The diversity field of New World leaf‐nosed bats (Phyllostomidae)

Aim To analyse how the patterns of species richness for the whole family Phyllostomidae determine the structure of diversity fields (sets of species‐richness values) within the ranges of individual bat species. Location The range of the family Phyllostomidae in North and South America. Methods We generated a database of the occurrence of 143 phyllostomid bat species in 6794 quadrats, analysing the species‐richness frequency distribution for all sites, and for subsets of sites defined by the geographic ranges of species. Range–diversity plots, depicting simultaneously the size and the mean species richness of ranges, were built to explore the patterns of co‐occurrence in widespread and restricted species. We compared the empirical patterns against two null models: (1) with scattered (non‐cohesive) ranges, and (2) with cohesive ranges modelled with the spreading‐dye algorithm. Diversity fields were analysed with richness maps for individual species and with comparisons of species‐richness frequency distributions. Results Overall richness frequency distribution showed a multimodal pattern, whereas simulated distributions showed lower values of variance, and were unimodal (for model 1) and bimodal (for model 2). Range–diversity plots for the empirical data and for the cohesive‐ranges simulation showed a strong tendency of species to co‐occur in high‐diversity sites. The scattered‐ranges simulation showed no such tendency. Diversity fields varied according to idiosyncratic features of species generating particular geographic patterns and richness frequency distributions. Main conclusions Phyllostomid bats show a higher level of co‐occurrence than expected from null models. That tendency in turn implies a higher variance in species richness among sites, generating a wider species‐richness frequency distribution. The diversity field of individual species results from the size, shape and location of ranges, but also depends on the general pattern of richness for the whole family.     

Co-diversity and co-distribution in phyllostomid bats: Evaluating the relative roles of climate and niche conservatism

Explaining the causes of geographic gradients in biodiversity remains an elusive task. Traditionally, correlative approaches have been used to relate species richness with contemporary climate, without actually explaining the causal factors. Recent approaches propose simulation models as more appropriate tools for assessing potential causes of macroecological patterns. Here we developed stochastic models to assess the relative contribution of climate and niche conservatism in determining compositional similarity among sites (co-diversity) and geographic association among species (co-distribution) in the bat family Phyllostomidae. We used range-diversity plots and variance-ratio tests to describe and evaluate such patterns. Our results supported a strong effect of climate in determining cohesive ranges causing positive co-diversity and co-distribution. We also demonstrated a marginal effect of niche conservatism, as modeled here, among species in shaping these patterns. However, climate and niche conservatism are not sufficient and other processes are still required to explain observed patterns. Our study highlights the importance of historical processes and demonstrates the usefulness of a simulation framework in testing biogeographical hypothesis to understand the relationship between diversity and distribution.     

Range size in mid-domain models of species diversity

Geographical patterns of species diversity have been examined using mid-domain null models, in which the ranges of individual species are simulated by randomly arranging them on a bounded one- or two-dimensional continent. These models have shown that structured patterns in the geographical distribution of biodiversity can arise even under a fully stochastic procedure. In particular, mid-domain models have demonstrated that the random generation of ranges of different sizes and locations can produce a gradient of species diversity similar to the one found in real assemblages, with a peak at the middle of a continent. A less explored feature of mid-domain models is the pattern of range-size frequency distribution. Numerical simulations have provided some insights about the geographic pattern of average range size, but no exploration of the shape of range-size frequency distributions has been carried out. Here I present analytical and numerical models that generate explicit predictions for patterns of range size under the assumptions of mid-domain models of species diversity. Some generalizations include: (1) Mid-domain models predict no geographic gradient of average range size; the mean range size of species occurring at any point on a continent is constant (0.5 of the extent of the continent in the one-dimensional model, 0.25 of the area of the continent in the two-dimensional case); (2) Variance in range size is lowest at the middle of a continent and highest near the corners of a square-shaped continent; (3) The range-size frequency distribution is highly right-skewed at any point of a continent, but the skewness is highest near the corners. Despite their alleged weaknesses, mid-domain models are adequate null models against which real-world patterns can be contrasted.     

