across vastly different spatial scales by taking into account other covariates. The HSARX framework allows researchers to explore the complex interactions among SAR parameters and modifying variables, to explicitly study the scale dependence, and to make robust predictions on multiple levels (island, study, global) with associated prediction intervals. From a prediction perspective, it is not the global pattern but the local variation that matters.     

Environmental and spatial drivers of spider diversity at contrasting microhabitats

The relative importance of environmental and spatial drivers of animal diversity varies across scales, but identifying these scales can be difficult if a sampling design does not match the scale of the target organisms' interaction with their habitat. In this study, we quantify and compare the effects of environmental variation and spatial proximity on ground‐dwelling spider assemblages sampled from three distinct microhabitat types (open grassland, logs, trees) that recur across structurally heterogeneous grassy woodlands. We used model selection and multivariate procedures to compare the effects of different environmental attributes and spatial proximity on spider assemblages at each microhabitat type. We found that species richness and assemblage composition differed among microhabitat types. Bare ground cover had a negative effect on spider richness under trees, but a positive effect on spider richness in open grassland. Turnover in spider assemblages from open grassland was correlated with environmental distance, but not geographic distance. By contrast, turnover in spiders at logs and trees was correlated with geographic distance, but not environmental distance. Our study suggests that spider assemblages from widespread and connected open grassland habitat were more affected by environmental than spatial gradients, whereas spiders at log and tree habitats were more affected by spatial distance among these discrete but recurring microhabitats. Deliberate selection and sampling of small‐scale habitat features can provide robust information about the drivers of arthropod diversity and turnover in landscapes.     

Dispersal ability links to cross‐scale species diversity patterns across the Eurasian Arctic tundra

Aim The role of dispersal in structuring biodiversity across spatial scales is controversial. If dispersal controls regional and local community assembly, it should also affect the degree of spatial species turnover as well as the extent to which regional communities are represented in local communities. Here we provide the first integrated assessment of relationships between dispersal ability and local‐to‐regional spatial aspects of species diversity across a large geographical area. Location Northern Eurasia. Methods Using a cross‐scale analysis covering local (0.64 m²) to continental (the Eurasian Arctic biome) scales, we compared slope parameters of the dissimilarity‐to‐distance relationship in species composition and the local‐to‐regional relationship in species richness among three plant‐like groups that differ in dispersal ability: lichens with the highest dispersal ability; mosses and moss allies with intermediate dispersal ability; and seed plants with the lowest dispersal ability. Results Diversity patterns generally differed between the three groups according to their dispersal ability, even after controlling for niche‐based processes. Increasing dispersal ability is linked to decreasing spatial species turnover and an increasing ratio of local to regional species richness. All comparisons supported our expectations, except for the slope of the local‐to‐regional relationship in species richness for mosses and moss allies which was not significantly steeper than that of seed plants. Main conclusions The negative link between dispersal ability and spatial species turnover and the corresponding positive link between dispersal ability and the ratio of local‐to‐regional species richness support the idea that dispersal affects community structure and diversity patterns across spatial scales.     

Using hierarchical sampling to understand scales of spatial variation in early coral recruitment

Ecological patterns are created by processes acting over multiple spatial and temporal scales. By combining spatially explicit sampling with variance components models, the relative importance of spatial scale to overall variability can be determined. We used a spatially structured experimental design in the Mombasa Marine National Park in Kenya to quantify variation in coral recruitment across four spatial scales (~1–1,000 m) and to generate hypotheses about processes affecting recruitment and potential sources of post-settlement mortality during early life history. For the dominant recruiting corals (Pocillopora spp.), variation in recruitment on surfaces protected from fish grazing was greatest at the largest spatial scale examined (1,000 m). We hypothesize that recruitment on protected surfaces varies mainly with larval delivery due to different lagoonal circulation and water flow between sites. Conversely, variation on surfaces exposed to fishes was greatest at the smallest spatial scale (1 m). We hypothesize that recruitment on exposed surfaces mainly reflects local differences in the scale and intensity of fish grazing, which may obscure larval delivery patterns. Spatial variation in recruitment can affect many ecological processes and factors, including growth, survival to maturity, the distribution of habitat, and variation in species interaction strengths. This study demonstrates how spatially explicit sampling, followed by variance components modeling to partition variance across scales, can help to identify potential drivers of patterns at each relevant scale.     

