Ecological biogeography of Mexican bats: the relative contributions of habitat heterogeneity,beta diversity,and environmental gradients to species richness and composition patterns

Mexico has higher mammalian diversity than expected for its size and geographic position. High environmental hetero geneity throughout Mexico is hypothesized to promote high turnover rates (β‐diversity), thus contributing more to observed species richness and composition than within‐habitat (α) diversity. This is true if species are strongly associated with their environments, such that changes in environmental attributes will result in changes in species composition. Also, greater heterogeneity in an area will result in greater species richness. This hypothesis has been deemed false for bats, as their ability to fly would reduce opportunities for habitat specialization. If so, we would expect no significant relationships between 1) species composition and environmental variables, 2) species richness and environmental heterogeneity, 3) β‐diversity and environmental heterogeneity. We tested these predictions using 31 bat assemblages distributed across Mexico. Using variance partitioning we evaluated the relative contribution of vegetation, climate, elevation, horizontal heterogeneity (a variate including vegetation, climate, and elevational heterogeneity), spatial variation (lat‐long), and vertical hetero geneity (of vegetation strata) to variation in bat species composition and richness. Variation in vegetation explained 92% of the variation in species composition and was correlated with all other variables examined, indicating that bats respond directly to habitat composition and structure. Beta‐diversity and vegetational heterogeneity were significantly correlated. Bat species richness was significantly correlated with vertical, but not horizontal, heterogeneity. Nonetheless, neither horizontal nor vertical heterogeneity were random; both were related to latitude and to elevation. Variation in bat community composition and richness in Mexico were primarily explained by local landscape heterogeneity and environmental factors. Significant relationships between β‐diversity and environmental variation reveal differences in habitat specialization by bats, and explain their high diversity in Mexico. Understanding mechanisms acting along environmental or geographic gradients is as important for understanding spatial variation in community composition as studying mechanisms that operate at local scales.     

Environmental determinants of geographic butterfly richness pattern in eastern China

A long-standing task for ecologists and biogeographers is to reveal the underlying mechanisms accounting for the geographic pattern of species diversity. The number of hypotheses to explain geographic variation in species diversity has increased dramatically during the past half century. The oldest and the most popular one is environmental determination. However, seasonality, the intra-annual variability in climate variables has been rarely related to species richness. In this study, we assessed the relative importance of three environmental hypotheses: energy, seasonality and heterogeneity in explaining species richness pattern of butterflies in Eastern China. In addition, we also examined how environmental variables affect the relationship between species richness of butterflies and seed plants at geographic scale. All the environmental factors significantly affected butterfly richness, except sampling area and coefficient of variation of mean monthly precipitation. Energy and seasonality hypotheses explained comparable variation in butterfly richness (42.3 vs. 39.3 %), higher than that of heterogeneity hypothesis (25.9 %). Variation partitioning indicated that the independent effect of seasonality was much lower (0.0 %) than that of energy (5.5 %) and heterogeneity (6.3 %). However, seasonality performed better in explaining butterfly richness in topographically complex areas, reducing spatial autocorrelation in butterfly richness, and more strongly affect the association between butterflies and seed plants. The positive relationship between seed plant richness and butterfly richness was most likely the result of environmental variables (especially seasonality) influencing them in parallel. Insufficient sampling may partly explain the low explanatory power of environmental model (52.1 %) for geographic butterfly richness pattern. Our results have important implications for predicting the response of butterfly diversity to climate change.     