The mid-domain effect: geometric constraints on the geography of species richness

Geographic patterns of species richness are influenced by many factors, but the role of shared physiographical and physiological boundaries in relation to range-size distributions has been surprisingly neglected, in spite of the fact that such geometric constraints lead to mid-domain richness peaks even without environmental gradients (the mid-domain effect). Relying on null models, several recent studies have begun to quantify this problem using simulated and empirical data. This approach promises to transform how we perceive geographic variation in diversity, including the long unresolved latitudinal gradient in species richness. The question is not whether geometry affects such patterns, but by how much.     

Predicting continental-scale patterns of bird species richness with spatially explicit models

The causes of global variation in species richness have been debated for nearly two centuries with no clear resolution in sight. Competing hypotheses have typically been evaluated with correlative models that do not explicitly incorporate the mechanisms responsible for biotic diversity gradients. Here, we employ a fundamentally different approach that uses spatially explicit Monte Carlo models of the placement of cohesive geographical ranges in an environmentally heterogeneous landscape. These models predict species richness of endemic South American birds (2248 species) measured at a continental scale. We demonstrate that the principal single-factor and composite (species-energy, water-energy and temperature-kinetics) models proposed thus far fail to predict (r(2) < or =.05) the richness of species with small to moderately large geographical ranges (first three range-size quartiles). These species constitute the bulk of the avifauna and are primary targets for conservation. Climate-driven models performed reasonably well only for species with the largest geographical ranges (fourth quartile) when range cohesion was enforced. Our analyses suggest that present models inadequately explain the extraordinary diversity of avian species in the montane tropics, the most species-rich region on Earth. Our findings imply that correlative climatic models substantially underestimate the importance of historical factors and small-scale niche-driven assembly processes in shaping contemporary species-richness patterns.     

Phylogenetic community structure metrics and null models: a review with new methods and software

Competitive exclusion and habitat filtering influence community assembly, but ecologists and evolutionary biologists have not reached consensus on how to quantify patterns that would reveal the action of these processes. Currently, at least 22 α‐diversity and 10 β‐diversity metrics of community phylogenetic structure can be combined with nine null models (eight for β‐diversity metrics), providing 278 potentially distinct approaches to test for phylogenetic clustering and overdispersion. Selecting the appropriate approach for a study is daunting. First, we describe similarities among metrics and null models across variance in phylogeny size and shape, species abundance, and species richness. Second, we develop spatially explicit, individual‐based simulations of neutral, competitive exclusion, or habitat filtering community assembly, and quantify the performance (type I and II error rates) of all 278 metric and null model combinations against each assembly process. Many α‐diversity metrics and null models are at least functionally equivalent, reducing the number of truly unique metrics to 12 and the number of unique metric + null model combinations to 72. An even smaller subset of metric and null model combinations showed robust statistical performance. For α‐diversity metrics, phylogenetic diversity and mean nearest taxon distance were best able to detect habitat filtering, while mean pairwise phylogenetic distance‐based metrics were best able to detect competitive exclusion. Overall, β‐diversity metrics tended to have greater power to detect habitat filtering and competitive exclusion than α‐diversity metrics, but had higher type 1 error in some cases. Across both α‐ and β‐diversity metrics, null model selection affected type I error rates more than metric selection. A null model that maintained species richness, and approximately maintained species occurrence frequency and abundance across sites, exhibited low type I and II error rates. This regional null model simulates neutral dispersal of individuals into local communities by sampling from a regional species pool. We introduce a flexible new R package, metricTester, to facilitate robust analyses of method performance.     

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.     