Spatial pattern of distribution of marine invertebrates within a subtidal community: do communities vary more among patches or plots?

Making links between ecological processes and the scales at which they operate is an enduring challenge of community ecology. Our understanding of ecological communities cannot advance if we do not distinguish larger scale processes from smaller ones. Variability at small spatial scales can be important because it carries information about biological interactions, which cannot be explained by environmental heterogeneity alone. Marine fouling communities are shaped by both the supply of larvae and competition for resources among colonizers—these two processes operate on distinctly different scales. Here, we demonstrate how fouling community structure varies with spatial scale in a temperate Australian environment, and we identify the spatial scale that captures the most variability. Community structure was quantified with both univariate (species richness and diversity) and multivariate (similarity in species composition) indices. Variation in community structure was unevenly distributed between the spatial scales that we examined. While variation in community structure within patch was usually greater than among patch, variation among patch was always significant. Opportunistic taxa that rely heavily on rapid colonization of free space spread more evenly among patches during early succession. In contrast, taxa that are strong adult competitors but slow colonizers spread more evenly among patches only during late succession. Our findings show significant patchiness can develop in a habitat showing no systematic environmental spatial variation, and this patchiness can be mediated through different biological factors at different spatial scales.     

Does functional homogenization accompany taxonomic homogenization of British birds and how do biotic factors and climate affect these processes?

Environmental change has reshuffled communities often causing taxonomic homogenization rather than differentiation. Some studies suggest that this increasing similarity of species composition between communities is accompanied by an increase in similarity of trait composition—functional homogenization—although different methodologies have failed to come to any consistent conclusions. Functional homogenization could have a large effect on ecosystem functioning and stability. Here, we use the general definition of homogenization as “reduced spatial turnover over time” to compare changes in Simpson's beta diversity (taxonomic turnover) with changes in Rao's quadratic entropy beta diversity (functional turnover) in British breeding birds at three spatial scales. Using biotic and climatic variables, we identify which factors may predispose a site to homogenization. The change in turnover measures between two time periods, 20 years apart, was calculated. A null model approach was taken to identify occurrences of functional homogenization and differentiation independent of changes in taxonomic turnover. We used conditional autoregressive models fitted using integrated nested Laplace approximations to determine how environmental drivers and factors relating to species distributions affect changes in spatial turnover of species and functional diversity. The measurement of functional homogenization affects the chance of rejection of the null models, with many sites showing taxonomic homogenization unaccompanied by functional homogenization, although occurrence varies with spatial scale. At the smallest scale, while temperature‐related variables drive changes in taxonomic turnover, changes in functional turnover are associated with variation in growing degree days; however, changes in functional turnover become more difficult to predict at larger spatial scales. Our results highlight the multifactorial processes underlying taxonomic and functional homogenization and that redundancy in species traits may allow ecosystem functioning to be maintained in some areas despite changes in species composition.     

Landscape-Scale Controls on Aboveground Forest Carbon Stocks on the Osa Peninsula,Costa Rica