Environmental correlates of leguminosae species richness in Mexico: Quantifying the contributions of energy and environmental seasonality

Explaining species richness patterns is a central issue in ecology, but a general explanation remains elusive. Environmental conditions have been proposed to be important drivers of these patterns, but we still need to better understand the relative contribution of environmental factors. Here, we aim at testing two environmental hypotheses for richness gradients: energy availability and environmental seasonality using diversity patterns of the family Leguminosae across Mexico. We compiled a data base of 502 species and 32,962 records. After dividing Mexico into 100 × 100 km grid cells, we constructed a map of variation in species richness that accounts for heterogeneity in sampling effort. We found the cells with the highest species richness of legumes are in the Neotropical region of Pacific coastal and southern Mexico, where the legume family dominates the tropical rain forests and seasonally dry tropical forests. Regression models show that energy and seasonality predictors can explain 25% and 49% of the variation in richness, respectively. Spatial autocorrelation analysis showed that richness has a strong spatial structure, but that most of this structure disappears when both energy and seasonality are used to account for richness gradient. Our study demonstrates multiple environmental conditions contribute complementarily to explain diversity gradients. Moreover, it shows that in some regions, environmental seasonality can be more important than energy availability, contradicting studies at coarser spatial scales. More basic taxonomic and floristic work is needed to help describe patterns of diversity for many groups to allow for testing the underlying mechanisms responsible for diversity gradients. Abstract in Spanish is available with online material.     

A test of multiple hypotheses for the species richness gradient of South American owls

Many mechanisms have been proposed to explain broad scale spatial patterns in species richness. In this paper, we evaluate five explanations for geographic gradients in species richness, using South American owls as a model. We compared the explanatory power of contemporary climate, landcover diversity, spatial climatic heterogeneity, evolutionary history, and area. An important aspect of our analyses is that very different hypotheses, such as history and area, can be quantified at the same observation scale and, consequently can be incorporated into a single analytical framework. Both area effects and owl phylogenetic history were poorly associated with richness, whereas contemporary climate, climatic heterogeneity at the mesoscale and landcover diversity explained ca. 53% of the variation in species richness. We conclude that both climate and environmental heterogeneity should be retained as plausible explanations for the diversity gradient. Turnover rates and scaling effects, on the other hand, although perhaps useful for detecting faunal changes and beta diversity at local and regional scales, are not strong explanations for the owl diversity gradient.     

Environmental effects on vertebrate species richness: testing the energy, environmental stability and habitat heterogeneity hypotheses

Background

Explaining species richness patterns is a central issue in biogeography and macroecology. Several hypotheses have been proposed to explain the mechanisms driving biodiversity patterns, but the causes of species richness gradients remain unclear. In this study, we aimed to explain the impacts of energy, environmental stability, and habitat heterogeneity factors on variation of vertebrate species richness (VSR), based on the VSR pattern in China, so as to test the energy hypothesis, the environmental stability hypothesis, and the habitat heterogeneity hypothesis.

Methodology/Principal Findings

A dataset was compiled containing the distributions of 2,665 vertebrate species and eleven ecogeographic predictive variables in China. We grouped these variables into categories of energy, environmental stability, and habitat heterogeneity and transformed the data into 100×100 km quadrat systems. To test the three hypotheses, AIC-based model selection was carried out between VSR and the variables in each group and correlation analyses were conducted. There was a decreasing VSR gradient from the southeast to the northwest of China. Our results showed that energy explained 67.6% of the VSR variation, with the annual mean temperature as the main factor, which was followed by annual precipitation and NDVI. Environmental stability factors explained 69.1% of the VSR variation and both temperature annual range and precipitation seasonality had important contributions. By contrast, habitat heterogeneity variables explained only 26.3% of the VSR variation. Significantly positive correlations were detected among VSR, annual mean temperature, annual precipitation, and NDVI, whereas the relationship of VSR and temperature annual range was strongly negative. In addition, other variables showed moderate or ambiguous relations to VSR.

Conclusions/Significance

The energy hypothesis and the environmental stability hypothesis were supported, whereas little support was found for the habitat heterogeneity hypothesis.     

Geographic variation in the relationship between large-scale environmental determinants and bat species richness

Several studies have already shown the close relationship between geographic gradients of biodiversity and distinct environmental determinants such as energy, environmental heterogeneity and seasonality. Nevertheless, whether and how such relationships vary around the globe remains poorly understood. Here we used spatial models to answer whether the bat species richness-environment relationship on a global scale are constant across geographic space. We also partitioned the contribution of the different environmental determinants on bat species richness at different regions of the globe. We found that the relationship between bat species richness and environment is not constant across geographic space and that the shared contributions of environmental determinants are more important than their unique contributions. We conclude that understanding geographic gradients of biodiversity and its environmental determinants, particularly for bats, is more complex than previously thought because the relationship between species richness and environment varies considerably across geographic space.     

