Summary Species distribution models (SDMs) have become a standard tool in ecology and applied conservation biology. Modelling rare and threatened species is particularly important for conservation purposes. However, modelling rare species is difficult because the combination of few occurrences and many predictor variables easily leads to model overfitting. A new strategy using ensembles of small models was recently developed in an attempt to overcome this limitation of rare species modelling and has been tested successfully for only a single species so far. Here, we aim to test the approach more comprehensively on a large number of species including a transferability assessment. For each species, numerous small (here bivariate) models were calibrated, evaluated and averaged to an ensemble weighted by AUC scores. These ‘ensembles of small models’ (ESMs) were compared to standard SDMs using three commonly used modelling techniques (GLM, GBM and Maxent) and their ensemble prediction. We tested 107 rare and under‐sampled plant species of conservation concern in Switzerland. We show that ESMs performed significantly better than standard SDMs. The rarer the species, the more pronounced the effects were. ESMs were also superior to standard SDMs and their ensemble when they were evaluated using a transferability assessment. By averaging simple small models to an ensemble, ESMs avoid overfitting without losing explanatory power through reducing the number of predictor variables. They further improve the reliability of species distribution models, especially for rare species, and thus help to overcome limitations of modelling rare species.

Urbanisation has an important impact on biodiversity, mostly driving changes in species assemblages, through the replacement of specialist with generalist species, thus leading to biotic homogenisation. Mobility is also assumed to greatly affect species' ability to cope in urban environments. Moreover, specialisation, mobility and their interaction are expected to greatly influence ecological processes such as metacommunity dynamics and assembly processes, and consequently the way and the spatial scale at which organisms respond to urbanisation. Here we investigate urbanisation impacts on distinct characteristics of species assemblages -namely specialisation degree in resource use, mobility and number of species, classified according to both characteristics and their combination -for vascular plants, butterflies and birds, across a range of spatial scales (from 1 × 1 km plots to 5 km-radius buffers around them). We found that the degree of specialisation, mobility and their interaction, greatly influenced species' responses to urbanisation, with highly mobile specialist species of all taxonomic groups being affected most. Two different patterns were found: for plants, urbanisation induced trait divergence by favouring highly mobile species with narrow habitat ranges. For birds and butterflies, however, it reduced the number of highly mobile specialist species, thus driving trait convergence. Mobile organisms, across and within taxonomic groups, tended to respond at larger spatial scales than those that are poorly mobile. These findings emphasize the need to take into consideration species' ecological aspects, as well as a wide range of spatial scales when evaluating the impact of urbanisation on biodiversity. Our results also highlight the harmful impact of widespread urban expansion on organisms such as butterflies, especially highly mobile specialists, which were negatively affected by urban areas even at great distances.

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Ensembles of Small Models (ESM) represent a novel strategy for species distribution modelling with few observations. ESMs are built by calibrating many small models and then averaging them into an ensemble model where the small models are weighted by their cross‐validated scores of predictive performance. In a previous paper (Breiner, Guisan, Bergamini, & Nobis, Methods in Ecology and Evolution, 6, 1210–1218, 2015), we reported two major findings. First, ESMs proved largely superior to standard models in terms of model performance and transferability. Second, ESMs including different modelling techniques did not clearly improve model performance compared to single‐technique ESMs. However, ESMs often require a large computation effort, which can become problematic when modelling large numbers of species. Given the appealing new perspectives offered by ESMs, it is especially important to investigate if some techniques yield increased performance while saving computation time and thus could be predominantly used for building ESMs. Here, we present results from a reanalysis of a subset of the data used in Breiner et al. (2015). More specifically, we ran ESMs: (1) fitted with 10 modelling techniques separately (in Breiner et al., 2015 we used only three techniques); and (2) using various parameter options for each modelling technique (i.e., model tuning). We show that ESMs vary in model performance and computation time across techniques, and some techniques are advantageous in terms of optimizing model performance and computation time (i.e., GLM, CTA and ANN). Including one of these modelling techniques could thus optimize computation time compared to using more computing‐intensive techniques like GBM. Next, we show that parameter tuning can improve performance and transferability of ESMs, but often at the cost of computation time. Parameter tuning could therefore be used when computing resources are not a limiting factor. These findings help improve the applicability and performance of ESMs when applied to large numbers of species.

Human‐driven environmental changes can induce marked shifts in the functional structure of biological communities with possible repercussion on important ecosystem functions and services. At the same time it remains unclear to which extent these changes may differently affect various types of organisms. We investigated species richness and community functional structure of species assemblages at the landscape scale (1 km2 plots) for two contrasting model taxa, i.e. plants (producers and sessile organisms) and birds (consumers and mobile organisms), along topography, climate, landscape heterogeneity, and land‐use (agriculture and urbanization) gradients in a densely populated region of Switzerland. Our study revealed that agricultural and urban land uses drove marked shifts in the functional structure of biological communities compared to changes along climate and topography gradients, especially for plants, while for birds these changes were comparable. Agricultural and urban land uses enhanced divergence in traits related to resource use for birds (diet and nesting), growth forms, dispersal, and reproductive traits for plants, while it induced convergence in vegetative plant traits (plant height and leaf dry matter content). These results suggest that contrasting assembly patterns may arise within and across taxonomic groups along the same environmental gradients as result of distinct underlying processes and ‘organism‐specific’ environmental perceptions. Our results further suggest a potential homogenization of biological communities, as well as low functional diversity and redundancy levels of bird assemblages in our human‐dominated study region. This might potentially compromise the maintenance of key ecological processes under future environmental changes.