Techniques to evaluate elements of metacommunity structure (EMS; coherence, species turnover and range boundary clumping) have been available for several years. Such approaches are capable of determining which idealized pattern of species distribution best describes distributions in a metacommunity. Nonetheless, this approach rarely is employed and such aspects of metacommunity structure remain poorly understood. We expanded an extant method to better investigate metacommunity structure for systems that respond to multiple environmental gradients. We used data obtained from 26 sites throughout Paraguay as a model system to demonstrate application of this methodology. Using presence-absence data for bats, we evaluated coherence, species turnover and boundary clumping to distinguish among six idealized patterns of species distribution. Analyses were conducted for all bats as well as for each of three feeding ensembles (aerial insectivores, frugivores and molossid insectivores). For each group of bats, analyses were conducted separately for primary and secondary axes of ordination as defined by reciprocal averaging. The Paraguayan bat metacommunity evinced Clementsian distributions for primary and secondary ordination axes. Patterns of species distribution for aerial insectivores were dependent on ordination axis, showing Gleasonian distributions when ordinated according to the primary axis and Clementsian distributions when ordinated according to the secondary axis. Distribution patterns for frugivores and molossid insectivores were best described as random. Analysis of metacommunities using multiple ordination axes can provide a more complete picture of environmental variables that mold patterns of species distribution. Moreover, analysis of EMS along defined gradients (e.g., latitude, elevation and depth) or based on alternative ordination techniques may complement insights based on reciprocal averaging because the fundamental questions addressed in analyses are contingent on the ordination technique that is employed.

Aim  To relate the composition of bat assemblages in Paraguay to environmental factors (vegetation) and to test the hypothesis that the observed patterns of distribution of Paraguayan mammals is ultimately due to soils and geological features. Location  Paraguay. Methods  Museum specimens were used to create a data base of 3762 individuals of forty‐eight species collected in twenty‐six 50 × 50 km sites distributed throughout the country. Proportion of each of sixteen vegetation types per site was estimated from vegetation maps. Vegetation and bat data were related using canonical correspondence analysis (CCA) and Mantel tests. The same analyses were performed with the bat data grouped in terms of trophic strategies. Results  A significant relationship was found between composition of vegetation and composition of bat assemblages. CCA ordination arranged plant associations and bat assemblages into three distinct groups: Dry Chaco, Floodable Lands and Eastern Paraguay, which correspond to the major characteristics of the Paraguayan vegetation, geology and soils. Frugivorous bats were restricted to Eastern Paraguay and Floodable Lands, whereas most insectivore and omnivore species occur across the entire country. However, the maximum abundance of insectivorous and omnivorous species within each genus indicates that there is at least a partial segregation of species to one of the three regions, and in those cases where the maximum abundance of congeneric species coincide, those species differ considerably in size. Main conclusions  The Paraguayan bat fauna is a composite of species from various South American biomes, with no endemic species. However, species are not randomly distributed across the country despite the lack of geographical barriers and the high dispersal capabilities of bats. Instead, species presence at any given site is strongly associated with vegetation patterns that are ultimately the result of the geological history of the area. This correlation can be explained partially in terms of habitat suitability and resource availability. Additionally, results suggest that interspecific interactions are also an important component in determining the composition of a given bat assemblage.

