Site-to-site variation in species composition (β-diversity) generally increases from low- to high-diversity regions. Although biogeographical differences in community assembly mechanisms may explain this pattern, random sampling effects can create this pattern through differences in regional species pools. Here, we compared assembly mechanisms between spatially extensive networks of temperate and tropical forest plots with highly divergent species pools (46 vs. 607 species). After controlling for sampling effects, β-diversity of woody plants was similar and higher than expected by chance in both forests, reflecting strong intraspecific aggregation. However, different mechanisms appeared to explain aggregation in the two forests. In the temperate forest, aggregation reflected stronger environmental correlations, suggesting an important role for species-sorting (e.g. environmental filtering) processes, whereas in the tropics, aggregation reflected stronger spatial correlations, more likely reflecting dispersal limitation. We suggest that biogeographical differences in the relative importance of different community assembly mechanisms contribute to these striking gradients in global biodiversity.

Aim Species distribution models and geographical information system (GIS) technologies are becoming increasingly important tools in conservation planning and decision-making. Often the rich data bases of museums and herbaria serve as the primary data for predicting species distributions. Yet key assumptions about the primary data often are untested, and violation of such assumptions may have consequences for model predictions. For example, users of primary data assume that sampling has been random with respect to geography and environmental gradients. Here we evaluate the assumption that plant voucher specimens adequately sample the climatic gradient and test whether violation of this assumption influences model predictions.Location Bolivia and Ecuador.Methods Using 323,711 georeferenced herbarium collections and nine climatic variables, we predicted the distribution of 76 plant species using maximum entropy models (MAXENT) with training points that sampled the climate environments randomly and training points that reflected the climate bias in the herbarium collections. To estimate the distribution of species, MAXENT finds the distribution of maximum entropy (i.e. closest to uniform) subject to the constraint that the expected value for each environmental variable under the estimated distribution matches its empirical average. The experimental design included species that differed in geographical range and elevation; all species were modelled with 20 and 100 training points. We examined the influence of the number of training points and climate bias in training points, elevation and range size on model performance using analysis of variance models. ResultsWe found that significant parts of the climatic gradient were poorly represented in herbarium collections for both countries. For the most part, existing climatic bias in collections did not greatly affect distribution predictions when compared with an unbiased data set. Although the effects of climate bias on prediction accuracy were found to be greater where geographical ranges were characterized by high spatial variation in the degree of climate bias (i.e. ranges where the bias of the various climates sampled by collections deviated considerably from the mean bias), the greatest influence on model performance was the number of presence points used to train the model. Main conclusionsThese results demonstrate that predictions of species distributions can be quite good despite existing climatic biases in primary data found in natural history collections, if a sufficiently large number of training points is available. Because of consistent overprediction of models, these results also confirm the importance of validating models with independent data or expert opinion. Failure to include independent model validation, especially in

Summary1. Ecological disturbances are often hypothesized to alter community assembly processes that influence variation in community composition (b-diversity). Disturbance can cause convergence in community composition (low b-diversity) by increasing niche selection of disturbance-tolerant species. Alternatively, disturbance can cause divergence in community composition (high b-diversity) by increasing habitat filtering across environmental gradients. However, because disturbance may also influence b-diversity through random sampling effects owing to changes in the number of individuals in local communities (community size) or abundances in the regional species pool, observed patterns of b-diversity alone cannot be used to unambiguously discern the relative importance of community assembly mechanisms. 2. We compared b-diversity of woody plants and inferred assembly mechanisms among unburned forests and forests managed with prescribed fires in the Missouri Ozarks, USA. Using a null-model approach, we compared how environmental gradients influenced b-diversity after controlling for differences in local community size and regional species abundances between unburned and burned landscapes. 3. Observed b-diversity was higher in burned landscapes. However, this pattern disappeared or reversed after controlling for smaller community size in burned landscapes. 4. b-diversity was higher than expected by chance in both landscapes, indicating an important role for processes that create clumped species distributions. Moreover, fire appeared to decrease clumping of species at broader spatial scales, suggesting homogenization of community composition through niche selection of disturbance-tolerant species. Environmental variables, however, explained similar amounts of variation in b-diversity in both landscapes, suggesting that disturbance did not alter the relative importance of habitat filtering. 5. Our results indicate that contingent responses of communities to fire reflect a combination of fireinduced changes in local community size and scale-dependent effects of fire on species clumping across landscapes. 6. Synthesis. Although niche-based mechanisms of community assembly are often invoked to explain changes in community composition following disturbance, our results suggest that these changes also arise through random sampling effects owing to the influence of disturbance on community size. Comparative studies of these processes across disturbed ecosystems will provide important insights into the ecological conditions that determine when disturbance alters the interplay of deterministic and stochastic processes in natural and human-modified landscapes.

Species are commonly delimited on the basis of gaps in patterns of morphological variation, but there seems to be little recent work on methods to objectively assess such gaps. Here, we introduce a statistical approach that uses measurements of continuous morphological characters and geographic variation in those characters to (i) measure the strength of the evidence for the existence of a gap in morphological variation between two hypothesized species and (ii) examine if a gap in morphological variation between two hypothesized species can be explained by an alternative hypothesis of geographic variation within a species. This approach is based on recent developments in analyses of multivariate normal mixtures, estimates of multivariate tolerance regions, and principal coordinates of neighboring matrices. We demonstrate the application of the approach by examining previously proposed hypotheses of species limits in the plant genus Escallonia. We discuss the main features of the method, including potential limitations, in relation to other approaches that use gaps in morphological variation as a criterion for species delimitation. The method we propose can help strengthen the link between the theory and practice of species delimitation by increasing the transparency and consistency of taxonomic decisions based on morphology, thus contributing to integrative approaches for species delimitation that consider morphological and geographic data on an equal footing with other kinds of information.

Aim Closely related species can vary tremendously in size of geographical range, yet the causes of such variation are poorly understood. Prominent hypotheses about range size emphasize effects of niche properties and habitat connectivity via the amount and occupancy of suitable habitat, respectively. Previous studies have examined single hypotheses in isolation; however, we assessed the relative importance of these effects along with their potential interactions, using monkeyflower species (genus Mimulus) as a study system. Location Western North America. Methods We used primary occurrence data and climatic layers to estimate climatic niche breadth and position (relative to average regional climate), connectivity of climatically suitable habitat, and geographical range size of 72 monkeyflower species. Using path analysis, we then assessed the relative importance of climatic niche properties and connectivity of climatically suitable habitat in explaining variation in the amount and occupancy of climatically suitable habitat, respectively, and in turn, variation in geographical range size. Results We documented strong support for the hypothesized effects of climatic niche breadth, but not niche position and connectivity of climatically suitable habitat. Amount of climatically suitable habitat explained more variation in range size than occupancy of climatically suitable habitat, with amount and occupancy of suitable habitat together explaining c. 83% of the variation in range size. Main conclusions To our knowledge, this is the first study to show that climatic niche breadth, via its effects on the amount of climatically suitable habitat, is a strong predictor of geographical range size, thereby improving our understanding of the mechanisms driving species rarity.