The mid-domain effect in ectomycorrhizal fungi: range overlap along an elevation gradient on Mount Fuji,Japan

Mid-domain effect (MDE) models predict that the random placement of species'' ranges within a bounded geographical area leads to increased range overlap and species richness in the center of the bounded area. These models are frequently applied to study species-richness patterns of macroorganisms, but the MDE in relation to microorganisms is poorly understood. In this study, we examined the characteristics of the MDE in richness patterns of ectomycorrhizal (EM) fungi, an ecologically important group of soil symbionts. We conducted intensive soil sampling to investigate overlap among species ranges and the applicability of the MDE to EM fungi in four temperate forest stands along an elevation gradient on Mount Fuji, Japan. Molecular analyses using direct sequencing revealed 302 EM fungal species. Of 73 EM fungal species found in multiple stands, 72 inhabited a continuous range along the elevation gradient. The maximum overlap in species range and the highest species richness occurred at elevations in the middle of the gradient. The observed richness pattern also fit within the 95% confidence interval of the mid-domain null model, supporting the role of the MDE in EM fungal richness. Deviation in observed richness from the mean of the mid-domain null estimation was negatively correlated with some environmental factors, including precipitation and soil C/N, indicating that unexplained richness patterns could be driven by these environmental factors. Our results clearly support the existence of microbial species'' ranges along environmental gradients and the potential applicability of the MDE to better understand microbial diversity patterns.     

Challenges in the application of geometric constraint models

Discerning the processes influencing geographical patterns of species richness remains one of the central goals of modern ecology. Traditional approaches to exploring these patterns have focused on environmental and ecological correlates of observed species richness. Recently, some have suggested these approaches suffer from the lack of an appropriate null model that accounts for species ranges being constrained to occur within a bounded domain. Proponents of these null geometric constraint models (GCMs), and the mid-domain effect these models produce, argue their utility in identifying meaningful gradients in species richness. This idea has generated substantial debate. Here we discuss what we believe are the three major challenges in the application of GCMs. First, we argue that there are actually two equally valid null models for the random placement of species ranges within a domain, one of which actually predicts a uniform distribution of species richness. Second, we highlight the numerous decisions that must be made to implement a GCM that lead to marked differences in the predictions of the null model. Finally, we discuss challenges in evaluating the importance of GCMs once they have been implemented.     

Comparison of co-occurrence structure of temperate forest herb-layer communities in 1949 and 2000

When species presence–absence data are analyzed across a range of sites, many communities show a “checkerboard distribution” in which two or more species do not co-occur despite sharing geographic ranges and habitat requirements. It is not clear how the loss of native species might shift the underlying checkerboard structure. I tracked changes in the incidence of 175 vascular plant species across 59 sites in northern Wisconsin that have declined in species density between 1950 and 2000. Based on C-scores and the number of perfect checkerboard distributions, there was significant co-occurrence structure in both time periods. The nature of that structure depended on the particular null model was constructed. When only row values are fixed, plant species showed greater degrees of co-occurrence than the null model predicted, while fixing both rows and columns yielded less co-occurrence than found in the null model. Changes in species density did not strongly influence co-occurrence patterns, reflecting relative stability of co-occurrence patterns over a 50-year interval. This suggests that minor losses of species will not necessarily lead to fundamental changes in co-occurrence structure.     

Species richness and range size of the terrestrial mammals of the world: biological signal within mathematical constraints

We explore global spatial diversity patterns for terrestrial mammals using as a tool range-diversity plots. These plots display simultaneously information about the number of species in localities and their spatial covariance in composition. These are highly informative, as we show by linking range-diversity plots with maps and by highlighting the correspondences between well defined regions of the plots with geographical regions or with taxonomic groups. Range-diversity plots are mathematically constrained by the lines of maximum and minimum mean covariance in species composition. We show how regions in the range-diversity plot corresponding to the line of maximum covariance correspond to large continental masses, and regions near the lower limit of the range-diversity plot correspond to archipelagos and mountain ranges. We show how curves of constant covariance correspond to nested faunas. Finally, we show that the observed distribution of the covariance range has significantly longer tails than random, with clear geographic correspondences. At the scale of our data we found that range-diversity plots reveal biodiversity patterns that cannot be replicated by null models, and correspond to conspicuous terrain features and taxonomic groupings.     