Tropical forests store large amounts of carbon in tree biomass, although the environmental controls on forest carbon stocks remain poorly resolved. Emerging airborne remote sensing techniques offer a powerful approach to understand how aboveground carbon density (ACD) varies across tropical landscapes. In this study, we evaluate the accuracy of the Carnegie Airborne Observatory (CAO) Light Detection and Ranging (LiDAR) system to detect top-of-canopy tree height (TCH) and ACD across the Osa Peninsula, Costa Rica. LiDAR and field-estimated TCH and ACD were highly correlated across a wide range of forest ages and types. Top-of-canopy height (TCH) reached 67 m, and ACD surpassed 225 Mg C ha^-1, indicating both that airborne CAO LiDAR-based estimates of ACD are accurate in tall, high-biomass forests and that the Osa Peninsula harbors some of the most carbon-rich forests in the Neotropics. We also examined the relative influence of lithologic, topoedaphic and climatic factors on regional patterns in ACD, which are known to influence ACD by regulating forest productivity and turnover. Analyses revealed a spatially nested set of factors controlling ACD patterns, with geologic variation explaining up to 16% of the mapped ACD variation at the regional scale, while local variation in topographic slope explained an additional 18%. Lithologic and topoedaphic factors also explained more ACD variation at 30-m than at 100-m spatial resolution, suggesting that environmental filtering depends on the spatial scale of terrain variation. Our result indicate that patterns in ACD are partially controlled by spatial variation in geologic history and geomorphic processes underpinning topographic diversity across landscapes. ACD also exhibited spatial autocorrelation, which may reflect biological processes that influence ACD, such as the assembly of species or phenotypes across the landscape, but additional research is needed to resolve how abiotic and biotic factors contribute to ACD variation across high biomass, high diversity tropical landscapes.     

Analytical evidence for scale-invariance in the shape of species abundance distributions

The distribution of species abundances within an ecological community provides a window into ecological processes and has important applications in conservation biology as an indicator of disturbance. Previous work indicates that species abundance distributions might be independent of the scales at which they are measured which has implications for data interpretation. Here we formulate an analytically tractable model for the species abundance distribution at different scales and discuss the biological relevance of its assumptions. Our model shows that as scale increases, the shape of the species abundance distribution converges to a particular shape given uniquely by the Jaccard index of spatial species turnover and by a parameter for the spatial correlation of abundances. Our model indicates that the shape of the species abundance distribution is taxon specific but does not depend on sample area, provided this area is large. We conclude that the species abundance distribution may indeed serve as an indicator of disturbances affecting species spatial turnover and that the assumption of conservation of energy in ecosystems, which is part of the Maximum Entropy approach, should be re-evaluated.     

Scale dependence of species-energy relationships: evidence from fishes in thousands of lakes

Variation in the shape of relationships between species richness and different measures of energy may be linked to variation in the spatial scale on which such relationships are measured. We examine scale dependence in the relationship between potential evapotranspiration and the species richness of fishes in 7,885 postglacial lakes. The strength of this relationship is weak across lake communities but strong and positive across groups of lakes or regions. In addition, the strength and slope of this relationship increase significantly as the regional scale of analysis is increased. We interpret the observed patterns in terms of a simple model whereby energy influences the linear character of the species-energy relationship through its influence on spatial turnover in the species composition (beta diversity). Our results suggest that if energy is strongly tied to patterns of site occupancy or abundance, the parameters of species-energy relationships will depend, to a considerable extent, on the scale of measurement. Furthermore, the ability of high-energy regions to accommodate relatively large numbers of rare or infrequent species may underlie any general tendency for the strength or shape of species-energy relationships to change with scale.     

Does the universality of the species–area relationship apply to smaller scales and across taxonomic groups?

The universality of the shape of the species–area relationship (SAR) is subject to regular debate. Recently, Storch et al. (2012) argued that species–area relationships collapse into a single curve at continental scales after the axes are rescaled adjusting the area‐axis being to the mean range size of species and the species‐axis to the species richness of an area equal to mean range size. It has been claimed that this rescaling generates a universal model, invariant of taxon and continent, and that it is driven by differences in range sizes. Here, we test the universality of the rescaled SAR across scales smaller than the continental level, using presence data for plants, birds and butterflies. We also test an alternative rescaling approach, by using the total extent of the study area and total species richness. At the scales analysed here, we found that the proposed rescaling by Storch et al. adjusts for differences in the extent of the study area and for variation in gamma diversity. Consequently, while the rescaled curves were closely aligned, they did not converge into a single curve. The observed remaining variation is independent of scale and biogeographical region, and is correlated with beta diversity; thus, it reflects the differentiation of species composition in space.