Latitudinal diversity gradients in bryophytes and woody plants: Roles of temperature and water availability

It remains unclear whether the latitudinal diversity gradients of micro- and macro-organisms are driven by the same macro-environmental variables. We used the newly completed species catalog and distribution information of bryophytes in China to explore their spatial species richness patterns, and to investigate the underlying roles of energy availability, climatic seasonality, and environmental heterogeneity in shaping these patterns. We then compared these patterns to those found for woody plants. We found that, unlike woody plants, mosses and liverworts showed only weakly negative latitudinal trends in species richness. The spatial patterns of liverwort richness and moss richness were overwhelmingly explained by contemporary environmental variables, although explained variation was lower than that for woody plants. Similar to woody plants, energy and climatic seasonality hypotheses dominate as explanatory variables but show high redundancy in shaping the distribution of bryophytes. Water variables, that is, the annual availability, intra-annual variability and spatial heterogeneity in precipitation, played a predominant role in explaining spatial variation of species richness of bryophytes, especially for liverworts, whereas woody plant richness was affected most by temperature variables. We suggest that further research on spatial patterns of bryophytes should incorporate the knowledge on their ecophysiology and evolution.     

Can stochastic geographical evolution re‐create macroecological richness–environment correlations?

Aim Richness gradients are frequently correlated with environmental characteristics at broad geographic scales. In particular, richness is often associated with energy and climate, while environmental heterogeneity is rarely its best correlate. These correlations have been interpreted as evidence in favour of environmental determinants of diversity gradients, particularly energy and climate. This interpretation assumes that the expected‐by‐random correlation between richness and environment is zero, and that this is equally true for all environmental characteristics. However, these expectations might be unrealistic. We investigated to what degree basic evolutionary/biogeographical processes occurring independently of environment could lead to richness gradients that correlate with environmental characteristics by chance alone. Location Africa, Australia, Eurasia and the New World. Methods We produced artificial richness gradients based on a stochastic simulation model of geographic diversification of clades. In these simulations, species speciate, go extinct and expand or shift their distributions independently of any environmental characteristic. One thousand two hundred repetitions of this model were run, and the resulting stochastic richness gradients were regressed against real‐world environmental variables. Stochastic species–environment relationships were then compared among continents and among three environmental characteristics: energy, environmental heterogeneity and climate seasonality. Results Simulations suggested that a significant degree of correlation between richness gradients and environment is expected even when clades diversify and species distribute stochastically. These correlations vary considerably in strength; but in the best cases, environment can spuriously account for almost 80% of variation in stochastic richness. Additionally, expected‐by‐chance relationships were different among continents and environmental characteristics, producing stronger spurious relationships with energy and climate than with heterogeneity. Main conclusions We conclude that some features of empirical species–environment relationships can be reproduced just by chance when taking into account evolutionary/biogeographical processes underlying the construction of species richness gradients. Future tests of environmental effects on richness should consider structure in richness–environment correlations that can be produced by simple evolutionary null models. Research should move away from the naive non‐biological null hypotheses that are implicit in traditional statistical tests.     

Determinants of species richness, endemism and turnover in European longhorn beetles