Adding energy gradients and long‐distance dispersal to a neutral model improves predictions of Madagascan bird diversity

Macroecological patterns are likely the result of both stochastically neutral mechanisms and deterministic differences between species. In Madagascar, the simplest stochastically neutral hypothesis – the mid‐domain effects (MDE) hypothesis – has already been rejected. However, rejecting the MDE hypothesis does not necessarily refute the existence of all other neutral mechanisms. Here, we test whether adding complexity to a basic neutral model improves predictions of biodiversity patterns. The simplest MDE model assumes that: (1) species' ranges are continuous and unfragmented, (2) are randomly located throughout the landscape, and (3) can be stacked independently and indefinitely. We designed a simulation based on neutral theory that allowed us to weaken each of these assumptions incrementally by adjusting the habitat capacity as well as the likelihood of short‐ and long‐distance dispersal. Simulated outputs were compared to four empirical patterns of bird diversity: the frequency distributions of species richness and range size, the within‐island latitudinal diversity gradient, and the distance‐decay of species compositional similarity. Neutral models emulated empirical diversity patterns for Madagascan birds accurately. The frequency distribution of range size, latitudinal diversity gradient, and the distance‐decay of species compositional similarity could be attributed to stochastic long‐distance migration events and zero‐sum population dynamics. However, heterogenous environmental gradients improved predictions of the frequency distribution of species richness. Patterns of bird diversity in Madagascar can broadly be attributed to stochastic long‐distance migration events and zero‐sum population dynamics. This implies that rejecting simple hypotheses, such as MDE, does not serve as evidence against stochastic processes in general. However, environmental gradients were necessary to explain patterns of species richness and deterministic differences between species are probably important for explaining the distributions of narrow‐range and endemic species.     

Effect of local and regional processes on plant species richness in tallgrass prairie

Historically, diversity in a community was often believed to result primarily from local processes, but recent evidence suggests that regional diversity may strongly influence local diversity as well. We used experimental and observational vegetation data from Konza Prairie, Kansas, USA, to determine if: (1) there is a relationship between local and regional richness in tallgrass prairie vegetation; (2) local dominance reduces local species richness; and (3) reducing local dominance increases local and regional species richness. We found a positive relationship between regional and local richness; however, this relationship varied with grazing, topography and fire frequency. The decline in variance explained in the grazed vegetation, in particular, suggested that local processes associated with grazing pressure on the dominant grasses strongly influenced local species richness. Experimental removal of one of the dominant grasses, Andropogon scoparius , from replicate plots resulted in a significant increase in local species richness compared to adjacent reference plots. Overall all sites, species richness was higher in grazed (192 spp.) compared to ungrazed (158 spp.) areas. Across the Konza Prairie landscape, however, there were no significant differences in the frequency distribution of species occurrences, or in the relationship between the number of sites occupied and average abundance in grazed compared to ungrazed areas. Thus, local processes strongly influenced local richness in this tallgrass prairie, but local processes did not produce different landscape-scale patterns in species distribution and abundance. Because richness was enhanced at all spatial scales by reducing the abundance of dominant species, we suggest that species richness in tallgrass prairie results from feedbacks between, and interactions among, processes operating at multiple scales in space and time.     

Continental and regional ranges of North American mammals: Rapoport's rule in real and null worlds

Aim To assess the relationship between species richness and distribution within regions arranged along a latitudinal gradient we use the North American mammalian fauna as a study case for testing theoretical models. Location North America. Methods We propose a conceptual framework based on a fully stochastic mid‐domain model to explore geographical patterns of range size and species richness that emerge when the size and position of species ranges along a one‐dimensional latitudinal gradient are randomly generated. We also analyse patterns for the mammal fauna of North America by comparing empirical results from a biogeographical data base with predictions based on randomization null models. Results We confirmed the validity of Rapoport's rule for the mammals of North America by documenting gradients in the size of the continental ranges of species. Additionally, we demonstrated gradients of mean regional range size that parallel those of continental range. Our data also demonstrated that mean range size, measured both as a continental or a regional variable, is significantly correlated with the geographical pattern in species richness. All these patterns deviated sharply from null models. Main conclusions Rapoport's statement of an areographic relationship between species distribution and richness is highly relevant in modern discussions about ecological patterns at the geographical scale.     