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Aim We tested the hypothesis that distributions of Mexican bats are defined by shared responses to environmental gradients for the entire Mexican bat metacommunity and for each of four metaensembles (frugivores, nectarivores, gleaning insectivores, and aerial insectivores). Further, we identified the main environmental factors to which bats respond for multiple spatial extents. Location Mexico.Methods Using bat presence-absence data, as well as vegetation composition for each of 31 sites, we analysed metacommunity structure via a comprehensive, hierarchical approach that uses reciprocal averaging (RA) to detect latent environmental gradients corresponding to each metacommunity structure (e.g. Clementsian, Gleasonian, nested, random). Canonical correspondence analysis (CCA) was used to relate such gradients to variation in vegetation composition.Results For all bat species and for each ensemble, the primary gradient of ordination from RA, which is based on species data only, recovered an axis of humidity that matched that obtained for the first axis of the CCA ordination, which is based both on vegetation attributes and on species composition of sites. For the complete assemblage as well as for aerial and gleaning insectivores, analyses revealed Clementsian or quasi-Clementsian structures with discrete compartments (distinctive groups of species along portions of an environmental gradient) coincident with the humidity gradient and with the NearcticNeotropical divide. Within-compartment analysis further revealed Clementsian or quasi-Clementsian structures corresponding to a gradient of elevational complexity that matched the second ordination axis in CCA. Frugivores had quasi-nested structure, whereas nectarivores had Gleasonian structure.Main conclusions Our hierarchical approach to metacommunity analysis detected complex metacommunity structures associated with multiple environmental gradients at different spatial extents. More importantly, the resulting structures and their extent along environmental gradients are determined by ensemble-specific characteristics and not by arbitrarily circumscribed study areas. This property renders compartment-level analyses particularly useful for large-scale ecological analyses in areas where more than one gradient may exist and species sorting may occur at multiple scales.

Summary 1.We examined the relative contributions of regional spatial characteristics and local environmental conditions in determining Paraguayan bat species composition. 2. We used a suite of full and partial redundancy analyses to estimate four additive partitions of variance in bat species composition: (a) unexplained variation, (b) that explained purely by spatial characteristics, (c) that explained purely by local environmental conditions and (d) that explained jointly by space and environment. The spatial component to bat species composition was greater than the environmental component and both pure spatial and pure environmental characteristics accounted for significant amounts of variation in bat species composition. 3. Results from variance decomposition suggest that the mass effects model describes metacommunity structure of Paraguayan bats better than species sorting or neutral models. Such mass effects may potentially be general for bats and could explain the inability of purely local factors to fully account for bat community organization. Mass effects also have substantial conservation implications because rescue effects may enhance the persistence of mobile species in fragmented landscapes with relatively few protected sites.

Summary Monitoring global biodiversity is critical for understanding responses to anthropogenic change, but biodiversity monitoring is often biased away from tropical, megadiverse areas that are experiencing more rapid environmental change. Acoustic surveys are increasingly used to monitor biodiversity change, especially for bats as they are important indicator species and most use sound to detect, localise and classify objects. However, using bat acoustic surveys for monitoring poses several challenges, particularly in megadiverse regions. Many species lack reference recordings, some species have high call similarity or differ in call detectability, and quantitative classification tools, such as machine learning algorithms, have rarely been applied to data from these areas. Here, we collate a reference call library for bat species that occur in a megadiverse country, Mexico. We use 4685 search‐phase calls from 1378 individual sequences of 59 bat species to create automatic species identification tools generated by machine learning algorithms (Random Forest). We evaluate the improvement in species‐level classification rates gained by using hierarchical classifications, reflecting either taxonomic or ecological constraints (guilds) on call design, and examine how classification rate accuracy changes at different hierarchical levels (family, genus and guild). Species‐level classification of calls had a mean accuracy of 66%, and the use of hierarchies improved mean species‐level classification accuracy by up to 6% (species within families 72%, species within genera 71·2% and species within guilds 69·1%). Classification accuracy to family, genus and guild‐level was 91·7%, 77·8% and 82·5%, respectively. The bioacoustic identification tools we have developed are accurate for rapid biodiversity assessments in a megadiverse region and can also be used effectively to classify species at broader taxonomic or ecological levels. This flexibility increases their usefulness when there are incomplete species reference recordings and also offers the opportunity to characterise and track changes in bat community structure. Our results show that bat bioacoustic surveys in megadiverse countries have more potential than previously thought to monitor biodiversity changes and can be used to direct further developments of bioacoustic monitoring programs in Mexico.

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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.