This study assessed the diversity patterns of a large family of beetles, Cerambycidae, in Europe and tested the following hypotheses: 1) richness gradients of this hyperdiverse taxon are driven by water and energy variables; 2) endemism is explained by the same factors, but variation between areas also reflects post‐glacial re‐colonization processes; and 3) faunal composition is determined by the same climatic variables and, therefore, beta diversity (species turnover) is related to richness gradients. Species richness, endemism and beta diversity were modelled using inventories of 37 European territories, built from a database containing the distributions of 609 species. Area, spatial position, and nine topographical and climatic variables were used as predictors in regression and constrained analysis of principal coordinates modelling. Species richness was mostly explained by a temperature gradient, which produced a south‐to‐north decreasing richness gradient. Endemism followed the same pattern, but was also determined by longitudinal variation, peaking in the southwestern and southeastern corners of the continent. Faunal turnover was explained by an important purely spatial pattern and a spatially structured environmental gradient. Thus, contrary to other groups, cerambycid richness was mostly explained by environmental energy, but not by water availability. Endemism was concentrated in the Iberian and Greek peninsulas, but not in Italy. Thus, the latter area may have been the major source of post‐glacial re‐colonization for European longhorn beetles or, otherwise, a poor refuge during glaciations. Turnover patterns were independent of the richness gradient, because northern faunas are nested in southern ones. Turnover, in contrast to richness, was driven by both the independent effects of climate and geographic constraints that might reflect dispersal limitation or stochastic colonization events, suggesting that richness gradients are more environmentally deterministic phenomena than turnover patterns.     

Exploring anthropogenic and natural processes shaping fern species richness along elevational gradients

Aim (1) To explore the impact of land use, climate and environmental heterogeneity on fern species richness along a complete elevational gradient, and (2) to evaluate the relative importance of the three groups of variables within different elevational intervals. Location A temperate mountain region (55,507 km²) of Italy on the southern border of the European Alps divided into a regular grid of 1476 cells (grain 35.7 km²). Methods We applied multiple regression (spatial and non‐spatial) to determine the relative influence of the three groups of variables on species richness, including variation partitioning at two scales. We considered the whole gradient (all 1476 cells) to explain the overall elevational pattern of species richness, and we grouped the cells into elevational intervals of 500 m in order to evaluate the explanatory power of the predictors within different zones along the gradient. Results Species richness showed a hump‐shaped pattern with elevation, forming a plateau between 800 and 1500 m. The lowest species richness was found in warm and relatively dry disturbed lowlands. Moving upwards, the greatest species richness was found in forest‐dominated mid‐elevations with high environmental heterogeneity. At high elevations dominated by open natural habitats, where temperature and precipitation were relatively low, species richness declined but less sharply than in the lowlands. Although it was impossible to separate the effects of the three groups of predictors along the whole gradient, the analysis of separate elevational intervals shed light on their relative importance. The decline of species richness within lowlands was mainly related to a combined effect of deforestation and low environmental heterogeneity. In the middle part of the gradient, habitat heterogeneity and topographic roughness were positively associated with species richness. The richness decline within high‐elevation areas was related mostly to climatic constraints. Main conclusions Human impact due to land‐use modifications strongly affects the elevational pattern of species richness. It is therefore increasingly important to adopt a multiple‐hypothesis approach, taking anthropogenic effects explicitly into account when describing ecological processes along elevational gradients.     

中国蚂蚁丰富度地理分布格局及其与环境因子的关系

物种丰富度分布格局及其形成机制的研究对于生物多样性保护具有重要意义。为了了解中国蚂蚁物种丰富度分布格局,利用中国省级尺度蚂蚁物种分布数据和环境信息,结合GIS和数理统计方法,探讨蚂蚁物种丰富度的地理分布格局与环境因子之间的关系。研究结果表明:(1)蚂蚁丰富度随纬度增加呈逐渐递减趋势,但缺乏显著的经度梯度。丰富度最高的地区主要集中在南方省份,我国北方、西北干旱区和青藏高原北部地区丰富度较低;(2)简单线性回归分析表明,能量、水分和季节性因素中,影响蚂蚁物种丰富度最强的因子分别为最冷月均温(TEMmin)(R2adj=0.532)、年均降水量(PREC)(R2adj=0.376)和年温度变化范围(TEMvar)(R2adj=0.539),而单个生境异质性因子对蚂蚁物种丰富度的影响均不显著;(3)最优模型由年均温(TEM)、海拔变化范围(ELErange)和年温度变化范围(TEMvar)组成,能够解释68.4%的蚂蚁丰富度地理分异。鉴于海拔变化范围更多地反映与温度相关的生境异质性,因此温度是限制中国蚂蚁分布的最重要因素。另外,分析结果还表明,海南、贵州、江西、四川、安徽和山西等6省蚂蚁区系调查最不充分,是未来发现蚂蚁新分布的热点地区。     