Are stacked species distribution models accurate at predicting multiple levels of diversity along a rainfall gradient?

We use observed patterns of species richness and composition of ant communities along a 1000 mm rainfall gradient in northern Australian savanna to assess the accuracy of species richness and turnover predictions derived from stacked species distribution models (S‐SDMs) and constrained by macroecological models (MEMs). We systematically sampled ants at 15 sites at 50 km intervals along the rainfall gradient in 2012 and 2013. Using the observed data, we created MEMs of species richness, composition and turnover. We built distribution models for 135 of the observed species using data from museum collections and online databases. We compared two approaches of stacking SDMs and three modelling algorithms to identify the most accurate way of predicting richness and composition. We then applied the same beta diversity metrics to compare the observed versus predicted patterns. Stacked SDMs consistently over‐predicted local species richness, and there was a mismatch between the observed pattern of richness estimated from the MEM, and the pattern predicted by S‐SDMs. The most accurate richness and turnover predictions occurred when the stacked models were rank‐ordered by their habitat suitability and constrained by the observed MEM richness predictions. In contrast with species richness, the predictions obtained by the MEM of community similarity, composition and turnover matched those predicted by the S‐SDMs. S‐SDMs regulated by MEMs may therefore be a useful tool in predicting compositional patterns despite being unreliable estimators of species richness. Our results highlight that the choice of species distribution model, the stacking method used, and underlying macroecological patterns all influence the accuracy of community assembly predictions derived from S‐SDMS.     

Do Stacked Species Distribution Models Reflect Altitudinal Diversity Patterns?

The objective of this study was to evaluate the performance of stacked species distribution models in predicting the alpha and gamma species diversity patterns of two important plant clades along elevation in the Andes. We modelled the distribution of the species in the Anthurium genus (53 species) and the Bromeliaceae family (89 species) using six modelling techniques. We combined all of the predictions for the same species in ensemble models based on two different criteria: the average of the rescaled predictions by all techniques and the average of the best techniques. The rescaled predictions were then reclassified into binary predictions (presence/absence). By stacking either the original predictions or binary predictions for both ensemble procedures, we obtained four different species richness models per taxa. The gamma and alpha diversity per elevation band (500 m) was also computed. To evaluate the prediction abilities for the four predictions of species richness and gamma diversity, the models were compared with the real data along an elevation gradient that was independently compiled by specialists. Finally, we also tested whether our richness models performed better than a null model of altitudinal changes of diversity based on the literature. Stacking of the ensemble prediction of the individual species models generated richness models that proved to be well correlated with the observed alpha diversity richness patterns along elevation and with the gamma diversity derived from the literature. Overall, these models tend to overpredict species richness. The use of the ensemble predictions from the species models built with different techniques seems very promising for modelling of species assemblages. Stacking of the binary models reduced the over-prediction, although more research is needed. The randomisation test proved to be a promising method for testing the performance of the stacked models, but other implementations may still be developed.     

Richness,nestedness, and randomness in parasite infracommunity structure

Within a host population, parasite infracommunities vary in both richness and species composition. If interspecific interactions among parasites are important in shaping infracommunities, the structure of these assemblages is expected to differ from the one predicted by null models, i.e. from the one that would result from chance alone. Using data from the literature, I tested for discrepancies between observed and random patterns in the richness and composition of gastrointestinal helminth infracommunities of birds and mammals. Both the Poisson distribution and a more sophisticated null model, derived from prevalence of the different parasite species in the host population, usually provided a good fit to the observed distributions of infracommunity richness among hosts. This suggests that parasite species do not co-occur more or less frequently than expected by chance. In mammals, the co-occurrence of all available parasite species in the same host individual, or maximum potential infracommunity richness, was less likely to be observed when several parasite species were available; this is also a phenomenon expected from the random assembly of parasite species. Finally, there was no evidence for a nested subset pattern among parasite species in a host population: rate species were distributed independently of common ones. The overall picture emerging from these results is one in which parasite assemblages are more likely to be the product of random events than of predictable and repeatable processes.     

The presence–absence matrix reloaded: the use and interpretation of range–diversity plots

Aim A great deal of information on distribution and diversity can be extracted from presence–absence matrices (PAMs), the basic analytical tool of many biogeographic studies. This paper presents numerical procedures that allow the analysis of such information by taking advantage of mathematical relationships within PAMs. In particular, we show how range–diversity (RD) plots summarize much of the information contained in the matrices by the simultaneous depiction of data on distribution and diversity. Innovation We use matrix algebra to extract and process data from PAMs. Information on the distribution of species and on species richness of sites is computed using the traditional R (by rows) and Q (by columns) procedures, as well as the new Rq (by rows, considering the structure of columns) and Qr (by columns, considering the structure by rows) methods. Matrix notation is particularly suitable for summarizing complex calculations using PAMs, and the associated algebra allows the implementation of efficient computational programs. We show how information on distribution and species richness can be depicted simultaneously in RD plots, allowing a direct examination of the relationship between those two aspects of diversity. We explore the properties of RD plots with a simple example, and use null models to show that while parameters of central tendency are not affected by randomization, the dispersion of points in RD plots does change, showing the significance of patterns of co‐occurrence of species and of similarity among sites. Main conclusion Species richness and range size are both valid measures of diversity that can be analysed simultaneously with RD plots. A full analysis of a system requires measures of central tendency and dispersion for both distribution and species richness.     

Species co-occurrences and neutral models: reassessing J. M. Diamond's assembly rules

The question whether species co-occurrence patterns are non-random has intrigued ecology for more than two decades. Recently Gotelli and McCabe used meta-analysis to show that natural assemblages indeed tend to have non-random species co-occurrence patterns and that these patterns are in line with the predictions of Diamond's assembly rule model. Here I show that neutral ecological drift models are able to generate patterns in line with Diamond's assembly rules and very similar to the empirical results in Gotelli and McCabe. Ecological drift shifted species co-occurrence patterns (measured by C-scores, checkerboard scores and species combination scores) of model species placed into a grid of the 25 cells (sites; metacommunity sizes 5 to 25 species with 100 individuals each) significantly from an initial random pattern towards a pattern predicted by the assembly rule model of Diamond. These findings imply that instead of asking whether natural communities are structured according to some assembly rules we should ask whether these non-random patterns are generated by species interactions or by stochastic drift processes.     

Spatial Scaling of Non-Native Fish Richness across the United States

A major goal and challenge of invasion ecology is to describe and interpret spatial and temporal patterns of species invasions. Here, we examined fish invasion patterns at four spatially structured and hierarchically nested scales across the contiguous United States (i.e., from large to small: region, basin, watershed, and sub-watershed). All spatial relationships in both richness and fraction between species groups (e.g., natives vs. exotics) were positive at large scales. However, contrary to predictions using null/neutral models, the patterns at small scales were hump-shaped (unimodal), not simply negative. The fractions of both domestic (introduced among watersheds within the USA) and foreign (introduced from abroad) exotics increased with area across scales but decreased within each scale. The foreign exotics exhibited the highest dominance (lowest evenness) and spatial variation in distribution, followed by domestic exotics and natives, although on average natives still occupy larger areas than domestic and foreign exotics. The results provide new insight into patterns and mechanisms of fish species invasions at multiple spatial scales in the United States.