The mid‐domain effect and habitat complexity applied to elevational gradients: Moss species richness in a temperate semihumid monsoon climate mountain of China

The utility of elevational gradients as tools to test either ecological hypotheses and delineate elevation‐associated environmental factors that explain the species diversity patterns is critical for moss species conservation. We examined the elevational patterns of species richness and evaluated the effects of spatial and environmental factors on moss species predicted a priori by alternative hypotheses, including mid‐domain effect (MDE), habitat complexity, energy, and environment proposed to explain the variation of diversity. Last, we assessed the contribution of elevation toward explaining the heterogeneity among sampling sites. We observed the hump‐shaped distribution pattern of species richness along elevational gradient. The MDE and the habitat complexity hypothesis were supported with MDE being the primary driver for richness patterns, whereas little support was found for the energy and the environmental factors.     

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.     

Beta diversity and latitude in North American mammals: testing the hypothesis of covariation

Several hypotheses attempt to explain the latitudinal gradient of species diversity, but some basic aspects of the pattern remain insufficiently explored, including the effect of scales and the role of beta diversity. To explore such components of the latitudinal gradient, we tested the hypothesis of covariation, which states that the gradient of species diversity should show the same pattern regardless of the scale of analysis. The hypothesis implies that there should be no gradients of beta diversity, of regional range size within regions, and of the slope of the species-area curve. For the fauna of North American mammals, we found contrasting results for bats and non-volant species. We could reject the hypothesis of covariation for non-volant mammals, for which the number of species increases towards lower latitudes, but at different rates depending on the scale. Also, for this group, beta diversity is higher at lower latitudes, the regional range size within regions is smaller at lower latitudes, and z, the slope of the species-area relationship is higher at lower latitudes. Contrarily bats did not show significant deviations from the predictions of the hypothesis of covariation: at two different scales, species richness shows similar trends of increase at lower latitudes, and no gradient can be demonstrated for beta diversity, for regional range size, or for the slopes of the species-area curve. Our results show that the higher diversity of non-volant mammals in tropical areas of North America is a consequence of the increase in beta diversity and not of higher diversity at smaller scales. In contrast, the diversity of bats at both scales is higher at lower latitudes. These contrasting patterns suggest different causes for the latitudinal gradient of species diversity in the two groups that are ultimately determined by differences in the patterns of geographic distribution of the species.     

Habitat is more important than climate and animal richness at shaping latitudinal variation in plant diversity in China

Species data from 249 National Nature Reserves in China were used to identify potential underlying drivers of latitudinal gradients in plant diversity. We used generalized linear models to assess correlations between predictor and plant species richness. Variance partitioning was then used to decompose the variation in plant richness into different taxonomic levels among the three groups of predictors (i.e., climate, habitat and animal). We found that species richness showed significant latitudinal trends in richness (p?<?0.001). This remained true when examining gymnosperms, angiosperms and ferns individually. Climate and habitat variables explained more variation in richness across different plant groups than did animal richness. Annual precipitation was the best climate variable across different taxonomic plants groups, and soil pH and elevation range were the best habitat variables across different taxonomic plant groups. The independent effects of habitat variables were higher than that of climate and animal variables across different taxonomic plant groups. Finally, climate, habitat heterogeneity, and animal richness explain 48.8% of the variation in total species richness, 28.2% in gymnosperm richness, 44.2% in angiosperm richness, and 38.9% in fern richness.     

Disentangling the Role of Climate,Topography and Vegetation in Species Richness Gradients

Environmental gradients (EG) related to climate, topography and vegetation are among the most important drivers of broad scale patterns of species richness. However, these different EG do not necessarily drive species richness in similar ways, potentially presenting synergistic associations when driving species richness. Understanding the synergism among EG allows us to address key questions arising from the effects of global climate and land use changes on biodiversity. Herein, we use variation partitioning (also know as commonality analysis) to disentangle unique and shared contributions of different EG in explaining species richness of Neotropical vertebrates. We use three broad sets of predictors to represent the environmental variability in (i) climate (annual mean temperature, temperature annual range, annual precipitation and precipitation range), (ii) topography (mean elevation, range and coefficient of variation of elevation), and (iii) vegetation (land cover diversity, standard deviation and range of forest canopy height). The shared contribution between two types of EG is used to quantify synergistic processes operating among EG, offering new perspectives on the causal relationships driving species richness. To account for spatially structured processes, we use Spatial EigenVector Mapping models. We perform analyses across groups with distinct dispersal abilities (amphibians, non-volant mammals, bats and birds) and discuss the influence of vagility on the partitioning results. Our findings indicate that broad scale patterns of vertebrate richness are mainly affected by the synergism between climate and vegetation, followed by the unique contribution of climate. Climatic factors were relatively more important in explaining species richness of good dispersers. Most of the variation in vegetation that explains vertebrate richness is climatically structured, supporting the productivity hypothesis. Further, the weak synergism between topography and vegetation urges caution when using topographic complexity as a surrogate of habitat (vegetation) heterogeneity.     

The effect of energy and seasonality on avian species richness and community composition

We analyzed geographic patterns of richness in both the breeding and winter season in relation to a remotely sensed index of seasonal production (normalized difference vegetation index [NDVI]) and to measures of habitat heterogeneity at four different spatial resolutions. The relationship between avian richness and NDVI was consistent between seasons, suggesting that the way in which available energy is converted to bird species is similar at these ecologically distinct times of year. The number and proportion of migrant species in breeding communities also increased predictably with the degree of seasonality. The NDVI was a much better predictor of seasonal richness at finer spatial scales, whereas habitat heterogeneity best predicted richness at coarser spatial resolutions. While we find strong support for a positive relationship between available energy and species richness, seasonal NDVI explained at most 61% of the variation in richness. Seasonal NDVI and habitat heterogeneity together explain up to 69% of the variation in richness.     

Water–energy,land‐cover and heterogeneity drivers of the distribution of plant species richness in a mountain region of the European Alps

Aim To evaluate the relative importance of water–energy, land‐cover, environmental heterogeneity and spatial variables on the regional distribution of Red‐Listed and common vascular plant species richness. Location Trento Province (c. 6200 km²) on the southern border of the European Alps (Italy), subdivided regularly into 228 3′ × 5′ quadrants. Methods Data from a floristic inventory were separated into two subsets, representing Red‐Listed and common (i.e. all except Red‐Listed) plant species richness. Both subsets were separately related to water–energy, land‐cover and environmental heterogeneity variables. We simultaneously applied ordinary least squares regression with variation partitioning and hierarchical partitioning, attempting to identify the most important factors controlling species richness. We combined the analysis of environmental variables with a trend surface analysis and a spatial autocorrelation analysis. Results At the regional scale, plant species richness of both Red‐Listed and common species was primarily related to energy availability and land cover, whereas environmental heterogeneity had a lesser effect. The greatest number of species of both subsets was found in quadrants with the largest energy availability and the greatest degree of urbanization. These findings suggest that the elevation range within our study region imposes an energy‐driven control on the distribution of species richness, which resembles that of the broader latitude gradient. Overall, the two species subsets had similar trends concerning the relative importance of water–energy, land cover and environmental heterogeneity, showing a few differences regarding the selection of some predictors of secondary importance. The incorporation of spatial variables did not improve the explanatory power of the environmental models and the high original spatial autocorrelation in the response variables was reduced drastically by including the selected environmental variables. Main conclusions Water–energy and land cover showed significant pure effects in explaining plant species richness, indicating that climate and land cover should both be included as explanatory variables in modelling species richness in human‐affected landscapes. However, the high degree of shared variation between the two groups made the relative effects difficult to separate. The relatively low range of variation in the environmental heterogeneity variables within our sampling domain might have caused the low importance of this complex factor.